| @@ -1,882 +1,882 | |||||
| 1 | import time |
|
1 | import time | |
| 2 | import itertools |
|
2 | import itertools | |
| 3 |
|
3 | |||
| 4 | import numpy |
|
4 | import numpy | |
| 5 |
|
5 | |||
| 6 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation |
|
6 | from schainpy.model.proc.jroproc_base import ProcessingUnit, MPDecorator, Operation | |
| 7 | from schainpy.model.data.jrodata import Spectra |
|
7 | from schainpy.model.data.jrodata import Spectra | |
| 8 | from schainpy.model.data.jrodata import hildebrand_sekhon |
|
8 | from schainpy.model.data.jrodata import hildebrand_sekhon | |
| 9 | from schainpy.utils import log |
|
9 | from schainpy.utils import log | |
| 10 |
|
10 | |||
| 11 |
|
11 | |||
| 12 | class SpectraProc(ProcessingUnit): |
|
12 | class SpectraProc(ProcessingUnit): | |
| 13 |
|
13 | |||
| 14 |
|
14 | |||
| 15 | def __init__(self): |
|
15 | def __init__(self): | |
| 16 |
|
16 | |||
| 17 | ProcessingUnit.__init__(self) |
|
17 | ProcessingUnit.__init__(self) | |
| 18 |
|
18 | |||
| 19 | self.buffer = None |
|
19 | self.buffer = None | |
| 20 | self.firstdatatime = None |
|
20 | self.firstdatatime = None | |
| 21 | self.profIndex = 0 |
|
21 | self.profIndex = 0 | |
| 22 | self.dataOut = Spectra() |
|
22 | self.dataOut = Spectra() | |
| 23 | self.id_min = None |
|
23 | self.id_min = None | |
| 24 | self.id_max = None |
|
24 | self.id_max = None | |
| 25 | self.setupReq = False #Agregar a todas las unidades de proc |
|
25 | self.setupReq = False #Agregar a todas las unidades de proc | |
| 26 |
|
26 | |||
| 27 | def __updateSpecFromVoltage(self): |
|
27 | def __updateSpecFromVoltage(self): | |
| 28 |
|
28 | |||
| 29 | self.dataOut.timeZone = self.dataIn.timeZone |
|
29 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 30 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
30 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 31 | self.dataOut.errorCount = self.dataIn.errorCount |
|
31 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 32 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
32 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 33 | try: |
|
33 | try: | |
| 34 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() |
|
34 | self.dataOut.processingHeaderObj = self.dataIn.processingHeaderObj.copy() | |
| 35 | except: |
|
35 | except: | |
| 36 | pass |
|
36 | pass | |
| 37 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
37 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 38 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
38 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 39 | self.dataOut.channelList = self.dataIn.channelList |
|
39 | self.dataOut.channelList = self.dataIn.channelList | |
| 40 | self.dataOut.heightList = self.dataIn.heightList |
|
40 | self.dataOut.heightList = self.dataIn.heightList | |
| 41 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) |
|
41 | self.dataOut.dtype = numpy.dtype([('real', '<f4'), ('imag', '<f4')]) | |
| 42 |
|
42 | |||
| 43 | self.dataOut.nBaud = self.dataIn.nBaud |
|
43 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 44 | self.dataOut.nCode = self.dataIn.nCode |
|
44 | self.dataOut.nCode = self.dataIn.nCode | |
| 45 | self.dataOut.code = self.dataIn.code |
|
45 | self.dataOut.code = self.dataIn.code | |
| 46 | self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
46 | self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 47 |
|
47 | |||
| 48 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
48 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 49 | self.dataOut.utctime = self.firstdatatime |
|
49 | self.dataOut.utctime = self.firstdatatime | |
| 50 | # asumo q la data esta decodificada |
|
50 | # asumo q la data esta decodificada | |
| 51 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData |
|
51 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData | |
| 52 | # asumo q la data esta sin flip |
|
52 | # asumo q la data esta sin flip | |
| 53 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData |
|
53 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData | |
| 54 | self.dataOut.flagShiftFFT = False |
|
54 | self.dataOut.flagShiftFFT = False | |
| 55 |
|
55 | |||
| 56 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
56 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 57 | self.dataOut.nIncohInt = 1 |
|
57 | self.dataOut.nIncohInt = 1 | |
| 58 |
|
58 | |||
| 59 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
59 | self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 60 |
|
60 | |||
| 61 | self.dataOut.frequency = self.dataIn.frequency |
|
61 | self.dataOut.frequency = self.dataIn.frequency | |
| 62 | self.dataOut.realtime = self.dataIn.realtime |
|
62 | self.dataOut.realtime = self.dataIn.realtime | |
| 63 |
|
63 | |||
| 64 | self.dataOut.azimuth = self.dataIn.azimuth |
|
64 | self.dataOut.azimuth = self.dataIn.azimuth | |
| 65 | self.dataOut.zenith = self.dataIn.zenith |
|
65 | self.dataOut.zenith = self.dataIn.zenith | |
| 66 |
|
66 | |||
| 67 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
67 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
| 68 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
68 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
| 69 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
69 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
| 70 |
|
70 | |||
| 71 | def __getFft(self): |
|
71 | def __getFft(self): | |
| 72 | """ |
|
72 | """ | |
| 73 | Convierte valores de Voltaje a Spectra |
|
73 | Convierte valores de Voltaje a Spectra | |
| 74 |
|
74 | |||
| 75 | Affected: |
|
75 | Affected: | |
| 76 | self.dataOut.data_spc |
|
76 | self.dataOut.data_spc | |
| 77 | self.dataOut.data_cspc |
|
77 | self.dataOut.data_cspc | |
| 78 | self.dataOut.data_dc |
|
78 | self.dataOut.data_dc | |
| 79 | self.dataOut.heightList |
|
79 | self.dataOut.heightList | |
| 80 | self.profIndex |
|
80 | self.profIndex | |
| 81 | self.buffer |
|
81 | self.buffer | |
| 82 | self.dataOut.flagNoData |
|
82 | self.dataOut.flagNoData | |
| 83 | """ |
|
83 | """ | |
| 84 | fft_volt = numpy.fft.fft( |
|
84 | fft_volt = numpy.fft.fft( | |
| 85 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) |
|
85 | self.buffer, n=self.dataOut.nFFTPoints, axis=1) | |
| 86 | fft_volt = fft_volt.astype(numpy.dtype('complex')) |
|
86 | fft_volt = fft_volt.astype(numpy.dtype('complex')) | |
| 87 | dc = fft_volt[:, 0, :] |
|
87 | dc = fft_volt[:, 0, :] | |
| 88 |
|
88 | |||
| 89 | # calculo de self-spectra |
|
89 | # calculo de self-spectra | |
| 90 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) |
|
90 | fft_volt = numpy.fft.fftshift(fft_volt, axes=(1,)) | |
| 91 | spc = fft_volt * numpy.conjugate(fft_volt) |
|
91 | spc = fft_volt * numpy.conjugate(fft_volt) | |
| 92 | spc = spc.real |
|
92 | spc = spc.real | |
| 93 |
|
93 | |||
| 94 | blocksize = 0 |
|
94 | blocksize = 0 | |
| 95 | blocksize += dc.size |
|
95 | blocksize += dc.size | |
| 96 | blocksize += spc.size |
|
96 | blocksize += spc.size | |
| 97 |
|
97 | |||
| 98 | cspc = None |
|
98 | cspc = None | |
| 99 | pairIndex = 0 |
|
99 | pairIndex = 0 | |
| 100 | if self.dataOut.pairsList != None: |
|
100 | if self.dataOut.pairsList != None: | |
| 101 | # calculo de cross-spectra |
|
101 | # calculo de cross-spectra | |
| 102 | cspc = numpy.zeros( |
|
102 | cspc = numpy.zeros( | |
| 103 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') |
|
103 | (self.dataOut.nPairs, self.dataOut.nFFTPoints, self.dataOut.nHeights), dtype='complex') | |
| 104 | for pair in self.dataOut.pairsList: |
|
104 | for pair in self.dataOut.pairsList: | |
| 105 | if pair[0] not in self.dataOut.channelList: |
|
105 | if pair[0] not in self.dataOut.channelList: | |
| 106 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( |
|
106 | raise ValueError("Error getting CrossSpectra: pair 0 of %s is not in channelList = %s" % ( | |
