| @@ -1,874 +1,876 | |||||
| 1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory |
|
1 | # Copyright (c) 2012-2020 Jicamarca Radio Observatory | |
| 2 | # All rights reserved. |
|
2 | # All rights reserved. | |
| 3 | # |
|
3 | # | |
| 4 | # Distributed under the terms of the BSD 3-clause license. |
|
4 | # Distributed under the terms of the BSD 3-clause license. | |
| 5 | """Spectra processing Unit and operations |
|
5 | """Spectra processing Unit and operations | |
| 6 |
|
6 | |||
| 7 | Here you will find the processing unit `SpectraProc` and several operations |
|
7 | Here you will find the processing unit `SpectraProc` and several operations | |
| 8 | to work with Spectra data type |
|
8 | to work with Spectra data type | |
| 9 | """ |
|
9 | """ | |
| 10 |
|
10 | |||
| 11 | import time |
|
11 | import time | |
| 12 | import itertools |
|
12 | import itertools | |
| 13 |
|
13 | |||
| 14 | import numpy |
|
14 | import numpy | |
| 15 |
|
15 | |||
| 16 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation |
|
16 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation | |
| 17 | from schainpy.model.data.jrodata import Spectra |
|
17 | from schainpy.model.data.jrodata import Spectra | |
| 18 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
18 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 19 | from schainpy.utils import log |
|
19 | from schainpy.utils import log | |
| 20 |
|
20 | |||
| 21 |
|
21 | |||
| 22 | class SpectraProc(ProcessingUnit): |
|
22 | class SpectraProc(ProcessingUnit): | |
| 23 |
|
23 | |||
| 24 | def __init__(self): |
|
24 | def __init__(self): | |
| 25 |
|
25 | |||
| 26 | ProcessingUnit.__init__(self) |
|
26 | ProcessingUnit.__init__(self) | |
| 27 |
|
27 | |||
| 28 | self.buffer = None |
|
28 | self.buffer = None | |
| 29 | self.firstdatatime = None |
|
29 | self.firstdatatime = None | |
| 30 | self.profIndex = 0 |
|
30 | self.profIndex = 0 | |
| 31 | self.dataOut = Spectra() |
|
31 | self.dataOut = Spectra() | |
| 32 | self.id_min = None |
|
32 | self.id_min = None | |
| 33 | self.id_max = None |
|
33 | self.id_max = None | |
| 34 | self.setupReq = False #Agregar a todas las unidades de proc |
|
34 | self.setupReq = False #Agregar a todas las unidades de proc | |
| 35 |
|
35 | |||
| 36 | def __updateSpecFromVoltage(self): |
|
36 | def __updateSpecFromVoltage(self): | |
| 37 |
|
37 | |||
| 38 | self.dataOut.timeZone = self.dataIn.timeZone |
|
38 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 39 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
39 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 40 | self.dataOut.errorCount = self.dataIn.errorCount |
|
40 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 41 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
41 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 42 | try: |
|
42 | try: | |
| 43 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() |
|
43 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() | |
| 44 | except: |
|
44 | except: | |
| 45 | pass |
|
45 | pass | |
| 46 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
46 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 47 |
|
||||
| 48 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
47 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 49 | self.dataOut.channelList = self.dataIn.channelList |
|
48 | self.dataOut.channelList = self.dataIn.channelList | |
| 50 | self.dataOut.heightList = self.dataIn.heightList |
|
49 | self.dataOut.heightList = self.dataIn.heightList | |
| 51 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
50 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) | |
| 52 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
51 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 53 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
52 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 54 | self.dataOut.utctime = self.firstdatatime |
|
53 | self.dataOut.utctime = self.firstdatatime | |
| 55 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData |
|
54 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData | |
| 56 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData |
|
55 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData | |
| 57 | self.dataOut.flagShiftFFT = False |
|
56 | self.dataOut.flagShiftFFT = False | |
| 58 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
57 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 59 | self.dataOut.nIncohInt = 1 |
|
58 | self.dataOut.nIncohInt = 1 | |
| 60 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
59 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 61 | self.dataOut.frequency = self.dataIn.frequency |
|
60 | self.dataOut.frequency = self.dataIn.frequency | |
| 62 | self.dataOut.realtime = self.dataIn.realtime |
|
61 | self.dataOut.realtime = self.dataIn.realtime | |
| 63 | self.dataOut.azimuth = self.dataIn.azimuth |
|
62 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 64 | self.dataOut.zenith = self.dataIn.zenith |
|
63 | self.dataOut.zenith = self.dataIn.zenith | |
| 65 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
64 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 66 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
65 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 67 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
66 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 68 |
|
67 | |||
| 69 | def __getFft(self): |
|
68 | def __getFft(self): | |
| 70 | """ |
|
69 | """ | |
| 71 | Convierte valores de Voltaje a Spectra |
|
70 | Convierte valores de Voltaje a Spectra | |
| 72 |
|
71 | |||
| 73 | Affected: |
|
72 | Affected: | |
| 74 | self.dataOut.data_spc |
|
73 | self.dataOut.data_spc | |
| 75 | self.dataOut.data_cspc |
|
74 | self.dataOut.data_cspc | |
| 76 | self.dataOut.data_dc |
|
75 | self.dataOut.data_dc | |
| 77 | self.dataOut.heightList |
|
76 | self.dataOut.heightList | |
| 78 | self.profIndex |
|
77 | self.profIndex | |
| 79 | self.buffer |
|
78 | self.buffer | |
| 80 | self.dataOut.flagNoData |
|
79 | self.dataOut.flagNoData | |
| 81 | """ |
|
80 | """ | |
| 82 | fft_volt = numpy.fft.fft( |
|
81 | fft_volt = numpy.fft.fft( | |
| 83 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) |
|
82 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) | |
| 84 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
83 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 85 | dc = fft_volt[:, 0, :] |
|
84 | dc = fft_volt[:, 0, :] | |
| 86 |
|
85 | |||
| 87 | # calculo de self-spectra |
|
86 | # calculo de self-spectra | |
| 88 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) |
|
87 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) | |
| 89 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
88 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 90 | spc = spc.real |
|
89 | spc = spc.real | |
| 91 |
|
90 | |||
| 92 | blocksize = 0 |
|
91 | blocksize = 0 | |
| 93 | blocksize += dc.size |
|
92 | blocksize += dc.size | |
| 94 | blocksize += spc.size |
|
93 | blocksize += spc.size | |
| 95 |
|
94 | |||
| 96 | cspc = None |
|
95 | cspc = None | |
| 97 | pairIndex = 0 |
|
96 | pairIndex = 0 | |
| 98 | if self.dataOut.pairsList != None: |
|
97 | if self.dataOut.pairsList != None: | |
| 99 | # calculo de cross-spectra |
|
98 | # calculo de cross-spectra | |
| 100 | cspc = numpy.zeros( |
|
99 | cspc = numpy.zeros( | |
| 101 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
100 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 102 | for pair in self.dataOut.pairsList: |
|
101 | for pair in self.dataOut.pairsList: | |
| 103 | if pair[0] not in self.dataOut.channelList: |
