| @@ -1,2158 +1,2599 | |||||
| 1 | import numpy |
|
1 | import numpy | |
| 2 | import math |
|
2 | import math | |
| 3 | from scipy import optimize |
|
3 | from scipy import optimize, interpolate, signal, stats, ndimage | |
| 4 | from scipy import interpolate |
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|||
| 5 | from scipy import signal |
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|||
| 6 | from scipy import stats |
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|||
| 7 | import re |
|
4 | import re | |
| 8 | import datetime |
|
5 | import datetime | |
| 9 | import copy |
|
6 | import copy | |
| 10 | import sys |
|
7 | import sys | |
| 11 | import importlib |
|
8 | import importlib | |
| 12 | import itertools |
|
9 | import itertools | |
| 13 |
|
10 | |||
| 14 | from jroproc_base import ProcessingUnit, Operation |
|
11 | from jroproc_base import ProcessingUnit, Operation | |
| 15 | from schainpy.model.data.jrodata import Parameters |
|
12 | from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon | |
| 16 |
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13 | |||
| 17 |
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14 | |||
| 18 | class ParametersProc(ProcessingUnit): |
|
15 | class ParametersProc(ProcessingUnit): | |
| 19 |
|
16 | |||
| 20 | nSeconds = None |
|
17 | nSeconds = None | |
| 21 |
|
18 | |||
| 22 | def __init__(self): |
|
19 | def __init__(self): | |
| 23 | ProcessingUnit.__init__(self) |
|
20 | ProcessingUnit.__init__(self) | |
| 24 |
|
21 | |||
| 25 | # self.objectDict = {} |
|
22 | # self.objectDict = {} | |
| 26 | self.buffer = None |
|
23 | self.buffer = None | |
| 27 | self.firstdatatime = None |
|
24 | self.firstdatatime = None | |
| 28 | self.profIndex = 0 |
|
25 | self.profIndex = 0 | |
| 29 | self.dataOut = Parameters() |
|
26 | self.dataOut = Parameters() | |
| 30 |
|
27 | |||
| 31 | def __updateObjFromInput(self): |
|
28 | def __updateObjFromInput(self): | |
| 32 |
|
29 | |||
| 33 | self.dataOut.inputUnit = self.dataIn.type |
|
30 | self.dataOut.inputUnit = self.dataIn.type | |
| 34 |
|
31 | |||
| 35 | self.dataOut.timeZone = self.dataIn.timeZone |
|
32 | self.dataOut.timeZone = self.dataIn.timeZone | |
| 36 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
33 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
| 37 | self.dataOut.errorCount = self.dataIn.errorCount |
|
34 | self.dataOut.errorCount = self.dataIn.errorCount | |
| 38 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
35 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
| 39 |
|
36 | |||
| 40 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() |
|
37 | self.dataOut.radarControllerHeaderObj = self.dataIn.radarControllerHeaderObj.copy() | |
| 41 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() |
|
38 | self.dataOut.systemHeaderObj = self.dataIn.systemHeaderObj.copy() | |
| 42 | self.dataOut.channelList = self.dataIn.channelList |
|
39 | self.dataOut.channelList = self.dataIn.channelList | |
| 43 | self.dataOut.heightList = self.dataIn.heightList |
|
40 | self.dataOut.heightList = self.dataIn.heightList | |
| 44 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) |
|
41 | self.dataOut.dtype = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
| 45 | # self.dataOut.nHeights = self.dataIn.nHeights |
|
42 | # self.dataOut.nHeights = self.dataIn.nHeights | |
| 46 | # self.dataOut.nChannels = self.dataIn.nChannels |
|
43 | # self.dataOut.nChannels = self.dataIn.nChannels | |
| 47 | self.dataOut.nBaud = self.dataIn.nBaud |
|
44 | self.dataOut.nBaud = self.dataIn.nBaud | |
| 48 | self.dataOut.nCode = self.dataIn.nCode |
|
45 | self.dataOut.nCode = self.dataIn.nCode | |
| 49 | self.dataOut.code = self.dataIn.code |
|
46 | self.dataOut.code = self.dataIn.code | |
| 50 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints |
|
47 | # self.dataOut.nProfiles = self.dataOut.nFFTPoints | |
| 51 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock |
|
48 | self.dataOut.flagDiscontinuousBlock = self.dataIn.flagDiscontinuousBlock | |
| 52 | # self.dataOut.utctime = self.firstdatatime |
|
49 | # self.dataOut.utctime = self.firstdatatime | |
| 53 | self.dataOut.utctime = self.dataIn.utctime |
|
50 | self.dataOut.utctime = self.dataIn.utctime | |
| 54 | 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 | |
| 55 | 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 | |
| 56 |
|
|
53 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
| 57 | # self.dataOut.nIncohInt = 1 |
|
54 | # self.dataOut.nIncohInt = 1 | |
| 58 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
55 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
| 59 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter |
|
56 | # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter | |
| 60 | self.dataOut.timeInterval = self.dataIn.timeInterval |
|
57 | self.dataOut.timeInterval = self.dataIn.timeInterval | |
| 61 | self.dataOut.heightList = self.dataIn.getHeiRange() |
|
58 | self.dataOut.heightList = self.dataIn.getHeiRange() | |
| 62 | self.dataOut.frequency = self.dataIn.frequency |
|
59 | self.dataOut.frequency = self.dataIn.frequency | |
|
|
60 | self.dataOut.noise = self.dataIn.noise | |||
| 63 |
|
61 | |||
| 64 | def run(self): |
|
62 | def run(self): | |
| 65 |
|
63 | |||
| 66 | #---------------------- Voltage Data --------------------------- |
|
64 | #---------------------- Voltage Data --------------------------- | |
| 67 |
|
65 | |||
| 68 | if self.dataIn.type == "Voltage": |
|
66 | if self.dataIn.type == "Voltage": | |
| 69 |
|
67 | |||
| 70 | self.__updateObjFromInput() |
|
68 | self.__updateObjFromInput() | |
| 71 | self.dataOut.data_pre = self.dataIn.data.copy() |
|
69 | self.dataOut.data_pre = self.dataIn.data.copy() | |
| 72 | self.dataOut.flagNoData = False |
|
70 | self.dataOut.flagNoData = False | |
| 73 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
71 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 74 | 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 | |
| 75 | return |
|
73 | return | |
| 76 |
|
74 | |||
| 77 | #---------------------- Spectra Data --------------------------- |
|
75 | #---------------------- Spectra Data --------------------------- | |
| 78 |
|
76 | |||
| 79 | if self.dataIn.type == "Spectra": |
|
77 | if self.dataIn.type == "Spectra": | |
| 80 | self.dataOut.data_pre = self.dataIn.data_spc.copy() |
|
78 | ||
|
|
79 | self.dataOut.data_pre = (self.dataIn.data_spc,self.dataIn.data_cspc) | |||
| 81 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) |
|
80 | self.dataOut.abscissaList = self.dataIn.getVelRange(1) | |
| 82 | self.dataOut.noise = self.dataIn.getNoise() |
|
81 | self.dataOut.noise = self.dataIn.getNoise() | |
| 83 | self.dataOut.normFactor = self.dataIn.normFactor |
|
82 | self.dataOut.normFactor = self.dataIn.normFactor | |
| 84 | self.dataOut.groupList = self.dataIn.pairsList |
|
83 | self.dataOut.groupList = self.dataIn.pairsList | |
| 85 | self.dataOut.flagNoData = False |
|
84 | self.dataOut.flagNoData = False | |
| 86 |
|
85 | |||
| 87 | #---------------------- Correlation Data --------------------------- |
|
86 | #---------------------- Correlation Data --------------------------- | |
| 88 |
|
87 | |||
| 89 | if self.dataIn.type == "Correlation": |
|
88 | if self.dataIn.type == "Correlation": | |
| 90 | lagRRange = self.dataIn.lagR |
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|||
| 91 | indR = numpy.where(lagRRange == 0)[0][0] |
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|||
| 92 |
|
89 | |||
| 93 | self.dataOut.data_pre = self.dataIn.data_corr.copy()[:,:,indR,:] |
|
90 | if self.dataIn.data_ccf is not None: | |
| 94 |
self.dataOut. |
|
91 | self.dataOut.data_pre = (self.dataIn.data_acf,self.dataIn.data_ccf) | |
|
|
92 | else: | |||
|
|
93 | self.dataOut.data_pre = self.dataIn.data_acf.copy() | |||
|
|
94 | ||||
|
|
95 | self.dataOut.abscissaList = self.dataIn.lagRange | |||
| 95 | self.dataOut.noise = self.dataIn.noise |
|
96 | self.dataOut.noise = self.dataIn.noise | |
| 96 | self.dataOut.normFactor = self.dataIn.normFactor |
|
97 | self.dataOut.normFactor = self.dataIn.normFactor | |
| 97 | self.dataOut.data_SNR = self.dataIn.SNR |
|
98 | self.dataOut.data_SNR = self.dataIn.SNR | |
| 98 | self.dataOut.groupList = self.dataIn.pairsList |
|
99 | self.dataOut.groupList = self.dataIn.pairsList | |
| 99 | self.dataOut.flagNoData = False |
|
100 | self.dataOut.flagNoData = False | |
|
|
101 | self.dataOut.nAvg = self.dataIn.nAvg | |||
| 100 |
|
102 | |||
| 101 |
#---------------------- |
|
103 | #---------------------- Parameters Data --------------------------- | |
| 102 |
|
104 | |||
| 103 | if self.dataIn.type == "Parameters": |
|
105 | if self.dataIn.type == "Parameters": | |
| 104 | self.dataOut.copy(self.dataIn) |
|
106 | self.dataOut.copy(self.dataIn) | |
| 105 | self.dataOut.flagNoData = False |
|
107 | self.dataOut.flagNoData = False | |
| 106 |
|
108 | |||
| 107 | return True |
|
109 | return True | |
| 108 |
|
110 | |||
| 109 | self.__updateObjFromInput() |
|
111 | self.__updateObjFromInput() | |
| 110 | self.dataOut.utctimeInit = self.dataIn.utctime |
|
112 | self.dataOut.utctimeInit = self.dataIn.utctime | |
| 111 | self.dataOut.paramInterval = self.dataIn.timeInterval |
|
113 | self.dataOut.paramInterval = self.dataIn.timeInterval | |
| 112 |
|
114 | |||
| 113 | #------------------- Get Moments ---------------------------------- |
|
115 | #------------------- Get Moments ---------------------------------- | |
| 114 | def GetMoments(self, channelList = None): |
|
116 | def GetMoments(self, channelList = None): | |
| 115 | ''' |
|
117 | ''' | |
| 116 | Function GetMoments() |
|
118 | Function GetMoments() | |
| 117 |
|
119 | |||
| 118 | Input: |
|
120 | Input: | |
| 119 | channelList : simple channel list to select e.g. [2,3,7] |
|
121 | channelList : simple channel list to select e.g. [2,3,7] | |
| 120 | self.dataOut.data_pre |
|
122 | self.dataOut.data_pre | |
| 121 | self.dataOut.abscissaList |
|
123 | self.dataOut.abscissaList | |
| 122 | self.dataOut.noise |
|
124 | self.dataOut.noise | |
| 123 |
|
125 | |||
| 124 | Affected: |
|
126 | Affected: | |
| 125 | self.dataOut.data_param |
|
127 | self.dataOut.data_param | |
| 126 | self.dataOut.data_SNR |
|
128 | self.dataOut.data_SNR | |
| 127 |
|
129 | |||
| 128 | ''' |
|
130 | ''' | |
|
|
131 | self.dataOut.data_pre = self.dataOut.data_pre[0] | |||
| 129 | data = self.dataOut.data_pre |
|
132 | data = self.dataOut.data_pre | |
| 130 | absc = self.dataOut.abscissaList[:-1] |
|
133 | absc = self.dataOut.abscissaList[:-1] | |
| 131 | noise = self.dataOut.noise |
|
134 | noise = self.dataOut.noise | |
| 132 |
|
135 | |||
| 133 | data_param = numpy.zeros((data.shape[0], 4, data.shape[2])) |
|
136 | data_param = numpy.zeros((data.shape[0], 4, data.shape[2])) | |
| 134 |
|
137 | |||
| 135 | if channelList== None: |
|
138 | if channelList== None: | |
| 136 | channelList = self.dataIn.channelList |
|
139 | channelList = self.dataIn.channelList | |
| 137 | self.dataOut.channelList = channelList |
|
140 | self.dataOut.channelList = channelList | |
| 138 |
|
141 | |||
| 139 | for ind in channelList: |
|
142 | for ind in channelList: | |
| 140 | data_param[ind,:,:] = self.__calculateMoments(data[ind,:,:], absc, noise[ind]) |
|
143 | data_param[ind,:,:] = self.__calculateMoments(data[ind,:,:], absc, noise[ind]) | |
| 141 |
|
144 | |||
| 142 | self.dataOut.data_param = data_param[:,1:,:] |
|
145 | self.dataOut.data_param = data_param[:,1:,:] | |
| 143 | self.dataOut.data_SNR = data_param[:,0] |
|
146 | self.dataOut.data_SNR = data_param[:,0] | |
| 144 | return |
|
147 | return | |
| 145 |
|
148 | |||
| 146 | 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): |
|
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): | |
| 147 |
|
150 | |||
| 148 | if (nicoh == None): nicoh = 1 |
|
151 | if (nicoh == None): nicoh = 1 | |
| 149 | if (graph == None): graph = 0 |
|
152 | if (graph == None): graph = 0 | |
| 150 | if (smooth == None): smooth = 0 |
|
153 | if (smooth == None): smooth = 0 | |
| 151 | elif (self.smooth < 3): smooth = 0 |
|
154 | elif (self.smooth < 3): smooth = 0 | |
| 152 |
|
155 | |||
| 153 | if (type1 == None): type1 = 0 |
|
156 | if (type1 == None): type1 = 0 | |
| 154 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 |
|
157 | if (fwindow == None): fwindow = numpy.zeros(oldfreq.size) + 1 | |
| 155 | if (snrth == None): snrth = -3 |
|
158 | if (snrth == None): snrth = -3 | |
| 156 | if (dc == None): dc = 0 |
|
159 | if (dc == None): dc = 0 | |
| 157 | if (aliasing == None): aliasing = 0 |
|
160 | if (aliasing == None): aliasing = 0 | |
| 158 | if (oldfd == None): oldfd = 0 |
|
161 | if (oldfd == None): oldfd = 0 | |
| 159 | if (wwauto == None): wwauto = 0 |
|
162 | if (wwauto == None): wwauto = 0 | |
| 160 |
|
163 | |||
| 161 | if (n0 < 1.e-20): n0 = 1.e-20 |
|
164 | if (n0 < 1.e-20): n0 = 1.e-20 | |
| 162 |
|
165 | |||
| 163 | freq = oldfreq |
|
166 | freq = oldfreq | |
| 164 | vec_power = numpy.zeros(oldspec.shape[1]) |
|
167 | vec_power = numpy.zeros(oldspec.shape[1]) | |
| 165 | vec_fd = numpy.zeros(oldspec.shape[1]) |
|
168 | vec_fd = numpy.zeros(oldspec.shape[1]) | |
| 166 | vec_w = numpy.zeros(oldspec.shape[1]) |
|
169 | vec_w = numpy.zeros(oldspec.shape[1]) | |
| 167 | vec_snr = numpy.zeros(oldspec.shape[1]) |
|
170 | vec_snr = numpy.zeros(oldspec.shape[1]) | |
| 168 |
|
171 | |||
| 169 | for ind in range(oldspec.shape[1]): |
|
172 | for ind in range(oldspec.shape[1]): | |
| 170 |
|
173 | |||
| 171 | spec = oldspec[:,ind] |
|
174 | spec = oldspec[:,ind] | |
| 172 | aux = spec*fwindow |
|
175 | aux = spec*fwindow | |
| 173 | max_spec = aux.max() |
|
176 | max_spec = aux.max() | |
| 174 | m = list(aux).index(max_spec) |
|
177 | m = list(aux).index(max_spec) | |
| 175 |
|
178 | |||
| 176 | #Smooth |
|
179 | #Smooth | |
| 177 | if (smooth == 0): spec2 = spec |
|
180 | if (smooth == 0): spec2 = spec | |
| 178 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) |
|
181 | else: spec2 = scipy.ndimage.filters.uniform_filter1d(spec,size=smooth) | |
| 179 |
|
182 | |||
| 180 | # Calculo de Momentos |
|
183 | # Calculo de Momentos | |
| 181 | bb = spec2[range(m,spec2.size)] |
|
184 | bb = spec2[range(m,spec2.size)] | |
| 182 | bb = (bb<n0).nonzero() |
|
185 | bb = (bb<n0).nonzero() | |
| 183 | bb = bb[0] |
|
186 | bb = bb[0] | |
| 184 |
|
187 | |||
| 185 | ss = spec2[range(0,m + 1)] |
|
188 | ss = spec2[range(0,m + 1)] | |
| 186 | ss = (ss<n0).nonzero() |
|
189 | ss = (ss<n0).nonzero() | |
| 187 | ss = ss[0] |
|
190 | ss = ss[0] | |
| 188 |
|
191 | |||
| 189 | if (bb.size == 0): |
|
192 | if (bb.size == 0): | |
| 190 | bb0 = spec.size - 1 - m |
|
193 | bb0 = spec.size - 1 - m | |
| 191 | else: |
|
194 | else: | |
| 192 | bb0 = bb[0] - 1 |
|
195 | bb0 = bb[0] - 1 | |
| 193 | if (bb0 < 0): |
|
196 | if (bb0 < 0): | |
| 194 | bb0 = 0 |
|
197 | bb0 = 0 | |
| 195 |
|
198 | |||
| 196 | if (ss.size == 0): ss1 = 1 |
|
199 | if (ss.size == 0): ss1 = 1 | |
| 197 | else: ss1 = max(ss) + 1 |
|
200 | else: ss1 = max(ss) + 1 | |
| 198 |
|
201 | |||
| 199 | if (ss1 > m): ss1 = m |
|
202 | if (ss1 > m): ss1 = m | |
| 200 |
|
203 | |||
| 201 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 |
|
204 | valid = numpy.asarray(range(int(m + bb0 - ss1 + 1))) + ss1 | |
| 202 | power = ((spec2[valid] - n0)*fwindow[valid]).sum() |
|
205 | power = ((spec2[valid] - n0)*fwindow[valid]).sum() | |
| 203 | fd = ((spec2[valid]- n0)*freq[valid]*fwindow[valid]).sum()/power |
|
206 | fd = ((spec2[valid]- n0)*freq[valid]*fwindow[valid]).sum()/power | |
| 204 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) |
|
207 | w = math.sqrt(((spec2[valid] - n0)*fwindow[valid]*(freq[valid]- fd)**2).sum()/power) | |
| 205 | snr = (spec2.mean()-n0)/n0 |
|
208 | snr = (spec2.mean()-n0)/n0 | |
| 206 |
|
209 | |||
| 207 | if (snr < 1.e-20) : |
|
210 | if (snr < 1.e-20) : | |
| 208 | snr = 1.e-20 |
|
211 | snr = 1.e-20 | |
| 209 |
|
212 | |||
| 210 | vec_power[ind] = power |
|
213 | vec_power[ind] = power | |
| 211 | vec_fd[ind] = fd |
|
214 | vec_fd[ind] = fd | |
| 212 | vec_w[ind] = w |
|
215 | vec_w[ind] = w | |
| 213 | vec_snr[ind] = snr |
|
216 | vec_snr[ind] = snr | |
| 214 |
|
217 | |||
| 215 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) |
|
218 | moments = numpy.vstack((vec_snr, vec_power, vec_fd, vec_w)) | |
| 216 | return moments |
|
219 | return moments | |
| 217 |
|
220 | |||
| 218 | #------------------ Get SA Parameters -------------------------- |
|
221 | #------------------ Get SA Parameters -------------------------- | |
| 219 |
|
222 | |||
| 220 | def GetSAParameters(self): |
|
223 | def GetSAParameters(self): | |
| 221 | pairslist = self.dataOut.groupList |
|
224 | pairslist = self.dataOut.groupList | |
| 222 | num_pairs = len(pairslist) |
|
225 | num_pairs = len(pairslist) | |
| 223 |
|
226 | |||
| 224 | vel = self.dataOut.abscissaList |
|
227 | vel = self.dataOut.abscissaList | |
| 225 | spectra = self.dataOut.data_pre |
|
228 | spectra = self.dataOut.data_pre | |
| 226 | cspectra = self.dataIn.data_cspc |
|
229 | cspectra = self.dataIn.data_cspc | |
| 227 | delta_v = vel[1] - vel[0] |
|
230 | delta_v = vel[1] - vel[0] | |
| 228 |
|
231 | |||
| 229 | #Calculating the power spectrum |
|
232 | #Calculating the power spectrum | |
| 230 | spc_pow = numpy.sum(spectra, 3)*delta_v |
|
233 | spc_pow = numpy.sum(spectra, 3)*delta_v | |
| 231 | #Normalizing Spectra |
|
234 | #Normalizing Spectra | |
| 232 | norm_spectra = spectra/spc_pow |
|
235 | norm_spectra = spectra/spc_pow | |
| 233 | #Calculating the norm_spectra at peak |
|
236 | #Calculating the norm_spectra at peak | |
| 234 | max_spectra = numpy.max(norm_spectra, 3) |
|
237 | max_spectra = numpy.max(norm_spectra, 3) | |
| 235 |
|
238 | |||
| 236 | #Normalizing Cross Spectra |
|
239 | #Normalizing Cross Spectra | |
| 237 | norm_cspectra = numpy.zeros(cspectra.shape) |
|
240 | norm_cspectra = numpy.zeros(cspectra.shape) | |
| 238 |
|
241 | |||
| 239 | for i in range(num_chan): |
|
242 | for i in range(num_chan): | |
| 240 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) |
|
243 | norm_cspectra[i,:,:] = cspectra[i,:,:]/numpy.sqrt(spc_pow[pairslist[i][0],:]*spc_pow[pairslist[i][1],:]) | |
| 241 |
|
244 | |||
| 242 | max_cspectra = numpy.max(norm_cspectra,2) |
|
245 | max_cspectra = numpy.max(norm_cspectra,2) | |
| 243 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) |
|
246 | max_cspectra_index = numpy.argmax(norm_cspectra, 2) | |
| 244 |
|
247 | |||
| 245 | for i in range(num_pairs): |
|
248 | for i in range(num_pairs): | |
| 246 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) |
|
249 | cspc_par[i,:,:] = __calculateMoments(norm_cspectra) | |
| 247 | #------------------- Get Lags ---------------------------------- |
|
250 | #------------------- Get Lags ---------------------------------- | |
| 248 |
|
251 | |||
| 249 | def GetLags(self): |
|
252 | def GetLags(self): | |
| 250 | ''' |
|
253 | ''' | |
| 251 | Function GetMoments() |
|
254 | Function GetMoments() | |
| 252 |
|
255 | |||
| 253 | Input: |
|
256 | Input: | |
| 254 | self.dataOut.data_pre |
|
257 | self.dataOut.data_pre | |
