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| 1 | import numpy |
|
1 | import numpy | |
| 2 | import math |
|
2 | import math | |
| 3 | from scipy import optimize, interpolate, signal, stats, ndimage |
|
3 | from scipy import optimize, interpolate, signal, stats, ndimage | |
| 4 | import re |
|
4 | import re | |
| 5 | import datetime |
|
5 | import datetime | |
| 6 | import copy |
|
6 | import copy | |
| 7 | import sys |
|
7 | import sys | |
| 8 | import importlib |
|
8 | import importlib | |
| 9 | import itertools |
|
9 | import itertools | |
| 10 |
|
10 | |||
| 11 | from jroproc_base import ProcessingUnit, Operation |
|
11 | from jroproc_base import ProcessingUnit, Operation | |
| 12 | from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon |
|
12 | from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon | |
| 13 |
|
13 | |||
| 14 |
|
14 | |||
| 15 | class ParametersProc(ProcessingUnit): |
|
15 | class ParametersProc(ProcessingUnit): | |
| 16 |
|
16 | |||
| 17 | nSeconds = None |
|
17 | nSeconds = None | |
| 18 |
|
18 | |||
| 19 | def __init__(self): |
|
19 | def __init__(self): | |
| 20 | ProcessingUnit.__init__(self) |
|
20 | ProcessingUnit.__init__(self) | |
| 21 |
|
21 | |||
| 22 | # self.objectDict = {} |
|
22 | # self.objectDict = {} | |
| 23 | self.buffer = None |
|
23 | self.buffer = None | |
| 24 | self.firstdatatime = None |
|
24 | self.firstdatatime = None | |
| 25 | self.profIndex = 0 |
|
25 | self.profIndex = 0 | |
| 26 | self.dataOut = Parameters() |
|
26 | self.dataOut = Parameters() | |
| 27 |
|
27 | |||
| 28 | def __updateObjFromInput(self): |
|
28 | def __updateObjFromInput(self): | |
| 29 |
|
29 | |||
| 30 | self.dataOut.inputUnit = self.dataIn.type |
|
30 | self.dataOut.inputUnit = self.dataIn.type | |
| 31 |
|
31 | |||
| 32 | self.dataOut.timeZone = self.dataIn.timeZone |
|
32 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 33 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
33 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 34 | self.dataOut.errorCount = self.dataIn.errorCount |
|
34 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 35 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
35 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 36 |
|
36 | |||
| 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 | # self.dataOut.nHeights = self.dataIn.nHeights |
|
42 | # self.dataOut.nHeights = self.dataIn.nHeights | |
| 43 | # self.dataOut.nChannels = self.dataIn.nChannels |
|
43 | # self.dataOut.nChannels = self.dataIn.nChannels | |
| 44 | self.dataOut.nBaud = self.dataIn.nBaud |
|
44 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 45 | self.dataOut.nCode = self.dataIn.nCode |
|
45 | self.dataOut.nCode = self.dataIn.nCode | |
| 46 | self.dataOut.code = self.dataIn.code |
|
46 | self.dataOut.code = self.dataIn.code | |
| 47 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
47 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 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 | self.dataOut.utctime = self.dataIn.utctime |
|
50 | self.dataOut.utctime = self.dataIn.utctime | |
| 51 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada |
|
51 | self.dataOut.flagDecodeData = self.dataIn.flagDecodeData #asumo q la data esta decodificada | |
| 52 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip |
|
52 | self.dataOut.flagDeflipData = self.dataIn.flagDeflipData #asumo q la data esta sin flip | |
| 53 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
53 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 54 | # self.dataOut.nIncohInt = 1 |
|
54 | # self.dataOut.nIncohInt = 1 | |
| 55 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
55 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 56 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
56 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 57 | self.dataOut.timeInterval = self.dataIn.timeInterval |
|
57 | self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 58 | self.dataOut.heightList = self.dataIn.getHeiRange() |
|
58 | self.dataOut.heightList = self.dataIn.getHeiRange() | |
| 59 | self.dataOut.frequency = self.dataIn.frequency |
|
59 | self.dataOut.frequency = self.dataIn.frequency | |
| 60 | self.dataOut.noise = self.dataIn.noise |
|
60 | self.dataOut.noise = self.dataIn.noise | |
| 61 |
|
61 | |||
| 62 | def run(self): |
|
62 | def run(self): | |
| 63 |
|
63 | |||
| 64 | #---------------------- Voltage Data --------------------------- |
|
64 | #---------------------- Voltage Data --------------------------- | |
| 65 |
|
65 | |||
| 66 | if self.dataIn.type == "Voltage": |
|
66 | if self.dataIn.type == "Voltage": | |
| 67 |
|
67 | |||
| 68 | self.__updateObjFromInput() |
|
68 | self.__updateObjFromInput() | |
| 69 | self.dataOut.data_pre = self.dataIn.data.copy() |
|
69 | self.dataOut.data_pre = self.dataIn.data.copy() | |
| 70 | self.dataOut.flagNoData = False |
|
70 | self.dataOut.flagNoData = False | |
| 71 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
71 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 72 | self.dataOut.paramInterval = self.dataIn.nProfiles*self.dataIn.nCohInt*self.dataIn.ippSeconds |
|
72 | self.dataOut.paramInterval = self.dataIn.nProfiles*self.dataIn.nCohInt*self.dataIn.ippSeconds | |
| 73 | return |
|
73 | return | |
| 74 |
|
74 | |||
| 75 | #---------------------- Spectra Data --------------------------- |
|
75 | #---------------------- Spectra Data --------------------------- | |
| 76 |
|
76 | |||
| 77 | if self.dataIn.type == "Spectra": |
|
77 | if self.dataIn.type == "Spectra": | |
| 78 |
|
78 | |||
| 79 | self.dataOut.data_pre = (self.dataIn.data_spc,self.dataIn.data_cspc) |
|
79 | self.dataOut.data_pre = (self.dataIn.data_spc,self.dataIn.data_cspc) | |
| 80 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) |
|
80 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) | |
| 81 | self.dataOut.noise = self.dataIn.getNoise() |
|
81 | self.dataOut.noise = self.dataIn.getNoise() | |
| 82 | self.dataOut.normFactor = self.dataIn.normFactor |
|
82 | self.dataOut.normFactor = self.dataIn.normFactor | |
| 83 | self.dataOut.groupList = self.dataIn.pairsList |
|
83 | self.dataOut.groupList = self.dataIn.pairsList | |
| 84 | self.dataOut.flagNoData = False |
|
84 | self.dataOut.flagNoData = False | |
| 85 |
|
85 | |||
| 86 | #---------------------- Correlation Data --------------------------- |
|
86 | #---------------------- Correlation Data --------------------------- | |
| 87 |
|
87 | |||
| 88 | if self.dataIn.type == "Correlation": |
|
88 | if self.dataIn.type == "Correlation": | |
| 89 |
|
89 | |||
| 90 | if self.dataIn.data_ccf is not None: |
|
90 | if self.dataIn.data_ccf is not None: | |
| 91 | self.dataOut.data_pre = (self.dataIn.data_acf,self.dataIn.data_ccf) |
|
91 | self.dataOut.data_pre = (self.dataIn.data_acf,self.dataIn.data_ccf) | |
| 92 | else: |
|
92 | else: | |
| 93 | self.dataOut.data_pre = self.dataIn.data_acf.copy() |
|
93 | self.dataOut.data_pre = self.dataIn.data_acf.copy() | |
| 94 |
|
94 | |||
| 95 | self.dataOut.abscissaList = self.dataIn.lagRange |
|
95 | self.dataOut.abscissaList = self.dataIn.lagRange | |
| 96 | self.dataOut.noise = self.dataIn.noise |
|
96 | self.dataOut.noise = self.dataIn.noise | |
| 97 | self.dataOut.normFactor = self.dataIn.normFactor |
|
97 | self.dataOut.normFactor = self.dataIn.normFactor | |
| 98 | self.dataOut.data_SNR = self.dataIn.SNR |
|
98 | self.dataOut.data_SNR = self.dataIn.SNR | |
| 99 | self.dataOut.groupList = self.dataIn.pairsList |
|
99 | self.dataOut.groupList = self.dataIn.pairsList | |
| 100 | self.dataOut.flagNoData = False |
|
100 | self.dataOut.flagNoData = False | |
| 101 | self.dataOut.nAvg = self.dataIn.nAvg |
|
101 | self.dataOut.nAvg = self.dataIn.nAvg | |
| 102 |
|
102 | |||
| 103 | #---------------------- Parameters Data --------------------------- |
|
103 | #---------------------- Parameters Data --------------------------- | |
| 104 |
|
104 | |||
| 105 | if self.dataIn.type == "Parameters": |
|
105 | if self.dataIn.type == "Parameters": | |
| 106 | self.dataOut.copy(self.dataIn) |
|
106 | self.dataOut.copy(self.dataIn) | |
| 107 | self.dataOut.flagNoData = False |
|
107 | self.dataOut.flagNoData = False | |
| 108 |
|
108 | |||
| 109 | return True |
|
109 | return True | |
| 110 |
|
110 | |||
| 111 | self.__updateObjFromInput() |
|
111 | self.__updateObjFromInput() | |
| 112 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
112 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 113 | self.dataOut.paramInterval = self.dataIn.timeInterval |
|
113 | self.dataOut.paramInterval = self.dataIn.timeInterval | |
| 114 |
|
|
114 | ||
| 115 | #------------------- Get Moments ---------------------------------- |
|
115 | return | |
| 116 | def GetMoments(self, channelList = None): |
|
116 | ||
|
|
117 | class SpectralMoments(Operation): | |||
|
|
118 | ||||
| 117 |
|
|
119 | ''' | |
| 118 |
Function |
|
120 | Function SpectralMoments() | |
|
|
121 | ||||
|
|
122 | Calculates moments (power, mean, standard deviation) and SNR of the signal | |||
|
|
123 | ||||
|
|
124 | Type of dataIn: Spectra | |||
| 119 |
|
125 | |||
| 120 | Input: |
|
126 | Input: | |
| 121 | channelList : simple channel list to select e.g. [2,3,7] |
|
127 | channelList : simple channel list to select e.g. [2,3,7] | |
| 122 | self.dataOut.data_pre |
|
128 | self.dataOut.data_pre : Spectral data | |
| 123 | self.dataOut.abscissaList |
|
129 | self.dataOut.abscissaList : List of frequencies | |
| 124 | self.dataOut.noise |
|
130 | self.dataOut.noise : Noise level per channel | |
| 125 |
|
131 | |||
| 126 | Affected: |
|
132 | Affected: | |
| 127 | self.dataOut.data_param |
|
133 | self.dataOut.data_param : Parameters per channel | |
| 128 | self.dataOut.data_SNR |
|
134 | self.dataOut.data_SNR : SNR per channel | |
| 129 |
|
135 | |||
| 130 |
|
|
136 | ''' | |
| 131 | self.dataOut.data_pre = self.dataOut.data_pre[0] |
|
137 | ||
| 132 | data = self.dataOut.data_pre |
|
138 | def run(self, dataOut, channelList=None): | |
| 133 | absc = self.dataOut.abscissaList[:-1] |
|
139 | ||
| 134 | noise = self.dataOut.noise |
|
140 | dataOut.data_pre = dataOut.data_pre[0] | |
|
|
141 | data = dataOut.data_pre | |||
|
|
142 | absc = dataOut.abscissaList[:-1] | |||
|
|
143 | noise = dataOut.noise | |||
| 135 |
|
144 | |||
| 136 | data_param = numpy.zeros((data.shape[0], 4, data.shape[2])) |
|
145 | data_param = numpy.zeros((data.shape[0], 4, data.shape[2])) | |
| 137 |
|
146 | |||
| 138 | if channelList== None: |
|
147 | if channelList== None: | |
| 139 |
channelList = |
|
148 | channelList = dataOut.channelList | |
| 140 |
|
|
149 | dataOut.channelList = channelList | |
| 141 |
|
150 | |||
| 142 | for ind in channelList: |
|
151 | for ind in channelList: | |
| 143 | data_param[ind,:,:] = self.__calculateMoments(data[ind,:,:], absc, noise[ind]) |
|
152 | data_param[ind,:,:] = self.__calculateMoments(data[ind,:,:], absc, noise[ind]) | |
| 144 |
|
153 | |||
| 145 |
|
|
154 | dataOut.data_param = data_param[:,1:,:] | |
| 146 |
|
|
155 | dataOut.data_SNR = data_param[:,0] | |
| 147 | return |
|
156 | return | |
| 148 |
|
157 | |||
| 149 | def __calculateMoments(self, oldspec, oldfreq, n0, nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None): |
|
158 | def __calculateMoments(self, oldspec, oldfreq, n0, nicoh = None, graph = None, smooth = None, type1 = None, fwindow = None, snrth = None, dc = None, aliasing = None, oldfd = None, wwauto = None): | |
| 150 |
|
159 | |||
| 151 | if (nicoh == None): nicoh = 1 |
|
160 | if (nicoh == None): nicoh = 1 | |
| 152 | if (graph == None): graph = 0 |
|
161 | if (graph == None): graph = 0 | |
| 153 | if (smooth == None): smooth = 0 |
|
162 | if (smooth == None): smooth = 0 | |
| 154 | elif (self.smooth < 3): smooth = 0 |
|
163 | elif (self.smooth < 3): smooth = 0 | |
| 155 |
|
164 | |||
| 156 | if (type1 == None): type1 = 0 |
|
165 | if (type1 == None): type1 = 0 | |
| 157 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 |
|
166 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 | |
| 158 | if (snrth == None): snrth = -3 |
|
167 | if (snrth == None): snrth = -3 | |
| 159 | if (dc == None): dc = 0 |
|
168 | if (dc == None): dc = 0 | |
| 160 | if (aliasing == None): aliasing = 0 |
|
169 | if (aliasing == None): aliasing = 0 | |
| 161 | if (oldfd == None): oldfd = 0 |
|
170 | if (oldfd == None): oldfd = 0 | |
| 162 | if (wwauto == None): wwauto = 0 |
|
171 | if (wwauto == None): wwauto = 0 | |
| 163 |
|
172 | |||
| 164 | if (n0 < 1.e-20): n0 = 1.e-20 |
|
173 | if (n0 < 1.e-20): n0 = 1.e-20 | |
| 165 |
|
174 | |||
| 166 | freq = oldfreq |
|
175 | freq = oldfreq | |
| 167 | vec_power = numpy.zeros(oldspec.shape[1]) |
|
176 | vec_power = numpy.zeros(oldspec.shape[1]) | |
| 168 | vec_fd = numpy.zeros(oldspec.shape[1]) |
|
177 | vec_fd = numpy.zeros(oldspec.shape[1]) | |
| 169 | vec_w = numpy.zeros(oldspec.shape[1]) |
|
178 | vec_w = numpy.zeros(oldspec.shape[1]) | |
| 170 | vec_snr = numpy.zeros(oldspec.shape[1]) |
|
179 | vec_snr = numpy.zeros(oldspec.shape[1]) | |
| 171 |
|
180 | |||
| 172 | for ind in range(oldspec.shape[1]): |
|
181 | for ind in range(oldspec.shape[1]): | |
| 173 |
|
182 | |||
| 174 | spec = oldspec[:,ind] |
|
183 | spec = oldspec[:,ind] | |
| 175 | aux = spec*fwindow |
|
184 | aux = spec*fwindow | |
| 176 | max_spec = aux.max() |
|
185 | max_spec = aux.max() | |
| 177 | m = list(aux).index(max_spec) |
|
186 | m = list(aux).index(max_spec) | |
| 178 |
|
187 | |||
| 179 | #Smooth |
|
188 | #Smooth | |
| 180 | if (smooth == 0): spec2 = spec |
|
189 | if (smooth == 0): spec2 = spec | |
| 181 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) |
|
190 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) | |
| 182 |
|
191 | |||
| 183 | # Calculo de Momentos |
|
192 | # Calculo de Momentos | |
| 184 | bb = spec2[range(m,spec2.size)] |
|
193 | bb = spec2[range(m,spec2.size)] | |
| 185 | bb = (bb<n0).nonzero() |
|
194 | bb = (bb<n0).nonzero() | |
| 186 | bb = bb[0] |
|
195 | bb = bb[0] | |
| 187 |
|
196 | |||
| 188 | ss = spec2[range(0,m + 1)] |
|
197 | ss = spec2[range(0,m + 1)] | |
| 189 | ss = (ss<n0).nonzero() |
|
198 | ss = (ss<n0).nonzero() | |
| 190 | ss = ss[0] |
|
199 | ss = ss[0] | |
| 191 |
|
200 | |||
| 192 | if (bb.size == 0): |
|
201 | if (bb.size == 0): | |
| 193 | bb0 = spec.size - 1 - m |
|
202 | bb0 = spec.size - 1 - m | |
| 194 | else: |
|
203 | else: | |
| 195 | bb0 = bb[0] - 1 |
|
204 | bb0 = bb[0] - 1 | |
| 196 | if (bb0 < 0): |
|
205 | if (bb0 < 0): | |
| 197 | bb0 = 0 |
|
206 | bb0 = 0 | |
| 198 |
|
207 | |||
| 199 | if (ss.size == 0): ss1 = 1 |
|
208 | if (ss.size == 0): ss1 = 1 | |
| 200 | else: ss1 = max(ss) + 1 |
|
209 | else: ss1 = max(ss) + 1 | |
| 201 |
|
210 | |||
| 202 | if (ss1 > m): ss1 = m |
|
211 | if (ss1 > m): ss1 = m | |
| 203 |
|
212 | |||
| 204 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 |
|
213 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 | |
| 205 | power = ((spec2[valid] - n0)*fwindow[valid]).sum() |
|
214 | power = ((spec2[valid] - n0)*fwindow[valid]).sum() | |
| 206 | fd = ((spec2[valid]- n0)*freq[valid]*fwindow[valid]).sum()/power |
|
215 | fd = ((spec2[valid]- n0)*freq[valid]*fwindow[valid]).sum()/power | |
| 207 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) |
|
216 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) | |
| 208 | snr = (spec2.mean()-n0)/n0 |
|
217 | snr = (spec2.mean()-n0)/n0 | |
| 209 |
|
218 | |||
| 210 | if (snr < 1.e-20) : |
|
219 | if (snr < 1.e-20) : | |
| 211 | snr = 1.e-20 |
|
220 | snr = 1.e-20 | |
| 212 |
|
221 | |||
| 213 | vec_power[ind] = power |
|
222 | vec_power[ind] = power | |
| 214 | vec_fd[ind] = fd |
|
223 | vec_fd[ind] = fd | |
| 215 | vec_w[ind] = w |
|
224 | vec_w[ind] = w | |
| 216 | vec_snr[ind] = snr |
|
225 | vec_snr[ind] = snr | |
| 217 |
|
226 | |||
| 218 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) |
|
227 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) | |
| 219 | return moments |
|
228 | return moments | |
| 220 |
|
229 | |||
| 221 | #------------------ Get SA Parameters -------------------------- |
|
230 | #------------------ Get SA Parameters -------------------------- | |
| 222 |
|
231 | |||
| 223 | def GetSAParameters(self): |
|
232 | def GetSAParameters(self): | |
|
|
233 | #SA en frecuencia | |||
| 224 | pairslist = self.dataOut.groupList |
|
234 | pairslist = self.dataOut.groupList | |
| 225 | num_pairs = len(pairslist) |
|
235 | num_pairs = len(pairslist) | |
| 226 |
|
236 | |||
| 227 | vel = self.dataOut.abscissaList |
|
237 | vel = self.dataOut.abscissaList | |
| 228 | spectra = self.dataOut.data_pre |
|
238 | spectra = self.dataOut.data_pre | |
| 229 | cspectra = self.dataIn.data_cspc |
|
239 | cspectra = self.dataIn.data_cspc | |
| 230 | delta_v = vel[1] - vel[0] |
|
240 | delta_v = vel[1] - vel[0] | |
| 231 |
|
241 | |||
| 232 | #Calculating the power spectrum |
|
242 | #Calculating the power spectrum | |
| 233 | spc_pow = numpy.sum(spectra, 3)*delta_v |
|
243 | spc_pow = numpy.sum(spectra, 3)*delta_v | |
| 234 | #Normalizing Spectra |
|
244 | #Normalizing Spectra | |
| 235 | norm_spectra = spectra/spc_pow |
|
245 | norm_spectra = spectra/spc_pow | |
| 236 | #Calculating the norm_spectra at peak |
|
246 | #Calculating the norm_spectra at peak | |
| 237 | max_spectra = numpy.max(norm_spectra, 3) |
|
247 | max_spectra = numpy.max(norm_spectra, 3) | |
| 238 |
|
248 | |||
| 239 | #Normalizing Cross Spectra |
|
249 | #Normalizing Cross Spectra | |
| 240 | norm_cspectra = numpy.zeros(cspectra.shape) |
|
250 | norm_cspectra = numpy.zeros(cspectra.shape) | |
| 241 |
|
251 | |||
| 242 | for i in range(num_chan): |
|
252 | for i in range(num_chan): | |
| 243 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) |
|
253 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) | |
| 244 |
|
254 | |||
| 245 | max_cspectra = numpy.max(norm_cspectra,2) |
|
255 | max_cspectra = numpy.max(norm_cspectra,2) | |
| 246 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) |
|
256 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) | |
| 247 |
|
257 | |||
| 248 | for i in range(num_pairs): |
|
258 | for i in range(num_pairs): | |
| 249 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) |
|
259 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) | |
| 250 | #------------------- Get Lags ---------------------------------- |
|
260 | #------------------- Get Lags ---------------------------------- | |
| 251 |
|
261 | |||
| 252 | def GetLags(self): |
|
262 | class SALags(Operation): | |
| 253 |
|
|
263 | ''' | |
| 254 |
|
|
264 | Function GetMoments() | |
| 255 |
|
265 | |||
| 256 |
|
|
266 | Input: | |
| 257 |
|
|
267 | self.dataOut.data_pre | |
| 258 |
|
|
268 | self.dataOut.abscissaList | |
| 259 |
|
|
269 | self.dataOut.noise | |
| 260 |
|
|
270 | self.dataOut.normFactor | |
| 261 |
|
|
271 | self.dataOut.data_SNR | |
| 262 |
|
|
272 | self.dataOut.groupList | |
| 263 |
|
|
273 | self.dataOut.nChannels | |
| 264 |
|
|
274 | ||
| 265 |
|
|
275 | Affected: | |
| 266 |
|
|
276 | self.dataOut.data_param | |
| 267 |
|
|
277 | ||
| 268 |
|
|
278 | ''' | |
|
|
279 | def run(self, dataOut): | |||
|
|
280 | data = dataOut.data_pre | |||
|
|
281 | data_acf = dataOut.data_pre[0] | |||
|
|
282 | data_ccf = dataOut.data_pre[1] | |||
| 269 |
|
283 | |||
| 270 |
|
|
284 | normFactor = dataOut.normFactor | |
| 271 | normFactor = self.dataOut.normFactor |
|
285 | nHeights = dataOut.nHeights | |
| 272 | nHeights = self.dataOut.nHeights |
|
286 | absc = dataOut.abscissaList[:-1] | |
| 273 | absc = self.dataOut.abscissaList[:-1] |
|
287 | noise = dataOut.noise | |
| 274 | noise = self.dataOut.noise |
|
288 | SNR = dataOut.data_SNR | |
| 275 | SNR = self.dataOut.data_SNR |
|
289 | # pairsList = dataOut.groupList | |
| 276 | pairsList = self.dataOut.groupList |
|
290 | nChannels = dataOut.nChannels | |
| 277 | nChannels = self.dataOut.nChannels |
|
291 | # pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) | |
| 278 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) |
|
292 | dataOut.data_param = numpy.zeros((len(pairsCrossCorr)*2 + 1, nHeights)) | |
| 279 | self.dataOut.data_param = numpy.zeros((len(pairsCrossCorr)*2 + 1, nHeights)) |
|
|||
| 280 |
|
293 | |||
| 281 | dataNorm = numpy.abs(data) |
|
294 | dataNorm = numpy.abs(data) | |
| 282 | for l in range(len(pairsList)): |
|
295 | for l in range(len(pairsList)): | |
| 283 | dataNorm[l,:,:] = dataNorm[l,:,:]/normFactor[l,:] |
|
296 | dataNorm[l,:,:] = dataNorm[l,:,:]/normFactor[l,:] | |
| 284 |
|
297 | |||
| 285 | self.dataOut.data_param[:-1,:] = self.__calculateTaus(dataNorm, pairsCrossCorr, pairsAutoCorr, absc) |
|
298 | self.dataOut.data_param[:-1,:] = self.__calculateTaus(dataNorm, pairsCrossCorr, pairsAutoCorr, absc) | |
| 286 |
self.dataOut.data_param[-1,:] = self.__calculateLag1Phase(data |
|
299 | self.dataOut.data_param[-1,:] = self.__calculateLag1Phase(data_acf, absc) | |
| 287 | return |
|
300 | return | |
| 288 |
|
301 | |||
| 289 | def __getPairsAutoCorr(self, pairsList, nChannels): |
|
302 | # def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 290 |
|
303 | # | ||
| 291 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
304 | # pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 292 |
|
305 | # | ||
| 293 | for l in range(len(pairsList)): |
|
306 | # for l in range(len(pairsList)): | |
| 294 | firstChannel = pairsList[l][0] |
|
307 | # firstChannel = pairsList[l][0] | |
| 295 | secondChannel = pairsList[l][1] |
|
308 | # secondChannel = pairsList[l][1] | |
| 296 |
|
309 | # | ||
| 297 | #Obteniendo pares de Autocorrelacion |
|
310 | # #Obteniendo pares de Autocorrelacion | |
| 298 | if firstChannel == secondChannel: |
|
311 | # if firstChannel == secondChannel: | |
| 299 | pairsAutoCorr[firstChannel] = int(l) |
|
312 | # pairsAutoCorr[firstChannel] = int(l) | |
| 300 |
|
313 | # | ||
| 301 | pairsAutoCorr = pairsAutoCorr.astype(int) |
|
314 | # pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 302 |
|
315 | # | ||
| 303 | pairsCrossCorr = range(len(pairsList)) |
|
316 | # pairsCrossCorr = range(len(pairsList)) | |
| 304 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
317 | # pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 305 |
|
318 | # | ||
| 306 | return pairsAutoCorr, pairsCrossCorr |
|
319 | # return pairsAutoCorr, pairsCrossCorr | |
| 307 |
|
320 | |||
| 308 | def __calculateTaus(self, data, pairsCrossCorr, pairsAutoCorr, lagTRange): |
|
321 | def __calculateTaus(self, data, pairsCrossCorr, pairsAutoCorr, lagTRange): | |
| 309 |
|
322 | |||
| 310 | Pt0 = data.shape[1]/2 |
|
323 | Pt0 = data.shape[1]/2 | |
| 311 | #Funcion de Autocorrelacion |
|
324 | #Funcion de Autocorrelacion | |
| 312 | dataAutoCorr = stats.nanmean(data[pairsAutoCorr,:,:], axis = 0) |
|
325 | dataAutoCorr = stats.nanmean(data[pairsAutoCorr,:,:], axis = 0) | |
| 313 |
|
326 | |||
| 314 | #Obtencion Indice de TauCross |
|
327 | #Obtencion Indice de TauCross | |
| 315 | indCross = data[pairsCrossCorr,:,:].argmax(axis = 1) |
|
328 | indCross = data[pairsCrossCorr,:,:].argmax(axis = 1) | |
| 316 | #Obtencion Indice de TauAuto |
|
329 | #Obtencion Indice de TauAuto | |
| 317 | indAuto = numpy.zeros(indCross.shape,dtype = 'int') |
|
330 | indAuto = numpy.zeros(indCross.shape,dtype = 'int') | |
| 318 | CCValue = data[pairsCrossCorr,Pt0,:] |
|
331 | CCValue = data[pairsCrossCorr,Pt0,:] | |
| 319 | for i in range(pairsCrossCorr.size): |
|
332 | for i in range(pairsCrossCorr.size): | |
| 320 | indAuto[i,:] = numpy.abs(dataAutoCorr - CCValue[i,:]).argmin(axis = 0) |
|
333 | indAuto[i,:] = numpy.abs(dataAutoCorr - CCValue[i,:]).argmin(axis = 0) | |
| 321 |
|
334 | |||
| 322 | #Obtencion de TauCross y TauAuto |
|
335 | #Obtencion de TauCross y TauAuto | |
| 323 | tauCross = lagTRange[indCross] |
|
336 | tauCross = lagTRange[indCross] | |
| 324 | tauAuto = lagTRange[indAuto] |
|
337 | tauAuto = lagTRange[indAuto] | |
| 325 |
|
338 | |||
| 326 | Nan1, Nan2 = numpy.where(tauCross == lagTRange[0]) |
|
339 | Nan1, Nan2 = numpy.where(tauCross == lagTRange[0]) | |
| 327 |
|
340 | |||
| 328 | tauCross[Nan1,Nan2] = numpy.nan |
|
341 | tauCross[Nan1,Nan2] = numpy.nan | |
| 329 | tauAuto[Nan1,Nan2] = numpy.nan |
|
342 | tauAuto[Nan1,Nan2] = numpy.nan | |
| 330 | tau = numpy.vstack((tauCross,tauAuto)) |
|
343 | tau = numpy.vstack((tauCross,tauAuto)) | |
| 331 |
|
344 | |||
| 332 | return tau |
|
345 | return tau | |
| 333 |
|
346 | |||
| 334 |
def __calculateLag1Phase(self, data, |
|
347 | def __calculateLag1Phase(self, data, lagTRange): | |
| 335 |
data1 = stats.nanmean(data |
|
348 | data1 = stats.nanmean(data, axis = 0) | |
| 336 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 |
|
349 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 | |
| 337 |
|
350 | |||
| 338 | phase = numpy.angle(data1[lag1,:]) |
|
351 | phase = numpy.angle(data1[lag1,:]) | |
| 339 |
|
352 | |||
| 340 | return phase |
|
353 | return phase | |
| 341 | #------------------- Detect Meteors ------------------------------ |
|
|||
| 342 |
|
||||
| 343 | def MeteorDetection(self, hei_ref = None, tauindex = 0, |
|
|||
| 344 | phaseOffsets = None, |
|
|||
| 345 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, |
|
|||
| 346 | noise_timeStep = 4, noise_multiple = 4, |
|
|||
| 347 | multDet_timeLimit = 1, multDet_rangeLimit = 3, |
|
|||
| 348 | phaseThresh = 20, SNRThresh = 5, |
|
|||
| 349 | hmin = 50, hmax=150, azimuth = 0, |
|
|||
| 350 | # channel25X = 0, channel20X = 4, channelCentX = 2, |
|
|||
| 351 | # channel25Y = 1, channel20Y = 3, channelCentY = 2, |
|
|||
| 352 | channelPositions = None) : |
|
|||
| 353 |
|
|
354 | ||
|
|
355 | class SpectralFitting(Operation): | |||
| 354 |
|
|
356 | ''' | |
| 355 |
Function |
|
357 | Function GetMoments() | |
| 356 | Project developed with paper: |
|
|||
| 357 | HOLDSWORTH ET AL. 2004 |
|
|||
| 358 |
|
|
358 | ||
| 359 | Input: |
|
359 | Input: | |
| 360 | self.dataOut.data_pre |
|
360 | Output: | |
|
|
361 | Variables modified: | |||
|
|
362 | ''' | |||
| 361 |
|
|
363 | ||
| 362 | centerReceiverIndex: From the channels, which is the center receiver |
|
364 | def run(self, dataOut, getSNR = True, path=None, file=None, groupList=None): | |
| 363 |
|
|
365 | ||
| 364 | hei_ref: Height reference for the Beacon signal extraction |
|
|||
| 365 | tauindex: |
|
|||
| 366 | predefinedPhaseShifts: Predefined phase offset for the voltge signals |
|
|||
| 367 |
|
|
366 | ||
| 368 | cohDetection: Whether to user Coherent detection or not |
|
367 | if path != None: | |
| 369 | cohDet_timeStep: Coherent Detection calculation time step |
|
368 | sys.path.append(path) | |
| 370 | cohDet_thresh: Coherent Detection phase threshold to correct phases |
|
369 | self.dataOut.library = importlib.import_module(file) | |
| 371 |
|
|
370 | ||
| 372 | noise_timeStep: Noise calculation time step |
|
371 | #To be inserted as a parameter | |
| 373 | noise_multiple: Noise multiple to define signal threshold |