| 107 | str(pair), str(self.dataOut.channelList))) |
|
107 | str(pair), str(self.dataOut.channelList))) | |
| 108 | if pair[1] not in self.dataOut.channelList: |
|
108 | if pair[1] not in self.dataOut.channelList: | |
| 109 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( |
|
109 | raise ValueError("Error getting CrossSpectra: pair 1 of %s is not in channelList = %s" % ( | |
| 110 | str(pair), str(self.dataOut.channelList))) |
|
110 | str(pair), str(self.dataOut.channelList))) | |
| 111 |
|
111 | |||
| 112 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ |
|
112 | cspc[pairIndex, :, :] = fft_volt[pair[0], :, :] * \ | |
| 113 | numpy.conjugate(fft_volt[pair[1], :, :]) |
|
113 | numpy.conjugate(fft_volt[pair[1], :, :]) | |
| 114 | pairIndex += 1 |
|
114 | pairIndex += 1 | |
| 115 | blocksize += cspc.size |
|
115 | blocksize += cspc.size | |
| 116 |
|
116 | |||
| 117 | self.dataOut.data_spc = spc |
|
117 | self.dataOut.data_spc = spc | |
| 118 | self.dataOut.data_cspc = cspc |
|
118 | self.dataOut.data_cspc = cspc | |
| 119 | self.dataOut.data_dc = dc |
|
119 | self.dataOut.data_dc = dc | |
| 120 | self.dataOut.blockSize = blocksize |
|
120 | self.dataOut.blockSize = blocksize | |
| 121 | self.dataOut.flagShiftFFT = False |
|
121 | self.dataOut.flagShiftFFT = False | |
| 122 |
|
122 | |||
| 123 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None, shift_fft=False): |
|
123 | def run(self, nProfiles=None, nFFTPoints=None, pairsList=[], ippFactor=None, shift_fft=False): | |
| 124 |
|
124 | |||
| 125 | if self.dataIn.type == "Spectra": |
|
125 | if self.dataIn.type == "Spectra": | |
| 126 | self.dataOut.copy(self.dataIn) |
|
126 | self.dataOut.copy(self.dataIn) | |
| 127 | if shift_fft: |
|
127 | if shift_fft: | |
| 128 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
128 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 129 | shift = int(self.dataOut.nFFTPoints/2) |
|
129 | shift = int(self.dataOut.nFFTPoints/2) | |
| 130 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) |
|
130 | self.dataOut.data_spc = numpy.roll(self.dataOut.data_spc, shift , axis=1) | |
| 131 |
|
131 | |||
| 132 | if self.dataOut.data_cspc is not None: |
|
132 | if self.dataOut.data_cspc is not None: | |
| 133 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
133 | #desplaza a la derecha en el eje 2 determinadas posiciones | |
| 134 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) |
|
134 | self.dataOut.data_cspc = numpy.roll(self.dataOut.data_cspc, shift, axis=1) | |
| 135 |
|
135 | |||
| 136 | return True |
|
136 | return True | |
| 137 |
|
137 | |||
| 138 | if self.dataIn.type == "Voltage": |
|
138 | if self.dataIn.type == "Voltage": | |
| 139 |
|
139 | |||
| 140 | self.dataOut.flagNoData = True |
|
140 | self.dataOut.flagNoData = True | |
| 141 |
|
141 | |||
| 142 | if nFFTPoints == None: |
|
142 | if nFFTPoints == None: | |
| 143 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") |
|
143 | raise ValueError("This SpectraProc.run() need nFFTPoints input variable") | |
| 144 |
|
144 | |||
| 145 | if nProfiles == None: |
|
145 | if nProfiles == None: | |
| 146 | nProfiles = nFFTPoints |
|
146 | nProfiles = nFFTPoints | |
| 147 |
|
147 | |||
| 148 | if ippFactor == None: |
|
148 | if ippFactor == None: | |
| 149 | ippFactor = 1 |
|
149 | ippFactor = 1 | |
| 150 |
|
150 | |||
| 151 | self.dataOut.ippFactor = ippFactor |
|
151 | self.dataOut.ippFactor = ippFactor | |
| 152 |
|
152 | |||
| 153 | self.dataOut.nFFTPoints = nFFTPoints |
|
153 | self.dataOut.nFFTPoints = nFFTPoints | |
| 154 | self.dataOut.pairsList = pairsList |
|
154 | self.dataOut.pairsList = pairsList | |
| 155 |
|
155 | |||
| 156 | if self.buffer is None: |
|
156 | if self.buffer is None: | |
| 157 | self.buffer = numpy.zeros((self.dataIn.nChannels, |
|
157 | self.buffer = numpy.zeros((self.dataIn.nChannels, | |
| 158 | nProfiles, |
|
158 | nProfiles, | |
| 159 | self.dataIn.nHeights), |
|
159 | self.dataIn.nHeights), | |
| 160 | dtype='complex') |
|
160 | dtype='complex') | |
| 161 |
|
161 | |||
| 162 | if self.dataIn.flagDataAsBlock: |
|
162 | if self.dataIn.flagDataAsBlock: | |
| 163 | nVoltProfiles = self.dataIn.data.shape[1] |
|
163 | nVoltProfiles = self.dataIn.data.shape[1] | |
| 164 |
|
164 | |||
| 165 | if nVoltProfiles == nProfiles: |
|
165 | if nVoltProfiles == nProfiles: | |
| 166 | self.buffer = self.dataIn.data.copy() |
|
166 | self.buffer = self.dataIn.data.copy() | |
| 167 | self.profIndex = nVoltProfiles |
|
167 | self.profIndex = nVoltProfiles | |
| 168 |
|
168 | |||
| 169 | elif nVoltProfiles < nProfiles: |
|
169 | elif nVoltProfiles < nProfiles: | |
| 170 |
|
170 | |||
| 171 | if self.profIndex == 0: |
|
171 | if self.profIndex == 0: | |
| 172 | self.id_min = 0 |
|
172 | self.id_min = 0 | |
| 173 | self.id_max = nVoltProfiles |
|
173 | self.id_max = nVoltProfiles | |
| 174 |
|
174 | |||
| 175 | self.buffer[:, self.id_min:self.id_max, |
|
175 | self.buffer[:, self.id_min:self.id_max, | |
| 176 | :] = self.dataIn.data |
|
176 | :] = self.dataIn.data | |
| 177 | self.profIndex += nVoltProfiles |
|
177 | self.profIndex += nVoltProfiles | |
| 178 | self.id_min += nVoltProfiles |
|
178 | self.id_min += nVoltProfiles | |
| 179 | self.id_max += nVoltProfiles |
|
179 | self.id_max += nVoltProfiles | |
| 180 | else: |
|
180 | else: | |
| 181 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( |
|
181 | raise ValueError("The type object %s has %d profiles, it should just has %d profiles" % ( | |
| 182 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) |
|
182 | self.dataIn.type, self.dataIn.data.shape[1], nProfiles)) | |
| 183 | self.dataOut.flagNoData = True |
|
183 | self.dataOut.flagNoData = True | |
| 184 | return 0 |
|
184 | return 0 | |
| 185 | else: |
|
185 | else: | |
| 186 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() |
|
186 | self.buffer[:, self.profIndex, :] = self.dataIn.data.copy() | |
| 187 | self.profIndex += 1 |
|
187 | self.profIndex += 1 | |
| 188 |
|
188 | |||
| 189 | if self.firstdatatime == None: |
|
189 | if self.firstdatatime == None: | |
| 190 | self.firstdatatime = self.dataIn.utctime |
|
190 | self.firstdatatime = self.dataIn.utctime | |
| 191 |
|
191 | |||
| 192 | if self.profIndex == nProfiles: |
|
192 | if self.profIndex == nProfiles: | |
| 193 | self.__updateSpecFromVoltage() |
|
193 | self.__updateSpecFromVoltage() | |
| 194 | self.__getFft() |
|
194 | self.__getFft() | |
| 195 |
|
195 | |||
| 196 | self.dataOut.flagNoData = False |
|
196 | self.dataOut.flagNoData = False | |
| 197 | self.firstdatatime = None |
|
197 | self.firstdatatime = None | |
| 198 | self.profIndex = 0 |
|
198 | self.profIndex = 0 | |
| 199 |
|
199 | |||
| 200 | return True |
|
200 | return True | |
| 201 |
|
201 | |||
| 202 | raise ValueError("The type of input object '%s' is not valid" % ( |
|
202 | raise ValueError("The type of input object '%s' is not valid" % ( | |
| 203 | self.dataIn.type)) |
|
203 | self.dataIn.type)) | |
| 204 |
|
204 | |||
| 205 | def __selectPairs(self, pairsList): |
|
205 | def __selectPairs(self, pairsList): | |
| 206 |
|
206 | |||
| 207 | if not pairsList: |
|
207 | if not pairsList: | |
| 208 | return |
|
208 | return | |
| 209 |
|
209 | |||
| 210 | pairs = [] |
|
210 | pairs = [] | |
| 211 | pairsIndex = [] |
|
211 | pairsIndex = [] | |
| 212 |
|
212 | |||
| 213 | for pair in pairsList: |
|
213 | for pair in pairsList: | |
| 214 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: |
|
214 | if pair[0] not in self.dataOut.channelList or pair[1] not in self.dataOut.channelList: | |
| 215 | continue |
|
215 | continue | |
| 216 | pairs.append(pair) |
|
216 | pairs.append(pair) | |
| 217 | pairsIndex.append(pairs.index(pair)) |
|
217 | pairsIndex.append(pairs.index(pair)) | |
| 218 |
|
218 | |||
| 219 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] |
|