| 255 | self.dataOut.abscissaList |
|
258 | self.dataOut.abscissaList | |
| 256 | self.dataOut.noise |
|
259 | self.dataOut.noise | |
| 257 | self.dataOut.normFactor |
|
260 | self.dataOut.normFactor | |
| 258 | self.dataOut.data_SNR |
|
261 | self.dataOut.data_SNR | |
| 259 | self.dataOut.groupList |
|
262 | self.dataOut.groupList | |
| 260 | self.dataOut.nChannels |
|
263 | self.dataOut.nChannels | |
| 261 |
|
264 | |||
| 262 | Affected: |
|
265 | Affected: | |
| 263 | self.dataOut.data_param |
|
266 | self.dataOut.data_param | |
| 264 |
|
267 | |||
| 265 | ''' |
|
268 | ''' | |
| 266 |
|
269 | |||
| 267 | data = self.dataOut.data_pre |
|
270 | data = self.dataOut.data_pre | |
| 268 | normFactor = self.dataOut.normFactor |
|
271 | normFactor = self.dataOut.normFactor | |
| 269 | nHeights = self.dataOut.nHeights |
|
272 | nHeights = self.dataOut.nHeights | |
| 270 | absc = self.dataOut.abscissaList[:-1] |
|
273 | absc = self.dataOut.abscissaList[:-1] | |
| 271 | noise = self.dataOut.noise |
|
274 | noise = self.dataOut.noise | |
| 272 | SNR = self.dataOut.data_SNR |
|
275 | SNR = self.dataOut.data_SNR | |
| 273 | pairsList = self.dataOut.groupList |
|
276 | pairsList = self.dataOut.groupList | |
| 274 | nChannels = self.dataOut.nChannels |
|
277 | nChannels = self.dataOut.nChannels | |
| 275 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) |
|
278 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) | |
| 276 | self.dataOut.data_param = numpy.zeros((len(pairsCrossCorr)*2 + 1, nHeights)) |
|
279 | self.dataOut.data_param = numpy.zeros((len(pairsCrossCorr)*2 + 1, nHeights)) | |
| 277 |
|
280 | |||
| 278 | dataNorm = numpy.abs(data) |
|
281 | dataNorm = numpy.abs(data) | |
| 279 | for l in range(len(pairsList)): |
|
282 | for l in range(len(pairsList)): | |
| 280 | dataNorm[l,:,:] = dataNorm[l,:,:]/normFactor[l,:] |
|
283 | dataNorm[l,:,:] = dataNorm[l,:,:]/normFactor[l,:] | |
| 281 |
|
284 | |||
| 282 | self.dataOut.data_param[:-1,:] = self.__calculateTaus(dataNorm, pairsCrossCorr, pairsAutoCorr, absc) |
|
285 | self.dataOut.data_param[:-1,:] = self.__calculateTaus(dataNorm, pairsCrossCorr, pairsAutoCorr, absc) | |
| 283 | self.dataOut.data_param[-1,:] = self.__calculateLag1Phase(data, pairsAutoCorr, absc) |
|
286 | self.dataOut.data_param[-1,:] = self.__calculateLag1Phase(data, pairsAutoCorr, absc) | |
| 284 | return |
|
287 | return | |
| 285 |
|
288 | |||
| 286 | def __getPairsAutoCorr(self, pairsList, nChannels): |
|
289 | def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 287 |
|
290 | |||
| 288 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
291 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 289 |
|
292 | |||
| 290 | for l in range(len(pairsList)): |
|
293 | for l in range(len(pairsList)): | |
| 291 | firstChannel = pairsList[l][0] |
|
294 | firstChannel = pairsList[l][0] | |
| 292 | secondChannel = pairsList[l][1] |
|
295 | secondChannel = pairsList[l][1] | |
| 293 |
|
296 | |||
| 294 | #Obteniendo pares de Autocorrelacion |
|
297 | #Obteniendo pares de Autocorrelacion | |
| 295 | if firstChannel == secondChannel: |
|
298 | if firstChannel == secondChannel: | |
| 296 | pairsAutoCorr[firstChannel] = int(l) |
|
299 | pairsAutoCorr[firstChannel] = int(l) | |
| 297 |
|
300 | |||
| 298 | pairsAutoCorr = pairsAutoCorr.astype(int) |
|
301 | pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 299 |
|
302 | |||
| 300 | pairsCrossCorr = range(len(pairsList)) |
|
303 | pairsCrossCorr = range(len(pairsList)) | |
| 301 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
304 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 302 |
|
305 | |||
| 303 | return pairsAutoCorr, pairsCrossCorr |
|
306 | return pairsAutoCorr, pairsCrossCorr | |
| 304 |
|
307 | |||
| 305 | def __calculateTaus(self, data, pairsCrossCorr, pairsAutoCorr, lagTRange): |
|
308 | def __calculateTaus(self, data, pairsCrossCorr, pairsAutoCorr, lagTRange): | |
| 306 |
|
309 | |||
| 307 | Pt0 = data.shape[1]/2 |
|
310 | Pt0 = data.shape[1]/2 | |
| 308 | #Funcion de Autocorrelacion |
|
311 | #Funcion de Autocorrelacion | |
| 309 | dataAutoCorr = stats.nanmean(data[pairsAutoCorr,:,:], axis = 0) |
|
312 | dataAutoCorr = stats.nanmean(data[pairsAutoCorr,:,:], axis = 0) | |
| 310 |
|
313 | |||
| 311 | #Obtencion Indice de TauCross |
|
314 | #Obtencion Indice de TauCross | |
| 312 | indCross = data[pairsCrossCorr,:,:].argmax(axis = 1) |
|
315 | indCross = data[pairsCrossCorr,:,:].argmax(axis = 1) | |
| 313 | #Obtencion Indice de TauAuto |
|
316 | #Obtencion Indice de TauAuto | |
| 314 | indAuto = numpy.zeros(indCross.shape,dtype = 'int') |
|
317 | indAuto = numpy.zeros(indCross.shape,dtype = 'int') | |
| 315 | CCValue = data[pairsCrossCorr,Pt0,:] |
|
318 | CCValue = data[pairsCrossCorr,Pt0,:] | |
| 316 | for i in range(pairsCrossCorr.size): |
|
319 | for i in range(pairsCrossCorr.size): | |
| 317 | indAuto[i,:] = numpy.abs(dataAutoCorr - CCValue[i,:]).argmin(axis = 0) |
|
320 | indAuto[i,:] = numpy.abs(dataAutoCorr - CCValue[i,:]).argmin(axis = 0) | |
| 318 |
|
321 | |||
| 319 | #Obtencion de TauCross y TauAuto |
|
322 | #Obtencion de TauCross y TauAuto | |
| 320 | tauCross = lagTRange[indCross] |
|
323 | tauCross = lagTRange[indCross] | |
| 321 | tauAuto = lagTRange[indAuto] |
|
324 | tauAuto = lagTRange[indAuto] | |
| 322 |
|
325 | |||
| 323 | Nan1, Nan2 = numpy.where(tauCross == lagTRange[0]) |
|
326 | Nan1, Nan2 = numpy.where(tauCross == lagTRange[0]) | |
| 324 |
|
327 | |||
| 325 | tauCross[Nan1,Nan2] = numpy.nan |
|
328 | tauCross[Nan1,Nan2] = numpy.nan | |
| 326 | tauAuto[Nan1,Nan2] = numpy.nan |
|
329 | tauAuto[Nan1,Nan2] = numpy.nan | |
| 327 | tau = numpy.vstack((tauCross,tauAuto)) |
|
330 | tau = numpy.vstack((tauCross,tauAuto)) | |
| 328 |
|
331 | |||
| 329 | return tau |
|
332 | return tau | |
| 330 |
|
333 | |||
| 331 | def __calculateLag1Phase(self, data, pairs, lagTRange): |
|
334 | def __calculateLag1Phase(self, data, pairs, lagTRange): | |
| 332 | data1 = stats.nanmean(data[pairs,:,:], axis = 0) |
|
335 | data1 = stats.nanmean(data[pairs,:,:], axis = 0) | |
| 333 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 |
|
336 | lag1 = numpy.where(lagTRange == 0)[0][0] + 1 | |
| 334 |
|
337 | |||
| 335 | phase = numpy.angle(data1[lag1,:]) |
|
338 | phase = numpy.angle(data1[lag1,:]) | |
| 336 |
|
339 | |||
| 337 | return phase |
|
340 | return phase | |
| 338 | #------------------- Detect Meteors ------------------------------ |
|
341 | #------------------- Detect Meteors ------------------------------ | |
| 339 |
|
342 | |||
| 340 | def MeteorDetection(self, hei_ref = None, tauindex = 0, |
|
343 | def MeteorDetection(self, hei_ref = None, tauindex = 0, | |
| 341 | phaseOffsets = None, |
|
344 | phaseOffsets = None, | |
| 342 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, |
|
345 | cohDetection = False, cohDet_timeStep = 1, cohDet_thresh = 25, | |
| 343 | noise_timeStep = 4, noise_multiple = 4, |
|
346 | noise_timeStep = 4, noise_multiple = 4, | |
| 344 | multDet_timeLimit = 1, multDet_rangeLimit = 3, |
|
347 | multDet_timeLimit = 1, multDet_rangeLimit = 3, | |
| 345 | phaseThresh = 20, SNRThresh = 8, |
|
348 | phaseThresh = 20, SNRThresh = 8, | |
| 346 | hmin = 50, hmax=150, azimuth = 0, |
|
349 | hmin = 50, hmax=150, azimuth = 0, | |
| 347 | channel25X = 0, channel20X = 4, channelCentX = 2, |
|
350 | channel25X = 0, channel20X = 4, channelCentX = 2, | |
| 348 | channel25Y = 1, channel20Y = 3, channelCentY = 2) : |
|
351 | channel25Y = 1, channel20Y = 3, channelCentY = 2) : | |
| 349 |
|
352 | |||
| 350 | ''' |
|
353 | ''' | |
| 351 | Function DetectMeteors() |
|
354 | Function DetectMeteors() | |
| 352 | Project developed with paper: |
|
355 | Project developed with paper: | |
| 353 | HOLDSWORTH ET AL. 2004 |
|
356 | HOLDSWORTH ET AL. 2004 | |
| 354 |
|
357 | |||
| 355 | Input: |
|
358 | Input: | |
| 356 | self.dataOut.data_pre |
|
359 | self.dataOut.data_pre | |
| 357 |
|
360 | |||
| 358 | centerReceiverIndex: From the channels, which is the center receiver |
|
361 | centerReceiverIndex: From the channels, which is the center receiver | |
| 359 |
|
362 | |||
| 360 | hei_ref: Height reference for the Beacon signal extraction |
|
363 | hei_ref: Height reference for the Beacon signal extraction | |
| 361 | tauindex: |
|
364 | tauindex: | |
| 362 | predefinedPhaseShifts: Predefined phase offset for the voltge signals |
|
365 | predefinedPhaseShifts: Predefined phase offset for the voltge signals | |
| 363 |
|
366 | |||
| 364 | cohDetection: Whether to user Coherent detection or not |
|
367 | cohDetection: Whether to user Coherent detection or not | |
| 365 | cohDet_timeStep: Coherent Detection calculation time step |
|
368 | cohDet_timeStep: Coherent Detection calculation time step | |
| 366 | cohDet_thresh: Coherent Detection phase threshold to correct phases |
|
369 | cohDet_thresh: Coherent Detection phase threshold to correct phases | |
| 367 |
|
370 | |||
| 368 | noise_timeStep: Noise calculation time step |
|
371 | noise_timeStep: Noise calculation time step | |
| 369 | noise_multiple: Noise multiple to define signal threshold |
|
372 | noise_multiple: Noise multiple to define signal threshold | |
| 370 |
|
373 | |||
| 371 | multDet_timeLimit: Multiple Detection Removal time limit in seconds |
|
374 | multDet_timeLimit: Multiple Detection Removal time limit in seconds | |
| 372 | multDet_rangeLimit: Multiple Detection Removal range limit in km |
|
375 | multDet_rangeLimit: Multiple Detection Removal range limit in km | |
| 373 |
|
376 | |||
| 374 | phaseThresh: Maximum phase difference between receiver to be consider a meteor |
|
377 | phaseThresh: Maximum phase difference between receiver to be consider a meteor | |
| 375 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor |
|
378 | SNRThresh: Minimum SNR threshold of the meteor signal to be consider a meteor | |
| 376 |
|
379 | |||
| 377 | hmin: Minimum Height of the meteor to use it in the further wind estimations |
|
380 | hmin: Minimum Height of the meteor to use it in the further wind estimations | |
| 378 | hmax: Maximum Height of the meteor to use it in the further wind estimations |
|
381 | hmax: Maximum Height of the meteor to use it in the further wind estimations | |
| 379 | azimuth: Azimuth angle correction |
|
382 | azimuth: Azimuth angle correction | |
| 380 |
|
383 | |||
| 381 | Affected: |
|
384 | Affected: | |
| 382 | self.dataOut.data_param |
|
385 | self.dataOut.data_param | |
| 383 |
|
386 | |||
| 384 | Rejection Criteria (Errors): |
|
387 | Rejection Criteria (Errors): | |
| 385 | 0: No error; analysis OK |
|
388 | 0: No error; analysis OK | |
| 386 | 1: SNR < SNR threshold |
|
389 | 1: SNR < SNR threshold | |
| 387 | 2: angle of arrival (AOA) ambiguously determined |
|
390 | 2: angle of arrival (AOA) ambiguously determined | |
| 388 | 3: AOA estimate not feasible |
|
391 | 3: AOA estimate not feasible | |
| 389 | 4: Large difference in AOAs obtained from different antenna baselines |
|
392 | 4: Large difference in AOAs obtained from different antenna baselines | |
| 390 | 5: echo at start or end of time series |
|
393 | 5: echo at start or end of time series | |
| 391 | 6: echo less than 5 examples long; too short for analysis |
|
394 | 6: echo less than 5 examples long; too short for analysis | |
| 392 | 7: echo rise exceeds 0.3s |
|
395 | 7: echo rise exceeds 0.3s | |
| 393 | 8: echo decay time less than twice rise time |
|
396 | 8: echo decay time less than twice rise time | |
| 394 | 9: large power level before echo |
|
397 | 9: large power level before echo | |
| 395 | 10: large power level after echo |
|
398 | 10: large power level after echo | |
| 396 | 11: poor fit to amplitude for estimation of decay time |
|
399 | 11: poor fit to amplitude for estimation of decay time | |
| 397 | 12: poor fit to CCF phase variation for estimation of radial drift velocity |
|
400 | 12: poor fit to CCF phase variation for estimation of radial drift velocity | |
| 398 | 13: height unresolvable echo: not valid height within 70 to 110 km |
|
401 | 13: height unresolvable echo: not valid height within 70 to 110 km | |
| 399 | 14: height ambiguous echo: more then one possible height within 70 to 110 km |
|
402 | 14: height ambiguous echo: more then one possible height within 70 to 110 km | |
| 400 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s |
|
403 | 15: radial drift velocity or projected horizontal velocity exceeds 200 m/s | |
| 401 | 16: oscilatory echo, indicating event most likely not an underdense echo |
|
404 | 16: oscilatory echo, indicating event most likely not an underdense echo | |
| 402 |
|
405 | |||
| 403 | 17: phase difference in meteor Reestimation |
|
406 | 17: phase difference in meteor Reestimation | |
| 404 |
|
407 | |||
| 405 | Data Storage: |
|
408 | Data Storage: | |
| 406 | Meteors for Wind Estimation (8): |
|
409 | Meteors for Wind Estimation (8): | |
| 407 | Utc Time | Range Height |
|
410 | Utc Time | Range Height | |
| 408 | Azimuth Zenith errorCosDir |
|
411 | Azimuth Zenith errorCosDir | |
| 409 | VelRad errorVelRad |
|
412 | VelRad errorVelRad | |
| 410 | Phase0 Phase1 Phase2 Phase3 |
|
413 | Phase0 Phase1 Phase2 Phase3 | |
| 411 | TypeError |
|
414 | TypeError | |
| 412 |
|
415 | |||
| 413 | ''' |
|
416 | ''' | |
| 414 | #Get Beacon signal |
|
417 | #Get Beacon signal | |
| 415 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) |
|
418 | newheis = numpy.where(self.dataOut.heightList>self.dataOut.radarControllerHeaderObj.Taus[tauindex]) | |
| 416 |
|
419 | |||
| 417 | if hei_ref != None: |
|
420 | if hei_ref != None: | |
| 418 | newheis = numpy.where(self.dataOut.heightList>hei_ref) |
|
421 | newheis = numpy.where(self.dataOut.heightList>hei_ref) | |
| 419 |
|
422 | |||
| 420 | heiRang = self.dataOut.getHeiRange() |
|
423 | heiRang = self.dataOut.getHeiRange() | |
| 421 | #Pairs List |
|
424 | #Pairs List | |
| 422 | ''' |
|
425 | ''' | |
| 423 | Cambiar este pairslist |
|
426 | Cambiar este pairslist | |
| 424 | ''' |
|
427 | ''' | |
| 425 | pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] |
|
428 | pairslist = [(channelCentX, channel25X),(channelCentX, channel20X),(channelCentY,channel25Y),(channelCentY, channel20Y)] | |
| 426 |
|
429 | |||
| 427 | # nChannel = self.dataOut.nChannels |
|
430 | # nChannel = self.dataOut.nChannels | |
| 428 | # for i in range(nChannel): |
|
431 | # for i in range(nChannel): | |
| 429 | # if i != centerReceiverIndex: |
|
432 | # if i != centerReceiverIndex: | |
| 430 | # pairslist.append((centerReceiverIndex,i)) |
|
433 | # pairslist.append((centerReceiverIndex,i)) | |
| 431 |
|
434 | |||
| 432 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** |
|
435 | #****************REMOVING HARDWARE PHASE DIFFERENCES*************** | |
| 433 | # see if the user put in pre defined phase shifts |
|
436 | # see if the user put in pre defined phase shifts | |
| 434 | voltsPShift = self.dataOut.data_pre.copy() |
|
437 | voltsPShift = self.dataOut.data_pre.copy() | |
| 435 |
|
438 | |||
| 436 | # if predefinedPhaseShifts != None: |
|
439 | # if predefinedPhaseShifts != None: | |
| 437 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 |
|
440 | # hardwarePhaseShifts = numpy.array(predefinedPhaseShifts)*numpy.pi/180 | |
| 438 | # |
|
441 | # | |
| 439 | # # elif beaconPhaseShifts: |
|
442 | # # elif beaconPhaseShifts: | |
| 440 | # # #get hardware phase shifts using beacon signal |
|
443 | # # #get hardware phase shifts using beacon signal | |
| 441 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) |
|
444 | # # hardwarePhaseShifts = self.__getHardwarePhaseDiff(self.dataOut.data_pre, pairslist, newheis, 10) | |
| 442 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) |
|
445 | # # hardwarePhaseShifts = numpy.insert(hardwarePhaseShifts,centerReceiverIndex,0) | |
| 443 | # |
|
446 | # | |
| 444 | # else: |
|
447 | # else: | |
| 445 | # hardwarePhaseShifts = numpy.zeros(5) |
|
448 | # hardwarePhaseShifts = numpy.zeros(5) | |
| 446 | # |
|
449 | # | |
| 447 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') |
|
450 | # voltsPShift = numpy.zeros((self.dataOut.data_pre.shape[0],self.dataOut.data_pre.shape[1],self.dataOut.data_pre.shape[2]), dtype = 'complex') | |
| 448 | # for i in range(self.dataOut.data_pre.shape[0]): |
|
451 | # for i in range(self.dataOut.data_pre.shape[0]): | |
| 449 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) |
|
452 | # voltsPShift[i,:,:] = self.__shiftPhase(self.dataOut.data_pre[i,:,:], hardwarePhaseShifts[i]) | |
| 450 |
|
453 | |||
| 451 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* |
|
454 | #******************END OF REMOVING HARDWARE PHASE DIFFERENCES********* | |
| 452 |
|
455 | |||
| 453 | #Remove DC |
|
456 | #Remove DC | |
| 454 | voltsDC = numpy.mean(voltsPShift,1) |
|
457 | voltsDC = numpy.mean(voltsPShift,1) | |
| 455 | voltsDC = numpy.mean(voltsDC,1) |
|
458 | voltsDC = numpy.mean(voltsDC,1) | |
| 456 | for i in range(voltsDC.shape[0]): |
|
459 | for i in range(voltsDC.shape[0]): | |
| 457 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] |
|
460 | voltsPShift[i] = voltsPShift[i] - voltsDC[i] | |
| 458 |
|
461 | |||
| 459 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift |
|
462 | #Don't considerate last heights, theyre used to calculate Hardware Phase Shift | |
| 460 | voltsPShift = voltsPShift[:,:,:newheis[0][0]] |
|
463 | voltsPShift = voltsPShift[:,:,:newheis[0][0]] | |
| 461 |
|
464 | |||
| 462 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** |
|
465 | #************ FIND POWER OF DATA W/COH OR NON COH DETECTION (3.4) ********** | |
| 463 | #Coherent Detection |
|
466 | #Coherent Detection | |
| 464 | if cohDetection: |
|
467 | if cohDetection: | |
| 465 | #use coherent detection to get the net power |
|
468 | #use coherent detection to get the net power | |
| 466 | cohDet_thresh = cohDet_thresh*numpy.pi/180 |
|
469 | cohDet_thresh = cohDet_thresh*numpy.pi/180 | |
| 467 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, self.dataOut.timeInterval, pairslist, cohDet_thresh) |
|
470 | voltsPShift = self.__coherentDetection(voltsPShift, cohDet_timeStep, self.dataOut.timeInterval, pairslist, cohDet_thresh) | |
| 468 |
|
471 | |||
| 469 | #Non-coherent detection! |
|
472 | #Non-coherent detection! | |
| 470 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) |
|
473 | powerNet = numpy.nansum(numpy.abs(voltsPShift[:,:,:])**2,0) | |
| 471 | #********** END OF COH/NON-COH POWER CALCULATION********************** |
|
474 | #********** END OF COH/NON-COH POWER CALCULATION********************** | |
| 472 |
|
475 | |||
| 473 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** |
|
476 | #********** FIND THE NOISE LEVEL AND POSSIBLE METEORS **************** | |
| 474 | #Get noise |
|
477 | #Get noise | |
| 475 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, self.dataOut.timeInterval) |
|
478 | noise, noise1 = self.__getNoise(powerNet, noise_timeStep, self.dataOut.timeInterval) | |
| 476 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) |
|
479 | # noise = self.getNoise1(powerNet, noise_timeStep, self.dataOut.timeInterval) | |
| 477 | #Get signal threshold |
|
480 | #Get signal threshold | |
