| @@ -1,780 +1,779 | |||||
| 1 | '''' |
|
1 | '''' | |
| 2 | Created on Set 9, 2015 |
|
2 | Created on Set 9, 2015 | |
| 3 |
|
3 | |||
| 4 | @author: roj-idl71 Karim Kuyeng |
|
4 | @author: roj-idl71 Karim Kuyeng | |
| 5 |
|
5 | |||
| 6 | @upgrade: 2021, Joab Apaza |
|
6 | @upgrade: 2021, Joab Apaza | |
| 7 |
|
7 | |||
| 8 | ''' |
|
8 | ''' | |
| 9 |
|
9 | |||
| 10 | import os |
|
10 | import os | |
| 11 | import sys |
|
11 | import sys | |
| 12 | import glob |
|
12 | import glob | |
| 13 | import fnmatch |
|
13 | import fnmatch | |
| 14 | import datetime |
|
14 | import datetime | |
| 15 | import time |
|
15 | import time | |
| 16 | import re |
|
16 | import re | |
| 17 | import h5py |
|
17 | import h5py | |
| 18 | import numpy |
|
18 | import numpy | |
| 19 |
|
19 | |||
| 20 | try: |
|
20 | try: | |
| 21 | from gevent import sleep |
|
21 | from gevent import sleep | |
| 22 | except: |
|
22 | except: | |
| 23 | from time import sleep |
|
23 | from time import sleep | |
| 24 |
|
24 | |||
| 25 | from schainpy.model.data.jroheaderIO import RadarControllerHeader, SystemHeader,ProcessingHeader |
|
25 | from schainpy.model.data.jroheaderIO import RadarControllerHeader, SystemHeader,ProcessingHeader | |
| 26 | from schainpy.model.data.jrodata import Voltage |
|
26 | from schainpy.model.data.jrodata import Voltage | |
| 27 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
27 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator | |
| 28 | from numpy import imag |
|
28 | from numpy import imag | |
| 29 | from schainpy.utils import log |
|
29 | from schainpy.utils import log | |
| 30 |
|
30 | |||
| 31 |
|
31 | |||
| 32 | class AMISRReader(ProcessingUnit): |
|
32 | class AMISRReader(ProcessingUnit): | |
| 33 | ''' |
|
33 | ''' | |
| 34 | classdocs |
|
34 | classdocs | |
| 35 | ''' |
|
35 | ''' | |
| 36 |
|
36 | |||
| 37 | def __init__(self): |
|
37 | def __init__(self): | |
| 38 | ''' |
|
38 | ''' | |
| 39 | Constructor |
|
39 | Constructor | |
| 40 | ''' |
|
40 | ''' | |
| 41 |
|
41 | |||
| 42 | ProcessingUnit.__init__(self) |
|
42 | ProcessingUnit.__init__(self) | |
| 43 |
|
43 | |||
| 44 | self.set = None |
|
44 | self.set = None | |
| 45 | self.subset = None |
|
45 | self.subset = None | |
| 46 | self.extension_file = '.h5' |
|
46 | self.extension_file = '.h5' | |
| 47 | self.dtc_str = 'dtc' |
|
47 | self.dtc_str = 'dtc' | |
| 48 | self.dtc_id = 0 |
|
48 | self.dtc_id = 0 | |
| 49 | self.status = True |
|
49 | self.status = True | |
| 50 | self.isConfig = False |
|
50 | self.isConfig = False | |
| 51 | self.dirnameList = [] |
|
51 | self.dirnameList = [] | |
| 52 | self.filenameList = [] |
|
52 | self.filenameList = [] | |
| 53 | self.fileIndex = None |
|
53 | self.fileIndex = None | |
| 54 | self.flagNoMoreFiles = False |
|
54 | self.flagNoMoreFiles = False | |
| 55 | self.flagIsNewFile = 0 |
|
55 | self.flagIsNewFile = 0 | |
| 56 | self.filename = '' |
|
56 | self.filename = '' | |
| 57 | self.amisrFilePointer = None |
|
57 | self.amisrFilePointer = None | |
| 58 |
|
58 | |||
| 59 | self.beamCodeMap = None |
|
59 | self.beamCodeMap = None | |
| 60 | self.azimuthList = [] |
|
60 | self.azimuthList = [] | |
| 61 | self.elevationList = [] |
|
61 | self.elevationList = [] | |
| 62 | self.dataShape = None |
|
62 | self.dataShape = None | |
| 63 | self.flag_old_beams = False |
|
63 | self.flag_old_beams = False | |
| 64 |
|
64 | |||
| 65 | self.flagAsync = False #Use when the experiment has no syncronization |
|
65 | self.flagAsync = False #Use when the experiment has no syncronization | |
| 66 | self.shiftChannels = 0 |
|
66 | self.shiftChannels = 0 | |
| 67 | self.profileIndex = 0 |
|
67 | self.profileIndex = 0 | |
| 68 |
|
68 | |||
| 69 |
|
69 | |||
| 70 | self.beamCodeByFrame = None |
|
70 | self.beamCodeByFrame = None | |
| 71 | self.radacTimeByFrame = None |
|
71 | self.radacTimeByFrame = None | |
| 72 |
|
72 | |||
| 73 | self.dataset = None |
|
73 | self.dataset = None | |
| 74 |
|
74 | |||
| 75 | self.__firstFile = True |
|
75 | self.__firstFile = True | |
| 76 |
|
76 | |||
| 77 | self.buffer = None |
|
77 | self.buffer = None | |
| 78 |
|
78 | |||
| 79 | self.timezone = 'ut' |
|
79 | self.timezone = 'ut' | |
| 80 |
|
80 | |||
| 81 | self.__waitForNewFile = 20 |
|
81 | self.__waitForNewFile = 20 | |
| 82 | self.__filename_online = None |
|
82 | self.__filename_online = None | |
| 83 | #Is really necessary create the output object in the initializer |
|
83 | #Is really necessary create the output object in the initializer | |
| 84 | self.dataOut = Voltage() |
|
84 | self.dataOut = Voltage() | |
| 85 | self.dataOut.error=False |
|
85 | self.dataOut.error=False | |
| 86 | self.margin_days = 1 |
|
86 | self.margin_days = 1 | |
| 87 | self.flag_ignoreFiles = False #to activate the ignoring Files flag |
|
87 | self.flag_ignoreFiles = False #to activate the ignoring Files flag | |
| 88 | self.flag_standby = False # just keep waiting, use when ignoring files |
|
88 | self.flag_standby = False # just keep waiting, use when ignoring files | |
| 89 | self.ignStartDateTime=None |
|
89 | self.ignStartDateTime=None | |
| 90 | self.ignEndDateTime=None |
|
90 | self.ignEndDateTime=None | |
| 91 |
|
91 | |||
| 92 | def setup(self,path=None, |
|
92 | def setup(self,path=None, | |
| 93 | startDate=None, |
|
93 | startDate=None, | |
| 94 | endDate=None, |
|
94 | endDate=None, | |
| 95 | startTime=None, |
|
95 | startTime=None, | |
| 96 | endTime=None, |
|
96 | endTime=None, | |
| 97 | walk=True, |
|
97 | walk=True, | |
| 98 | timezone='ut', |
|
98 | timezone='ut', | |
| 99 | all=0, |
|
99 | all=0, | |
| 100 | code = 1, |
|
100 | code = 1, | |
| 101 | nCode = 1, |
|
101 | nCode = 1, | |
| 102 | nBaud = 0, |
|
102 | nBaud = 0, | |
| 103 | nOsamp = 0, |
|
103 | nOsamp = 0, | |
| 104 | online=False, |
|
104 | online=False, | |
| 105 | old_beams=False, |
|
105 | old_beams=False, | |
| 106 | margin_days=1, |
|
106 | margin_days=1, | |
| 107 | nFFT = None, |
|
107 | nFFT = None, | |
| 108 | nChannels = None, |
|
108 | nChannels = None, | |
| 109 | ignStartDate=None, |
|
109 | ignStartDate=None, | |
| 110 | ignEndDate=None, |
|
110 | ignEndDate=None, | |
| 111 | ignStartTime=None, |
|
111 | ignStartTime=None, | |
| 112 | ignEndTime=None, |
|
112 | ignEndTime=None, | |
| 113 | syncronization=True, |
|
113 | syncronization=True, | |
| 114 | shiftChannels=0 |
|
114 | shiftChannels=0 | |
| 115 | ): |
|
115 | ): | |
| 116 |
|
116 | |||
| 117 |
|
117 | |||
| 118 |
|
118 | |||
| 119 | self.timezone = timezone |
|
119 | self.timezone = timezone | |
| 120 | self.all = all |
|
120 | self.all = all | |
| 121 | self.online = online |
|
121 | self.online = online | |
| 122 | self.flag_old_beams = old_beams |
|
122 | self.flag_old_beams = old_beams | |
| 123 | self.code = code |
|
123 | self.code = code | |
| 124 | self.nCode = int(nCode) |
|
124 | self.nCode = int(nCode) | |
| 125 | self.nBaud = int(nBaud) |
|
125 | self.nBaud = int(nBaud) | |
| 126 | self.nOsamp = int(nOsamp) |
|
126 | self.nOsamp = int(nOsamp) | |
| 127 | self.margin_days = margin_days |
|
127 | self.margin_days = margin_days | |
| 128 | self.__sampleRate = None |
|
128 | self.__sampleRate = None | |
| 129 | self.flagAsync = not syncronization |
|
129 | self.flagAsync = not syncronization | |
| 130 | self.shiftChannels = shiftChannels |
|
130 | self.shiftChannels = shiftChannels | |
| 131 | self.nFFT = nFFT |
|
131 | self.nFFT = nFFT | |
| 132 | self.nChannels = nChannels |
|
132 | self.nChannels = nChannels | |
| 133 | if ignStartTime!=None and ignEndTime!=None: |
|
133 | if ignStartTime!=None and ignEndTime!=None: | |
| 134 | if ignStartDate!=None and ignEndDate!=None: |
|
134 | if ignStartDate!=None and ignEndDate!=None: | |
| 135 | self.ignStartDateTime=datetime.datetime.combine(ignStartDate,ignStartTime) |
|
135 | self.ignStartDateTime=datetime.datetime.combine(ignStartDate,ignStartTime) | |
| 136 | self.ignEndDateTime=datetime.datetime.combine(ignEndDate,ignEndTime) |
|
136 | self.ignEndDateTime=datetime.datetime.combine(ignEndDate,ignEndTime) | |
| 137 | else: |
|
137 | else: | |
| 138 | self.ignStartDateTime=datetime.datetime.combine(startDate,ignStartTime) |
|
138 | self.ignStartDateTime=datetime.datetime.combine(startDate,ignStartTime) | |
| 139 | self.ignEndDateTime=datetime.datetime.combine(endDate,ignEndTime) |
|
139 | self.ignEndDateTime=datetime.datetime.combine(endDate,ignEndTime) | |
| 140 | self.flag_ignoreFiles = True |
|
140 | self.flag_ignoreFiles = True | |
| 141 |
|
141 | |||
| 142 | #self.findFiles() |
|
142 | #self.findFiles() | |
| 143 | if not(online): |
|
143 | if not(online): | |
| 144 | #Busqueda de archivos offline |
|
144 | #Busqueda de archivos offline | |
| 145 | self.searchFilesOffLine(path, startDate, endDate, startTime, endTime, walk,) |
|
145 | self.searchFilesOffLine(path, startDate, endDate, startTime, endTime, walk,) | |
| 146 | else: |
|
146 | else: | |
| 147 | self.searchFilesOnLine(path, startDate, endDate, startTime,endTime,walk) |
|
147 | self.searchFilesOnLine(path, startDate, endDate, startTime,endTime,walk) | |
| 148 |
|
148 | |||
| 149 | if not(self.filenameList): |
|
149 | if not(self.filenameList): | |
| 150 | raise schainpy.admin.SchainWarning("There is no files into the folder: %s"%(path)) |
|
150 | raise schainpy.admin.SchainWarning("There is no files into the folder: %s"%(path)) | |
| 151 | #sys.exit(0) |
|
151 | #sys.exit(0) | |
| 152 | self.dataOut.error = True |
|
152 | self.dataOut.error = True | |
| 153 |
|
153 | |||
| 154 | self.fileIndex = 0 |
|
154 | self.fileIndex = 0 | |
| 155 |
|
155 | |||
| 156 | self.readNextFile(online) |
|
156 | self.readNextFile(online) | |
| 157 |
|
157 | |||
| 158 | ''' |
|
158 | ''' | |
| 159 | Add code |
|
159 | Add code | |
| 160 | ''' |
|
160 | ''' | |
| 161 | self.isConfig = True |
|
161 | self.isConfig = True | |
| 162 | # print("Setup Done") |
|
162 | # print("Setup Done") | |
| 163 | pass |
|
163 | pass | |
| 164 |
|
164 | |||
| 165 |
|
165 | |||
| 166 | def readAMISRHeader(self,fp): |
|
166 | def readAMISRHeader(self,fp): | |
| 167 |
|
167 | |||
| 168 | if self.isConfig and (not self.flagNoMoreFiles): |
|
168 | if self.isConfig and (not self.flagNoMoreFiles): | |
| 169 | newShape = fp.get('Raw11/Data/Samples/Data').shape[1:] |
|
169 | newShape = fp.get('Raw11/Data/Samples/Data').shape[1:] | |
| 170 | if self.dataShape != newShape and newShape != None and not self.flag_standby: |
|
170 | if self.dataShape != newShape and newShape != None and not self.flag_standby: | |
| 171 | raise schainpy.admin.SchainError("NEW FILE HAS A DIFFERENT SHAPE: ") |
|
171 | raise schainpy.admin.SchainError("NEW FILE HAS A DIFFERENT SHAPE: ") | |
| 172 | print(self.dataShape,newShape,"\n") |
|
172 | print(self.dataShape,newShape,"\n") | |
| 173 | return 0 |
|
173 | return 0 | |
| 174 | else: |
|
174 | else: | |
| 175 | self.dataShape = fp.get('Raw11/Data/Samples/Data').shape[1:] |
|
175 | self.dataShape = fp.get('Raw11/Data/Samples/Data').shape[1:] | |
| 176 |
|
176 | |||
| 177 |
|
177 | |||
| 178 | header = 'Raw11/Data/RadacHeader' |
|
178 | header = 'Raw11/Data/RadacHeader' | |
| 179 | if self.nChannels == None: |
|
179 | if self.nChannels == None: | |
| 180 | expFile = fp['Setup/Experimentfile'][()].decode() |
|
180 | expFile = fp['Setup/Experimentfile'][()].decode() | |
| 181 | linesExp = expFile.split("\n") |
|
181 | linesExp = expFile.split("\n") | |
| 182 | a = [line for line in linesExp if "nbeamcodes" in line] |
|
182 | a = [line for line in linesExp if "nbeamcodes" in line] | |
| 183 | self.nChannels = int(a[0][11:]) |
|
183 | self.nChannels = int(a[0][11:]) | |
| 184 |
|
184 | |||
| 185 | if not self.flagAsync: #for experiments with no syncronization |
|
185 | if not self.flagAsync: #for experiments with no syncronization | |
| 186 | self.shiftChannels = 0 |
|
186 | self.shiftChannels = 0 | |
| 187 |
|
187 | |||
| 188 |
|
188 | |||
| 189 |
|
189 | |||
| 190 | self.beamCodeByPulse = fp.get(header+'/BeamCode') # LIST OF BEAMS PER PROFILE, TO BE USED ON REARRANGE |
|
190 | self.beamCodeByPulse = fp.get(header+'/BeamCode') # LIST OF BEAMS PER PROFILE, TO BE USED ON REARRANGE | |
| 191 |
|
191 | |||
| 192 |
|
192 | |||
| 193 | if (self.startDate > datetime.date(2021, 7, 15)) or self.flag_old_beams: #Se cambiΓ³ la forma de extracciΓ³n de Apuntes el 17 o forzar con flag de reorganizaciΓ³n |
|
193 | if (self.startDate > datetime.date(2021, 7, 15)) or self.flag_old_beams: #Se cambiΓ³ la forma de extracciΓ³n de Apuntes el 17 o forzar con flag de reorganizaciΓ³n | |
| 194 | self.beamcodeFile = fp['Setup/Beamcodefile'][()].decode() |
|
194 | self.beamcodeFile = fp['Setup/Beamcodefile'][()].decode() | |
| 195 | self.trueBeams = self.beamcodeFile.split("\n") |
|
195 | self.trueBeams = self.beamcodeFile.split("\n") | |
| 196 | self.trueBeams.pop()#remove last |
|
196 | self.trueBeams.pop()#remove last | |
| 197 | if self.nFFT == None: |
|
197 | if self.nFFT == None: | |
| 198 | log.error("FFT or number of repetitions per channels is needed",self.name) |
|
198 | log.error("FFT or number of repetitions per channels is needed",self.name) | |
| 199 | beams_idx = [k*self.nFFT for k in range(self.nChannels)] |
|
199 | beams_idx = [k*self.nFFT for k in range(self.nChannels)] | |
| 200 | beams = [self.trueBeams[b] for b in beams_idx] |
|
200 | beams = [self.trueBeams[b] for b in beams_idx] | |
| 201 | self.beamCode = [int(x, 16) for x in beams] |
|
201 | self.beamCode = [int(x, 16) for x in beams] | |
| 202 |
|
202 | |||
| 203 | if(self.flagAsync and self.shiftChannels == 0): |
|
203 | if(self.flagAsync and self.shiftChannels == 0): | |
| 204 | initBeam = self.beamCodeByPulse[0, 0] |
|
204 | initBeam = self.beamCodeByPulse[0, 0] | |
| 205 | self.shiftChannels = numpy.argwhere(self.beamCode ==initBeam)[0,0] |
|
205 | self.shiftChannels = numpy.argwhere(self.beamCode ==initBeam)[0,0] | |
| 206 |
|
206 | |||
| 207 | else: |
|
207 | else: | |
| 208 | _beamCode= fp.get('Raw11/Data/Beamcodes') #se usa la manera previa al cambio de apuntes |
|
208 | _beamCode= fp.get('Raw11/Data/Beamcodes') #se usa la manera previa al cambio de apuntes | |
| 209 | self.beamCode = _beamCode[0,:] |
|
209 | self.beamCode = _beamCode[0,:] | |
| 210 |
|
210 | |||
| 211 |
|
211 | |||
| 212 |
|
212 | |||
| 213 |
|
213 | |||
| 214 | if self.beamCodeMap == None: |
|
214 | if self.beamCodeMap == None: | |
| 215 | self.beamCodeMap = fp['Setup/BeamcodeMap'] |
|
215 | self.beamCodeMap = fp['Setup/BeamcodeMap'] | |
| 216 | for beam in self.beamCode: |
|
216 | for beam in self.beamCode: | |
| 217 | beamAziElev = numpy.where(self.beamCodeMap[:,0]==beam) |
|
217 | beamAziElev = numpy.where(self.beamCodeMap[:,0]==beam) | |
| 218 | beamAziElev = beamAziElev[0].squeeze() |
|
218 | beamAziElev = beamAziElev[0].squeeze() | |
| 219 | self.azimuthList.append(self.beamCodeMap[beamAziElev,1]) |
|
219 | self.azimuthList.append(self.beamCodeMap[beamAziElev,1]) | |
| 220 | self.elevationList.append(self.beamCodeMap[beamAziElev,2]) |
|
220 | self.elevationList.append(self.beamCodeMap[beamAziElev,2]) | |
| 221 | #print("Beamssss: ",self.beamCodeMap[beamAziElev,1],self.beamCodeMap[beamAziElev,2]) |
|
221 | #print("Beamssss: ",self.beamCodeMap[beamAziElev,1],self.beamCodeMap[beamAziElev,2]) | |
| 222 | #print(self.beamCode) |
|
222 | #print(self.beamCode) | |
| 223 | #self.code = fp.get(header+'/Code') # NOT USE FOR THIS |
|
223 | #self.code = fp.get(header+'/Code') # NOT USE FOR THIS | |
| 224 | self.frameCount = fp.get(header+'/FrameCount')# NOT USE FOR THIS |
|
224 | self.frameCount = fp.get(header+'/FrameCount')# NOT USE FOR THIS | |
| 225 | self.modeGroup = fp.get(header+'/ModeGroup')# NOT USE FOR THIS |
|
225 | self.modeGroup = fp.get(header+'/ModeGroup')# NOT USE FOR THIS | |
| 226 | self.nsamplesPulse = fp.get(header+'/NSamplesPulse')# TO GET NSA OR USING DATA FOR THAT |
|
226 | self.nsamplesPulse = fp.get(header+'/NSamplesPulse')# TO GET NSA OR USING DATA FOR THAT | |
| 227 | self.pulseCount = fp.get(header+'/PulseCount')# NOT USE FOR THIS |
|
227 | self.pulseCount = fp.get(header+'/PulseCount')# NOT USE FOR THIS | |
| 228 | self.radacTime = fp.get(header+'/RadacTime')# 1st TIME ON FILE ANDE CALCULATE THE REST WITH IPP*nindexprofile |
|
228 | self.radacTime = fp.get(header+'/RadacTime')# 1st TIME ON FILE ANDE CALCULATE THE REST WITH IPP*nindexprofile | |
| 229 | self.timeCount = fp.get(header+'/TimeCount')# NOT USE FOR THIS |
|
229 | self.timeCount = fp.get(header+'/TimeCount')# NOT USE FOR THIS | |
| 230 | self.timeStatus = fp.get(header+'/TimeStatus')# NOT USE FOR THIS |
|
230 | self.timeStatus = fp.get(header+'/TimeStatus')# NOT USE FOR THIS | |
| 231 | self.rangeFromFile = fp.get('Raw11/Data/Samples/Range') |
|
231 | self.rangeFromFile = fp.get('Raw11/Data/Samples/Range') | |
| 232 | self.frequency = fp.get('Rx/Frequency') |
|
232 | self.frequency = fp.get('Rx/Frequency') | |
| 233 | txAus = fp.get('Raw11/Data/Pulsewidth') #seconds |
|
233 | txAus = fp.get('Raw11/Data/Pulsewidth') #seconds | |
| 234 | self.baud = fp.get('Raw11/Data/TxBaud') |
|
234 | self.baud = fp.get('Raw11/Data/TxBaud') | |
| 235 | sampleRate = fp.get('Rx/SampleRate') |
|
235 | sampleRate = fp.get('Rx/SampleRate') | |
| 236 | self.__sampleRate = sampleRate[()] |
|
236 | self.__sampleRate = sampleRate[()] | |
| 237 | self.nblocks = self.pulseCount.shape[0] #nblocks |
|
237 | self.nblocks = self.pulseCount.shape[0] #nblocks | |
| 238 | self.profPerBlockRAW = self.pulseCount.shape[1] #profiles per block in raw data |
|
238 | self.profPerBlockRAW = self.pulseCount.shape[1] #profiles per block in raw data | |
| 239 | self.nprofiles = self.pulseCount.shape[1] #nprofile |
|
239 | self.nprofiles = self.pulseCount.shape[1] #nprofile | |
| 240 | #self.nsa = self.nsamplesPulse[0,0] #ngates |
|
240 | #self.nsa = self.nsamplesPulse[0,0] #ngates | |
| 241 | self.nsa = len(self.rangeFromFile[0]) |
|
241 | self.nsa = len(self.rangeFromFile[0]) | |
| 242 | self.nchannels = len(self.beamCode) |
|
242 | self.nchannels = len(self.beamCode) | |
| 243 | self.ippSeconds = (self.radacTime[0][1] -self.radacTime[0][0]) #Ipp in seconds |
|
243 | self.ippSeconds = (self.radacTime[0][1] -self.radacTime[0][0]) #Ipp in seconds | |
| 244 | #print("IPPS secs: ",self.ippSeconds) |
|
244 | #print("IPPS secs: ",self.ippSeconds) | |
| 245 | #self.__waitForNewFile = self.nblocks # wait depending on the number of blocks since each block is 1 sec |
|
245 | #self.__waitForNewFile = self.nblocks # wait depending on the number of blocks since each block is 1 sec | |
| 246 | self.__waitForNewFile = self.nblocks * self.nprofiles * self.ippSeconds # wait until new file is created |
|
246 | self.__waitForNewFile = self.nblocks * self.nprofiles * self.ippSeconds # wait until new file is created | |
| 247 |
|
247 | |||
| 248 | #filling radar controller header parameters |
|
248 | #filling radar controller header parameters | |
| 249 | self.__ippKm = self.ippSeconds *.15*1e6 # in km |
|
249 | self.__ippKm = self.ippSeconds *.15*1e6 # in km | |
| 250 | #self.__txA = txAus[()]*.15 #(ipp[us]*.15km/1us) in km |
|
250 | #self.__txA = txAus[()]*.15 #(ipp[us]*.15km/1us) in km | |
| 251 | self.__txA = txAus[()] #seconds |
|
251 | self.__txA = txAus[()] #seconds | |
| 252 | self.__txAKm = self.__txA*1e6*.15 |
|
252 | self.__txAKm = self.__txA*1e6*.15 | |
| 253 | self.__txB = 0 |
|
253 | self.__txB = 0 | |
| 254 | nWindows=1 |
|
254 | nWindows=1 | |
| 255 | self.__nSamples = self.nsa |
|
255 | self.__nSamples = self.nsa | |
| 256 | self.__firstHeight = self.rangeFromFile[0][0]/1000 #in km |
|
256 | self.__firstHeight = self.rangeFromFile[0][0]/1000 #in km | |
| 257 | self.__deltaHeight = (self.rangeFromFile[0][1] - self.rangeFromFile[0][0])/1000 |
|
257 | self.__deltaHeight = (self.rangeFromFile[0][1] - self.rangeFromFile[0][0])/1000 | |
| 258 | #print("amisr-ipp:",self.ippSeconds, self.__ippKm) |
|
258 | #print("amisr-ipp:",self.ippSeconds, self.__ippKm) | |
| 259 | #for now until understand why the code saved is different (code included even though code not in tuf file) |
|
259 | #for now until understand why the code saved is different (code included even though code not in tuf file) | |
| 260 | #self.__codeType = 0 |
|
260 | #self.__codeType = 0 | |
| 261 | # self.__nCode = None |
|
261 | # self.__nCode = None | |
| 262 | # self.__nBaud = None |
|
262 | # self.__nBaud = None | |
| 263 | self.__code = self.code |
|
263 | self.__code = self.code | |
| 264 | self.__codeType = 0 |
|
264 | self.__codeType = 0 | |
| 265 | if self.code != None: |
|
265 | if self.code != None: | |
| 266 | self.__codeType = 1 |
|
266 | self.__codeType = 1 | |
| 267 | self.__nCode = self.nCode |
|
267 | self.__nCode = self.nCode | |
| 268 | self.__nBaud = self.nBaud |
|
268 | self.__nBaud = self.nBaud | |
| 269 | self.__baudTX = self.__txA/(self.nBaud) |
|
269 | self.__baudTX = self.__txA/(self.nBaud) | |
| 270 | #self.__code = 0 |
|
270 | #self.__code = 0 | |
| 271 |
|
271 | |||
| 272 | #filling system header parameters |
|
272 | #filling system header parameters | |
| 273 | self.__nSamples = self.nsa |
|
273 | self.__nSamples = self.nsa | |
| 274 | self.newProfiles = self.nprofiles/self.nchannels |
|
274 | self.newProfiles = self.nprofiles/self.nchannels | |
| 275 | self.__channelList = [n for n in range(self.nchannels)] |
|
275 | self.__channelList = [n for n in range(self.nchannels)] | |
| 276 |
|
276 | |||
| 277 | self.__frequency = self.frequency[0][0] |
|
277 | self.__frequency = self.frequency[0][0] | |
| 278 |
|
278 | |||
| 279 |
|
279 | |||
| 280 | return 1 |
|
280 | return 1 | |
| 281 |
|
281 | |||
| 282 |
|
282 | |||
| 283 | def createBuffers(self): |
|
283 | def createBuffers(self): | |
| 284 |
|
284 | |||
| 285 | pass |
|
285 | pass | |
| 286 |
|
286 | |||
| 287 | def __setParameters(self,path='', startDate='',endDate='',startTime='', endTime='', walk=''): |
|
287 | def __setParameters(self,path='', startDate='',endDate='',startTime='', endTime='', walk=''): | |
| 288 | self.path = path |
|
288 | self.path = path | |
| 289 | self.startDate = startDate |
|
289 | self.startDate = startDate | |
| 290 | self.endDate = endDate |
|
290 | self.endDate = endDate | |
| 291 | self.startTime = startTime |
|
291 | self.startTime = startTime | |
| 292 | self.endTime = endTime |
|
292 | self.endTime = endTime | |
| 293 | self.walk = walk |
|
293 | self.walk = walk | |
| 294 |
|
294 | |||
| 295 |
|
295 | |||
| 296 | def __checkPath(self): |
|
296 | def __checkPath(self): | |
| 297 | if os.path.exists(self.path): |
|
297 | if os.path.exists(self.path): | |
| 298 | self.status = 1 |
|
298 | self.status = 1 | |
| 299 | else: |
|
299 | else: | |
| 300 | self.status = 0 |
|
300 | self.status = 0 | |
| 301 | print('Path:%s does not exists'%self.path) |
|
301 | print('Path:%s does not exists'%self.path) | |
| 302 |
|
302 | |||
| 303 | return |
|
303 | return | |
| 304 |
|
304 | |||
| 305 |
|
305 | |||
| 306 | def __selDates(self, amisr_dirname_format): |
|
306 | def __selDates(self, amisr_dirname_format): | |
| 307 | try: |
|
307 | try: | |
| 308 | year = int(amisr_dirname_format[0:4]) |
|
308 | year = int(amisr_dirname_format[0:4]) | |
| 309 | month = int(amisr_dirname_format[4:6]) |
|
309 | month = int(amisr_dirname_format[4:6]) | |
| 310 | dom = int(amisr_dirname_format[6:8]) |
|
310 | dom = int(amisr_dirname_format[6:8]) | |
| 311 | thisDate = datetime.date(year,month,dom) |
|
311 | thisDate = datetime.date(year,month,dom) | |
| 312 | #margen de un dΓa extra, igual luego se filtra for fecha y hora |
|
312 | #margen de un dΓa extra, igual luego se filtra for fecha y hora | |
| 313 | if (thisDate>=(self.startDate - datetime.timedelta(days=self.margin_days)) and thisDate <= (self.endDate)+ datetime.timedelta(days=1)): |
|
313 | if (thisDate>=(self.startDate - datetime.timedelta(days=self.margin_days)) and thisDate <= (self.endDate)+ datetime.timedelta(days=1)): | |
| 314 | return amisr_dirname_format |
|
314 | return amisr_dirname_format | |
| 315 | except: |
|
315 | except: | |
| 316 | return None |
|
316 | return None | |
| 317 |
|
317 | |||
| 318 |
|
318 | |||
| 319 | def __findDataForDates(self,online=False): |
|
319 | def __findDataForDates(self,online=False): | |
| 320 |
|
320 | |||
| 321 | if not(self.status): |
|
321 | if not(self.status): | |
| 322 | return None |
|
322 | return None | |
| 323 |
|
323 | |||
| 324 | pat = '\d+.\d+' |
|
324 | pat = '\d+.\d+' | |
| 325 | dirnameList = [re.search(pat,x) for x in os.listdir(self.path)] |
|
325 | dirnameList = [re.search(pat,x) for x in os.listdir(self.path)] | |
| 326 | dirnameList = [x for x in dirnameList if x!=None] |
|
326 | dirnameList = [x for x in dirnameList if x!=None] | |
| 327 | dirnameList = [x.string for x in dirnameList] |
|
327 | dirnameList = [x.string for x in dirnameList] | |
| 328 | if not(online): |
|
328 | if not(online): | |
| 329 | dirnameList = [self.__selDates(x) for x in dirnameList] |
|
329 | dirnameList = [self.__selDates(x) for x in dirnameList] | |
| 330 | dirnameList = [x for x in dirnameList if x!=None] |
|
330 | dirnameList = [x for x in dirnameList if x!=None] | |
| 331 | if len(dirnameList)>0: |
|
331 | if len(dirnameList)>0: | |
| 332 | self.status = 1 |
|
332 | self.status = 1 | |
| 333 | self.dirnameList = dirnameList |
|
333 | self.dirnameList = dirnameList | |
| 334 | self.dirnameList.sort() |
|
334 | self.dirnameList.sort() | |
| 335 | else: |
|
335 | else: | |
| 336 | self.status = 0 |
|
336 | self.status = 0 | |
| 337 | return None |
|
337 | return None | |
| 338 |
|
338 | |||
| 339 | def __getTimeFromData(self): |
|
339 | def __getTimeFromData(self): | |
| 340 | startDateTime_Reader = datetime.datetime.combine(self.startDate,self.startTime) |
|
340 | startDateTime_Reader = datetime.datetime.combine(self.startDate,self.startTime) | |
| 341 | endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime) |
|
341 | endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime) | |
| 342 |
|
342 | |||
| 343 | print('Filtering Files from %s to %s'%(startDateTime_Reader, endDateTime_Reader)) |
|
343 | print('Filtering Files from %s to %s'%(startDateTime_Reader, endDateTime_Reader)) | |
| 344 | print('........................................') |
|
344 | print('........................................') | |
| 345 | filter_filenameList = [] |
|
345 | filter_filenameList = [] | |
| 346 | self.filenameList.sort() |
|
346 | self.filenameList.sort() | |
| 347 | total_files = len(self.filenameList) |
|
347 | total_files = len(self.filenameList) | |
| 348 | #for i in range(len(self.filenameList)-1): |
|
348 | #for i in range(len(self.filenameList)-1): | |
| 349 | for i in range(total_files): |
|
349 | for i in range(total_files): | |
| 350 | filename = self.filenameList[i] |
|
350 | filename = self.filenameList[i] | |
| 351 | #print("file-> ",filename) |
|
351 | #print("file-> ",filename) | |
| 352 | try: |
|
352 | try: | |
| 353 | fp = h5py.File(filename,'r') |
|
353 | fp = h5py.File(filename,'r') | |
| 354 | time_str = fp.get('Time/RadacTimeString') |
|
354 | time_str = fp.get('Time/RadacTimeString') | |
| 355 |
|
355 | |||
| 356 | startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0] |
|
356 | startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0] | |
| 357 | #startDateTimeStr_File = "2019-12-16 09:21:11" |
|
357 | #startDateTimeStr_File = "2019-12-16 09:21:11" | |
| 358 | junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S') |
|
358 | junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S') | |
| 359 | startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) |
|
359 | startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) | |
| 360 |
|
360 | |||
| 361 | #endDateTimeStr_File = "2019-12-16 11:10:11" |
|
361 | #endDateTimeStr_File = "2019-12-16 11:10:11" | |
| 362 | endDateTimeStr_File = time_str[-1][-1].decode('UTF-8').split('.')[0] |
|
362 | endDateTimeStr_File = time_str[-1][-1].decode('UTF-8').split('.')[0] | |
| 363 | junk = time.strptime(endDateTimeStr_File, '%Y-%m-%d %H:%M:%S') |
|
363 | junk = time.strptime(endDateTimeStr_File, '%Y-%m-%d %H:%M:%S') | |
| 364 | endDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) |
|
364 | endDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) | |
| 365 |
|
365 | |||
| 366 | fp.close() |
|
366 | fp.close() | |
| 367 |
|
367 | |||
| 368 | #print("check time", startDateTime_File) |
|
368 | #print("check time", startDateTime_File) | |
| 369 | if self.timezone == 'lt': |
|
369 | if self.timezone == 'lt': | |
| 370 | startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300) |
|
370 | startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300) | |
| 371 | endDateTime_File = endDateTime_File - datetime.timedelta(minutes = 300) |
|
371 | endDateTime_File = endDateTime_File - datetime.timedelta(minutes = 300) | |
| 372 | if (startDateTime_File >=startDateTime_Reader and endDateTime_File<=endDateTime_Reader): |
|
372 | if (startDateTime_File >=startDateTime_Reader and endDateTime_File<=endDateTime_Reader): | |
| 373 | filter_filenameList.append(filename) |
|
373 | filter_filenameList.append(filename) | |
| 374 |
|
374 | |||
| 375 | if (startDateTime_File>endDateTime_Reader): |
|
375 | if (startDateTime_File>endDateTime_Reader): | |
| 376 | break |
|
376 | break | |
| 377 | except Exception as e: |
|
377 | except Exception as e: | |
| 378 | log.warning("Error opening file {} -> {}".format(os.path.split(filename)[1],e)) |
|
378 | log.warning("Error opening file {} -> {}".format(os.path.split(filename)[1],e)) | |
| 379 |
|
379 | |||
| 380 | filter_filenameList.sort() |
|
380 | filter_filenameList.sort() | |
| 381 | self.filenameList = filter_filenameList |
|
381 | self.filenameList = filter_filenameList | |
| 382 |
|
382 | |||
| 383 | return 1 |
|
383 | return 1 | |
| 384 |
|
384 | |||
| 385 | def __filterByGlob1(self, dirName): |
|
385 | def __filterByGlob1(self, dirName): | |
| 386 | filter_files = glob.glob1(dirName, '*.*%s'%self.extension_file) |
|
386 | filter_files = glob.glob1(dirName, '*.*%s'%self.extension_file) | |
| 387 | filter_files.sort() |
|
387 | filter_files.sort() | |
| 388 | filterDict = {} |
|
388 | filterDict = {} | |
| 389 | filterDict.setdefault(dirName) |
|
389 | filterDict.setdefault(dirName) | |
| 390 | filterDict[dirName] = filter_files |
|
390 | filterDict[dirName] = filter_files | |
| 391 | return filterDict |
|
391 | return filterDict | |
| 392 |
|
392 | |||
| 393 | def __getFilenameList(self, fileListInKeys, dirList): |
|
393 | def __getFilenameList(self, fileListInKeys, dirList): | |
| 394 | for value in fileListInKeys: |
|
394 | for value in fileListInKeys: | |
| 395 | dirName = list(value.keys())[0] |
|
395 | dirName = list(value.keys())[0] | |
| 396 | for file in value[dirName]: |
|
396 | for file in value[dirName]: | |
| 397 | filename = os.path.join(dirName, file) |
|
397 | filename = os.path.join(dirName, file) | |
| 398 | self.filenameList.append(filename) |
|
398 | self.filenameList.append(filename) | |
| 399 |
|
399 | |||
| 400 |
|
400 | |||
| 401 | def __selectDataForTimes(self, online=False): |
|
401 | def __selectDataForTimes(self, online=False): | |
| 402 | #aun no esta implementado el filtro for tiempo-> implementado en readNextFile |
|
402 | #aun no esta implementado el filtro for tiempo-> implementado en readNextFile | |
| 403 | if not(self.status): |
|
403 | if not(self.status): | |
| 404 | return None |
|
404 | return None | |
| 405 |
|
405 | |||
| 406 | dirList = [os.path.join(self.path,x) for x in self.dirnameList] |
|
406 | dirList = [os.path.join(self.path,x) for x in self.dirnameList] | |
| 407 | fileListInKeys = [self.__filterByGlob1(x) for x in dirList] |
|
407 | fileListInKeys = [self.__filterByGlob1(x) for x in dirList] | |
| 408 | self.__getFilenameList(fileListInKeys, dirList) |
|
408 | self.__getFilenameList(fileListInKeys, dirList) | |
| 409 | if not(online): |
|
409 | if not(online): | |
| 410 | #filtro por tiempo |
|
410 | #filtro por tiempo | |
| 411 | if not(self.all): |
|
411 | if not(self.all): | |
| 412 | self.__getTimeFromData() |
|
412 | self.__getTimeFromData() | |
| 413 |
|
413 | |||
| 414 | if len(self.filenameList)>0: |
|
414 | if len(self.filenameList)>0: | |
| 415 | self.status = 1 |
|
415 | self.status = 1 | |
| 416 | self.filenameList.sort() |
|
416 | self.filenameList.sort() | |
| 417 | else: |
|
417 | else: | |
| 418 | self.status = 0 |
|
418 | self.status = 0 | |
| 419 | return None |
|
419 | return None | |
| 420 |
|
420 | |||
| 421 | else: |
|
421 | else: | |
| 422 | #get the last file - 1 |
|
422 | #get the last file - 1 | |
| 423 | self.filenameList = [self.filenameList[-2]] |
|
423 | self.filenameList = [self.filenameList[-2]] | |
| 424 | new_dirnameList = [] |
|
424 | new_dirnameList = [] | |
| 425 | for dirname in self.dirnameList: |
|
425 | for dirname in self.dirnameList: | |
| 426 | junk = numpy.array([dirname in x for x in self.filenameList]) |
|
426 | junk = numpy.array([dirname in x for x in self.filenameList]) | |
| 427 | junk_sum = junk.sum() |
|
427 | junk_sum = junk.sum() | |
| 428 | if junk_sum > 0: |
|
428 | if junk_sum > 0: | |
| 429 | new_dirnameList.append(dirname) |
|
429 | new_dirnameList.append(dirname) | |
| 430 | self.dirnameList = new_dirnameList |
|
430 | self.dirnameList = new_dirnameList | |
| 431 | return 1 |
|
431 | return 1 | |
| 432 |
|
432 | |||
| 433 | def searchFilesOnLine(self, path, startDate, endDate, startTime=datetime.time(0,0,0), |
|
433 | def searchFilesOnLine(self, path, startDate, endDate, startTime=datetime.time(0,0,0), | |
| 434 | endTime=datetime.time(23,59,59),walk=True): |
|
434 | endTime=datetime.time(23,59,59),walk=True): | |
| 435 |
|
435 | |||
| 436 | if endDate ==None: |
|
436 | if endDate ==None: | |
| 437 | startDate = datetime.datetime.utcnow().date() |
|
437 | startDate = datetime.datetime.utcnow().date() | |
| 438 | endDate = datetime.datetime.utcnow().date() |
|
438 | endDate = datetime.datetime.utcnow().date() | |
| 439 |
|
439 | |||
| 440 | self.__setParameters(path=path, startDate=startDate, endDate=endDate,startTime = startTime,endTime=endTime, walk=walk) |
|
440 | self.__setParameters(path=path, startDate=startDate, endDate=endDate,startTime = startTime,endTime=endTime, walk=walk) | |
| 441 |
|
441 | |||
| 442 | self.__checkPath() |
|
442 | self.__checkPath() | |
| 443 |
|
443 | |||
| 444 | self.__findDataForDates(online=True) |
|
444 | self.__findDataForDates(online=True) | |
| 445 |
|
445 | |||
| 446 | self.dirnameList = [self.dirnameList[-1]] |
|
446 | self.dirnameList = [self.dirnameList[-1]] | |
| 447 |
|
447 | |||
| 448 | self.__selectDataForTimes(online=True) |
|
448 | self.__selectDataForTimes(online=True) | |
| 449 |
|
449 | |||
| 450 | return |
|
450 | return | |
| 451 |
|
451 | |||
| 452 |
|
452 | |||
| 453 | def searchFilesOffLine(self, |
|
453 | def searchFilesOffLine(self, | |
| 454 | path, |
|
454 | path, | |
| 455 | startDate, |
|
455 | startDate, | |
| 456 | endDate, |
|
456 | endDate, | |
| 457 | startTime=datetime.time(0,0,0), |
|
457 | startTime=datetime.time(0,0,0), | |
| 458 | endTime=datetime.time(23,59,59), |
|
458 | endTime=datetime.time(23,59,59), | |
| 459 | walk=True): |
|
459 | walk=True): | |
| 460 |
|
460 | |||
| 461 | self.__setParameters(path, startDate, endDate, startTime, endTime, walk) |
|
461 | self.__setParameters(path, startDate, endDate, startTime, endTime, walk) | |
| 462 |
|
462 | |||
| 463 | self.__checkPath() |
|
463 | self.__checkPath() | |
| 464 |
|
464 | |||
| 465 | self.__findDataForDates() |
|
465 | self.__findDataForDates() | |
| 466 |
|
466 | |||
| 467 | self.__selectDataForTimes() |
|
467 | self.__selectDataForTimes() | |
| 468 |
|
468 | |||
| 469 | for i in range(len(self.filenameList)): |
|
469 | for i in range(len(self.filenameList)): | |
| 470 | print("%s" %(self.filenameList[i])) |
|
470 | print("%s" %(self.filenameList[i])) | |
| 471 |
|
471 | |||
| 472 | return |
|
472 | return | |
| 473 |
|
473 | |||
| 474 | def __setNextFileOffline(self): |
|
474 | def __setNextFileOffline(self): | |
| 475 |
|
475 | |||
| 476 | try: |
|
476 | try: | |
| 477 | self.filename = self.filenameList[self.fileIndex] |
|
477 | self.filename = self.filenameList[self.fileIndex] | |
| 478 | self.amisrFilePointer = h5py.File(self.filename,'r') |
|
478 | self.amisrFilePointer = h5py.File(self.filename,'r') | |
| 479 | self.fileIndex += 1 |
|
479 | self.fileIndex += 1 | |
| 480 | except: |
|
480 | except: | |
| 481 | self.flagNoMoreFiles = 1 |
|
481 | self.flagNoMoreFiles = 1 | |
| 482 | raise schainpy.admin.SchainError('No more files to read') |
|
482 | raise schainpy.admin.SchainError('No more files to read') | |
| 483 | return 0 |
|
483 | return 0 | |
| 484 |
|
484 | |||
| 485 | self.flagIsNewFile = 1 |
|
485 | self.flagIsNewFile = 1 | |
| 486 | print("Setting the file: %s"%self.filename) |
|
486 | print("Setting the file: %s"%self.filename) | |
| 487 |
|
487 | |||
| 488 | return 1 |
|
488 | return 1 | |
| 489 |
|
489 | |||
| 490 |
|
490 | |||
| 491 | def __setNextFileOnline(self): |
|
491 | def __setNextFileOnline(self): | |
| 492 | filename = self.filenameList[0] |
|
492 | filename = self.filenameList[0] | |
| 493 | if self.__filename_online != None: |
|
493 | if self.__filename_online != None: | |
| 494 | self.__selectDataForTimes(online=True) |
|
494 | self.__selectDataForTimes(online=True) | |
| 495 | filename = self.filenameList[0] |
|
495 | filename = self.filenameList[0] | |
| 496 | wait = 0 |
|
496 | wait = 0 | |
| 497 | self.__waitForNewFile=300 ## DEBUG: |
|
497 | self.__waitForNewFile=300 ## DEBUG: | |
| 498 | while self.__filename_online == filename: |
|
498 | while self.__filename_online == filename: | |
| 499 | print('waiting %d seconds to get a new file...'%(self.__waitForNewFile)) |
|
499 | print('waiting %d seconds to get a new file...'%(self.__waitForNewFile)) | |
| 500 | if wait == 5: |
|
500 | if wait == 5: | |
| 501 | self.flagNoMoreFiles = 1 |
|
501 | self.flagNoMoreFiles = 1 | |
| 502 | return 0 |
|
502 | return 0 | |
| 503 | sleep(self.__waitForNewFile) |
|
503 | sleep(self.__waitForNewFile) | |
| 504 | self.__selectDataForTimes(online=True) |
|
504 | self.__selectDataForTimes(online=True) | |
| 505 | filename = self.filenameList[0] |
|
505 | filename = self.filenameList[0] | |
| 506 | wait += 1 |
|
506 | wait += 1 | |
| 507 |
|
507 | |||
| 508 | self.__filename_online = filename |
|
508 | self.__filename_online = filename | |
| 509 |
|
509 | |||
| 510 | self.amisrFilePointer = h5py.File(filename,'r') |
|
510 | self.amisrFilePointer = h5py.File(filename,'r') | |
| 511 | self.flagIsNewFile = 1 |
|
511 | self.flagIsNewFile = 1 | |
| 512 | self.filename = filename |
|
512 | self.filename = filename | |
| 513 | print("Setting the file: %s"%self.filename) |
|
513 | print("Setting the file: %s"%self.filename) | |
| 514 | return 1 |
|
514 | return 1 | |
| 515 |
|
515 | |||
| 516 |
|
516 | |||
| 517 | def readData(self): |
|
517 | def readData(self): | |
| 518 | buffer = self.amisrFilePointer.get('Raw11/Data/Samples/Data') |
|
518 | buffer = self.amisrFilePointer.get('Raw11/Data/Samples/Data') | |
| 519 | re = buffer[:,:,:,0] |
|
519 | re = buffer[:,:,:,0] | |
| 520 | im = buffer[:,:,:,1] |
|
520 | im = buffer[:,:,:,1] | |
| 521 | dataset = re + im*1j |
|
521 | dataset = re + im*1j | |
| 522 |
|
522 | |||
| 523 | self.radacTime = self.amisrFilePointer.get('Raw11/Data/RadacHeader/RadacTime') |
|
523 | self.radacTime = self.amisrFilePointer.get('Raw11/Data/RadacHeader/RadacTime') | |
| 524 | timeset = self.radacTime[:,0] |
|
524 | timeset = self.radacTime[:,0] | |
| 525 |
|
525 | |||
| 526 | return dataset,timeset |
|
526 | return dataset,timeset | |
| 527 |
|
527 | |||
| 528 | def reshapeData(self): |
|
528 | def reshapeData(self): | |
| 529 | #print(self.beamCodeByPulse, self.beamCode, self.nblocks, self.nprofiles, self.nsa) |
|
529 | #print(self.beamCodeByPulse, self.beamCode, self.nblocks, self.nprofiles, self.nsa) | |
| 530 | channels = self.beamCodeByPulse[0,:] |
|
530 | channels = self.beamCodeByPulse[0,:] | |
| 531 | nchan = self.nchannels |
|
531 | nchan = self.nchannels | |
| 532 | #self.newProfiles = self.nprofiles/nchan #must be defined on filljroheader |
|
532 | #self.newProfiles = self.nprofiles/nchan #must be defined on filljroheader | |
| 533 | nblocks = self.nblocks |
|
533 | nblocks = self.nblocks | |
| 534 | nsamples = self.nsa |
|
534 | nsamples = self.nsa | |
| 535 | #print("Channels: ",self.nChannels) |
|
535 | #print("Channels: ",self.nChannels) | |
| 536 | print("dataset: ", self.dataset.shape) |
|
|||
| 537 | #Dimensions : nChannels, nProfiles, nSamples |
|
536 | #Dimensions : nChannels, nProfiles, nSamples | |
| 538 | new_block = numpy.empty((nblocks, nchan, numpy.int_(self.newProfiles), nsamples), dtype="complex64") |
|
537 | new_block = numpy.empty((nblocks, nchan, numpy.int_(self.newProfiles), nsamples), dtype="complex64") | |
| 539 | ############################################ |
|
538 | ############################################ | |
| 540 | profPerCH = int(self.profPerBlockRAW / (self.nFFT* self.nChannels)) |
|
539 | profPerCH = int(self.profPerBlockRAW / (self.nFFT* self.nChannels)) | |
| 541 | #profPerCH = int(self.profPerBlockRAW / self.nChannels) |
|
540 | #profPerCH = int(self.profPerBlockRAW / self.nChannels) | |
| 542 | for thisChannel in range(nchan): |
|
541 | for thisChannel in range(nchan): | |
| 543 |
|
542 | |||
| 544 | ich = thisChannel |
|
543 | ich = thisChannel | |
| 545 |
|
544 | |||
| 546 | idx_ch = [self.nFFT*(ich + nchan*k) for k in range(profPerCH)] |
|
545 | idx_ch = [self.nFFT*(ich + nchan*k) for k in range(profPerCH)] | |
| 547 | #print(idx_ch) |
|
546 | #print(idx_ch) | |
| 548 | if self.nFFT > 1: |
|
547 | if self.nFFT > 1: | |
| 549 | aux = [numpy.arange(i, i+self.nFFT) for i in idx_ch] |
|
548 | aux = [numpy.arange(i, i+self.nFFT) for i in idx_ch] | |
| 550 | idx_ch = None |
|
549 | idx_ch = None | |
| 551 | idx_ch =aux |
|
550 | idx_ch =aux | |
| 552 | idx_ch = numpy.array(idx_ch, dtype=int).flatten() |
|
551 | idx_ch = numpy.array(idx_ch, dtype=int).flatten() | |
| 553 | else: |
|
552 | else: | |
| 554 | idx_ch = numpy.array(idx_ch, dtype=int) |
|
553 | idx_ch = numpy.array(idx_ch, dtype=int) | |
| 555 |
|
554 | |||
| 556 | #print(ich,profPerCH,idx_ch) |
|
555 | #print(ich,profPerCH,idx_ch) | |
| 557 | #print(numpy.where(channels==self.beamCode[ich])[0]) |
|
556 | #print(numpy.where(channels==self.beamCode[ich])[0]) | |
| 558 | #new_block[:,ich,:,:] = self.dataset[:,numpy.where(channels==self.beamCode[ich])[0],:] |
|
557 | #new_block[:,ich,:,:] = self.dataset[:,numpy.where(channels==self.beamCode[ich])[0],:] | |
| 559 | new_block[:,ich,:,:] = self.dataset[:,idx_ch,:] |
|
558 | new_block[:,ich,:,:] = self.dataset[:,idx_ch,:] | |
| 560 |
|
559 | |||
| 561 | new_block = numpy.transpose(new_block, (1,0,2,3)) |
|
560 | new_block = numpy.transpose(new_block, (1,0,2,3)) | |
| 562 | new_block = numpy.reshape(new_block, (nchan,-1, nsamples)) |
|
561 | new_block = numpy.reshape(new_block, (nchan,-1, nsamples)) | |
| 563 | if self.flagAsync: |
|
562 | if self.flagAsync: | |
| 564 | new_block = numpy.roll(new_block, self.shiftChannels, axis=0) |
|
563 | new_block = numpy.roll(new_block, self.shiftChannels, axis=0) | |
| 565 | return new_block |
|
564 | return new_block | |
| 566 |
|
565 | |||
| 567 | def updateIndexes(self): |
|
566 | def updateIndexes(self): | |
| 568 |
|
567 | |||
| 569 | pass |
|
568 | pass | |
| 570 |
|
569 | |||
| 571 | def fillJROHeader(self): |
|
570 | def fillJROHeader(self): | |
| 572 |
|
571 | |||
| 573 | #fill radar controller header |
|
572 | #fill radar controller header | |
| 574 |
|
573 | |||
| 575 | #fill system header |
|
574 | #fill system header | |
| 576 | self.dataOut.systemHeaderObj = SystemHeader(nSamples=self.__nSamples, |
|
575 | self.dataOut.systemHeaderObj = SystemHeader(nSamples=self.__nSamples, | |
| 577 | nProfiles=self.newProfiles, |
|
576 | nProfiles=self.newProfiles, | |
| 578 | nChannels=len(self.__channelList), |
|
577 | nChannels=len(self.__channelList), | |
| 579 | adcResolution=14, |
|
578 | adcResolution=14, | |
| 580 | pciDioBusWidth=32) |
|
579 | pciDioBusWidth=32) | |
| 581 |
|
580 | |||
| 582 | self.dataOut.type = "Voltage" |
|
581 | self.dataOut.type = "Voltage" | |
| 583 | self.dataOut.data = None |
|
582 | self.dataOut.data = None | |
| 584 | self.dataOut.dtype = numpy.dtype([('real','<i8'),('imag','<i8')]) |
|
583 | self.dataOut.dtype = numpy.dtype([('real','<i8'),('imag','<i8')]) | |
| 585 | # self.dataOut.nChannels = 0 |
|
584 | # self.dataOut.nChannels = 0 | |
| 586 |
|
585 | |||
| 587 | # self.dataOut.nHeights = 0 |
|
586 | # self.dataOut.nHeights = 0 | |
| 588 |
|
587 | |||
| 589 | self.dataOut.nProfiles = self.newProfiles*self.nblocks |
|
588 | self.dataOut.nProfiles = self.newProfiles*self.nblocks | |
| 590 | #self.dataOut.heightList = self.__firstHeigth + numpy.arange(self.__nSamples, dtype = numpy.float)*self.__deltaHeigth |
|
589 | #self.dataOut.heightList = self.__firstHeigth + numpy.arange(self.__nSamples, dtype = numpy.float)*self.__deltaHeigth | |
| 591 | ranges = numpy.reshape(self.rangeFromFile[()],(-1)) |
|
590 | ranges = numpy.reshape(self.rangeFromFile[()],(-1)) | |
| 592 | self.dataOut.heightList = ranges/1000.0 #km |
|
591 | self.dataOut.heightList = ranges/1000.0 #km | |
| 593 | self.dataOut.channelList = self.__channelList |
|
592 | self.dataOut.channelList = self.__channelList | |
| 594 |
|
593 | |||
| 595 | self.dataOut.blocksize = self.dataOut.nChannels * self.dataOut.nHeights |
|
594 | self.dataOut.blocksize = self.dataOut.nChannels * self.dataOut.nHeights | |
| 596 |
|
595 | |||
| 597 | # self.dataOut.channelIndexList = None |
|
596 | # self.dataOut.channelIndexList = None | |
| 598 |
|
597 | |||
| 599 |
|
598 | |||
| 600 | # #self.dataOut.azimuthList = numpy.roll( numpy.array(self.azimuthList) ,self.shiftChannels) |
|
599 | # #self.dataOut.azimuthList = numpy.roll( numpy.array(self.azimuthList) ,self.shiftChannels) | |
| 601 | # #self.dataOut.elevationList = numpy.roll(numpy.array(self.elevationList) ,self.shiftChannels) |
|
600 | # #self.dataOut.elevationList = numpy.roll(numpy.array(self.elevationList) ,self.shiftChannels) | |
| 602 | # #self.dataOut.codeList = numpy.roll(numpy.array(self.beamCode), self.shiftChannels) |
|
601 | # #self.dataOut.codeList = numpy.roll(numpy.array(self.beamCode), self.shiftChannels) | |
| 603 |
|
602 | |||
| 604 | self.dataOut.azimuthList = self.azimuthList |
|
603 | self.dataOut.azimuthList = self.azimuthList | |
| 605 | self.dataOut.elevationList = self.elevationList |
|
604 | self.dataOut.elevationList = self.elevationList | |
| 606 | self.dataOut.codeList = self.beamCode |
|
605 | self.dataOut.codeList = self.beamCode | |
| 607 |
|
606 | |||
| 608 |
|
607 | |||
| 609 |
|
608 | |||
| 610 | #print(self.dataOut.elevationList) |
|
609 | #print(self.dataOut.elevationList) | |
| 611 | self.dataOut.flagNoData = True |
|
610 | self.dataOut.flagNoData = True | |
| 612 |
|
611 | |||
| 613 | #Set to TRUE if the data is discontinuous |
|
612 | #Set to TRUE if the data is discontinuous | |
| 614 | self.dataOut.flagDiscontinuousBlock = False |
|
613 | self.dataOut.flagDiscontinuousBlock = False | |
| 615 |
|
614 | |||
| 616 | self.dataOut.utctime = None |
|
615 | self.dataOut.utctime = None | |
| 617 |
|
616 | |||
| 618 | #self.dataOut.timeZone = -5 #self.__timezone/60 #timezone like jroheader, difference in minutes between UTC and localtime |
|
617 | #self.dataOut.timeZone = -5 #self.__timezone/60 #timezone like jroheader, difference in minutes between UTC and localtime | |
| 619 | if self.timezone == 'lt': |
|
618 | if self.timezone == 'lt': | |
| 620 | self.dataOut.timeZone = time.timezone / 60. #get the timezone in minutes |
|
619 | self.dataOut.timeZone = time.timezone / 60. #get the timezone in minutes | |
| 621 | else: |
|
620 | else: | |
| 622 | self.dataOut.timeZone = 0 #by default time is UTC |
|
621 | self.dataOut.timeZone = 0 #by default time is UTC | |
| 623 |
|
622 | |||
| 624 | self.dataOut.dstFlag = 0 |
|
623 | self.dataOut.dstFlag = 0 | |
| 625 | self.dataOut.errorCount = 0 |
|
624 | self.dataOut.errorCount = 0 | |
| 626 | self.dataOut.nCohInt = 1 |
|
625 | self.dataOut.nCohInt = 1 | |
| 627 | self.dataOut.flagDecodeData = False #asumo que la data esta decodificada |
|
626 | self.dataOut.flagDecodeData = False #asumo que la data esta decodificada | |
| 628 | self.dataOut.flagDeflipData = False #asumo que la data esta sin flip |
|
627 | self.dataOut.flagDeflipData = False #asumo que la data esta sin flip | |
| 629 | self.dataOut.flagShiftFFT = False |
|
628 | self.dataOut.flagShiftFFT = False | |
| 630 | self.dataOut.ippSeconds = self.ippSeconds |
|
629 | self.dataOut.ippSeconds = self.ippSeconds | |
| 631 | self.dataOut.ipp = self.__ippKm |
|
630 | self.dataOut.ipp = self.__ippKm | |
| 632 | self.dataOut.nCode = self.__nCode |
|
631 | self.dataOut.nCode = self.__nCode | |
| 633 | self.dataOut.code = self.__code |
|
632 | self.dataOut.code = self.__code | |
| 634 | self.dataOut.nBaud = self.__nBaud |
|
633 | self.dataOut.nBaud = self.__nBaud | |
| 635 |
|
634 | |||
| 636 |
|
635 | |||
| 637 | self.dataOut.frequency = self.__frequency |
|
636 | self.dataOut.frequency = self.__frequency | |
| 638 | self.dataOut.realtime = self.online |
|
637 | self.dataOut.realtime = self.online | |
| 639 |
|
638 | |||
| 640 | self.dataOut.radarControllerHeaderObj = RadarControllerHeader(ipp=self.__ippKm, |
|
639 | self.dataOut.radarControllerHeaderObj = RadarControllerHeader(ipp=self.__ippKm, | |
| 641 | txA=self.__txAKm, |
|
640 | txA=self.__txAKm, | |
| 642 | txB=0, |
|
641 | txB=0, | |
| 643 | nWindows=1, |
|
642 | nWindows=1, | |
| 644 | nHeights=self.__nSamples, |
|
643 | nHeights=self.__nSamples, | |
| 645 | firstHeight=self.__firstHeight, |
|
644 | firstHeight=self.__firstHeight, | |
| 646 | codeType=self.__codeType, |
|
645 | codeType=self.__codeType, | |
| 647 | nCode=self.__nCode, nBaud=self.__nBaud, |
|
646 | nCode=self.__nCode, nBaud=self.__nBaud, | |
| 648 | code = self.__code, |
|
647 | code = self.__code, | |
| 649 | nOsamp=self.nOsamp, |
|
648 | nOsamp=self.nOsamp, | |
| 650 | frequency = self.__frequency, |
|
649 | frequency = self.__frequency, | |
| 651 | sampleRate= self.__sampleRate, |
|
650 | sampleRate= self.__sampleRate, | |
| 652 | fClock=self.__sampleRate) |
|
651 | fClock=self.__sampleRate) | |
| 653 |
|
652 | |||
| 654 |
|
653 | |||
| 655 | self.dataOut.radarControllerHeaderObj.heightList = ranges/1000.0 #km |
|
654 | self.dataOut.radarControllerHeaderObj.heightList = ranges/1000.0 #km | |
| 656 | self.dataOut.radarControllerHeaderObj.heightResolution = self.__deltaHeight |
|
655 | self.dataOut.radarControllerHeaderObj.heightResolution = self.__deltaHeight | |
| 657 | self.dataOut.radarControllerHeaderObj.rangeIpp = self.__ippKm #km |
|
656 | self.dataOut.radarControllerHeaderObj.rangeIpp = self.__ippKm #km | |
| 658 | self.dataOut.radarControllerHeaderObj.rangeTxA = self.__txA*1e6*.15 #km |
|
657 | self.dataOut.radarControllerHeaderObj.rangeTxA = self.__txA*1e6*.15 #km | |
| 659 | self.dataOut.radarControllerHeaderObj.nChannels = self.nchannels |
|
658 | self.dataOut.radarControllerHeaderObj.nChannels = self.nchannels | |
| 660 | self.dataOut.radarControllerHeaderObj.channelList = self.__channelList |
|
659 | self.dataOut.radarControllerHeaderObj.channelList = self.__channelList | |
| 661 | self.dataOut.radarControllerHeaderObj.azimuthList = self.azimuthList |
|
660 | self.dataOut.radarControllerHeaderObj.azimuthList = self.azimuthList | |
| 662 | self.dataOut.radarControllerHeaderObj.elevationList = self.elevationList |
|
661 | self.dataOut.radarControllerHeaderObj.elevationList = self.elevationList | |
| 663 | self.dataOut.radarControllerHeaderObj.dtype = "Voltage" |
|
662 | self.dataOut.radarControllerHeaderObj.dtype = "Voltage" | |
| 664 | self.dataOut.ippSeconds = self.ippSeconds |
|
663 | self.dataOut.ippSeconds = self.ippSeconds | |
| 665 | self.dataOut.ippFactor = self.nFFT |
|
664 | self.dataOut.ippFactor = self.nFFT | |
| 666 | pass |
|
665 | pass | |
| 667 |
|
666 | |||
| 668 | def readNextFile(self,online=False): |
|
667 | def readNextFile(self,online=False): | |
| 669 |
|
668 | |||
| 670 | if not(online): |
|
669 | if not(online): | |
| 671 | newFile = self.__setNextFileOffline() |
|
670 | newFile = self.__setNextFileOffline() | |
| 672 | else: |
|
671 | else: | |
| 673 | newFile = self.__setNextFileOnline() |
|
672 | newFile = self.__setNextFileOnline() | |
| 674 |
|
673 | |||
| 675 | if not(newFile): |
|
674 | if not(newFile): | |
| 676 | self.dataOut.error = True |
|
675 | self.dataOut.error = True | |
| 677 | return 0 |
|
676 | return 0 | |
| 678 |
|
677 | |||
| 679 | if not self.readAMISRHeader(self.amisrFilePointer): |
|
678 | if not self.readAMISRHeader(self.amisrFilePointer): | |
| 680 | self.dataOut.error = True |
|
679 | self.dataOut.error = True | |
| 681 | return 0 |
|
680 | return 0 | |
| 682 |
|
681 | |||
| 683 | #self.createBuffers() |
|
682 | #self.createBuffers() | |
| 684 | self.fillJROHeader() |
|
683 | self.fillJROHeader() | |
| 685 |
|
684 | |||
| 686 | #self.__firstFile = False |
|
685 | #self.__firstFile = False | |
| 687 |
|
686 | |||
| 688 | self.dataset,self.timeset = self.readData() |
|
687 | self.dataset,self.timeset = self.readData() | |
| 689 |
|
688 | |||
| 690 | if self.endDate!=None: |
|
689 | if self.endDate!=None: | |
| 691 | endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime) |
|
690 | endDateTime_Reader = datetime.datetime.combine(self.endDate,self.endTime) | |
| 692 | time_str = self.amisrFilePointer.get('Time/RadacTimeString') |
|
691 | time_str = self.amisrFilePointer.get('Time/RadacTimeString') | |
| 693 | startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0] |
|
692 | startDateTimeStr_File = time_str[0][0].decode('UTF-8').split('.')[0] | |
| 694 | junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S') |
|
693 | junk = time.strptime(startDateTimeStr_File, '%Y-%m-%d %H:%M:%S') | |
| 695 | startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) |
|
694 | startDateTime_File = datetime.datetime(junk.tm_year,junk.tm_mon,junk.tm_mday,junk.tm_hour, junk.tm_min, junk.tm_sec) | |
| 696 | if self.timezone == 'lt': |
|
695 | if self.timezone == 'lt': | |
| 697 | startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300) |
|
696 | startDateTime_File = startDateTime_File - datetime.timedelta(minutes = 300) | |
| 698 | if (startDateTime_File>endDateTime_Reader): |
|
697 | if (startDateTime_File>endDateTime_Reader): | |
| 699 | self.flag_standby = False |
|
698 | self.flag_standby = False | |
| 700 | return 0 |
|
699 | return 0 | |
| 701 | if self.flag_ignoreFiles and (startDateTime_File >= self.ignStartDateTime and startDateTime_File <= self.ignEndDateTime): |
|
700 | if self.flag_ignoreFiles and (startDateTime_File >= self.ignStartDateTime and startDateTime_File <= self.ignEndDateTime): | |
| 702 | print("Ignoring...") |
|
701 | print("Ignoring...") | |
| 703 | self.flag_standby = True |
|
702 | self.flag_standby = True | |
| 704 | return 1 |
|
703 | return 1 | |
| 705 | self.flag_standby = False |
|
704 | self.flag_standby = False | |
| 706 |
|
705 | |||
| 707 | self.jrodataset = self.reshapeData() |
|
706 | self.jrodataset = self.reshapeData() | |
| 708 | #----self.updateIndexes() |
|
707 | #----self.updateIndexes() | |
| 709 | self.profileIndex = 0 |
|
708 | self.profileIndex = 0 | |
| 710 |
|
709 | |||
| 711 | return 1 |
|
710 | return 1 | |
| 712 |
|
711 | |||
| 713 |
|
712 | |||
| 714 | def __hasNotDataInBuffer(self): |
|
713 | def __hasNotDataInBuffer(self): | |
| 715 | if self.profileIndex >= (self.newProfiles*self.nblocks): |
|
714 | if self.profileIndex >= (self.newProfiles*self.nblocks): | |
| 716 | return 1 |
|
715 | return 1 | |
| 717 | return 0 |
|
716 | return 0 | |
| 718 |
|
717 | |||
| 719 |
|
718 | |||
| 720 | def getData(self): |
|
719 | def getData(self): | |
| 721 |
|
720 | |||
| 722 | if self.flagNoMoreFiles: |
|
721 | if self.flagNoMoreFiles: | |
| 723 | self.dataOut.flagNoData = True |
|
722 | self.dataOut.flagNoData = True | |
| 724 | return 0 |
|
723 | return 0 | |
| 725 |
|
724 | |||
| 726 | if self.profileIndex >= (self.newProfiles*self.nblocks): # |
|
725 | if self.profileIndex >= (self.newProfiles*self.nblocks): # | |
| 727 | #if self.__hasNotDataInBuffer(): |
|
726 | #if self.__hasNotDataInBuffer(): | |
| 728 | if not (self.readNextFile(self.online)): |
|
727 | if not (self.readNextFile(self.online)): | |
| 729 | print("Profile Index break...") |
|
728 | print("Profile Index break...") | |
| 730 | return 0 |
|
729 | return 0 | |
| 731 |
|
730 | |||
| 732 | if self.flag_standby: #Standby mode, if files are being ignoring, just return with no error flag |
|
731 | if self.flag_standby: #Standby mode, if files are being ignoring, just return with no error flag | |
| 733 | return 0 |
|
732 | return 0 | |
| 734 |
|
733 | |||
| 735 | if self.dataset is None: # setear esta condicion cuando no hayan datos por leer |
|
734 | if self.dataset is None: # setear esta condicion cuando no hayan datos por leer | |
| 736 | self.dataOut.flagNoData = True |
|
735 | self.dataOut.flagNoData = True | |
| 737 | print("No more data break...") |
|
736 | print("No more data break...") | |
| 738 | return 0 |
|
737 | return 0 | |
| 739 |
|
738 | |||
| 740 | #self.dataOut.data = numpy.reshape(self.jrodataset[self.profileIndex,:],(1,-1)) |
|
739 | #self.dataOut.data = numpy.reshape(self.jrodataset[self.profileIndex,:],(1,-1)) | |
| 741 |
|
740 | |||
| 742 | self.dataOut.data = self.jrodataset[:,self.profileIndex,:] |
|
741 | self.dataOut.data = self.jrodataset[:,self.profileIndex,:] | |
| 743 |
|
742 | |||
| 744 | #print("R_t",self.timeset) |
|
743 | #print("R_t",self.timeset) | |
| 745 |
|
744 | |||
| 746 | #self.dataOut.utctime = self.jrotimeset[self.profileIndex] |
|
745 | #self.dataOut.utctime = self.jrotimeset[self.profileIndex] | |
| 747 | #verificar basic header de jro data y ver si es compatible con este valor |
|
746 | #verificar basic header de jro data y ver si es compatible con este valor | |
| 748 | #self.dataOut.utctime = self.timeset + (self.profileIndex * self.ippSeconds * self.nchannels) |
|
747 | #self.dataOut.utctime = self.timeset + (self.profileIndex * self.ippSeconds * self.nchannels) | |
| 749 | indexprof = numpy.mod(self.profileIndex, self.newProfiles) |
|
748 | indexprof = numpy.mod(self.profileIndex, self.newProfiles) | |
| 750 | indexblock = self.profileIndex/self.newProfiles |
|
749 | indexblock = self.profileIndex/self.newProfiles | |
| 751 | #print (indexblock, indexprof) |
|
750 | #print (indexblock, indexprof) | |
| 752 | diffUTC = 0 |
|
751 | diffUTC = 0 | |
| 753 | t_comp = (indexprof * self.ippSeconds * self.nchannels) + diffUTC # |
|
752 | t_comp = (indexprof * self.ippSeconds * self.nchannels) + diffUTC # | |
| 754 |
|
753 | |||
| 755 | #print("utc :",indexblock," __ ",t_comp) |
|
754 | #print("utc :",indexblock," __ ",t_comp) | |
| 756 | #print(numpy.shape(self.timeset)) |
|
755 | #print(numpy.shape(self.timeset)) | |
| 757 | self.dataOut.utctime = self.timeset[numpy.int_(indexblock)] + t_comp |
|
756 | self.dataOut.utctime = self.timeset[numpy.int_(indexblock)] + t_comp | |
| 758 | #self.dataOut.utctime = self.timeset[self.profileIndex] + t_comp |
|
757 | #self.dataOut.utctime = self.timeset[self.profileIndex] + t_comp | |
