| @@ -1,1861 +1,1885 | |||||
| 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 time import time |
|
7 | from time import time | |
| 8 |
|
8 | |||
| 9 |
|
9 | |||
| 10 |
|
10 | |||
| 11 | class VoltageProc(ProcessingUnit): |
|
11 | class VoltageProc(ProcessingUnit): | |
| 12 |
|
12 | |||
| 13 | def __init__(self): |
|
13 | def __init__(self): | |
| 14 |
|
14 | |||
| 15 | ProcessingUnit.__init__(self) |
|
15 | ProcessingUnit.__init__(self) | |
| 16 |
|
16 | |||
| 17 | self.dataOut = Voltage() |
|
17 | self.dataOut = Voltage() | |
| 18 | self.flip = 1 |
|
18 | self.flip = 1 | |
| 19 | self.setupReq = False |
|
19 | self.setupReq = False | |
| 20 |
|
20 | |||
| 21 | def run(self): |
|
21 | def run(self): | |
| 22 |
|
22 | |||
| 23 | if self.dataIn.type == 'AMISR': |
|
23 | if self.dataIn.type == 'AMISR': | |
| 24 | self.__updateObjFromAmisrInput() |
|
24 | self.__updateObjFromAmisrInput() | |
| 25 |
|
25 | |||
| 26 | if self.dataIn.type == 'Voltage': |
|
26 | if self.dataIn.type == 'Voltage': | |
| 27 | self.dataOut.copy(self.dataIn) |
|
27 | self.dataOut.copy(self.dataIn) | |
| 28 |
|
28 | |||
| 29 | def __updateObjFromAmisrInput(self): |
|
29 | def __updateObjFromAmisrInput(self): | |
| 30 |
|
30 | |||
| 31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
31 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
32 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
33 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 35 |
|
35 | |||
| 36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
36 | self.dataOut.flagNoData = self.dataIn.flagNoData | |
| 37 | self.dataOut.data = self.dataIn.data |
|
37 | self.dataOut.data = self.dataIn.data | |
| 38 | self.dataOut.utctime = self.dataIn.utctime |
|
38 | self.dataOut.utctime = self.dataIn.utctime | |
| 39 | self.dataOut.channelList = self.dataIn.channelList |
|
39 | self.dataOut.channelList = self.dataIn.channelList | |
| 40 | #self.dataOut.timeInterval = self.dataIn.timeInterval |
|
40 | #self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 41 | self.dataOut.heightList = self.dataIn.heightList |
|
41 | self.dataOut.heightList = self.dataIn.heightList | |
| 42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
42 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
| 43 |
|
43 | |||
| 44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
44 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 46 | self.dataOut.frequency = self.dataIn.frequency |
|
46 | self.dataOut.frequency = self.dataIn.frequency | |
| 47 |
|
47 | |||
| 48 | self.dataOut.azimuth = self.dataIn.azimuth |
|
48 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 49 | self.dataOut.zenith = self.dataIn.zenith |
|
49 | self.dataOut.zenith = self.dataIn.zenith | |
| 50 |
|
50 | |||
| 51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 54 |
|
54 | |||
| 55 |
|
55 | |||
| 56 | class selectChannels(Operation): |
|
56 | class selectChannels(Operation): | |
| 57 |
|
57 | |||
| 58 | def run(self, dataOut, channelList): |
|
58 | def run(self, dataOut, channelList): | |
| 59 |
|
59 | |||
| 60 | channelIndexList = [] |
|
60 | channelIndexList = [] | |
| 61 | self.dataOut = dataOut |
|
61 | self.dataOut = dataOut | |
| 62 | for channel in channelList: |
|
62 | for channel in channelList: | |
| 63 | if channel not in self.dataOut.channelList: |
|
63 | if channel not in self.dataOut.channelList: | |
| 64 | raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList))) |
|
64 | raise ValueError("Channel %d is not in %s" %(channel, str(self.dataOut.channelList))) | |
| 65 |
|
65 | |||
| 66 | index = self.dataOut.channelList.index(channel) |
|
66 | index = self.dataOut.channelList.index(channel) | |
| 67 | channelIndexList.append(index) |
|
67 | channelIndexList.append(index) | |
| 68 | self.selectChannelsByIndex(channelIndexList) |
|
68 | self.selectChannelsByIndex(channelIndexList) | |
| 69 | return self.dataOut |
|
69 | return self.dataOut | |
| 70 |
|
70 | |||
| 71 | def selectChannelsByIndex(self, channelIndexList): |
|
71 | def selectChannelsByIndex(self, channelIndexList): | |
| 72 | """ |
|
72 | """ | |
| 73 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
73 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
| 74 |
|
74 | |||
| 75 | Input: |
|
75 | Input: | |
| 76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
76 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
| 77 |
|
77 | |||
| 78 | Affected: |
|
78 | Affected: | |
| 79 | self.dataOut.data |
|
79 | self.dataOut.data | |
| 80 | self.dataOut.channelIndexList |
|
80 | self.dataOut.channelIndexList | |
| 81 | self.dataOut.nChannels |
|
81 | self.dataOut.nChannels | |
| 82 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
82 | self.dataOut.m_ProcessingHeader.totalSpectra | |
| 83 | self.dataOut.systemHeaderObj.numChannels |
|
83 | self.dataOut.systemHeaderObj.numChannels | |
| 84 | self.dataOut.m_ProcessingHeader.blockSize |
|
84 | self.dataOut.m_ProcessingHeader.blockSize | |
| 85 |
|
85 | |||
| 86 | Return: |
|
86 | Return: | |
| 87 | None |
|
87 | None | |
| 88 | """ |
|
88 | """ | |
| 89 |
|
89 | |||
| 90 | for channelIndex in channelIndexList: |
|
90 | for channelIndex in channelIndexList: | |
| 91 | if channelIndex not in self.dataOut.channelIndexList: |
|
91 | if channelIndex not in self.dataOut.channelIndexList: | |
| 92 | raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) |
|
92 | raise ValueError("The value %d in channelIndexList is not valid" %channelIndex) | |
| 93 |
|
93 | |||
| 94 | if self.dataOut.type == 'Voltage': |
|
94 | if self.dataOut.type == 'Voltage': | |
| 95 | if self.dataOut.flagDataAsBlock: |
|
95 | if self.dataOut.flagDataAsBlock: | |
| 96 | """ |
|
96 | """ | |
| 97 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
97 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 98 | """ |
|
98 | """ | |
| 99 | data = self.dataOut.data[channelIndexList,:,:] |
|
99 | data = self.dataOut.data[channelIndexList,:,:] | |
| 100 | else: |
|
100 | else: | |
| 101 | data = self.dataOut.data[channelIndexList,:] |
|
101 | data = self.dataOut.data[channelIndexList,:] | |
| 102 |
|
102 | |||
| 103 | self.dataOut.data = data |
|
103 | self.dataOut.data = data | |
| 104 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
104 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 105 | self.dataOut.channelList = range(len(channelIndexList)) |
|
105 | self.dataOut.channelList = range(len(channelIndexList)) | |
| 106 |
|
106 | |||
| 107 | elif self.dataOut.type == 'Spectra': |
|
107 | elif self.dataOut.type == 'Spectra': | |
| 108 | data_spc = self.dataOut.data_spc[channelIndexList, :] |
|
108 | data_spc = self.dataOut.data_spc[channelIndexList, :] | |
| 109 | data_dc = self.dataOut.data_dc[channelIndexList, :] |
|
109 | data_dc = self.dataOut.data_dc[channelIndexList, :] | |
| 110 |
|
110 | |||
| 111 | self.dataOut.data_spc = data_spc |
|
111 | self.dataOut.data_spc = data_spc | |
| 112 | self.dataOut.data_dc = data_dc |
|
112 | self.dataOut.data_dc = data_dc | |
| 113 |
|
113 | |||
| 114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
114 | # self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
| 115 | self.dataOut.channelList = range(len(channelIndexList)) |
|
115 | self.dataOut.channelList = range(len(channelIndexList)) | |
| 116 | self.__selectPairsByChannel(channelIndexList) |
|
116 | self.__selectPairsByChannel(channelIndexList) | |
| 117 |
|
117 | |||
| 118 | return 1 |
|
118 | return 1 | |
| 119 |
|
119 | |||
| 120 | def __selectPairsByChannel(self, channelList=None): |
|
120 | def __selectPairsByChannel(self, channelList=None): | |
| 121 |
|
121 | |||
| 122 | if channelList == None: |
|
122 | if channelList == None: | |
| 123 | return |
|
123 | return | |
| 124 |
|
124 | |||
| 125 | pairsIndexListSelected = [] |
|
125 | pairsIndexListSelected = [] | |
| 126 | for pairIndex in self.dataOut.pairsIndexList: |
|
126 | for pairIndex in self.dataOut.pairsIndexList: | |
| 127 | # First pair |
|
127 | # First pair | |
| 128 | if self.dataOut.pairsList[pairIndex][0] not in channelList: |
|
128 | if self.dataOut.pairsList[pairIndex][0] not in channelList: | |
| 129 | continue |
|
129 | continue | |
| 130 | # Second pair |
|
130 | # Second pair | |
| 131 | if self.dataOut.pairsList[pairIndex][1] not in channelList: |
|
131 | if self.dataOut.pairsList[pairIndex][1] not in channelList: | |
| 132 | continue |
|
132 | continue | |
| 133 |
|
133 | |||
| 134 | pairsIndexListSelected.append(pairIndex) |
|
134 | pairsIndexListSelected.append(pairIndex) | |
| 135 |
|
135 | |||
| 136 | if not pairsIndexListSelected: |
|
136 | if not pairsIndexListSelected: | |
| 137 | self.dataOut.data_cspc = None |
|
137 | self.dataOut.data_cspc = None | |
| 138 | self.dataOut.pairsList = [] |
|
138 | self.dataOut.pairsList = [] | |
| 139 | return |
|
139 | return | |
| 140 |
|
140 | |||
| 141 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] |
|
141 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndexListSelected] | |
| 142 | self.dataOut.pairsList = [self.dataOut.pairsList[i] |
|
142 | self.dataOut.pairsList = [self.dataOut.pairsList[i] | |
| 143 | for i in pairsIndexListSelected] |
|
143 | for i in pairsIndexListSelected] | |
| 144 |
|
144 | |||
| 145 | return |
|
145 | return | |
| 146 |
|
146 | |||
| 147 | class selectHeights(Operation): |
|
147 | class selectHeights(Operation): | |
| 148 |
|
148 | |||
| 149 | def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None): |
|
149 | def run(self, dataOut, minHei=None, maxHei=None, minIndex=None, maxIndex=None): | |
| 150 | """ |
|
150 | """ | |
| 151 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
151 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
| 152 | minHei <= height <= maxHei |
|
152 | minHei <= height <= maxHei | |
| 153 |
|
153 | |||
| 154 | Input: |
|
154 | Input: | |
| 155 | minHei : valor minimo de altura a considerar |
|
155 | minHei : valor minimo de altura a considerar | |
| 156 | maxHei : valor maximo de altura a considerar |
|
156 | maxHei : valor maximo de altura a considerar | |
| 157 |
|
157 | |||
| 158 | Affected: |
|
158 | Affected: | |
| 159 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
159 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
| 160 |
|
160 | |||
| 161 | Return: |
|
161 | Return: | |
| 162 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
162 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 163 | """ |
|
163 | """ | |
| 164 |
|
164 | |||
| 165 | self.dataOut = dataOut |
|
165 | self.dataOut = dataOut | |
| 166 |
|
166 | |||
| 167 | if minHei and maxHei: |
|
167 | if minHei and maxHei: | |
| 168 |
|
168 | |||
| 169 | if (minHei < self.dataOut.heightList[0]): |
|
169 | if (minHei < self.dataOut.heightList[0]): | |
| 170 | minHei = self.dataOut.heightList[0] |
|
170 | minHei = self.dataOut.heightList[0] | |
| 171 |
|
171 | |||
| 172 | if (maxHei > self.dataOut.heightList[-1]): |
|
172 | if (maxHei > self.dataOut.heightList[-1]): | |
| 173 | maxHei = self.dataOut.heightList[-1] |
|
173 | maxHei = self.dataOut.heightList[-1] | |
| 174 |
|
174 | |||
| 175 | minIndex = 0 |
|
175 | minIndex = 0 | |
| 176 | maxIndex = 0 |
|
176 | maxIndex = 0 | |
| 177 | heights = self.dataOut.heightList |
|
177 | heights = self.dataOut.heightList | |
| 178 |
|
178 | |||
| 179 | inda = numpy.where(heights >= minHei) |
|
179 | inda = numpy.where(heights >= minHei) | |
| 180 | indb = numpy.where(heights <= maxHei) |
|
180 | indb = numpy.where(heights <= maxHei) | |
| 181 |
|
181 | |||
| 182 | try: |
|
182 | try: | |
| 183 | minIndex = inda[0][0] |
|
183 | minIndex = inda[0][0] | |
| 184 | except: |
|
184 | except: | |
| 185 | minIndex = 0 |
|
185 | minIndex = 0 | |
| 186 |
|
186 | |||
| 187 | try: |
|
187 | try: | |
| 188 | maxIndex = indb[0][-1] |
|
188 | maxIndex = indb[0][-1] | |
| 189 | except: |
|
189 | except: | |
| 190 | maxIndex = len(heights) |
|
190 | maxIndex = len(heights) | |
| 191 |
|
191 | |||
| 192 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
192 | self.selectHeightsByIndex(minIndex, maxIndex) | |
| 193 |
|
193 | |||
| 194 | return self.dataOut |
|
194 | return self.dataOut | |
| 195 |
|
195 | |||
| 196 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
196 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
| 197 | """ |
|
197 | """ | |
| 198 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
198 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
| 199 | minIndex <= index <= maxIndex |
|
199 | minIndex <= index <= maxIndex | |
| 200 |
|
200 | |||
| 201 | Input: |
|
201 | Input: | |
| 202 | minIndex : valor de indice minimo de altura a considerar |
|
202 | minIndex : valor de indice minimo de altura a considerar | |
| 203 | maxIndex : valor de indice maximo de altura a considerar |
|
203 | maxIndex : valor de indice maximo de altura a considerar | |
| 204 |
|
204 | |||
| 205 | Affected: |
|
205 | Affected: | |
| 206 | self.dataOut.data |
|
206 | self.dataOut.data | |
| 207 | self.dataOut.heightList |
|
207 | self.dataOut.heightList | |
| 208 |
|
208 | |||
| 209 | Return: |
|
209 | Return: | |
| 210 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
210 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
| 211 | """ |
|
211 | """ | |
| 212 |
|
212 | |||
| 213 | if self.dataOut.type == 'Voltage': |
|
213 | if self.dataOut.type == 'Voltage': | |
| 214 | if (minIndex < 0) or (minIndex > maxIndex): |
|
214 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 215 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
215 | raise ValueError("Height index range (%d,%d) is not valid" % (minIndex, maxIndex)) | |
| 216 |
|
216 | |||
| 217 | if (maxIndex >= self.dataOut.nHeights): |
|
217 | if (maxIndex >= self.dataOut.nHeights): | |
| 218 | maxIndex = self.dataOut.nHeights |
|
218 | maxIndex = self.dataOut.nHeights | |
| 219 | #print("shapeeee",self.dataOut.data.shape) |
|
219 | #print("shapeeee",self.dataOut.data.shape) | |
| 220 | #voltage |
|
220 | #voltage | |
| 221 | if self.dataOut.flagDataAsBlock: |
|
221 | if self.dataOut.flagDataAsBlock: | |
| 222 | """ |
|
222 | """ | |
| 223 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
223 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 224 | """ |
|
224 | """ | |
| 225 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
225 | data = self.dataOut.data[:,:, minIndex:maxIndex] | |
| 226 | else: |
|
226 | else: | |
| 227 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
227 | data = self.dataOut.data[:, minIndex:maxIndex] | |
| 228 |
|
228 | |||
| 229 | # firstHeight = self.dataOut.heightList[minIndex] |
|
229 | # firstHeight = self.dataOut.heightList[minIndex] | |
| 230 |
|
230 | |||
| 231 | self.dataOut.data = data |
|
231 | self.dataOut.data = data | |
| 232 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
232 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] | |
| 233 |
|
233 | |||
| 234 | if self.dataOut.nHeights <= 1: |
|
234 | if self.dataOut.nHeights <= 1: | |
| 235 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) |
|
235 | raise ValueError("selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights)) | |
| 236 | elif self.dataOut.type == 'Spectra': |
|
236 | elif self.dataOut.type == 'Spectra': | |
| 237 | if (minIndex < 0) or (minIndex > maxIndex): |
|
237 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 238 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( |
|
238 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % ( | |
| 239 | minIndex, maxIndex)) |
|
239 | minIndex, maxIndex)) | |
| 240 |
|
240 | |||
| 241 | if (maxIndex >= self.dataOut.nHeights): |
|
241 | if (maxIndex >= self.dataOut.nHeights): | |
| 242 | maxIndex = self.dataOut.nHeights - 1 |
|
242 | maxIndex = self.dataOut.nHeights - 1 | |
| 243 |
|
243 | |||
| 244 | # Spectra |
|
244 | # Spectra | |
| 245 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