| 478 | signalThresh = noise_multiple*noise |
|
481 | signalThresh = noise_multiple*noise | |
| 479 | #Meteor echoes detection |
|
482 | #Meteor echoes detection | |
| 480 | listMeteors = self.__findMeteors(powerNet, signalThresh) |
|
483 | listMeteors = self.__findMeteors(powerNet, signalThresh) | |
| 481 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** |
|
484 | #******* END OF NOISE LEVEL AND POSSIBLE METEORS CACULATION ********** | |
| 482 |
|
485 | |||
| 483 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** |
|
486 | #************** REMOVE MULTIPLE DETECTIONS (3.5) *************************** | |
| 484 | #Parameters |
|
487 | #Parameters | |
| 485 | heiRange = self.dataOut.getHeiRange() |
|
488 | heiRange = self.dataOut.getHeiRange() | |
| 486 | rangeInterval = heiRange[1] - heiRange[0] |
|
489 | rangeInterval = heiRange[1] - heiRange[0] | |
| 487 | rangeLimit = multDet_rangeLimit/rangeInterval |
|
490 | rangeLimit = multDet_rangeLimit/rangeInterval | |
| 488 | timeLimit = multDet_timeLimit/self.dataOut.timeInterval |
|
491 | timeLimit = multDet_timeLimit/self.dataOut.timeInterval | |
| 489 | #Multiple detection removals |
|
492 | #Multiple detection removals | |
| 490 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) |
|
493 | listMeteors1 = self.__removeMultipleDetections(listMeteors, rangeLimit, timeLimit) | |
| 491 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** |
|
494 | #************ END OF REMOVE MULTIPLE DETECTIONS ********************** | |
| 492 |
|
495 | |||
| 493 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** |
|
496 | #********************* METEOR REESTIMATION (3.7, 3.8, 3.9, 3.10) ******************** | |
| 494 | #Parameters |
|
497 | #Parameters | |
| 495 | phaseThresh = phaseThresh*numpy.pi/180 |
|
498 | phaseThresh = phaseThresh*numpy.pi/180 | |
| 496 | thresh = [phaseThresh, noise_multiple, SNRThresh] |
|
499 | thresh = [phaseThresh, noise_multiple, SNRThresh] | |
| 497 | #Meteor reestimation (Errors N 1, 6, 12, 17) |
|
500 | #Meteor reestimation (Errors N 1, 6, 12, 17) | |
| 498 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist, thresh, noise, self.dataOut.timeInterval, self.dataOut.frequency) |
|
501 | listMeteors2, listMeteorsPower, listMeteorsVolts = self.__meteorReestimation(listMeteors1, voltsPShift, pairslist, thresh, noise, self.dataOut.timeInterval, self.dataOut.frequency) | |
| 499 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) |
|
502 | # listMeteors2, listMeteorsPower, listMeteorsVolts = self.meteorReestimation3(listMeteors2, listMeteorsPower, listMeteorsVolts, voltsPShift, pairslist, thresh, noise) | |
| 500 | #Estimation of decay times (Errors N 7, 8, 11) |
|
503 | #Estimation of decay times (Errors N 7, 8, 11) | |
| 501 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, self.dataOut.timeInterval, self.dataOut.frequency) |
|
504 | listMeteors3 = self.__estimateDecayTime(listMeteors2, listMeteorsPower, self.dataOut.timeInterval, self.dataOut.frequency) | |
| 502 | #******************* END OF METEOR REESTIMATION ******************* |
|
505 | #******************* END OF METEOR REESTIMATION ******************* | |
| 503 |
|
506 | |||
| 504 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** |
|
507 | #********************* METEOR PARAMETERS CALCULATION (3.11, 3.12, 3.13) ************************** | |
| 505 | #Calculating Radial Velocity (Error N 15) |
|
508 | #Calculating Radial Velocity (Error N 15) | |
| 506 | radialStdThresh = 10 |
|
509 | radialStdThresh = 10 | |
| 507 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist, self.dataOut.timeInterval) |
|
510 | listMeteors4 = self.__getRadialVelocity(listMeteors3, listMeteorsVolts, radialStdThresh, pairslist, self.dataOut.timeInterval) | |
| 508 |
|
511 | |||
| 509 | if len(listMeteors4) > 0: |
|
512 | if len(listMeteors4) > 0: | |
| 510 | #Setting New Array |
|
513 | #Setting New Array | |
| 511 | date = self.dataOut.utctime |
|
514 | date = self.dataOut.utctime | |
| 512 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) |
|
515 | arrayParameters = self.__setNewArrays(listMeteors4, date, heiRang) | |
| 513 |
|
516 | |||
| 514 | #Correcting phase offset |
|
517 | #Correcting phase offset | |
| 515 | if phaseOffsets != None: |
|
518 | if phaseOffsets != None: | |
| 516 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
519 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |
| 517 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
520 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |
| 518 |
|
521 | |||
| 519 | #Second Pairslist |
|
522 | #Second Pairslist | |
| 520 | pairsList = [] |
|
523 | pairsList = [] | |
| 521 | pairx = (0,1) |
|
524 | pairx = (0,1) | |
| 522 | pairy = (2,3) |
|
525 | pairy = (2,3) | |
| 523 | pairsList.append(pairx) |
|
526 | pairsList.append(pairx) | |
| 524 | pairsList.append(pairy) |
|
527 | pairsList.append(pairy) | |
| 525 |
|
528 | |||
| 526 | meteorOps = MeteorOperations() |
|
529 | meteorOps = MeteorOperations() | |
| 527 | jph = numpy.array([0,0,0,0]) |
|
530 | jph = numpy.array([0,0,0,0]) | |
| 528 | h = (hmin,hmax) |
|
531 | h = (hmin,hmax) | |
| 529 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, jph) |
|
532 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, jph) | |
| 530 |
|
533 | |||
| 531 | # #Calculate AOA (Error N 3, 4) |
|
534 | # #Calculate AOA (Error N 3, 4) | |
| 532 | # #JONES ET AL. 1998 |
|
535 | # #JONES ET AL. 1998 | |
| 533 | # error = arrayParameters[:,-1] |
|
536 | # error = arrayParameters[:,-1] | |
| 534 | # AOAthresh = numpy.pi/8 |
|
537 | # AOAthresh = numpy.pi/8 | |
| 535 | # phases = -arrayParameters[:,9:13] |
|
538 | # phases = -arrayParameters[:,9:13] | |
| 536 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) |
|
539 | # arrayParameters[:,4:7], arrayParameters[:,-1] = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) | |
| 537 | # |
|
540 | # | |
| 538 | # #Calculate Heights (Error N 13 and 14) |
|
541 | # #Calculate Heights (Error N 13 and 14) | |
| 539 | # error = arrayParameters[:,-1] |
|
542 | # error = arrayParameters[:,-1] | |
| 540 | # Ranges = arrayParameters[:,2] |
|
543 | # Ranges = arrayParameters[:,2] | |
| 541 | # zenith = arrayParameters[:,5] |
|
544 | # zenith = arrayParameters[:,5] | |
| 542 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) |
|
545 | # arrayParameters[:,3], arrayParameters[:,-1] = meteorOps.getHeights(Ranges, zenith, error, hmin, hmax) | |
| 543 | # error = arrayParameters[:,-1] |
|
546 | # error = arrayParameters[:,-1] | |
| 544 | #********************* END OF PARAMETERS CALCULATION ************************** |
|
547 | #********************* END OF PARAMETERS CALCULATION ************************** | |
| 545 |
|
548 | |||
| 546 | #***************************+ PASS DATA TO NEXT STEP ********************** |
|
549 | #***************************+ PASS DATA TO NEXT STEP ********************** | |
| 547 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) |
|
550 | # arrayFinal = arrayParameters.reshape((1,arrayParameters.shape[0],arrayParameters.shape[1])) | |
| 548 | self.dataOut.data_param = arrayParameters |
|
551 | self.dataOut.data_param = arrayParameters | |
| 549 |
|
552 | |||
| 550 | if arrayParameters == None: |
|
553 | if arrayParameters == None: | |
| 551 | self.dataOut.flagNoData = True |
|
554 | self.dataOut.flagNoData = True | |
| 552 |
|
555 | |||
| 553 | return |
|
556 | return | |
| 554 |
|
557 | |||
| 555 | def CorrectMeteorPhases(self, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45): |
|
558 | def CorrectMeteorPhases(self, phaseOffsets, hmin = 50, hmax = 150, azimuth = 45): | |
| 556 |
|
559 | |||
| 557 | arrayParameters = self.dataOut.data_param |
|
560 | arrayParameters = self.dataOut.data_param | |
| 558 | pairsList = [] |
|
561 | pairsList = [] | |
| 559 | pairx = (0,1) |
|
562 | pairx = (0,1) | |
| 560 | pairy = (2,3) |
|
563 | pairy = (2,3) | |
| 561 | pairsList.append(pairx) |
|
564 | pairsList.append(pairx) | |
| 562 | pairsList.append(pairy) |
|
565 | pairsList.append(pairy) | |
| 563 | jph = numpy.zeros(4) |
|
566 | jph = numpy.zeros(4) | |
| 564 |
|
567 | |||
| 565 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 |
|
568 | phaseOffsets = numpy.array(phaseOffsets)*numpy.pi/180 | |
| 566 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) |
|
569 | arrayParameters[:,8:12] = numpy.unwrap(arrayParameters[:,8:12] + phaseOffsets) | |
| 567 |
|
570 | |||
| 568 | meteorOps = MeteorOperations() |
|
571 | meteorOps = MeteorOperations() | |
| 569 | h = (hmin,hmax) |
|
572 | h = (hmin,hmax) | |
| 570 |
|
573 | |||
| 571 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, jph) |
|
574 | arrayParameters = meteorOps.getMeteorParams(arrayParameters, azimuth, h, pairsList, jph) | |
| 572 | self.dataOut.data_param = arrayParameters |
|
575 | self.dataOut.data_param = arrayParameters | |
| 573 | return |
|
576 | return | |
| 574 |
|
577 | |||
| 575 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): |
|
578 | def __getHardwarePhaseDiff(self, voltage0, pairslist, newheis, n): | |
| 576 |
|
579 | |||
| 577 | minIndex = min(newheis[0]) |
|
580 | minIndex = min(newheis[0]) | |
| 578 | maxIndex = max(newheis[0]) |
|
581 | maxIndex = max(newheis[0]) | |
| 579 |
|
582 | |||
| 580 | voltage = voltage0[:,:,minIndex:maxIndex+1] |
|
583 | voltage = voltage0[:,:,minIndex:maxIndex+1] | |
| 581 | nLength = voltage.shape[1]/n |
|
584 | nLength = voltage.shape[1]/n | |
| 582 | nMin = 0 |
|
585 | nMin = 0 | |
| 583 | nMax = 0 |
|
586 | nMax = 0 | |
| 584 | phaseOffset = numpy.zeros((len(pairslist),n)) |
|
587 | phaseOffset = numpy.zeros((len(pairslist),n)) | |
| 585 |
|
588 | |||
| 586 | for i in range(n): |
|
589 | for i in range(n): | |
| 587 | nMax += nLength |
|
590 | nMax += nLength | |
| 588 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) |
|
591 | phaseCCF = -numpy.angle(self.__calculateCCF(voltage[:,nMin:nMax,:], pairslist, [0])) | |
| 589 | phaseCCF = numpy.mean(phaseCCF, axis = 2) |
|
592 | phaseCCF = numpy.mean(phaseCCF, axis = 2) | |
| 590 | phaseOffset[:,i] = phaseCCF.transpose() |
|
593 | phaseOffset[:,i] = phaseCCF.transpose() | |
| 591 | nMin = nMax |
|
594 | nMin = nMax | |
| 592 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) |
|
595 | # phaseDiff, phaseArrival = self.estimatePhaseDifference(voltage, pairslist) | |
| 593 |
|
596 | |||
| 594 | #Remove Outliers |
|
597 | #Remove Outliers | |
| 595 | factor = 2 |
|
598 | factor = 2 | |
| 596 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) |
|
599 | wt = phaseOffset - signal.medfilt(phaseOffset,(1,5)) | |
| 597 | dw = numpy.std(wt,axis = 1) |
|
600 | dw = numpy.std(wt,axis = 1) | |
| 598 | dw = dw.reshape((dw.size,1)) |
|
601 | dw = dw.reshape((dw.size,1)) | |
| 599 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) |
|
602 | ind = numpy.where(numpy.logical_or(wt>dw*factor,wt<-dw*factor)) | |
| 600 | phaseOffset[ind] = numpy.nan |
|
603 | phaseOffset[ind] = numpy.nan | |
| 601 | phaseOffset = stats.nanmean(phaseOffset, axis=1) |
|
604 | phaseOffset = stats.nanmean(phaseOffset, axis=1) | |
| 602 |
|
605 | |||
| 603 | return phaseOffset |
|
606 | return phaseOffset | |
| 604 |
|
607 | |||
| 605 | def __shiftPhase(self, data, phaseShift): |
|
608 | def __shiftPhase(self, data, phaseShift): | |
| 606 | #this will shift the phase of a complex number |
|
609 | #this will shift the phase of a complex number | |
| 607 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) |
|
610 | dataShifted = numpy.abs(data) * numpy.exp((numpy.angle(data)+phaseShift)*1j) | |
| 608 | return dataShifted |
|
611 | return dataShifted | |
| 609 |
|
612 | |||
| 610 | def __estimatePhaseDifference(self, array, pairslist): |
|
613 | def __estimatePhaseDifference(self, array, pairslist): | |
| 611 | nChannel = array.shape[0] |
|
614 | nChannel = array.shape[0] | |
| 612 | nHeights = array.shape[2] |
|
615 | nHeights = array.shape[2] | |
| 613 | numPairs = len(pairslist) |
|
616 | numPairs = len(pairslist) | |
| 614 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) |
|
617 | # phaseCCF = numpy.zeros((nChannel, 5, nHeights)) | |
| 615 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) |
|
618 | phaseCCF = numpy.angle(self.__calculateCCF(array, pairslist, [-2,-1,0,1,2])) | |
| 616 |
|
619 | |||
| 617 | #Correct phases |
|
620 | #Correct phases | |
| 618 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] |
|
621 | derPhaseCCF = phaseCCF[:,1:,:] - phaseCCF[:,0:-1,:] | |
| 619 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
622 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |
| 620 |
|
623 | |||
| 621 | if indDer[0].shape[0] > 0: |
|
624 | if indDer[0].shape[0] > 0: | |
| 622 | for i in range(indDer[0].shape[0]): |
|
625 | for i in range(indDer[0].shape[0]): | |
| 623 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) |
|
626 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i],indDer[2][i]]) | |
| 624 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi |
|
627 | phaseCCF[indDer[0][i],indDer[1][i]+1:,:] += signo*2*numpy.pi | |
| 625 |
|
628 | |||
| 626 | # for j in range(numSides): |
|
629 | # for j in range(numSides): | |
| 627 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) |
|
630 | # phaseCCFAux = self.calculateCCF(arrayCenter, arraySides[j,:,:], [-2,1,0,1,2]) | |
| 628 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) |
|
631 | # phaseCCF[j,:,:] = numpy.angle(phaseCCFAux) | |
| 629 | # |
|
632 | # | |
| 630 | #Linear |
|
633 | #Linear | |
| 631 | phaseInt = numpy.zeros((numPairs,1)) |
|
634 | phaseInt = numpy.zeros((numPairs,1)) | |
| 632 | angAllCCF = phaseCCF[:,[0,1,3,4],0] |
|
635 | angAllCCF = phaseCCF[:,[0,1,3,4],0] | |
| 633 | for j in range(numPairs): |
|
636 | for j in range(numPairs): | |
| 634 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) |
|
637 | fit = stats.linregress([-2,-1,1,2],angAllCCF[j,:]) | |
| 635 | phaseInt[j] = fit[1] |
|
638 | phaseInt[j] = fit[1] | |
| 636 | #Phase Differences |
|
639 | #Phase Differences | |
| 637 | phaseDiff = phaseInt - phaseCCF[:,2,:] |
|
640 | phaseDiff = phaseInt - phaseCCF[:,2,:] | |
| 638 | phaseArrival = phaseInt.reshape(phaseInt.size) |
|
641 | phaseArrival = phaseInt.reshape(phaseInt.size) | |
| 639 |
|
642 | |||
| 640 | #Dealias |
|
643 | #Dealias | |
| 641 | indAlias = numpy.where(phaseArrival > numpy.pi) |
|
644 | indAlias = numpy.where(phaseArrival > numpy.pi) | |
| 642 | phaseArrival[indAlias] -= 2*numpy.pi |
|
645 | phaseArrival[indAlias] -= 2*numpy.pi | |
| 643 | indAlias = numpy.where(phaseArrival < -numpy.pi) |
|
646 | indAlias = numpy.where(phaseArrival < -numpy.pi) | |
| 644 | phaseArrival[indAlias] += 2*numpy.pi |
|
647 | phaseArrival[indAlias] += 2*numpy.pi | |
| 645 |
|
648 | |||
| 646 | return phaseDiff, phaseArrival |
|
649 | return phaseDiff, phaseArrival | |
| 647 |
|
650 | |||
| 648 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): |
|
651 | def __coherentDetection(self, volts, timeSegment, timeInterval, pairslist, thresh): | |
| 649 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power |
|
652 | #this function will run the coherent detection used in Holdworth et al. 2004 and return the net power | |
| 650 | #find the phase shifts of each channel over 1 second intervals |
|
653 | #find the phase shifts of each channel over 1 second intervals | |
| 651 | #only look at ranges below the beacon signal |
|
654 | #only look at ranges below the beacon signal | |
| 652 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
655 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |
| 653 | numBlocks = int(volts.shape[1]/numProfPerBlock) |
|
656 | numBlocks = int(volts.shape[1]/numProfPerBlock) | |
| 654 | numHeights = volts.shape[2] |
|
657 | numHeights = volts.shape[2] | |
| 655 | nChannel = volts.shape[0] |
|
658 | nChannel = volts.shape[0] | |
| 656 | voltsCohDet = volts.copy() |
|
659 | voltsCohDet = volts.copy() | |
| 657 |
|
660 | |||
| 658 | pairsarray = numpy.array(pairslist) |
|
661 | pairsarray = numpy.array(pairslist) | |
| 659 | indSides = pairsarray[:,1] |
|
662 | indSides = pairsarray[:,1] | |
| 660 | # indSides = numpy.array(range(nChannel)) |
|
663 | # indSides = numpy.array(range(nChannel)) | |
| 661 | # indSides = numpy.delete(indSides, indCenter) |
|
664 | # indSides = numpy.delete(indSides, indCenter) | |
| 662 | # |
|
665 | # | |
| 663 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) |
|
666 | # listCenter = numpy.array_split(volts[indCenter,:,:], numBlocks, 0) | |
| 664 | listBlocks = numpy.array_split(volts, numBlocks, 1) |
|
667 | listBlocks = numpy.array_split(volts, numBlocks, 1) | |
| 665 |
|
668 | |||
| 666 | startInd = 0 |
|
669 | startInd = 0 | |
| 667 | endInd = 0 |
|
670 | endInd = 0 | |
| 668 |
|
671 | |||
| 669 | for i in range(numBlocks): |
|
672 | for i in range(numBlocks): | |
| 670 | startInd = endInd |
|
673 | startInd = endInd | |
| 671 | endInd = endInd + listBlocks[i].shape[1] |
|
674 | endInd = endInd + listBlocks[i].shape[1] | |
| 672 |
|
675 | |||
| 673 | arrayBlock = listBlocks[i] |
|
676 | arrayBlock = listBlocks[i] | |
| 674 | # arrayBlockCenter = listCenter[i] |
|
677 | # arrayBlockCenter = listCenter[i] | |
| 675 |
|
678 | |||
| 676 | #Estimate the Phase Difference |
|
679 | #Estimate the Phase Difference | |
| 677 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) |
|
680 | phaseDiff, aux = self.__estimatePhaseDifference(arrayBlock, pairslist) | |
| 678 | #Phase Difference RMS |
|
681 | #Phase Difference RMS | |
| 679 | arrayPhaseRMS = numpy.abs(phaseDiff) |
|
682 | arrayPhaseRMS = numpy.abs(phaseDiff) | |
| 680 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) |
|
683 | phaseRMSaux = numpy.sum(arrayPhaseRMS < thresh,0) | |
| 681 | indPhase = numpy.where(phaseRMSaux==4) |
|
684 | indPhase = numpy.where(phaseRMSaux==4) | |
| 682 | #Shifting |
|
685 | #Shifting | |
| 683 | if indPhase[0].shape[0] > 0: |
|
686 | if indPhase[0].shape[0] > 0: | |
| 684 | for j in range(indSides.size): |
|
687 | for j in range(indSides.size): | |
| 685 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) |
|
688 | arrayBlock[indSides[j],:,indPhase] = self.__shiftPhase(arrayBlock[indSides[j],:,indPhase], phaseDiff[j,indPhase].transpose()) | |
| 686 | voltsCohDet[:,startInd:endInd,:] = arrayBlock |
|
689 | voltsCohDet[:,startInd:endInd,:] = arrayBlock | |
| 687 |
|
690 | |||
| 688 | return voltsCohDet |
|
691 | return voltsCohDet | |
| 689 |
|
692 | |||
| 690 | def __calculateCCF(self, volts, pairslist ,laglist): |
|
693 | def __calculateCCF(self, volts, pairslist ,laglist): | |
| 691 |
|
694 | |||
| 692 | nHeights = volts.shape[2] |
|
695 | nHeights = volts.shape[2] | |
| 693 | nPoints = volts.shape[1] |
|
696 | nPoints = volts.shape[1] | |
| 694 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') |
|
697 | voltsCCF = numpy.zeros((len(pairslist), len(laglist), nHeights),dtype = 'complex') | |
| 695 |
|
698 | |||
| 696 | for i in range(len(pairslist)): |
|
699 | for i in range(len(pairslist)): | |
| 697 | volts1 = volts[pairslist[i][0]] |
|
700 | volts1 = volts[pairslist[i][0]] | |
| 698 | volts2 = volts[pairslist[i][1]] |
|
701 | volts2 = volts[pairslist[i][1]] | |
| 699 |
|
702 | |||