| 759 |
|
758 | |||
| 760 | self.dataOut.profileIndex = self.profileIndex |
|
759 | self.dataOut.profileIndex = self.profileIndex | |
| 761 | #print("N profile:",self.profileIndex,self.newProfiles,self.nblocks,self.dataOut.utctime) |
|
760 | #print("N profile:",self.profileIndex,self.newProfiles,self.nblocks,self.dataOut.utctime) | |
| 762 | self.dataOut.flagNoData = False |
|
761 | self.dataOut.flagNoData = False | |
| 763 | # if indexprof == 0: |
|
762 | # if indexprof == 0: | |
| 764 | # print("kamisr: ",self.dataOut.utctime) |
|
763 | # print("kamisr: ",self.dataOut.utctime) | |
| 765 |
|
764 | |||
| 766 | self.profileIndex += 1 |
|
765 | self.profileIndex += 1 | |
| 767 |
|
766 | |||
| 768 | return self.dataOut.data #retorno necesario?? |
|
767 | return self.dataOut.data #retorno necesario?? | |
| 769 |
|
768 | |||
| 770 |
|
769 | |||
| 771 | def run(self, **kwargs): |
|
770 | def run(self, **kwargs): | |
| 772 | ''' |
|
771 | ''' | |
| 773 | This method will be called many times so here you should put all your code |
|
772 | This method will be called many times so here you should put all your code | |
| 774 | ''' |
|
773 | ''' | |
| 775 | #print("running kamisr") |
|
774 | #print("running kamisr") | |
| 776 | if not self.isConfig: |
|
775 | if not self.isConfig: | |
| 777 | self.setup(**kwargs) |
|
776 | self.setup(**kwargs) | |
| 778 | self.isConfig = True |
|
777 | self.isConfig = True | |
| 779 |
|
778 | |||
| 780 | self.getData() |
|
779 | self.getData() | |
| @@ -1,2306 +1,2305 | |||||
| 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
|
1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory | |
| 2 | # All rights reserved. |
|
2 | # All rights reserved. | |
| 3 | # |
|
3 | # | |
| 4 | # Distributed under the terms of the BSD 3-clause license. |
|
4 | # Distributed under the terms of the BSD 3-clause license. | |
| 5 | """Spectra processing Unit and operations |
|
5 | """Spectra processing Unit and operations | |
| 6 |
|
6 | |||
| 7 | Here you will find the processing unit `SpectraProc` and several operations |
|
7 | Here you will find the processing unit `SpectraProc` and several operations | |
| 8 | to work with Spectra data type |
|
8 | to work with Spectra data type | |
| 9 | """ |
|
9 | """ | |
| 10 |
|
10 | |||
| 11 | import time |
|
11 | import time | |
| 12 | import itertools |
|
12 | import itertools | |
| 13 |
|
13 | |||
| 14 | import numpy |
|
14 | import numpy | |
| 15 | import math |
|
15 | import math | |
| 16 |
|
16 | |||
| 17 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation |
|
17 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation | |
| 18 | from schainpy.model.data.jrodata import Spectra |
|
18 | from schainpy.model.data.jrodata import Spectra | |
| 19 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
19 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 20 | from schainpy.model.data import _noise |
|
20 | from schainpy.model.data import _noise | |
| 21 |
|
21 | |||
| 22 | from schainpy.utils import log |
|
22 | from schainpy.utils import log | |
| 23 | import matplotlib.pyplot as plt |
|
23 | import matplotlib.pyplot as plt | |
| 24 | #from scipy.optimize import curve_fit |
|
24 | #from scipy.optimize import curve_fit | |
| 25 | from schainpy.model.io.utilsIO import getHei_index |
|
25 | from schainpy.model.io.utilsIO import getHei_index | |
| 26 | import datetime |
|
26 | import datetime | |
| 27 |
|
27 | |||
| 28 | class SpectraProc(ProcessingUnit): |
|
28 | class SpectraProc(ProcessingUnit): | |
| 29 |
|
29 | |||
| 30 | def __init__(self): |
|
30 | def __init__(self): | |
| 31 |
|
31 | |||
| 32 | ProcessingUnit.__init__(self) |
|
32 | ProcessingUnit.__init__(self) | |
| 33 |
|
33 | |||
| 34 | self.buffer = None |
|
34 | self.buffer = None | |
| 35 | self.firstdatatime = None |
|
35 | self.firstdatatime = None | |
| 36 | self.profIndex = 0 |
|
36 | self.profIndex = 0 | |
| 37 | self.dataOut = Spectra() |
|
37 | self.dataOut = Spectra() | |
| 38 | self.id_min = None |
|
38 | self.id_min = None | |
| 39 | self.id_max = None |
|
39 | self.id_max = None | |
| 40 | self.setupReq = False #Agregar a todas las unidades de proc |
|
40 | self.setupReq = False #Agregar a todas las unidades de proc | |
| 41 | self.nsamplesFFT = 0 |
|
41 | self.nsamplesFFT = 0 | |
| 42 |
|
42 | |||
| 43 | def __updateSpecFromVoltage(self): |
|
43 | def __updateSpecFromVoltage(self): | |
| 44 |
|
44 | |||
| 45 |
|
45 | |||
| 46 |
|
46 | |||
| 47 | self.dataOut.timeZone = self.dataIn.timeZone |
|
47 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 48 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
48 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 49 | self.dataOut.errorCount = self.dataIn.errorCount |
|
49 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 50 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
50 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 51 |
|
51 | |||
| 52 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() |
|
52 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() | |
| 53 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
53 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 54 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
54 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 55 | self.dataOut.ipp = self.dataIn.ipp |
|
55 | self.dataOut.ipp = self.dataIn.ipp | |
| 56 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
56 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 57 | self.dataOut.channelList = self.dataIn.channelList |
|
57 | self.dataOut.channelList = self.dataIn.channelList | |
| 58 | self.dataOut.heightList = self.dataIn.heightList |
|
58 | self.dataOut.heightList = self.dataIn.heightList | |
| 59 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
59 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) | |
| 60 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
60 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 61 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
61 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 62 | self.dataOut.utctime = self.firstdatatime |
|
62 | self.dataOut.utctime = self.firstdatatime | |
| 63 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData |
|
63 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData | |
| 64 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData |
|
64 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData | |
| 65 | self.dataOut.flagShiftFFT = False |
|
65 | self.dataOut.flagShiftFFT = False | |
| 66 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
66 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 67 | self.dataOut.nIncohInt = 1 |
|
67 | self.dataOut.nIncohInt = 1 | |
| 68 | self.dataOut.deltaHeight = self.dataIn.deltaHeight |
|
68 | self.dataOut.deltaHeight = self.dataIn.deltaHeight | |
| 69 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
69 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 70 | self.dataOut.frequency = self.dataIn.frequency |
|
70 | self.dataOut.frequency = self.dataIn.frequency | |
| 71 | self.dataOut.realtime = self.dataIn.realtime |
|
71 | self.dataOut.realtime = self.dataIn.realtime | |
| 72 | self.dataOut.azimuth = self.dataIn.azimuth |
|
72 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 73 | self.dataOut.zenith = self.dataIn.zenith |
|
73 | self.dataOut.zenith = self.dataIn.zenith | |
| 74 | self.dataOut.codeList = self.dataIn.codeList |
|
74 | self.dataOut.codeList = self.dataIn.codeList | |
| 75 | self.dataOut.azimuthList = self.dataIn.azimuthList |
|
75 | self.dataOut.azimuthList = self.dataIn.azimuthList | |
| 76 | self.dataOut.elevationList = self.dataIn.elevationList |
|
76 | self.dataOut.elevationList = self.dataIn.elevationList | |
| 77 | self.dataOut.code = self.dataIn.code |
|
77 | self.dataOut.code = self.dataIn.code | |
| 78 | self.dataOut.nCode = self.dataIn.nCode |
|
78 | self.dataOut.nCode = self.dataIn.nCode | |
| 79 | self.dataOut.flagProfilesByRange = self.dataIn.flagProfilesByRange |
|
79 | self.dataOut.flagProfilesByRange = self.dataIn.flagProfilesByRange | |
| 80 | self.dataOut.nProfilesByRange = self.dataIn.nProfilesByRange |
|
80 | self.dataOut.nProfilesByRange = self.dataIn.nProfilesByRange | |
| 81 |
|
81 | |||
| 82 |
|
82 | |||
| 83 | def __getFft(self): |
|
83 | def __getFft(self): | |
| 84 | # print("fft donw") |
|
84 | # print("fft donw") | |
| 85 | """ |
|
85 | """ | |
| 86 | Convierte valores de Voltaje a Spectra |
|
86 | Convierte valores de Voltaje a Spectra | |
| 87 |
|
87 | |||
| 88 | Affected: |
|
88 | Affected: | |
| 89 | self.dataOut.data_spc |
|
89 | self.dataOut.data_spc | |
| 90 | self.dataOut.data_cspc |
|
90 | self.dataOut.data_cspc | |
| 91 | self.dataOut.data_dc |
|
91 | self.dataOut.data_dc | |
| 92 | self.dataOut.heightList |
|
92 | self.dataOut.heightList | |
| 93 | self.profIndex |
|
93 | self.profIndex | |
| 94 | self.buffer |
|
94 | self.buffer | |
| 95 | self.dataOut.flagNoData |
|
95 | self.dataOut.flagNoData | |
| 96 | """ |
|
96 | """ | |
| 97 | fft_volt = numpy.fft.fft( |
|
97 | fft_volt = numpy.fft.fft( | |
| 98 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) |
|
98 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) | |
| 99 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
99 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 100 | dc = fft_volt[:, 0, :] |
|
100 | dc = fft_volt[:, 0, :] | |
| 101 |
|
101 | |||
| 102 | # calculo de self-spectra |
|
102 | # calculo de self-spectra | |
| 103 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) |
|
103 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) | |
| 104 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
104 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 105 | spc = spc.real |
|
105 | spc = spc.real | |
| 106 |
|
106 | |||
| 107 | blocksize = 0 |
|
107 | blocksize = 0 | |
| 108 | blocksize += dc.size |
|
108 | blocksize += dc.size | |
| 109 | blocksize += spc.size |
|
109 | blocksize += spc.size | |
| 110 |
|
110 | |||
| 111 | cspc = None |
|
111 | cspc = None | |
| 112 | pairIndex = 0 |
|
112 | pairIndex = 0 | |
| 113 | if self.dataOut.pairsList != None: |
|
113 | if self.dataOut.pairsList != None: | |
| 114 | # calculo de cross-spectra |
|
114 | # calculo de cross-spectra | |
| 115 | cspc = numpy.zeros( |
|
115 | cspc = numpy.zeros( | |
| 116 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
116 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 117 | for pair in self.dataOut.pairsList: |
|
117 | for pair in self.dataOut.pairsList: | |
| 118 | if pair[0] not in self.dataOut.channelList: |
|
118 | if pair[0] not in self.dataOut.channelList: | |
| 119 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( |
|
119 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( | |
| 120 | str(pair), str(self.dataOut.channelList))) |
|
120 | str(pair), str(self.dataOut.channelList))) | |
| 121 | if pair[1] not in self.dataOut.channelList: |
|
121 | if pair[1] not in self.dataOut.channelList: | |
| 122 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( |
|
122 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( | |
| 123 | str(pair), str(self.dataOut.channelList))) |
|
123 | str(pair), str(self.dataOut.channelList))) | |
| 124 |
|
124 | |||
| 125 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ |
|
125 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ | |
| 126 | numpy.conjugate(fft_volt[pair[1], :, :]) |
|
126 | numpy.conjugate(fft_volt[pair[1], :, :]) | |
| 127 | pairIndex += 1 |
|
127 | pairIndex += 1 | |
| 128 | blocksize += cspc.size |
|
128 | blocksize += cspc.size | |
| 129 |
|
129 | |||
| 130 | self.dataOut.data_spc = spc |
|
130 | self.dataOut.data_spc = spc | |
| 131 | self.dataOut.data_cspc = cspc |
|
131 | self.dataOut.data_cspc = cspc | |
| 132 | self.dataOut.data_dc = dc |
|
132 | self.dataOut.data_dc = dc | |
| 133 | self.dataOut.blockSize = blocksize |
|
133 | self.dataOut.blockSize = blocksize | |
| 134 | self.dataOut.flagShiftFFT = False |
|
134 | self.dataOut.flagShiftFFT = False | |
| 135 |
|
135 | |||
| 136 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None, shift_fft=False, zeroPad=False, zeroPoints=0): |
|
136 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None, shift_fft=False, zeroPad=False, zeroPoints=0): | |
| 137 |
|
137 | |||
| 138 |
|
138 | |||
| 139 | try: |
|
139 | try: | |
| 140 | type = self.dataIn.type.decode("utf-8") |
|
140 | type = self.dataIn.type.decode("utf-8") | |
| 141 | self.dataIn.type = type |
|
141 | self.dataIn.type = type | |
| 142 | except: |
|
142 | except: | |
| 143 | pass |
|
143 | pass | |
| 144 | if self.dataIn.type == "Spectra": |
|
144 | if self.dataIn.type == "Spectra": | |
| 145 |
|
145 | |||
| 146 | try: |
|
146 | try: | |
| 147 | self.dataOut.copy(self.dataIn) |
|
147 | self.dataOut.copy(self.dataIn) | |
| 148 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
148 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 149 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() |
|
149 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() | |
| 150 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
150 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 151 | #self.dataOut.nHeights = len(self.dataOut.heightList) |
|
151 | #self.dataOut.nHeights = len(self.dataOut.heightList) | |
| 152 | except Exception as e: |
|
152 | except Exception as e: | |
| 153 | print("Error dataIn ",e) |
|
153 | print("Error dataIn ",e) | |
| 154 |
|
154 | |||
| 155 |
|
155 | |||
| 156 |
|
156 | |||
| 157 | if shift_fft: |
|
157 | if shift_fft: | |
| 158 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
158 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 159 | shift = int(self.dataOut.nFFTPoints/2) |
|
159 | shift = int(self.dataOut.nFFTPoints/2) | |
| 160 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) |
|
160 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) | |
| 161 |
|
161 | |||
| 162 | if self.dataOut.data_cspc is not None: |
|
162 | if self.dataOut.data_cspc is not None: | |
| 163 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
163 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 164 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) |
|
164 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) | |
| 165 | if pairsList: |
|
165 | if pairsList: | |
| 166 | self.__selectPairs(pairsList) |
|
166 | self.__selectPairs(pairsList) | |
| 167 |
|
167 | |||
| 168 |
|
168 | |||
| 169 | elif self.dataIn.type == "Voltage": |
|
169 | elif self.dataIn.type == "Voltage": | |
| 170 |
|
170 | |||
| 171 | self.dataOut.flagNoData = True |
|
171 | self.dataOut.flagNoData = True | |
| 172 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
172 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 173 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() |
|
173 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() | |
| 174 | if nFFTPoints == None: |
|
174 | if nFFTPoints == None: | |
| 175 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") |
|
175 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") | |
| 176 |
|
176 | |||
| 177 | if nProfiles == None: |
|
177 | if nProfiles == None: | |
| 178 | nProfiles = nFFTPoints |
|
178 | nProfiles = nFFTPoints | |
| 179 |
|
179 | |||
| 180 | #if ippFactor == None: |
|
180 | #if ippFactor == None: | |
| 181 | # self.dataOut.ippFactor = 1 |
|
181 | # self.dataOut.ippFactor = 1 | |
| 182 | if ippFactor == None: |
|
182 | if ippFactor == None: | |
| 183 | self.dataOut.ippFactor = self.dataIn.ippFactor |
|
183 | self.dataOut.ippFactor = self.dataIn.ippFactor | |
| 184 | else: |
|
184 | else: | |
| 185 | self.dataOut.ippFactor = ippFactor |
|
185 | self.dataOut.ippFactor = ippFactor | |
| 186 |
|
186 | |||
| 187 | #print(" volts ch,prof, h: ", self.dataIn.data.shape) |
|
187 | #print(" volts ch,prof, h: ", self.dataIn.data.shape) | |
| 188 | if self.buffer is None: |
|
188 | if self.buffer is None: | |
| 189 | if not zeroPad: |
|
189 | if not zeroPad: | |
| 190 | self.buffer = numpy.zeros((self.dataIn.nChannels, |
|
190 | self.buffer = numpy.zeros((self.dataIn.nChannels, | |
| 191 | nProfiles, |
|
191 | nProfiles, | |
| 192 | self.dataIn.nHeights), |
|
192 | self.dataIn.nHeights), | |
| 193 | dtype='complex') |
|
193 | dtype='complex') | |
| 194 | zeroPoints = 0 |
|
194 | zeroPoints = 0 | |
| 195 | else: |
|
195 | else: | |
| 196 | self.buffer = numpy.zeros((self.dataIn.nChannels, |
|
196 | self.buffer = numpy.zeros((self.dataIn.nChannels, | |
| 197 | nFFTPoints+int(zeroPoints), |
|
197 | nFFTPoints+int(zeroPoints), | |
| 198 | self.dataIn.nHeights), |
|
198 | self.dataIn.nHeights), | |
| 199 | dtype='complex') |
|
199 | dtype='complex') | |
| 200 |
|
200 | |||
| 201 | self.dataOut.nFFTPoints = nFFTPoints + int(zeroPoints) |
|
201 | self.dataOut.nFFTPoints = nFFTPoints + int(zeroPoints) | |
| 202 |
|
202 | |||
| 203 | if self.dataIn.flagDataAsBlock: |
|
203 | if self.dataIn.flagDataAsBlock: | |
| 204 | nVoltProfiles = self.dataIn.data.shape[1] |
|
204 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 205 | zeroPoints = 0 |
|
205 | zeroPoints = 0 | |
| 206 | if nVoltProfiles == nProfiles or zeroPad: |
|
206 | if nVoltProfiles == nProfiles or zeroPad: | |
| 207 | self.buffer = self.dataIn.data.copy() |
|
207 | self.buffer = self.dataIn.data.copy() | |
| 208 | self.profIndex = nVoltProfiles |
|
208 | self.profIndex = nVoltProfiles | |
| 209 |
|
209 | |||
| 210 | elif nVoltProfiles < nProfiles: |
|
210 | elif nVoltProfiles < nProfiles: | |
| 211 |
|
211 | |||
| 212 | if self.profIndex == 0: |
|
212 | if self.profIndex == 0: | |
| 213 | self.id_min = 0 |
|
213 | self.id_min = 0 | |
| 214 | self.id_max = nVoltProfiles |
|
214 | self.id_max = nVoltProfiles | |
| 215 |
|
215 | |||
| 216 | self.buffer[:, self.id_min:self.id_max, |
|
216 | self.buffer[:, self.id_min:self.id_max, | |
| 217 | :] = self.dataIn.data |
|
217 | :] = self.dataIn.data | |
| 218 | self.profIndex += nVoltProfiles |
|
218 | self.profIndex += nVoltProfiles | |
| 219 | self.id_min += nVoltProfiles |
|
219 | self.id_min += nVoltProfiles | |
| 220 | self.id_max += nVoltProfiles |
|
220 | self.id_max += nVoltProfiles | |
| 221 | else: |
|
221 | else: | |
| 222 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( |
|
222 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( | |
| 223 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) |
|
223 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) | |
| 224 | self.dataOut.flagNoData = True |
|
224 | self.dataOut.flagNoData = True | |
| 225 | else: |
|
225 | else: | |
| 226 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() |
|
226 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() | |
| 227 | self.profIndex += 1 |
|
227 | self.profIndex += 1 | |
| 228 |
|
228 | |||
| 229 | if self.firstdatatime == None: |
|
229 | if self.firstdatatime == None: | |
| 230 | self.firstdatatime = self.dataIn.utctime |
|
230 | self.firstdatatime = self.dataIn.utctime | |
| 231 |
|
231 | |||
| 232 | if self.profIndex == nProfiles or (zeroPad and zeroPoints==0): |
|
232 | if self.profIndex == nProfiles or (zeroPad and zeroPoints==0): | |
| 233 |
|
233 | |||
| 234 | self.__updateSpecFromVoltage() |
|
234 | self.__updateSpecFromVoltage() | |
| 235 |
|
235 | |||
| 236 | if pairsList == None: |
|
236 | if pairsList == None: | |
| 237 | self.dataOut.pairsList = [pair for pair in itertools.combinations(self.dataOut.channelList, 2)] |
|
237 | self.dataOut.pairsList = [pair for pair in itertools.combinations(self.dataOut.channelList, 2)] | |
| 238 | else: |
|
238 | else: | |
| 239 | self.dataOut.pairsList = pairsList |
|
239 | self.dataOut.pairsList = pairsList | |
| 240 | self.__getFft() |
|
240 | self.__getFft() | |
| 241 | self.dataOut.flagNoData = False |
|
241 | self.dataOut.flagNoData = False | |
| 242 | self.firstdatatime = None |
|
242 | self.firstdatatime = None | |
| 243 | self.nsamplesFFT = self.profIndex |
|
243 | self.nsamplesFFT = self.profIndex | |
| 244 | self.profIndex = 0 |
|
244 | self.profIndex = 0 | |
| 245 |
|
245 | |||
| 246 | #update Processing Header: |
|
246 | #update Processing Header: | |
| 247 | self.dataOut.processingHeaderObj.dtype = "Spectra" |
|
247 | self.dataOut.processingHeaderObj.dtype = "Spectra" | |
| 248 | self.dataOut.processingHeaderObj.nFFTPoints = self.dataOut.nFFTPoints |
|
248 | self.dataOut.processingHeaderObj.nFFTPoints = self.dataOut.nFFTPoints | |
| 249 | self.dataOut.processingHeaderObj.nSamplesFFT = self.nsamplesFFT |
|
249 | self.dataOut.processingHeaderObj.nSamplesFFT = self.nsamplesFFT | |
| 250 | self.dataOut.processingHeaderObj.nIncohInt = 1 |
|
250 | self.dataOut.processingHeaderObj.nIncohInt = 1 | |
| 251 |
|
251 | |||
| 252 |
|
252 | |||
| 253 | elif self.dataIn.type == "Parameters": |
|
253 | elif self.dataIn.type == "Parameters": | |
| 254 |
|
254 | |||
| 255 | self.dataOut.data_spc = self.dataIn.data_spc |
|
255 | self.dataOut.data_spc = self.dataIn.data_spc | |
| 256 | self.dataOut.data_cspc = self.dataIn.data_cspc |
|
256 | self.dataOut.data_cspc = self.dataIn.data_cspc | |
| 257 | self.dataOut.data_outlier = self.dataIn.data_outlier |
|
257 | self.dataOut.data_outlier = self.dataIn.data_outlier | |
| 258 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
258 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
| 259 | self.dataOut.nIncohInt = self.dataIn.nIncohInt |
|
259 | self.dataOut.nIncohInt = self.dataIn.nIncohInt | |
| 260 | self.dataOut.nFFTPoints = self.dataIn.nFFTPoints |
|
260 | self.dataOut.nFFTPoints = self.dataIn.nFFTPoints | |
| 261 | self.dataOut.ippFactor = self.dataIn.ippFactor |
|
261 | self.dataOut.ippFactor = self.dataIn.ippFactor | |
| 262 | self.dataOut.max_nIncohInt = self.dataIn.max_nIncohInt |
|
262 | self.dataOut.max_nIncohInt = self.dataIn.max_nIncohInt | |
| 263 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
263 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 264 | self.dataOut.ProcessingHeader = self.dataIn.ProcessingHeader.copy() |
|
264 | self.dataOut.ProcessingHeader = self.dataIn.ProcessingHeader.copy() | |
| 265 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
265 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 266 | self.dataOut.ipp = self.dataIn.ipp |
|
266 | self.dataOut.ipp = self.dataIn.ipp | |
| 267 | #self.dataOut.abscissaList = self.dataIn.getVelRange(1) |
|
267 | #self.dataOut.abscissaList = self.dataIn.getVelRange(1) | |
| 268 | #self.dataOut.spc_noise = self.dataIn.getNoise() |
|
268 | #self.dataOut.spc_noise = self.dataIn.getNoise() | |
| 269 | #self.dataOut.spc_range = (self.dataIn.getFreqRange(1) , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1)) |
|
269 | #self.dataOut.spc_range = (self.dataIn.getFreqRange(1) , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1)) | |
| 270 | # self.dataOut.normFactor = self.dataIn.normFactor |
|
270 | # self.dataOut.normFactor = self.dataIn.normFactor | |
| 271 | if hasattr(self.dataIn, 'channelList'): |
|
271 | if hasattr(self.dataIn, 'channelList'): | |
| 272 | self.dataOut.channelList = self.dataIn.channelList |
|
272 | self.dataOut.channelList = self.dataIn.channelList | |
| 273 | if hasattr(self.dataIn, 'pairsList'): |
|
273 | if hasattr(self.dataIn, 'pairsList'): | |
| 274 | self.dataOut.pairsList = self.dataIn.pairsList |
|
274 | self.dataOut.pairsList = self.dataIn.pairsList | |
| 275 | self.dataOut.groupList = self.dataIn.pairsList |
|
275 | self.dataOut.groupList = self.dataIn.pairsList | |
| 276 |
|
276 | |||
| 277 | self.dataOut.flagNoData = False |
|
277 | self.dataOut.flagNoData = False | |
| 278 |
|
278 | |||
| 279 | if hasattr(self.dataIn, 'ChanDist'): #Distances of receiver channels |
|
279 | if hasattr(self.dataIn, 'ChanDist'): #Distances of receiver channels | |
| 280 | self.dataOut.ChanDist = self.dataIn.ChanDist |
|
280 | self.dataOut.ChanDist = self.dataIn.ChanDist | |
| 281 | else: self.dataOut.ChanDist = None |
|
281 | else: self.dataOut.ChanDist = None | |
| 282 |
|
282 | |||
| 283 | #if hasattr(self.dataIn, 'VelRange'): #Velocities range |
|
283 | #if hasattr(self.dataIn, 'VelRange'): #Velocities range | |
| 284 | # self.dataOut.VelRange = self.dataIn.VelRange |
|
284 | # self.dataOut.VelRange = self.dataIn.VelRange | |
| 285 | #else: self.dataOut.VelRange = None |
|
285 | #else: self.dataOut.VelRange = None | |
| 286 |
|
286 | |||
| 287 |
|
287 | |||
| 288 |
|
288 | |||
| 289 | else: |
|
289 | else: | |
| 290 | raise ValueError("The type of input object {} is not valid".format( |
|
290 | raise ValueError("The type of input object {} is not valid".format( | |
| 291 | self.dataIn.type)) |
|
291 | self.dataIn.type)) | |
| 292 |
|
292 | |||
| 293 |
|
293 | |||
| 294 |
|
294 | |||
| 295 |
|
295 | |||
| 296 | #print("spc proc Done", self.dataOut.data_spc.shape) |
|
296 | #print("spc proc Done", self.dataOut.data_spc.shape) | |
| 297 | #print(self.dataOut.data_spc) |
|
297 | #print(self.dataOut.data_spc) | |
| 298 | return |
|
298 | return | |
| 299 |
|
299 | |||
| 300 | def __selectPairs(self, pairsList): |
|
300 | def __selectPairs(self, pairsList): | |
| 301 |
|
301 | |||
| 302 | if not pairsList: |
|
302 | if not pairsList: | |
| 303 | return |
|
303 | return | |
| 304 |
|
304 | |||
| 305 | pairs = [] |
|
305 | pairs = [] | |
| 306 | pairsIndex = [] |
|
306 | pairsIndex = [] | |
| 307 |
|
307 | |||
| 308 | for pair in pairsList: |
|
308 | for pair in pairsList: | |
| 309 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: |
|
309 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: | |
| 310 | continue |
|
310 | continue | |
| 311 | pairs.append(pair) |
|
311 | pairs.append(pair) | |
| 312 | pairsIndex.append(pairs.index(pair)) |
|
312 | pairsIndex.append(pairs.index(pair)) | |
| 313 |
|
313 | |||
| 314 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] |
|
314 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] | |
| 315 | self.dataOut.pairsList = pairs |
|
315 | self.dataOut.pairsList = pairs | |
| 316 |
|
316 | |||
| 317 | return |
|
317 | return | |
| 318 |
|
318 | |||
| 319 | def selectFFTs(self, minFFT, maxFFT ): |
|
319 | def selectFFTs(self, minFFT, maxFFT ): | |
| 320 | """ |
|
320 | """ | |
| 321 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango |
|
321 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango | |
| 322 | minFFT<= FFT <= maxFFT |
|
322 | minFFT<= FFT <= maxFFT | |
| 323 | """ |
|
323 | """ | |
| 324 |
|
324 | |||
| 325 | if (minFFT > maxFFT): |
|
325 | if (minFFT > maxFFT): | |
| 326 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) |
|
326 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) | |
| 327 |
|
327 | |||
| 328 | if (minFFT < self.dataOut.getFreqRange()[0]): |
|
328 | if (minFFT < self.dataOut.getFreqRange()[0]): | |
| 329 | minFFT = self.dataOut.getFreqRange()[0] |
|
329 | minFFT = self.dataOut.getFreqRange()[0] | |
| 330 |
|
330 | |||
| 331 | if (maxFFT > self.dataOut.getFreqRange()[-1]): |
|
331 | if (maxFFT > self.dataOut.getFreqRange()[-1]): | |
| 332 | maxFFT = self.dataOut.getFreqRange()[-1] |
|
332 | maxFFT = self.dataOut.getFreqRange()[-1] | |
| 333 |
|
333 | |||
| 334 | minIndex = 0 |
|
334 | minIndex = 0 | |
| 335 | maxIndex = 0 |
|
335 | maxIndex = 0 | |
| 336 | FFTs = self.dataOut.getFreqRange() |
|
336 | FFTs = self.dataOut.getFreqRange() | |
| 337 |
|
337 | |||
| 338 | inda = numpy.where(FFTs >= minFFT) |
|
338 | inda = numpy.where(FFTs >= minFFT) | |
| 339 | indb = numpy.where(FFTs <= maxFFT) |
|
339 | indb = numpy.where(FFTs <= maxFFT) | |
| 340 |
|
340 | |||
| 341 | try: |
|
341 | try: | |
| 342 | minIndex = inda[0][0] |
|
342 | minIndex = inda[0][0] | |
| 343 | except: |
|
343 | except: | |
| 344 | minIndex = 0 |
|
344 | minIndex = 0 | |
| 345 |
|
345 | |||
| 346 | try: |
|
346 | try: | |
| 347 | maxIndex = indb[0][-1] |
|
347 | maxIndex = indb[0][-1] | |
| 348 | except: |
|
348 | except: | |
| 349 | maxIndex = len(FFTs) |
|
349 | maxIndex = len(FFTs) | |
| 350 |
|
350 | |||
| 351 | self.selectFFTsByIndex(minIndex, maxIndex) |
|
351 | self.selectFFTsByIndex(minIndex, maxIndex) | |
| 352 |
|
352 | |||
| 353 | return 1 |
|
353 | return 1 | |
| 354 |
|
354 | |||
| 355 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): |
|
355 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): | |
| 356 | newheis = numpy.where( |
|
356 | newheis = numpy.where( | |
| 357 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
357 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 358 |
|
358 | |||
| 359 | if hei_ref != None: |
|
359 | if hei_ref != None: | |
| 360 | newheis = numpy.where(self.dataOut.heightList > hei_ref) |
|
360 | newheis = numpy.where(self.dataOut.heightList > hei_ref) | |
| 361 |
|
361 | |||
| 362 | minIndex = min(newheis[0]) |
|
362 | minIndex = min(newheis[0]) | |
| 363 | maxIndex = max(newheis[0]) |
|
363 | maxIndex = max(newheis[0]) | |
| 364 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
364 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] | |
| 365 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
365 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] | |
| 366 |
|
366 | |||
| 367 | # determina indices |
|
367 | # determina indices | |
| 368 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / |
|
368 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / | |
| 369 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) |
|
369 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) | |
| 370 | avg_dB = 10 * \ |
|
370 | avg_dB = 10 * \ | |
| 371 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) |
|
371 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) | |
| 372 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
372 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 373 | beacon_heiIndexList = [] |
|
373 | beacon_heiIndexList = [] | |
| 374 | for val in avg_dB.tolist(): |
|
374 | for val in avg_dB.tolist(): | |
| 375 | if val >= beacon_dB[0]: |
|
375 | if val >= beacon_dB[0]: | |
| 376 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
376 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 377 |
|
377 | |||
| 378 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
378 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 379 | data_cspc = None |
|
379 | data_cspc = None | |
| 380 | if self.dataOut.data_cspc is not None: |
|
380 | if self.dataOut.data_cspc is not None: | |
| 381 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
381 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] | |
| 382 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
382 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 383 |
|
383 | |||
| 384 | data_dc = None |
|
384 | data_dc = None | |
| 385 | if self.dataOut.data_dc is not None: |
|
385 | if self.dataOut.data_dc is not None: | |
| 386 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
386 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] | |
| 387 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
387 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 388 |
|
388 | |||
| 389 | self.dataOut.data_spc = data_spc |
|
389 | self.dataOut.data_spc = data_spc | |
| 390 | self.dataOut.data_cspc = data_cspc |
|
390 | self.dataOut.data_cspc = data_cspc | |
| 391 | self.dataOut.data_dc = data_dc |
|
391 | self.dataOut.data_dc = data_dc | |
| 392 | self.dataOut.heightList = heightList |
|
392 | self.dataOut.heightList = heightList | |
| 393 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
393 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 394 |
|
394 | |||
| 395 | return 1 |
|
395 | return 1 | |
| 396 |
|
396 | |||
| 397 | def selectFFTsByIndex(self, minIndex, maxIndex): |
|
397 | def selectFFTsByIndex(self, minIndex, maxIndex): | |
| 398 | """ |
|
398 | """ | |
| 399 |
|
399 | |||
| 400 | """ |
|
400 | """ | |
| 401 |
|
401 | |||
| 402 | if (minIndex < 0) or (minIndex > maxIndex): |
|
402 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 403 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
403 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) | |
| 404 |
|
404 | |||
| 405 | if (maxIndex >= self.dataOut.nProfiles): |
|
405 | if (maxIndex >= self.dataOut.nProfiles): | |
| 406 | maxIndex = self.dataOut.nProfiles-1 |
|
406 | maxIndex = self.dataOut.nProfiles-1 | |
| 407 |
|
407 | |||
| 408 | #Spectra |
|
408 | #Spectra | |
| 409 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] |
|
409 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] | |
| 410 |
|
410 | |||
| 411 | data_cspc = None |
|
411 | data_cspc = None | |
| 412 | if self.dataOut.data_cspc is not None: |
|
412 | if self.dataOut.data_cspc is not None: | |
| 413 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] |
|
413 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] | |
| 414 |
|
414 | |||
| 415 | data_dc = None |
|
415 | data_dc = None | |
| 416 | if self.dataOut.data_dc is not None: |
|
416 | if self.dataOut.data_dc is not None: | |
| 417 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] |
|
417 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] | |
| 418 |
|
418 | |||
| 419 | self.dataOut.data_spc = data_spc |
|
419 | self.dataOut.data_spc = data_spc | |
| 420 | self.dataOut.data_cspc = data_cspc |
|
420 | self.dataOut.data_cspc = data_cspc | |
| 421 | self.dataOut.data_dc = data_dc |
|
421 | self.dataOut.data_dc = data_dc | |
| 422 |
|
422 | |||
| 423 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) |
|
423 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) | |
| 424 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] |
|
424 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] | |
| 425 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] |
|
425 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] | |
| 426 |
|
426 | |||
| 427 | return 1 |
|
427 | return 1 | |
| 428 |
|
428 | |||
| 429 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
429 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 430 | # validacion de rango |
|
430 | # validacion de rango | |
| 431 | if minHei == None: |
|
431 | if minHei == None: | |
| 432 | minHei = self.dataOut.heightList[0] |
|
432 | minHei = self.dataOut.heightList[0] | |
| 433 |
|
433 | |||
| 434 | if maxHei == None: |
|
434 | if maxHei == None: | |
| 435 | maxHei = self.dataOut.heightList[-1] |
|
435 | maxHei = self.dataOut.heightList[-1] | |
| 436 |
|
436 | |||
| 437 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
437 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 438 | print('minHei: %.2f is out of the heights range' % (minHei)) |
|
438 | print('minHei: %.2f is out of the heights range' % (minHei)) | |
| 439 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) |
|
439 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) | |
| 440 | minHei = self.dataOut.heightList[0] |
|
440 | minHei = self.dataOut.heightList[0] | |
| 441 |
|
441 | |||
| 442 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
442 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 443 | print('maxHei: %.2f is out of the heights range' % (maxHei)) |
|
443 | print('maxHei: %.2f is out of the heights range' % (maxHei)) | |
| 444 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) |
|
444 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) | |
| 445 | maxHei = self.dataOut.heightList[-1] |
|
445 | maxHei = self.dataOut.heightList[-1] | |
| 446 |
|
446 | |||
| 447 | # validacion de velocidades |
|
447 | # validacion de velocidades | |
| 448 | velrange = self.dataOut.getVelRange(1) |
|
448 | velrange = self.dataOut.getVelRange(1) | |
| 449 |
|
449 | |||
| 450 | if minVel == None: |
|
450 | if minVel == None: | |
| 451 | minVel = velrange[0] |
|
451 | minVel = velrange[0] | |
| 452 |
|
452 | |||
| 453 | if maxVel == None: |
|
453 | if maxVel == None: | |
| 454 | maxVel = velrange[-1] |
|
454 | maxVel = velrange[-1] | |
| 455 |
|
455 | |||
| 456 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
456 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 457 | print('minVel: %.2f is out of the velocity range' % (minVel)) |
|
457 | print('minVel: %.2f is out of the velocity range' % (minVel)) | |
| 458 | print('minVel is setting to %.2f' % (velrange[0])) |
|
458 | print('minVel is setting to %.2f' % (velrange[0])) | |
| 459 | minVel = velrange[0] |
|
459 | minVel = velrange[0] | |
| 460 |
|
460 | |||
| 461 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
461 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 462 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) |
|
462 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) | |
| 463 | print('maxVel is setting to %.2f' % (velrange[-1])) |
|
463 | print('maxVel is setting to %.2f' % (velrange[-1])) | |
| 464 | maxVel = velrange[-1] |
|
464 | maxVel = velrange[-1] | |
| 465 |
|
465 | |||
| 466 | # seleccion de indices para rango |
|
466 | # seleccion de indices para rango | |
| 467 | minIndex = 0 |
|
467 | minIndex = 0 | |
| 468 | maxIndex = 0 |
|
468 | maxIndex = 0 | |
| 469 | heights = self.dataOut.heightList |
|
469 | heights = self.dataOut.heightList | |
| 470 |
|
470 | |||
| 471 | inda = numpy.where(heights >= minHei) |
|
471 | inda = numpy.where(heights >= minHei) | |
| 472 | indb = numpy.where(heights <= maxHei) |
|
472 | indb = numpy.where(heights <= maxHei) | |
| 473 |
|
473 | |||
| 474 | try: |
|
474 | try: | |
| 475 | minIndex = inda[0][0] |
|
475 | minIndex = inda[0][0] | |
| 476 | except: |
|
476 | except: | |
| 477 | minIndex = 0 |
|
477 | minIndex = 0 | |
| 478 |
|
478 | |||
| 479 | try: |
|
479 | try: | |
| 480 | maxIndex = indb[0][-1] |
|
480 | maxIndex = indb[0][-1] | |
| 481 | except: |
|
481 | except: | |
| 482 | maxIndex = len(heights) |
|
482 | maxIndex = len(heights) | |
| 483 |
|
483 | |||
| 484 | if (minIndex < 0) or (minIndex > maxIndex): |
|
484 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 485 | raise ValueError("some value in (%d,%d) is not valid" % ( |
|
485 | raise ValueError("some value in (%d,%d) is not valid" % ( | |
| 486 | minIndex, maxIndex)) |
|
486 | minIndex, maxIndex)) | |
| 487 |
|
487 | |||
| 488 | if (maxIndex >= self.dataOut.nHeights): |
|
488 | if (maxIndex >= self.dataOut.nHeights): | |
| 489 | maxIndex = self.dataOut.nHeights - 1 |
|
489 | maxIndex = self.dataOut.nHeights - 1 | |
| 490 |
|
490 | |||
| 491 | # seleccion de indices para velocidades |
|
491 | # seleccion de indices para velocidades | |
| 492 | indminvel = numpy.where(velrange >= minVel) |
|
492 | indminvel = numpy.where(velrange >= minVel) | |
| 493 | indmaxvel = numpy.where(velrange <= maxVel) |
|
493 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 494 | try: |
|
494 | try: | |
| 495 | minIndexVel = indminvel[0][0] |
|
495 | minIndexVel = indminvel[0][0] | |
| 496 | except: |
|
496 | except: | |
| 497 | minIndexVel = 0 |
|
497 | minIndexVel = 0 | |
| 498 |
|
498 | |||
| 499 | try: |
|
499 | try: | |
| 500 | maxIndexVel = indmaxvel[0][-1] |
|
500 | maxIndexVel = indmaxvel[0][-1] | |
| 501 | except: |
|
501 | except: | |
| 502 | maxIndexVel = len(velrange) |
|
502 | maxIndexVel = len(velrange) | |
| 503 |
|
503 | |||
| 504 | # seleccion del espectro |
|
504 | # seleccion del espectro | |
| 505 | data_spc = self.dataOut.data_spc[:, |
|
505 | data_spc = self.dataOut.data_spc[:, | |
| 506 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] |
|
506 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] | |
| 507 | # estimacion de ruido |
|
507 | # estimacion de ruido | |
| 508 | noise = numpy.zeros(self.dataOut.nChannels) |
|
508 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 509 |
|
509 | |||
| 510 | for channel in range(self.dataOut.nChannels): |
|
510 | for channel in range(self.dataOut.nChannels): | |
| 511 | daux = data_spc[channel, :, :] |
|
511 | daux = data_spc[channel, :, :] | |
| 512 | sortdata = numpy.sort(daux, axis=None) |
|
512 | sortdata = numpy.sort(daux, axis=None) | |
| 513 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) |
|
513 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) | |
| 514 |
|
514 | |||
| 515 | self.dataOut.noise_estimation = noise.copy() |
|
515 | self.dataOut.noise_estimation = noise.copy() | |
| 516 |
|
516 | |||
| 517 | return 1 |
|
517 | return 1 | |
| 518 |
|
518 | |||
| 519 | class removeDC(Operation): |
|
519 | class removeDC(Operation): | |
| 520 |
|
520 | |||
| 521 | def run(self, dataOut, mode=2): |
|
521 | def run(self, dataOut, mode=2): | |
| 522 | self.dataOut = dataOut |
|
522 | self.dataOut = dataOut | |
| 523 | jspectra = self.dataOut.data_spc |
|
523 | jspectra = self.dataOut.data_spc | |
| 524 | jcspectra = self.dataOut.data_cspc |
|
524 | jcspectra = self.dataOut.data_cspc | |
| 525 |
|
525 | |||
| 526 | num_chan = jspectra.shape[0] |
|
526 | num_chan = jspectra.shape[0] | |
| 527 | num_hei = jspectra.shape[2] |
|
527 | num_hei = jspectra.shape[2] | |
| 528 |
|
528 | |||
| 529 | if jcspectra is not None: |
|
529 | if jcspectra is not None: | |
| 530 | jcspectraExist = True |
|
530 | jcspectraExist = True | |
| 531 | num_pairs = jcspectra.shape[0] |
|
531 | num_pairs = jcspectra.shape[0] | |
| 532 | else: |
|
532 | else: | |
| 533 | jcspectraExist = False |
|
533 | jcspectraExist = False | |
| 534 |
|
534 | |||
| 535 | freq_dc = int(jspectra.shape[1] / 2) |
|
535 | freq_dc = int(jspectra.shape[1] / 2) | |
| 536 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc |
|
536 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc | |
| 537 | ind_vel = ind_vel.astype(int) |
|
537 | ind_vel = ind_vel.astype(int) | |
| 538 |
|
538 | |||
| 539 | if ind_vel[0] < 0: |
|
539 | if ind_vel[0] < 0: | |
| 540 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof |
|
540 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof | |
| 541 |
|
541 | |||
| 542 | if mode == 1: |
|
542 | if mode == 1: | |
| 543 | jspectra[:, freq_dc, :] = ( |
|
543 | jspectra[:, freq_dc, :] = ( | |
| 544 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION |
|
544 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION | |
| 545 |
|
545 | |||
| 546 | if jcspectraExist: |
|
546 | if jcspectraExist: | |
| 547 | jcspectra[:, freq_dc, :] = ( |
|
547 | jcspectra[:, freq_dc, :] = ( | |
| 548 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 |
|
548 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 | |
| 549 |
|
549 | |||
| 550 | if mode == 2: |
|
550 | if mode == 2: | |
| 551 |
|
551 | |||
| 552 | vel = numpy.array([-2, -1, 1, 2]) |
|
552 | vel = numpy.array([-2, -1, 1, 2]) | |
| 553 | xx = numpy.zeros([4, 4]) |
|
553 | xx = numpy.zeros([4, 4]) | |
| 554 |
|
554 | |||
| 555 | for fil in range(4): |
|
555 | for fil in range(4): | |
| 556 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) |
|
556 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) | |
| 557 |
|
557 | |||
| 558 | xx_inv = numpy.linalg.inv(xx) |
|
558 | xx_inv = numpy.linalg.inv(xx) | |
| 559 | xx_aux = xx_inv[0, :] |
|
559 | xx_aux = xx_inv[0, :] | |
| 560 |
|
560 | |||
| 561 | for ich in range(num_chan): |
|
561 | for ich in range(num_chan): | |
| 562 | yy = jspectra[ich, ind_vel, :] |
|
562 | yy = jspectra[ich, ind_vel, :] | |
| 563 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
563 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 564 |
|
564 | |||
| 565 | junkid = jspectra[ich, freq_dc, :] <= 0 |
|
565 | junkid = jspectra[ich, freq_dc, :] <= 0 | |
| 566 | cjunkid = sum(junkid) |
|
566 | cjunkid = sum(junkid) | |
| 567 |
|
567 | |||
| 568 | if cjunkid.any(): |
|
568 | if cjunkid.any(): | |
| 569 | jspectra[ich, freq_dc, junkid.nonzero()] = ( |
|
569 | jspectra[ich, freq_dc, junkid.nonzero()] = ( | |
| 570 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 |
|
570 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 | |
| 571 |
|
571 | |||
| 572 | if jcspectraExist: |
|
572 | if jcspectraExist: | |
| 573 | for ip in range(num_pairs): |
|
573 | for ip in range(num_pairs): | |
| 574 | yy = jcspectra[ip, ind_vel, :] |
|
574 | yy = jcspectra[ip, ind_vel, :] | |
| 575 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
575 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 576 |
|
576 | |||
| 577 | self.dataOut.data_spc = jspectra |
|
577 | self.dataOut.data_spc = jspectra | |
| 578 | self.dataOut.data_cspc = jcspectra |
|
578 | self.dataOut.data_cspc = jcspectra | |
| 579 |
|
579 | |||
| 580 | return self.dataOut |
|
580 | return self.dataOut | |
| 581 |
|
581 | |||
| 582 | class getNoiseB(Operation): |
|
582 | class getNoiseB(Operation): | |
| 583 |
|
583 | |||
| 584 | __slots__ =('offset','warnings', 'isConfig', 'minIndex','maxIndex','minIndexFFT','maxIndexFFT') |
|
584 | __slots__ =('offset','warnings', 'isConfig', 'minIndex','maxIndex','minIndexFFT','maxIndexFFT') | |
| 585 | def __init__(self): |
|
585 | def __init__(self): | |
| 586 |
|
586 | |||
| 587 | Operation.__init__(self) |
|
587 | Operation.__init__(self) | |
| 588 | self.isConfig = False |
|
588 | self.isConfig = False | |
| 589 |
|
589 | |||
| 590 | def setup(self, offset=None, minHei=None, maxHei=None,minVel=None, maxVel=None, minFreq= None, maxFreq=None, warnings=False): |
|
590 | def setup(self, offset=None, minHei=None, maxHei=None,minVel=None, maxVel=None, minFreq= None, maxFreq=None, warnings=False): | |
| 591 |
|
591 | |||
| 592 | self.warnings = warnings |
|
592 | self.warnings = warnings | |
| 593 | if minHei == None: |
|
593 | if minHei == None: | |
| 594 | minHei = self.dataOut.heightList[0] |
|
594 | minHei = self.dataOut.heightList[0] | |
| 595 |
|
595 | |||
| 596 | if maxHei == None: |
|
596 | if maxHei == None: | |
| 597 | maxHei = self.dataOut.heightList[-1] |
|
597 | maxHei = self.dataOut.heightList[-1] | |
| 598 |
|
598 | |||
| 599 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
599 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 600 | if self.warnings: |
|
600 | if self.warnings: | |
| 601 | print('minHei: %.2f is out of the heights range' % (minHei)) |
|
601 | print('minHei: %.2f is out of the heights range' % (minHei)) | |
| 602 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) |
|
602 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) | |
| 603 | minHei = self.dataOut.heightList[0] |
|
603 | minHei = self.dataOut.heightList[0] | |
| 604 |
|
604 | |||
| 605 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
605 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 606 | if self.warnings: |
|
606 | if self.warnings: | |
| 607 | print('maxHei: %.2f is out of the heights range' % (maxHei)) |
|
607 | print('maxHei: %.2f is out of the heights range' % (maxHei)) | |
| 608 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) |
|
608 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) | |
| 609 | maxHei = self.dataOut.heightList[-1] |
|
609 | maxHei = self.dataOut.heightList[-1] | |
| 610 |
|
610 | |||
| 611 |
|
611 | |||
| 612 | #indices relativos a los puntos de fft, puede ser de acuerdo a velocidad o frecuencia |
|
612 | #indices relativos a los puntos de fft, puede ser de acuerdo a velocidad o frecuencia | |
| 613 | minIndexFFT = 0 |
|
613 | minIndexFFT = 0 | |
| 614 | maxIndexFFT = 0 |
|
614 | maxIndexFFT = 0 | |
| 615 | # validacion de velocidades |
|
615 | # validacion de velocidades | |
| 616 | indminPoint = None |
|
616 | indminPoint = None | |
| 617 | indmaxPoint = None |
|
617 | indmaxPoint = None | |
| 618 | if self.dataOut.type == 'Spectra': |
|
618 | if self.dataOut.type == 'Spectra': | |
| 619 | if minVel == None and maxVel == None : |
|
619 | if minVel == None and maxVel == None : | |
| 620 |
|
620 | |||
| 621 | freqrange = self.dataOut.getFreqRange(1) |
|
621 | freqrange = self.dataOut.getFreqRange(1) | |
| 622 |
|
622 | |||
| 623 | if minFreq == None: |
|
623 | if minFreq == None: | |
| 624 | minFreq = freqrange[0] |
|
624 | minFreq = freqrange[0] | |
| 625 |
|
625 | |||
| 626 | if maxFreq == None: |
|
626 | if maxFreq == None: | |
| 627 | maxFreq = freqrange[-1] |
|
627 | maxFreq = freqrange[-1] | |
| 628 |
|
628 | |||
| 629 | if (minFreq < freqrange[0]) or (minFreq > maxFreq): |
|
629 | if (minFreq < freqrange[0]) or (minFreq > maxFreq): | |
| 630 | if self.warnings: |
|
630 | if self.warnings: | |
| 631 | print('minFreq: %.2f is out of the frequency range' % (minFreq)) |
|
631 | print('minFreq: %.2f is out of the frequency range' % (minFreq)) | |
| 632 | print('minFreq is setting to %.2f' % (freqrange[0])) |
|
632 | print('minFreq is setting to %.2f' % (freqrange[0])) | |
| 633 | minFreq = freqrange[0] |
|
633 | minFreq = freqrange[0] | |
| 634 |
|
634 | |||
| 635 | if (maxFreq > freqrange[-1]) or (maxFreq < minFreq): |
|
635 | if (maxFreq > freqrange[-1]) or (maxFreq < minFreq): | |
| 636 | if self.warnings: |
|
636 | if self.warnings: | |
| 637 | print('maxFreq: %.2f is out of the frequency range' % (maxFreq)) |
|
637 | print('maxFreq: %.2f is out of the frequency range' % (maxFreq)) | |
| 638 | print('maxFreq is setting to %.2f' % (freqrange[-1])) |
|
638 | print('maxFreq is setting to %.2f' % (freqrange[-1])) | |
| 639 | maxFreq = freqrange[-1] |
|
639 | maxFreq = freqrange[-1] | |
| 640 |
|
640 | |||
| 641 | indminPoint = numpy.where(freqrange >= minFreq) |
|
641 | indminPoint = numpy.where(freqrange >= minFreq) | |
| 642 | indmaxPoint = numpy.where(freqrange <= maxFreq) |
|
642 | indmaxPoint = numpy.where(freqrange <= maxFreq) | |
| 643 |
|
643 | |||
| 644 | else: |
|
644 | else: | |
| 645 |
|
645 | |||
| 646 | velrange = self.dataOut.getVelRange(1) |
|
646 | velrange = self.dataOut.getVelRange(1) | |
| 647 |
|
647 | |||
| 648 | if minVel == None: |
|
648 | if minVel == None: | |
| 649 | minVel = velrange[0] |
|
649 | minVel = velrange[0] | |
| 650 |
|
650 | |||
| 651 | if maxVel == None: |
|
651 | if maxVel == None: | |
| 652 | maxVel = velrange[-1] |
|
652 | maxVel = velrange[-1] | |
| 653 |
|
653 | |||
| 654 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
654 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 655 | if self.warnings: |
|
655 | if self.warnings: | |
| 656 | print('minVel: %.2f is out of the velocity range' % (minVel)) |
|
656 | print('minVel: %.2f is out of the velocity range' % (minVel)) | |
| 657 | print('minVel is setting to %.2f' % (velrange[0])) |
|
657 | print('minVel is setting to %.2f' % (velrange[0])) | |
| 658 | minVel = velrange[0] |
|
658 | minVel = velrange[0] | |
| 659 |
|
659 | |||
| 660 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
660 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 661 | if self.warnings: |
|
661 | if self.warnings: | |
| 662 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) |
|
662 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) | |
| 663 | print('maxVel is setting to %.2f' % (velrange[-1])) |
|
663 | print('maxVel is setting to %.2f' % (velrange[-1])) | |
| 664 | maxVel = velrange[-1] |
|
664 | maxVel = velrange[-1] | |
| 665 |
|
665 | |||
| 666 | indminPoint = numpy.where(velrange >= minVel) |
|
666 | indminPoint = numpy.where(velrange >= minVel) | |
| 667 | indmaxPoint = numpy.where(velrange <= maxVel) |
|
667 | indmaxPoint = numpy.where(velrange <= maxVel) | |
| 668 |
|
668 | |||
| 669 |
|
669 | |||
| 670 | # seleccion de indices para rango |
|
670 | # seleccion de indices para rango | |
| 671 | minIndex = 0 |
|
671 | minIndex = 0 | |
| 672 | maxIndex = 0 |
|
672 | maxIndex = 0 | |
| 673 | heights = self.dataOut.heightList |
|
673 | heights = self.dataOut.heightList | |
| 674 |
|
674 | |||
| 675 | inda = numpy.where(heights >= minHei) |
|
675 | inda = numpy.where(heights >= minHei) | |
| 676 | indb = numpy.where(heights <= maxHei) |
|
676 | indb = numpy.where(heights <= maxHei) | |
| 677 |
|
677 | |||
| 678 | try: |
|
678 | try: | |
| 679 | minIndex = inda[0][0] |
|
679 | minIndex = inda[0][0] | |
| 680 | except: |
|
680 | except: | |
| 681 | minIndex = 0 |
|
681 | minIndex = 0 | |
| 682 |
|
682 | |||
| 683 | try: |
|
683 | try: | |
| 684 | maxIndex = indb[0][-1] |
|
684 | maxIndex = indb[0][-1] | |
| 685 | except: |
|
685 | except: | |
| 686 | maxIndex = len(heights) |
|
686 | maxIndex = len(heights) | |
| 687 |
|
687 | |||
| 688 | if (minIndex < 0) or (minIndex > maxIndex): |
|
688 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 689 | raise ValueError("some value in (%d,%d) is not valid" % ( |
|
689 | raise ValueError("some value in (%d,%d) is not valid" % ( | |
| 690 | minIndex, maxIndex)) |
|
690 | minIndex, maxIndex)) | |
| 691 |
|
691 | |||
| 692 | if (maxIndex >= self.dataOut.nHeights): |
|
692 | if (maxIndex >= self.dataOut.nHeights): | |
| 693 | maxIndex = self.dataOut.nHeights - 1 |
|
693 | maxIndex = self.dataOut.nHeights - 1 | |
| 694 | #############################################################3 |
|
694 | #############################################################3 | |
| 695 | # seleccion de indices para velocidades |
|
695 | # seleccion de indices para velocidades | |
| 696 | if self.dataOut.type == 'Spectra': |
|
696 | if self.dataOut.type == 'Spectra': | |
| 697 | try: |
|
697 | try: | |
| 698 | minIndexFFT = indminPoint[0][0] |
|
698 | minIndexFFT = indminPoint[0][0] | |
| 699 | except: |
|
699 | except: | |
| 700 | minIndexFFT = 0 |
|
700 | minIndexFFT = 0 | |
| 701 |
|
701 | |||
| 702 | try: |
|
702 | try: | |
| 703 | maxIndexFFT = indmaxPoint[0][-1] |
|
703 | maxIndexFFT = indmaxPoint[0][-1] | |
| 704 | except: |
|
704 | except: | |
| 705 | maxIndexFFT = len( self.dataOut.getFreqRange(1)) |
|
705 | maxIndexFFT = len( self.dataOut.getFreqRange(1)) | |
| 706 |
|
706 | |||
| 707 | self.minIndex, self.maxIndex, self.minIndexFFT, self.maxIndexFFT = minIndex, maxIndex, minIndexFFT, maxIndexFFT |
|
707 | self.minIndex, self.maxIndex, self.minIndexFFT, self.maxIndexFFT = minIndex, maxIndex, minIndexFFT, maxIndexFFT | |
| 708 | self.isConfig = True |
|
708 | self.isConfig = True | |
| 709 | self.offset = 1 |
|
709 | self.offset = 1 | |
| 710 | if offset!=None: |
|
710 | if offset!=None: | |
| 711 | self.offset = 10**(offset/10) |
|
711 | self.offset = 10**(offset/10) | |
| 712 | #print("config getNoiseB Done") |
|
712 | #print("config getNoiseB Done") | |
| 713 |
|
713 | |||
| 714 | def run(self, dataOut, offset=None, minHei=None, maxHei=None,minVel=None, maxVel=None, minFreq= None, maxFreq=None, warnings=False): |
|
714 | def run(self, dataOut, offset=None, minHei=None, maxHei=None,minVel=None, maxVel=None, minFreq= None, maxFreq=None, warnings=False): | |
| 715 | self.dataOut = dataOut |
|
715 | self.dataOut = dataOut | |
| 716 |
|
716 | |||
| 717 | if not self.isConfig: |
|
717 | if not self.isConfig: | |
| 718 | self.setup(offset, minHei, maxHei,minVel, maxVel, minFreq, maxFreq, warnings) |
|
718 | self.setup(offset, minHei, maxHei,minVel, maxVel, minFreq, maxFreq, warnings) | |
| 719 |
|
719 | |||
| 720 | self.dataOut.noise_estimation = None |
|
720 | self.dataOut.noise_estimation = None | |
| 721 | noise = None |
|
721 | noise = None | |
| 722 | #print("data type: ",self.dataOut.type, self.dataOut.nIncohInt, self.dataOut.max_nIncohInt) |
|
722 | #print("data type: ",self.dataOut.type, self.dataOut.nIncohInt, self.dataOut.max_nIncohInt) | |
| 723 | if self.dataOut.type == 'Voltage': |
|
723 | if self.dataOut.type == 'Voltage': | |
| 724 | noise = self.dataOut.getNoise(ymin_index=self.minIndex, ymax_index=self.maxIndex) |
|
724 | noise = self.dataOut.getNoise(ymin_index=self.minIndex, ymax_index=self.maxIndex) | |
| 725 | #print(minIndex, maxIndex,minIndexVel, maxIndexVel) |
|
725 | #print(minIndex, maxIndex,minIndexVel, maxIndexVel) | |
| 726 | elif self.dataOut.type == 'Spectra': |
|
726 | elif self.dataOut.type == 'Spectra': | |
| 727 | #print(self.dataOut.nChannels, self.minIndex, self.maxIndex,self.minIndexFFT, self.maxIndexFFT, self.dataOut.max_nIncohInt, self.dataOut.nIncohInt) |
|
727 | #print(self.dataOut.nChannels, self.minIndex, self.maxIndex,self.minIndexFFT, self.maxIndexFFT, self.dataOut.max_nIncohInt, self.dataOut.nIncohInt) | |
| 728 | noise = numpy.zeros( self.dataOut.nChannels) |
|
728 | noise = numpy.zeros( self.dataOut.nChannels) | |
| 729 | norm = 1 |
|
729 | norm = 1 | |
| 730 |
|
730 | |||
| 731 | for channel in range( self.dataOut.nChannels): |
|
731 | for channel in range( self.dataOut.nChannels): | |
| 732 | if not hasattr(self.dataOut.nIncohInt,'__len__'): |
|
732 | if not hasattr(self.dataOut.nIncohInt,'__len__'): | |
| 733 | norm = 1 |
|
733 | norm = 1 | |
| 734 | else: |
|
734 | else: | |
| 735 | norm = self.dataOut.max_nIncohInt[channel]/self.dataOut.nIncohInt[channel, self.minIndex:self.maxIndex] |
|
735 | norm = self.dataOut.max_nIncohInt[channel]/self.dataOut.nIncohInt[channel, self.minIndex:self.maxIndex] | |
| 736 |
|
736 | |||
| 737 | #print("norm nIncoh: ", norm ,self.dataOut.data_spc.shape, self.dataOut.max_nIncohInt) |
|
737 | #print("norm nIncoh: ", norm ,self.dataOut.data_spc.shape, self.dataOut.max_nIncohInt) | |
| 738 | daux = self.dataOut.data_spc[channel,self.minIndexFFT:self.maxIndexFFT, self.minIndex:self.maxIndex] |
|
738 | daux = self.dataOut.data_spc[channel,self.minIndexFFT:self.maxIndexFFT, self.minIndex:self.maxIndex] | |
| 739 | daux = numpy.multiply(daux, norm) |
|
739 | daux = numpy.multiply(daux, norm) | |
| 740 | #print("offset: ", self.offset, 10*numpy.log10(self.offset)) |
|
740 | #print("offset: ", self.offset, 10*numpy.log10(self.offset)) | |
| 741 | # noise[channel] = self.getNoiseByMean(daux)/self.offset |
|
741 | # noise[channel] = self.getNoiseByMean(daux)/self.offset | |
| 742 | #print(daux.shape, daux) |
|
742 | #print(daux.shape, daux) | |
| 743 | #noise[channel] = self.getNoiseByHS(daux, self.dataOut.max_nIncohInt)/self.offset |
|
743 | #noise[channel] = self.getNoiseByHS(daux, self.dataOut.max_nIncohInt)/self.offset | |
| 744 | sortdata = numpy.sort(daux, axis=None) |
|
744 | sortdata = numpy.sort(daux, axis=None) | |
| 745 |
|
745 | |||
| 746 | noise[channel] = _noise.hildebrand_sekhon(sortdata, self.dataOut.max_nIncohInt[channel])/self.offset |
|
746 | noise[channel] = _noise.hildebrand_sekhon(sortdata, self.dataOut.max_nIncohInt[channel])/self.offset | |
| 747 | #print("noise shape", noise[channel], self.name) |
|
747 | #print("noise shape", noise[channel], self.name) | |
| 748 |
|
748 | |||
| 749 | #noise = self.dataOut.getNoise(xmin_index=self.minIndexFFT, xmax_index=self.maxIndexFFT, ymin_index=self.minIndex, ymax_index=self.maxIndex) |
|
749 | #noise = self.dataOut.getNoise(xmin_index=self.minIndexFFT, xmax_index=self.maxIndexFFT, ymin_index=self.minIndex, ymax_index=self.maxIndex) | |
| 750 | else: |
|
750 | else: | |
| 751 | noise = self.dataOut.getNoise(xmin_index=self.minIndexFFT, xmax_index=self.maxIndexFFT, ymin_index=self.minIndex, ymax_index=self.maxIndex) |
|
751 | noise = self.dataOut.getNoise(xmin_index=self.minIndexFFT, xmax_index=self.maxIndexFFT, ymin_index=self.minIndex, ymax_index=self.maxIndex) | |
| 752 |
|
752 | |||
| 753 | self.dataOut.noise_estimation = noise.copy() # dataOut.noise |
|
753 | self.dataOut.noise_estimation = noise.copy() # dataOut.noise | |
| 754 | #print("2: ",10*numpy.log10(self.dataOut.noise_estimation/64)) |
|
754 | #print("2: ",10*numpy.log10(self.dataOut.noise_estimation/64)) | |
| 755 | #print("2: ",self.dataOut.noise_estimation) |
|
755 | #print("2: ",self.dataOut.noise_estimation) | |
| 756 | #print(self.dataOut.flagNoData) |
|
756 | #print(self.dataOut.flagNoData) | |
| 757 | #print("getNoise Done", 10*numpy.log10(noise)) |
|
757 | #print("getNoise Done", 10*numpy.log10(noise)) | |