245 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] | |
| 246 |
|
246 | |||
| 247 | data_cspc = None |
|
247 | data_cspc = None | |
| 248 | if self.dataOut.data_cspc is not None: |
|
248 | if self.dataOut.data_cspc is not None: | |
| 249 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
249 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] | |
| 250 |
|
250 | |||
| 251 | data_dc = None |
|
251 | data_dc = None | |
| 252 | if self.dataOut.data_dc is not None: |
|
252 | if self.dataOut.data_dc is not None: | |
| 253 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
253 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] | |
| 254 |
|
254 | |||
| 255 | self.dataOut.data_spc = data_spc |
|
255 | self.dataOut.data_spc = data_spc | |
| 256 | self.dataOut.data_cspc = data_cspc |
|
256 | self.dataOut.data_cspc = data_cspc | |
| 257 | self.dataOut.data_dc = data_dc |
|
257 | self.dataOut.data_dc = data_dc | |
| 258 |
|
258 | |||
| 259 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
259 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex + 1] | |
| 260 |
|
260 | |||
| 261 | return 1 |
|
261 | return 1 | |
| 262 |
|
262 | |||
| 263 |
|
263 | |||
| 264 | class filterByHeights(Operation): |
|
264 | class filterByHeights(Operation): | |
| 265 |
|
265 | |||
| 266 | def run(self, dataOut, window): |
|
266 | def run(self, dataOut, window): | |
| 267 |
|
267 | |||
| 268 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
268 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 269 |
|
269 | |||
| 270 | if window == None: |
|
270 | if window == None: | |
| 271 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
271 | window = (dataOut.radarControllerHeaderObj.txA/dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
| 272 |
|
272 | |||
| 273 | newdelta = deltaHeight * window |
|
273 | newdelta = deltaHeight * window | |
| 274 | r = dataOut.nHeights % window |
|
274 | r = dataOut.nHeights % window | |
| 275 | newheights = (dataOut.nHeights-r)/window |
|
275 | newheights = (dataOut.nHeights-r)/window | |
| 276 |
|
276 | |||
| 277 | if newheights <= 1: |
|
277 | if newheights <= 1: | |
| 278 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) |
|
278 | raise ValueError("filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(dataOut.nHeights, window)) | |
| 279 |
|
279 | |||
| 280 | if dataOut.flagDataAsBlock: |
|
280 | if dataOut.flagDataAsBlock: | |
| 281 | """ |
|
281 | """ | |
| 282 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
282 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 283 | """ |
|
283 | """ | |
| 284 | buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] |
|
284 | buffer = dataOut.data[:, :, 0:int(dataOut.nHeights-r)] | |
| 285 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window) |
|
285 | buffer = buffer.reshape(dataOut.nChannels, dataOut.nProfiles, int(dataOut.nHeights/window), window) | |
| 286 | buffer = numpy.sum(buffer,3) |
|
286 | buffer = numpy.sum(buffer,3) | |
| 287 |
|
287 | |||
| 288 | else: |
|
288 | else: | |
| 289 | buffer = dataOut.data[:,0:int(dataOut.nHeights-r)] |
|
289 | buffer = dataOut.data[:,0:int(dataOut.nHeights-r)] | |
| 290 | buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window)) |
|
290 | buffer = buffer.reshape(dataOut.nChannels,int(dataOut.nHeights/window),int(window)) | |
| 291 | buffer = numpy.sum(buffer,2) |
|
291 | buffer = numpy.sum(buffer,2) | |
| 292 |
|
292 | |||
| 293 | dataOut.data = buffer |
|
293 | dataOut.data = buffer | |
| 294 | dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
294 | dataOut.heightList = dataOut.heightList[0] + numpy.arange( newheights )*newdelta | |
| 295 | dataOut.windowOfFilter = window |
|
295 | dataOut.windowOfFilter = window | |
| 296 |
|
296 | |||
| 297 | return dataOut |
|
297 | return dataOut | |
| 298 |
|
298 | |||
| 299 |
|
299 | |||
| 300 | class setH0(Operation): |
|
300 | class setH0(Operation): | |
| 301 |
|
301 | |||
| 302 | def run(self, dataOut, h0, deltaHeight = None): |
|
302 | def run(self, dataOut, h0, deltaHeight = None): | |
| 303 |
|
303 | |||
| 304 | if not deltaHeight: |
|
304 | if not deltaHeight: | |
| 305 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
305 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 306 |
|
306 | |||
| 307 | nHeights = dataOut.nHeights |
|
307 | nHeights = dataOut.nHeights | |
| 308 |
|
308 | |||
| 309 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
309 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight | |
| 310 |
|
310 | |||
| 311 | dataOut.heightList = newHeiRange |
|
311 | dataOut.heightList = newHeiRange | |
| 312 |
|
312 | |||
| 313 | return dataOut |
|
313 | return dataOut | |
| 314 |
|
314 | |||
| 315 |
|
315 | |||
| 316 | class deFlip(Operation): |
|
316 | class deFlip(Operation): | |
| 317 |
|
317 | |||
| 318 | def run(self, dataOut, channelList = []): |
|
318 | def run(self, dataOut, channelList = []): | |
| 319 |
|
319 | |||
| 320 | data = dataOut.data.copy() |
|
320 | data = dataOut.data.copy() | |
| 321 |
|
321 | |||
| 322 | if dataOut.flagDataAsBlock: |
|
322 | if dataOut.flagDataAsBlock: | |
| 323 | flip = self.flip |
|
323 | flip = self.flip | |
| 324 | profileList = list(range(dataOut.nProfiles)) |
|
324 | profileList = list(range(dataOut.nProfiles)) | |
| 325 |
|
325 | |||
| 326 | if not channelList: |
|
326 | if not channelList: | |
| 327 | for thisProfile in profileList: |
|
327 | for thisProfile in profileList: | |
| 328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
328 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip | |
| 329 | flip *= -1.0 |
|
329 | flip *= -1.0 | |
| 330 | else: |
|
330 | else: | |
| 331 | for thisChannel in channelList: |
|
331 | for thisChannel in channelList: | |
| 332 | if thisChannel not in dataOut.channelList: |
|
332 | if thisChannel not in dataOut.channelList: | |
| 333 | continue |
|
333 | continue | |
| 334 |
|
334 | |||
| 335 | for thisProfile in profileList: |
|
335 | for thisProfile in profileList: | |
| 336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
336 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip | |
| 337 | flip *= -1.0 |
|
337 | flip *= -1.0 | |
| 338 |
|
338 | |||
| 339 | self.flip = flip |
|
339 | self.flip = flip | |
| 340 |
|
340 | |||
| 341 | else: |
|
341 | else: | |
| 342 | if not channelList: |
|
342 | if not channelList: | |
| 343 | data[:,:] = data[:,:]*self.flip |
|
343 | data[:,:] = data[:,:]*self.flip | |
| 344 | else: |
|
344 | else: | |
| 345 | for thisChannel in channelList: |
|
345 | for thisChannel in channelList: | |
| 346 | if thisChannel not in dataOut.channelList: |
|
346 | if thisChannel not in dataOut.channelList: | |
| 347 | continue |
|
347 | continue | |
| 348 |
|
348 | |||
| 349 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
349 | data[thisChannel,:] = data[thisChannel,:]*self.flip | |
| 350 |
|
350 | |||
| 351 | self.flip *= -1. |
|
351 | self.flip *= -1. | |
| 352 |
|
352 | |||
| 353 | dataOut.data = data |
|
353 | dataOut.data = data | |
| 354 |
|
354 | |||
| 355 | return dataOut |
|
355 | return dataOut | |
| 356 |
|
356 | |||
| 357 |
|
357 | |||
| 358 | class setAttribute(Operation): |
|
358 | class setAttribute(Operation): | |
| 359 | ''' |
|
359 | ''' | |
| 360 | Set an arbitrary attribute(s) to dataOut |
|
360 | Set an arbitrary attribute(s) to dataOut | |
| 361 | ''' |
|
361 | ''' | |
| 362 |
|
362 | |||
| 363 | def __init__(self): |
|
363 | def __init__(self): | |
| 364 |
|
364 | |||
| 365 | Operation.__init__(self) |
|
365 | Operation.__init__(self) | |
| 366 | self._ready = False |
|
366 | self._ready = False | |
| 367 |
|
367 | |||
| 368 | def run(self, dataOut, **kwargs): |
|
368 | def run(self, dataOut, **kwargs): | |
| 369 |
|
369 | |||
| 370 | for key, value in kwargs.items(): |
|
370 | for key, value in kwargs.items(): | |
| 371 | setattr(dataOut, key, value) |
|
371 | setattr(dataOut, key, value) | |
| 372 |
|
372 | |||
| 373 | return dataOut |
|
373 | return dataOut | |
| 374 |
|
374 | |||
| 375 |
|
375 | |||
| 376 | @MPDecorator |
|
376 | @MPDecorator | |
| 377 | class printAttribute(Operation): |
|
377 | class printAttribute(Operation): | |
| 378 | ''' |
|
378 | ''' | |
| 379 | Print an arbitrary attribute of dataOut |
|
379 | Print an arbitrary attribute of dataOut | |
| 380 | ''' |
|
380 | ''' | |
| 381 |
|
381 | |||
| 382 | def __init__(self): |
|
382 | def __init__(self): | |
| 383 |
|
383 | |||
| 384 | Operation.__init__(self) |
|
384 | Operation.__init__(self) | |
| 385 |
|
385 | |||
| 386 | def run(self, dataOut, attributes): |
|
386 | def run(self, dataOut, attributes): | |
| 387 |
|
387 | |||
| 388 | if isinstance(attributes, str): |
|
388 | if isinstance(attributes, str): | |
| 389 | attributes = [attributes] |
|
389 | attributes = [attributes] | |
| 390 | for attr in attributes: |
|
390 | for attr in attributes: | |
| 391 | if hasattr(dataOut, attr): |
|
391 | if hasattr(dataOut, attr): | |
| 392 | log.log(getattr(dataOut, attr), attr) |
|
392 | log.log(getattr(dataOut, attr), attr) | |
| 393 |
|
393 | |||
| 394 |
|
394 | |||
| 395 | class interpolateHeights(Operation): |
|
395 | class interpolateHeights(Operation): | |
| 396 |
|
396 | |||
| 397 | def run(self, dataOut, topLim, botLim): |
|
397 | def run(self, dataOut, topLim, botLim): | |
| 398 | #69 al 72 para julia |
|
398 | #69 al 72 para julia | |
| 399 | #82-84 para meteoros |
|
399 | #82-84 para meteoros | |
| 400 | if len(numpy.shape(dataOut.data))==2: |
|
400 | if len(numpy.shape(dataOut.data))==2: | |
| 401 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 |
|
401 | sampInterp = (dataOut.data[:,botLim-1] + dataOut.data[:,topLim+1])/2 | |
| 402 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
402 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) | |
| 403 | #dataOut.data[:,botLim:limSup+1] = sampInterp |
|
403 | #dataOut.data[:,botLim:limSup+1] = sampInterp | |
| 404 | dataOut.data[:,botLim:topLim+1] = sampInterp |
|
404 | dataOut.data[:,botLim:topLim+1] = sampInterp | |
| 405 | else: |
|
405 | else: | |
| 406 | nHeights = dataOut.data.shape[2] |
|
406 | nHeights = dataOut.data.shape[2] | |
| 407 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
407 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) | |
| 408 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] |
|
408 | y = dataOut.data[:,:,list(range(botLim))+list(range(topLim+1,nHeights))] | |
| 409 | f = interpolate.interp1d(x, y, axis = 2) |
|
409 | f = interpolate.interp1d(x, y, axis = 2) | |
| 410 | xnew = numpy.arange(botLim,topLim+1) |
|
410 | xnew = numpy.arange(botLim,topLim+1) | |
| 411 | ynew = f(xnew) |
|
411 | ynew = f(xnew) | |
| 412 | dataOut.data[:,:,botLim:topLim+1] = ynew |
|
412 | dataOut.data[:,:,botLim:topLim+1] = ynew | |
| 413 |
|
413 | |||
| 414 | return dataOut |
|
414 | return dataOut | |
| 415 |
|
415 | |||
| 416 |
|
416 | |||
| 417 | class CohInt(Operation): |
|
417 | class CohInt(Operation): | |
| 418 |
|
418 | |||
| 419 | isConfig = False |
|
419 | isConfig = False | |
| 420 | __profIndex = 0 |
|
420 | __profIndex = 0 | |
| 421 | __byTime = False |
|
421 | __byTime = False | |
| 422 | __initime = None |
|
422 | __initime = None | |
| 423 | __lastdatatime = None |
|
423 | __lastdatatime = None | |
| 424 | __integrationtime = None |
|
424 | __integrationtime = None | |
| 425 | __buffer = None |
|
425 | __buffer = None | |
| 426 | __bufferStride = [] |
|
426 | __bufferStride = [] | |
| 427 | __dataReady = False |
|
427 | __dataReady = False | |
| 428 | __profIndexStride = 0 |
|
428 | __profIndexStride = 0 | |
| 429 | __dataToPutStride = False |
|
429 | __dataToPutStride = False | |
| 430 | n = None |
|
430 | n = None | |
| 431 |
|
431 | |||
| 432 | def __init__(self, **kwargs): |
|
432 | def __init__(self, **kwargs): | |
| 433 |
|
433 | |||
| 434 | Operation.__init__(self, **kwargs) |
|
434 | Operation.__init__(self, **kwargs) | |
| 435 |
|
435 | |||
| 436 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
436 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): | |
| 437 | """ |
|
437 | """ | |
| 438 | Set the parameters of the integration class. |
|
438 | Set the parameters of the integration class. | |
| 439 |
|
439 | |||
| 440 | Inputs: |
|
440 | Inputs: | |
| 441 |
|
441 | |||
| 442 | n : Number of coherent integrations |
|
442 | n : Number of coherent integrations | |
| 443 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
443 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 444 | overlapping : |
|
444 | overlapping : | |
| 445 | """ |
|
445 | """ | |
| 446 |
|
446 | |||
| 447 | self.__initime = None |
|
447 | self.__initime = None | |
| 448 | self.__lastdatatime = 0 |
|
448 | self.__lastdatatime = 0 | |
| 449 | self.__buffer = None |
|
449 | self.__buffer = None | |
| 450 | self.__dataReady = False |
|
450 | self.__dataReady = False | |
| 451 | self.byblock = byblock |
|
451 | self.byblock = byblock | |
| 452 | self.stride = stride |
|
452 | self.stride = stride | |
| 453 |
|
453 | |||
| 454 | if n == None and timeInterval == None: |
|
454 | if n == None and timeInterval == None: | |
| 455 | raise ValueError("n or timeInterval should be specified ...") |
|
455 | raise ValueError("n or timeInterval should be specified ...") | |
| 456 |
|
456 | |||
| 457 | if n != None: |
|
457 | if n != None: | |
| 458 | self.n = n |
|
458 | self.n = n | |
| 459 | self.__byTime = False |
|
459 | self.__byTime = False | |
| 460 | else: |
|
460 | else: | |
| 461 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
461 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
| 462 | self.n = 9999 |
|
462 | self.n = 9999 | |
| 463 | self.__byTime = True |
|
463 | self.__byTime = True | |
| 464 |
|
464 | |||
| 465 | if overlapping: |
|
465 | if overlapping: | |
| 466 | self.__withOverlapping = True |
|
466 | self.__withOverlapping = True | |
| 467 | self.__buffer = None |
|
467 | self.__buffer = None | |
| 468 | else: |
|
468 | else: | |
| 469 | self.__withOverlapping = False |
|
469 | self.__withOverlapping = False | |
| 470 | self.__buffer = 0 |
|
470 | self.__buffer = 0 | |
| 471 |
|
471 | |||
| 472 | self.__profIndex = 0 |
|
472 | self.__profIndex = 0 | |
| 473 |
|
473 | |||
| 474 | def putData(self, data): |
|
474 | def putData(self, data): | |
| 475 |
|
475 | |||
| 476 | """ |
|
476 | """ | |
| 477 | Add a profile to the __buffer and increase in one the __profileIndex |
|
477 | Add a profile to the __buffer and increase in one the __profileIndex | |
| 478 |
|
478 | |||
| 479 | """ |
|
479 | """ | |
| 480 |
|
480 | |||
| 481 | if not self.__withOverlapping: |
|
481 | if not self.__withOverlapping: | |
| 482 | self.__buffer += data.copy() |
|
482 | self.__buffer += data.copy() | |
| 483 | self.__profIndex += 1 |
|
483 | self.__profIndex += 1 | |
| 484 | return |
|
484 | return | |
| 485 |
|
485 | |||
| 486 | #Overlapping data |
|
486 | #Overlapping data | |
| 487 | nChannels, nHeis = data.shape |
|
487 | nChannels, nHeis = data.shape | |
| 488 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
488 | data = numpy.reshape(data, (1, nChannels, nHeis)) | |
| 489 |
|
489 | |||
| 490 | #If the buffer is empty then it takes the data value |
|
490 | #If the buffer is empty then it takes the data value | |
| 491 | if self.__buffer is None: |
|
491 | if self.__buffer is None: | |
| 492 | self.__buffer = data |
|
492 | self.__buffer = data | |
| 493 | self.__profIndex += 1 |
|
493 | self.__profIndex += 1 | |
| 494 | return |
|
494 | return | |
| 495 |
|
495 | |||
| 496 | #If the buffer length is lower than n then stakcing the data value |
|
496 | #If the buffer length is lower than n then stakcing the data value | |
| 497 | if self.__profIndex < self.n: |
|
497 | if self.__profIndex < self.n: | |
| 498 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
498 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
| 499 | self.__profIndex += 1 |