| 700 | for t in range(len(laglist)): |
|
703 | for t in range(len(laglist)): | |
| 701 | idxT = laglist[t] |
|
704 | idxT = laglist[t] | |
| 702 | if idxT >= 0: |
|
705 | if idxT >= 0: | |
| 703 | vStacked = numpy.vstack((volts2[idxT:,:], |
|
706 | vStacked = numpy.vstack((volts2[idxT:,:], | |
| 704 | numpy.zeros((idxT, nHeights),dtype='complex'))) |
|
707 | numpy.zeros((idxT, nHeights),dtype='complex'))) | |
| 705 | else: |
|
708 | else: | |
| 706 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), |
|
709 | vStacked = numpy.vstack((numpy.zeros((-idxT, nHeights),dtype='complex'), | |
| 707 | volts2[:(nPoints + idxT),:])) |
|
710 | volts2[:(nPoints + idxT),:])) | |
| 708 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) |
|
711 | voltsCCF[i,t,:] = numpy.sum((numpy.conjugate(volts1)*vStacked),axis=0) | |
| 709 |
|
712 | |||
| 710 | vStacked = None |
|
713 | vStacked = None | |
| 711 | return voltsCCF |
|
714 | return voltsCCF | |
| 712 |
|
715 | |||
| 713 | def __getNoise(self, power, timeSegment, timeInterval): |
|
716 | def __getNoise(self, power, timeSegment, timeInterval): | |
| 714 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) |
|
717 | numProfPerBlock = numpy.ceil(timeSegment/timeInterval) | |
| 715 | numBlocks = int(power.shape[0]/numProfPerBlock) |
|
718 | numBlocks = int(power.shape[0]/numProfPerBlock) | |
| 716 | numHeights = power.shape[1] |
|
719 | numHeights = power.shape[1] | |
| 717 |
|
720 | |||
| 718 | listPower = numpy.array_split(power, numBlocks, 0) |
|
721 | listPower = numpy.array_split(power, numBlocks, 0) | |
| 719 | noise = numpy.zeros((power.shape[0], power.shape[1])) |
|
722 | noise = numpy.zeros((power.shape[0], power.shape[1])) | |
| 720 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) |
|
723 | noise1 = numpy.zeros((power.shape[0], power.shape[1])) | |
| 721 |
|
724 | |||
| 722 | startInd = 0 |
|
725 | startInd = 0 | |
| 723 | endInd = 0 |
|
726 | endInd = 0 | |
| 724 |
|
727 | |||
| 725 | for i in range(numBlocks): #split por canal |
|
728 | for i in range(numBlocks): #split por canal | |
| 726 | startInd = endInd |
|
729 | startInd = endInd | |
| 727 | endInd = endInd + listPower[i].shape[0] |
|
730 | endInd = endInd + listPower[i].shape[0] | |
| 728 |
|
731 | |||
| 729 | arrayBlock = listPower[i] |
|
732 | arrayBlock = listPower[i] | |
| 730 | noiseAux = numpy.mean(arrayBlock, 0) |
|
733 | noiseAux = numpy.mean(arrayBlock, 0) | |
| 731 | # noiseAux = numpy.median(noiseAux) |
|
734 | # noiseAux = numpy.median(noiseAux) | |
| 732 | # noiseAux = numpy.mean(arrayBlock) |
|
735 | # noiseAux = numpy.mean(arrayBlock) | |
| 733 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux |
|
736 | noise[startInd:endInd,:] = noise[startInd:endInd,:] + noiseAux | |
| 734 |
|
737 | |||
| 735 | noiseAux1 = numpy.mean(arrayBlock) |
|
738 | noiseAux1 = numpy.mean(arrayBlock) | |
| 736 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 |
|
739 | noise1[startInd:endInd,:] = noise1[startInd:endInd,:] + noiseAux1 | |
| 737 |
|
740 | |||
| 738 | return noise, noise1 |
|
741 | return noise, noise1 | |
| 739 |
|
742 | |||
| 740 | def __findMeteors(self, power, thresh): |
|
743 | def __findMeteors(self, power, thresh): | |
| 741 | nProf = power.shape[0] |
|
744 | nProf = power.shape[0] | |
| 742 | nHeights = power.shape[1] |
|
745 | nHeights = power.shape[1] | |
| 743 | listMeteors = [] |
|
746 | listMeteors = [] | |
| 744 |
|
747 | |||
| 745 | for i in range(nHeights): |
|
748 | for i in range(nHeights): | |
| 746 | powerAux = power[:,i] |
|
749 | powerAux = power[:,i] | |
| 747 | threshAux = thresh[:,i] |
|
750 | threshAux = thresh[:,i] | |
| 748 |
|
751 | |||
| 749 | indUPthresh = numpy.where(powerAux > threshAux)[0] |
|
752 | indUPthresh = numpy.where(powerAux > threshAux)[0] | |
| 750 | indDNthresh = numpy.where(powerAux <= threshAux)[0] |
|
753 | indDNthresh = numpy.where(powerAux <= threshAux)[0] | |
| 751 |
|
754 | |||
| 752 | j = 0 |
|
755 | j = 0 | |
| 753 |
|
756 | |||
| 754 | while (j < indUPthresh.size - 2): |
|
757 | while (j < indUPthresh.size - 2): | |
| 755 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): |
|
758 | if (indUPthresh[j + 2] == indUPthresh[j] + 2): | |
| 756 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) |
|
759 | indDNAux = numpy.where(indDNthresh > indUPthresh[j]) | |
| 757 | indDNthresh = indDNthresh[indDNAux] |
|
760 | indDNthresh = indDNthresh[indDNAux] | |
| 758 |
|
761 | |||
| 759 | if (indDNthresh.size > 0): |
|
762 | if (indDNthresh.size > 0): | |
| 760 | indEnd = indDNthresh[0] - 1 |
|
763 | indEnd = indDNthresh[0] - 1 | |
| 761 | indInit = indUPthresh[j] |
|
764 | indInit = indUPthresh[j] | |
| 762 |
|
765 | |||
| 763 | meteor = powerAux[indInit:indEnd + 1] |
|
766 | meteor = powerAux[indInit:indEnd + 1] | |
| 764 | indPeak = meteor.argmax() + indInit |
|
767 | indPeak = meteor.argmax() + indInit | |
| 765 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) |
|
768 | FLA = sum(numpy.conj(meteor)*numpy.hstack((meteor[1:],0))) | |
| 766 |
|
769 | |||
| 767 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! |
|
770 | listMeteors.append(numpy.array([i,indInit,indPeak,indEnd,FLA])) #CHEQUEAR!!!!! | |
| 768 | j = numpy.where(indUPthresh == indEnd)[0] + 1 |
|
771 | j = numpy.where(indUPthresh == indEnd)[0] + 1 | |
| 769 | else: j+=1 |
|
772 | else: j+=1 | |
| 770 | else: j+=1 |
|
773 | else: j+=1 | |
| 771 |
|
774 | |||
| 772 | return listMeteors |
|
775 | return listMeteors | |
| 773 |
|
776 | |||
| 774 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): |
|
777 | def __removeMultipleDetections(self,listMeteors, rangeLimit, timeLimit): | |
| 775 |
|
778 | |||
| 776 | arrayMeteors = numpy.asarray(listMeteors) |
|
779 | arrayMeteors = numpy.asarray(listMeteors) | |
| 777 | listMeteors1 = [] |
|
780 | listMeteors1 = [] | |
| 778 |
|
781 | |||
| 779 | while arrayMeteors.shape[0] > 0: |
|
782 | while arrayMeteors.shape[0] > 0: | |
| 780 | FLAs = arrayMeteors[:,4] |
|
783 | FLAs = arrayMeteors[:,4] | |
| 781 | maxFLA = FLAs.argmax() |
|
784 | maxFLA = FLAs.argmax() | |
| 782 | listMeteors1.append(arrayMeteors[maxFLA,:]) |
|
785 | listMeteors1.append(arrayMeteors[maxFLA,:]) | |
| 783 |
|
786 | |||
| 784 | MeteorInitTime = arrayMeteors[maxFLA,1] |
|
787 | MeteorInitTime = arrayMeteors[maxFLA,1] | |
| 785 | MeteorEndTime = arrayMeteors[maxFLA,3] |
|
788 | MeteorEndTime = arrayMeteors[maxFLA,3] | |
| 786 | MeteorHeight = arrayMeteors[maxFLA,0] |
|
789 | MeteorHeight = arrayMeteors[maxFLA,0] | |
| 787 |
|
790 | |||
| 788 | #Check neighborhood |
|
791 | #Check neighborhood | |
| 789 | maxHeightIndex = MeteorHeight + rangeLimit |
|
792 | maxHeightIndex = MeteorHeight + rangeLimit | |
| 790 | minHeightIndex = MeteorHeight - rangeLimit |
|
793 | minHeightIndex = MeteorHeight - rangeLimit | |
| 791 | minTimeIndex = MeteorInitTime - timeLimit |
|
794 | minTimeIndex = MeteorInitTime - timeLimit | |
| 792 | maxTimeIndex = MeteorEndTime + timeLimit |
|
795 | maxTimeIndex = MeteorEndTime + timeLimit | |
| 793 |
|
796 | |||
| 794 | #Check Heights |
|
797 | #Check Heights | |
| 795 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) |
|
798 | indHeight = numpy.logical_and(arrayMeteors[:,0] >= minHeightIndex, arrayMeteors[:,0] <= maxHeightIndex) | |
| 796 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) |
|
799 | indTime = numpy.logical_and(arrayMeteors[:,3] >= minTimeIndex, arrayMeteors[:,1] <= maxTimeIndex) | |
| 797 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) |
|
800 | indBoth = numpy.where(numpy.logical_and(indTime,indHeight)) | |
| 798 |
|
801 | |||
| 799 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) |
|
802 | arrayMeteors = numpy.delete(arrayMeteors, indBoth, axis = 0) | |
| 800 |
|
803 | |||
| 801 | return listMeteors1 |
|
804 | return listMeteors1 | |
| 802 |
|
805 | |||
| 803 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): |
|
806 | def __meteorReestimation(self, listMeteors, volts, pairslist, thresh, noise, timeInterval,frequency): | |
| 804 | numHeights = volts.shape[2] |
|
807 | numHeights = volts.shape[2] | |
| 805 | nChannel = volts.shape[0] |
|
808 | nChannel = volts.shape[0] | |
| 806 |
|
809 | |||
| 807 | thresholdPhase = thresh[0] |
|
810 | thresholdPhase = thresh[0] | |
| 808 | thresholdNoise = thresh[1] |
|
811 | thresholdNoise = thresh[1] | |
| 809 | thresholdDB = float(thresh[2]) |
|
812 | thresholdDB = float(thresh[2]) | |
| 810 |
|
813 | |||
| 811 | thresholdDB1 = 10**(thresholdDB/10) |
|
814 | thresholdDB1 = 10**(thresholdDB/10) | |
| 812 | pairsarray = numpy.array(pairslist) |
|
815 | pairsarray = numpy.array(pairslist) | |
| 813 | indSides = pairsarray[:,1] |
|
816 | indSides = pairsarray[:,1] | |
| 814 |
|
817 | |||
| 815 | pairslist1 = list(pairslist) |
|
818 | pairslist1 = list(pairslist) | |
| 816 | pairslist1.append((0,1)) |
|
819 | pairslist1.append((0,1)) | |
| 817 | pairslist1.append((3,4)) |
|
820 | pairslist1.append((3,4)) | |
| 818 |
|
821 | |||
| 819 | listMeteors1 = [] |
|
822 | listMeteors1 = [] | |
| 820 | listPowerSeries = [] |
|
823 | listPowerSeries = [] | |
| 821 | listVoltageSeries = [] |
|
824 | listVoltageSeries = [] | |
| 822 | #volts has the war data |
|
825 | #volts has the war data | |
| 823 |
|
826 | |||
| 824 | if frequency == 30e6: |
|
827 | if frequency == 30e6: | |
| 825 | timeLag = 45*10**-3 |
|
828 | timeLag = 45*10**-3 | |
| 826 | else: |
|
829 | else: | |
| 827 | timeLag = 15*10**-3 |
|
830 | timeLag = 15*10**-3 | |
| 828 | lag = numpy.ceil(timeLag/timeInterval) |
|
831 | lag = numpy.ceil(timeLag/timeInterval) | |
| 829 |
|
832 | |||
| 830 | for i in range(len(listMeteors)): |
|
833 | for i in range(len(listMeteors)): | |
| 831 |
|
834 | |||
| 832 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### |
|
835 | ###################### 3.6 - 3.7 PARAMETERS REESTIMATION ######################### | |
| 833 | meteorAux = numpy.zeros(16) |
|
836 | meteorAux = numpy.zeros(16) | |
| 834 |
|
837 | |||
| 835 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) |
|
838 | #Loading meteor Data (mHeight, mStart, mPeak, mEnd) | |
| 836 | mHeight = listMeteors[i][0] |
|
839 | mHeight = listMeteors[i][0] | |
| 837 | mStart = listMeteors[i][1] |
|
840 | mStart = listMeteors[i][1] | |
| 838 | mPeak = listMeteors[i][2] |
|
841 | mPeak = listMeteors[i][2] | |
| 839 | mEnd = listMeteors[i][3] |
|
842 | mEnd = listMeteors[i][3] | |
| 840 |
|
843 | |||
| 841 | #get the volt data between the start and end times of the meteor |
|
844 | #get the volt data between the start and end times of the meteor | |
| 842 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] |
|
845 | meteorVolts = volts[:,mStart:mEnd+1,mHeight] | |
| 843 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
846 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |
| 844 |
|
847 | |||
| 845 | #3.6. Phase Difference estimation |
|
848 | #3.6. Phase Difference estimation | |
| 846 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) |
|
849 | phaseDiff, aux = self.__estimatePhaseDifference(meteorVolts, pairslist) | |
| 847 |
|
850 | |||
| 848 | #3.7. Phase difference removal & meteor start, peak and end times reestimated |
|
851 | #3.7. Phase difference removal & meteor start, peak and end times reestimated | |
| 849 | #meteorVolts0.- all Channels, all Profiles |
|
852 | #meteorVolts0.- all Channels, all Profiles | |
| 850 | meteorVolts0 = volts[:,:,mHeight] |
|
853 | meteorVolts0 = volts[:,:,mHeight] | |
| 851 | meteorThresh = noise[:,mHeight]*thresholdNoise |
|
854 | meteorThresh = noise[:,mHeight]*thresholdNoise | |
| 852 | meteorNoise = noise[:,mHeight] |
|
855 | meteorNoise = noise[:,mHeight] | |
| 853 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting |
|
856 | meteorVolts0[indSides,:] = self.__shiftPhase(meteorVolts0[indSides,:], phaseDiff) #Phase Shifting | |
| 854 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power |
|
857 | powerNet0 = numpy.nansum(numpy.abs(meteorVolts0)**2, axis = 0) #Power | |
| 855 |
|
858 | |||
| 856 | #Times reestimation |
|
859 | #Times reestimation | |
| 857 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] |
|
860 | mStart1 = numpy.where(powerNet0[:mPeak] < meteorThresh[:mPeak])[0] | |
| 858 | if mStart1.size > 0: |
|
861 | if mStart1.size > 0: | |
| 859 | mStart1 = mStart1[-1] + 1 |
|
862 | mStart1 = mStart1[-1] + 1 | |
| 860 |
|
863 | |||
| 861 | else: |
|
864 | else: | |
| 862 | mStart1 = mPeak |
|
865 | mStart1 = mPeak | |
| 863 |
|
866 | |||
| 864 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 |
|
867 | mEnd1 = numpy.where(powerNet0[mPeak:] < meteorThresh[mPeak:])[0][0] + mPeak - 1 | |
| 865 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] |
|
868 | mEndDecayTime1 = numpy.where(powerNet0[mPeak:] < meteorNoise[mPeak:])[0] | |
| 866 | if mEndDecayTime1.size == 0: |
|
869 | if mEndDecayTime1.size == 0: | |
| 867 | mEndDecayTime1 = powerNet0.size |
|
870 | mEndDecayTime1 = powerNet0.size | |
| 868 | else: |
|
871 | else: | |
| 869 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 |
|
872 | mEndDecayTime1 = mEndDecayTime1[0] + mPeak - 1 | |
| 870 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() |
|
873 | # mPeak1 = meteorVolts0[mStart1:mEnd1 + 1].argmax() | |
| 871 |
|
874 | |||
| 872 | #meteorVolts1.- all Channels, from start to end |
|
875 | #meteorVolts1.- all Channels, from start to end | |
| 873 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] |
|
876 | meteorVolts1 = meteorVolts0[:,mStart1:mEnd1 + 1] | |
| 874 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] |
|
877 | meteorVolts2 = meteorVolts0[:,mPeak + lag:mEnd1 + 1] | |
| 875 | if meteorVolts2.shape[1] == 0: |
|
878 | if meteorVolts2.shape[1] == 0: | |
| 876 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] |
|
879 | meteorVolts2 = meteorVolts0[:,mPeak:mEnd1 + 1] | |
| 877 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) |
|
880 | meteorVolts1 = meteorVolts1.reshape(meteorVolts1.shape[0], meteorVolts1.shape[1], 1) | |
| 878 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) |
|
881 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1], 1) | |
| 879 | ##################### END PARAMETERS REESTIMATION ######################### |
|
882 | ##################### END PARAMETERS REESTIMATION ######################### | |
| 880 |
|
883 | |||
| 881 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## |
|
884 | ##################### 3.8 PHASE DIFFERENCE REESTIMATION ######################## | |
| 882 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis |
|
885 | # if mEnd1 - mStart1 > 4: #Error Number 6: echo less than 5 samples long; too short for analysis | |
| 883 | if meteorVolts2.shape[1] > 0: |
|
886 | if meteorVolts2.shape[1] > 0: | |
| 884 | #Phase Difference re-estimation |
|
887 | #Phase Difference re-estimation | |
| 885 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation |
|
888 | phaseDiff1, phaseDiffint = self.__estimatePhaseDifference(meteorVolts2, pairslist1) #Phase Difference Estimation | |
| 886 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) |
|
889 | # phaseDiff1, phaseDiffint = self.estimatePhaseDifference(meteorVolts2, pairslist) | |
| 887 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) |
|
890 | meteorVolts2 = meteorVolts2.reshape(meteorVolts2.shape[0], meteorVolts2.shape[1]) | |
| 888 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) |
|
891 | phaseDiff11 = numpy.reshape(phaseDiff1, (phaseDiff1.shape[0],1)) | |
| 889 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting |
|
892 | meteorVolts2[indSides,:] = self.__shiftPhase(meteorVolts2[indSides,:], phaseDiff11[0:4]) #Phase Shifting | |
| 890 |
|
893 | |||
| 891 | #Phase Difference RMS |
|
894 | #Phase Difference RMS | |
| 892 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) |
|
895 | phaseRMS1 = numpy.sqrt(numpy.mean(numpy.square(phaseDiff1))) | |
| 893 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) |
|
896 | powerNet1 = numpy.nansum(numpy.abs(meteorVolts1[:,:])**2,0) | |
| 894 | #Data from Meteor |
|
897 | #Data from Meteor | |
| 895 | mPeak1 = powerNet1.argmax() + mStart1 |
|
898 | mPeak1 = powerNet1.argmax() + mStart1 | |
| 896 | mPeakPower1 = powerNet1.max() |
|
899 | mPeakPower1 = powerNet1.max() | |
| 897 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) |
|
900 | noiseAux = sum(noise[mStart1:mEnd1 + 1,mHeight]) | |
| 898 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux |
|
901 | mSNR1 = (sum(powerNet1)-noiseAux)/noiseAux | |
| 899 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) |
|
902 | Meteor1 = numpy.array([mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1]) | |
| 900 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) |
|
903 | Meteor1 = numpy.hstack((Meteor1,phaseDiffint)) | |
| 901 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] |
|
904 | PowerSeries = powerNet0[mStart1:mEndDecayTime1 + 1] | |
| 902 | #Vectorize |
|
905 | #Vectorize | |
| 903 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] |
|
906 | meteorAux[0:7] = [mHeight, mStart1, mPeak1, mEnd1, mPeakPower1, mSNR1, phaseRMS1] | |
| 904 | meteorAux[7:11] = phaseDiffint[0:4] |
|
907 | meteorAux[7:11] = phaseDiffint[0:4] | |
| 905 |
|
908 | |||
| 906 | #Rejection Criterions |
|
909 | #Rejection Criterions | |
| 907 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation |
|
910 | if phaseRMS1 > thresholdPhase: #Error Number 17: Phase variation | |
| 908 | meteorAux[-1] = 17 |
|
911 | meteorAux[-1] = 17 | |
| 909 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB |
|
912 | elif mSNR1 < thresholdDB1: #Error Number 1: SNR < threshold dB | |
| 910 | meteorAux[-1] = 1 |
|
913 | meteorAux[-1] = 1 | |
| 911 |
|
914 | |||
| 912 |
|
915 | |||
| 913 | else: |
|
916 | else: | |
| 914 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] |
|
917 | meteorAux[0:4] = [mHeight, mStart, mPeak, mEnd] | |
| 915 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis |
|
918 | meteorAux[-1] = 6 #Error Number 6: echo less than 5 samples long; too short for analysis | |
| 916 | PowerSeries = 0 |
|
919 | PowerSeries = 0 | |
| 917 |
|
920 | |||
| 918 | listMeteors1.append(meteorAux) |
|
921 | listMeteors1.append(meteorAux) | |
| 919 | listPowerSeries.append(PowerSeries) |
|
922 | listPowerSeries.append(PowerSeries) | |
| 920 | listVoltageSeries.append(meteorVolts1) |
|
923 | listVoltageSeries.append(meteorVolts1) | |
| 921 |
|
924 | |||
| 922 | return listMeteors1, listPowerSeries, listVoltageSeries |
|
925 | return listMeteors1, listPowerSeries, listVoltageSeries | |
| 923 |
|
926 | |||
| 924 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): |
|
927 | def __estimateDecayTime(self, listMeteors, listPower, timeInterval, frequency): | |
| 925 |
|
928 | |||
| 926 | threshError = 10 |
|
929 | threshError = 10 | |
| 927 | #Depending if it is 30 or 50 MHz |
|
930 | #Depending if it is 30 or 50 MHz | |
| 928 | if frequency == 30e6: |
|
931 | if frequency == 30e6: | |
| 929 | timeLag = 45*10**-3 |
|
932 | timeLag = 45*10**-3 | |
| 930 | else: |
|
933 | else: | |
| 931 | timeLag = 15*10**-3 |
|
934 | timeLag = 15*10**-3 | |
| 932 | lag = numpy.ceil(timeLag/timeInterval) |
|
935 | lag = numpy.ceil(timeLag/timeInterval) | |
| 933 |
|
936 | |||