|
102 | if pair[0] not in self.dataOut.channelList: | |
| 104 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( |
|
103 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( | |
| 105 | str(pair), str(self.dataOut.channelList))) |
|
104 | str(pair), str(self.dataOut.channelList))) | |
| 106 | if pair[1] not in self.dataOut.channelList: |
|
105 | if pair[1] not in self.dataOut.channelList: | |
| 107 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( |
|
106 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( | |
| 108 | str(pair), str(self.dataOut.channelList))) |
|
107 | str(pair), str(self.dataOut.channelList))) | |
| 109 |
|
108 | |||
| 110 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ |
|
109 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ | |
| 111 | numpy.conjugate(fft_volt[pair[1], :, :]) |
|
110 | numpy.conjugate(fft_volt[pair[1], :, :]) | |
| 112 | pairIndex += 1 |
|
111 | pairIndex += 1 | |
| 113 | blocksize += cspc.size |
|
112 | blocksize += cspc.size | |
| 114 |
|
113 | |||
| 115 | self.dataOut.data_spc = spc |
|
114 | self.dataOut.data_spc = spc | |
| 116 | self.dataOut.data_cspc = cspc |
|
115 | self.dataOut.data_cspc = cspc | |
| 117 | self.dataOut.data_dc = dc |
|
116 | self.dataOut.data_dc = dc | |
| 118 | self.dataOut.blockSize = blocksize |
|
117 | self.dataOut.blockSize = blocksize | |
| 119 | self.dataOut.flagShiftFFT = False |
|
118 | self.dataOut.flagShiftFFT = False | |
| 120 |
|
119 | |||
| 121 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None, shift_fft=False): |
|
120 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=None, ippFactor=None, shift_fft=False): | |
| 122 |
|
121 | |||
| 123 | if self.dataIn.type == "Spectra": |
|
122 | if self.dataIn.type == "Spectra": | |
| 124 | self.dataOut.copy(self.dataIn) |
|
123 | self.dataOut.copy(self.dataIn) | |
| 125 | if shift_fft: |
|
124 | if shift_fft: | |
| 126 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
125 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 127 | shift = int(self.dataOut.nFFTPoints/2) |
|
126 | shift = int(self.dataOut.nFFTPoints/2) | |
| 128 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) |
|
127 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) | |
| 129 |
|
128 | |||
| 130 | if self.dataOut.data_cspc is not None: |
|
129 | if self.dataOut.data_cspc is not None: | |
| 131 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
130 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 132 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) |
|
131 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) | |
|
|
132 | if pairsList: | |||
|
|
133 | self.__selectPairs(pairsList) | |||
| 133 |
|
134 | |||
| 134 | elif self.dataIn.type == "Voltage": |
|
135 | elif self.dataIn.type == "Voltage": | |
| 135 |
|
136 | |||
| 136 | self.dataOut.flagNoData = True |
|
137 | self.dataOut.flagNoData = True | |
| 137 |
|
138 | |||
| 138 | if nFFTPoints == None: |
|
139 | if nFFTPoints == None: | |
| 139 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") |
|
140 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") | |
| 140 |
|
141 | |||
| 141 | if nProfiles == None: |
|
142 | if nProfiles == None: | |
| 142 | nProfiles = nFFTPoints |
|
143 | nProfiles = nFFTPoints | |
| 143 |
|
144 | |||
| 144 | if ippFactor == None: |
|
145 | if ippFactor == None: | |
| 145 | self.dataOut.ippFactor = 1 |
|
146 | self.dataOut.ippFactor = 1 | |
| 146 |
|
147 | |||
| 147 | self.dataOut.nFFTPoints = nFFTPoints |
|
148 | self.dataOut.nFFTPoints = nFFTPoints | |
| 148 |
|
149 | |||
| 149 | if self.buffer is None: |
|
150 | if self.buffer is None: | |
| 150 | self.buffer = numpy.zeros((self.dataIn.nChannels, |
|
151 | self.buffer = numpy.zeros((self.dataIn.nChannels, | |
| 151 | nProfiles, |
|
152 | nProfiles, | |
| 152 | self.dataIn.nHeights), |
|
153 | self.dataIn.nHeights), | |
| 153 | dtype='complex') |
|
154 | dtype='complex') | |
| 154 |
|
155 | |||
| 155 | if self.dataIn.flagDataAsBlock: |
|
156 | if self.dataIn.flagDataAsBlock: | |
| 156 | nVoltProfiles = self.dataIn.data.shape[1] |
|
157 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 157 |
|
158 | |||
| 158 | if nVoltProfiles == nProfiles: |
|
159 | if nVoltProfiles == nProfiles: | |
| 159 | self.buffer = self.dataIn.data.copy() |
|
160 | self.buffer = self.dataIn.data.copy() | |
| 160 | self.profIndex = nVoltProfiles |
|
161 | self.profIndex = nVoltProfiles | |
| 161 |
|
162 | |||
| 162 | elif nVoltProfiles < nProfiles: |
|
163 | elif nVoltProfiles < nProfiles: | |
| 163 |
|
164 | |||
| 164 | if self.profIndex == 0: |
|
165 | if self.profIndex == 0: | |
| 165 | self.id_min = 0 |
|
166 | self.id_min = 0 | |
| 166 | self.id_max = nVoltProfiles |
|
167 | self.id_max = nVoltProfiles | |
| 167 |
|
168 | |||
| 168 | self.buffer[:, self.id_min:self.id_max, |
|
169 | self.buffer[:, self.id_min:self.id_max, | |
| 169 | :] = self.dataIn.data |
|
170 | :] = self.dataIn.data | |
| 170 | self.profIndex += nVoltProfiles |
|
171 | self.profIndex += nVoltProfiles | |
| 171 | self.id_min += nVoltProfiles |
|
172 | self.id_min += nVoltProfiles | |
| 172 | self.id_max += nVoltProfiles |
|
173 | self.id_max += nVoltProfiles | |
| 173 | else: |
|
174 | else: | |
| 174 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( |
|
175 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( | |
| 175 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) |
|
176 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) | |
| 176 | self.dataOut.flagNoData = True |
|
177 | self.dataOut.flagNoData = True | |
| 177 | else: |
|
178 | else: | |
| 178 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() |
|
179 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() | |
| 179 | self.profIndex += 1 |
|
180 | self.profIndex += 1 | |
| 180 |
|
181 | |||
| 181 | if self.firstdatatime == None: |
|
182 | if self.firstdatatime == None: | |
| 182 | self.firstdatatime = self.dataIn.utctime |
|
183 | self.firstdatatime = self.dataIn.utctime | |
| 183 |
|
184 | |||
| 184 | if self.profIndex == nProfiles: |
|
185 | if self.profIndex == nProfiles: | |
| 185 | self.__updateSpecFromVoltage() |
|
186 | self.__updateSpecFromVoltage() | |
| 186 | if pairsList == None: |
|
187 | if pairsList == None: | |
| 187 | self.dataOut.pairsList = [pair for pair in itertools.combinations(self.dataOut.channelList, 2)] |
|
188 | self.dataOut.pairsList = [pair for pair in itertools.combinations(self.dataOut.channelList, 2)] | |
|
|
189 | else: | |||
|
|
190 | self.dataOut.pairsList = pairsList | |||
| 188 | self.__getFft() |
|
191 | self.__getFft() | |
| 189 |
|
||||
| 190 | self.dataOut.flagNoData = False |
|
192 | self.dataOut.flagNoData = False | |
| 191 | self.firstdatatime = None |
|
193 | self.firstdatatime = None | |
| 192 | self.profIndex = 0 |
|
194 | self.profIndex = 0 | |
| 193 | else: |
|
195 | else: | |
| 194 | raise ValueError("The type of input object '%s' is not valid".format( |
|
196 | raise ValueError("The type of input object '%s' is not valid".format( | |
| 195 | self.dataIn.type)) |
|
197 | self.dataIn.type)) | |
| 196 |
|
198 | |||
| 197 | def __selectPairs(self, pairsList): |
|
199 | def __selectPairs(self, pairsList): | |
| 198 |
|
200 | |||
| 199 | if not pairsList: |
|
201 | if not pairsList: | |
| 200 | return |
|
202 | return | |
| 201 |
|
203 | |||
| 202 | pairs = [] |
|
204 | pairs = [] | |
| 203 | pairsIndex = [] |
|
205 | pairsIndex = [] | |
| 204 |
|
206 | |||
| 205 | for pair in pairsList: |
|
207 | for pair in pairsList: | |
| 206 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: |
|
208 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: | |