219 | self.dataOut.data_cspc = self.dataOut.data_cspc[pairsIndex] | |
| 220 | self.dataOut.pairsList = pairs |
|
220 | self.dataOut.pairsList = pairs | |
| 221 |
|
221 | |||
| 222 | return |
|
222 | return | |
| 223 |
|
223 | |||
| 224 | def selectFFTs(self, minFFT, maxFFT ): |
|
224 | def selectFFTs(self, minFFT, maxFFT ): | |
| 225 | """ |
|
225 | """ | |
| 226 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango |
|
226 | Selecciona un bloque de datos en base a un grupo de valores de puntos FFTs segun el rango | |
| 227 | minFFT<= FFT <= maxFFT |
|
227 | minFFT<= FFT <= maxFFT | |
| 228 | """ |
|
228 | """ | |
| 229 |
|
229 | |||
| 230 | if (minFFT > maxFFT): |
|
230 | if (minFFT > maxFFT): | |
| 231 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) |
|
231 | raise ValueError("Error selecting heights: Height range (%d,%d) is not valid" % (minFFT, maxFFT)) | |
| 232 |
|
232 | |||
| 233 | if (minFFT < self.dataOut.getFreqRange()[0]): |
|
233 | if (minFFT < self.dataOut.getFreqRange()[0]): | |
| 234 | minFFT = self.dataOut.getFreqRange()[0] |
|
234 | minFFT = self.dataOut.getFreqRange()[0] | |
| 235 |
|
235 | |||
| 236 | if (maxFFT > self.dataOut.getFreqRange()[-1]): |
|
236 | if (maxFFT > self.dataOut.getFreqRange()[-1]): | |
| 237 | maxFFT = self.dataOut.getFreqRange()[-1] |
|
237 | maxFFT = self.dataOut.getFreqRange()[-1] | |
| 238 |
|
238 | |||
| 239 | minIndex = 0 |
|
239 | minIndex = 0 | |
| 240 | maxIndex = 0 |
|
240 | maxIndex = 0 | |
| 241 | FFTs = self.dataOut.getFreqRange() |
|
241 | FFTs = self.dataOut.getFreqRange() | |
| 242 |
|
242 | |||
| 243 | inda = numpy.where(FFTs >= minFFT) |
|
243 | inda = numpy.where(FFTs >= minFFT) | |
| 244 | indb = numpy.where(FFTs <= maxFFT) |
|
244 | indb = numpy.where(FFTs <= maxFFT) | |
| 245 |
|
245 | |||
| 246 | try: |
|
246 | try: | |
| 247 | minIndex = inda[0][0] |
|
247 | minIndex = inda[0][0] | |
| 248 | except: |
|
248 | except: | |
| 249 | minIndex = 0 |
|
249 | minIndex = 0 | |
| 250 |
|
250 | |||
| 251 | try: |
|
251 | try: | |
| 252 | maxIndex = indb[0][-1] |
|
252 | maxIndex = indb[0][-1] | |
| 253 | except: |
|
253 | except: | |
| 254 | maxIndex = len(FFTs) |
|
254 | maxIndex = len(FFTs) | |
| 255 |
|
255 | |||
| 256 | self.selectFFTsByIndex(minIndex, maxIndex) |
|
256 | self.selectFFTsByIndex(minIndex, maxIndex) | |
| 257 |
|
257 | |||
| 258 | return 1 |
|
258 | return 1 | |
| 259 |
|
259 | |||
| 260 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): |
|
260 | def getBeaconSignal(self, tauindex=0, channelindex=0, hei_ref=None): | |
| 261 | newheis = numpy.where( |
|
261 | newheis = numpy.where( | |
| 262 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
262 | self.dataOut.heightList > self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 263 |
|
263 | |||
| 264 | if hei_ref != None: |
|
264 | if hei_ref != None: | |
| 265 | newheis = numpy.where(self.dataOut.heightList > hei_ref) |
|
265 | newheis = numpy.where(self.dataOut.heightList > hei_ref) | |
| 266 |
|
266 | |||
| 267 | minIndex = min(newheis[0]) |
|
267 | minIndex = min(newheis[0]) | |
| 268 | maxIndex = max(newheis[0]) |
|
268 | maxIndex = max(newheis[0]) | |
| 269 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] |
|
269 | data_spc = self.dataOut.data_spc[:, :, minIndex:maxIndex + 1] | |
| 270 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] |
|
270 | heightList = self.dataOut.heightList[minIndex:maxIndex + 1] | |
| 271 |
|
271 | |||
| 272 | # determina indices |
|
272 | # determina indices | |
| 273 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / |
|
273 | nheis = int(self.dataOut.radarControllerHeaderObj.txB / | |
| 274 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) |
|
274 | (self.dataOut.heightList[1] - self.dataOut.heightList[0])) | |
| 275 | avg_dB = 10 * \ |
|
275 | avg_dB = 10 * \ | |
| 276 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) |
|
276 | numpy.log10(numpy.sum(data_spc[channelindex, :, :], axis=0)) | |
| 277 | beacon_dB = numpy.sort(avg_dB)[-nheis:] |
|
277 | beacon_dB = numpy.sort(avg_dB)[-nheis:] | |
| 278 | beacon_heiIndexList = [] |
|
278 | beacon_heiIndexList = [] | |
| 279 | for val in avg_dB.tolist(): |
|
279 | for val in avg_dB.tolist(): | |
| 280 | if val >= beacon_dB[0]: |
|
280 | if val >= beacon_dB[0]: | |
| 281 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) |
|
281 | beacon_heiIndexList.append(avg_dB.tolist().index(val)) | |
| 282 |
|
282 | |||
| 283 | #data_spc = data_spc[:,:,beacon_heiIndexList] |
|
283 | #data_spc = data_spc[:,:,beacon_heiIndexList] | |
| 284 | data_cspc = None |
|
284 | data_cspc = None | |
| 285 | if self.dataOut.data_cspc is not None: |
|
285 | if self.dataOut.data_cspc is not None: | |
| 286 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] |
|
286 | data_cspc = self.dataOut.data_cspc[:, :, minIndex:maxIndex + 1] | |
| 287 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] |
|
287 | #data_cspc = data_cspc[:,:,beacon_heiIndexList] | |
| 288 |
|
288 | |||
| 289 | data_dc = None |
|
289 | data_dc = None | |
| 290 | if self.dataOut.data_dc is not None: |
|
290 | if self.dataOut.data_dc is not None: | |
| 291 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] |
|
291 | data_dc = self.dataOut.data_dc[:, minIndex:maxIndex + 1] | |
| 292 | #data_dc = data_dc[:,beacon_heiIndexList] |
|
292 | #data_dc = data_dc[:,beacon_heiIndexList] | |
| 293 |
|
293 | |||
| 294 | self.dataOut.data_spc = data_spc |
|
294 | self.dataOut.data_spc = data_spc | |
| 295 | self.dataOut.data_cspc = data_cspc |
|
295 | self.dataOut.data_cspc = data_cspc | |
| 296 | self.dataOut.data_dc = data_dc |
|
296 | self.dataOut.data_dc = data_dc | |
| 297 | self.dataOut.heightList = heightList |
|
297 | self.dataOut.heightList = heightList | |
| 298 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList |
|
298 | self.dataOut.beacon_heiIndexList = beacon_heiIndexList | |
| 299 |
|
299 | |||
| 300 | return 1 |
|
300 | return 1 | |
| 301 |
|
301 | |||
| 302 | def selectFFTsByIndex(self, minIndex, maxIndex): |
|
302 | def selectFFTsByIndex(self, minIndex, maxIndex): | |
| 303 | """ |
|
303 | """ | |
| 304 |
|
304 | |||
| 305 | """ |
|
305 | """ | |
| 306 |
|
306 | |||
| 307 | if (minIndex < 0) or (minIndex > maxIndex): |
|
307 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 308 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) |
|
308 | raise ValueError("Error selecting heights: Index range (%d,%d) is not valid" % (minIndex, maxIndex)) | |
| 309 |
|
309 | |||
| 310 | if (maxIndex >= self.dataOut.nProfiles): |
|
310 | if (maxIndex >= self.dataOut.nProfiles): | |
| 311 | maxIndex = self.dataOut.nProfiles-1 |
|
311 | maxIndex = self.dataOut.nProfiles-1 | |
| 312 |
|
312 | |||
| 313 | #Spectra |
|
313 | #Spectra | |
| 314 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] |
|
314 | data_spc = self.dataOut.data_spc[:,minIndex:maxIndex+1,:] | |
| 315 |
|
315 | |||
| 316 | data_cspc = None |
|
316 | data_cspc = None | |
| 317 | if self.dataOut.data_cspc is not None: |
|
317 | if self.dataOut.data_cspc is not None: | |
| 318 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] |
|
318 | data_cspc = self.dataOut.data_cspc[:,minIndex:maxIndex+1,:] | |
| 319 |
|
319 | |||
| 320 | data_dc = None |
|
320 | data_dc = None | |
| 321 | if self.dataOut.data_dc is not None: |
|
321 | if self.dataOut.data_dc is not None: | |
| 322 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] |
|
322 | data_dc = self.dataOut.data_dc[minIndex:maxIndex+1,:] | |
| 323 |
|
323 | |||
| 324 | self.dataOut.data_spc = data_spc |
|
324 | self.dataOut.data_spc = data_spc | |
| 325 | self.dataOut.data_cspc = data_cspc |
|
325 | self.dataOut.data_cspc = data_cspc | |
| 326 | self.dataOut.data_dc = data_dc |
|
326 | self.dataOut.data_dc = data_dc | |
| 327 |
|
327 | |||
| 328 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) |