| 934 | listMeteors1 = [] |
|
937 | listMeteors1 = [] | |
| 935 |
|
938 | |||
| 936 | for i in range(len(listMeteors)): |
|
939 | for i in range(len(listMeteors)): | |
| 937 | meteorPower = listPower[i] |
|
940 | meteorPower = listPower[i] | |
| 938 | meteorAux = listMeteors[i] |
|
941 | meteorAux = listMeteors[i] | |
| 939 |
|
942 | |||
| 940 | if meteorAux[-1] == 0: |
|
943 | if meteorAux[-1] == 0: | |
| 941 |
|
944 | |||
| 942 | try: |
|
945 | try: | |
| 943 | indmax = meteorPower.argmax() |
|
946 | indmax = meteorPower.argmax() | |
| 944 | indlag = indmax + lag |
|
947 | indlag = indmax + lag | |
| 945 |
|
948 | |||
| 946 | y = meteorPower[indlag:] |
|
949 | y = meteorPower[indlag:] | |
| 947 | x = numpy.arange(0, y.size)*timeLag |
|
950 | x = numpy.arange(0, y.size)*timeLag | |
| 948 |
|
951 | |||
| 949 | #first guess |
|
952 | #first guess | |
| 950 | a = y[0] |
|
953 | a = y[0] | |
| 951 | tau = timeLag |
|
954 | tau = timeLag | |
| 952 | #exponential fit |
|
955 | #exponential fit | |
| 953 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) |
|
956 | popt, pcov = optimize.curve_fit(self.__exponential_function, x, y, p0 = [a, tau]) | |
| 954 | y1 = self.__exponential_function(x, *popt) |
|
957 | y1 = self.__exponential_function(x, *popt) | |
| 955 | #error estimation |
|
958 | #error estimation | |
| 956 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) |
|
959 | error = sum((y - y1)**2)/(numpy.var(y)*(y.size - popt.size)) | |
| 957 |
|
960 | |||
| 958 | decayTime = popt[1] |
|
961 | decayTime = popt[1] | |
| 959 | riseTime = indmax*timeInterval |
|
962 | riseTime = indmax*timeInterval | |
| 960 | meteorAux[11:13] = [decayTime, error] |
|
963 | meteorAux[11:13] = [decayTime, error] | |
| 961 |
|
964 | |||
| 962 | #Table items 7, 8 and 11 |
|
965 | #Table items 7, 8 and 11 | |
| 963 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s |
|
966 | if (riseTime > 0.3): #Number 7: Echo rise exceeds 0.3s | |
| 964 | meteorAux[-1] = 7 |
|
967 | meteorAux[-1] = 7 | |
| 965 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time |
|
968 | elif (decayTime < 2*riseTime) : #Number 8: Echo decay time less than than twice rise time | |
| 966 | meteorAux[-1] = 8 |
|
969 | meteorAux[-1] = 8 | |
| 967 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time |
|
970 | if (error > threshError): #Number 11: Poor fit to amplitude for estimation of decay time | |
| 968 | meteorAux[-1] = 11 |
|
971 | meteorAux[-1] = 11 | |
| 969 |
|
972 | |||
| 970 |
|
973 | |||
| 971 | except: |
|
974 | except: | |
| 972 | meteorAux[-1] = 11 |
|
975 | meteorAux[-1] = 11 | |
| 973 |
|
976 | |||
| 974 |
|
977 | |||
| 975 | listMeteors1.append(meteorAux) |
|
978 | listMeteors1.append(meteorAux) | |
| 976 |
|
979 | |||
| 977 | return listMeteors1 |
|
980 | return listMeteors1 | |
| 978 |
|
981 | |||
| 979 | #Exponential Function |
|
982 | #Exponential Function | |
| 980 |
|
983 | |||
| 981 | def __exponential_function(self, x, a, tau): |
|
984 | def __exponential_function(self, x, a, tau): | |
| 982 | y = a*numpy.exp(-x/tau) |
|
985 | y = a*numpy.exp(-x/tau) | |
| 983 | return y |
|
986 | return y | |
| 984 |
|
987 | |||
| 985 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): |
|
988 | def __getRadialVelocity(self, listMeteors, listVolts, radialStdThresh, pairslist, timeInterval): | |
| 986 |
|
989 | |||
| 987 | pairslist1 = list(pairslist) |
|
990 | pairslist1 = list(pairslist) | |
| 988 | pairslist1.append((0,1)) |
|
991 | pairslist1.append((0,1)) | |
| 989 | pairslist1.append((3,4)) |
|
992 | pairslist1.append((3,4)) | |
| 990 | numPairs = len(pairslist1) |
|
993 | numPairs = len(pairslist1) | |
| 991 | #Time Lag |
|
994 | #Time Lag | |
| 992 | timeLag = 45*10**-3 |
|
995 | timeLag = 45*10**-3 | |
| 993 | c = 3e8 |
|
996 | c = 3e8 | |
| 994 | lag = numpy.ceil(timeLag/timeInterval) |
|
997 | lag = numpy.ceil(timeLag/timeInterval) | |
| 995 | freq = 30e6 |
|
998 | freq = 30e6 | |
| 996 |
|
999 | |||
| 997 | listMeteors1 = [] |
|
1000 | listMeteors1 = [] | |
| 998 |
|
1001 | |||
| 999 | for i in range(len(listMeteors)): |
|
1002 | for i in range(len(listMeteors)): | |
| 1000 | meteorAux = listMeteors[i] |
|
1003 | meteorAux = listMeteors[i] | |
| 1001 | if meteorAux[-1] == 0: |
|
1004 | if meteorAux[-1] == 0: | |
| 1002 | mStart = listMeteors[i][1] |
|
1005 | mStart = listMeteors[i][1] | |
| 1003 | mPeak = listMeteors[i][2] |
|
1006 | mPeak = listMeteors[i][2] | |
| 1004 | mLag = mPeak - mStart + lag |
|
1007 | mLag = mPeak - mStart + lag | |
| 1005 |
|
1008 | |||
| 1006 | #get the volt data between the start and end times of the meteor |
|
1009 | #get the volt data between the start and end times of the meteor | |
| 1007 | meteorVolts = listVolts[i] |
|
1010 | meteorVolts = listVolts[i] | |
| 1008 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) |
|
1011 | meteorVolts = meteorVolts.reshape(meteorVolts.shape[0], meteorVolts.shape[1], 1) | |
| 1009 |
|
1012 | |||
| 1010 | #Get CCF |
|
1013 | #Get CCF | |
| 1011 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) |
|
1014 | allCCFs = self.__calculateCCF(meteorVolts, pairslist1, [-2,-1,0,1,2]) | |
| 1012 |
|
1015 | |||
| 1013 | #Method 2 |
|
1016 | #Method 2 | |
| 1014 | slopes = numpy.zeros(numPairs) |
|
1017 | slopes = numpy.zeros(numPairs) | |
| 1015 | time = numpy.array([-2,-1,1,2])*timeInterval |
|
1018 | time = numpy.array([-2,-1,1,2])*timeInterval | |
| 1016 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) |
|
1019 | angAllCCF = numpy.angle(allCCFs[:,[0,1,3,4],0]) | |
| 1017 |
|
1020 | |||
| 1018 | #Correct phases |
|
1021 | #Correct phases | |
| 1019 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] |
|
1022 | derPhaseCCF = angAllCCF[:,1:] - angAllCCF[:,0:-1] | |
| 1020 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) |
|
1023 | indDer = numpy.where(numpy.abs(derPhaseCCF) > numpy.pi) | |
| 1021 |
|
1024 | |||
| 1022 | if indDer[0].shape[0] > 0: |
|
1025 | if indDer[0].shape[0] > 0: | |
| 1023 | for i in range(indDer[0].shape[0]): |
|
1026 | for i in range(indDer[0].shape[0]): | |
| 1024 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) |
|
1027 | signo = -numpy.sign(derPhaseCCF[indDer[0][i],indDer[1][i]]) | |
| 1025 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi |
|
1028 | angAllCCF[indDer[0][i],indDer[1][i]+1:] += signo*2*numpy.pi | |
| 1026 |
|
1029 | |||
| 1027 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) |
|
1030 | # fit = scipy.stats.linregress(numpy.array([-2,-1,1,2])*timeInterval, numpy.array([phaseLagN2s[i],phaseLagN1s[i],phaseLag1s[i],phaseLag2s[i]])) | |
| 1028 | for j in range(numPairs): |
|
1031 | for j in range(numPairs): | |
| 1029 | fit = stats.linregress(time, angAllCCF[j,:]) |
|
1032 | fit = stats.linregress(time, angAllCCF[j,:]) | |
| 1030 | slopes[j] = fit[0] |
|
1033 | slopes[j] = fit[0] | |
| 1031 |
|
1034 | |||
| 1032 | #Remove Outlier |
|
1035 | #Remove Outlier | |
| 1033 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
1036 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |
| 1034 | # slopes = numpy.delete(slopes,indOut) |
|
1037 | # slopes = numpy.delete(slopes,indOut) | |
| 1035 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) |
|
1038 | # indOut = numpy.argmax(numpy.abs(slopes - numpy.mean(slopes))) | |
| 1036 | # slopes = numpy.delete(slopes,indOut) |
|
1039 | # slopes = numpy.delete(slopes,indOut) | |
| 1037 |
|
1040 | |||
| 1038 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) |
|
1041 | radialVelocity = -numpy.mean(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 1039 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) |
|
1042 | radialError = numpy.std(slopes)*(0.25/numpy.pi)*(c/freq) | |
| 1040 | meteorAux[-2] = radialError |
|
1043 | meteorAux[-2] = radialError | |
| 1041 | meteorAux[-3] = radialVelocity |
|
1044 | meteorAux[-3] = radialVelocity | |
| 1042 |
|
1045 | |||
| 1043 | #Setting Error |
|
1046 | #Setting Error | |
| 1044 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s |
|
1047 | #Number 15: Radial Drift velocity or projected horizontal velocity exceeds 200 m/s | |
| 1045 | if numpy.abs(radialVelocity) > 200: |
|
1048 | if numpy.abs(radialVelocity) > 200: | |
| 1046 | meteorAux[-1] = 15 |
|
1049 | meteorAux[-1] = 15 | |
| 1047 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity |
|
1050 | #Number 12: Poor fit to CCF variation for estimation of radial drift velocity | |
| 1048 | elif radialError > radialStdThresh: |
|
1051 | elif radialError > radialStdThresh: | |
| 1049 | meteorAux[-1] = 12 |
|
1052 | meteorAux[-1] = 12 | |
| 1050 |
|
1053 | |||
| 1051 | listMeteors1.append(meteorAux) |
|
1054 | listMeteors1.append(meteorAux) | |
| 1052 | return listMeteors1 |
|
1055 | return listMeteors1 | |
| 1053 |
|
1056 | |||
| 1054 | def __setNewArrays(self, listMeteors, date, heiRang): |
|
1057 | def __setNewArrays(self, listMeteors, date, heiRang): | |
| 1055 |
|
1058 | |||
| 1056 | #New arrays |
|
1059 | #New arrays | |
| 1057 | arrayMeteors = numpy.array(listMeteors) |
|
1060 | arrayMeteors = numpy.array(listMeteors) | |
| 1058 | arrayParameters = numpy.zeros((len(listMeteors), 13)) |
|
1061 | arrayParameters = numpy.zeros((len(listMeteors), 13)) | |
| 1059 |
|
1062 | |||
| 1060 | #Date inclusion |
|
1063 | #Date inclusion | |
| 1061 | # date = re.findall(r'\((.*?)\)', date) |
|
1064 | # date = re.findall(r'\((.*?)\)', date) | |
| 1062 | # date = date[0].split(',') |
|
1065 | # date = date[0].split(',') | |
| 1063 | # date = map(int, date) |
|
1066 | # date = map(int, date) | |
| 1064 | # |
|
1067 | # | |
| 1065 | # if len(date)<6: |
|
1068 | # if len(date)<6: | |
| 1066 | # date.append(0) |
|
1069 | # date.append(0) | |
| 1067 | # |
|
1070 | # | |
| 1068 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] |
|
1071 | # date = [date[0]*10000 + date[1]*100 + date[2], date[3]*10000 + date[4]*100 + date[5]] | |
| 1069 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) |
|
1072 | # arrayDate = numpy.tile(date, (len(listMeteors), 1)) | |
| 1070 | arrayDate = numpy.tile(date, (len(listMeteors))) |
|
1073 | arrayDate = numpy.tile(date, (len(listMeteors))) | |
| 1071 |
|
1074 | |||
| 1072 | #Meteor array |
|
1075 | #Meteor array | |
| 1073 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] |
|
1076 | # arrayMeteors[:,0] = heiRang[arrayMeteors[:,0].astype(int)] | |
| 1074 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) |
|
1077 | # arrayMeteors = numpy.hstack((arrayDate, arrayMeteors)) | |
| 1075 |
|
1078 | |||
| 1076 | #Parameters Array |
|
1079 | #Parameters Array | |
| 1077 | arrayParameters[:,0] = arrayDate #Date |
|
1080 | arrayParameters[:,0] = arrayDate #Date | |
| 1078 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range |
|
1081 | arrayParameters[:,1] = heiRang[arrayMeteors[:,0].astype(int)] #Range | |
| 1079 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error |
|
1082 | arrayParameters[:,6:8] = arrayMeteors[:,-3:-1] #Radial velocity and its error | |
| 1080 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases |
|
1083 | arrayParameters[:,8:12] = arrayMeteors[:,7:11] #Phases | |
| 1081 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error |
|
1084 | arrayParameters[:,-1] = arrayMeteors[:,-1] #Error | |
| 1082 |
|
1085 | |||
| 1083 |
|
1086 | |||
| 1084 | return arrayParameters |
|
1087 | return arrayParameters | |
| 1085 |
|
1088 | |||
| 1086 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): |
|
1089 | # def __getAOA(self, phases, pairsList, error, AOAthresh, azimuth): | |
| 1087 | # |
|
1090 | # | |
| 1088 | # arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
1091 | # arrayAOA = numpy.zeros((phases.shape[0],3)) | |
| 1089 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) |
|
1092 | # cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) | |
| 1090 | # |
|
1093 | # | |
| 1091 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
1094 | # arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |
| 1092 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
1095 | # cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |
| 1093 | # arrayAOA[:,2] = cosDirError |
|
1096 | # arrayAOA[:,2] = cosDirError | |
| 1094 | # |
|
1097 | # | |
| 1095 | # azimuthAngle = arrayAOA[:,0] |
|
1098 | # azimuthAngle = arrayAOA[:,0] | |
| 1096 | # zenithAngle = arrayAOA[:,1] |
|
1099 | # zenithAngle = arrayAOA[:,1] | |
| 1097 | # |
|
1100 | # | |
| 1098 | # #Setting Error |
|
1101 | # #Setting Error | |
| 1099 | # #Number 3: AOA not fesible |
|
1102 | # #Number 3: AOA not fesible | |
| 1100 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
1103 | # indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |
| 1101 | # error[indInvalid] = 3 |
|
1104 | # error[indInvalid] = 3 | |
| 1102 | # #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
1105 | # #Number 4: Large difference in AOAs obtained from different antenna baselines | |
| 1103 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
1106 | # indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |
| 1104 | # error[indInvalid] = 4 |
|
1107 | # error[indInvalid] = 4 | |
| 1105 | # return arrayAOA, error |
|
1108 | # return arrayAOA, error | |
| 1106 | # |
|
1109 | # | |
| 1107 | # def __getDirectionCosines(self, arrayPhase, pairsList): |
|
1110 | # def __getDirectionCosines(self, arrayPhase, pairsList): | |
| 1108 | # |
|
1111 | # | |
| 1109 | # #Initializing some variables |
|
1112 | # #Initializing some variables | |
| 1110 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
1113 | # ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |
| 1111 | # ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
1114 | # ang_aux = ang_aux.reshape(1,ang_aux.size) | |
| 1112 | # |
|
1115 | # | |
| 1113 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
1116 | # cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |
| 1114 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
1117 | # cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |
| 1115 | # |
|
1118 | # | |
| 1116 | # |
|
1119 | # | |
| 1117 | # for i in range(2): |
|
1120 | # for i in range(2): | |
| 1118 | # #First Estimation |
|
1121 | # #First Estimation | |
| 1119 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] |
|
1122 | # phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] | |
| 1120 | # #Dealias |
|
1123 | # #Dealias | |
| 1121 | # indcsi = numpy.where(phi0_aux > numpy.pi) |
|
1124 | # indcsi = numpy.where(phi0_aux > numpy.pi) | |
| 1122 | # phi0_aux[indcsi] -= 2*numpy.pi |
|
1125 | # phi0_aux[indcsi] -= 2*numpy.pi | |
| 1123 | # indcsi = numpy.where(phi0_aux < -numpy.pi) |
|
1126 | # indcsi = numpy.where(phi0_aux < -numpy.pi) | |
| 1124 | # phi0_aux[indcsi] += 2*numpy.pi |
|
1127 | # phi0_aux[indcsi] += 2*numpy.pi | |
| 1125 | # #Direction Cosine 0 |
|
1128 | # #Direction Cosine 0 | |
| 1126 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) |
|
1129 | # cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) | |
| 1127 | # |
|
1130 | # | |
| 1128 | # #Most-Accurate Second Estimation |
|
1131 | # #Most-Accurate Second Estimation | |
| 1129 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] |
|
1132 | # phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] | |
| 1130 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
1133 | # phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |
| 1131 | # #Direction Cosine 1 |
|
1134 | # #Direction Cosine 1 | |
| 1132 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) |
|
1135 | # cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) | |
| 1133 | # |
|
1136 | # | |
| 1134 | # #Searching the correct Direction Cosine |
|
1137 | # #Searching the correct Direction Cosine | |
| 1135 | # cosdir0_aux = cosdir0[:,i] |
|
1138 | # cosdir0_aux = cosdir0[:,i] | |
| 1136 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
1139 | # cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |
| 1137 | # #Minimum Distance |
|
1140 | # #Minimum Distance | |
| 1138 | # cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
1141 | # cosDiff = (cosdir1 - cosdir0_aux)**2 | |
| 1139 | # indcos = cosDiff.argmin(axis = 1) |
|
1142 | # indcos = cosDiff.argmin(axis = 1) | |
| 1140 | # #Saving Value obtained |
|
1143 | # #Saving Value obtained | |
| 1141 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
1144 | # cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |
| 1142 | # |
|
1145 | # | |
| 1143 | # return cosdir0, cosdir |
|
1146 | # return cosdir0, cosdir | |
| 1144 | # |
|
1147 | # | |
| 1145 | # def __calculateAOA(self, cosdir, azimuth): |
|
1148 | # def __calculateAOA(self, cosdir, azimuth): | |
| 1146 | # cosdirX = cosdir[:,0] |
|
1149 | # cosdirX = cosdir[:,0] | |
| 1147 | # cosdirY = cosdir[:,1] |
|
1150 | # cosdirY = cosdir[:,1] | |
| 1148 | # |
|
1151 | # | |
| 1149 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
1152 | # zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |
| 1150 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east |
|
1153 | # azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east | |
| 1151 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
1154 | # angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |
| 1152 | # |
|
1155 | # | |
| 1153 | # return angles |
|
1156 | # return angles | |
| 1154 | # |
|
1157 | # | |
| 1155 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
1158 | # def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |
| 1156 | # |
|
1159 | # | |
| 1157 | # Ramb = 375 #Ramb = c/(2*PRF) |
|
1160 | # Ramb = 375 #Ramb = c/(2*PRF) | |
| 1158 | # Re = 6371 #Earth Radius |
|
1161 | # Re = 6371 #Earth Radius | |
| 1159 | # heights = numpy.zeros(Ranges.shape) |
|
1162 | # heights = numpy.zeros(Ranges.shape) | |
| 1160 | # |
|
1163 | # | |
| 1161 | # R_aux = numpy.array([0,1,2])*Ramb |
|
1164 | # R_aux = numpy.array([0,1,2])*Ramb | |
| 1162 | # R_aux = R_aux.reshape(1,R_aux.size) |
|
1165 | # R_aux = R_aux.reshape(1,R_aux.size) | |
| 1163 | # |
|
1166 | # | |
| 1164 | # Ranges = Ranges.reshape(Ranges.size,1) |
|
1167 | # Ranges = Ranges.reshape(Ranges.size,1) | |
| 1165 | # |
|
1168 | # | |
| 1166 | # Ri = Ranges + R_aux |
|
1169 | # Ri = Ranges + R_aux | |
| 1167 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
1170 | # hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |
| 1168 | # |
|
1171 | # | |
| 1169 | # #Check if there is a height between 70 and 110 km |
|
1172 | # #Check if there is a height between 70 and 110 km | |
| 1170 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
1173 | # h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |
| 1171 | # ind_h = numpy.where(h_bool == 1)[0] |
|
1174 | # ind_h = numpy.where(h_bool == 1)[0] | |
| 1172 | # |
|
1175 | # | |
| 1173 | # hCorr = hi[ind_h, :] |
|
1176 | # hCorr = hi[ind_h, :] | |
| 1174 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
1177 | # ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |
| 1175 | # |
|
1178 | # | |
| 1176 | # hCorr = hi[ind_hCorr] |
|
1179 | # hCorr = hi[ind_hCorr] | |
| 1177 | # heights[ind_h] = hCorr |
|
1180 | # heights[ind_h] = hCorr | |
| 1178 | # |
|
1181 | # | |
| 1179 | # #Setting Error |
|
1182 | # #Setting Error | |
| 1180 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