|
499 | self.__profIndex += 1 | |
| 500 | return |
|
500 | return | |
| 501 |
|
501 | |||
| 502 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
502 | #If the buffer length is equal to n then replacing the last buffer value with the data value | |
| 503 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
503 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
| 504 | self.__buffer[self.n-1] = data |
|
504 | self.__buffer[self.n-1] = data | |
| 505 | self.__profIndex = self.n |
|
505 | self.__profIndex = self.n | |
| 506 | return |
|
506 | return | |
| 507 |
|
507 | |||
| 508 |
|
508 | |||
| 509 | def pushData(self): |
|
509 | def pushData(self): | |
| 510 | """ |
|
510 | """ | |
| 511 | Return the sum of the last profiles and the profiles used in the sum. |
|
511 | Return the sum of the last profiles and the profiles used in the sum. | |
| 512 |
|
512 | |||
| 513 | Affected: |
|
513 | Affected: | |
| 514 |
|
514 | |||
| 515 | self.__profileIndex |
|
515 | self.__profileIndex | |
| 516 |
|
516 | |||
| 517 | """ |
|
517 | """ | |
| 518 |
|
518 | |||
| 519 | if not self.__withOverlapping: |
|
519 | if not self.__withOverlapping: | |
| 520 | data = self.__buffer |
|
520 | data = self.__buffer | |
| 521 | n = self.__profIndex |
|
521 | n = self.__profIndex | |
| 522 |
|
522 | |||
| 523 | self.__buffer = 0 |
|
523 | self.__buffer = 0 | |
| 524 | self.__profIndex = 0 |
|
524 | self.__profIndex = 0 | |
| 525 |
|
525 | |||
| 526 | return data, n |
|
526 | return data, n | |
| 527 |
|
527 | |||
| 528 | #Integration with Overlapping |
|
528 | #Integration with Overlapping | |
| 529 | data = numpy.sum(self.__buffer, axis=0) |
|
529 | data = numpy.sum(self.__buffer, axis=0) | |
| 530 | # print data |
|
530 | # print data | |
| 531 | # raise |
|
531 | # raise | |
| 532 | n = self.__profIndex |
|
532 | n = self.__profIndex | |
| 533 |
|
533 | |||
| 534 | return data, n |
|
534 | return data, n | |
| 535 |
|
535 | |||
| 536 | def byProfiles(self, data): |
|
536 | def byProfiles(self, data): | |
| 537 |
|
537 | |||
| 538 | self.__dataReady = False |
|
538 | self.__dataReady = False | |
| 539 | avgdata = None |
|
539 | avgdata = None | |
| 540 | # n = None |
|
540 | # n = None | |
| 541 | # print data |
|
541 | # print data | |
| 542 | # raise |
|
542 | # raise | |
| 543 | self.putData(data) |
|
543 | self.putData(data) | |
| 544 |
|
544 | |||
| 545 | if self.__profIndex == self.n: |
|
545 | if self.__profIndex == self.n: | |
| 546 | avgdata, n = self.pushData() |
|
546 | avgdata, n = self.pushData() | |
| 547 | self.__dataReady = True |
|
547 | self.__dataReady = True | |
| 548 |
|
548 | |||
| 549 | return avgdata |
|
549 | return avgdata | |
| 550 |
|
550 | |||
| 551 | def byTime(self, data, datatime): |
|
551 | def byTime(self, data, datatime): | |
| 552 |
|
552 | |||
| 553 | self.__dataReady = False |
|
553 | self.__dataReady = False | |
| 554 | avgdata = None |
|
554 | avgdata = None | |
| 555 | n = None |
|
555 | n = None | |
| 556 |
|
556 | |||
| 557 | self.putData(data) |
|
557 | self.putData(data) | |
| 558 |
|
558 | |||
| 559 | if (datatime - self.__initime) >= self.__integrationtime: |
|
559 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 560 | avgdata, n = self.pushData() |
|
560 | avgdata, n = self.pushData() | |
| 561 | self.n = n |
|
561 | self.n = n | |
| 562 | self.__dataReady = True |
|
562 | self.__dataReady = True | |
| 563 |
|
563 | |||
| 564 | return avgdata |
|
564 | return avgdata | |
| 565 |
|
565 | |||
| 566 | def integrateByStride(self, data, datatime): |
|
566 | def integrateByStride(self, data, datatime): | |
| 567 | # print data |
|
567 | # print data | |
| 568 | if self.__profIndex == 0: |
|
568 | if self.__profIndex == 0: | |
| 569 | self.__buffer = [[data.copy(), datatime]] |
|
569 | self.__buffer = [[data.copy(), datatime]] | |
| 570 | else: |
|
570 | else: | |
| 571 | self.__buffer.append([data.copy(),datatime]) |
|
571 | self.__buffer.append([data.copy(),datatime]) | |
| 572 | self.__profIndex += 1 |
|
572 | self.__profIndex += 1 | |
| 573 | self.__dataReady = False |
|
573 | self.__dataReady = False | |
| 574 |
|
574 | |||
| 575 | if self.__profIndex == self.n * self.stride : |
|
575 | if self.__profIndex == self.n * self.stride : | |
| 576 | self.__dataToPutStride = True |
|
576 | self.__dataToPutStride = True | |
| 577 | self.__profIndexStride = 0 |
|
577 | self.__profIndexStride = 0 | |
| 578 | self.__profIndex = 0 |
|
578 | self.__profIndex = 0 | |
| 579 | self.__bufferStride = [] |
|
579 | self.__bufferStride = [] | |
| 580 | for i in range(self.stride): |
|
580 | for i in range(self.stride): | |
| 581 | current = self.__buffer[i::self.stride] |
|
581 | current = self.__buffer[i::self.stride] | |
| 582 | data = numpy.sum([t[0] for t in current], axis=0) |
|
582 | data = numpy.sum([t[0] for t in current], axis=0) | |
| 583 | avgdatatime = numpy.average([t[1] for t in current]) |
|
583 | avgdatatime = numpy.average([t[1] for t in current]) | |
| 584 | # print data |
|
584 | # print data | |
| 585 | self.__bufferStride.append((data, avgdatatime)) |
|
585 | self.__bufferStride.append((data, avgdatatime)) | |
| 586 |
|
586 | |||
| 587 | if self.__dataToPutStride: |
|
587 | if self.__dataToPutStride: | |
| 588 | self.__dataReady = True |
|
588 | self.__dataReady = True | |
| 589 | self.__profIndexStride += 1 |
|
589 | self.__profIndexStride += 1 | |
| 590 | if self.__profIndexStride == self.stride: |
|
590 | if self.__profIndexStride == self.stride: | |
| 591 | self.__dataToPutStride = False |
|
591 | self.__dataToPutStride = False | |
| 592 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
592 | # print self.__bufferStride[self.__profIndexStride - 1] | |
| 593 | # raise |
|
593 | # raise | |
| 594 | return self.__bufferStride[self.__profIndexStride - 1] |
|
594 | return self.__bufferStride[self.__profIndexStride - 1] | |
| 595 |
|
595 | |||
| 596 |
|
596 | |||
| 597 | return None, None |
|
597 | return None, None | |
| 598 |
|
598 | |||
| 599 | def integrate(self, data, datatime=None): |
|
599 | def integrate(self, data, datatime=None): | |
| 600 |
|
600 | |||
| 601 | if self.__initime == None: |
|
601 | if self.__initime == None: | |
| 602 | self.__initime = datatime |
|
602 | self.__initime = datatime | |
| 603 |
|
603 | |||
| 604 | if self.__byTime: |
|
604 | if self.__byTime: | |
| 605 | avgdata = self.byTime(data, datatime) |
|
605 | avgdata = self.byTime(data, datatime) | |
| 606 | else: |
|
606 | else: | |
| 607 | avgdata = self.byProfiles(data) |
|
607 | avgdata = self.byProfiles(data) | |
| 608 |
|
608 | |||
| 609 |
|
609 | |||
| 610 | self.__lastdatatime = datatime |
|
610 | self.__lastdatatime = datatime | |
| 611 |
|
611 | |||
| 612 | if avgdata is None: |
|
612 | if avgdata is None: | |
| 613 | return None, None |
|
613 | return None, None | |
| 614 |
|
614 | |||
| 615 | avgdatatime = self.__initime |
|
615 | avgdatatime = self.__initime | |
| 616 |
|
616 | |||
| 617 | deltatime = datatime - self.__lastdatatime |
|
617 | deltatime = datatime - self.__lastdatatime | |
| 618 |
|
618 | |||
| 619 | if not self.__withOverlapping: |
|
619 | if not self.__withOverlapping: | |
| 620 | self.__initime = datatime |
|
620 | self.__initime = datatime | |
| 621 | else: |
|
621 | else: | |
| 622 | self.__initime += deltatime |
|
622 | self.__initime += deltatime | |
| 623 |
|
623 | |||
| 624 | return avgdata, avgdatatime |
|
624 | return avgdata, avgdatatime | |
| 625 |
|
625 | |||
| 626 | def integrateByBlock(self, dataOut): |
|
626 | def integrateByBlock(self, dataOut): | |
| 627 |
|
627 | |||
| 628 | times = int(dataOut.data.shape[1]/self.n) |
|
628 | times = int(dataOut.data.shape[1]/self.n) | |
| 629 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
629 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) | |
| 630 |
|
630 | |||
| 631 | id_min = 0 |
|
631 | id_min = 0 | |
| 632 | id_max = self.n |
|
632 | id_max = self.n | |
| 633 |
|
633 | |||
| 634 | for i in range(times): |
|
634 | for i in range(times): | |
| 635 | junk = dataOut.data[:,id_min:id_max,:] |
|
635 | junk = dataOut.data[:,id_min:id_max,:] | |
| 636 | avgdata[:,i,:] = junk.sum(axis=1) |
|
636 | avgdata[:,i,:] = junk.sum(axis=1) | |
| 637 | id_min += self.n |
|
637 | id_min += self.n | |
| 638 | id_max += self.n |
|
638 | id_max += self.n | |
| 639 |
|
639 | |||
| 640 | timeInterval = dataOut.ippSeconds*self.n |
|
640 | timeInterval = dataOut.ippSeconds*self.n | |
| 641 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
641 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime | |
| 642 | self.__dataReady = True |
|
642 | self.__dataReady = True | |
| 643 | return avgdata, avgdatatime |
|
643 | return avgdata, avgdatatime | |
| 644 |
|
644 | |||
| 645 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
645 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): | |
| 646 |
|
646 | |||
| 647 | if not self.isConfig: |
|
647 | if not self.isConfig: | |
| 648 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
648 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) | |
| 649 | self.isConfig = True |
|
649 | self.isConfig = True | |
| 650 |
|
650 | |||
| 651 | if dataOut.flagDataAsBlock: |
|
651 | if dataOut.flagDataAsBlock: | |
| 652 | """ |
|
652 | """ | |
| 653 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
653 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
| 654 | """ |
|
654 | """ | |
| 655 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
655 | avgdata, avgdatatime = self.integrateByBlock(dataOut) | |
| 656 | dataOut.nProfiles /= self.n |
|
656 | dataOut.nProfiles /= self.n | |
| 657 | else: |
|
657 | else: | |
| 658 | if stride is None: |
|
658 | if stride is None: | |
| 659 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
659 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |
| 660 | else: |
|
660 | else: | |
| 661 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
661 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) | |
| 662 |
|
662 | |||
| 663 |
|
663 | |||
| 664 | # dataOut.timeInterval *= n |
|
664 | # dataOut.timeInterval *= n | |
| 665 | dataOut.flagNoData = True |
|
665 | dataOut.flagNoData = True | |
| 666 |
|
666 | |||
| 667 | if self.__dataReady: |
|
667 | if self.__dataReady: | |
| 668 | dataOut.data = avgdata |
|
668 | dataOut.data = avgdata | |
| 669 | if not dataOut.flagCohInt: |
|
669 | if not dataOut.flagCohInt: | |
| 670 | dataOut.nCohInt *= self.n |
|
670 | dataOut.nCohInt *= self.n | |
| 671 | dataOut.flagCohInt = True |
|
671 | dataOut.flagCohInt = True | |
| 672 | ####################################dataOut.utctime = avgdatatime |
|
672 | ####################################dataOut.utctime = avgdatatime | |
| 673 | # print avgdata, avgdatatime |
|
673 | # print avgdata, avgdatatime | |
| 674 | # raise |
|
674 | # raise | |
| 675 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
675 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
| 676 | dataOut.flagNoData = False |
|
676 | dataOut.flagNoData = False | |
| 677 | return dataOut |
|
677 | return dataOut | |
| 678 |
|
678 | |||
| 679 | class Decoder(Operation): |
|
679 | class Decoder(Operation): | |
| 680 |
|
680 | |||
| 681 | isConfig = False |
|
681 | isConfig = False | |
| 682 | __profIndex = 0 |
|
682 | __profIndex = 0 | |
| 683 |
|
683 | |||
| 684 | code = None |
|
684 | code = None | |
| 685 |
|
685 | |||
| 686 | nCode = None |
|
686 | nCode = None | |
| 687 | nBaud = None |
|
687 | nBaud = None | |
| 688 |
|
688 | |||
| 689 | def __init__(self, **kwargs): |
|
689 | def __init__(self, **kwargs): | |
| 690 |
|
690 | |||
| 691 | Operation.__init__(self, **kwargs) |
|
691 | Operation.__init__(self, **kwargs) | |
| 692 |
|
692 | |||
| 693 | self.times = None |
|
693 | self.times = None | |
| 694 | self.osamp = None |
|
694 | self.osamp = None | |
| 695 | # self.__setValues = False |
|
695 | # self.__setValues = False | |
| 696 | self.isConfig = False |
|
696 | self.isConfig = False | |
| 697 | self.setupReq = False |
|
697 | self.setupReq = False | |
| 698 | def setup(self, code, osamp, dataOut): |
|
698 | def setup(self, code, osamp, dataOut): | |
| 699 |
|
699 | |||
| 700 | self.__profIndex = 0 |
|
700 | self.__profIndex = 0 | |
| 701 |
|
701 | |||
| 702 | self.code = code |
|
702 | self.code = code | |
| 703 |
|
703 | |||
| 704 | self.nCode = len(code) |
|
704 | self.nCode = len(code) | |
| 705 | self.nBaud = len(code[0]) |
|
705 | self.nBaud = len(code[0]) | |
| 706 |
|
706 | |||
| 707 | if (osamp != None) and (osamp >1): |
|
707 | if (osamp != None) and (osamp >1): | |
| 708 | self.osamp = osamp |
|
708 | self.osamp = osamp | |
| 709 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
709 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) | |
| 710 | self.nBaud = self.nBaud*self.osamp |
|
710 | self.nBaud = self.nBaud*self.osamp | |
| 711 |
|
711 | |||
| 712 | self.__nChannels = dataOut.nChannels |
|
712 | self.__nChannels = dataOut.nChannels | |
| 713 | self.__nProfiles = dataOut.nProfiles |
|
713 | self.__nProfiles = dataOut.nProfiles | |
| 714 | self.__nHeis = dataOut.nHeights |
|
714 | self.__nHeis = dataOut.nHeights | |
| 715 |
|
715 | |||
| 716 | if self.__nHeis < self.nBaud: |
|
716 | if self.__nHeis < self.nBaud: | |
| 717 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) |
|
717 | raise ValueError('Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud)) | |
| 718 |
|
718 | |||
| 719 | #Frequency |
|
719 | #Frequency | |
| 720 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
720 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
| 721 |
|
721 | |||
| 722 | __codeBuffer[:,0:self.nBaud] = self.code |
|
722 | __codeBuffer[:,0:self.nBaud] = self.code | |
| 723 |
|
723 | |||
| 724 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
724 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
| 725 |
|
725 | |||
| 726 | if dataOut.flagDataAsBlock: |
|
726 | if dataOut.flagDataAsBlock: | |
| 727 |
|
727 | |||
| 728 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
728 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 729 |
|
729 | |||
| 730 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
730 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) | |
| 731 |
|
731 | |||
| 732 | else: |
|
732 | else: | |
| 733 |
|
733 | |||
| 734 | #Time |
|
734 | #Time | |
| 735 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
735 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
| 736 |
|
736 | |||
| 737 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
737 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |
| 738 |
|
738 | |||
| 739 | def __convolutionInFreq(self, data): |
|
739 | def __convolutionInFreq(self, data): | |
| 740 |
|
740 | |||
| 741 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
741 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 742 |
|
742 | |||
| 743 | fft_data = numpy.fft.fft(data, axis=1) |
|
743 | fft_data = numpy.fft.fft(data, axis=1) | |
| 744 |
|
744 | |||
| 745 | conv = fft_data*fft_code |
|
745 | conv = fft_data*fft_code | |
| 746 |
|
746 | |||
| 747 | data = numpy.fft.ifft(conv,axis=1) |
|
747 | data = numpy.fft.ifft(conv,axis=1) | |
| 748 |
|
748 | |||
| 749 | return data |
|
749 | return data | |
| 750 |
|
750 | |||
| 751 | def __convolutionInFreqOpt(self, data): |
|
751 | def __convolutionInFreqOpt(self, data): | |
| 752 |
|
752 | |||
| 753 | raise NotImplementedError |
|
753 | raise NotImplementedError | |
| 754 |
|
754 | |||
| 755 | def __convolutionInTime(self, data): |
|
755 | def __convolutionInTime(self, data): | |
| 756 |
|
756 | |||
| 757 | code = self.code[self.__profIndex] |
|
757 | code = self.code[self.__profIndex] | |
| 758 | for i in range(self.__nChannels): |
|
758 | for i in range(self.__nChannels): | |
| 759 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
759 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] | |