|
328 | self.dataOut.ippSeconds = self.dataOut.ippSeconds*(self.dataOut.nFFTPoints / numpy.shape(data_cspc)[1]) | |
| 329 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] |
|
329 | self.dataOut.nFFTPoints = numpy.shape(data_cspc)[1] | |
| 330 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] |
|
330 | self.dataOut.profilesPerBlock = numpy.shape(data_cspc)[1] | |
| 331 |
|
331 | |||
| 332 | return 1 |
|
332 | return 1 | |
| 333 |
|
333 | |||
| 334 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): |
|
334 | def getNoise(self, minHei=None, maxHei=None, minVel=None, maxVel=None): | |
| 335 | # validacion de rango |
|
335 | # validacion de rango | |
| 336 | if minHei == None: |
|
336 | if minHei == None: | |
| 337 | minHei = self.dataOut.heightList[0] |
|
337 | minHei = self.dataOut.heightList[0] | |
| 338 |
|
338 | |||
| 339 | if maxHei == None: |
|
339 | if maxHei == None: | |
| 340 | maxHei = self.dataOut.heightList[-1] |
|
340 | maxHei = self.dataOut.heightList[-1] | |
| 341 |
|
341 | |||
| 342 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): |
|
342 | if (minHei < self.dataOut.heightList[0]) or (minHei > maxHei): | |
| 343 | print('minHei: %.2f is out of the heights range' % (minHei)) |
|
343 | print('minHei: %.2f is out of the heights range' % (minHei)) | |
| 344 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) |
|
344 | print('minHei is setting to %.2f' % (self.dataOut.heightList[0])) | |
| 345 | minHei = self.dataOut.heightList[0] |
|
345 | minHei = self.dataOut.heightList[0] | |
| 346 |
|
346 | |||
| 347 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): |
|
347 | if (maxHei > self.dataOut.heightList[-1]) or (maxHei < minHei): | |
| 348 | print('maxHei: %.2f is out of the heights range' % (maxHei)) |
|
348 | print('maxHei: %.2f is out of the heights range' % (maxHei)) | |
| 349 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) |
|
349 | print('maxHei is setting to %.2f' % (self.dataOut.heightList[-1])) | |
| 350 | maxHei = self.dataOut.heightList[-1] |
|
350 | maxHei = self.dataOut.heightList[-1] | |
| 351 |
|
351 | |||
| 352 | # validacion de velocidades |
|
352 | # validacion de velocidades | |
| 353 | velrange = self.dataOut.getVelRange(1) |
|
353 | velrange = self.dataOut.getVelRange(1) | |
| 354 |
|
354 | |||
| 355 | if minVel == None: |
|
355 | if minVel == None: | |
| 356 | minVel = velrange[0] |
|
356 | minVel = velrange[0] | |
| 357 |
|
357 | |||
| 358 | if maxVel == None: |
|
358 | if maxVel == None: | |
| 359 | maxVel = velrange[-1] |
|
359 | maxVel = velrange[-1] | |
| 360 |
|
360 | |||
| 361 | if (minVel < velrange[0]) or (minVel > maxVel): |
|
361 | if (minVel < velrange[0]) or (minVel > maxVel): | |
| 362 | print('minVel: %.2f is out of the velocity range' % (minVel)) |
|
362 | print('minVel: %.2f is out of the velocity range' % (minVel)) | |
| 363 | print('minVel is setting to %.2f' % (velrange[0])) |
|
363 | print('minVel is setting to %.2f' % (velrange[0])) | |
| 364 | minVel = velrange[0] |
|
364 | minVel = velrange[0] | |
| 365 |
|
365 | |||
| 366 | if (maxVel > velrange[-1]) or (maxVel < minVel): |
|
366 | if (maxVel > velrange[-1]) or (maxVel < minVel): | |
| 367 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) |
|
367 | print('maxVel: %.2f is out of the velocity range' % (maxVel)) | |
| 368 | print('maxVel is setting to %.2f' % (velrange[-1])) |
|
368 | print('maxVel is setting to %.2f' % (velrange[-1])) | |
| 369 | maxVel = velrange[-1] |
|
369 | maxVel = velrange[-1] | |
| 370 |
|
370 | |||
| 371 | # seleccion de indices para rango |
|
371 | # seleccion de indices para rango | |
| 372 | minIndex = 0 |
|
372 | minIndex = 0 | |
| 373 | maxIndex = 0 |
|
373 | maxIndex = 0 | |
| 374 | heights = self.dataOut.heightList |
|
374 | heights = self.dataOut.heightList | |
| 375 |
|
375 | |||
| 376 | inda = numpy.where(heights >= minHei) |
|
376 | inda = numpy.where(heights >= minHei) | |
| 377 | indb = numpy.where(heights <= maxHei) |
|
377 | indb = numpy.where(heights <= maxHei) | |
| 378 |
|
378 | |||
| 379 | try: |
|
379 | try: | |
| 380 | minIndex = inda[0][0] |
|
380 | minIndex = inda[0][0] | |
| 381 | except: |
|
381 | except: | |
| 382 | minIndex = 0 |
|
382 | minIndex = 0 | |
| 383 |
|
383 | |||
| 384 | try: |
|
384 | try: | |
| 385 | maxIndex = indb[0][-1] |
|
385 | maxIndex = indb[0][-1] | |
| 386 | except: |
|
386 | except: | |
| 387 | maxIndex = len(heights) |
|
387 | maxIndex = len(heights) | |
| 388 |
|
388 | |||
| 389 | if (minIndex < 0) or (minIndex > maxIndex): |
|
389 | if (minIndex < 0) or (minIndex > maxIndex): | |
| 390 | raise ValueError("some value in (%d,%d) is not valid" % ( |
|
390 | raise ValueError("some value in (%d,%d) is not valid" % ( | |
| 391 | minIndex, maxIndex)) |
|
391 | minIndex, maxIndex)) | |
| 392 |
|
392 | |||
| 393 | if (maxIndex >= self.dataOut.nHeights): |
|
393 | if (maxIndex >= self.dataOut.nHeights): | |
| 394 | maxIndex = self.dataOut.nHeights - 1 |
|
394 | maxIndex = self.dataOut.nHeights - 1 | |
| 395 |
|
395 | |||
| 396 | # seleccion de indices para velocidades |
|
396 | # seleccion de indices para velocidades | |
| 397 | indminvel = numpy.where(velrange >= minVel) |
|
397 | indminvel = numpy.where(velrange >= minVel) | |
| 398 | indmaxvel = numpy.where(velrange <= maxVel) |
|
398 | indmaxvel = numpy.where(velrange <= maxVel) | |
| 399 | try: |
|
399 | try: | |
| 400 | minIndexVel = indminvel[0][0] |
|
400 | minIndexVel = indminvel[0][0] | |
| 401 | except: |
|
401 | except: | |
| 402 | minIndexVel = 0 |
|
402 | minIndexVel = 0 | |
| 403 |
|
403 | |||
| 404 | try: |
|
404 | try: | |
| 405 | maxIndexVel = indmaxvel[0][-1] |
|
405 | maxIndexVel = indmaxvel[0][-1] | |
| 406 | except: |
|
406 | except: | |
| 407 | maxIndexVel = len(velrange) |
|
407 | maxIndexVel = len(velrange) | |
| 408 |
|
408 | |||
| 409 | # seleccion del espectro |
|
409 | # seleccion del espectro | |
| 410 | data_spc = self.dataOut.data_spc[:, |
|
410 | data_spc = self.dataOut.data_spc[:, | |
| 411 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] |
|
411 | minIndexVel:maxIndexVel + 1, minIndex:maxIndex + 1] | |
| 412 | # estimacion de ruido |
|
412 | # estimacion de ruido | |
| 413 | noise = numpy.zeros(self.dataOut.nChannels) |
|
413 | noise = numpy.zeros(self.dataOut.nChannels) | |
| 414 |
|
414 | |||
| 415 | for channel in range(self.dataOut.nChannels): |
|
415 | for channel in range(self.dataOut.nChannels): | |
| 416 | daux = data_spc[channel, :, :] |
|
416 | daux = data_spc[channel, :, :] | |
| 417 | sortdata = numpy.sort(daux, axis=None) |
|
417 | sortdata = numpy.sort(daux, axis=None) | |
| 418 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) |
|
418 | noise[channel] = hildebrand_sekhon(sortdata, self.dataOut.nIncohInt) | |
| 419 |
|
419 | |||
| 420 | self.dataOut.noise_estimation = noise.copy() |
|
420 | self.dataOut.noise_estimation = noise.copy() | |
| 421 |
|
421 | |||
| 422 | return 1 |
|
422 | return 1 | |
| 423 |
|
423 | |||
| 424 | class removeDC(Operation): |
|
424 | class removeDC(Operation): | |
| 425 |
|
425 | |||
| 426 | def run(self, dataOut, mode=2): |
|
426 | def run(self, dataOut, mode=2): | |
| 427 | self.dataOut = dataOut |
|
427 | self.dataOut = dataOut | |
| 428 | jspectra = self.dataOut.data_spc |
|
428 | jspectra = self.dataOut.data_spc | |
| 429 | jcspectra = self.dataOut.data_cspc |
|
429 | jcspectra = self.dataOut.data_cspc | |
| 430 |
|
430 | |||
| 431 | num_chan = jspectra.shape[0] |
|
431 | num_chan = jspectra.shape[0] | |
| 432 | num_hei = jspectra.shape[2] |
|
432 | num_hei = jspectra.shape[2] | |
| 433 |
|
433 | |||
| 434 | if jcspectra is not None: |
|
434 | if jcspectra is not None: | |
| 435 | jcspectraExist = True |
|
435 | jcspectraExist = True | |
| 436 | num_pairs = jcspectra.shape[0] |
|
436 | num_pairs = jcspectra.shape[0] | |
| 437 | else: |
|
437 | else: | |