| 207 | continue |
|
209 | continue | |
| 208 | pairs.append(pair) |
|
210 | pairs.append(pair) | |
| 209 | pairsIndex.append(pairs.index(pair)) |
|
211 | pairsIndex.append(pairs.index(pair)) | |
| 210 |
|
212 | |||
| 211 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] |
|
213 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] | |
| 212 | self.dataOut.pairsList = pairs |
|
214 | self.dataOut.pairsList = pairs | |
| 213 |
|
215 | |||
| 214 | return |
|
216 | return | |
| 215 |
|
217 | |||
| 216 | def selectFFTs(self, minFFT, maxFFT ): |
|
218 | def selectFFTs(self, minFFT, maxFFT ): | |
| 217 | """ |
|
219 | """ | |
| 218 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango |
|
220 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango | |
| 219 | minFFT<= FFT <= maxFFT |
|
221 | minFFT<= FFT <= maxFFT | |
| 220 | """ |
|
222 | """ | |
| 221 |
|
223 | |||
| 222 | if (minFFT > maxFFT): |
|
224 | if (minFFT > maxFFT): | |
| 223 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) |
|
225 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) | |
| 224 |
|
226 | |||
| 225 | if (minFFT < self.dataOut.getFreqRange()[0]): |
|
227 | if (minFFT < self.dataOut.getFreqRange()[0]): | |
| 226 | minFFT = self.dataOut.getFreqRange()[0] |
|
228 | minFFT = self.dataOut.getFreqRange()[0] | |
| 227 |
|
229 | |||
| 228 | if (maxFFT > self.dataOut.getFreqRange()[-1]): |
|
230 | if (maxFFT > self.dataOut.getFreqRange()[-1]): | |
| 229 | maxFFT = self.dataOut.getFreqRange()[-1] |
|
231 | maxFFT = self.dataOut.getFreqRange()[-1] | |
| 230 |
|
232 | |||
| 231 | minIndex = 0 |
|
233 | minIndex = 0 | |
| 232 | maxIndex = 0 |
|
234 | maxIndex = 0 | |
| 233 | FFTs = self.dataOut.getFreqRange() |
|
235 | FFTs = self.dataOut.getFreqRange() | |
| 234 |
|
236 | |||
| 235 | inda = numpy.where(FFTs >= minFFT) |
|
237 | inda = numpy.where(FFTs >= minFFT) | |
| 236 | indb = numpy.where(FFTs <= maxFFT) |
|
238 | indb = numpy.where(FFTs <= maxFFT) | |
| 237 |
|
239 | |||
| 238 | try: |
|
240 | try: | |
| 239 | minIndex = inda[0][0] |
|
241 | minIndex = inda[0][0] | |
| 240 | except: |
|
242 | except: | |
| 241 | minIndex = 0 |
|
243 | minIndex = 0 | |
| 242 |
|
244 | |||
| 243 | try: |
|
245 | try: | |
| 244 | maxIndex = indb[0][-1] |
|
246 | maxIndex = indb[0][-1] | |
| 245 | except: |
|
247 | except: | |
| 246 | maxIndex = len(FFTs) |
|
248 | maxIndex = len(FFTs) | |
| 247 |
|
249 | |||
| 248 | self.selectFFTsByIndex(minIndex, maxIndex) |
|
250 | self.selectFFTsByIndex(minIndex, maxIndex) | |
| 249 |
|
251 | |||
| 250 | return 1 |
|
252 | return 1 | |
| 251 |
|
253 | |||
| 252 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): |
|
254 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): | |
| 253 | newheis = numpy.where( |
|
255 | newheis = numpy.where( | |
| 254 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
256 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 255 |
|
257 | |||
| 256 | if hei_ref != None: |
|
258 | if hei_ref != None: | |
| 257 | newheis = numpy.where(self.dataOut.heightList > hei_ref) |
|
259 | newheis = numpy.where(self.dataOut.heightList > hei_ref) | |
| 258 |
|
260 | |||
| 259 | minIndex = min(newheis[0]) |
|
261 | minIndex = min(newheis[0]) | |
| 260 | maxIndex = max(newheis[0]) |
|
262 | maxIndex = max(newheis[0]) | |
| 261 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
263 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] | |
| 262 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
264 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] | |
| 263 |
|
265 | |||
| 264 | # determina indices |
|
266 | # determina indices | |
| 265 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / |
|
267 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / | |
| 266 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) |
|
268 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) | |
| 267 | avg_dB = 10 * \ |
|
269 | avg_dB = 10 * \ | |
| 268 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) |
|
270 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) | |
| 269 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
271 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 270 | beacon_heiIndexList = [] |
|
272 | beacon_heiIndexList = [] | |
| 271 | for val in avg_dB.tolist(): |
|
273 | for val in avg_dB.tolist(): | |
| 272 | if val >= beacon_dB[0]: |
|
274 | if val >= beacon_dB[0]: | |
| 273 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
275 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 274 |
|
276 | |||
| 275 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
277 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 276 | data_cspc = None |
|
278 | data_cspc = None | |
| 277 | if self.dataOut.data_cspc is not None: |
|
279 | if self.dataOut.data_cspc is not None: | |
| 278 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
280 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] | |
| 279 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
281 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 280 |
|
282 | |||
| 281 | data_dc = None |
|
283 | data_dc = None | |
| 282 | if self.dataOut.data_dc is not None: |
|
284 | if self.dataOut.data_dc is not None: | |
| 283 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
285 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] | |
| 284 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
286 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 285 |
|
287 | |||
| 286 | self.dataOut.data_spc = data_spc |
|
288 | self.dataOut.data_spc = data_spc | |
| 287 | self.dataOut.data_cspc = data_cspc |
|
289 | self.dataOut.data_cspc = data_cspc | |
| 288 | self.dataOut.data_dc = data_dc |
|
290 | self.dataOut.data_dc = data_dc | |
| 289 | self.dataOut.heightList = heightList |
|
291 | self.dataOut.heightList = heightList | |
| 290 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
292 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 291 |
|
293 | |||
| 292 | return 1 |
|
294 | return 1 | |
| 293 |
|
295 | |||
| 294 | def selectFFTsByIndex(self, minIndex, maxIndex): |
|
296 | def selectFFTsByIndex(self, minIndex, maxIndex): | |
| 295 | """ |
|
297 | """ | |
| 296 |
|
298 | |||
| 297 | """ |
|
299 | """ | |
| 298 |
|
300 | |||
| 299 | if (minIndex < 0) or (minIndex > maxIndex): |
|
301 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 300 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
302 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) | |
| 301 |
|
303 | |||
| 302 | if (maxIndex >= self.dataOut.nProfiles): |
|
304 | if (maxIndex >= self.dataOut.nProfiles): | |
| 303 | maxIndex = self.dataOut.nProfiles-1 |
|
305 | maxIndex = self.dataOut.nProfiles-1 | |
| 304 |
|
306 | |||
| 305 | #Spectra |
|
307 | #Spectra | |
| 306 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] |
|
308 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] | |
| 307 |
|
309 | |||
| 308 | data_cspc = None |
|
310 | data_cspc = None | |
| 309 | if self.dataOut.data_cspc is not None: |
|
311 | if self.dataOut.data_cspc is not None: | |
| 310 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] |
|
312 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] | |
| 311 |
|
313 | |||
| 312 | data_dc = None |
|
314 | data_dc = None | |
| 313 | if self.dataOut.data_dc is not None: |
|
315 | if self.dataOut.data_dc is not None: | |
| 314 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] |
|
316 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] | |
| 315 |
|
317 | |||
| 316 | self.dataOut.data_spc = data_spc |
|
318 | self.dataOut.data_spc = data_spc | |
| 317 | self.dataOut.data_cspc = data_cspc |
|