| 758 | return self.dataOut |
|
758 | return self.dataOut | |
| 759 |
|
759 | |||
| 760 | def getNoiseByMean(self,data): |
|
760 | def getNoiseByMean(self,data): | |
| 761 | #data debe estar ordenado |
|
761 | #data debe estar ordenado | |
| 762 | data = numpy.mean(data,axis=1) |
|
762 | data = numpy.mean(data,axis=1) | |
| 763 | sortdata = numpy.sort(data, axis=None) |
|
763 | sortdata = numpy.sort(data, axis=None) | |
| 764 | #sortID=data.argsort() |
|
764 | #sortID=data.argsort() | |
| 765 | #print(data.shape) |
|
765 | #print(data.shape) | |
| 766 |
|
766 | |||
| 767 | pnoise = None |
|
767 | pnoise = None | |
| 768 | j = 0 |
|
768 | j = 0 | |
| 769 |
|
769 | |||
| 770 | mean = numpy.mean(sortdata) |
|
770 | mean = numpy.mean(sortdata) | |
| 771 | min = numpy.min(sortdata) |
|
771 | min = numpy.min(sortdata) | |
| 772 | delta = mean - min |
|
772 | delta = mean - min | |
| 773 | indexes = numpy.where(sortdata > (mean+delta))[0] #only array of indexes |
|
773 | indexes = numpy.where(sortdata > (mean+delta))[0] #only array of indexes | |
| 774 | #print(len(indexes)) |
|
774 | #print(len(indexes)) | |
| 775 | if len(indexes)==0: |
|
775 | if len(indexes)==0: | |
| 776 | pnoise = numpy.mean(sortdata) |
|
776 | pnoise = numpy.mean(sortdata) | |
| 777 | else: |
|
777 | else: | |
| 778 | j = indexes[0] |
|
778 | j = indexes[0] | |
| 779 | pnoise = numpy.mean(sortdata[0:j]) |
|
779 | pnoise = numpy.mean(sortdata[0:j]) | |
| 780 |
|
780 | |||
| 781 | # from matplotlib import pyplot as plt |
|
781 | # from matplotlib import pyplot as plt | |
| 782 | # plt.plot(sortdata) |
|
782 | # plt.plot(sortdata) | |
| 783 | # plt.vlines(j,(pnoise-delta),(pnoise+delta), color='r') |
|
783 | # plt.vlines(j,(pnoise-delta),(pnoise+delta), color='r') | |
| 784 | # plt.show() |
|
784 | # plt.show() | |
| 785 | #print("noise: ", 10*numpy.log10(pnoise)) |
|
785 | #print("noise: ", 10*numpy.log10(pnoise)) | |
| 786 | return pnoise |
|
786 | return pnoise | |
| 787 |
|
787 | |||
| 788 | def getNoiseByHS(self,data, navg): |
|
788 | def getNoiseByHS(self,data, navg): | |
| 789 | #data debe estar ordenado |
|
789 | #data debe estar ordenado | |
| 790 | #data = numpy.mean(data,axis=1) |
|
790 | #data = numpy.mean(data,axis=1) | |
| 791 | sortdata = numpy.sort(data, axis=None) |
|
791 | sortdata = numpy.sort(data, axis=None) | |
| 792 |
|
792 | |||
| 793 | lenOfData = len(sortdata) |
|
793 | lenOfData = len(sortdata) | |
| 794 | nums_min = lenOfData*0.2 |
|
794 | nums_min = lenOfData*0.2 | |
| 795 |
|
795 | |||
| 796 | if nums_min <= 5: |
|
796 | if nums_min <= 5: | |
| 797 |
|
797 | |||
| 798 | nums_min = 5 |
|
798 | nums_min = 5 | |
| 799 |
|
799 | |||
| 800 | sump = 0. |
|
800 | sump = 0. | |
| 801 | sumq = 0. |
|
801 | sumq = 0. | |
| 802 |
|
802 | |||
| 803 | j = 0 |
|
803 | j = 0 | |
| 804 | cont = 1 |
|
804 | cont = 1 | |
| 805 |
|
805 | |||
| 806 | while((cont == 1)and(j < lenOfData)): |
|
806 | while((cont == 1)and(j < lenOfData)): | |
| 807 |
|
807 | |||
| 808 | sump += sortdata[j] |
|
808 | sump += sortdata[j] | |
| 809 | sumq += sortdata[j]**2 |
|
809 | sumq += sortdata[j]**2 | |
| 810 | #sumq -= sump**2 |
|
810 | #sumq -= sump**2 | |
| 811 | if j > nums_min: |
|
811 | if j > nums_min: | |
| 812 | rtest = float(j)/(j-1) + 1.0/navg |
|
812 | rtest = float(j)/(j-1) + 1.0/navg | |
| 813 | #if ((sumq*j) > (sump**2)): |
|
813 | #if ((sumq*j) > (sump**2)): | |
| 814 | if ((sumq*j) > (rtest*sump**2)): |
|
814 | if ((sumq*j) > (rtest*sump**2)): | |
| 815 | j = j - 1 |
|
815 | j = j - 1 | |
| 816 | sump = sump - sortdata[j] |
|
816 | sump = sump - sortdata[j] | |
| 817 | sumq = sumq - sortdata[j]**2 |
|
817 | sumq = sumq - sortdata[j]**2 | |
| 818 | cont = 0 |
|
818 | cont = 0 | |
| 819 |
|
819 | |||
| 820 | j += 1 |
|
820 | j += 1 | |
| 821 |
|
821 | |||
| 822 | lnoise = sump / j |
|
822 | lnoise = sump / j | |
| 823 |
|
823 | |||
| 824 | return lnoise |
|
824 | return lnoise | |
| 825 |
|
825 | |||
| 826 |
|
826 | |||
| 827 |
|
827 | |||
| 828 | def fit_func( x, a0, a1, a2): #, a3, a4, a5): |
|
828 | def fit_func( x, a0, a1, a2): #, a3, a4, a5): | |
| 829 | z = (x - a1) / a2 |
|
829 | z = (x - a1) / a2 | |
| 830 | y = a0 * numpy.exp(-z**2 / a2) #+ a3 + a4 * x + a5 * x**2 |
|
830 | y = a0 * numpy.exp(-z**2 / a2) #+ a3 + a4 * x + a5 * x**2 | |
| 831 | return y |
|
831 | return y | |
| 832 |
|
832 | |||
| 833 |
|
833 | |||
| 834 | # class CleanRayleigh(Operation): |
|
834 | # class CleanRayleigh(Operation): | |
| 835 | # |
|
835 | # | |
| 836 | # def __init__(self): |
|
836 | # def __init__(self): | |
| 837 | # |
|
837 | # | |
| 838 | # Operation.__init__(self) |
|
838 | # Operation.__init__(self) | |
| 839 | # self.i=0 |
|
839 | # self.i=0 | |
| 840 | # self.isConfig = False |
|
840 | # self.isConfig = False | |
| 841 | # self.__dataReady = False |
|
841 | # self.__dataReady = False | |
| 842 | # self.__profIndex = 0 |
|
842 | # self.__profIndex = 0 | |
| 843 | # self.byTime = False |
|
843 | # self.byTime = False | |
| 844 | # self.byProfiles = False |
|
844 | # self.byProfiles = False | |
| 845 | # |
|
845 | # | |
| 846 | # self.bloques = None |
|
846 | # self.bloques = None | |
| 847 | # self.bloque0 = None |
|
847 | # self.bloque0 = None | |
| 848 | # |
|
848 | # | |
| 849 | # self.index = 0 |
|
849 | # self.index = 0 | |
| 850 | # |
|
850 | # | |
| 851 | # self.buffer = 0 |
|
851 | # self.buffer = 0 | |
| 852 | # self.buffer2 = 0 |
|
852 | # self.buffer2 = 0 | |
| 853 | # self.buffer3 = 0 |
|
853 | # self.buffer3 = 0 | |
| 854 | # |
|
854 | # | |
| 855 | # |
|
855 | # | |
| 856 | # def setup(self,dataOut,min_hei,max_hei,n, timeInterval,factor_stdv): |
|
856 | # def setup(self,dataOut,min_hei,max_hei,n, timeInterval,factor_stdv): | |
| 857 | # |
|
857 | # | |
| 858 | # self.nChannels = dataOut.nChannels |
|
858 | # self.nChannels = dataOut.nChannels | |
| 859 | # self.nProf = dataOut.nProfiles |
|
859 | # self.nProf = dataOut.nProfiles | |
| 860 | # self.nPairs = dataOut.data_cspc.shape[0] |
|
860 | # self.nPairs = dataOut.data_cspc.shape[0] | |
| 861 | # self.pairsArray = numpy.array(dataOut.pairsList) |
|
861 | # self.pairsArray = numpy.array(dataOut.pairsList) | |
| 862 | # self.spectra = dataOut.data_spc |
|
862 | # self.spectra = dataOut.data_spc | |
| 863 | # self.cspectra = dataOut.data_cspc |
|
863 | # self.cspectra = dataOut.data_cspc | |
| 864 | # self.heights = dataOut.heightList #alturas totales |
|
864 | # self.heights = dataOut.heightList #alturas totales | |
| 865 | # self.nHeights = len(self.heights) |
|
865 | # self.nHeights = len(self.heights) | |
| 866 | # self.min_hei = min_hei |
|
866 | # self.min_hei = min_hei | |
| 867 | # self.max_hei = max_hei |
|
867 | # self.max_hei = max_hei | |
| 868 | # if (self.min_hei == None): |
|
868 | # if (self.min_hei == None): | |
| 869 | # self.min_hei = 0 |
|
869 | # self.min_hei = 0 | |
| 870 | # if (self.max_hei == None): |
|
870 | # if (self.max_hei == None): | |
| 871 | # self.max_hei = dataOut.heightList[-1] |
|
871 | # self.max_hei = dataOut.heightList[-1] | |
| 872 | # self.hval = ((self.max_hei>=self.heights) & (self.heights >= self.min_hei)).nonzero() |
|
872 | # self.hval = ((self.max_hei>=self.heights) & (self.heights >= self.min_hei)).nonzero() | |
| 873 | # self.heightsClean = self.heights[self.hval] #alturas filtradas |
|
873 | # self.heightsClean = self.heights[self.hval] #alturas filtradas | |
| 874 | # self.hval = self.hval[0] # forma (N,), an solo N elementos -> Indices de alturas |
|
874 | # self.hval = self.hval[0] # forma (N,), an solo N elementos -> Indices de alturas | |
| 875 | # self.nHeightsClean = len(self.heightsClean) |
|
875 | # self.nHeightsClean = len(self.heightsClean) | |
| 876 | # self.channels = dataOut.channelList |
|
876 | # self.channels = dataOut.channelList | |
| 877 | # self.nChan = len(self.channels) |
|
877 | # self.nChan = len(self.channels) | |
| 878 | # self.nIncohInt = dataOut.nIncohInt |
|
878 | # self.nIncohInt = dataOut.nIncohInt | |
| 879 | # self.__initime = dataOut.utctime |
|
879 | # self.__initime = dataOut.utctime | |
| 880 | # self.maxAltInd = self.hval[-1]+1 |
|
880 | # self.maxAltInd = self.hval[-1]+1 | |
| 881 | # self.minAltInd = self.hval[0] |
|
881 | # self.minAltInd = self.hval[0] | |
| 882 | # |
|
882 | # | |
| 883 | # self.crosspairs = dataOut.pairsList |
|
883 | # self.crosspairs = dataOut.pairsList | |
| 884 | # self.nPairs = len(self.crosspairs) |
|
884 | # self.nPairs = len(self.crosspairs) | |
| 885 | # self.normFactor = dataOut.normFactor |
|
885 | # self.normFactor = dataOut.normFactor | |
| 886 | # self.nFFTPoints = dataOut.nFFTPoints |
|
886 | # self.nFFTPoints = dataOut.nFFTPoints | |
| 887 | # self.ippSeconds = dataOut.ippSeconds |
|
887 | # self.ippSeconds = dataOut.ippSeconds | |
| 888 | # self.currentTime = self.__initime |
|
888 | # self.currentTime = self.__initime | |
| 889 | # self.pairsArray = numpy.array(dataOut.pairsList) |
|
889 | # self.pairsArray = numpy.array(dataOut.pairsList) | |
| 890 | # self.factor_stdv = factor_stdv |
|
890 | # self.factor_stdv = factor_stdv | |
| 891 | # |
|
891 | # | |
| 892 | # if n != None : |
|
892 | # if n != None : | |
| 893 | # self.byProfiles = True |
|
893 | # self.byProfiles = True | |
| 894 | # self.nIntProfiles = n |
|
894 | # self.nIntProfiles = n | |
| 895 | # else: |
|
895 | # else: | |
| 896 | # self.__integrationtime = timeInterval |
|
896 | # self.__integrationtime = timeInterval | |
| 897 | # |
|
897 | # | |
| 898 | # self.__dataReady = False |
|
898 | # self.__dataReady = False | |
| 899 | # self.isConfig = True |
|
899 | # self.isConfig = True | |
| 900 | # |
|
900 | # | |
| 901 | # |
|
901 | # | |
| 902 | # |
|
902 | # | |
| 903 | # def run(self, dataOut,min_hei=None,max_hei=None, n=None, timeInterval=10,factor_stdv=2.5): |
|
903 | # def run(self, dataOut,min_hei=None,max_hei=None, n=None, timeInterval=10,factor_stdv=2.5): | |
| 904 | # #print("runing cleanRayleigh") |
|
904 | # #print("runing cleanRayleigh") | |
| 905 | # if not self.isConfig : |
|
905 | # if not self.isConfig : | |
| 906 | # |
|
906 | # | |
| 907 | # self.setup(dataOut, min_hei,max_hei,n,timeInterval,factor_stdv) |
|
907 | # self.setup(dataOut, min_hei,max_hei,n,timeInterval,factor_stdv) | |
| 908 | # |
|
908 | # | |
| 909 | # tini=dataOut.utctime |
|
909 | # tini=dataOut.utctime | |
| 910 | # |
|
910 | # | |
| 911 | # if self.byProfiles: |
|
911 | # if self.byProfiles: | |
| 912 | # if self.__profIndex == self.nIntProfiles: |
|
912 | # if self.__profIndex == self.nIntProfiles: | |
| 913 | # self.__dataReady = True |
|
913 | # self.__dataReady = True | |
| 914 | # else: |
|
914 | # else: | |
| 915 | # if (tini - self.__initime) >= self.__integrationtime: |
|
915 | # if (tini - self.__initime) >= self.__integrationtime: | |
| 916 | # |
|
916 | # | |
| 917 | # self.__dataReady = True |
|
917 | # self.__dataReady = True | |
| 918 | # self.__initime = tini |
|
918 | # self.__initime = tini | |
| 919 | # |
|
919 | # | |
| 920 | # #if (tini.tm_min % 2) == 0 and (tini.tm_sec < 5 and self.fint==0): |
|
920 | # #if (tini.tm_min % 2) == 0 and (tini.tm_sec < 5 and self.fint==0): | |
| 921 | # |
|
921 | # | |
| 922 | # if self.__dataReady: |
|
922 | # if self.__dataReady: | |
| 923 | # |
|
923 | # | |
| 924 | # self.__profIndex = 0 |
|
924 | # self.__profIndex = 0 | |
| 925 | # jspc = self.buffer |
|
925 | # jspc = self.buffer | |
| 926 | # jcspc = self.buffer2 |
|
926 | # jcspc = self.buffer2 | |
| 927 | # #jnoise = self.buffer3 |
|
927 | # #jnoise = self.buffer3 | |
| 928 | # self.buffer = dataOut.data_spc |
|
928 | # self.buffer = dataOut.data_spc | |
| 929 | # self.buffer2 = dataOut.data_cspc |
|
929 | # self.buffer2 = dataOut.data_cspc | |
| 930 | # #self.buffer3 = dataOut.noise |
|
930 | # #self.buffer3 = dataOut.noise | |
| 931 | # self.currentTime = dataOut.utctime |
|
931 | # self.currentTime = dataOut.utctime | |
| 932 | # if numpy.any(jspc) : |
|
932 | # if numpy.any(jspc) : | |
| 933 | # #print( jspc.shape, jcspc.shape) |
|
933 | # #print( jspc.shape, jcspc.shape) | |
| 934 | # jspc = numpy.reshape(jspc,(int(len(jspc)/self.nChannels),self.nChannels,self.nFFTPoints,self.nHeights)) |
|
934 | # jspc = numpy.reshape(jspc,(int(len(jspc)/self.nChannels),self.nChannels,self.nFFTPoints,self.nHeights)) | |
| 935 | # try: |
|
935 | # try: | |
| 936 | # jcspc= numpy.reshape(jcspc,(int(len(jcspc)/self.nPairs),self.nPairs,self.nFFTPoints,self.nHeights)) |
|
936 | # jcspc= numpy.reshape(jcspc,(int(len(jcspc)/self.nPairs),self.nPairs,self.nFFTPoints,self.nHeights)) | |
| 937 | # except: |
|
937 | # except: | |
| 938 | # print("no cspc") |
|
938 | # print("no cspc") | |
| 939 | # self.__dataReady = False |
|
939 | # self.__dataReady = False | |
| 940 | # #print( jspc.shape, jcspc.shape) |
|
940 | # #print( jspc.shape, jcspc.shape) | |
| 941 | # dataOut.flagNoData = False |
|
941 | # dataOut.flagNoData = False | |
| 942 | # else: |
|
942 | # else: | |
| 943 | # dataOut.flagNoData = True |
|
943 | # dataOut.flagNoData = True | |
| 944 | # self.__dataReady = False |
|
944 | # self.__dataReady = False | |
| 945 | # return dataOut |
|
945 | # return dataOut | |
| 946 | # else: |
|
946 | # else: | |
| 947 | # #print( len(self.buffer)) |
|
947 | # #print( len(self.buffer)) | |
| 948 | # if numpy.any(self.buffer): |
|
948 | # if numpy.any(self.buffer): | |
| 949 | # self.buffer = numpy.concatenate((self.buffer,dataOut.data_spc), axis=0) |
|
949 | # self.buffer = numpy.concatenate((self.buffer,dataOut.data_spc), axis=0) | |
| 950 | # try: |
|
950 | # try: | |
| 951 | # self.buffer2 = numpy.concatenate((self.buffer2,dataOut.data_cspc), axis=0) |
|
951 | # self.buffer2 = numpy.concatenate((self.buffer2,dataOut.data_cspc), axis=0) | |
| 952 | # self.buffer3 += dataOut.data_dc |
|
952 | # self.buffer3 += dataOut.data_dc | |
| 953 | # except: |
|
953 | # except: | |
| 954 | # pass |
|
954 | # pass | |
| 955 | # else: |
|
955 | # else: | |
| 956 | # self.buffer = dataOut.data_spc |
|
956 | # self.buffer = dataOut.data_spc | |
| 957 | # self.buffer2 = dataOut.data_cspc |
|
957 | # self.buffer2 = dataOut.data_cspc | |
| 958 | # self.buffer3 = dataOut.data_dc |
|
958 | # self.buffer3 = dataOut.data_dc | |
| 959 | # #print self.index, self.fint |
|
959 | # #print self.index, self.fint | |
| 960 | # #print self.buffer2.shape |
|
960 | # #print self.buffer2.shape | |
| 961 | # dataOut.flagNoData = True ## NOTE: ?? revisar LUEGO |
|
961 | # dataOut.flagNoData = True ## NOTE: ?? revisar LUEGO | |
| 962 | # self.__profIndex += 1 |
|
962 | # self.__profIndex += 1 | |
| 963 | # return dataOut ## NOTE: REV |
|
963 | # return dataOut ## NOTE: REV | |
| 964 | # |
|
964 | # | |
| 965 | # |
|
965 | # | |
| 966 | # #index = tini.tm_hour*12+tini.tm_min/5 |
|
966 | # #index = tini.tm_hour*12+tini.tm_min/5 | |
| 967 | # ''' |
|
967 | # ''' | |
| 968 | # #REVISAR |
|
968 | # #REVISAR | |
| 969 | # ''' |
|
969 | # ''' | |
| 970 | # # jspc = jspc/self.nFFTPoints/self.normFactor |
|
970 | # # jspc = jspc/self.nFFTPoints/self.normFactor | |
| 971 | # # jcspc = jcspc/self.nFFTPoints/self.normFactor |
|
971 | # # jcspc = jcspc/self.nFFTPoints/self.normFactor | |
| 972 | # |
|
972 | # | |
| 973 | # |
|
973 | # | |
| 974 | # |
|
974 | # | |
| 975 | # tmp_spectra,tmp_cspectra = self.cleanRayleigh(dataOut,jspc,jcspc,self.factor_stdv) |
|
975 | # tmp_spectra,tmp_cspectra = self.cleanRayleigh(dataOut,jspc,jcspc,self.factor_stdv) | |
| 976 | # dataOut.data_spc = tmp_spectra |
|
976 | # dataOut.data_spc = tmp_spectra | |
| 977 | # dataOut.data_cspc = tmp_cspectra |
|
977 | # dataOut.data_cspc = tmp_cspectra | |
| 978 | # |
|
978 | # | |
| 979 | # #dataOut.data_spc,dataOut.data_cspc = self.cleanRayleigh(dataOut,jspc,jcspc,self.factor_stdv) |
|
979 | # #dataOut.data_spc,dataOut.data_cspc = self.cleanRayleigh(dataOut,jspc,jcspc,self.factor_stdv) | |
| 980 | # |
|
980 | # | |
| 981 | # dataOut.data_dc = self.buffer3 |
|
981 | # dataOut.data_dc = self.buffer3 | |
| 982 | # dataOut.nIncohInt *= self.nIntProfiles |
|
982 | # dataOut.nIncohInt *= self.nIntProfiles | |
| 983 | # dataOut.max_nIncohInt = self.nIntProfiles |
|
983 | # dataOut.max_nIncohInt = self.nIntProfiles | |
| 984 | # dataOut.utctime = self.currentTime #tiempo promediado |
|
984 | # dataOut.utctime = self.currentTime #tiempo promediado | |
| 985 | # #print("Time: ",time.localtime(dataOut.utctime)) |
|
985 | # #print("Time: ",time.localtime(dataOut.utctime)) | |
| 986 | # # dataOut.data_spc = sat_spectra |
|
986 | # # dataOut.data_spc = sat_spectra | |
| 987 | # # dataOut.data_cspc = sat_cspectra |
|
987 | # # dataOut.data_cspc = sat_cspectra | |
| 988 | # self.buffer = 0 |
|
988 | # self.buffer = 0 | |
| 989 | # self.buffer2 = 0 |
|
989 | # self.buffer2 = 0 | |
| 990 | # self.buffer3 = 0 |
|
990 | # self.buffer3 = 0 | |
| 991 | # |
|
991 | # | |
| 992 | # return dataOut |
|
992 | # return dataOut | |
| 993 | # |
|
993 | # | |
| 994 | # def cleanRayleigh(self,dataOut,spectra,cspectra,factor_stdv): |
|
994 | # def cleanRayleigh(self,dataOut,spectra,cspectra,factor_stdv): | |
| 995 | # print("OP cleanRayleigh") |
|
995 | # print("OP cleanRayleigh") | |
| 996 | # #import matplotlib.pyplot as plt |
|
996 | # #import matplotlib.pyplot as plt | |
| 997 | # #for k in range(149): |
|
997 | # #for k in range(149): | |
| 998 | # #channelsProcssd = [] |
|
998 | # #channelsProcssd = [] | |
| 999 | # #channelA_ok = False |
|
999 | # #channelA_ok = False | |
| 1000 | # #rfunc = cspectra.copy() #self.bloques |
|
1000 | # #rfunc = cspectra.copy() #self.bloques | |
| 1001 | # rfunc = spectra.copy() |
|
1001 | # rfunc = spectra.copy() | |
| 1002 | # #rfunc = cspectra |
|
1002 | # #rfunc = cspectra | |
| 1003 | # #val_spc = spectra*0.0 #self.bloque0*0.0 |
|
1003 | # #val_spc = spectra*0.0 #self.bloque0*0.0 | |
| 1004 | # #val_cspc = cspectra*0.0 #self.bloques*0.0 |
|
1004 | # #val_cspc = cspectra*0.0 #self.bloques*0.0 | |
| 1005 | # #in_sat_spectra = spectra.copy() #self.bloque0 |
|
1005 | # #in_sat_spectra = spectra.copy() #self.bloque0 | |
| 1006 | # #in_sat_cspectra = cspectra.copy() #self.bloques |
|
1006 | # #in_sat_cspectra = cspectra.copy() #self.bloques | |
| 1007 | # |
|
1007 | # | |
| 1008 | # |
|
1008 | # | |
| 1009 | # ###ONLY FOR TEST: |
|
1009 | # ###ONLY FOR TEST: | |
| 1010 | # raxs = math.ceil(math.sqrt(self.nPairs)) |
|
1010 | # raxs = math.ceil(math.sqrt(self.nPairs)) | |
| 1011 | # if raxs == 0: |
|
1011 | # if raxs == 0: | |
| 1012 | # raxs = 1 |
|
1012 | # raxs = 1 | |
| 1013 | # caxs = math.ceil(self.nPairs/raxs) |
|
1013 | # caxs = math.ceil(self.nPairs/raxs) | |
| 1014 | # if self.nPairs <4: |
|
1014 | # if self.nPairs <4: | |
| 1015 | # raxs = 2 |
|
1015 | # raxs = 2 | |
| 1016 | # caxs = 2 |
|
1016 | # caxs = 2 | |
| 1017 | # #print(raxs, caxs) |
|
1017 | # #print(raxs, caxs) | |
| 1018 | # fft_rev = 14 #nFFT to plot |
|
1018 | # fft_rev = 14 #nFFT to plot | |
| 1019 | # hei_rev = ((self.heights >= 550) & (self.heights <= 551)).nonzero() #hei to plot |
|
1019 | # hei_rev = ((self.heights >= 550) & (self.heights <= 551)).nonzero() #hei to plot | |
| 1020 | # hei_rev = hei_rev[0] |
|
1020 | # hei_rev = hei_rev[0] | |
| 1021 | # #print(hei_rev) |
|
1021 | # #print(hei_rev) | |
| 1022 | # |
|
1022 | # | |
| 1023 | # #print numpy.absolute(rfunc[:,0,0,14]) |
|
1023 | # #print numpy.absolute(rfunc[:,0,0,14]) | |
| 1024 | # |
|
1024 | # | |
| 1025 | # gauss_fit, covariance = None, None |
|
1025 | # gauss_fit, covariance = None, None | |
| 1026 | # for ih in range(self.minAltInd,self.maxAltInd): |
|
1026 | # for ih in range(self.minAltInd,self.maxAltInd): | |
| 1027 | # for ifreq in range(self.nFFTPoints): |
|
1027 | # for ifreq in range(self.nFFTPoints): | |
| 1028 | # ''' |
|
1028 | # ''' | |
| 1029 | # ###ONLY FOR TEST: |
|
1029 | # ###ONLY FOR TEST: | |
| 1030 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY |
|
1030 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY | |
| 1031 | # fig, axs = plt.subplots(raxs, caxs) |
|
1031 | # fig, axs = plt.subplots(raxs, caxs) | |
| 1032 | # fig2, axs2 = plt.subplots(raxs, caxs) |
|
1032 | # fig2, axs2 = plt.subplots(raxs, caxs) | |
| 1033 | # col_ax = 0 |
|
1033 | # col_ax = 0 | |
| 1034 | # row_ax = 0 |
|
1034 | # row_ax = 0 | |
| 1035 | # ''' |
|
1035 | # ''' | |
| 1036 | # #print(self.nPairs) |
|
1036 | # #print(self.nPairs) | |
| 1037 | # for ii in range(self.nChan): #PARES DE CANALES SELF y CROSS |
|
1037 | # for ii in range(self.nChan): #PARES DE CANALES SELF y CROSS | |
| 1038 | # # if self.crosspairs[ii][1]-self.crosspairs[ii][0] > 1: # APLICAR SOLO EN PARES CONTIGUOS |
|
1038 | # # if self.crosspairs[ii][1]-self.crosspairs[ii][0] > 1: # APLICAR SOLO EN PARES CONTIGUOS | |
| 1039 | # # continue |
|
1039 | # # continue | |
| 1040 | # # if not self.crosspairs[ii][0] in channelsProcssd: |
|
1040 | # # if not self.crosspairs[ii][0] in channelsProcssd: | |
| 1041 | # # channelA_ok = True |
|
1041 | # # channelA_ok = True | |
| 1042 | # #print("pair: ",self.crosspairs[ii]) |
|
1042 | # #print("pair: ",self.crosspairs[ii]) | |
| 1043 | # ''' |
|
1043 | # ''' | |
| 1044 | # ###ONLY FOR TEST: |
|
1044 | # ###ONLY FOR TEST: | |
| 1045 | # if (col_ax%caxs==0 and col_ax!=0 and self.nPairs !=1): |
|
1045 | # if (col_ax%caxs==0 and col_ax!=0 and self.nPairs !=1): | |
| 1046 | # col_ax = 0 |
|
1046 | # col_ax = 0 | |
| 1047 | # row_ax += 1 |
|
1047 | # row_ax += 1 | |
| 1048 | # ''' |
|
1048 | # ''' | |
| 1049 | # func2clean = 10*numpy.log10(numpy.absolute(rfunc[:,ii,ifreq,ih])) #Potencia? |
|
1049 | # func2clean = 10*numpy.log10(numpy.absolute(rfunc[:,ii,ifreq,ih])) #Potencia? | |
| 1050 | # #print(func2clean.shape) |
|
1050 | # #print(func2clean.shape) | |
| 1051 | # val = (numpy.isfinite(func2clean)==True).nonzero() |
|
1051 | # val = (numpy.isfinite(func2clean)==True).nonzero() | |
| 1052 | # |
|
1052 | # | |
| 1053 | # if len(val)>0: #limitador |
|
1053 | # if len(val)>0: #limitador | |
| 1054 | # min_val = numpy.around(numpy.amin(func2clean)-2) #> (-40) |
|
1054 | # min_val = numpy.around(numpy.amin(func2clean)-2) #> (-40) | |
| 1055 | # if min_val <= -40 : |
|
1055 | # if min_val <= -40 : | |
| 1056 | # min_val = -40 |
|
1056 | # min_val = -40 | |
| 1057 | # max_val = numpy.around(numpy.amax(func2clean)+2) #< 200 |
|
1057 | # max_val = numpy.around(numpy.amax(func2clean)+2) #< 200 | |
| 1058 | # if max_val >= 200 : |
|
1058 | # if max_val >= 200 : | |
| 1059 | # max_val = 200 |
|
1059 | # max_val = 200 | |
| 1060 | # #print min_val, max_val |
|
1060 | # #print min_val, max_val | |
| 1061 | # step = 1 |
|
1061 | # step = 1 | |
| 1062 | # #print("Getting bins and the histogram") |
|
1062 | # #print("Getting bins and the histogram") | |
| 1063 | # x_dist = min_val + numpy.arange(1 + ((max_val-(min_val))/step))*step |
|
1063 | # x_dist = min_val + numpy.arange(1 + ((max_val-(min_val))/step))*step | |
| 1064 | # y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step)) |
|
1064 | # y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step)) | |
| 1065 | # #print(len(y_dist),len(binstep[:-1])) |
|
1065 | # #print(len(y_dist),len(binstep[:-1])) | |
| 1066 | # #print(row_ax,col_ax, " ..") |
|
1066 | # #print(row_ax,col_ax, " ..") | |
| 1067 | # #print(self.pairsArray[ii][0],self.pairsArray[ii][1]) |
|
1067 | # #print(self.pairsArray[ii][0],self.pairsArray[ii][1]) | |
| 1068 | # mean = numpy.sum(x_dist * y_dist) / numpy.sum(y_dist) |
|
1068 | # mean = numpy.sum(x_dist * y_dist) / numpy.sum(y_dist) | |
| 1069 | # sigma = numpy.sqrt(numpy.sum(y_dist * (x_dist - mean)**2) / numpy.sum(y_dist)) |
|
1069 | # sigma = numpy.sqrt(numpy.sum(y_dist * (x_dist - mean)**2) / numpy.sum(y_dist)) | |
| 1070 | # parg = [numpy.amax(y_dist),mean,sigma] |
|
1070 | # parg = [numpy.amax(y_dist),mean,sigma] | |
| 1071 | # |
|
1071 | # | |
| 1072 | # newY = None |
|
1072 | # newY = None | |
| 1073 | # |
|
1073 | # | |
| 1074 | # try : |
|
1074 | # try : | |
| 1075 | # gauss_fit, covariance = curve_fit(fit_func, x_dist, y_dist,p0=parg) |
|
1075 | # gauss_fit, covariance = curve_fit(fit_func, x_dist, y_dist,p0=parg) | |
| 1076 | # mode = gauss_fit[1] |
|
1076 | # mode = gauss_fit[1] | |
| 1077 | # stdv = gauss_fit[2] |
|
1077 | # stdv = gauss_fit[2] | |
| 1078 | # #print(" FIT OK",gauss_fit) |
|
1078 | # #print(" FIT OK",gauss_fit) | |
| 1079 | # ''' |
|
1079 | # ''' | |
| 1080 | # ###ONLY FOR TEST: |
|
1080 | # ###ONLY FOR TEST: | |
| 1081 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY |
|
1081 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY | |
| 1082 | # newY = fit_func(x_dist,gauss_fit[0],gauss_fit[1],gauss_fit[2]) |
|
1082 | # newY = fit_func(x_dist,gauss_fit[0],gauss_fit[1],gauss_fit[2]) | |
| 1083 | # axs[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green') |
|
1083 | # axs[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green') | |
| 1084 | # axs[row_ax,col_ax].plot(binstep[:-1],newY,color='red') |
|
1084 | # axs[row_ax,col_ax].plot(binstep[:-1],newY,color='red') | |
| 1085 | # axs[row_ax,col_ax].set_title("CH "+str(self.channels[ii])) |
|
1085 | # axs[row_ax,col_ax].set_title("CH "+str(self.channels[ii])) | |
| 1086 | # ''' |
|
1086 | # ''' | |
| 1087 | # except: |
|
1087 | # except: | |
| 1088 | # mode = mean |
|
1088 | # mode = mean | |
| 1089 | # stdv = sigma |
|
1089 | # stdv = sigma | |
| 1090 | # #print("FIT FAIL") |
|
1090 | # #print("FIT FAIL") | |
| 1091 | # #continue |
|
1091 | # #continue | |
| 1092 | # |
|
1092 | # | |
| 1093 | # |
|
1093 | # | |
| 1094 | # #print(mode,stdv) |
|
1094 | # #print(mode,stdv) | |
| 1095 | # #Removing echoes greater than mode + std_factor*stdv |
|
1095 | # #Removing echoes greater than mode + std_factor*stdv | |
| 1096 | # noval = (abs(func2clean - mode)>=(factor_stdv*stdv)).nonzero() |
|
1096 | # noval = (abs(func2clean - mode)>=(factor_stdv*stdv)).nonzero() | |
| 1097 | # #noval tiene los indices que se van a remover |
|
1097 | # #noval tiene los indices que se van a remover | |
| 1098 | # #print("Chan ",ii," novals: ",len(noval[0])) |
|
1098 | # #print("Chan ",ii," novals: ",len(noval[0])) | |
| 1099 | # if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N) |
|
1099 | # if len(noval[0]) > 0: #forma de array (N,) es igual a longitud (N) | |
| 1100 | # novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero() |
|
1100 | # novall = ((func2clean - mode) >= (factor_stdv*stdv)).nonzero() | |
| 1101 | # #print(novall) |
|
1101 | # #print(novall) | |
| 1102 | # #print(" ",self.pairsArray[ii]) |
|
1102 | # #print(" ",self.pairsArray[ii]) | |
| 1103 | # #cross_pairs = self.pairsArray[ii] |
|
1103 | # #cross_pairs = self.pairsArray[ii] | |
| 1104 | # #Getting coherent echoes which are removed. |
|
1104 | # #Getting coherent echoes which are removed. | |
| 1105 | # # if len(novall[0]) > 0: |
|
1105 | # # if len(novall[0]) > 0: | |
| 1106 | # # |
|
1106 | # # | |
| 1107 | # # val_spc[novall[0],cross_pairs[0],ifreq,ih] = 1 |
|
1107 | # # val_spc[novall[0],cross_pairs[0],ifreq,ih] = 1 | |
| 1108 | # # val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1 |
|
1108 | # # val_spc[novall[0],cross_pairs[1],ifreq,ih] = 1 | |
| 1109 | # # val_cspc[novall[0],ii,ifreq,ih] = 1 |
|
1109 | # # val_cspc[novall[0],ii,ifreq,ih] = 1 | |
| 1110 | # #print("OUT NOVALL 1") |
|
1110 | # #print("OUT NOVALL 1") | |
| 1111 | # try: |
|
1111 | # try: | |
| 1112 | # pair = (self.channels[ii],self.channels[ii + 1]) |
|
1112 | # pair = (self.channels[ii],self.channels[ii + 1]) | |
| 1113 | # except: |
|
1113 | # except: | |
| 1114 | # pair = (99,99) |
|
1114 | # pair = (99,99) | |
| 1115 | # #print("par ", pair) |
|
1115 | # #print("par ", pair) | |
| 1116 | # if ( pair in self.crosspairs): |
|
1116 | # if ( pair in self.crosspairs): | |
| 1117 | # q = self.crosspairs.index(pair) |
|
1117 | # q = self.crosspairs.index(pair) | |
| 1118 | # #print("estΓ‘ aqui: ", q, (ii,ii + 1)) |
|
1118 | # #print("estΓ‘ aqui: ", q, (ii,ii + 1)) | |
| 1119 | # new_a = numpy.delete(cspectra[:,q,ifreq,ih], noval[0]) |
|
1119 | # new_a = numpy.delete(cspectra[:,q,ifreq,ih], noval[0]) | |
| 1120 | # cspectra[noval,q,ifreq,ih] = numpy.mean(new_a) #mean CrossSpectra |
|
1120 | # cspectra[noval,q,ifreq,ih] = numpy.mean(new_a) #mean CrossSpectra | |
| 1121 | # |
|
1121 | # | |
| 1122 | # #if channelA_ok: |
|
1122 | # #if channelA_ok: | |
| 1123 | # #chA = self.channels.index(cross_pairs[0]) |
|
1123 | # #chA = self.channels.index(cross_pairs[0]) | |
| 1124 | # new_b = numpy.delete(spectra[:,ii,ifreq,ih], noval[0]) |
|
1124 | # new_b = numpy.delete(spectra[:,ii,ifreq,ih], noval[0]) | |
| 1125 | # spectra[noval,ii,ifreq,ih] = numpy.mean(new_b) #mean Spectra Pair A |
|
1125 | # spectra[noval,ii,ifreq,ih] = numpy.mean(new_b) #mean Spectra Pair A | |
| 1126 | # #channelA_ok = False |
|
1126 | # #channelA_ok = False | |
| 1127 | # |
|
1127 | # | |
| 1128 | # # chB = self.channels.index(cross_pairs[1]) |
|
1128 | # # chB = self.channels.index(cross_pairs[1]) | |
| 1129 | # # new_c = numpy.delete(spectra[:,chB,ifreq,ih], noval[0]) |
|
1129 | # # new_c = numpy.delete(spectra[:,chB,ifreq,ih], noval[0]) | |
| 1130 | # # spectra[noval,chB,ifreq,ih] = numpy.mean(new_c) #mean Spectra Pair B |
|
1130 | # # spectra[noval,chB,ifreq,ih] = numpy.mean(new_c) #mean Spectra Pair B | |
| 1131 | # # |
|
1131 | # # | |
| 1132 | # # channelsProcssd.append(self.crosspairs[ii][0]) # save channel A |
|
1132 | # # channelsProcssd.append(self.crosspairs[ii][0]) # save channel A | |
| 1133 | # # channelsProcssd.append(self.crosspairs[ii][1]) # save channel B |
|
1133 | # # channelsProcssd.append(self.crosspairs[ii][1]) # save channel B | |
| 1134 | # ''' |
|
1134 | # ''' | |
| 1135 | # ###ONLY FOR TEST: |
|
1135 | # ###ONLY FOR TEST: | |
| 1136 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY |
|
1136 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY | |
| 1137 | # func2clean = 10*numpy.log10(numpy.absolute(spectra[:,ii,ifreq,ih])) |
|
1137 | # func2clean = 10*numpy.log10(numpy.absolute(spectra[:,ii,ifreq,ih])) | |
| 1138 | # y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step)) |
|
1138 | # y_dist,binstep = numpy.histogram(func2clean,bins=range(int(min_val),int(max_val+2),step)) | |
| 1139 | # axs2[row_ax,col_ax].plot(binstep[:-1],newY,color='red') |
|
1139 | # axs2[row_ax,col_ax].plot(binstep[:-1],newY,color='red') | |
| 1140 | # axs2[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green') |
|
1140 | # axs2[row_ax,col_ax].plot(binstep[:-1],y_dist,color='green') | |
| 1141 | # axs2[row_ax,col_ax].set_title("CH "+str(self.channels[ii])) |
|
1141 | # axs2[row_ax,col_ax].set_title("CH "+str(self.channels[ii])) | |
| 1142 | # ''' |
|
1142 | # ''' | |
| 1143 | # ''' |
|
1143 | # ''' | |
| 1144 | # ###ONLY FOR TEST: |
|
1144 | # ###ONLY FOR TEST: | |
| 1145 | # col_ax += 1 #contador de ploteo columnas |
|
1145 | # col_ax += 1 #contador de ploteo columnas | |
| 1146 | # ##print(col_ax) |
|
1146 | # ##print(col_ax) | |
| 1147 | # ###ONLY FOR TEST: |
|
1147 | # ###ONLY FOR TEST: | |
| 1148 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY |
|
1148 | # if ifreq ==fft_rev and ih==hei_rev: #TO VIEW A SIGNLE FREQUENCY | |
| 1149 | # title = str(dataOut.datatime)+" nFFT: "+str(ifreq)+" Alt: "+str(self.heights[ih])+ " km" |
|
1149 | # title = str(dataOut.datatime)+" nFFT: "+str(ifreq)+" Alt: "+str(self.heights[ih])+ " km" | |
| 1150 | # title2 = str(dataOut.datatime)+" nFFT: "+str(ifreq)+" Alt: "+str(self.heights[ih])+ " km CLEANED" |
|
1150 | # title2 = str(dataOut.datatime)+" nFFT: "+str(ifreq)+" Alt: "+str(self.heights[ih])+ " km CLEANED" | |
| 1151 | # fig.suptitle(title) |
|
1151 | # fig.suptitle(title) | |
| 1152 | # fig2.suptitle(title2) |
|
1152 | # fig2.suptitle(title2) | |
| 1153 | # plt.show() |
|
1153 | # plt.show() | |
| 1154 | # ''' |
|
1154 | # ''' | |
| 1155 | # ################################################################################################## |
|
1155 | # ################################################################################################## | |
| 1156 | # |
|
1156 | # | |
| 1157 | # #print("Getting average of the spectra and cross-spectra from incoherent echoes.") |
|
1157 | # #print("Getting average of the spectra and cross-spectra from incoherent echoes.") | |
| 1158 | # out_spectra = numpy.zeros([self.nChan,self.nFFTPoints,self.nHeights], dtype=float) #+numpy.nan |
|
1158 | # out_spectra = numpy.zeros([self.nChan,self.nFFTPoints,self.nHeights], dtype=float) #+numpy.nan | |
| 1159 | # out_cspectra = numpy.zeros([self.nPairs,self.nFFTPoints,self.nHeights], dtype=complex) #+numpy.nan |
|
1159 | # out_cspectra = numpy.zeros([self.nPairs,self.nFFTPoints,self.nHeights], dtype=complex) #+numpy.nan | |
| 1160 | # for ih in range(self.nHeights): |
|
1160 | # for ih in range(self.nHeights): | |
| 1161 | # for ifreq in range(self.nFFTPoints): |
|
1161 | # for ifreq in range(self.nFFTPoints): | |
| 1162 | # for ich in range(self.nChan): |
|
1162 | # for ich in range(self.nChan): | |
| 1163 | # tmp = spectra[:,ich,ifreq,ih] |
|
1163 | # tmp = spectra[:,ich,ifreq,ih] | |
| 1164 | # valid = (numpy.isfinite(tmp[:])==True).nonzero() |
|
1164 | # valid = (numpy.isfinite(tmp[:])==True).nonzero() | |
| 1165 | # |
|
1165 | # | |
| 1166 | # if len(valid[0]) >0 : |
|
1166 | # if len(valid[0]) >0 : | |
| 1167 | # out_spectra[ich,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0]) |
|
1167 | # out_spectra[ich,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0]) | |
| 1168 | # |
|
1168 | # | |
| 1169 | # for icr in range(self.nPairs): |
|
1169 | # for icr in range(self.nPairs): | |
| 1170 | # tmp = numpy.squeeze(cspectra[:,icr,ifreq,ih]) |
|
1170 | # tmp = numpy.squeeze(cspectra[:,icr,ifreq,ih]) | |
| 1171 | # valid = (numpy.isfinite(tmp)==True).nonzero() |
|
1171 | # valid = (numpy.isfinite(tmp)==True).nonzero() | |
| 1172 | # if len(valid[0]) > 0: |
|
1172 | # if len(valid[0]) > 0: | |
| 1173 | # out_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0]) |
|
1173 | # out_cspectra[icr,ifreq,ih] = numpy.nansum(tmp)#/len(valid[0]) | |
| 1174 | # |
|
1174 | # | |
| 1175 | # return out_spectra, out_cspectra |
|
1175 | # return out_spectra, out_cspectra | |
| 1176 | # |
|
1176 | # | |
| 1177 | # def REM_ISOLATED_POINTS(self,array,rth): |
|
1177 | # def REM_ISOLATED_POINTS(self,array,rth): | |
| 1178 | # # import matplotlib.pyplot as plt |
|
1178 | # # import matplotlib.pyplot as plt | |
| 1179 | # if rth == None : |
|
1179 | # if rth == None : | |
| 1180 | # rth = 4 |
|
1180 | # rth = 4 | |
| 1181 | # #print("REM ISO") |
|
1181 | # #print("REM ISO") | |
| 1182 | # num_prof = len(array[0,:,0]) |
|
1182 | # num_prof = len(array[0,:,0]) | |
| 1183 | # num_hei = len(array[0,0,:]) |
|
1183 | # num_hei = len(array[0,0,:]) | |
| 1184 | # n2d = len(array[:,0,0]) |
|
1184 | # n2d = len(array[:,0,0]) | |
| 1185 | # |
|
1185 | # | |
| 1186 | # for ii in range(n2d) : |
|
1186 | # for ii in range(n2d) : | |
| 1187 | # #print ii,n2d |
|
1187 | # #print ii,n2d | |
| 1188 | # tmp = array[ii,:,:] |
|
1188 | # tmp = array[ii,:,:] | |
| 1189 | # #print tmp.shape, array[ii,101,:],array[ii,102,:] |
|
1189 | # #print tmp.shape, array[ii,101,:],array[ii,102,:] | |
| 1190 | # |
|
1190 | # | |
| 1191 | # # fig = plt.figure(figsize=(6,5)) |
|
1191 | # # fig = plt.figure(figsize=(6,5)) | |
| 1192 | # # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 |
|
1192 | # # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 | |
| 1193 | # # ax = fig.add_axes([left, bottom, width, height]) |
|
1193 | # # ax = fig.add_axes([left, bottom, width, height]) | |
| 1194 | # # x = range(num_prof) |
|
1194 | # # x = range(num_prof) | |
| 1195 | # # y = range(num_hei) |
|
1195 | # # y = range(num_hei) | |
| 1196 | # # cp = ax.contour(y,x,tmp) |
|
1196 | # # cp = ax.contour(y,x,tmp) | |
| 1197 | # # ax.clabel(cp, inline=True,fontsize=10) |
|
1197 | # # ax.clabel(cp, inline=True,fontsize=10) | |
| 1198 | # # plt.show() |
|
1198 | # # plt.show() | |
| 1199 | # |
|
1199 | # | |
| 1200 | # #indxs = WHERE(FINITE(tmp) AND tmp GT 0,cindxs) |
|
1200 | # #indxs = WHERE(FINITE(tmp) AND tmp GT 0,cindxs) | |
| 1201 | # tmp = numpy.reshape(tmp,num_prof*num_hei) |
|
1201 | # tmp = numpy.reshape(tmp,num_prof*num_hei) | |
| 1202 | # indxs1 = (numpy.isfinite(tmp)==True).nonzero() |
|
1202 | # indxs1 = (numpy.isfinite(tmp)==True).nonzero() | |
| 1203 | # indxs2 = (tmp > 0).nonzero() |
|
1203 | # indxs2 = (tmp > 0).nonzero() | |
| 1204 | # |
|
1204 | # | |
| 1205 | # indxs1 = (indxs1[0]) |
|
1205 | # indxs1 = (indxs1[0]) | |
| 1206 | # indxs2 = indxs2[0] |
|
1206 | # indxs2 = indxs2[0] | |
| 1207 | # #indxs1 = numpy.array(indxs1[0]) |
|
1207 | # #indxs1 = numpy.array(indxs1[0]) | |
| 1208 | # #indxs2 = numpy.array(indxs2[0]) |
|
1208 | # #indxs2 = numpy.array(indxs2[0]) | |
| 1209 | # indxs = None |
|
1209 | # indxs = None | |
| 1210 | # #print indxs1 , indxs2 |
|
1210 | # #print indxs1 , indxs2 | |
| 1211 | # for iv in range(len(indxs2)): |
|
1211 | # for iv in range(len(indxs2)): | |
| 1212 | # indv = numpy.array((indxs1 == indxs2[iv]).nonzero()) |
|
1212 | # indv = numpy.array((indxs1 == indxs2[iv]).nonzero()) | |
| 1213 | # #print len(indxs2), indv |
|
1213 | # #print len(indxs2), indv | |
| 1214 | # if len(indv[0]) > 0 : |
|
1214 | # if len(indv[0]) > 0 : | |
| 1215 | # indxs = numpy.concatenate((indxs,indxs2[iv]), axis=None) |
|
1215 | # indxs = numpy.concatenate((indxs,indxs2[iv]), axis=None) | |
| 1216 | # # print indxs |
|
1216 | # # print indxs | |
| 1217 | # indxs = indxs[1:] |
|
1217 | # indxs = indxs[1:] | |
| 1218 | # #print(indxs, len(indxs)) |
|
1218 | # #print(indxs, len(indxs)) | |
| 1219 | # if len(indxs) < 4 : |
|
1219 | # if len(indxs) < 4 : | |
| 1220 | # array[ii,:,:] = 0. |
|
1220 | # array[ii,:,:] = 0. | |
| 1221 | # return |
|
1221 | # return | |
| 1222 | # |
|
1222 | # | |
| 1223 | # xpos = numpy.mod(indxs ,num_hei) |
|
1223 | # xpos = numpy.mod(indxs ,num_hei) | |
| 1224 | # ypos = (indxs / num_hei) |
|
1224 | # ypos = (indxs / num_hei) | |
| 1225 | # sx = numpy.argsort(xpos) # Ordering respect to "x" (time) |
|
1225 | # sx = numpy.argsort(xpos) # Ordering respect to "x" (time) | |
| 1226 | # #print sx |
|
1226 | # #print sx | |
| 1227 | # xpos = xpos[sx] |
|
1227 | # xpos = xpos[sx] | |
| 1228 | # ypos = ypos[sx] |
|
1228 | # ypos = ypos[sx] | |
| 1229 | # |
|
1229 | # | |
| 1230 | # # *********************************** Cleaning isolated points ********************************** |
|
1230 | # # *********************************** Cleaning isolated points ********************************** | |
| 1231 | # ic = 0 |
|
1231 | # ic = 0 | |
| 1232 | # while True : |
|
1232 | # while True : | |
| 1233 | # r = numpy.sqrt(list(numpy.power((xpos[ic]-xpos),2)+ numpy.power((ypos[ic]-ypos),2))) |
|
1233 | # r = numpy.sqrt(list(numpy.power((xpos[ic]-xpos),2)+ numpy.power((ypos[ic]-ypos),2))) | |
| 1234 | # #no_coh = WHERE(FINITE(r) AND (r LE rth),cno_coh) |
|
1234 | # #no_coh = WHERE(FINITE(r) AND (r LE rth),cno_coh) | |
| 1235 | # #plt.plot(r) |
|
1235 | # #plt.plot(r) | |
| 1236 | # #plt.show() |
|
1236 | # #plt.show() | |
| 1237 | # no_coh1 = (numpy.isfinite(r)==True).nonzero() |
|
1237 | # no_coh1 = (numpy.isfinite(r)==True).nonzero() | |
| 1238 | # no_coh2 = (r <= rth).nonzero() |
|
1238 | # no_coh2 = (r <= rth).nonzero() | |
| 1239 | # #print r, no_coh1, no_coh2 |
|
1239 | # #print r, no_coh1, no_coh2 | |
| 1240 | # no_coh1 = numpy.array(no_coh1[0]) |
|
1240 | # no_coh1 = numpy.array(no_coh1[0]) | |
| 1241 | # no_coh2 = numpy.array(no_coh2[0]) |
|
1241 | # no_coh2 = numpy.array(no_coh2[0]) | |
| 1242 | # no_coh = None |
|
1242 | # no_coh = None | |
| 1243 | # #print valid1 , valid2 |
|
1243 | # #print valid1 , valid2 | |
| 1244 | # for iv in range(len(no_coh2)): |
|
1244 | # for iv in range(len(no_coh2)): | |
| 1245 | # indv = numpy.array((no_coh1 == no_coh2[iv]).nonzero()) |
|
1245 | # indv = numpy.array((no_coh1 == no_coh2[iv]).nonzero()) | |
| 1246 | # if len(indv[0]) > 0 : |
|
1246 | # if len(indv[0]) > 0 : | |
| 1247 | # no_coh = numpy.concatenate((no_coh,no_coh2[iv]), axis=None) |
|
1247 | # no_coh = numpy.concatenate((no_coh,no_coh2[iv]), axis=None) | |
| 1248 | # no_coh = no_coh[1:] |
|
1248 | # no_coh = no_coh[1:] | |
| 1249 | # #print len(no_coh), no_coh |
|
1249 | # #print len(no_coh), no_coh | |
| 1250 | # if len(no_coh) < 4 : |
|
1250 | # if len(no_coh) < 4 : | |
| 1251 | # #print xpos[ic], ypos[ic], ic |
|
1251 | # #print xpos[ic], ypos[ic], ic | |
| 1252 | # # plt.plot(r) |
|
1252 | # # plt.plot(r) | |
| 1253 | # # plt.show() |
|
1253 | # # plt.show() | |
| 1254 | # xpos[ic] = numpy.nan |
|
1254 | # xpos[ic] = numpy.nan | |
| 1255 | # ypos[ic] = numpy.nan |
|
1255 | # ypos[ic] = numpy.nan | |
| 1256 | # |
|
1256 | # | |
| 1257 | # ic = ic + 1 |
|
1257 | # ic = ic + 1 | |
| 1258 | # if (ic == len(indxs)) : |
|
1258 | # if (ic == len(indxs)) : | |
| 1259 | # break |
|
1259 | # break | |
| 1260 | # #print( xpos, ypos) |
|
1260 | # #print( xpos, ypos) | |
| 1261 | # |
|
1261 | # | |
| 1262 | # indxs = (numpy.isfinite(list(xpos))==True).nonzero() |
|
1262 | # indxs = (numpy.isfinite(list(xpos))==True).nonzero() | |
| 1263 | # #print indxs[0] |
|
1263 | # #print indxs[0] | |
| 1264 | # if len(indxs[0]) < 4 : |
|
1264 | # if len(indxs[0]) < 4 : | |
| 1265 | # array[ii,:,:] = 0. |
|
1265 | # array[ii,:,:] = 0. | |
| 1266 | # return |
|
1266 | # return | |
| 1267 | # |
|
1267 | # | |
| 1268 | # xpos = xpos[indxs[0]] |
|
1268 | # xpos = xpos[indxs[0]] | |
| 1269 | # ypos = ypos[indxs[0]] |
|
1269 | # ypos = ypos[indxs[0]] | |
| 1270 | # for i in range(0,len(ypos)): |
|
1270 | # for i in range(0,len(ypos)): | |
| 1271 | # ypos[i]=int(ypos[i]) |
|
1271 | # ypos[i]=int(ypos[i]) | |
| 1272 | # junk = tmp |
|
1272 | # junk = tmp | |
| 1273 | # tmp = junk*0.0 |
|
1273 | # tmp = junk*0.0 | |
| 1274 | # |
|
1274 | # | |
| 1275 | # tmp[list(xpos + (ypos*num_hei))] = junk[list(xpos + (ypos*num_hei))] |
|
1275 | # tmp[list(xpos + (ypos*num_hei))] = junk[list(xpos + (ypos*num_hei))] | |
| 1276 | # array[ii,:,:] = numpy.reshape(tmp,(num_prof,num_hei)) |
|
1276 | # array[ii,:,:] = numpy.reshape(tmp,(num_prof,num_hei)) | |
| 1277 | # |
|
1277 | # | |
| 1278 | # #print array.shape |
|
1278 | # #print array.shape | |
| 1279 | # #tmp = numpy.reshape(tmp,(num_prof,num_hei)) |
|
1279 | # #tmp = numpy.reshape(tmp,(num_prof,num_hei)) | |
| 1280 | # #print tmp.shape |
|
1280 | # #print tmp.shape | |
| 1281 | # |
|
1281 | # | |
| 1282 | # # fig = plt.figure(figsize=(6,5)) |
|
1282 | # # fig = plt.figure(figsize=(6,5)) | |
| 1283 | # # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 |
|
1283 | # # left, bottom, width, height = 0.1, 0.1, 0.8, 0.8 | |
| 1284 | # # ax = fig.add_axes([left, bottom, width, height]) |
|
1284 | # # ax = fig.add_axes([left, bottom, width, height]) | |
| 1285 | # # x = range(num_prof) |
|
1285 | # # x = range(num_prof) | |
| 1286 | # # y = range(num_hei) |
|
1286 | # # y = range(num_hei) | |
| 1287 | # # cp = ax.contour(y,x,array[ii,:,:]) |
|
1287 | # # cp = ax.contour(y,x,array[ii,:,:]) | |
| 1288 | # # ax.clabel(cp, inline=True,fontsize=10) |
|
1288 | # # ax.clabel(cp, inline=True,fontsize=10) | |
| 1289 | # # plt.show() |
|
1289 | # # plt.show() | |
| 1290 | # return array |
|
1290 | # return array | |
| 1291 | # |
|
1291 | # | |
| 1292 |
|
1292 | |||
| 1293 | class IntegrationFaradaySpectra(Operation): |
|
1293 | class IntegrationFaradaySpectra(Operation): | |
| 1294 |
|
1294 | |||
| 1295 | __profIndex = 0 |
|
1295 | __profIndex = 0 | |
| 1296 | __withOverapping = False |
|
1296 | __withOverapping = False | |
| 1297 |
|
1297 | |||
| 1298 | __byTime = False |
|
1298 | __byTime = False | |
| 1299 | __initime = None |
|
1299 | __initime = None | |
| 1300 | __lastdatatime = None |
|
1300 | __lastdatatime = None | |
| 1301 | __integrationtime = None |
|
1301 | __integrationtime = None | |
| 1302 |
|
1302 | |||
| 1303 | __buffer_spc = None |
|
1303 | __buffer_spc = None | |
| 1304 | __buffer_cspc = None |
|
1304 | __buffer_cspc = None | |
| 1305 | __buffer_dc = None |
|
1305 | __buffer_dc = None | |
| 1306 |
|
1306 | |||
| 1307 | __dataReady = False |
|
1307 | __dataReady = False | |
| 1308 |
|
1308 | |||
| 1309 | __timeInterval = None |
|
1309 | __timeInterval = None | |
| 1310 | n_ints = None #matriz de numero de integracions (CH,HEI) |
|
1310 | n_ints = None #matriz de numero de integracions (CH,HEI) | |
| 1311 | n = None |
|
1311 | n = None | |
| 1312 | minHei_ind = None |
|
1312 | minHei_ind = None | |
| 1313 | maxHei_ind = None |
|
1313 | maxHei_ind = None | |
| 1314 | navg = 1.0 |
|
1314 | navg = 1.0 | |
| 1315 | factor = 0.0 |
|
1315 | factor = 0.0 | |
| 1316 | dataoutliers = None # (CHANNELS, HEIGHTS) |
|
1316 | dataoutliers = None # (CHANNELS, HEIGHTS) | |
| 1317 |
|
1317 | |||
| 1318 | _flagProfilesByRange = False |
|
1318 | _flagProfilesByRange = False | |
| 1319 | _nProfilesByRange = 0 |
|
1319 | _nProfilesByRange = 0 | |
| 1320 |
|
1320 | |||
| 1321 | def __init__(self): |
|
1321 | def __init__(self): | |
| 1322 |
|
1322 | |||
| 1323 | Operation.__init__(self) |
|
1323 | Operation.__init__(self) | |
| 1324 |
|
1324 | |||
| 1325 | def setup(self, dataOut,n=None, timeInterval=None, overlapping=False, DPL=None, minHei=None, maxHei=None, avg=1,factor=0.75): |
|
1325 | def setup(self, dataOut,n=None, timeInterval=None, overlapping=False, DPL=None, minHei=None, maxHei=None, avg=1,factor=0.75): | |
| 1326 | """ |
|
1326 | """ | |
| 1327 | Set the parameters of the integration class. |
|
1327 | Set the parameters of the integration class. | |
| 1328 |
|
1328 | |||
| 1329 | Inputs: |
|
1329 | Inputs: | |
| 1330 |
|
1330 | |||
| 1331 | n : Number of coherent integrations |
|
1331 | n : Number of coherent integrations | |
| 1332 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
1332 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 1333 | overlapping : |
|
1333 | overlapping : | |
| 1334 |
|
1334 | |||
| 1335 | """ |
|
1335 | """ | |
| 1336 |
|
1336 | |||
| 1337 | self.__initime = None |
|
1337 | self.__initime = None | |
| 1338 | self.__lastdatatime = 0 |
|
1338 | self.__lastdatatime = 0 | |
| 1339 |
|
1339 | |||
| 1340 | self.__buffer_spc = [] |
|
1340 | self.__buffer_spc = [] | |
| 1341 | self.__buffer_cspc = [] |
|
1341 | self.__buffer_cspc = [] | |
| 1342 | self.__buffer_dc = 0 |
|
1342 | self.__buffer_dc = 0 | |
| 1343 |
|
1343 | |||
| 1344 | self.__profIndex = 0 |
|
1344 | self.__profIndex = 0 | |
| 1345 | self.__dataReady = False |
|
1345 | self.__dataReady = False | |
| 1346 | self.__byTime = False |
|
1346 | self.__byTime = False | |
| 1347 |
|
1347 | |||
| 1348 | self.factor = factor |
|
1348 | self.factor = factor | |
| 1349 | self.navg = avg |
|
1349 | self.navg = avg | |
| 1350 | #self.ByLags = dataOut.ByLags ###REDEFINIR |
|
1350 | #self.ByLags = dataOut.ByLags ###REDEFINIR | |
| 1351 | self.ByLags = False |
|
1351 | self.ByLags = False | |
| 1352 | self.maxProfilesInt = 0 |
|
1352 | self.maxProfilesInt = 0 | |
| 1353 | self.__nChannels = dataOut.nChannels |
|
1353 | self.__nChannels = dataOut.nChannels | |
| 1354 | if DPL != None: |
|
1354 | if DPL != None: | |
| 1355 | self.DPL=DPL |
|
1355 | self.DPL=DPL | |
| 1356 | else: |
|
1356 | else: | |
| 1357 | #self.DPL=dataOut.DPL ###REDEFINIR |
|
1357 | #self.DPL=dataOut.DPL ###REDEFINIR | |
| 1358 | self.DPL=0 |
|
1358 | self.DPL=0 | |
| 1359 |
|
1359 | |||
| 1360 | if n is None and timeInterval is None: |
|
1360 | if n is None and timeInterval is None: | |
| 1361 | raise ValueError("n or timeInterval should be specified ...") |
|
1361 | raise ValueError("n or timeInterval should be specified ...") | |
| 1362 |
|
1362 | |||
| 1363 | if n is not None: |
|
1363 | if n is not None: | |
| 1364 | self.n = int(n) |
|
1364 | self.n = int(n) | |
| 1365 | else: |
|
1365 | else: | |
| 1366 | self.__integrationtime = int(timeInterval) |
|
1366 | self.__integrationtime = int(timeInterval) | |
| 1367 | self.n = None |
|
1367 | self.n = None | |
| 1368 | self.__byTime = True |
|
1368 | self.__byTime = True | |
| 1369 |
|
1369 | |||
| 1370 |
|
1370 | |||
| 1371 | if minHei == None: |
|
1371 | if minHei == None: | |
| 1372 | minHei = self.dataOut.heightList[0] |
|
1372 | minHei = self.dataOut.heightList[0] | |
| 1373 |
|
1373 | |||
| 1374 | if maxHei == None: |
|
1374 | if maxHei == None: | |
| 1375 | maxHei = self.dataOut.heightList[-1] |
|
1375 | maxHei = self.dataOut.heightList[-1] | |
| 1376 |
|
1376 | |||
| 1377 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
1377 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 1378 | print('minHei: %.2f is out of the heights range' % (minHei)) |
|
1378 | print('minHei: %.2f is out of the heights range' % (minHei)) | |
| 1379 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) |
|
1379 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) | |
| 1380 | minHei = self.dataOut.heightList[0] |
|
1380 | minHei = self.dataOut.heightList[0] | |
| 1381 |
|
1381 | |||
| 1382 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
1382 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 1383 | print('maxHei: %.2f is out of the heights range' % (maxHei)) |
|
1383 | print('maxHei: %.2f is out of the heights range' % (maxHei)) | |
| 1384 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) |
|
1384 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) | |
| 1385 | maxHei = self.dataOut.heightList[-1] |
|
1385 | maxHei = self.dataOut.heightList[-1] | |
| 1386 |
|
1386 | |||
| 1387 | ind_list1 = numpy.where(self.dataOut.heightList >= minHei) |
|
1387 | ind_list1 = numpy.where(self.dataOut.heightList >= minHei) | |
| 1388 | ind_list2 = numpy.where(self.dataOut.heightList <= maxHei) |
|
1388 | ind_list2 = numpy.where(self.dataOut.heightList <= maxHei) | |
| 1389 | self.minHei_ind = ind_list1[0][0] |
|
1389 | self.minHei_ind = ind_list1[0][0] | |
| 1390 | self.maxHei_ind = ind_list2[0][-1] |
|
1390 | self.maxHei_ind = ind_list2[0][-1] | |
| 1391 |
|
1391 | |||
| 1392 | def putData(self, data_spc, data_cspc, data_dc): |
|
1392 | def putData(self, data_spc, data_cspc, data_dc): | |
| 1393 | """ |
|
1393 | """ | |
| 1394 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
1394 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 1395 |
|
1395 | |||
| 1396 | """ |
|
1396 | """ | |
| 1397 |
|
1397 | |||
| 1398 | self.__buffer_spc.append(data_spc) |
|
1398 | self.__buffer_spc.append(data_spc) | |
| 1399 |
|
1399 | |||
| 1400 | if self.__nChannels < 2: |
|
1400 | if self.__nChannels < 2: | |
| 1401 | self.__buffer_cspc = None |
|
1401 | self.__buffer_cspc = None | |
| 1402 | else: |
|
1402 | else: | |
| 1403 | self.__buffer_cspc.append(data_cspc) |
|
1403 | self.__buffer_cspc.append(data_cspc) | |
| 1404 |
|
1404 | |||
| 1405 | if data_dc is None: |
|
1405 | if data_dc is None: | |
| 1406 | self.__buffer_dc = None |
|
1406 | self.__buffer_dc = None | |
| 1407 | else: |
|
1407 | else: | |
| 1408 | self.__buffer_dc += data_dc |
|
1408 | self.__buffer_dc += data_dc | |
| 1409 |
|
1409 | |||
| 1410 | self.__profIndex += 1 |
|
1410 | self.__profIndex += 1 | |
| 1411 |
|
1411 | |||
| 1412 | return |
|
1412 | return | |
| 1413 |
|
1413 | |||
| 1414 | def hildebrand_sekhon_Integration(self,sortdata,navg, factor): |
|
1414 | def hildebrand_sekhon_Integration(self,sortdata,navg, factor): | |
| 1415 | #data debe estar ordenado |
|
1415 | #data debe estar ordenado | |
| 1416 | #sortdata = numpy.sort(data, axis=None) |
|
1416 | #sortdata = numpy.sort(data, axis=None) | |
| 1417 | #sortID=data.argsort() |
|
1417 | #sortID=data.argsort() | |
| 1418 | lenOfData = len(sortdata) |
|
1418 | lenOfData = len(sortdata) | |
| 1419 | nums_min = lenOfData*factor |
|
1419 | nums_min = lenOfData*factor | |
| 1420 | if nums_min <= 5: |
|
1420 | if nums_min <= 5: | |
| 1421 | nums_min = 5 |
|
1421 | nums_min = 5 | |
| 1422 | sump = 0. |
|
1422 | sump = 0. | |
| 1423 | sumq = 0. |
|
1423 | sumq = 0. | |
| 1424 | j = 0 |
|
1424 | j = 0 | |
| 1425 | cont = 1 |
|
1425 | cont = 1 | |
| 1426 | while((cont == 1)and(j < lenOfData)): |
|
1426 | while((cont == 1)and(j < lenOfData)): | |
| 1427 | sump += sortdata[j] |
|
1427 | sump += sortdata[j] | |
| 1428 | sumq += sortdata[j]**2 |
|
1428 | sumq += sortdata[j]**2 | |
| 1429 | if j > nums_min: |
|
1429 | if j > nums_min: | |
| 1430 | rtest = float(j)/(j-1) + 1.0/navg |
|
1430 | rtest = float(j)/(j-1) + 1.0/navg | |
| 1431 | if ((sumq*j) > (rtest*sump**2)): |
|
1431 | if ((sumq*j) > (rtest*sump**2)): | |
| 1432 | j = j - 1 |
|
1432 | j = j - 1 | |
| 1433 | sump = sump - sortdata[j] |
|
1433 | sump = sump - sortdata[j] | |
| 1434 | sumq = sumq - sortdata[j]**2 |
|
1434 | sumq = sumq - sortdata[j]**2 | |
| 1435 | cont = 0 |
|
1435 | cont = 0 | |
| 1436 | j += 1 |
|
1436 | j += 1 | |
| 1437 | #lnoise = sump / j |
|
1437 | #lnoise = sump / j | |
| 1438 | #print("H S done") |
|
1438 | #print("H S done") | |
| 1439 | #return j,sortID |
|
1439 | #return j,sortID | |
| 1440 | return j |
|
1440 | return j | |
| 1441 |
|
1441 | |||
| 1442 |
|
1442 | |||
| 1443 | def pushData(self): |
|
1443 | def pushData(self): | |
| 1444 | """ |
|
1444 | """ | |
| 1445 | Return the sum of the last profiles and the profiles used in the sum. |
|
1445 | Return the sum of the last profiles and the profiles used in the sum. | |
| 1446 |
|
1446 | |||
| 1447 | Affected: |
|
1447 | Affected: | |
| 1448 |
|
1448 | |||
| 1449 | self.__profileIndex |
|
1449 | self.__profileIndex | |
| 1450 |
|
1450 | |||
| 1451 | """ |
|
1451 | """ | |
| 1452 | bufferH=None |
|
1452 | bufferH=None | |
| 1453 | buffer=None |
|
1453 | buffer=None | |
| 1454 | buffer1=None |
|
1454 | buffer1=None | |
| 1455 | buffer_cspc=None |
|
1455 | buffer_cspc=None | |
| 1456 | #print("aes: ", self.__buffer_cspc) |
|
1456 | #print("aes: ", self.__buffer_cspc) | |
| 1457 | self.__buffer_spc=numpy.array(self.__buffer_spc) |
|
1457 | self.__buffer_spc=numpy.array(self.__buffer_spc) | |
| 1458 | if self.__nChannels > 1 : |
|
1458 | if self.__nChannels > 1 : | |
| 1459 | self.__buffer_cspc=numpy.array(self.__buffer_cspc) |
|
1459 | self.__buffer_cspc=numpy.array(self.__buffer_cspc) | |
| 1460 |
|
1460 | |||
| 1461 | #print("FREQ_DC",self.__buffer_spc.shape,self.__buffer_cspc.shape) |
|
1461 | #print("FREQ_DC",self.__buffer_spc.shape,self.__buffer_cspc.shape) | |
| 1462 |
|
1462 | |||
| 1463 | freq_dc = int(self.__buffer_spc.shape[2] / 2) |
|
1463 | freq_dc = int(self.__buffer_spc.shape[2] / 2) | |
| 1464 | #print("FREQ_DC",freq_dc,self.__buffer_spc.shape,self.nHeights) |
|
1464 | #print("FREQ_DC",freq_dc,self.__buffer_spc.shape,self.nHeights) | |
| 1465 |
|
1465 | |||
| 1466 | self.dataOutliers = numpy.zeros((self.nChannels,self.nHeights)) # --> almacen de outliers |
|
1466 | self.dataOutliers = numpy.zeros((self.nChannels,self.nHeights)) # --> almacen de outliers | |
| 1467 |
|
1467 | |||
| 1468 | for k in range(self.minHei_ind,self.maxHei_ind): |
|
1468 | for k in range(self.minHei_ind,self.maxHei_ind): | |
| 1469 | if self.__nChannels > 1: |
|
1469 | if self.__nChannels > 1: | |
| 1470 | buffer_cspc=numpy.copy(self.__buffer_cspc[:,:,:,k]) |
|
1470 | buffer_cspc=numpy.copy(self.__buffer_cspc[:,:,:,k]) | |
| 1471 |
|
1471 | |||
| 1472 | outliers_IDs_cspc=[] |
|
1472 | outliers_IDs_cspc=[] | |
| 1473 | cspc_outliers_exist=False |
|
1473 | cspc_outliers_exist=False | |
| 1474 | for i in range(self.nChannels):#dataOut.nChannels): |
|
1474 | for i in range(self.nChannels):#dataOut.nChannels): | |
| 1475 |
|
1475 | |||
| 1476 | buffer1=numpy.copy(self.__buffer_spc[:,i,:,k]) |
|
1476 | buffer1=numpy.copy(self.__buffer_spc[:,i,:,k]) | |
| 1477 | indexes=[] |
|
1477 | indexes=[] | |
| 1478 | #sortIDs=[] |
|
1478 | #sortIDs=[] | |
| 1479 | outliers_IDs=[] |
|
1479 | outliers_IDs=[] | |
| 1480 |
|
1480 | |||
| 1481 | for j in range(self.nProfiles): #frecuencias en el tiempo |
|
1481 | for j in range(self.nProfiles): #frecuencias en el tiempo | |
| 1482 | # if i==0 and j==freq_dc: #NOT CONSIDERING DC PROFILE AT CHANNEL 0 |
|
1482 | # if i==0 and j==freq_dc: #NOT CONSIDERING DC PROFILE AT CHANNEL 0 | |
| 1483 | # continue |
|
1483 | # continue | |
| 1484 | # if i==1 and j==0: #NOT CONSIDERING DC PROFILE AT CHANNEL 1 |
|
1484 | # if i==1 and j==0: #NOT CONSIDERING DC PROFILE AT CHANNEL 1 | |
| 1485 | # continue |
|
1485 | # continue | |
| 1486 | buffer=buffer1[:,j] |
|
1486 | buffer=buffer1[:,j] | |
| 1487 | sortdata = numpy.sort(buffer, axis=None) |
|
1487 | sortdata = numpy.sort(buffer, axis=None) | |
| 1488 |
|
1488 | |||
| 1489 | sortID=buffer.argsort() |
|
1489 | sortID=buffer.argsort() | |
| 1490 | index = _noise.hildebrand_sekhon2(sortdata,self.navg) |
|
1490 | index = _noise.hildebrand_sekhon2(sortdata,self.navg) | |
| 1491 |
|
1491 | |||
| 1492 | #index,sortID=self.hildebrand_sekhon_Integration(buffer,1,self.factor) |
|
1492 | #index,sortID=self.hildebrand_sekhon_Integration(buffer,1,self.factor) | |
| 1493 |
|
1493 | |||
| 1494 | # fig,ax = plt.subplots() |
|
1494 | # fig,ax = plt.subplots() | |
| 1495 | # ax.set_title(str(k)+" "+str(j)) |
|
1495 | # ax.set_title(str(k)+" "+str(j)) | |
| 1496 | # x=range(len(sortdata)) |
|
1496 | # x=range(len(sortdata)) | |
| 1497 | # ax.scatter(x,sortdata) |
|
1497 | # ax.scatter(x,sortdata) | |
| 1498 | # ax.axvline(index) |
|
1498 | # ax.axvline(index) | |
| 1499 | # plt.show() |
|
1499 | # plt.show() | |
| 1500 |
|
1500 | |||
| 1501 | indexes.append(index) |
|
1501 | indexes.append(index) | |
| 1502 | #sortIDs.append(sortID) |
|
1502 | #sortIDs.append(sortID) | |
| 1503 | outliers_IDs=numpy.append(outliers_IDs,sortID[index:]) |
|
1503 | outliers_IDs=numpy.append(outliers_IDs,sortID[index:]) | |
| 1504 |
|
1504 | |||
| 1505 | #print("Outliers: ",outliers_IDs) |
|
1505 | #print("Outliers: ",outliers_IDs) | |
| 1506 | outliers_IDs=numpy.array(outliers_IDs) |
|
1506 | outliers_IDs=numpy.array(outliers_IDs) | |
| 1507 | outliers_IDs=outliers_IDs.ravel() |
|
1507 | outliers_IDs=outliers_IDs.ravel() | |
| 1508 | outliers_IDs=numpy.unique(outliers_IDs) |
|
1508 | outliers_IDs=numpy.unique(outliers_IDs) | |
| 1509 | outliers_IDs=outliers_IDs.astype(numpy.dtype('int64')) |
|
1509 | outliers_IDs=outliers_IDs.astype(numpy.dtype('int64')) | |
| 1510 | indexes=numpy.array(indexes) |
|
1510 | indexes=numpy.array(indexes) | |
| 1511 | indexmin=numpy.min(indexes) |
|
1511 | indexmin=numpy.min(indexes) | |
| 1512 |
|
1512 | |||
| 1513 |
|
1513 | |||
| 1514 | #print(indexmin,buffer1.shape[0], k) |
|
1514 | #print(indexmin,buffer1.shape[0], k) | |
| 1515 |
|
1515 | |||
| 1516 | # fig,ax = plt.subplots() |
|
1516 | # fig,ax = plt.subplots() | |
| 1517 | # ax.plot(sortdata) |
|
1517 | # ax.plot(sortdata) | |
| 1518 | # ax2 = ax.twinx() |
|
1518 | # ax2 = ax.twinx() | |
| 1519 | # x=range(len(indexes)) |
|
1519 | # x=range(len(indexes)) | |
| 1520 | # #plt.scatter(x,indexes) |
|
1520 | # #plt.scatter(x,indexes) | |
| 1521 | # ax2.scatter(x,indexes) |
|
1521 | # ax2.scatter(x,indexes) | |
| 1522 | # plt.show() |
|
1522 | # plt.show() | |
| 1523 |
|
1523 | |||
| 1524 | if indexmin != buffer1.shape[0]: |
|
1524 | if indexmin != buffer1.shape[0]: | |
| 1525 | if self.__nChannels > 1: |
|
1525 | if self.__nChannels > 1: | |
| 1526 | cspc_outliers_exist= True |
|
1526 | cspc_outliers_exist= True | |
| 1527 |
|
1527 | |||
| 1528 | lt=outliers_IDs |
|
1528 | lt=outliers_IDs | |
| 1529 | #avg=numpy.mean(buffer1[[t for t in range(buffer1.shape[0]) if t not in lt],:],axis=0) |