| 438 | jcspectraExist = False |
|
438 | jcspectraExist = False | |
| 439 |
|
439 | |||
| 440 | freq_dc = int(jspectra.shape[1] / 2) |
|
440 | freq_dc = int(jspectra.shape[1] / 2) | |
| 441 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc |
|
441 | ind_vel = numpy.array([-2, -1, 1, 2]) + freq_dc | |
| 442 | ind_vel = ind_vel.astype(int) |
|
442 | ind_vel = ind_vel.astype(int) | |
| 443 |
|
443 | |||
| 444 | if ind_vel[0] < 0: |
|
444 | if ind_vel[0] < 0: | |
| 445 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof |
|
445 | ind_vel[list(range(0, 1))] = ind_vel[list(range(0, 1))] + self.num_prof | |
| 446 |
|
446 | |||
| 447 | if mode == 1: |
|
447 | if mode == 1: | |
| 448 | jspectra[:, freq_dc, :] = ( |
|
448 | jspectra[:, freq_dc, :] = ( | |
| 449 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION |
|
449 | jspectra[:, ind_vel[1], :] + jspectra[:, ind_vel[2], :]) / 2 # CORRECCION | |
| 450 |
|
450 | |||
| 451 | if jcspectraExist: |
|
451 | if jcspectraExist: | |
| 452 | jcspectra[:, freq_dc, :] = ( |
|
452 | jcspectra[:, freq_dc, :] = ( | |
| 453 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 |
|
453 | jcspectra[:, ind_vel[1], :] + jcspectra[:, ind_vel[2], :]) / 2 | |
| 454 |
|
454 | |||
| 455 | if mode == 2: |
|
455 | if mode == 2: | |
| 456 |
|
456 | |||
| 457 | vel = numpy.array([-2, -1, 1, 2]) |
|
457 | vel = numpy.array([-2, -1, 1, 2]) | |
| 458 | xx = numpy.zeros([4, 4]) |
|
458 | xx = numpy.zeros([4, 4]) | |
| 459 |
|
459 | |||
| 460 | for fil in range(4): |
|
460 | for fil in range(4): | |
| 461 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) |
|
461 | xx[fil, :] = vel[fil]**numpy.asarray(list(range(4))) | |
| 462 |
|
462 | |||
| 463 | xx_inv = numpy.linalg.inv(xx) |
|
463 | xx_inv = numpy.linalg.inv(xx) | |
| 464 | xx_aux = xx_inv[0, :] |
|
464 | xx_aux = xx_inv[0, :] | |
| 465 |
|
465 | |||
| 466 | for ich in range(num_chan): |
|
466 | for ich in range(num_chan): | |
| 467 | yy = jspectra[ich, ind_vel, :] |
|
467 | yy = jspectra[ich, ind_vel, :] | |
| 468 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
468 | jspectra[ich, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 469 |
|
469 | |||
| 470 | junkid = jspectra[ich, freq_dc, :] <= 0 |
|
470 | junkid = jspectra[ich, freq_dc, :] <= 0 | |
| 471 | cjunkid = sum(junkid) |
|
471 | cjunkid = sum(junkid) | |
| 472 |
|
472 | |||
| 473 | if cjunkid.any(): |
|
473 | if cjunkid.any(): | |
| 474 | jspectra[ich, freq_dc, junkid.nonzero()] = ( |
|
474 | jspectra[ich, freq_dc, junkid.nonzero()] = ( | |
| 475 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 |
|
475 | jspectra[ich, ind_vel[1], junkid] + jspectra[ich, ind_vel[2], junkid]) / 2 | |
| 476 |
|
476 | |||
| 477 | if jcspectraExist: |
|
477 | if jcspectraExist: | |
| 478 | for ip in range(num_pairs): |
|
478 | for ip in range(num_pairs): | |
| 479 | yy = jcspectra[ip, ind_vel, :] |
|
479 | yy = jcspectra[ip, ind_vel, :] | |
| 480 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) |
|
480 | jcspectra[ip, freq_dc, :] = numpy.dot(xx_aux, yy) | |
| 481 |
|
481 | |||
| 482 | self.dataOut.data_spc = jspectra |
|
482 | self.dataOut.data_spc = jspectra | |
| 483 | self.dataOut.data_cspc = jcspectra |
|
483 | self.dataOut.data_cspc = jcspectra | |
| 484 |
|
484 | |||
| 485 | return self.dataOut |
|
485 | return self.dataOut | |
| 486 |
|
486 | |||
| 487 | class removeInterference(Operation): |
|
487 | class removeInterference(Operation): | |
| 488 |
|
488 | |||
| 489 | def removeInterference2(self): |
|
489 | def removeInterference2(self): | |
| 490 |
|
490 | |||
| 491 | cspc = self.dataOut.data_cspc |
|
491 | cspc = self.dataOut.data_cspc | |
| 492 | spc = self.dataOut.data_spc |
|
492 | spc = self.dataOut.data_spc | |
| 493 | Heights = numpy.arange(cspc.shape[2]) |
|
493 | Heights = numpy.arange(cspc.shape[2]) | |
| 494 | realCspc = numpy.abs(cspc) |
|
494 | realCspc = numpy.abs(cspc) | |
| 495 |
|
495 | |||
| 496 | for i in range(cspc.shape[0]): |
|
496 | for i in range(cspc.shape[0]): | |
| 497 | LinePower= numpy.sum(realCspc[i], axis=0) |
|
497 | LinePower= numpy.sum(realCspc[i], axis=0) | |
| 498 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] |
|
498 | Threshold = numpy.amax(LinePower)-numpy.sort(LinePower)[len(Heights)-int(len(Heights)*0.1)] | |
| 499 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] |
|
499 | SelectedHeights = Heights[ numpy.where( LinePower < Threshold ) ] | |
| 500 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) |
|
500 | InterferenceSum = numpy.sum( realCspc[i,:,SelectedHeights], axis=0 ) | |
| 501 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] |
|
501 | InterferenceThresholdMin = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.98)] | |
| 502 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] |
|
502 | InterferenceThresholdMax = numpy.sort(InterferenceSum)[int(len(InterferenceSum)*0.99)] | |
| 503 |
|
503 | |||
| 504 |
|
504 | |||
| 505 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) |
|
505 | InterferenceRange = numpy.where( ([InterferenceSum > InterferenceThresholdMin]))# , InterferenceSum < InterferenceThresholdMax]) ) | |
| 506 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) |
|
506 | #InterferenceRange = numpy.where( ([InterferenceRange < InterferenceThresholdMax])) | |
| 507 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): |
|
507 | if len(InterferenceRange)<int(cspc.shape[1]*0.3): | |
| 508 | cspc[i,InterferenceRange,:] = numpy.NaN |
|
508 | cspc[i,InterferenceRange,:] = numpy.NaN | |
| 509 |
|
509 | |||
| 510 | self.dataOut.data_cspc = cspc |
|
510 | self.dataOut.data_cspc = cspc | |
| 511 |
|
511 | |||
| 512 | def removeInterference(self): |
|
512 | def removeInterference(self, interf = 2, hei_interf = None, nhei_interf = None, offhei_interf = None): | |
| 513 |
|
513 | |||
| 514 | jspectra = self.dataOut.data_spc |
|
514 | jspectra = self.dataOut.data_spc | |
| 515 | jcspectra = self.dataOut.data_cspc |
|
515 | jcspectra = self.dataOut.data_cspc | |
| 516 | jnoise = self.dataOut.getNoise() |
|
516 | jnoise = self.dataOut.getNoise() | |
| 517 | num_incoh = self.dataOut.nIncohInt |
|
517 | num_incoh = self.dataOut.nIncohInt | |
| 518 |
|
518 | |||
| 519 | num_channel = jspectra.shape[0] |
|
519 | num_channel = jspectra.shape[0] | |
| 520 | num_prof = jspectra.shape[1] |
|
520 | num_prof = jspectra.shape[1] | |
| 521 | num_hei = jspectra.shape[2] |
|
521 | num_hei = jspectra.shape[2] | |
| 522 |
|
522 | |||
| 523 | # hei_interf |
|
523 | # hei_interf | |
| 524 | if hei_interf is None: |
|
524 | if hei_interf is None: | |
| 525 | count_hei = int(num_hei / 2) |
|
525 | count_hei = int(num_hei / 2) | |
| 526 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei |
|
526 | hei_interf = numpy.asmatrix(list(range(count_hei))) + num_hei - count_hei | |
| 527 | hei_interf = numpy.asarray(hei_interf)[0] |
|
527 | hei_interf = numpy.asarray(hei_interf)[0] | |
| 528 | # nhei_interf |
|
528 | # nhei_interf | |
| 529 | if (nhei_interf == None): |
|
529 | if (nhei_interf == None): | |
| 530 | nhei_interf = 5 |
|
530 | nhei_interf = 5 | |
| 531 | if (nhei_interf < 1): |
|
531 | if (nhei_interf < 1): | |
| 532 | nhei_interf = 1 |
|
532 | nhei_interf = 1 | |
| 533 | if (nhei_interf > count_hei): |
|
533 | if (nhei_interf > count_hei): | |
| 534 | nhei_interf = count_hei |
|
534 | nhei_interf = count_hei | |
| 535 | if (offhei_interf == None): |
|
535 | if (offhei_interf == None): | |
| 536 | offhei_interf = 0 |
|
536 | offhei_interf = 0 | |
| 537 |
|
537 | |||
| 538 | ind_hei = list(range(num_hei)) |
|
538 | ind_hei = list(range(num_hei)) | |
| 539 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 |
|
539 | # mask_prof = numpy.asarray(range(num_prof - 2)) + 1 | |
| 540 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 |
|
540 | # mask_prof[range(num_prof/2 - 1,len(mask_prof))] += 1 | |