319 | self.dataOut.data_cspc = data_cspc | |
| 318 | self.dataOut.data_dc = data_dc |
|
320 | self.dataOut.data_dc = data_dc | |
| 319 |
|
321 | |||
| 320 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) |
|
322 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) | |
| 321 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] |
|
323 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] | |
| 322 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] |
|
324 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] | |
| 323 |
|
325 | |||
| 324 | return 1 |
|
326 | return 1 | |
| 325 |
|
327 | |||
| 326 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
328 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 327 | # validacion de rango |
|
329 | # validacion de rango | |
| 328 | if minHei == None: |
|
330 | if minHei == None: | |
| 329 | minHei = self.dataOut.heightList[0] |
|
331 | minHei = self.dataOut.heightList[0] | |
| 330 |
|
332 | |||
| 331 | if maxHei == None: |
|
333 | if maxHei == None: | |
| 332 | maxHei = self.dataOut.heightList[-1] |
|
334 | maxHei = self.dataOut.heightList[-1] | |
| 333 |
|
335 | |||
| 334 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
336 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 335 | print('minHei: %.2f is out of the heights range' % (minHei)) |
|
337 | print('minHei: %.2f is out of the heights range' % (minHei)) | |
| 336 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) |
|
338 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) | |
| 337 | minHei = self.dataOut.heightList[0] |
|
339 | minHei = self.dataOut.heightList[0] | |
| 338 |
|
340 | |||
| 339 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
341 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 340 | print('maxHei: %.2f is out of the heights range' % (maxHei)) |
|
342 | print('maxHei: %.2f is out of the heights range' % (maxHei)) | |
| 341 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) |
|
343 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) | |
| 342 | maxHei = self.dataOut.heightList[-1] |
|
344 | maxHei = self.dataOut.heightList[-1] | |
| 343 |
|
345 | |||
| 344 | # validacion de velocidades |
|
346 | # validacion de velocidades | |
| 345 | velrange = self.dataOut.getVelRange(1) |
|
347 | velrange = self.dataOut.getVelRange(1) | |
| 346 |
|
348 | |||
| 347 | if minVel == None: |
|
349 | if minVel == None: | |
| 348 | minVel = velrange[0] |
|
350 | minVel = velrange[0] | |
| 349 |
|
351 | |||
| 350 | if maxVel == None: |
|
352 | if maxVel == None: | |
| 351 | maxVel = velrange[-1] |
|
353 | maxVel = velrange[-1] | |
| 352 |
|
354 | |||
| 353 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
355 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 354 | print('minVel: %.2f is out of the velocity range' % (minVel)) |
|
356 | print('minVel: %.2f is out of the velocity range' % (minVel)) | |
| 355 | print('minVel is setting to %.2f' % (velrange[0])) |
|
357 | print('minVel is setting to %.2f' % (velrange[0])) | |
| 356 | minVel = velrange[0] |
|
358 | minVel = velrange[0] | |
| 357 |
|
359 | |||
| 358 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
360 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 359 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) |
|
361 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) | |
| 360 | print('maxVel is setting to %.2f' % (velrange[-1])) |
|
362 | print('maxVel is setting to %.2f' % (velrange[-1])) | |
| 361 | maxVel = velrange[-1] |
|
363 | maxVel = velrange[-1] | |
| 362 |
|
364 | |||
| 363 | # seleccion de indices para rango |
|
365 | # seleccion de indices para rango | |
| 364 | minIndex = 0 |
|
366 | minIndex = 0 | |
| 365 | maxIndex = 0 |
|
367 | maxIndex = 0 | |
| 366 | heights = self.dataOut.heightList |
|
368 | heights = self.dataOut.heightList | |
| 367 |
|
369 | |||
| 368 | inda = numpy.where(heights >= minHei) |
|
370 | inda = numpy.where(heights >= minHei) | |
| 369 | indb = numpy.where(heights <= maxHei) |
|
371 | indb = numpy.where(heights <= maxHei) | |
| 370 |
|
372 | |||
| 371 | try: |
|
373 | try: | |
| 372 | minIndex = inda[0][0] |
|
374 | minIndex = inda[0][0] | |
| 373 | except: |
|
375 | except: | |
| 374 | minIndex = 0 |
|
376 | minIndex = 0 | |
| 375 |
|
377 | |||
| 376 | try: |
|
378 | try: | |
| 377 | maxIndex = indb[0][-1] |
|
379 | maxIndex = indb[0][-1] | |
| 378 | except: |
|
380 | except: | |
| 379 | maxIndex = len(heights) |
|
381 | maxIndex = len(heights) | |
| 380 |
|
382 | |||
| 381 | if (minIndex < 0) or (minIndex > maxIndex): |
|
383 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 382 | raise ValueError("some value in (%d,%d) is not valid" % ( |
|
384 | raise ValueError("some value in (%d,%d) is not valid" % ( | |
| 383 | minIndex, maxIndex)) |
|
385 | minIndex, maxIndex)) | |
| 384 |
|
386 | |||
| 385 | if (maxIndex >= self.dataOut.nHeights): |
|
387 | if (maxIndex >= self.dataOut.nHeights): | |
| 386 | maxIndex = self.dataOut.nHeights - 1 |
|
388 | maxIndex = self.dataOut.nHeights - 1 | |
| 387 |
|
389 | |||
| 388 | # seleccion de indices para velocidades |
|
390 | # seleccion de indices para velocidades | |
| 389 | indminvel = numpy.where(velrange >= minVel) |
|
391 | indminvel = numpy.where(velrange >= minVel) | |
| 390 | indmaxvel = numpy.where(velrange <= maxVel) |
|
392 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 391 | try: |
|
393 | try: | |
| 392 | minIndexVel = indminvel[0][0] |
|
394 | minIndexVel = indminvel[0][0] | |
| 393 | except: |
|
395 | except: | |
| 394 | minIndexVel = 0 |
|
396 | minIndexVel = 0 | |
| 395 |
|
397 | |||
| 396 | try: |
|
398 | try: | |
| 397 | maxIndexVel = indmaxvel[0][-1] |
|
399 | maxIndexVel = indmaxvel[0][-1] | |
| 398 | except: |
|
400 | except: | |
| 399 | maxIndexVel = len(velrange) |
|
401 | maxIndexVel = len(velrange) | |
| 400 |
|
402 | |||
| 401 | # seleccion del espectro |
|
403 | # seleccion del espectro | |
| 402 | data_spc = self.dataOut.data_spc[:, |
|
404 | data_spc = self.dataOut.data_spc[:, | |
| 403 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] |
|
405 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] | |
| 404 | # estimacion de ruido |
|
406 | # estimacion de ruido | |
| 405 | noise = numpy.zeros(self.dataOut.nChannels) |
|
407 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 406 |
|
408 | |||
| 407 | for channel in range(self.dataOut.nChannels): |
|
409 | for channel in range(self.dataOut.nChannels): | |
| 408 | daux = data_spc[channel, :, :] |
|
410 | daux = data_spc[channel, :, :] | |
| 409 | sortdata = numpy.sort(daux, axis=None) |
|
411 | sortdata = numpy.sort(daux, axis=None) | |
| 410 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) |
|
412 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) | |
| 411 |
|
413 | |||
| 412 | self.dataOut.noise_estimation = noise.copy() |
|
414 | self.dataOut.noise_estimation = noise.copy() | |
| 413 |
|
415 | |||
| 414 | return 1 |
|
416 | return 1 | |
| 415 |
|
417 | |||
| 416 | class removeDC(Operation): |
|
418 | class removeDC(Operation): | |
| 417 |
|
419 | |||
| 418 | def run(self, dataOut, mode=2): |
|
420 | def run(self, dataOut, mode=2): | |
| 419 | self.dataOut = dataOut |
|
421 | self.dataOut = dataOut | |
| 420 | jspectra = self.dataOut.data_spc |
|
422 | jspectra = self.dataOut.data_spc | |
| 421 | jcspectra = self.dataOut.data_cspc |
|
423 | jcspectra = self.dataOut.data_cspc | |
| 422 |
|
424 | |||
| 423 | num_chan = jspectra.shape[0] |
|
425 | num_chan = jspectra.shape[0] | |
| 424 | num_hei = jspectra.shape[2] |
|
426 | num_hei = jspectra.shape[2] | |
| 425 |
|
427 | |||
| 426 | if jcspectra is not None: |
|