1183 | # #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |
| 1181 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
1184 | # #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |
| 1182 | # |
|
1185 | # | |
| 1183 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
1186 | # indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |
| 1184 | # error[indInvalid2] = 14 |
|
1187 | # error[indInvalid2] = 14 | |
| 1185 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
1188 | # indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |
| 1186 | # error[indInvalid1] = 13 |
|
1189 | # error[indInvalid1] = 13 | |
| 1187 | # |
|
1190 | # | |
| 1188 | # return heights, error |
|
1191 | # return heights, error | |
| 1189 |
|
1192 | |||
| 1190 | def SpectralFitting(self, getSNR = True, path=None, file=None, groupList=None): |
|
1193 | def SpectralFitting(self, getSNR = True, path=None, file=None, groupList=None): | |
| 1191 |
|
1194 | |||
| 1192 | ''' |
|
1195 | ''' | |
| 1193 | Function GetMoments() |
|
1196 | Function GetMoments() | |
| 1194 |
|
1197 | |||
| 1195 | Input: |
|
1198 | Input: | |
| 1196 | Output: |
|
1199 | Output: | |
| 1197 | Variables modified: |
|
1200 | Variables modified: | |
| 1198 | ''' |
|
1201 | ''' | |
| 1199 | if path != None: |
|
1202 | if path != None: | |
| 1200 | sys.path.append(path) |
|
1203 | sys.path.append(path) | |
| 1201 | self.dataOut.library = importlib.import_module(file) |
|
1204 | self.dataOut.library = importlib.import_module(file) | |
| 1202 |
|
1205 | |||
| 1203 | #To be inserted as a parameter |
|
1206 | #To be inserted as a parameter | |
| 1204 | groupArray = numpy.array(groupList) |
|
1207 | groupArray = numpy.array(groupList) | |
| 1205 | # groupArray = numpy.array([[0,1],[2,3]]) |
|
1208 | # groupArray = numpy.array([[0,1],[2,3]]) | |
| 1206 | self.dataOut.groupList = groupArray |
|
1209 | self.dataOut.groupList = groupArray | |
| 1207 |
|
1210 | |||
| 1208 | nGroups = groupArray.shape[0] |
|
1211 | nGroups = groupArray.shape[0] | |
| 1209 | nChannels = self.dataIn.nChannels |
|
1212 | nChannels = self.dataIn.nChannels | |
| 1210 | nHeights=self.dataIn.heightList.size |
|
1213 | nHeights=self.dataIn.heightList.size | |
| 1211 |
|
1214 | |||
| 1212 | #Parameters Array |
|
1215 | #Parameters Array | |
| 1213 | self.dataOut.data_param = None |
|
1216 | self.dataOut.data_param = None | |
| 1214 |
|
1217 | |||
| 1215 | #Set constants |
|
1218 | #Set constants | |
| 1216 | constants = self.dataOut.library.setConstants(self.dataIn) |
|
1219 | constants = self.dataOut.library.setConstants(self.dataIn) | |
| 1217 | self.dataOut.constants = constants |
|
1220 | self.dataOut.constants = constants | |
| 1218 | M = self.dataIn.normFactor |
|
1221 | M = self.dataIn.normFactor | |
| 1219 | N = self.dataIn.nFFTPoints |
|
1222 | N = self.dataIn.nFFTPoints | |
| 1220 | ippSeconds = self.dataIn.ippSeconds |
|
1223 | ippSeconds = self.dataIn.ippSeconds | |
| 1221 | K = self.dataIn.nIncohInt |
|
1224 | K = self.dataIn.nIncohInt | |
| 1222 | pairsArray = numpy.array(self.dataIn.pairsList) |
|
1225 | pairsArray = numpy.array(self.dataIn.pairsList) | |
| 1223 |
|
1226 | |||
| 1224 | #List of possible combinations |
|
1227 | #List of possible combinations | |
| 1225 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) |
|
1228 | listComb = itertools.combinations(numpy.arange(groupArray.shape[1]),2) | |
| 1226 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') |
|
1229 | indCross = numpy.zeros(len(list(listComb)), dtype = 'int') | |
| 1227 |
|
1230 | |||
| 1228 | if getSNR: |
|
1231 | if getSNR: | |
| 1229 | listChannels = groupArray.reshape((groupArray.size)) |
|
1232 | listChannels = groupArray.reshape((groupArray.size)) | |
| 1230 | listChannels.sort() |
|
1233 | listChannels.sort() | |
| 1231 | noise = self.dataIn.getNoise() |
|
1234 | noise = self.dataIn.getNoise() | |
| 1232 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) |
|
1235 | self.dataOut.data_SNR = self.__getSNR(self.dataIn.data_spc[listChannels,:,:], noise[listChannels]) | |
| 1233 |
|
1236 | |||
| 1234 | for i in range(nGroups): |
|
1237 | for i in range(nGroups): | |
| 1235 | coord = groupArray[i,:] |
|
1238 | coord = groupArray[i,:] | |
| 1236 |
|
1239 | |||
| 1237 | #Input data array |
|
1240 | #Input data array | |
| 1238 | data = self.dataIn.data_spc[coord,:,:]/(M*N) |
|
1241 | data = self.dataIn.data_spc[coord,:,:]/(M*N) | |
| 1239 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) |
|
1242 | data = data.reshape((data.shape[0]*data.shape[1],data.shape[2])) | |
| 1240 |
|
1243 | |||
| 1241 | #Cross Spectra data array for Covariance Matrixes |
|
1244 | #Cross Spectra data array for Covariance Matrixes | |
| 1242 | ind = 0 |
|
1245 | ind = 0 | |
| 1243 | for pairs in listComb: |
|
1246 | for pairs in listComb: | |
| 1244 | pairsSel = numpy.array([coord[x],coord[y]]) |
|
1247 | pairsSel = numpy.array([coord[x],coord[y]]) | |
| 1245 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) |
|
1248 | indCross[ind] = int(numpy.where(numpy.all(pairsArray == pairsSel, axis = 1))[0][0]) | |
| 1246 | ind += 1 |
|
1249 | ind += 1 | |
| 1247 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) |
|
1250 | dataCross = self.dataIn.data_cspc[indCross,:,:]/(M*N) | |
| 1248 | dataCross = dataCross**2/K |
|
1251 | dataCross = dataCross**2/K | |
| 1249 |
|
1252 | |||
| 1250 | for h in range(nHeights): |
|
1253 | for h in range(nHeights): | |
| 1251 | # print self.dataOut.heightList[h] |
|
1254 | # print self.dataOut.heightList[h] | |
| 1252 |
|
1255 | |||
| 1253 | #Input |
|
1256 | #Input | |
| 1254 | d = data[:,h] |
|
1257 | d = data[:,h] | |
| 1255 |
|
1258 | |||
| 1256 | #Covariance Matrix |
|
1259 | #Covariance Matrix | |
| 1257 | D = numpy.diag(d**2/K) |
|
1260 | D = numpy.diag(d**2/K) | |
| 1258 | ind = 0 |
|
1261 | ind = 0 | |
| 1259 | for pairs in listComb: |
|
1262 | for pairs in listComb: | |
| 1260 | #Coordinates in Covariance Matrix |
|
1263 | #Coordinates in Covariance Matrix | |
| 1261 | x = pairs[0] |
|
1264 | x = pairs[0] | |
| 1262 | y = pairs[1] |
|
1265 | y = pairs[1] | |
| 1263 | #Channel Index |
|
1266 | #Channel Index | |
| 1264 | S12 = dataCross[ind,:,h] |
|
1267 | S12 = dataCross[ind,:,h] | |
| 1265 | D12 = numpy.diag(S12) |
|
1268 | D12 = numpy.diag(S12) | |
| 1266 | #Completing Covariance Matrix with Cross Spectras |
|
1269 | #Completing Covariance Matrix with Cross Spectras | |
| 1267 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 |
|
1270 | D[x*N:(x+1)*N,y*N:(y+1)*N] = D12 | |
| 1268 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 |
|
1271 | D[y*N:(y+1)*N,x*N:(x+1)*N] = D12 | |
| 1269 | ind += 1 |
|
1272 | ind += 1 | |
| 1270 | Dinv=numpy.linalg.inv(D) |
|
1273 | Dinv=numpy.linalg.inv(D) | |
| 1271 | L=numpy.linalg.cholesky(Dinv) |
|
1274 | L=numpy.linalg.cholesky(Dinv) | |
| 1272 | LT=L.T |
|
1275 | LT=L.T | |
| 1273 |
|
1276 | |||
| 1274 | dp = numpy.dot(LT,d) |
|
1277 | dp = numpy.dot(LT,d) | |
| 1275 |
|
1278 | |||
| 1276 | #Initial values |
|
1279 | #Initial values | |
| 1277 | data_spc = self.dataIn.data_spc[coord,:,h] |
|
1280 | data_spc = self.dataIn.data_spc[coord,:,h] | |
| 1278 |
|
1281 | |||
| 1279 | if (h>0)and(error1[3]<5): |
|
1282 | if (h>0)and(error1[3]<5): | |
| 1280 | p0 = self.dataOut.data_param[i,:,h-1] |
|
1283 | p0 = self.dataOut.data_param[i,:,h-1] | |
| 1281 | else: |
|
1284 | else: | |
| 1282 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) |
|
1285 | p0 = numpy.array(self.dataOut.library.initialValuesFunction(data_spc, constants, i)) | |
| 1283 |
|
1286 | |||
| 1284 | try: |
|
1287 | try: | |
| 1285 | #Least Squares |
|
1288 | #Least Squares | |
| 1286 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) |
|
1289 | minp,covp,infodict,mesg,ier = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants),full_output=True) | |
| 1287 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) |
|
1290 | # minp,covp = optimize.leastsq(self.__residFunction,p0,args=(dp,LT,constants)) | |
| 1288 | #Chi square error |
|
1291 | #Chi square error | |
| 1289 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) |
|
1292 | error0 = numpy.sum(infodict['fvec']**2)/(2*N) | |
| 1290 | #Error with Jacobian |
|
1293 | #Error with Jacobian | |
| 1291 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) |
|
1294 | error1 = self.dataOut.library.errorFunction(minp,constants,LT) | |
| 1292 | except: |
|
1295 | except: | |
| 1293 | minp = p0*numpy.nan |
|
1296 | minp = p0*numpy.nan | |
| 1294 | error0 = numpy.nan |
|
1297 | error0 = numpy.nan | |
| 1295 | error1 = p0*numpy.nan |
|
1298 | error1 = p0*numpy.nan | |
| 1296 |
|
1299 | |||
| 1297 | #Save |
|
1300 | #Save | |
| 1298 | if self.dataOut.data_param == None: |
|
1301 | if self.dataOut.data_param == None: | |
| 1299 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan |
|
1302 | self.dataOut.data_param = numpy.zeros((nGroups, p0.size, nHeights))*numpy.nan | |
| 1300 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan |
|
1303 | self.dataOut.data_error = numpy.zeros((nGroups, p0.size + 1, nHeights))*numpy.nan | |
| 1301 |
|
1304 | |||
| 1302 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) |
|
1305 | self.dataOut.data_error[i,:,h] = numpy.hstack((error0,error1)) | |
| 1303 | self.dataOut.data_param[i,:,h] = minp |
|
1306 | self.dataOut.data_param[i,:,h] = minp | |
| 1304 | return |
|
1307 | return | |
| 1305 |
|
1308 | |||
| 1306 | def __residFunction(self, p, dp, LT, constants): |
|
1309 | def __residFunction(self, p, dp, LT, constants): | |
| 1307 |
|
1310 | |||
| 1308 | fm = self.dataOut.library.modelFunction(p, constants) |
|
1311 | fm = self.dataOut.library.modelFunction(p, constants) | |
| 1309 | fmp=numpy.dot(LT,fm) |
|
1312 | fmp=numpy.dot(LT,fm) | |
| 1310 |
|
1313 | |||
| 1311 | return dp-fmp |
|
1314 | return dp-fmp | |
| 1312 |
|
1315 | |||
| 1313 | def __getSNR(self, z, noise): |
|
1316 | def __getSNR(self, z, noise): | |
| 1314 |
|
1317 | |||
| 1315 | avg = numpy.average(z, axis=1) |
|
1318 | avg = numpy.average(z, axis=1) | |
| 1316 | SNR = (avg.T-noise)/noise |
|
1319 | SNR = (avg.T-noise)/noise | |
| 1317 | SNR = SNR.T |
|
1320 | SNR = SNR.T | |
| 1318 | return SNR |
|
1321 | return SNR | |
| 1319 |
|
1322 | |||
| 1320 | def __chisq(p,chindex,hindex): |
|
1323 | def __chisq(p,chindex,hindex): | |
| 1321 | #similar to Resid but calculates CHI**2 |
|
1324 | #similar to Resid but calculates CHI**2 | |
| 1322 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) |
|
1325 | [LT,d,fm]=setupLTdfm(p,chindex,hindex) | |
| 1323 | dp=numpy.dot(LT,d) |
|
1326 | dp=numpy.dot(LT,d) | |
| 1324 | fmp=numpy.dot(LT,fm) |
|
1327 | fmp=numpy.dot(LT,fm) | |
| 1325 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) |
|
1328 | chisq=numpy.dot((dp-fmp).T,(dp-fmp)) | |
| 1326 | return chisq |
|
1329 | return chisq | |
|
|
1330 | ||||
|
|
1331 | def NonSpecularMeteorDetection(self, mode, SNRthresh=8, phaseDerThresh=0.5, cohThresh=0.8, allData = False): | |||
|
|
1332 | data_acf = self.dataOut.data_pre[0] | |||
|
|
1333 | data_ccf = self.dataOut.data_pre[1] | |||
| 1327 |
|
1334 | |||
|
|
1335 | lamb = self.dataOut.C/self.dataOut.frequency | |||
|
|
1336 | tSamp = self.dataOut.ippSeconds*self.dataOut.nCohInt | |||
|
|
1337 | paramInterval = self.dataOut.paramInterval | |||
|
|
1338 | ||||
|
|
1339 | nChannels = data_acf.shape[0] | |||
|
|
1340 | nLags = data_acf.shape[1] | |||
|
|
1341 | nProfiles = data_acf.shape[2] | |||
|
|
1342 | nHeights = self.dataOut.nHeights | |||
|
|
1343 | nCohInt = self.dataOut.nCohInt | |||
|
|
1344 | sec = numpy.round(nProfiles/self.dataOut.paramInterval) | |||
|
|
1345 | heightList = self.dataOut.heightList | |||
|
|
1346 | ippSeconds = self.dataOut.ippSeconds*self.dataOut.nCohInt*self.dataOut.nAvg | |||
|
|
1347 | utctime = self.dataOut.utctime | |||
|
|
1348 | ||||
|
|
1349 | self.dataOut.abscissaList = numpy.arange(0,paramInterval+ippSeconds,ippSeconds) | |||
|
|
1350 | ||||
|
|
1351 | #------------------------ SNR -------------------------------------- | |||
|
|
1352 | power = data_acf[:,0,:,:].real | |||
|
|
1353 | noise = numpy.zeros(nChannels) | |||
|
|
1354 | SNR = numpy.zeros(power.shape) | |||
|
|
1355 | for i in range(nChannels): | |||
|
|
1356 | noise[i] = hildebrand_sekhon(power[i,:], nCohInt) | |||
|
|
1357 | SNR[i] = (power[i]-noise[i])/noise[i] | |||
|
|
1358 | SNRm = numpy.nanmean(SNR, axis = 0) | |||
|
|
1359 | SNRdB = 10*numpy.log10(SNR) | |||
|
|
1360 | ||||
|
|
1361 | if mode == 'SA': | |||
|
|
1362 | nPairs = data_ccf.shape[0] | |||
|
|
1363 | #---------------------- Coherence and Phase -------------------------- | |||
|
|
1364 | phase = numpy.zeros(data_ccf[:,0,:,:].shape) | |||
|
|
1365 | # phase1 = numpy.copy(phase) | |||
|
|
1366 | coh1 = numpy.zeros(data_ccf[:,0,:,:].shape) | |||
|
|
1367 | ||||
|
|
1368 | for p in range(nPairs): | |||
|
|
1369 | ch0 = self.dataOut.groupList[p][0] | |||
|
|
1370 | ch1 = self.dataOut.groupList[p][1] | |||
|
|
1371 | ccf = data_ccf[p,0,:,:]/numpy.sqrt(data_acf[ch0,0,:,:]*data_acf[ch1,0,:,:]) | |||
|
|
1372 | phase[p,:,:] = ndimage.median_filter(numpy.angle(ccf), size = (5,1)) #median filter | |||
|
|
1373 | # phase1[p,:,:] = numpy.angle(ccf) #median filter | |||
|
|
1374 | coh1[p,:,:] = ndimage.median_filter(numpy.abs(ccf), 5) #median filter | |||
|
|
1375 | # coh1[p,:,:] = numpy.abs(ccf) #median filter | |||
|
|
1376 | coh = numpy.nanmax(coh1, axis = 0) | |||
|
|
1377 | # struc = numpy.ones((5,1)) | |||
|
|
1378 | # coh = ndimage.morphology.grey_dilation(coh, size=(10,1)) | |||
|
|
1379 | #---------------------- Radial Velocity ---------------------------- | |||
|
|
1380 | phaseAux = numpy.mean(numpy.angle(data_acf[:,1,:,:]), axis = 0) | |||
|
|
1381 | velRad = phaseAux*lamb/(4*numpy.pi*tSamp) | |||
|
|
1382 | ||||
|
|
1383 | if allData: | |||
|
|
1384 | boolMetFin = ~numpy.isnan(SNRm) | |||
|
|
1385 | # coh[:-1,:] = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |||
|
|
1386 | else: | |||
|
|
1387 | #------------------------ Meteor mask --------------------------------- | |||
|
|
1388 | # #SNR mask | |||
|
|
1389 | # boolMet = (SNRdB>SNRthresh)#|(~numpy.isnan(SNRdB)) | |||
|
|
1390 | # | |||
|
|
1391 | # #Erase small objects | |||
|
|
1392 | # boolMet1 = self.__erase_small(boolMet, 2*sec, 5) | |||
|
|
1393 | # | |||
|
|
1394 | # auxEEJ = numpy.sum(boolMet1,axis=0) | |||
|
|
1395 | # indOver = auxEEJ>nProfiles*0.8 #Use this later | |||
|
|
1396 | # indEEJ = numpy.where(indOver)[0] | |||
|
|
1397 | # indNEEJ = numpy.where(~indOver)[0] | |||
|
|
1398 | # | |||
|
|
1399 | # boolMetFin = boolMet1 | |||
|
|
1400 | # | |||
|
|
1401 | # if indEEJ.size > 0: | |||
|
|
1402 | # boolMet1[:,indEEJ] = False #Erase heights with EEJ | |||
|
|
1403 | # | |||
|
|
1404 | # boolMet2 = coh > cohThresh | |||
|
|
1405 | # boolMet2 = self.__erase_small(boolMet2, 2*sec,5) | |||
|
|
1406 | # | |||
|
|
1407 | # #Final Meteor mask | |||
|
|
1408 | # boolMetFin = boolMet1|boolMet2 | |||
|
|
1409 | ||||
|
|
1410 | #Coherence mask | |||
|
|
1411 | boolMet1 = coh > 0.75 | |||
|
|
1412 | struc = numpy.ones((30,1)) | |||
|
|
1413 | boolMet1 = ndimage.morphology.binary_dilation(boolMet1, structure=struc) | |||
|
|
1414 | ||||
|
|
1415 | #Derivative mask | |||
|
|
1416 | derPhase = numpy.nanmean(numpy.abs(phase[:,1:,:] - phase[:,:-1,:]),axis=0) | |||
|
|
1417 | boolMet2 = derPhase < 0.2 | |||
|
|
1418 | # boolMet2 = ndimage.morphology.binary_opening(boolMet2) | |||
|
|
1419 | # boolMet2 = ndimage.morphology.binary_closing(boolMet2, structure = numpy.ones((10,1))) | |||
|
|
1420 | boolMet2 = ndimage.median_filter(boolMet2,size=5) | |||
|
|
1421 | boolMet2 = numpy.vstack((boolMet2,numpy.full((1,nHeights), True, dtype=bool))) | |||
|
|
1422 | # #Final mask | |||
|
|
1423 | # boolMetFin = boolMet2 | |||
|
|
1424 | boolMetFin = boolMet1&boolMet2 | |||
|
|
1425 | # boolMetFin = ndimage.morphology.binary_dilation(boolMetFin) | |||
|
|
1426 | #Creating data_param | |||
|
|
1427 | coordMet = numpy.where(boolMetFin) | |||
|
|
1428 | ||||
|
|
1429 | tmet = coordMet[0] | |||
|
|
1430 | hmet = coordMet[1] | |||
|
|
1431 | ||||
|
|
1432 | data_param = numpy.zeros((tmet.size, 6 + nPairs)) | |||
|
|
1433 | data_param[:,0] = utctime | |||
|
|
1434 | data_param[:,1] = tmet | |||
|
|
1435 | data_param[:,2] = hmet | |||
|
|
1436 | data_param[:,3] = SNRm[tmet,hmet] | |||
|
|
1437 | data_param[:,4] = velRad[tmet,hmet] | |||
|
|
1438 | data_param[:,5] = coh[tmet,hmet] | |||
|
|
1439 | data_param[:,6:] = phase[:,tmet,hmet].T | |||
|
|
1440 | ||||
|
|
1441 | elif mode == 'DBS': | |||
|
|
1442 | self.dataOut.groupList = numpy.arange(nChannels) | |||
|
|
1443 | ||||
|
|
1444 | #Radial Velocities | |||
|
|
1445 | # phase = numpy.angle(data_acf[:,1,:,:]) | |||
|
|
1446 | phase = ndimage.median_filter(numpy.angle(data_acf[:,1,:,:]), size = (1,5,1)) | |||
|
|
1447 | velRad = phase*lamb/(4*numpy.pi*tSamp) | |||
|
|
1448 | ||||
|
|
1449 | #Spectral width | |||
|
|
1450 | acf1 = ndimage.median_filter(numpy.abs(data_acf[:,1,:,:]), size = (1,5,1)) | |||
|
|
1451 | acf2 = ndimage.median_filter(numpy.abs(data_acf[:,2,:,:]), size = (1,5,1)) | |||
|
|
1452 | ||||
|
|
1453 | spcWidth = (lamb/(2*numpy.sqrt(6)*numpy.pi*tSamp))*numpy.sqrt(numpy.log(acf1/acf2)) | |||
|
|
1454 | # velRad = ndimage.median_filter(velRad, size = (1,5,1)) | |||
|
|
1455 | if allData: | |||
|
|
1456 | boolMetFin = ~numpy.isnan(SNRdB) | |||
|
|
1457 | else: | |||
|
|
1458 | #SNR | |||
|
|
1459 | boolMet1 = (SNRdB>SNRthresh) #SNR mask | |||
|
|
1460 | boolMet1 = ndimage.median_filter(boolMet1, size=(1,5,5)) | |||
|
|
1461 | ||||
|
|
1462 | #Radial velocity | |||
|
|
1463 | boolMet2 = numpy.abs(velRad) < 30 | |||
|
|
1464 | boolMet2 = ndimage.median_filter(boolMet2, (1,5,5)) | |||
|
|
1465 | ||||
|
|
1466 | #Spectral Width | |||
|
|
1467 | boolMet3 = spcWidth < 30 | |||
|
|
1468 | boolMet3 = ndimage.median_filter(boolMet3, (1,5,5)) | |||
|
|
1469 | # boolMetFin = self.__erase_small(boolMet1, 10,5) | |||
|
|
1470 | boolMetFin = boolMet1&boolMet2&boolMet3 | |||
|
|
1471 | ||||
|
|
1472 | #Creating data_param | |||
|
|
1473 | coordMet = numpy.where(boolMetFin) | |||
|
|
1474 | ||||
|
|
1475 | cmet = coordMet[0] | |||
|
|
1476 | tmet = coordMet[1] | |||
|
|
1477 | hmet = coordMet[2] | |||
|
|
1478 | ||||
|
|
1479 | data_param = numpy.zeros((tmet.size, 7)) | |||
|
|
1480 | data_param[:,0] = utctime | |||
|
|
1481 | data_param[:,1] = cmet | |||
|
|
1482 | data_param[:,2] = tmet | |||
|
|
1483 | data_param[:,3] = hmet | |||
|
|
1484 | data_param[:,4] = SNR[cmet,tmet,hmet].T | |||
|
|
1485 | data_param[:,5] = velRad[cmet,tmet,hmet].T | |||
|
|
1486 | data_param[:,6] = spcWidth[cmet,tmet,hmet].T | |||
|
|
1487 | ||||
|
|
1488 | # self.dataOut.data_param = data_int | |||
|
|
1489 | if len(data_param) == 0: | |||
|
|
1490 | self.dataOut.flagNoData = True | |||
|
|
1491 | else: | |||
|
|
1492 | self.dataOut.data_param = data_param | |||
|
|
1493 | ||||
|
|
1494 | def __erase_small(self, binArray, threshX, threshY): | |||
|
|
1495 | labarray, numfeat = ndimage.measurements.label(binArray) | |||
|
|
1496 | binArray1 = numpy.copy(binArray) | |||
|
|
1497 | ||||
|
|
1498 | for i in range(1,numfeat + 1): | |||
|
|
1499 | auxBin = (labarray==i) | |||