| 760 |
|
760 | |||
| 761 | return self.datadecTime |
|
761 | return self.datadecTime | |
| 762 |
|
762 | |||
| 763 | def __convolutionByBlockInTime(self, data): |
|
763 | def __convolutionByBlockInTime(self, data): | |
| 764 |
|
764 | |||
| 765 | repetitions = int(self.__nProfiles / self.nCode) |
|
765 | repetitions = int(self.__nProfiles / self.nCode) | |
| 766 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
766 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) | |
| 767 | junk = junk.flatten() |
|
767 | junk = junk.flatten() | |
| 768 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
768 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) | |
| 769 | profilesList = range(self.__nProfiles) |
|
769 | profilesList = range(self.__nProfiles) | |
| 770 |
|
770 | |||
| 771 | for i in range(self.__nChannels): |
|
771 | for i in range(self.__nChannels): | |
| 772 | for j in profilesList: |
|
772 | for j in profilesList: | |
| 773 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
773 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] | |
| 774 | return self.datadecTime |
|
774 | return self.datadecTime | |
| 775 |
|
775 | |||
| 776 | def __convolutionByBlockInFreq(self, data): |
|
776 | def __convolutionByBlockInFreq(self, data): | |
| 777 |
|
777 | |||
| 778 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") |
|
778 | raise NotImplementedError("Decoder by frequency fro Blocks not implemented") | |
| 779 |
|
779 | |||
| 780 |
|
780 | |||
| 781 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
781 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
| 782 |
|
782 | |||
| 783 | fft_data = numpy.fft.fft(data, axis=2) |
|
783 | fft_data = numpy.fft.fft(data, axis=2) | |
| 784 |
|
784 | |||
| 785 | conv = fft_data*fft_code |
|
785 | conv = fft_data*fft_code | |
| 786 |
|
786 | |||
| 787 | data = numpy.fft.ifft(conv,axis=2) |
|
787 | data = numpy.fft.ifft(conv,axis=2) | |
| 788 |
|
788 | |||
| 789 | return data |
|
789 | return data | |
| 790 |
|
790 | |||
| 791 |
|
791 | |||
| 792 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
792 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): | |
| 793 |
|
793 | |||
| 794 | if dataOut.flagDecodeData: |
|
794 | if dataOut.flagDecodeData: | |
| 795 | print("This data is already decoded, recoding again ...") |
|
795 | print("This data is already decoded, recoding again ...") | |
| 796 |
|
796 | |||
| 797 | if not self.isConfig: |
|
797 | if not self.isConfig: | |
| 798 |
|
798 | |||
| 799 | if code is None: |
|
799 | if code is None: | |
| 800 | if dataOut.code is None: |
|
800 | if dataOut.code is None: | |
| 801 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) |
|
801 | raise ValueError("Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type) | |
| 802 |
|
802 | |||
| 803 | code = dataOut.code |
|
803 | code = dataOut.code | |
| 804 | else: |
|
804 | else: | |
| 805 | code = numpy.array(code).reshape(nCode,nBaud) |
|
805 | code = numpy.array(code).reshape(nCode,nBaud) | |
| 806 | self.setup(code, osamp, dataOut) |
|
806 | self.setup(code, osamp, dataOut) | |
| 807 |
|
807 | |||
| 808 | self.isConfig = True |
|
808 | self.isConfig = True | |
| 809 |
|
809 | |||
| 810 | if mode == 3: |
|
810 | if mode == 3: | |
| 811 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
811 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) | |
| 812 |
|
812 | |||
| 813 | if times != None: |
|
813 | if times != None: | |
| 814 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
814 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") | |
| 815 |
|
815 | |||
| 816 | if self.code is None: |
|
816 | if self.code is None: | |
| 817 | print("Fail decoding: Code is not defined.") |
|
817 | print("Fail decoding: Code is not defined.") | |
| 818 | return |
|
818 | return | |
| 819 |
|
819 | |||
| 820 | self.__nProfiles = dataOut.nProfiles |
|
820 | self.__nProfiles = dataOut.nProfiles | |
| 821 | datadec = None |
|
821 | datadec = None | |
| 822 |
|
822 | |||
| 823 | if mode == 3: |
|
823 | if mode == 3: | |
| 824 | mode = 0 |
|
824 | mode = 0 | |
| 825 |
|
825 | |||
| 826 | if dataOut.flagDataAsBlock: |
|
826 | if dataOut.flagDataAsBlock: | |
| 827 | """ |
|
827 | """ | |
| 828 | Decoding when data have been read as block, |
|
828 | Decoding when data have been read as block, | |
| 829 | """ |
|
829 | """ | |
| 830 |
|
830 | |||
| 831 | if mode == 0: |
|
831 | if mode == 0: | |
| 832 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
832 | datadec = self.__convolutionByBlockInTime(dataOut.data) | |
| 833 | if mode == 1: |
|
833 | if mode == 1: | |
| 834 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
834 | datadec = self.__convolutionByBlockInFreq(dataOut.data) | |
| 835 | else: |
|
835 | else: | |
| 836 | """ |
|
836 | """ | |
| 837 | Decoding when data have been read profile by profile |
|
837 | Decoding when data have been read profile by profile | |
| 838 | """ |
|
838 | """ | |
| 839 | if mode == 0: |
|
839 | if mode == 0: | |
| 840 | datadec = self.__convolutionInTime(dataOut.data) |
|
840 | datadec = self.__convolutionInTime(dataOut.data) | |
| 841 |
|
841 | |||
| 842 | if mode == 1: |
|
842 | if mode == 1: | |
| 843 | datadec = self.__convolutionInFreq(dataOut.data) |
|
843 | datadec = self.__convolutionInFreq(dataOut.data) | |
| 844 |
|
844 | |||
| 845 | if mode == 2: |
|
845 | if mode == 2: | |
| 846 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
846 | datadec = self.__convolutionInFreqOpt(dataOut.data) | |
| 847 |
|
847 | |||
| 848 | if datadec is None: |
|
848 | if datadec is None: | |
| 849 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) |
|
849 | raise ValueError("Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode) | |
| 850 |
|
850 | |||
| 851 | dataOut.code = self.code |
|
851 | dataOut.code = self.code | |
| 852 | dataOut.nCode = self.nCode |
|
852 | dataOut.nCode = self.nCode | |
| 853 | dataOut.nBaud = self.nBaud |
|
853 | dataOut.nBaud = self.nBaud | |
| 854 |
|
854 | |||
| 855 | dataOut.data = datadec |
|
855 | dataOut.data = datadec | |
| 856 |
|
856 | |||
| 857 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
857 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] | |
| 858 |
|
858 | |||
| 859 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
859 | dataOut.flagDecodeData = True #asumo q la data esta decodificada | |
| 860 |
|
860 | |||
| 861 | if self.__profIndex == self.nCode-1: |
|
861 | if self.__profIndex == self.nCode-1: | |
| 862 | self.__profIndex = 0 |
|
862 | self.__profIndex = 0 | |
| 863 | return dataOut |
|
863 | return dataOut | |
| 864 |
|
864 | |||
| 865 | self.__profIndex += 1 |
|
865 | self.__profIndex += 1 | |
| 866 |
|
866 | |||
| 867 | return dataOut |
|
867 | return dataOut | |
| 868 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
868 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip | |
| 869 |
|
869 | |||
| 870 |
|
870 | |||
| 871 | class ProfileConcat(Operation): |
|
871 | class ProfileConcat(Operation): | |
| 872 |
|
872 | |||
| 873 | isConfig = False |
|
873 | isConfig = False | |
| 874 | buffer = None |
|
874 | buffer = None | |
| 875 |
|
875 | |||
| 876 | def __init__(self, **kwargs): |
|
876 | def __init__(self, **kwargs): | |
| 877 |
|
877 | |||
| 878 | Operation.__init__(self, **kwargs) |
|
878 | Operation.__init__(self, **kwargs) | |
| 879 | self.profileIndex = 0 |
|
879 | self.profileIndex = 0 | |
| 880 |
|
880 | |||
| 881 | def reset(self): |
|
881 | def reset(self): | |
| 882 | self.buffer = numpy.zeros_like(self.buffer) |
|
882 | self.buffer = numpy.zeros_like(self.buffer) | |
| 883 | self.start_index = 0 |
|
883 | self.start_index = 0 | |
| 884 | self.times = 1 |
|
884 | self.times = 1 | |
| 885 |
|
885 | |||
| 886 | def setup(self, data, m, n=1): |
|
886 | def setup(self, data, m, n=1): | |
| 887 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
887 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |
| 888 | self.nHeights = data.shape[1]#.nHeights |
|
888 | self.nHeights = data.shape[1]#.nHeights | |
| 889 | self.start_index = 0 |
|
889 | self.start_index = 0 | |
| 890 | self.times = 1 |
|
890 | self.times = 1 | |
| 891 |
|
891 | |||
| 892 | def concat(self, data): |
|
892 | def concat(self, data): | |
| 893 |
|
893 | |||
| 894 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
894 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() | |
| 895 | self.start_index = self.start_index + self.nHeights |
|
895 | self.start_index = self.start_index + self.nHeights | |
| 896 |
|
896 | |||
| 897 | def run(self, dataOut, m): |
|
897 | def run(self, dataOut, m): | |
| 898 | dataOut.flagNoData = True |
|
898 | dataOut.flagNoData = True | |
| 899 |
|
899 | |||
| 900 | if not self.isConfig: |
|
900 | if not self.isConfig: | |
| 901 | self.setup(dataOut.data, m, 1) |
|
901 | self.setup(dataOut.data, m, 1) | |
| 902 | self.isConfig = True |
|
902 | self.isConfig = True | |
| 903 |
|
903 | |||
| 904 | if dataOut.flagDataAsBlock: |
|
904 | if dataOut.flagDataAsBlock: | |
| 905 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") |
|
905 | raise ValueError("ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False") | |
| 906 |
|
906 | |||
| 907 | else: |
|
907 | else: | |
| 908 | self.concat(dataOut.data) |
|
908 | self.concat(dataOut.data) | |
| 909 | self.times += 1 |
|
909 | self.times += 1 | |
| 910 | if self.times > m: |
|
910 | if self.times > m: | |
| 911 | dataOut.data = self.buffer |
|
911 | dataOut.data = self.buffer | |
| 912 | self.reset() |
|
912 | self.reset() | |
| 913 | dataOut.flagNoData = False |
|
913 | dataOut.flagNoData = False | |
| 914 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
914 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |
| 915 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
915 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 916 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
916 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m | |
| 917 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
917 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |
| 918 | dataOut.ippSeconds *= m |
|
918 | dataOut.ippSeconds *= m | |
| 919 | return dataOut |
|
919 | return dataOut | |
| 920 |
|
920 | |||
| 921 | class ProfileSelector(Operation): |
|
921 | class ProfileSelector(Operation): | |
| 922 |
|
922 | |||
| 923 | profileIndex = None |
|
923 | profileIndex = None | |
| 924 | # Tamanho total de los perfiles |
|
924 | # Tamanho total de los perfiles | |
| 925 | nProfiles = None |
|
925 | nProfiles = None | |
| 926 |
|
926 | |||
| 927 | def __init__(self, **kwargs): |
|
927 | def __init__(self, **kwargs): | |
| 928 |
|
928 | |||
| 929 | Operation.__init__(self, **kwargs) |
|
929 | Operation.__init__(self, **kwargs) | |
| 930 | self.profileIndex = 0 |
|
930 | self.profileIndex = 0 | |
| 931 |
|
931 | |||
| 932 | def incProfileIndex(self): |
|
932 | def incProfileIndex(self): | |
| 933 |
|
933 | |||
| 934 | self.profileIndex += 1 |
|
934 | self.profileIndex += 1 | |
| 935 |
|
935 | |||
| 936 | if self.profileIndex >= self.nProfiles: |
|
936 | if self.profileIndex >= self.nProfiles: | |
| 937 | self.profileIndex = 0 |
|
937 | self.profileIndex = 0 | |
| 938 |
|
938 | |||
| 939 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
939 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): | |
| 940 |
|
940 | |||
| 941 | if profileIndex < minIndex: |
|
941 | if profileIndex < minIndex: | |
| 942 | return False |
|
942 | return False | |
| 943 |
|
943 | |||
| 944 | if profileIndex > maxIndex: |
|
944 | if profileIndex > maxIndex: | |
| 945 | return False |
|
945 | return False | |
| 946 |
|
946 | |||
| 947 | return True |
|
947 | return True | |
| 948 |
|
948 | |||
| 949 | def isThisProfileInList(self, profileIndex, profileList): |
|
949 | def isThisProfileInList(self, profileIndex, profileList): | |
| 950 |
|
950 | |||
| 951 | if profileIndex not in profileList: |
|
951 | if profileIndex not in profileList: | |
| 952 | return False |
|
952 | return False | |
| 953 |
|
953 | |||
| 954 | return True |
|
954 | return True | |
| 955 |
|
955 | |||
| 956 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
956 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): | |
| 957 | #print("before",dataOut.data.shape) |
|
957 | #print("before",dataOut.data.shape) | |
| 958 | """ |
|
958 | """ | |
| 959 | ProfileSelector: |
|
959 | ProfileSelector: | |
| 960 |
|
960 | |||
| 961 | Inputs: |
|
961 | Inputs: | |
| 962 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
962 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) | |
| 963 |
|
963 | |||
| 964 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
964 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) | |
| 965 |
|
965 | |||
| 966 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
966 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) | |
| 967 |
|
967 | |||
| 968 | """ |
|
968 | """ | |
| 969 |
|
969 | |||
| 970 | if rangeList is not None: |
|
970 | if rangeList is not None: | |
| 971 | if type(rangeList[0]) not in (tuple, list): |
|
971 | if type(rangeList[0]) not in (tuple, list): | |
| 972 | rangeList = [rangeList] |
|
972 | rangeList = [rangeList] | |
| 973 |
|
973 | |||
| 974 | dataOut.flagNoData = True |
|
974 | dataOut.flagNoData = True | |
| 975 |
|
975 | |||
| 976 | if dataOut.flagDataAsBlock: |
|
976 | if dataOut.flagDataAsBlock: | |
| 977 | """ |
|
977 | """ | |
| 978 | data dimension = [nChannels, nProfiles, nHeis] |
|
978 | data dimension = [nChannels, nProfiles, nHeis] | |
| 979 | """ |
|
979 | """ | |
| 980 | if profileList != None: |
|
980 | if profileList != None: | |
| 981 | dataOut.data = dataOut.data[:,profileList,:] |
|
981 | dataOut.data = dataOut.data[:,profileList,:] | |
| 982 |
|
982 | |||
| 983 | if profileRangeList != None: |
|
983 | if profileRangeList != None: | |
| 984 | minIndex = profileRangeList[0] |
|
984 | minIndex = profileRangeList[0] | |
| 985 | maxIndex = profileRangeList[1] |
|
985 | maxIndex = profileRangeList[1] | |
| 986 | profileList = list(range(minIndex, maxIndex+1)) |
|
986 | profileList = list(range(minIndex, maxIndex+1)) | |
| 987 |
|
987 | |||
| 988 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
988 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] | |
| 989 |
|
989 | |||
| 990 | if rangeList != None: |
|
990 | if rangeList != None: | |
| 991 |
|
991 | |||
| 992 | profileList = [] |
|
992 | profileList = [] | |
| 993 |
|
993 | |||
| 994 | for thisRange in rangeList: |
|
994 | for thisRange in rangeList: | |
| 995 | minIndex = thisRange[0] |
|
995 | minIndex = thisRange[0] | |
| 996 | maxIndex = thisRange[1] |
|
996 | maxIndex = thisRange[1] | |
| 997 |
|
997 | |||
| 998 | profileList.extend(list(range(minIndex, maxIndex+1))) |
|
998 | profileList.extend(list(range(minIndex, maxIndex+1))) | |
| 999 |
|
999 | |||
| 1000 | dataOut.data = dataOut.data[:,profileList,:] |
|
1000 | dataOut.data = dataOut.data[:,profileList,:] | |
| 1001 |
|
1001 | |||
| 1002 | dataOut.nProfiles = len(profileList) |
|
1002 | dataOut.nProfiles = len(profileList) | |
| 1003 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
1003 | dataOut.profileIndex = dataOut.nProfiles - 1 | |
| 1004 | dataOut.flagNoData = False |
|
1004 | dataOut.flagNoData = False | |
| 1005 | #print(dataOut.data.shape) |
|
1005 | #print(dataOut.data.shape) | |
| 1006 | return dataOut |
|
1006 | return dataOut | |
| 1007 |
|
1007 | |||
| 1008 | """ |
|
1008 | """ | |
| 1009 | data dimension = [nChannels, nHeis] |
|
1009 | data dimension = [nChannels, nHeis] | |
| 1010 | """ |
|
1010 | """ | |
| 1011 |
|
1011 | |||
| 1012 | if profileList != None: |
|
1012 | if profileList != None: | |
| 1013 |
|
1013 | |||
| 1014 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
1014 | if self.isThisProfileInList(dataOut.profileIndex, profileList): | |