|
372 | groupArray = numpy.array(groupList) | |
|
|
373 | # groupArray = numpy.array([[0,1],[2,3]]) | |||
|
|
374 | self.dataOut.groupList = groupArray | |||
| 374 |
|
|
375 | ||
| 375 | multDet_timeLimit: Multiple Detection Removal time limit in seconds |
|
376 | nGroups = groupArray.shape[0] | |
| 376 | multDet_rangeLimit: Multiple Detection Removal range limit in km |
|
377 | nChannels = self.dataIn.nChannels | |
|
|
378 | nHeights=self.dataIn.heightList.size | |||
| 377 |
|
|
379 | ||
| 378 | phaseThresh: Maximum phase difference between receiver to be consider a meteor |
|
380 | #Parameters Array | |
| 379 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor |
|
381 | self.dataOut.data_param = None | |
| 380 |
|
|
382 | ||
| 381 | hmin: Minimum Height of the meteor to use it in the further wind estimations |
|
383 | #Set constants | |
| 382 | hmax: Maximum Height of the meteor to use it in the further wind estimations |
|
384 | constants = self.dataOut.library.setConstants(self.dataIn) | |
| 383 | azimuth: Azimuth angle correction |
|
385 | self.dataOut.constants = constants | |
|
|
386 | M = self.dataIn.normFactor | |||
|
|
387 | N = self.dataIn.nFFTPoints | |||
|
|
388 | ippSeconds = self.dataIn.ippSeconds | |||
|
|
389 | K = self.dataIn.nIncohInt | |||
|
|
390 | pairsArray = numpy.array(self.dataIn.pairsList) | |||
| 384 |
|
|
391 | ||
| 385 | Affected: |
|
392 | #List of possible combinations | |
| 386 | self.dataOut.data_param |
|
393 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) | |
|
|
394 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') | |||
| 387 |
|
395 | |||
| 388 | Rejection Criteria (Errors): |
|
396 | if getSNR: | |
| 389 | 0: No error; analysis OK |
|
397 | listChannels = groupArray.reshape((groupArray.size)) | |
| 390 | 1: SNR < SNR threshold |
|
398 | listChannels.sort() | |
| 391 | 2: angle of arrival (AOA) ambiguously determined |
|
399 | noise = self.dataIn.getNoise() | |
| 392 | 3: AOA estimate not feasible |
|
400 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) | |
| 393 | 4: Large difference in AOAs obtained from different antenna baselines |
|
|||
| 394 | 5: echo at start or end of time series |
|
|||
| 395 | 6: echo less than 5 examples long; too short for analysis |
|
|||
| 396 | 7: echo rise exceeds 0.3s |
|
|||
| 397 | 8: echo decay time less than twice rise time |
|
|||
| 398 | 9: large power level before echo |
|
|||
| 399 | 10: large power level after echo |
|
|||
| 400 | 11: poor fit to amplitude for estimation of decay time |
|
|||
| 401 | 12: poor fit to CCF phase variation for estimation of radial drift velocity |
|
|||
| 402 | 13: height unresolvable echo: not valid height within 70 to 110 km |
|
|||
| 403 | 14: height ambiguous echo: more then one possible height within 70 to 110 km |
|
|||
| 404 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s |
|
|||
| 405 | 16: oscilatory echo, indicating event most likely not an underdense echo |
|
|||
| 406 |
|
|
401 | ||
| 407 | 17: phase difference in meteor Reestimation |
|
402 | for i in range(nGroups): | |
|
|
403 | coord = groupArray[i,:] | |||
| 408 |
|
404 | |||
| 409 | Data Storage: |
|
405 | #Input data array | |
| 410 | Meteors for Wind Estimation (8): |
|
406 | data = self.dataIn.data_spc[coord,:,:]/(M*N) | |
| 411 | Utc Time | Range Height |
|
407 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) | |
| 412 | Azimuth Zenith errorCosDir |
|
|||
| 413 | VelRad errorVelRad |
|
|||
| 414 | Phase0 Phase1 Phase2 Phase3 |
|
|||
| 415 | TypeError |
|
|||
| 416 |
|
408 | |||
| 417 | ''' |
|
409 | #Cross Spectra data array for Covariance Matrixes | |
| 418 | #Getting Pairslist |
|
410 | ind = 0 | |
| 419 | if channelPositions == None: |
|
411 | for pairs in listComb: | |
| 420 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
412 | pairsSel = numpy.array([coord[x],coord[y]]) | |
| 421 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
413 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) | |
| 422 | meteorOps = MeteorOperations() |
|
414 | ind += 1 | |
| 423 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
415 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) | |
|
|
416 | dataCross = dataCross**2/K | |||
| 424 |
|
417 | |||
| 425 | #Get Beacon signal |
|
418 | for h in range(nHeights): | |
| 426 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
419 | # print self.dataOut.heightList[h] | |
| 427 |
|
420 | |||
| 428 | if hei_ref != None: |
|
421 | #Input | |
| 429 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
422 | d = data[:,h] | |
| 430 |
|
423 | |||
| 431 | heiRang = self.dataOut.getHeiRange() |
|
424 | #Covariance Matrix | |
|
|
425 | D = numpy.diag(d**2/K) | |||
|
|
426 | ind = 0 | |||
|
|
427 | for pairs in listComb: | |||
|
|
428 | #Coordinates in Covariance Matrix | |||
|
|
429 | x = pairs[0] | |||
|
|
430 | y = pairs[1] | |||
|
|
431 | #Channel Index | |||
|
|
432 | S12 = dataCross[ind,:,h] | |||
|
|
433 | D12 = numpy.diag(S12) | |||
|
|
434 | #Completing Covariance Matrix with Cross Spectras | |||
|
|
435 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 | |||
|
|
436 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 | |||
|
|
437 | ind += 1 | |||
|
|
438 | Dinv=numpy.linalg.inv(D) | |||
|
|
439 | L=numpy.linalg.cholesky(Dinv) | |||
|
|
440 | LT=L.T | |||
| 432 |
|
441 | |||
| 433 | # nChannel = self.dataOut.nChannels |
|
442 | dp = numpy.dot(LT,d) | |
| 434 | # for i in range(nChannel): |
|
|||
| 435 | # if i != centerReceiverIndex: |
|
|||
| 436 | # pairslist.append((centerReceiverIndex,i)) |
|
|||
| 437 |
|
443 | |||
| 438 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** |
|
444 | #Initial values | |
| 439 | # see if the user put in pre defined phase shifts |
|
445 | data_spc = self.dataIn.data_spc[coord,:,h] | |
| 440 | voltsPShift = self.dataOut.data_pre.copy() |
|
|||
| 441 |
|
446 | |||
| 442 | # if predefinedPhaseShifts != None: |
|
447 | if (h>0)and(error1[3]<5): | |
| 443 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 |
|
448 | p0 = self.dataOut.data_param[i,:,h-1] | |
| 444 | # |
|
449 | else: | |
| 445 | # # elif beaconPhaseShifts: |
|
450 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) | |
| 446 | # # #get hardware phase shifts using beacon signal |
|
|||
| 447 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) |
|
|||
| 448 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) |
|
|||
| 449 | # |
|
|||
| 450 | # else: |
|
|||
| 451 | # hardwarePhaseShifts = numpy.zeros(5) |
|
|||
| 452 | # |
|
|||
| 453 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') |
|
|||
| 454 | # for i in range(self.dataOut.data_pre.shape[0]): |
|
|||
| 455 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) |
|
|||
| 456 |
|
451 | |||
| 457 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* |
|
452 | try: | |
|
|
453 | #Least Squares | |||
|
|
454 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) | |||
|
|
455 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) | |||
|
|
456 | #Chi square error | |||
|
|
457 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) | |||
|
|
458 | #Error with Jacobian | |||
|
|
459 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) | |||
|
|
460 | except: | |||
|
|
461 | minp = p0*numpy.nan | |||
|
|
462 | error0 = numpy.nan | |||
|
|
463 | error1 = p0*numpy.nan | |||
| 458 |
|
464 | |||
| 459 | #Remove DC |
|
465 | #Save | |
| 460 | voltsDC = numpy.mean(voltsPShift,1) |
|
466 | if self.dataOut.data_param == None: | |
| 461 | voltsDC = numpy.mean(voltsDC,1) |
|
467 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan | |
| 462 | for i in range(voltsDC.shape[0]): |
|
468 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan | |
| 463 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] |
|
|||
| 464 |
|
469 | |||
| 465 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift |
|
470 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) | |
| 466 | voltsPShift = voltsPShift[:,:,:newheis[0][0]] |
|
471 | self.dataOut.data_param[i,:,h] = minp | |
|
|
472 | return | |||
| 467 |
|
|
473 | ||
| 468 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** |
|
474 | def __residFunction(self, p, dp, LT, constants): | |
| 469 | #Coherent Detection |
|
|||
| 470 | if cohDetection: |
|
|||
| 471 | #use coherent detection to get the net power |
|
|||
| 472 | cohDet_thresh = cohDet_thresh*numpy.pi/180 |
|
|||
| 473 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, self.dataOut.timeInterval, pairslist0, cohDet_thresh) |
|
|||
| 474 |
|
475 | |||
| 475 | #Non-coherent detection! |
|
476 | fm = self.dataOut.library.modelFunction(p, constants) | |
| 476 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) |
|
477 | fmp=numpy.dot(LT,fm) | |
| 477 | #********** END OF COH/NON-COH POWER CALCULATION********************** |
|
|||
| 478 |
|
478 | |||
| 479 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** |
|
479 | return dp-fmp | |
| 480 | #Get noise |
|
|||
| 481 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, self.dataOut.timeInterval) |
|
|||
| 482 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) |
|
|||
| 483 | #Get signal threshold |
|
|||
| 484 | signalThresh = noise_multiple*noise |
|
|||
| 485 | #Meteor echoes detection |
|
|||
| 486 | listMeteors = self.__findMeteors(powerNet, signalThresh) |
|
|||
| 487 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** |
|
|||
| 488 |
|
480 | |||
| 489 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** |
|
481 | def __getSNR(self, z, noise): | |
| 490 | #Parameters |
|
|||
| 491 | heiRange = self.dataOut.getHeiRange() |
|
|||
| 492 | rangeInterval = heiRange[1] - heiRange[0] |
|
|||
| 493 | rangeLimit = multDet_rangeLimit/rangeInterval |
|
|||
| 494 | timeLimit = multDet_timeLimit/self.dataOut.timeInterval |
|
|||
| 495 | #Multiple detection removals |
|
|||
| 496 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) |
|
|||
| 497 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** |
|
|||
| 498 |
|
482 | |||
| 499 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** |
|
483 | avg = numpy.average(z, axis=1) | |
| 500 | #Parameters |
|
484 | SNR = (avg.T-noise)/noise | |
| 501 | phaseThresh = phaseThresh*numpy.pi/180 |
|
485 | SNR = SNR.T | |
| 502 | thresh = [phaseThresh, noise_multiple, SNRThresh] |
|
486 | return SNR | |
| 503 | #Meteor reestimation (Errors N 1, 6, 12, 17) |
|
|||
| 504 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist0, thresh, noise, self.dataOut.timeInterval, self.dataOut.frequency) |
|
|||
| 505 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) |
|
|||
| 506 | #Estimation of decay times (Errors N 7, 8, 11) |
|
|||
| 507 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, self.dataOut.timeInterval, self.dataOut.frequency) |
|
|||
| 508 | #******************* END OF METEOR REESTIMATION ******************* |
|
|||
| 509 |
|
|
487 | ||
| 510 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** |
|
488 | def __chisq(p,chindex,hindex): | |
| 511 | #Calculating Radial Velocity (Error N 15) |
|
489 | #similar to Resid but calculates CHI**2 | |
| 512 | radialStdThresh = 10 |
|
490 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) | |
| 513 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist0, self.dataOut.timeInterval) |
|
491 | dp=numpy.dot(LT,d) | |
|
|
492 | fmp=numpy.dot(LT,fm) | |||
|
|
493 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) | |||
|
|
494 | return chisq | |||
| 514 |
|
495 | |||
| 515 | if len(listMeteors4) > 0: |
|
496 | class WindProfiler(Operation): | |
| 516 | #Setting New Array |
|
|||
| 517 | date = self.dataOut.utctime |
|
|||
| 518 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) |
|
|||
| 519 |
|
|
497 | ||
| 520 | #Correcting phase offset |
|
498 | __isConfig = False | |
| 521 | if phaseOffsets != None: |
|
|||
| 522 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
|||
| 523 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
|||
| 524 |
|
|
499 | ||
| 525 | #Second Pairslist |
|
500 | __initime = None | |
| 526 | pairsList = [] |
|
501 | __lastdatatime = None | |
| 527 | pairx = (0,1) |
|
502 | __integrationtime = None | |
| 528 | pairy = (2,3) |
|
|||
| 529 | pairsList.append(pairx) |
|
|||
| 530 | pairsList.append(pairy) |
|
|||
| 531 |
|
503 | |||
| 532 | jph = numpy.array([0,0,0,0]) |
|
504 | __buffer = None | |
| 533 | h = (hmin,hmax) |
|
|||
| 534 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) |
|
|||
| 535 |
|
505 | |||
| 536 | # #Calculate AOA (Error N 3, 4) |
|
506 | __dataReady = False | |
| 537 | # #JONES ET AL. 1998 |
|
|||
| 538 | # error = arrayParameters[:,-1] |
|
|||
| 539 | # AOAthresh = numpy.pi/8 |
|
|||
| 540 | # phases = -arrayParameters[:,9:13] |
|
|||
| 541 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) |
|
|||
| 542 | # |
|
|||
| 543 | # #Calculate Heights (Error N 13 and 14) |
|
|||
| 544 | # error = arrayParameters[:,-1] |
|
|||
| 545 | # Ranges = arrayParameters[:,2] |
|
|||
| 546 | # zenith = arrayParameters[:,5] |
|
|||
| 547 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) |
|
|||
| 548 | # error = arrayParameters[:,-1] |
|
|||
| 549 | #********************* END OF PARAMETERS CALCULATION ************************** |
|
|||
| 550 |
|
507 | |||
| 551 | #***************************+ PASS DATA TO NEXT STEP ********************** |
|
508 | __firstdata = None | |
| 552 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) |
|
|||
| 553 | self.dataOut.data_param = arrayParameters |
|
|||
| 554 |
|
509 | |||
| 555 | if arrayParameters == None: |
|
510 | n = None | |
| 556 | self.dataOut.flagNoData = True |
|
|||
| 557 | else: |
|
|||
| 558 | self.dataOut.flagNoData = True |
|
|||
| 559 |
|
511 | |||
| 560 | return |
|
512 | def __init__(self): | |
|
|
513 | Operation.__init__(self) | |||
| 561 |
|
514 | |||
| 562 | def CorrectMeteorPhases(self, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45, channelPositions = None): |
|
515 | def __calculateCosDir(self, elev, azim): | |
|
|
516 | zen = (90 - elev)*numpy.pi/180 | |||
|
|
517 | azim = azim*numpy.pi/180 | |||
|
|
518 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) | |||
|
|
519 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) | |||
| 563 |
|
520 | |||
| 564 | arrayParameters = self.dataOut.data_param |
|
521 | signX = numpy.sign(numpy.cos(azim)) | |
| 565 | pairsList = [] |
|
522 | signY = numpy.sign(numpy.sin(azim)) | |
| 566 | pairx = (0,1) |
|
|||
| 567 | pairy = (2,3) |
|
|||
| 568 | pairsList.append(pairx) |
|
|||
| 569 | pairsList.append(pairy) |
|
|||
| 570 | jph = numpy.zeros(4) |
|
|||
| 571 |
|
523 | |||
| 572 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
524 | cosDirX = numpy.copysign(cosDirX, signX) | |
| 573 | # arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
525 | cosDirY = numpy.copysign(cosDirY, signY) | |
| 574 | arrayParameters[:,8:12] = numpy.angle(numpy.exp(1j*(arrayParameters[:,8:12] + phaseOffsets))) |
|
526 | return cosDirX, cosDirY | |
| 575 |
|
|
527 | ||
| 576 | meteorOps = MeteorOperations() |
|
528 | def __calculateAngles(self, theta_x, theta_y, azimuth): | |
| 577 | if channelPositions == None: |
|
|||
| 578 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
|||
| 579 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
|||
| 580 |
|
|
529 | ||
| 581 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
530 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) | |
| 582 | h = (hmin,hmax) |
|
531 | zenith_arr = numpy.arccos(dir_cosw) | |
|
|
532 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 | |||
| 583 |
|
533 | |||
| 584 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) |
|
534 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) | |
|
|
535 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) | |||
| 585 |
|
536 | |||
| 586 | self.dataOut.data_param = arrayParameters |
|
537 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw | |
| 587 | return |
|
|||
| 588 |
|
538 | |||
| 589 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): |
|
539 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): | |
| 590 |
|
|
540 | ||
| 591 | minIndex = min(newheis[0]) |
|
541 | # | |
| 592 | maxIndex = max(newheis[0]) |
|
542 | if horOnly: | |
|
|
543 | A = numpy.c_[dir_cosu,dir_cosv] | |||
|
|
544 | else: | |||
|
|
545 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] | |||
|
|
546 | A = numpy.asmatrix(A) | |||
|
|
547 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() | |||
| 593 |
|
548 | |||
| 594 | voltage = voltage0[:,:,minIndex:maxIndex+1] |
|
549 | return A1 | |
| 595 | nLength = voltage.shape[1]/n |
|
|||
| 596 | nMin = 0 |
|
|||
| 597 | nMax = 0 |
|
|||
| 598 | phaseOffset = numpy.zeros((len(pairslist),n)) |
|
|||
| 599 |
|
550 | |||
| 600 | for i in range(n): |
|
551 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
| 601 | nMax += nLength |
|
552 | listPhi = phi.tolist() | |
| 602 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) |
|
553 | maxid = listPhi.index(max(listPhi)) | |
| 603 | phaseCCF = numpy.mean(phaseCCF, axis = 2) |
|
554 | minid = listPhi.index(min(listPhi)) | |
| 604 | phaseOffset[:,i] = phaseCCF.transpose() |
|
|||
| 605 | nMin = nMax |
|
|||
| 606 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) |
|
|||
| 607 |
|
555 | |||
| 608 | #Remove Outliers |
|
556 | rango = range(len(phi)) | |
| 609 | factor = 2 |
|
557 | # rango = numpy.delete(rango,maxid) | |
| 610 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) |
|
|||
| 611 | dw = numpy.std(wt,axis = 1) |
|
|||
| 612 | dw = dw.reshape((dw.size,1)) |
|
|||
| 613 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) |
|
|||
| 614 | phaseOffset[ind] = numpy.nan |
|
|||
| 615 | phaseOffset = stats.nanmean(phaseOffset, axis=1) |
|
|||
| 616 |
|
558 | |||
| 617 | return phaseOffset |
|
559 | heiRang1 = heiRang*math.cos(phi[maxid]) | |
|
|
560 | heiRangAux = heiRang*math.cos(phi[minid]) | |||
|
|
561 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |||
|
|
562 | heiRang1 = numpy.delete(heiRang1,indOut) | |||
| 618 |
|
563 | |||
| 619 | def __shiftPhase(self, data, phaseShift): |
|
564 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 620 | #this will shift the phase of a complex number |
|
565 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 621 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) |
|
|||
| 622 | return dataShifted |
|
|||
| 623 |
|
566 | |||
| 624 | def __estimatePhaseDifference(self, array, pairslist): |
|
567 | for i in rango: | |
| 625 | nChannel = array.shape[0] |
|
568 | x = heiRang*math.cos(phi[i]) | |
| 626 | nHeights = array.shape[2] |
|
569 | y1 = velRadial[i,:] | |
| 627 | numPairs = len(pairslist) |
|
570 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |
| 628 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) |
|
|||
| 629 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) |
|
|||
| 630 |
|
571 | |||
| 631 | #Correct phases |
|
572 | x1 = heiRang1 | |
| 632 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] |
|
573 | y11 = f1(x1) | |
| 633 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
|||
| 634 |
|
574 | |||
| 635 | if indDer[0].shape[0] > 0: |
|
575 | y2 = SNR[i,:] | |
| 636 | for i in range(indDer[0].shape[0]): |
|
576 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |
| 637 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) |
|
577 | y21 = f2(x1) | |
| 638 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi |
|
|||
| 639 |
|
578 | |||
| 640 | # for j in range(numSides): |
|
579 | velRadial1[i,:] = y11 | |
| 641 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) |
|
580 | SNR1[i,:] = y21 | |
| 642 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) |
|
|||
| 643 | # |
|
|||
| 644 | #Linear |
|
|||
| 645 | phaseInt = numpy.zeros((numPairs,1)) |
|
|||
| 646 | angAllCCF = phaseCCF[:,[0,1,3,4],0] |
|
|||
| 647 | for j in range(numPairs): |
|
|||
| 648 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) |
|
|||
| 649 | phaseInt[j] = fit[1] |
|
|||
| 650 | #Phase Differences |
|
|||
| 651 | phaseDiff = phaseInt - phaseCCF[:,2,:] |
|
|||
| 652 | phaseArrival = phaseInt.reshape(phaseInt.size) |
|
|||
| 653 |
|
581 | |||
| 654 | #Dealias |
|
582 | return heiRang1, velRadial1, SNR1 | |
| 655 | phaseArrival = numpy.angle(numpy.exp(1j*phaseArrival)) |
|
|||
| 656 | # indAlias = numpy.where(phaseArrival > numpy.pi) |
|
|||
| 657 | # phaseArrival[indAlias] -= 2*numpy.pi |
|
|||
| 658 | # indAlias = numpy.where(phaseArrival < -numpy.pi) |
|
|||
| 659 | # phaseArrival[indAlias] += 2*numpy.pi |
|
|||
| 660 |
|
583 | |||
| 661 | return phaseDiff, phaseArrival |
|
584 | def __calculateVelUVW(self, A, velRadial): | |
| 662 |
|
585 | |||
| 663 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): |
|
586 | #Operacion Matricial | |
| 664 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power |
|
587 | # velUVW = numpy.zeros((velRadial.shape[1],3)) | |
| 665 | #find the phase shifts of each channel over 1 second intervals |
|
588 | # for ind in range(velRadial.shape[1]): | |
| 666 | #only look at ranges below the beacon signal |
|
589 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) | |
| 667 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
590 | # velUVW = velUVW.transpose() | |
| 668 | numBlocks = int(volts.shape[1]/numProfPerBlock) |
|
591 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) | |
| 669 | numHeights = volts.shape[2] |
|
592 | velUVW[:,:] = numpy.dot(A,velRadial) | |
| 670 | nChannel = volts.shape[0] |
|
|||
| 671 | voltsCohDet = volts.copy() |
|
|||
| 672 |
|
593 | |||
| 673 | pairsarray = numpy.array(pairslist) |
|
|||
| 674 | indSides = pairsarray[:,1] |
|
|||
| 675 | # indSides = numpy.array(range(nChannel)) |
|
|||
| 676 | # indSides = numpy.delete(indSides, indCenter) |
|
|||
| 677 | # |
|
|||
| 678 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) |
|
|||
| 679 | listBlocks = numpy.array_split(volts, numBlocks, 1) |
|
|||
| 680 |
|
594 | |||
| 681 | startInd = 0 |
|
595 | return velUVW | |
| 682 | endInd = 0 |
|
|||
| 683 |
|
596 | |||
| 684 | for i in range(numBlocks): |
|
597 | # def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): | |
| 685 | startInd = endInd |
|
598 | def techniqueDBS(self, velRadial0, heiRang, SNR0, kwargs): | |
| 686 | endInd = endInd + listBlocks[i].shape[1] |
|
599 | """ | |
|
|
600 | Function that implements Doppler Beam Swinging (DBS) technique. | |||
| 687 |
|
|
601 | ||
| 688 | arrayBlock = listBlocks[i] |
|
602 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
| 689 | # arrayBlockCenter = listCenter[i] |
|
603 | Direction correction (if necessary), Ranges and SNR | |
| 690 |
|
|
604 | ||
| 691 | #Estimate the Phase Difference |
|
605 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 692 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) |
|
|||
| 693 | #Phase Difference RMS |
|
|||
| 694 | arrayPhaseRMS = numpy.abs(phaseDiff) |
|
|||
| 695 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) |
|
|||
| 696 | indPhase = numpy.where(phaseRMSaux==4) |
|
|||
| 697 | #Shifting |
|
|||
| 698 | if indPhase[0].shape[0] > 0: |
|
|||
| 699 | for j in range(indSides.size): |
|
|||
| 700 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) |
|
|||
| 701 | voltsCohDet[:,startInd:endInd,:] = arrayBlock |
|
|||
| 702 |
|
|
606 | ||
| 703 | return voltsCohDet |
|
607 | Parameters affected: Winds, height range, SNR | |
|
|
608 | """ | |||
| 704 |
|
609 | |||
| 705 | def __calculateCCF(self, volts, pairslist ,laglist): |
|
610 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): | |
|
|
611 | theta_x = numpy.array(kwargs['dirCosx']) | |||
|
|
612 | theta_y = numpy.array(kwargs['dirCosy']) | |||
|
|
613 | else: | |||
|
|
614 | elev = numpy.array(kwargs['elevation']) | |||
|
|
615 | azim = numpy.array(kwargs['azimuth']) | |||
|
|
616 | theta_x, theta_y = self.__calculateCosDir(elev, azim) | |||
|
|
617 | azimuth = kwargs['correctAzimuth'] | |||
|
|
618 | if kwargs.has_key('horizontalOnly'): | |||
|
|
619 | horizontalOnly = kwargs['horizontalOnly'] | |||
|
|
620 | else: horizontalOnly = False | |||
|
|
621 | if kwargs.has_key('correctFactor'): | |||
|
|
622 | correctFactor = kwargs['correctFactor'] | |||
|
|
623 | else: correctFactor = 1 | |||
|
|
624 | if kwargs.has_key('channelList'): | |||
|
|
625 | channelList = kwargs['channelList'] | |||
|
|
626 | if len(channelList) == 2: | |||
|
|
627 | horizontalOnly = True | |||
|
|
628 | arrayChannel = numpy.array(channelList) | |||
|
|
629 | param = param[arrayChannel,:,:] | |||
|
|
630 | theta_x = theta_x[arrayChannel] | |||
|
|
631 | theta_y = theta_y[arrayChannel] | |||
| 706 |
|
|
632 | ||
| 707 | nHeights = volts.shape[2] |
|
633 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(theta_x, theta_y, azimuth) | |
| 708 | nPoints = volts.shape[1] |
|
634 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correctFactor*velRadial0, SNR0) | |
| 709 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') |
|
635 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) | |
| 710 |
|
636 | |||
| 711 | for i in range(len(pairslist)): |
|
637 | #Calculo de Componentes de la velocidad con DBS | |
| 712 | volts1 = volts[pairslist[i][0]] |
|
638 | winds = self.__calculateVelUVW(A,velRadial1) | |
| 713 | volts2 = volts[pairslist[i][1]] |
|
|||
| 714 |
|
|
639 | ||
| 715 | for t in range(len(laglist)): |
|
640 | return winds, heiRang1, SNR1 | |
| 716 | idxT = laglist[t] |
|
|||
| 717 | if idxT >= 0: |
|
|||
| 718 | vStacked = numpy.vstack((volts2[idxT:,:], |
|
|||
| 719 | numpy.zeros((idxT, nHeights),dtype='complex'))) |
|
|||
| 720 | else: |
|
|||
| 721 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), |
|
|||
| 722 | volts2[:(nPoints + idxT),:])) |
|
|||
| 723 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) |
|
|||
| 724 |
|
641 | |||
| 725 | vStacked = None |
|
642 | def __calculateDistance(self, posx, posy, pairsCrossCorr, pairsList, pairs, azimuth = None): | |
| 726 | return voltsCCF |
|
|||
| 727 |
|
643 | |||
| 728 | def __getNoise(self, power, timeSegment, timeInterval): |
|
644 | posx = numpy.asarray(posx) | |
| 729 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
645 | posy = numpy.asarray(posy) | |
| 730 | numBlocks = int(power.shape[0]/numProfPerBlock) |
|
|||
| 731 | numHeights = power.shape[1] |
|
|||
| 732 |
|
646 | |||
| 733 | listPower = numpy.array_split(power, numBlocks, 0) |
|
647 | #Rotacion Inversa para alinear con el azimuth | |
| 734 | noise = numpy.zeros((power.shape[0], power.shape[1])) |
|
648 | if azimuth!= None: | |
| 735 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) |
|
649 | azimuth = azimuth*math.pi/180 | |
|
|
650 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) | |||
|
|
651 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) | |||
|
|
652 | else: | |||
|
|
653 | posx1 = posx | |||
|
|
654 | posy1 = posy | |||
| 736 |
|
655 | |||
| 737 | startInd = 0 |
|
656 | #Calculo de Distancias | |