|
1529 | #avg=numpy.mean(buffer1[[t for t in range(buffer1.shape[0]) if t not in lt],:],axis=0) | |
| 1530 |
|
1530 | |||
| 1531 | for p in list(outliers_IDs): |
|
1531 | for p in list(outliers_IDs): | |
| 1532 | #buffer1[p,:]=avg |
|
1532 | #buffer1[p,:]=avg | |
| 1533 | buffer1[p,:] = numpy.NaN |
|
1533 | buffer1[p,:] = numpy.NaN | |
| 1534 |
|
1534 | |||
| 1535 | self.dataOutliers[i,k] = len(outliers_IDs) |
|
1535 | self.dataOutliers[i,k] = len(outliers_IDs) | |
| 1536 |
|
1536 | |||
| 1537 |
|
1537 | |||
| 1538 | self.__buffer_spc[:,i,:,k]=numpy.copy(buffer1) |
|
1538 | self.__buffer_spc[:,i,:,k]=numpy.copy(buffer1) | |
| 1539 |
|
1539 | |||
| 1540 |
|
1540 | |||
| 1541 | if self.__nChannels > 1: |
|
1541 | if self.__nChannels > 1: | |
| 1542 | outliers_IDs_cspc=numpy.append(outliers_IDs_cspc,outliers_IDs) |
|
1542 | outliers_IDs_cspc=numpy.append(outliers_IDs_cspc,outliers_IDs) | |
| 1543 |
|
1543 | |||
| 1544 |
|
1544 | |||
| 1545 | if self.__nChannels > 1: |
|
1545 | if self.__nChannels > 1: | |
| 1546 | outliers_IDs_cspc=outliers_IDs_cspc.astype(numpy.dtype('int64')) |
|
1546 | outliers_IDs_cspc=outliers_IDs_cspc.astype(numpy.dtype('int64')) | |
| 1547 | if cspc_outliers_exist: |
|
1547 | if cspc_outliers_exist: | |
| 1548 |
|
1548 | |||
| 1549 | lt=outliers_IDs_cspc |
|
1549 | lt=outliers_IDs_cspc | |
| 1550 |
|
1550 | |||
| 1551 | #avg=numpy.mean(buffer_cspc[[t for t in range(buffer_cspc.shape[0]) if t not in lt],:],axis=0) |
|
1551 | #avg=numpy.mean(buffer_cspc[[t for t in range(buffer_cspc.shape[0]) if t not in lt],:],axis=0) | |
| 1552 | for p in list(outliers_IDs_cspc): |
|
1552 | for p in list(outliers_IDs_cspc): | |
| 1553 | #buffer_cspc[p,:]=avg |
|
1553 | #buffer_cspc[p,:]=avg | |
| 1554 | buffer_cspc[p,:] = numpy.NaN |
|
1554 | buffer_cspc[p,:] = numpy.NaN | |
| 1555 |
|
1555 | |||
| 1556 | if self.__nChannels > 1: |
|
1556 | if self.__nChannels > 1: | |
| 1557 | self.__buffer_cspc[:,:,:,k]=numpy.copy(buffer_cspc) |
|
1557 | self.__buffer_cspc[:,:,:,k]=numpy.copy(buffer_cspc) | |
| 1558 |
|
1558 | |||
| 1559 |
|
1559 | |||
| 1560 |
|
1560 | |||
| 1561 |
|
1561 | |||
| 1562 | nOutliers = len(outliers_IDs) |
|
1562 | nOutliers = len(outliers_IDs) | |
| 1563 | #print("Outliers n: ",self.dataOutliers,nOutliers) |
|
1563 | #print("Outliers n: ",self.dataOutliers,nOutliers) | |
| 1564 | buffer=None |
|
1564 | buffer=None | |
| 1565 | bufferH=None |
|
1565 | bufferH=None | |
| 1566 | buffer1=None |
|
1566 | buffer1=None | |
| 1567 | buffer_cspc=None |
|
1567 | buffer_cspc=None | |
| 1568 |
|
1568 | |||
| 1569 |
|
1569 | |||
| 1570 | buffer=None |
|
1570 | buffer=None | |
| 1571 |
|
1571 | |||
| 1572 | #data_spc = numpy.sum(self.__buffer_spc,axis=0) |
|
1572 | #data_spc = numpy.sum(self.__buffer_spc,axis=0) | |
| 1573 | data_spc = numpy.nansum(self.__buffer_spc,axis=0) |
|
1573 | data_spc = numpy.nansum(self.__buffer_spc,axis=0) | |
| 1574 | if self.__nChannels > 1: |
|
1574 | if self.__nChannels > 1: | |
| 1575 | #data_cspc = numpy.sum(self.__buffer_cspc,axis=0) |
|
1575 | #data_cspc = numpy.sum(self.__buffer_cspc,axis=0) | |
| 1576 | data_cspc = numpy.nansum(self.__buffer_cspc,axis=0) |
|
1576 | data_cspc = numpy.nansum(self.__buffer_cspc,axis=0) | |
| 1577 | else: |
|
1577 | else: | |
| 1578 | data_cspc = None |
|
1578 | data_cspc = None | |
| 1579 | data_dc = self.__buffer_dc |
|
1579 | data_dc = self.__buffer_dc | |
| 1580 | #(CH, HEIGH) |
|
1580 | #(CH, HEIGH) | |
| 1581 | self.maxProfilesInt = self.__profIndex - 1 |
|
1581 | self.maxProfilesInt = self.__profIndex - 1 | |
| 1582 | n = self.__profIndex - self.dataOutliers # n becomes a matrix |
|
1582 | n = self.__profIndex - self.dataOutliers # n becomes a matrix | |
| 1583 |
|
1583 | |||
| 1584 | self.__buffer_spc = [] |
|
1584 | self.__buffer_spc = [] | |
| 1585 | self.__buffer_cspc = [] |
|
1585 | self.__buffer_cspc = [] | |
| 1586 | self.__buffer_dc = 0 |
|
1586 | self.__buffer_dc = 0 | |
| 1587 | self.__profIndex = 0 |
|
1587 | self.__profIndex = 0 | |
| 1588 | #print("cleaned ",data_cspc) |
|
1588 | #print("cleaned ",data_cspc) | |
| 1589 | return data_spc, data_cspc, data_dc, n |
|
1589 | return data_spc, data_cspc, data_dc, n | |
| 1590 |
|
1590 | |||
| 1591 | def byProfiles(self, *args): |
|
1591 | def byProfiles(self, *args): | |
| 1592 |
|
1592 | |||
| 1593 | self.__dataReady = False |
|
1593 | self.__dataReady = False | |
| 1594 | avgdata_spc = None |
|
1594 | avgdata_spc = None | |
| 1595 | avgdata_cspc = None |
|
1595 | avgdata_cspc = None | |
| 1596 | avgdata_dc = None |
|
1596 | avgdata_dc = None | |
| 1597 |
|
1597 | |||
| 1598 | self.putData(*args) |
|
1598 | self.putData(*args) | |
| 1599 |
|
1599 | |||
| 1600 | if self.__profIndex >= self.n: |
|
1600 | if self.__profIndex >= self.n: | |
| 1601 |
|
1601 | |||
| 1602 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
1602 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 1603 | self.n_ints = n |
|
1603 | self.n_ints = n | |
| 1604 | self.__dataReady = True |
|
1604 | self.__dataReady = True | |
| 1605 |
|
1605 | |||
| 1606 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
1606 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1607 |
|
1607 | |||
| 1608 | def byTime(self, datatime, *args): |
|
1608 | def byTime(self, datatime, *args): | |
| 1609 |
|
1609 | |||
| 1610 | self.__dataReady = False |
|
1610 | self.__dataReady = False | |
| 1611 | avgdata_spc = None |
|
1611 | avgdata_spc = None | |
| 1612 | avgdata_cspc = None |
|
1612 | avgdata_cspc = None | |
| 1613 | avgdata_dc = None |
|
1613 | avgdata_dc = None | |
| 1614 |
|
1614 | |||
| 1615 | self.putData(*args) |
|
1615 | self.putData(*args) | |
| 1616 |
|
1616 | |||
| 1617 | if (datatime - self.__initime) >= self.__integrationtime: |
|
1617 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 1618 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
1618 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 1619 | self.n_ints = n |
|
1619 | self.n_ints = n | |
| 1620 | self.__dataReady = True |
|
1620 | self.__dataReady = True | |
| 1621 |
|
1621 | |||
| 1622 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
1622 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1623 |
|
1623 | |||
| 1624 | def integrate(self, datatime, *args): |
|
1624 | def integrate(self, datatime, *args): | |
| 1625 |
|
1625 | |||
| 1626 | if self.__profIndex == 0: |
|
1626 | if self.__profIndex == 0: | |
| 1627 | self.__initime = datatime |
|
1627 | self.__initime = datatime | |
| 1628 |
|
1628 | |||
| 1629 | if self.__byTime: |
|
1629 | if self.__byTime: | |
| 1630 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( |
|
1630 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( | |
| 1631 | datatime, *args) |
|
1631 | datatime, *args) | |
| 1632 | else: |
|
1632 | else: | |
| 1633 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
1633 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 1634 |
|
1634 | |||
| 1635 | if not self.__dataReady: |
|
1635 | if not self.__dataReady: | |
| 1636 | return None, None, None, None |
|
1636 | return None, None, None, None | |
| 1637 |
|
1637 | |||
| 1638 | #print("integrate", avgdata_cspc) |
|
1638 | #print("integrate", avgdata_cspc) | |
| 1639 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
1639 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 1640 |
|
1640 | |||
| 1641 | def run(self, dataOut, n=None, DPL = None,timeInterval=None, overlapping=False, minHei=None, maxHei=None, avg=1, factor=0.75): |
|
1641 | def run(self, dataOut, n=None, DPL = None,timeInterval=None, overlapping=False, minHei=None, maxHei=None, avg=1, factor=0.75): | |
| 1642 | self.dataOut = dataOut |
|
1642 | self.dataOut = dataOut | |
| 1643 | if n == 1: |
|
1643 | if n == 1: | |
| 1644 | return self.dataOut |
|
1644 | return self.dataOut | |
| 1645 | self.dataOut.processingHeaderObj.timeIncohInt = timeInterval |
|
1645 | self.dataOut.processingHeaderObj.timeIncohInt = timeInterval | |
| 1646 |
|
1646 | |||
| 1647 | if dataOut.flagProfilesByRange: |
|
1647 | if dataOut.flagProfilesByRange: | |
| 1648 | self._flagProfilesByRange = True |
|
1648 | self._flagProfilesByRange = True | |
| 1649 |
|
1649 | |||
| 1650 | if self.dataOut.nChannels == 1: |
|
1650 | if self.dataOut.nChannels == 1: | |
| 1651 | self.dataOut.data_cspc = None #si es un solo canal no vale la pena acumular DATOS |
|
1651 | self.dataOut.data_cspc = None #si es un solo canal no vale la pena acumular DATOS | |
| 1652 | #print("IN spc:", self.dataOut.data_spc.shape, self.dataOut.data_cspc) |
|
1652 | #print("IN spc:", self.dataOut.data_spc.shape, self.dataOut.data_cspc) | |
| 1653 | if not self.isConfig: |
|
1653 | if not self.isConfig: | |
| 1654 | self.setup(self.dataOut, n, timeInterval, overlapping,DPL ,minHei, maxHei, avg, factor) |
|
1654 | self.setup(self.dataOut, n, timeInterval, overlapping,DPL ,minHei, maxHei, avg, factor) | |
| 1655 | self.isConfig = True |
|
1655 | self.isConfig = True | |
| 1656 |
|
1656 | |||
| 1657 | if not self.ByLags: |
|
1657 | if not self.ByLags: | |
| 1658 | self.nProfiles=self.dataOut.nProfiles |
|
1658 | self.nProfiles=self.dataOut.nProfiles | |
| 1659 | self.nChannels=self.dataOut.nChannels |
|
1659 | self.nChannels=self.dataOut.nChannels | |
| 1660 | self.nHeights=self.dataOut.nHeights |
|
1660 | self.nHeights=self.dataOut.nHeights | |
| 1661 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(self.dataOut.utctime, |
|
1661 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(self.dataOut.utctime, | |
| 1662 | self.dataOut.data_spc, |
|
1662 | self.dataOut.data_spc, | |
| 1663 | self.dataOut.data_cspc, |
|
1663 | self.dataOut.data_cspc, | |
| 1664 | self.dataOut.data_dc) |
|
1664 | self.dataOut.data_dc) | |
| 1665 | else: |
|
1665 | else: | |
| 1666 | self.nProfiles=self.dataOut.nProfiles |
|
1666 | self.nProfiles=self.dataOut.nProfiles | |
| 1667 | self.nChannels=self.dataOut.nChannels |
|
1667 | self.nChannels=self.dataOut.nChannels | |
| 1668 | self.nHeights=self.dataOut.nHeights |
|
1668 | self.nHeights=self.dataOut.nHeights | |
| 1669 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(self.dataOut.utctime, |
|
1669 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(self.dataOut.utctime, | |
| 1670 | self.dataOut.dataLag_spc, |
|
1670 | self.dataOut.dataLag_spc, | |
| 1671 | self.dataOut.dataLag_cspc, |
|
1671 | self.dataOut.dataLag_cspc, | |
| 1672 | self.dataOut.dataLag_dc) |
|
1672 | self.dataOut.dataLag_dc) | |
| 1673 | self.dataOut.flagNoData = True |
|
1673 | self.dataOut.flagNoData = True | |
| 1674 |
|
1674 | |||
| 1675 | if self._flagProfilesByRange: |
|
1675 | if self._flagProfilesByRange: | |
| 1676 | dataOut.flagProfilesByRange = True |
|
1676 | dataOut.flagProfilesByRange = True | |
| 1677 | self._nProfilesByRange += dataOut.nProfilesByRange |
|
1677 | self._nProfilesByRange += dataOut.nProfilesByRange | |
| 1678 |
|
1678 | |||
| 1679 | if self.__dataReady: |
|
1679 | if self.__dataReady: | |
| 1680 |
|
1680 | |||
| 1681 | if not self.ByLags: |
|
1681 | if not self.ByLags: | |
| 1682 | if self.nChannels == 1: |
|
1682 | if self.nChannels == 1: | |
| 1683 | #print("f int", avgdata_spc.shape) |
|
1683 | #print("f int", avgdata_spc.shape) | |
| 1684 | self.dataOut.data_spc = avgdata_spc |
|
1684 | self.dataOut.data_spc = avgdata_spc | |
| 1685 | self.dataOut.data_cspc = None |
|
1685 | self.dataOut.data_cspc = None | |
| 1686 | else: |
|
1686 | else: | |
| 1687 | self.dataOut.data_spc = numpy.squeeze(avgdata_spc) |
|
1687 | self.dataOut.data_spc = numpy.squeeze(avgdata_spc) | |
| 1688 | self.dataOut.data_cspc = numpy.squeeze(avgdata_cspc) |
|
1688 | self.dataOut.data_cspc = numpy.squeeze(avgdata_cspc) | |
| 1689 | self.dataOut.data_dc = avgdata_dc |
|
1689 | self.dataOut.data_dc = avgdata_dc | |
| 1690 | self.dataOut.data_outlier = self.dataOutliers |
|
1690 | self.dataOut.data_outlier = self.dataOutliers | |
| 1691 |
|
1691 | |||
| 1692 |
|
1692 | |||
| 1693 | else: |
|
1693 | else: | |
| 1694 | self.dataOut.dataLag_spc = avgdata_spc |
|
1694 | self.dataOut.dataLag_spc = avgdata_spc | |
| 1695 | self.dataOut.dataLag_cspc = avgdata_cspc |
|
1695 | self.dataOut.dataLag_cspc = avgdata_cspc | |
| 1696 | self.dataOut.dataLag_dc = avgdata_dc |
|
1696 | self.dataOut.dataLag_dc = avgdata_dc | |
| 1697 |
|
1697 | |||
| 1698 | self.dataOut.data_spc=self.dataOut.dataLag_spc[:,:,:,self.dataOut.LagPlot] |
|
1698 | self.dataOut.data_spc=self.dataOut.dataLag_spc[:,:,:,self.dataOut.LagPlot] | |
| 1699 | self.dataOut.data_cspc=self.dataOut.dataLag_cspc[:,:,:,self.dataOut.LagPlot] |
|
1699 | self.dataOut.data_cspc=self.dataOut.dataLag_cspc[:,:,:,self.dataOut.LagPlot] | |
| 1700 | self.dataOut.data_dc=self.dataOut.dataLag_dc[:,:,self.dataOut.LagPlot] |
|
1700 | self.dataOut.data_dc=self.dataOut.dataLag_dc[:,:,self.dataOut.LagPlot] | |
| 1701 |
|
1701 | |||
| 1702 | self.dataOut.nIncohInt *= self.n_ints |
|
1702 | self.dataOut.nIncohInt *= self.n_ints | |
| 1703 | #print("maxProfilesInt: ",self.maxProfilesInt) |
|
1703 | #print("maxProfilesInt: ",self.maxProfilesInt) | |
| 1704 |
|
1704 | |||
| 1705 | self.dataOut.utctime = avgdatatime |
|
1705 | self.dataOut.utctime = avgdatatime | |
| 1706 | self.dataOut.flagNoData = False |
|
1706 | self.dataOut.flagNoData = False | |
| 1707 |
|
1707 | |||
| 1708 | dataOut.nProfilesByRange = self._nProfilesByRange |
|
1708 | dataOut.nProfilesByRange = self._nProfilesByRange | |
| 1709 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) |
|
1709 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) | |
| 1710 | self._flagProfilesByRange = False |
|
1710 | self._flagProfilesByRange = False | |
| 1711 |
|
1711 | |||
| 1712 | # #update Processing Header: |
|
1712 | # #update Processing Header: | |
| 1713 | # self.dataOut.processingHeaderObj.nIncohInt = |
|
1713 | # self.dataOut.processingHeaderObj.nIncohInt = | |
| 1714 | # self.dataOut.processingHeaderObj.nFFTPoints = self.dataOut.nFFTPoints |
|
1714 | # self.dataOut.processingHeaderObj.nFFTPoints = self.dataOut.nFFTPoints | |
| 1715 |
|
1715 | |||
| 1716 | #print("Faraday Integration DONE...", self.dataOut.data_cspc) |
|
1716 | #print("Faraday Integration DONE...", self.dataOut.data_cspc) | |
| 1717 | #print(self.dataOut.flagNoData) |
|
1717 | #print(self.dataOut.flagNoData) | |
| 1718 | return self.dataOut |
|
1718 | return self.dataOut | |
| 1719 |
|
1719 | |||
| 1720 |
|
1720 | |||
| 1721 |
|
1721 | |||
| 1722 | class removeInterference(Operation): |
|
1722 | class removeInterference(Operation): | |
| 1723 |
|
1723 | |||
| 1724 | def removeInterference3(self, min_hei = None, max_hei = None): |
|
1724 | def removeInterference3(self, min_hei = None, max_hei = None): | |
| 1725 |
|
1725 | |||
| 1726 | jspectra = self.dataOut.data_spc |
|
1726 | jspectra = self.dataOut.data_spc | |
| 1727 | #jcspectra = self.dataOut.data_cspc |
|
1727 | #jcspectra = self.dataOut.data_cspc | |
| 1728 | jnoise = self.dataOut.getNoise() |
|
1728 | jnoise = self.dataOut.getNoise() | |
| 1729 | num_incoh = self.dataOut.max_nIncohInt |
|
1729 | num_incoh = self.dataOut.max_nIncohInt | |
| 1730 | #print(jspectra.shape) |
|
1730 | #print(jspectra.shape) | |
| 1731 | num_channel, num_prof, num_hei = jspectra.shape |
|
1731 | num_channel, num_prof, num_hei = jspectra.shape | |
| 1732 | minHei = min_hei |
|
1732 | minHei = min_hei | |
| 1733 | maxHei = max_hei |
|
1733 | maxHei = max_hei | |
| 1734 | ######################################################################## |
|
1734 | ######################################################################## | |
| 1735 | if minHei == None or (minHei < self.dataOut.heightList[0]): |
|
1735 | if minHei == None or (minHei < self.dataOut.heightList[0]): | |
| 1736 | minHei = self.dataOut.heightList[0] |
|
1736 | minHei = self.dataOut.heightList[0] | |
| 1737 |
|
1737 | |||
| 1738 | if maxHei == None or (maxHei > self.dataOut.heightList[-1]): |
|
1738 | if maxHei == None or (maxHei > self.dataOut.heightList[-1]): | |
| 1739 | maxHei = self.dataOut.heightList[-1] |
|
1739 | maxHei = self.dataOut.heightList[-1] | |
| 1740 | minIndex = 0 |
|
1740 | minIndex = 0 | |
| 1741 | maxIndex = 0 |
|
1741 | maxIndex = 0 | |
| 1742 | heights = self.dataOut.heightList |
|
1742 | heights = self.dataOut.heightList | |
| 1743 |
|
1743 | |||
| 1744 | inda = numpy.where(heights >= minHei) |
|
1744 | inda = numpy.where(heights >= minHei) | |
| 1745 | indb = numpy.where(heights <= maxHei) |
|
1745 | indb = numpy.where(heights <= maxHei) | |
| 1746 |
|
1746 | |||
| 1747 | try: |
|
1747 | try: | |
| 1748 | minIndex = inda[0][0] |
|
1748 | minIndex = inda[0][0] | |
| 1749 | except: |
|
1749 | except: | |
| 1750 | minIndex = 0 |
|
1750 | minIndex = 0 | |
| 1751 | try: |
|
1751 | try: | |
| 1752 | maxIndex = indb[0][-1] |
|
1752 | maxIndex = indb[0][-1] | |
| 1753 | except: |
|
1753 | except: | |
| 1754 | maxIndex = len(heights) |
|
1754 | maxIndex = len(heights) | |
| 1755 |
|
1755 | |||
| 1756 | if (minIndex < 0) or (minIndex > maxIndex): |
|
1756 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 1757 | raise ValueError("some value in (%d,%d) is not valid" % ( |
|
1757 | raise ValueError("some value in (%d,%d) is not valid" % ( | |
| 1758 | minIndex, maxIndex)) |
|
1758 | minIndex, maxIndex)) | |
| 1759 | if (maxIndex >= self.dataOut.nHeights): |
|
1759 | if (maxIndex >= self.dataOut.nHeights): | |
| 1760 | maxIndex = self.dataOut.nHeights - 1 |
|
1760 | maxIndex = self.dataOut.nHeights - 1 | |
| 1761 |
|
1761 | |||
| 1762 | ######################################################################## |
|
1762 | ######################################################################## | |
| 1763 |
|
1763 | |||
| 1764 |
|
1764 | |||
| 1765 | #dataOut.max_nIncohInt * dataOut.nCohInt |
|
1765 | #dataOut.max_nIncohInt * dataOut.nCohInt | |
| 1766 | if hasattr(self.dataOut.nIncohInt, 'shape'): |
|
1766 | if hasattr(self.dataOut.nIncohInt, 'shape'): | |
| 1767 | norm = self.dataOut.nIncohInt.T /self.dataOut.max_nIncohInt |
|
1767 | norm = self.dataOut.nIncohInt.T /self.dataOut.max_nIncohInt | |
| 1768 | norm = norm.T |
|
1768 | norm = norm.T | |
| 1769 | else: |
|
1769 | else: | |
| 1770 | norm = self.dataOut.nIncohInt /self.dataOut.max_nIncohInt |
|
1770 | norm = self.dataOut.nIncohInt /self.dataOut.max_nIncohInt | |
| 1771 | norm = norm |
|
1771 | norm = norm | |
| 1772 |
|
1772 | |||
| 1773 | # Subrutina de Remocion de la Interferencia |
|
1773 | # Subrutina de Remocion de la Interferencia | |
| 1774 | for ich in range(num_channel): |
|
1774 | for ich in range(num_channel): | |
| 1775 | # Se ordena los espectros segun su potencia (menor a mayor) |
|
1775 | # Se ordena los espectros segun su potencia (menor a mayor) | |
| 1776 | #power = jspectra[ich, mask_prof, :] |
|
1776 | #power = jspectra[ich, mask_prof, :] | |
| 1777 | if hasattr(self.dataOut.nIncohInt, 'shape'): |
|
1777 | if hasattr(self.dataOut.nIncohInt, 'shape'): | |
| 1778 | interf = jspectra[ich, :, minIndex:maxIndex]/norm[ich,minIndex:maxIndex] |
|
1778 | interf = jspectra[ich, :, minIndex:maxIndex]/norm[ich,minIndex:maxIndex] | |
| 1779 | else: |
|
1779 | else: | |
| 1780 | interf = jspectra[ich, :, minIndex:maxIndex]/norm |
|
1780 | interf = jspectra[ich, :, minIndex:maxIndex]/norm | |
| 1781 | # print(interf.shape) |
|
1781 | # print(interf.shape) | |
| 1782 | inttef = interf.mean(axis=1) |
|
1782 | inttef = interf.mean(axis=1) | |
| 1783 |
|
1783 | |||
| 1784 | for hei in range(num_hei): |
|
1784 | for hei in range(num_hei): | |
| 1785 | temp = jspectra[ich,:, hei]#/norm[ich,hei] |
|
1785 | temp = jspectra[ich,:, hei]#/norm[ich,hei] | |
| 1786 | temp -= inttef |
|
1786 | temp -= inttef | |
| 1787 | temp += jnoise[ich] |
|
1787 | temp += jnoise[ich] | |
| 1788 | # print(jspectra.shape, temp.shape) |
|
1788 | # print(jspectra.shape, temp.shape) | |
| 1789 | jspectra[ich,:, hei] = temp |
|
1789 | jspectra[ich,:, hei] = temp | |
| 1790 |
|
1790 | |||
| 1791 | # Guardar Resultados |
|
1791 | # Guardar Resultados | |
| 1792 | self.dataOut.data_spc = jspectra |
|
1792 | self.dataOut.data_spc = jspectra | |
| 1793 | #self.dataOut.data_cspc = jcspectra |
|
1793 | #self.dataOut.data_cspc = jcspectra | |
| 1794 |
|
1794 | |||
| 1795 | return 1 |
|
1795 | return 1 | |
| 1796 |
|
1796 | |||
| 1797 | def removeInterference2(self): |
|
1797 | def removeInterference2(self): | |
| 1798 |
|
1798 | |||
| 1799 | cspc = self.dataOut.data_cspc |
|
1799 | cspc = self.dataOut.data_cspc | |
| 1800 | spc = self.dataOut.data_spc |
|
1800 | spc = self.dataOut.data_spc | |
| 1801 | Heights = numpy.arange(cspc.shape[2]) |
|
1801 | Heights = numpy.arange(cspc.shape[2]) | |
| 1802 | realCspc = numpy.abs(cspc) |
|
1802 | realCspc = numpy.abs(cspc) | |
| 1803 |
|
1803 | |||
| 1804 | for i in range(cspc.shape[0]): |
|
1804 | for i in range(cspc.shape[0]): | |
| 1805 | LinePower= numpy.sum(realCspc[i], axis=0) |
|
1805 | LinePower= numpy.sum(realCspc[i], axis=0) | |
| 1806 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] |
|
1806 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] | |
| 1807 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] |
|
1807 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] | |
| 1808 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) |
|
1808 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) | |
| 1809 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] |
|
1809 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] | |
| 1810 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] |
|
1810 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] | |
| 1811 |
|
1811 | |||
| 1812 |
|
1812 | |||
| 1813 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) |
|
1813 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) | |
| 1814 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) |
|
1814 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) | |
| 1815 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): |
|
1815 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): | |
| 1816 | cspc[i,InterferenceRange,:] = numpy.NaN |
|
1816 | cspc[i,InterferenceRange,:] = numpy.NaN | |
| 1817 |
|
1817 | |||
| 1818 | self.dataOut.data_cspc = cspc |
|
1818 | self.dataOut.data_cspc = cspc | |
| 1819 |
|
1819 | |||
| 1820 | def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
1820 | def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 1821 |
|
1821 | |||
| 1822 | jspectra = self.dataOut.data_spc |
|
1822 | jspectra = self.dataOut.data_spc | |
| 1823 | jcspectra = self.dataOut.data_cspc |
|
1823 | jcspectra = self.dataOut.data_cspc | |
| 1824 | jnoise = self.dataOut.getNoise() |
|
1824 | jnoise = self.dataOut.getNoise() | |
| 1825 | #num_incoh = self.dataOut.nIncohInt |
|
1825 | #num_incoh = self.dataOut.nIncohInt | |
| 1826 | num_incoh = self.dataOut.max_nIncohInt |
|
1826 | num_incoh = self.dataOut.max_nIncohInt | |
| 1827 | #print("spc: ", jspectra.shape, jcspectra) |
|
1827 | #print("spc: ", jspectra.shape, jcspectra) | |
| 1828 | num_channel = jspectra.shape[0] |
|
1828 | num_channel = jspectra.shape[0] | |
| 1829 | num_prof = jspectra.shape[1] |
|
1829 | num_prof = jspectra.shape[1] | |
| 1830 | num_hei = jspectra.shape[2] |
|
1830 | num_hei = jspectra.shape[2] | |
| 1831 |
|
1831 | |||
| 1832 | count_hei = nhei_interf |
|
1832 | count_hei = nhei_interf | |
| 1833 | # hei_interf |
|
1833 | # hei_interf | |
| 1834 | if hei_interf is None: |
|
1834 | if hei_interf is None: | |
| 1835 | count_hei = int(num_hei / 2) # a half of total ranges |
|
1835 | count_hei = int(num_hei / 2) # a half of total ranges | |
| 1836 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei |
|
1836 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei | |
| 1837 | hei_interf = numpy.asarray(hei_interf)[0] |
|
1837 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 1838 | #print(hei_interf) |
|
1838 | #print(hei_interf) | |
| 1839 | # nhei_interf |
|
1839 | # nhei_interf | |
| 1840 | if (nhei_interf == None): |
|
1840 | if (nhei_interf == None): | |
| 1841 | nhei_interf = 5 |
|
1841 | nhei_interf = 5 | |
| 1842 | if (nhei_interf < 1): |
|
1842 | if (nhei_interf < 1): | |
| 1843 | nhei_interf = 1 |
|
1843 | nhei_interf = 1 | |
| 1844 | if (nhei_interf > count_hei): |
|
1844 | if (nhei_interf > count_hei): | |
| 1845 | nhei_interf = count_hei |
|
1845 | nhei_interf = count_hei | |
| 1846 | if (offhei_interf == None): |
|
1846 | if (offhei_interf == None): | |
| 1847 | offhei_interf = 0 |
|
1847 | offhei_interf = 0 | |
| 1848 |
|
1848 | |||
| 1849 | ind_hei = list(range(num_hei)) |
|
1849 | ind_hei = list(range(num_hei)) | |
| 1850 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
1850 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 1851 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
1851 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 1852 | mask_prof = numpy.asarray(list(range(num_prof))) |
|
1852 | mask_prof = numpy.asarray(list(range(num_prof))) | |
| 1853 | num_mask_prof = mask_prof.size |
|
1853 | num_mask_prof = mask_prof.size | |
| 1854 | comp_mask_prof = [0, num_prof / 2] |
|
1854 | comp_mask_prof = [0, num_prof / 2] | |
| 1855 |
|
1855 | |||
| 1856 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
1856 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 1857 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
1857 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 1858 | jnoise = numpy.nan |
|
1858 | jnoise = numpy.nan | |
| 1859 | noise_exist = jnoise[0] < numpy.Inf |
|
1859 | noise_exist = jnoise[0] < numpy.Inf | |
| 1860 |
|
1860 | |||
| 1861 | # Subrutina de Remocion de la Interferencia |
|
1861 | # Subrutina de Remocion de la Interferencia | |
| 1862 | for ich in range(num_channel): |
|
1862 | for ich in range(num_channel): | |
| 1863 | # Se ordena los espectros segun su potencia (menor a mayor) |
|
1863 | # Se ordena los espectros segun su potencia (menor a mayor) | |
| 1864 | power = jspectra[ich, mask_prof, :] |
|
1864 | power = jspectra[ich, mask_prof, :] | |
| 1865 | power = power[:, hei_interf] |
|
1865 | power = power[:, hei_interf] | |
| 1866 | power = power.sum(axis=0) |
|
1866 | power = power.sum(axis=0) | |
| 1867 | psort = power.ravel().argsort() |
|
1867 | psort = power.ravel().argsort() | |
| 1868 | #print(hei_interf[psort[list(range(offhei_interf, nhei_interf + offhei_interf))]]) |
|
1868 | #print(hei_interf[psort[list(range(offhei_interf, nhei_interf + offhei_interf))]]) | |
| 1869 | # Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
1869 | # Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 1870 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( |
|
1870 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( | |
| 1871 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
1871 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 1872 |
|
1872 | |||
| 1873 | if noise_exist: |
|
1873 | if noise_exist: | |
| 1874 | # tmp_noise = jnoise[ich] / num_prof |
|
1874 | # tmp_noise = jnoise[ich] / num_prof | |
| 1875 | tmp_noise = jnoise[ich] |
|
1875 | tmp_noise = jnoise[ich] | |
| 1876 | junkspc_interf = junkspc_interf - tmp_noise |
|
1876 | junkspc_interf = junkspc_interf - tmp_noise | |
| 1877 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
1877 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 1878 | #print(junkspc_interf.shape) |
|
1878 | #print(junkspc_interf.shape) | |
| 1879 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf |
|
1879 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf | |
| 1880 | jspc_interf = jspc_interf.transpose() |
|
1880 | jspc_interf = jspc_interf.transpose() | |
| 1881 | # Calculando el espectro de interferencia promedio |
|
1881 | # Calculando el espectro de interferencia promedio | |
| 1882 | noiseid = numpy.where(jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) |
|
1882 | noiseid = numpy.where(jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) | |
| 1883 | noiseid = noiseid[0] |
|
1883 | noiseid = noiseid[0] | |
| 1884 | cnoiseid = noiseid.size |
|
1884 | cnoiseid = noiseid.size | |
| 1885 | interfid = numpy.where(jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) |
|
1885 | interfid = numpy.where(jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) | |
| 1886 | interfid = interfid[0] |
|
1886 | interfid = interfid[0] | |
| 1887 | cinterfid = interfid.size |
|
1887 | cinterfid = interfid.size | |
| 1888 |
|
1888 | |||
| 1889 | if (cnoiseid > 0): |
|
1889 | if (cnoiseid > 0): | |
| 1890 | jspc_interf[noiseid] = 0 |
|
1890 | jspc_interf[noiseid] = 0 | |
| 1891 | # Expandiendo los perfiles a limpiar |
|
1891 | # Expandiendo los perfiles a limpiar | |
| 1892 | if (cinterfid > 0): |
|
1892 | if (cinterfid > 0): | |
| 1893 | new_interfid = ( |
|
1893 | new_interfid = ( | |
| 1894 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof |
|
1894 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof | |
| 1895 | new_interfid = numpy.asarray(new_interfid) |
|
1895 | new_interfid = numpy.asarray(new_interfid) | |
| 1896 | new_interfid = {x for x in new_interfid} |
|
1896 | new_interfid = {x for x in new_interfid} | |
| 1897 | new_interfid = numpy.array(list(new_interfid)) |
|
1897 | new_interfid = numpy.array(list(new_interfid)) | |
| 1898 | new_cinterfid = new_interfid.size |
|
1898 | new_cinterfid = new_interfid.size | |
| 1899 | else: |
|
1899 | else: | |
| 1900 | new_cinterfid = 0 |
|
1900 | new_cinterfid = 0 | |
| 1901 |
|
1901 | |||
| 1902 | for ip in range(new_cinterfid): |
|
1902 | for ip in range(new_cinterfid): | |
| 1903 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() |
|
1903 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() | |
| 1904 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] |
|
1904 | jspc_interf[new_interfid[ip]] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] | |
| 1905 |
|
1905 | |||
| 1906 | jspectra[ich, :, ind_hei] = jspectra[ich, :,ind_hei] - jspc_interf # Corregir indices |
|
1906 | jspectra[ich, :, ind_hei] = jspectra[ich, :,ind_hei] - jspc_interf # Corregir indices | |
| 1907 |
|
1907 | |||
| 1908 | # Removiendo la interferencia del punto de mayor interferencia |
|
1908 | # Removiendo la interferencia del punto de mayor interferencia | |
| 1909 | ListAux = jspc_interf[mask_prof].tolist() |
|
1909 | ListAux = jspc_interf[mask_prof].tolist() | |
| 1910 | maxid = ListAux.index(max(ListAux)) |
|
1910 | maxid = ListAux.index(max(ListAux)) | |
| 1911 | #print(cinterfid) |
|
1911 | #print(cinterfid) | |
| 1912 | if cinterfid > 0: |
|
1912 | if cinterfid > 0: | |
| 1913 | for ip in range(cinterfid * (interf == 2) - 1): |
|
1913 | for ip in range(cinterfid * (interf == 2) - 1): | |
| 1914 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * |
|
1914 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * | |
| 1915 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() |
|
1915 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 1916 | cind = len(ind) |
|
1916 | cind = len(ind) | |
| 1917 |
|
1917 | |||
| 1918 | if (cind > 0): |
|
1918 | if (cind > 0): | |
| 1919 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ |
|
1919 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ | |
| 1920 | (1 + (numpy.random.uniform(cind) - 0.5) / |
|
1920 | (1 + (numpy.random.uniform(cind) - 0.5) / | |
| 1921 | numpy.sqrt(num_incoh)) |
|
1921 | numpy.sqrt(num_incoh)) | |
| 1922 |
|
1922 | |||
| 1923 | ind = numpy.array([-2, -1, 1, 2]) |
|
1923 | ind = numpy.array([-2, -1, 1, 2]) | |
| 1924 | xx = numpy.zeros([4, 4]) |
|
1924 | xx = numpy.zeros([4, 4]) | |
| 1925 |
|
1925 | |||
| 1926 | for id1 in range(4): |
|
1926 | for id1 in range(4): | |
| 1927 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
1927 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 1928 | xx_inv = numpy.linalg.inv(xx) |
|
1928 | xx_inv = numpy.linalg.inv(xx) | |
| 1929 | xx = xx_inv[:, 0] |
|
1929 | xx = xx_inv[:, 0] | |
| 1930 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
1930 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 1931 | yy = jspectra[ich, mask_prof[ind], :] |
|
1931 | yy = jspectra[ich, mask_prof[ind], :] | |
| 1932 | jspectra[ich, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) |
|
1932 | jspectra[ich, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) | |
| 1933 |
|
1933 | |||
| 1934 | indAux = (jspectra[ich, :, :] < tmp_noise * |
|
1934 | indAux = (jspectra[ich, :, :] < tmp_noise * | |
| 1935 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() |
|
1935 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 1936 | #print(indAux) |
|
1936 | #print(indAux) | |
| 1937 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ |
|
1937 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ | |
| 1938 | (1 - 1 / numpy.sqrt(num_incoh)) |
|
1938 | (1 - 1 / numpy.sqrt(num_incoh)) | |
| 1939 |
|
1939 | |||
| 1940 | # Remocion de Interferencia en el Cross Spectra |
|
1940 | # Remocion de Interferencia en el Cross Spectra | |
| 1941 | if jcspectra is None: |
|
1941 | if jcspectra is None: | |
| 1942 | return jspectra, jcspectra |
|
1942 | return jspectra, jcspectra | |
| 1943 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) |
|
1943 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) | |
| 1944 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
1944 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 1945 |
|
1945 | |||
| 1946 | for ip in range(num_pairs): |
|
1946 | for ip in range(num_pairs): | |
| 1947 |
|
1947 | |||
| 1948 | #------------------------------------------- |
|
1948 | #------------------------------------------- | |
| 1949 |
|
1949 | |||
| 1950 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) |
|
1950 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) | |
| 1951 | cspower = cspower[:, hei_interf] |
|
1951 | cspower = cspower[:, hei_interf] | |
| 1952 | cspower = cspower.sum(axis=0) |
|
1952 | cspower = cspower.sum(axis=0) | |
| 1953 |
|
1953 | |||
| 1954 | cspsort = cspower.ravel().argsort() |
|
1954 | cspsort = cspower.ravel().argsort() | |
| 1955 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( |
|
1955 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( | |
| 1956 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
1956 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 1957 | junkcspc_interf = junkcspc_interf.transpose() |
|
1957 | junkcspc_interf = junkcspc_interf.transpose() | |
| 1958 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf |
|
1958 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf | |
| 1959 |
|
1959 | |||
| 1960 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
1960 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 1961 |
|
1961 | |||
| 1962 | median_real = int(numpy.median(numpy.real( |
|
1962 | median_real = int(numpy.median(numpy.real( | |
| 1963 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
1963 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 1964 | median_imag = int(numpy.median(numpy.imag( |
|
1964 | median_imag = int(numpy.median(numpy.imag( | |
| 1965 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
1965 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 1966 | comp_mask_prof = [int(e) for e in comp_mask_prof] |
|
1966 | comp_mask_prof = [int(e) for e in comp_mask_prof] | |
| 1967 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( |
|
1967 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( | |
| 1968 | median_real, median_imag) |
|
1968 | median_real, median_imag) | |
| 1969 |
|
1969 | |||
| 1970 | for iprof in range(num_prof): |
|
1970 | for iprof in range(num_prof): | |
| 1971 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() |
|
1971 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() | |
| 1972 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] |
|
1972 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] | |
| 1973 |
|
1973 | |||
| 1974 | # Removiendo la Interferencia |
|
1974 | # Removiendo la Interferencia | |
| 1975 | jcspectra[ip, :, ind_hei] = jcspectra[ip, |
|
1975 | jcspectra[ip, :, ind_hei] = jcspectra[ip, | |
| 1976 | :, ind_hei] - jcspc_interf |
|
1976 | :, ind_hei] - jcspc_interf | |
| 1977 |
|
1977 | |||
| 1978 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
1978 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 1979 | maxid = ListAux.index(max(ListAux)) |
|
1979 | maxid = ListAux.index(max(ListAux)) | |
| 1980 |
|
1980 | |||
| 1981 | ind = numpy.array([-2, -1, 1, 2]) |
|
1981 | ind = numpy.array([-2, -1, 1, 2]) | |
| 1982 | xx = numpy.zeros([4, 4]) |
|
1982 | xx = numpy.zeros([4, 4]) | |
| 1983 |
|
1983 | |||
| 1984 | for id1 in range(4): |
|
1984 | for id1 in range(4): | |
| 1985 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
1985 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 1986 |
|
1986 | |||
| 1987 | xx_inv = numpy.linalg.inv(xx) |
|
1987 | xx_inv = numpy.linalg.inv(xx) | |
| 1988 | xx = xx_inv[:, 0] |
|
1988 | xx = xx_inv[:, 0] | |
| 1989 |
|
1989 | |||
| 1990 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
1990 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 1991 | yy = jcspectra[ip, mask_prof[ind], :] |
|
1991 | yy = jcspectra[ip, mask_prof[ind], :] | |
| 1992 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) |
|
1992 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) | |
| 1993 |
|
1993 | |||
| 1994 | # Guardar Resultados |
|
1994 | # Guardar Resultados | |
| 1995 | self.dataOut.data_spc = jspectra |
|
1995 | self.dataOut.data_spc = jspectra | |
| 1996 | self.dataOut.data_cspc = jcspectra |
|
1996 | self.dataOut.data_cspc = jcspectra | |
| 1997 |
|
1997 | |||
| 1998 | return 1 |
|
1998 | return 1 | |
| 1999 |
|
1999 | |||
| 2000 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1, minHei=None, maxHei=None): |
|
2000 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1, minHei=None, maxHei=None): | |
| 2001 |
|
2001 | |||
| 2002 | self.dataOut = dataOut |
|
2002 | self.dataOut = dataOut | |
| 2003 |
|
2003 | |||
| 2004 | if mode == 1: |
|
2004 | if mode == 1: | |
| 2005 | self.removeInterference(interf = 2,hei_interf = hei_interf, nhei_interf = nhei_interf, offhei_interf = offhei_interf) |
|
2005 | self.removeInterference(interf = 2,hei_interf = hei_interf, nhei_interf = nhei_interf, offhei_interf = offhei_interf) | |
| 2006 | elif mode == 2: |
|
2006 | elif mode == 2: | |
| 2007 | self.removeInterference2() |
|
2007 | self.removeInterference2() | |
| 2008 | elif mode == 3: |
|
2008 | elif mode == 3: | |
| 2009 | self.removeInterference3(min_hei=minHei, max_hei=maxHei) |
|
2009 | self.removeInterference3(min_hei=minHei, max_hei=maxHei) | |
| 2010 | return self.dataOut |
|
2010 | return self.dataOut | |
| 2011 |
|
2011 | |||
| 2012 |
|
2012 | |||
| 2013 | class IncohInt(Operation): |
|
2013 | class IncohInt(Operation): | |
| 2014 |
|
2014 | |||
| 2015 | __profIndex = 0 |
|
2015 | __profIndex = 0 | |
| 2016 | __withOverapping = False |
|
2016 | __withOverapping = False | |
| 2017 |
|
2017 | |||
| 2018 | __byTime = False |
|
2018 | __byTime = False | |
| 2019 | __initime = None |
|
2019 | __initime = None | |
| 2020 | __lastdatatime = None |
|
2020 | __lastdatatime = None | |
| 2021 | __integrationtime = None |
|
2021 | __integrationtime = None | |
| 2022 |
|
2022 | |||
| 2023 | __buffer_spc = None |
|
2023 | __buffer_spc = None | |
| 2024 | __buffer_cspc = None |
|
2024 | __buffer_cspc = None | |
| 2025 | __buffer_dc = None |
|
2025 | __buffer_dc = None | |
| 2026 |
|
2026 | |||
| 2027 | __dataReady = False |
|
2027 | __dataReady = False | |
| 2028 |
|
2028 | |||
| 2029 | __timeInterval = None |
|
2029 | __timeInterval = None | |
| 2030 | incohInt = 0 |
|
2030 | incohInt = 0 | |
| 2031 | nOutliers = 0 |
|
2031 | nOutliers = 0 | |
| 2032 | n = None |
|
2032 | n = None | |
| 2033 |
|
2033 | |||
| 2034 | _flagProfilesByRange = False |
|
2034 | _flagProfilesByRange = False | |
| 2035 | _nProfilesByRange = 0 |
|
2035 | _nProfilesByRange = 0 | |
| 2036 | def __init__(self): |
|
2036 | def __init__(self): | |
| 2037 |
|
2037 | |||
| 2038 | Operation.__init__(self) |
|
2038 | Operation.__init__(self) | |
| 2039 |
|
2039 | |||
| 2040 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
2040 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 2041 | """ |
|
2041 | """ | |
| 2042 | Set the parameters of the integration class. |
|
2042 | Set the parameters of the integration class. | |
| 2043 |
|
2043 | |||
| 2044 | Inputs: |
|
2044 | Inputs: | |
| 2045 |
|
2045 | |||
| 2046 | n : Number of coherent integrations |
|
2046 | n : Number of coherent integrations | |
| 2047 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
2047 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 2048 | overlapping : |
|
2048 | overlapping : | |
| 2049 |
|
2049 | |||
| 2050 | """ |
|
2050 | """ | |
| 2051 |
|
2051 | |||
| 2052 | self.__initime = None |
|
2052 | self.__initime = None | |
| 2053 | self.__lastdatatime = 0 |
|
2053 | self.__lastdatatime = 0 | |
| 2054 |
|
2054 | |||
| 2055 | self.__buffer_spc = 0 |
|
2055 | self.__buffer_spc = 0 | |
| 2056 | self.__buffer_cspc = 0 |
|
2056 | self.__buffer_cspc = 0 | |
| 2057 | self.__buffer_dc = 0 |
|
2057 | self.__buffer_dc = 0 | |
| 2058 |
|
2058 | |||
| 2059 | self.__profIndex = 0 |
|
2059 | self.__profIndex = 0 | |
| 2060 | self.__dataReady = False |
|
2060 | self.__dataReady = False | |
| 2061 | self.__byTime = False |
|
2061 | self.__byTime = False | |
| 2062 | self.incohInt = 0 |
|
2062 | self.incohInt = 0 | |
| 2063 | self.nOutliers = 0 |
|
2063 | self.nOutliers = 0 | |
| 2064 | if n is None and timeInterval is None: |
|
2064 | if n is None and timeInterval is None: | |
| 2065 | raise ValueError("n or timeInterval should be specified ...") |
|
2065 | raise ValueError("n or timeInterval should be specified ...") | |
| 2066 |
|
2066 | |||
| 2067 | if n is not None: |
|
2067 | if n is not None: | |
| 2068 | self.n = int(n) |
|
2068 | self.n = int(n) | |
| 2069 | else: |
|
2069 | else: | |
| 2070 |
|
2070 | |||
| 2071 | self.__integrationtime = int(timeInterval) |
|
2071 | self.__integrationtime = int(timeInterval) | |
| 2072 | self.n = None |
|
2072 | self.n = None | |
| 2073 | self.__byTime = True |
|
2073 | self.__byTime = True | |
| 2074 |
|
2074 | |||
| 2075 |
|
2075 | |||
| 2076 |
|
2076 | |||
| 2077 | def putData(self, data_spc, data_cspc, data_dc): |
|
2077 | def putData(self, data_spc, data_cspc, data_dc): | |
| 2078 | """ |
|
2078 | """ | |
| 2079 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
2079 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 2080 |
|
2080 | |||
| 2081 | """ |
|
2081 | """ | |
| 2082 | if data_spc.all() == numpy.nan : |
|
2082 | if data_spc.all() == numpy.nan : | |
| 2083 | print("nan ") |
|
2083 | print("nan ") | |
| 2084 | return |
|
2084 | return | |
| 2085 | self.__buffer_spc += data_spc |
|
2085 | self.__buffer_spc += data_spc | |
| 2086 |
|
2086 | |||
| 2087 | if data_cspc is None: |
|
2087 | if data_cspc is None: | |
| 2088 | self.__buffer_cspc = None |
|
2088 | self.__buffer_cspc = None | |
| 2089 | else: |
|
2089 | else: | |
| 2090 | self.__buffer_cspc += data_cspc |
|
2090 | self.__buffer_cspc += data_cspc | |
| 2091 |
|
2091 | |||
| 2092 | if data_dc is None: |
|
2092 | if data_dc is None: | |
| 2093 | self.__buffer_dc = None |
|
2093 | self.__buffer_dc = None | |
| 2094 | else: |
|
2094 | else: | |
| 2095 | self.__buffer_dc += data_dc |
|
2095 | self.__buffer_dc += data_dc | |
| 2096 |
|
2096 | |||
| 2097 | self.__profIndex += 1 |
|
2097 | self.__profIndex += 1 | |
| 2098 |
|
2098 | |||
| 2099 | return |
|
2099 | return | |
| 2100 |
|
2100 | |||
| 2101 | def pushData(self): |
|
2101 | def pushData(self): | |
| 2102 | """ |
|
2102 | """ | |
| 2103 | Return the sum of the last profiles and the profiles used in the sum. |
|
2103 | Return the sum of the last profiles and the profiles used in the sum. | |
| 2104 |
|
2104 | |||
| 2105 | Affected: |
|
2105 | Affected: | |
| 2106 |
|
2106 | |||
| 2107 | self.__profileIndex |
|
2107 | self.__profileIndex | |
| 2108 |
|
2108 | |||
| 2109 | """ |
|
2109 | """ | |
| 2110 |
|
2110 | |||
| 2111 | data_spc = self.__buffer_spc |
|
2111 | data_spc = self.__buffer_spc | |
| 2112 | data_cspc = self.__buffer_cspc |
|
2112 | data_cspc = self.__buffer_cspc | |
| 2113 | data_dc = self.__buffer_dc |
|
2113 | data_dc = self.__buffer_dc | |
| 2114 | n = self.__profIndex |
|
2114 | n = self.__profIndex | |
| 2115 |
|
2115 | |||
| 2116 | self.__buffer_spc = 0 |
|
2116 | self.__buffer_spc = 0 | |
| 2117 | self.__buffer_cspc = 0 |
|
2117 | self.__buffer_cspc = 0 | |
| 2118 | self.__buffer_dc = 0 |
|
2118 | self.__buffer_dc = 0 | |
| 2119 |
|
2119 | |||
| 2120 |
|
2120 | |||
| 2121 | return data_spc, data_cspc, data_dc, n |
|
2121 | return data_spc, data_cspc, data_dc, n | |
| 2122 |
|
2122 | |||
| 2123 | def byProfiles(self, *args): |
|
2123 | def byProfiles(self, *args): | |
| 2124 |
|
2124 | |||
| 2125 | self.__dataReady = False |
|
2125 | self.__dataReady = False | |
| 2126 | avgdata_spc = None |
|
2126 | avgdata_spc = None | |
| 2127 | avgdata_cspc = None |
|
2127 | avgdata_cspc = None | |
| 2128 | avgdata_dc = None |
|
2128 | avgdata_dc = None | |
| 2129 |
|
2129 | |||
| 2130 | self.putData(*args) |
|
2130 | self.putData(*args) | |
| 2131 |
|
2131 | |||
| 2132 | if self.__profIndex == self.n: |
|
2132 | if self.__profIndex == self.n: | |
| 2133 |
|
2133 | |||
| 2134 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
2134 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 2135 | self.n = n |
|
2135 | self.n = n | |
| 2136 | self.__dataReady = True |
|
2136 | self.__dataReady = True | |
| 2137 |
|
2137 | |||
| 2138 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
2138 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 2139 |
|
2139 | |||
| 2140 | def byTime(self, datatime, *args): |
|
2140 | def byTime(self, datatime, *args): | |
| 2141 |
|
2141 | |||
| 2142 | self.__dataReady = False |
|
2142 | self.__dataReady = False | |
| 2143 | avgdata_spc = None |
|
2143 | avgdata_spc = None | |
| 2144 | avgdata_cspc = None |
|
2144 | avgdata_cspc = None | |
| 2145 | avgdata_dc = None |
|
2145 | avgdata_dc = None | |
| 2146 |
|
2146 | |||
| 2147 | self.putData(*args) |
|
2147 | self.putData(*args) | |
| 2148 |
|
2148 | |||
| 2149 | if (datatime - self.__initime) >= self.__integrationtime: |
|
2149 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 2150 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
2150 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 2151 | self.n = n |
|
2151 | self.n = n | |
| 2152 | self.__dataReady = True |
|
2152 | self.__dataReady = True | |
| 2153 |
|
2153 | |||
| 2154 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
2154 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 2155 |
|
2155 | |||
| 2156 | def integrate(self, datatime, *args): |
|
2156 | def integrate(self, datatime, *args): | |
| 2157 |
|
2157 | |||
| 2158 | if self.__profIndex == 0: |
|
2158 | if self.__profIndex == 0: | |
| 2159 | self.__initime = datatime |
|
2159 | self.__initime = datatime | |
| 2160 |
|
2160 | |||
| 2161 | if self.__byTime: |
|
2161 | if self.__byTime: | |
| 2162 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( |
|
2162 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( | |
| 2163 | datatime, *args) |
|
2163 | datatime, *args) | |
| 2164 | else: |
|
2164 | else: | |
| 2165 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
2165 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 2166 |
|
2166 | |||
| 2167 | if not self.__dataReady: |
|
2167 | if not self.__dataReady: | |
| 2168 | return None, None, None, None |
|
2168 | return None, None, None, None | |
| 2169 |
|
2169 | |||
| 2170 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
2170 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 2171 |
|
2171 | |||
| 2172 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
2172 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 2173 | if n == 1: |
|
2173 | if n == 1: | |
| 2174 | return dataOut |
|
2174 | return dataOut | |
| 2175 |
|
2175 | |||
| 2176 | if dataOut.flagNoData == True: |
|
2176 | if dataOut.flagNoData == True: | |
| 2177 | return dataOut |
|
2177 | return dataOut | |
| 2178 |
|
2178 | |||
| 2179 | if dataOut.flagProfilesByRange == True: |
|
2179 | if dataOut.flagProfilesByRange == True: | |
| 2180 | self._flagProfilesByRange = True |
|
2180 | self._flagProfilesByRange = True | |
| 2181 |
|
2181 | |||
| 2182 | dataOut.flagNoData = True |
|
2182 | dataOut.flagNoData = True | |
| 2183 | dataOut.processingHeaderObj.timeIncohInt = timeInterval |
|
2183 | dataOut.processingHeaderObj.timeIncohInt = timeInterval | |
| 2184 | if not self.isConfig: |
|
2184 | if not self.isConfig: | |
| 2185 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) |
|
2185 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) | |
| 2186 | self.setup(n, timeInterval, overlapping) |
|
2186 | self.setup(n, timeInterval, overlapping) | |
| 2187 | self.isConfig = True |
|
2187 | self.isConfig = True | |
| 2188 |
|
2188 | |||
| 2189 |
|
2189 | |||
| 2190 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
2190 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 2191 | dataOut.data_spc, |
|
2191 | dataOut.data_spc, | |
| 2192 | dataOut.data_cspc, |
|
2192 | dataOut.data_cspc, | |
| 2193 | dataOut.data_dc) |
|
2193 | dataOut.data_dc) | |
| 2194 |
|
2194 | |||
| 2195 | self.incohInt += dataOut.nIncohInt |
|
2195 | self.incohInt += dataOut.nIncohInt | |
| 2196 |
|
2196 | |||
| 2197 |
|
2197 | |||
| 2198 | if isinstance(dataOut.data_outlier,numpy.ndarray) or isinstance(dataOut.data_outlier,int) or isinstance(dataOut.data_outlier, float): |
|
2198 | if isinstance(dataOut.data_outlier,numpy.ndarray) or isinstance(dataOut.data_outlier,int) or isinstance(dataOut.data_outlier, float): | |
| 2199 | self.nOutliers += dataOut.data_outlier |
|
2199 | self.nOutliers += dataOut.data_outlier | |
| 2200 |
|
2200 | |||
| 2201 | if self._flagProfilesByRange: |
|
2201 | if self._flagProfilesByRange: | |
| 2202 | dataOut.flagProfilesByRange = True |
|
2202 | dataOut.flagProfilesByRange = True | |
| 2203 | self._nProfilesByRange += dataOut.nProfilesByRange |
|
2203 | self._nProfilesByRange += dataOut.nProfilesByRange | |
| 2204 |
|
2204 | |||
| 2205 | if self.__dataReady: |
|
2205 | if self.__dataReady: | |
| 2206 | print("IncohInt Done ", self.incohInt) |
|
|||
| 2207 | #print("prof: ",dataOut.max_nIncohInt,self.__profIndex) |
|
2206 | #print("prof: ",dataOut.max_nIncohInt,self.__profIndex) | |
| 2208 | dataOut.data_spc = avgdata_spc |
|
2207 | dataOut.data_spc = avgdata_spc | |
| 2209 | dataOut.data_cspc = avgdata_cspc |
|
2208 | dataOut.data_cspc = avgdata_cspc | |
| 2210 | dataOut.data_dc = avgdata_dc |
|
2209 | dataOut.data_dc = avgdata_dc | |
| 2211 | dataOut.nIncohInt = self.incohInt |
|
2210 | dataOut.nIncohInt = self.incohInt | |
| 2212 | dataOut.data_outlier = self.nOutliers |
|
2211 | dataOut.data_outlier = self.nOutliers | |
| 2213 | dataOut.utctime = avgdatatime |
|
2212 | dataOut.utctime = avgdatatime | |
| 2214 | dataOut.flagNoData = False |
|
2213 | dataOut.flagNoData = False | |
| 2215 | self.incohInt = 0 |
|
2214 | self.incohInt = 0 | |
| 2216 | self.nOutliers = 0 |
|
2215 | self.nOutliers = 0 | |
| 2217 | self.__profIndex = 0 |
|
2216 | self.__profIndex = 0 | |
| 2218 | dataOut.nProfilesByRange = self._nProfilesByRange |
|
2217 | dataOut.nProfilesByRange = self._nProfilesByRange | |
| 2219 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) |
|
2218 | self._nProfilesByRange = numpy.zeros((1,len(dataOut.heightList))) | |
| 2220 | self._flagProfilesByRange = False |
|
2219 | self._flagProfilesByRange = False | |
| 2221 |
|
2220 | #print("IncohInt Done") | ||
| 2222 | return dataOut |
|
2221 | return dataOut | |
| 2223 |
|
2222 | |||
| 2224 | class dopplerFlip(Operation): |
|
2223 | class dopplerFlip(Operation): | |
| 2225 |
|
2224 | |||
| 2226 | def run(self, dataOut): |
|
2225 | def run(self, dataOut): | |
| 2227 | # arreglo 1: (num_chan, num_profiles, num_heights) |
|
2226 | # arreglo 1: (num_chan, num_profiles, num_heights) | |
| 2228 | self.dataOut = dataOut |
|
2227 | self.dataOut = dataOut | |
| 2229 | # JULIA-oblicua, indice 2 |
|
2228 | # JULIA-oblicua, indice 2 | |
| 2230 | # arreglo 2: (num_profiles, num_heights) |
|
2229 | # arreglo 2: (num_profiles, num_heights) | |
| 2231 | jspectra = self.dataOut.data_spc[2] |
|
2230 | jspectra = self.dataOut.data_spc[2] | |
| 2232 | jspectra_tmp = numpy.zeros(jspectra.shape) |
|
2231 | jspectra_tmp = numpy.zeros(jspectra.shape) | |
| 2233 | num_profiles = jspectra.shape[0] |
|
2232 | num_profiles = jspectra.shape[0] | |
| 2234 | freq_dc = int(num_profiles / 2) |
|
2233 | freq_dc = int(num_profiles / 2) | |
| 2235 | # Flip con for |
|
2234 | # Flip con for | |
| 2236 | for j in range(num_profiles): |
|
2235 | for j in range(num_profiles): | |
| 2237 | jspectra_tmp[num_profiles-j-1]= jspectra[j] |
|
2236 | jspectra_tmp[num_profiles-j-1]= jspectra[j] | |
| 2238 | # Intercambio perfil de DC con perfil inmediato anterior |
|
2237 | # Intercambio perfil de DC con perfil inmediato anterior | |
| 2239 | jspectra_tmp[freq_dc-1]= jspectra[freq_dc-1] |
|
2238 | jspectra_tmp[freq_dc-1]= jspectra[freq_dc-1] | |
| 2240 | jspectra_tmp[freq_dc]= jspectra[freq_dc] |
|
2239 | jspectra_tmp[freq_dc]= jspectra[freq_dc] | |
| 2241 | # canal modificado es re-escrito en el arreglo de canales |
|
2240 | # canal modificado es re-escrito en el arreglo de canales | |
| 2242 | self.dataOut.data_spc[2] = jspectra_tmp |
|
2241 | self.dataOut.data_spc[2] = jspectra_tmp | |
| 2243 |
|
2242 | |||
| 2244 | return self.dataOut |
|
2243 | return self.dataOut | |
| 2245 |
|
2244 | |||
| 2246 |
|
2245 | |||
| 2247 |
|
2246 | |||
| 2248 |
|
2247 | |||
| 2249 |
|
2248 | |||
| 2250 |
|
2249 | |||
| 2251 | class cleanJULIAInterf(Operation): |
|
2250 | class cleanJULIAInterf(Operation): | |
| 2252 | """ |
|
2251 | """ | |
| 2253 | OperaciΓ³n de prueba |
|
2252 | OperaciΓ³n de prueba | |
| 2254 | """ |
|
2253 | """ | |
| 2255 | __slots__ =('heights_indx', 'repeats','span' ,'step', 'factor', 'idate', 'idxs','isConfig','minHrefN', 'maxHrefN') |
|
2254 | __slots__ =('heights_indx', 'repeats','span' ,'step', 'factor', 'idate', 'idxs','isConfig','minHrefN', 'maxHrefN') | |
| 2256 | def __init__(self): |
|
2255 | def __init__(self): | |
| 2257 | self.repeats = 0 |
|
2256 | self.repeats = 0 | |
| 2258 | self.factor=1 |
|
2257 | self.factor=1 | |
| 2259 | self.isConfig = False |
|
2258 | self.isConfig = False | |
| 2260 | self.idxs = None |
|
2259 | self.idxs = None | |
| 2261 | self.heights_indx = None |
|
2260 | self.heights_indx = None | |
| 2262 |
|
2261 | |||
| 2263 | def setup(self, dataOutHeightsList, heightsList, span=10, repeats=0, step=0, idate=None, startH=None, endH=None, minHref=None, maxHref=None): |
|
2262 | def setup(self, dataOutHeightsList, heightsList, span=10, repeats=0, step=0, idate=None, startH=None, endH=None, minHref=None, maxHref=None): | |
| 2264 | totalHeihtList = dataOutHeightsList |
|
2263 | totalHeihtList = dataOutHeightsList | |
| 2265 | heights = [float(hei) for hei in heightsList] |
|
2264 | heights = [float(hei) for hei in heightsList] | |
| 2266 | for r in range(repeats): |
|
2265 | for r in range(repeats): | |
| 2267 | heights += [ (h+(step*(r+1))) for h in heights] |
|
2266 | heights += [ (h+(step*(r+1))) for h in heights] | |
| 2268 | #print(heights) |
|
2267 | #print(heights) | |
| 2269 | self.heights_indx = [getHei_index(h,h,totalHeihtList)[0] for h in heights] |
|
2268 | self.heights_indx = [getHei_index(h,h,totalHeihtList)[0] for h in heights] | |
| 2270 |
|
2269 | |||
| 2271 | self.minHrefN, self.maxHrefN = getHei_index(minHref,maxHref,totalHeihtList) |
|
2270 | self.minHrefN, self.maxHrefN = getHei_index(minHref,maxHref,totalHeihtList) | |
| 2272 |
|
2271 | |||
| 2273 |
|
2272 | |||
| 2274 | self.config = True |
|
2273 | self.config = True | |
| 2275 | self.span = span |
|
2274 | self.span = span | |
| 2276 |
|
2275 | |||
| 2277 | def run(self, dataOut, heightsList, span=10, repeats=0, step=0, idate=None, startH=None, endH=None, minHref=None, maxHref=None): |
|
2276 | def run(self, dataOut, heightsList, span=10, repeats=0, step=0, idate=None, startH=None, endH=None, minHref=None, maxHref=None): | |
| 2278 |
|
2277 | |||
| 2279 |
|
2278 | |||
| 2280 | self.dataOut = dataOut |
|
2279 | self.dataOut = dataOut | |
| 2281 | startTime = datetime.datetime.combine(idate,startH) |
|
2280 | startTime = datetime.datetime.combine(idate,startH) | |
| 2282 | endTime = datetime.datetime.combine(idate,endH) |
|
2281 | endTime = datetime.datetime.combine(idate,endH) | |
| 2283 | currentTime = datetime.datetime.fromtimestamp(self.dataOut.utctime) |
|
2282 | currentTime = datetime.datetime.fromtimestamp(self.dataOut.utctime) | |
| 2284 |
|
2283 | |||
| 2285 | if currentTime < startTime or currentTime > endTime: |
|
2284 | if currentTime < startTime or currentTime > endTime: | |
| 2286 | return self.dataOut |
|
2285 | return self.dataOut | |
| 2287 |
|
2286 | |||
| 2288 | if not self.isConfig: |
|
2287 | if not self.isConfig: | |
| 2289 | self.setup(self.dataOut.heightList,heightsList, span=span, repeats=repeats, step=step, idate=idate, startH=startH, endH=endH, minHref=minHref, maxHref=maxHref ) |
|
2288 | self.setup(self.dataOut.heightList,heightsList, span=span, repeats=repeats, step=step, idate=idate, startH=startH, endH=endH, minHref=minHref, maxHref=maxHref ) | |
| 2290 |
|
2289 | |||
| 2291 | for ch in range(self.dataOut.data_spc.shape[0]): |
|
2290 | for ch in range(self.dataOut.data_spc.shape[0]): | |
| 2292 | i = 0 |
|
2291 | i = 0 | |
| 2293 | N_ref = self.dataOut.data_spc[ch, :, self.minHrefN: self.maxHrefN].mean() |
|
2292 | N_ref = self.dataOut.data_spc[ch, :, self.minHrefN: self.maxHrefN].mean() | |
| 2294 | mn = self.heights_indx[-1] - self.span/2 |
|
2293 | mn = self.heights_indx[-1] - self.span/2 | |
| 2295 | mx = self.heights_indx[-1] + self.span/2 |
|
2294 | mx = self.heights_indx[-1] + self.span/2 | |
| 2296 | J_lev = self.dataOut.data_spc[ch, :, mn: mx].mean() - N_ref |
|
2295 | J_lev = self.dataOut.data_spc[ch, :, mn: mx].mean() - N_ref | |
| 2297 |
|
2296 | |||
| 2298 | for hei in self.heights_indx: |
|
2297 | for hei in self.heights_indx: | |
| 2299 | h = hei - 1 |
|
2298 | h = hei - 1 | |
| 2300 | mn_i = hei - self.span/2 |
|
2299 | mn_i = hei - self.span/2 | |
| 2301 | mx_i = hei + self.span/2 |
|
2300 | mx_i = hei + self.span/2 | |
| 2302 | self.dataOut.data_spc[ch, :,mn_i:mx_i ] -= J_lev |
|
2301 | self.dataOut.data_spc[ch, :,mn_i:mx_i ] -= J_lev | |
| 2303 | i += 1 |
|
2302 | i += 1 | |
| 2304 |
|
2303 | |||
| 2305 |
|
2304 | |||
| 2306 | return self.dataOut No newline at end of file |
|
2305 | return self.dataOut | |
| @@ -1,3259 +1,3249 | |||||
| 1 | import sys |
|
1 | import sys | |
| 2 | import numpy,math |
|
2 | import numpy,math | |
| 3 | from scipy import interpolate |
|
3 | from scipy import interpolate | |
| 4 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator |
|
4 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation, MPDecorator | |
| 5 | from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon |
|
5 | from schainpy.model.data.jrodata import Voltage,hildebrand_sekhon | |
| 6 | from schainpy.utils import log |
|
6 | from schainpy.utils import log | |
| 7 | from schainpy.model.io.utilsIO import getHei_index |
|