| 1015 |
|
1015 | |||
| 1016 | self.nProfiles = len(profileList) |
|
1016 | self.nProfiles = len(profileList) | |
| 1017 | dataOut.nProfiles = self.nProfiles |
|
1017 | dataOut.nProfiles = self.nProfiles | |
| 1018 | dataOut.profileIndex = self.profileIndex |
|
1018 | dataOut.profileIndex = self.profileIndex | |
| 1019 | dataOut.flagNoData = False |
|
1019 | dataOut.flagNoData = False | |
| 1020 |
|
1020 | |||
| 1021 | self.incProfileIndex() |
|
1021 | self.incProfileIndex() | |
| 1022 | return dataOut |
|
1022 | return dataOut | |
| 1023 |
|
1023 | |||
| 1024 | if profileRangeList != None: |
|
1024 | if profileRangeList != None: | |
| 1025 |
|
1025 | |||
| 1026 | minIndex = profileRangeList[0] |
|
1026 | minIndex = profileRangeList[0] | |
| 1027 | maxIndex = profileRangeList[1] |
|
1027 | maxIndex = profileRangeList[1] | |
| 1028 |
|
1028 | |||
| 1029 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1029 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 1030 |
|
1030 | |||
| 1031 | self.nProfiles = maxIndex - minIndex + 1 |
|
1031 | self.nProfiles = maxIndex - minIndex + 1 | |
| 1032 | dataOut.nProfiles = self.nProfiles |
|
1032 | dataOut.nProfiles = self.nProfiles | |
| 1033 | dataOut.profileIndex = self.profileIndex |
|
1033 | dataOut.profileIndex = self.profileIndex | |
| 1034 | dataOut.flagNoData = False |
|
1034 | dataOut.flagNoData = False | |
| 1035 |
|
1035 | |||
| 1036 | self.incProfileIndex() |
|
1036 | self.incProfileIndex() | |
| 1037 | return dataOut |
|
1037 | return dataOut | |
| 1038 |
|
1038 | |||
| 1039 | if rangeList != None: |
|
1039 | if rangeList != None: | |
| 1040 |
|
1040 | |||
| 1041 | nProfiles = 0 |
|
1041 | nProfiles = 0 | |
| 1042 |
|
1042 | |||
| 1043 | for thisRange in rangeList: |
|
1043 | for thisRange in rangeList: | |
| 1044 | minIndex = thisRange[0] |
|
1044 | minIndex = thisRange[0] | |
| 1045 | maxIndex = thisRange[1] |
|
1045 | maxIndex = thisRange[1] | |
| 1046 |
|
1046 | |||
| 1047 | nProfiles += maxIndex - minIndex + 1 |
|
1047 | nProfiles += maxIndex - minIndex + 1 | |
| 1048 |
|
1048 | |||
| 1049 | for thisRange in rangeList: |
|
1049 | for thisRange in rangeList: | |
| 1050 |
|
1050 | |||
| 1051 | minIndex = thisRange[0] |
|
1051 | minIndex = thisRange[0] | |
| 1052 | maxIndex = thisRange[1] |
|
1052 | maxIndex = thisRange[1] | |
| 1053 |
|
1053 | |||
| 1054 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
1054 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
| 1055 |
|
1055 | |||
| 1056 | self.nProfiles = nProfiles |
|
1056 | self.nProfiles = nProfiles | |
| 1057 | dataOut.nProfiles = self.nProfiles |
|
1057 | dataOut.nProfiles = self.nProfiles | |
| 1058 | dataOut.profileIndex = self.profileIndex |
|
1058 | dataOut.profileIndex = self.profileIndex | |
| 1059 | dataOut.flagNoData = False |
|
1059 | dataOut.flagNoData = False | |
| 1060 |
|
1060 | |||
| 1061 | self.incProfileIndex() |
|
1061 | self.incProfileIndex() | |
| 1062 |
|
1062 | |||
| 1063 | break |
|
1063 | break | |
| 1064 |
|
1064 | |||
| 1065 | return dataOut |
|
1065 | return dataOut | |
| 1066 |
|
1066 | |||
| 1067 |
|
1067 | |||
| 1068 | if beam != None: #beam is only for AMISR data |
|
1068 | if beam != None: #beam is only for AMISR data | |
| 1069 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
1069 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): | |
| 1070 | dataOut.flagNoData = False |
|
1070 | dataOut.flagNoData = False | |
| 1071 | dataOut.profileIndex = self.profileIndex |
|
1071 | dataOut.profileIndex = self.profileIndex | |
| 1072 |
|
1072 | |||
| 1073 | self.incProfileIndex() |
|
1073 | self.incProfileIndex() | |
| 1074 |
|
1074 | |||
| 1075 | return dataOut |
|
1075 | return dataOut | |
| 1076 |
|
1076 | |||
| 1077 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") |
|
1077 | raise ValueError("ProfileSelector needs profileList, profileRangeList or rangeList parameter") | |
| 1078 |
|
1078 | |||
| 1079 |
|
1079 | |||
| 1080 | class Reshaper(Operation): |
|
1080 | class Reshaper(Operation): | |
| 1081 |
|
1081 | |||
| 1082 | def __init__(self, **kwargs): |
|
1082 | def __init__(self, **kwargs): | |
| 1083 |
|
1083 | |||
| 1084 | Operation.__init__(self, **kwargs) |
|
1084 | Operation.__init__(self, **kwargs) | |
| 1085 |
|
1085 | |||
| 1086 | self.__buffer = None |
|
1086 | self.__buffer = None | |
| 1087 | self.__nitems = 0 |
|
1087 | self.__nitems = 0 | |
| 1088 |
|
1088 | |||
| 1089 | def __appendProfile(self, dataOut, nTxs): |
|
1089 | def __appendProfile(self, dataOut, nTxs): | |
| 1090 |
|
1090 | |||
| 1091 | if self.__buffer is None: |
|
1091 | if self.__buffer is None: | |
| 1092 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
1092 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) | |
| 1093 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
1093 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) | |
| 1094 |
|
1094 | |||
| 1095 | ini = dataOut.nHeights * self.__nitems |
|
1095 | ini = dataOut.nHeights * self.__nitems | |
| 1096 | end = ini + dataOut.nHeights |
|
1096 | end = ini + dataOut.nHeights | |
| 1097 |
|
1097 | |||
| 1098 | self.__buffer[:, ini:end] = dataOut.data |
|
1098 | self.__buffer[:, ini:end] = dataOut.data | |
| 1099 |
|
1099 | |||
| 1100 | self.__nitems += 1 |
|
1100 | self.__nitems += 1 | |
| 1101 |
|
1101 | |||
| 1102 | return int(self.__nitems*nTxs) |
|
1102 | return int(self.__nitems*nTxs) | |
| 1103 |
|
1103 | |||
| 1104 | def __getBuffer(self): |
|
1104 | def __getBuffer(self): | |
| 1105 |
|
1105 | |||
| 1106 | if self.__nitems == int(1./self.__nTxs): |
|
1106 | if self.__nitems == int(1./self.__nTxs): | |
| 1107 |
|
1107 | |||
| 1108 | self.__nitems = 0 |
|
1108 | self.__nitems = 0 | |
| 1109 |
|
1109 | |||
| 1110 | return self.__buffer.copy() |
|
1110 | return self.__buffer.copy() | |
| 1111 |
|
1111 | |||
| 1112 | return None |
|
1112 | return None | |
| 1113 |
|
1113 | |||
| 1114 | def __checkInputs(self, dataOut, shape, nTxs): |
|
1114 | def __checkInputs(self, dataOut, shape, nTxs): | |
| 1115 |
|
1115 | |||
| 1116 | if shape is None and nTxs is None: |
|
1116 | if shape is None and nTxs is None: | |
| 1117 | raise ValueError("Reshaper: shape of factor should be defined") |
|
1117 | raise ValueError("Reshaper: shape of factor should be defined") | |
| 1118 |
|
1118 | |||
| 1119 | if nTxs: |
|
1119 | if nTxs: | |
| 1120 | if nTxs < 0: |
|
1120 | if nTxs < 0: | |
| 1121 | raise ValueError("nTxs should be greater than 0") |
|
1121 | raise ValueError("nTxs should be greater than 0") | |
| 1122 |
|
1122 | |||
| 1123 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
1123 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: | |
| 1124 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) |
|
1124 | raise ValueError("nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs))) | |
| 1125 |
|
1125 | |||
| 1126 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
1126 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] | |
| 1127 |
|
1127 | |||
| 1128 | return shape, nTxs |
|
1128 | return shape, nTxs | |
| 1129 |
|
1129 | |||
| 1130 | if len(shape) != 2 and len(shape) != 3: |
|
1130 | if len(shape) != 2 and len(shape) != 3: | |
| 1131 | 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)) |
|
1131 | 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)) | |
| 1132 |
|
1132 | |||
| 1133 | if len(shape) == 2: |
|
1133 | if len(shape) == 2: | |
| 1134 | shape_tuple = [dataOut.nChannels] |
|
1134 | shape_tuple = [dataOut.nChannels] | |
| 1135 | shape_tuple.extend(shape) |
|
1135 | shape_tuple.extend(shape) | |
| 1136 | else: |
|
1136 | else: | |
| 1137 | shape_tuple = list(shape) |
|
1137 | shape_tuple = list(shape) | |
| 1138 |
|
1138 | |||
| 1139 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
1139 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles | |
| 1140 |
|
1140 | |||
| 1141 | return shape_tuple, nTxs |
|
1141 | return shape_tuple, nTxs | |
| 1142 |
|
1142 | |||
| 1143 | def run(self, dataOut, shape=None, nTxs=None): |
|
1143 | def run(self, dataOut, shape=None, nTxs=None): | |
| 1144 |
|
1144 | |||
| 1145 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
1145 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) | |
| 1146 |
|
1146 | |||
| 1147 | dataOut.flagNoData = True |
|
1147 | dataOut.flagNoData = True | |
| 1148 | profileIndex = None |
|
1148 | profileIndex = None | |
| 1149 |
|
1149 | |||
| 1150 | if dataOut.flagDataAsBlock: |
|
1150 | if dataOut.flagDataAsBlock: | |
| 1151 |
|
1151 | |||
| 1152 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
1152 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) | |
| 1153 | dataOut.flagNoData = False |
|
1153 | dataOut.flagNoData = False | |
| 1154 |
|
1154 | |||
| 1155 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
1155 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 | |
| 1156 |
|
1156 | |||
| 1157 | else: |
|
1157 | else: | |
| 1158 |
|
1158 | |||
| 1159 | if self.__nTxs < 1: |
|
1159 | if self.__nTxs < 1: | |
| 1160 |
|
1160 | |||
| 1161 | self.__appendProfile(dataOut, self.__nTxs) |
|
1161 | self.__appendProfile(dataOut, self.__nTxs) | |
| 1162 | new_data = self.__getBuffer() |
|
1162 | new_data = self.__getBuffer() | |
| 1163 |
|
1163 | |||
| 1164 | if new_data is not None: |
|
1164 | if new_data is not None: | |
| 1165 | dataOut.data = new_data |
|
1165 | dataOut.data = new_data | |
| 1166 | dataOut.flagNoData = False |
|
1166 | dataOut.flagNoData = False | |
| 1167 |
|
1167 | |||
| 1168 | profileIndex = dataOut.profileIndex*nTxs |
|
1168 | profileIndex = dataOut.profileIndex*nTxs | |
| 1169 |
|
1169 | |||
| 1170 | else: |
|
1170 | else: | |
| 1171 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") |
|
1171 | raise ValueError("nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)") | |
| 1172 |
|
1172 | |||
| 1173 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1173 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1174 |
|
1174 | |||
| 1175 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
1175 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] | |
| 1176 |
|
1176 | |||
| 1177 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
1177 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) | |
| 1178 |
|
1178 | |||
| 1179 | dataOut.profileIndex = profileIndex |
|
1179 | dataOut.profileIndex = profileIndex | |
| 1180 |
|
1180 | |||
| 1181 | dataOut.ippSeconds /= self.__nTxs |
|
1181 | dataOut.ippSeconds /= self.__nTxs | |
| 1182 |
|
1182 | |||
| 1183 | return dataOut |
|
1183 | return dataOut | |
| 1184 |
|
1184 | |||
| 1185 | class SplitProfiles(Operation): |
|
1185 | class SplitProfiles(Operation): | |
| 1186 |
|
1186 | |||
| 1187 | def __init__(self, **kwargs): |
|
1187 | def __init__(self, **kwargs): | |
| 1188 |
|
1188 | |||
| 1189 | Operation.__init__(self, **kwargs) |
|
1189 | Operation.__init__(self, **kwargs) | |
| 1190 |
|
1190 | |||
| 1191 | def run(self, dataOut, n): |
|
1191 | def run(self, dataOut, n): | |
| 1192 |
|
1192 | |||
| 1193 | dataOut.flagNoData = True |
|
1193 | dataOut.flagNoData = True | |
| 1194 | profileIndex = None |
|
1194 | profileIndex = None | |
| 1195 |
|
1195 | |||
| 1196 | if dataOut.flagDataAsBlock: |
|
1196 | if dataOut.flagDataAsBlock: | |
| 1197 |
|
1197 | |||
| 1198 | #nchannels, nprofiles, nsamples |
|
1198 | #nchannels, nprofiles, nsamples | |
| 1199 | shape = dataOut.data.shape |
|
1199 | shape = dataOut.data.shape | |
| 1200 |
|
1200 | |||
| 1201 | if shape[2] % n != 0: |
|
1201 | if shape[2] % n != 0: | |
| 1202 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) |
|
1202 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[2])) | |
| 1203 |
|
1203 | |||
| 1204 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) |
|
1204 | new_shape = shape[0], shape[1]*n, int(shape[2]/n) | |
| 1205 |
|
1205 | |||
| 1206 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1206 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1207 | dataOut.flagNoData = False |
|
1207 | dataOut.flagNoData = False | |
| 1208 |
|
1208 | |||
| 1209 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
1209 | profileIndex = int(dataOut.nProfiles/n) - 1 | |
| 1210 |
|
1210 | |||
| 1211 | else: |
|
1211 | else: | |
| 1212 |
|
1212 | |||
| 1213 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") |
|
1213 | raise ValueError("Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)") | |
| 1214 |
|
1214 | |||
| 1215 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1215 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1216 |
|
1216 | |||
| 1217 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
1217 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] | |
| 1218 |
|
1218 | |||
| 1219 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
1219 | dataOut.nProfiles = int(dataOut.nProfiles*n) | |
| 1220 |
|
1220 | |||
| 1221 | dataOut.profileIndex = profileIndex |
|
1221 | dataOut.profileIndex = profileIndex | |
| 1222 |
|
1222 | |||
| 1223 | dataOut.ippSeconds /= n |
|
1223 | dataOut.ippSeconds /= n | |
| 1224 |
|
1224 | |||
| 1225 | return dataOut |
|
1225 | return dataOut | |
| 1226 |
|
1226 | |||
| 1227 | class CombineProfiles(Operation): |
|
1227 | class CombineProfiles(Operation): | |
| 1228 | def __init__(self, **kwargs): |
|
1228 | def __init__(self, **kwargs): | |
| 1229 |
|
1229 | |||
| 1230 | Operation.__init__(self, **kwargs) |
|
1230 | Operation.__init__(self, **kwargs) | |
| 1231 |
|
1231 | |||
| 1232 | self.__remData = None |
|
1232 | self.__remData = None | |
| 1233 | self.__profileIndex = 0 |
|
1233 | self.__profileIndex = 0 | |
| 1234 |
|
1234 | |||
| 1235 | def run(self, dataOut, n): |
|
1235 | def run(self, dataOut, n): | |
| 1236 |
|
1236 | |||
| 1237 | dataOut.flagNoData = True |
|
1237 | dataOut.flagNoData = True | |
| 1238 | profileIndex = None |
|
1238 | profileIndex = None | |
| 1239 |
|
1239 | |||
| 1240 | if dataOut.flagDataAsBlock: |
|
1240 | if dataOut.flagDataAsBlock: | |
| 1241 |
|
1241 | |||
| 1242 | #nchannels, nprofiles, nsamples |
|
1242 | #nchannels, nprofiles, nsamples | |
| 1243 | shape = dataOut.data.shape |
|
1243 | shape = dataOut.data.shape | |
| 1244 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
1244 | new_shape = shape[0], shape[1]/n, shape[2]*n | |
| 1245 |
|
1245 | |||
| 1246 | if shape[1] % n != 0: |
|
1246 | if shape[1] % n != 0: | |
| 1247 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) |
|
1247 | raise ValueError("Could not split the data, n=%d has to be multiple of %d" %(n, shape[1])) | |
| 1248 |
|
1248 | |||
| 1249 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1249 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
| 1250 | dataOut.flagNoData = False |
|
1250 | dataOut.flagNoData = False | |
| 1251 |
|
1251 | |||
| 1252 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
1252 | profileIndex = int(dataOut.nProfiles*n) - 1 | |
| 1253 |
|
1253 | |||
| 1254 | else: |
|
1254 | else: | |
| 1255 |
|
1255 | |||
| 1256 | #nchannels, nsamples |
|
1256 | #nchannels, nsamples | |
| 1257 | if self.__remData is None: |
|
1257 | if self.__remData is None: | |
| 1258 | newData = dataOut.data |
|
1258 | newData = dataOut.data | |
| 1259 | else: |
|
1259 | else: | |
| 1260 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
1260 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) | |
| 1261 |
|
1261 | |||
| 1262 | self.__profileIndex += 1 |
|
1262 | self.__profileIndex += 1 | |
| 1263 |
|
1263 | |||
| 1264 | if self.__profileIndex < n: |
|
1264 | if self.__profileIndex < n: | |
| 1265 | self.__remData = newData |
|
1265 | self.__remData = newData | |
| 1266 | #continue |
|
1266 | #continue | |
| 1267 | return |
|
1267 | return | |
| 1268 |
|
1268 | |||
| 1269 | self.__profileIndex = 0 |
|
1269 | self.__profileIndex = 0 | |
| 1270 | self.__remData = None |
|
1270 | self.__remData = None | |
| 1271 |
|
1271 | |||
| 1272 | dataOut.data = newData |