| 738 | endInd = 0 |
|
657 | distx = numpy.zeros(pairsCrossCorr.size) | |
|
|
658 | disty = numpy.zeros(pairsCrossCorr.size) | |||
|
|
659 | dist = numpy.zeros(pairsCrossCorr.size) | |||
|
|
660 | ang = numpy.zeros(pairsCrossCorr.size) | |||
| 739 |
|
661 | |||
| 740 | for i in range(numBlocks): #split por canal |
|
662 | for i in range(pairsCrossCorr.size): | |
| 741 | startInd = endInd |
|
663 | distx[i] = posx1[pairsList[pairsCrossCorr[i]][1]] - posx1[pairsList[pairsCrossCorr[i]][0]] | |
| 742 | endInd = endInd + listPower[i].shape[0] |
|
664 | disty[i] = posy1[pairsList[pairsCrossCorr[i]][1]] - posy1[pairsList[pairsCrossCorr[i]][0]] | |
|
|
665 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) | |||
|
|
666 | ang[i] = numpy.arctan2(disty[i],distx[i]) | |||
|
|
667 | #Calculo de Matrices | |||
|
|
668 | nPairs = len(pairs) | |||
|
|
669 | ang1 = numpy.zeros((nPairs, 2, 1)) | |||
|
|
670 | dist1 = numpy.zeros((nPairs, 2, 1)) | |||
| 743 |
|
|
671 | ||
| 744 | arrayBlock = listPower[i] |
|
672 | for j in range(nPairs): | |
| 745 | noiseAux = numpy.mean(arrayBlock, 0) |
|
673 | dist1[j,0,0] = dist[pairs[j][0]] | |
| 746 | # noiseAux = numpy.median(noiseAux) |
|
674 | dist1[j,1,0] = dist[pairs[j][1]] | |
| 747 | # noiseAux = numpy.mean(arrayBlock) |
|
675 | ang1[j,0,0] = ang[pairs[j][0]] | |
| 748 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux |
|
676 | ang1[j,1,0] = ang[pairs[j][1]] | |
| 749 |
|
677 | |||
| 750 | noiseAux1 = numpy.mean(arrayBlock) |
|
678 | return distx,disty, dist1,ang1 | |
| 751 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 |
|
|||
| 752 |
|
679 | |||
| 753 | return noise, noise1 |
|
680 | def __calculateVelVer(self, phase, lagTRange, _lambda): | |
| 754 |
|
681 | |||
| 755 | def __findMeteors(self, power, thresh): |
|
682 | Ts = lagTRange[1] - lagTRange[0] | |
| 756 | nProf = power.shape[0] |
|
683 | velW = -_lambda*phase/(4*math.pi*Ts) | |
| 757 | nHeights = power.shape[1] |
|
|||
| 758 | listMeteors = [] |
|
|||
| 759 |
|
684 | |||
| 760 | for i in range(nHeights): |
|
685 | return velW | |
| 761 | powerAux = power[:,i] |
|
|||
| 762 | threshAux = thresh[:,i] |
|
|||
| 763 |
|
686 | |||
| 764 | indUPthresh = numpy.where(powerAux > threshAux)[0] |
|
687 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): | |
| 765 | indDNthresh = numpy.where(powerAux <= threshAux)[0] |
|
688 | nPairs = tau1.shape[0] | |
|
|
689 | vel = numpy.zeros((nPairs,3,tau1.shape[2])) | |||
| 766 |
|
|
690 | ||
| 767 | j = 0 |
|
691 | angCos = numpy.cos(ang) | |
|
|
692 | angSin = numpy.sin(ang) | |||
| 768 |
|
|
693 | ||
| 769 | while (j < indUPthresh.size - 2): |
|
694 | vel0 = dist*tau1/(2*tau2**2) | |
| 770 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): |
|
695 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) | |
| 771 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) |
|
696 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) | |
| 772 | indDNthresh = indDNthresh[indDNAux] |
|
|||
| 773 |
|
697 | |||
| 774 | if (indDNthresh.size > 0): |
|
698 | ind = numpy.where(numpy.isinf(vel)) | |
| 775 | indEnd = indDNthresh[0] - 1 |
|
699 | vel[ind] = numpy.nan | |
| 776 | indInit = indUPthresh[j] |
|
|||
| 777 |
|
|
700 | ||
| 778 | meteor = powerAux[indInit:indEnd + 1] |
|
701 | return vel | |
| 779 | indPeak = meteor.argmax() + indInit |
|
|||
| 780 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) |
|
|||
| 781 |
|
702 | |||
| 782 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! |
|
703 | def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 783 | j = numpy.where(indUPthresh == indEnd)[0] + 1 |
|
|||
| 784 | else: j+=1 |
|
|||
| 785 | else: j+=1 |
|
|||
| 786 |
|
704 | |||
| 787 | return listMeteors |
|
705 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 788 |
|
706 | |||
| 789 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): |
|
707 | for l in range(len(pairsList)): | |
|
|
708 | firstChannel = pairsList[l][0] | |||
|
|
709 | secondChannel = pairsList[l][1] | |||
| 790 |
|
710 | |||
| 791 | arrayMeteors = numpy.asarray(listMeteors) |
|
711 | #Obteniendo pares de Autocorrelacion | |
| 792 | listMeteors1 = [] |
|
712 | if firstChannel == secondChannel: | |
|
|
713 | pairsAutoCorr[firstChannel] = int(l) | |||
| 793 |
|
714 | |||
| 794 | while arrayMeteors.shape[0] > 0: |
|
715 | pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 795 | FLAs = arrayMeteors[:,4] |
|
|||
| 796 | maxFLA = FLAs.argmax() |
|
|||
| 797 | listMeteors1.append(arrayMeteors[maxFLA,:]) |
|
|||
| 798 |
|
|
716 | ||
| 799 | MeteorInitTime = arrayMeteors[maxFLA,1] |
|
717 | pairsCrossCorr = range(len(pairsList)) | |
| 800 | MeteorEndTime = arrayMeteors[maxFLA,3] |
|
718 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 801 | MeteorHeight = arrayMeteors[maxFLA,0] |
|
|||
| 802 |
|
|
719 | ||
| 803 | #Check neighborhood |
|
720 | return pairsAutoCorr, pairsCrossCorr | |
| 804 | maxHeightIndex = MeteorHeight + rangeLimit |
|
|||
| 805 | minHeightIndex = MeteorHeight - rangeLimit |
|
|||
| 806 | minTimeIndex = MeteorInitTime - timeLimit |
|
|||
| 807 | maxTimeIndex = MeteorEndTime + timeLimit |
|
|||
| 808 |
|
721 | |||
| 809 | #Check Heights |
|
722 | def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): | |
| 810 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) |
|
723 | """ | |
| 811 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) |
|
724 | Function that implements Spaced Antenna (SA) technique. | |
| 812 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) |
|
|||
| 813 |
|
|
725 | ||
| 814 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) |
|
726 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
|
|
727 | Direction correction (if necessary), Ranges and SNR | |||
| 815 |
|
|
728 | ||
| 816 | return listMeteors1 |
|
729 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 817 |
|
730 | |||
| 818 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): |
|
731 | Parameters affected: Winds | |
| 819 | numHeights = volts.shape[2] |
|
732 | """ | |
| 820 | nChannel = volts.shape[0] |
|
733 | #Cross Correlation pairs obtained | |
|
|
734 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) | |||
|
|
735 | pairsArray = numpy.array(pairsList)[pairsCrossCorr] | |||
|
|
736 | pairsSelArray = numpy.array(pairsSelected) | |||
|
|
737 | pairs = [] | |||
| 821 |
|
738 | |||
| 822 | thresholdPhase = thresh[0] |
|
739 | #Wind estimation pairs obtained | |
| 823 | thresholdNoise = thresh[1] |
|
740 | for i in range(pairsSelArray.shape[0]/2): | |
| 824 | thresholdDB = float(thresh[2]) |
|
741 | ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] | |
|
|
742 | ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] | |||
|
|
743 | pairs.append((ind1,ind2)) | |||
| 825 |
|
744 | |||
| 826 | thresholdDB1 = 10**(thresholdDB/10) |
|
745 | indtau = tau.shape[0]/2 | |
| 827 | pairsarray = numpy.array(pairslist) |
|
746 | tau1 = tau[:indtau,:] | |
| 828 | indSides = pairsarray[:,1] |
|
747 | tau2 = tau[indtau:-1,:] | |
|
|
748 | tau1 = tau1[pairs,:] | |||
|
|
749 | tau2 = tau2[pairs,:] | |||
|
|
750 | phase1 = tau[-1,:] | |||
| 829 |
|
751 | |||
| 830 | pairslist1 = list(pairslist) |
|
752 | #--------------------------------------------------------------------- | |
| 831 | pairslist1.append((0,1)) |
|
753 | #Metodo Directo | |
| 832 | pairslist1.append((3,4)) |
|
754 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairsCrossCorr, pairsList, pairs,azimuth) | |
|
|
755 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) | |||
|
|
756 | winds = stats.nanmean(winds, axis=0) | |||
|
|
757 | #--------------------------------------------------------------------- | |||
|
|
758 | #Metodo General | |||
|
|
759 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) | |||
|
|
760 | # #Calculo Coeficientes de Funcion de Correlacion | |||
|
|
761 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) | |||
|
|
762 | # #Calculo de Velocidades | |||
|
|
763 | # winds = self.calculateVelUV(F,G,A,B,H) | |||
| 833 |
|
764 | |||
| 834 | listMeteors1 = [] |
|
765 | #--------------------------------------------------------------------- | |
| 835 | listPowerSeries = [] |
|
766 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) | |
| 836 | listVoltageSeries = [] |
|
767 | winds = correctFactor*winds | |
| 837 | #volts has the war data |
|
768 | return winds | |
| 838 |
|
|
769 | ||
| 839 | if frequency == 30e6: |
|
770 | def __checkTime(self, currentTime, paramInterval, outputInterval): | |
| 840 | timeLag = 45*10**-3 |
|
|||
| 841 | else: |
|
|||
| 842 | timeLag = 15*10**-3 |
|
|||
| 843 | lag = numpy.ceil(timeLag/timeInterval) |
|
|||
| 844 |
|
771 | |||
| 845 | for i in range(len(listMeteors)): |
|
772 | dataTime = currentTime + paramInterval | |
|
|
773 | deltaTime = dataTime - self.__initime | |||
| 846 |
|
|
774 | ||
| 847 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### |
|
775 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 848 | meteorAux = numpy.zeros(16) |
|
776 | self.__dataReady = True | |
|
|
777 | return | |||
| 849 |
|
778 | |||
| 850 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) |
|
779 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): | |
| 851 | mHeight = listMeteors[i][0] |
|
780 | ''' | |
| 852 | mStart = listMeteors[i][1] |
|
781 | Function that implements winds estimation technique with detected meteors. | |
| 853 | mPeak = listMeteors[i][2] |
|
|||
| 854 | mEnd = listMeteors[i][3] |
|
|||
| 855 |
|
|
782 | ||
| 856 | #get the volt data between the start and end times of the meteor |
|
783 | Input: Detected meteors, Minimum meteor quantity to wind estimation | |
| 857 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] |
|
|||
| 858 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
|||
| 859 |
|
|
784 | ||
| 860 | #3.6. Phase Difference estimation |
|
785 | Output: Winds estimation (Zonal and Meridional) | |
| 861 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) |
|
|||
| 862 |
|
||||
| 863 | #3.7. Phase difference removal & meteor start, peak and end times reestimated |
|
|||
| 864 | #meteorVolts0.- all Channels, all Profiles |
|
|||
| 865 | meteorVolts0 = volts[:,:,mHeight] |
|
|||
| 866 | meteorThresh = noise[:,mHeight]*thresholdNoise |
|
|||
| 867 | meteorNoise = noise[:,mHeight] |
|
|||
| 868 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting |
|
|||
| 869 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power |
|
|||
| 870 |
|
||||
| 871 | #Times reestimation |
|
|||
| 872 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] |
|
|||
| 873 | if mStart1.size > 0: |
|
|||
| 874 | mStart1 = mStart1[-1] + 1 |
|
|||
| 875 |
|
||||
| 876 | else: |
|
|||
| 877 | mStart1 = mPeak |
|
|||
| 878 |
|
|
786 | ||
| 879 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 |
|
787 | Parameters affected: Winds | |
| 880 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] |
|
788 | ''' | |
| 881 | if mEndDecayTime1.size == 0: |
|
789 | # print arrayMeteor.shape | |
| 882 | mEndDecayTime1 = powerNet0.size |
|
790 | #Settings | |
| 883 | else: |
|
791 | nInt = (heightMax - heightMin)/2 | |
| 884 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 |
|
792 | # print nInt | |
| 885 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() |
|
793 | nInt = int(nInt) | |
|
|
794 | # print nInt | |||
|
|
795 | winds = numpy.zeros((2,nInt))*numpy.nan | |||
| 886 |
|
|
796 | ||
| 887 | #meteorVolts1.- all Channels, from start to end |
|
797 | #Filter errors | |
| 888 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] |
|
798 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] | |
| 889 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] |
|
799 | finalMeteor = arrayMeteor[error,:] | |
| 890 | if meteorVolts2.shape[1] == 0: |
|
|||
| 891 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] |
|
|||
| 892 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) |
|
|||
| 893 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) |
|
|||
| 894 | ##################### END PARAMETERS REESTIMATION ######################### |
|
|||
| 895 |
|
|
800 | ||
| 896 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## |
|
801 | #Meteor Histogram | |
| 897 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis |
|
802 | finalHeights = finalMeteor[:,2] | |
| 898 | if meteorVolts2.shape[1] > 0: |
|
803 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) | |
| 899 | #Phase Difference re-estimation |
|
804 | nMeteorsPerI = hist[0] | |
| 900 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation |
|
805 | heightPerI = hist[1] | |
| 901 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) |
|
|||
| 902 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) |
|
|||
| 903 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) |
|
|||
| 904 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting |
|
|||
| 905 |
|
|
806 | ||
| 906 | #Phase Difference RMS |
|
807 | #Sort of meteors | |
| 907 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) |
|
808 | indSort = finalHeights.argsort() | |
| 908 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) |
|
809 | finalMeteor2 = finalMeteor[indSort,:] | |
| 909 | #Data from Meteor |
|
|||
| 910 | mPeak1 = powerNet1.argmax() + mStart1 |
|
|||
| 911 | mPeakPower1 = powerNet1.max() |
|
|||
| 912 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) |
|
|||
| 913 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux |
|
|||
| 914 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) |
|
|||
| 915 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) |
|
|||
| 916 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] |
|
|||
| 917 | #Vectorize |
|
|||
| 918 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] |
|
|||
| 919 | meteorAux[7:11] = phaseDiffint[0:4] |
|
|||
| 920 |
|
|
810 | ||
| 921 | #Rejection Criterions |
|
811 | # Calculating winds | |
| 922 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation |
|
812 | ind1 = 0 | |
| 923 | meteorAux[-1] = 17 |
|
813 | ind2 = 0 | |
| 924 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB |
|
|||
| 925 | meteorAux[-1] = 1 |
|
|||
| 926 |
|
|
814 | ||
|
|
815 | for i in range(nInt): | |||
|
|
816 | nMet = nMeteorsPerI[i] | |||
|
|
817 | ind1 = ind2 | |||
|
|
818 | ind2 = ind1 + nMet | |||
| 927 |
|
819 | |||
| 928 | else: |
|
820 | meteorAux = finalMeteor2[ind1:ind2,:] | |
| 929 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] |
|
|||
| 930 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis |
|
|||
| 931 | PowerSeries = 0 |
|
|||
| 932 |
|
|
821 | ||
| 933 | listMeteors1.append(meteorAux) |
|
822 | if meteorAux.shape[0] >= meteorThresh: | |
| 934 | listPowerSeries.append(PowerSeries) |
|
823 | vel = meteorAux[:, 6] | |
| 935 | listVoltageSeries.append(meteorVolts1) |
|
824 | zen = meteorAux[:, 4]*numpy.pi/180 | |
|
|
825 | azim = meteorAux[:, 3]*numpy.pi/180 | |||
| 936 |
|
|
826 | ||
| 937 | return listMeteors1, listPowerSeries, listVoltageSeries |
|
827 | n = numpy.cos(zen) | |
|
|
828 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) | |||
|
|
829 | # l = m*numpy.tan(azim) | |||
|
|
830 | l = numpy.sin(zen)*numpy.sin(azim) | |||
|
|
831 | m = numpy.sin(zen)*numpy.cos(azim) | |||
| 938 |
|
832 | |||
| 939 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): |
|
833 | A = numpy.vstack((l, m)).transpose() | |
|
|
834 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) | |||
|
|
835 | windsAux = numpy.dot(A1, vel) | |||
| 940 |
|
836 | |||
| 941 | threshError = 10 |
|
837 | winds[0,i] = windsAux[0] | |
| 942 | #Depending if it is 30 or 50 MHz |
|
838 | winds[1,i] = windsAux[1] | |
| 943 | if frequency == 30e6: |
|
|||
| 944 | timeLag = 45*10**-3 |
|
|||
| 945 | else: |
|
|||
| 946 | timeLag = 15*10**-3 |
|
|||
| 947 | lag = numpy.ceil(timeLag/timeInterval) |
|
|||
| 948 |
|
839 | |||
| 949 | listMeteors1 = [] |
|
840 | return winds, heightPerI[:-1] | |
| 950 |
|
|
841 | ||
| 951 | for i in range(len(listMeteors)): |
|
842 | def techniqueNSM_SA(self, **kwargs): | |
| 952 | meteorPower = listPower[i] |
|
843 | metArray = kwargs['metArray'] | |
| 953 | meteorAux = listMeteors[i] |
|
844 | heightList = kwargs['heightList'] | |
|
|
845 | timeList = kwargs['timeList'] | |||
| 954 |
|
|
846 | ||
| 955 | if meteorAux[-1] == 0: |
|
847 | rx_location = kwargs['rx_location'] | |
|
|
848 | groupList = kwargs['groupList'] | |||
|
|
849 | azimuth = kwargs['azimuth'] | |||
|
|
850 | dfactor = kwargs['dfactor'] | |||
|
|
851 | k = kwargs['k'] | |||
| 956 |
|
852 | |||
| 957 | try: |
|
853 | azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth) | |
| 958 | indmax = meteorPower.argmax() |
|
854 | d = dist*dfactor | |
| 959 | indlag = indmax + lag |
|
855 | #Phase calculation | |
|
|
856 | metArray1 = self.__getPhaseSlope(metArray, heightList, timeList) | |||
| 960 |
|
857 | |||
| 961 | y = meteorPower[indlag:] |
|
858 | metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities | |
| 962 | x = numpy.arange(0, y.size)*timeLag |
|
|||
| 963 |
|
859 | |||
| 964 | #first guess |
|
860 | velEst = numpy.zeros((heightList.size,2))*numpy.nan | |
| 965 | a = y[0] |
|
861 | azimuth1 = azimuth1*numpy.pi/180 | |
| 966 | tau = timeLag |
|
|||
| 967 | #exponential fit |
|
|||
| 968 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) |
|
|||
| 969 | y1 = self.__exponential_function(x, *popt) |
|
|||
| 970 | #error estimation |
|
|||
| 971 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) |
|
|||
| 972 |
|
862 | |||
| 973 | decayTime = popt[1] |
|
863 | for i in range(heightList.size): | |
| 974 | riseTime = indmax*timeInterval |
|
864 | h = heightList[i] | |
| 975 | meteorAux[11:13] = [decayTime, error] |
|
865 | indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0] | |
|
|
866 | metHeight = metArray1[indH,:] | |||
|
|
867 | if metHeight.shape[0] >= 2: | |||
|
|
868 | velAux = numpy.asmatrix(metHeight[:,-2]).T #Radial Velocities | |||
|
|
869 | iazim = metHeight[:,1].astype(int) | |||
|
|
870 | azimAux = numpy.asmatrix(azimuth1[iazim]).T #Azimuths | |||
|
|
871 | A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux))) | |||
|
|
872 | A = numpy.asmatrix(A) | |||
|
|
873 | A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose() | |||
|
|
874 | velHor = numpy.dot(A1,velAux) | |||
| 976 |
|
|
875 | ||
| 977 | #Table items 7, 8 and 11 |
|
876 | velEst[i,:] = numpy.squeeze(velHor) | |
| 978 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s |
|
877 | return velEst | |
| 979 | meteorAux[-1] = 7 |
|
|||
| 980 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time |
|
|||
| 981 | meteorAux[-1] = 8 |
|
|||
| 982 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time |
|
|||
| 983 | meteorAux[-1] = 11 |
|
|||
| 984 |
|
878 | |||
|
|
879 | def __getPhaseSlope(self, metArray, heightList, timeList): | |||
|
|
880 | meteorList = [] | |||
|
|
881 | #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2 | |||
|
|
882 | #Putting back together the meteor matrix | |||
|
|
883 | utctime = metArray[:,0] | |||
|
|
884 | uniqueTime = numpy.unique(utctime) | |||
| 985 |
|
885 | |||
| 986 | except: |
|
886 | phaseDerThresh = 0.5 | |
| 987 | meteorAux[-1] = 11 |
|
887 | ippSeconds = timeList[1] - timeList[0] | |
|
|
888 | sec = numpy.where(timeList>1)[0][0] | |||
|
|
889 | nPairs = metArray.shape[1] - 6 | |||
|
|
890 | nHeights = len(heightList) | |||
| 988 |
|
|
891 | ||
|
|
892 | for t in uniqueTime: | |||
|
|
893 | metArray1 = metArray[utctime==t,:] | |||
|
|
894 | # phaseDerThresh = numpy.pi/4 #reducir Phase thresh | |||
|
|
895 | tmet = metArray1[:,1].astype(int) | |||
|
|
896 | hmet = metArray1[:,2].astype(int) | |||
| 989 |
|
897 | |||
| 990 | listMeteors1.append(meteorAux) |
|
898 | metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1)) | |
|
|
899 | metPhase[:,:] = numpy.nan | |||
|
|
900 | metPhase[:,hmet,tmet] = metArray1[:,6:].T | |||
| 991 |
|
901 | |||
| 992 | return listMeteors1 |
|
902 | #Delete short trails | |
|
|
903 | metBool = ~numpy.isnan(metPhase[0,:,:]) | |||
|
|
904 | heightVect = numpy.sum(metBool, axis = 1) | |||
|
|
905 | metBool[heightVect<sec,:] = False | |||
|
|
906 | metPhase[:,heightVect<sec,:] = numpy.nan | |||
| 993 |
|
907 | |||
| 994 | #Exponential Function |
|
908 | #Derivative | |
|
|
909 | metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1]) | |||
|
|
910 | phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh)) | |||
|
|
911 | metPhase[phDerAux] = numpy.nan | |||
| 995 |
|
912 | |||
| 996 | def __exponential_function(self, x, a, tau): |
|
913 | #--------------------------METEOR DETECTION ----------------------------------------- | |
| 997 | y = a*numpy.exp(-x/tau) |
|
914 | indMet = numpy.where(numpy.any(metBool,axis=1))[0] | |
| 998 | return y |
|
|||
| 999 |
|
915 | |||
| 1000 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): |
|
916 | for p in numpy.arange(nPairs): | |
|
|
917 | phase = metPhase[p,:,:] | |||
|
|
918 | phDer = metDer[p,:,:] | |||
| 1001 |
|
919 | |||
| 1002 | pairslist1 = list(pairslist) |
|
920 | for h in indMet: | |
| 1003 | pairslist1.append((0,1)) |
|
921 | height = heightList[h] | |
| 1004 | pairslist1.append((3,4)) |
|
922 | phase1 = phase[h,:] #82 | |
| 1005 | numPairs = len(pairslist1) |
|
923 | phDer1 = phDer[h,:] | |
| 1006 | #Time Lag |
|
|||
| 1007 | timeLag = 45*10**-3 |
|
|||
| 1008 | c = 3e8 |
|
|||
| 1009 | lag = numpy.ceil(timeLag/timeInterval) |
|
|||
| 1010 | freq = 30e6 |
|
|||
| 1011 |
|
924 | |||
| 1012 | listMeteors1 = [] |
|
925 | phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)]) #Unwrap | |
| 1013 |
|
926 | |||
| 1014 | for i in range(len(listMeteors)): |
|
927 | indValid = numpy.where(~numpy.isnan(phase1))[0] | |
| 1015 | meteorAux = listMeteors[i] |
|
928 | initMet = indValid[0] | |
| 1016 | if meteorAux[-1] == 0: |
|
929 | endMet = 0 | |
| 1017 | mStart = listMeteors[i][1] |
|
|||
| 1018 | mPeak = listMeteors[i][2] |
|
|||
| 1019 | mLag = mPeak - mStart + lag |
|
|||
| 1020 |
|
930 | |||
| 1021 | #get the volt data between the start and end times of the meteor |
|
931 | for i in range(len(indValid)-1): | |
| 1022 | meteorVolts = listVolts[i] |
|
|||
| 1023 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
|||
| 1024 |
|
932 | |||
| 1025 | #Get CCF |
|
933 | #Time difference | |
| 1026 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) |
|
934 | inow = indValid[i] | |
|
|
935 | inext = indValid[i+1] | |||
|
|
936 | idiff = inext - inow | |||
|
|
937 | #Phase difference | |||
|
|
938 | phDiff = numpy.abs(phase1[inext] - phase1[inow]) | |||
| 1027 |
|
939 | |||
| 1028 | #Method 2 |
|
940 | if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]: #End of Meteor | |
| 1029 | slopes = numpy.zeros(numPairs) |
|
941 | sizeTrail = inow - initMet + 1 | |
| 1030 | time = numpy.array([-2,-1,1,2])*timeInterval |
|
942 | if sizeTrail>3*sec: #Too short meteors | |
| 1031 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) |
|
943 | x = numpy.arange(initMet,inow+1)*ippSeconds | |
|
|
944 | y = phase1[initMet:inow+1] | |||
|
|
945 | ynnan = ~numpy.isnan(y) | |||
|
|
946 | x = x[ynnan] | |||
|
|
947 | y = y[ynnan] | |||
|
|
948 | slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) | |||
|
|
949 | ylin = x*slope + intercept | |||
|
|
950 | rsq = r_value**2 | |||
|
|
951 | if rsq > 0.5: | |||
|
|
952 | vel = slope#*height*1000/(k*d) | |||
|
|
953 | estAux = numpy.array([utctime,p,height, vel, rsq]) | |||
|
|
954 | meteorList.append(estAux) | |||
|
|
955 | initMet = inext | |||
|
|
956 | metArray2 = numpy.array(meteorList) | |||
| 1032 |
|
|
957 | ||
| 1033 | #Correct phases |
|
958 | return metArray2 | |
| 1034 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] |
|
|||
| 1035 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
|||
| 1036 |
|
959 | |||
| 1037 | if indDer[0].shape[0] > 0: |
|
960 | def __calculateAzimuth1(self, rx_location, pairslist, azimuth0): | |
| 1038 | for i in range(indDer[0].shape[0]): |
|
|||
| 1039 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) |
|
|||
| 1040 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi |
|
|||
| 1041 |
|
961 | |||
| 1042 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) |
|
962 | azimuth1 = numpy.zeros(len(pairslist)) | |
| 1043 | for j in range(numPairs): |
|
963 | dist = numpy.zeros(len(pairslist)) | |
| 1044 | fit = stats.linregress(time, angAllCCF[j,:]) |
|
|||
| 1045 | slopes[j] = fit[0] |
|
|||
| 1046 |
|
|
964 | ||
| 1047 | #Remove Outlier |
|
965 | for i in range(len(rx_location)): | |
| 1048 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
966 | ch0 = pairslist[i][0] | |
| 1049 | # slopes = numpy.delete(slopes,indOut) |
|
967 | ch1 = pairslist[i][1] | |
| 1050 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
|||
| 1051 | # slopes = numpy.delete(slopes,indOut) |
|
|||
| 1052 |
|
|
968 | ||
| 1053 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) |
|
969 | diffX = rx_location[ch0][0] - rx_location[ch1][0] | |
| 1054 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) |
|
970 | diffY = rx_location[ch0][1] - rx_location[ch1][1] | |
| 1055 | meteorAux[-2] = radialError |
|
971 | azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi | |
| 1056 | meteorAux[-3] = radialVelocity |
|
972 | dist[i] = numpy.sqrt(diffX**2 + diffY**2) | |
| 1057 |
|
|
973 | ||
| 1058 | #Setting Error |
|
974 | azimuth1 -= azimuth0 | |
| 1059 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s |
|
975 | return azimuth1, dist | |
| 1060 | if numpy.abs(radialVelocity) > 200: |
|
|||
| 1061 | meteorAux[-1] = 15 |
|
|||
| 1062 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity |
|
|||
| 1063 | elif radialError > radialStdThresh: |
|
|||
| 1064 | meteorAux[-1] = 12 |
|
|||
| 1065 |
|
976 | |||
| 1066 | listMeteors1.append(meteorAux) |
|
977 | def techniqueNSM_DBS(self, **kwargs): | |
| 1067 | return listMeteors1 |
|
978 | metArray = kwargs['metArray'] | |
|
|
979 | heightList = kwargs['heightList'] | |||
|
|
980 | timeList = kwargs['timeList'] | |||
|
|
981 | zenithList = kwargs['zenithList'] | |||
|
|
982 | nChan = numpy.max(cmet) + 1 | |||
|
|
983 | nHeights = len(heightList) | |||
| 1068 |
|
984 | |||
| 1069 | def __setNewArrays(self, listMeteors, date, heiRang): |
|
985 | utctime = metArray[:,0] | |
|
|
986 | cmet = metArray[:,1] | |||
|
|
987 | hmet = metArray1[:,3].astype(int) | |||
|
|
988 | h1met = heightList[hmet]*zenithList[cmet] | |||
|
|
989 | vmet = metArray1[:,5] | |||
| 1070 |
|
990 | |||
| 1071 | #New arrays |
|
991 | for i in range(nHeights - 1): | |
| 1072 | arrayMeteors = numpy.array(listMeteors) |
|
992 | hmin = heightList[i] | |
| 1073 | arrayParameters = numpy.zeros((len(listMeteors), 13)) |
|
993 | hmax = heightList[i + 1] | |
| 1074 |
|
994 | |||
| 1075 | #Date inclusion |
|
995 | vthisH = vmet[(h1met>=hmin) & (h1met<hmax)] | |
| 1076 | # date = re.findall(r'\((.*?)\)', date) |
|
|||
| 1077 | # date = date[0].split(',') |
|
|||
| 1078 | # date = map(int, date) |
|
|||
| 1079 | # |
|
|||
| 1080 | # if len(date)<6: |
|
|||