7 | from schainpy.model.io.utilsIO import getHei_index | |
| 8 | from time import time |
|
8 | from time import time | |
| 9 | import datetime |
|
9 | import datetime | |
| 10 | import numpy |
|
10 | import numpy | |
| 11 | #import copy |
|
11 | #import copy | |
| 12 | from schainpy.model.data import _noise |
|
12 | from schainpy.model.data import _noise | |
| 13 |
|
13 | |||
| 14 | from matplotlib import pyplot as plt |
|
14 | from matplotlib import pyplot as plt | |
| 15 |
|
15 | |||
| 16 | class VoltageProc(ProcessingUnit): |
|
16 | class VoltageProc(ProcessingUnit): | |
| 17 |
|
17 | |||
| 18 | def __init__(self): |
|
18 | def __init__(self): | |
| 19 |
|
19 | |||
| 20 | ProcessingUnit.__init__(self) |
|
20 | ProcessingUnit.__init__(self) | |
| 21 |
|
21 | |||
| 22 | self.dataOut = Voltage() |
|
22 | self.dataOut = Voltage() | |
| 23 | self.flip = 1 |
|
23 | self.flip = 1 | |
| 24 | self.setupReq = False |
|
24 | self.setupReq = False | |
| 25 |
|
25 | |||
| 26 | def run(self): |
|
26 | def run(self): | |
| 27 | #print("running volt proc") |
|
27 | #print("running volt proc") | |
| 28 |
|
28 | |||
| 29 | if self.dataIn.type == 'AMISR': |
|
29 | if self.dataIn.type == 'AMISR': | |
| 30 | self.__updateObjFromAmisrInput() |
|
30 | self.__updateObjFromAmisrInput() | |
| 31 |
|
31 | |||
| 32 | if self.dataOut.buffer_empty: |
|
32 | if self.dataOut.buffer_empty: | |
| 33 | if self.dataIn.type == 'Voltage': |
|
33 | if self.dataIn.type == 'Voltage': | |
| 34 | self.dataOut.copy(self.dataIn) |
|
34 | self.dataOut.copy(self.dataIn) | |
| 35 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
35 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 36 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
36 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 37 | self.dataOut.ipp = self.dataIn.ipp |
|
37 | self.dataOut.ipp = self.dataIn.ipp | |
| 38 |
|
38 | |||
| 39 | #update Processing Header: |
|
39 | #update Processing Header: | |
| 40 | self.dataOut.processingHeaderObj.heightList = self.dataOut.heightList |
|
40 | self.dataOut.processingHeaderObj.heightList = self.dataOut.heightList | |
| 41 | self.dataOut.processingHeaderObj.ipp = self.dataOut.ipp |
|
41 | self.dataOut.processingHeaderObj.ipp = self.dataOut.ipp | |
| 42 | self.dataOut.processingHeaderObj.nCohInt = self.dataOut.nCohInt |
|
42 | self.dataOut.processingHeaderObj.nCohInt = self.dataOut.nCohInt | |
| 43 | self.dataOut.processingHeaderObj.dtype = self.dataOut.type |
|
43 | self.dataOut.processingHeaderObj.dtype = self.dataOut.type | |
| 44 | self.dataOut.processingHeaderObj.channelList = self.dataOut.channelList |
|
44 | self.dataOut.processingHeaderObj.channelList = self.dataOut.channelList | |
| 45 | self.dataOut.processingHeaderObj.azimuthList = self.dataOut.azimuthList |
|
45 | self.dataOut.processingHeaderObj.azimuthList = self.dataOut.azimuthList | |
| 46 | self.dataOut.processingHeaderObj.elevationList = self.dataOut.elevationList |
|
46 | self.dataOut.processingHeaderObj.elevationList = self.dataOut.elevationList | |
| 47 | self.dataOut.processingHeaderObj.codeList = self.dataOut.nChannels |
|
47 | self.dataOut.processingHeaderObj.codeList = self.dataOut.nChannels | |
| 48 | self.dataOut.processingHeaderObj.heightList = self.dataOut.heightList |
|
48 | self.dataOut.processingHeaderObj.heightList = self.dataOut.heightList | |
| 49 | self.dataOut.processingHeaderObj.heightResolution = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
49 | self.dataOut.processingHeaderObj.heightResolution = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
| 50 |
|
50 | |||
| 51 |
|
51 | |||
| 52 |
|
52 | |||
| 53 | def __updateObjFromAmisrInput(self): |
|
53 | def __updateObjFromAmisrInput(self): | |
| 54 |
|
54 | |||
| 55 | self.dataOut.timeZone = self.dataIn.timeZone |
|
55 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 56 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
56 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 57 | self.dataOut.errorCount = self.dataIn.errorCount |
|
57 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 58 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
58 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 59 |
|
59 | |||
| 60 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
60 | self.dataOut.flagNoData = self.dataIn.flagNoData | |
| 61 | self.dataOut.data = self.dataIn.data |
|
61 | self.dataOut.data = self.dataIn.data | |
| 62 | self.dataOut.utctime = self.dataIn.utctime |
|
62 | self.dataOut.utctime = self.dataIn.utctime | |
| 63 | self.dataOut.channelList = self.dataIn.channelList |
|
63 | self.dataOut.channelList = self.dataIn.channelList | |
| 64 | #self.dataOut.timeInterval = self.dataIn.timeInterval |
|
64 | #self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 65 | self.dataOut.heightList = self.dataIn.heightList |
|
65 | self.dataOut.heightList = self.dataIn.heightList | |
| 66 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
66 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
| 67 |
|
67 | |||
| 68 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
68 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 69 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
69 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 70 | self.dataOut.frequency = self.dataIn.frequency |
|
70 | self.dataOut.frequency = self.dataIn.frequency | |
| 71 |
|
71 | |||
| 72 | self.dataOut.azimuth = self.dataIn.azimuth |
|
72 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 73 | self.dataOut.zenith = self.dataIn.zenith |
|
73 | self.dataOut.zenith = self.dataIn.zenith | |
| 74 |
|
74 | |||
| 75 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
75 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 76 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
76 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 77 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
77 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 78 |
|
78 | |||
| 79 |
|
79 | |||
| 80 | class selectChannels(Operation): |
|
80 | class selectChannels(Operation): | |
| 81 |
|
81 | |||
| 82 | def run(self, dataOut, channelList=[]): |
|
82 | def run(self, dataOut, channelList=[]): | |
| 83 |
|
83 | |||
| 84 | if isinstance(channelList, int): |
|
84 | if isinstance(channelList, int): | |
| 85 | channelList = [channelList] |
|
85 | channelList = [channelList] | |
| 86 |
|
86 | |||
| 87 | self.channelList = channelList |
|
87 | self.channelList = channelList | |
| 88 | if len(self.channelList) == 0: |
|
88 | if len(self.channelList) == 0: | |
| 89 | print("Missing channelList") |
|
89 | print("Missing channelList") | |
| 90 | return dataOut |
|
90 | return dataOut | |
| 91 | channelIndexList = [] |
|
91 | channelIndexList = [] | |
| 92 | if not dataOut.buffer_empty: # cuando se usa proc volts como buffer de datos |
|
92 | if not dataOut.buffer_empty: # cuando se usa proc volts como buffer de datos | |
| 93 | return dataOut |
|
93 | return dataOut | |
| 94 | #print("channel List: ", dataOut.channelList) |
|
94 | #print("channel List: ", dataOut.channelList) | |
| 95 | if type(dataOut.channelList) is not list: #leer array desde HDF5 |
|
95 | if type(dataOut.channelList) is not list: #leer array desde HDF5 | |
| 96 | try: |
|
96 | try: | |
| 97 | dataOut.channelList = dataOut.channelList.tolist() |
|
97 | dataOut.channelList = dataOut.channelList.tolist() | |
| 98 | except Exception as e: |
|
98 | except Exception as e: | |
| 99 | print("Select Channels: ",e) |
|
99 | print("Select Channels: ",e) | |
| 100 | for channel in self.channelList: |
|
100 | for channel in self.channelList: | |
| 101 | if channel not in dataOut.channelList: |
|
101 | if channel not in dataOut.channelList: | |
| 102 | raise ValueError("Channel %d is not in %s" %(channel, str(dataOut.channelList))) |
|
102 | raise ValueError("Channel %d is not in %s" %(channel, str(dataOut.channelList))) | |
| 103 |
|
103 | |||
| 104 | index = dataOut.channelList.index(channel) |
|
104 | index = dataOut.channelList.index(channel) | |
| 105 | channelIndexList.append(index) |
|
105 | channelIndexList.append(index) | |
| 106 |
|
106 | |||
| 107 | dataOut = self.selectChannelsByIndex(dataOut,channelIndexList) |
|
107 | dataOut = self.selectChannelsByIndex(dataOut,channelIndexList) | |
| 108 |
|
108 | |||
| 109 | #update Processing Header: |
|
109 | #update Processing Header: | |
| 110 | dataOut.processingHeaderObj.channelList = dataOut.channelList |
|
110 | dataOut.processingHeaderObj.channelList = dataOut.channelList | |
| 111 | dataOut.processingHeaderObj.elevationList = dataOut.elevationList |
|
111 | dataOut.processingHeaderObj.elevationList = dataOut.elevationList | |
| 112 | dataOut.processingHeaderObj.azimuthList = dataOut.azimuthList |
|
112 | dataOut.processingHeaderObj.azimuthList = dataOut.azimuthList | |
| 113 | dataOut.processingHeaderObj.codeList = dataOut.codeList |
|
113 | dataOut.processingHeaderObj.codeList = dataOut.codeList | |
| 114 | dataOut.processingHeaderObj.nChannels = len(dataOut.channelList) |
|
114 | dataOut.processingHeaderObj.nChannels = len(dataOut.channelList) | |
| 115 |
|
115 | |||
| 116 | return dataOut |
|
116 | return dataOut | |
| 117 |
|
117 | |||
| 118 | def selectChannelsByIndex(self, dataOut, channelIndexList): |
|
118 | def selectChannelsByIndex(self, dataOut, channelIndexList): | |
| 119 | """ |
|
119 | """ | |
| 120 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
120 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 121 |
|
121 | |||
| 122 | Input: |
|
122 | Input: | |
| 123 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
123 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 124 |
|
124 | |||
| 125 | Affected: |
|
125 | Affected: | |
| 126 | dataOut.data |
|
126 | dataOut.data | |
| 127 | dataOut.channelIndexList |
|
127 | dataOut.channelIndexList | |
| 128 | dataOut.nChannels |
|
128 | dataOut.nChannels | |
| 129 | dataOut.m_ProcessingHeader.totalSpectra |
|
129 | dataOut.m_ProcessingHeader.totalSpectra | |
| 130 | dataOut.systemHeaderObj.numChannels |
|
130 | dataOut.systemHeaderObj.numChannels | |
| 131 | dataOut.m_ProcessingHeader.blockSize |
|
131 | dataOut.m_ProcessingHeader.blockSize | |
| 132 |
|
132 | |||
| 133 | Return: |
|
133 | Return: | |
| 134 | None |
|
134 | None | |
| 135 | """ |
|
135 | """ | |
| 136 | #print("selectChannelsByIndex") |
|
136 | #print("selectChannelsByIndex") | |
| 137 | # for channelIndex in channelIndexList: |
|
137 | # for channelIndex in channelIndexList: | |
| 138 | # if channelIndex not in dataOut.channelIndexList: |
|
138 | # if channelIndex not in dataOut.channelIndexList: | |
| 139 | # raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) |
|
139 | # raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) | |
| 140 |
|
140 | |||
| 141 | if dataOut.type == 'Voltage': |
|
141 | if dataOut.type == 'Voltage': | |
| 142 | if dataOut.flagDataAsBlock: |
|
142 | if dataOut.flagDataAsBlock: | |
| 143 | """ |
|
143 | """ | |
| 144 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
144 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 145 | """ |
|
145 | """ | |
| 146 | data = dataOut.data[channelIndexList,:,:] |
|
146 | data = dataOut.data[channelIndexList,:,:] | |
| 147 | else: |
|
147 | else: | |
| 148 | data = dataOut.data[channelIndexList,:] |
|
148 | data = dataOut.data[channelIndexList,:] | |
| 149 |
|
149 | |||
| 150 | dataOut.data = data |
|
150 | dataOut.data = data | |
| 151 | # dataOut.channelList = [dataOut.channelList[i] for i in channelIndexList] |
|
151 | # dataOut.channelList = [dataOut.channelList[i] for i in channelIndexList] | |
| 152 | dataOut.channelList = [n for n in range(len(channelIndexList))] |
|
152 | dataOut.channelList = [n for n in range(len(channelIndexList))] | |
| 153 |
|
153 | |||
| 154 | elif dataOut.type == 'Spectra': |
|
154 | elif dataOut.type == 'Spectra': | |
| 155 | if hasattr(dataOut, 'data_spc'): |
|
155 | if hasattr(dataOut, 'data_spc'): | |
| 156 | if dataOut.data_spc is None: |
|
156 | if dataOut.data_spc is None: | |
| 157 | raise ValueError("data_spc is None") |
|
157 | raise ValueError("data_spc is None") | |
| 158 | return dataOut |
|
158 | return dataOut | |
| 159 | else: |
|
159 | else: | |
| 160 | data_spc = dataOut.data_spc[channelIndexList, :] |
|
160 | data_spc = dataOut.data_spc[channelIndexList, :] | |
| 161 | dataOut.data_spc = data_spc |
|
161 | dataOut.data_spc = data_spc | |
| 162 |
|
162 | |||
| 163 | # if hasattr(dataOut, 'data_dc') :# and |
|
163 | # if hasattr(dataOut, 'data_dc') :# and | |
| 164 | # if dataOut.data_dc is None: |
|
164 | # if dataOut.data_dc is None: | |
| 165 | # raise ValueError("data_dc is None") |
|
165 | # raise ValueError("data_dc is None") | |
| 166 | # return dataOut |
|
166 | # return dataOut | |
| 167 | # else: |
|
167 | # else: | |
| 168 | # data_dc = dataOut.data_dc[channelIndexList, :] |
|
168 | # data_dc = dataOut.data_dc[channelIndexList, :] | |
| 169 | # dataOut.data_dc = data_dc |
|
169 | # dataOut.data_dc = data_dc | |
| 170 | # dataOut.channelList = [dataOut.channelList[i] for i in channelIndexList] |
|
170 | # dataOut.channelList = [dataOut.channelList[i] for i in channelIndexList] | |
| 171 | dataOut.channelList = channelIndexList |
|
171 | dataOut.channelList = channelIndexList | |
| 172 | dataOut = self.__selectPairsByChannel(dataOut,channelIndexList) |
|
172 | dataOut = self.__selectPairsByChannel(dataOut,channelIndexList) | |
| 173 |
|
173 | |||
| 174 | # channelIndexList = numpy.asarray(channelIndexList) |
|
174 | # channelIndexList = numpy.asarray(channelIndexList) | |
| 175 | dataOut.elevationList = numpy.asarray(dataOut.elevationList) |
|
175 | dataOut.elevationList = numpy.asarray(dataOut.elevationList) | |
| 176 | dataOut.azimuthList = numpy.asarray(dataOut.azimuthList) |
|
176 | dataOut.azimuthList = numpy.asarray(dataOut.azimuthList) | |
| 177 | dataOut.codeList = numpy.asarray(dataOut.codeList) |
|
177 | dataOut.codeList = numpy.asarray(dataOut.codeList) | |
| 178 | if (len(dataOut.elevationList) > 0): |
|
178 | if (len(dataOut.elevationList) > 0): | |
| 179 | dataOut.elevationList = dataOut.elevationList[channelIndexList] |
|
179 | dataOut.elevationList = dataOut.elevationList[channelIndexList] | |
| 180 | dataOut.azimuthList = dataOut.azimuthList[channelIndexList] |
|
180 | dataOut.azimuthList = dataOut.azimuthList[channelIndexList] | |
| 181 | dataOut.codeList = dataOut.codeList[channelIndexList] |
|
181 | dataOut.codeList = dataOut.codeList[channelIndexList] | |
| 182 |
|
182 | |||
| 183 | return dataOut |
|
183 | return dataOut | |
| 184 |
|
184 | |||
| 185 | def __selectPairsByChannel(self, dataOut, channelList=None): |
|
185 | def __selectPairsByChannel(self, dataOut, channelList=None): | |
| 186 | #print("__selectPairsByChannel") |
|
186 | #print("__selectPairsByChannel") | |
| 187 | if channelList == None: |
|
187 | if channelList == None: | |
| 188 | return |
|
188 | return | |
| 189 |
|
189 | |||
| 190 | pairsIndexListSelected = [] |
|
190 | pairsIndexListSelected = [] | |
| 191 | for pairIndex in dataOut.pairsIndexList: |
|
191 | for pairIndex in dataOut.pairsIndexList: | |
| 192 | # First pair |
|
192 | # First pair | |
| 193 | if dataOut.pairsList[pairIndex][0] not in channelList: |
|
193 | if dataOut.pairsList[pairIndex][0] not in channelList: | |
| 194 | continue |
|
194 | continue | |
| 195 | # Second pair |
|
195 | # Second pair | |
| 196 | if dataOut.pairsList[pairIndex][1] not in channelList: |
|
196 | if dataOut.pairsList[pairIndex][1] not in channelList: | |
| 197 | continue |
|
197 | continue | |
| 198 |
|
198 | |||
| 199 | pairsIndexListSelected.append(pairIndex) |
|
199 | pairsIndexListSelected.append(pairIndex) | |
| 200 | if not pairsIndexListSelected: |
|
200 | if not pairsIndexListSelected: | |
| 201 | dataOut.data_cspc = None |
|
201 | dataOut.data_cspc = None | |
| 202 | dataOut.pairsList = [] |
|
202 | dataOut.pairsList = [] | |
| 203 | return |
|
203 | return | |
| 204 |
|
204 | |||
| 205 | dataOut.data_cspc = dataOut.data_cspc[pairsIndexListSelected] |
|
205 | dataOut.data_cspc = dataOut.data_cspc[pairsIndexListSelected] | |
| 206 | dataOut.pairsList = [dataOut.pairsList[i] |
|
206 | dataOut.pairsList = [dataOut.pairsList[i] | |
| 207 | for i in pairsIndexListSelected] |
|
207 | for i in pairsIndexListSelected] | |
| 208 |
|
208 | |||
| 209 | return dataOut |
|
209 | return dataOut | |
| 210 |
|
210 | |||
| 211 | class selectHeights(Operation): |
|
211 | class selectHeights(Operation): | |
| 212 |
|
212 | |||
| 213 | def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None): |
|
213 | def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None): | |
| 214 | """ |
|
214 | """ | |
| 215 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
215 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 216 | minHei <= height <= maxHei |
|
216 | minHei <= height <= maxHei | |
| 217 |
|
217 | |||
| 218 | Input: |
|
218 | Input: | |
| 219 | minHei : valor minimo de altura a considerar |
|
219 | minHei : valor minimo de altura a considerar | |
| 220 | maxHei : valor maximo de altura a considerar |
|
220 | maxHei : valor maximo de altura a considerar | |
| 221 |
|
221 | |||
| 222 | Affected: |
|
222 | Affected: | |
| 223 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
223 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 224 |
|
224 | |||
| 225 | Return: |
|
225 | Return: | |
| 226 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
226 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 227 | """ |
|
227 | """ | |
| 228 |
|
228 | |||
| 229 | self.dataOut = dataOut |
|
229 | self.dataOut = dataOut | |
| 230 |
|
230 | |||
| 231 | if minHei and maxHei: |
|
231 | if minHei and maxHei: | |
| 232 |
|
232 | |||
| 233 | if (minHei < dataOut.heightList[0]): |
|
233 | if (minHei < dataOut.heightList[0]): | |
| 234 | minHei = dataOut.heightList[0] |
|
234 | minHei = dataOut.heightList[0] | |
| 235 |
|
235 | |||
| 236 | if (maxHei > dataOut.heightList[-1]): |
|
236 | if (maxHei > dataOut.heightList[-1]): | |
| 237 | maxHei = dataOut.heightList[-1] |
|
237 | maxHei = dataOut.heightList[-1] | |
| 238 |
|
238 | |||
| 239 | minIndex = 0 |
|
239 | minIndex = 0 | |
| 240 | maxIndex = 0 |
|
240 | maxIndex = 0 | |
| 241 | heights = dataOut.heightList |
|
241 | heights = dataOut.heightList | |
| 242 |
|
242 | |||
| 243 | inda = numpy.where(heights >= minHei) |
|
243 | inda = numpy.where(heights >= minHei) | |
| 244 | indb = numpy.where(heights <= maxHei) |
|
244 | indb = numpy.where(heights <= maxHei) | |
| 245 |
|
245 | |||
| 246 | try: |
|
246 | try: | |
| 247 | minIndex = inda[0][0] |
|
247 | minIndex = inda[0][0] | |
| 248 | except: |
|
248 | except: | |
| 249 | minIndex = 0 |
|
249 | minIndex = 0 | |
| 250 |
|
250 | |||
| 251 | try: |
|
251 | try: | |
| 252 | maxIndex = indb[0][-1] |
|
252 | maxIndex = indb[0][-1] | |
| 253 | except: |
|
253 | except: | |
| 254 | maxIndex = len(heights) |
|
254 | maxIndex = len(heights) | |
| 255 |
|
255 | |||
| 256 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
256 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 257 |
|
257 | |||
| 258 | #update Processing Header: |
|
258 | #update Processing Header: | |
| 259 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
259 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 260 |
|
260 | |||
| 261 |
|
261 | |||
| 262 |
|
262 | |||
| 263 | return dataOut |
|
263 | return dataOut | |
| 264 |
|
264 | |||
| 265 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
265 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 266 | """ |
|
266 | """ | |
| 267 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
267 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 268 | minIndex <= index <= maxIndex |
|
268 | minIndex <= index <= maxIndex | |
| 269 |
|
269 | |||
| 270 | Input: |
|
270 | Input: | |
| 271 | minIndex : valor de indice minimo de altura a considerar |
|
271 | minIndex : valor de indice minimo de altura a considerar | |
| 272 | maxIndex : valor de indice maximo de altura a considerar |
|
272 | maxIndex : valor de indice maximo de altura a considerar | |
| 273 |
|
273 | |||
| 274 | Affected: |
|
274 | Affected: | |
| 275 | self.dataOut.data |
|
275 | self.dataOut.data | |
| 276 | self.dataOut.heightList |
|
276 | self.dataOut.heightList | |
| 277 |
|
277 | |||
| 278 | Return: |
|
278 | Return: | |
| 279 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
279 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 280 | """ |
|
280 | """ | |
| 281 |
|
281 | |||
| 282 | if self.dataOut.type == 'Voltage': |
|
282 | if self.dataOut.type == 'Voltage': | |
| 283 | if (minIndex < 0) or (minIndex > maxIndex): |
|
283 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 284 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
284 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) | |
| 285 |
|
285 | |||
| 286 | if (maxIndex >= self.dataOut.nHeights): |
|
286 | if (maxIndex >= self.dataOut.nHeights): | |
| 287 | maxIndex = self.dataOut.nHeights |
|
287 | maxIndex = self.dataOut.nHeights | |
| 288 |
|
288 | |||
| 289 | #voltage |
|
289 | #voltage | |
| 290 | if self.dataOut.flagDataAsBlock: |
|
290 | if self.dataOut.flagDataAsBlock: | |
| 291 | """ |
|
291 | """ | |
| 292 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
292 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 293 | """ |
|
293 | """ | |
| 294 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
294 | data = self.dataOut.data[:,:, minIndex:maxIndex] | |
| 295 | else: |
|
295 | else: | |
| 296 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
296 | data = self.dataOut.data[:, minIndex:maxIndex] | |
| 297 |
|
297 | |||
| 298 | # firstHeight = self.dataOut.heightList[minIndex] |
|
298 | # firstHeight = self.dataOut.heightList[minIndex] | |
| 299 |
|
299 | |||
| 300 | self.dataOut.data = data |
|
300 | self.dataOut.data = data | |
| 301 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
301 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] | |
| 302 |
|
302 | |||
| 303 | if self.dataOut.nHeights <= 1: |
|
303 | if self.dataOut.nHeights <= 1: | |
| 304 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) |
|
304 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) | |
| 305 | elif self.dataOut.type == 'Spectra': |
|
305 | elif self.dataOut.type == 'Spectra': | |
| 306 | if (minIndex < 0) or (minIndex > maxIndex): |
|
306 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 307 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( |
|
307 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( | |
| 308 | minIndex, maxIndex)) |
|
308 | minIndex, maxIndex)) | |
| 309 |
|
309 | |||
| 310 | if (maxIndex >= self.dataOut.nHeights): |
|
310 | if (maxIndex >= self.dataOut.nHeights): | |
| 311 | maxIndex = self.dataOut.nHeights - 1 |
|
311 | maxIndex = self.dataOut.nHeights - 1 | |
| 312 |
|
312 | |||
| 313 | # Spectra |
|
313 | # Spectra | |
| 314 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
314 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] | |
| 315 |
|
315 | |||
| 316 | data_cspc = None |
|
316 | data_cspc = None | |
| 317 | if self.dataOut.data_cspc is not None: |
|
317 | if self.dataOut.data_cspc is not None: | |
| 318 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
318 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] | |
| 319 |
|
319 | |||
| 320 | data_dc = None |
|
320 | data_dc = None | |
| 321 | if self.dataOut.data_dc is not None: |
|
321 | if self.dataOut.data_dc is not None: | |
| 322 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
322 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] | |
| 323 |
|
323 | |||
| 324 | self.dataOut.data_spc = data_spc |
|
324 | self.dataOut.data_spc = data_spc | |
| 325 | self.dataOut.data_cspc = data_cspc |
|
325 | self.dataOut.data_cspc = data_cspc | |
| 326 | self.dataOut.data_dc = data_dc |
|
326 | self.dataOut.data_dc = data_dc | |
| 327 |
|
327 | |||
| 328 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
328 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] | |
| 329 |
|
329 | |||
| 330 | return 1 |
|
330 | return 1 | |
| 331 |
|
331 | |||
| 332 |
|
332 | |||
| 333 | class filterByHeights(Operation): |
|
333 | class filterByHeights(Operation): | |
| 334 | ifConfig=False |
|
334 | ifConfig=False | |
| 335 | deltaHeight = None |
|
335 | deltaHeight = None | |
| 336 | newdelta=None |
|
336 | newdelta=None | |
| 337 | newheights=None |
|
337 | newheights=None | |
| 338 | r=None |
|
338 | r=None | |
| 339 | h0=None |
|
339 | h0=None | |
| 340 | nHeights=None |
|
340 | nHeights=None | |
| 341 | def run(self, dataOut, window): |
|
341 | def run(self, dataOut, window): | |
| 342 |
|
342 | |||
| 343 |
|
343 | |||
| 344 | # print("1",dataOut.data.shape) |
|
344 | # print("1",dataOut.data.shape) | |
| 345 | # print(dataOut.nHeights) |
|
345 | # print(dataOut.nHeights) | |
| 346 | if window == None: |
|
346 | if window == None: | |
| 347 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / self.deltaHeight |
|
347 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / self.deltaHeight | |
| 348 |
|
348 | |||
| 349 | if not self.ifConfig: #and dataOut.useInputBuffer: |
|
349 | if not self.ifConfig: #and dataOut.useInputBuffer: | |
| 350 | self.deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
350 | self.deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 351 | self.ifConfig = True |
|
351 | self.ifConfig = True | |
| 352 | self.newdelta = self.deltaHeight * window |
|
352 | self.newdelta = self.deltaHeight * window | |
| 353 | self.r = dataOut.nHeights % window |
|
353 | self.r = dataOut.nHeights % window | |
| 354 | self.newheights = (dataOut.nHeights-self.r)/window |
|
354 | self.newheights = (dataOut.nHeights-self.r)/window | |
| 355 | self.h0 = dataOut.heightList[0] |
|
355 | self.h0 = dataOut.heightList[0] | |
| 356 | self.nHeights = dataOut.nHeights |
|
356 | self.nHeights = dataOut.nHeights | |
| 357 | if self.newheights <= 1: |
|
357 | if self.newheights <= 1: | |
| 358 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) |
|
358 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) | |
| 359 |
|
359 | |||
| 360 | if dataOut.flagDataAsBlock: |
|
360 | if dataOut.flagDataAsBlock: | |
| 361 | """ |
|
361 | """ | |
| 362 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
362 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 363 | """ |
|
363 | """ | |
| 364 | buffer = dataOut.data[:, :, 0:int(self.nHeights-self.r)] |
|
364 | buffer = dataOut.data[:, :, 0:int(self.nHeights-self.r)] | |
| 365 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(self.nHeights/window), window) |
|
365 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(self.nHeights/window), window) | |
| 366 | buffer = numpy.sum(buffer,3) |
|
366 | buffer = numpy.sum(buffer,3) | |
| 367 |
|
367 | |||
| 368 | else: |
|
368 | else: | |
| 369 | buffer = dataOut.data[:,0:int(self.nHeights-self.r)] |
|
369 | buffer = dataOut.data[:,0:int(self.nHeights-self.r)] | |
| 370 | buffer = buffer.reshape(dataOut.nChannels,int(self.nHeights/window),int(window)) |
|
370 | buffer = buffer.reshape(dataOut.nChannels,int(self.nHeights/window),int(window)) | |
| 371 | buffer = numpy.sum(buffer,2) |
|
371 | buffer = numpy.sum(buffer,2) | |
| 372 |
|
372 | |||
| 373 | dataOut.data = buffer |
|
373 | dataOut.data = buffer | |
| 374 | dataOut.heightList = self.h0 + numpy.arange( self.newheights )*self.newdelta |
|
374 | dataOut.heightList = self.h0 + numpy.arange( self.newheights )*self.newdelta | |
| 375 | dataOut.windowOfFilter = window |
|
375 | dataOut.windowOfFilter = window | |
| 376 |
|
376 | |||
| 377 | #update Processing Header: |
|
377 | #update Processing Header: | |
| 378 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
378 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 379 | dataOut.processingHeaderObj.nWindows = window |
|
379 | dataOut.processingHeaderObj.nWindows = window | |
| 380 |
|
380 | |||
| 381 | return dataOut |
|
381 | return dataOut | |
| 382 |
|
382 | |||
| 383 |
|
383 | |||
| 384 |
|
384 | |||
| 385 | class setH0(Operation): |
|
385 | class setH0(Operation): | |
| 386 |
|
386 | |||
| 387 | def run(self, dataOut, h0, deltaHeight = None): |
|
387 | def run(self, dataOut, h0, deltaHeight = None): | |
| 388 |
|
388 | |||
| 389 | if not deltaHeight: |
|
389 | if not deltaHeight: | |
| 390 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
390 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 391 |
|
391 | |||
| 392 | nHeights = dataOut.nHeights |
|
392 | nHeights = dataOut.nHeights | |
| 393 |
|
393 | |||
| 394 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
394 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight | |
| 395 |
|
395 | |||
| 396 | dataOut.heightList = newHeiRange |
|
396 | dataOut.heightList = newHeiRange | |
| 397 |
|
397 | |||
| 398 | #update Processing Header: |
|
398 | #update Processing Header: | |
| 399 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
399 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 400 |
|
400 | |||
| 401 | return dataOut |
|
401 | return dataOut | |
| 402 |
|
402 | |||
| 403 |
|
403 | |||
| 404 | class deFlip(Operation): |
|
404 | class deFlip(Operation): | |
| 405 |
|
405 | |||
| 406 | def run(self, dataOut, channelList = []): |
|
406 | def run(self, dataOut, channelList = []): | |
| 407 |
|
407 | |||
| 408 | data = dataOut.data.copy() |
|
408 | data = dataOut.data.copy() | |
| 409 |
|
409 | |||
| 410 | if dataOut.flagDataAsBlock: |
|
410 | if dataOut.flagDataAsBlock: | |
| 411 | flip = self.flip |
|
411 | flip = self.flip | |
| 412 | profileList = list(range(dataOut.nProfiles)) |
|
412 | profileList = list(range(dataOut.nProfiles)) | |
| 413 |
|
413 | |||
| 414 | if not channelList: |
|
414 | if not channelList: | |
| 415 | for thisProfile in profileList: |
|
415 | for thisProfile in profileList: | |
| 416 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
416 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip | |
| 417 | flip *= -1.0 |
|
417 | flip *= -1.0 | |
| 418 | else: |
|
418 | else: | |
| 419 | for thisChannel in channelList: |
|
419 | for thisChannel in channelList: | |
| 420 | if thisChannel not in dataOut.channelList: |
|
420 | if thisChannel not in dataOut.channelList: | |
| 421 | continue |
|
421 | continue | |
| 422 |
|
422 | |||
| 423 | for thisProfile in profileList: |
|
423 | for thisProfile in profileList: | |
| 424 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
424 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip | |
| 425 | flip *= -1.0 |
|
425 | flip *= -1.0 | |
| 426 |
|
426 | |||
| 427 | self.flip = flip |
|
427 | self.flip = flip | |
| 428 |
|
428 | |||
| 429 | else: |
|
429 | else: | |
| 430 | if not channelList: |
|
430 | if not channelList: | |
| 431 | data[:,:] = data[:,:]*self.flip |
|
431 | data[:,:] = data[:,:]*self.flip | |
| 432 | else: |
|
432 | else: | |
| 433 | for thisChannel in channelList: |
|
433 | for thisChannel in channelList: | |
| 434 | if thisChannel not in dataOut.channelList: |
|
434 | if thisChannel not in dataOut.channelList: | |
| 435 | continue |
|
435 | continue | |
| 436 |
|
436 | |||
| 437 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
437 | data[thisChannel,:] = data[thisChannel,:]*self.flip | |
| 438 |
|
438 | |||
| 439 | self.flip *= -1. |
|
439 | self.flip *= -1. | |
| 440 |
|
440 | |||
| 441 | dataOut.data = data |
|
441 | dataOut.data = data | |
| 442 |
|
442 | |||
| 443 | return dataOut |
|
443 | return dataOut | |
| 444 |
|
444 | |||
| 445 |
|
445 | |||
| 446 | class setAttribute(Operation): |
|
446 | class setAttribute(Operation): | |
| 447 | ''' |
|
447 | ''' | |
| 448 | Set an arbitrary attribute(s) to dataOut |
|
448 | Set an arbitrary attribute(s) to dataOut | |
| 449 | ''' |
|
449 | ''' | |
| 450 |
|
450 | |||
| 451 | def __init__(self): |
|
451 | def __init__(self): | |
| 452 |
|
452 | |||
| 453 | Operation.__init__(self) |
|
453 | Operation.__init__(self) | |
| 454 | self._ready = False |
|
454 | self._ready = False | |
| 455 |
|
455 | |||
| 456 | def run(self, dataOut, **kwargs): |
|
456 | def run(self, dataOut, **kwargs): | |
| 457 |
|
457 | |||
| 458 | for key, value in kwargs.items(): |
|
458 | for key, value in kwargs.items(): | |
| 459 | setattr(dataOut, key, value) |
|
459 | setattr(dataOut, key, value) | |
| 460 |
|
460 | |||
| 461 | return dataOut |
|
461 | return dataOut | |
| 462 |
|
462 | |||
| 463 |
|
463 | |||
| 464 | @MPDecorator |
|
464 | @MPDecorator | |
| 465 | class printAttribute(Operation): |
|
465 | class printAttribute(Operation): | |
| 466 | ''' |
|
466 | ''' | |
| 467 | Print an arbitrary attribute of dataOut |
|
467 | Print an arbitrary attribute of dataOut | |
| 468 | ''' |
|
468 | ''' | |
| 469 |
|
469 | |||
| 470 | def __init__(self): |
|
470 | def __init__(self): | |
| 471 |
|
471 | |||
| 472 | Operation.__init__(self) |
|
472 | Operation.__init__(self) | |
| 473 |
|
473 | |||
| 474 | def run(self, dataOut, attributes): |
|
474 | def run(self, dataOut, attributes): | |
| 475 |
|
475 | |||
| 476 | if isinstance(attributes, str): |
|
476 | if isinstance(attributes, str): | |
| 477 | attributes = [attributes] |
|
477 | attributes = [attributes] | |
| 478 | for attr in attributes: |
|
478 | for attr in attributes: | |
| 479 | if hasattr(dataOut, attr): |
|
479 | if hasattr(dataOut, attr): | |
| 480 | log.log(getattr(dataOut, attr), attr) |
|
480 | log.log(getattr(dataOut, attr), attr) | |
| 481 |
|
481 | |||
| 482 | class cleanHeightsInterf(Operation): |
|
482 | class cleanHeightsInterf(Operation): | |
| 483 | __slots__ =('heights_indx', 'repeats', 'step', 'factor', 'idate', 'idxs','config','wMask') |
|
483 | __slots__ =('heights_indx', 'repeats', 'step', 'factor', 'idate', 'idxs','config','wMask') | |
| 484 | def __init__(self): |
|
484 | def __init__(self): | |
| 485 | self.repeats = 0 |
|
485 | self.repeats = 0 | |
| 486 | self.factor=1 |
|
486 | self.factor=1 | |
| 487 | self.wMask = None |
|
487 | self.wMask = None | |
| 488 | self.config = False |
|
488 | self.config = False | |
| 489 | self.idxs = None |
|
489 | self.idxs = None | |
| 490 | self.heights_indx = None |
|
490 | self.heights_indx = None | |
| 491 |
|
491 | |||
| 492 | def run(self, dataOut, heightsList, repeats=0, step=0, factor=1, idate=None, startH=None, endH=None): |
|
492 | def run(self, dataOut, heightsList, repeats=0, step=0, factor=1, idate=None, startH=None, endH=None): | |
| 493 |
|
493 | |||
| 494 | #print(dataOut.data.shape) |
|
494 | #print(dataOut.data.shape) | |
| 495 |
|
495 | |||
| 496 | startTime = datetime.datetime.combine(idate,startH) |
|
496 | startTime = datetime.datetime.combine(idate,startH) | |
| 497 | endTime = datetime.datetime.combine(idate,endH) |
|
497 | endTime = datetime.datetime.combine(idate,endH) | |
| 498 | currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) |
|
498 | currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) | |
| 499 |
|
499 | |||
| 500 | if currentTime < startTime or currentTime > endTime: |
|
500 | if currentTime < startTime or currentTime > endTime: | |
| 501 | return dataOut |
|
501 | return dataOut | |
| 502 | if not self.config: |
|
502 | if not self.config: | |
| 503 |
|
503 | |||
| 504 | #print(wMask) |
|
504 | #print(wMask) | |
| 505 | heights = [float(hei) for hei in heightsList] |
|
505 | heights = [float(hei) for hei in heightsList] | |
| 506 | for r in range(repeats): |
|
506 | for r in range(repeats): | |
| 507 | heights += [ (h+(step*(r+1))) for h in heights] |
|
507 | heights += [ (h+(step*(r+1))) for h in heights] | |
| 508 | #print(heights) |
|
508 | #print(heights) | |
| 509 | heiList = dataOut.heightList |
|
509 | heiList = dataOut.heightList | |
| 510 | self.heights_indx = [getHei_index(h,h,heiList)[0] for h in heights] |
|
510 | self.heights_indx = [getHei_index(h,h,heiList)[0] for h in heights] | |
| 511 |
|
511 | |||
| 512 | self.wMask = numpy.asarray(factor) |
|
512 | self.wMask = numpy.asarray(factor) | |
| 513 | self.wMask = numpy.tile(self.wMask,(repeats+2)) |
|
513 | self.wMask = numpy.tile(self.wMask,(repeats+2)) | |
| 514 | self.config = True |
|
514 | self.config = True | |
| 515 |
|
515 | |||
| 516 | """ |
|
516 | """ | |
| 517 | getNoisebyHildebrand(self, channel=None, ymin_index=None, ymax_index=None) |
|
517 | getNoisebyHildebrand(self, channel=None, ymin_index=None, ymax_index=None) | |
| 518 | """ |
|
518 | """ | |
| 519 | #print(self.noise =10*numpy.log10(dataOut.getNoisebyHildebrand(ymin_index=self.min_ref, ymax_index=self.max_ref))) |
|
519 | #print(self.noise =10*numpy.log10(dataOut.getNoisebyHildebrand(ymin_index=self.min_ref, ymax_index=self.max_ref))) | |
| 520 |
|
520 | |||
| 521 |
|
521 | |||
| 522 | for ch in range(dataOut.data.shape[0]): |
|
522 | for ch in range(dataOut.data.shape[0]): | |
| 523 | i = 0 |
|
523 | i = 0 | |
| 524 |
|
524 | |||
| 525 |
|
525 | |||
| 526 | for hei in self.heights_indx: |
|
526 | for hei in self.heights_indx: | |
| 527 | h = hei - 1 |
|
527 | h = hei - 1 | |
| 528 |
|
528 | |||
| 529 |
|
529 | |||
| 530 | if dataOut.data.ndim < 3: |
|
530 | if dataOut.data.ndim < 3: | |
| 531 | module = numpy.absolute(dataOut.data[ch,h]) |
|
531 | module = numpy.absolute(dataOut.data[ch,h]) | |
| 532 | prev_h1 = numpy.absolute(dataOut.data[ch,h-1]) |
|
532 | prev_h1 = numpy.absolute(dataOut.data[ch,h-1]) | |
| 533 | dataOut.data[ch,h] = (dataOut.data[ch,h])/module * prev_h1 |
|
533 | dataOut.data[ch,h] = (dataOut.data[ch,h])/module * prev_h1 | |
| 534 |
|
534 | |||
| 535 | #dataOut.data[ch,hei-1] = (dataOut.data[ch,hei-1])*self.wMask[i] |
|
535 | #dataOut.data[ch,hei-1] = (dataOut.data[ch,hei-1])*self.wMask[i] | |
| 536 | else: |
|
536 | else: | |
| 537 | module = numpy.absolute(dataOut.data[ch,:,h]) |
|
537 | module = numpy.absolute(dataOut.data[ch,:,h]) | |
| 538 | prev_h1 = numpy.absolute(dataOut.data[ch,:,h-1]) |
|
538 | prev_h1 = numpy.absolute(dataOut.data[ch,:,h-1]) | |
| 539 | dataOut.data[ch,:,h] = (dataOut.data[ch,:,h])/module * prev_h1 |
|
539 | dataOut.data[ch,:,h] = (dataOut.data[ch,:,h])/module * prev_h1 | |
| 540 | #dataOut.data[ch,:,hei-1] = (dataOut.data[ch,:,hei-1])*self.wMask[i] |
|
540 | #dataOut.data[ch,:,hei-1] = (dataOut.data[ch,:,hei-1])*self.wMask[i] | |
| 541 | #print("done") |
|
541 | #print("done") | |
| 542 | i += 1 |
|
542 | i += 1 | |
| 543 |
|
543 | |||
| 544 |
|
544 | |||
| 545 | return dataOut |
|
545 | return dataOut | |
| 546 |
|
546 | |||
| 547 |
|
547 | |||
| 548 |
|
548 | |||
| 549 | class interpolateHeights(Operation): |
|
549 | class interpolateHeights(Operation): | |
| 550 |
|
550 | |||
| 551 | def run(self, dataOut, topLim, botLim): |
|
551 | def run(self, dataOut, topLim, botLim): | |
| 552 | #69 al 72 para julia |
|
552 | #69 al 72 para julia | |
| 553 | #82-84 para meteoros |
|
553 | #82-84 para meteoros | |
| 554 | if len(numpy.shape(dataOut.data))==2: |
|
554 | if len(numpy.shape(dataOut.data))==2: | |
| 555 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 |
|
555 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 | |
| 556 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
556 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) | |
| 557 | #dataOut.data[:,botLim:limSup+1] = sampInterp |
|
557 | #dataOut.data[:,botLim:limSup+1] = sampInterp | |
| 558 | dataOut.data[:,botLim:topLim+1] = sampInterp |
|
558 | dataOut.data[:,botLim:topLim+1] = sampInterp | |
| 559 | else: |
|
559 | else: | |
| 560 | nHeights = dataOut.data.shape[2] |
|
560 | nHeights = dataOut.data.shape[2] | |
| 561 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
561 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) | |
| 562 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] |
|
562 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] | |
| 563 | f = interpolate.interp1d(x, y, axis = 2) |
|
563 | f = interpolate.interp1d(x, y, axis = 2) | |
| 564 | xnew = numpy.arange(botLim,topLim+1) |
|
564 | xnew = numpy.arange(botLim,topLim+1) | |
| 565 | ynew = f(xnew) |
|
565 | ynew = f(xnew) | |
| 566 | dataOut.data[:,:,botLim:topLim+1] = ynew |
|
566 | dataOut.data[:,:,botLim:topLim+1] = ynew | |
| 567 |
|
567 | |||
| 568 | return dataOut |
|
568 | return dataOut | |
| 569 |
|
569 | |||
| 570 |
|
570 | |||
| 571 | class CohInt(Operation): |
|
571 | class CohInt(Operation): | |
| 572 |
|
572 | |||
| 573 | isConfig = False |
|
573 | isConfig = False | |
| 574 | __profIndex = 0 |
|
574 | __profIndex = 0 | |
| 575 | __byTime = False |
|
575 | __byTime = False | |
| 576 | __initime = None |
|
576 | __initime = None | |
| 577 | __lastdatatime = None |
|
577 | __lastdatatime = None | |
| 578 | __integrationtime = None |
|
578 | __integrationtime = None | |
| 579 | __buffer = None |
|
579 | __buffer = None | |
| 580 | __bufferStride = [] |
|
580 | __bufferStride = [] | |
| 581 | __dataReady = False |
|
581 | __dataReady = False | |
| 582 | __profIndexStride = 0 |
|
582 | __profIndexStride = 0 | |
| 583 | __dataToPutStride = False |
|
583 | __dataToPutStride = False | |
| 584 | n = None |
|
584 | n = None | |
| 585 |
|
585 | |||
| 586 | def __init__(self, **kwargs): |
|
586 | def __init__(self, **kwargs): | |
| 587 |
|
587 | |||
| 588 | Operation.__init__(self, **kwargs) |
|
588 | Operation.__init__(self, **kwargs) | |
| 589 |
|
589 | |||
| 590 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
590 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): | |
| 591 | """ |
|
591 | """ | |
| 592 | Set the parameters of the integration class. |
|
592 | Set the parameters of the integration class. | |
| 593 |
|
593 | |||
| 594 | Inputs: |
|
594 | Inputs: | |
| 595 |
|
595 | |||
| 596 | n : Number of coherent integrations |
|
596 | n : Number of coherent integrations | |
| 597 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
597 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 598 | overlapping : |
|
598 | overlapping : | |
| 599 | """ |
|
599 | """ | |
| 600 |
|
600 | |||
| 601 | self.__initime = None |
|
601 | self.__initime = None | |
| 602 | self.__lastdatatime = 0 |
|
602 | self.__lastdatatime = 0 | |
| 603 | self.__buffer = None |
|
603 | self.__buffer = None | |
| 604 | self.__dataReady = False |
|
604 | self.__dataReady = False | |
| 605 | self.byblock = byblock |
|
605 | self.byblock = byblock | |
| 606 | self.stride = stride |
|
606 | self.stride = stride | |
| 607 |
|
607 | |||
| 608 | if n == None and timeInterval == None: |
|
608 | if n == None and timeInterval == None: | |
| 609 | raise ValueError("n or timeInterval should be specified ...") |
|
609 | raise ValueError("n or timeInterval should be specified ...") | |
| 610 |
|
610 | |||
| 611 | if n != None: |
|
611 | if n != None: | |
| 612 | self.n = n |
|
612 | self.n = n | |
| 613 | self.__byTime = False |
|
613 | self.__byTime = False | |
| 614 | else: |
|
614 | else: | |
| 615 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
615 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
| 616 | self.n = 9999 |
|
616 | self.n = 9999 | |
| 617 | self.__byTime = True |
|
617 | self.__byTime = True | |
| 618 |
|
618 | |||
| 619 | if overlapping: |
|
619 | if overlapping: | |
| 620 | self.__withOverlapping = True |
|
620 | self.__withOverlapping = True | |
| 621 | self.__buffer = None |
|
621 | self.__buffer = None | |
| 622 | else: |
|
622 | else: | |
| 623 | self.__withOverlapping = False |
|
623 | self.__withOverlapping = False | |
| 624 | self.__buffer = 0 |
|
624 | self.__buffer = 0 | |
| 625 |
|
625 | |||
| 626 | self.__profIndex = 0 |
|
626 | self.__profIndex = 0 | |
| 627 |
|
627 | |||
| 628 | def putData(self, data): |
|
628 | def putData(self, data): | |
| 629 |
|
629 | |||
| 630 | """ |
|
630 | """ | |
| 631 | Add a profile to the __buffer and increase in one the __profileIndex |
|
631 | Add a profile to the __buffer and increase in one the __profileIndex | |
| 632 |
|
632 | |||
| 633 | """ |
|
633 | """ | |
| 634 |
|
634 | |||
| 635 | if not self.__withOverlapping: |
|
635 | if not self.__withOverlapping: | |
| 636 | self.__buffer += data.copy() |
|
636 | self.__buffer += data.copy() | |
| 637 | self.__profIndex += 1 |
|
637 | self.__profIndex += 1 | |
| 638 | return |
|
638 | return | |
| 639 |
|
639 | |||
| 640 | #Overlapping data |
|
640 | #Overlapping data | |
| 641 | nChannels, nHeis = data.shape |
|
641 | nChannels, nHeis = data.shape | |
| 642 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
642 | data = numpy.reshape(data, (1, nChannels, nHeis)) | |
| 643 |
|
643 | |||
| 644 | #If the buffer is empty then it takes the data value |
|
644 | #If the buffer is empty then it takes the data value | |
| 645 | if self.__buffer is None: |
|
645 | if self.__buffer is None: | |
| 646 | self.__buffer = data |
|
646 | self.__buffer = data | |
| 647 | self.__profIndex += 1 |
|
647 | self.__profIndex += 1 | |
| 648 | return |
|
648 | return | |
| 649 |
|
649 | |||
| 650 | #If the buffer length is lower than n then stakcing the data value |
|
650 | #If the buffer length is lower than n then stakcing the data value | |
| 651 | if self.__profIndex < self.n: |
|
651 | if self.__profIndex < self.n: | |
| 652 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
652 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
| 653 | self.__profIndex += 1 |
|
653 | self.__profIndex += 1 | |
| 654 | return |
|
654 | return | |
| 655 |
|
655 | |||
| 656 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
656 | #If the buffer length is equal to n then replacing the last buffer value with the data value | |
| 657 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
657 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
| 658 | self.__buffer[self.n-1] = data |
|
658 | self.__buffer[self.n-1] = data | |
| 659 | self.__profIndex = self.n |
|
659 | self.__profIndex = self.n | |
| 660 | return |
|
660 | return | |
| 661 |
|
661 | |||
| 662 |
|
662 | |||
| 663 | def pushData(self): |
|
663 | def pushData(self): | |
| 664 | """ |
|
664 | """ | |
| 665 | Return the sum of the last profiles and the profiles used in the sum. |
|
665 | Return the sum of the last profiles and the profiles used in the sum. | |
| 666 |
|
666 | |||
| 667 | Affected: |
|
667 | Affected: | |
| 668 |
|
668 | |||
| 669 | self.__profileIndex |
|
669 | self.__profileIndex | |
| 670 |
|
670 | |||
| 671 | """ |
|
671 | """ | |
| 672 |
|
672 | |||
| 673 | if not self.__withOverlapping: |
|
673 | if not self.__withOverlapping: | |
| 674 | data = self.__buffer |
|
674 | data = self.__buffer | |
| 675 | n = self.__profIndex |
|
675 | n = self.__profIndex | |
| 676 |
|
676 | |||
| 677 | self.__buffer = 0 |
|
677 | self.__buffer = 0 | |
| 678 | self.__profIndex = 0 |
|
678 | self.__profIndex = 0 | |
| 679 |
|
679 | |||
| 680 | return data, n |
|
680 | return data, n | |
| 681 |
|
681 | |||
| 682 | #Integration with Overlapping |
|
682 | #Integration with Overlapping | |
| 683 | data = numpy.sum(self.__buffer, axis=0) |
|
683 | data = numpy.sum(self.__buffer, axis=0) | |
| 684 | # print data |
|
684 | # print data | |
| 685 | # raise |
|
685 | # raise | |
| 686 | n = self.__profIndex |
|
686 | n = self.__profIndex | |
| 687 |
|
687 | |||
| 688 | return data, n |
|
688 | return data, n | |
| 689 |
|
689 | |||
| 690 | def byProfiles(self, data): |
|
690 | def byProfiles(self, data): | |
| 691 |
|
691 | |||
| 692 | self.__dataReady = False |
|
692 | self.__dataReady = False | |
| 693 | avgdata = None |
|
693 | avgdata = None | |
| 694 | # n = None |
|
694 | # n = None | |
| 695 | # print data |
|
695 | # print data | |
| 696 | # raise |
|
696 | # raise | |
| 697 | self.putData(data) |
|
697 | self.putData(data) | |
| 698 |
|
698 | |||
| 699 | if self.__profIndex == self.n: |
|
699 | if self.__profIndex == self.n: | |
| 700 | avgdata, n = self.pushData() |
|
700 | avgdata, n = self.pushData() | |
| 701 | self.__dataReady = True |
|
701 | self.__dataReady = True | |
| 702 |
|
702 | |||
| 703 | return avgdata |
|
703 | return avgdata | |
| 704 |
|
704 | |||
| 705 | def byTime(self, data, datatime): |
|
705 | def byTime(self, data, datatime): | |
| 706 |
|
706 | |||
| 707 | self.__dataReady = False |
|
707 | self.__dataReady = False | |
| 708 | avgdata = None |
|
708 | avgdata = None | |
| 709 | n = None |
|
709 | n = None | |
| 710 |
|
710 | |||
| 711 | self.putData(data) |
|
711 | self.putData(data) | |
| 712 |
|
712 | |||
| 713 | if (datatime - self.__initime) >= self.__integrationtime: |
|
713 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 714 | avgdata, n = self.pushData() |
|
714 | avgdata, n = self.pushData() | |
| 715 | self.n = n |
|
715 | self.n = n | |
| 716 | self.__dataReady = True |
|
716 | self.__dataReady = True | |
| 717 |
|
717 | |||
| 718 | return avgdata |
|
718 | return avgdata | |
| 719 |
|
719 | |||
| 720 | def integrateByStride(self, data, datatime): |
|
720 | def integrateByStride(self, data, datatime): | |
| 721 | # print data |
|
721 | # print data | |
| 722 | if self.__profIndex == 0: |
|
722 | if self.__profIndex == 0: | |
| 723 | self.__buffer = [[data.copy(), datatime]] |
|
723 | self.__buffer = [[data.copy(), datatime]] | |
| 724 | else: |
|
724 | else: | |
| 725 | self.__buffer.append([data.copy(),datatime]) |
|
725 | self.__buffer.append([data.copy(),datatime]) | |
| 726 | self.__profIndex += 1 |
|
726 | self.__profIndex += 1 | |
| 727 | self.__dataReady = False |
|
727 | self.__dataReady = False | |
| 728 |
|
728 | |||
| 729 | if self.__profIndex == self.n * self.stride : |
|
729 | if self.__profIndex == self.n * self.stride : | |
| 730 | self.__dataToPutStride = True |
|
730 | self.__dataToPutStride = True | |
| 731 | self.__profIndexStride = 0 |
|
731 | self.__profIndexStride = 0 | |
| 732 | self.__profIndex = 0 |
|
732 | self.__profIndex = 0 | |
| 733 | self.__bufferStride = [] |
|
733 | self.__bufferStride = [] | |
| 734 | for i in range(self.stride): |
|
734 | for i in range(self.stride): | |
| 735 | current = self.__buffer[i::self.stride] |
|
735 | current = self.__buffer[i::self.stride] | |
| 736 | data = numpy.sum([t[0] for t in current], axis=0) |
|
736 | data = numpy.sum([t[0] for t in current], axis=0) | |
| 737 | avgdatatime = numpy.average([t[1] for t in current]) |
|
737 | avgdatatime = numpy.average([t[1] for t in current]) | |
| 738 | # print data |
|
738 | # print data | |
| 739 | self.__bufferStride.append((data, avgdatatime)) |
|
739 | self.__bufferStride.append((data, avgdatatime)) | |
| 740 |
|
740 | |||
| 741 | if self.__dataToPutStride: |
|
741 | if self.__dataToPutStride: | |
| 742 | self.__dataReady = True |
|
742 | self.__dataReady = True | |
| 743 | self.__profIndexStride += 1 |
|
743 | self.__profIndexStride += 1 | |
| 744 | if self.__profIndexStride == self.stride: |
|
744 | if self.__profIndexStride == self.stride: | |
| 745 | self.__dataToPutStride = False |
|
745 | self.__dataToPutStride = False | |
| 746 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
746 | # print self.__bufferStride[self.__profIndexStride - 1] | |
| 747 | # raise |
|
747 | # raise | |
| 748 | return self.__bufferStride[self.__profIndexStride - 1] |
|
748 | return self.__bufferStride[self.__profIndexStride - 1] | |
| 749 |
|
749 | |||
| 750 |
|
750 | |||
| 751 | return None, None |
|
751 | return None, None | |
| 752 |
|
752 | |||
| 753 | def integrate(self, data, datatime=None): |
|
753 | def integrate(self, data, datatime=None): | |
| 754 |
|
754 | |||
| 755 | if self.__initime == None: |
|
755 | if self.__initime == None: | |
| 756 | self.__initime = datatime |
|
756 | self.__initime = datatime | |
| 757 |
|
757 | |||
| 758 | if self.__byTime: |
|
758 | if self.__byTime: | |
| 759 | avgdata = self.byTime(data, datatime) |
|
759 | avgdata = self.byTime(data, datatime) | |
| 760 | else: |
|
760 | else: | |
| 761 | avgdata = self.byProfiles(data) |
|
761 | avgdata = self.byProfiles(data) | |
| 762 |
|
762 | |||
| 763 |
|
763 | |||
| 764 | self.__lastdatatime = datatime |
|
764 | self.__lastdatatime = datatime | |
| 765 |
|
765 | |||
| 766 | if avgdata is None: |
|
766 | if avgdata is None: | |
| 767 | return None, None |
|
767 | return None, None | |
| 768 |
|
768 | |||
| 769 | avgdatatime = self.__initime |
|
769 | avgdatatime = self.__initime | |
| 770 |
|
770 | |||
| 771 | deltatime = datatime - self.__lastdatatime |
|
771 | deltatime = datatime - self.__lastdatatime | |
| 772 |
|
772 | |||
| 773 | if not self.__withOverlapping: |
|
773 | if not self.__withOverlapping: | |
| 774 | self.__initime = datatime |
|
774 | self.__initime = datatime | |
| 775 | else: |
|
775 | else: | |
| 776 | self.__initime += deltatime |
|
776 | self.__initime += deltatime | |
| 777 |
|
777 | |||
| 778 | return avgdata, avgdatatime |
|
778 | return avgdata, avgdatatime | |
| 779 |
|
779 | |||
| 780 | def integrateByBlock(self, dataOut): |
|
780 | def integrateByBlock(self, dataOut): | |
| 781 |
|
781 | |||
| 782 | times = int(dataOut.data.shape[1]/self.n) |
|
782 | times = int(dataOut.data.shape[1]/self.n) | |
| 783 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
783 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) | |
| 784 |
|
784 | |||
| 785 | id_min = 0 |
|
785 | id_min = 0 | |
| 786 | id_max = self.n |
|
786 | id_max = self.n | |
| 787 |
|
787 | |||
| 788 | for i in range(times): |
|
788 | for i in range(times): | |
| 789 | junk = dataOut.data[:,id_min:id_max,:] |
|
789 | junk = dataOut.data[:,id_min:id_max,:] | |
| 790 | avgdata[:,i,:] = junk.sum(axis=1) |
|
790 | avgdata[:,i,:] = junk.sum(axis=1) | |
| 791 | id_min += self.n |
|
791 | id_min += self.n | |
| 792 | id_max += self.n |
|
792 | id_max += self.n | |
| 793 |
|
793 | |||
| 794 | timeInterval = dataOut.ippSeconds*self.n |
|
794 | timeInterval = dataOut.ippSeconds*self.n | |
| 795 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
795 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime | |
| 796 | self.__dataReady = True |
|
796 | self.__dataReady = True | |
| 797 | return avgdata, avgdatatime |
|
797 | return avgdata, avgdatatime | |
| 798 |
|
798 | |||
| 799 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
799 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): | |
| 800 |
|
800 | |||
| 801 | if not self.isConfig: |
|
801 | if not self.isConfig: | |
| 802 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
802 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) | |
| 803 | self.isConfig = True |
|
803 | self.isConfig = True | |
| 804 |
|
804 | |||
| 805 | if dataOut.flagDataAsBlock: |
|
805 | if dataOut.flagDataAsBlock: | |
| 806 | """ |
|
806 | """ | |
| 807 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
807 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 808 | """ |
|
808 | """ | |
| 809 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
809 | avgdata, avgdatatime = self.integrateByBlock(dataOut) | |
| 810 | dataOut.nProfiles /= self.n |
|
810 | dataOut.nProfiles /= self.n | |
| 811 | else: |
|
811 | else: | |
| 812 | if stride is None: |
|
812 | if stride is None: | |
| 813 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
813 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |
| 814 | else: |
|
814 | else: | |
| 815 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
815 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) | |
| 816 |
|
816 | |||
| 817 |
|
817 | |||
| 818 | # dataOut.timeInterval *= n |
|
818 | # dataOut.timeInterval *= n | |
| 819 | dataOut.flagNoData = True |
|
819 | dataOut.flagNoData = True | |
| 820 |
|
820 | |||
| 821 | if self.__dataReady: |
|
821 | if self.__dataReady: | |
| 822 | dataOut.data = avgdata |
|
822 | dataOut.data = avgdata | |
| 823 | if not dataOut.flagCohInt: |
|
823 | if not dataOut.flagCohInt: | |
| 824 | dataOut.nCohInt *= self.n |
|
824 | dataOut.nCohInt *= self.n | |
| 825 | dataOut.flagCohInt = True |
|
825 | dataOut.flagCohInt = True | |
| 826 | dataOut.utctime = avgdatatime |
|
826 | dataOut.utctime = avgdatatime | |
| 827 | # print avgdata, avgdatatime |
|
827 | # print avgdata, avgdatatime | |
| 828 | # raise |
|
828 | # raise | |
| 829 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
829 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
| 830 | dataOut.flagNoData = False |
|
830 | dataOut.flagNoData = False | |
| 831 |
|
831 | |||
| 832 | #update Processing Header: |
|
832 | #update Processing Header: | |
| 833 | dataOut.processingHeaderObj.nCohInt = dataOut.nCohInt |
|
833 | dataOut.processingHeaderObj.nCohInt = dataOut.nCohInt | |
| 834 |
|
834 | |||
| 835 |
|
835 | |||
| 836 | return dataOut |
|
836 | return dataOut | |
| 837 |
|
837 | |||
| 838 | class Decoder(Operation): |
|
838 | class Decoder(Operation): | |
| 839 |
|
839 | |||
| 840 | isConfig = False |
|
840 | isConfig = False | |
| 841 | __profIndex = 0 |
|
841 | __profIndex = 0 | |
| 842 |
|
842 | |||
| 843 | code = None |
|
843 | code = None | |
| 844 |
|
844 | |||
| 845 | nCode = None |
|
845 | nCode = None | |
| 846 | nBaud = None |
|
846 | nBaud = None | |
| 847 |
|
847 | |||
| 848 | def __init__(self, **kwargs): |
|
848 | def __init__(self, **kwargs): | |
| 849 |
|
849 | |||
| 850 | Operation.__init__(self, **kwargs) |
|
850 | Operation.__init__(self, **kwargs) | |
| 851 |
|
851 | |||
| 852 | self.times = None |
|
852 | self.times = None | |
| 853 | self.osamp = None |
|
853 | self.osamp = None | |
| 854 | # self.__setValues = False |
|
854 | # self.__setValues = False | |
| 855 | self.isConfig = False |
|
855 | self.isConfig = False | |
| 856 | self.setupReq = False |
|
856 | self.setupReq = False | |
| 857 | def setup(self, code, osamp, dataOut): |
|
857 | def setup(self, code, osamp, dataOut): | |
| 858 |
|
858 | |||
| 859 | self.__profIndex = 0 |
|
859 | self.__profIndex = 0 | |
| 860 |
|
860 | |||
| 861 | self.code = code |
|
861 | self.code = code | |
| 862 |
|
862 | |||
| 863 | self.nCode = len(code) |
|
863 | self.nCode = len(code) | |
| 864 | self.nBaud = len(code[0]) |
|
864 | self.nBaud = len(code[0]) | |
| 865 | if (osamp != None) and (osamp >1): |
|
865 | if (osamp != None) and (osamp >1): | |
| 866 | self.osamp = osamp |
|
866 | self.osamp = osamp | |
| 867 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
867 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) | |
| 868 | self.nBaud = self.nBaud*self.osamp |
|
868 | self.nBaud = self.nBaud*self.osamp | |
| 869 |
|
869 | |||
| 870 | self.__nChannels = dataOut.nChannels |
|
870 | self.__nChannels = dataOut.nChannels | |
| 871 | self.__nProfiles = dataOut.nProfiles |
|
871 | self.__nProfiles = dataOut.nProfiles | |
| 872 | self.__nHeis = dataOut.nHeights |
|
872 | self.__nHeis = dataOut.nHeights | |
| 873 |
|
873 | |||
| 874 | if self.__nHeis < self.nBaud: |
|
874 | if self.__nHeis < self.nBaud: | |
| 875 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) |
|
875 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) | |
| 876 |
|
876 | |||
| 877 | #Frequency |
|
877 | #Frequency | |
| 878 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
878 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
| 879 |
|
879 | |||
| 880 | __codeBuffer[:,0:self.nBaud] = self.code |
|
880 | __codeBuffer[:,0:self.nBaud] = self.code | |
| 881 |
|
881 | |||
| 882 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
882 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
| 883 |
|
883 | |||
| 884 | if dataOut.flagDataAsBlock: |
|
884 | if dataOut.flagDataAsBlock: | |