|
1272 | dataOut.data = newData | |
| 1273 | dataOut.flagNoData = False |
|
1273 | dataOut.flagNoData = False | |
| 1274 |
|
1274 | |||
| 1275 | profileIndex = dataOut.profileIndex/n |
|
1275 | profileIndex = dataOut.profileIndex/n | |
| 1276 |
|
1276 | |||
| 1277 |
|
1277 | |||
| 1278 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1278 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1279 |
|
1279 | |||
| 1280 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
1280 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] | |
| 1281 |
|
1281 | |||
| 1282 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1282 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1283 |
|
1283 | |||
| 1284 | dataOut.profileIndex = profileIndex |
|
1284 | dataOut.profileIndex = profileIndex | |
| 1285 |
|
1285 | |||
| 1286 | dataOut.ippSeconds *= n |
|
1286 | dataOut.ippSeconds *= n | |
| 1287 |
|
1287 | |||
| 1288 | return dataOut |
|
1288 | return dataOut | |
| 1289 |
|
1289 | |||
| 1290 | class PulsePair(Operation): |
|
1290 | class PulsePair(Operation): | |
| 1291 | ''' |
|
1291 | ''' | |
| 1292 | Function PulsePair(Signal Power, Velocity) |
|
1292 | Function PulsePair(Signal Power, Velocity) | |
| 1293 | The real component of Lag[0] provides Intensity Information |
|
1293 | The real component of Lag[0] provides Intensity Information | |
| 1294 | The imag component of Lag[1] Phase provides Velocity Information |
|
1294 | The imag component of Lag[1] Phase provides Velocity Information | |
| 1295 |
|
1295 | |||
| 1296 | Configuration Parameters: |
|
1296 | Configuration Parameters: | |
| 1297 | nPRF = Number of Several PRF |
|
1297 | nPRF = Number of Several PRF | |
| 1298 | theta = Degree Azimuth angel Boundaries |
|
1298 | theta = Degree Azimuth angel Boundaries | |
| 1299 |
|
1299 | |||
| 1300 | Input: |
|
1300 | Input: | |
| 1301 | self.dataOut |
|
1301 | self.dataOut | |
| 1302 | lag[N] |
|
1302 | lag[N] | |
| 1303 | Affected: |
|
1303 | Affected: | |
| 1304 | self.dataOut.spc |
|
1304 | self.dataOut.spc | |
| 1305 | ''' |
|
1305 | ''' | |
| 1306 | isConfig = False |
|
1306 | isConfig = False | |
| 1307 | __profIndex = 0 |
|
1307 | __profIndex = 0 | |
| 1308 | __initime = None |
|
1308 | __initime = None | |
| 1309 | __lastdatatime = None |
|
1309 | __lastdatatime = None | |
| 1310 | __buffer = None |
|
1310 | __buffer = None | |
| 1311 | noise = None |
|
1311 | noise = None | |
| 1312 | __dataReady = False |
|
1312 | __dataReady = False | |
| 1313 | n = None |
|
1313 | n = None | |
| 1314 | __nch = 0 |
|
1314 | __nch = 0 | |
| 1315 | __nHeis = 0 |
|
1315 | __nHeis = 0 | |
| 1316 | removeDC = False |
|
1316 | removeDC = False | |
| 1317 | ipp = None |
|
1317 | ipp = None | |
| 1318 | lambda_ = 0 |
|
1318 | lambda_ = 0 | |
| 1319 |
|
1319 | |||
| 1320 | def __init__(self,**kwargs): |
|
1320 | def __init__(self,**kwargs): | |
| 1321 | Operation.__init__(self,**kwargs) |
|
1321 | Operation.__init__(self,**kwargs) | |
| 1322 |
|
1322 | |||
| 1323 | def setup(self, dataOut, n = None, removeDC=False): |
|
1323 | def setup(self, dataOut, n = None, removeDC=False): | |
| 1324 | ''' |
|
1324 | ''' | |
| 1325 | n= Numero de PRF's de entrada |
|
1325 | n= Numero de PRF's de entrada | |
| 1326 | ''' |
|
1326 | ''' | |
| 1327 | self.__initime = None |
|
1327 | self.__initime = None | |
| 1328 | ####print("[INICIO]-setup del METODO PULSE PAIR") |
|
1328 | ####print("[INICIO]-setup del METODO PULSE PAIR") | |
| 1329 | self.__lastdatatime = 0 |
|
1329 | self.__lastdatatime = 0 | |
| 1330 | self.__dataReady = False |
|
1330 | self.__dataReady = False | |
| 1331 | self.__buffer = 0 |
|
1331 | self.__buffer = 0 | |
| 1332 | self.__profIndex = 0 |
|
1332 | self.__profIndex = 0 | |
| 1333 | self.noise = None |
|
1333 | self.noise = None | |
| 1334 | self.__nch = dataOut.nChannels |
|
1334 | self.__nch = dataOut.nChannels | |
| 1335 | self.__nHeis = dataOut.nHeights |
|
1335 | self.__nHeis = dataOut.nHeights | |
| 1336 | self.removeDC = removeDC |
|
1336 | self.removeDC = removeDC | |
| 1337 | self.lambda_ = 3.0e8/(9345.0e6) |
|
1337 | self.lambda_ = 3.0e8/(9345.0e6) | |
| 1338 | self.ippSec = dataOut.ippSeconds |
|
1338 | self.ippSec = dataOut.ippSeconds | |
| 1339 | self.nCohInt = dataOut.nCohInt |
|
1339 | self.nCohInt = dataOut.nCohInt | |
| 1340 | ####print("IPPseconds",dataOut.ippSeconds) |
|
1340 | ####print("IPPseconds",dataOut.ippSeconds) | |
| 1341 | ####print("ELVALOR DE n es:", n) |
|
1341 | ####print("ELVALOR DE n es:", n) | |
| 1342 | if n == None: |
|
1342 | if n == None: | |
| 1343 | raise ValueError("n should be specified.") |
|
1343 | raise ValueError("n should be specified.") | |
| 1344 |
|
1344 | |||
| 1345 | if n != None: |
|
1345 | if n != None: | |
| 1346 | if n<2: |
|
1346 | if n<2: | |
| 1347 | raise ValueError("n should be greater than 2") |
|
1347 | raise ValueError("n should be greater than 2") | |
| 1348 |
|
1348 | |||
| 1349 | self.n = n |
|
1349 | self.n = n | |
| 1350 | self.__nProf = n |
|
1350 | self.__nProf = n | |
| 1351 |
|
1351 | |||
| 1352 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
1352 | self.__buffer = numpy.zeros((dataOut.nChannels, | |
| 1353 | n, |
|
1353 | n, | |
| 1354 | dataOut.nHeights), |
|
1354 | dataOut.nHeights), | |
| 1355 | dtype='complex') |
|
1355 | dtype='complex') | |
| 1356 |
|
1356 | |||
| 1357 | def putData(self,data): |
|
1357 | def putData(self,data): | |
| 1358 | ''' |
|
1358 | ''' | |
| 1359 | Add a profile to he __buffer and increase in one the __profiel Index |
|
1359 | Add a profile to he __buffer and increase in one the __profiel Index | |
| 1360 | ''' |
|
1360 | ''' | |
| 1361 | self.__buffer[:,self.__profIndex,:]= data |
|
1361 | self.__buffer[:,self.__profIndex,:]= data | |
| 1362 | self.__profIndex += 1 |
|
1362 | self.__profIndex += 1 | |
| 1363 | return |
|
1363 | return | |
| 1364 |
|
1364 | |||
| 1365 | def pushData(self,dataOut): |
|
1365 | def pushData(self,dataOut): | |
| 1366 | ''' |
|
1366 | ''' | |
| 1367 | Return the PULSEPAIR and the profiles used in the operation |
|
1367 | Return the PULSEPAIR and the profiles used in the operation | |
| 1368 | Affected : self.__profileIndex |
|
1368 | Affected : self.__profileIndex | |
| 1369 | ''' |
|
1369 | ''' | |
| 1370 | #----------------- Remove DC----------------------------------- |
|
1370 | #----------------- Remove DC----------------------------------- | |
| 1371 | if self.removeDC==True: |
|
1371 | if self.removeDC==True: | |
| 1372 | mean = numpy.mean(self.__buffer,1) |
|
1372 | mean = numpy.mean(self.__buffer,1) | |
| 1373 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
1373 | tmp = mean.reshape(self.__nch,1,self.__nHeis) | |
| 1374 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
1374 | dc= numpy.tile(tmp,[1,self.__nProf,1]) | |
| 1375 | self.__buffer = self.__buffer - dc |
|
1375 | self.__buffer = self.__buffer - dc | |
| 1376 | #------------------Calculo de Potencia ------------------------ |
|
1376 | #------------------Calculo de Potencia ------------------------ | |
| 1377 | pair0 = self.__buffer*numpy.conj(self.__buffer) |
|
1377 | pair0 = self.__buffer*numpy.conj(self.__buffer) | |
| 1378 | pair0 = pair0.real |
|
1378 | pair0 = pair0.real | |
| 1379 | lag_0 = numpy.sum(pair0,1) |
|
1379 | lag_0 = numpy.sum(pair0,1) | |
| 1380 | #-----------------Calculo de Cscp------------------------------ New |
|
1380 | #-----------------Calculo de Cscp------------------------------ New | |
| 1381 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] |
|
1381 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] | |
| 1382 | #------------------Calculo de Ruido x canal-------------------- |
|
1382 | #------------------Calculo de Ruido x canal-------------------- | |
| 1383 | self.noise = numpy.zeros(self.__nch) |
|
1383 | self.noise = numpy.zeros(self.__nch) | |
| 1384 | for i in range(self.__nch): |
|
1384 | for i in range(self.__nch): | |
| 1385 | daux = numpy.sort(pair0[i,:,:],axis= None) |
|
1385 | daux = numpy.sort(pair0[i,:,:],axis= None) | |
| 1386 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) |
|
1386 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) | |
| 1387 |
|
1387 | |||
| 1388 | self.noise = self.noise.reshape(self.__nch,1) |
|
1388 | self.noise = self.noise.reshape(self.__nch,1) | |
| 1389 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) |
|
1389 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) | |
| 1390 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) |
|
1390 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) | |
| 1391 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) |
|
1391 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) | |
| 1392 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- |
|
1392 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- | |
| 1393 | #------------------ P= S+N ,P=lag_0/N --------------------------------- |
|
1393 | #------------------ P= S+N ,P=lag_0/N --------------------------------- | |
| 1394 | #-------------------- Power -------------------------------------------------- |
|
1394 | #-------------------- Power -------------------------------------------------- | |
| 1395 | data_power = lag_0/(self.n*self.nCohInt) |
|
1395 | data_power = lag_0/(self.n*self.nCohInt) | |
| 1396 | #--------------------CCF------------------------------------------------------ |
|
1396 | #--------------------CCF------------------------------------------------------ | |
| 1397 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) |
|
1397 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) | |
| 1398 | #------------------ Senal -------------------------------------------------- |
|
1398 | #------------------ Senal -------------------------------------------------- | |
| 1399 | data_intensity = pair0 - noise_buffer |
|
1399 | data_intensity = pair0 - noise_buffer | |
| 1400 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) |
|
1400 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) | |
| 1401 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) |
|
1401 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) | |
| 1402 | for i in range(self.__nch): |
|
1402 | for i in range(self.__nch): | |
| 1403 | for j in range(self.__nHeis): |
|
1403 | for j in range(self.__nHeis): | |
| 1404 | if data_intensity[i][j] < 0: |
|
1404 | if data_intensity[i][j] < 0: | |
| 1405 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) |
|
1405 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) | |
| 1406 |
|
1406 | |||
| 1407 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- |
|
1407 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- | |
| 1408 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
1408 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) | |
| 1409 | lag_1 = numpy.sum(pair1,1) |
|
1409 | lag_1 = numpy.sum(pair1,1) | |
| 1410 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) |
|
1410 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) | |
| 1411 | data_velocity = (self.lambda_/2.0)*data_freq |
|
1411 | data_velocity = (self.lambda_/2.0)*data_freq | |
| 1412 |
|
1412 | |||
| 1413 | #---------------- Potencia promedio estimada de la Senal----------- |
|
1413 | #---------------- Potencia promedio estimada de la Senal----------- | |
| 1414 | lag_0 = lag_0/self.n |
|
1414 | lag_0 = lag_0/self.n | |
| 1415 | S = lag_0-self.noise |
|
1415 | S = lag_0-self.noise | |
| 1416 |
|
1416 | |||
| 1417 | #---------------- Frecuencia Doppler promedio --------------------- |
|
1417 | #---------------- Frecuencia Doppler promedio --------------------- | |
| 1418 | lag_1 = lag_1/(self.n-1) |
|
1418 | lag_1 = lag_1/(self.n-1) | |
| 1419 | R1 = numpy.abs(lag_1) |
|
1419 | R1 = numpy.abs(lag_1) | |
| 1420 |
|
1420 | |||
| 1421 | #---------------- Calculo del SNR---------------------------------- |
|
1421 | #---------------- Calculo del SNR---------------------------------- | |
| 1422 | data_snrPP = S/self.noise |
|
1422 | data_snrPP = S/self.noise | |
| 1423 | for i in range(self.__nch): |
|
1423 | for i in range(self.__nch): | |
| 1424 | for j in range(self.__nHeis): |
|
1424 | for j in range(self.__nHeis): | |
| 1425 | if data_snrPP[i][j] < 1.e-20: |
|
1425 | if data_snrPP[i][j] < 1.e-20: | |
| 1426 | data_snrPP[i][j] = 1.e-20 |
|
1426 | data_snrPP[i][j] = 1.e-20 | |
| 1427 |
|
1427 | |||
| 1428 | #----------------- Calculo del ancho espectral ---------------------- |
|
1428 | #----------------- Calculo del ancho espectral ---------------------- | |
| 1429 | L = S/R1 |
|
1429 | L = S/R1 | |
| 1430 | L = numpy.where(L<0,1,L) |
|
1430 | L = numpy.where(L<0,1,L) | |
| 1431 | L = numpy.log(L) |
|
1431 | L = numpy.log(L) | |
| 1432 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
1432 | tmp = numpy.sqrt(numpy.absolute(L)) | |
| 1433 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) |
|
1433 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) | |
| 1434 | n = self.__profIndex |
|
1434 | n = self.__profIndex | |
| 1435 |
|
1435 | |||
| 1436 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
1436 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') | |
| 1437 | self.__profIndex = 0 |
|
1437 | self.__profIndex = 0 | |
| 1438 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n |
|
1438 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n | |
| 1439 |
|
1439 | |||
| 1440 |
|
1440 | |||
| 1441 | def pulsePairbyProfiles(self,dataOut): |
|
1441 | def pulsePairbyProfiles(self,dataOut): | |
| 1442 |
|
1442 | |||
| 1443 | self.__dataReady = False |
|
1443 | self.__dataReady = False | |
| 1444 | data_power = None |
|
1444 | data_power = None | |
| 1445 | data_intensity = None |
|
1445 | data_intensity = None | |
| 1446 | data_velocity = None |
|
1446 | data_velocity = None | |
| 1447 | data_specwidth = None |
|
1447 | data_specwidth = None | |
| 1448 | data_snrPP = None |
|
1448 | data_snrPP = None | |
| 1449 | data_ccf = None |
|
1449 | data_ccf = None | |
| 1450 | self.putData(data=dataOut.data) |
|
1450 | self.putData(data=dataOut.data) | |
| 1451 | if self.__profIndex == self.n: |
|
1451 | if self.__profIndex == self.n: | |
| 1452 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) |
|
1452 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) | |
| 1453 | self.__dataReady = True |
|
1453 | self.__dataReady = True | |
| 1454 |
|
1454 | |||
| 1455 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf |
|
1455 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf | |
| 1456 |
|
1456 | |||
| 1457 |
|
1457 | |||
| 1458 | def pulsePairOp(self, dataOut, datatime= None): |
|
1458 | def pulsePairOp(self, dataOut, datatime= None): | |
| 1459 |
|
1459 | |||
| 1460 | if self.__initime == None: |
|
1460 | if self.__initime == None: | |
| 1461 | self.__initime = datatime |
|
1461 | self.__initime = datatime | |
| 1462 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut) |
|
1462 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut) | |
| 1463 | self.__lastdatatime = datatime |
|
1463 | self.__lastdatatime = datatime | |
| 1464 |
|
1464 | |||
| 1465 | if data_power is None: |
|
1465 | if data_power is None: | |
| 1466 | return None, None, None,None,None,None,None |
|
1466 | return None, None, None,None,None,None,None | |
| 1467 |
|
1467 | |||
| 1468 | avgdatatime = self.__initime |
|
1468 | avgdatatime = self.__initime | |
| 1469 | deltatime = datatime - self.__lastdatatime |
|
1469 | deltatime = datatime - self.__lastdatatime | |
| 1470 | self.__initime = datatime |
|
1470 | self.__initime = datatime | |
| 1471 |
|
1471 | |||
| 1472 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime |
|
1472 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime | |
| 1473 |
|
1473 | |||
| 1474 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
1474 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): | |
| 1475 | #print("hey") |