| 1081 | # date.append(0) |
|
|||
| 1082 | # |
|
|||
| 1083 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] |
|
|||
| 1084 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) |
|
|||
| 1085 | arrayDate = numpy.tile(date, (len(listMeteors))) |
|
|||
| 1086 |
|
996 | |||
| 1087 | #Meteor array |
|
|||
| 1088 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] |
|
|||
| 1089 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) |
|
|||
| 1090 |
|
997 | |||
| 1091 | #Parameters Array |
|
|||
| 1092 | arrayParameters[:,0] = arrayDate #Date |
|
|||
| 1093 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range |
|
|||
| 1094 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error |
|
|||
| 1095 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases |
|
|||
| 1096 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error |
|
|||
| 1097 |
|
998 | |||
|
|
999 | return data_output | |||
| 1098 |
|
1000 | |||
| 1099 | return arrayParameters |
|
1001 | def run(self, dataOut, technique, **kwargs): | |
| 1100 |
|
1002 | |||
| 1101 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): |
|
1003 | param = dataOut.data_param | |
| 1102 | # |
|
1004 | if dataOut.abscissaList != None: | |
| 1103 | # arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
1005 | absc = dataOut.abscissaList[:-1] | |
| 1104 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) |
|
1006 | noise = dataOut.noise | |
| 1105 | # |
|
1007 | heightList = dataOut.heightList | |
| 1106 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
1008 | SNR = dataOut.data_SNR | |
| 1107 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
|||
| 1108 | # arrayAOA[:,2] = cosDirError |
|
|||
| 1109 | # |
|
|||
| 1110 | # azimuthAngle = arrayAOA[:,0] |
|
|||
| 1111 | # zenithAngle = arrayAOA[:,1] |
|
|||
| 1112 | # |
|
|||
| 1113 | # #Setting Error |
|
|||
| 1114 | # #Number 3: AOA not fesible |
|
|||
| 1115 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
|||
| 1116 | # error[indInvalid] = 3 |
|
|||
| 1117 | # #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
|||
| 1118 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
|||
| 1119 | # error[indInvalid] = 4 |
|
|||
| 1120 | # return arrayAOA, error |
|
|||
| 1121 | # |
|
|||
| 1122 | # def __getDirectionCosines(self, arrayPhase, pairsList): |
|
|||
| 1123 | # |
|
|||
| 1124 | # #Initializing some variables |
|
|||
| 1125 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
|||
| 1126 | # ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
|||
| 1127 | # |
|
|||
| 1128 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
|||
| 1129 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
|||
| 1130 | # |
|
|||
| 1131 | # |
|
|||
| 1132 | # for i in range(2): |
|
|||
| 1133 | # #First Estimation |
|
|||
| 1134 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] |
|
|||
| 1135 | # #Dealias |
|
|||
| 1136 | # indcsi = numpy.where(phi0_aux > numpy.pi) |
|
|||
| 1137 | # phi0_aux[indcsi] -= 2*numpy.pi |
|
|||
| 1138 | # indcsi = numpy.where(phi0_aux < -numpy.pi) |
|
|||
| 1139 | # phi0_aux[indcsi] += 2*numpy.pi |
|
|||
| 1140 | # #Direction Cosine 0 |
|
|||
| 1141 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) |
|
|||
| 1142 | # |
|
|||
| 1143 | # #Most-Accurate Second Estimation |
|
|||
| 1144 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] |
|
|||
| 1145 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
|||
| 1146 | # #Direction Cosine 1 |
|
|||
| 1147 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) |
|
|||
| 1148 | # |
|
|||
| 1149 | # #Searching the correct Direction Cosine |
|
|||
| 1150 | # cosdir0_aux = cosdir0[:,i] |
|
|||
| 1151 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
|||
| 1152 | # #Minimum Distance |
|
|||
| 1153 | # cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
|||
| 1154 | # indcos = cosDiff.argmin(axis = 1) |
|
|||
| 1155 | # #Saving Value obtained |
|
|||
| 1156 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
|||
| 1157 | # |
|
|||
| 1158 | # return cosdir0, cosdir |
|
|||
| 1159 | # |
|
|||
| 1160 | # def __calculateAOA(self, cosdir, azimuth): |
|
|||
| 1161 | # cosdirX = cosdir[:,0] |
|
|||
| 1162 | # cosdirY = cosdir[:,1] |
|
|||
| 1163 | # |
|
|||
| 1164 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
|||
| 1165 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east |
|
|||
| 1166 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
|||
| 1167 | # |
|
|||
| 1168 | # return angles |
|
|||
| 1169 | # |
|
|||
| 1170 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
|||
| 1171 | # |
|
|||
| 1172 | # Ramb = 375 #Ramb = c/(2*PRF) |
|
|||
| 1173 | # Re = 6371 #Earth Radius |
|
|||
| 1174 | # heights = numpy.zeros(Ranges.shape) |
|
|||
| 1175 | # |
|
|||
| 1176 | # R_aux = numpy.array([0,1,2])*Ramb |
|
|||
| 1177 | # R_aux = R_aux.reshape(1,R_aux.size) |
|
|||
| 1178 | # |
|
|||
| 1179 | # Ranges = Ranges.reshape(Ranges.size,1) |
|
|||
| 1180 | # |
|
|||
| 1181 | # Ri = Ranges + R_aux |
|
|||
| 1182 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
|||
| 1183 | # |
|
|||
| 1184 | # #Check if there is a height between 70 and 110 km |
|
|||
| 1185 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
|||
| 1186 | # ind_h = numpy.where(h_bool == 1)[0] |
|
|||
| 1187 | # |
|
|||
| 1188 | # hCorr = hi[ind_h, :] |
|
|||
| 1189 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
|||
| 1190 | # |
|
|||
| 1191 | # hCorr = hi[ind_hCorr] |
|
|||
| 1192 | # heights[ind_h] = hCorr |
|
|||
| 1193 | # |
|
|||
| 1194 | # #Setting Error |
|
|||
| 1195 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
|||
| 1196 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
|||
| 1197 | # |
|
|||
| 1198 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
|||
| 1199 | # error[indInvalid2] = 14 |
|
|||
| 1200 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
|||
| 1201 | # error[indInvalid1] = 13 |
|
|||
| 1202 | # |
|
|||
| 1203 | # return heights, error |
|
|||
| 1204 |
|
1009 | |||
| 1205 | def SpectralFitting(self, getSNR = True, path=None, file=None, groupList=None): |
|
1010 | if technique == 'DBS': | |
|
|
1011 | # if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): | |||
|
|
1012 | # theta_x = numpy.array(kwargs['dirCosx']) | |||
|
|
1013 | # theta_y = numpy.array(kwargs['dirCosy']) | |||
|
|
1014 | # else: | |||
|
|
1015 | # elev = numpy.array(kwargs['elevation']) | |||
|
|
1016 | # azim = numpy.array(kwargs['azimuth']) | |||
|
|
1017 | # theta_x, theta_y = self.__calculateCosDir(elev, azim) | |||
|
|
1018 | # azimuth = kwargs['correctAzimuth'] | |||
|
|
1019 | # if kwargs.has_key('horizontalOnly'): | |||
|
|
1020 | # horizontalOnly = kwargs['horizontalOnly'] | |||
|
|
1021 | # else: horizontalOnly = False | |||
|
|
1022 | # if kwargs.has_key('correctFactor'): | |||
|
|
1023 | # correctFactor = kwargs['correctFactor'] | |||
|
|
1024 | # else: correctFactor = 1 | |||
|
|
1025 | # if kwargs.has_key('channelList'): | |||
|
|
1026 | # channelList = kwargs['channelList'] | |||
|
|
1027 | # if len(channelList) == 2: | |||
|
|
1028 | # horizontalOnly = True | |||
|
|
1029 | # arrayChannel = numpy.array(channelList) | |||
|
|
1030 | # param = param[arrayChannel,:,:] | |||
|
|
1031 | # theta_x = theta_x[arrayChannel] | |||
|
|
1032 | # theta_y = theta_y[arrayChannel] | |||
| 1206 |
|
1033 | |||
| 1207 | ''' |
|
1034 | velRadial0 = param[:,1,:] #Radial velocity | |
| 1208 | Function GetMoments() |
|
1035 | # dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(velRadial0, theta_x, theta_y, azimuth, correctFactor, horizontalOnly, heightList, SNR) #DBS Function | |
|
|
1036 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(velRadial0, heightList, SNR, kwargs) #DBS Function | |||
|
|
1037 | dataOut.utctimeInit = dataOut.utctime | |||
|
|
1038 | dataOut.outputInterval = dataOut.paramInterval | |||
| 1209 |
|
1039 | |||
| 1210 | Input: |
|
1040 | elif technique == 'SA': | |
| 1211 | Output: |
|
|||
| 1212 | Variables modified: |
|
|||
| 1213 | ''' |
|
|||
| 1214 | if path != None: |
|
|||
| 1215 | sys.path.append(path) |
|
|||
| 1216 | self.dataOut.library = importlib.import_module(file) |
|
|||
| 1217 |
|
1041 | |||
| 1218 | #To be inserted as a parameter |
|
1042 | #Parameters | |
| 1219 | groupArray = numpy.array(groupList) |
|
1043 | position_x = kwargs['positionX'] | |
| 1220 | # groupArray = numpy.array([[0,1],[2,3]]) |
|
1044 | position_y = kwargs['positionY'] | |
| 1221 | self.dataOut.groupList = groupArray |
|
1045 | azimuth = kwargs['azimuth'] | |
| 1222 |
|
1046 | |||
| 1223 | nGroups = groupArray.shape[0] |
|
1047 | if kwargs.has_key('crosspairsList'): | |
| 1224 | nChannels = self.dataIn.nChannels |
|
1048 | pairs = kwargs['crosspairsList'] | |
| 1225 | nHeights=self.dataIn.heightList.size |
|
1049 | else: | |
|
|
1050 | pairs = None | |||
| 1226 |
|
1051 | |||
| 1227 | #Parameters Array |
|
1052 | if kwargs.has_key('correctFactor'): | |
| 1228 | self.dataOut.data_param = None |
|
1053 | correctFactor = kwargs['correctFactor'] | |
|
|
1054 | else: | |||
|
|
1055 | correctFactor = 1 | |||
| 1229 |
|
1056 | |||
| 1230 | #Set constants |
|
1057 | tau = dataOut.data_param | |
| 1231 | constants = self.dataOut.library.setConstants(self.dataIn) |
|
1058 | _lambda = dataOut.C/dataOut.frequency | |
| 1232 | self.dataOut.constants = constants |
|
1059 | pairsList = dataOut.groupList | |
| 1233 | M = self.dataIn.normFactor |
|
1060 | nChannels = dataOut.nChannels | |
| 1234 | N = self.dataIn.nFFTPoints |
|
|||
| 1235 | ippSeconds = self.dataIn.ippSeconds |
|
|||
| 1236 | K = self.dataIn.nIncohInt |
|
|||
| 1237 | pairsArray = numpy.array(self.dataIn.pairsList) |
|
|||
| 1238 |
|
1061 | |||
| 1239 | #List of possible combinations |
|
1062 | dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) | |
| 1240 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) |
|
1063 | dataOut.utctimeInit = dataOut.utctime | |
| 1241 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') |
|
1064 | dataOut.outputInterval = dataOut.timeInterval | |
| 1242 |
|
1065 | |||
| 1243 | if getSNR: |
|
1066 | elif technique == 'Meteors': | |
| 1244 | listChannels = groupArray.reshape((groupArray.size)) |
|
1067 | dataOut.flagNoData = True | |
| 1245 | listChannels.sort() |
|
1068 | self.__dataReady = False | |
| 1246 | noise = self.dataIn.getNoise() |
|
|||
| 1247 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) |
|
|||
| 1248 |
|
1069 | |||
| 1249 | for i in range(nGroups): |
|
1070 | if kwargs.has_key('nHours'): | |
| 1250 | coord = groupArray[i,:] |
|
1071 | nHours = kwargs['nHours'] | |
|
|
1072 | else: | |||
|
|
1073 | nHours = 1 | |||
| 1251 |
|
1074 | |||
| 1252 | #Input data array |
|
1075 | if kwargs.has_key('meteorsPerBin'): | |
| 1253 | data = self.dataIn.data_spc[coord,:,:]/(M*N) |
|
1076 | meteorThresh = kwargs['meteorsPerBin'] | |
| 1254 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) |
|
1077 | else: | |
|
|
1078 | meteorThresh = 6 | |||
| 1255 |
|
1079 | |||
| 1256 | #Cross Spectra data array for Covariance Matrixes |
|
1080 | if kwargs.has_key('hmin'): | |
| 1257 |
in |
|
1081 | hmin = kwargs['hmin'] | |
| 1258 | for pairs in listComb: |
|
1082 | else: hmin = 70 | |
| 1259 | pairsSel = numpy.array([coord[x],coord[y]]) |
|
1083 | if kwargs.has_key('hmax'): | |
| 1260 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) |
|
1084 | hmax = kwargs['hmax'] | |
| 1261 |
|
|
1085 | else: hmax = 110 | |
| 1262 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) |
|
|||
| 1263 | dataCross = dataCross**2/K |
|
|||
| 1264 |
|
1086 | |||
| 1265 | for h in range(nHeights): |
|
1087 | dataOut.outputInterval = nHours*3600 | |
| 1266 | # print self.dataOut.heightList[h] |
|
|||
| 1267 |
|
|
1088 | ||
| 1268 | #Input |
|
1089 | if self.__isConfig == False: | |
| 1269 | d = data[:,h] |
|
1090 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
|
|
1091 | #Get Initial LTC time | |||
|
|
1092 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |||
|
|
1093 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |||
| 1270 |
|
1094 | |||
| 1271 | #Covariance Matrix |
|
1095 | self.__isConfig = True | |
| 1272 | D = numpy.diag(d**2/K) |
|
|||
| 1273 | ind = 0 |
|
|||
| 1274 | for pairs in listComb: |
|
|||
| 1275 | #Coordinates in Covariance Matrix |
|
|||
| 1276 | x = pairs[0] |
|
|||
| 1277 | y = pairs[1] |
|
|||
| 1278 | #Channel Index |
|
|||
| 1279 | S12 = dataCross[ind,:,h] |
|
|||
| 1280 | D12 = numpy.diag(S12) |
|
|||
| 1281 | #Completing Covariance Matrix with Cross Spectras |
|
|||
| 1282 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 |
|
|||
| 1283 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 |
|
|||
| 1284 | ind += 1 |
|
|||
| 1285 | Dinv=numpy.linalg.inv(D) |
|
|||
| 1286 | L=numpy.linalg.cholesky(Dinv) |
|
|||
| 1287 | LT=L.T |
|
|||
| 1288 |
|
1096 | |||
| 1289 | dp = numpy.dot(LT,d) |
|
1097 | if self.__buffer == None: | |
|
|
1098 | self.__buffer = dataOut.data_param | |||
|
|
1099 | self.__firstdata = copy.copy(dataOut) | |||
| 1290 |
|
1100 | |||
| 1291 | #Initial values |
|
1101 | else: | |
| 1292 | data_spc = self.dataIn.data_spc[coord,:,h] |
|
1102 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
|
|
1103 | ||||
|
|
1104 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |||
|
|
1105 | ||||
|
|
1106 | if self.__dataReady: | |||
|
|
1107 | dataOut.utctimeInit = self.__initime | |||
|
|
1108 | ||||
|
|
1109 | self.__initime += dataOut.outputInterval #to erase time offset | |||
|
|
1110 | ||||
|
|
1111 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) | |||
|
|
1112 | dataOut.flagNoData = False | |||
|
|
1113 | self.__buffer = None | |||
|
|
1114 | ||||
|
|
1115 | elif technique == 'Meteors1': | |||
|
|
1116 | dataOut.flagNoData = True | |||
|
|
1117 | self.__dataReady = False | |||
|
|
1118 | ||||
|
|
1119 | if kwargs.has_key('nMins'): | |||
|
|
1120 | nMins = kwargs['nMins'] | |||
|
|
1121 | else: nMins = 20 | |||
|
|
1122 | if kwargs.has_key('rx_location'): | |||
|
|
1123 | rx_location = kwargs['rx_location'] | |||
|
|
1124 | else: rx_location = [(0,1),(1,1),(1,0)] | |||
|
|
1125 | if kwargs.has_key('azimuth'): | |||
|
|
1126 | azimuth = kwargs['azimuth'] | |||
|
|
1127 | else: azimuth = 51 | |||
|
|
1128 | if kwargs.has_key('dfactor'): | |||
|
|
1129 | dfactor = kwargs['dfactor'] | |||
|
|
1130 | if kwargs.has_key('mode'): | |||
|
|
1131 | mode = kwargs['mode'] | |||
|
|
1132 | else: mode = 'SA' | |||
|
|
1133 | ||||
|
|
1134 | #Borrar luego esto | |||
|
|
1135 | if dataOut.groupList == None: | |||
|
|
1136 | dataOut.groupList = [(0,1),(0,2),(1,2)] | |||
|
|
1137 | groupList = dataOut.groupList | |||
|
|
1138 | C = 3e8 | |||
|
|
1139 | freq = 50e6 | |||
|
|
1140 | lamb = C/freq | |||
|
|
1141 | k = 2*numpy.pi/lamb | |||
|
|
1142 | ||||
|
|
1143 | timeList = dataOut.abscissaList | |||
|
|
1144 | heightList = dataOut.heightList | |||
|
|
1145 | ||||
|
|
1146 | if self.__isConfig == False: | |||
|
|
1147 | dataOut.outputInterval = nMins*60 | |||
|
|
1148 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |||
|
|
1149 | #Get Initial LTC time | |||
|
|
1150 | initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |||
|
|
1151 | minuteAux = initime.minute | |||
|
|
1152 | minuteNew = int(numpy.floor(minuteAux/nMins)*nMins) | |||
|
|
1153 | self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |||
|
|
1154 | ||||
|
|
1155 | self.__isConfig = True | |||
|
|
1156 | ||||
|
|
1157 | if self.__buffer == None: | |||
|
|
1158 | self.__buffer = dataOut.data_param | |||
|
|
1159 | self.__firstdata = copy.copy(dataOut) | |||
| 1293 |
|
1160 | |||
| 1294 | if (h>0)and(error1[3]<5): |
|
|||
| 1295 | p0 = self.dataOut.data_param[i,:,h-1] |
|
|||
| 1296 |
|
|
1161 | else: | |
| 1297 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) |
|
1162 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 1298 |
|
|
1163 | ||
| 1299 | try: |
|
1164 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 1300 | #Least Squares |
|
|||
| 1301 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) |
|
|||
| 1302 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) |
|
|||
| 1303 | #Chi square error |
|
|||
| 1304 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) |
|
|||
| 1305 | #Error with Jacobian |
|
|||
| 1306 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) |
|
|||
| 1307 | except: |
|
|||
| 1308 | minp = p0*numpy.nan |
|
|||
| 1309 | error0 = numpy.nan |
|
|||
| 1310 | error1 = p0*numpy.nan |
|
|||
| 1311 |
|
1165 | |||
| 1312 | #Save |
|
1166 | if self.__dataReady: | |
| 1313 |
|
|
1167 | dataOut.utctimeInit = self.__initime | |
| 1314 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan |
|
1168 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 1315 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan |
|
1169 | ||
|
|
1170 | metArray = self.__buffer | |||
|
|
1171 | if mode == 'SA': | |||
|
|
1172 | dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList) | |||
|
|
1173 | elif mode == 'DBS': | |||
|
|
1174 | dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList) | |||
|
|
1175 | dataOut.data_output = dataOut.data_output.T | |||
|
|
1176 | dataOut.flagNoData = False | |||
|
|
1177 | self.__buffer = None | |||
| 1316 |
|
1178 | |||
| 1317 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) |
|
|||
| 1318 | self.dataOut.data_param[i,:,h] = minp |
|
|||
| 1319 | return |
|
1179 | return | |
| 1320 |
|
1180 | |||
| 1321 | def __residFunction(self, p, dp, LT, constants): |
|
1181 | class EWDriftsEstimation(Operation): | |
| 1322 |
|
1182 | |||
| 1323 | fm = self.dataOut.library.modelFunction(p, constants) |
|
1183 | def __init__(self): | |
| 1324 | fmp=numpy.dot(LT,fm) |
|
1184 | Operation.__init__(self) | |
| 1325 |
|
1185 | |||
| 1326 | return dp-fmp |
|
1186 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
|
|
1187 | listPhi = phi.tolist() | |||
|
|
1188 | maxid = listPhi.index(max(listPhi)) | |||
|
|
1189 | minid = listPhi.index(min(listPhi)) | |||
|
|
1190 | ||||
|
|
1191 | rango = range(len(phi)) | |||
|
|
1192 | # rango = numpy.delete(rango,maxid) | |||
|
|
1193 | ||||
|
|
1194 | heiRang1 = heiRang*math.cos(phi[maxid]) | |||
|
|
1195 | heiRangAux = heiRang*math.cos(phi[minid]) | |||
|
|
1196 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |||
|
|
1197 | heiRang1 = numpy.delete(heiRang1,indOut) | |||
|
|
1198 | ||||
|
|
1199 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |||
|
|
1200 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |||
|
|
1201 | ||||
|
|
1202 | for i in rango: | |||
|
|
1203 | x = heiRang*math.cos(phi[i]) | |||
|
|
1204 | y1 = velRadial[i,:] | |||
|
|
1205 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |||
|
|
1206 | ||||
|
|
1207 | x1 = heiRang1 | |||
|
|
1208 | y11 = f1(x1) | |||
|
|
1209 | ||||
|
|
1210 | y2 = SNR[i,:] | |||
|
|
1211 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |||
|
|
1212 | y21 = f2(x1) | |||
|
|
1213 | ||||
|
|
1214 | velRadial1[i,:] = y11 | |||
|
|
1215 | SNR1[i,:] = y21 | |||
|
|
1216 | ||||
|
|
1217 | return heiRang1, velRadial1, SNR1 | |||
|
|
1218 | ||||
|
|
1219 | def run(self, dataOut, zenith, zenithCorrection): | |||
|
|
1220 | heiRang = dataOut.heightList | |||
|
|
1221 | velRadial = dataOut.data_param[:,3,:] | |||
|
|
1222 | SNR = dataOut.data_SNR | |||
|
|
1223 | ||||
|
|
1224 | zenith = numpy.array(zenith) | |||
|
|
1225 | zenith -= zenithCorrection | |||
|
|
1226 | zenith *= numpy.pi/180 | |||
|
|
1227 | ||||
|
|
1228 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) | |||
|
|
1229 | ||||
|
|
1230 | alp = zenith[0] | |||
|
|
1231 | bet = zenith[1] | |||
|
|
1232 | ||||
|
|
1233 | w_w = velRadial1[0,:] | |||
|
|
1234 | w_e = velRadial1[1,:] | |||
|
|
1235 | ||||
|
|
1236 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) | |||
|
|
1237 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) | |||
|
|
1238 | ||||
|
|
1239 | winds = numpy.vstack((u,w)) | |||
|
|
1240 | ||||
|
|
1241 | dataOut.heightList = heiRang1 | |||
|
|
1242 | dataOut.data_output = winds | |||
|
|
1243 | dataOut.data_SNR = SNR1 | |||
| 1327 |
|
1244 | |||
| 1328 | def __getSNR(self, z, noise): |
|
1245 | dataOut.utctimeInit = dataOut.utctime | |
|
|
1246 | dataOut.outputInterval = dataOut.timeInterval | |||
|
|
1247 | return | |||
| 1329 |
|
1248 | |||
| 1330 | avg = numpy.average(z, axis=1) |
|
1249 | #--------------- Non Specular Meteor ---------------- | |
| 1331 | SNR = (avg.T-noise)/noise |
|
|||
| 1332 | SNR = SNR.T |
|
|||
| 1333 | return SNR |
|
|||
| 1334 |
|
1250 | |||
| 1335 | def __chisq(p,chindex,hindex): |
|
1251 | class NonSpecularMeteorDetection(Operation): | |
| 1336 | #similar to Resid but calculates CHI**2 |
|
|||
| 1337 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) |
|
|||
| 1338 | dp=numpy.dot(LT,d) |
|
|||
| 1339 | fmp=numpy.dot(LT,fm) |
|
|||
| 1340 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) |
|
|||
| 1341 | return chisq |
|
|||
| 1342 |
|
1252 | |||
| 1343 |
def |
|
1253 | def run(self, mode, SNRthresh=8, phaseDerThresh=0.5, cohThresh=0.8, allData = False): | |
| 1344 | data_acf = self.dataOut.data_pre[0] |
|
1254 | data_acf = self.dataOut.data_pre[0] | |
| 1345 | data_ccf = self.dataOut.data_pre[1] |
|
1255 | data_ccf = self.dataOut.data_pre[1] | |
| 1346 |
|
1256 | |||
| 1347 | lamb = self.dataOut.C/self.dataOut.frequency |
|
1257 | lamb = self.dataOut.C/self.dataOut.frequency | |
| 1348 | tSamp = self.dataOut.ippSeconds*self.dataOut.nCohInt |
|
1258 | tSamp = self.dataOut.ippSeconds*self.dataOut.nCohInt | |
| 1349 | paramInterval = self.dataOut.paramInterval |
|
1259 | paramInterval = self.dataOut.paramInterval | |
| 1350 |
|
1260 | |||
| 1351 | nChannels = data_acf.shape[0] |
|
1261 | nChannels = data_acf.shape[0] | |
| 1352 | nLags = data_acf.shape[1] |
|
1262 | nLags = data_acf.shape[1] | |
| 1353 | nProfiles = data_acf.shape[2] |
|
1263 | nProfiles = data_acf.shape[2] | |
| 1354 | nHeights = self.dataOut.nHeights |
|
1264 | nHeights = self.dataOut.nHeights | |
| 1355 | nCohInt = self.dataOut.nCohInt |
|
1265 | nCohInt = self.dataOut.nCohInt | |
| 1356 | sec = numpy.round(nProfiles/self.dataOut.paramInterval) |
|
1266 | sec = numpy.round(nProfiles/self.dataOut.paramInterval) | |
| 1357 | heightList = self.dataOut.heightList |
|
1267 | heightList = self.dataOut.heightList | |
| 1358 | ippSeconds = self.dataOut.ippSeconds*self.dataOut.nCohInt*self.dataOut.nAvg |
|
1268 | ippSeconds = self.dataOut.ippSeconds*self.dataOut.nCohInt*self.dataOut.nAvg | |
| 1359 | utctime = self.dataOut.utctime |
|
1269 | utctime = self.dataOut.utctime | |
| 1360 |
|
1270 | |||
| 1361 | self.dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds) |
|
1271 | self.dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds) | |
| 1362 |
|
1272 | |||
| 1363 | #------------------------ SNR -------------------------------------- |
|
1273 | #------------------------ SNR -------------------------------------- | |
| 1364 | power = data_acf[:,0,:,:].real |
|
1274 | power = data_acf[:,0,:,:].real | |
| 1365 | noise = numpy.zeros(nChannels) |
|
1275 | noise = numpy.zeros(nChannels) | |
| 1366 | SNR = numpy.zeros(power.shape) |
|
1276 | SNR = numpy.zeros(power.shape) | |
| 1367 | for i in range(nChannels): |
|
1277 | for i in range(nChannels): | |
| 1368 | noise[i] = hildebrand_sekhon(power[i,:], nCohInt) |
|
1278 | noise[i] = hildebrand_sekhon(power[i,:], nCohInt) | |
| 1369 | SNR[i] = (power[i]-noise[i])/noise[i] |
|
1279 | SNR[i] = (power[i]-noise[i])/noise[i] | |
| 1370 | SNRm = numpy.nanmean(SNR, axis = 0) |
|
1280 | SNRm = numpy.nanmean(SNR, axis = 0) | |
| 1371 | SNRdB = 10*numpy.log10(SNR) |
|
1281 | SNRdB = 10*numpy.log10(SNR) | |
| 1372 |
|
1282 | |||
| 1373 | if mode == 'SA': |
|
1283 | if mode == 'SA': | |
| 1374 | nPairs = data_ccf.shape[0] |
|
1284 | nPairs = data_ccf.shape[0] | |
| 1375 | #---------------------- Coherence and Phase -------------------------- |
|
1285 | #---------------------- Coherence and Phase -------------------------- | |
| 1376 | phase = numpy.zeros(data_ccf[:,0,:,:].shape) |
|
1286 | phase = numpy.zeros(data_ccf[:,0,:,:].shape) | |
| 1377 | # phase1 = numpy.copy(phase) |
|
1287 | # phase1 = numpy.copy(phase) | |
| 1378 | coh1 = numpy.zeros(data_ccf[:,0,:,:].shape) |
|
1288 | coh1 = numpy.zeros(data_ccf[:,0,:,:].shape) | |
| 1379 |
|
1289 | |||
| 1380 | for p in range(nPairs): |
|
1290 | for p in range(nPairs): | |
| 1381 | ch0 = self.dataOut.groupList[p][0] |
|
1291 | ch0 = self.dataOut.groupList[p][0] | |
| 1382 | ch1 = self.dataOut.groupList[p][1] |
|
1292 | ch1 = self.dataOut.groupList[p][1] | |
| 1383 | ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:]) |
|
1293 | ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:]) | |
| 1384 | phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter |
|
1294 | phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter | |
| 1385 | # phase1[p,:,:] = numpy.angle(ccf) #median filter |
|
1295 | # phase1[p,:,:] = numpy.angle(ccf) #median filter | |
| 1386 | coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter |
|
1296 | coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter | |
| 1387 | # coh1[p,:,:] = numpy.abs(ccf) #median filter |
|
1297 | # coh1[p,:,:] = numpy.abs(ccf) #median filter | |
| 1388 | coh = numpy.nanmax(coh1, axis = 0) |
|
1298 | coh = numpy.nanmax(coh1, axis = 0) | |
| 1389 | # struc = numpy.ones((5,1)) |
|
1299 | # struc = numpy.ones((5,1)) | |
| 1390 | # coh = ndimage.morphology.grey_dilation(coh, size=(10,1)) |
|
1300 | # coh = ndimage.morphology.grey_dilation(coh, size=(10,1)) | |
| 1391 | #---------------------- Radial Velocity ---------------------------- |
|
1301 | #---------------------- Radial Velocity ---------------------------- | |
| 1392 | phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0) |
|
1302 | phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0) | |
| 1393 | velRad = phaseAux*lamb/(4*numpy.pi*tSamp) |
|
1303 | velRad = phaseAux*lamb/(4*numpy.pi*tSamp) | |
| 1394 |
|
1304 | |||
| 1395 | if allData: |
|
1305 | if allData: | |
| 1396 | boolMetFin = ~numpy.isnan(SNRm) |
|
1306 | boolMetFin = ~numpy.isnan(SNRm) | |
| 1397 | # coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) |
|
1307 | # coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |
| 1398 | else: |
|
1308 | else: | |
| 1399 | #------------------------ Meteor mask --------------------------------- |
|
1309 | #------------------------ Meteor mask --------------------------------- | |
| 1400 | # #SNR mask |
|
1310 | # #SNR mask | |
| 1401 | # boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB)) |
|
1311 | # boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB)) | |
| 1402 | # |
|
1312 | # | |
| 1403 | # #Erase small objects |
|
1313 | # #Erase small objects | |
| 1404 | # boolMet1 = self.__erase_small(boolMet, 2*sec, 5) |
|
1314 | # boolMet1 = self.__erase_small(boolMet, 2*sec, 5) | |
| 1405 | # |
|
1315 | # | |
| 1406 | # auxEEJ = numpy.sum(boolMet1,axis=0) |
|
1316 | # auxEEJ = numpy.sum(boolMet1,axis=0) | |