|
|
1500 | auxSize = auxBin.sum() | |||
|
|
1501 | ||||
|
|
1502 | x,y = numpy.where(auxBin) | |||
|
|
1503 | widthX = x.max() - x.min() | |||
|
|
1504 | widthY = y.max() - y.min() | |||
|
|
1505 | ||||
|
|
1506 | #width X: 3 seg -> 12.5*3 | |||
|
|
1507 | #width Y: | |||
|
|
1508 | ||||
|
|
1509 | if (auxSize < 50) or (widthX < threshX) or (widthY < threshY): | |||
|
|
1510 | binArray1[auxBin] = False | |||
|
|
1511 | ||||
|
|
1512 | return binArray1 | |||
|
|
1513 | ||||
|
|
1514 | def WeirdEcho(self): | |||
|
|
1515 | # data_pre = self.dataOut.data_pre | |||
|
|
1516 | # nHeights = self.dataOut.nHeights | |||
|
|
1517 | # # nProfiles = self.dataOut.data_pre.shape[1] | |||
|
|
1518 | # # data_param = numpy.zeros((len(pairslist),nProfiles,nHeights)) | |||
|
|
1519 | # data_param = numpy.zeros((len(pairslist),nHeights)) | |||
|
|
1520 | # | |||
|
|
1521 | # for i in range(len(pairslist)): | |||
|
|
1522 | # chan0 = data_pre[pairslist[i][0],:] | |||
|
|
1523 | # chan1 = data_pre[pairslist[i][1],:] | |||
|
|
1524 | # #calcular correlacion cruzada | |||
|
|
1525 | # #magnitud es coherencia | |||
|
|
1526 | # #fase es dif fase | |||
|
|
1527 | # correl = chan0*numpy.conj(chan1) | |||
|
|
1528 | # coherence = numpy.abs(correl)/(numpy.abs(chan0)*numpy.abs(chan1)) | |||
|
|
1529 | # phase = numpy.angle(correl) | |||
|
|
1530 | # # data_param[2*i,:,:] = coherence | |||
|
|
1531 | # data_param[i,:] = phase | |||
|
|
1532 | # | |||
|
|
1533 | # self.dataOut.data_param = data_param | |||
|
|
1534 | # self.dataOut.groupList = pairslist | |||
|
|
1535 | data_cspc = self.dataOut.data_pre[1] | |||
|
|
1536 | ccf = numpy.average(data_cspc,axis=1) | |||
|
|
1537 | phases = numpy.angle(ccf).T | |||
|
|
1538 | ||||
|
|
1539 | meteorOps = MeteorOperations() | |||
|
|
1540 | pairsList = ((0,1),(2,3)) | |||
|
|
1541 | jph = numpy.array([0,0,0,0]) | |||
|
|
1542 | AOAthresh = numpy.pi/8 | |||
|
|
1543 | azimuth = 45 | |||
|
|
1544 | error = numpy.zeros((phases.shape[0],1)) | |||
|
|
1545 | AOA,error = meteorOps.getAOA(phases, pairsList, error, AOAthresh, azimuth) | |||
|
|
1546 | self.dataOut.data_param = AOA.T | |||
| 1328 |
|
1547 | |||
| 1329 | class WindProfiler(Operation): |
|
1548 | class WindProfiler(Operation): | |
| 1330 |
|
1549 | |||
| 1331 | __isConfig = False |
|
1550 | __isConfig = False | |
| 1332 |
|
1551 | |||
| 1333 | __initime = None |
|
1552 | __initime = None | |
| 1334 | __lastdatatime = None |
|
1553 | __lastdatatime = None | |
| 1335 | __integrationtime = None |
|
1554 | __integrationtime = None | |
| 1336 |
|
1555 | |||
| 1337 | __buffer = None |
|
1556 | __buffer = None | |
| 1338 |
|
1557 | |||
| 1339 | __dataReady = False |
|
1558 | __dataReady = False | |
| 1340 |
|
1559 | |||
| 1341 | __firstdata = None |
|
1560 | __firstdata = None | |
| 1342 |
|
1561 | |||
| 1343 | n = None |
|
1562 | n = None | |
| 1344 |
|
1563 | |||
| 1345 | def __init__(self): |
|
1564 | def __init__(self): | |
| 1346 | Operation.__init__(self) |
|
1565 | Operation.__init__(self) | |
| 1347 |
|
1566 | |||
| 1348 | def __calculateCosDir(self, elev, azim): |
|
1567 | def __calculateCosDir(self, elev, azim): | |
| 1349 | zen = (90 - elev)*numpy.pi/180 |
|
1568 | zen = (90 - elev)*numpy.pi/180 | |
| 1350 | azim = azim*numpy.pi/180 |
|
1569 | azim = azim*numpy.pi/180 | |
| 1351 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) |
|
1570 | cosDirX = numpy.sqrt((1-numpy.cos(zen)**2)/((1+numpy.tan(azim)**2))) | |
| 1352 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) |
|
1571 | cosDirY = numpy.sqrt(1-numpy.cos(zen)**2-cosDirX**2) | |
| 1353 |
|
1572 | |||
| 1354 | signX = numpy.sign(numpy.cos(azim)) |
|
1573 | signX = numpy.sign(numpy.cos(azim)) | |
| 1355 | signY = numpy.sign(numpy.sin(azim)) |
|
1574 | signY = numpy.sign(numpy.sin(azim)) | |
| 1356 |
|
1575 | |||
| 1357 | cosDirX = numpy.copysign(cosDirX, signX) |
|
1576 | cosDirX = numpy.copysign(cosDirX, signX) | |
| 1358 | cosDirY = numpy.copysign(cosDirY, signY) |
|
1577 | cosDirY = numpy.copysign(cosDirY, signY) | |
| 1359 | return cosDirX, cosDirY |
|
1578 | return cosDirX, cosDirY | |
| 1360 |
|
1579 | |||
| 1361 | def __calculateAngles(self, theta_x, theta_y, azimuth): |
|
1580 | def __calculateAngles(self, theta_x, theta_y, azimuth): | |
| 1362 |
|
1581 | |||
| 1363 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) |
|
1582 | dir_cosw = numpy.sqrt(1-theta_x**2-theta_y**2) | |
| 1364 | zenith_arr = numpy.arccos(dir_cosw) |
|
1583 | zenith_arr = numpy.arccos(dir_cosw) | |
| 1365 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 |
|
1584 | azimuth_arr = numpy.arctan2(theta_x,theta_y) + azimuth*math.pi/180 | |
| 1366 |
|
1585 | |||
| 1367 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) |
|
1586 | dir_cosu = numpy.sin(azimuth_arr)*numpy.sin(zenith_arr) | |
| 1368 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) |
|
1587 | dir_cosv = numpy.cos(azimuth_arr)*numpy.sin(zenith_arr) | |
| 1369 |
|
1588 | |||
| 1370 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw |
|
1589 | return azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw | |
| 1371 |
|
1590 | |||
| 1372 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): |
|
1591 | def __calculateMatA(self, dir_cosu, dir_cosv, dir_cosw, horOnly): | |
| 1373 |
|
1592 | |||
| 1374 | # |
|
1593 | # | |
| 1375 | if horOnly: |
|
1594 | if horOnly: | |
| 1376 | A = numpy.c_[dir_cosu,dir_cosv] |
|
1595 | A = numpy.c_[dir_cosu,dir_cosv] | |
| 1377 | else: |
|
1596 | else: | |
| 1378 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] |
|
1597 | A = numpy.c_[dir_cosu,dir_cosv,dir_cosw] | |
| 1379 | A = numpy.asmatrix(A) |
|
1598 | A = numpy.asmatrix(A) | |
| 1380 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() |
|
1599 | A1 = numpy.linalg.inv(A.transpose()*A)*A.transpose() | |
| 1381 |
|
1600 | |||
| 1382 | return A1 |
|
1601 | return A1 | |
| 1383 |
|
1602 | |||
| 1384 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
1603 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
| 1385 | listPhi = phi.tolist() |
|
1604 | listPhi = phi.tolist() | |
| 1386 | maxid = listPhi.index(max(listPhi)) |
|
1605 | maxid = listPhi.index(max(listPhi)) | |
| 1387 | minid = listPhi.index(min(listPhi)) |
|
1606 | minid = listPhi.index(min(listPhi)) | |
| 1388 |
|
1607 | |||
| 1389 | rango = range(len(phi)) |
|
1608 | rango = range(len(phi)) | |
| 1390 | # rango = numpy.delete(rango,maxid) |
|
1609 | # rango = numpy.delete(rango,maxid) | |
| 1391 |
|
1610 | |||
| 1392 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
1611 | heiRang1 = heiRang*math.cos(phi[maxid]) | |
| 1393 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
1612 | heiRangAux = heiRang*math.cos(phi[minid]) | |
| 1394 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
1613 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |
| 1395 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
1614 | heiRang1 = numpy.delete(heiRang1,indOut) | |
| 1396 |
|
1615 | |||
| 1397 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1616 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1398 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
1617 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1399 |
|
1618 | |||
| 1400 | for i in rango: |
|
1619 | for i in rango: | |
| 1401 | x = heiRang*math.cos(phi[i]) |
|
1620 | x = heiRang*math.cos(phi[i]) | |
| 1402 | y1 = velRadial[i,:] |
|
1621 | y1 = velRadial[i,:] | |
| 1403 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
1622 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |
| 1404 |
|
1623 | |||
| 1405 | x1 = heiRang1 |
|
1624 | x1 = heiRang1 | |
| 1406 | y11 = f1(x1) |
|
1625 | y11 = f1(x1) | |
| 1407 |
|
1626 | |||
| 1408 | y2 = SNR[i,:] |
|
1627 | y2 = SNR[i,:] | |
| 1409 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
1628 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |
| 1410 | y21 = f2(x1) |
|
1629 | y21 = f2(x1) | |
| 1411 |
|
1630 | |||
| 1412 | velRadial1[i,:] = y11 |
|
1631 | velRadial1[i,:] = y11 | |
| 1413 | SNR1[i,:] = y21 |
|
1632 | SNR1[i,:] = y21 | |
| 1414 |
|
1633 | |||
| 1415 | return heiRang1, velRadial1, SNR1 |
|
1634 | return heiRang1, velRadial1, SNR1 | |
| 1416 |
|
1635 | |||
| 1417 | def __calculateVelUVW(self, A, velRadial): |
|
1636 | def __calculateVelUVW(self, A, velRadial): | |
| 1418 |
|
1637 | |||
| 1419 | #Operacion Matricial |
|
1638 | #Operacion Matricial | |
| 1420 | # velUVW = numpy.zeros((velRadial.shape[1],3)) |
|
1639 | # velUVW = numpy.zeros((velRadial.shape[1],3)) | |
| 1421 | # for ind in range(velRadial.shape[1]): |
|
1640 | # for ind in range(velRadial.shape[1]): | |
| 1422 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) |
|
1641 | # velUVW[ind,:] = numpy.dot(A,velRadial[:,ind]) | |
| 1423 | # velUVW = velUVW.transpose() |
|
1642 | # velUVW = velUVW.transpose() | |
| 1424 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) |
|
1643 | velUVW = numpy.zeros((A.shape[0],velRadial.shape[1])) | |
| 1425 | velUVW[:,:] = numpy.dot(A,velRadial) |
|
1644 | velUVW[:,:] = numpy.dot(A,velRadial) | |
| 1426 |
|
1645 | |||
| 1427 |
|
1646 | |||
| 1428 | return velUVW |
|
1647 | return velUVW | |
| 1429 |
|
1648 | |||
| 1430 | def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): |
|
1649 | def techniqueDBS(self, velRadial0, dirCosx, disrCosy, azimuth, correct, horizontalOnly, heiRang, SNR0): | |
| 1431 | """ |
|
1650 | """ | |
| 1432 | Function that implements Doppler Beam Swinging (DBS) technique. |
|
1651 | Function that implements Doppler Beam Swinging (DBS) technique. | |
| 1433 |
|
1652 | |||
| 1434 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1653 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
| 1435 | Direction correction (if necessary), Ranges and SNR |
|
1654 | Direction correction (if necessary), Ranges and SNR | |
| 1436 |
|
1655 | |||
| 1437 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1656 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 1438 |
|
1657 | |||
| 1439 | Parameters affected: Winds, height range, SNR |
|
1658 | Parameters affected: Winds, height range, SNR | |
| 1440 | """ |
|
1659 | """ | |
| 1441 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(dirCosx, disrCosy, azimuth) |
|
1660 | azimuth_arr, zenith_arr, dir_cosu, dir_cosv, dir_cosw = self.__calculateAngles(dirCosx, disrCosy, azimuth) | |
| 1442 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correct*velRadial0, SNR0) |
|
1661 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, zenith_arr, correct*velRadial0, SNR0) | |
| 1443 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) |
|
1662 | A = self.__calculateMatA(dir_cosu, dir_cosv, dir_cosw, horizontalOnly) | |
| 1444 |
|
1663 | |||
| 1445 | #Calculo de Componentes de la velocidad con DBS |
|
1664 | #Calculo de Componentes de la velocidad con DBS | |
| 1446 | winds = self.__calculateVelUVW(A,velRadial1) |
|
1665 | winds = self.__calculateVelUVW(A,velRadial1) | |
| 1447 |
|
1666 | |||
| 1448 | return winds, heiRang1, SNR1 |
|
1667 | return winds, heiRang1, SNR1 | |
| 1449 |
|
1668 | |||
| 1450 | def __calculateDistance(self, posx, posy, pairsCrossCorr, pairsList, pairs, azimuth = None): |
|
1669 | def __calculateDistance(self, posx, posy, pairsCrossCorr, pairsList, pairs, azimuth = None): | |
| 1451 |
|
1670 | |||
| 1452 | posx = numpy.asarray(posx) |
|
1671 | posx = numpy.asarray(posx) | |
| 1453 | posy = numpy.asarray(posy) |
|
1672 | posy = numpy.asarray(posy) | |
| 1454 |
|
1673 | |||
| 1455 | #Rotacion Inversa para alinear con el azimuth |
|
1674 | #Rotacion Inversa para alinear con el azimuth | |
| 1456 | if azimuth!= None: |
|
1675 | if azimuth!= None: | |
| 1457 | azimuth = azimuth*math.pi/180 |
|
1676 | azimuth = azimuth*math.pi/180 | |
| 1458 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) |
|
1677 | posx1 = posx*math.cos(azimuth) + posy*math.sin(azimuth) | |
| 1459 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) |
|
1678 | posy1 = -posx*math.sin(azimuth) + posy*math.cos(azimuth) | |
| 1460 | else: |
|
1679 | else: | |
| 1461 | posx1 = posx |
|
1680 | posx1 = posx | |
| 1462 | posy1 = posy |
|
1681 | posy1 = posy | |
| 1463 |
|
1682 | |||
| 1464 | #Calculo de Distancias |
|
1683 | #Calculo de Distancias | |
| 1465 | distx = numpy.zeros(pairsCrossCorr.size) |
|
1684 | distx = numpy.zeros(pairsCrossCorr.size) | |
| 1466 | disty = numpy.zeros(pairsCrossCorr.size) |
|
1685 | disty = numpy.zeros(pairsCrossCorr.size) | |
| 1467 | dist = numpy.zeros(pairsCrossCorr.size) |
|
1686 | dist = numpy.zeros(pairsCrossCorr.size) | |
| 1468 | ang = numpy.zeros(pairsCrossCorr.size) |
|
1687 | ang = numpy.zeros(pairsCrossCorr.size) | |
| 1469 |
|
1688 | |||
| 1470 | for i in range(pairsCrossCorr.size): |
|
1689 | for i in range(pairsCrossCorr.size): | |
| 1471 | distx[i] = posx1[pairsList[pairsCrossCorr[i]][1]] - posx1[pairsList[pairsCrossCorr[i]][0]] |
|
1690 | distx[i] = posx1[pairsList[pairsCrossCorr[i]][1]] - posx1[pairsList[pairsCrossCorr[i]][0]] | |
| 1472 | disty[i] = posy1[pairsList[pairsCrossCorr[i]][1]] - posy1[pairsList[pairsCrossCorr[i]][0]] |
|
1691 | disty[i] = posy1[pairsList[pairsCrossCorr[i]][1]] - posy1[pairsList[pairsCrossCorr[i]][0]] | |
| 1473 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) |
|
1692 | dist[i] = numpy.sqrt(distx[i]**2 + disty[i]**2) | |
| 1474 | ang[i] = numpy.arctan2(disty[i],distx[i]) |
|
1693 | ang[i] = numpy.arctan2(disty[i],distx[i]) | |
| 1475 | #Calculo de Matrices |
|
1694 | #Calculo de Matrices | |
| 1476 | nPairs = len(pairs) |
|
1695 | nPairs = len(pairs) | |
| 1477 | ang1 = numpy.zeros((nPairs, 2, 1)) |
|
1696 | ang1 = numpy.zeros((nPairs, 2, 1)) | |
| 1478 | dist1 = numpy.zeros((nPairs, 2, 1)) |
|
1697 | dist1 = numpy.zeros((nPairs, 2, 1)) | |
| 1479 |
|
1698 | |||
| 1480 | for j in range(nPairs): |
|
1699 | for j in range(nPairs): | |
| 1481 | dist1[j,0,0] = dist[pairs[j][0]] |
|
1700 | dist1[j,0,0] = dist[pairs[j][0]] | |
| 1482 | dist1[j,1,0] = dist[pairs[j][1]] |
|
1701 | dist1[j,1,0] = dist[pairs[j][1]] | |
| 1483 | ang1[j,0,0] = ang[pairs[j][0]] |
|
1702 | ang1[j,0,0] = ang[pairs[j][0]] | |
| 1484 | ang1[j,1,0] = ang[pairs[j][1]] |
|
1703 | ang1[j,1,0] = ang[pairs[j][1]] | |
| 1485 |
|
1704 | |||
| 1486 | return distx,disty, dist1,ang1 |
|
1705 | return distx,disty, dist1,ang1 | |
| 1487 |
|
1706 | |||
| 1488 | def __calculateVelVer(self, phase, lagTRange, _lambda): |
|
1707 | def __calculateVelVer(self, phase, lagTRange, _lambda): | |
| 1489 |
|
1708 | |||
| 1490 | Ts = lagTRange[1] - lagTRange[0] |
|
1709 | Ts = lagTRange[1] - lagTRange[0] | |
| 1491 | velW = -_lambda*phase/(4*math.pi*Ts) |
|
1710 | velW = -_lambda*phase/(4*math.pi*Ts) | |
| 1492 |
|
1711 | |||
| 1493 | return velW |
|
1712 | return velW | |
| 1494 |
|
1713 | |||
| 1495 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): |
|
1714 | def __calculateVelHorDir(self, dist, tau1, tau2, ang): | |
| 1496 | nPairs = tau1.shape[0] |
|
1715 | nPairs = tau1.shape[0] | |
| 1497 | vel = numpy.zeros((nPairs,3,tau1.shape[2])) |
|
1716 | vel = numpy.zeros((nPairs,3,tau1.shape[2])) | |
| 1498 |
|
1717 | |||
| 1499 | angCos = numpy.cos(ang) |
|
1718 | angCos = numpy.cos(ang) | |
| 1500 | angSin = numpy.sin(ang) |
|
1719 | angSin = numpy.sin(ang) | |
| 1501 |
|
1720 | |||
| 1502 | vel0 = dist*tau1/(2*tau2**2) |
|
1721 | vel0 = dist*tau1/(2*tau2**2) | |
| 1503 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) |
|
1722 | vel[:,0,:] = (vel0*angCos).sum(axis = 1) | |
| 1504 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) |
|
1723 | vel[:,1,:] = (vel0*angSin).sum(axis = 1) | |
| 1505 |
|
1724 | |||
| 1506 | ind = numpy.where(numpy.isinf(vel)) |
|
1725 | ind = numpy.where(numpy.isinf(vel)) | |
| 1507 | vel[ind] = numpy.nan |
|
1726 | vel[ind] = numpy.nan | |
| 1508 |
|
1727 | |||
| 1509 | return vel |
|
1728 | return vel | |
| 1510 |
|
1729 | |||
| 1511 | def __getPairsAutoCorr(self, pairsList, nChannels): |
|
1730 | def __getPairsAutoCorr(self, pairsList, nChannels): | |
| 1512 |
|
1731 | |||
| 1513 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan |
|
1732 | pairsAutoCorr = numpy.zeros(nChannels, dtype = 'int')*numpy.nan | |
| 1514 |
|
1733 | |||
| 1515 | for l in range(len(pairsList)): |
|
1734 | for l in range(len(pairsList)): | |
| 1516 | firstChannel = pairsList[l][0] |
|
1735 | firstChannel = pairsList[l][0] | |
| 1517 | secondChannel = pairsList[l][1] |
|
1736 | secondChannel = pairsList[l][1] | |
| 1518 |
|
1737 | |||
| 1519 | #Obteniendo pares de Autocorrelacion |
|
1738 | #Obteniendo pares de Autocorrelacion | |
| 1520 | if firstChannel == secondChannel: |
|
1739 | if firstChannel == secondChannel: | |
| 1521 | pairsAutoCorr[firstChannel] = int(l) |
|
1740 | pairsAutoCorr[firstChannel] = int(l) | |
| 1522 |
|
1741 | |||
| 1523 | pairsAutoCorr = pairsAutoCorr.astype(int) |
|
1742 | pairsAutoCorr = pairsAutoCorr.astype(int) | |
| 1524 |
|
1743 | |||
| 1525 | pairsCrossCorr = range(len(pairsList)) |
|
1744 | pairsCrossCorr = range(len(pairsList)) | |
| 1526 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) |
|
1745 | pairsCrossCorr = numpy.delete(pairsCrossCorr,pairsAutoCorr) | |
| 1527 |
|
1746 | |||
| 1528 | return pairsAutoCorr, pairsCrossCorr |
|
1747 | return pairsAutoCorr, pairsCrossCorr | |
| 1529 |
|
1748 | |||
| 1530 | def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): |
|
1749 | def techniqueSA(self, pairsSelected, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, lagTRange, correctFactor): | |
| 1531 | """ |
|
1750 | """ | |
| 1532 | Function that implements Spaced Antenna (SA) technique. |
|
1751 | Function that implements Spaced Antenna (SA) technique. | |
| 1533 |
|
1752 | |||
| 1534 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, |
|
1753 | Input: Radial velocities, Direction cosines (x and y) of the Beam, Antenna azimuth, | |
| 1535 | Direction correction (if necessary), Ranges and SNR |
|
1754 | Direction correction (if necessary), Ranges and SNR | |
| 1536 |
|
1755 | |||
| 1537 | Output: Winds estimation (Zonal, Meridional and Vertical) |
|
1756 | Output: Winds estimation (Zonal, Meridional and Vertical) | |
| 1538 |
|
1757 | |||
| 1539 | Parameters affected: Winds |
|
1758 | Parameters affected: Winds | |
| 1540 | """ |
|
1759 | """ | |
| 1541 | #Cross Correlation pairs obtained |
|
1760 | #Cross Correlation pairs obtained | |
| 1542 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) |
|
1761 | pairsAutoCorr, pairsCrossCorr = self.__getPairsAutoCorr(pairsList, nChannels) | |
| 1543 | pairsArray = numpy.array(pairsList)[pairsCrossCorr] |
|
1762 | pairsArray = numpy.array(pairsList)[pairsCrossCorr] | |
| 1544 | pairsSelArray = numpy.array(pairsSelected) |
|
1763 | pairsSelArray = numpy.array(pairsSelected) | |
| 1545 | pairs = [] |
|
1764 | pairs = [] | |
| 1546 |
|
1765 | |||
| 1547 | #Wind estimation pairs obtained |
|
1766 | #Wind estimation pairs obtained | |
| 1548 | for i in range(pairsSelArray.shape[0]/2): |
|
1767 | for i in range(pairsSelArray.shape[0]/2): | |
| 1549 | ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] |
|
1768 | ind1 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i], axis = 1))[0][0] | |
| 1550 | ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] |