| 541 | mask_prof = numpy.asarray(list(range(num_prof))) |
|
541 | mask_prof = numpy.asarray(list(range(num_prof))) | |
| 542 | num_mask_prof = mask_prof.size |
|
542 | num_mask_prof = mask_prof.size | |
| 543 | comp_mask_prof = [0, num_prof / 2] |
|
543 | comp_mask_prof = [0, num_prof / 2] | |
| 544 |
|
544 | |||
| 545 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal |
|
545 | # noise_exist: Determina si la variable jnoise ha sido definida y contiene la informacion del ruido de cada canal | |
| 546 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): |
|
546 | if (jnoise.size < num_channel or numpy.isnan(jnoise).any()): | |
| 547 | jnoise = numpy.nan |
|
547 | jnoise = numpy.nan | |
| 548 | noise_exist = jnoise[0] < numpy.Inf |
|
548 | noise_exist = jnoise[0] < numpy.Inf | |
| 549 |
|
549 | |||
| 550 | # Subrutina de Remocion de la Interferencia |
|
550 | # Subrutina de Remocion de la Interferencia | |
| 551 | for ich in range(num_channel): |
|
551 | for ich in range(num_channel): | |
| 552 | # Se ordena los espectros segun su potencia (menor a mayor) |
|
552 | # Se ordena los espectros segun su potencia (menor a mayor) | |
| 553 | power = jspectra[ich, mask_prof, :] |
|
553 | power = jspectra[ich, mask_prof, :] | |
| 554 | power = power[:, hei_interf] |
|
554 | power = power[:, hei_interf] | |
| 555 | power = power.sum(axis=0) |
|
555 | power = power.sum(axis=0) | |
| 556 | psort = power.ravel().argsort() |
|
556 | psort = power.ravel().argsort() | |
| 557 |
|
557 | |||
| 558 | # Se estima la interferencia promedio en los Espectros de Potencia empleando |
|
558 | # Se estima la interferencia promedio en los Espectros de Potencia empleando | |
| 559 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( |
|
559 | junkspc_interf = jspectra[ich, :, hei_interf[psort[list(range( | |
| 560 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
560 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 561 |
|
561 | |||
| 562 | if noise_exist: |
|
562 | if noise_exist: | |
| 563 | # tmp_noise = jnoise[ich] / num_prof |
|
563 | # tmp_noise = jnoise[ich] / num_prof | |
| 564 | tmp_noise = jnoise[ich] |
|
564 | tmp_noise = jnoise[ich] | |
| 565 | junkspc_interf = junkspc_interf - tmp_noise |
|
565 | junkspc_interf = junkspc_interf - tmp_noise | |
| 566 | #junkspc_interf[:,comp_mask_prof] = 0 |
|
566 | #junkspc_interf[:,comp_mask_prof] = 0 | |
| 567 |
|
567 | |||
| 568 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf |
|
568 | jspc_interf = junkspc_interf.sum(axis=0) / nhei_interf | |
| 569 | jspc_interf = jspc_interf.transpose() |
|
569 | jspc_interf = jspc_interf.transpose() | |
| 570 | # Calculando el espectro de interferencia promedio |
|
570 | # Calculando el espectro de interferencia promedio | |
| 571 | noiseid = numpy.where( |
|
571 | noiseid = numpy.where( | |
| 572 | jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) |
|
572 | jspc_interf <= tmp_noise / numpy.sqrt(num_incoh)) | |
| 573 | noiseid = noiseid[0] |
|
573 | noiseid = noiseid[0] | |
| 574 | cnoiseid = noiseid.size |
|
574 | cnoiseid = noiseid.size | |
| 575 | interfid = numpy.where( |
|
575 | interfid = numpy.where( | |
| 576 | jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) |
|
576 | jspc_interf > tmp_noise / numpy.sqrt(num_incoh)) | |
| 577 | interfid = interfid[0] |
|
577 | interfid = interfid[0] | |
| 578 | cinterfid = interfid.size |
|
578 | cinterfid = interfid.size | |
| 579 |
|
579 | |||
| 580 | if (cnoiseid > 0): |
|
580 | if (cnoiseid > 0): | |
| 581 | jspc_interf[noiseid] = 0 |
|
581 | jspc_interf[noiseid] = 0 | |
| 582 |
|
582 | |||
| 583 | # Expandiendo los perfiles a limpiar |
|
583 | # Expandiendo los perfiles a limpiar | |
| 584 | if (cinterfid > 0): |
|
584 | if (cinterfid > 0): | |
| 585 | new_interfid = ( |
|
585 | new_interfid = ( | |
| 586 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof |
|
586 | numpy.r_[interfid - 1, interfid, interfid + 1] + num_prof) % num_prof | |
| 587 | new_interfid = numpy.asarray(new_interfid) |
|
587 | new_interfid = numpy.asarray(new_interfid) | |
| 588 | new_interfid = {x for x in new_interfid} |
|
588 | new_interfid = {x for x in new_interfid} | |
| 589 | new_interfid = numpy.array(list(new_interfid)) |
|
589 | new_interfid = numpy.array(list(new_interfid)) | |
| 590 | new_cinterfid = new_interfid.size |
|
590 | new_cinterfid = new_interfid.size | |
| 591 | else: |
|
591 | else: | |
| 592 | new_cinterfid = 0 |
|
592 | new_cinterfid = 0 | |
| 593 |
|
593 | |||
| 594 | for ip in range(new_cinterfid): |
|
594 | for ip in range(new_cinterfid): | |
| 595 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() |
|
595 | ind = junkspc_interf[:, new_interfid[ip]].ravel().argsort() | |
| 596 | jspc_interf[new_interfid[ip] |
|
596 | jspc_interf[new_interfid[ip] | |
| 597 | ] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] |
|
597 | ] = junkspc_interf[ind[nhei_interf // 2], new_interfid[ip]] | |
| 598 |
|
598 | |||
| 599 | jspectra[ich, :, ind_hei] = jspectra[ich, :, |
|
599 | jspectra[ich, :, ind_hei] = jspectra[ich, :, | |
| 600 | ind_hei] - jspc_interf # Corregir indices |
|
600 | ind_hei] - jspc_interf # Corregir indices | |
| 601 |
|
601 | |||
| 602 | # Removiendo la interferencia del punto de mayor interferencia |
|
602 | # Removiendo la interferencia del punto de mayor interferencia | |
| 603 | ListAux = jspc_interf[mask_prof].tolist() |
|
603 | ListAux = jspc_interf[mask_prof].tolist() | |
| 604 | maxid = ListAux.index(max(ListAux)) |
|
604 | maxid = ListAux.index(max(ListAux)) | |
| 605 |
|
605 | |||
| 606 | if cinterfid > 0: |
|
606 | if cinterfid > 0: | |
| 607 | for ip in range(cinterfid * (interf == 2) - 1): |
|
607 | for ip in range(cinterfid * (interf == 2) - 1): | |
| 608 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * |
|
608 | ind = (jspectra[ich, interfid[ip], :] < tmp_noise * | |
| 609 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() |
|
609 | (1 + 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 610 | cind = len(ind) |
|
610 | cind = len(ind) | |
| 611 |
|
611 | |||
| 612 | if (cind > 0): |
|
612 | if (cind > 0): | |
| 613 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ |
|
613 | jspectra[ich, interfid[ip], ind] = tmp_noise * \ | |
| 614 | (1 + (numpy.random.uniform(cind) - 0.5) / |
|
614 | (1 + (numpy.random.uniform(cind) - 0.5) / | |
| 615 | numpy.sqrt(num_incoh)) |
|
615 | numpy.sqrt(num_incoh)) | |
| 616 |
|
616 | |||
| 617 | ind = numpy.array([-2, -1, 1, 2]) |
|
617 | ind = numpy.array([-2, -1, 1, 2]) | |
| 618 | xx = numpy.zeros([4, 4]) |
|
618 | xx = numpy.zeros([4, 4]) | |
| 619 |
|
619 | |||
| 620 | for id1 in range(4): |
|
620 | for id1 in range(4): | |
| 621 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
621 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 622 |
|
622 | |||
| 623 | xx_inv = numpy.linalg.inv(xx) |
|
623 | xx_inv = numpy.linalg.inv(xx) | |
| 624 | xx = xx_inv[:, 0] |
|
624 | xx = xx_inv[:, 0] | |
| 625 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
625 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 626 | yy = jspectra[ich, mask_prof[ind], :] |
|
626 | yy = jspectra[ich, mask_prof[ind], :] | |
| 627 | jspectra[ich, mask_prof[maxid], :] = numpy.dot( |
|
627 | jspectra[ich, mask_prof[maxid], :] = numpy.dot( | |
| 628 | yy.transpose(), xx) |
|
628 | yy.transpose(), xx) | |
| 629 |
|
629 | |||
| 630 | indAux = (jspectra[ich, :, :] < tmp_noise * |
|
630 | indAux = (jspectra[ich, :, :] < tmp_noise * | |
| 631 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() |
|
631 | (1 - 1 / numpy.sqrt(num_incoh))).nonzero() | |
| 632 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ |
|
632 | jspectra[ich, indAux[0], indAux[1]] = tmp_noise * \ | |
| 633 | (1 - 1 / numpy.sqrt(num_incoh)) |
|
633 | (1 - 1 / numpy.sqrt(num_incoh)) | |
| 634 |
|
634 | |||
| 635 | # Remocion de Interferencia en el Cross Spectra |