428 | if jcspectra is not None: | |
| 427 | jcspectraExist = True |
|
429 | jcspectraExist = True | |
| 428 | num_pairs = jcspectra.shape[0] |
|
430 | num_pairs = jcspectra.shape[0] | |
| 429 | else: |
|
431 | else: | |
| 430 | jcspectraExist = False |
|
432 | jcspectraExist = False | |
| 431 |
|
433 | |||
| 432 | freq_dc = int(jspectra.shape[1] / 2) |
|
434 | freq_dc = int(jspectra.shape[1] / 2) | |
| 433 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc |
|
435 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc | |
| 434 | ind_vel = ind_vel.astype(int) |
|
436 | ind_vel = ind_vel.astype(int) | |
| 435 |
|
437 | |||
| 436 | if ind_vel[0] < 0: |
|
438 | if ind_vel[0] < 0: | |
| 437 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof |
|
439 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof | |
| 438 |
|
440 | |||
| 439 | if mode == 1: |
|
441 | if mode == 1: | |
| 440 | jspectra[:, freq_dc, :] = ( |
|
442 | jspectra[:, freq_dc, :] = ( | |
| 441 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION |
|
443 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION | |
| 442 |
|
444 | |||
| 443 | if jcspectraExist: |
|
445 | if jcspectraExist: | |
| 444 | jcspectra[:, freq_dc, :] = ( |
|
446 | jcspectra[:, freq_dc, :] = ( | |
| 445 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 |
|
447 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 | |
| 446 |
|
448 | |||
| 447 | if mode == 2: |
|
449 | if mode == 2: | |
| 448 |
|
450 | |||
| 449 | vel = numpy.array([-2, -1, 1, 2]) |
|
451 | vel = numpy.array([-2, -1, 1, 2]) | |
| 450 | xx = numpy.zeros([4, 4]) |
|
452 | xx = numpy.zeros([4, 4]) | |
| 451 |
|
453 | |||
| 452 | for fil in range(4): |
|
454 | for fil in range(4): | |
| 453 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) |
|
455 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) | |
| 454 |
|
456 | |||
| 455 | xx_inv = numpy.linalg.inv(xx) |
|
457 | xx_inv = numpy.linalg.inv(xx) | |
| 456 | xx_aux = xx_inv[0, :] |
|
458 | xx_aux = xx_inv[0, :] | |
| 457 |
|
459 | |||
| 458 | for ich in range(num_chan): |
|
460 | for ich in range(num_chan): | |
| 459 | yy = jspectra[ich, ind_vel, :] |
|
461 | yy = jspectra[ich, ind_vel, :] | |
| 460 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
462 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 461 |
|
463 | |||
| 462 | junkid = jspectra[ich, freq_dc, :] <= 0 |
|
464 | junkid = jspectra[ich, freq_dc, :] <= 0 | |
| 463 | cjunkid = sum(junkid) |
|
465 | cjunkid = sum(junkid) | |
| 464 |
|
466 | |||
| 465 | if cjunkid.any(): |
|
467 | if cjunkid.any(): | |
| 466 | jspectra[ich, freq_dc, junkid.nonzero()] = ( |
|
468 | jspectra[ich, freq_dc, junkid.nonzero()] = ( | |
| 467 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 |
|
469 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 | |
| 468 |
|
470 | |||
| 469 | if jcspectraExist: |
|
471 | if jcspectraExist: | |
| 470 | for ip in range(num_pairs): |
|
472 | for ip in range(num_pairs): | |
| 471 | yy = jcspectra[ip, ind_vel, :] |
|
473 | yy = jcspectra[ip, ind_vel, :] | |
| 472 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
474 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 473 |
|
475 | |||
| 474 | self.dataOut.data_spc = jspectra |
|
476 | self.dataOut.data_spc = jspectra | |
| 475 | self.dataOut.data_cspc = jcspectra |
|
477 | self.dataOut.data_cspc = jcspectra | |
| 476 |
|
478 | |||
| 477 | return self.dataOut |
|
479 | return self.dataOut | |
| 478 |
|
480 | |||
| 479 | class removeInterference(Operation): |
|
481 | class removeInterference(Operation): | |
| 480 |
|
482 | |||
| 481 | def removeInterference2(self): |
|
483 | def removeInterference2(self): | |
| 482 |
|
484 | |||
| 483 | cspc = self.dataOut.data_cspc |
|
485 | cspc = self.dataOut.data_cspc | |
| 484 | spc = self.dataOut.data_spc |
|
486 | spc = self.dataOut.data_spc | |
| 485 | Heights = numpy.arange(cspc.shape[2]) |
|
487 | Heights = numpy.arange(cspc.shape[2]) | |
| 486 | realCspc = numpy.abs(cspc) |
|
488 | realCspc = numpy.abs(cspc) | |
| 487 |
|
489 | |||
| 488 | for i in range(cspc.shape[0]): |
|
490 | for i in range(cspc.shape[0]): | |
| 489 | LinePower= numpy.sum(realCspc[i], axis=0) |
|
491 | LinePower= numpy.sum(realCspc[i], axis=0) | |
| 490 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] |
|
492 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] | |
| 491 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] |
|
493 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] | |
| 492 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) |
|
494 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) | |
| 493 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] |
|
495 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] | |
| 494 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] |
|
496 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] | |
| 495 |
|
497 | |||
| 496 |
|
498 | |||
| 497 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) |
|
499 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) | |
| 498 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) |
|
500 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) | |
| 499 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): |
|
501 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): | |
| 500 | cspc[i,InterferenceRange,:] = numpy.NaN |
|
502 | cspc[i,InterferenceRange,:] = numpy.NaN | |
| 501 |
|
503 | |||
| 502 | self.dataOut.data_cspc = cspc |
|
504 | self.dataOut.data_cspc = cspc | |
| 503 |
|
505 | |||
| 504 | def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None): |
|
506 | def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 505 |
|
507 | |||
| 506 | jspectra = self.dataOut.data_spc |
|
508 | jspectra = self.dataOut.data_spc | |
| 507 | jcspectra = self.dataOut.data_cspc |
|
509 | jcspectra = self.dataOut.data_cspc | |
| 508 | jnoise = self.dataOut.getNoise() |
|
510 | jnoise = self.dataOut.getNoise() | |
| 509 | num_incoh = self.dataOut.nIncohInt |
|
511 | num_incoh = self.dataOut.nIncohInt | |
| 510 |
|
512 | |||
| 511 | num_channel = jspectra.shape[0] |
|
513 | num_channel = jspectra.shape[0] | |
| 512 | num_prof = jspectra.shape[1] |
|
514 | num_prof = jspectra.shape[1] | |
| 513 | num_hei = jspectra.shape[2] |
|
515 | num_hei = jspectra.shape[2] | |
| 514 |
|
516 | |||
| 515 | # hei_interf |
|
517 | # hei_interf | |
| 516 | if hei_interf is None: |
|
518 | if hei_interf is None: | |
| 517 | count_hei = int(num_hei / 2) |
|
519 | count_hei = int(num_hei / 2) | |
| 518 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei |
|
520 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei | |
| 519 | hei_interf = numpy.asarray(hei_interf)[0] |
|
521 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 520 | # nhei_interf |
|
522 | # nhei_interf | |
| 521 | if (nhei_interf == None): |
|
523 | if (nhei_interf == None): | |
| 522 | nhei_interf = 5 |
|
524 | nhei_interf = 5 | |
| 523 | if (nhei_interf < 1): |
|
525 | if (nhei_interf < 1): | |
| 524 | nhei_interf = 1 |
|
526 | nhei_interf = 1 | |
| 525 | if (nhei_interf > count_hei): |
|
527 | if (nhei_interf > count_hei): | |
| 526 | nhei_interf = count_hei |
|
528 | nhei_interf = count_hei | |
| 527 | if (offhei_interf == None): |
|
529 | if (offhei_interf == None): | |
| 528 | offhei_interf = 0 |
|
530 | offhei_interf = 0 | |
| 529 |
|
531 | |||
| 530 | ind_hei = list(range(num_hei)) |
|
532 | ind_hei = list(range(num_hei)) | |
| 531 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
533 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 532 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