|
1475 | #print("hey") | |
| 1476 | #print(dataOut.data.shape) |
|
1476 | #print(dataOut.data.shape) | |
| 1477 | #exit(1) |
|
1477 | #exit(1) | |
| 1478 | #print(self.__profIndex) |
|
1478 | #print(self.__profIndex) | |
| 1479 | if not self.isConfig: |
|
1479 | if not self.isConfig: | |
| 1480 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
1480 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) | |
| 1481 | self.isConfig = True |
|
1481 | self.isConfig = True | |
| 1482 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) |
|
1482 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, dataOut.utctime) | |
| 1483 | dataOut.flagNoData = True |
|
1483 | dataOut.flagNoData = True | |
| 1484 |
|
1484 | |||
| 1485 | if self.__dataReady: |
|
1485 | if self.__dataReady: | |
| 1486 | ###print("READY ----------------------------------") |
|
1486 | ###print("READY ----------------------------------") | |
| 1487 | dataOut.nCohInt *= self.n |
|
1487 | dataOut.nCohInt *= self.n | |
| 1488 | dataOut.dataPP_POW = data_intensity # S |
|
1488 | dataOut.dataPP_POW = data_intensity # S | |
| 1489 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO |
|
1489 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO | |
| 1490 | dataOut.dataPP_DOP = data_velocity |
|
1490 | dataOut.dataPP_DOP = data_velocity | |
| 1491 | dataOut.dataPP_SNR = data_snrPP |
|
1491 | dataOut.dataPP_SNR = data_snrPP | |
| 1492 | dataOut.dataPP_WIDTH = data_specwidth |
|
1492 | dataOut.dataPP_WIDTH = data_specwidth | |
| 1493 | dataOut.dataPP_CCF = data_ccf |
|
1493 | dataOut.dataPP_CCF = data_ccf | |
| 1494 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
1494 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. | |
| 1495 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1495 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1496 | dataOut.utctime = avgdatatime |
|
1496 | dataOut.utctime = avgdatatime | |
| 1497 | dataOut.flagNoData = False |
|
1497 | dataOut.flagNoData = False | |
| 1498 | return dataOut |
|
1498 | return dataOut | |
| 1499 |
|
1499 | |||
| 1500 | class PulsePair_vRF(Operation): |
|
1500 | class PulsePair_vRF(Operation): | |
| 1501 | ''' |
|
1501 | ''' | |
| 1502 | Function PulsePair(Signal Power, Velocity) |
|
1502 | Function PulsePair(Signal Power, Velocity) | |
| 1503 | The real component of Lag[0] provides Intensity Information |
|
1503 | The real component of Lag[0] provides Intensity Information | |
| 1504 | The imag component of Lag[1] Phase provides Velocity Information |
|
1504 | The imag component of Lag[1] Phase provides Velocity Information | |
| 1505 |
|
1505 | |||
| 1506 | Configuration Parameters: |
|
1506 | Configuration Parameters: | |
| 1507 | nPRF = Number of Several PRF |
|
1507 | nPRF = Number of Several PRF | |
| 1508 | theta = Degree Azimuth angel Boundaries |
|
1508 | theta = Degree Azimuth angel Boundaries | |
| 1509 |
|
1509 | |||
| 1510 | Input: |
|
1510 | Input: | |
| 1511 | self.dataOut |
|
1511 | self.dataOut | |
| 1512 | lag[N] |
|
1512 | lag[N] | |
| 1513 | Affected: |
|
1513 | Affected: | |
| 1514 | self.dataOut.spc |
|
1514 | self.dataOut.spc | |
| 1515 | ''' |
|
1515 | ''' | |
| 1516 | isConfig = False |
|
1516 | isConfig = False | |
| 1517 | __profIndex = 0 |
|
1517 | __profIndex = 0 | |
| 1518 | __initime = None |
|
1518 | __initime = None | |
| 1519 | __lastdatatime = None |
|
1519 | __lastdatatime = None | |
| 1520 | __buffer = None |
|
1520 | __buffer = None | |
| 1521 | noise = None |
|
1521 | noise = None | |
| 1522 | __dataReady = False |
|
1522 | __dataReady = False | |
| 1523 | n = None |
|
1523 | n = None | |
| 1524 | __nch = 0 |
|
1524 | __nch = 0 | |
| 1525 | __nHeis = 0 |
|
1525 | __nHeis = 0 | |
| 1526 | removeDC = False |
|
1526 | removeDC = False | |
| 1527 | ipp = None |
|
1527 | ipp = None | |
| 1528 | lambda_ = 0 |
|
1528 | lambda_ = 0 | |
| 1529 |
|
1529 | |||
| 1530 | def __init__(self,**kwargs): |
|
1530 | def __init__(self,**kwargs): | |
| 1531 | Operation.__init__(self,**kwargs) |
|
1531 | Operation.__init__(self,**kwargs) | |
| 1532 |
|
1532 | |||
| 1533 | def setup(self, dataOut, n = None, removeDC=False): |
|
1533 | def setup(self, dataOut, n = None, removeDC=False): | |
| 1534 | ''' |
|
1534 | ''' | |
| 1535 | n= Numero de PRF's de entrada |
|
1535 | n= Numero de PRF's de entrada | |
| 1536 | ''' |
|
1536 | ''' | |
| 1537 | self.__initime = None |
|
1537 | self.__initime = None | |
| 1538 | ####print("[INICIO]-setup del METODO PULSE PAIR") |
|
1538 | ####print("[INICIO]-setup del METODO PULSE PAIR") | |
| 1539 | self.__lastdatatime = 0 |
|
1539 | self.__lastdatatime = 0 | |
| 1540 | self.__dataReady = False |
|
1540 | self.__dataReady = False | |
| 1541 | self.__buffer = 0 |
|
1541 | self.__buffer = 0 | |
| 1542 | self.__profIndex = 0 |
|
1542 | self.__profIndex = 0 | |
| 1543 | self.noise = None |
|
1543 | self.noise = None | |
| 1544 | self.__nch = dataOut.nChannels |
|
1544 | self.__nch = dataOut.nChannels | |
| 1545 | self.__nHeis = dataOut.nHeights |
|
1545 | self.__nHeis = dataOut.nHeights | |
| 1546 | self.removeDC = removeDC |
|
1546 | self.removeDC = removeDC | |
| 1547 | self.lambda_ = 3.0e8/(9345.0e6) |
|
1547 | self.lambda_ = 3.0e8/(9345.0e6) | |
| 1548 | self.ippSec = dataOut.ippSeconds |
|
1548 | self.ippSec = dataOut.ippSeconds | |
| 1549 | self.nCohInt = dataOut.nCohInt |
|
1549 | self.nCohInt = dataOut.nCohInt | |
| 1550 | ####print("IPPseconds",dataOut.ippSeconds) |
|
1550 | ####print("IPPseconds",dataOut.ippSeconds) | |
| 1551 | ####print("ELVALOR DE n es:", n) |
|
1551 | ####print("ELVALOR DE n es:", n) | |
| 1552 | if n == None: |
|
1552 | if n == None: | |
| 1553 | raise ValueError("n should be specified.") |
|
1553 | raise ValueError("n should be specified.") | |
| 1554 |
|
1554 | |||
| 1555 | if n != None: |
|
1555 | if n != None: | |
| 1556 | if n<2: |
|
1556 | if n<2: | |
| 1557 | raise ValueError("n should be greater than 2") |
|
1557 | raise ValueError("n should be greater than 2") | |
| 1558 |
|
1558 | |||
| 1559 | self.n = n |
|
1559 | self.n = n | |
| 1560 | self.__nProf = n |
|
1560 | self.__nProf = n | |
| 1561 |
|
1561 | |||
| 1562 | self.__buffer = numpy.zeros((dataOut.nChannels, |
|
1562 | self.__buffer = numpy.zeros((dataOut.nChannels, | |
| 1563 | n, |
|
1563 | n, | |
| 1564 | dataOut.nHeights), |
|
1564 | dataOut.nHeights), | |
| 1565 | dtype='complex') |
|
1565 | dtype='complex') | |
| 1566 |
|
1566 | |||
| 1567 | def putData(self,data): |
|
1567 | def putData(self,data): | |
| 1568 | ''' |
|
1568 | ''' | |
| 1569 | Add a profile to he __buffer and increase in one the __profiel Index |
|
1569 | Add a profile to he __buffer and increase in one the __profiel Index | |
| 1570 | ''' |
|
1570 | ''' | |
| 1571 | self.__buffer[:,self.__profIndex,:]= data |
|
1571 | self.__buffer[:,self.__profIndex,:]= data | |
| 1572 | self.__profIndex += 1 |
|
1572 | self.__profIndex += 1 | |
| 1573 | return |
|
1573 | return | |
| 1574 |
|
1574 | |||
| 1575 | def putDataByBlock(self,data,n): |
|
1575 | def putDataByBlock(self,data,n): | |
| 1576 | ''' |
|
1576 | ''' | |
| 1577 | Add a profile to he __buffer and increase in one the __profiel Index |
|
1577 | Add a profile to he __buffer and increase in one the __profiel Index | |
| 1578 | ''' |
|
1578 | ''' | |
| 1579 | self.__buffer[:]= data |
|
1579 | self.__buffer[:]= data | |
| 1580 | self.__profIndex = n |
|
1580 | self.__profIndex = n | |
| 1581 | return |
|
1581 | return | |
| 1582 |
|
1582 | |||
| 1583 | def pushData(self,dataOut): |
|
1583 | def pushData(self,dataOut): | |
| 1584 | ''' |
|
1584 | ''' | |
| 1585 | Return the PULSEPAIR and the profiles used in the operation |
|
1585 | Return the PULSEPAIR and the profiles used in the operation | |
| 1586 | Affected : self.__profileIndex |
|
1586 | Affected : self.__profileIndex | |
|
|
1587 | NOTA: | |||
|
|
1588 | 1.) Calculo de Potencia | |||
|
|
1589 | PdBm = 10 *log10(10*(I**2 + Q**2)) Unidades dBm | |||
|
|
1590 | self.__buffer = I + Qj | |||
|
|
1591 | ||||
|
|
1592 | 2.) Data decodificada | |||
|
|
1593 | Se toma como referencia el factor estimado en jrodata.py y se adiciona | |||
|
|
1594 | en PulsePair solo pwcode. | |||
|
|
1595 | if self.flagDecodeData: | |||
|
|
1596 | pwcode = numpy.sum(self.code[0]**2) | |||
|
|
1597 | normFactor = self.nProfiles * self.nIncohInt * self.nCohInt * pwcode * self.windowOfFilter | |||
|
|
1598 | 3.) hildebrand_sekhon | |||
|
|
1599 | Se pasa el arreglo de Potencia pair0 que contiene canales perfiles y altura dividiendole entre el | |||
|
|
1600 | factor pwcode. | |||
|
|
1601 | 4.) data_power | |||
|
|
1602 | Este parametro esta dividido por los factores: nro. perfiles, nro intCoh y pwcode | |||
|
|
1603 | 5.) lag_0 | |||
|
|
1604 | Este parametro esta dividido por los factores: nro. perfiles, nro intCoh y pwcode | |||
|
|
1605 | Igual a data_power | |||
|
|
1606 | ||||
| 1587 | ''' |
|
1607 | ''' | |
| 1588 | #----------------- Remove DC----------------------------------- |
|
1608 | #----------------- Remove DC----------------------------------- | |
| 1589 | if self.removeDC==True: |
|
1609 | if self.removeDC==True: | |
| 1590 | mean = numpy.mean(self.__buffer,1) |
|
1610 | mean = numpy.mean(self.__buffer,1) | |
| 1591 | tmp = mean.reshape(self.__nch,1,self.__nHeis) |
|
1611 | tmp = mean.reshape(self.__nch,1,self.__nHeis) | |
| 1592 | dc= numpy.tile(tmp,[1,self.__nProf,1]) |
|
1612 | dc= numpy.tile(tmp,[1,self.__nProf,1]) | |
| 1593 | self.__buffer = self.__buffer - dc |
|
1613 | self.__buffer = self.__buffer - dc | |
| 1594 | #------------------Calculo de Potencia ------------------------ |
|
1614 | #------------------Calculo de Potencia ------------------------ | |
| 1595 | pair0 = self.__buffer*numpy.conj(self.__buffer) |
|
1615 | pair0 = self.__buffer*numpy.conj(self.__buffer) * 10.0 | |
| 1596 | pair0 = pair0.real |
|
1616 | pair0 = pair0.real | |
| 1597 | lag_0 = numpy.sum(pair0,1) |
|
1617 | lag_0 = numpy.sum(pair0,1) | |
| 1598 | #-----------------Calculo de Cscp------------------------------ New |
|
1618 | #-----------------Calculo de Cscp------------------------------ New | |
| 1599 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] |
|
1619 | cspc_pair01 = self.__buffer[0]*self.__buffer[1] | |
|
|
1620 | #------------------ Data Decodificada------------------------ | |||
|
|
1621 | pwcode = 1 | |||
|
|
1622 | if dataOut.flagDecodeData == True: | |||
|
|
1623 | pwcode = numpy.sum(dataOut.code[0]**2) | |||
| 1600 | #------------------Calculo de Ruido x canal-------------------- |
|
1624 | #------------------Calculo de Ruido x canal-------------------- | |
| 1601 | self.noise = numpy.zeros(self.__nch) |
|
1625 | self.noise = numpy.zeros(self.__nch) | |
| 1602 | for i in range(self.__nch): |
|
1626 | for i in range(self.__nch): | |
| 1603 | daux = numpy.sort(pair0[i,:,:],axis= None) |
|
1627 | daux = numpy.sort(pair0[i,:,:],axis= None) | |
| 1604 | self.noise[i]=hildebrand_sekhon( daux ,self.nCohInt) |
|
1628 | self.noise[i]=hildebrand_sekhon( daux/pwcode ,self.nCohInt) | |
| 1605 |
|
1629 | |||
| 1606 | self.noise = self.noise.reshape(self.__nch,1) |
|
1630 | self.noise = self.noise.reshape(self.__nch,1) | |
| 1607 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) |
|
1631 | self.noise = numpy.tile(self.noise,[1,self.__nHeis]) | |
| 1608 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) |
|
1632 | noise_buffer = self.noise.reshape(self.__nch,1,self.__nHeis) | |
| 1609 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) |
|
1633 | noise_buffer = numpy.tile(noise_buffer,[1,self.__nProf,1]) | |
| 1610 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- |
|
1634 | #------------------ Potencia recibida= P , Potencia senal = S , Ruido= N-- | |
| 1611 | #------------------ P= S+N ,P=lag_0/N --------------------------------- |
|
1635 | #------------------ P= S+N ,P=lag_0/N --------------------------------- | |
| 1612 | #-------------------- Power -------------------------------------------------- |
|
1636 | #-------------------- Power -------------------------------------------------- | |
| 1613 | data_power = lag_0/(self.n*self.nCohInt) |
|
1637 | data_power = lag_0/(self.n*self.nCohInt*pwcode) | |
| 1614 | #--------------------CCF------------------------------------------------------ |
|
1638 | #--------------------CCF------------------------------------------------------ | |
| 1615 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) |
|
1639 | data_ccf =numpy.sum(cspc_pair01,axis=0)/(self.n*self.nCohInt) | |
| 1616 | #------------------ Senal -------------------------------------------------- |
|
1640 | #------------------ Senal -------------------------------------------------- | |
| 1617 | data_intensity = pair0 - noise_buffer |
|
1641 | data_intensity = pair0 - noise_buffer | |
| 1618 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) |
|
1642 | data_intensity = numpy.sum(data_intensity,axis=1)*(self.n*self.nCohInt)#*self.nCohInt) | |
| 1619 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) |
|
1643 | #data_intensity = (lag_0-self.noise*self.n)*(self.n*self.nCohInt) | |
| 1620 | for i in range(self.__nch): |
|
1644 | for i in range(self.__nch): | |
| 1621 | for j in range(self.__nHeis): |
|
1645 | for j in range(self.__nHeis): | |
| 1622 | if data_intensity[i][j] < 0: |
|
1646 | if data_intensity[i][j] < 0: | |
| 1623 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) |
|
1647 | data_intensity[i][j] = numpy.min(numpy.absolute(data_intensity[i][j])) | |
| 1624 |
|
1648 | |||
| 1625 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- |
|
1649 | #----------------- Calculo de Frecuencia y Velocidad doppler-------- | |
| 1626 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) |
|
1650 | pair1 = self.__buffer[:,:-1,:]*numpy.conjugate(self.__buffer[:,1:,:]) | |
| 1627 | lag_1 = numpy.sum(pair1,1) |
|
1651 | lag_1 = numpy.sum(pair1,1) | |
| 1628 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) |
|
1652 | data_freq = (-1/(2.0*math.pi*self.ippSec*self.nCohInt))*numpy.angle(lag_1) | |
| 1629 | data_velocity = (self.lambda_/2.0)*data_freq |
|
1653 | data_velocity = (self.lambda_/2.0)*data_freq | |
| 1630 |
|
1654 | |||
| 1631 | #---------------- Potencia promedio estimada de la Senal----------- |
|
1655 | #---------------- Potencia promedio estimada de la Senal----------- | |
| 1632 |
lag_0 = |
|
1656 | lag_0 = data_power | |
| 1633 | S = lag_0-self.noise |
|
1657 | S = lag_0-self.noise | |
| 1634 |
|
1658 | |||
| 1635 | #---------------- Frecuencia Doppler promedio --------------------- |
|
1659 | #---------------- Frecuencia Doppler promedio --------------------- | |
| 1636 | lag_1 = lag_1/(self.n-1) |
|
1660 | lag_1 = lag_1/(self.n-1) | |
| 1637 | R1 = numpy.abs(lag_1) |
|
1661 | R1 = numpy.abs(lag_1) | |
| 1638 |
|
1662 | |||
| 1639 | #---------------- Calculo del SNR---------------------------------- |
|
1663 | #---------------- Calculo del SNR---------------------------------- | |
| 1640 | data_snrPP = S/self.noise |
|
1664 | data_snrPP = S/self.noise | |
| 1641 | for i in range(self.__nch): |
|
1665 | for i in range(self.__nch): | |
| 1642 | for j in range(self.__nHeis): |
|
1666 | for j in range(self.__nHeis): | |
| 1643 | if data_snrPP[i][j] < 1.e-20: |
|
1667 | if data_snrPP[i][j] < 1.e-20: | |
| 1644 | data_snrPP[i][j] = 1.e-20 |
|
1668 | data_snrPP[i][j] = 1.e-20 | |
| 1645 |
|
1669 | |||
| 1646 | #----------------- Calculo del ancho espectral ---------------------- |
|
1670 | #----------------- Calculo del ancho espectral ---------------------- | |
| 1647 | L = S/R1 |
|
1671 | L = S/R1 | |
| 1648 | L = numpy.where(L<0,1,L) |
|
1672 | L = numpy.where(L<0,1,L) | |
| 1649 | L = numpy.log(L) |
|
1673 | L = numpy.log(L) | |
| 1650 | tmp = numpy.sqrt(numpy.absolute(L)) |
|
1674 | tmp = numpy.sqrt(numpy.absolute(L)) | |
| 1651 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) |