| 885 |
|
885 | |||
| 886 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
886 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 887 |
|
887 | |||
| 888 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
888 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) | |
| 889 |
|
889 | |||
| 890 | else: |
|
890 | else: | |
| 891 |
|
891 | |||
| 892 | #Time |
|
892 | #Time | |
| 893 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
893 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 894 |
|
894 | |||
| 895 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
895 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |
| 896 |
|
896 | |||
| 897 | def __convolutionInFreq(self, data): |
|
897 | def __convolutionInFreq(self, data): | |
| 898 |
|
898 | |||
| 899 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
899 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 900 |
|
900 | |||
| 901 | fft_data = numpy.fft.fft(data, axis=1) |
|
901 | fft_data = numpy.fft.fft(data, axis=1) | |
| 902 |
|
902 | |||
| 903 | conv = fft_data*fft_code |
|
903 | conv = fft_data*fft_code | |
| 904 |
|
904 | |||
| 905 | data = numpy.fft.ifft(conv,axis=1) |
|
905 | data = numpy.fft.ifft(conv,axis=1) | |
| 906 |
|
906 | |||
| 907 | return data |
|
907 | return data | |
| 908 |
|
908 | |||
| 909 | def __convolutionInFreqOpt(self, data): |
|
909 | def __convolutionInFreqOpt(self, data): | |
| 910 |
|
910 | |||
| 911 | raise NotImplementedError |
|
911 | raise NotImplementedError | |
| 912 |
|
912 | |||
| 913 | def __convolutionInTime(self, data): |
|
913 | def __convolutionInTime(self, data): | |
| 914 |
|
914 | |||
| 915 | code = self.code[self.__profIndex] |
|
915 | code = self.code[self.__profIndex] | |
| 916 | for i in range(self.__nChannels): |
|
916 | for i in range(self.__nChannels): | |
| 917 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
917 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] | |
| 918 |
|
918 | |||
| 919 | return self.datadecTime |
|
919 | return self.datadecTime | |
| 920 |
|
920 | |||
| 921 | def __convolutionByBlockInTime(self, data): |
|
921 | def __convolutionByBlockInTime(self, data): | |
| 922 |
|
922 | |||
| 923 | repetitions = int(self.__nProfiles / self.nCode) |
|
923 | repetitions = int(self.__nProfiles / self.nCode) | |
| 924 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
924 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) | |
| 925 | junk = junk.flatten() |
|
925 | junk = junk.flatten() | |
| 926 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
926 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) | |
| 927 | profilesList = range(self.__nProfiles) |
|
927 | profilesList = range(self.__nProfiles) | |
| 928 |
|
928 | |||
| 929 | for i in range(self.__nChannels): |
|
929 | for i in range(self.__nChannels): | |
| 930 | for j in profilesList: |
|
930 | for j in profilesList: | |
| 931 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
931 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] | |
| 932 | return self.datadecTime |
|
932 | return self.datadecTime | |
| 933 |
|
933 | |||
| 934 | def __convolutionByBlockInFreq(self, data): |
|
934 | def __convolutionByBlockInFreq(self, data): | |
| 935 |
|
935 | |||
| 936 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") |
|
936 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") | |
| 937 |
|
937 | |||
| 938 |
|
938 | |||
| 939 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
939 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 940 |
|
940 | |||
| 941 | fft_data = numpy.fft.fft(data, axis=2) |
|
941 | fft_data = numpy.fft.fft(data, axis=2) | |
| 942 |
|
942 | |||
| 943 | conv = fft_data*fft_code |
|
943 | conv = fft_data*fft_code | |
| 944 |
|
944 | |||
| 945 | data = numpy.fft.ifft(conv,axis=2) |
|
945 | data = numpy.fft.ifft(conv,axis=2) | |
| 946 |
|
946 | |||
| 947 | return data |
|
947 | return data | |
| 948 |
|
948 | |||
| 949 |
|
949 | |||
| 950 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
950 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): | |
| 951 |
|
951 | |||
| 952 | if dataOut.flagDecodeData: |
|
952 | if dataOut.flagDecodeData: | |
| 953 | print("This data is already decoded, recoding again ...") |
|
953 | print("This data is already decoded, recoding again ...") | |
| 954 |
|
954 | |||
| 955 | if not self.isConfig: |
|
955 | if not self.isConfig: | |
| 956 |
|
956 | |||
| 957 | if code is None: |
|
957 | if code is None: | |
| 958 | if dataOut.code is None: |
|
958 | if dataOut.code is None: | |
| 959 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) |
|
959 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) | |
| 960 |
|
960 | |||
| 961 | code = dataOut.code |
|
961 | code = dataOut.code | |
| 962 | else: |
|
962 | else: | |
| 963 | code = numpy.array(code).reshape(nCode,nBaud) |
|
963 | code = numpy.array(code).reshape(nCode,nBaud) | |
| 964 | self.setup(code, osamp, dataOut) |
|
964 | self.setup(code, osamp, dataOut) | |
| 965 |
|
965 | |||
| 966 | self.isConfig = True |
|
966 | self.isConfig = True | |
| 967 |
|
967 | |||
| 968 | if mode == 3: |
|
968 | if mode == 3: | |
| 969 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
969 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) | |
| 970 |
|
970 | |||
| 971 | if times != None: |
|
971 | if times != None: | |
| 972 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
972 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") | |
| 973 |
|
973 | |||
| 974 | if self.code is None: |
|
974 | if self.code is None: | |
| 975 | print("Fail decoding: Code is not defined.") |
|
975 | print("Fail decoding: Code is not defined.") | |
| 976 | return |
|
976 | return | |
| 977 |
|
977 | |||
| 978 | self.__nProfiles = dataOut.nProfiles |
|
978 | self.__nProfiles = dataOut.nProfiles | |
| 979 | datadec = None |
|
979 | datadec = None | |
| 980 |
|
980 | |||
| 981 | if mode == 3: |
|
981 | if mode == 3: | |
| 982 | mode = 0 |
|
982 | mode = 0 | |
| 983 |
|
983 | |||
| 984 | if dataOut.flagDataAsBlock: |
|
984 | if dataOut.flagDataAsBlock: | |
| 985 | """ |
|
985 | """ | |
| 986 | Decoding when data have been read as block, |
|
986 | Decoding when data have been read as block, | |
| 987 | """ |
|
987 | """ | |
| 988 |
|
988 | |||
| 989 | if mode == 0: |
|
989 | if mode == 0: | |
| 990 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
990 | datadec = self.__convolutionByBlockInTime(dataOut.data) | |
| 991 | if mode == 1: |
|
991 | if mode == 1: | |
| 992 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
992 | datadec = self.__convolutionByBlockInFreq(dataOut.data) | |
| 993 | else: |
|
993 | else: | |
| 994 | """ |
|
994 | """ | |
| 995 | Decoding when data have been read profile by profile |
|
995 | Decoding when data have been read profile by profile | |
| 996 | """ |
|
996 | """ | |
| 997 | if mode == 0: |
|
997 | if mode == 0: | |
| 998 | datadec = self.__convolutionInTime(dataOut.data) |
|
998 | datadec = self.__convolutionInTime(dataOut.data) | |
| 999 |
|
999 | |||
| 1000 | if mode == 1: |
|
1000 | if mode == 1: | |
| 1001 | datadec = self.__convolutionInFreq(dataOut.data) |
|
1001 | datadec = self.__convolutionInFreq(dataOut.data) | |
| 1002 |
|
1002 | |||
| 1003 | if mode == 2: |
|
1003 | if mode == 2: | |
| 1004 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
1004 | datadec = self.__convolutionInFreqOpt(dataOut.data) | |
| 1005 |
|
1005 | |||
| 1006 | if datadec is None: |
|
1006 | if datadec is None: | |
| 1007 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) |
|
1007 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) | |
| 1008 |
|
1008 | |||
| 1009 | dataOut.code = self.code |
|
1009 | dataOut.code = self.code | |
| 1010 | dataOut.nCode = self.nCode |
|
1010 | dataOut.nCode = self.nCode | |
| 1011 | dataOut.nBaud = self.nBaud |
|
1011 | dataOut.nBaud = self.nBaud | |
| 1012 |
|
1012 | |||
| 1013 | dataOut.data = datadec |
|
1013 | dataOut.data = datadec | |
| 1014 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
1014 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] | |
| 1015 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
1015 | dataOut.flagDecodeData = True #asumo q la data esta decodificada | |
| 1016 |
|
1016 | |||
| 1017 |
|
1017 | |||
| 1018 | #update Processing Header: |
|
1018 | #update Processing Header: | |
| 1019 | dataOut.radarControllerHeaderObj.code = self.code |
|
1019 | dataOut.radarControllerHeaderObj.code = self.code | |
| 1020 | dataOut.radarControllerHeaderObj.nCode = self.nCode |
|
1020 | dataOut.radarControllerHeaderObj.nCode = self.nCode | |
| 1021 | dataOut.radarControllerHeaderObj.nBaud = self.nBaud |
|
1021 | dataOut.radarControllerHeaderObj.nBaud = self.nBaud | |
| 1022 | dataOut.radarControllerHeaderObj.nOsamp = osamp |
|
1022 | dataOut.radarControllerHeaderObj.nOsamp = osamp | |
| 1023 | #update Processing Header: |
|
1023 | #update Processing Header: | |
| 1024 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
1024 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 1025 | dataOut.processingHeaderObj.heightResolution = dataOut.heightList[1]-dataOut.heightList[0] |
|
1025 | dataOut.processingHeaderObj.heightResolution = dataOut.heightList[1]-dataOut.heightList[0] | |
| 1026 |
|
1026 | |||
| 1027 | if self.__profIndex == self.nCode-1: |
|
1027 | if self.__profIndex == self.nCode-1: | |
| 1028 | self.__profIndex = 0 |
|
1028 | self.__profIndex = 0 | |
| 1029 | return dataOut |
|
1029 | return dataOut | |
| 1030 |
|
1030 | |||
| 1031 | self.__profIndex += 1 |
|
1031 | self.__profIndex += 1 | |
| 1032 |
|
1032 | |||
| 1033 | return dataOut |
|
1033 | return dataOut | |
| 1034 |
|
1034 | |||
| 1035 | class ProfileConcat(Operation): |
|
1035 | class ProfileConcat(Operation): | |
| 1036 |
|
1036 | |||
| 1037 | isConfig = False |
|
1037 | isConfig = False | |
| 1038 | buffer = None |
|
1038 | buffer = None | |
| 1039 |
|
1039 | |||
| 1040 | def __init__(self, **kwargs): |
|
1040 | def __init__(self, **kwargs): | |
| 1041 |
|
1041 | |||
| 1042 | Operation.__init__(self, **kwargs) |
|
1042 | Operation.__init__(self, **kwargs) | |
| 1043 | self.profileIndex = 0 |
|
1043 | self.profileIndex = 0 | |
| 1044 |
|
1044 | |||
| 1045 | def reset(self): |
|
1045 | def reset(self): | |
| 1046 | self.buffer = numpy.zeros_like(self.buffer) |
|
1046 | self.buffer = numpy.zeros_like(self.buffer) | |
| 1047 | self.start_index = 0 |
|
1047 | self.start_index = 0 | |
| 1048 | self.times = 1 |
|
1048 | self.times = 1 | |
| 1049 |
|
1049 | |||
| 1050 | def setup(self, data, m, n=1): |
|
1050 | def setup(self, data, m, n=1): | |
| 1051 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
1051 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |
| 1052 | self.nHeights = data.shape[1]#.nHeights |
|
1052 | self.nHeights = data.shape[1]#.nHeights | |
| 1053 | self.start_index = 0 |
|
1053 | self.start_index = 0 | |
| 1054 | self.times = 1 |
|
1054 | self.times = 1 | |
| 1055 |
|
1055 | |||
| 1056 | def concat(self, data): |
|
1056 | def concat(self, data): | |
| 1057 |
|
1057 | |||
| 1058 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
1058 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() | |
| 1059 | self.start_index = self.start_index + self.nHeights |
|
1059 | self.start_index = self.start_index + self.nHeights | |
| 1060 |
|
1060 | |||
| 1061 | def run(self, dataOut, m): |
|
1061 | def run(self, dataOut, m): | |
| 1062 | dataOut.flagNoData = True |
|
1062 | dataOut.flagNoData = True | |
| 1063 |
|
1063 | |||
| 1064 | if not self.isConfig: |
|
1064 | if not self.isConfig: | |
| 1065 | self.setup(dataOut.data, m, 1) |
|
1065 | self.setup(dataOut.data, m, 1) | |
| 1066 | self.isConfig = True |
|
1066 | self.isConfig = True | |
| 1067 |
|
1067 | |||
| 1068 | if dataOut.flagDataAsBlock: |
|
1068 | if dataOut.flagDataAsBlock: | |
| 1069 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") |
|
1069 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") | |
| 1070 |
|
1070 | |||
| 1071 | else: |
|
1071 | else: | |
| 1072 | self.concat(dataOut.data) |
|
1072 | self.concat(dataOut.data) | |
| 1073 | self.times += 1 |
|
1073 | self.times += 1 | |
| 1074 | if self.times > m: |
|
1074 | if self.times > m: | |
| 1075 | dataOut.data = self.buffer |
|
1075 | dataOut.data = self.buffer | |
| 1076 | self.reset() |
|
1076 | self.reset() | |
| 1077 | dataOut.flagNoData = False |
|
1077 | dataOut.flagNoData = False | |
| 1078 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
1078 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |
| 1079 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1079 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1080 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
1080 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m | |
| 1081 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
1081 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |
| 1082 | dataOut.ippSeconds *= m |
|
1082 | dataOut.ippSeconds *= m | |
| 1083 |
|
1083 | |||
| 1084 | #update Processing Header: |
|
1084 | #update Processing Header: | |
| 1085 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
1085 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 1086 | dataOut.processingHeaderObj.ipp = dataOut.ippSeconds |
|
1086 | dataOut.processingHeaderObj.ipp = dataOut.ippSeconds | |
| 1087 |
|
1087 | |||
| 1088 | return dataOut |
|
1088 | return dataOut | |
| 1089 |
|
1089 | |||
| 1090 | class ProfileSelector(Operation): |
|
1090 | class ProfileSelector(Operation): | |
| 1091 |
|
1091 | |||
| 1092 | profileIndex = None |
|
1092 | profileIndex = None | |
| 1093 | # Tamanho total de los perfiles |
|
1093 | # Tamanho total de los perfiles | |
| 1094 | nProfiles = None |
|
1094 | nProfiles = None | |
| 1095 |
|
1095 | |||
| 1096 | def __init__(self, **kwargs): |
|
1096 | def __init__(self, **kwargs): | |
| 1097 |
|
1097 | |||
| 1098 | Operation.__init__(self, **kwargs) |
|
1098 | Operation.__init__(self, **kwargs) | |
| 1099 | self.profileIndex = 0 |
|
1099 | self.profileIndex = 0 | |
| 1100 |
|
1100 | |||
| 1101 | def incProfileIndex(self): |
|
1101 | def incProfileIndex(self): | |
| 1102 |
|
1102 | |||
| 1103 | self.profileIndex += 1 |
|
1103 | self.profileIndex += 1 | |
| 1104 |
|
1104 | |||
| 1105 | if self.profileIndex >= self.nProfiles: |
|
1105 | if self.profileIndex >= self.nProfiles: | |
| 1106 | self.profileIndex = 0 |
|
1106 | self.profileIndex = 0 | |
| 1107 |
|
1107 | |||
| 1108 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
1108 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): | |
| 1109 |
|
1109 | |||
| 1110 | if profileIndex < minIndex: |
|
1110 | if profileIndex < minIndex: | |
| 1111 | return False |
|
1111 | return False | |
| 1112 |
|
1112 | |||
| 1113 | if profileIndex > maxIndex: |
|
1113 | if profileIndex > maxIndex: | |
| 1114 | return False |
|
1114 | return False | |
| 1115 |
|
1115 | |||
| 1116 | return True |
|
1116 | return True | |
| 1117 |
|
1117 | |||
| 1118 | def isThisProfileInList(self, profileIndex, profileList): |
|
1118 | def isThisProfileInList(self, profileIndex, profileList): | |
| 1119 |
|
1119 | |||
| 1120 | if profileIndex not in profileList: |
|
1120 | if profileIndex not in profileList: | |
| 1121 | return False |
|
1121 | return False | |
| 1122 |
|
1122 | |||
| 1123 | return True |
|
1123 | return True | |
| 1124 |
|
1124 | |||
| 1125 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
1125 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): | |
| 1126 |
|
1126 | |||
| 1127 | """ |
|
1127 | """ | |
| 1128 | ProfileSelector: |
|
1128 | ProfileSelector: | |
| 1129 |
|
1129 | |||
| 1130 | Inputs: |
|
1130 | Inputs: | |
| 1131 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
1131 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) | |
| 1132 |
|
1132 | |||
| 1133 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
1133 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) | |
| 1134 |
|
1134 | |||
| 1135 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
1135 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) | |
| 1136 |
|
1136 | |||
| 1137 | """ |
|
1137 | """ | |
| 1138 |
|
1138 | |||
| 1139 | if rangeList is not None: |
|
1139 | if rangeList is not None: | |
| 1140 | if type(rangeList[0]) not in (tuple, list): |
|
1140 | if type(rangeList[0]) not in (tuple, list): | |
| 1141 | rangeList = [rangeList] |
|
1141 | rangeList = [rangeList] | |
| 1142 |
|
1142 | |||
| 1143 | dataOut.flagNoData = True |
|
1143 | dataOut.flagNoData = True | |
| 1144 |
|
1144 | |||
| 1145 | if dataOut.flagDataAsBlock: |
|
1145 | if dataOut.flagDataAsBlock: | |
| 1146 | """ |
|
1146 | """ | |
| 1147 | data dimension = [nChannels, nProfiles, nHeis] |
|
1147 | data dimension = [nChannels, nProfiles, nHeis] | |
| 1148 | """ |
|
1148 | """ | |
| 1149 | if profileList != None: |
|
1149 | if profileList != None: | |
| 1150 | dataOut.data = dataOut.data[:,profileList,:] |
|
1150 | dataOut.data = dataOut.data[:,profileList,:] | |
| 1151 |
|
1151 | |||
| 1152 | if profileRangeList != None: |
|
1152 | if profileRangeList != None: | |
| 1153 | minIndex = profileRangeList[0] |
|
1153 | minIndex = profileRangeList[0] | |
| 1154 | maxIndex = profileRangeList[1] |
|
1154 | maxIndex = profileRangeList[1] | |
| 1155 | profileList = list(range(minIndex, maxIndex+1)) |
|
1155 | profileList = list(range(minIndex, maxIndex+1)) | |
| 1156 |
|
1156 | |||
| 1157 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
1157 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] | |
| 1158 |
|
1158 | |||
| 1159 | if rangeList != None: |
|
1159 | if rangeList != None: | |
| 1160 |
|
1160 | |||
| 1161 | profileList = [] |
|
1161 | profileList = [] | |
| 1162 |
|
1162 | |||
| 1163 | for thisRange in rangeList: |
|
1163 | for thisRange in rangeList: | |
| 1164 | minIndex = thisRange[0] |
|
1164 | minIndex = thisRange[0] | |
| 1165 | maxIndex = thisRange[1] |
|
1165 | maxIndex = thisRange[1] | |
| 1166 |
|
1166 | |||
| 1167 | profileList.extend(list(range(minIndex, maxIndex+1))) |
|
1167 | profileList.extend(list(range(minIndex, maxIndex+1))) | |
| 1168 |
|
1168 | |||
| 1169 | dataOut.data = dataOut.data[:,profileList,:] |
|
1169 | dataOut.data = dataOut.data[:,profileList,:] | |
| 1170 |
|
1170 | |||
| 1171 | dataOut.nProfiles = len(profileList) |
|
1171 | dataOut.nProfiles = len(profileList) | |
| 1172 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
1172 | dataOut.profileIndex = dataOut.nProfiles - 1 | |
| 1173 | dataOut.flagNoData = False |
|
1173 | dataOut.flagNoData = False | |
| 1174 |
|
1174 | |||
| 1175 | return dataOut |
|
1175 | return dataOut | |
| 1176 |
|
1176 | |||
| 1177 | """ |
|
1177 | """ | |
| 1178 | data dimension = [nChannels, nHeis] |
|
1178 | data dimension = [nChannels, nHeis] | |
| 1179 | """ |
|
1179 | """ | |
| 1180 |
|
1180 | |||
| 1181 | if profileList != None: |
|
1181 | if profileList != None: | |
| 1182 |
|
1182 | |||
| 1183 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
1183 | if self.isThisProfileInList(dataOut.profileIndex, profileList): | |
| 1184 |
|
1184 | |||
| 1185 | self.nProfiles = len(profileList) |
|
1185 | self.nProfiles = len(profileList) | |
| 1186 | dataOut.nProfiles = self.nProfiles |
|
1186 | dataOut.nProfiles = self.nProfiles | |
| 1187 | dataOut.profileIndex = self.profileIndex |
|
1187 | dataOut.profileIndex = self.profileIndex | |
| 1188 | dataOut.flagNoData = False |
|
1188 | dataOut.flagNoData = False | |
| 1189 |
|
1189 | |||
| 1190 | self.incProfileIndex() |
|
1190 | self.incProfileIndex() | |
| 1191 | return dataOut |
|
1191 | return dataOut | |
| 1192 |
|
1192 | |||
| 1193 | if profileRangeList != None: |
|
1193 | if profileRangeList != None: | |
| 1194 |
|
1194 | |||
| 1195 | minIndex = profileRangeList[0] |
|
1195 | minIndex = profileRangeList[0] | |
| 1196 | maxIndex = profileRangeList[1] |
|
1196 | maxIndex = profileRangeList[1] | |
| 1197 |
|
1197 | |||
| 1198 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1198 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 1199 |
|
1199 | |||
| 1200 | self.nProfiles = maxIndex - minIndex + 1 |
|
1200 | self.nProfiles = maxIndex - minIndex + 1 | |
| 1201 | dataOut.nProfiles = self.nProfiles |
|
1201 | dataOut.nProfiles = self.nProfiles | |
| 1202 | dataOut.profileIndex = self.profileIndex |
|
1202 | dataOut.profileIndex = self.profileIndex | |
| 1203 | dataOut.flagNoData = False |
|
1203 | dataOut.flagNoData = False | |
| 1204 |
|
1204 | |||
| 1205 | self.incProfileIndex() |
|
1205 | self.incProfileIndex() | |
| 1206 | return dataOut |
|
1206 | return dataOut | |
| 1207 |
|
1207 | |||
| 1208 | if rangeList != None: |
|
1208 | if rangeList != None: | |
| 1209 |
|
1209 | |||
| 1210 | nProfiles = 0 |
|
1210 | nProfiles = 0 | |
| 1211 |
|
1211 | |||
| 1212 | for thisRange in rangeList: |
|
1212 | for thisRange in rangeList: | |
| 1213 | minIndex = thisRange[0] |
|
1213 | minIndex = thisRange[0] | |
| 1214 | maxIndex = thisRange[1] |
|
1214 | maxIndex = thisRange[1] | |
| 1215 |
|
1215 | |||
| 1216 | nProfiles += maxIndex - minIndex + 1 |
|
1216 | nProfiles += maxIndex - minIndex + 1 | |
| 1217 |
|
1217 | |||
| 1218 | for thisRange in rangeList: |
|
1218 | for thisRange in rangeList: | |
| 1219 |
|
1219 | |||
| 1220 | minIndex = thisRange[0] |
|
1220 | minIndex = thisRange[0] | |
| 1221 | maxIndex = thisRange[1] |
|
1221 | maxIndex = thisRange[1] | |
| 1222 |
|
1222 | |||
| 1223 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1223 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 1224 |
|
1224 | |||
| 1225 | self.nProfiles = nProfiles |
|
1225 | self.nProfiles = nProfiles | |
| 1226 | dataOut.nProfiles = self.nProfiles |
|
1226 | dataOut.nProfiles = self.nProfiles | |
| 1227 | dataOut.profileIndex = self.profileIndex |
|
1227 | dataOut.profileIndex = self.profileIndex | |
| 1228 | dataOut.flagNoData = False |
|
1228 | dataOut.flagNoData = False | |
| 1229 |
|
1229 | |||
| 1230 | self.incProfileIndex() |
|
1230 | self.incProfileIndex() | |
| 1231 |
|
1231 | |||
| 1232 | break |
|
1232 | break | |
| 1233 |
|
1233 | |||
| 1234 | return dataOut |
|
1234 | return dataOut | |
| 1235 |
|
1235 | |||
| 1236 |
|
1236 | |||
| 1237 | if beam != None: #beam is only for AMISR data |
|
1237 | if beam != None: #beam is only for AMISR data | |
| 1238 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
1238 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): | |
| 1239 | dataOut.flagNoData = False |
|
1239 | dataOut.flagNoData = False | |
| 1240 | dataOut.profileIndex = self.profileIndex |
|
1240 | dataOut.profileIndex = self.profileIndex | |
| 1241 |
|
1241 | |||
| 1242 | self.incProfileIndex() |
|
1242 | self.incProfileIndex() | |
| 1243 |
|
1243 | |||
| 1244 | return dataOut |
|
1244 | return dataOut | |
| 1245 |
|
1245 | |||
| 1246 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") |
|
1246 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") | |
| 1247 |
|
1247 | |||
| 1248 |
|
1248 | |||
| 1249 | class Reshaper(Operation): |
|
1249 | class Reshaper(Operation): | |
| 1250 |
|
1250 | |||
| 1251 | def __init__(self, **kwargs): |
|
1251 | def __init__(self, **kwargs): | |
| 1252 |
|
1252 | |||
| 1253 | Operation.__init__(self, **kwargs) |
|
1253 | Operation.__init__(self, **kwargs) | |
| 1254 |
|
1254 | |||
| 1255 | self.__buffer = None |
|
1255 | self.__buffer = None | |
| 1256 | self.__nitems = 0 |
|
1256 | self.__nitems = 0 | |
| 1257 |
|
1257 | |||
| 1258 | def __appendProfile(self, dataOut, nTxs): |
|
1258 | def __appendProfile(self, dataOut, nTxs): | |
| 1259 |
|
1259 | |||
| 1260 | if self.__buffer is None: |
|
1260 | if self.__buffer is None: | |
| 1261 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
1261 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) | |
| 1262 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
1262 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) | |
| 1263 |
|
1263 | |||
| 1264 | ini = dataOut.nHeights * self.__nitems |
|
1264 | ini = dataOut.nHeights * self.__nitems | |
| 1265 | end = ini + dataOut.nHeights |
|
1265 | end = ini + dataOut.nHeights | |
| 1266 |
|
1266 | |||
| 1267 | self.__buffer[:, ini:end] = dataOut.data |
|
1267 | self.__buffer[:, ini:end] = dataOut.data | |
| 1268 |
|
1268 | |||
| 1269 | self.__nitems += 1 |
|
1269 | self.__nitems += 1 | |
| 1270 |
|
1270 | |||
| 1271 | return int(self.__nitems*nTxs) |
|
1271 | return int(self.__nitems*nTxs) | |
| 1272 |
|
1272 | |||
| 1273 | def __getBuffer(self): |
|
1273 | def __getBuffer(self): | |
| 1274 |
|
1274 | |||
| 1275 | if self.__nitems == int(1./self.__nTxs): |
|
1275 | if self.__nitems == int(1./self.__nTxs): | |
| 1276 |
|
1276 | |||
| 1277 | self.__nitems = 0 |
|
1277 | self.__nitems = 0 | |
| 1278 |
|
1278 | |||
| 1279 | return self.__buffer.copy() |
|
1279 | return self.__buffer.copy() | |
| 1280 |
|
1280 | |||
| 1281 | return None |
|
1281 | return None | |
| 1282 |
|
1282 | |||
| 1283 | def __checkInputs(self, dataOut, shape, nTxs): |
|
1283 | def __checkInputs(self, dataOut, shape, nTxs): | |
| 1284 |
|
1284 | |||
| 1285 | if shape is None and nTxs is None: |
|
1285 | if shape is None and nTxs is None: | |
| 1286 | raise ValueError("Reshaper: shape of factor should be defined") |
|
1286 | raise ValueError("Reshaper: shape of factor should be defined") | |
| 1287 |
|
1287 | |||
| 1288 | if nTxs: |
|
1288 | if nTxs: | |
| 1289 | if nTxs < 0: |
|
1289 | if nTxs < 0: | |
| 1290 | raise ValueError("nTxs should be greater than 0") |
|
1290 | raise ValueError("nTxs should be greater than 0") | |
| 1291 |
|
1291 | |||
| 1292 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
1292 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: | |
| 1293 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) |
|
1293 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) | |
| 1294 |
|
1294 | |||
| 1295 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
1295 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] | |
| 1296 |
|
1296 | |||
| 1297 | return shape, nTxs |
|
1297 | return shape, nTxs | |
| 1298 |
|
1298 | |||
| 1299 | if len(shape) != 2 and len(shape) != 3: |
|
1299 | if len(shape) != 2 and len(shape) != 3: | |
| 1300 | raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights)) |
|
1300 | raise ValueError("shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights)) | |
| 1301 |
|
1301 | |||
| 1302 | if len(shape) == 2: |
|
1302 | if len(shape) == 2: | |
| 1303 | shape_tuple = [dataOut.nChannels] |
|
1303 | shape_tuple = [dataOut.nChannels] | |
| 1304 | shape_tuple.extend(shape) |
|
1304 | shape_tuple.extend(shape) | |
| 1305 | else: |
|
1305 | else: | |
| 1306 | shape_tuple = list(shape) |
|
1306 | shape_tuple = list(shape) | |
| 1307 |
|
1307 | |||
| 1308 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
1308 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles | |
| 1309 |
|
1309 | |||
| 1310 | return shape_tuple, nTxs |
|
1310 | return shape_tuple, nTxs | |
| 1311 |
|
1311 | |||
| 1312 | def run(self, dataOut, shape=None, nTxs=None): |
|
1312 | def run(self, dataOut, shape=None, nTxs=None): | |
| 1313 |
|
1313 | |||
| 1314 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
1314 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) | |
| 1315 |
|
1315 | |||
| 1316 | dataOut.flagNoData = True |
|
1316 | dataOut.flagNoData = True | |
| 1317 | profileIndex = None |
|
1317 | profileIndex = None | |
| 1318 |
|
1318 | |||
| 1319 | if dataOut.flagDataAsBlock: |
|
1319 | if dataOut.flagDataAsBlock: | |
| 1320 |
|
1320 | |||
| 1321 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
1321 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) | |
| 1322 | dataOut.flagNoData = False |
|
1322 | dataOut.flagNoData = False | |
| 1323 |
|
1323 | |||
| 1324 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
1324 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 | |
| 1325 |
|
1325 | |||
| 1326 | else: |
|
1326 | else: | |
| 1327 |
|
1327 | |||
| 1328 | if self.__nTxs < 1: |
|
1328 | if self.__nTxs < 1: | |
| 1329 |
|
1329 | |||
| 1330 | self.__appendProfile(dataOut, self.__nTxs) |
|
1330 | self.__appendProfile(dataOut, self.__nTxs) | |
| 1331 | new_data = self.__getBuffer() |
|
1331 | new_data = self.__getBuffer() | |
| 1332 |
|
1332 | |||
| 1333 | if new_data is not None: |
|
1333 | if new_data is not None: | |
| 1334 | dataOut.data = new_data |
|
1334 | dataOut.data = new_data | |
| 1335 | dataOut.flagNoData = False |
|
1335 | dataOut.flagNoData = False | |
| 1336 |
|
1336 | |||
| 1337 | profileIndex = dataOut.profileIndex*nTxs |
|
1337 | profileIndex = dataOut.profileIndex*nTxs | |
| 1338 |
|
1338 | |||
| 1339 | else: |
|
1339 | else: | |
| 1340 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") |
|
1340 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") | |
| 1341 |
|
1341 | |||
| 1342 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1342 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1343 |
|
1343 | |||
| 1344 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
1344 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] | |
| 1345 |
|
1345 | |||
| 1346 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
1346 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) | |
| 1347 |
|
1347 | |||
| 1348 | dataOut.profileIndex = profileIndex |
|
1348 | dataOut.profileIndex = profileIndex | |
| 1349 |
|
1349 | |||
| 1350 | dataOut.ippSeconds /= self.__nTxs |
|
1350 | dataOut.ippSeconds /= self.__nTxs | |
| 1351 |
|
1351 | |||
| 1352 | return dataOut |
|
1352 | return dataOut | |
| 1353 |
|
1353 | |||
| 1354 | class SplitProfiles(Operation): |
|
1354 | class SplitProfiles(Operation): | |
| 1355 |
|
1355 | |||
| 1356 | def __init__(self, **kwargs): |
|
1356 | def __init__(self, **kwargs): | |
| 1357 |
|
1357 | |||
| 1358 | Operation.__init__(self, **kwargs) |
|
1358 | Operation.__init__(self, **kwargs) | |
| 1359 |
|
1359 | |||
| 1360 | def run(self, dataOut, n): |
|
1360 | def run(self, dataOut, n): | |
| 1361 |
|
1361 | |||
| 1362 | dataOut.flagNoData = True |
|
1362 | dataOut.flagNoData = True | |
| 1363 | profileIndex = None |
|
1363 | profileIndex = None | |
| 1364 |
|
1364 | |||
| 1365 | if dataOut.flagDataAsBlock: |
|
1365 | if dataOut.flagDataAsBlock: | |
| 1366 |
|
1366 | |||
| 1367 | #nchannels, nprofiles, nsamples |
|
1367 | #nchannels, nprofiles, nsamples | |
| 1368 | shape = dataOut.data.shape |
|
1368 | shape = dataOut.data.shape | |
| 1369 |
|
1369 | |||
| 1370 | if shape[2] % n != 0: |
|
1370 | if shape[2] % n != 0: | |
| 1371 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) |
|
1371 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) | |
| 1372 |
|
1372 | |||
| 1373 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) |
|
1373 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) | |
| 1374 |
|
1374 | |||
| 1375 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1375 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1376 | dataOut.flagNoData = False |
|
1376 | dataOut.flagNoData = False | |
| 1377 |
|
1377 | |||
| 1378 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
1378 | profileIndex = int(dataOut.nProfiles/n) - 1 | |
| 1379 |
|
1379 | |||
| 1380 | else: |
|
1380 | else: | |
| 1381 |
|
1381 | |||
| 1382 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") |
|
1382 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") | |
| 1383 |
|
1383 | |||
| 1384 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1384 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1385 |
|
1385 | |||
| 1386 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
1386 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] | |
| 1387 |
|
1387 | |||
| 1388 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
1388 | dataOut.nProfiles = int(dataOut.nProfiles*n) | |
| 1389 |
|
1389 | |||
| 1390 | dataOut.profileIndex = profileIndex |
|
1390 | dataOut.profileIndex = profileIndex | |
| 1391 |
|
1391 | |||
| 1392 | dataOut.ippSeconds /= n |
|
1392 | dataOut.ippSeconds /= n | |
| 1393 |
|
1393 | |||
| 1394 | return dataOut |
|
1394 | return dataOut | |
| 1395 |
|
1395 | |||
| 1396 | class CombineProfiles(Operation): |
|
1396 | class CombineProfiles(Operation): | |
| 1397 | def __init__(self, **kwargs): |
|
1397 | def __init__(self, **kwargs): | |
| 1398 |
|
1398 | |||
| 1399 | Operation.__init__(self, **kwargs) |
|
1399 | Operation.__init__(self, **kwargs) | |
| 1400 |
|
1400 | |||
| 1401 | self.__remData = None |
|
1401 | self.__remData = None | |
| 1402 | self.__profileIndex = 0 |
|
1402 | self.__profileIndex = 0 | |
| 1403 |
|
1403 | |||
| 1404 | def run(self, dataOut, n): |
|
1404 | def run(self, dataOut, n): | |
| 1405 |
|
1405 | |||
| 1406 | dataOut.flagNoData = True |
|
1406 | dataOut.flagNoData = True | |
| 1407 | profileIndex = None |
|
1407 | profileIndex = None | |
| 1408 |
|
1408 | |||
| 1409 | if dataOut.flagDataAsBlock: |
|
1409 | if dataOut.flagDataAsBlock: | |
| 1410 |
|
1410 | |||
| 1411 | #nchannels, nprofiles, nsamples |
|
1411 | #nchannels, nprofiles, nsamples | |
| 1412 | shape = dataOut.data.shape |
|
1412 | shape = dataOut.data.shape | |
| 1413 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
1413 | new_shape = shape[0], shape[1]/n, shape[2]*n | |
| 1414 |
|
1414 | |||
| 1415 | if shape[1] % n != 0: |
|
1415 | if shape[1] % n != 0: | |
| 1416 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) |
|
1416 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) | |
| 1417 |
|
1417 | |||
| 1418 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1418 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1419 | dataOut.flagNoData = False |
|
1419 | dataOut.flagNoData = False | |
| 1420 |
|
1420 | |||
| 1421 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
1421 | profileIndex = int(dataOut.nProfiles*n) - 1 | |
| 1422 |
|
1422 | |||
| 1423 | else: |
|
1423 | else: | |
| 1424 |
|
1424 | |||
| 1425 | #nchannels, nsamples |
|
1425 | #nchannels, nsamples | |
| 1426 | if self.__remData is None: |
|
1426 | if self.__remData is None: | |
| 1427 | newData = dataOut.data |
|
1427 | newData = dataOut.data | |
| 1428 | else: |
|
1428 | else: | |
| 1429 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
1429 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) | |
| 1430 |
|
1430 | |||
| 1431 | self.__profileIndex += 1 |
|
1431 | self.__profileIndex += 1 | |
| 1432 |
|
1432 | |||
| 1433 | if self.__profileIndex < n: |
|
1433 | if self.__profileIndex < n: | |
| 1434 | self.__remData = newData |
|
1434 | self.__remData = newData | |
| 1435 | #continue |
|
1435 | #continue | |
| 1436 | return |
|
1436 | return | |
| 1437 |
|
1437 | |||
| 1438 | self.__profileIndex = 0 |
|
1438 | self.__profileIndex = 0 | |
| 1439 | self.__remData = None |
|
1439 | self.__remData = None | |
| 1440 |
|
1440 | |||
| 1441 | dataOut.data = newData |
|
1441 | dataOut.data = newData | |
| 1442 | dataOut.flagNoData = False |
|
1442 | dataOut.flagNoData = False | |
| 1443 |
|
1443 | |||
| 1444 | profileIndex = dataOut.profileIndex/n |
|
1444 | profileIndex = dataOut.profileIndex/n | |
| 1445 |
|
1445 | |||
| 1446 |
|
1446 | |||
| 1447 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1447 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1448 |
|
1448 | |||
| 1449 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
1449 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] | |
| 1450 |
|
1450 | |||
| 1451 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1451 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1452 |
|
1452 | |||
| 1453 | dataOut.profileIndex = profileIndex |
|
1453 | dataOut.profileIndex = profileIndex | |
| 1454 |
|
1454 | |||
| 1455 | dataOut.ippSeconds *= n |
|
1455 | dataOut.ippSeconds *= n | |
| 1456 |
|
1456 | |||
| 1457 | return dataOut |
|
1457 | return dataOut | |
| 1458 |
|
1458 | |||
| 1459 | class PulsePairVoltage(Operation): |
|
1459 | class PulsePairVoltage(Operation): | |
| 1460 | ''' |
|
1460 | ''' | |
| 1461 | Function PulsePair(Signal Power, Velocity) |
|
1461 | Function PulsePair(Signal Power, Velocity) | |
| 1462 | The real component of Lag[0] provides Intensity Information |
|
1462 | The real component of Lag[0] provides Intensity Information | |
| 1463 | The imag component of Lag[1] Phase provides Velocity Information |
|
1463 | The imag component of Lag[1] Phase provides Velocity Information | |
| 1464 |
|
1464 | |||
| 1465 | Configuration Parameters: |
|
1465 | Configuration Parameters: | |
| 1466 | nPRF = Number of Several PRF |
|
1466 | nPRF = Number of Several PRF | |
| 1467 | theta = Degree Azimuth angel Boundaries |
|
1467 | theta = Degree Azimuth angel Boundaries | |
| 1468 |
|
1468 | |||
| 1469 | Input: |
|
1469 | Input: | |
| 1470 | self.dataOut |
|
1470 | self.dataOut | |
| 1471 | lag[N] |
|
1471 | lag[N] | |
| 1472 | Affected: |
|
1472 | Affected: | |
| 1473 | self.dataOut.spc |
|
1473 | self.dataOut.spc | |
| 1474 | ''' |
|
1474 | ''' | |
| 1475 | isConfig = False |
|
1475 | isConfig = False | |
| 1476 | __profIndex = 0 |
|
1476 | __profIndex = 0 | |
| 1477 | __initime = None |
|
1477 | __initime = None | |
| 1478 | __lastdatatime = None |
|
1478 | __lastdatatime = None | |
| 1479 | __buffer = None |
|
1479 | __buffer = None | |
| 1480 | noise = None |
|
1480 | noise = None | |
| 1481 | __dataReady = False |
|
1481 | __dataReady = False | |
| 1482 | n = None |
|
1482 | n = None | |
| 1483 | __nch = 0 |
|
1483 | __nch = 0 | |
| 1484 | __nHeis = 0 |
|
1484 | __nHeis = 0 | |
| 1485 | removeDC = False |
|
1485 | removeDC = False | |
| 1486 | ipp = None |
|
1486 | ipp = None | |
| 1487 | lambda_ = 0 |
|
1487 | lambda_ = 0 | |
| 1488 |
|
1488 | |||
| 1489 | def __init__(self,**kwargs): |
|
1489 | def __init__(self,**kwargs): | |
| 1490 | Operation.__init__(self,**kwargs) |
|
1490 | Operation.__init__(self,**kwargs) | |
| 1491 |
|
1491 | |||
| 1492 | def setup(self, dataOut, n = None, removeDC=False): |
|
1492 | def setup(self, dataOut, n = None, removeDC=False): | |
| 1493 | ''' |
|
1493 | ''' | |
| 1494 | n= Numero de PRF's de entrada |
|
1494 | n= Numero de PRF's de entrada | |
| 1495 | ''' |
|
1495 | ''' | |
| 1496 | self.__initime = None |
|
1496 | self.__initime = None | |
| 1497 | self.__lastdatatime = 0 |
|
1497 | self.__lastdatatime = 0 | |
| 1498 | self.__dataReady = False |
|
1498 | self.__dataReady = False | |
| 1499 | self.__buffer = 0 |
|
1499 | self.__buffer = 0 | |
| 1500 | self.__profIndex = 0 |
|
1500 | self.__profIndex = 0 | |
| 1501 | self.noise = None |
|
1501 | self.noise = None | |
| 1502 | self.__nch = dataOut.nChannels |
|
1502 | self.__nch = dataOut.nChannels | |
| 1503 | self.__nHeis = dataOut.nHeights |
|
1503 | self.__nHeis = dataOut.nHeights | |
| 1504 | self.removeDC = removeDC |
|
1504 | self.removeDC = removeDC | |
| 1505 | self.lambda_ = 3.0e8/(9345.0e6) |
|
1505 | self.lambda_ = 3.0e8/(9345.0e6) | |
| 1506 | self.ippSec = dataOut.ippSeconds |
|
1506 | self.ippSec = dataOut.ippSeconds | |
| 1507 | self.nCohInt = dataOut.nCohInt |
|
1507 | self.nCohInt = dataOut.nCohInt | |
| 1508 |
|
1508 | |||
| 1509 | if n == None: |
|
1509 | if n == None: | |
| 1510 | raise ValueError("n should be specified.") |
|
1510 | raise ValueError("n should be specified.") | |
| 1511 |
|
1511 | |||
| 1512 | if n != None: |
|
1512 | if n != None: | |
| 1513 | if n<2: |
|
1513 | if n<2: | |
| 1514 | raise ValueError("n should be greater than 2") |
|
1514 | raise ValueError("n should be greater than 2") | |
| 1515 |
|
1515 | |||
| 1516 | self.n = n |
|
1516 | self.n = n | |
| 1517 | self.__nProf = n |
|
1517 | self.__nProf = n | |
| 1518 |
|
1518 | |||
| 1519 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
1519 | self.__buffer = numpy.zeros((dataOut.nChannels, | |
| 1520 | n, |
|
1520 | n, | |
| 1521 | dataOut.nHeights), |
|
1521 | dataOut.nHeights), | |
| 1522 | dtype='complex') |
|
1522 | dtype='complex') | |
| 1523 |
|
1523 | |||
| 1524 | def putData(self,data): |
|
1524 | def putData(self,data): | |
| 1525 | ''' |
|
1525 | ''' | |
| 1526 | Add a profile to he __buffer and increase in one the __profiel Index |
|
1526 | Add a profile to he __buffer and increase in one the __profiel Index | |
| 1527 | ''' |
|
1527 | ''' | |
| 1528 | self.__buffer[:,self.__profIndex,:]= data |
|
1528 | self.__buffer[:,self.__profIndex,:]= data | |
| 1529 | self.__profIndex += 1 |
|
1529 | self.__profIndex += 1 | |
| 1530 | return |
|
1530 | return | |
| 1531 |
|
1531 | |||
| 1532 | def pushData(self,dataOut): |
|
1532 | def pushData(self,dataOut): | |
| 1533 | ''' |
|
1533 | ''' | |
| 1534 | Return the PULSEPAIR and the profiles used in the operation |
|
1534 | Return the PULSEPAIR and the profiles used in the operation | |
| 1535 | Affected : self.__profileIndex |
|
1535 | Affected : self.__profileIndex | |
| 1536 | ''' |
|
1536 | ''' | |
| 1537 | #----------------- Remove DC----------------------------------- |
|
1537 | #----------------- Remove DC----------------------------------- | |
| 1538 | if self.removeDC==True: |
|
1538 | if self.removeDC==True: | |
| 1539 | mean = numpy.mean(self.__buffer,1) |
|
1539 | mean = numpy.mean(self.__buffer,1) | |
| 1540 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
1540 | tmp = mean.reshape(self.__nch,1,self.__nHeis) | |
| 1541 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
1541 | dc= numpy.tile(tmp,[1,self.__nProf,1]) | |
| 1542 | self.__buffer = self.__buffer - dc |
|
1542 | self.__buffer = self.__buffer - dc | |
| 1543 | #------------------Calculo de Potencia ------------------------ |
|
1543 | #------------------Calculo de Potencia ------------------------ | |
| 1544 | pair0 = self.__buffer*numpy.conj(self.__buffer) |
|
1544 | pair0 = self.__buffer*numpy.conj(self.__buffer) | |
| 1545 | pair0 = pair0.real |
|
1545 | pair0 = pair0.real | |
| 1546 | lag_0 = numpy.sum(pair0,1) |
|
1546 | lag_0 = numpy.sum(pair0,1) | |
| 1547 | #------------------Calculo de Ruido x canal-------------------- |
|
1547 | #------------------Calculo de Ruido x canal-------------------- | |
| 1548 | self.noise = numpy.zeros(self.__nch) |
|
1548 | self.noise = numpy.zeros(self.__nch) | |
| 1549 | for i in range(self.__nch): |
|
1549 | for i in range(self.__nch): | |
| 1550 | daux = numpy.sort(pair0[i,:,:],axis= None) |
|
1550 | daux = numpy.sort(pair0[i,:,:],axis= None) | |
| 1551 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) |
|
1551 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) | |
| 1552 |
|
1552 | |||
| 1553 | self.noise = self.noise.reshape(self.__nch,1) |
|
1553 | self.noise = self.noise.reshape(self.__nch,1) | |
| 1554 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) |
|
1554 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) | |
| 1555 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) |
|
1555 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) | |
| 1556 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) |
|
1556 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) | |
| 1557 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- |
|
1557 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- | |
| 1558 | #------------------ P= S+N ,P=lag_0/N --------------------------------- |
|
1558 | #------------------ P= S+N ,P=lag_0/N --------------------------------- | |
| 1559 | #-------------------- Power -------------------------------------------------- |
|
1559 | #-------------------- Power -------------------------------------------------- | |
| 1560 | data_power = lag_0/(self.n*self.nCohInt) |
|
1560 | data_power = lag_0/(self.n*self.nCohInt) | |
| 1561 | #------------------ Senal --------------------------------------------------- |
|
1561 | #------------------ Senal --------------------------------------------------- | |
| 1562 | data_intensity = pair0 - noise_buffer |
|
1562 | data_intensity = pair0 - noise_buffer | |
| 1563 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) |
|
1563 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) | |
| 1564 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) |
|
1564 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) | |
| 1565 | for i in range(self.__nch): |
|
1565 | for i in range(self.__nch): | |
| 1566 | for j in range(self.__nHeis): |
|
1566 | for j in range(self.__nHeis): | |
| 1567 | if data_intensity[i][j] < 0: |
|
1567 | if data_intensity[i][j] < 0: | |
| 1568 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) |
|
1568 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) | |
| 1569 |
|
1569 | |||
| 1570 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- |
|
1570 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- | |
| 1571 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
1571 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) | |
| 1572 | lag_1 = numpy.sum(pair1,1) |
|
1572 | lag_1 = numpy.sum(pair1,1) | |
| 1573 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) |
|
1573 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) | |
| 1574 | data_velocity = (self.lambda_/2.0)*data_freq |
|
1574 | data_velocity = (self.lambda_/2.0)*data_freq | |
| 1575 |
|
1575 | |||
| 1576 | #---------------- Potencia promedio estimada de la Senal----------- |
|
1576 | #---------------- Potencia promedio estimada de la Senal----------- | |
| 1577 | lag_0 = lag_0/self.n |
|
1577 | lag_0 = lag_0/self.n | |
| 1578 | S = lag_0-self.noise |
|
1578 | S = lag_0-self.noise | |
| 1579 |
|
1579 | |||
| 1580 | #---------------- Frecuencia Doppler promedio --------------------- |
|
1580 | #---------------- Frecuencia Doppler promedio --------------------- | |
| 1581 | lag_1 = lag_1/(self.n-1) |
|
1581 | lag_1 = lag_1/(self.n-1) | |
| 1582 | R1 = numpy.abs(lag_1) |
|
1582 | R1 = numpy.abs(lag_1) | |
| 1583 |
|
1583 | |||
| 1584 | #---------------- Calculo del SNR---------------------------------- |
|
1584 | #---------------- Calculo del SNR---------------------------------- | |
| 1585 | data_snrPP = S/self.noise |
|
1585 | data_snrPP = S/self.noise | |
| 1586 | for i in range(self.__nch): |
|
1586 | for i in range(self.__nch): | |
| 1587 | for j in range(self.__nHeis): |
|
1587 | for j in range(self.__nHeis): | |
| 1588 | if data_snrPP[i][j] < 1.e-20: |
|
1588 | if data_snrPP[i][j] < 1.e-20: | |
| 1589 | data_snrPP[i][j] = 1.e-20 |
|
1589 | data_snrPP[i][j] = 1.e-20 | |
| 1590 |
|
1590 | |||
| 1591 | #----------------- Calculo del ancho espectral ---------------------- |
|
1591 | #----------------- Calculo del ancho espectral ---------------------- | |
| 1592 | L = S/R1 |
|
1592 | L = S/R1 | |
| 1593 | L = numpy.where(L<0,1,L) |
|
1593 | L = numpy.where(L<0,1,L) | |
| 1594 | L = numpy.log(L) |
|
1594 | L = numpy.log(L) | |
| 1595 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
1595 | tmp = numpy.sqrt(numpy.absolute(L)) | |
| 1596 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) |
|
1596 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) | |
| 1597 | n = self.__profIndex |
|
1597 | n = self.__profIndex | |
| 1598 |
|
1598 | |||
| 1599 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
1599 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') | |
| 1600 | self.__profIndex = 0 |
|
1600 | self.__profIndex = 0 | |
| 1601 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,n |
|
1601 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,n | |
| 1602 |
|
1602 | |||
| 1603 |
|
1603 | |||
| 1604 | def pulsePairbyProfiles(self,dataOut): |
|
1604 | def pulsePairbyProfiles(self,dataOut): | |
| 1605 |
|
1605 | |||
| 1606 | self.__dataReady = False |
|
1606 | self.__dataReady = False | |
| 1607 | data_power = None |
|
1607 | data_power = None | |
| 1608 | data_intensity = None |
|
1608 | data_intensity = None | |
| 1609 | data_velocity = None |
|
1609 | data_velocity = None | |
| 1610 | data_specwidth = None |
|
1610 | data_specwidth = None | |
| 1611 | data_snrPP = None |
|
1611 | data_snrPP = None | |
| 1612 | self.putData(data=dataOut.data) |
|
1612 | self.putData(data=dataOut.data) | |
| 1613 | if self.__profIndex == self.n: |
|
1613 | if self.__profIndex == self.n: | |
| 1614 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth, n = self.pushData(dataOut=dataOut) |
|
1614 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth, n = self.pushData(dataOut=dataOut) | |
| 1615 | self.__dataReady = True |
|
1615 | self.__dataReady = True | |
| 1616 |
|
1616 | |||
| 1617 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth |
|
1617 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth | |
| 1618 |
|
1618 | |||
| 1619 |
|
1619 | |||
| 1620 | def pulsePairOp(self, dataOut, datatime= None): |
|
1620 | def pulsePairOp(self, dataOut, datatime= None): | |
| 1621 |
|
1621 | |||
| 1622 | if self.__initime == None: |
|
1622 | if self.__initime == None: | |
| 1623 | self.__initime = datatime |
|
1623 | self.__initime = datatime | |
| 1624 | data_power, data_intensity, data_velocity, data_snrPP, data_specwidth = self.pulsePairbyProfiles(dataOut) |
|
1624 | data_power, data_intensity, data_velocity, data_snrPP, data_specwidth = self.pulsePairbyProfiles(dataOut) | |
| 1625 | self.__lastdatatime = datatime |
|
1625 | self.__lastdatatime = datatime | |
| 1626 |
|
1626 | |||
| 1627 | if data_power is None: |
|
1627 | if data_power is None: | |
| 1628 | return None, None, None,None,None,None |
|
1628 | return None, None, None,None,None,None | |
| 1629 |
|
1629 | |||
| 1630 | avgdatatime = self.__initime |
|
1630 | avgdatatime = self.__initime | |
| 1631 | deltatime = datatime - self.__lastdatatime |
|
1631 | deltatime = datatime - self.__lastdatatime | |
| 1632 | self.__initime = datatime |
|
1632 | self.__initime = datatime | |
| 1633 |
|
1633 | |||
| 1634 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth, avgdatatime |
|
1634 | return data_power, data_intensity, data_velocity, data_snrPP, data_specwidth, avgdatatime | |
| 1635 |
|
1635 | |||
| 1636 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
1636 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): | |
| 1637 |
|
1637 | |||
| 1638 | if not self.isConfig: |
|
1638 | if not self.isConfig: | |
| 1639 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
1639 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) | |
| 1640 | self.isConfig = True |
|
1640 | self.isConfig = True | |
| 1641 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) |
|
1641 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) | |
| 1642 | dataOut.flagNoData = True |
|
1642 | dataOut.flagNoData = True | |
| 1643 |
|
1643 | |||
| 1644 | if self.__dataReady: |
|
1644 | if self.__dataReady: | |
| 1645 | dataOut.nCohInt *= self.n |
|
1645 | dataOut.nCohInt *= self.n | |
| 1646 | dataOut.dataPP_POW = data_intensity # S |
|
1646 | dataOut.dataPP_POW = data_intensity # S | |
| 1647 | dataOut.dataPP_POWER = data_power # P |
|
1647 | dataOut.dataPP_POWER = data_power # P | |
| 1648 | dataOut.dataPP_DOP = data_velocity |
|
1648 | dataOut.dataPP_DOP = data_velocity | |
| 1649 | dataOut.dataPP_SNR = data_snrPP |
|
1649 | dataOut.dataPP_SNR = data_snrPP | |
| 1650 | dataOut.dataPP_WIDTH = data_specwidth |
|
1650 | dataOut.dataPP_WIDTH = data_specwidth | |
| 1651 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
1651 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. | |
| 1652 | dataOut.utctime = avgdatatime |
|
1652 | dataOut.utctime = avgdatatime | |
| 1653 | dataOut.flagNoData = False |
|
1653 | dataOut.flagNoData = False | |
| 1654 | return dataOut |
|
1654 | return dataOut | |
| 1655 |
|
1655 | |||
| 1656 |
|
1656 | |||
| 1657 |
|
1657 | |||
| 1658 | # import collections |
|
1658 | # import collections | |
| 1659 | # from scipy.stats import mode |
|
1659 | # from scipy.stats import mode | |
| 1660 | # |
|
1660 | # | |
| 1661 | # class Synchronize(Operation): |
|
1661 | # class Synchronize(Operation): | |
| 1662 | # |
|
1662 | # | |
| 1663 | # isConfig = False |
|
1663 | # isConfig = False | |
| 1664 | # __profIndex = 0 |
|
1664 | # __profIndex = 0 | |
| 1665 | # |
|
1665 | # | |
| 1666 | # def __init__(self, **kwargs): |
|
1666 | # def __init__(self, **kwargs): | |
| 1667 | # |
|
1667 | # | |
| 1668 | # Operation.__init__(self, **kwargs) |
|
1668 | # Operation.__init__(self, **kwargs) | |
| 1669 | # # self.isConfig = False |
|
1669 | # # self.isConfig = False | |
| 1670 | # self.__powBuffer = None |
|
1670 | # self.__powBuffer = None | |
| 1671 | # self.__startIndex = 0 |
|
1671 | # self.__startIndex = 0 | |
| 1672 | # self.__pulseFound = False |
|
1672 | # self.__pulseFound = False | |
| 1673 | # |
|
1673 | # | |
| 1674 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
1674 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): | |
| 1675 | # |
|
1675 | # | |
| 1676 | # #Read data |
|
1676 | # #Read data | |
| 1677 | # |
|
1677 | # | |
| 1678 | # powerdB = dataOut.getPower(channel = channel) |
|
1678 | # powerdB = dataOut.getPower(channel = channel) | |
| 1679 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
1679 | # noisedB = dataOut.getNoise(channel = channel)[0] | |
| 1680 | # |
|
1680 | # | |
| 1681 | # self.__powBuffer.extend(powerdB.flatten()) |
|
1681 | # self.__powBuffer.extend(powerdB.flatten()) | |
| 1682 | # |
|
1682 | # | |
| 1683 | # dataArray = numpy.array(self.__powBuffer) |
|
1683 | # dataArray = numpy.array(self.__powBuffer) | |
| 1684 | # |
|
1684 | # | |
| 1685 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
1685 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") | |
| 1686 | # |
|
1686 | # | |
| 1687 | # maxValue = numpy.nanmax(filteredPower) |
|
1687 | # maxValue = numpy.nanmax(filteredPower) | |
| 1688 | # |
|
1688 | # | |
| 1689 | # if maxValue < noisedB + 10: |
|
1689 | # if maxValue < noisedB + 10: | |
| 1690 | # #No se encuentra ningun pulso de transmision |
|
1690 | # #No se encuentra ningun pulso de transmision | |
| 1691 | # return None |
|
1691 | # return None | |
| 1692 | # |
|
1692 | # | |
| 1693 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
1693 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] | |
| 1694 | # |
|
1694 | # | |
| 1695 | # if len(maxValuesIndex) < 2: |
|
1695 | # if len(maxValuesIndex) < 2: | |
| 1696 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
1696 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX | |
| 1697 | # return None |
|
1697 | # return None | |
| 1698 | # |
|
1698 | # | |
| 1699 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
1699 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples | |
| 1700 | # |
|
1700 | # | |
| 1701 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
1701 | # #Seleccionar solo valores con un espaciamiento de nSamples | |
| 1702 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
1702 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) | |
| 1703 | # |
|
1703 | # | |
| 1704 | # if len(pulseIndex) < 2: |
|
1704 | # if len(pulseIndex) < 2: | |
| 1705 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1705 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1706 | # return None |
|
1706 | # return None | |
| 1707 | # |
|
1707 | # | |
| 1708 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
1708 | # spacing = pulseIndex[1:] - pulseIndex[:-1] | |
| 1709 | # |
|
1709 | # | |
| 1710 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
1710 | # #remover senales que se distancien menos de 10 unidades o muestras | |
| 1711 | # #(No deberian existir IPP menor a 10 unidades) |
|
1711 | # #(No deberian existir IPP menor a 10 unidades) | |
| 1712 | # |
|
1712 | # | |
| 1713 | # realIndex = numpy.where(spacing > 10 )[0] |
|
1713 | # realIndex = numpy.where(spacing > 10 )[0] | |
| 1714 | # |
|
1714 | # | |
| 1715 | # if len(realIndex) < 2: |
|
1715 | # if len(realIndex) < 2: | |
| 1716 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1716 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1717 | # return None |
|
1717 | # return None | |
| 1718 | # |
|
1718 | # | |
| 1719 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
1719 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) | |
| 1720 | # realPulseIndex = pulseIndex[realIndex] |
|
1720 | # realPulseIndex = pulseIndex[realIndex] | |
| 1721 | # |
|
1721 | # | |
| 1722 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
1722 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] | |
| 1723 | # |
|
1723 | # | |
| 1724 | # print "IPP = %d samples" %period |
|
1724 | # print "IPP = %d samples" %period | |
| 1725 | # |
|
1725 | # | |
| 1726 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
1726 | # self.__newNSamples = dataOut.nHeights #int(period) | |
| 1727 | # self.__startIndex = int(realPulseIndex[0]) |
|
1727 | # self.__startIndex = int(realPulseIndex[0]) | |
| 1728 | # |
|
1728 | # | |
| 1729 | # return 1 |
|
1729 | # return 1 | |
| 1730 | # |
|
1730 | # | |
| 1731 | # |
|
1731 | # | |
| 1732 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
1732 | # def setup(self, nSamples, nChannels, buffer_size = 4): | |
| 1733 | # |
|
1733 | # | |
| 1734 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
1734 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), | |
| 1735 | # maxlen = buffer_size*nSamples) |
|
1735 | # maxlen = buffer_size*nSamples) | |
| 1736 | # |
|
1736 | # | |
| 1737 | # bufferList = [] |
|
1737 | # bufferList = [] | |
| 1738 | # |
|
1738 | # | |
| 1739 | # for i in range(nChannels): |
|
1739 | # for i in range(nChannels): | |
| 1740 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
1740 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, | |
| 1741 | # maxlen = buffer_size*nSamples) |
|
1741 | # maxlen = buffer_size*nSamples) | |
| 1742 | # |
|
1742 | # | |
| 1743 | # bufferList.append(bufferByChannel) |
|
1743 | # bufferList.append(bufferByChannel) | |
| 1744 | # |
|
1744 | # | |
| 1745 | # self.__nSamples = nSamples |
|
1745 | # self.__nSamples = nSamples | |
| 1746 | # self.__nChannels = nChannels |
|
1746 | # self.__nChannels = nChannels | |
| 1747 | # self.__bufferList = bufferList |
|
1747 | # self.__bufferList = bufferList | |
| 1748 | # |
|
1748 | # | |
| 1749 | # def run(self, dataOut, channel = 0): |
|
1749 | # def run(self, dataOut, channel = 0): | |
| 1750 | # |
|
1750 | # | |
| 1751 | # if not self.isConfig: |
|
1751 | # if not self.isConfig: | |
| 1752 | # nSamples = dataOut.nHeights |
|
1752 | # nSamples = dataOut.nHeights | |
| 1753 | # nChannels = dataOut.nChannels |
|
1753 | # nChannels = dataOut.nChannels | |
| 1754 | # self.setup(nSamples, nChannels) |
|
1754 | # self.setup(nSamples, nChannels) | |
| 1755 | # self.isConfig = True |
|
1755 | # self.isConfig = True | |
| 1756 | # |
|
1756 | # | |
| 1757 | # #Append new data to internal buffer |
|
1757 | # #Append new data to internal buffer | |
| 1758 | # for thisChannel in range(self.__nChannels): |
|
1758 | # for thisChannel in range(self.__nChannels): | |
| 1759 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1759 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1760 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
1760 | # bufferByChannel.extend(dataOut.data[thisChannel]) | |
| 1761 | # |
|
1761 | # | |
| 1762 | # if self.__pulseFound: |
|
1762 | # if self.__pulseFound: | |
| 1763 | # self.__startIndex -= self.__nSamples |
|
1763 | # self.__startIndex -= self.__nSamples | |
| 1764 | # |
|
1764 | # | |
| 1765 | # #Finding Tx Pulse |
|
1765 | # #Finding Tx Pulse | |
| 1766 | # if not self.__pulseFound: |
|
1766 | # if not self.__pulseFound: | |