534 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 533 | mask_prof = numpy.asarray(list(range(num_prof))) |
|
535 | mask_prof = numpy.asarray(list(range(num_prof))) | |
| 534 | num_mask_prof = mask_prof.size |
|
536 | num_mask_prof = mask_prof.size | |
| 535 | comp_mask_prof = [0, num_prof / 2] |
|
537 | comp_mask_prof = [0, num_prof / 2] | |
| 536 |
|
538 | |||
| 537 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
539 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 538 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
540 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 539 | jnoise = numpy.nan |
|
541 | jnoise = numpy.nan | |
| 540 | noise_exist = jnoise[0] < numpy.Inf |
|
542 | noise_exist = jnoise[0] < numpy.Inf | |
| 541 |
|
543 | |||
| 542 | # Subrutina de Remocion de la Interferencia |
|
544 | # Subrutina de Remocion de la Interferencia | |
| 543 | for ich in range(num_channel): |
|
545 | for ich in range(num_channel): | |
| 544 | # Se ordena los espectros segun su potencia (menor a mayor) |
|
546 | # Se ordena los espectros segun su potencia (menor a mayor) | |
| 545 | power = jspectra[ich, mask_prof, :] |
|
547 | power = jspectra[ich, mask_prof, :] | |
| 546 | power = power[:, hei_interf] |
|
548 | power = power[:, hei_interf] | |
| 547 | power = power.sum(axis=0) |
|
549 | power = power.sum(axis=0) | |
| 548 | psort = power.ravel().argsort() |
|
550 | psort = power.ravel().argsort() | |
| 549 |
|
551 | |||
| 550 | # Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
552 | # Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 551 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( |
|
553 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( | |
| 552 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
554 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 553 |
|
555 | |||
| 554 | if noise_exist: |
|
556 | if noise_exist: | |
| 555 | # tmp_noise = jnoise[ich] / num_prof |
|
557 | # tmp_noise = jnoise[ich] / num_prof | |
| 556 | tmp_noise = jnoise[ich] |
|
558 | tmp_noise = jnoise[ich] | |
| 557 | junkspc_interf = junkspc_interf - tmp_noise |
|
559 | junkspc_interf = junkspc_interf - tmp_noise | |
| 558 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
560 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 559 |
|
561 | |||
| 560 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf |
|
562 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf | |
| 561 | jspc_interf = jspc_interf.transpose() |
|
563 | jspc_interf = jspc_interf.transpose() | |
| 562 | # Calculando el espectro de interferencia promedio |
|
564 | # Calculando el espectro de interferencia promedio | |
| 563 | noiseid = numpy.where( |
|
565 | noiseid = numpy.where( | |
| 564 | jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) |
|
566 | jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) | |
| 565 | noiseid = noiseid[0] |
|
567 | noiseid = noiseid[0] | |
| 566 | cnoiseid = noiseid.size |
|
568 | cnoiseid = noiseid.size | |
| 567 | interfid = numpy.where( |
|
569 | interfid = numpy.where( | |
| 568 | jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) |
|
570 | jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) | |
| 569 | interfid = interfid[0] |
|
571 | interfid = interfid[0] | |
| 570 | cinterfid = interfid.size |
|
572 | cinterfid = interfid.size | |
| 571 |
|
573 | |||
| 572 | if (cnoiseid > 0): |
|
574 | if (cnoiseid > 0): | |
| 573 | jspc_interf[noiseid] = 0 |
|
575 | jspc_interf[noiseid] = 0 | |
| 574 |
|
576 | |||
| 575 | # Expandiendo los perfiles a limpiar |
|
577 | # Expandiendo los perfiles a limpiar | |
| 576 | if (cinterfid > 0): |
|
578 | if (cinterfid > 0): | |
| 577 | new_interfid = ( |
|
579 | new_interfid = ( | |
| 578 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof |
|
580 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof | |
| 579 | new_interfid = numpy.asarray(new_interfid) |
|
581 | new_interfid = numpy.asarray(new_interfid) | |
| 580 | new_interfid = {x for x in new_interfid} |
|
582 | new_interfid = {x for x in new_interfid} | |
| 581 | new_interfid = numpy.array(list(new_interfid)) |
|
583 | new_interfid = numpy.array(list(new_interfid)) | |
| 582 | new_cinterfid = new_interfid.size |
|
584 | new_cinterfid = new_interfid.size | |
| 583 | else: |
|
585 | else: | |
| 584 | new_cinterfid = 0 |
|
586 | new_cinterfid = 0 | |
| 585 |
|
587 | |||
| 586 | for ip in range(new_cinterfid): |
|
588 | for ip in range(new_cinterfid): | |
| 587 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() |
|
589 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() | |
| 588 | jspc_interf[new_interfid[ip] |
|
590 | jspc_interf[new_interfid[ip] | |
| 589 | ] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] |
|
591 | ] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] | |
| 590 |
|
592 | |||
| 591 | jspectra[ich, :, ind_hei] = jspectra[ich, :, |
|
593 | jspectra[ich, :, ind_hei] = jspectra[ich, :, | |
| 592 | ind_hei] - jspc_interf # Corregir indices |
|
594 | ind_hei] - jspc_interf # Corregir indices | |
| 593 |
|
595 | |||
| 594 | # Removiendo la interferencia del punto de mayor interferencia |
|
596 | # Removiendo la interferencia del punto de mayor interferencia | |
| 595 | ListAux = jspc_interf[mask_prof].tolist() |
|
597 | ListAux = jspc_interf[mask_prof].tolist() | |
| 596 | maxid = ListAux.index(max(ListAux)) |
|
598 | maxid = ListAux.index(max(ListAux)) | |
| 597 |
|
599 | |||
| 598 | if cinterfid > 0: |
|
600 | if cinterfid > 0: | |
| 599 | for ip in range(cinterfid * (interf == 2) - 1): |
|
601 | for ip in range(cinterfid * (interf == 2) - 1): | |
| 600 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * |
|
602 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * | |
| 601 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() |
|
603 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 602 | cind = len(ind) |
|
604 | cind = len(ind) | |
| 603 |
|
605 | |||
| 604 | if (cind > 0): |
|
606 | if (cind > 0): | |
| 605 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ |
|
607 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ | |
| 606 | (1 + (numpy.random.uniform(cind) - 0.5) / |
|
608 | (1 + (numpy.random.uniform(cind) - 0.5) / | |
| 607 | numpy.sqrt(num_incoh)) |
|
609 | numpy.sqrt(num_incoh)) | |
| 608 |
|
610 | |||
| 609 | ind = numpy.array([-2, -1, 1, 2]) |
|
611 | ind = numpy.array([-2, -1, 1, 2]) | |
| 610 | xx = numpy.zeros([4, 4]) |
|
612 | xx = numpy.zeros([4, 4]) | |
| 611 |
|
613 | |||
| 612 | for id1 in range(4): |
|
614 | for id1 in range(4): | |
| 613 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
615 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 614 |
|
616 | |||
| 615 | xx_inv = numpy.linalg.inv(xx) |
|
617 | xx_inv = numpy.linalg.inv(xx) | |
| 616 | xx = xx_inv[:, 0] |
|
618 | xx = xx_inv[:, 0] | |
| 617 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
619 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 618 | yy = jspectra[ich, mask_prof[ind], :] |
|
620 | yy = jspectra[ich, mask_prof[ind], :] | |
| 619 | jspectra[ich, mask_prof[maxid], :] = numpy.dot( |
|
621 | jspectra[ich, mask_prof[maxid], :] = numpy.dot( | |
| 620 | yy.transpose(), xx) |
|
622 | yy.transpose(), xx) | |
| 621 |
|
623 | |||
| 622 | indAux = (jspectra[ich, :, :] < tmp_noise * |
|
624 | indAux = (jspectra[ich, :, :] < tmp_noise * | |
| 623 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() |
|
625 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 624 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ |
|
626 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ | |
| 625 | (1 - 1 / numpy.sqrt(num_incoh)) |
|
627 | (1 - 1 / numpy.sqrt(num_incoh)) | |