| 1407 | # indOver = auxEEJ>nProfiles*0.8 #Use this later |
|
1317 | # indOver = auxEEJ>nProfiles*0.8 #Use this later | |
| 1408 | # indEEJ = numpy.where(indOver)[0] |
|
1318 | # indEEJ = numpy.where(indOver)[0] | |
| 1409 | # indNEEJ = numpy.where(~indOver)[0] |
|
1319 | # indNEEJ = numpy.where(~indOver)[0] | |
| 1410 | # |
|
1320 | # | |
| 1411 | # boolMetFin = boolMet1 |
|
1321 | # boolMetFin = boolMet1 | |
| 1412 | # |
|
1322 | # | |
| 1413 | # if indEEJ.size > 0: |
|
1323 | # if indEEJ.size > 0: | |
| 1414 | # boolMet1[:,indEEJ] = False #Erase heights with EEJ |
|
1324 | # boolMet1[:,indEEJ] = False #Erase heights with EEJ | |
| 1415 | # |
|
1325 | # | |
| 1416 | # boolMet2 = coh > cohThresh |
|
1326 | # boolMet2 = coh > cohThresh | |
| 1417 | # boolMet2 = self.__erase_small(boolMet2, 2*sec,5) |
|
1327 | # boolMet2 = self.__erase_small(boolMet2, 2*sec,5) | |
| 1418 | # |
|
1328 | # | |
| 1419 | # #Final Meteor mask |
|
1329 | # #Final Meteor mask | |
| 1420 | # boolMetFin = boolMet1|boolMet2 |
|
1330 | # boolMetFin = boolMet1|boolMet2 | |
| 1421 |
|
1331 | |||
| 1422 | #Coherence mask |
|
1332 | #Coherence mask | |
| 1423 | boolMet1 = coh > 0.75 |
|
1333 | boolMet1 = coh > 0.75 | |
| 1424 | struc = numpy.ones((30,1)) |
|
1334 | struc = numpy.ones((30,1)) | |
| 1425 | boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc) |
|
1335 | boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc) | |
| 1426 |
|
1336 | |||
| 1427 | #Derivative mask |
|
1337 | #Derivative mask | |
| 1428 | derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) |
|
1338 | derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |
| 1429 | boolMet2 = derPhase < 0.2 |
|
1339 | boolMet2 = derPhase < 0.2 | |
| 1430 | # boolMet2 = ndimage.morphology.binary_opening(boolMet2) |
|
1340 | # boolMet2 = ndimage.morphology.binary_opening(boolMet2) | |
| 1431 | # boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1))) |
|
1341 | # boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1))) | |
| 1432 | boolMet2 = ndimage.median_filter(boolMet2,size=5) |
|
1342 | boolMet2 = ndimage.median_filter(boolMet2,size=5) | |
| 1433 | boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool))) |
|
1343 | boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool))) | |
| 1434 | # #Final mask |
|
1344 | # #Final mask | |
| 1435 | # boolMetFin = boolMet2 |
|
1345 | # boolMetFin = boolMet2 | |
| 1436 | boolMetFin = boolMet1&boolMet2 |
|
1346 | boolMetFin = boolMet1&boolMet2 | |
| 1437 | # boolMetFin = ndimage.morphology.binary_dilation(boolMetFin) |
|
1347 | # boolMetFin = ndimage.morphology.binary_dilation(boolMetFin) | |
| 1438 | #Creating data_param |
|
1348 | #Creating data_param | |
| 1439 | coordMet = numpy.where(boolMetFin) |
|
1349 | coordMet = numpy.where(boolMetFin) | |
| 1440 |
|
1350 | |||
| 1441 | tmet = coordMet[0] |
|
1351 | tmet = coordMet[0] | |
| 1442 | hmet = coordMet[1] |
|
1352 | hmet = coordMet[1] | |
| 1443 |
|
1353 | |||
| 1444 | data_param = numpy.zeros((tmet.size, 6 + nPairs)) |
|
1354 | data_param = numpy.zeros((tmet.size, 6 + nPairs)) | |
| 1445 | data_param[:,0] = utctime |
|
1355 | data_param[:,0] = utctime | |
| 1446 | data_param[:,1] = tmet |
|
1356 | data_param[:,1] = tmet | |
| 1447 | data_param[:,2] = hmet |
|
1357 | data_param[:,2] = hmet | |
| 1448 | data_param[:,3] = SNRm[tmet,hmet] |
|
1358 | data_param[:,3] = SNRm[tmet,hmet] | |
| 1449 | data_param[:,4] = velRad[tmet,hmet] |
|
1359 | data_param[:,4] = velRad[tmet,hmet] | |
| 1450 | data_param[:,5] = coh[tmet,hmet] |
|
1360 | data_param[:,5] = coh[tmet,hmet] | |
| 1451 | data_param[:,6:] = phase[:,tmet,hmet].T |
|
1361 | data_param[:,6:] = phase[:,tmet,hmet].T | |
| 1452 |
|
1362 | |||
| 1453 | elif mode == 'DBS': |
|
1363 | elif mode == 'DBS': | |
| 1454 | self.dataOut.groupList = numpy.arange(nChannels) |
|
1364 | self.dataOut.groupList = numpy.arange(nChannels) | |
| 1455 |
|
1365 | |||
| 1456 | #Radial Velocities |
|
1366 | #Radial Velocities | |
| 1457 | # phase = numpy.angle(data_acf[:,1,:,:]) |
|
1367 | # phase = numpy.angle(data_acf[:,1,:,:]) | |
| 1458 | phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1)) |
|
1368 | phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1)) | |
| 1459 | velRad = phase*lamb/(4*numpy.pi*tSamp) |
|
1369 | velRad = phase*lamb/(4*numpy.pi*tSamp) | |
| 1460 |
|
1370 | |||
| 1461 | #Spectral width |
|
1371 | #Spectral width | |
| 1462 | acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1)) |
|
1372 | acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1)) | |
| 1463 | acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1)) |
|
1373 | acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1)) | |
| 1464 |
|
1374 | |||
| 1465 | spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2)) |
|
1375 | spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2)) | |
| 1466 | # velRad = ndimage.median_filter(velRad, size = (1,5,1)) |
|
1376 | # velRad = ndimage.median_filter(velRad, size = (1,5,1)) | |
| 1467 | if allData: |
|
1377 | if allData: | |
| 1468 | boolMetFin = ~numpy.isnan(SNRdB) |
|
1378 | boolMetFin = ~numpy.isnan(SNRdB) | |
| 1469 | else: |
|
1379 | else: | |
| 1470 | #SNR |
|
1380 | #SNR | |
| 1471 | boolMet1 = (SNRdB>SNRthresh) #SNR mask |
|
1381 | boolMet1 = (SNRdB>SNRthresh) #SNR mask | |
| 1472 | boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5)) |
|
1382 | boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5)) | |
| 1473 |
|
1383 | |||
| 1474 | #Radial velocity |
|
1384 | #Radial velocity | |
| 1475 | boolMet2 = numpy.abs(velRad) < 30 |
|
1385 | boolMet2 = numpy.abs(velRad) < 30 | |
| 1476 | boolMet2 = ndimage.median_filter(boolMet2, (1,5,5)) |
|
1386 | boolMet2 = ndimage.median_filter(boolMet2, (1,5,5)) | |
| 1477 |
|
1387 | |||
| 1478 | #Spectral Width |
|
1388 | #Spectral Width | |
| 1479 | boolMet3 = spcWidth < 30 |
|
1389 | boolMet3 = spcWidth < 30 | |
| 1480 | boolMet3 = ndimage.median_filter(boolMet3, (1,5,5)) |
|
1390 | boolMet3 = ndimage.median_filter(boolMet3, (1,5,5)) | |
| 1481 | # boolMetFin = self.__erase_small(boolMet1, 10,5) |
|
1391 | # boolMetFin = self.__erase_small(boolMet1, 10,5) | |
| 1482 | boolMetFin = boolMet1&boolMet2&boolMet3 |
|
1392 | boolMetFin = boolMet1&boolMet2&boolMet3 | |
| 1483 |
|
1393 | |||
| 1484 | #Creating data_param |
|
1394 | #Creating data_param | |
| 1485 | coordMet = numpy.where(boolMetFin) |
|
1395 | coordMet = numpy.where(boolMetFin) | |
| 1486 |
|
1396 | |||
| 1487 | cmet = coordMet[0] |
|
1397 | cmet = coordMet[0] | |
| 1488 | tmet = coordMet[1] |
|
1398 | tmet = coordMet[1] | |
| 1489 | hmet = coordMet[2] |
|
1399 | hmet = coordMet[2] | |
| 1490 |
|
1400 | |||
| 1491 | data_param = numpy.zeros((tmet.size, 7)) |
|
1401 | data_param = numpy.zeros((tmet.size, 7)) | |
| 1492 | data_param[:,0] = utctime |
|
1402 | data_param[:,0] = utctime | |
| 1493 | data_param[:,1] = cmet |
|
1403 | data_param[:,1] = cmet | |
| 1494 | data_param[:,2] = tmet |
|
1404 | data_param[:,2] = tmet | |
| 1495 | data_param[:,3] = hmet |
|
1405 | data_param[:,3] = hmet | |
| 1496 | data_param[:,4] = SNR[cmet,tmet,hmet].T |
|
1406 | data_param[:,4] = SNR[cmet,tmet,hmet].T | |
| 1497 | data_param[:,5] = velRad[cmet,tmet,hmet].T |
|
1407 | data_param[:,5] = velRad[cmet,tmet,hmet].T | |
| 1498 | data_param[:,6] = spcWidth[cmet,tmet,hmet].T |
|
1408 | data_param[:,6] = spcWidth[cmet,tmet,hmet].T | |
| 1499 |
|
1409 | |||
| 1500 | # self.dataOut.data_param = data_int |
|
1410 | # self.dataOut.data_param = data_int | |
| 1501 | if len(data_param) == 0: |
|
1411 | if len(data_param) == 0: | |
| 1502 | self.dataOut.flagNoData = True |
|
1412 | self.dataOut.flagNoData = True | |
| 1503 | else: |
|
1413 | else: | |
| 1504 | self.dataOut.data_param = data_param |
|
1414 | self.dataOut.data_param = data_param | |
| 1505 |
|
1415 | |||
| 1506 | def __erase_small(self, binArray, threshX, threshY): |
|
1416 | def __erase_small(self, binArray, threshX, threshY): | |
| 1507 | labarray, numfeat = ndimage.measurements.label(binArray) |
|
1417 | labarray, numfeat = ndimage.measurements.label(binArray) | |
| 1508 | binArray1 = numpy.copy(binArray) |
|
1418 | binArray1 = numpy.copy(binArray) | |
| 1509 |
|
1419 | |||
| 1510 | for i in range(1,numfeat + 1): |
|
1420 | for i in range(1,numfeat + 1): | |
| 1511 | auxBin = (labarray==i) |
|
1421 | auxBin = (labarray==i) | |
| 1512 | auxSize = auxBin.sum() |
|
1422 | auxSize = auxBin.sum() | |
| 1513 |
|
1423 | |||
| 1514 | x,y = numpy.where(auxBin) |
|
1424 | x,y = numpy.where(auxBin) | |
| 1515 | widthX = x.max() - x.min() |
|
1425 | widthX = x.max() - x.min() | |
| 1516 | widthY = y.max() - y.min() |
|
1426 | widthY = y.max() - y.min() | |
| 1517 |
|
1427 | |||
| 1518 | #width X: 3 seg -> 12.5*3 |
|
1428 | #width X: 3 seg -> 12.5*3 | |
| 1519 | #width Y: |
|
1429 | #width Y: | |
| 1520 |
|
1430 | |||
| 1521 | if (auxSize < 50) or (widthX < threshX) or (widthY < threshY): |
|
1431 | if (auxSize < 50) or (widthX < threshX) or (widthY < threshY): | |
| 1522 | binArray1[auxBin] = False |
|
1432 | binArray1[auxBin] = False | |
| 1523 |
|
1433 | |||
| 1524 | return binArray1 |
|
1434 | return binArray1 | |
| 1525 |
|
1435 | |||
| 1526 | def WeirdEcho(self): |
|
1436 | #--------------- Specular Meteor ---------------- | |
| 1527 | # data_pre = self.dataOut.data_pre |
|
|||
| 1528 | # nHeights = self.dataOut.nHeights |
|
|||
| 1529 | # # nProfiles = self.dataOut.data_pre.shape[1] |
|
|||
| 1530 | # # data_param = numpy.zeros((len(pairslist),nProfiles,nHeights)) |
|
|||
| 1531 | # data_param = numpy.zeros((len(pairslist),nHeights)) |
|
|||
| 1532 | # |
|
|||
| 1533 | # for i in range(len(pairslist)): |
|
|||
| 1534 | # chan0 = data_pre[pairslist[i][0],:] |
|
|||
| 1535 | # chan1 = data_pre[pairslist[i][1],:] |
|
|||
| 1536 | # #calcular correlacion cruzada |
|
|||
| 1537 | # #magnitud es coherencia |
|
|||
| 1538 | # #fase es dif fase |
|
|||
| 1539 | # correl = chan0*numpy.conj(chan1) |
|
|||
| 1540 | # coherence = numpy.abs(correl)/(numpy.abs(chan0)*numpy.abs(chan1)) |
|
|||
| 1541 | # phase = numpy.angle(correl) |
|
|||
| 1542 | # # data_param[2*i,:,:] = coherence |
|
|||
| 1543 | # data_param[i,:] = phase |
|
|||
| 1544 | # |
|
|||
| 1545 | # self.dataOut.data_param = data_param |
|
|||
| 1546 | # self.dataOut.groupList = pairslist |
|
|||
| 1547 | data_cspc = self.dataOut.data_pre[1] |
|
|||
| 1548 | ccf = numpy.average(data_cspc,axis=1) |
|
|||
| 1549 | phases = numpy.angle(ccf).T |
|
|||
| 1550 |
|
||||
| 1551 | meteorOps = MeteorOperations() |
|
|||
| 1552 | pairsList = ((0,1),(2,3)) |
|
|||
| 1553 | jph = numpy.array([0,0,0,0]) |
|
|||
| 1554 | AOAthresh = numpy.pi/8 |
|
|||
| 1555 | azimuth = 45 |
|
|||
| 1556 | error = numpy.zeros((phases.shape[0],1)) |
|
|||
| 1557 | AOA,error = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) |
|
|||
| 1558 | self.dataOut.data_param = AOA.T |
|
|||
| 1559 |
|
||||
| 1560 | class WindProfiler(Operation): |
|
|||
| 1561 |
|
||||
| 1562 | __isConfig = False |
|
|||
| 1563 |
|
||||
| 1564 | __initime = None |
|
|||
| 1565 | __lastdatatime = None |
|
|||
| 1566 | __integrationtime = None |
|
|||
| 1567 |
|
||||
| 1568 | __buffer = None |
|
|||
| 1569 |
|
||||
| 1570 | __dataReady = False |
|
|||
| 1571 |
|
||||
| 1572 | __firstdata = None |
|
|||
| 1573 |
|
||||
| 1574 | n = None |
|
|||
| 1575 |
|
||||
| 1576 | def __init__(self): |
|
|||
| 1577 | Operation.__init__(self) |
|
|||
| 1578 |
|
||||
| 1579 | def __calculateCosDir(self, elev, azim): |
|
|||
| 1580 | zen = (90 - elev)*numpy.pi/180 |
|
|||
| 1581 | azim = azim*numpy.pi/180 |
|
|||
| 1582 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) |
|
|||
| 1583 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) |
|
|||
| 1584 |
|
||||
| 1585 | signX = numpy.sign(numpy.cos(azim)) |
|
|||
| 1586 | signY = numpy.sign(numpy.sin(azim)) |
|
|||
| 1587 |
|
||||
| 1588 | cosDirX = numpy.copysign(cosDirX, signX) |
|
|||
| 1589 | cosDirY = numpy.copysign(cosDirY, signY) |
|
|||
| 1590 | return cosDirX, cosDirY |
|
|||
| 1591 |
|
||||
| 1592 | def __calculateAngles(self, theta_x, theta_y, azimuth): |
|
|||
| 1593 |
|
||||
| 1594 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) |
|
|||
| 1595 | zenith_arr = numpy.arccos(dir_cosw) |
|
|||
| 1596 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 |
|
|||
| 1597 |
|
||||
| 1598 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) |
|
|||
| 1599 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) |
|
|||
| 1600 |
|
||||
| 1601 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw |
|
|||
| 1602 |
|
||||
| 1603 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): |
|
|||
| 1604 |
|
||||
| 1605 | # |
|
|||
| 1606 | if horOnly: |
|
|||
| 1607 | A = numpy.c_[dir_cosu,dir_cosv] |
|
|||
| 1608 | else: |
|
|||
| 1609 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] |
|
|||
| 1610 | A = numpy.asmatrix(A) |
|
|||
| 1611 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() |
|
|||
| 1612 |
|
||||
| 1613 | return A1 |
|
|||
| 1614 |
|
||||
| 1615 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
|||
| 1616 | listPhi = phi.tolist() |
|
|||
| 1617 | maxid = listPhi.index(max(listPhi)) |
|
|||
| 1618 | minid = listPhi.index(min(listPhi)) |
|
|||
| 1619 |
|
||||
| 1620 | rango = range(len(phi)) |
|
|||
| 1621 | # rango = numpy.delete(rango,maxid) |
|
|||
| 1622 |
|
1437 | |||
| 1623 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
1438 | class MeteorDetection(Operation): | |
| 1624 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
1439 | ''' | |
| 1625 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
1440 | Function DetectMeteors() | |
| 1626 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
1441 | Project developed with paper: | |
|
|
1442 | HOLDSWORTH ET AL. 2004 | |||
| 1627 |
|
1443 | |||
| 1628 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1444 | Input: | |
| 1629 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1445 | self.dataOut.data_pre | |
| 1630 |
|
|
1446 | ||
| 1631 | for i in rango: |
|
1447 | centerReceiverIndex: From the channels, which is the center receiver | |
| 1632 | x = heiRang*math.cos(phi[i]) |
|
|||
| 1633 | y1 = velRadial[i,:] |
|
|||
| 1634 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
|||
| 1635 |
|
|
1448 | ||
| 1636 | x1 = heiRang1 |
|
1449 | hei_ref: Height reference for the Beacon signal extraction | |
| 1637 | y11 = f1(x1) |
|
1450 | tauindex: | |
|
|
1451 | predefinedPhaseShifts: Predefined phase offset for the voltge signals | |||
| 1638 |
|
|
1452 | ||
| 1639 | y2 = SNR[i,:] |
|
1453 | cohDetection: Whether to user Coherent detection or not | |
| 1640 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
1454 | cohDet_timeStep: Coherent Detection calculation time step | |
| 1641 | y21 = f2(x1) |
|
1455 | cohDet_thresh: Coherent Detection phase threshold to correct phases | |
| 1642 |
|
|
1456 | ||
| 1643 | velRadial1[i,:] = y11 |
|
1457 | noise_timeStep: Noise calculation time step | |
| 1644 | SNR1[i,:] = y21 |
|
1458 | noise_multiple: Noise multiple to define signal threshold | |
| 1645 |
|
|
1459 | ||
| 1646 | return heiRang1, velRadial1, SNR1 |
|
1460 | multDet_timeLimit: Multiple Detection Removal time limit in seconds | |
|
|
1461 | multDet_rangeLimit: Multiple Detection Removal range limit in km | |||
| 1647 |
|
1462 | |||
| 1648 | def __calculateVelUVW(self, A, velRadial): |
|
1463 | phaseThresh: Maximum phase difference between receiver to be consider a meteor | |
|
|
1464 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor | |||
| 1649 |
|
1465 | |||
| 1650 | #Operacion Matricial |
|
1466 | hmin: Minimum Height of the meteor to use it in the further wind estimations | |
| 1651 | # velUVW = numpy.zeros((velRadial.shape[1],3)) |
|
1467 | hmax: Maximum Height of the meteor to use it in the further wind estimations | |
| 1652 | # for ind in range(velRadial.shape[1]): |
|
1468 | azimuth: Azimuth angle correction | |
| 1653 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) |
|
|||
| 1654 | # velUVW = velUVW.transpose() |
|
|||
| 1655 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) |
|
|||
| 1656 | velUVW[:,:] = numpy.dot(A,velRadial) |
|
|||
| 1657 |
|
1469 | |||
|
|
1470 | Affected: | |||
|
|
1471 | self.dataOut.data_param | |||
| 1658 |
|
|
1472 | ||
| 1659 | return velUVW |
|
1473 | Rejection Criteria (Errors): | |
|
|
1474 | 0: No error; analysis OK | |||
|
|
1475 | 1: SNR < SNR threshold | |||
|
|
1476 | 2: angle of arrival (AOA) ambiguously determined | |||
|
|
1477 | 3: AOA estimate not feasible | |||
|
|
1478 | 4: Large difference in AOAs obtained from different antenna baselines | |||
|
|
1479 | 5: echo at start or end of time series | |||
|
|
1480 | 6: echo less than 5 examples long; too short for analysis | |||
|
|
1481 | 7: echo rise exceeds 0.3s | |||
|
|
1482 | 8: echo decay time less than twice rise time | |||
|
|
1483 | 9: large power level before echo | |||
|
|
1484 | 10: large power level after echo | |||
|
|
1485 | 11: poor fit to amplitude for estimation of decay time | |||
|
|
1486 | 12: poor fit to CCF phase variation for estimation of radial drift velocity | |||
|
|
1487 | 13: height unresolvable echo: not valid height within 70 to 110 km | |||
|
|
1488 | 14: height ambiguous echo: more then one possible height within 70 to 110 km | |||
|
|
1489 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s | |||
|
|
1490 | 16: oscilatory echo, indicating event most likely not an underdense echo | |||
| 1660 |
|
1491 | |||
| 1661 | def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): |
|
1492 | 17: phase difference in meteor Reestimation | |
| 1662 | """ |
|
|||
| 1663 | Function that implements Doppler Beam Swinging (DBS) technique. |
|
|||
| 1664 |
|
1493 | |||
| 1665 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1494 | Data Storage: | |
| 1666 | Direction correction (if necessary), Ranges and SNR |
|
1495 | Meteors for Wind Estimation (8): | |
|
|
1496 | Utc Time | Range Height | |||
|
|
1497 | Azimuth Zenith errorCosDir | |||
|
|
1498 | VelRad errorVelRad | |||
|
|
1499 | Phase0 Phase1 Phase2 Phase3 | |||
|
|
1500 | TypeError | |||
| 1667 |
|
1501 | |||
| 1668 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1502 | ''' | |
| 1669 |
|
|
1503 | ||
| 1670 | Parameters affected: Winds, height range, SNR |
|
1504 | def run(self, dataOut, hei_ref = None, tauindex = 0, | |
| 1671 | """ |
|
1505 | phaseOffsets = None, | |
| 1672 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(dirCosx, disrCosy, azimuth) |
|
1506 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, | |
| 1673 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correct*velRadial0, SNR0) |
|
1507 | noise_timeStep = 4, noise_multiple = 4, | |
| 1674 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) |
|
1508 | multDet_timeLimit = 1, multDet_rangeLimit = 3, | |
|
|
1509 | phaseThresh = 20, SNRThresh = 5, | |||
|
|
1510 | hmin = 50, hmax=150, azimuth = 0, | |||
|
|
1511 | channelPositions = None) : | |||
| 1675 |
|
|
1512 | ||
| 1676 | #Calculo de Componentes de la velocidad con DBS |
|
|||
| 1677 | winds = self.__calculateVelUVW(A,velRadial1) |
|
|||
| 1678 |
|
1513 | |||
| 1679 | return winds, heiRang1, SNR1 |
|
1514 | #Getting Pairslist | |
|
|
1515 | if channelPositions == None: | |||
|
|
1516 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |||
|
|
1517 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |||
|
|
1518 | meteorOps = MeteorOperations() | |||
|
|
1519 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |||
| 1680 |
|
1520 | |||
| 1681 | def __calculateDistance(self, posx, posy, pairsCrossCorr, pairsList, pairs, azimuth = None): |
|
1521 | #Get Beacon signal | |
|
|
1522 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |||
| 1682 |
|
1523 | |||
| 1683 | posx = numpy.asarray(posx) |
|
1524 | if hei_ref != None: | |
| 1684 | posy = numpy.asarray(posy) |
|
1525 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 1685 |
|
1526 | |||
| 1686 | #Rotacion Inversa para alinear con el azimuth |
|
1527 | heiRang = dataOut.getHeiRange() | |
| 1687 | if azimuth!= None: |
|
|||
| 1688 | azimuth = azimuth*math.pi/180 |
|
|||
| 1689 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) |
|
|||
| 1690 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) |
|
|||
| 1691 | else: |
|
|||
| 1692 | posx1 = posx |
|
|||
| 1693 | posy1 = posy |
|
|||
| 1694 |
|
1528 | |||
| 1695 | #Calculo de Distancias |
|
1529 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** | |
| 1696 | distx = numpy.zeros(pairsCrossCorr.size) |
|
1530 | # see if the user put in pre defined phase shifts | |
| 1697 | disty = numpy.zeros(pairsCrossCorr.size) |
|
1531 | voltsPShift = self.dataOut.data_pre.copy() | |
| 1698 | dist = numpy.zeros(pairsCrossCorr.size) |
|
|||
| 1699 | ang = numpy.zeros(pairsCrossCorr.size) |
|
|||
| 1700 |
|
1532 | |||
| 1701 | for i in range(pairsCrossCorr.size): |
|
1533 | # if predefinedPhaseShifts != None: | |
| 1702 | distx[i] = posx1[pairsList[pairsCrossCorr[i]][1]] - posx1[pairsList[pairsCrossCorr[i]][0]] |
|
1534 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 | |
| 1703 | disty[i] = posy1[pairsList[pairsCrossCorr[i]][1]] - posy1[pairsList[pairsCrossCorr[i]][0]] |
|
1535 | # | |
| 1704 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) |
|
1536 | # # elif beaconPhaseShifts: | |
| 1705 | ang[i] = numpy.arctan2(disty[i],distx[i]) |
|
1537 | # # #get hardware phase shifts using beacon signal | |
| 1706 | #Calculo de Matrices |
|
1538 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) | |
| 1707 | nPairs = len(pairs) |
|
1539 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) | |
| 1708 | ang1 = numpy.zeros((nPairs, 2, 1)) |
|
1540 | # | |
| 1709 | dist1 = numpy.zeros((nPairs, 2, 1)) |
|
1541 | # else: | |
|
|
1542 | # hardwarePhaseShifts = numpy.zeros(5) | |||
|
|
1543 | # | |||
|
|
1544 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') | |||
|
|
1545 | # for i in range(self.dataOut.data_pre.shape[0]): | |||
|
|
1546 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) | |||
| 1710 |
|
1547 | |||
| 1711 | for j in range(nPairs): |
|
1548 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* | |
| 1712 | dist1[j,0,0] = dist[pairs[j][0]] |
|
|||
| 1713 | dist1[j,1,0] = dist[pairs[j][1]] |
|
|||
| 1714 | ang1[j,0,0] = ang[pairs[j][0]] |
|
|||
| 1715 | ang1[j,1,0] = ang[pairs[j][1]] |
|
|||
| 1716 |
|
1549 | |||
| 1717 | return distx,disty, dist1,ang1 |
|
1550 | #Remove DC | |
|
|
1551 | voltsDC = numpy.mean(voltsPShift,1) | |||
|
|
1552 | voltsDC = numpy.mean(voltsDC,1) | |||
|
|
1553 | for i in range(voltsDC.shape[0]): | |||
|
|
1554 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] | |||
| 1718 |
|
1555 | |||
| 1719 | def __calculateVelVer(self, phase, lagTRange, _lambda): |
|
1556 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift | |
|
|
1557 | voltsPShift = voltsPShift[:,:,:newheis[0][0]] | |||
| 1720 |
|
1558 | |||
| 1721 | Ts = lagTRange[1] - lagTRange[0] |
|
1559 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** | |
| 1722 | velW = -_lambda*phase/(4*math.pi*Ts) |
|
1560 | #Coherent Detection | |
|
|
1561 | if cohDetection: | |||
|
|
1562 | #use coherent detection to get the net power | |||
|
|
1563 | cohDet_thresh = cohDet_thresh*numpy.pi/180 | |||
|
|
1564 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, self.dataOut.timeInterval, pairslist0, cohDet_thresh) | |||
| 1723 |
|
1565 | |||
| 1724 | return velW |
|
1566 | #Non-coherent detection! | |
|
|
1567 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) | |||
|
|
1568 | #********** END OF COH/NON-COH POWER CALCULATION********************** | |||
| 1725 |
|
1569 | |||
| 1726 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): |
|
1570 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** | |
| 1727 | nPairs = tau1.shape[0] |
|
1571 | #Get noise | |
| 1728 | vel = numpy.zeros((nPairs,3,tau1.shape[2])) |
|
1572 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, self.dataOut.timeInterval) | |
|
|
1573 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) | |||
|
|
1574 | #Get signal threshold | |||
|
|
1575 | signalThresh = noise_multiple*noise | |||
|
|
1576 | #Meteor echoes detection | |||
|
|
1577 | listMeteors = self.__findMeteors(powerNet, signalThresh) | |||
|
|
1578 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** | |||
| 1729 |
|
1579 | |||
| 1730 | angCos = numpy.cos(ang) |
|
1580 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** | |
| 1731 | angSin = numpy.sin(ang) |
|
1581 | #Parameters | |
|
|
1582 | heiRange = self.dataOut.getHeiRange() | |||
|
|
1583 | rangeInterval = heiRange[1] - heiRange[0] | |||
|
|
1584 | rangeLimit = multDet_rangeLimit/rangeInterval | |||
|
|
1585 | timeLimit = multDet_timeLimit/self.dataOut.timeInterval | |||
|
|
1586 | #Multiple detection removals | |||
|
|
1587 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) | |||
|
|
1588 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** | |||
| 1732 |
|
1589 | |||
| 1733 | vel0 = dist*tau1/(2*tau2**2) |
|
1590 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** | |
| 1734 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) |
|
1591 | #Parameters | |
| 1735 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) |
|
1592 | phaseThresh = phaseThresh*numpy.pi/180 | |
|
|
1593 | thresh = [phaseThresh, noise_multiple, SNRThresh] | |||
|
|
1594 | #Meteor reestimation (Errors N 1, 6, 12, 17) | |||
|
|
1595 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist0, thresh, noise, self.dataOut.timeInterval, self.dataOut.frequency) | |||
|
|
1596 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) | |||
|
|
1597 | #Estimation of decay times (Errors N 7, 8, 11) | |||
|
|
1598 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, self.dataOut.timeInterval, self.dataOut.frequency) | |||
|
|
1599 | #******************* END OF METEOR REESTIMATION ******************* | |||
| 1736 |
|
1600 | |||
| 1737 | ind = numpy.where(numpy.isinf(vel)) |
|
1601 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** | |
| 1738 | vel[ind] = numpy.nan |
|
1602 | #Calculating Radial Velocity (Error N 15) | |
|
|
1603 | radialStdThresh = 10 | |||
|
|
1604 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist0, self.dataOut.timeInterval) | |||
| 1739 |
|
1605 | |||
| 1740 | return vel |
|
1606 | if len(listMeteors4) > 0: | |
|
|
1607 | #Setting New Array | |||
|
|
1608 | date = self.dataOut.utctime | |||
|
|
1609 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) | |||
| 1741 |
|
1610 | |||
| 1742 | def __getPairsAutoCorr(self, pairsList, nChannels): |
|
1611 | #Correcting phase offset | |
|
|
1612 | if phaseOffsets != None: | |||
|
|
1613 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |||
|
|
1614 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |||
| 1743 |
|
1615 | |||
| 1744 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
1616 | #Second Pairslist | |
|
|