|
635 | # Remocion de Interferencia en el Cross Spectra | |
| 636 | if jcspectra is None: |
|
636 | if jcspectra is None: | |
| 637 | return jspectra, jcspectra |
|
637 | return jspectra, jcspectra | |
| 638 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) |
|
638 | num_pairs = int(jcspectra.size / (num_prof * num_hei)) | |
| 639 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) |
|
639 | jcspectra = jcspectra.reshape(num_pairs, num_prof, num_hei) | |
| 640 |
|
640 | |||
| 641 | for ip in range(num_pairs): |
|
641 | for ip in range(num_pairs): | |
| 642 |
|
642 | |||
| 643 | #------------------------------------------- |
|
643 | #------------------------------------------- | |
| 644 |
|
644 | |||
| 645 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) |
|
645 | cspower = numpy.abs(jcspectra[ip, mask_prof, :]) | |
| 646 | cspower = cspower[:, hei_interf] |
|
646 | cspower = cspower[:, hei_interf] | |
| 647 | cspower = cspower.sum(axis=0) |
|
647 | cspower = cspower.sum(axis=0) | |
| 648 |
|
648 | |||
| 649 | cspsort = cspower.ravel().argsort() |
|
649 | cspsort = cspower.ravel().argsort() | |
| 650 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( |
|
650 | junkcspc_interf = jcspectra[ip, :, hei_interf[cspsort[list(range( | |
| 651 | offhei_interf, nhei_interf + offhei_interf))]]] |
|
651 | offhei_interf, nhei_interf + offhei_interf))]]] | |
| 652 | junkcspc_interf = junkcspc_interf.transpose() |
|
652 | junkcspc_interf = junkcspc_interf.transpose() | |
| 653 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf |
|
653 | jcspc_interf = junkcspc_interf.sum(axis=1) / nhei_interf | |
| 654 |
|
654 | |||
| 655 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() |
|
655 | ind = numpy.abs(jcspc_interf[mask_prof]).ravel().argsort() | |
| 656 |
|
656 | |||
| 657 | median_real = int(numpy.median(numpy.real( |
|
657 | median_real = int(numpy.median(numpy.real( | |
| 658 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
658 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 659 | median_imag = int(numpy.median(numpy.imag( |
|
659 | median_imag = int(numpy.median(numpy.imag( | |
| 660 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) |
|
660 | junkcspc_interf[mask_prof[ind[list(range(3 * num_prof // 4))]], :]))) | |
| 661 | comp_mask_prof = [int(e) for e in comp_mask_prof] |
|
661 | comp_mask_prof = [int(e) for e in comp_mask_prof] | |
| 662 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( |
|
662 | junkcspc_interf[comp_mask_prof, :] = numpy.complex( | |
| 663 | median_real, median_imag) |
|
663 | median_real, median_imag) | |
| 664 |
|
664 | |||
| 665 | for iprof in range(num_prof): |
|
665 | for iprof in range(num_prof): | |
| 666 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() |
|
666 | ind = numpy.abs(junkcspc_interf[iprof, :]).ravel().argsort() | |
| 667 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] |
|
667 | jcspc_interf[iprof] = junkcspc_interf[iprof, ind[nhei_interf // 2]] | |
| 668 |
|
668 | |||
| 669 | # Removiendo la Interferencia |
|
669 | # Removiendo la Interferencia | |
| 670 | jcspectra[ip, :, ind_hei] = jcspectra[ip, |
|
670 | jcspectra[ip, :, ind_hei] = jcspectra[ip, | |
| 671 | :, ind_hei] - jcspc_interf |
|
671 | :, ind_hei] - jcspc_interf | |
| 672 |
|
672 | |||
| 673 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() |
|
673 | ListAux = numpy.abs(jcspc_interf[mask_prof]).tolist() | |
| 674 | maxid = ListAux.index(max(ListAux)) |
|
674 | maxid = ListAux.index(max(ListAux)) | |
| 675 |
|
675 | |||
| 676 | ind = numpy.array([-2, -1, 1, 2]) |
|
676 | ind = numpy.array([-2, -1, 1, 2]) | |
| 677 | xx = numpy.zeros([4, 4]) |
|
677 | xx = numpy.zeros([4, 4]) | |
| 678 |
|
678 | |||
| 679 | for id1 in range(4): |
|
679 | for id1 in range(4): | |
| 680 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) |
|
680 | xx[:, id1] = ind[id1]**numpy.asarray(list(range(4))) | |
| 681 |
|
681 | |||
| 682 | xx_inv = numpy.linalg.inv(xx) |
|
682 | xx_inv = numpy.linalg.inv(xx) | |
| 683 | xx = xx_inv[:, 0] |
|
683 | xx = xx_inv[:, 0] | |
| 684 |
|
684 | |||
| 685 | ind = (ind + maxid + num_mask_prof) % num_mask_prof |
|
685 | ind = (ind + maxid + num_mask_prof) % num_mask_prof | |
| 686 | yy = jcspectra[ip, mask_prof[ind], :] |
|
686 | yy = jcspectra[ip, mask_prof[ind], :] | |
| 687 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) |
|
687 | jcspectra[ip, mask_prof[maxid], :] = numpy.dot(yy.transpose(), xx) | |
| 688 |
|
688 | |||
| 689 | # Guardar Resultados |
|
689 | # Guardar Resultados | |
| 690 | self.dataOut.data_spc = jspectra |
|
690 | self.dataOut.data_spc = jspectra | |
| 691 | self.dataOut.data_cspc = jcspectra |
|
691 | self.dataOut.data_cspc = jcspectra | |
| 692 |
|
692 | |||
| 693 | return 1 |
|
693 | return 1 | |
| 694 |
|
694 | |||
| 695 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1): |
|
695 | def run(self, dataOut, interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None, mode=1): | |
| 696 |
|
696 | |||
| 697 | self.dataOut = dataOut |
|
697 | self.dataOut = dataOut | |
| 698 |
|
698 | |||
| 699 | if mode == 1: |
|
699 | if mode == 1: | |
| 700 | self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None) |
|
700 | self.removeInterference(interf = 2,hei_interf = None, nhei_interf = None, offhei_interf = None) | |
| 701 | elif mode == 2: |
|
701 | elif mode == 2: | |
| 702 | self.removeInterference2() |
|
702 | self.removeInterference2() | |
| 703 |
|
703 | |||
| 704 | return self.dataOut |
|
704 | return self.dataOut | |
| 705 |
|
705 | |||
| 706 |
|
706 | |||
| 707 | class IncohInt(Operation): |
|
707 | class IncohInt(Operation): | |
| 708 |
|
708 | |||
| 709 | __profIndex = 0 |
|
709 | __profIndex = 0 | |
| 710 | __withOverapping = False |
|
710 | __withOverapping = False | |
| 711 |
|
711 | |||
| 712 | __byTime = False |
|
712 | __byTime = False | |
| 713 | __initime = None |
|
713 | __initime = None | |
| 714 | __lastdatatime = None |
|
714 | __lastdatatime = None | |
| 715 | __integrationtime = None |
|
715 | __integrationtime = None | |
| 716 |
|
716 | |||
| 717 | __buffer_spc = None |
|
717 | __buffer_spc = None | |
| 718 | __buffer_cspc = None |
|
718 | __buffer_cspc = None | |
| 719 | __buffer_dc = None |
|
719 | __buffer_dc = None | |
| 720 |
|
720 | |||
| 721 | __dataReady = False |
|
721 | __dataReady = False | |
| 722 |
|
722 | |||
| 723 | __timeInterval = None |
|
723 | __timeInterval = None | |
| 724 |
|
724 | |||
| 725 | n = None |
|
725 | n = None | |
| 726 |
|
726 | |||
| 727 | def __init__(self): |
|
727 | def __init__(self): | |
| 728 |
|
728 | |||
| 729 | Operation.__init__(self) |
|
729 | Operation.__init__(self) | |
| 730 |
|
730 | |||
| 731 | def setup(self, n=None, timeInterval=None, overlapping=False): |
|
731 | def setup(self, n=None, timeInterval=None, overlapping=False): | |
| 732 | """ |
|
732 | """ | |
| 733 | Set the parameters of the integration class. |
|
733 | Set the parameters of the integration class. | |
| 734 |
|
734 | |||
| 735 | Inputs: |
|
735 | Inputs: | |
| 736 |
|
736 | |||
| 737 | n : Number of coherent integrations |
|
737 | n : Number of coherent integrations | |
| 738 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
738 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
| 739 | overlapping : |
|
739 | overlapping : | |
| 740 |
|
740 | |||
| 741 | """ |
|
741 | """ | |
| 742 |
|
742 | |||
| 743 | self.__initime = None |
|
743 | self.__initime = None | |
| 744 | self.__lastdatatime = 0 |
|
744 | self.__lastdatatime = 0 | |
| 745 |
|
745 | |||
| 746 | self.__buffer_spc = 0 |
|
746 | self.__buffer_spc = 0 | |
| 747 | self.__buffer_cspc = 0 |
|
747 | self.__buffer_cspc = 0 | |
| 748 | self.__buffer_dc = 0 |
|
748 | self.__buffer_dc = 0 | |
| 749 |
|
749 | |||
| 750 | self.__profIndex = 0 |
|
750 | self.__profIndex = 0 | |
| 751 | self.__dataReady = False |