| 626 |
|
628 | |||
| 627 | # Remocion de Interferencia en el Cross Spectra |
|
629 | # Remocion de Interferencia en el Cross Spectra | |
| 628 | if jcspectra is None: |
|
630 | if jcspectra is None: | |
| 629 | return jspectra, jcspectra |
|
631 | return jspectra, jcspectra | |
| 630 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) |
|
632 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) | |
| 631 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
633 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 632 |
|
634 | |||
| 633 | for ip in range(num_pairs): |
|
635 | for ip in range(num_pairs): | |
| 634 |
|
636 | |||
| 635 | #------------------------------------------- |
|
637 | #------------------------------------------- | |
| 636 |
|
638 | |||
| 637 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) |
|
639 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) | |
| 638 | cspower = cspower[:, hei_interf] |
|
640 | cspower = cspower[:, hei_interf] | |
| 639 | cspower = cspower.sum(axis=0) |
|
641 | cspower = cspower.sum(axis=0) | |
| 640 |
|
642 | |||
| 641 | cspsort = cspower.ravel().argsort() |
|
643 | cspsort = cspower.ravel().argsort() | |
| 642 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( |
|
644 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( | |
| 643 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
645 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 644 | junkcspc_interf = junkcspc_interf.transpose() |
|
646 | junkcspc_interf = junkcspc_interf.transpose() | |
| 645 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf |
|
647 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf | |
| 646 |
|
648 | |||
| 647 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
649 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 648 |
|
650 | |||
| 649 | median_real = int(numpy.median(numpy.real( |
|
651 | median_real = int(numpy.median(numpy.real( | |
| 650 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
652 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 651 | median_imag = int(numpy.median(numpy.imag( |
|
653 | median_imag = int(numpy.median(numpy.imag( | |
| 652 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
654 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 653 | comp_mask_prof = [int(e) for e in comp_mask_prof] |
|
655 | comp_mask_prof = [int(e) for e in comp_mask_prof] | |
| 654 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( |
|
656 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( | |
| 655 | median_real, median_imag) |
|
657 | median_real, median_imag) | |
| 656 |
|
658 | |||
| 657 | for iprof in range(num_prof): |
|
659 | for iprof in range(num_prof): | |
| 658 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() |
|
660 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() | |
| 659 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] |
|
661 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] | |
| 660 |
|
662 | |||
| 661 | # Removiendo la Interferencia |
|
663 | # Removiendo la Interferencia | |
| 662 | jcspectra[ip, :, ind_hei] = jcspectra[ip, |
|
664 | jcspectra[ip, :, ind_hei] = jcspectra[ip, | |
| 663 | :, ind_hei] - jcspc_interf |
|
665 | :, ind_hei] - jcspc_interf | |
| 664 |
|
666 | |||
| 665 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
667 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 666 | maxid = ListAux.index(max(ListAux)) |
|
668 | maxid = ListAux.index(max(ListAux)) | |
| 667 |
|
669 | |||
| 668 | ind = numpy.array([-2, -1, 1, 2]) |
|
670 | ind = numpy.array([-2, -1, 1, 2]) | |
| 669 | xx = numpy.zeros([4, 4]) |
|
671 | xx = numpy.zeros([4, 4]) | |
| 670 |
|
672 | |||
| 671 | for id1 in range(4): |
|
673 | for id1 in range(4): | |
| 672 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
674 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 673 |
|
675 | |||
| 674 | xx_inv = numpy.linalg.inv(xx) |
|
676 | xx_inv = numpy.linalg.inv(xx) | |
| 675 | xx = xx_inv[:, 0] |
|
677 | xx = xx_inv[:, 0] | |
| 676 |
|
678 | |||
| 677 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
679 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 678 | yy = jcspectra[ip, mask_prof[ind], :] |
|
680 | yy = jcspectra[ip, mask_prof[ind], :] | |
| 679 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) |
|
681 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) | |
| 680 |
|
682 | |||
| 681 | # Guardar Resultados |
|
683 | # Guardar Resultados | |
| 682 | self.dataOut.data_spc = jspectra |
|
684 | self.dataOut.data_spc = jspectra | |
| 683 | self.dataOut.data_cspc = jcspectra |
|
685 | self.dataOut.data_cspc = jcspectra | |
| 684 |
|
686 | |||
| 685 | return 1 |
|
687 | return 1 | |
| 686 |
|
688 | |||
| 687 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1): |
|
689 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1): | |
| 688 |
|
690 | |||
| 689 | self.dataOut = dataOut |
|
691 | self.dataOut = dataOut | |
| 690 |
|
692 | |||
| 691 | if mode == 1: |
|
693 | if mode == 1: | |
| 692 | self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None) |
|
694 | self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None) | |
| 693 | elif mode == 2: |
|
695 | elif mode == 2: | |
| 694 | self.removeInterference2() |
|
696 | self.removeInterference2() | |
| 695 |
|
697 | |||
| 696 | return self.dataOut |
|
698 | return self.dataOut | |
| 697 |
|
699 | |||
| 698 |
|
700 | |||
| 699 | class IncohInt(Operation): |
|
701 | class IncohInt(Operation): | |
| 700 |
|
702 | |||
| 701 | __profIndex = 0 |
|
703 | __profIndex = 0 | |
| 702 | __withOverapping = False |
|
704 | __withOverapping = False | |
| 703 |
|
705 | |||
| 704 | __byTime = False |
|
706 | __byTime = False | |
| 705 | __initime = None |
|
707 | __initime = None | |
| 706 | __lastdatatime = None |
|
708 | __lastdatatime = None | |
| 707 | __integrationtime = None |
|
709 | __integrationtime = None | |
| 708 |
|
710 | |||
| 709 | __buffer_spc = None |
|
711 | __buffer_spc = None | |
| 710 | __buffer_cspc = None |
|
712 | __buffer_cspc = None | |
| 711 | __buffer_dc = None |
|
713 | __buffer_dc = None | |
| 712 |
|
714 | |||
| 713 | __dataReady = False |
|
715 | __dataReady = False | |
| 714 |
|
716 | |||
| 715 | __timeInterval = None |
|
717 | __timeInterval = None | |
| 716 |
|
718 | |||
| 717 | n = None |
|
719 | n = None | |
| 718 |
|
720 | |||
| 719 | def __init__(self): |
|
721 | def __init__(self): | |
| 720 |
|
722 | |||
| 721 | Operation.__init__(self) |
|
723 | Operation.__init__(self) | |
| 722 |
|
724 | |||
| 723 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
725 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 724 | """ |
|
726 | """ | |
| 725 | Set the parameters of the integration class. |
|
727 | Set the parameters of the integration class. | |
| 726 |
|
728 | |||
| 727 | Inputs: |
|
729 | Inputs: | |
| 728 |
|
730 | |||
| 729 | n : Number of coherent integrations |
|
731 | n : Number of coherent integrations | |
| 730 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
732 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 731 | overlapping : |
|
733 | overlapping : | |
| 732 |
|
734 | |||
| 733 | """ |
|
735 | """ | |
| 734 |
|
736 | |||
| 735 | self.__initime = None |
|
737 | self.__initime = None | |
| 736 | self.__lastdatatime = 0 |
|
738 | self.__lastdatatime = 0 | |
| 737 |
|
739 | |||
| 738 | self.__buffer_spc = 0 |
|
740 | self.__buffer_spc = 0 | |
| 739 | self.__buffer_cspc = 0 |
|
741 | self.__buffer_cspc = 0 | |
| 740 | self.__buffer_dc = 0 |
|
742 | self.__buffer_dc = 0 | |
| 741 |
|
743 | |||
| 742 | self.__profIndex = 0 |
|
744 | self.__profIndex = 0 | |
| 743 | self.__dataReady = False |