| 1767 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
1767 | # indexFound = self.__findTxPulse(dataOut, channel) | |
| 1768 | # |
|
1768 | # | |
| 1769 | # if indexFound == None: |
|
1769 | # if indexFound == None: | |
| 1770 | # dataOut.flagNoData = True |
|
1770 | # dataOut.flagNoData = True | |
| 1771 | # return |
|
1771 | # return | |
| 1772 | # |
|
1772 | # | |
| 1773 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
1773 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) | |
| 1774 | # self.__pulseFound = True |
|
1774 | # self.__pulseFound = True | |
| 1775 | # self.__startIndex = indexFound |
|
1775 | # self.__startIndex = indexFound | |
| 1776 | # |
|
1776 | # | |
| 1777 | # #If pulse was found ... |
|
1777 | # #If pulse was found ... | |
| 1778 | # for thisChannel in range(self.__nChannels): |
|
1778 | # for thisChannel in range(self.__nChannels): | |
| 1779 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1779 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1780 | # #print self.__startIndex |
|
1780 | # #print self.__startIndex | |
| 1781 | # x = numpy.array(bufferByChannel) |
|
1781 | # x = numpy.array(bufferByChannel) | |
| 1782 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
1782 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] | |
| 1783 | # |
|
1783 | # | |
| 1784 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1784 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1785 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
1785 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight | |
| 1786 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
1786 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 | |
| 1787 | # |
|
1787 | # | |
| 1788 | # dataOut.data = self.__arrayBuffer |
|
1788 | # dataOut.data = self.__arrayBuffer | |
| 1789 | # |
|
1789 | # | |
| 1790 | # self.__startIndex += self.__newNSamples |
|
1790 | # self.__startIndex += self.__newNSamples | |
| 1791 | # |
|
1791 | # | |
| 1792 | # return |
|
1792 | # return | |
| 1793 | class SSheightProfiles(Operation): |
|
1793 | class SSheightProfiles(Operation): | |
| 1794 |
|
1794 | |||
| 1795 | step = None |
|
1795 | step = None | |
| 1796 | nsamples = None |
|
1796 | nsamples = None | |
| 1797 | bufferShape = None |
|
1797 | bufferShape = None | |
| 1798 | profileShape = None |
|
1798 | profileShape = None | |
| 1799 | sshProfiles = None |
|
1799 | sshProfiles = None | |
| 1800 | profileIndex = None |
|
1800 | profileIndex = None | |
| 1801 |
|
1801 | |||
| 1802 | def __init__(self, **kwargs): |
|
1802 | def __init__(self, **kwargs): | |
| 1803 |
|
1803 | |||
| 1804 | Operation.__init__(self, **kwargs) |
|
1804 | Operation.__init__(self, **kwargs) | |
| 1805 | self.isConfig = False |
|
1805 | self.isConfig = False | |
| 1806 |
|
1806 | |||
| 1807 | def setup(self,dataOut ,step = None , nsamples = None): |
|
1807 | def setup(self,dataOut ,step = None , nsamples = None): | |
| 1808 |
|
1808 | |||
| 1809 | if step == None and nsamples == None: |
|
1809 | if step == None and nsamples == None: | |
| 1810 | raise ValueError("step or nheights should be specified ...") |
|
1810 | raise ValueError("step or nheights should be specified ...") | |
| 1811 |
|
1811 | |||
| 1812 | self.step = step |
|
1812 | self.step = step | |
| 1813 | self.nsamples = nsamples |
|
1813 | self.nsamples = nsamples | |
| 1814 | self.__nChannels = dataOut.nChannels |
|
1814 | self.__nChannels = dataOut.nChannels | |
| 1815 | self.__nProfiles = dataOut.nProfiles |
|
1815 | self.__nProfiles = dataOut.nProfiles | |
| 1816 | self.__nHeis = dataOut.nHeights |
|
1816 | self.__nHeis = dataOut.nHeights | |
| 1817 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples |
|
1817 | shape = dataOut.data.shape #nchannels, nprofiles, nsamples | |
| 1818 |
|
1818 | |||
| 1819 | residue = (shape[1] - self.nsamples) % self.step |
|
1819 | residue = (shape[1] - self.nsamples) % self.step | |
| 1820 | if residue != 0: |
|
1820 | if residue != 0: | |
| 1821 | print("The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,shape[1] - self.nsamples,residue)) |
|
1821 | print("The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,shape[1] - self.nsamples,residue)) | |
| 1822 |
|
1822 | |||
| 1823 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1823 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1824 | numberProfile = self.nsamples |
|
1824 | numberProfile = self.nsamples | |
| 1825 | numberSamples = (shape[1] - self.nsamples)/self.step |
|
1825 | numberSamples = (shape[1] - self.nsamples)/self.step | |
| 1826 |
|
1826 | |||
| 1827 | self.bufferShape = int(shape[0]), int(numberSamples), int(numberProfile) # nchannels, nsamples , nprofiles |
|
1827 | self.bufferShape = int(shape[0]), int(numberSamples), int(numberProfile) # nchannels, nsamples , nprofiles | |
| 1828 | self.profileShape = int(shape[0]), int(numberProfile), int(numberSamples) # nchannels, nprofiles, nsamples |
|
1828 | self.profileShape = int(shape[0]), int(numberProfile), int(numberSamples) # nchannels, nprofiles, nsamples | |
| 1829 |
|
1829 | |||
| 1830 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) |
|
1830 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) | |
| 1831 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) |
|
1831 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) | |
| 1832 |
|
1832 | |||
| 1833 | def run(self, dataOut, step, nsamples, code = None, repeat = None): |
|
1833 | def run(self, dataOut, step, nsamples, code = None, repeat = None): | |
| 1834 | dataOut.flagNoData = True |
|
1834 | dataOut.flagNoData = True | |
| 1835 |
|
1835 | |||
| 1836 | profileIndex = None |
|
1836 | profileIndex = None | |
| 1837 | #print("nProfiles, nHeights ",dataOut.nProfiles, dataOut.nHeights) |
|
1837 | #print("nProfiles, nHeights ",dataOut.nProfiles, dataOut.nHeights) | |
| 1838 | #print(dataOut.getFreqRange(1)/1000.) |
|
1838 | #print(dataOut.getFreqRange(1)/1000.) | |
| 1839 | #exit(1) |
|
1839 | #exit(1) | |
| 1840 | if dataOut.flagDataAsBlock: |
|
1840 | if dataOut.flagDataAsBlock: | |
| 1841 | dataOut.data = numpy.average(dataOut.data,axis=1) |
|
1841 | dataOut.data = numpy.average(dataOut.data,axis=1) | |
| 1842 | #print("jee") |
|
1842 | #print("jee") | |
| 1843 | dataOut.flagDataAsBlock = False |
|
1843 | dataOut.flagDataAsBlock = False | |
| 1844 | if not self.isConfig: |
|
1844 | if not self.isConfig: | |
| 1845 | self.setup(dataOut, step=step , nsamples=nsamples) |
|
1845 | self.setup(dataOut, step=step , nsamples=nsamples) | |
| 1846 | #print("Setup done") |
|
1846 | #print("Setup done") | |
| 1847 | self.isConfig = True |
|
1847 | self.isConfig = True | |
| 1848 |
|
1848 | |||
| 1849 |
|
1849 | |||
| 1850 | if code is not None: |
|
1850 | if code is not None: | |
| 1851 | code = numpy.array(code) |
|
1851 | code = numpy.array(code) | |
| 1852 | code_block = code |
|
1852 | code_block = code | |
| 1853 |
|
1853 | |||
| 1854 | if repeat is not None: |
|
1854 | if repeat is not None: | |
| 1855 | code_block = numpy.repeat(code_block, repeats=repeat, axis=1) |
|
1855 | code_block = numpy.repeat(code_block, repeats=repeat, axis=1) | |
| 1856 | #print(code_block.shape) |
|
1856 | #print(code_block.shape) | |
| 1857 | for i in range(self.buffer.shape[1]): |
|
1857 | for i in range(self.buffer.shape[1]): | |
| 1858 |
|
1858 | |||
| 1859 | if code is not None: |
|
1859 | if code is not None: | |
| 1860 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples]*code_block |
|
1860 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples]*code_block | |
| 1861 |
|
1861 | |||
| 1862 | else: |
|
1862 | else: | |
| 1863 |
|
1863 | |||
| 1864 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples]#*code[dataOut.profileIndex,:] |
|
1864 | self.buffer[:,i] = dataOut.data[:,i*self.step:i*self.step + self.nsamples]#*code[dataOut.profileIndex,:] | |
| 1865 |
|
1865 | |||
| 1866 | #self.buffer[:,j,self.__nHeis-j*self.step - self.nheights:self.__nHeis-j*self.step] = numpy.flip(dataOut.data[:,j*self.step:j*self.step + self.nheights]) |
|
1866 | #self.buffer[:,j,self.__nHeis-j*self.step - self.nheights:self.__nHeis-j*self.step] = numpy.flip(dataOut.data[:,j*self.step:j*self.step + self.nheights]) | |
| 1867 |
|
1867 | |||
| 1868 | for j in range(self.buffer.shape[0]): |
|
1868 | for j in range(self.buffer.shape[0]): | |
| 1869 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) |
|
1869 | self.sshProfiles[j] = numpy.transpose(self.buffer[j]) | |
| 1870 |
|
1870 | |||
| 1871 | profileIndex = self.nsamples |
|
1871 | profileIndex = self.nsamples | |
| 1872 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1872 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1873 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) |
|
1873 | ippSeconds = (deltaHeight*1.0e-6)/(0.15) | |
| 1874 | #print("ippSeconds, dH: ",ippSeconds,deltaHeight) |
|
1874 | #print("ippSeconds, dH: ",ippSeconds,deltaHeight) | |
| 1875 | try: |
|
1875 | try: | |
| 1876 | if dataOut.concat_m is not None: |
|
1876 | if dataOut.concat_m is not None: | |
| 1877 | ippSeconds= ippSeconds/float(dataOut.concat_m) |
|
1877 | ippSeconds= ippSeconds/float(dataOut.concat_m) | |
| 1878 | #print "Profile concat %d"%dataOut.concat_m |
|
1878 | #print "Profile concat %d"%dataOut.concat_m | |
| 1879 | except: |
|
1879 | except: | |
| 1880 | pass |
|
1880 | pass | |
| 1881 |
|
1881 | |||
| 1882 | dataOut.data = self.sshProfiles |
|
1882 | dataOut.data = self.sshProfiles | |
| 1883 | dataOut.flagNoData = False |
|
1883 | dataOut.flagNoData = False | |
| 1884 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] |
|
1884 | dataOut.heightList = numpy.arange(self.buffer.shape[1]) *self.step*deltaHeight + dataOut.heightList[0] | |
| 1885 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) |
|
1885 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) | |
| 1886 |
|
1886 | |||
| 1887 | dataOut.profileIndex = profileIndex |
|
1887 | dataOut.profileIndex = profileIndex | |
| 1888 | dataOut.flagDataAsBlock = True |
|
1888 | dataOut.flagDataAsBlock = True | |
| 1889 | dataOut.ippSeconds = ippSeconds |
|
1889 | dataOut.ippSeconds = ippSeconds | |
| 1890 | dataOut.step = self.step |
|
1890 | dataOut.step = self.step | |
| 1891 | #print(numpy.shape(dataOut.data)) |
|
1891 | #print(numpy.shape(dataOut.data)) | |
| 1892 | #exit(1) |
|
1892 | #exit(1) | |
| 1893 | #print("new data shape and time:", dataOut.data.shape, dataOut.utctime) |
|
1893 | #print("new data shape and time:", dataOut.data.shape, dataOut.utctime) | |
| 1894 |
|
1894 | |||
| 1895 | return dataOut |
|
1895 | return dataOut | |
| 1896 | ################################################################################3############################3 |
|
1896 | ################################################################################3############################3 | |
| 1897 | ################################################################################3############################3 |
|
1897 | ################################################################################3############################3 | |
| 1898 | ################################################################################3############################3 |
|
1898 | ################################################################################3############################3 | |
| 1899 | ################################################################################3############################3 |
|
1899 | ################################################################################3############################3 | |
| 1900 |
|
1900 | |||
| 1901 | class SSheightProfiles2(Operation): |
|
1901 | class SSheightProfiles2(Operation): | |
| 1902 | ''' |
|
1902 | ''' | |
| 1903 | Procesa por perfiles y por bloques |
|
1903 | Procesa por perfiles y por bloques | |
| 1904 | VersiΓ³n corregida y actualizada para trabajar con RemoveProfileSats2 |
|
1904 | VersiΓ³n corregida y actualizada para trabajar con RemoveProfileSats2 | |
| 1905 | Usar esto |
|
1905 | Usar esto | |
| 1906 | ''' |
|
1906 | ''' | |
| 1907 |
|
1907 | |||
| 1908 |
|
1908 | |||
| 1909 | bufferShape = None |
|
1909 | bufferShape = None | |
| 1910 | profileShape = None |
|
1910 | profileShape = None | |
| 1911 | sshProfiles = None |
|
1911 | sshProfiles = None | |
| 1912 | profileIndex = None |
|
1912 | profileIndex = None | |
| 1913 | #nsamples = None |
|
1913 | #nsamples = None | |
| 1914 | #step = None |
|
1914 | #step = None | |
| 1915 | #deltaHeight = None |
|
1915 | #deltaHeight = None | |
| 1916 | #init_range = None |
|
1916 | #init_range = None | |
| 1917 | __slots__ = ('step', 'nsamples', 'deltaHeight', 'init_range', 'isConfig', '__nChannels', |
|
1917 | __slots__ = ('step', 'nsamples', 'deltaHeight', 'init_range', 'isConfig', '__nChannels', | |
| 1918 | '__nProfiles', '__nHeis', 'deltaHeight', 'new_nHeights') |
|
1918 | '__nProfiles', '__nHeis', 'deltaHeight', 'new_nHeights') | |
| 1919 |
|
1919 | |||
| 1920 | def __init__(self, **kwargs): |
|
1920 | def __init__(self, **kwargs): | |
| 1921 |
|
1921 | |||
| 1922 | Operation.__init__(self, **kwargs) |
|
1922 | Operation.__init__(self, **kwargs) | |
| 1923 | self.isConfig = False |
|
1923 | self.isConfig = False | |
| 1924 |
|
1924 | |||
| 1925 | def setup(self,dataOut ,step = None , nsamples = None): |
|
1925 | def setup(self,dataOut ,step = None , nsamples = None): | |
| 1926 |
|
1926 | |||
| 1927 | if step == None and nsamples == None: |
|
1927 | if step == None and nsamples == None: | |
| 1928 | raise ValueError("step or nheights should be specified ...") |
|
1928 | raise ValueError("step or nheights should be specified ...") | |
| 1929 |
|
1929 | |||
| 1930 | self.step = step |
|
1930 | self.step = step | |
| 1931 | self.nsamples = nsamples |
|
1931 | self.nsamples = nsamples | |
| 1932 | self.__nChannels = int(dataOut.nChannels) |
|
1932 | self.__nChannels = int(dataOut.nChannels) | |
| 1933 | self.__nProfiles = int(dataOut.nProfiles) |
|
1933 | self.__nProfiles = int(dataOut.nProfiles) | |
| 1934 | self.__nHeis = int(dataOut.nHeights) |
|
1934 | self.__nHeis = int(dataOut.nHeights) | |
| 1935 |
|
1935 | |||
| 1936 | residue = (self.__nHeis - self.nsamples) % self.step |
|
1936 | residue = (self.__nHeis - self.nsamples) % self.step | |
| 1937 | if residue != 0: |
|
1937 | if residue != 0: | |
| 1938 | print("The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,self.__nProfiles - self.nsamples,residue)) |
|
1938 | print("The residue is %d, step=%d should be multiple of %d to avoid loss of %d samples"%(residue,step,self.__nProfiles - self.nsamples,residue)) | |
| 1939 |
|
1939 | |||
| 1940 | self.deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1940 | self.deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1941 | self.init_range = dataOut.heightList[0] |
|
1941 | self.init_range = dataOut.heightList[0] | |
| 1942 | #numberProfile = self.nsamples |
|
1942 | #numberProfile = self.nsamples | |
| 1943 | numberSamples = (self.__nHeis - self.nsamples)/self.step |
|
1943 | numberSamples = (self.__nHeis - self.nsamples)/self.step | |
| 1944 |
|
1944 | |||
| 1945 | self.new_nHeights = numberSamples |
|
1945 | self.new_nHeights = numberSamples | |
| 1946 |
|
1946 | |||
| 1947 | self.bufferShape = int(self.__nChannels), int(numberSamples), int(self.nsamples) # nchannels, nsamples , nprofiles |
|
1947 | self.bufferShape = int(self.__nChannels), int(numberSamples), int(self.nsamples) # nchannels, nsamples , nprofiles | |
| 1948 | self.profileShape = int(self.__nChannels), int(self.nsamples), int(numberSamples) # nchannels, nprofiles, nsamples |
|
1948 | self.profileShape = int(self.__nChannels), int(self.nsamples), int(numberSamples) # nchannels, nprofiles, nsamples | |
| 1949 |
|
1949 | |||
| 1950 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) |
|
1950 | self.buffer = numpy.zeros(self.bufferShape , dtype=numpy.complex) | |
| 1951 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) |
|
1951 | self.sshProfiles = numpy.zeros(self.profileShape, dtype=numpy.complex) | |
| 1952 |
|
1952 | |||
| 1953 | def getNewProfiles(self, data, code=None, repeat=None): |
|
1953 | def getNewProfiles(self, data, code=None, repeat=None): | |
| 1954 |
|
1954 | |||
| 1955 | if code is not None: |
|
1955 | if code is not None: | |
| 1956 | code = numpy.array(code) |
|
1956 | code = numpy.array(code) | |
| 1957 | code_block = code |
|
1957 | code_block = code | |
| 1958 |
|
1958 | |||
| 1959 | if repeat is not None: |
|
1959 | if repeat is not None: | |
| 1960 | code_block = numpy.repeat(code_block, repeats=repeat, axis=1) |
|
1960 | code_block = numpy.repeat(code_block, repeats=repeat, axis=1) | |
| 1961 | if data.ndim < 3: |
|
1961 | if data.ndim < 3: | |
| 1962 | data = data.reshape(self.__nChannels,1,self.__nHeis ) |
|
1962 | data = data.reshape(self.__nChannels,1,self.__nHeis ) | |
| 1963 | #print("buff, data, :",self.buffer.shape, data.shape,self.sshProfiles.shape, code_block.shape) |
|
1963 | #print("buff, data, :",self.buffer.shape, data.shape,self.sshProfiles.shape, code_block.shape) | |
| 1964 | for ch in range(self.__nChannels): |
|
1964 | for ch in range(self.__nChannels): | |
| 1965 | for i in range(int(self.new_nHeights)): #nuevas alturas |
|
1965 | for i in range(int(self.new_nHeights)): #nuevas alturas | |
| 1966 | if code is not None: |
|
1966 | if code is not None: | |
| 1967 | self.buffer[ch,i,:] = data[ch,:,i*self.step:i*self.step + self.nsamples]*code_block |
|
1967 | self.buffer[ch,i,:] = data[ch,:,i*self.step:i*self.step + self.nsamples]*code_block | |
| 1968 | else: |
|
1968 | else: | |
| 1969 | self.buffer[ch,i,:] = data[ch,:,i*self.step:i*self.step + self.nsamples]#*code[dataOut.profileIndex,:] |
|
1969 | self.buffer[ch,i,:] = data[ch,:,i*self.step:i*self.step + self.nsamples]#*code[dataOut.profileIndex,:] | |
| 1970 |
|
1970 | |||
| 1971 | for j in range(self.__nChannels): #en los cananles |
|
1971 | for j in range(self.__nChannels): #en los cananles | |
| 1972 | self.sshProfiles[j,:,:] = numpy.transpose(self.buffer[j,:,:]) |
|
1972 | self.sshProfiles[j,:,:] = numpy.transpose(self.buffer[j,:,:]) | |
| 1973 | #print("new profs Done") |
|
1973 | #print("new profs Done") | |
| 1974 |
|
1974 | |||
| 1975 |
|
1975 | |||
| 1976 |
|
1976 | |||
| 1977 | def run(self, dataOut, step, nsamples, code = None, repeat = None): |
|
1977 | def run(self, dataOut, step, nsamples, code = None, repeat = None): | |
| 1978 | # print("running") |
|
1978 | # print("running") | |
| 1979 | if dataOut.flagNoData == True: |
|
1979 | if dataOut.flagNoData == True: | |
| 1980 | return dataOut |
|
1980 | return dataOut | |
| 1981 | dataOut.flagNoData = True |
|
1981 | dataOut.flagNoData = True | |
| 1982 | #print("init data shape:", dataOut.data.shape) |
|
1982 | #print("init data shape:", dataOut.data.shape) | |
| 1983 | #print("ch: {} prof: {} hs: {}".format(int(dataOut.nChannels), |
|
1983 | #print("ch: {} prof: {} hs: {}".format(int(dataOut.nChannels), | |
| 1984 | # int(dataOut.nProfiles),int(dataOut.nHeights))) |
|
1984 | # int(dataOut.nProfiles),int(dataOut.nHeights))) | |
| 1985 |
|
1985 | |||
| 1986 | profileIndex = None |
|
1986 | profileIndex = None | |
| 1987 | # if not dataOut.flagDataAsBlock: |
|
1987 | # if not dataOut.flagDataAsBlock: | |
| 1988 | # dataOut.nProfiles = 1 |
|
1988 | # dataOut.nProfiles = 1 | |
| 1989 |
|
1989 | |||
| 1990 | if not self.isConfig: |
|
1990 | if not self.isConfig: | |
| 1991 | self.setup(dataOut, step=step , nsamples=nsamples) |
|
1991 | self.setup(dataOut, step=step , nsamples=nsamples) | |
| 1992 | #print("Setup done") |
|
1992 | #print("Setup done") | |
| 1993 | self.isConfig = True |
|
1993 | self.isConfig = True | |
| 1994 |
|
1994 | |||
| 1995 | dataBlock = None |
|
1995 | dataBlock = None | |
| 1996 |
|
1996 | |||
| 1997 | nprof = 1 |
|
1997 | nprof = 1 | |
| 1998 | if dataOut.flagDataAsBlock: |
|
1998 | if dataOut.flagDataAsBlock: | |
| 1999 | nprof = int(dataOut.nProfiles) |
|
1999 | nprof = int(dataOut.nProfiles) | |
| 2000 |
|
2000 | |||
| 2001 | #print("dataOut nProfiles:", dataOut.nProfiles) |
|
2001 | #print("dataOut nProfiles:", dataOut.nProfiles) | |
| 2002 | for profile in range(nprof): |
|
2002 | for profile in range(nprof): | |
| 2003 | if dataOut.flagDataAsBlock: |
|
2003 | if dataOut.flagDataAsBlock: | |
| 2004 | #print("read blocks") |
|
2004 | #print("read blocks") | |
| 2005 | self.getNewProfiles(dataOut.data[:,profile,:], code=code, repeat=repeat) |
|
2005 | self.getNewProfiles(dataOut.data[:,profile,:], code=code, repeat=repeat) | |
| 2006 | else: |
|
2006 | else: | |
| 2007 | #print("read profiles") |
|
2007 | #print("read profiles") | |
| 2008 | self.getNewProfiles(dataOut.data, code=code, repeat=repeat) #only one channe |
|
2008 | self.getNewProfiles(dataOut.data, code=code, repeat=repeat) #only one channe | |
| 2009 | if profile == 0: |
|
2009 | if profile == 0: | |
| 2010 | dataBlock = self.sshProfiles.copy() |
|
2010 | dataBlock = self.sshProfiles.copy() | |
| 2011 | else: #by blocks |
|
2011 | else: #by blocks | |
| 2012 | dataBlock = numpy.concatenate((dataBlock,self.sshProfiles), axis=1) #profile axis |
|
2012 | dataBlock = numpy.concatenate((dataBlock,self.sshProfiles), axis=1) #profile axis | |
| 2013 | #print("by blocks: ",dataBlock.shape, self.sshProfiles.shape) |
|
2013 | #print("by blocks: ",dataBlock.shape, self.sshProfiles.shape) | |
| 2014 |
|
2014 | |||
| 2015 | profileIndex = self.nsamples |
|
2015 | profileIndex = self.nsamples | |
| 2016 | #deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
2016 | #deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 2017 | ippSeconds = (self.deltaHeight*1.0e-6)/(0.15) |
|
2017 | ippSeconds = (self.deltaHeight*1.0e-6)/(0.15) | |
| 2018 |
|
2018 | |||
| 2019 |
|
2019 | |||
| 2020 | dataOut.data = dataBlock |
|
2020 | dataOut.data = dataBlock | |
| 2021 | #print("show me: ",self.step,self.deltaHeight, dataOut.heightList, self.new_nHeights) |
|
2021 | #print("show me: ",self.step,self.deltaHeight, dataOut.heightList, self.new_nHeights) | |
| 2022 | dataOut.heightList = numpy.arange(int(self.new_nHeights)) *self.step*self.deltaHeight + self.init_range |
|
2022 | dataOut.heightList = numpy.arange(int(self.new_nHeights)) *self.step*self.deltaHeight + self.init_range | |
| 2023 | dataOut.sampled_heightsFFT = self.nsamples |
|
2023 | dataOut.sampled_heightsFFT = self.nsamples | |
| 2024 | dataOut.ippSeconds = ippSeconds |
|
2024 | dataOut.ippSeconds = ippSeconds | |
| 2025 | dataOut.step = self.step |
|
2025 | dataOut.step = self.step | |
| 2026 | dataOut.deltaHeight = self.step*self.deltaHeight |
|
2026 | dataOut.deltaHeight = self.step*self.deltaHeight | |
| 2027 | dataOut.flagNoData = False |
|
2027 | dataOut.flagNoData = False | |
| 2028 | if dataOut.flagDataAsBlock: |
|
2028 | if dataOut.flagDataAsBlock: | |
| 2029 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) |
|
2029 | dataOut.nProfiles = int(dataOut.nProfiles*self.nsamples) | |
| 2030 |
|
2030 | |||
| 2031 | else: |
|
2031 | else: | |
| 2032 | dataOut.nProfiles = int(self.nsamples) |
|
2032 | dataOut.nProfiles = int(self.nsamples) | |
| 2033 | dataOut.profileIndex = dataOut.nProfiles |
|
2033 | dataOut.profileIndex = dataOut.nProfiles | |
| 2034 | dataOut.flagDataAsBlock = True |
|
2034 | dataOut.flagDataAsBlock = True | |
| 2035 |
|
2035 | |||
| 2036 | dataBlock = None |
|
2036 | dataBlock = None | |
| 2037 |
|
2037 | |||
| 2038 | #print("new data shape:", dataOut.data.shape, dataOut.utctime) |
|
2038 | #print("new data shape:", dataOut.data.shape, dataOut.utctime) | |
| 2039 |
|
2039 | |||
| 2040 | #update Processing Header: |
|
2040 | #update Processing Header: | |
| 2041 | dataOut.processingHeaderObj.heightList = dataOut.heightList |
|
2041 | dataOut.processingHeaderObj.heightList = dataOut.heightList | |
| 2042 | dataOut.processingHeaderObj.ipp = ippSeconds |
|
2042 | dataOut.processingHeaderObj.ipp = ippSeconds | |
| 2043 | dataOut.processingHeaderObj.heightResolution = dataOut.deltaHeight |
|
2043 | dataOut.processingHeaderObj.heightResolution = dataOut.deltaHeight | |
| 2044 | #dataOut.processingHeaderObj.profilesPerBlock = nProfiles |
|
2044 | #dataOut.processingHeaderObj.profilesPerBlock = nProfiles | |
| 2045 |
|
2045 | |||
| 2046 | # # dataOut.data = CH, PROFILES, HEIGHTS |
|
2046 | # # dataOut.data = CH, PROFILES, HEIGHTS | |
| 2047 | #print(dataOut.data .shape) |
|
2047 | #print(dataOut.data .shape) | |
| 2048 | if dataOut.flagProfilesByRange: |
|
2048 | if dataOut.flagProfilesByRange: | |
| 2049 | # #assuming the same remotion for all channels |
|
2049 | # #assuming the same remotion for all channels | |
| 2050 | aux = [ self.nsamples - numpy.count_nonzero(dataOut.data[0, :, h]==0) for h in range(len(dataOut.heightList))] |
|
2050 | aux = [ self.nsamples - numpy.count_nonzero(dataOut.data[0, :, h]==0) for h in range(len(dataOut.heightList))] | |
| 2051 | dataOut.nProfilesByRange = (numpy.asarray(aux)).reshape((1,len(dataOut.heightList) )) |
|
2051 | dataOut.nProfilesByRange = (numpy.asarray(aux)).reshape((1,len(dataOut.heightList) )) | |
| 2052 | #print(dataOut.nProfilesByRange.shape) |
|
2052 | #print(dataOut.nProfilesByRange.shape) | |
| 2053 | else: |
|
2053 | else: | |
| 2054 | dataOut.nProfilesByRange = numpy.ones((1, len(dataOut.heightList)))*dataOut.nProfiles |
|
2054 | dataOut.nProfilesByRange = numpy.ones((1, len(dataOut.heightList)))*dataOut.nProfiles | |
| 2055 | return dataOut |
|
2055 | return dataOut | |
| 2056 |
|
2056 | |||
| 2057 |
|
2057 | |||
| 2058 |
|
2058 | |||
| 2059 | class RemoveProfileSats(Operation): |
|
2059 | class RemoveProfileSats(Operation): | |
| 2060 | ''' |
|
2060 | ''' | |
| 2061 | Escrito: Joab Apaza |
|
2061 | Escrito: Joab Apaza | |
| 2062 |
|
2062 | |||
| 2063 | Omite los perfiles contaminados con seΓ±al de satΓ©lites, usando una altura de referencia |
|
2063 | Omite los perfiles contaminados con seΓ±al de satΓ©lites, usando una altura de referencia | |
| 2064 | In: minHei = min_sat_range |
|
2064 | In: minHei = min_sat_range | |
| 2065 | max_sat_range |
|
2065 | max_sat_range | |
| 2066 | min_hei_ref |
|
2066 | min_hei_ref | |
| 2067 | max_hei_ref |
|
2067 | max_hei_ref | |
| 2068 | th = diference between profiles mean, ref and sats |
|
2068 | th = diference between profiles mean, ref and sats | |
| 2069 | Out: |
|
2069 | Out: | |
| 2070 | profile clean |
|
2070 | profile clean | |
| 2071 | ''' |
|
2071 | ''' | |
| 2072 |
|
2072 | |||
| 2073 |
|
2073 | |||
| 2074 | __buffer_data = [] |
|
2074 | __buffer_data = [] | |
| 2075 | __buffer_times = [] |
|
2075 | __buffer_times = [] | |
| 2076 |
|
2076 | |||
| 2077 | buffer = None |
|
2077 | buffer = None | |
| 2078 |
|
2078 | |||
| 2079 | outliers_IDs_list = [] |
|
2079 | outliers_IDs_list = [] | |
| 2080 |
|
2080 | |||
| 2081 |
|
2081 | |||
| 2082 | __slots__ = ('n','navg','profileMargin','thHistOutlier','minHei_idx','maxHei_idx','nHeights', |
|
2082 | __slots__ = ('n','navg','profileMargin','thHistOutlier','minHei_idx','maxHei_idx','nHeights', | |
| 2083 | 'first_utcBlock','__profIndex','init_prof','end_prof','lenProfileOut','nChannels', |
|
2083 | 'first_utcBlock','__profIndex','init_prof','end_prof','lenProfileOut','nChannels', | |
| 2084 | '__count_exec','__initime','__dataReady','__ipp', 'minRef', 'maxRef', 'thdB') |
|
2084 | '__count_exec','__initime','__dataReady','__ipp', 'minRef', 'maxRef', 'thdB') | |
| 2085 | def __init__(self, **kwargs): |
|
2085 | def __init__(self, **kwargs): | |
| 2086 |
|
2086 | |||
| 2087 | Operation.__init__(self, **kwargs) |
|
2087 | Operation.__init__(self, **kwargs) | |
| 2088 | self.isConfig = False |
|
2088 | self.isConfig = False | |
| 2089 |
|
2089 | |||
| 2090 | def setup(self,dataOut, n=None , navg=0.8, profileMargin=50,thHistOutlier=15, |
|
2090 | def setup(self,dataOut, n=None , navg=0.8, profileMargin=50,thHistOutlier=15, | |
| 2091 | minHei=None, maxHei=None, minRef=None, maxRef=None, thdB=10): |
|
2091 | minHei=None, maxHei=None, minRef=None, maxRef=None, thdB=10): | |
| 2092 |
|
2092 | |||
| 2093 | if n == None and timeInterval == None: |
|
2093 | if n == None and timeInterval == None: | |
| 2094 | raise ValueError("nprofiles or timeInterval should be specified ...") |
|
2094 | raise ValueError("nprofiles or timeInterval should be specified ...") | |
| 2095 |
|
2095 | |||
| 2096 | if n != None: |
|
2096 | if n != None: | |
| 2097 | self.n = n |
|
2097 | self.n = n | |
| 2098 |
|
2098 | |||
| 2099 | self.navg = navg |
|
2099 | self.navg = navg | |
| 2100 | self.profileMargin = profileMargin |
|
2100 | self.profileMargin = profileMargin | |
| 2101 | self.thHistOutlier = thHistOutlier |
|
2101 | self.thHistOutlier = thHistOutlier | |
| 2102 | self.__profIndex = 0 |
|
2102 | self.__profIndex = 0 | |
| 2103 | self.buffer = None |
|
2103 | self.buffer = None | |
| 2104 | self._ipp = dataOut.ippSeconds |
|
2104 | self._ipp = dataOut.ippSeconds | |
| 2105 | self.n_prof_released = 0 |
|
2105 | self.n_prof_released = 0 | |
| 2106 | self.heightList = dataOut.heightList |
|
2106 | self.heightList = dataOut.heightList | |
| 2107 | self.init_prof = 0 |
|
2107 | self.init_prof = 0 | |
| 2108 | self.end_prof = 0 |
|
2108 | self.end_prof = 0 | |
| 2109 | self.__count_exec = 0 |
|
2109 | self.__count_exec = 0 | |
| 2110 | self.__profIndex = 0 |
|
2110 | self.__profIndex = 0 | |
| 2111 | self.first_utcBlock = None |
|
2111 | self.first_utcBlock = None | |
| 2112 | #self.__dh = dataOut.heightList[1] - dataOut.heightList[0] |
|
2112 | #self.__dh = dataOut.heightList[1] - dataOut.heightList[0] | |
| 2113 | minHei = minHei |
|
2113 | minHei = minHei | |
| 2114 | maxHei = maxHei |
|
2114 | maxHei = maxHei | |
| 2115 | if minHei==None : |
|
2115 | if minHei==None : | |
| 2116 | minHei = dataOut.heightList[0] |
|
2116 | minHei = dataOut.heightList[0] | |
| 2117 | if maxHei==None : |
|
2117 | if maxHei==None : | |
| 2118 | maxHei = dataOut.heightList[-1] |
|
2118 | maxHei = dataOut.heightList[-1] | |
| 2119 | self.minHei_idx,self.maxHei_idx = getHei_index(minHei, maxHei, dataOut.heightList) |
|
2119 | self.minHei_idx,self.maxHei_idx = getHei_index(minHei, maxHei, dataOut.heightList) | |
| 2120 | self.min_ref, self.max_ref = getHei_index(minRef, maxRef, dataOut.heightList) |
|
2120 | self.min_ref, self.max_ref = getHei_index(minRef, maxRef, dataOut.heightList) | |
| 2121 | self.nChannels = dataOut.nChannels |
|
2121 | self.nChannels = dataOut.nChannels | |
| 2122 | self.nHeights = dataOut.nHeights |
|
2122 | self.nHeights = dataOut.nHeights | |
| 2123 | self.test_counter = 0 |
|
2123 | self.test_counter = 0 | |
| 2124 | self.thdB = thdB |
|
2124 | self.thdB = thdB | |
| 2125 |
|
2125 | |||
| 2126 | def filterSatsProfiles(self): |
|
2126 | def filterSatsProfiles(self): | |
| 2127 | data = self.__buffer_data |
|
2127 | data = self.__buffer_data | |
| 2128 | #print(data.shape) |
|
2128 | #print(data.shape) | |
| 2129 | nChannels, profiles, heights = data.shape |
|
2129 | nChannels, profiles, heights = data.shape | |
| 2130 | indexes=numpy.zeros([], dtype=int) |
|
2130 | indexes=numpy.zeros([], dtype=int) | |
| 2131 | outliers_IDs=[] |
|
2131 | outliers_IDs=[] | |
| 2132 | for c in range(nChannels): |
|
2132 | for c in range(nChannels): | |
| 2133 | #print(self.min_ref,self.max_ref) |
|
2133 | #print(self.min_ref,self.max_ref) | |
| 2134 | noise_ref = 10* numpy.log10((data[c,:,self.min_ref:self.max_ref] * numpy.conjugate(data[c,:,self.min_ref:self.max_ref])).real) |
|
2134 | noise_ref = 10* numpy.log10((data[c,:,self.min_ref:self.max_ref] * numpy.conjugate(data[c,:,self.min_ref:self.max_ref])).real) | |
| 2135 | #print("Noise ",numpy.percentile(noise_ref,95)) |
|
2135 | #print("Noise ",numpy.percentile(noise_ref,95)) | |
| 2136 | p95 = numpy.percentile(noise_ref,95) |
|
2136 | p95 = numpy.percentile(noise_ref,95) | |
| 2137 | noise_ref = noise_ref.mean() |
|
2137 | noise_ref = noise_ref.mean() | |
| 2138 | #print("Noise ",noise_ref |
|
2138 | #print("Noise ",noise_ref | |
| 2139 |
|
2139 | |||
| 2140 |
|
2140 | |||
| 2141 | for h in range(self.minHei_idx, self.maxHei_idx): |
|
2141 | for h in range(self.minHei_idx, self.maxHei_idx): | |
| 2142 | power = 10* numpy.log10((data[c,:,h] * numpy.conjugate(data[c,:,h])).real) |
|
2142 | power = 10* numpy.log10((data[c,:,h] * numpy.conjugate(data[c,:,h])).real) | |
| 2143 | #th = noise_ref + self.thdB |
|
2143 | #th = noise_ref + self.thdB | |
| 2144 | th = noise_ref + 1.5*(p95-noise_ref) |
|
2144 | th = noise_ref + 1.5*(p95-noise_ref) | |
| 2145 | index = numpy.where(power > th ) |
|
2145 | index = numpy.where(power > th ) | |
| 2146 | if index[0].size > 10 and index[0].size < int(self.navg*profiles): |
|
2146 | if index[0].size > 10 and index[0].size < int(self.navg*profiles): | |
| 2147 | indexes = numpy.append(indexes, index[0]) |
|
2147 | indexes = numpy.append(indexes, index[0]) | |
| 2148 | #print(index[0]) |
|
2148 | #print(index[0]) | |
| 2149 | #print(index[0]) |
|
2149 | #print(index[0]) | |
| 2150 |
|
2150 | |||
| 2151 | # fig,ax = plt.subplots() |
|
2151 | # fig,ax = plt.subplots() | |
| 2152 | # #ax.set_title(str(k)+" "+str(j)) |
|
2152 | # #ax.set_title(str(k)+" "+str(j)) | |
| 2153 | # x=range(len(power)) |
|
2153 | # x=range(len(power)) | |
| 2154 | # ax.scatter(x,power) |
|
2154 | # ax.scatter(x,power) | |
| 2155 | # #ax.axvline(index) |
|
2155 | # #ax.axvline(index) | |
| 2156 | # plt.grid() |
|
2156 | # plt.grid() | |
| 2157 | # plt.show() |
|
2157 | # plt.show() | |
| 2158 | #print(indexes) |
|
2158 | #print(indexes) | |
| 2159 |
|
2159 | |||
| 2160 | #outliers_IDs = outliers_IDs.astype(numpy.dtype('int64')) |
|
2160 | #outliers_IDs = outliers_IDs.astype(numpy.dtype('int64')) | |
| 2161 | #outliers_IDs = numpy.unique(outliers_IDs) |
|
2161 | #outliers_IDs = numpy.unique(outliers_IDs) | |
| 2162 |
|
2162 | |||
| 2163 | outs_lines = numpy.unique(indexes) |
|
2163 | outs_lines = numpy.unique(indexes) | |
| 2164 |
|
2164 | |||
| 2165 |
|
2165 | |||
| 2166 | #Agrupando el histograma de outliers, |
|
2166 | #Agrupando el histograma de outliers, | |
| 2167 | my_bins = numpy.linspace(0,int(profiles), int(profiles/100), endpoint=True) |
|
2167 | my_bins = numpy.linspace(0,int(profiles), int(profiles/100), endpoint=True) | |
| 2168 |
|
2168 | |||
| 2169 |
|
2169 | |||
| 2170 | hist, bins = numpy.histogram(outs_lines,bins=my_bins) |
|
2170 | hist, bins = numpy.histogram(outs_lines,bins=my_bins) | |
| 2171 | hist_outliers_indexes = numpy.where(hist > self.thHistOutlier) #es outlier |
|
2171 | hist_outliers_indexes = numpy.where(hist > self.thHistOutlier) #es outlier | |
| 2172 | hist_outliers_indexes = hist_outliers_indexes[0] |
|
2172 | hist_outliers_indexes = hist_outliers_indexes[0] | |
| 2173 | # if len(hist_outliers_indexes>0): |
|
2173 | # if len(hist_outliers_indexes>0): | |
| 2174 | # hist_outliers_indexes = numpy.append(hist_outliers_indexes,hist_outliers_indexes[-1]+1) |
|
2174 | # hist_outliers_indexes = numpy.append(hist_outliers_indexes,hist_outliers_indexes[-1]+1) | |
| 2175 | #print(hist_outliers_indexes) |
|
2175 | #print(hist_outliers_indexes) | |
| 2176 | #print(bins, hist_outliers_indexes) |
|
2176 | #print(bins, hist_outliers_indexes) | |
| 2177 | bins_outliers_indexes = [int(i) for i in (bins[hist_outliers_indexes])] # |
|
2177 | bins_outliers_indexes = [int(i) for i in (bins[hist_outliers_indexes])] # | |
| 2178 | outlier_loc_index = [] |
|
2178 | outlier_loc_index = [] | |
| 2179 | # for n in range(len(bins_outliers_indexes)): |
|
2179 | # for n in range(len(bins_outliers_indexes)): | |
| 2180 | # for e in range(bins_outliers_indexes[n]-self.profileMargin,bins_outliers_indexes[n]+ self.profileMargin): |
|
2180 | # for e in range(bins_outliers_indexes[n]-self.profileMargin,bins_outliers_indexes[n]+ self.profileMargin): | |
| 2181 | # outlier_loc_index.append(e) |
|
2181 | # outlier_loc_index.append(e) | |
| 2182 | outlier_loc_index = [e for n in range(len(bins_outliers_indexes)) for e in range(bins_outliers_indexes[n]-self.profileMargin,bins_outliers_indexes[n]+ profiles//100 + self.profileMargin) ] |
|
2182 | outlier_loc_index = [e for n in range(len(bins_outliers_indexes)) for e in range(bins_outliers_indexes[n]-self.profileMargin,bins_outliers_indexes[n]+ profiles//100 + self.profileMargin) ] | |
| 2183 | outlier_loc_index = numpy.asarray(outlier_loc_index) |
|
2183 | outlier_loc_index = numpy.asarray(outlier_loc_index) | |
| 2184 |
|
2184 | |||
| 2185 |
|
2185 | |||
| 2186 |
|
2186 | |||
| 2187 |
|
2187 | |||
| 2188 | #print("outliers Ids: ", outlier_loc_index, outlier_loc_index.shape) |
|
2188 | #print("outliers Ids: ", outlier_loc_index, outlier_loc_index.shape) | |
| 2189 | outlier_loc_index = outlier_loc_index[ (outlier_loc_index >= 0) & (outlier_loc_index<profiles)] |
|
2189 | outlier_loc_index = outlier_loc_index[ (outlier_loc_index >= 0) & (outlier_loc_index<profiles)] | |
| 2190 | #print("outliers final: ", outlier_loc_index) |
|
2190 | #print("outliers final: ", outlier_loc_index) | |
| 2191 |
|
2191 | |||
| 2192 | from matplotlib import pyplot as plt |
|
2192 | from matplotlib import pyplot as plt | |
| 2193 | x, y = numpy.meshgrid(numpy.arange(profiles), self.heightList) |
|
2193 | x, y = numpy.meshgrid(numpy.arange(profiles), self.heightList) | |
| 2194 | fig, ax = plt.subplots(1,2,figsize=(8, 6)) |
|
2194 | fig, ax = plt.subplots(1,2,figsize=(8, 6)) | |
| 2195 | dat = data[0,:,:].real |
|
2195 | dat = data[0,:,:].real | |
| 2196 | dat = 10* numpy.log10((data[0,:,:] * numpy.conjugate(data[0,:,:])).real) |
|
2196 | dat = 10* numpy.log10((data[0,:,:] * numpy.conjugate(data[0,:,:])).real) | |
| 2197 | m = numpy.nanmean(dat) |
|
2197 | m = numpy.nanmean(dat) | |
| 2198 | o = numpy.nanstd(dat) |
|
2198 | o = numpy.nanstd(dat) | |
| 2199 | #print(m, o, x.shape, y.shape) |
|
2199 | #print(m, o, x.shape, y.shape) | |
| 2200 | #c = ax[0].pcolormesh(x, y, dat.T, cmap ='YlGnBu', vmin = (m-2*o), vmax = (m+2*o)) |
|
2200 | #c = ax[0].pcolormesh(x, y, dat.T, cmap ='YlGnBu', vmin = (m-2*o), vmax = (m+2*o)) | |
| 2201 | c = ax[0].pcolormesh(x, y, dat.T, cmap ='YlGnBu', vmin = 50, vmax = 75) |
|
2201 | c = ax[0].pcolormesh(x, y, dat.T, cmap ='YlGnBu', vmin = 50, vmax = 75) | |
| 2202 | ax[0].vlines(outs_lines,200,600, linestyles='dashed', label = 'outs', color='w') |
|
2202 | ax[0].vlines(outs_lines,200,600, linestyles='dashed', label = 'outs', color='w') | |
| 2203 | fig.colorbar(c) |
|
2203 | fig.colorbar(c) | |
| 2204 | ax[0].vlines(outlier_loc_index,650,750, linestyles='dashed', label = 'outs', color='r') |
|
2204 | ax[0].vlines(outlier_loc_index,650,750, linestyles='dashed', label = 'outs', color='r') | |
| 2205 | ax[1].hist(outs_lines,bins=my_bins) |
|
2205 | ax[1].hist(outs_lines,bins=my_bins) | |
| 2206 | plt.show() |
|
2206 | plt.show() | |
| 2207 |
|
2207 | |||
| 2208 |
|
2208 | |||
| 2209 | self.outliers_IDs_list = outlier_loc_index |
|
2209 | self.outliers_IDs_list = outlier_loc_index | |
| 2210 | #print("outs list: ", self.outliers_IDs_list) |
|
2210 | #print("outs list: ", self.outliers_IDs_list) | |
| 2211 | return data |
|
2211 | return data | |
| 2212 |
|
2212 | |||
| 2213 |
|
2213 | |||
| 2214 |
|
2214 | |||
| 2215 | def fillBuffer(self, data, datatime): |
|
2215 | def fillBuffer(self, data, datatime): | |
| 2216 |
|
2216 | |||
| 2217 | if self.__profIndex == 0: |
|
2217 | if self.__profIndex == 0: | |
| 2218 | self.__buffer_data = data.copy() |
|
2218 | self.__buffer_data = data.copy() | |
| 2219 |
|
2219 | |||
| 2220 | else: |
|
2220 | else: | |
| 2221 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles |
|
2221 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles | |
| 2222 | self.__profIndex += 1 |
|
2222 | self.__profIndex += 1 | |
| 2223 | self.__buffer_times.append(datatime) |
|
2223 | self.__buffer_times.append(datatime) | |
| 2224 |
|
2224 | |||
| 2225 | def getData(self, data, datatime=None): |
|
2225 | def getData(self, data, datatime=None): | |
| 2226 |
|
2226 | |||
| 2227 | if self.__profIndex == 0: |
|
2227 | if self.__profIndex == 0: | |
| 2228 | self.__initime = datatime |
|
2228 | self.__initime = datatime | |
| 2229 |
|
2229 | |||
| 2230 |
|
2230 | |||
| 2231 | self.__dataReady = False |
|
2231 | self.__dataReady = False | |
| 2232 |
|
2232 | |||
| 2233 | self.fillBuffer(data, datatime) |
|
2233 | self.fillBuffer(data, datatime) | |
| 2234 | dataBlock = None |
|
2234 | dataBlock = None | |
| 2235 |
|
2235 | |||
| 2236 | if self.__profIndex == self.n: |
|
2236 | if self.__profIndex == self.n: | |
| 2237 | #print("apnd : ",data) |
|
2237 | #print("apnd : ",data) | |
| 2238 | dataBlock = self.filterSatsProfiles() |
|
2238 | dataBlock = self.filterSatsProfiles() | |
| 2239 | self.__dataReady = True |
|
2239 | self.__dataReady = True | |
| 2240 |
|
2240 | |||
| 2241 | return dataBlock |
|
2241 | return dataBlock | |
| 2242 |
|
2242 | |||
| 2243 | if dataBlock is None: |
|
2243 | if dataBlock is None: | |
| 2244 | return None, None |
|
2244 | return None, None | |
| 2245 |
|
2245 | |||
| 2246 |
|
2246 | |||
| 2247 |
|
2247 | |||
| 2248 | return dataBlock |
|
2248 | return dataBlock | |
| 2249 |
|
2249 | |||
| 2250 | def releaseBlock(self): |
|
2250 | def releaseBlock(self): | |
| 2251 |
|
2251 | |||
| 2252 | if self.n % self.lenProfileOut != 0: |
|
2252 | if self.n % self.lenProfileOut != 0: | |
| 2253 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) |
|
2253 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) | |
| 2254 | return None |
|
2254 | return None | |
| 2255 |
|
2255 | |||
| 2256 | data = self.buffer[:,self.init_prof:self.end_prof:,:] #ch, prof, alt |
|
2256 | data = self.buffer[:,self.init_prof:self.end_prof:,:] #ch, prof, alt | |
| 2257 |
|
2257 | |||
| 2258 | self.init_prof = self.end_prof |
|
2258 | self.init_prof = self.end_prof | |
| 2259 | self.end_prof += self.lenProfileOut |
|
2259 | self.end_prof += self.lenProfileOut | |
| 2260 | #print("data release shape: ",dataOut.data.shape, self.end_prof) |
|
2260 | #print("data release shape: ",dataOut.data.shape, self.end_prof) | |
| 2261 | self.n_prof_released += 1 |
|
2261 | self.n_prof_released += 1 | |
| 2262 |
|
2262 | |||
| 2263 | return data |
|
2263 | return data | |
| 2264 |
|
2264 | |||
| 2265 | def run(self, dataOut, n=None, navg=0.8, nProfilesOut=1, profile_margin=50, |
|
2265 | def run(self, dataOut, n=None, navg=0.8, nProfilesOut=1, profile_margin=50, | |
| 2266 | th_hist_outlier=15,minHei=None, maxHei=None, minRef=None, maxRef=None, thdB=10): |
|
2266 | th_hist_outlier=15,minHei=None, maxHei=None, minRef=None, maxRef=None, thdB=10): | |
| 2267 |
|
2267 | |||
| 2268 | if not self.isConfig: |
|
2268 | if not self.isConfig: | |
| 2269 | #print("init p idx: ", dataOut.profileIndex ) |
|
2269 | #print("init p idx: ", dataOut.profileIndex ) | |
| 2270 | self.setup(dataOut,n=n, navg=navg,profileMargin=profile_margin,thHistOutlier=th_hist_outlier, |
|
2270 | self.setup(dataOut,n=n, navg=navg,profileMargin=profile_margin,thHistOutlier=th_hist_outlier, | |
| 2271 | minHei=minHei, maxHei=maxHei, minRef=minRef, maxRef=maxRef, thdB=thdB) |
|
2271 | minHei=minHei, maxHei=maxHei, minRef=minRef, maxRef=maxRef, thdB=thdB) | |
| 2272 | self.isConfig = True |
|
2272 | self.isConfig = True | |
| 2273 |
|
2273 | |||
| 2274 | dataBlock = None |
|
2274 | dataBlock = None | |
| 2275 |
|
2275 | |||
| 2276 | if not dataOut.buffer_empty: #hay datos acumulados |
|
2276 | if not dataOut.buffer_empty: #hay datos acumulados | |
| 2277 |
|
2277 | |||
| 2278 | if self.init_prof == 0: |
|
2278 | if self.init_prof == 0: | |
| 2279 | self.n_prof_released = 0 |
|
2279 | self.n_prof_released = 0 | |
| 2280 | self.lenProfileOut = nProfilesOut |
|
2280 | self.lenProfileOut = nProfilesOut | |
| 2281 | dataOut.flagNoData = False |
|
2281 | dataOut.flagNoData = False | |
| 2282 | #print("tp 2 ",dataOut.data.shape) |
|
2282 | #print("tp 2 ",dataOut.data.shape) | |
| 2283 |
|
2283 | |||
| 2284 | self.init_prof = 0 |
|
2284 | self.init_prof = 0 | |
| 2285 | self.end_prof = self.lenProfileOut |
|
2285 | self.end_prof = self.lenProfileOut | |
| 2286 |
|
2286 | |||
| 2287 | dataOut.nProfiles = self.lenProfileOut |
|
2287 | dataOut.nProfiles = self.lenProfileOut | |
| 2288 | if nProfilesOut == 1: |
|
2288 | if nProfilesOut == 1: | |
| 2289 | dataOut.flagDataAsBlock = False |
|
2289 | dataOut.flagDataAsBlock = False | |
| 2290 | else: |
|
2290 | else: | |
| 2291 | dataOut.flagDataAsBlock = True |
|
2291 | dataOut.flagDataAsBlock = True | |
| 2292 | #print("prof: ",self.init_prof) |
|
2292 | #print("prof: ",self.init_prof) | |
| 2293 | dataOut.flagNoData = False |
|
2293 | dataOut.flagNoData = False | |
| 2294 | if numpy.isin(self.n_prof_released, self.outliers_IDs_list): |
|
2294 | if numpy.isin(self.n_prof_released, self.outliers_IDs_list): | |
| 2295 | #print("omitting: ", self.n_prof_released) |
|
2295 | #print("omitting: ", self.n_prof_released) | |
| 2296 | dataOut.flagNoData = True |
|
2296 | dataOut.flagNoData = True | |
| 2297 | dataOut.ippSeconds = self._ipp |
|
2297 | dataOut.ippSeconds = self._ipp | |
| 2298 | dataOut.utctime = self.first_utcBlock + self.init_prof*self._ipp |
|
2298 | dataOut.utctime = self.first_utcBlock + self.init_prof*self._ipp | |
| 2299 | # print("time: ", dataOut.utctime, self.first_utcBlock, self.init_prof,self._ipp,dataOut.ippSeconds) |
|
2299 | # print("time: ", dataOut.utctime, self.first_utcBlock, self.init_prof,self._ipp,dataOut.ippSeconds) | |
| 2300 | #dataOut.data = self.releaseBlock() |
|
2300 | #dataOut.data = self.releaseBlock() | |
| 2301 | #########################################################3 |
|
2301 | #########################################################3 | |
| 2302 | if self.n % self.lenProfileOut != 0: |
|
2302 | if self.n % self.lenProfileOut != 0: | |
| 2303 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) |
|
2303 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) | |
| 2304 | return None |
|
2304 | return None | |
| 2305 |
|
2305 | |||
| 2306 | dataOut.data = None |
|
2306 | dataOut.data = None | |
| 2307 |
|
2307 | |||
| 2308 | if nProfilesOut == 1: |
|
2308 | if nProfilesOut == 1: | |
| 2309 | dataOut.data = self.buffer[:,self.end_prof-1,:] #ch, prof, alt |
|
2309 | dataOut.data = self.buffer[:,self.end_prof-1,:] #ch, prof, alt | |
| 2310 | else: |
|
2310 | else: | |
| 2311 | dataOut.data = self.buffer[:,self.init_prof:self.end_prof,:] #ch, prof, alt |
|
2311 | dataOut.data = self.buffer[:,self.init_prof:self.end_prof,:] #ch, prof, alt | |
| 2312 |
|
2312 | |||
| 2313 | self.init_prof = self.end_prof |
|
2313 | self.init_prof = self.end_prof | |
| 2314 | self.end_prof += self.lenProfileOut |
|
2314 | self.end_prof += self.lenProfileOut | |
| 2315 | #print("data release shape: ",dataOut.data.shape, self.end_prof, dataOut.flagNoData) |
|
2315 | #print("data release shape: ",dataOut.data.shape, self.end_prof, dataOut.flagNoData) | |
| 2316 | self.n_prof_released += 1 |
|
2316 | self.n_prof_released += 1 | |
| 2317 |
|
2317 | |||
| 2318 | if self.end_prof >= (self.n +self.lenProfileOut): |
|
2318 | if self.end_prof >= (self.n +self.lenProfileOut): | |
| 2319 |
|
2319 | |||
| 2320 | self.init_prof = 0 |
|
2320 | self.init_prof = 0 | |
| 2321 | self.__profIndex = 0 |
|
2321 | self.__profIndex = 0 | |
| 2322 | self.buffer = None |
|
2322 | self.buffer = None | |
| 2323 | dataOut.buffer_empty = True |
|
2323 | dataOut.buffer_empty = True | |
| 2324 | self.outliers_IDs_list = [] |
|
2324 | self.outliers_IDs_list = [] | |
| 2325 | self.n_prof_released = 0 |
|
2325 | self.n_prof_released = 0 | |
| 2326 | dataOut.flagNoData = False #enviar ultimo aunque sea outlier :( |
|
2326 | dataOut.flagNoData = False #enviar ultimo aunque sea outlier :( | |
| 2327 | #print("cleaning...", dataOut.buffer_empty) |
|
2327 | #print("cleaning...", dataOut.buffer_empty) | |
| 2328 | dataOut.profileIndex = 0 #self.lenProfileOut |
|
2328 | dataOut.profileIndex = 0 #self.lenProfileOut | |
| 2329 | #################################################################### |
|
2329 | #################################################################### | |
| 2330 | return dataOut |
|
2330 | return dataOut | |
| 2331 |
|
2331 | |||
| 2332 |
|
2332 | |||
| 2333 | #print("tp 223 ",dataOut.data.shape) |
|
2333 | #print("tp 223 ",dataOut.data.shape) | |
| 2334 | dataOut.flagNoData = True |
|
2334 | dataOut.flagNoData = True | |
| 2335 |
|
2335 | |||
| 2336 |
|
2336 | |||
| 2337 |
|
2337 | |||
| 2338 | try: |
|
2338 | try: | |
| 2339 | #dataBlock = self.getData(dataOut.data.reshape(self.nChannels,1,self.nHeights), dataOut.utctime) |
|
2339 | #dataBlock = self.getData(dataOut.data.reshape(self.nChannels,1,self.nHeights), dataOut.utctime) | |
| 2340 | dataBlock = self.getData(numpy.reshape(dataOut.data,(self.nChannels,1,self.nHeights)), dataOut.utctime) |
|
2340 | dataBlock = self.getData(numpy.reshape(dataOut.data,(self.nChannels,1,self.nHeights)), dataOut.utctime) | |
| 2341 | self.__count_exec +=1 |
|
2341 | self.__count_exec +=1 | |
| 2342 | except Exception as e: |
|
2342 | except Exception as e: | |
| 2343 | print("Error getting profiles data",self.__count_exec ) |
|
2343 | print("Error getting profiles data",self.__count_exec ) | |
| 2344 | print(e) |
|
2344 | print(e) | |
| 2345 | sys.exit() |
|
2345 | sys.exit() | |
| 2346 |
|
2346 | |||
| 2347 | if self.__dataReady: |
|
2347 | if self.__dataReady: | |
| 2348 | #print("omitting: ", len(self.outliers_IDs_list)) |
|
2348 | #print("omitting: ", len(self.outliers_IDs_list)) | |
| 2349 | self.__count_exec = 0 |
|
2349 | self.__count_exec = 0 | |
| 2350 | #dataOut.data = |
|
2350 | #dataOut.data = | |
| 2351 | #self.buffer = numpy.flip(dataBlock, axis=1) |
|
2351 | #self.buffer = numpy.flip(dataBlock, axis=1) | |
| 2352 | self.buffer = dataBlock |
|
2352 | self.buffer = dataBlock | |
| 2353 | self.first_utcBlock = self.__initime |
|
2353 | self.first_utcBlock = self.__initime | |
| 2354 | dataOut.utctime = self.__initime |
|
2354 | dataOut.utctime = self.__initime | |
| 2355 | dataOut.nProfiles = self.__profIndex |
|
2355 | dataOut.nProfiles = self.__profIndex | |
| 2356 | #dataOut.flagNoData = False |
|
2356 | #dataOut.flagNoData = False | |
| 2357 | self.init_prof = 0 |
|
2357 | self.init_prof = 0 | |
| 2358 | self.__profIndex = 0 |
|
2358 | self.__profIndex = 0 | |
| 2359 | self.__initime = None |
|
2359 | self.__initime = None | |
| 2360 | dataBlock = None |
|
2360 | dataBlock = None | |
| 2361 | self.__buffer_times = [] |
|
2361 | self.__buffer_times = [] | |
| 2362 | dataOut.error = False |
|
2362 | dataOut.error = False | |
| 2363 | dataOut.useInputBuffer = True |
|
2363 | dataOut.useInputBuffer = True | |
| 2364 | dataOut.buffer_empty = False |
|
2364 | dataOut.buffer_empty = False | |
| 2365 | #print("1 ch: {} prof: {} hs: {}".format(int(dataOut.nChannels),int(dataOut.nProfiles),int(dataOut.nHeights))) |
|
2365 | #print("1 ch: {} prof: {} hs: {}".format(int(dataOut.nChannels),int(dataOut.nProfiles),int(dataOut.nHeights))) | |
| 2366 |
|
2366 | |||
| 2367 |
|
2367 | |||
| 2368 |
|
2368 | |||
| 2369 | #print(self.__count_exec) |
|
2369 | #print(self.__count_exec) | |
| 2370 |
|
2370 | |||
| 2371 | return dataOut |
|
2371 | return dataOut | |
| 2372 |
|
2372 | |||
| 2373 |
|
2373 | |||
| 2374 | class RemoveProfileSats2(Operation): |
|
2374 | class RemoveProfileSats2(Operation): | |
| 2375 | ''' |
|
2375 | ''' | |
| 2376 | Escrito: Joab Apaza |
|
2376 | Escrito: Joab Apaza | |
| 2377 |
|
2377 | |||
| 2378 | Omite los perfiles contaminados con seΓ±al de satΓ©lites, usando una altura de referencia |
|
2378 | Omite los perfiles contaminados con seΓ±al de satΓ©lites, usando una altura de referencia | |
| 2379 | promedia todas las alturas para los cΓ‘lculos |
|
2379 | promedia todas las alturas para los cΓ‘lculos | |
| 2380 | In: |
|
2380 | In: | |
| 2381 | n = Cantidad de perfiles que se acumularan, usualmente 10 segundos |
|
2381 | n = Cantidad de perfiles que se acumularan, usualmente 10 segundos | |
| 2382 | navg = Porcentaje de perfiles que puede considerarse como satΓ©lite, mΓ‘ximo 90% |
|
2382 | navg = Porcentaje de perfiles que puede considerarse como satΓ©lite, mΓ‘ximo 90% | |
| 2383 | minHei = |
|
2383 | minHei = | |
| 2384 | minRef = |
|
2384 | minRef = | |
| 2385 | maxRef = |
|
2385 | maxRef = | |
| 2386 | nBins = |
|
2386 | nBins = | |
| 2387 | profile_margin = |
|
2387 | profile_margin = | |
| 2388 | th_hist_outlier = |
|
2388 | th_hist_outlier = | |
| 2389 | nProfilesOut = |
|
2389 | nProfilesOut = | |
| 2390 |
|
2390 | |||
| 2391 | Pensado para remover interferencias de las YAGI, se puede adaptar a otras interferencias |
|
2391 | Pensado para remover interferencias de las YAGI, se puede adaptar a otras interferencias | |
| 2392 |
|
2392 | |||
| 2393 | remYagi = Activa la funcion de remociΓ³n de interferencias de la YAGI |
|
2393 | remYagi = Activa la funcion de remociΓ³n de interferencias de la YAGI | |
| 2394 | nProfYagi = Cantidad de perfiles que son afectados, acorde NTX de la YAGI |
|
2394 | nProfYagi = Cantidad de perfiles que son afectados, acorde NTX de la YAGI | |
| 2395 | offYagi = |
|
2395 | offYagi = | |
| 2396 | minHJULIA = Altura mΓnima donde aparece la seΓ±al referencia de JULIA (-50) |
|
2396 | minHJULIA = Altura mΓnima donde aparece la seΓ±al referencia de JULIA (-50) | |
| 2397 | maxHJULIA = Altura mΓ‘xima donde aparece la seΓ±al referencia de JULIA (-15) |
|
2397 | maxHJULIA = Altura mΓ‘xima donde aparece la seΓ±al referencia de JULIA (-15) | |
| 2398 |
|
2398 | |||
| 2399 | debug = Activa los grΓ‘ficos, recomendable ejecutar para ajustar los parΓ‘metros |
|
2399 | debug = Activa los grΓ‘ficos, recomendable ejecutar para ajustar los parΓ‘metros | |
| 2400 | para un experimento en especΓfico. |
|
2400 | para un experimento en especΓfico. | |
| 2401 |
|
2401 | |||
| 2402 | ** se modifica para remover interferencias puntuales, es decir, desde otros radares. |
|
2402 | ** se modifica para remover interferencias puntuales, es decir, desde otros radares. | |
| 2403 | Inicialmente se ha configurado para omitir tambiΓ©n los perfiles de la YAGI en los datos |
|
2403 | Inicialmente se ha configurado para omitir tambiΓ©n los perfiles de la YAGI en los datos | |
| 2404 | de AMISR-ISR. |
|
2404 | de AMISR-ISR. | |
| 2405 |
|
2405 | |||
| 2406 | Out: |
|
2406 | Out: | |
| 2407 | profile clean |
|
2407 | profile clean | |
| 2408 | ''' |
|
2408 | ''' | |
| 2409 |
|
2409 | |||
| 2410 |
|
2410 | |||
| 2411 | __buffer_data = [] |
|
2411 | __buffer_data = [] | |
| 2412 | __buffer_times = [] |
|
2412 | __buffer_times = [] | |
| 2413 |
|
2413 | |||
| 2414 | buffer = None |
|
2414 | buffer = None | |
| 2415 |
|
2415 | |||
| 2416 | outliers_IDs_list = [] |
|
2416 | outliers_IDs_list = [] | |
| 2417 |
|
2417 | |||
| 2418 |
|
2418 | |||
| 2419 | __slots__ = ('n','navg','profileMargin','thHistOutlier','minHei_idx','maxHei_idx','nHeights', |
|
2419 | __slots__ = ('n','navg','profileMargin','thHistOutlier','minHei_idx','maxHei_idx','nHeights', | |
| 2420 | 'first_utcBlock','__profIndex','init_prof','end_prof','lenProfileOut','nChannels','cohFactor', |
|
2420 | 'first_utcBlock','__profIndex','init_prof','end_prof','lenProfileOut','nChannels','cohFactor', | |
| 2421 | '__count_exec','__initime','__dataReady','__ipp', 'minRef', 'maxRef', 'debug','prev_pnoise','thfactor') |
|
2421 | '__count_exec','__initime','__dataReady','__ipp', 'minRef', 'maxRef', 'debug','prev_pnoise','thfactor') | |
| 2422 | def __init__(self, **kwargs): |
|
2422 | def __init__(self, **kwargs): | |
| 2423 |
|
2423 | |||
| 2424 | Operation.__init__(self, **kwargs) |
|
2424 | Operation.__init__(self, **kwargs) | |
| 2425 | self.isConfig = False |
|
2425 | self.isConfig = False | |
| 2426 | self.currentTime = None |
|
2426 | self.currentTime = None | |
| 2427 |
|
2427 | |||
| 2428 | def setup(self,dataOut, n=None , navg=0.9, profileMargin=50,thHistOutlier=15,minHei=None, maxHei=None, nBins=10, |
|
2428 | def setup(self,dataOut, n=None , navg=0.9, profileMargin=50,thHistOutlier=15,minHei=None, maxHei=None, nBins=10, | |
| 2429 | minRef=None, maxRef=None, debug=False, remYagi=False, nProfYagi = 0, offYagi=0, minHJULIA=None, maxHJULIA=None, |
|
2429 | minRef=None, maxRef=None, debug=False, remYagi=False, nProfYagi = 0, offYagi=0, minHJULIA=None, maxHJULIA=None, | |
| 2430 | idate=None,startH=None,endH=None, thfactor=1 ): |
|
2430 | idate=None,startH=None,endH=None, thfactor=1 ): | |
| 2431 |
|
2431 | |||
| 2432 | if n == None and timeInterval == None: |
|
2432 | if n == None and timeInterval == None: | |
| 2433 | raise ValueError("nprofiles or timeInterval should be specified ...") |
|
2433 | raise ValueError("nprofiles or timeInterval should be specified ...") | |
| 2434 |
|
2434 | |||
| 2435 | if n != None: |
|
2435 | if n != None: | |
| 2436 | self.n = n |
|
2436 | self.n = n | |
| 2437 |
|
2437 | |||
| 2438 | self.navg = navg |
|
2438 | self.navg = navg | |
| 2439 | self.profileMargin = profileMargin |
|
2439 | self.profileMargin = profileMargin | |
| 2440 | self.thHistOutlier = thHistOutlier |
|
2440 | self.thHistOutlier = thHistOutlier | |
| 2441 | self.__profIndex = 0 |
|
2441 | self.__profIndex = 0 | |
| 2442 | self.buffer = None |
|
2442 | self.buffer = None | |
| 2443 | self._ipp = dataOut.ippSeconds |
|
2443 | self._ipp = dataOut.ippSeconds | |
| 2444 | self.n_prof_released = 0 |
|
2444 | self.n_prof_released = 0 | |
| 2445 | self.heightList = dataOut.heightList |
|
2445 | self.heightList = dataOut.heightList | |
| 2446 | self.init_prof = 0 |
|
2446 | self.init_prof = 0 | |
| 2447 | self.end_prof = 0 |
|
2447 | self.end_prof = 0 | |
| 2448 | self.__count_exec = 0 |
|
2448 | self.__count_exec = 0 | |
| 2449 | self.__profIndex = 0 |
|
2449 | self.__profIndex = 0 | |
| 2450 | self.first_utcBlock = None |
|
2450 | self.first_utcBlock = None | |
| 2451 | self.prev_pnoise = None |
|
2451 | self.prev_pnoise = None | |
| 2452 | self.nBins = nBins |
|
2452 | self.nBins = nBins | |
| 2453 | self.thfactor = thfactor |
|
2453 | self.thfactor = thfactor | |
| 2454 | #self.__dh = dataOut.heightList[1] - dataOut.heightList[0] |
|
2454 | #self.__dh = dataOut.heightList[1] - dataOut.heightList[0] | |
| 2455 | minHei = minHei |
|
2455 | minHei = minHei | |
| 2456 | maxHei = maxHei |
|
2456 | maxHei = maxHei | |
| 2457 | if minHei==None : |
|
2457 | if minHei==None : | |
| 2458 | minHei = dataOut.heightList[0] |
|
2458 | minHei = dataOut.heightList[0] | |
| 2459 | if maxHei==None : |
|
2459 | if maxHei==None : | |
| 2460 | maxHei = dataOut.heightList[-1] |
|
2460 | maxHei = dataOut.heightList[-1] | |
| 2461 | self.minHei_idx,self.maxHei_idx = getHei_index(minHei, maxHei, dataOut.heightList) |
|
2461 | self.minHei_idx,self.maxHei_idx = getHei_index(minHei, maxHei, dataOut.heightList) | |
| 2462 | self.min_ref, self.max_ref = getHei_index(minRef, maxRef, dataOut.heightList) |
|
2462 | self.min_ref, self.max_ref = getHei_index(minRef, maxRef, dataOut.heightList) | |
| 2463 | self.nChannels = dataOut.nChannels |
|
2463 | self.nChannels = dataOut.nChannels | |
| 2464 | self.nHeights = dataOut.nHeights |
|
2464 | self.nHeights = dataOut.nHeights | |
| 2465 | self.test_counter = 0 |
|
2465 | self.test_counter = 0 | |
| 2466 | self.debug = debug |
|
2466 | self.debug = debug | |
| 2467 | self.remYagi = remYagi |
|
2467 | self.remYagi = remYagi | |
| 2468 | self.cohFactor = dataOut.nCohInt |
|
2468 | self.cohFactor = dataOut.nCohInt | |