|
1675 | data_specwidth = (self.lambda_/(2*math.sqrt(2)*math.pi*self.ippSec*self.nCohInt))*tmp*numpy.sign(L) | |
| 1652 | n = self.__profIndex |
|
1676 | n = self.__profIndex | |
| 1653 |
|
1677 | |||
| 1654 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') |
|
1678 | self.__buffer = numpy.zeros((self.__nch, self.__nProf,self.__nHeis), dtype='complex') | |
| 1655 | self.__profIndex = 0 |
|
1679 | self.__profIndex = 0 | |
| 1656 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n |
|
1680 | return data_power,data_intensity,data_velocity,data_snrPP,data_specwidth,data_ccf,n | |
| 1657 |
|
1681 | |||
| 1658 |
|
1682 | |||
| 1659 | def pulsePairbyProfiles(self,dataOut,n): |
|
1683 | def pulsePairbyProfiles(self,dataOut,n): | |
| 1660 |
|
1684 | |||
| 1661 | self.__dataReady = False |
|
1685 | self.__dataReady = False | |
| 1662 | data_power = None |
|
1686 | data_power = None | |
| 1663 | data_intensity = None |
|
1687 | data_intensity = None | |
| 1664 | data_velocity = None |
|
1688 | data_velocity = None | |
| 1665 | data_specwidth = None |
|
1689 | data_specwidth = None | |
| 1666 | data_snrPP = None |
|
1690 | data_snrPP = None | |
| 1667 | data_ccf = None |
|
1691 | data_ccf = None | |
| 1668 |
|
1692 | |||
| 1669 | if dataOut.flagDataAsBlock: |
|
1693 | if dataOut.flagDataAsBlock: | |
| 1670 | self.putDataByBlock(data=dataOut.data,n=n) |
|
1694 | self.putDataByBlock(data=dataOut.data,n=n) | |
| 1671 | else: |
|
1695 | else: | |
| 1672 | self.putData(data=dataOut.data) |
|
1696 | self.putData(data=dataOut.data) | |
| 1673 | if self.__profIndex == self.n: |
|
1697 | if self.__profIndex == self.n: | |
| 1674 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) |
|
1698 | data_power,data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, n = self.pushData(dataOut=dataOut) | |
| 1675 | self.__dataReady = True |
|
1699 | self.__dataReady = True | |
| 1676 |
|
1700 | |||
| 1677 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf |
|
1701 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf | |
| 1678 |
|
1702 | |||
| 1679 |
|
1703 | |||
| 1680 | def pulsePairOp(self, dataOut, n, datatime= None): |
|
1704 | def pulsePairOp(self, dataOut, n, datatime= None): | |
| 1681 |
|
1705 | |||
| 1682 | if self.__initime == None: |
|
1706 | if self.__initime == None: | |
| 1683 | self.__initime = datatime |
|
1707 | self.__initime = datatime | |
| 1684 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n) |
|
1708 | data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf = self.pulsePairbyProfiles(dataOut,n) | |
| 1685 | self.__lastdatatime = datatime |
|
1709 | self.__lastdatatime = datatime | |
| 1686 |
|
1710 | |||
| 1687 | if data_power is None: |
|
1711 | if data_power is None: | |
| 1688 | return None, None, None,None,None,None,None |
|
1712 | return None, None, None,None,None,None,None | |
| 1689 |
|
1713 | |||
| 1690 | avgdatatime = self.__initime |
|
1714 | avgdatatime = self.__initime | |
| 1691 | deltatime = datatime - self.__lastdatatime |
|
1715 | deltatime = datatime - self.__lastdatatime | |
| 1692 | self.__initime = datatime |
|
1716 | self.__initime = datatime | |
| 1693 |
|
1717 | |||
| 1694 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime |
|
1718 | return data_power, data_intensity, data_velocity, data_snrPP,data_specwidth,data_ccf, avgdatatime | |
| 1695 |
|
1719 | |||
| 1696 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): |
|
1720 | def run(self, dataOut,n = None,removeDC= False, overlapping= False,**kwargs): | |
| 1697 |
|
1721 | |||
| 1698 | if dataOut.flagDataAsBlock: |
|
1722 | if dataOut.flagDataAsBlock: | |
| 1699 | n = int(dataOut.nProfiles) |
|
1723 | n = int(dataOut.nProfiles) | |
| 1700 | #print("n",n) |
|
1724 | #print("n",n) | |
| 1701 |
|
1725 | |||
| 1702 | if not self.isConfig: |
|
1726 | if not self.isConfig: | |
| 1703 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) |
|
1727 | self.setup(dataOut = dataOut, n = n , removeDC=removeDC , **kwargs) | |
| 1704 | self.isConfig = True |
|
1728 | self.isConfig = True | |
| 1705 |
|
1729 | |||
| 1706 |
|
1730 | |||
| 1707 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime) |
|
1731 | data_power, data_intensity, data_velocity,data_snrPP,data_specwidth,data_ccf, avgdatatime = self.pulsePairOp(dataOut, n, dataOut.utctime) | |
| 1708 |
|
1732 | |||
| 1709 |
|
1733 | |||
| 1710 | dataOut.flagNoData = True |
|
1734 | dataOut.flagNoData = True | |
| 1711 |
|
1735 | |||
| 1712 | if self.__dataReady: |
|
1736 | if self.__dataReady: | |
| 1713 | ###print("READY ----------------------------------") |
|
1737 | ###print("READY ----------------------------------") | |
| 1714 | dataOut.nCohInt *= self.n |
|
1738 | dataOut.nCohInt *= self.n | |
| 1715 | dataOut.dataPP_POW = data_intensity # S |
|
1739 | dataOut.dataPP_POW = data_intensity # S | |
| 1716 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO |
|
1740 | dataOut.dataPP_POWER = data_power # P valor que corresponde a POTENCIA MOMENTO | |
| 1717 | dataOut.dataPP_DOP = data_velocity |
|
1741 | dataOut.dataPP_DOP = data_velocity | |
| 1718 | dataOut.dataPP_SNR = data_snrPP |
|
1742 | dataOut.dataPP_SNR = data_snrPP | |
| 1719 | dataOut.dataPP_WIDTH = data_specwidth |
|
1743 | dataOut.dataPP_WIDTH = data_specwidth | |
| 1720 | dataOut.dataPP_CCF = data_ccf |
|
1744 | dataOut.dataPP_CCF = data_ccf | |
| 1721 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. |
|
1745 | dataOut.PRFbyAngle = self.n #numero de PRF*cada angulo rotado que equivale a un tiempo. | |
| 1722 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1746 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
| 1723 | dataOut.utctime = avgdatatime |
|
1747 | dataOut.utctime = avgdatatime | |
| 1724 | dataOut.flagNoData = False |
|
1748 | dataOut.flagNoData = False | |
| 1725 | return dataOut |
|
1749 | return dataOut | |
| 1726 |
|
1750 | |||
| 1727 | # import collections |
|
1751 | # import collections | |
| 1728 | # from scipy.stats import mode |
|
1752 | # from scipy.stats import mode | |
| 1729 | # |
|
1753 | # | |
| 1730 | # class Synchronize(Operation): |
|
1754 | # class Synchronize(Operation): | |
| 1731 | # |
|
1755 | # | |
| 1732 | # isConfig = False |
|
1756 | # isConfig = False | |
| 1733 | # __profIndex = 0 |
|
1757 | # __profIndex = 0 | |
| 1734 | # |
|
1758 | # | |
| 1735 | # def __init__(self, **kwargs): |
|
1759 | # def __init__(self, **kwargs): | |
| 1736 | # |
|
1760 | # | |
| 1737 | # Operation.__init__(self, **kwargs) |
|
1761 | # Operation.__init__(self, **kwargs) | |
| 1738 | # # self.isConfig = False |
|
1762 | # # self.isConfig = False | |
| 1739 | # self.__powBuffer = None |
|
1763 | # self.__powBuffer = None | |
| 1740 | # self.__startIndex = 0 |
|
1764 | # self.__startIndex = 0 | |
| 1741 | # self.__pulseFound = False |
|
1765 | # self.__pulseFound = False | |
| 1742 | # |
|
1766 | # | |
| 1743 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
1767 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): | |
| 1744 | # |
|
1768 | # | |
| 1745 | # #Read data |
|
1769 | # #Read data | |
| 1746 | # |
|
1770 | # | |
| 1747 | # powerdB = dataOut.getPower(channel = channel) |
|
1771 | # powerdB = dataOut.getPower(channel = channel) | |
| 1748 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
1772 | # noisedB = dataOut.getNoise(channel = channel)[0] | |
| 1749 | # |
|
1773 | # | |
| 1750 | # self.__powBuffer.extend(powerdB.flatten()) |
|
1774 | # self.__powBuffer.extend(powerdB.flatten()) | |
| 1751 | # |
|
1775 | # | |
| 1752 | # dataArray = numpy.array(self.__powBuffer) |
|
1776 | # dataArray = numpy.array(self.__powBuffer) | |
| 1753 | # |
|
1777 | # | |
| 1754 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
1778 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") | |
| 1755 | # |
|
1779 | # | |
| 1756 | # maxValue = numpy.nanmax(filteredPower) |
|
1780 | # maxValue = numpy.nanmax(filteredPower) | |
| 1757 | # |
|
1781 | # | |
| 1758 | # if maxValue < noisedB + 10: |
|
1782 | # if maxValue < noisedB + 10: | |
| 1759 | # #No se encuentra ningun pulso de transmision |
|
1783 | # #No se encuentra ningun pulso de transmision | |
| 1760 | # return None |
|
1784 | # return None | |
| 1761 | # |
|
1785 | # | |
| 1762 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
1786 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] | |
| 1763 | # |
|
1787 | # | |
| 1764 | # if len(maxValuesIndex) < 2: |
|
1788 | # if len(maxValuesIndex) < 2: | |
| 1765 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
1789 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX | |
| 1766 | # return None |
|
1790 | # return None | |
| 1767 | # |
|
1791 | # | |
| 1768 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
1792 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples | |
| 1769 | # |
|
1793 | # | |
| 1770 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
1794 | # #Seleccionar solo valores con un espaciamiento de nSamples | |
| 1771 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
1795 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) | |
| 1772 | # |
|
1796 | # | |
| 1773 | # if len(pulseIndex) < 2: |
|
1797 | # if len(pulseIndex) < 2: | |
| 1774 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1798 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1775 | # return None |
|
1799 | # return None | |
| 1776 | # |
|
1800 | # | |
| 1777 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
1801 | # spacing = pulseIndex[1:] - pulseIndex[:-1] | |
| 1778 | # |
|
1802 | # | |
| 1779 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
1803 | # #remover senales que se distancien menos de 10 unidades o muestras | |
| 1780 | # #(No deberian existir IPP menor a 10 unidades) |
|
1804 | # #(No deberian existir IPP menor a 10 unidades) | |
| 1781 | # |
|
1805 | # | |
| 1782 | # realIndex = numpy.where(spacing > 10 )[0] |
|
1806 | # realIndex = numpy.where(spacing > 10 )[0] | |
| 1783 | # |
|
1807 | # | |
| 1784 | # if len(realIndex) < 2: |
|
1808 | # if len(realIndex) < 2: | |
| 1785 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1809 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
| 1786 | # return None |
|
1810 | # return None | |
| 1787 | # |
|
1811 | # | |
| 1788 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
1812 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) | |
| 1789 | # realPulseIndex = pulseIndex[realIndex] |
|
1813 | # realPulseIndex = pulseIndex[realIndex] | |
| 1790 | # |
|
1814 | # | |
| 1791 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
1815 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] | |
| 1792 | # |
|
1816 | # | |
| 1793 | # print "IPP = %d samples" %period |
|
1817 | # print "IPP = %d samples" %period | |
| 1794 | # |
|
1818 | # | |
| 1795 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
1819 | # self.__newNSamples = dataOut.nHeights #int(period) | |
| 1796 | # self.__startIndex = int(realPulseIndex[0]) |
|
1820 | # self.__startIndex = int(realPulseIndex[0]) | |
| 1797 | # |
|
1821 | # | |
| 1798 | # return 1 |
|
1822 | # return 1 | |
| 1799 | # |
|
1823 | # | |
| 1800 | # |
|
1824 | # | |
| 1801 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
1825 | # def setup(self, nSamples, nChannels, buffer_size = 4): | |
| 1802 | # |
|
1826 | # | |
| 1803 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
1827 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), | |
| 1804 | # maxlen = buffer_size*nSamples) |
|
1828 | # maxlen = buffer_size*nSamples) | |
| 1805 | # |
|
1829 | # | |
| 1806 | # bufferList = [] |
|
1830 | # bufferList = [] | |
| 1807 | # |
|
1831 | # | |
| 1808 | # for i in range(nChannels): |
|
1832 | # for i in range(nChannels): | |
| 1809 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
1833 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, | |
| 1810 | # maxlen = buffer_size*nSamples) |
|
1834 | # maxlen = buffer_size*nSamples) | |
| 1811 | # |
|
1835 | # | |
| 1812 | # bufferList.append(bufferByChannel) |
|
1836 | # bufferList.append(bufferByChannel) | |
| 1813 | # |
|
1837 | # | |
| 1814 | # self.__nSamples = nSamples |
|
1838 | # self.__nSamples = nSamples | |
| 1815 | # self.__nChannels = nChannels |
|
1839 | # self.__nChannels = nChannels | |
| 1816 | # self.__bufferList = bufferList |
|
1840 | # self.__bufferList = bufferList | |
| 1817 | # |
|
1841 | # | |
| 1818 | # def run(self, dataOut, channel = 0): |
|
1842 | # def run(self, dataOut, channel = 0): | |
| 1819 | # |
|
1843 | # | |
| 1820 | # if not self.isConfig: |
|
1844 | # if not self.isConfig: | |
| 1821 | # nSamples = dataOut.nHeights |
|
1845 | # nSamples = dataOut.nHeights | |
| 1822 | # nChannels = dataOut.nChannels |
|
1846 | # nChannels = dataOut.nChannels | |
| 1823 | # self.setup(nSamples, nChannels) |
|
1847 | # self.setup(nSamples, nChannels) | |
| 1824 | # self.isConfig = True |
|
1848 | # self.isConfig = True | |
| 1825 | # |
|
1849 | # | |
| 1826 | # #Append new data to internal buffer |
|
1850 | # #Append new data to internal buffer | |
| 1827 | # for thisChannel in range(self.__nChannels): |
|
1851 | # for thisChannel in range(self.__nChannels): | |
| 1828 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1852 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1829 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
1853 | # bufferByChannel.extend(dataOut.data[thisChannel]) | |
| 1830 | # |
|
1854 | # | |
| 1831 | # if self.__pulseFound: |
|
1855 | # if self.__pulseFound: | |
| 1832 | # self.__startIndex -= self.__nSamples |
|
1856 | # self.__startIndex -= self.__nSamples | |
| 1833 | # |
|
1857 | # | |
| 1834 | # #Finding Tx Pulse |
|
1858 | # #Finding Tx Pulse | |
| 1835 | # if not self.__pulseFound: |
|
1859 | # if not self.__pulseFound: | |
| 1836 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
1860 | # indexFound = self.__findTxPulse(dataOut, channel) | |
| 1837 | # |
|
1861 | # | |
| 1838 | # if indexFound == None: |
|
1862 | # if indexFound == None: | |
| 1839 | # dataOut.flagNoData = True |
|
1863 | # dataOut.flagNoData = True | |
| 1840 | # return |
|
1864 | # return | |
| 1841 | # |
|
1865 | # | |
| 1842 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
1866 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) | |
| 1843 | # self.__pulseFound = True |
|
1867 | # self.__pulseFound = True | |
| 1844 | # self.__startIndex = indexFound |
|
1868 | # self.__startIndex = indexFound | |
| 1845 | # |
|
1869 | # | |
| 1846 | # #If pulse was found ... |
|
1870 | # #If pulse was found ... | |
| 1847 | # for thisChannel in range(self.__nChannels): |
|
1871 | # for thisChannel in range(self.__nChannels): | |
| 1848 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1872 | # bufferByChannel = self.__bufferList[thisChannel] | |
| 1849 | # #print self.__startIndex |
|
1873 | # #print self.__startIndex | |
| 1850 | # x = numpy.array(bufferByChannel) |
|
1874 | # x = numpy.array(bufferByChannel) | |
| 1851 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
1875 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] | |
| 1852 | # |
|
1876 | # | |
| 1853 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1877 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
| 1854 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
1878 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight | |
| 1855 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
1879 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 | |
| 1856 | # |
|
1880 | # | |
| 1857 | # dataOut.data = self.__arrayBuffer |
|
1881 | # dataOut.data = self.__arrayBuffer | |
| 1858 | # |
|
1882 | # | |
| 1859 | # self.__startIndex += self.__newNSamples |
|
1883 | # self.__startIndex += self.__newNSamples | |
| 1860 | # |
|
1884 | # | |
| 1861 | # return |
|
1885 | # return | |
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