|
751 | self.__dataReady = False | |
| 752 | self.__byTime = False |
|
752 | self.__byTime = False | |
| 753 |
|
753 | |||
| 754 | if n is None and timeInterval is None: |
|
754 | if n is None and timeInterval is None: | |
| 755 | raise ValueError("n or timeInterval should be specified ...") |
|
755 | raise ValueError("n or timeInterval should be specified ...") | |
| 756 |
|
756 | |||
| 757 | if n is not None: |
|
757 | if n is not None: | |
| 758 | self.n = int(n) |
|
758 | self.n = int(n) | |
| 759 | else: |
|
759 | else: | |
| 760 |
|
760 | |||
| 761 | self.__integrationtime = int(timeInterval) |
|
761 | self.__integrationtime = int(timeInterval) | |
| 762 | self.n = None |
|
762 | self.n = None | |
| 763 | self.__byTime = True |
|
763 | self.__byTime = True | |
| 764 |
|
764 | |||
| 765 | def putData(self, data_spc, data_cspc, data_dc): |
|
765 | def putData(self, data_spc, data_cspc, data_dc): | |
| 766 | """ |
|
766 | """ | |
| 767 | Add a profile to the __buffer_spc and increase in one the __profileIndex |
|
767 | Add a profile to the __buffer_spc and increase in one the __profileIndex | |
| 768 |
|
768 | |||
| 769 | """ |
|
769 | """ | |
| 770 |
|
770 | |||
| 771 | self.__buffer_spc += data_spc |
|
771 | self.__buffer_spc += data_spc | |
| 772 |
|
772 | |||
| 773 | if data_cspc is None: |
|
773 | if data_cspc is None: | |
| 774 | self.__buffer_cspc = None |
|
774 | self.__buffer_cspc = None | |
| 775 | else: |
|
775 | else: | |
| 776 | self.__buffer_cspc += data_cspc |
|
776 | self.__buffer_cspc += data_cspc | |
| 777 |
|
777 | |||
| 778 | if data_dc is None: |
|
778 | if data_dc is None: | |
| 779 | self.__buffer_dc = None |
|
779 | self.__buffer_dc = None | |
| 780 | else: |
|
780 | else: | |
| 781 | self.__buffer_dc += data_dc |
|
781 | self.__buffer_dc += data_dc | |
| 782 |
|
782 | |||
| 783 | self.__profIndex += 1 |
|
783 | self.__profIndex += 1 | |
| 784 |
|
784 | |||
| 785 | return |
|
785 | return | |
| 786 |
|
786 | |||
| 787 | def pushData(self): |
|
787 | def pushData(self): | |
| 788 | """ |
|
788 | """ | |
| 789 | Return the sum of the last profiles and the profiles used in the sum. |
|
789 | Return the sum of the last profiles and the profiles used in the sum. | |
| 790 |
|
790 | |||
| 791 | Affected: |
|
791 | Affected: | |
| 792 |
|
792 | |||
| 793 | self.__profileIndex |
|
793 | self.__profileIndex | |
| 794 |
|
794 | |||
| 795 | """ |
|
795 | """ | |
| 796 |
|
796 | |||
| 797 | data_spc = self.__buffer_spc |
|
797 | data_spc = self.__buffer_spc | |
| 798 | data_cspc = self.__buffer_cspc |
|
798 | data_cspc = self.__buffer_cspc | |
| 799 | data_dc = self.__buffer_dc |
|
799 | data_dc = self.__buffer_dc | |
| 800 | n = self.__profIndex |
|
800 | n = self.__profIndex | |
| 801 |
|
801 | |||
| 802 | self.__buffer_spc = 0 |
|
802 | self.__buffer_spc = 0 | |
| 803 | self.__buffer_cspc = 0 |
|
803 | self.__buffer_cspc = 0 | |
| 804 | self.__buffer_dc = 0 |
|
804 | self.__buffer_dc = 0 | |
| 805 | self.__profIndex = 0 |
|
805 | self.__profIndex = 0 | |
| 806 |
|
806 | |||
| 807 | return data_spc, data_cspc, data_dc, n |
|
807 | return data_spc, data_cspc, data_dc, n | |
| 808 |
|
808 | |||
| 809 | def byProfiles(self, *args): |
|
809 | def byProfiles(self, *args): | |
| 810 |
|
810 | |||
| 811 | self.__dataReady = False |
|
811 | self.__dataReady = False | |
| 812 | avgdata_spc = None |
|
812 | avgdata_spc = None | |
| 813 | avgdata_cspc = None |
|
813 | avgdata_cspc = None | |
| 814 | avgdata_dc = None |
|
814 | avgdata_dc = None | |
| 815 |
|
815 | |||
| 816 | self.putData(*args) |
|
816 | self.putData(*args) | |
| 817 |
|
817 | |||
| 818 | if self.__profIndex == self.n: |
|
818 | if self.__profIndex == self.n: | |
| 819 |
|
819 | |||
| 820 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
820 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 821 | self.n = n |
|
821 | self.n = n | |
| 822 | self.__dataReady = True |
|
822 | self.__dataReady = True | |
| 823 |
|
823 | |||
| 824 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
824 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 825 |
|
825 | |||
| 826 | def byTime(self, datatime, *args): |
|
826 | def byTime(self, datatime, *args): | |
| 827 |
|
827 | |||
| 828 | self.__dataReady = False |
|
828 | self.__dataReady = False | |
| 829 | avgdata_spc = None |
|
829 | avgdata_spc = None | |
| 830 | avgdata_cspc = None |
|
830 | avgdata_cspc = None | |
| 831 | avgdata_dc = None |
|
831 | avgdata_dc = None | |
| 832 |
|
832 | |||
| 833 | self.putData(*args) |
|
833 | self.putData(*args) | |
| 834 |
|
834 | |||
| 835 | if (datatime - self.__initime) >= self.__integrationtime: |
|
835 | if (datatime - self.__initime) >= self.__integrationtime: | |
| 836 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() |
|
836 | avgdata_spc, avgdata_cspc, avgdata_dc, n = self.pushData() | |
| 837 | self.n = n |
|
837 | self.n = n | |
| 838 | self.__dataReady = True |
|
838 | self.__dataReady = True | |
| 839 |
|
839 | |||
| 840 | return avgdata_spc, avgdata_cspc, avgdata_dc |
|
840 | return avgdata_spc, avgdata_cspc, avgdata_dc | |
| 841 |
|
841 | |||
| 842 | def integrate(self, datatime, *args): |
|
842 | def integrate(self, datatime, *args): | |
| 843 |
|
843 | |||
| 844 | if self.__profIndex == 0: |
|
844 | if self.__profIndex == 0: | |
| 845 | self.__initime = datatime |
|
845 | self.__initime = datatime | |
| 846 |
|
846 | |||
| 847 | if self.__byTime: |
|
847 | if self.__byTime: | |
| 848 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( |
|
848 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byTime( | |
| 849 | datatime, *args) |
|
849 | datatime, *args) | |
| 850 | else: |
|
850 | else: | |
| 851 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) |
|
851 | avgdata_spc, avgdata_cspc, avgdata_dc = self.byProfiles(*args) | |
| 852 |
|
852 | |||
| 853 | if not self.__dataReady: |
|
853 | if not self.__dataReady: | |
| 854 | return None, None, None, None |
|
854 | return None, None, None, None | |
| 855 |
|
855 | |||
| 856 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc |
|
856 | return self.__initime, avgdata_spc, avgdata_cspc, avgdata_dc | |
| 857 |
|
857 | |||
| 858 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): |
|
858 | def run(self, dataOut, n=None, timeInterval=None, overlapping=False): | |
| 859 | if n == 1: |
|
859 | if n == 1: | |
| 860 | return dataOut |
|
860 | return dataOut | |
| 861 |
|
861 | |||
| 862 | dataOut.flagNoData = True |
|
862 | dataOut.flagNoData = True | |
| 863 |
|
863 | |||
| 864 | if not self.isConfig: |
|
864 | if not self.isConfig: | |
| 865 | self.setup(n, timeInterval, overlapping) |
|
865 | self.setup(n, timeInterval, overlapping) | |
| 866 | self.isConfig = True |
|
866 | self.isConfig = True | |
| 867 |
|
867 | |||
| 868 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, |
|
868 | avgdatatime, avgdata_spc, avgdata_cspc, avgdata_dc = self.integrate(dataOut.utctime, | |
| 869 | dataOut.data_spc, |
|
869 | dataOut.data_spc, | |
| 870 | dataOut.data_cspc, |
|
870 | dataOut.data_cspc, | |
| 871 | dataOut.data_dc) |
|
871 | dataOut.data_dc) | |
| 872 |
|
872 | |||
| 873 | if self.__dataReady: |
|
873 | if self.__dataReady: | |
| 874 |
|
874 | |||
| 875 | dataOut.data_spc = avgdata_spc |
|
875 | dataOut.data_spc = avgdata_spc | |
| 876 | dataOut.data_cspc = avgdata_cspc |
|
876 | dataOut.data_cspc = avgdata_cspc | |
| 877 | dataOut.data_dc = avgdata_dc |
|
877 | dataOut.data_dc = avgdata_dc | |
| 878 | dataOut.nIncohInt *= self.n |
|
878 | dataOut.nIncohInt *= self.n | |
| 879 | dataOut.utctime = avgdatatime |
|
879 | dataOut.utctime = avgdatatime | |
| 880 | dataOut.flagNoData = False |
|
880 | dataOut.flagNoData = False | |
| 881 |
|
881 | |||
| 882 | return dataOut No newline at end of file |
|
882 | return dataOut | |
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