| 2469 | if self.remYagi : |
|
2469 | if self.remYagi : | |
| 2470 | if minHJULIA==None or maxHJULIA==None: |
|
2470 | if minHJULIA==None or maxHJULIA==None: | |
| 2471 | raise ValueError("Parameters minHYagi and minHYagi are necessary!") |
|
2471 | raise ValueError("Parameters minHYagi and minHYagi are necessary!") | |
| 2472 | return |
|
2472 | return | |
| 2473 | if idate==None or startH==None or endH==None: |
|
2473 | if idate==None or startH==None or endH==None: | |
| 2474 | raise ValueError("Date and hour parameters are necessary!") |
|
2474 | raise ValueError("Date and hour parameters are necessary!") | |
| 2475 | return |
|
2475 | return | |
| 2476 | self.minHJULIA_idx,self.maxHJULIA_idx = getHei_index(minHJULIA, maxHJULIA, dataOut.heightList) |
|
2476 | self.minHJULIA_idx,self.maxHJULIA_idx = getHei_index(minHJULIA, maxHJULIA, dataOut.heightList) | |
| 2477 | self.offYagi = offYagi |
|
2477 | self.offYagi = offYagi | |
| 2478 | self.nTxYagi = nProfYagi |
|
2478 | self.nTxYagi = nProfYagi | |
| 2479 |
|
2479 | |||
| 2480 | self.startTime = datetime.datetime.combine(idate,startH) |
|
2480 | self.startTime = datetime.datetime.combine(idate,startH) | |
| 2481 | self.endTime = datetime.datetime.combine(idate,endH) |
|
2481 | self.endTime = datetime.datetime.combine(idate,endH) | |
| 2482 |
|
2482 | |||
| 2483 | log.warning("Be careful with the selection of parameters for sats removal! It is avisable to \ |
|
2483 | log.warning("Be careful with the selection of parameters for sats removal! It is avisable to \ | |
| 2484 | activate the debug parameter in this operation for calibration", self.name) |
|
2484 | activate the debug parameter in this operation for calibration", self.name) | |
| 2485 |
|
2485 | |||
| 2486 |
|
2486 | |||
| 2487 | def filterSatsProfiles(self): |
|
2487 | def filterSatsProfiles(self): | |
| 2488 |
|
2488 | |||
| 2489 | data = self.__buffer_data.copy() |
|
2489 | data = self.__buffer_data.copy() | |
| 2490 | #print(data.shape) |
|
2490 | #print(data.shape) | |
| 2491 | nChannels, profiles, heights = data.shape |
|
2491 | nChannels, profiles, heights = data.shape | |
| 2492 | indexes=numpy.zeros([], dtype=int) |
|
2492 | indexes=numpy.zeros([], dtype=int) | |
| 2493 | indexes = numpy.delete(indexes,0) |
|
2493 | indexes = numpy.delete(indexes,0) | |
| 2494 |
|
2494 | |||
| 2495 | indexesYagi=numpy.zeros([], dtype=int) |
|
2495 | indexesYagi=numpy.zeros([], dtype=int) | |
| 2496 | indexesYagi = numpy.delete(indexesYagi,0) |
|
2496 | indexesYagi = numpy.delete(indexesYagi,0) | |
| 2497 |
|
2497 | |||
| 2498 | indexesYagi_up=numpy.zeros([], dtype=int) |
|
2498 | indexesYagi_up=numpy.zeros([], dtype=int) | |
| 2499 | indexesYagi_up = numpy.delete(indexesYagi_up,0) |
|
2499 | indexesYagi_up = numpy.delete(indexesYagi_up,0) | |
| 2500 | indexesYagi_down=numpy.zeros([], dtype=int) |
|
2500 | indexesYagi_down=numpy.zeros([], dtype=int) | |
| 2501 | indexesYagi_down = numpy.delete(indexesYagi_down,0) |
|
2501 | indexesYagi_down = numpy.delete(indexesYagi_down,0) | |
| 2502 |
|
2502 | |||
| 2503 |
|
2503 | |||
| 2504 | indexesJULIA=numpy.zeros([], dtype=int) |
|
2504 | indexesJULIA=numpy.zeros([], dtype=int) | |
| 2505 | indexesJULIA = numpy.delete(indexesJULIA,0) |
|
2505 | indexesJULIA = numpy.delete(indexesJULIA,0) | |
| 2506 |
|
2506 | |||
| 2507 | outliers_IDs=[] |
|
2507 | outliers_IDs=[] | |
| 2508 |
|
2508 | |||
| 2509 | div = profiles//self.nBins |
|
2509 | div = profiles//self.nBins | |
| 2510 |
|
2510 | |||
| 2511 | for c in range(nChannels): |
|
2511 | for c in range(nChannels): | |
| 2512 | #print(self.min_ref,self.max_ref) |
|
2512 | #print(self.min_ref,self.max_ref) | |
| 2513 |
|
2513 | |||
| 2514 | import scipy.signal |
|
2514 | import scipy.signal | |
| 2515 | b, a = scipy.signal.butter(3, 0.5) |
|
2515 | b, a = scipy.signal.butter(3, 0.5) | |
| 2516 | #noise_ref = (data[c,:,self.min_ref:self.max_ref] * numpy.conjugate(data[c,:,self.min_ref:self.max_ref])) |
|
2516 | #noise_ref = (data[c,:,self.min_ref:self.max_ref] * numpy.conjugate(data[c,:,self.min_ref:self.max_ref])) | |
| 2517 | noise_ref = numpy.abs(data[c,:,self.min_ref:self.max_ref]) |
|
2517 | noise_ref = numpy.abs(data[c,:,self.min_ref:self.max_ref]) | |
| 2518 | lnoise = len(noise_ref[0,:]) |
|
2518 | lnoise = len(noise_ref[0,:]) | |
| 2519 | #print(noise_ref.shape) |
|
2519 | #print(noise_ref.shape) | |
| 2520 | noise_ref = noise_ref.mean(axis=1) |
|
2520 | noise_ref = noise_ref.mean(axis=1) | |
| 2521 | #fnoise = noise_ref |
|
2521 | #fnoise = noise_ref | |
| 2522 | fnoise = scipy.signal.filtfilt(b, a, noise_ref) |
|
2522 | fnoise = scipy.signal.filtfilt(b, a, noise_ref) | |
| 2523 | #noise_refdB = 10* numpy.log10(noise_ref) |
|
2523 | #noise_refdB = 10* numpy.log10(noise_ref) | |
| 2524 | #print("Noise ",numpy.percentile(noise_ref,95)) |
|
2524 | #print("Noise ",numpy.percentile(noise_ref,95)) | |
| 2525 | p95 = numpy.percentile(fnoise,95) |
|
2525 | p95 = numpy.percentile(fnoise,95) | |
| 2526 | mean_noise = fnoise.mean() |
|
2526 | mean_noise = fnoise.mean() | |
| 2527 |
|
2527 | |||
| 2528 | if self.prev_pnoise != None: |
|
2528 | if self.prev_pnoise != None: | |
| 2529 | if mean_noise < (1.1 * self.prev_pnoise) and mean_noise > (0.9 * self.prev_pnoise): |
|
2529 | if mean_noise < (1.1 * self.prev_pnoise) and mean_noise > (0.9 * self.prev_pnoise): | |
| 2530 | mean_noise = 0.9*mean_noise + 0.1*self.prev_pnoise |
|
2530 | mean_noise = 0.9*mean_noise + 0.1*self.prev_pnoise | |
| 2531 | self.prev_pnoise = mean_noise |
|
2531 | self.prev_pnoise = mean_noise | |
| 2532 | else: |
|
2532 | else: | |
| 2533 | mean_noise = self.prev_pnoise |
|
2533 | mean_noise = self.prev_pnoise | |
| 2534 | else: |
|
2534 | else: | |
| 2535 | self.prev_pnoise = mean_noise |
|
2535 | self.prev_pnoise = mean_noise | |
| 2536 |
|
2536 | |||
| 2537 | std = fnoise.std()+ fnoise.mean() |
|
2537 | std = fnoise.std()+ fnoise.mean() | |
| 2538 |
|
2538 | |||
| 2539 |
|
2539 | |||
| 2540 |
|
2540 | |||
| 2541 | #power = (data[c,:,self.minHei_idx:self.maxHei_idx] * numpy.conjugate(data[c,:,self.minHei_idx:self.maxHei_idx])) |
|
2541 | #power = (data[c,:,self.minHei_idx:self.maxHei_idx] * numpy.conjugate(data[c,:,self.minHei_idx:self.maxHei_idx])) | |
| 2542 | power = numpy.abs(data[c,:,self.minHei_idx:self.maxHei_idx]) |
|
2542 | power = numpy.abs(data[c,:,self.minHei_idx:self.maxHei_idx]) | |
| 2543 | npower = len(power[0,:]) |
|
2543 | npower = len(power[0,:]) | |
| 2544 | #print(power.shape) |
|
2544 | #print(power.shape) | |
| 2545 | power = power.mean(axis=1) |
|
2545 | power = power.mean(axis=1) | |
| 2546 |
|
2546 | |||
| 2547 | fpower = scipy.signal.filtfilt(b, a, power) |
|
2547 | fpower = scipy.signal.filtfilt(b, a, power) | |
| 2548 | #print(power.shape) |
|
2548 | #print(power.shape) | |
| 2549 | #powerdB = 10* numpy.log10(power) |
|
2549 | #powerdB = 10* numpy.log10(power) | |
| 2550 |
|
2550 | |||
| 2551 | #th = p95 * self.thfactor |
|
2551 | #th = p95 * self.thfactor | |
| 2552 | th = mean_noise * self.thfactor |
|
2552 | th = mean_noise * self.thfactor | |
| 2553 |
|
2553 | |||
| 2554 | index = numpy.where(fpower > th ) |
|
2554 | index = numpy.where(fpower > th ) | |
| 2555 | #print("Noise ",mean_noise, p95) |
|
2555 | #print("Noise ",mean_noise, p95) | |
| 2556 | #print(index) |
|
2556 | #print(index) | |
| 2557 |
|
2557 | |||
| 2558 |
|
2558 | |||
| 2559 |
|
2559 | |||
| 2560 | if index[0].size <= int(self.navg*profiles): #outliers from sats |
|
2560 | if index[0].size <= int(self.navg*profiles): #outliers from sats | |
| 2561 | indexes = numpy.append(indexes, index[0]) |
|
2561 | indexes = numpy.append(indexes, index[0]) | |
| 2562 |
|
2562 | |||
| 2563 | index2low = numpy.where(fpower < (th*0.5 )) #outliers from no TX |
|
2563 | index2low = numpy.where(fpower < (th*0.5 )) #outliers from no TX | |
| 2564 | if index2low[0].size <= int(self.navg*profiles): |
|
2564 | if index2low[0].size <= int(self.navg*profiles): | |
| 2565 | indexes = numpy.append(indexes, index2low[0]) |
|
2565 | indexes = numpy.append(indexes, index2low[0]) | |
| 2566 |
|
2566 | |||
| 2567 | #print("sdas ", noise_ref.mean()) |
|
2567 | #print("sdas ", noise_ref.mean()) | |
| 2568 |
|
2568 | |||
| 2569 | if self.remYagi : |
|
2569 | if self.remYagi : | |
| 2570 | #print(self.minHJULIA_idx, self.maxHJULIA_idx) |
|
2570 | #print(self.minHJULIA_idx, self.maxHJULIA_idx) | |
| 2571 | powerJULIA = (data[c,:,self.minHJULIA_idx:self.maxHJULIA_idx] * numpy.conjugate(data[c,:,self.minHJULIA_idx:self.maxHJULIA_idx])).real |
|
2571 | powerJULIA = (data[c,:,self.minHJULIA_idx:self.maxHJULIA_idx] * numpy.conjugate(data[c,:,self.minHJULIA_idx:self.maxHJULIA_idx])).real | |
| 2572 | powerJULIA = powerJULIA.mean(axis=1) |
|
2572 | powerJULIA = powerJULIA.mean(axis=1) | |
| 2573 | th_JULIA = powerJULIA.mean()*0.85 |
|
2573 | th_JULIA = powerJULIA.mean()*0.85 | |
| 2574 | indexJULIA = numpy.where(powerJULIA >= th_JULIA ) |
|
2574 | indexJULIA = numpy.where(powerJULIA >= th_JULIA ) | |
| 2575 |
|
2575 | |||
| 2576 | indexesJULIA= numpy.append(indexesJULIA, indexJULIA[0]) |
|
2576 | indexesJULIA= numpy.append(indexesJULIA, indexJULIA[0]) | |
| 2577 |
|
2577 | |||
| 2578 | # fig, ax = plt.subplots() |
|
2578 | # fig, ax = plt.subplots() | |
| 2579 | # ax.plot(powerJULIA) |
|
2579 | # ax.plot(powerJULIA) | |
| 2580 | # ax.axhline(th_JULIA, color='r') |
|
2580 | # ax.axhline(th_JULIA, color='r') | |
| 2581 | # plt.grid() |
|
2581 | # plt.grid() | |
| 2582 | # plt.show() |
|
2582 | # plt.show() | |
| 2583 |
|
2583 | |||
| 2584 | if self.debug: |
|
2584 | if self.debug: | |
| 2585 | fig, ax = plt.subplots() |
|
2585 | fig, ax = plt.subplots() | |
| 2586 | ax.plot(fpower, label="power") |
|
2586 | ax.plot(fpower, label="power") | |
| 2587 | #ax.plot(fnoise, label="noise ref") |
|
2587 | #ax.plot(fnoise, label="noise ref") | |
| 2588 | ax.axhline(th, color='g', label="th") |
|
2588 | ax.axhline(th, color='g', label="th") | |
| 2589 | #ax.axhline(std, color='b', label="mean") |
|
2589 | #ax.axhline(std, color='b', label="mean") | |
| 2590 | ax.legend() |
|
2590 | ax.legend() | |
| 2591 | plt.grid() |
|
2591 | plt.grid() | |
| 2592 | plt.show() |
|
2592 | plt.show() | |
| 2593 |
|
2593 | |||
| 2594 | #print(indexes) |
|
2594 | #print(indexes) | |
| 2595 |
|
2595 | |||
| 2596 | #outliers_IDs = outliers_IDs.astype(numpy.dtype('int64')) |
|
2596 | #outliers_IDs = outliers_IDs.astype(numpy.dtype('int64')) | |
| 2597 | #outliers_IDs = numpy.unique(outliers_IDs) |
|
2597 | #outliers_IDs = numpy.unique(outliers_IDs) | |
| 2598 | # print(indexesJULIA) |
|
2598 | # print(indexesJULIA) | |
| 2599 | if len(indexesJULIA > 1): |
|
2599 | if len(indexesJULIA > 1): | |
| 2600 | iJ = indexesJULIA |
|
2600 | iJ = indexesJULIA | |
| 2601 | locs = [ (iJ[n]-iJ[n-1]) > 5 for n in range(len(iJ))] |
|
2601 | locs = [ (iJ[n]-iJ[n-1]) > 5 for n in range(len(iJ))] | |
| 2602 | locs_2 = numpy.where(locs)[0] |
|
2602 | locs_2 = numpy.where(locs)[0] | |
| 2603 | #print(locs_2, indexesJULIA[locs_2-1]) |
|
2603 | #print(locs_2, indexesJULIA[locs_2-1]) | |
| 2604 | indexesYagi_up = numpy.append(indexesYagi_up, indexesJULIA[locs_2-1]) |
|
2604 | indexesYagi_up = numpy.append(indexesYagi_up, indexesJULIA[locs_2-1]) | |
| 2605 | indexesYagi_down = numpy.append(indexesYagi_down, indexesJULIA[locs_2]) |
|
2605 | indexesYagi_down = numpy.append(indexesYagi_down, indexesJULIA[locs_2]) | |
| 2606 |
|
2606 | |||
| 2607 |
|
2607 | |||
| 2608 | indexesYagi_up = numpy.append(indexesYagi_up,indexesJULIA[-1]) |
|
2608 | indexesYagi_up = numpy.append(indexesYagi_up,indexesJULIA[-1]) | |
| 2609 | indexesYagi_down = numpy.append(indexesYagi_down,indexesJULIA[0]) |
|
2609 | indexesYagi_down = numpy.append(indexesYagi_down,indexesJULIA[0]) | |
| 2610 |
|
2610 | |||
| 2611 | indexesYagi_up = numpy.unique(indexesYagi_up) |
|
2611 | indexesYagi_up = numpy.unique(indexesYagi_up) | |
| 2612 | indexesYagi_down = numpy.unique(indexesYagi_down) |
|
2612 | indexesYagi_down = numpy.unique(indexesYagi_down) | |
| 2613 |
|
2613 | |||
| 2614 |
|
2614 | |||
| 2615 | aux_ind = [ numpy.arange( (self.offYagi + k)+1, (self.offYagi + k + self.nTxYagi)+1, 1, dtype=int) for k in indexesYagi_up] |
|
2615 | aux_ind = [ numpy.arange( (self.offYagi + k)+1, (self.offYagi + k + self.nTxYagi)+1, 1, dtype=int) for k in indexesYagi_up] | |
| 2616 | indexesYagi_up = (numpy.asarray(aux_ind)).flatten() |
|
2616 | indexesYagi_up = (numpy.asarray(aux_ind)).flatten() | |
| 2617 |
|
2617 | |||
| 2618 | aux_ind2 = [ numpy.arange( (k - self.nTxYagi)+1, k+1 , 1, dtype=int) for k in indexesYagi_down] |
|
2618 | aux_ind2 = [ numpy.arange( (k - self.nTxYagi)+1, k+1 , 1, dtype=int) for k in indexesYagi_down] | |
| 2619 | indexesYagi_down = (numpy.asarray(aux_ind2)).flatten() |
|
2619 | indexesYagi_down = (numpy.asarray(aux_ind2)).flatten() | |
| 2620 |
|
2620 | |||
| 2621 | indexesYagi = numpy.append(indexesYagi,indexesYagi_up) |
|
2621 | indexesYagi = numpy.append(indexesYagi,indexesYagi_up) | |
| 2622 | indexesYagi = numpy.append(indexesYagi,indexesYagi_down) |
|
2622 | indexesYagi = numpy.append(indexesYagi,indexesYagi_down) | |
| 2623 |
|
2623 | |||
| 2624 |
|
2624 | |||
| 2625 | indexesYagi = indexesYagi[ (indexesYagi >= 0) & (indexesYagi<profiles)] |
|
2625 | indexesYagi = indexesYagi[ (indexesYagi >= 0) & (indexesYagi<profiles)] | |
| 2626 | indexesYagi = numpy.unique(indexesYagi) |
|
2626 | indexesYagi = numpy.unique(indexesYagi) | |
| 2627 |
|
2627 | |||
| 2628 | #print("indexes: " ,indexes) |
|
2628 | #print("indexes: " ,indexes) | |
| 2629 | outs_lines = numpy.unique(indexes) |
|
2629 | outs_lines = numpy.unique(indexes) | |
| 2630 | #print(outs_lines) |
|
2630 | #print(outs_lines) | |
| 2631 |
|
2631 | |||
| 2632 | #Agrupando el histograma de outliers, |
|
2632 | #Agrupando el histograma de outliers, | |
| 2633 | my_bins = numpy.linspace(0,int(profiles), div, endpoint=True) |
|
2633 | my_bins = numpy.linspace(0,int(profiles), div, endpoint=True) | |
| 2634 |
|
2634 | |||
| 2635 |
|
2635 | |||
| 2636 | hist, bins = numpy.histogram(outs_lines,bins=my_bins) |
|
2636 | hist, bins = numpy.histogram(outs_lines,bins=my_bins) | |
| 2637 | #print("hist: ",hist) |
|
2637 | #print("hist: ",hist) | |
| 2638 | hist_outliers_indexes = numpy.where(hist >= self.thHistOutlier)[0] #es outlier |
|
2638 | hist_outliers_indexes = numpy.where(hist >= self.thHistOutlier)[0] #es outlier | |
| 2639 | # print(hist_outliers_indexes) |
|
2639 | # print(hist_outliers_indexes) | |
| 2640 | if len(hist_outliers_indexes>0): |
|
2640 | if len(hist_outliers_indexes>0): | |
| 2641 | hist_outliers_indexes = numpy.append(hist_outliers_indexes,hist_outliers_indexes[-1]+1) |
|
2641 | hist_outliers_indexes = numpy.append(hist_outliers_indexes,hist_outliers_indexes[-1]+1) | |
| 2642 |
|
2642 | |||
| 2643 | bins_outliers_indexes = [int(i)+1 for i in (bins[hist_outliers_indexes])] # |
|
2643 | bins_outliers_indexes = [int(i)+1 for i in (bins[hist_outliers_indexes])] # | |
| 2644 | outlier_loc_index = [] |
|
2644 | outlier_loc_index = [] | |
| 2645 | #print("out indexes ", bins_outliers_indexes) |
|
2645 | #print("out indexes ", bins_outliers_indexes) | |
| 2646 |
|
2646 | |||
| 2647 | # if len(bins_outliers_indexes) <= 2: |
|
2647 | # if len(bins_outliers_indexes) <= 2: | |
| 2648 | # extprof = 0 |
|
2648 | # extprof = 0 | |
| 2649 | # else: |
|
2649 | # else: | |
| 2650 | # extprof = self.profileMargin |
|
2650 | # extprof = self.profileMargin | |
| 2651 |
|
2651 | |||
| 2652 | extprof = self.profileMargin |
|
2652 | extprof = self.profileMargin | |
| 2653 |
|
2653 | |||
| 2654 | outlier_loc_index = [e for n in range(len(bins_outliers_indexes)) for e in range(bins_outliers_indexes[n]-extprof,bins_outliers_indexes[n] + extprof) ] |
|
2654 | outlier_loc_index = [e for n in range(len(bins_outliers_indexes)) for e in range(bins_outliers_indexes[n]-extprof,bins_outliers_indexes[n] + extprof) ] | |
| 2655 | outlier_loc_index = numpy.asarray(outlier_loc_index) |
|
2655 | outlier_loc_index = numpy.asarray(outlier_loc_index) | |
| 2656 | # if len(outlier_loc_index)>1: |
|
2656 | # if len(outlier_loc_index)>1: | |
| 2657 | # ipmax = numpy.where(fpower==fpower.max())[0] |
|
2657 | # ipmax = numpy.where(fpower==fpower.max())[0] | |
| 2658 | # print("pmax: ",ipmax) |
|
2658 | # print("pmax: ",ipmax) | |
| 2659 |
|
2659 | |||
| 2660 |
|
2660 | |||
| 2661 |
|
2661 | |||
| 2662 |
|
2662 | |||
| 2663 | #print("outliers Ids: ", outlier_loc_index, outlier_loc_index.shape) |
|
2663 | #print("outliers Ids: ", outlier_loc_index, outlier_loc_index.shape) | |
| 2664 | outlier_loc_index = outlier_loc_index[ (outlier_loc_index >= 0) & (outlier_loc_index<profiles)] |
|
2664 | outlier_loc_index = outlier_loc_index[ (outlier_loc_index >= 0) & (outlier_loc_index<profiles)] | |
| 2665 | #print("outliers final: ", outlier_loc_index) |
|
2665 | #print("outliers final: ", outlier_loc_index) | |
| 2666 |
|
2666 | |||
| 2667 |
|
2667 | |||
| 2668 | if self.debug: |
|
2668 | if self.debug: | |
| 2669 | x, y = numpy.meshgrid(numpy.arange(profiles), self.heightList) |
|
2669 | x, y = numpy.meshgrid(numpy.arange(profiles), self.heightList) | |
| 2670 | fig, ax = plt.subplots(nChannels,2,figsize=(8, 6)) |
|
2670 | fig, ax = plt.subplots(nChannels,2,figsize=(8, 6)) | |
| 2671 |
|
2671 | |||
| 2672 | for i in range(nChannels): |
|
2672 | for i in range(nChannels): | |
| 2673 | dat = data[i,:,:].real |
|
2673 | dat = data[i,:,:].real | |
| 2674 | dat = 10* numpy.log10((data[i,:,:] * numpy.conjugate(data[i,:,:])).real) |
|
2674 | dat = 10* numpy.log10((data[i,:,:] * numpy.conjugate(data[i,:,:])).real) | |
| 2675 | m = numpy.nanmean(dat) |
|
2675 | m = numpy.nanmean(dat) | |
| 2676 | o = numpy.nanstd(dat) |
|
2676 | o = numpy.nanstd(dat) | |
| 2677 | if nChannels>1: |
|
2677 | if nChannels>1: | |
| 2678 | c = ax[i][0].pcolormesh(x, y, dat.T, cmap ='jet', vmin = 60, vmax = 70) |
|
2678 | c = ax[i][0].pcolormesh(x, y, dat.T, cmap ='jet', vmin = 60, vmax = 70) | |
| 2679 | ax[i][0].vlines(outs_lines,650,700, linestyles='dashed', label = 'outs', color='w') |
|
2679 | ax[i][0].vlines(outs_lines,650,700, linestyles='dashed', label = 'outs', color='w') | |
| 2680 | #fig.colorbar(c) |
|
2680 | #fig.colorbar(c) | |
| 2681 | ax[i][0].vlines(outlier_loc_index,700,750, linestyles='dashed', label = 'outs', color='r') |
|
2681 | ax[i][0].vlines(outlier_loc_index,700,750, linestyles='dashed', label = 'outs', color='r') | |
| 2682 | ax[i][1].hist(outs_lines,bins=my_bins) |
|
2682 | ax[i][1].hist(outs_lines,bins=my_bins) | |
| 2683 | if self.remYagi : |
|
2683 | if self.remYagi : | |
| 2684 | ax[0].vlines(indexesYagi,750,850, linestyles='dashed', label = 'yagi', color='m') |
|
2684 | ax[0].vlines(indexesYagi,750,850, linestyles='dashed', label = 'yagi', color='m') | |
| 2685 | else: |
|
2685 | else: | |
| 2686 | c = ax[0].pcolormesh(x, y, dat.T, cmap ='jet', vmin = 60, vmax = (70+2*self.cohFactor)) |
|
2686 | c = ax[0].pcolormesh(x, y, dat.T, cmap ='jet', vmin = 60, vmax = (70+2*self.cohFactor)) | |
| 2687 | ax[0].vlines(outs_lines,650,700, linestyles='dashed', label = 'outs', color='w') |
|
2687 | ax[0].vlines(outs_lines,650,700, linestyles='dashed', label = 'outs', color='w') | |
| 2688 | #fig.colorbar(c) |
|
2688 | #fig.colorbar(c) | |
| 2689 | ax[0].vlines(outlier_loc_index,700,750, linestyles='dashed', label = 'outs', color='r') |
|
2689 | ax[0].vlines(outlier_loc_index,700,750, linestyles='dashed', label = 'outs', color='r') | |
| 2690 |
|
2690 | |||
| 2691 | ax[1].hist(outs_lines,bins=my_bins) |
|
2691 | ax[1].hist(outs_lines,bins=my_bins) | |
| 2692 | if self.remYagi : |
|
2692 | if self.remYagi : | |
| 2693 | ax[0].vlines(indexesYagi,750,850, linestyles='dashed', label = 'yagi', color='m') |
|
2693 | ax[0].vlines(indexesYagi,750,850, linestyles='dashed', label = 'yagi', color='m') | |
| 2694 | plt.show() |
|
2694 | plt.show() | |
| 2695 |
|
2695 | |||
| 2696 |
|
2696 | |||
| 2697 |
|
2697 | |||
| 2698 |
|
2698 | |||
| 2699 | if self.remYagi and (self.currentTime < self.startTime and self.currentTime < self.endTime): |
|
2699 | if self.remYagi and (self.currentTime < self.startTime and self.currentTime < self.endTime): | |
| 2700 | outlier_loc_index = numpy.append(outlier_loc_index,indexesYagi) |
|
2700 | outlier_loc_index = numpy.append(outlier_loc_index,indexesYagi) | |
| 2701 |
|
2701 | |||
| 2702 | self.outliers_IDs_list = numpy.unique(outlier_loc_index) |
|
2702 | self.outliers_IDs_list = numpy.unique(outlier_loc_index) | |
| 2703 |
|
2703 | |||
| 2704 | #print("outs list: ", self.outliers_IDs_list) |
|
2704 | #print("outs list: ", self.outliers_IDs_list) | |
| 2705 | return self.__buffer_data |
|
2705 | return self.__buffer_data | |
| 2706 |
|
2706 | |||
| 2707 |
|
2707 | |||
| 2708 |
|
2708 | |||
| 2709 | def fillBuffer(self, data, datatime): |
|
2709 | def fillBuffer(self, data, datatime): | |
| 2710 |
|
2710 | |||
| 2711 | if self.__profIndex == 0: |
|
2711 | if self.__profIndex == 0: | |
| 2712 | self.__buffer_data = data.copy() |
|
2712 | self.__buffer_data = data.copy() | |
| 2713 |
|
2713 | |||
| 2714 | else: |
|
2714 | else: | |
| 2715 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles |
|
2715 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles | |
| 2716 | self.__profIndex += 1 |
|
2716 | self.__profIndex += 1 | |
| 2717 | self.__buffer_times.append(datatime) |
|
2717 | self.__buffer_times.append(datatime) | |
| 2718 |
|
2718 | |||
| 2719 | def getData(self, data, datatime=None): |
|
2719 | def getData(self, data, datatime=None): | |
| 2720 |
|
2720 | |||
| 2721 | if self.__profIndex == 0: |
|
2721 | if self.__profIndex == 0: | |
| 2722 | self.__initime = datatime |
|
2722 | self.__initime = datatime | |
| 2723 |
|
2723 | |||
| 2724 |
|
2724 | |||
| 2725 | self.__dataReady = False |
|
2725 | self.__dataReady = False | |
| 2726 |
|
2726 | |||
| 2727 | self.fillBuffer(data, datatime) |
|
2727 | self.fillBuffer(data, datatime) | |
| 2728 | dataBlock = None |
|
2728 | dataBlock = None | |
| 2729 |
|
2729 | |||
| 2730 | if self.__profIndex == self.n: |
|
2730 | if self.__profIndex == self.n: | |
| 2731 | #print("apnd : ",data) |
|
2731 | #print("apnd : ",data) | |
| 2732 | dataBlock = self.filterSatsProfiles() |
|
2732 | dataBlock = self.filterSatsProfiles() | |
| 2733 | self.__dataReady = True |
|
2733 | self.__dataReady = True | |
| 2734 |
|
2734 | |||
| 2735 | return dataBlock |
|
2735 | return dataBlock | |
| 2736 |
|
2736 | |||
| 2737 | if dataBlock is None: |
|
2737 | if dataBlock is None: | |
| 2738 | return None, None |
|
2738 | return None, None | |
| 2739 |
|
2739 | |||
| 2740 |
|
2740 | |||
| 2741 |
|
2741 | |||
| 2742 | return dataBlock |
|
2742 | return dataBlock | |
| 2743 |
|
2743 | |||
| 2744 | def releaseBlock(self): |
|
2744 | def releaseBlock(self): | |
| 2745 |
|
2745 | |||
| 2746 | if self.n % self.lenProfileOut != 0: |
|
2746 | if self.n % self.lenProfileOut != 0: | |
| 2747 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) |
|
2747 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) | |
| 2748 | return None |
|
2748 | return None | |
| 2749 |
|
2749 | |||
| 2750 | data = self.buffer[:,self.init_prof:self.end_prof:,:] #ch, prof, alt |
|
2750 | data = self.buffer[:,self.init_prof:self.end_prof:,:] #ch, prof, alt | |
| 2751 |
|
2751 | |||
| 2752 | self.init_prof = self.end_prof |
|
2752 | self.init_prof = self.end_prof | |
| 2753 | self.end_prof += self.lenProfileOut |
|
2753 | self.end_prof += self.lenProfileOut | |
| 2754 | #print("data release shape: ",dataOut.data.shape, self.end_prof) |
|
2754 | #print("data release shape: ",dataOut.data.shape, self.end_prof) | |
| 2755 | self.n_prof_released += 1 |
|
2755 | self.n_prof_released += 1 | |
| 2756 |
|
2756 | |||
| 2757 | return data |
|
2757 | return data | |
| 2758 |
|
2758 | |||
| 2759 | def run(self, dataOut, n=None, navg=0.9, nProfilesOut=1, profile_margin=50, th_hist_outlier=15,minHei=None,nBins=10, |
|
2759 | def run(self, dataOut, n=None, navg=0.9, nProfilesOut=1, profile_margin=50, th_hist_outlier=15,minHei=None,nBins=10, | |
| 2760 | maxHei=None, minRef=None, maxRef=None, debug=False, remYagi=False, nProfYagi = 0, offYagi=0, minHJULIA=None, maxHJULIA=None, |
|
2760 | maxHei=None, minRef=None, maxRef=None, debug=False, remYagi=False, nProfYagi = 0, offYagi=0, minHJULIA=None, maxHJULIA=None, | |
| 2761 | idate=None,startH=None,endH=None, thfactor=1): |
|
2761 | idate=None,startH=None,endH=None, thfactor=1): | |
| 2762 |
|
2762 | |||
| 2763 | if not self.isConfig: |
|
2763 | if not self.isConfig: | |
| 2764 | #print("init p idx: ", dataOut.profileIndex ) |
|
2764 | #print("init p idx: ", dataOut.profileIndex ) | |
| 2765 | self.setup(dataOut,n=n, navg=navg,profileMargin=profile_margin,thHistOutlier=th_hist_outlier,minHei=minHei, |
|
2765 | self.setup(dataOut,n=n, navg=navg,profileMargin=profile_margin,thHistOutlier=th_hist_outlier,minHei=minHei, | |
| 2766 | nBins=10, maxHei=maxHei, minRef=minRef, maxRef=maxRef, debug=debug, remYagi=remYagi, nProfYagi = nProfYagi, |
|
2766 | nBins=10, maxHei=maxHei, minRef=minRef, maxRef=maxRef, debug=debug, remYagi=remYagi, nProfYagi = nProfYagi, | |
| 2767 | offYagi=offYagi, minHJULIA=minHJULIA,maxHJULIA=maxHJULIA,idate=idate,startH=startH,endH=endH, thfactor=thfactor) |
|
2767 | offYagi=offYagi, minHJULIA=minHJULIA,maxHJULIA=maxHJULIA,idate=idate,startH=startH,endH=endH, thfactor=thfactor) | |
| 2768 |
|
2768 | |||
| 2769 | self.isConfig = True |
|
2769 | self.isConfig = True | |
| 2770 |
|
2770 | |||
| 2771 | dataBlock = None |
|
2771 | dataBlock = None | |
| 2772 | self.currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) |
|
2772 | self.currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) | |
| 2773 |
|
2773 | |||
| 2774 | if not dataOut.buffer_empty: #hay datos acumulados |
|
2774 | if not dataOut.buffer_empty: #hay datos acumulados | |
| 2775 |
|
2775 | |||
| 2776 | if self.init_prof == 0: |
|
2776 | if self.init_prof == 0: | |
| 2777 | self.n_prof_released = 0 |
|
2777 | self.n_prof_released = 0 | |
| 2778 | self.lenProfileOut = nProfilesOut |
|
2778 | self.lenProfileOut = nProfilesOut | |
| 2779 | dataOut.flagNoData = False |
|
2779 | dataOut.flagNoData = False | |
| 2780 | #print("tp 2 ",dataOut.data.shape) |
|
2780 | #print("tp 2 ",dataOut.data.shape) | |
| 2781 |
|
2781 | |||
| 2782 | self.init_prof = 0 |
|
2782 | self.init_prof = 0 | |
| 2783 | self.end_prof = self.lenProfileOut |
|
2783 | self.end_prof = self.lenProfileOut | |
| 2784 |
|
2784 | |||
| 2785 | dataOut.nProfiles = self.lenProfileOut |
|
2785 | dataOut.nProfiles = self.lenProfileOut | |
| 2786 | if nProfilesOut == 1: |
|
2786 | if nProfilesOut == 1: | |
| 2787 | dataOut.flagDataAsBlock = False |
|
2787 | dataOut.flagDataAsBlock = False | |
| 2788 | else: |
|
2788 | else: | |
| 2789 | dataOut.flagDataAsBlock = True |
|
2789 | dataOut.flagDataAsBlock = True | |
| 2790 | #print("prof: ",self.init_prof) |
|
2790 | #print("prof: ",self.init_prof) | |
| 2791 | dataOut.flagNoData = False |
|
2791 | dataOut.flagNoData = False | |
| 2792 | if numpy.isin(self.n_prof_released, self.outliers_IDs_list): |
|
2792 | if numpy.isin(self.n_prof_released, self.outliers_IDs_list): | |
| 2793 | #print("omitting: ", self.n_prof_released) |
|
2793 | #print("omitting: ", self.n_prof_released) | |
| 2794 | dataOut.flagNoData = True |
|
2794 | dataOut.flagNoData = True | |
| 2795 | dataOut.ippSeconds = self._ipp |
|
2795 | dataOut.ippSeconds = self._ipp | |
| 2796 | dataOut.utctime = self.first_utcBlock + self.init_prof*self._ipp |
|
2796 | dataOut.utctime = self.first_utcBlock + self.init_prof*self._ipp | |
| 2797 | # print("time: ", dataOut.utctime, self.first_utcBlock, self.init_prof,self._ipp,dataOut.ippSeconds) |
|
2797 | # print("time: ", dataOut.utctime, self.first_utcBlock, self.init_prof,self._ipp,dataOut.ippSeconds) | |
| 2798 | #dataOut.data = self.releaseBlock() |
|
2798 | #dataOut.data = self.releaseBlock() | |
| 2799 | #########################################################3 |
|
2799 | #########################################################3 | |
| 2800 | if self.n % self.lenProfileOut != 0: |
|
2800 | if self.n % self.lenProfileOut != 0: | |
| 2801 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) |
|
2801 | raise ValueError("lenProfileOut %d must be submultiple of nProfiles %d" %(self.lenProfileOut, self.n)) | |
| 2802 | return None |
|
2802 | return None | |
| 2803 |
|
2803 | |||
| 2804 | dataOut.data = None |
|
2804 | dataOut.data = None | |
| 2805 |
|
2805 | |||
| 2806 | if nProfilesOut == 1: |
|
2806 | if nProfilesOut == 1: | |
| 2807 | dataOut.data = self.buffer[:,self.end_prof-1,:] #ch, prof, alt |
|
2807 | dataOut.data = self.buffer[:,self.end_prof-1,:] #ch, prof, alt | |
| 2808 | else: |
|
2808 | else: | |
| 2809 | dataOut.data = self.buffer[:,self.init_prof:self.end_prof,:] #ch, prof, alt |
|
2809 | dataOut.data = self.buffer[:,self.init_prof:self.end_prof,:] #ch, prof, alt | |
| 2810 |
|
2810 | |||
| 2811 | self.init_prof = self.end_prof |
|
2811 | self.init_prof = self.end_prof | |
| 2812 | self.end_prof += self.lenProfileOut |
|
2812 | self.end_prof += self.lenProfileOut | |
| 2813 | #print("data release shape: ",dataOut.data.shape, self.end_prof, dataOut.flagNoData) |
|
2813 | #print("data release shape: ",dataOut.data.shape, self.end_prof, dataOut.flagNoData) | |
| 2814 | self.n_prof_released += 1 |
|
2814 | self.n_prof_released += 1 | |
| 2815 |
|
2815 | |||
| 2816 | if self.end_prof >= (self.n +self.lenProfileOut): |
|
2816 | if self.end_prof >= (self.n +self.lenProfileOut): | |
| 2817 |
|
2817 | |||
| 2818 | self.init_prof = 0 |
|
2818 | self.init_prof = 0 | |
| 2819 | self.__profIndex = 0 |
|
2819 | self.__profIndex = 0 | |
| 2820 | self.buffer = None |
|
2820 | self.buffer = None | |
| 2821 | dataOut.buffer_empty = True |
|
2821 | dataOut.buffer_empty = True | |
| 2822 | self.outliers_IDs_list = [] |
|
2822 | self.outliers_IDs_list = [] | |
| 2823 | self.n_prof_released = 0 |
|
2823 | self.n_prof_released = 0 | |
| 2824 | dataOut.flagNoData = False #enviar ultimo aunque sea outlier :( |
|
2824 | dataOut.flagNoData = False #enviar ultimo aunque sea outlier :( | |
| 2825 | #print("cleaning...", dataOut.buffer_empty) |
|
2825 | #print("cleaning...", dataOut.buffer_empty) | |
| 2826 | dataOut.profileIndex = self.__profIndex |
|
2826 | dataOut.profileIndex = self.__profIndex | |
| 2827 | #################################################################### |
|
2827 | #################################################################### | |
| 2828 | return dataOut |
|
2828 | return dataOut | |
| 2829 |
|
2829 | |||
| 2830 |
|
2830 | |||
| 2831 | #print("tp 223 ",dataOut.data.shape) |
|
2831 | #print("tp 223 ",dataOut.data.shape) | |
| 2832 | dataOut.flagNoData = True |
|
2832 | dataOut.flagNoData = True | |
| 2833 |
|
2833 | |||
| 2834 |
|
2834 | |||
| 2835 |
|
2835 | |||
| 2836 | try: |
|
2836 | try: | |
| 2837 | #dataBlock = self.getData(dataOut.data.reshape(self.nChannels,1,self.nHeights), dataOut.utctime) |
|
2837 | #dataBlock = self.getData(dataOut.data.reshape(self.nChannels,1,self.nHeights), dataOut.utctime) | |
| 2838 | dataBlock = self.getData(numpy.reshape(dataOut.data,(self.nChannels,1,self.nHeights)), dataOut.utctime) |
|
2838 | dataBlock = self.getData(numpy.reshape(dataOut.data,(self.nChannels,1,self.nHeights)), dataOut.utctime) | |
| 2839 | self.__count_exec +=1 |
|
2839 | self.__count_exec +=1 | |
| 2840 | except Exception as e: |
|
2840 | except Exception as e: | |
| 2841 | print("Error getting profiles data",self.__count_exec ) |
|
2841 | print("Error getting profiles data",self.__count_exec ) | |
| 2842 | print(e) |
|
2842 | print(e) | |
| 2843 | sys.exit() |
|
2843 | sys.exit() | |
| 2844 |
|
2844 | |||
| 2845 | if self.__dataReady: |
|
2845 | if self.__dataReady: | |
| 2846 | #print("omitting: ", len(self.outliers_IDs_list)) |
|
2846 | #print("omitting: ", len(self.outliers_IDs_list)) | |
| 2847 | self.__count_exec = 0 |
|
2847 | self.__count_exec = 0 | |
| 2848 | #dataOut.data = |
|
2848 | #dataOut.data = | |
| 2849 | #self.buffer = numpy.flip(dataBlock, axis=1) |
|
2849 | #self.buffer = numpy.flip(dataBlock, axis=1) | |
| 2850 | self.buffer = dataBlock |
|
2850 | self.buffer = dataBlock | |
| 2851 | self.first_utcBlock = self.__initime |
|
2851 | self.first_utcBlock = self.__initime | |
| 2852 | dataOut.utctime = self.__initime |
|
2852 | dataOut.utctime = self.__initime | |
| 2853 | dataOut.nProfiles = self.__profIndex |
|
2853 | dataOut.nProfiles = self.__profIndex | |
| 2854 | #dataOut.flagNoData = False |
|
2854 | #dataOut.flagNoData = False | |
| 2855 | self.init_prof = 0 |
|
2855 | self.init_prof = 0 | |
| 2856 | self.__profIndex = 0 |
|
2856 | self.__profIndex = 0 | |
| 2857 | self.__initime = None |
|
2857 | self.__initime = None | |
| 2858 | dataBlock = None |
|
2858 | dataBlock = None | |
| 2859 | self.__buffer_times = [] |
|
2859 | self.__buffer_times = [] | |
| 2860 | dataOut.error = False |
|
2860 | dataOut.error = False | |
| 2861 | dataOut.useInputBuffer = True |
|
2861 | dataOut.useInputBuffer = True | |
| 2862 | dataOut.buffer_empty = False |
|
2862 | dataOut.buffer_empty = False | |
| 2863 | #print("1 ch: {} prof: {} hs: {}".format(int(dataOut.nChannels),int(dataOut.nProfiles),int(dataOut.nHeights))) |
|
2863 | #print("1 ch: {} prof: {} hs: {}".format(int(dataOut.nChannels),int(dataOut.nProfiles),int(dataOut.nHeights))) | |
| 2864 |
|
2864 | |||
| 2865 |
|
2865 | |||
| 2866 |
|
2866 | |||
| 2867 | #print(self.__count_exec) |
|
2867 | #print(self.__count_exec) | |
| 2868 |
|
2868 | |||
| 2869 | return dataOut |
|
2869 | return dataOut | |
| 2870 |
|
2870 | |||
| 2871 |
|
2871 | |||
| 2872 |
|
2872 | |||
| 2873 |
|
2873 | |||
| 2874 | class remHeightsIppInterf(Operation): |
|
2874 | class remHeightsIppInterf(Operation): | |
| 2875 |
|
2875 | |||
| 2876 | def __init__(self, **kwargs): |
|
2876 | def __init__(self, **kwargs): | |
| 2877 |
|
2877 | |||
| 2878 |
|
2878 | |||
| 2879 | Operation.__init__(self, **kwargs) |
|
2879 | Operation.__init__(self, **kwargs) | |
| 2880 |
|
2880 | |||
| 2881 | self.isConfig = False |
|
2881 | self.isConfig = False | |
| 2882 |
|
2882 | |||
| 2883 | self.heights_indx = None |
|
2883 | self.heights_indx = None | |
| 2884 | self.heightsList = [] |
|
2884 | self.heightsList = [] | |
| 2885 |
|
2885 | |||
| 2886 | self.ipp1 = None |
|
2886 | self.ipp1 = None | |
| 2887 | self.ipp2 = None |
|
2887 | self.ipp2 = None | |
| 2888 | self.tx1 = None |
|
2888 | self.tx1 = None | |
| 2889 | self.tx2 = None |
|
2889 | self.tx2 = None | |
| 2890 | self.dh1 = None |
|
2890 | self.dh1 = None | |
| 2891 |
|
2891 | |||
| 2892 |
|
2892 | |||
| 2893 | def setup(self, dataOut, ipp1=None, ipp2=None, tx1=None, tx2=None, dh1=None, |
|
2893 | def setup(self, dataOut, ipp1=None, ipp2=None, tx1=None, tx2=None, dh1=None, | |
| 2894 | idate=None, startH=None, endH=None): |
|
2894 | idate=None, startH=None, endH=None): | |
| 2895 |
|
2895 | |||
| 2896 |
|
2896 | |||
| 2897 | self.ipp1 = ipp1 |
|
2897 | self.ipp1 = ipp1 | |
| 2898 | self.ipp2 = ipp2 |
|
2898 | self.ipp2 = ipp2 | |
| 2899 | self.tx1 = tx1 |
|
2899 | self.tx1 = tx1 | |
| 2900 | self.tx2 = tx2 |
|
2900 | self.tx2 = tx2 | |
| 2901 | self.dh1 = dh1 |
|
2901 | self.dh1 = dh1 | |
| 2902 |
|
2902 | |||
| 2903 | _maxIpp1R = dataOut.heightList.max() |
|
2903 | _maxIpp1R = dataOut.heightList.max() | |
| 2904 |
|
2904 | |||
| 2905 | _n_repeats = int(_maxIpp1R / ipp2) |
|
2905 | _n_repeats = int(_maxIpp1R / ipp2) | |
| 2906 | _init_hIntf = (tx1 + ipp2/2)+ dh1 |
|
2906 | _init_hIntf = (tx1 + ipp2/2)+ dh1 | |
| 2907 | _n_hIntf = int(tx2 / dh1) |
|
2907 | _n_hIntf = int(tx2 / dh1) | |
| 2908 |
|
2908 | |||
| 2909 | self.heightsList = [_init_hIntf+n*ipp2 for n in range(_n_repeats) ] |
|
2909 | self.heightsList = [_init_hIntf+n*ipp2 for n in range(_n_repeats) ] | |
| 2910 | heiList = dataOut.heightList |
|
2910 | heiList = dataOut.heightList | |
| 2911 | self.heights_indx = [getHei_index(h,h,heiList)[0] for h in self.heightsList] |
|
2911 | self.heights_indx = [getHei_index(h,h,heiList)[0] for h in self.heightsList] | |
| 2912 |
|
2912 | |||
| 2913 | self.heights_indx = [ numpy.asarray([k for k in range(_n_hIntf+2)])+(getHei_index(h,h,heiList)[0] -1) for h in self.heightsList] |
|
2913 | self.heights_indx = [ numpy.asarray([k for k in range(_n_hIntf+2)])+(getHei_index(h,h,heiList)[0] -1) for h in self.heightsList] | |
| 2914 |
|
2914 | |||
| 2915 | self.heights_indx = numpy.asarray(self.heights_indx ) |
|
2915 | self.heights_indx = numpy.asarray(self.heights_indx ) | |
| 2916 | self.isConfig = True |
|
2916 | self.isConfig = True | |
| 2917 | self.startTime = datetime.datetime.combine(idate,startH) |
|
2917 | self.startTime = datetime.datetime.combine(idate,startH) | |
| 2918 | self.endTime = datetime.datetime.combine(idate,endH) |
|
2918 | self.endTime = datetime.datetime.combine(idate,endH) | |
| 2919 | #print(self.startTime, self.endTime) |
|
2919 | #print(self.startTime, self.endTime) | |
| 2920 | #print("nrepeats: ", _n_repeats, " _nH: ",_n_hIntf ) |
|
2920 | #print("nrepeats: ", _n_repeats, " _nH: ",_n_hIntf ) | |
| 2921 |
|
2921 | |||
| 2922 | log.warning("Heights set to zero (km): ", self.name) |
|
2922 | log.warning("Heights set to zero (km): ", self.name) | |
| 2923 | log.warning(str((dataOut.heightList[self.heights_indx].flatten())), self.name) |
|
2923 | log.warning(str((dataOut.heightList[self.heights_indx].flatten())), self.name) | |
| 2924 | log.warning("Be careful with the selection of heights for noise calculation!") |
|
2924 | log.warning("Be careful with the selection of heights for noise calculation!") | |
| 2925 |
|
2925 | |||
| 2926 | def run(self, dataOut, ipp1=None, ipp2=None, tx1=None, tx2=None, dh1=None, idate=None, |
|
2926 | def run(self, dataOut, ipp1=None, ipp2=None, tx1=None, tx2=None, dh1=None, idate=None, | |
| 2927 | startH=None, endH=None): |
|
2927 | startH=None, endH=None): | |
| 2928 | #print(locals().values()) |
|
2928 | #print(locals().values()) | |
| 2929 | if None in locals().values(): |
|
2929 | if None in locals().values(): | |
| 2930 | log.warning('Missing kwargs, invalid values """None""" ', self.name) |
|
2930 | log.warning('Missing kwargs, invalid values """None""" ', self.name) | |
| 2931 | return dataOut |
|
2931 | return dataOut | |
| 2932 |
|
2932 | |||
| 2933 |
|
2933 | |||
| 2934 | if not self.isConfig: |
|
2934 | if not self.isConfig: | |
| 2935 | self.setup(dataOut, ipp1=ipp1, ipp2=ipp2, tx1=tx1, tx2=tx2, dh1=dh1, |
|
2935 | self.setup(dataOut, ipp1=ipp1, ipp2=ipp2, tx1=tx1, tx2=tx2, dh1=dh1, | |
| 2936 | idate=idate, startH=startH, endH=endH) |
|
2936 | idate=idate, startH=startH, endH=endH) | |
| 2937 |
|
2937 | |||
| 2938 | dataOut.flagProfilesByRange = False |
|
2938 | dataOut.flagProfilesByRange = False | |
| 2939 | currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) |
|
2939 | currentTime = datetime.datetime.fromtimestamp(dataOut.utctime) | |
| 2940 |
|
2940 | |||
| 2941 | if currentTime < self.startTime or currentTime > self.endTime: |
|
2941 | if currentTime < self.startTime or currentTime > self.endTime: | |
| 2942 | return dataOut |
|
2942 | return dataOut | |
| 2943 |
|
2943 | |||
| 2944 | for ch in range(dataOut.data.shape[0]): |
|
2944 | for ch in range(dataOut.data.shape[0]): | |
| 2945 |
|
2945 | |||
| 2946 | for hk in self.heights_indx.flatten(): |
|
2946 | for hk in self.heights_indx.flatten(): | |
| 2947 | if dataOut.data.ndim < 3: |
|
2947 | if dataOut.data.ndim < 3: | |
| 2948 | dataOut.data[ch,hk] = 0.0 + 0.0j |
|
2948 | dataOut.data[ch,hk] = 0.0 + 0.0j | |
| 2949 | else: |
|
2949 | else: | |
| 2950 | dataOut.data[ch,:,hk] = 0.0 + 0.0j |
|
2950 | dataOut.data[ch,:,hk] = 0.0 + 0.0j | |
| 2951 |
|
2951 | |||
| 2952 | dataOut.flagProfilesByRange = True |
|
2952 | dataOut.flagProfilesByRange = True | |
| 2953 |
|
2953 | |||
| 2954 | return dataOut |
|
2954 | return dataOut | |
| 2955 |
|
2955 | |||
| 2956 |
|
2956 | |||
| 2957 |
|
2957 | |||
| 2958 |
|
2958 | |||
| 2959 | class profiles2Block(Operation): |
|
2959 | class profiles2Block(Operation): | |
| 2960 | ''' |
|
2960 | ''' | |
| 2961 | Escrito: Joab Apaza |
|
2961 | Escrito: Joab Apaza | |
| 2962 |
|
2962 | |||
| 2963 | genera un bloque de perfiles |
|
2963 | genera un bloque de perfiles | |
| 2964 |
|
2964 | |||
| 2965 |
|
2965 | |||
| 2966 | Out: |
|
2966 | Out: | |
| 2967 | block |
|
2967 | block | |
| 2968 | ''' |
|
2968 | ''' | |
| 2969 |
|
2969 | |||
| 2970 | isConfig = False |
|
2970 | isConfig = False | |
| 2971 | __buffer_data = [] |
|
2971 | __buffer_data = [] | |
| 2972 | __buffer_times = [] |
|
2972 | __buffer_times = [] | |
| 2973 | __profIndex = 0 |
|
2973 | __profIndex = 0 | |
| 2974 | __byTime = False |
|
2974 | __byTime = False | |
| 2975 | __initime = None |
|
2975 | __initime = None | |
| 2976 | __lastdatatime = None |
|
2976 | __lastdatatime = None | |
| 2977 | buffer = None |
|
2977 | buffer = None | |
| 2978 | n = None |
|
2978 | n = None | |
| 2979 | __dataReady = False |
|
2979 | __dataReady = False | |
| 2980 | __nChannels = None |
|
2980 | __nChannels = None | |
| 2981 | __nHeis = None |
|
2981 | __nHeis = None | |
| 2982 |
|
2982 | |||
| 2983 | def __init__(self, **kwargs): |
|
2983 | def __init__(self, **kwargs): | |
| 2984 |
|
2984 | |||
| 2985 | Operation.__init__(self, **kwargs) |
|
2985 | Operation.__init__(self, **kwargs) | |
| 2986 | self.isConfig = False |
|
2986 | self.isConfig = False | |
| 2987 |
|
2987 | |||
| 2988 | def setup(self,n=None, timeInterval=None): |
|
2988 | def setup(self,n=None, timeInterval=None): | |
| 2989 |
|
2989 | |||
| 2990 | if n == None and timeInterval == None: |
|
2990 | if n == None and timeInterval == None: | |
| 2991 | raise ValueError("n or timeInterval should be specified ...") |
|
2991 | raise ValueError("n or timeInterval should be specified ...") | |
| 2992 |
|
2992 | |||
| 2993 | if n != None: |
|
2993 | if n != None: | |
| 2994 | self.n = n |
|
2994 | self.n = n | |
| 2995 | self.__byTime = False |
|
2995 | self.__byTime = False | |
| 2996 | else: |
|
2996 | else: | |
| 2997 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
2997 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
| 2998 | self.n = 9999 |
|
2998 | self.n = 9999 | |
| 2999 | self.__byTime = True |
|
2999 | self.__byTime = True | |
| 3000 |
|
3000 | |||
| 3001 | self.__profIndex = 0 |
|
3001 | self.__profIndex = 0 | |
| 3002 |
|
3002 | |||
| 3003 |
|
3003 | |||
| 3004 | def fillBuffer(self, data, datatime): |
|
3004 | def fillBuffer(self, data, datatime): | |
| 3005 |
|
3005 | |||
| 3006 | if self.__profIndex == 0: |
|
3006 | if self.__profIndex == 0: | |
| 3007 | self.__buffer_data = data.copy() |
|
3007 | self.__buffer_data = data.copy() | |
| 3008 |
|
3008 | |||
| 3009 | else: |
|
3009 | else: | |
| 3010 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles |
|
3010 | self.__buffer_data = numpy.concatenate((self.__buffer_data,data), axis=1)#en perfiles | |
| 3011 | self.__profIndex += 1 |
|
3011 | self.__profIndex += 1 | |
| 3012 | self.__buffer_times.append(datatime) |
|
3012 | self.__buffer_times.append(datatime) | |
| 3013 |
|
3013 | |||
| 3014 | def getData(self, data, datatime=None): |
|
3014 | def getData(self, data, datatime=None): | |
| 3015 | if self.__initime == None: |
|
3015 | if self.__initime == None: | |
| 3016 | self.__initime = datatime |
|
3016 | self.__initime = datatime | |
| 3017 |
|
3017 | |||
| 3018 | if data.ndim < 3: |
|
3018 | if data.ndim < 3: | |
| 3019 | data = data.reshape(self.__nChannels,1,self.__nHeis ) |
|
3019 | data = data.reshape(self.__nChannels,1,self.__nHeis ) | |
| 3020 |
|
3020 | |||
| 3021 | if self.__byTime: |
|
3021 | if self.__byTime: | |
| 3022 | dataBlock = self.byTime(data, datatime) |
|
3022 | dataBlock = self.byTime(data, datatime) | |
| 3023 | else: |
|
3023 | else: | |
| 3024 | dataBlock = self.byProfiles(data, datatime) |
|
3024 | dataBlock = self.byProfiles(data, datatime) | |
| 3025 |
|
3025 | |||
| 3026 |
|
3026 | |||
| 3027 | self.__lastdatatime = datatime |
|
3027 | self.__lastdatatime = datatime | |
| 3028 |
|
3028 | |||
| 3029 | if dataBlock is None: |
|
3029 | if dataBlock is None: | |
| 3030 | return None, None |
|
3030 | return None, None | |
| 3031 |
|
3031 | |||
| 3032 | return dataBlock, self.__buffer_times |
|
3032 | return dataBlock, self.__buffer_times | |
| 3033 |
|
3033 | |||
| 3034 | def byProfiles(self, data, datatime): |
|
3034 | def byProfiles(self, data, datatime): | |
| 3035 |
|
3035 | |||
| 3036 | self.__dataReady = False |
|
3036 | self.__dataReady = False | |
| 3037 | dataBlock = None |
|
3037 | dataBlock = None | |
| 3038 | # n = None |
|
3038 | # n = None | |
| 3039 | # print data |
|
3039 | # print data | |
| 3040 | # raise |
|
3040 | # raise | |
| 3041 | self.fillBuffer(data, datatime) |
|
3041 | self.fillBuffer(data, datatime) | |
| 3042 |
|
3042 | |||
| 3043 | if self.__profIndex == self.n: |
|
3043 | if self.__profIndex == self.n: | |
| 3044 | dataBlock = self.__buffer_data |
|
3044 | dataBlock = self.__buffer_data | |
| 3045 | self.__dataReady = True |
|
3045 | self.__dataReady = True | |
| 3046 |
|
3046 | |||
| 3047 | return dataBlock |
|
3047 | return dataBlock | |
| 3048 |
|
3048 | |||
| 3049 | def byTime(self, data, datatime): |
|
3049 | def byTime(self, data, datatime): | |
| 3050 |
|
3050 | |||
| 3051 | self.__dataReady = False |
|
3051 | self.__dataReady = False | |
| 3052 | dataBlock = None |
|
3052 | dataBlock = None | |
| 3053 | n = None |
|
3053 | n = None | |
| 3054 |
|
3054 | |||
| 3055 | self.fillBuffer(data, datatime) |
|
3055 | self.fillBuffer(data, datatime) | |
| 3056 |
|
3056 | |||
| 3057 | if (datatime - self.__initime) >= self.__integrationtime: |
|
3057 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 3058 | dataBlock = self.__buffer_data |
|
3058 | dataBlock = self.__buffer_data | |
| 3059 | self.n = self.__profIndex |
|
3059 | self.n = self.__profIndex | |
| 3060 | self.__dataReady = True |
|
3060 | self.__dataReady = True | |
| 3061 |
|
3061 | |||
| 3062 | return dataBlock |
|
3062 | return dataBlock | |
| 3063 |
|
3063 | |||
| 3064 |
|
3064 | |||
| 3065 | def run(self, dataOut, n=None, timeInterval=None, **kwargs): |
|
3065 | def run(self, dataOut, n=None, timeInterval=None, **kwargs): | |
| 3066 |
|
3066 | |||
| 3067 | if not self.isConfig: |
|
3067 | if not self.isConfig: | |
| 3068 | self.setup(n=n, timeInterval=timeInterval, **kwargs) |
|
3068 | self.setup(n=n, timeInterval=timeInterval, **kwargs) | |
| 3069 | self.__nChannels = dataOut.nChannels |
|
3069 | self.__nChannels = dataOut.nChannels | |
| 3070 | self.__nHeis = len(dataOut.heightList) |
|
3070 | self.__nHeis = len(dataOut.heightList) | |
| 3071 | self.isConfig = True |
|
3071 | self.isConfig = True | |
| 3072 |
|
3072 | |||
| 3073 | if dataOut.flagDataAsBlock: |
|
3073 | if dataOut.flagDataAsBlock: | |
| 3074 | """ |
|
3074 | """ | |
| 3075 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
3075 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 3076 | """ |
|
3076 | """ | |
| 3077 | raise ValueError("The data is already a block") |
|
3077 | raise ValueError("The data is already a block") | |
| 3078 | return |
|
3078 | return | |
| 3079 | else: |
|
3079 | else: | |
| 3080 |
|
3080 | |||
| 3081 | dataBlock, timeBlock = self.getData(dataOut.data, dataOut.utctime) |
|
3081 | dataBlock, timeBlock = self.getData(dataOut.data, dataOut.utctime) | |
| 3082 |
|
3082 | |||
| 3083 |
|
3083 | |||
| 3084 | # print(dataOut.data.shape) |
|
3084 | # print(dataOut.data.shape) | |
| 3085 | # dataOut.timeInterval *= n |
|
3085 | # dataOut.timeInterval *= n | |
| 3086 | dataOut.flagNoData = True |
|
3086 | dataOut.flagNoData = True | |
| 3087 |
|
3087 | |||
| 3088 | if self.__dataReady: |
|
3088 | if self.__dataReady: | |
| 3089 | dataOut.data = dataBlock |
|
3089 | dataOut.data = dataBlock | |
| 3090 | dataOut.flagDataAsBlock = True |
|
3090 | dataOut.flagDataAsBlock = True | |
| 3091 | dataOut.utctime = timeBlock[-1] |
|
3091 | dataOut.utctime = timeBlock[-1] | |
| 3092 | dataOut.nProfiles = self.__profIndex |
|
3092 | dataOut.nProfiles = self.__profIndex | |
| 3093 | # print avgdata, avgdatatime |
|
3093 | # print avgdata, avgdatatime | |
| 3094 | # raise |
|
3094 | # raise | |
| 3095 | dataOut.flagNoData = False |
|
3095 | dataOut.flagNoData = False | |
| 3096 | self.__profIndex = 0 |
|
3096 | self.__profIndex = 0 | |
| 3097 | self.__initime = None |
|
3097 | self.__initime = None | |
| 3098 | #update Processing Header: |
|
3098 | #update Processing Header: | |
| 3099 | # print(dataOut.data.shape) |
|
3099 | # print(dataOut.data.shape) | |
| 3100 |
|
3100 | |||
| 3101 | return dataOut |
|
3101 | return dataOut | |
| 3102 |
|
3102 | |||
| 3103 |
|
3103 | |||
| 3104 | class remFaradayProfiles(Operation): |
|
3104 | class remFaradayProfiles(Operation): | |
| 3105 |
|
3105 | |||
| 3106 | def __init__(self, **kwargs): |
|
3106 | def __init__(self, **kwargs): | |
| 3107 |
|
3107 | |||
| 3108 |
|
3108 | |||
| 3109 | Operation.__init__(self, **kwargs) |
|
3109 | Operation.__init__(self, **kwargs) | |
| 3110 |
|
3110 | |||
| 3111 | self.isConfig = False |
|
3111 | self.isConfig = False | |
| 3112 |
|
3112 | |||
| 3113 | self.nprofile2 = 0 |
|
3113 | self.nprofile2 = 0 | |
| 3114 | self.profile = 0 |
|
3114 | self.profile = 0 | |
| 3115 | self.flagRun = False |
|
3115 | self.flagRun = False | |
| 3116 | self.flagRemove = False |
|
3116 | self.flagRemove = False | |
| 3117 | self.k = 0 |
|
3117 | self.k = 0 | |
| 3118 |
|
3118 | |||
| 3119 |
def setup(self, channel,nChannels=5, nProfiles=300,nBlocks=100, nIpp2= |
|
3119 | def setup(self, channel,nChannels=5, nProfiles=300,nBlocks=100, nIpp2=300, nTx2=132, nTaus=22, offTaus=14, iTaus=8, | |
| 3120 | nfft=1): |
|
3120 | nfft=1): | |
| 3121 | ''' |
|
3121 | ''' | |
| 3122 | nProfiles = amisr profiles per block -> raw data |
|
3122 | nProfiles = amisr profiles per block -> raw data | |
| 3123 | nIpp1 = number of profiles in one AMISR sync |
|
3123 | nIpp1 = number of profiles in one AMISR sync | |
| 3124 | nIpp2 = number of profiles in one Jicamarca sync |
|
3124 | nIpp2 = number of profiles in one Jicamarca sync | |
| 3125 | nTx2 = number of profiles transmited for Faraday Experiment |
|
3125 | nTx2 = number of profiles transmited for Faraday Experiment | |
| 3126 | nTaus = Total profiles for lags |
|
3126 | nTaus = Total profiles for lags | |
| 3127 | offTaus = where starts the interference, (profile) |
|
3127 | offTaus = where starts the interference, (profile) | |
| 3128 | iTaus = lenght of the interference |
|
3128 | iTaus = lenght of the interference | |
| 3129 | irepeat = number of repetition of the Taus |
|
3129 | irepeat = number of repetition of the Taus | |
| 3130 | ''' |
|
3130 | ''' | |
| 3131 | self.nIpp2 = nIpp2 |
|
3131 | self.nIpp2 = nIpp2 | |
| 3132 | self.channel = channel |
|
3132 | self.channel = channel | |
| 3133 | self.nChannels = nChannels |
|
3133 | self.nChannels = nChannels | |
| 3134 | self.nTx2 = nTx2 |
|
3134 | self.nTx2 = nTx2 | |
| 3135 | self.nTaus = nTaus |
|
3135 | self.nTaus = nTaus | |
| 3136 |
|
3136 | |||
| 3137 |
|
3137 | |||
| 3138 | booldataset = numpy.ones( (nBlocks, nProfiles) ) |
|
3138 | booldataset = numpy.ones( (nBlocks, nProfiles) ) | |
| 3139 | self.profilesFlag = None |
|
3139 | self.profilesFlag = None | |
| 3140 | #marking the afected profiles |
|
3140 | #marking the afected profiles | |
| 3141 | f_iTaus=False |
|
3141 | f_iTaus=False | |
| 3142 | f_ntx = False |
|
3142 | f_ntx = False | |
| 3143 | fi = 0 |
|
3143 | fi = 0 | |
| 3144 | k = 0 |
|
3144 | k = 0 | |
| 3145 | kt =0 |
|
3145 | kt =0 | |
| 3146 | fi_reps = 0 |
|
3146 | fi_reps = 0 | |
| 3147 | for i in range(nBlocks): |
|
3147 | for i in range(nBlocks): | |
| 3148 | for j in range(nProfiles): |
|
3148 | for j in range(nProfiles): | |
| 3149 | # fi 0---nTaus |
|
3149 | # fi 0---nTaus | |
| 3150 | # |
|
3150 | # | |
| 3151 | if k%nIpp2==0: #each sync PPs or 2, 3, or 5 |
|
3151 | if k%nIpp2==0: #each sync PPs or 2, 3, or 5 | |
| 3152 | f_ntx = True |
|
3152 | f_ntx = True | |
| 3153 | kt = 0 |
|
3153 | kt = 0 | |
| 3154 | #print(k, fi, j, f_iTaus) |
|
|||
| 3155 | if f_ntx: |
|
3154 | if f_ntx: | |
| 3156 |
|
3155 | |||
| 3157 | if kt%nTaus==0: #each sequence of Taus |
|
3156 | if kt%nTaus==0: #each sequence of Taus | |
| 3158 | f_iTaus = True |
|
3157 | f_iTaus = True | |
| 3159 | fi = 0 |
|
3158 | fi = 0 | |
| 3160 |
|
3159 | |||
| 3161 | if f_iTaus: |
|
3160 | if f_iTaus: | |
| 3162 | if fi > offTaus-1: |
|
3161 | if fi > offTaus-1: | |
| 3163 | booldataset[i, j]=0 #Afected profile |
|
3162 | booldataset[i, j]=0 #Afected profile | |
| 3164 | fi += 1 |
|
3163 | fi += 1 | |
| 3165 | if fi == nTaus-1: #restart the taus sequence |
|
3164 | if fi == nTaus-1: #restart the taus sequence | |
| 3166 | fi = 0 |
|
3165 | fi = 0 | |
| 3167 | f_iTaus = False |
|
3166 | f_iTaus = False | |
| 3168 | fi_reps += 1 |
|
3167 | fi_reps += 1 | |
| 3169 | if fi_reps == (nTx2/nTaus): |
|
3168 | if fi_reps == (nTx2/nTaus): | |
| 3170 | fi = 0 |
|
3169 | fi = 0 | |
| 3171 | #print("AQUI, ", fi_reps, k, fi) |
|
|||
| 3172 | fi_reps = 0 |
|
3170 | fi_reps = 0 | |
| 3173 | f_ntx=False |
|
3171 | f_ntx=False | |
| 3174 | # if i < 1: |
|
|||
| 3175 | # print(fi, kt) |
|
|||
| 3176 | kt += 1 |
|
3172 | kt += 1 | |
| 3177 | k += 1 |
|
3173 | k += 1 | |
| 3178 |
|
3174 | |||
| 3179 | # fig = plt.figure() |
|
3175 | # fig = plt.figure() | |
| 3180 | # ax = fig.add_subplot(111) |
|
3176 | # ax = fig.add_subplot(111) | |
| 3181 | # cax = ax.pcolormesh(booldataset, cmap='plasma') |
|
3177 | # cax = ax.pcolormesh(booldataset, cmap='plasma') | |
| 3182 | # cbar = fig.colorbar(cax) |
|
3178 | # cbar = fig.colorbar(cax) | |
| 3183 | # plt.show() |
|
3179 | # plt.show() | |
| 3184 |
|
3180 | |||
| 3185 |
|
3181 | |||
| 3186 | #print ("AQUI") |
|
|||
| 3187 | #reshape the Flag as AMISR reader |
|
3182 | #reshape the Flag as AMISR reader | |
| 3188 |
|
3183 | |||
| 3189 | profPerCH = int( (nProfiles) / (nfft*nChannels)) |
|
3184 | profPerCH = int( (nProfiles) / (nfft*nChannels)) | |
| 3190 | new_block = numpy.empty( (nBlocks, nChannels, int(nProfiles/nChannels) ) ) |
|
3185 | new_block = numpy.empty( (nBlocks, nChannels, int(nProfiles/nChannels) ) ) | |
| 3191 | # print(new_block.shape, profPerCH) |
|
3186 | # print(new_block.shape, profPerCH) | |
| 3192 | for thisChannel in range(nChannels): |
|
3187 | for thisChannel in range(nChannels): | |
| 3193 |
|
3188 | |||
| 3194 | ich = thisChannel |
|
3189 | ich = thisChannel | |
| 3195 |
|
3190 | |||
| 3196 | idx_ch = [nfft*(ich + nChannels*k) for k in range(profPerCH)] |
|
3191 | idx_ch = [nfft*(ich + nChannels*k) for k in range(profPerCH)] | |
| 3197 | #print(idx_ch) |
|
3192 | #print(idx_ch) | |
| 3198 | if nfft > 1: |
|
3193 | if nfft > 1: | |
| 3199 | aux = [numpy.arange(i, i+nfft) for i in idx_ch] |
|
3194 | aux = [numpy.arange(i, i+nfft) for i in idx_ch] | |
| 3200 | idx_ch = None |
|
3195 | idx_ch = None | |
| 3201 | idx_ch =aux |
|
3196 | idx_ch =aux | |
| 3202 | idx_ch = numpy.array(idx_ch, dtype=int).flatten() |
|
3197 | idx_ch = numpy.array(idx_ch, dtype=int).flatten() | |
| 3203 | else: |
|
3198 | else: | |
| 3204 | idx_ch = numpy.array(idx_ch, dtype=int) |
|
3199 | idx_ch = numpy.array(idx_ch, dtype=int) | |
| 3205 |
|
3200 | |||
| 3206 | new_block[:,ich,:] = booldataset[:,idx_ch] |
|
3201 | new_block[:,ich,:] = booldataset[:,idx_ch] | |
| 3207 |
|
3202 | |||
| 3208 | new_block = numpy.transpose(new_block, (1,0,2)) |
|
3203 | new_block = numpy.transpose(new_block, (1,0,2)) | |
| 3209 | new_block = numpy.reshape(new_block, (nChannels,-1)) |
|
3204 | #new_block = numpy.reshape(new_block, (nChannels,-1)) | |
| 3210 |
|
|
3205 | new_block = numpy.reshape(new_block, (nChannels,profPerCH*nBlocks)) | |
| 3211 | self.profilesFlag = new_block.copy() |
|
3206 | self.profilesFlag = new_block.copy() | |
| 3212 |
|
3207 | |||
| 3213 | # fig = plt.figure() |
|
3208 | # fig = plt.figure() | |
| 3214 | # ax = fig.add_subplot(111) |
|
3209 | # ax = fig.add_subplot(111) | |
| 3215 | # cax = ax.pcolormesh(new_block, cmap='plasma') |
|
3210 | # cax = ax.pcolormesh(new_block, cmap='plasma') | |
| 3216 | # cbar = fig.colorbar(cax) |
|
3211 | # cbar = fig.colorbar(cax) | |
| 3217 | # plt.show() |
|
3212 | # plt.show() | |
| 3218 |
|
3213 | |||
| 3219 | self.isConfig = True |
|
3214 | self.isConfig = True | |
| 3220 |
|
3215 | |||
| 3221 | #print(self.profilesFlag.shape) |
|
|||
| 3222 |
|
3216 | |||
| 3223 | def run(self,dataOut, channel=0, nChannels=5, nProfiles=300,nBlocks=100,nIpp1=100, |
|
3217 | def run(self,dataOut, channel=0, nChannels=5, nProfiles=300,nBlocks=100,nIpp1=100, | |
| 3224 | nIpp2=300, nTx2=132, nTaus=22, offTaus=8, iTaus=14, nfft=1 ,offIpp=0): |
|
3218 | nIpp2=300, nTx2=132, nTaus=22, offTaus=8, iTaus=14, nfft=1 ,offIpp=0): | |
| 3225 |
|
3219 | |||
| 3226 | dataOut.flagNoData = False |
|
3220 | dataOut.flagNoData = False | |
| 3227 |
|
3221 | |||
| 3228 | if not self.isConfig: |
|
3222 | if not self.isConfig: | |
| 3229 | self.setup(channel,nChannels=nChannels, nProfiles=nProfiles,nBlocks=nBlocks, nIpp2=nIpp2, |
|
3223 | self.setup(channel,nChannels=nChannels, nProfiles=nProfiles,nBlocks=nBlocks, nIpp2=nIpp2, | |
| 3230 | nTx2=nTx2, nTaus=nTaus, offTaus=offTaus, iTaus=iTaus, nfft=nfft) |
|
3224 | nTx2=nTx2, nTaus=nTaus, offTaus=offTaus, iTaus=iTaus, nfft=nfft) | |
| 3231 | #print("Setup Done") |
|
3225 | #print("Setup Done") | |
| 3232 | #print(offIpp*nIpp1/nChannels) |
|
3226 | #print(offIpp*nIpp1/nChannels) | |
| 3233 | if not self.flagRun: |
|
3227 | if not self.flagRun: | |
| 3234 | if self.nprofile2 < offIpp*nIpp1/nChannels : |
|
3228 | if self.nprofile2 < offIpp*nIpp1/nChannels : | |
| 3235 | self.nprofile2 += 1 |
|
3229 | self.nprofile2 += 1 | |
| 3236 | return dataOut |
|
3230 | return dataOut | |
| 3237 | else: |
|
3231 | else: | |
| 3238 | self.flagRun = True |
|
3232 | self.flagRun = True | |
| 3239 | self.profile = 0 |
|
3233 | self.profile = 0 | |
| 3240 |
|
||||
| 3241 |
|
3234 | |||
| 3242 | #check profile ## Faraday interference |
|
3235 | #check profile ## Faraday interference | |
| 3243 | if self.profilesFlag[channel, self.profile]==0: |
|
3236 | if self.profilesFlag[channel, self.profile]==0: | |
| 3244 | dataOut.flagNoData = True # do not pass this profile |
|
3237 | dataOut.flagNoData = True # do not pass this profile | |
| 3245 | # print(self.nprofile, dataOut.flagNoData) |
|
3238 | ||
| 3246 | #print(self.nprofile2, self.profile, dataOut.flagNoData) |
|
|||
| 3247 | self.profile +=1 |
|
3239 | self.profile +=1 | |
| 3248 | # if self.profile == int((nProfiles*nBlocks)/self.nChannels): |
|
3240 | ||
| 3249 | # self.flagRun=False |
|
|||
| 3250 | # self.profile = 0 |
|
|||
| 3251 |
|
3241 | |||
| 3252 | self.nprofile2 +=1 |
|
3242 | self.nprofile2 +=1 | |
| 3253 |
|
3243 | |||
| 3254 | if self.nprofile2 == int((nProfiles*nBlocks)/self.nChannels): |
|
3244 | if self.nprofile2 == int((nProfiles*nBlocks)/self.nChannels): | |
| 3255 | self.nprofile2 = 0 |
|
3245 | self.nprofile2 = 0 | |
| 3256 | self.profile = 0 |
|
3246 | self.profile = 0 | |
| 3257 | self.flagRun = False |
|
3247 | self.flagRun = False | |
| 3258 |
|
3248 | |||
| 3259 | return dataOut No newline at end of file |
|
3249 | return dataOut | |
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