|
745 | self.__dataReady = False | |
| 744 | self.__byTime = False |
|
746 | self.__byTime = False | |
| 745 |
|
747 | |||
| 746 | if n is None and timeInterval is None: |
|
748 | if n is None and timeInterval is None: | |
| 747 | raise ValueError("n or timeInterval should be specified ...") |
|
749 | raise ValueError("n or timeInterval should be specified ...") | |
| 748 |
|
750 | |||
| 749 | if n is not None: |
|
751 | if n is not None: | |
| 750 | self.n = int(n) |
|
752 | self.n = int(n) | |
| 751 | else: |
|
753 | else: | |
| 752 |
|
754 | |||
| 753 | self.__integrationtime = int(timeInterval) |
|
755 | self.__integrationtime = int(timeInterval) | |
| 754 | self.n = None |
|
756 | self.n = None | |
| 755 | self.__byTime = True |
|
757 | self.__byTime = True | |
| 756 |
|
758 | |||
| 757 | def putData(self, data_spc, data_cspc, data_dc): |
|
759 | def putData(self, data_spc, data_cspc, data_dc): | |
| 758 | """ |
|
760 | """ | |
| 759 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
761 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 760 |
|
762 | |||
| 761 | """ |
|
763 | """ | |
| 762 |
|
764 | |||
| 763 | self.__buffer_spc += data_spc |
|
765 | self.__buffer_spc += data_spc | |
| 764 |
|
766 | |||
| 765 | if data_cspc is None: |
|
767 | if data_cspc is None: | |
| 766 | self.__buffer_cspc = None |
|
768 | self.__buffer_cspc = None | |
| 767 | else: |
|
769 | else: | |
| 768 | self.__buffer_cspc += data_cspc |
|
770 | self.__buffer_cspc += data_cspc | |
| 769 |
|
771 | |||
| 770 | if data_dc is None: |
|
772 | if data_dc is None: | |
| 771 | self.__buffer_dc = None |
|
773 | self.__buffer_dc = None | |
| 772 | else: |
|
774 | else: | |
| 773 | self.__buffer_dc += data_dc |
|
775 | self.__buffer_dc += data_dc | |
| 774 |
|
776 | |||
| 775 | self.__profIndex += 1 |
|
777 | self.__profIndex += 1 | |
| 776 |
|
778 | |||
| 777 | return |
|
779 | return | |
| 778 |
|
780 | |||
| 779 | def pushData(self): |
|
781 | def pushData(self): | |
| 780 | """ |
|
782 | """ | |
| 781 | Return the sum of the last profiles and the profiles used in the sum. |
|
783 | Return the sum of the last profiles and the profiles used in the sum. | |
| 782 |
|
784 | |||
| 783 | Affected: |
|
785 | Affected: | |
| 784 |
|
786 | |||
| 785 | self.__profileIndex |
|
787 | self.__profileIndex | |
| 786 |
|
788 | |||
| 787 | """ |
|
789 | """ | |
| 788 |
|
790 | |||
| 789 | data_spc = self.__buffer_spc |
|
791 | data_spc = self.__buffer_spc | |
| 790 | data_cspc = self.__buffer_cspc |
|
792 | data_cspc = self.__buffer_cspc | |
| 791 | data_dc = self.__buffer_dc |
|
793 | data_dc = self.__buffer_dc | |
| 792 | n = self.__profIndex |
|
794 | n = self.__profIndex | |
| 793 |
|
795 | |||
| 794 | self.__buffer_spc = 0 |
|
796 | self.__buffer_spc = 0 | |
| 795 | self.__buffer_cspc = 0 |
|
797 | self.__buffer_cspc = 0 | |
| 796 | self.__buffer_dc = 0 |
|
798 | self.__buffer_dc = 0 | |
| 797 | self.__profIndex = 0 |
|
799 | self.__profIndex = 0 | |
| 798 |
|
800 | |||
| 799 | return data_spc, data_cspc, data_dc, n |
|
801 | return data_spc, data_cspc, data_dc, n | |
| 800 |
|
802 | |||
| 801 | def byProfiles(self, *args): |
|
803 | def byProfiles(self, *args): | |
| 802 |
|
804 | |||
| 803 | self.__dataReady = False |
|
805 | self.__dataReady = False | |
| 804 | avgdata_spc = None |
|
806 | avgdata_spc = None | |
| 805 | avgdata_cspc = None |
|
807 | avgdata_cspc = None | |
| 806 | avgdata_dc = None |
|
808 | avgdata_dc = None | |
| 807 |
|
809 | |||
| 808 | self.putData(*args) |
|
810 | self.putData(*args) | |
| 809 |
|
811 | |||
| 810 | if self.__profIndex == self.n: |
|
812 | if self.__profIndex == self.n: | |
| 811 |
|
813 | |||
| 812 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
814 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 813 | self.n = n |
|
815 | self.n = n | |
| 814 | self.__dataReady = True |
|
816 | self.__dataReady = True | |
| 815 |
|
817 | |||
| 816 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
818 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 817 |
|
819 | |||
| 818 | def byTime(self, datatime, *args): |
|
820 | def byTime(self, datatime, *args): | |
| 819 |
|
821 | |||
| 820 | self.__dataReady = False |
|
822 | self.__dataReady = False | |
| 821 | avgdata_spc = None |
|
823 | avgdata_spc = None | |
| 822 | avgdata_cspc = None |
|
824 | avgdata_cspc = None | |
| 823 | avgdata_dc = None |
|
825 | avgdata_dc = None | |
| 824 |
|
826 | |||
| 825 | self.putData(*args) |
|
827 | self.putData(*args) | |
| 826 |
|
828 | |||
| 827 | if (datatime - self.__initime) >= self.__integrationtime: |
|
829 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 828 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
830 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 829 | self.n = n |
|
831 | self.n = n | |
| 830 | self.__dataReady = True |
|
832 | self.__dataReady = True | |
| 831 |
|
833 | |||
| 832 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
834 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 833 |
|
835 | |||
| 834 | def integrate(self, datatime, *args): |
|
836 | def integrate(self, datatime, *args): | |
| 835 |
|
837 | |||
| 836 | if self.__profIndex == 0: |
|
838 | if self.__profIndex == 0: | |
| 837 | self.__initime = datatime |
|
839 | self.__initime = datatime | |
| 838 |
|
840 | |||
| 839 | if self.__byTime: |
|
841 | if self.__byTime: | |
| 840 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( |
|
842 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( | |
| 841 | datatime, *args) |
|
843 | datatime, *args) | |
| 842 | else: |
|
844 | else: | |
| 843 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
845 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 844 |
|
846 | |||
| 845 | if not self.__dataReady: |
|
847 | if not self.__dataReady: | |
| 846 | return None, None, None, None |
|
848 | return None, None, None, None | |
| 847 |
|
849 | |||
| 848 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
850 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 849 |
|
851 | |||
| 850 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
852 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 851 | if n == 1: |
|
853 | if n == 1: | |
| 852 | return dataOut |
|
854 | return dataOut | |
| 853 |
|
855 | |||
| 854 | dataOut.flagNoData = True |
|
856 | dataOut.flagNoData = True | |
| 855 |
|
857 | |||
| 856 | if not self.isConfig: |
|
858 | if not self.isConfig: | |
| 857 | self.setup(n, timeInterval, overlapping) |
|
859 | self.setup(n, timeInterval, overlapping) | |
| 858 | self.isConfig = True |
|
860 | self.isConfig = True | |
| 859 |
|
861 | |||
| 860 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
862 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 861 | dataOut.data_spc, |
|
863 | dataOut.data_spc, | |
| 862 | dataOut.data_cspc, |
|
864 | dataOut.data_cspc, | |
| 863 | dataOut.data_dc) |
|
865 | dataOut.data_dc) | |
| 864 |
|
866 | |||
| 865 | if self.__dataReady: |
|
867 | if self.__dataReady: | |
| 866 |
|
868 | |||
| 867 | dataOut.data_spc = avgdata_spc |
|
869 | dataOut.data_spc = avgdata_spc | |
| 868 | dataOut.data_cspc = avgdata_cspc |
|
870 | dataOut.data_cspc = avgdata_cspc | |
| 869 | dataOut.data_dc = avgdata_dc |
|
871 | dataOut.data_dc = avgdata_dc | |
| 870 | dataOut.nIncohInt *= self.n |
|
872 | dataOut.nIncohInt *= self.n | |
| 871 | dataOut.utctime = avgdatatime |
|
873 | dataOut.utctime = avgdatatime | |
| 872 | dataOut.flagNoData = False |
|
874 | dataOut.flagNoData = False | |
| 873 |
|
875 | |||
| 874 | return dataOut No newline at end of file |
|
876 | return dataOut | |
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