1617 | pairsList = [] | |||
|
|
1618 | pairx = (0,1) | |||
|
|
1619 | pairy = (2,3) | |||
|
|
1620 | pairsList.append(pairx) | |||
|
|
1621 | pairsList.append(pairy) | |||
| 1745 |
|
1622 | |||
| 1746 | for l in range(len(pairsList)): |
|
1623 | jph = numpy.array([0,0,0,0]) | |
| 1747 | firstChannel = pairsList[l][0] |
|
1624 | h = (hmin,hmax) | |
| 1748 | secondChannel = pairsList[l][1] |
|
1625 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) | |
| 1749 |
|
|
1626 | ||
| 1750 | #Obteniendo pares de Autocorrelacion |
|
1627 | # #Calculate AOA (Error N 3, 4) | |
| 1751 | if firstChannel == secondChannel: |
|
1628 | # #JONES ET AL. 1998 | |
| 1752 | pairsAutoCorr[firstChannel] = int(l) |
|
1629 | # error = arrayParameters[:,-1] | |
|
|
1630 | # AOAthresh = numpy.pi/8 | |||
|
|
1631 | # phases = -arrayParameters[:,9:13] | |||
|
|
1632 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) | |||
|
|
1633 | # | |||
|
|
1634 | # #Calculate Heights (Error N 13 and 14) | |||
|
|
1635 | # error = arrayParameters[:,-1] | |||
|
|
1636 | # Ranges = arrayParameters[:,2] | |||
|
|
1637 | # zenith = arrayParameters[:,5] | |||
|
|
1638 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) | |||
|
|
1639 | # error = arrayParameters[:,-1] | |||
|
|
1640 | #********************* END OF PARAMETERS CALCULATION ************************** | |||
| 1753 |
|
1641 | |||
| 1754 | pairsAutoCorr = pairsAutoCorr.astype(int) |
|
1642 | #***************************+ PASS DATA TO NEXT STEP ********************** | |
|
|
1643 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) | |||
|
|
1644 | self.dataOut.data_param = arrayParameters | |||
| 1755 |
|
1645 | |||
| 1756 | pairsCrossCorr = range(len(pairsList)) |
|
1646 | if arrayParameters == None: | |
| 1757 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
1647 | self.dataOut.flagNoData = True | |
|
|
1648 | else: | |||
|
|
1649 | self.dataOut.flagNoData = True | |||
| 1758 |
|
1650 | |||
| 1759 | return pairsAutoCorr, pairsCrossCorr |
|
1651 | return | |
| 1760 |
|
1652 | |||
| 1761 | def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): |
|
1653 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): | |
| 1762 | """ |
|
|||
| 1763 | Function that implements Spaced Antenna (SA) technique. |
|
|||
| 1764 |
|
1654 | |||
| 1765 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1655 | minIndex = min(newheis[0]) | |
| 1766 | Direction correction (if necessary), Ranges and SNR |
|
1656 | maxIndex = max(newheis[0]) | |
| 1767 |
|
1657 | |||
| 1768 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1658 | voltage = voltage0[:,:,minIndex:maxIndex+1] | |
|
|
1659 | nLength = voltage.shape[1]/n | |||
|
|
1660 | nMin = 0 | |||
|
|
1661 | nMax = 0 | |||
|
|
1662 | phaseOffset = numpy.zeros((len(pairslist),n)) | |||
| 1769 |
|
1663 | |||
| 1770 | Parameters affected: Winds |
|
1664 | for i in range(n): | |
| 1771 | """ |
|
1665 | nMax += nLength | |
| 1772 | #Cross Correlation pairs obtained |
|
1666 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) | |
| 1773 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) |
|
1667 | phaseCCF = numpy.mean(phaseCCF, axis = 2) | |
| 1774 | pairsArray = numpy.array(pairsList)[pairsCrossCorr] |
|
1668 | phaseOffset[:,i] = phaseCCF.transpose() | |
| 1775 | pairsSelArray = numpy.array(pairsSelected) |
|
1669 | nMin = nMax | |
| 1776 | pairs = [] |
|
1670 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) | |
| 1777 |
|
1671 | |||
| 1778 | #Wind estimation pairs obtained |
|
1672 | #Remove Outliers | |
| 1779 | for i in range(pairsSelArray.shape[0]/2): |
|
1673 | factor = 2 | |
| 1780 | ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] |
|
1674 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) | |
| 1781 | ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] |
|
1675 | dw = numpy.std(wt,axis = 1) | |
| 1782 | pairs.append((ind1,ind2)) |
|
1676 | dw = dw.reshape((dw.size,1)) | |
|
|
1677 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) | |||
|
|
1678 | phaseOffset[ind] = numpy.nan | |||
|
|
1679 | phaseOffset = stats.nanmean(phaseOffset, axis=1) | |||
| 1783 |
|
1680 | |||
| 1784 | indtau = tau.shape[0]/2 |
|
1681 | return phaseOffset | |
| 1785 | tau1 = tau[:indtau,:] |
|
|||
| 1786 | tau2 = tau[indtau:-1,:] |
|
|||
| 1787 | tau1 = tau1[pairs,:] |
|
|||
| 1788 | tau2 = tau2[pairs,:] |
|
|||
| 1789 | phase1 = tau[-1,:] |
|
|||
| 1790 |
|
|
1682 | ||
| 1791 | #--------------------------------------------------------------------- |
|
1683 | def __shiftPhase(self, data, phaseShift): | |
| 1792 | #Metodo Directo |
|
1684 | #this will shift the phase of a complex number | |
| 1793 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairsCrossCorr, pairsList, pairs,azimuth) |
|
1685 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) | |
| 1794 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) |
|
1686 | return dataShifted | |
| 1795 | winds = stats.nanmean(winds, axis=0) |
|
|||
| 1796 | #--------------------------------------------------------------------- |
|
|||
| 1797 | #Metodo General |
|
|||
| 1798 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) |
|
|||
| 1799 | # #Calculo Coeficientes de Funcion de Correlacion |
|
|||
| 1800 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) |
|
|||
| 1801 | # #Calculo de Velocidades |
|
|||
| 1802 | # winds = self.calculateVelUV(F,G,A,B,H) |
|
|||
| 1803 |
|
1687 | |||
| 1804 | #--------------------------------------------------------------------- |
|
1688 | def __estimatePhaseDifference(self, array, pairslist): | |
| 1805 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) |
|
1689 | nChannel = array.shape[0] | |
| 1806 | winds = correctFactor*winds |
|
1690 | nHeights = array.shape[2] | |
| 1807 | return winds |
|
1691 | numPairs = len(pairslist) | |
|
|
1692 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) | |||
|
|
1693 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) | |||
| 1808 |
|
1694 | |||
| 1809 | def __checkTime(self, currentTime, paramInterval, outputInterval): |
|
1695 | #Correct phases | |
|
|
1696 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] | |||
|
|
1697 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |||
| 1810 |
|
1698 | |||
| 1811 | dataTime = currentTime + paramInterval |
|
1699 | if indDer[0].shape[0] > 0: | |
| 1812 | deltaTime = dataTime - self.__initime |
|
1700 | for i in range(indDer[0].shape[0]): | |
|
|
1701 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) | |||
|
|
1702 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi | |||
| 1813 |
|
|
1703 | ||
| 1814 | if deltaTime >= outputInterval or deltaTime < 0: |
|
1704 | # for j in range(numSides): | |
| 1815 | self.__dataReady = True |
|
1705 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) | |
| 1816 | return |
|
1706 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) | |
|
|
1707 | # | |||
|
|
1708 | #Linear | |||
|
|
1709 | phaseInt = numpy.zeros((numPairs,1)) | |||
|
|
1710 | angAllCCF = phaseCCF[:,[0,1,3,4],0] | |||
|
|
1711 | for j in range(numPairs): | |||
|
|
1712 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) | |||
|
|
1713 | phaseInt[j] = fit[1] | |||
|
|
1714 | #Phase Differences | |||
|
|
1715 | phaseDiff = phaseInt - phaseCCF[:,2,:] | |||
|
|
1716 | phaseArrival = phaseInt.reshape(phaseInt.size) | |||
| 1817 |
|
1717 | |||
| 1818 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): |
|
1718 | #Dealias | |
| 1819 | ''' |
|
1719 | phaseArrival = numpy.angle(numpy.exp(1j*phaseArrival)) | |
| 1820 | Function that implements winds estimation technique with detected meteors. |
|
1720 | # indAlias = numpy.where(phaseArrival > numpy.pi) | |
|
|
1721 | # phaseArrival[indAlias] -= 2*numpy.pi | |||
|
|
1722 | # indAlias = numpy.where(phaseArrival < -numpy.pi) | |||
|
|
1723 | # phaseArrival[indAlias] += 2*numpy.pi | |||
| 1821 |
|
1724 | |||
| 1822 | Input: Detected meteors, Minimum meteor quantity to wind estimation |
|
1725 | return phaseDiff, phaseArrival | |
| 1823 |
|
|
1726 | ||
| 1824 | Output: Winds estimation (Zonal and Meridional) |
|
1727 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): | |
|
|
1728 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power | |||
|
|
1729 | #find the phase shifts of each channel over 1 second intervals | |||
|
|
1730 | #only look at ranges below the beacon signal | |||
|
|
1731 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |||
|
|
1732 | numBlocks = int(volts.shape[1]/numProfPerBlock) | |||
|
|
1733 | numHeights = volts.shape[2] | |||
|
|
1734 | nChannel = volts.shape[0] | |||
|
|
1735 | voltsCohDet = volts.copy() | |||
| 1825 |
|
1736 | |||
| 1826 | Parameters affected: Winds |
|
1737 | pairsarray = numpy.array(pairslist) | |
| 1827 | ''' |
|
1738 | indSides = pairsarray[:,1] | |
| 1828 | # print arrayMeteor.shape |
|
1739 | # indSides = numpy.array(range(nChannel)) | |
| 1829 | #Settings |
|
1740 | # indSides = numpy.delete(indSides, indCenter) | |
| 1830 | nInt = (heightMax - heightMin)/2 |
|
1741 | # | |
| 1831 | # print nInt |
|
1742 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) | |
| 1832 | nInt = int(nInt) |
|
1743 | listBlocks = numpy.array_split(volts, numBlocks, 1) | |
| 1833 | # print nInt |
|
|||
| 1834 | winds = numpy.zeros((2,nInt))*numpy.nan |
|
|||
| 1835 |
|
1744 | |||
| 1836 | #Filter errors |
|
1745 | startInd = 0 | |
| 1837 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] |
|
1746 | endInd = 0 | |
| 1838 | finalMeteor = arrayMeteor[error,:] |
|
|||
| 1839 |
|
1747 | |||
| 1840 | #Meteor Histogram |
|
1748 | for i in range(numBlocks): | |
| 1841 | finalHeights = finalMeteor[:,2] |
|
1749 | startInd = endInd | |
| 1842 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) |
|
1750 | endInd = endInd + listBlocks[i].shape[1] | |
| 1843 | nMeteorsPerI = hist[0] |
|
|||
| 1844 | heightPerI = hist[1] |
|
|||
| 1845 |
|
1751 | |||
| 1846 | #Sort of meteors |
|
1752 | arrayBlock = listBlocks[i] | |
| 1847 | indSort = finalHeights.argsort() |
|
1753 | # arrayBlockCenter = listCenter[i] | |
| 1848 | finalMeteor2 = finalMeteor[indSort,:] |
|
|||
| 1849 |
|
1754 | |||
| 1850 | # Calculating winds |
|
1755 | #Estimate the Phase Difference | |
| 1851 | ind1 = 0 |
|
1756 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) | |
| 1852 | ind2 = 0 |
|
1757 | #Phase Difference RMS | |
|
|
1758 | arrayPhaseRMS = numpy.abs(phaseDiff) | |||
|
|
1759 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) | |||
|
|
1760 | indPhase = numpy.where(phaseRMSaux==4) | |||
|
|
1761 | #Shifting | |||
|
|
1762 | if indPhase[0].shape[0] > 0: | |||
|
|
1763 | for j in range(indSides.size): | |||
|
|
1764 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) | |||
|
|
1765 | voltsCohDet[:,startInd:endInd,:] = arrayBlock | |||
| 1853 |
|
1766 | |||
| 1854 | for i in range(nInt): |
|
1767 | return voltsCohDet | |
| 1855 | nMet = nMeteorsPerI[i] |
|
|||
| 1856 | ind1 = ind2 |
|
|||
| 1857 | ind2 = ind1 + nMet |
|
|||
| 1858 |
|
1768 | |||
| 1859 | meteorAux = finalMeteor2[ind1:ind2,:] |
|
1769 | def __calculateCCF(self, volts, pairslist ,laglist): | |
| 1860 |
|
|
1770 | ||
| 1861 | if meteorAux.shape[0] >= meteorThresh: |
|
1771 | nHeights = volts.shape[2] | |
| 1862 | vel = meteorAux[:, 6] |
|
1772 | nPoints = volts.shape[1] | |
| 1863 | zen = meteorAux[:, 4]*numpy.pi/180 |
|
1773 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') | |
| 1864 | azim = meteorAux[:, 3]*numpy.pi/180 |
|
|||
| 1865 |
|
|
1774 | ||
| 1866 | n = numpy.cos(zen) |
|
1775 | for i in range(len(pairslist)): | |
| 1867 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) |
|
1776 | volts1 = volts[pairslist[i][0]] | |
| 1868 | # l = m*numpy.tan(azim) |
|
1777 | volts2 = volts[pairslist[i][1]] | |
| 1869 | l = numpy.sin(zen)*numpy.sin(azim) |
|
|||
| 1870 | m = numpy.sin(zen)*numpy.cos(azim) |
|
|||
| 1871 |
|
|
1778 | ||
| 1872 | A = numpy.vstack((l, m)).transpose() |
|
1779 | for t in range(len(laglist)): | |
| 1873 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) |
|
1780 | idxT = laglist[t] | |
| 1874 | windsAux = numpy.dot(A1, vel) |
|
1781 | if idxT >= 0: | |
|
|
1782 | vStacked = numpy.vstack((volts2[idxT:,:], | |||
|
|
1783 | numpy.zeros((idxT, nHeights),dtype='complex'))) | |||
|
|
1784 | else: | |||
|
|
1785 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), | |||
|
|
1786 | volts2[:(nPoints + idxT),:])) | |||
|
|
1787 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) | |||
| 1875 |
|
1788 | |||
| 1876 | winds[0,i] = windsAux[0] |
|
1789 | vStacked = None | |
| 1877 | winds[1,i] = windsAux[1] |
|
1790 | return voltsCCF | |
| 1878 |
|
|
1791 | ||
| 1879 | return winds, heightPerI[:-1] |
|
1792 | def __getNoise(self, power, timeSegment, timeInterval): | |
|
|
1793 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |||
|
|
1794 | numBlocks = int(power.shape[0]/numProfPerBlock) | |||
|
|
1795 | numHeights = power.shape[1] | |||
| 1880 |
|
1796 | |||
| 1881 | def techniqueNSM_SA(self, **kwargs): |
|
1797 | listPower = numpy.array_split(power, numBlocks, 0) | |
| 1882 | metArray = kwargs['metArray'] |
|
1798 | noise = numpy.zeros((power.shape[0], power.shape[1])) | |
| 1883 | heightList = kwargs['heightList'] |
|
1799 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) | |
| 1884 | timeList = kwargs['timeList'] |
|
|||
| 1885 |
|
1800 | |||
| 1886 | rx_location = kwargs['rx_location'] |
|
1801 | startInd = 0 | |
| 1887 | groupList = kwargs['groupList'] |
|
1802 | endInd = 0 | |
| 1888 | azimuth = kwargs['azimuth'] |
|
|||
| 1889 | dfactor = kwargs['dfactor'] |
|
|||
| 1890 | k = kwargs['k'] |
|
|||
| 1891 |
|
1803 | |||
| 1892 | azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth) |
|
1804 | for i in range(numBlocks): #split por canal | |
| 1893 | d = dist*dfactor |
|
1805 | startInd = endInd | |
| 1894 | #Phase calculation |
|
1806 | endInd = endInd + listPower[i].shape[0] | |
| 1895 | metArray1 = self.__getPhaseSlope(metArray, heightList, timeList) |
|
|||
| 1896 |
|
1807 | |||
| 1897 | metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities |
|
1808 | arrayBlock = listPower[i] | |
|
|
1809 | noiseAux = numpy.mean(arrayBlock, 0) | |||
|
|
1810 | # noiseAux = numpy.median(noiseAux) | |||
|
|
1811 | # noiseAux = numpy.mean(arrayBlock) | |||
|
|
1812 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux | |||
| 1898 |
|
1813 | |||
| 1899 | velEst = numpy.zeros((heightList.size,2))*numpy.nan |
|
1814 | noiseAux1 = numpy.mean(arrayBlock) | |
| 1900 | azimuth1 = azimuth1*numpy.pi/180 |
|
1815 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 | |
| 1901 |
|
1816 | |||
| 1902 | for i in range(heightList.size): |
|
1817 | return noise, noise1 | |
| 1903 | h = heightList[i] |
|
|||
| 1904 | indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0] |
|
|||
| 1905 | metHeight = metArray1[indH,:] |
|
|||
| 1906 | if metHeight.shape[0] >= 2: |
|
|||
| 1907 | velAux = numpy.asmatrix(metHeight[:,-2]).T #Radial Velocities |
|
|||
| 1908 | iazim = metHeight[:,1].astype(int) |
|
|||
| 1909 | azimAux = numpy.asmatrix(azimuth1[iazim]).T #Azimuths |
|
|||
| 1910 | A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux))) |
|
|||
| 1911 | A = numpy.asmatrix(A) |
|
|||
| 1912 | A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose() |
|
|||
| 1913 | velHor = numpy.dot(A1,velAux) |
|
|||
| 1914 |
|
1818 | |||
| 1915 | velEst[i,:] = numpy.squeeze(velHor) |
|
1819 | def __findMeteors(self, power, thresh): | |
| 1916 | return velEst |
|
1820 | nProf = power.shape[0] | |
|
|
1821 | nHeights = power.shape[1] | |||
|
|
1822 | listMeteors = [] | |||
| 1917 |
|
1823 | |||
| 1918 | def __getPhaseSlope(self, metArray, heightList, timeList): |
|
1824 | for i in range(nHeights): | |
| 1919 | meteorList = [] |
|
1825 | powerAux = power[:,i] | |
| 1920 | #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2 |
|
1826 | threshAux = thresh[:,i] | |
| 1921 | #Putting back together the meteor matrix |
|
|||
| 1922 | utctime = metArray[:,0] |
|
|||
| 1923 | uniqueTime = numpy.unique(utctime) |
|
|||
| 1924 |
|
1827 | |||
| 1925 | phaseDerThresh = 0.5 |
|
1828 | indUPthresh = numpy.where(powerAux > threshAux)[0] | |
| 1926 | ippSeconds = timeList[1] - timeList[0] |
|
1829 | indDNthresh = numpy.where(powerAux <= threshAux)[0] | |
| 1927 | sec = numpy.where(timeList>1)[0][0] |
|
|||
| 1928 | nPairs = metArray.shape[1] - 6 |
|
|||
| 1929 | nHeights = len(heightList) |
|
|||
| 1930 |
|
1830 | |||
| 1931 | for t in uniqueTime: |
|
1831 | j = 0 | |
| 1932 | metArray1 = metArray[utctime==t,:] |
|
|||
| 1933 | # phaseDerThresh = numpy.pi/4 #reducir Phase thresh |
|
|||
| 1934 | tmet = metArray1[:,1].astype(int) |
|
|||
| 1935 | hmet = metArray1[:,2].astype(int) |
|
|||
| 1936 |
|
1832 | |||
| 1937 | metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1)) |
|
1833 | while (j < indUPthresh.size - 2): | |
| 1938 | metPhase[:,:] = numpy.nan |
|
1834 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): | |
| 1939 | metPhase[:,hmet,tmet] = metArray1[:,6:].T |
|
1835 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) | |
|
|
1836 | indDNthresh = indDNthresh[indDNAux] | |||
| 1940 |
|
1837 | |||
| 1941 | #Delete short trails |
|
1838 | if (indDNthresh.size > 0): | |
| 1942 | metBool = ~numpy.isnan(metPhase[0,:,:]) |
|
1839 | indEnd = indDNthresh[0] - 1 | |
| 1943 | heightVect = numpy.sum(metBool, axis = 1) |
|
1840 | indInit = indUPthresh[j] | |
| 1944 | metBool[heightVect<sec,:] = False |
|
|||
| 1945 | metPhase[:,heightVect<sec,:] = numpy.nan |
|
|||
| 1946 |
|
1841 | |||
| 1947 | #Derivative |
|
1842 | meteor = powerAux[indInit:indEnd + 1] | |
| 1948 | metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1]) |
|
1843 | indPeak = meteor.argmax() + indInit | |
| 1949 | phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh)) |
|
1844 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) | |
| 1950 | metPhase[phDerAux] = numpy.nan |
|
|||
| 1951 |
|
1845 | |||
| 1952 | #--------------------------METEOR DETECTION ----------------------------------------- |
|
1846 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! | |
| 1953 | indMet = numpy.where(numpy.any(metBool,axis=1))[0] |
|
1847 | j = numpy.where(indUPthresh == indEnd)[0] + 1 | |
|
|
1848 | else: j+=1 | |||
|
|
1849 | else: j+=1 | |||
| 1954 |
|
1850 | |||
| 1955 | for p in numpy.arange(nPairs): |
|
1851 | return listMeteors | |
| 1956 | phase = metPhase[p,:,:] |
|
|||
| 1957 | phDer = metDer[p,:,:] |
|
|||
| 1958 |
|
1852 | |||
| 1959 | for h in indMet: |
|
1853 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): | |
| 1960 | height = heightList[h] |
|
|||
| 1961 | phase1 = phase[h,:] #82 |
|
|||
| 1962 | phDer1 = phDer[h,:] |
|
|||
| 1963 |
|
1854 | |||
| 1964 | phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)]) #Unwrap |
|
1855 | arrayMeteors = numpy.asarray(listMeteors) | |
|
|
1856 | listMeteors1 = [] | |||
| 1965 |
|
1857 | |||
| 1966 | indValid = numpy.where(~numpy.isnan(phase1))[0] |
|
1858 | while arrayMeteors.shape[0] > 0: | |
| 1967 | initMet = indValid[0] |
|
1859 | FLAs = arrayMeteors[:,4] | |
| 1968 | endMet = 0 |
|
1860 | maxFLA = FLAs.argmax() | |
|
|
1861 | listMeteors1.append(arrayMeteors[maxFLA,:]) | |||
| 1969 |
|
1862 | |||
| 1970 | for i in range(len(indValid)-1): |
|
1863 | MeteorInitTime = arrayMeteors[maxFLA,1] | |
|
|
1864 | MeteorEndTime = arrayMeteors[maxFLA,3] | |||
|
|
1865 | MeteorHeight = arrayMeteors[maxFLA,0] | |||
| 1971 |
|
|
1866 | ||
| 1972 | #Time difference |
|
1867 | #Check neighborhood | |
| 1973 | inow = indValid[i] |
|
1868 | maxHeightIndex = MeteorHeight + rangeLimit | |
| 1974 | inext = indValid[i+1] |
|
1869 | minHeightIndex = MeteorHeight - rangeLimit | |
| 1975 | idiff = inext - inow |
|
1870 | minTimeIndex = MeteorInitTime - timeLimit | |
| 1976 | #Phase difference |
|
1871 | maxTimeIndex = MeteorEndTime + timeLimit | |
| 1977 | phDiff = numpy.abs(phase1[inext] - phase1[inow]) |
|
|||
| 1978 |
|
|
1872 | ||
| 1979 | if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]: #End of Meteor |
|
1873 | #Check Heights | |
| 1980 | sizeTrail = inow - initMet + 1 |
|
1874 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) | |
| 1981 | if sizeTrail>3*sec: #Too short meteors |
|
1875 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) | |
| 1982 | x = numpy.arange(initMet,inow+1)*ippSeconds |
|
1876 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) | |
| 1983 | y = phase1[initMet:inow+1] |
|
|||
| 1984 | ynnan = ~numpy.isnan(y) |
|
|||
| 1985 | x = x[ynnan] |
|
|||
| 1986 | y = y[ynnan] |
|
|||
| 1987 | slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) |
|
|||
| 1988 | ylin = x*slope + intercept |
|
|||
| 1989 | rsq = r_value**2 |
|
|||
| 1990 | if rsq > 0.5: |
|
|||
| 1991 | vel = slope#*height*1000/(k*d) |
|
|||
| 1992 | estAux = numpy.array([utctime,p,height, vel, rsq]) |
|
|||
| 1993 | meteorList.append(estAux) |
|
|||
| 1994 | initMet = inext |
|
|||
| 1995 | metArray2 = numpy.array(meteorList) |
|
|||
| 1996 |
|
1877 | |||
| 1997 | return metArray2 |
|
1878 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) | |
| 1998 |
|
1879 | |||
| 1999 | def __calculateAzimuth1(self, rx_location, pairslist, azimuth0): |
|
1880 | return listMeteors1 | |
| 2000 |
|
|
1881 | ||
| 2001 | azimuth1 = numpy.zeros(len(pairslist)) |
|
1882 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): | |
| 2002 | dist = numpy.zeros(len(pairslist)) |
|
1883 | numHeights = volts.shape[2] | |
|
|
1884 | nChannel = volts.shape[0] | |||
| 2003 |
|
1885 | |||
| 2004 | for i in range(len(rx_location)): |
|
1886 | thresholdPhase = thresh[0] | |
| 2005 | ch0 = pairslist[i][0] |
|
1887 | thresholdNoise = thresh[1] | |
| 2006 | ch1 = pairslist[i][1] |
|
1888 | thresholdDB = float(thresh[2]) | |
| 2007 |
|
|
1889 | ||
| 2008 | diffX = rx_location[ch0][0] - rx_location[ch1][0] |
|
1890 | thresholdDB1 = 10**(thresholdDB/10) | |
| 2009 | diffY = rx_location[ch0][1] - rx_location[ch1][1] |
|
1891 | pairsarray = numpy.array(pairslist) | |
| 2010 | azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi |
|
1892 | indSides = pairsarray[:,1] | |
| 2011 | dist[i] = numpy.sqrt(diffX**2 + diffY**2) |
|
|||
| 2012 |
|
1893 | |||
| 2013 | azimuth1 -= azimuth0 |
|
1894 | pairslist1 = list(pairslist) | |
| 2014 | return azimuth1, dist |
|
1895 | pairslist1.append((0,1)) | |
|
|
1896 | pairslist1.append((3,4)) | |||
| 2015 |
|
1897 | |||
| 2016 | def techniqueNSM_DBS(self, **kwargs): |
|
1898 | listMeteors1 = [] | |
| 2017 | metArray = kwargs['metArray'] |
|
1899 | listPowerSeries = [] | |
| 2018 | heightList = kwargs['heightList'] |
|
1900 | listVoltageSeries = [] | |
| 2019 | timeList = kwargs['timeList'] |
|
1901 | #volts has the war data | |
| 2020 | zenithList = kwargs['zenithList'] |
|
|||
| 2021 | nChan = numpy.max(cmet) + 1 |
|
|||
| 2022 | nHeights = len(heightList) |
|
|||
| 2023 |
|
1902 | |||
| 2024 | utctime = metArray[:,0] |
|
1903 | if frequency == 30e6: | |
| 2025 | cmet = metArray[:,1] |
|
1904 | timeLag = 45*10**-3 | |
| 2026 | hmet = metArray1[:,3].astype(int) |
|
1905 | else: | |
| 2027 | h1met = heightList[hmet]*zenithList[cmet] |
|
1906 | timeLag = 15*10**-3 | |
| 2028 | vmet = metArray1[:,5] |
|
1907 | lag = numpy.ceil(timeLag/timeInterval) | |
| 2029 |
|
1908 | |||
| 2030 |
for i in range( |
|
1909 | for i in range(len(listMeteors)): | |
| 2031 | hmin = heightList[i] |
|
|||
| 2032 | hmax = heightList[i + 1] |
|
|||
| 2033 |
|
1910 | |||
| 2034 | vthisH = vmet[(h1met>=hmin) & (h1met<hmax)] |
|
1911 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### | |
|
|
1912 | meteorAux = numpy.zeros(16) | |||
| 2035 |
|
1913 | |||
|
|
1914 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) | |||
|
|
1915 | mHeight = listMeteors[i][0] | |||
|
|
1916 | mStart = listMeteors[i][1] | |||
|
|
1917 | mPeak = listMeteors[i][2] | |||
|
|
1918 | mEnd = listMeteors[i][3] | |||
| 2036 |
|
1919 | |||
|
|
1920 | #get the volt data between the start and end times of the meteor | |||
|
|
1921 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] | |||
|
|
1922 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |||
| 2037 |
|
1923 | |||
| 2038 | return data_output |
|
1924 | #3.6. Phase Difference estimation | |
|
|
1925 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) | |||
| 2039 |
|
1926 | |||
| 2040 | def run(self, dataOut, technique, **kwargs): |
|
1927 | #3.7. Phase difference removal & meteor start, peak and end times reestimated | |
|
|
1928 | #meteorVolts0.- all Channels, all Profiles | |||
|
|
1929 | meteorVolts0 = volts[:,:,mHeight] | |||
|
|
1930 | meteorThresh = noise[:,mHeight]*thresholdNoise | |||
|
|
1931 | meteorNoise = noise[:,mHeight] | |||
|
|
1932 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting | |||
|
|
1933 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power | |||
| 2041 |
|
1934 | |||
| 2042 | param = dataOut.data_param |
|
1935 | #Times reestimation | |
| 2043 | if dataOut.abscissaList != None: |
|
1936 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] | |
| 2044 | absc = dataOut.abscissaList[:-1] |
|
1937 | if mStart1.size > 0: | |
| 2045 | noise = dataOut.noise |
|
1938 | mStart1 = mStart1[-1] + 1 | |
| 2046 | heightList = dataOut.heightList |
|
|||
| 2047 | SNR = dataOut.data_SNR |
|
|||
| 2048 |
|
1939 | |||
| 2049 | if technique == 'DBS': |
|
1940 | else: | |
|
|
1941 | mStart1 = mPeak | |||
| 2050 |
|
1942 | |||
| 2051 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): |
|
1943 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 | |
| 2052 | theta_x = numpy.array(kwargs['dirCosx']) |
|
1944 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] | |
| 2053 | theta_y = numpy.array(kwargs['dirCosy']) |
|
1945 | if mEndDecayTime1.size == 0: | |
|
|
1946 | mEndDecayTime1 = powerNet0.size | |||
| 2054 | else: |
|
1947 | else: | |
| 2055 | elev = numpy.array(kwargs['elevation']) |
|
1948 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 | |
| 2056 | azim = numpy.array(kwargs['azimuth']) |
|
1949 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() | |
| 2057 | theta_x, theta_y = self.__calculateCosDir(elev, azim) |
|
|||
| 2058 | azimuth = kwargs['correctAzimuth'] |
|
|||
| 2059 | if kwargs.has_key('horizontalOnly'): |
|
|||
| 2060 | horizontalOnly = kwargs['horizontalOnly'] |
|
|||
| 2061 | else: horizontalOnly = False |
|
|||
| 2062 | if kwargs.has_key('correctFactor'): |
|
|||
| 2063 | correctFactor = kwargs['correctFactor'] |
|
|||
| 2064 | else: correctFactor = 1 |
|
|||
| 2065 | if kwargs.has_key('channelList'): |
|
|||
| 2066 | channelList = kwargs['channelList'] |
|
|||
| 2067 | if len(channelList) == 2: |
|
|||
| 2068 | horizontalOnly = True |
|
|||
| 2069 | arrayChannel = numpy.array(channelList) |
|
|||
| 2070 | param = param[arrayChannel,:,:] |
|
|||
| 2071 | theta_x = theta_x[arrayChannel] |
|
|||
| 2072 | theta_y = theta_y[arrayChannel] |
|
|||
| 2073 |
|
1950 | |||
| 2074 | velRadial0 = param[:,1,:] #Radial velocity |
|
1951 | #meteorVolts1.- all Channels, from start to end | |
| 2075 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(velRadial0, theta_x, theta_y, azimuth, correctFactor, horizontalOnly, heightList, SNR) #DBS Function |
|
1952 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] | |
| 2076 | dataOut.utctimeInit = dataOut.utctime |
|
1953 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] | |
| 2077 | dataOut.outputInterval = dataOut.paramInterval |
|
1954 | if meteorVolts2.shape[1] == 0: | |
|
|
1955 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] | |||
|
|
1956 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) | |||
|
|
1957 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) | |||
|
|
1958 | ##################### END PARAMETERS REESTIMATION ######################### | |||
| 2078 |
|
1959 | |||
| 2079 | elif technique == 'SA': |
|
1960 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## | |
|
|
1961 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis | |||
|
|
1962 | if meteorVolts2.shape[1] > 0: | |||
|
|
1963 | #Phase Difference re-estimation | |||
|
|
1964 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation | |||
|
|
1965 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) | |||
|
|
1966 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) | |||
|
|
1967 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) | |||
|
|
1968 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting | |||
| 2080 |
|
1969 | |||
| 2081 |
|
|
1970 | #Phase Difference RMS | |
| 2082 | position_x = kwargs['positionX'] |
|
1971 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) | |
| 2083 | position_y = kwargs['positionY'] |
|
1972 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) | |
| 2084 | azimuth = kwargs['azimuth'] |
|
1973 | #Data from Meteor | |
|
|
1974 | mPeak1 = powerNet1.argmax() + mStart1 | |||
|
|
1975 | mPeakPower1 = powerNet1.max() | |||
|
|
1976 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) | |||
|
|
1977 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux | |||
|
|
1978 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) | |||
|
|
1979 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) | |||
|
|
1980 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] | |||
|
|
1981 | #Vectorize | |||
|
|
1982 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] | |||
|
|
1983 | meteorAux[7:11] = phaseDiffint[0:4] | |||
|
|
1984 | ||||
|
|
1985 | #Rejection Criterions | |||
|
|
1986 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation | |||
|
|
1987 | meteorAux[-1] = 17 | |||
|
|
1988 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB | |||
|
|
1989 | meteorAux[-1] = 1 | |||
| 2085 |
|
1990 | |||
| 2086 | if kwargs.has_key('crosspairsList'): |
|
|||
| 2087 | pairs = kwargs['crosspairsList'] |
|
|||
| 2088 | else: |
|
|||
| 2089 | pairs = None |
|
|||
| 2090 |
|
1991 | |||
| 2091 | if kwargs.has_key('correctFactor'): |
|
|||
| 2092 | correctFactor = kwargs['correctFactor'] |
|
|||
| 2093 | else: |
|
1992 | else: | |
| 2094 | correctFactor = 1 |
|
1993 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] | |
|
|
1994 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis | |||
|
|
1995 | PowerSeries = 0 | |||
| 2095 |
|
1996 | |||
| 2096 | tau = dataOut.data_param |
|
1997 | listMeteors1.append(meteorAux) | |
| 2097 | _lambda = dataOut.C/dataOut.frequency |
|
1998 | listPowerSeries.append(PowerSeries) | |
| 2098 | pairsList = dataOut.groupList |
|
1999 | listVoltageSeries.append(meteorVolts1) | |
| 2099 | nChannels = dataOut.nChannels |
|
|||
| 2100 |
|
2000 | |||
| 2101 | dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) |
|
2001 | return listMeteors1, listPowerSeries, listVoltageSeries | |
| 2102 | dataOut.utctimeInit = dataOut.utctime |
|
|||
| 2103 | dataOut.outputInterval = dataOut.timeInterval |
|
|||
| 2104 |
|
|
2002 | ||
| 2105 | elif technique == 'Meteors': |
|
2003 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): | |
| 2106 | dataOut.flagNoData = True |
|
|||
| 2107 | self.__dataReady = False |
|
|||
| 2108 |
|
|
2004 | ||
| 2109 | if kwargs.has_key('nHours'): |
|
2005 | threshError = 10 | |
| 2110 | nHours = kwargs['nHours'] |
|
2006 | #Depending if it is 30 or 50 MHz | |
|
|
2007 | if frequency == 30e6: | |||
|
|
2008 | timeLag = 45*10**-3 | |||
| 2111 |
|
|
2009 | else: | |
| 2112 | nHours = 1 |
|
2010 | timeLag = 15*10**-3 | |
|
|
2011 | lag = numpy.ceil(timeLag/timeInterval) | |||
| 2113 |
|
|
2012 | ||
| 2114 | if kwargs.has_key('meteorsPerBin'): |
|
2013 | listMeteors1 = [] | |
| 2115 | meteorThresh = kwargs['meteorsPerBin'] |
|
|||
| 2116 | else: |
|
|||
| 2117 | meteorThresh = 6 |
|
|||
| 2118 |
|
|
2014 | ||
| 2119 | if kwargs.has_key('hmin'): |
|
2015 | for i in range(len(listMeteors)): | |
| 2120 | hmin = kwargs['hmin'] |
|
2016 | meteorPower = listPower[i] | |
| 2121 | else: hmin = 70 |
|
2017 | meteorAux = listMeteors[i] | |
| 2122 | if kwargs.has_key('hmax'): |
|
|||
| 2123 | hmax = kwargs['hmax'] |
|
|||
| 2124 | else: hmax = 110 |
|
|||
| 2125 |
|
|
2018 | ||
| 2126 | dataOut.outputInterval = nHours*3600 |
|
2019 | if meteorAux[-1] == 0: | |
| 2127 |
|
2020 | |||
| 2128 | if self.__isConfig == False: |
|
2021 | try: | |
| 2129 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2022 | indmax = meteorPower.argmax() | |
| 2130 | #Get Initial LTC time |
|
2023 | indlag = indmax + lag | |
| 2131 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
|||
| 2132 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
|||
| 2133 |
|
2024 | |||
| 2134 | self.__isConfig = True |
|
2025 | y = meteorPower[indlag:] | |
|
|
2026 | x = numpy.arange(0, y.size)*timeLag | |||
| 2135 |
|
2027 | |||
| 2136 | if self.__buffer == None: |
|
2028 | #first guess | |
| 2137 | self.__buffer = dataOut.data_param |
|
2029 | a = y[0] | |
| 2138 | self.__firstdata = copy.copy(dataOut) |
|
2030 | tau = timeLag | |
|
|
2031 | #exponential fit | |||
|
|
2032 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) | |||
|
|
2033 | y1 = self.__exponential_function(x, *popt) | |||
|
|
2034 | #error estimation | |||
|
|
2035 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) | |||
| 2139 |
|
2036 | |||
| 2140 | else: |
|
2037 | decayTime = popt[1] | |
| 2141 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2038 | riseTime = indmax*timeInterval | |
|
|
2039 | meteorAux[11:13] = [decayTime, error] | |||
| 2142 |
|
2040 | |||
| 2143 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2041 | #Table items 7, 8 and 11 | |
|
|
2042 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s | |||
|
|
2043 | meteorAux[-1] = 7 | |||
|
|
2044 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time | |||
|
|
2045 | meteorAux[-1] = 8 | |||
|
|
2046 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time | |||
|
|
2047 | meteorAux[-1] = 11 | |||
| 2144 |
|
2048 | |||
| 2145 | if self.__dataReady: |
|
|||
| 2146 | dataOut.utctimeInit = self.__initime |
|
|||
| 2147 |
|
2049 | |||
| 2148 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2050 | except: | |
|
|
2051 | meteorAux[-1] = 11 | |||
| 2149 |
|
2052 | |||
| 2150 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) |
|
|||
| 2151 | dataOut.flagNoData = False |
|
|||
| 2152 | self.__buffer = None |
|
|||
| 2153 |
|
|
2053 | ||
| 2154 | elif technique == 'Meteors1': |
|
2054 | listMeteors1.append(meteorAux) | |
| 2155 | dataOut.flagNoData = True |
|
|||
| 2156 | self.__dataReady = False |
|
|||
| 2157 |
|
|
2055 | ||
| 2158 | if kwargs.has_key('nMins'): |
|
2056 | return listMeteors1 | |
| 2159 | nMins = kwargs['nMins'] |
|
|||
| 2160 | else: nMins = 20 |
|
|||
| 2161 | if kwargs.has_key('rx_location'): |
|
|||
| 2162 | rx_location = kwargs['rx_location'] |
|
|||
| 2163 | else: rx_location = [(0,1),(1,1),(1,0)] |
|
|||
| 2164 | if kwargs.has_key('azimuth'): |
|
|||
| 2165 | azimuth = kwargs['azimuth'] |
|
|||
| 2166 | else: azimuth = 51 |
|
|||
| 2167 | if kwargs.has_key('dfactor'): |
|
|||
| 2168 | dfactor = kwargs['dfactor'] |
|
|||
| 2169 | if kwargs.has_key('mode'): |
|
|||
| 2170 | mode = kwargs['mode'] |
|
|||
| 2171 | else: mode = 'SA' |
|
|||
| 2172 |
|
2057 | |||
| 2173 | #Borrar luego esto |
|
2058 | #Exponential Function | |
| 2174 | if dataOut.groupList == None: |
|
|||
| 2175 | dataOut.groupList = [(0,1),(0,2),(1,2)] |
|
|||
| 2176 | groupList = dataOut.groupList |
|
|||
| 2177 | C = 3e8 |
|
|||
| 2178 | freq = 50e6 |
|
|||
| 2179 | lamb = C/freq |
|
|||
| 2180 | k = 2*numpy.pi/lamb |
|
|||
| 2181 |
|
2059 | |||
| 2182 | timeList = dataOut.abscissaList |
|
2060 | def __exponential_function(self, x, a, tau): | |
| 2183 | heightList = dataOut.heightList |
|
2061 | y = a*numpy.exp(-x/tau) | |
|
|
2062 | return y | |||
| 2184 |
|
2063 | |||
| 2185 | if self.__isConfig == False: |
|
2064 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): | |
| 2186 | dataOut.outputInterval = nMins*60 |
|
2065 | ||
| 2187 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2066 | pairslist1 = list(pairslist) | |
| 2188 | #Get Initial LTC time |
|
2067 | pairslist1.append((0,1)) | |
| 2189 | initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2068 | pairslist1.append((3,4)) | |
| 2190 | minuteAux = initime.minute |
|
2069 | numPairs = len(pairslist1) | |
| 2191 | minuteNew = int(numpy.floor(minuteAux/nMins)*nMins) |
|
2070 | #Time Lag | |
| 2192 | self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2071 | timeLag = 45*10**-3 | |
|
|
2072 | c = 3e8 | |||
|
|
2073 | lag = numpy.ceil(timeLag/timeInterval) | |||
|
|
2074 | freq = 30e6 | |||
| 2193 |
|
2075 | |||
| 2194 | self.__isConfig = True |
|
2076 | listMeteors1 = [] | |
| 2195 |
|
|
2077 | ||
| 2196 | if self.__buffer == None: |
|
2078 | for i in range(len(listMeteors)): | |
| 2197 | self.__buffer = dataOut.data_param |
|
2079 | meteorAux = listMeteors[i] | |
| 2198 | self.__firstdata = copy.copy(dataOut) |
|
2080 | if meteorAux[-1] == 0: | |
|
|
2081 | mStart = listMeteors[i][1] | |||
|
|
2082 | mPeak = listMeteors[i][2] | |||
|
|
2083 | mLag = mPeak - mStart + lag | |||
| 2199 |
|
2084 | |||
| 2200 | else: |
|
2085 | #get the volt data between the start and end times of the meteor | |
| 2201 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2086 | meteorVolts = listVolts[i] | |
|
|
2087 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |||
| 2202 |
|
2088 | |||
| 2203 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2089 | #Get CCF | |
|
|
2090 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) | |||
| 2204 |
|
2091 | |||
| 2205 | if self.__dataReady: |
|
2092 | #Method 2 | |
| 2206 | dataOut.utctimeInit = self.__initime |
|
2093 | slopes = numpy.zeros(numPairs) | |
| 2207 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2094 | time = numpy.array([-2,-1,1,2])*timeInterval | |
|
|
2095 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) | |||
| 2208 |
|
2096 | |||
| 2209 | metArray = self.__buffer |
|
2097 | #Correct phases | |
| 2210 | if mode == 'SA': |
|
2098 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] | |
| 2211 | dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList) |
|
2099 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |
| 2212 | elif mode == 'DBS': |
|
|||
| 2213 | dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList) |
|
|||
| 2214 | dataOut.data_output = dataOut.data_output.T |
|
|||
| 2215 | dataOut.flagNoData = False |
|
|||
| 2216 | self.__buffer = None |
|
|||
| 2217 |
|
2100 | |||
| 2218 | return |
|
2101 | if indDer[0].shape[0] > 0: | |
|
|
2102 | for i in range(indDer[0].shape[0]): | |||
|
|
2103 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) | |||
|
|
2104 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi | |||
| 2219 |
|
2105 | |||
| 2220 | class EWDriftsEstimation(Operation): |
|
2106 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) | |
|
|
2107 | for j in range(numPairs): | |||
|
|
2108 | fit = stats.linregress(time, angAllCCF[j,:]) | |||
|
|
2109 | slopes[j] = fit[0] | |||
| 2221 |
|
2110 | |||
| 2222 | def __init__(self): |
|
2111 | #Remove Outlier | |
| 2223 | Operation.__init__(self) |
|
2112 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |
|
|
2113 | # slopes = numpy.delete(slopes,indOut) | |||
|
|
2114 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |||
|
|
2115 | # slopes = numpy.delete(slopes,indOut) | |||
| 2224 |
|
2116 | |||
| 2225 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
2117 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 2226 | listPhi = phi.tolist() |
|
2118 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 2227 | maxid = listPhi.index(max(listPhi)) |
|
2119 | meteorAux[-2] = radialError | |
| 2228 | minid = listPhi.index(min(listPhi)) |
|
2120 | meteorAux[-3] = radialVelocity | |
| 2229 |
|
2121 | |||
| 2230 | rango = range(len(phi)) |
|
2122 | #Setting Error | |
| 2231 | # rango = numpy.delete(rango,maxid) |
|
2123 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s | |
|
|
2124 | if numpy.abs(radialVelocity) > 200: | |||
|
|
2125 | meteorAux[-1] = 15 | |||
|
|
2126 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity | |||
|
|
2127 | elif radialError > radialStdThresh: | |||
|
|
2128 | meteorAux[-1] = 12 | |||
| 2232 |
|
2129 | |||
| 2233 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
2130 | listMeteors1.append(meteorAux) | |
| 2234 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
2131 | return listMeteors1 | |
| 2235 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
|||
| 2236 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
|||
| 2237 |
|
|
2132 | ||
| 2238 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
2133 | def __setNewArrays(self, listMeteors, date, heiRang): | |
| 2239 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
|||
| 2240 |
|
2134 | |||
| 2241 | for i in rango: |
|
2135 | #New arrays | |
| 2242 | x = heiRang*math.cos(phi[i]) |
|
2136 | arrayMeteors = numpy.array(listMeteors) | |
| 2243 | y1 = velRadial[i,:] |
|
2137 | arrayParameters = numpy.zeros((len(listMeteors), 13)) | |
| 2244 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
|||
| 2245 |
|
|
2138 | ||
| 2246 | x1 = heiRang1 |
|
2139 | #Date inclusion | |
| 2247 | y11 = f1(x1) |
|
2140 | # date = re.findall(r'\((.*?)\)', date) | |
|
|
2141 | # date = date[0].split(',') | |||
|
|
2142 | # date = map(int, date) | |||
|
|
2143 | # | |||
|
|
2144 | # if len(date)<6: | |||
|
|
2145 | # date.append(0) | |||
|
|
2146 | # | |||
|
|
2147 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] | |||
|
|
2148 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) | |||
|
|
2149 | arrayDate = numpy.tile(date, (len(listMeteors))) | |||
| 2248 |
|
|
2150 | ||
| 2249 | y2 = SNR[i,:] |
|
2151 | #Meteor array | |
| 2250 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
2152 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] | |
| 2251 | y21 = f2(x1) |
|
2153 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) | |
| 2252 |
|
|
2154 | ||
| 2253 | velRadial1[i,:] = y11 |
|
2155 | #Parameters Array | |
| 2254 | SNR1[i,:] = y21 |
|
2156 | arrayParameters[:,0] = arrayDate #Date | |
|
|
2157 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range | |||
|
|
2158 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error | |||
|
|
2159 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases | |||
|
|
2160 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error | |||
| 2255 |
|
2161 | |||
| 2256 | return heiRang1, velRadial1, SNR1 |
|
|||
| 2257 |
|
2162 | |||
| 2258 | def run(self, dataOut, zenith, zenithCorrection): |
|
2163 | return arrayParameters | |
| 2259 | heiRang = dataOut.heightList |
|
|||
| 2260 | velRadial = dataOut.data_param[:,3,:] |
|
|||
| 2261 | SNR = dataOut.data_SNR |
|
|||
| 2262 |
|
2164 | |||
| 2263 | zenith = numpy.array(zenith) |
|
2165 | class CorrectMeteorPhases(Operation): | |
| 2264 | zenith -= zenithCorrection |
|
|||
| 2265 | zenith *= numpy.pi/180 |
|
|||
| 2266 |
|
|
2166 | ||
| 2267 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) |
|
2167 | def run(self, dataOut, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45, channelPositions = None): | |
| 2268 |
|
2168 | |||
| 2269 | alp = zenith[0] |
|
2169 | arrayParameters = dataOut.data_param | |
| 2270 |
|
|
2170 | pairsList = [] | |
|
|
2171 | pairx = (0,1) | |||
|
|
2172 | pairy = (2,3) | |||
|
|
2173 | pairsList.append(pairx) | |||
|
|
2174 | pairsList.append(pairy) | |||
|
|
2175 | jph = numpy.zeros(4) | |||
| 2271 |
|
2176 | |||
| 2272 | w_w = velRadial1[0,:] |
|
2177 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |
| 2273 | w_e = velRadial1[1,:] |
|
2178 | # arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |
|
|
2179 | arrayParameters[:,8:12] = numpy.angle(numpy.exp(1j*(arrayParameters[:,8:12] + phaseOffsets))) | |||
| 2274 |
|
2180 | |||
| 2275 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) |
|
2181 | meteorOps = MeteorOperations() | |
| 2276 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) |
|
2182 | if channelPositions == None: | |
|
|
2183 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |||
|
|
2184 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |||
| 2277 |
|
|
2185 | ||
| 2278 | winds = numpy.vstack((u,w)) |
|
2186 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |
|
|
2187 | h = (hmin,hmax) | |||
| 2279 |
|
|
2188 | ||
| 2280 | dataOut.heightList = heiRang1 |
|
2189 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, distances, jph) | |
| 2281 | dataOut.data_output = winds |
|
|||
| 2282 | dataOut.data_SNR = SNR1 |
|
|||
| 2283 |
|
2190 | |||
| 2284 | dataOut.utctimeInit = dataOut.utctime |
|
2191 | dataOut.data_param = arrayParameters | |
| 2285 | dataOut.outputInterval = dataOut.timeInterval |
|
|||
| 2286 | return |
|
2192 | return | |
| 2287 |
|
2193 | |||
| 2288 | class PhaseCalibration(Operation): |
|
2194 | class PhaseCalibration(Operation): | |
| 2289 |
|
2195 | |||
| 2290 | __buffer = None |
|
2196 | __buffer = None | |
| 2291 |
|
2197 | |||
| 2292 | __initime = None |
|
2198 | __initime = None | |
| 2293 |
|
2199 | |||
| 2294 | __dataReady = False |
|
2200 | __dataReady = False | |
| 2295 |
|
2201 | |||
| 2296 | __isConfig = False |
|
2202 | __isConfig = False | |
| 2297 |
|
2203 | |||
| 2298 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): |
|
2204 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): | |
| 2299 |
|
2205 | |||
| 2300 | dataTime = currentTime + paramInterval |
|
2206 | dataTime = currentTime + paramInterval | |
| 2301 | deltaTime = dataTime - initTime |
|
2207 | deltaTime = dataTime - initTime | |
| 2302 |
|
2208 | |||
| 2303 | if deltaTime >= outputInterval or deltaTime < 0: |
|
2209 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 2304 | return True |
|
2210 | return True | |
| 2305 |
|
2211 | |||
| 2306 | return False |
|
2212 | return False | |
| 2307 |
|
2213 | |||
| 2308 | def __getGammas(self, pairs, d, phases): |
|
2214 | def __getGammas(self, pairs, d, phases): | |
| 2309 | gammas = numpy.zeros(2) |
|
2215 | gammas = numpy.zeros(2) | |
| 2310 |
|
2216 | |||
| 2311 | for i in range(len(pairs)): |
|
2217 | for i in range(len(pairs)): | |
| 2312 |
|
2218 | |||
| 2313 | pairi = pairs[i] |
|
2219 | pairi = pairs[i] | |
| 2314 |
|
2220 | |||
| 2315 | phip3 = phases[:,pairi[1]] |
|
2221 | phip3 = phases[:,pairi[1]] | |
| 2316 | d3 = d[pairi[1]] |
|
2222 | d3 = d[pairi[1]] | |
| 2317 | phip2 = phases[:,pairi[0]] |
|
2223 | phip2 = phases[:,pairi[0]] | |
| 2318 | d2 = d[pairi[0]] |
|
2224 | d2 = d[pairi[0]] | |
| 2319 | #Calculating gamma |
|
2225 | #Calculating gamma | |
| 2320 | # jdcos = alp1/(k*d1) |
|
2226 | # jdcos = alp1/(k*d1) | |
| 2321 | # jgamma = numpy.angle(numpy.exp(1j*(d0*alp1/d1 - alp0))) |
|
2227 | # jgamma = numpy.angle(numpy.exp(1j*(d0*alp1/d1 - alp0))) | |
| 2322 | jgamma = -phip2*d3/d2 - phip3 |
|
2228 | jgamma = -phip2*d3/d2 - phip3 | |
| 2323 | jgamma = numpy.angle(numpy.exp(1j*jgamma)) |
|
2229 | jgamma = numpy.angle(numpy.exp(1j*jgamma)) | |
| 2324 | # jgamma[jgamma>numpy.pi] -= 2*numpy.pi |
|
2230 | # jgamma[jgamma>numpy.pi] -= 2*numpy.pi | |
| 2325 | # jgamma[jgamma<-numpy.pi] += 2*numpy.pi |
|
2231 | # jgamma[jgamma<-numpy.pi] += 2*numpy.pi | |
| 2326 |
|
2232 | |||
| 2327 | #Revised distribution |
|
2233 | #Revised distribution | |
| 2328 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) |
|
2234 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) | |
| 2329 |
|
2235 | |||
| 2330 | #Histogram |
|
2236 | #Histogram | |
| 2331 | nBins = 64.0 |
|
2237 | nBins = 64.0 | |
| 2332 | rmin = -0.5*numpy.pi |
|
2238 | rmin = -0.5*numpy.pi | |
| 2333 | rmax = 0.5*numpy.pi |
|
2239 | rmax = 0.5*numpy.pi | |
| 2334 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) |
|
2240 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) | |
| 2335 |
|
2241 | |||
| 2336 | meteorsY = phaseHisto[0] |
|
2242 | meteorsY = phaseHisto[0] | |
| 2337 | phasesX = phaseHisto[1][:-1] |
|
2243 | phasesX = phaseHisto[1][:-1] | |
| 2338 | width = phasesX[1] - phasesX[0] |
|
2244 | width = phasesX[1] - phasesX[0] | |
| 2339 | phasesX += width/2 |
|
2245 | phasesX += width/2 | |
| 2340 |
|
2246 | |||
| 2341 | #Gaussian aproximation |
|
2247 | #Gaussian aproximation | |
| 2342 | bpeak = meteorsY.argmax() |
|
2248 | bpeak = meteorsY.argmax() | |
| 2343 | peak = meteorsY.max() |
|
2249 | peak = meteorsY.max() | |
| 2344 | jmin = bpeak - 5 |
|
2250 | jmin = bpeak - 5 | |
| 2345 | jmax = bpeak + 5 + 1 |
|
2251 | jmax = bpeak + 5 + 1 | |
| 2346 |
|
2252 | |||
| 2347 | if jmin<0: |
|
2253 | if jmin<0: | |
| 2348 | jmin = 0 |
|
2254 | jmin = 0 | |
| 2349 | jmax = 6 |
|
2255 | jmax = 6 | |
| 2350 | elif jmax > meteorsY.size: |
|
2256 | elif jmax > meteorsY.size: | |
| 2351 | jmin = meteorsY.size - 6 |
|
2257 | jmin = meteorsY.size - 6 | |
| 2352 | jmax = meteorsY.size |
|
2258 | jmax = meteorsY.size | |
| 2353 |
|
2259 | |||
| 2354 | x0 = numpy.array([peak,bpeak,50]) |
|
2260 | x0 = numpy.array([peak,bpeak,50]) | |
| 2355 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) |
|
2261 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) | |
| 2356 |
|
2262 | |||
| 2357 | #Gammas |
|
2263 | #Gammas | |
| 2358 | gammas[i] = coeff[0][1] |
|
2264 | gammas[i] = coeff[0][1] | |
| 2359 |
|
2265 | |||
| 2360 | return gammas |
|
2266 | return gammas | |
| 2361 |
|
2267 | |||
| 2362 | def __residualFunction(self, coeffs, y, t): |
|
2268 | def __residualFunction(self, coeffs, y, t): | |
| 2363 |
|
2269 | |||
| 2364 | return y - self.__gauss_function(t, coeffs) |
|
2270 | return y - self.__gauss_function(t, coeffs) | |
| 2365 |
|
2271 | |||
| 2366 | def __gauss_function(self, t, coeffs): |
|
2272 | def __gauss_function(self, t, coeffs): | |
| 2367 |
|
2273 | |||
| 2368 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) |
|
2274 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) | |
| 2369 |
|
2275 | |||
| 2370 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): |
|
2276 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): | |
| 2371 | meteorOps = MeteorOperations() |
|
2277 | meteorOps = MeteorOperations() | |
| 2372 | nchan = 4 |
|
2278 | nchan = 4 | |
| 2373 | pairx = pairsList[0] |
|
2279 | pairx = pairsList[0] | |
| 2374 | pairy = pairsList[1] |
|
2280 | pairy = pairsList[1] | |
| 2375 | center_xangle = 0 |
|
2281 | center_xangle = 0 | |
| 2376 | center_yangle = 0 |
|
2282 | center_yangle = 0 | |
| 2377 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) |
|
2283 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) | |
| 2378 | ntimes = len(range_angle) |
|
2284 | ntimes = len(range_angle) | |
| 2379 |
|
2285 | |||
| 2380 | nstepsx = 20.0 |
|
2286 | nstepsx = 20.0 | |
| 2381 | nstepsy = 20.0 |
|
2287 | nstepsy = 20.0 | |
| 2382 |
|
2288 | |||
| 2383 | for iz in range(ntimes): |
|
2289 | for iz in range(ntimes): | |
| 2384 | min_xangle = -range_angle[iz]/2 + center_xangle |
|
2290 | min_xangle = -range_angle[iz]/2 + center_xangle | |
| 2385 | max_xangle = range_angle[iz]/2 + center_xangle |
|
2291 | max_xangle = range_angle[iz]/2 + center_xangle | |
| 2386 | min_yangle = -range_angle[iz]/2 + center_yangle |
|
2292 | min_yangle = -range_angle[iz]/2 + center_yangle | |
| 2387 | max_yangle = range_angle[iz]/2 + center_yangle |
|
2293 | max_yangle = range_angle[iz]/2 + center_yangle | |
| 2388 |
|
2294 | |||
| 2389 | inc_x = (max_xangle-min_xangle)/nstepsx |
|
2295 | inc_x = (max_xangle-min_xangle)/nstepsx | |
| 2390 | inc_y = (max_yangle-min_yangle)/nstepsy |
|
2296 | inc_y = (max_yangle-min_yangle)/nstepsy | |
| 2391 |
|
2297 | |||
| 2392 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle |
|
2298 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle | |
| 2393 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle |
|
2299 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle | |
| 2394 | penalty = numpy.zeros((nstepsx,nstepsy)) |
|
2300 | penalty = numpy.zeros((nstepsx,nstepsy)) | |
| 2395 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) |
|
2301 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) | |
| 2396 | jph = numpy.zeros(nchan) |
|
2302 | jph = numpy.zeros(nchan) | |
| 2397 |
|
2303 | |||
| 2398 | # Iterations looking for the offset |
|
2304 | # Iterations looking for the offset | |
| 2399 | for iy in range(int(nstepsy)): |
|
2305 | for iy in range(int(nstepsy)): | |
| 2400 | for ix in range(int(nstepsx)): |
|
2306 | for ix in range(int(nstepsx)): | |
| 2401 | jph[pairy[1]] = alpha_y[iy] |
|
2307 | jph[pairy[1]] = alpha_y[iy] | |
| 2402 | jph[pairy[0]] = -gammas[1] - alpha_y[iy]*d[pairy[1]]/d[pairy[0]] |
|
2308 | jph[pairy[0]] = -gammas[1] - alpha_y[iy]*d[pairy[1]]/d[pairy[0]] | |
| 2403 |
|
2309 | |||
| 2404 | jph[pairx[1]] = alpha_x[ix] |
|
2310 | jph[pairx[1]] = alpha_x[ix] | |
| 2405 | jph[pairx[0]] = -gammas[0] - alpha_x[ix]*d[pairx[1]]/d[pairx[0]] |
|
2311 | jph[pairx[0]] = -gammas[0] - alpha_x[ix]*d[pairx[1]]/d[pairx[0]] | |
| 2406 |
|
2312 | |||
| 2407 | jph_array[:,ix,iy] = jph |
|
2313 | jph_array[:,ix,iy] = jph | |
| 2408 |
|
2314 | |||
| 2409 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, d, jph) |
|
2315 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, d, jph) | |
| 2410 | error = meteorsArray1[:,-1] |
|
2316 | error = meteorsArray1[:,-1] | |
| 2411 | ind1 = numpy.where(error==0)[0] |
|
2317 | ind1 = numpy.where(error==0)[0] | |
| 2412 | penalty[ix,iy] = ind1.size |
|
2318 | penalty[ix,iy] = ind1.size | |
| 2413 |
|
2319 | |||
| 2414 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) |
|
2320 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) | |
| 2415 | phOffset = jph_array[:,i,j] |
|
2321 | phOffset = jph_array[:,i,j] | |
| 2416 |
|
2322 | |||
| 2417 | center_xangle = phOffset[pairx[1]] |
|
2323 | center_xangle = phOffset[pairx[1]] | |
| 2418 | center_yangle = phOffset[pairy[1]] |
|
2324 | center_yangle = phOffset[pairy[1]] | |
| 2419 |
|
2325 | |||
| 2420 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) |
|
2326 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) | |
| 2421 | phOffset = phOffset*180/numpy.pi |
|
2327 | phOffset = phOffset*180/numpy.pi | |
| 2422 | return phOffset |
|
2328 | return phOffset | |
| 2423 |
|
2329 | |||
| 2424 |
|
2330 | |||
| 2425 | def run(self, dataOut, hmin, hmax, channelPositions=None, nHours = 1): |
|
2331 | def run(self, dataOut, hmin, hmax, channelPositions=None, nHours = 1): | |
| 2426 |
|
2332 | |||
| 2427 | dataOut.flagNoData = True |
|
2333 | dataOut.flagNoData = True | |
| 2428 | self.__dataReady = False |
|
2334 | self.__dataReady = False | |
| 2429 | dataOut.outputInterval = nHours*3600 |
|
2335 | dataOut.outputInterval = nHours*3600 | |
| 2430 |
|
2336 | |||
| 2431 | if self.__isConfig == False: |
|
2337 | if self.__isConfig == False: | |
| 2432 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2338 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 2433 | #Get Initial LTC time |
|
2339 | #Get Initial LTC time | |
| 2434 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2340 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 2435 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2341 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 2436 |
|
2342 | |||
| 2437 | self.__isConfig = True |
|
2343 | self.__isConfig = True | |
| 2438 |
|
2344 | |||
| 2439 | if self.__buffer == None: |
|
2345 | if self.__buffer == None: | |
| 2440 | self.__buffer = dataOut.data_param.copy() |
|
2346 | self.__buffer = dataOut.data_param.copy() | |
| 2441 |
|
2347 | |||
| 2442 | else: |
|
2348 | else: | |
| 2443 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2349 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 2444 |
|
2350 | |||
| 2445 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2351 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 2446 |
|
2352 | |||
| 2447 | if self.__dataReady: |
|
2353 | if self.__dataReady: | |
| 2448 | dataOut.utctimeInit = self.__initime |
|
2354 | dataOut.utctimeInit = self.__initime | |
| 2449 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2355 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 2450 |
|
2356 | |||
| 2451 | freq = dataOut.frequency |
|
2357 | freq = dataOut.frequency | |
| 2452 | c = dataOut.C #m/s |
|
2358 | c = dataOut.C #m/s | |
| 2453 | lamb = c/freq |
|
2359 | lamb = c/freq | |
| 2454 | k = 2*numpy.pi/lamb |
|
2360 | k = 2*numpy.pi/lamb | |
| 2455 | azimuth = 0 |
|
2361 | azimuth = 0 | |
| 2456 | h = (hmin, hmax) |
|
2362 | h = (hmin, hmax) | |
| 2457 | pairs = ((0,1),(2,3)) |
|
2363 | pairs = ((0,1),(2,3)) | |
| 2458 |
|
2364 | |||
| 2459 | if channelPositions == None: |
|
2365 | if channelPositions == None: | |
| 2460 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T |
|
2366 | # channelPositions = [(2.5,0), (0,2.5), (0,0), (0,4.5), (-2,0)] #T | |
| 2461 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella |
|
2367 | channelPositions = [(4.5,2), (2,4.5), (2,2), (2,0), (0,2)] #Estrella | |
| 2462 | meteorOps = MeteorOperations() |
|
2368 | meteorOps = MeteorOperations() | |
| 2463 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) |
|
2369 | pairslist0, distances = meteorOps.getPhasePairs(channelPositions) | |
| 2464 |
|
2370 | |||
| 2465 | # distances1 = [-distances[0]*lamb, distances[1]*lamb, -distances[2]*lamb, distances[3]*lamb] |
|
2371 | # distances1 = [-distances[0]*lamb, distances[1]*lamb, -distances[2]*lamb, distances[3]*lamb] | |
| 2466 |
|
2372 | |||
| 2467 | meteorsArray = self.__buffer |
|
2373 | meteorsArray = self.__buffer | |
| 2468 | error = meteorsArray[:,-1] |
|
2374 | error = meteorsArray[:,-1] | |
| 2469 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) |
|
2375 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) | |
| 2470 | ind1 = numpy.where(boolError)[0] |
|
2376 | ind1 = numpy.where(boolError)[0] | |
| 2471 | meteorsArray = meteorsArray[ind1,:] |
|
2377 | meteorsArray = meteorsArray[ind1,:] | |
| 2472 | meteorsArray[:,-1] = 0 |
|
2378 | meteorsArray[:,-1] = 0 | |
| 2473 | phases = meteorsArray[:,8:12] |
|
2379 | phases = meteorsArray[:,8:12] | |
| 2474 |
|
2380 | |||
| 2475 | #Calculate Gammas |
|
2381 | #Calculate Gammas | |
| 2476 | gammas = self.__getGammas(pairs, distances, phases) |
|
2382 | gammas = self.__getGammas(pairs, distances, phases) | |
| 2477 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 |
|
2383 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 | |
| 2478 | #Calculate Phases |
|
2384 | #Calculate Phases | |
| 2479 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) |
|
2385 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) | |
| 2480 | phasesOff = phasesOff.reshape((1,phasesOff.size)) |
|
2386 | phasesOff = phasesOff.reshape((1,phasesOff.size)) | |
| 2481 | dataOut.data_output = -phasesOff |
|
2387 | dataOut.data_output = -phasesOff | |
| 2482 | dataOut.flagNoData = False |
|
2388 | dataOut.flagNoData = False | |
| 2483 | self.__buffer = None |
|
2389 | self.__buffer = None | |
| 2484 |
|
2390 | |||
| 2485 |
|
2391 | |||
| 2486 | return |
|
2392 | return | |
| 2487 |
|
2393 | |||
| 2488 | class MeteorOperations(): |
|
2394 | class MeteorOperations(): | |
| 2489 |
|
2395 | |||
| 2490 | def __init__(self): |
|
2396 | def __init__(self): | |
| 2491 |
|
2397 | |||
| 2492 | return |
|
2398 | return | |
| 2493 |
|
2399 | |||
| 2494 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, distances, jph): |
|
2400 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, distances, jph): | |
| 2495 |
|
2401 | |||
| 2496 | arrayParameters = arrayParameters0.copy() |
|
2402 | arrayParameters = arrayParameters0.copy() | |
| 2497 | hmin = h[0] |
|
2403 | hmin = h[0] | |
| 2498 | hmax = h[1] |
|
2404 | hmax = h[1] | |
| 2499 |
|
2405 | |||
| 2500 | #Calculate AOA (Error N 3, 4) |
|
2406 | #Calculate AOA (Error N 3, 4) | |
| 2501 | #JONES ET AL. 1998 |
|
2407 | #JONES ET AL. 1998 | |
| 2502 | AOAthresh = numpy.pi/8 |
|
2408 | AOAthresh = numpy.pi/8 | |
| 2503 | error = arrayParameters[:,-1] |
|
2409 | error = arrayParameters[:,-1] | |
| 2504 | phases = -arrayParameters[:,8:12] + jph |
|
2410 | phases = -arrayParameters[:,8:12] + jph | |
| 2505 | # phases = numpy.unwrap(phases) |
|
2411 | # phases = numpy.unwrap(phases) | |
| 2506 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, distances, error, AOAthresh, azimuth) |
|
2412 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, distances, error, AOAthresh, azimuth) | |
| 2507 |
|
2413 | |||
| 2508 | #Calculate Heights (Error N 13 and 14) |
|
2414 | #Calculate Heights (Error N 13 and 14) | |
| 2509 | error = arrayParameters[:,-1] |
|
2415 | error = arrayParameters[:,-1] | |
| 2510 | Ranges = arrayParameters[:,1] |
|
2416 | Ranges = arrayParameters[:,1] | |
| 2511 | zenith = arrayParameters[:,4] |
|
2417 | zenith = arrayParameters[:,4] | |
| 2512 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) |
|
2418 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) | |
| 2513 |
|
2419 | |||
| 2514 | #----------------------- Get Final data ------------------------------------ |
|
2420 | #----------------------- Get Final data ------------------------------------ | |
| 2515 | # error = arrayParameters[:,-1] |
|
2421 | # error = arrayParameters[:,-1] | |
| 2516 | # ind1 = numpy.where(error==0)[0] |
|
2422 | # ind1 = numpy.where(error==0)[0] | |
| 2517 | # arrayParameters = arrayParameters[ind1,:] |
|
2423 | # arrayParameters = arrayParameters[ind1,:] | |
| 2518 |
|
2424 | |||
| 2519 | return arrayParameters |
|
2425 | return arrayParameters | |
| 2520 |
|
2426 | |||
| 2521 | def __getAOA(self, phases, pairsList, directions, error, AOAthresh, azimuth): |
|
2427 | def __getAOA(self, phases, pairsList, directions, error, AOAthresh, azimuth): | |
| 2522 |
|
2428 | |||
| 2523 | arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
2429 | arrayAOA = numpy.zeros((phases.shape[0],3)) | |
| 2524 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList,directions) |
|
2430 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList,directions) | |
| 2525 |
|
2431 | |||
| 2526 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
2432 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |
| 2527 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
2433 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |
| 2528 | arrayAOA[:,2] = cosDirError |
|
2434 | arrayAOA[:,2] = cosDirError | |
| 2529 |
|
2435 | |||
| 2530 | azimuthAngle = arrayAOA[:,0] |
|
2436 | azimuthAngle = arrayAOA[:,0] | |
| 2531 | zenithAngle = arrayAOA[:,1] |
|
2437 | zenithAngle = arrayAOA[:,1] | |
| 2532 |
|
2438 | |||
| 2533 | #Setting Error |
|
2439 | #Setting Error | |
| 2534 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] |
|
2440 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] | |
| 2535 | error[indError] = 0 |
|
2441 | error[indError] = 0 | |
| 2536 | #Number 3: AOA not fesible |
|
2442 | #Number 3: AOA not fesible | |
| 2537 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
2443 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |
| 2538 | error[indInvalid] = 3 |
|
2444 | error[indInvalid] = 3 | |
| 2539 | #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
2445 | #Number 4: Large difference in AOAs obtained from different antenna baselines | |
| 2540 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
2446 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |
| 2541 | error[indInvalid] = 4 |
|
2447 | error[indInvalid] = 4 | |
| 2542 | return arrayAOA, error |
|
2448 | return arrayAOA, error | |
| 2543 |
|
2449 | |||
| 2544 | def __getDirectionCosines(self, arrayPhase, pairsList, distances): |
|
2450 | def __getDirectionCosines(self, arrayPhase, pairsList, distances): | |
| 2545 |
|
2451 | |||
| 2546 | #Initializing some variables |
|
2452 | #Initializing some variables | |
| 2547 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
2453 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |
| 2548 | ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
2454 | ang_aux = ang_aux.reshape(1,ang_aux.size) | |
| 2549 |
|
2455 | |||
| 2550 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
2456 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |
| 2551 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
2457 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |
| 2552 |
|
2458 | |||
| 2553 |
|
2459 | |||
| 2554 | for i in range(2): |
|
2460 | for i in range(2): | |
| 2555 | ph0 = arrayPhase[:,pairsList[i][0]] |
|
2461 | ph0 = arrayPhase[:,pairsList[i][0]] | |
| 2556 | ph1 = arrayPhase[:,pairsList[i][1]] |
|
2462 | ph1 = arrayPhase[:,pairsList[i][1]] | |
| 2557 | d0 = distances[pairsList[i][0]] |
|
2463 | d0 = distances[pairsList[i][0]] | |
| 2558 | d1 = distances[pairsList[i][1]] |
|
2464 | d1 = distances[pairsList[i][1]] | |
| 2559 |
|
2465 | |||
| 2560 | ph0_aux = ph0 + ph1 |
|
2466 | ph0_aux = ph0 + ph1 | |
| 2561 | ph0_aux = numpy.angle(numpy.exp(1j*ph0_aux)) |
|
2467 | ph0_aux = numpy.angle(numpy.exp(1j*ph0_aux)) | |
| 2562 | # ph0_aux[ph0_aux > numpy.pi] -= 2*numpy.pi |
|
2468 | # ph0_aux[ph0_aux > numpy.pi] -= 2*numpy.pi | |
| 2563 | # ph0_aux[ph0_aux < -numpy.pi] += 2*numpy.pi |
|
2469 | # ph0_aux[ph0_aux < -numpy.pi] += 2*numpy.pi | |
| 2564 | #First Estimation |
|
2470 | #First Estimation | |
| 2565 | cosdir0[:,i] = (ph0_aux)/(2*numpy.pi*(d0 - d1)) |
|
2471 | cosdir0[:,i] = (ph0_aux)/(2*numpy.pi*(d0 - d1)) | |
| 2566 |
|
2472 | |||
| 2567 | #Most-Accurate Second Estimation |
|
2473 | #Most-Accurate Second Estimation | |
| 2568 | phi1_aux = ph0 - ph1 |
|
2474 | phi1_aux = ph0 - ph1 | |
| 2569 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
2475 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |
| 2570 | #Direction Cosine 1 |
|
2476 | #Direction Cosine 1 | |
| 2571 | cosdir1 = (phi1_aux + ang_aux)/(2*numpy.pi*(d0 + d1)) |
|
2477 | cosdir1 = (phi1_aux + ang_aux)/(2*numpy.pi*(d0 + d1)) | |
| 2572 |
|
2478 | |||
| 2573 | #Searching the correct Direction Cosine |
|
2479 | #Searching the correct Direction Cosine | |
| 2574 | cosdir0_aux = cosdir0[:,i] |
|
2480 | cosdir0_aux = cosdir0[:,i] | |
| 2575 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
2481 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |
| 2576 | #Minimum Distance |
|
2482 | #Minimum Distance | |
| 2577 | cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
2483 | cosDiff = (cosdir1 - cosdir0_aux)**2 | |
| 2578 | indcos = cosDiff.argmin(axis = 1) |
|
2484 | indcos = cosDiff.argmin(axis = 1) | |
| 2579 | #Saving Value obtained |
|
2485 | #Saving Value obtained | |
| 2580 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
2486 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |
| 2581 |
|
2487 | |||
| 2582 | return cosdir0, cosdir |
|
2488 | return cosdir0, cosdir | |
| 2583 |
|
2489 | |||
| 2584 | def __calculateAOA(self, cosdir, azimuth): |
|
2490 | def __calculateAOA(self, cosdir, azimuth): | |
| 2585 | cosdirX = cosdir[:,0] |
|
2491 | cosdirX = cosdir[:,0] | |
| 2586 | cosdirY = cosdir[:,1] |
|
2492 | cosdirY = cosdir[:,1] | |
| 2587 |
|
2493 | |||
| 2588 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
2494 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |
| 2589 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth#0 deg north, 90 deg east |
|
2495 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth#0 deg north, 90 deg east | |
| 2590 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
2496 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |
| 2591 |
|
2497 | |||
| 2592 | return angles |
|
2498 | return angles | |
| 2593 |
|
2499 | |||
| 2594 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
2500 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |
| 2595 |
|
2501 | |||
| 2596 | Ramb = 375 #Ramb = c/(2*PRF) |
|
2502 | Ramb = 375 #Ramb = c/(2*PRF) | |
| 2597 | Re = 6371 #Earth Radius |
|
2503 | Re = 6371 #Earth Radius | |
| 2598 | heights = numpy.zeros(Ranges.shape) |
|
2504 | heights = numpy.zeros(Ranges.shape) | |
| 2599 |
|
2505 | |||
| 2600 | R_aux = numpy.array([0,1,2])*Ramb |
|
2506 | R_aux = numpy.array([0,1,2])*Ramb | |
| 2601 | R_aux = R_aux.reshape(1,R_aux.size) |
|
2507 | R_aux = R_aux.reshape(1,R_aux.size) | |
| 2602 |
|
2508 | |||
| 2603 | Ranges = Ranges.reshape(Ranges.size,1) |
|
2509 | Ranges = Ranges.reshape(Ranges.size,1) | |
| 2604 |
|
2510 | |||
| 2605 | Ri = Ranges + R_aux |
|
2511 | Ri = Ranges + R_aux | |
| 2606 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
2512 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |
| 2607 |
|
2513 | |||
| 2608 | #Check if there is a height between 70 and 110 km |
|
2514 | #Check if there is a height between 70 and 110 km | |
| 2609 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
2515 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |
| 2610 | ind_h = numpy.where(h_bool == 1)[0] |
|
2516 | ind_h = numpy.where(h_bool == 1)[0] | |
| 2611 |
|
2517 | |||
| 2612 | hCorr = hi[ind_h, :] |
|
2518 | hCorr = hi[ind_h, :] | |
| 2613 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
2519 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |
| 2614 |
|
2520 | |||
| 2615 | hCorr = hi[ind_hCorr] |
|
2521 | hCorr = hi[ind_hCorr] | |
| 2616 | heights[ind_h] = hCorr |
|
2522 | heights[ind_h] = hCorr | |
| 2617 |
|
2523 | |||
| 2618 | #Setting Error |
|
2524 | #Setting Error | |
| 2619 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
2525 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |
| 2620 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
2526 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |
| 2621 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] |
|
2527 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] | |
| 2622 | error[indError] = 0 |
|
2528 | error[indError] = 0 | |
| 2623 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
2529 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |
| 2624 | error[indInvalid2] = 14 |
|
2530 | error[indInvalid2] = 14 | |
| 2625 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
2531 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |
| 2626 | error[indInvalid1] = 13 |
|
2532 | error[indInvalid1] = 13 | |
| 2627 |
|
2533 | |||
| 2628 | return heights, error |
|
2534 | return heights, error | |
| 2629 |
|
2535 | |||
| 2630 | def getPhasePairs(self, channelPositions): |
|
2536 | def getPhasePairs(self, channelPositions): | |
| 2631 | chanPos = numpy.array(channelPositions) |
|
2537 | chanPos = numpy.array(channelPositions) | |
| 2632 | listOper = list(itertools.combinations(range(5),2)) |
|
2538 | listOper = list(itertools.combinations(range(5),2)) | |
| 2633 |
|
2539 | |||
| 2634 | distances = numpy.zeros(4) |
|
2540 | distances = numpy.zeros(4) | |
| 2635 | axisX = [] |
|
2541 | axisX = [] | |
| 2636 | axisY = [] |
|
2542 | axisY = [] | |
| 2637 | distX = numpy.zeros(3) |
|
2543 | distX = numpy.zeros(3) | |
| 2638 | distY = numpy.zeros(3) |
|
2544 | distY = numpy.zeros(3) | |
| 2639 | ix = 0 |
|
2545 | ix = 0 | |
| 2640 | iy = 0 |
|
2546 | iy = 0 | |
| 2641 |
|
2547 | |||
| 2642 | pairX = numpy.zeros((2,2)) |
|
2548 | pairX = numpy.zeros((2,2)) | |
| 2643 | pairY = numpy.zeros((2,2)) |
|
2549 | pairY = numpy.zeros((2,2)) | |
| 2644 |
|
2550 | |||
| 2645 | for i in range(len(listOper)): |
|
2551 | for i in range(len(listOper)): | |
| 2646 | pairi = listOper[i] |
|
2552 | pairi = listOper[i] | |
| 2647 |
|
2553 | |||
| 2648 | posDif = numpy.abs(chanPos[pairi[0],:] - chanPos[pairi[1],:]) |
|
2554 | posDif = numpy.abs(chanPos[pairi[0],:] - chanPos[pairi[1],:]) | |
| 2649 |
|
2555 | |||
| 2650 | if posDif[0] == 0: |
|
2556 | if posDif[0] == 0: | |
| 2651 | axisY.append(pairi) |
|
2557 | axisY.append(pairi) | |
| 2652 | distY[iy] = posDif[1] |
|
2558 | distY[iy] = posDif[1] | |
| 2653 | iy += 1 |
|
2559 | iy += 1 | |
| 2654 | elif posDif[1] == 0: |
|
2560 | elif posDif[1] == 0: | |
| 2655 | axisX.append(pairi) |
|
2561 | axisX.append(pairi) | |
| 2656 | distX[ix] = posDif[0] |
|
2562 | distX[ix] = posDif[0] | |
| 2657 | ix += 1 |
|
2563 | ix += 1 | |
| 2658 |
|
2564 | |||
| 2659 | for i in range(2): |
|
2565 | for i in range(2): | |
| 2660 | if i==0: |
|
2566 | if i==0: | |
| 2661 | dist0 = distX |
|
2567 | dist0 = distX | |
| 2662 | axis0 = axisX |
|
2568 | axis0 = axisX | |
| 2663 | else: |
|
2569 | else: | |
| 2664 | dist0 = distY |
|
2570 | dist0 = distY | |
| 2665 | axis0 = axisY |
|
2571 | axis0 = axisY | |
| 2666 |
|
2572 | |||
| 2667 | side = numpy.argsort(dist0)[:-1] |
|
2573 | side = numpy.argsort(dist0)[:-1] | |
| 2668 | axis0 = numpy.array(axis0)[side,:] |
|
2574 | axis0 = numpy.array(axis0)[side,:] | |
| 2669 | chanC = int(numpy.intersect1d(axis0[0,:], axis0[1,:])[0]) |
|
2575 | chanC = int(numpy.intersect1d(axis0[0,:], axis0[1,:])[0]) | |
| 2670 | axis1 = numpy.unique(numpy.reshape(axis0,4)) |
|
2576 | axis1 = numpy.unique(numpy.reshape(axis0,4)) | |
| 2671 | side = axis1[axis1 != chanC] |
|
2577 | side = axis1[axis1 != chanC] | |
| 2672 | diff1 = chanPos[chanC,i] - chanPos[side[0],i] |
|
2578 | diff1 = chanPos[chanC,i] - chanPos[side[0],i] | |
| 2673 | diff2 = chanPos[chanC,i] - chanPos[side[1],i] |
|
2579 | diff2 = chanPos[chanC,i] - chanPos[side[1],i] | |
| 2674 | if diff1<0: |
|
2580 | if diff1<0: | |
| 2675 | chan2 = side[0] |
|
2581 | chan2 = side[0] | |
| 2676 | d2 = numpy.abs(diff1) |
|
2582 | d2 = numpy.abs(diff1) | |
| 2677 | chan1 = side[1] |
|
2583 | chan1 = side[1] | |
| 2678 | d1 = numpy.abs(diff2) |
|
2584 | d1 = numpy.abs(diff2) | |
| 2679 | else: |
|
2585 | else: | |
| 2680 | chan2 = side[1] |
|
2586 | chan2 = side[1] | |
| 2681 | d2 = numpy.abs(diff2) |
|
2587 | d2 = numpy.abs(diff2) | |
| 2682 | chan1 = side[0] |
|
2588 | chan1 = side[0] | |
| 2683 | d1 = numpy.abs(diff1) |
|
2589 | d1 = numpy.abs(diff1) | |
| 2684 |
|
2590 | |||
| 2685 | if i==0: |
|
2591 | if i==0: | |
| 2686 | chanCX = chanC |
|
2592 | chanCX = chanC | |
| 2687 | chan1X = chan1 |
|
2593 | chan1X = chan1 | |
| 2688 | chan2X = chan2 |
|
2594 | chan2X = chan2 | |
| 2689 | distances[0:2] = numpy.array([d1,d2]) |
|
2595 | distances[0:2] = numpy.array([d1,d2]) | |
| 2690 | else: |
|
2596 | else: | |
| 2691 | chanCY = chanC |
|
2597 | chanCY = chanC | |
| 2692 | chan1Y = chan1 |
|
2598 | chan1Y = chan1 | |
| 2693 | chan2Y = chan2 |
|
2599 | chan2Y = chan2 | |
| 2694 | distances[2:4] = numpy.array([d1,d2]) |
|
2600 | distances[2:4] = numpy.array([d1,d2]) | |
| 2695 | # axisXsides = numpy.reshape(axisX[ix,:],4) |
|
2601 | # axisXsides = numpy.reshape(axisX[ix,:],4) | |
| 2696 | # |
|
2602 | # | |
| 2697 | # channelCentX = int(numpy.intersect1d(pairX[0,:], pairX[1,:])[0]) |
|
2603 | # channelCentX = int(numpy.intersect1d(pairX[0,:], pairX[1,:])[0]) | |
| 2698 | # channelCentY = int(numpy.intersect1d(pairY[0,:], pairY[1,:])[0]) |
|
2604 | # channelCentY = int(numpy.intersect1d(pairY[0,:], pairY[1,:])[0]) | |
| 2699 | # |
|
2605 | # | |
| 2700 | # ind25X = numpy.where(pairX[0,:] != channelCentX)[0][0] |
|
2606 | # ind25X = numpy.where(pairX[0,:] != channelCentX)[0][0] | |
| 2701 | # ind20X = numpy.where(pairX[1,:] != channelCentX)[0][0] |
|
2607 | # ind20X = numpy.where(pairX[1,:] != channelCentX)[0][0] | |
| 2702 | # channel25X = int(pairX[0,ind25X]) |
|
2608 | # channel25X = int(pairX[0,ind25X]) | |
| 2703 | # channel20X = int(pairX[1,ind20X]) |
|
2609 | # channel20X = int(pairX[1,ind20X]) | |
| 2704 | # ind25Y = numpy.where(pairY[0,:] != channelCentY)[0][0] |
|
2610 | # ind25Y = numpy.where(pairY[0,:] != channelCentY)[0][0] | |
| 2705 | # ind20Y = numpy.where(pairY[1,:] != channelCentY)[0][0] |
|
2611 | # ind20Y = numpy.where(pairY[1,:] != channelCentY)[0][0] | |
| 2706 | # channel25Y = int(pairY[0,ind25Y]) |
|
2612 | # channel25Y = int(pairY[0,ind25Y]) | |
| 2707 | # channel20Y = int(pairY[1,ind20Y]) |
|
2613 | # channel20Y = int(pairY[1,ind20Y]) | |
| 2708 |
|
2614 | |||
| 2709 | # pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] |
|
2615 | # pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] | |
| 2710 | pairslist = [(chanCX, chan1X),(chanCX, chan2X),(chanCY,chan1Y),(chanCY, chan2Y)] |
|
2616 | pairslist = [(chanCX, chan1X),(chanCX, chan2X),(chanCY,chan1Y),(chanCY, chan2Y)] | |
| 2711 |
|
2617 | |||
| 2712 | return pairslist, distances |
|
2618 | return pairslist, distances | |
|
|
2619 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): | |||
|
|
2620 | # | |||
|
|
2621 | # arrayAOA = numpy.zeros((phases.shape[0],3)) | |||
|
|
2622 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) | |||
|
|
2623 | # | |||
|
|
2624 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |||
|
|
2625 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |||
|
|
2626 | # arrayAOA[:,2] = cosDirError | |||
|
|
2627 | # | |||
|
|
2628 | # azimuthAngle = arrayAOA[:,0] | |||
|
|
2629 | # zenithAngle = arrayAOA[:,1] | |||
|
|
2630 | # | |||
|
|
2631 | # #Setting Error | |||
|
|
2632 | # #Number 3: AOA not fesible | |||
|
|
2633 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |||
|
|
2634 | # error[indInvalid] = 3 | |||
|
|
2635 | # #Number 4: Large difference in AOAs obtained from different antenna baselines | |||
|
|
2636 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |||
|
|
2637 | # error[indInvalid] = 4 | |||
|
|
2638 | # return arrayAOA, error | |||
|
|
2639 | # | |||
|
|
2640 | # def __getDirectionCosines(self, arrayPhase, pairsList): | |||
|
|
2641 | # | |||
|
|
2642 | # #Initializing some variables | |||
|
|
2643 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |||
|
|
2644 | # ang_aux = ang_aux.reshape(1,ang_aux.size) | |||
|
|
2645 | # | |||
|
|
2646 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |||
|
|
2647 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |||
|
|
2648 | # | |||
|
|
2649 | # | |||
|
|
2650 | # for i in range(2): | |||
|
|
2651 | # #First Estimation | |||
|
|
2652 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] | |||
|
|
2653 | # #Dealias | |||
|
|
2654 | # indcsi = numpy.where(phi0_aux > numpy.pi) | |||
|
|
2655 | # phi0_aux[indcsi] -= 2*numpy.pi | |||
|
|
2656 | # indcsi = numpy.where(phi0_aux < -numpy.pi) | |||
|
|
2657 | # phi0_aux[indcsi] += 2*numpy.pi | |||
|
|
2658 | # #Direction Cosine 0 | |||
|
|
2659 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) | |||
|
|
2660 | # | |||
|
|
2661 | # #Most-Accurate Second Estimation | |||
|
|
2662 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] | |||
|
|
2663 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |||
|
|
2664 | # #Direction Cosine 1 | |||
|
|
2665 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) | |||
|
|
2666 | # | |||
|
|
2667 | # #Searching the correct Direction Cosine | |||
|
|
2668 | # cosdir0_aux = cosdir0[:,i] | |||
|
|
2669 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |||
|
|
2670 | # #Minimum Distance | |||
|
|
2671 | # cosDiff = (cosdir1 - cosdir0_aux)**2 | |||
|
|
2672 | # indcos = cosDiff.argmin(axis = 1) | |||
|
|
2673 | # #Saving Value obtained | |||
|
|
2674 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |||
|
|
2675 | # | |||
|
|
2676 | # return cosdir0, cosdir | |||
|
|
2677 | # | |||
|
|
2678 | # def __calculateAOA(self, cosdir, azimuth): | |||
|
|
2679 | # cosdirX = cosdir[:,0] | |||
|
|
2680 | # cosdirY = cosdir[:,1] | |||
|
|
2681 | # | |||
|
|
2682 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |||
|
|
2683 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east | |||
|
|
2684 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |||
|
|
2685 | # | |||
|
|
2686 | # return angles | |||
|
|
2687 | # | |||
|
|
2688 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |||
|
|
2689 | # | |||
|
|
2690 | # Ramb = 375 #Ramb = c/(2*PRF) | |||
|
|
2691 | # Re = 6371 #Earth Radius | |||
|
|
2692 | # heights = numpy.zeros(Ranges.shape) | |||
|
|
2693 | # | |||
|
|
2694 | # R_aux = numpy.array([0,1,2])*Ramb | |||
|
|
2695 | # R_aux = R_aux.reshape(1,R_aux.size) | |||
|
|
2696 | # | |||
|
|
2697 | # Ranges = Ranges.reshape(Ranges.size,1) | |||
|
|
2698 | # | |||
|
|
2699 | # Ri = Ranges + R_aux | |||
|
|
2700 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |||
|
|
2701 | # | |||
|
|
2702 | # #Check if there is a height between 70 and 110 km | |||
|
|
2703 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |||
|
|
2704 | # ind_h = numpy.where(h_bool == 1)[0] | |||
|
|
2705 | # | |||
|
|
2706 | # hCorr = hi[ind_h, :] | |||
|
|
2707 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |||
|
|
2708 | # | |||
|
|
2709 | # hCorr = hi[ind_hCorr] | |||
|
|
2710 | # heights[ind_h] = hCorr | |||
|
|
2711 | # | |||
|
|
2712 | # #Setting Error | |||
|
|
2713 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |||
|
|
2714 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |||
|
|
2715 | # | |||
|
|
2716 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |||
|
|
2717 | # error[indInvalid2] = 14 | |||
|
|
2718 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |||
|
|
2719 | # error[indInvalid1] = 13 | |||
|
|
2720 | # | |||
|
|
2721 | # return heights, error | |||
|
|
2722 | No newline at end of file | |||
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