|
1769 | ind2 = numpy.where(numpy.all(pairsArray == pairsSelArray[2*i + 1], axis = 1))[0][0] | |
| 1551 | pairs.append((ind1,ind2)) |
|
1770 | pairs.append((ind1,ind2)) | |
| 1552 |
|
1771 | |||
| 1553 | indtau = tau.shape[0]/2 |
|
1772 | indtau = tau.shape[0]/2 | |
| 1554 | tau1 = tau[:indtau,:] |
|
1773 | tau1 = tau[:indtau,:] | |
| 1555 | tau2 = tau[indtau:-1,:] |
|
1774 | tau2 = tau[indtau:-1,:] | |
| 1556 | tau1 = tau1[pairs,:] |
|
1775 | tau1 = tau1[pairs,:] | |
| 1557 | tau2 = tau2[pairs,:] |
|
1776 | tau2 = tau2[pairs,:] | |
| 1558 | phase1 = tau[-1,:] |
|
1777 | phase1 = tau[-1,:] | |
| 1559 |
|
1778 | |||
| 1560 | #--------------------------------------------------------------------- |
|
1779 | #--------------------------------------------------------------------- | |
| 1561 | #Metodo Directo |
|
1780 | #Metodo Directo | |
| 1562 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairsCrossCorr, pairsList, pairs,azimuth) |
|
1781 | distx, disty, dist, ang = self.__calculateDistance(position_x, position_y, pairsCrossCorr, pairsList, pairs,azimuth) | |
| 1563 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) |
|
1782 | winds = self.__calculateVelHorDir(dist, tau1, tau2, ang) | |
| 1564 | winds = stats.nanmean(winds, axis=0) |
|
1783 | winds = stats.nanmean(winds, axis=0) | |
| 1565 | #--------------------------------------------------------------------- |
|
1784 | #--------------------------------------------------------------------- | |
| 1566 | #Metodo General |
|
1785 | #Metodo General | |
| 1567 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) |
|
1786 | # distx, disty, dist = self.calculateDistance(position_x,position_y,pairsCrossCorr, pairsList, azimuth) | |
| 1568 | # #Calculo Coeficientes de Funcion de Correlacion |
|
1787 | # #Calculo Coeficientes de Funcion de Correlacion | |
| 1569 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) |
|
1788 | # F,G,A,B,H = self.calculateCoef(tau1,tau2,distx,disty,n) | |
| 1570 | # #Calculo de Velocidades |
|
1789 | # #Calculo de Velocidades | |
| 1571 | # winds = self.calculateVelUV(F,G,A,B,H) |
|
1790 | # winds = self.calculateVelUV(F,G,A,B,H) | |
| 1572 |
|
1791 | |||
| 1573 | #--------------------------------------------------------------------- |
|
1792 | #--------------------------------------------------------------------- | |
| 1574 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) |
|
1793 | winds[2,:] = self.__calculateVelVer(phase1, lagTRange, _lambda) | |
| 1575 | winds = correctFactor*winds |
|
1794 | winds = correctFactor*winds | |
| 1576 | return winds |
|
1795 | return winds | |
| 1577 |
|
1796 | |||
| 1578 | def __checkTime(self, currentTime, paramInterval, outputInterval): |
|
1797 | def __checkTime(self, currentTime, paramInterval, outputInterval): | |
| 1579 |
|
1798 | |||
| 1580 | dataTime = currentTime + paramInterval |
|
1799 | dataTime = currentTime + paramInterval | |
| 1581 | deltaTime = dataTime - self.__initime |
|
1800 | deltaTime = dataTime - self.__initime | |
| 1582 |
|
1801 | |||
| 1583 | if deltaTime >= outputInterval or deltaTime < 0: |
|
1802 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 1584 | self.__dataReady = True |
|
1803 | self.__dataReady = True | |
| 1585 | return |
|
1804 | return | |
| 1586 |
|
1805 | |||
| 1587 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): |
|
1806 | def techniqueMeteors(self, arrayMeteor, meteorThresh, heightMin, heightMax): | |
| 1588 | ''' |
|
1807 | ''' | |
| 1589 | Function that implements winds estimation technique with detected meteors. |
|
1808 | Function that implements winds estimation technique with detected meteors. | |
| 1590 |
|
1809 | |||
| 1591 | Input: Detected meteors, Minimum meteor quantity to wind estimation |
|
1810 | Input: Detected meteors, Minimum meteor quantity to wind estimation | |
| 1592 |
|
1811 | |||
| 1593 | Output: Winds estimation (Zonal and Meridional) |
|
1812 | Output: Winds estimation (Zonal and Meridional) | |
| 1594 |
|
1813 | |||
| 1595 | Parameters affected: Winds |
|
1814 | Parameters affected: Winds | |
| 1596 | ''' |
|
1815 | ''' | |
| 1597 | # print arrayMeteor.shape |
|
1816 | # print arrayMeteor.shape | |
| 1598 | #Settings |
|
1817 | #Settings | |
| 1599 | nInt = (heightMax - heightMin)/2 |
|
1818 | nInt = (heightMax - heightMin)/2 | |
| 1600 | # print nInt |
|
1819 | # print nInt | |
| 1601 | nInt = int(nInt) |
|
1820 | nInt = int(nInt) | |
| 1602 | # print nInt |
|
1821 | # print nInt | |
| 1603 | winds = numpy.zeros((2,nInt))*numpy.nan |
|
1822 | winds = numpy.zeros((2,nInt))*numpy.nan | |
| 1604 |
|
1823 | |||
| 1605 | #Filter errors |
|
1824 | #Filter errors | |
| 1606 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] |
|
1825 | error = numpy.where(arrayMeteor[:,-1] == 0)[0] | |
| 1607 | finalMeteor = arrayMeteor[error,:] |
|
1826 | finalMeteor = arrayMeteor[error,:] | |
| 1608 |
|
1827 | |||
| 1609 | #Meteor Histogram |
|
1828 | #Meteor Histogram | |
| 1610 | finalHeights = finalMeteor[:,2] |
|
1829 | finalHeights = finalMeteor[:,2] | |
| 1611 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) |
|
1830 | hist = numpy.histogram(finalHeights, bins = nInt, range = (heightMin,heightMax)) | |
| 1612 | nMeteorsPerI = hist[0] |
|
1831 | nMeteorsPerI = hist[0] | |
| 1613 | heightPerI = hist[1] |
|
1832 | heightPerI = hist[1] | |
| 1614 |
|
1833 | |||
| 1615 | #Sort of meteors |
|
1834 | #Sort of meteors | |
| 1616 | indSort = finalHeights.argsort() |
|
1835 | indSort = finalHeights.argsort() | |
| 1617 | finalMeteor2 = finalMeteor[indSort,:] |
|
1836 | finalMeteor2 = finalMeteor[indSort,:] | |
| 1618 |
|
1837 | |||
| 1619 | # Calculating winds |
|
1838 | # Calculating winds | |
| 1620 | ind1 = 0 |
|
1839 | ind1 = 0 | |
| 1621 | ind2 = 0 |
|
1840 | ind2 = 0 | |
| 1622 |
|
1841 | |||
| 1623 | for i in range(nInt): |
|
1842 | for i in range(nInt): | |
| 1624 | nMet = nMeteorsPerI[i] |
|
1843 | nMet = nMeteorsPerI[i] | |
| 1625 | ind1 = ind2 |
|
1844 | ind1 = ind2 | |
| 1626 | ind2 = ind1 + nMet |
|
1845 | ind2 = ind1 + nMet | |
| 1627 |
|
1846 | |||
| 1628 | meteorAux = finalMeteor2[ind1:ind2,:] |
|
1847 | meteorAux = finalMeteor2[ind1:ind2,:] | |
| 1629 |
|
1848 | |||
| 1630 | if meteorAux.shape[0] >= meteorThresh: |
|
1849 | if meteorAux.shape[0] >= meteorThresh: | |
| 1631 | vel = meteorAux[:, 6] |
|
1850 | vel = meteorAux[:, 6] | |
| 1632 | zen = meteorAux[:, 4]*numpy.pi/180 |
|
1851 | zen = meteorAux[:, 4]*numpy.pi/180 | |
| 1633 | azim = meteorAux[:, 3]*numpy.pi/180 |
|
1852 | azim = meteorAux[:, 3]*numpy.pi/180 | |
| 1634 |
|
1853 | |||
| 1635 | n = numpy.cos(zen) |
|
1854 | n = numpy.cos(zen) | |
| 1636 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) |
|
1855 | # m = (1 - n**2)/(1 - numpy.tan(azim)**2) | |
| 1637 | # l = m*numpy.tan(azim) |
|
1856 | # l = m*numpy.tan(azim) | |
| 1638 | l = numpy.sin(zen)*numpy.sin(azim) |
|
1857 | l = numpy.sin(zen)*numpy.sin(azim) | |
| 1639 | m = numpy.sin(zen)*numpy.cos(azim) |
|
1858 | m = numpy.sin(zen)*numpy.cos(azim) | |
| 1640 |
|
1859 | |||
| 1641 | A = numpy.vstack((l, m)).transpose() |
|
1860 | A = numpy.vstack((l, m)).transpose() | |
| 1642 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) |
|
1861 | A1 = numpy.dot(numpy.linalg.inv( numpy.dot(A.transpose(),A) ),A.transpose()) | |
| 1643 | windsAux = numpy.dot(A1, vel) |
|
1862 | windsAux = numpy.dot(A1, vel) | |
| 1644 |
|
1863 | |||
| 1645 | winds[0,i] = windsAux[0] |
|
1864 | winds[0,i] = windsAux[0] | |
| 1646 | winds[1,i] = windsAux[1] |
|
1865 | winds[1,i] = windsAux[1] | |
| 1647 |
|
1866 | |||
| 1648 | return winds, heightPerI[:-1] |
|
1867 | return winds, heightPerI[:-1] | |
| 1649 |
|
1868 | |||
|
|
1869 | def techniqueNSM_SA(self, **kwargs): | |||
|
|
1870 | metArray = kwargs['metArray'] | |||
|
|
1871 | heightList = kwargs['heightList'] | |||
|
|
1872 | timeList = kwargs['timeList'] | |||
|
|
1873 | ||||
|
|
1874 | rx_location = kwargs['rx_location'] | |||
|
|
1875 | groupList = kwargs['groupList'] | |||
|
|
1876 | azimuth = kwargs['azimuth'] | |||
|
|
1877 | dfactor = kwargs['dfactor'] | |||
|
|
1878 | k = kwargs['k'] | |||
|
|
1879 | ||||
|
|
1880 | azimuth1, dist = self.__calculateAzimuth1(rx_location, groupList, azimuth) | |||
|
|
1881 | d = dist*dfactor | |||
|
|
1882 | #Phase calculation | |||
|
|
1883 | metArray1 = self.__getPhaseSlope(metArray, heightList, timeList) | |||
|
|
1884 | ||||
|
|
1885 | metArray1[:,-2] = metArray1[:,-2]*metArray1[:,2]*1000/(k*d[metArray1[:,1].astype(int)]) #angles into velocities | |||
|
|
1886 | ||||
|
|
1887 | velEst = numpy.zeros((heightList.size,2))*numpy.nan | |||
|
|
1888 | azimuth1 = azimuth1*numpy.pi/180 | |||
|
|
1889 | ||||
|
|
1890 | for i in range(heightList.size): | |||
|
|
1891 | h = heightList[i] | |||
|
|
1892 | indH = numpy.where((metArray1[:,2] == h)&(numpy.abs(metArray1[:,-2]) < 100))[0] | |||
|
|
1893 | metHeight = metArray1[indH,:] | |||
|
|
1894 | if metHeight.shape[0] >= 2: | |||
|
|
1895 | velAux = numpy.asmatrix(metHeight[:,-2]).T #Radial Velocities | |||
|
|
1896 | iazim = metHeight[:,1].astype(int) | |||
|
|
1897 | azimAux = numpy.asmatrix(azimuth1[iazim]).T #Azimuths | |||
|
|
1898 | A = numpy.hstack((numpy.cos(azimAux),numpy.sin(azimAux))) | |||
|
|
1899 | A = numpy.asmatrix(A) | |||
|
|
1900 | A1 = numpy.linalg.pinv(A.transpose()*A)*A.transpose() | |||
|
|
1901 | velHor = numpy.dot(A1,velAux) | |||
|
|
1902 | ||||
|
|
1903 | velEst[i,:] = numpy.squeeze(velHor) | |||
|
|
1904 | return velEst | |||
|
|
1905 | ||||
|
|
1906 | def __getPhaseSlope(self, metArray, heightList, timeList): | |||
|
|
1907 | meteorList = [] | |||
|
|
1908 | #utctime sec1 height SNR velRad ph0 ph1 ph2 coh0 coh1 coh2 | |||
|
|
1909 | #Putting back together the meteor matrix | |||
|
|
1910 | utctime = metArray[:,0] | |||
|
|
1911 | uniqueTime = numpy.unique(utctime) | |||
|
|
1912 | ||||
|
|
1913 | phaseDerThresh = 0.5 | |||
|
|
1914 | ippSeconds = timeList[1] - timeList[0] | |||
|
|
1915 | sec = numpy.where(timeList>1)[0][0] | |||
|
|
1916 | nPairs = metArray.shape[1] - 6 | |||
|
|
1917 | nHeights = len(heightList) | |||
|
|
1918 | ||||
|
|
1919 | for t in uniqueTime: | |||
|
|
1920 | metArray1 = metArray[utctime==t,:] | |||
|
|
1921 | # phaseDerThresh = numpy.pi/4 #reducir Phase thresh | |||
|
|
1922 | tmet = metArray1[:,1].astype(int) | |||
|
|
1923 | hmet = metArray1[:,2].astype(int) | |||
|
|
1924 | ||||
|
|
1925 | metPhase = numpy.zeros((nPairs, heightList.size, timeList.size - 1)) | |||
|
|
1926 | metPhase[:,:] = numpy.nan | |||
|
|
1927 | metPhase[:,hmet,tmet] = metArray1[:,6:].T | |||
|
|
1928 | ||||
|
|
1929 | #Delete short trails | |||
|
|
1930 | metBool = ~numpy.isnan(metPhase[0,:,:]) | |||
|
|
1931 | heightVect = numpy.sum(metBool, axis = 1) | |||
|
|
1932 | metBool[heightVect<sec,:] = False | |||
|
|
1933 | metPhase[:,heightVect<sec,:] = numpy.nan | |||
|
|
1934 | ||||
|
|
1935 | #Derivative | |||
|
|
1936 | metDer = numpy.abs(metPhase[:,:,1:] - metPhase[:,:,:-1]) | |||
|
|
1937 | phDerAux = numpy.dstack((numpy.full((nPairs,nHeights,1), False, dtype=bool),metDer > phaseDerThresh)) | |||
|
|
1938 | metPhase[phDerAux] = numpy.nan | |||
|
|
1939 | ||||
|
|
1940 | #--------------------------METEOR DETECTION ----------------------------------------- | |||
|
|
1941 | indMet = numpy.where(numpy.any(metBool,axis=1))[0] | |||
|
|
1942 | ||||
|
|
1943 | for p in numpy.arange(nPairs): | |||
|
|
1944 | phase = metPhase[p,:,:] | |||
|
|
1945 | phDer = metDer[p,:,:] | |||
|
|
1946 | ||||
|
|
1947 | for h in indMet: | |||
|
|
1948 | height = heightList[h] | |||
|
|
1949 | phase1 = phase[h,:] #82 | |||
|
|
1950 | phDer1 = phDer[h,:] | |||
|
|
1951 | ||||
|
|
1952 | phase1[~numpy.isnan(phase1)] = numpy.unwrap(phase1[~numpy.isnan(phase1)]) #Unwrap | |||
|
|
1953 | ||||
|
|
1954 | indValid = numpy.where(~numpy.isnan(phase1))[0] | |||
|
|
1955 | initMet = indValid[0] | |||
|
|
1956 | endMet = 0 | |||
|
|
1957 | ||||
|
|
1958 | for i in range(len(indValid)-1): | |||
|
|
1959 | ||||
|
|
1960 | #Time difference | |||
|
|
1961 | inow = indValid[i] | |||
|
|
1962 | inext = indValid[i+1] | |||
|
|
1963 | idiff = inext - inow | |||
|
|
1964 | #Phase difference | |||
|
|
1965 | phDiff = numpy.abs(phase1[inext] - phase1[inow]) | |||
|
|
1966 | ||||
|
|
1967 | if idiff>sec or phDiff>numpy.pi/4 or inext==indValid[-1]: #End of Meteor | |||
|
|
1968 | sizeTrail = inow - initMet + 1 | |||
|
|
1969 | if sizeTrail>3*sec: #Too short meteors | |||
|
|
1970 | x = numpy.arange(initMet,inow+1)*ippSeconds | |||
|
|
1971 | y = phase1[initMet:inow+1] | |||
|
|
1972 | ynnan = ~numpy.isnan(y) | |||
|
|
1973 | x = x[ynnan] | |||
|
|
1974 | y = y[ynnan] | |||
|
|
1975 | slope, intercept, r_value, p_value, std_err = stats.linregress(x,y) | |||
|
|
1976 | ylin = x*slope + intercept | |||
|
|
1977 | rsq = r_value**2 | |||
|
|
1978 | if rsq > 0.5: | |||
|
|
1979 | vel = slope#*height*1000/(k*d) | |||
|
|
1980 | estAux = numpy.array([utctime,p,height, vel, rsq]) | |||
|
|
1981 | meteorList.append(estAux) | |||
|
|
1982 | initMet = inext | |||
|
|
1983 | metArray2 = numpy.array(meteorList) | |||
|
|
1984 | ||||
|
|
1985 | return metArray2 | |||
|
|
1986 | ||||
|
|
1987 | def __calculateAzimuth1(self, rx_location, pairslist, azimuth0): | |||
|
|
1988 | ||||
|
|
1989 | azimuth1 = numpy.zeros(len(pairslist)) | |||
|
|
1990 | dist = numpy.zeros(len(pairslist)) | |||
|
|
1991 | ||||
|
|
1992 | for i in range(len(rx_location)): | |||
|
|
1993 | ch0 = pairslist[i][0] | |||
|
|
1994 | ch1 = pairslist[i][1] | |||
|
|
1995 | ||||
|
|
1996 | diffX = rx_location[ch0][0] - rx_location[ch1][0] | |||
|
|
1997 | diffY = rx_location[ch0][1] - rx_location[ch1][1] | |||
|
|
1998 | azimuth1[i] = numpy.arctan2(diffY,diffX)*180/numpy.pi | |||
|
|
1999 | dist[i] = numpy.sqrt(diffX**2 + diffY**2) | |||
|
|
2000 | ||||
|
|
2001 | azimuth1 -= azimuth0 | |||
|
|
2002 | return azimuth1, dist | |||
|
|
2003 | ||||
|
|
2004 | def techniqueNSM_DBS(self, **kwargs): | |||
|
|
2005 | metArray = kwargs['metArray'] | |||
|
|
2006 | heightList = kwargs['heightList'] | |||
|
|
2007 | timeList = kwargs['timeList'] | |||
|
|
2008 | zenithList = kwargs['zenithList'] | |||
|
|
2009 | nChan = numpy.max(cmet) + 1 | |||
|
|
2010 | nHeights = len(heightList) | |||
|
|
2011 | ||||
|
|
2012 | utctime = metArray[:,0] | |||
|
|
2013 | cmet = metArray[:,1] | |||
|
|
2014 | hmet = metArray1[:,3].astype(int) | |||
|
|
2015 | h1met = heightList[hmet]*zenithList[cmet] | |||
|
|
2016 | vmet = metArray1[:,5] | |||
|
|
2017 | ||||
|
|
2018 | for i in range(nHeights - 1): | |||
|
|
2019 | hmin = heightList[i] | |||
|
|
2020 | hmax = heightList[i + 1] | |||
|
|
2021 | ||||
|
|
2022 | vthisH = vmet[(h1met>=hmin) & (h1met<hmax)] | |||
|
|
2023 | ||||
|
|
2024 | ||||
|
|
2025 | ||||
|
|
2026 | return data_output | |||
|
|
2027 | ||||
| 1650 | def run(self, dataOut, technique, **kwargs): |
|
2028 | def run(self, dataOut, technique, **kwargs): | |
| 1651 |
|
2029 | |||
| 1652 | param = dataOut.data_param |
|
2030 | param = dataOut.data_param | |
| 1653 | if dataOut.abscissaList != None: |
|
2031 | if dataOut.abscissaList != None: | |
| 1654 | absc = dataOut.abscissaList[:-1] |
|
2032 | absc = dataOut.abscissaList[:-1] | |
| 1655 | noise = dataOut.noise |
|
2033 | noise = dataOut.noise | |
| 1656 | heightList = dataOut.heightList |
|
2034 | heightList = dataOut.heightList | |
| 1657 | SNR = dataOut.data_SNR |
|
2035 | SNR = dataOut.data_SNR | |
| 1658 |
|
2036 | |||
| 1659 | if technique == 'DBS': |
|
2037 | if technique == 'DBS': | |
| 1660 |
|
2038 | |||
| 1661 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): |
|
2039 | if kwargs.has_key('dirCosx') and kwargs.has_key('dirCosy'): | |
| 1662 | theta_x = numpy.array(kwargs['dirCosx']) |
|
2040 | theta_x = numpy.array(kwargs['dirCosx']) | |
| 1663 | theta_y = numpy.array(kwargs['dirCosy']) |
|
2041 | theta_y = numpy.array(kwargs['dirCosy']) | |
| 1664 | else: |
|
2042 | else: | |
| 1665 | elev = numpy.array(kwargs['elevation']) |
|
2043 | elev = numpy.array(kwargs['elevation']) | |
| 1666 | azim = numpy.array(kwargs['azimuth']) |
|
2044 | azim = numpy.array(kwargs['azimuth']) | |
| 1667 | theta_x, theta_y = self.__calculateCosDir(elev, azim) |
|
2045 | theta_x, theta_y = self.__calculateCosDir(elev, azim) | |
| 1668 | azimuth = kwargs['correctAzimuth'] |
|
2046 | azimuth = kwargs['correctAzimuth'] | |
| 1669 | if kwargs.has_key('horizontalOnly'): |
|
2047 | if kwargs.has_key('horizontalOnly'): | |
| 1670 | horizontalOnly = kwargs['horizontalOnly'] |
|
2048 | horizontalOnly = kwargs['horizontalOnly'] | |
| 1671 | else: horizontalOnly = False |
|
2049 | else: horizontalOnly = False | |
| 1672 | if kwargs.has_key('correctFactor'): |
|
2050 | if kwargs.has_key('correctFactor'): | |
| 1673 | correctFactor = kwargs['correctFactor'] |
|
2051 | correctFactor = kwargs['correctFactor'] | |
| 1674 | else: correctFactor = 1 |
|
2052 | else: correctFactor = 1 | |
| 1675 | if kwargs.has_key('channelList'): |
|
2053 | if kwargs.has_key('channelList'): | |
| 1676 | channelList = kwargs['channelList'] |
|
2054 | channelList = kwargs['channelList'] | |
| 1677 | if len(channelList) == 2: |
|
2055 | if len(channelList) == 2: | |
| 1678 | horizontalOnly = True |
|
2056 | horizontalOnly = True | |
| 1679 | arrayChannel = numpy.array(channelList) |
|
2057 | arrayChannel = numpy.array(channelList) | |
| 1680 | param = param[arrayChannel,:,:] |
|
2058 | param = param[arrayChannel,:,:] | |
| 1681 | theta_x = theta_x[arrayChannel] |
|
2059 | theta_x = theta_x[arrayChannel] | |
| 1682 | theta_y = theta_y[arrayChannel] |
|
2060 | theta_y = theta_y[arrayChannel] | |
| 1683 |
|
2061 | |||
| 1684 | velRadial0 = param[:,1,:] #Radial velocity |
|
2062 | velRadial0 = param[:,1,:] #Radial velocity | |
| 1685 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(velRadial0, theta_x, theta_y, azimuth, correctFactor, horizontalOnly, heightList, SNR) #DBS Function |
|
2063 | dataOut.data_output, dataOut.heightList, dataOut.data_SNR = self.techniqueDBS(velRadial0, theta_x, theta_y, azimuth, correctFactor, horizontalOnly, heightList, SNR) #DBS Function | |
| 1686 | dataOut.utctimeInit = dataOut.utctime |
|
2064 | dataOut.utctimeInit = dataOut.utctime | |
| 1687 |
dataOut.outputInterval = dataOut. |
|
2065 | dataOut.outputInterval = dataOut.paramInterval | |
| 1688 |
|
2066 | |||
| 1689 | elif technique == 'SA': |
|
2067 | elif technique == 'SA': | |
| 1690 |
|
2068 | |||
| 1691 | #Parameters |
|
2069 | #Parameters | |
| 1692 | position_x = kwargs['positionX'] |
|
2070 | position_x = kwargs['positionX'] | |
| 1693 | position_y = kwargs['positionY'] |
|
2071 | position_y = kwargs['positionY'] | |
| 1694 | azimuth = kwargs['azimuth'] |
|
2072 | azimuth = kwargs['azimuth'] | |
| 1695 |
|
2073 | |||
| 1696 | if kwargs.has_key('crosspairsList'): |
|
2074 | if kwargs.has_key('crosspairsList'): | |
| 1697 | pairs = kwargs['crosspairsList'] |
|
2075 | pairs = kwargs['crosspairsList'] | |
| 1698 | else: |
|
2076 | else: | |
| 1699 | pairs = None |
|
2077 | pairs = None | |
| 1700 |
|
2078 | |||
| 1701 | if kwargs.has_key('correctFactor'): |
|
2079 | if kwargs.has_key('correctFactor'): | |
| 1702 | correctFactor = kwargs['correctFactor'] |
|
2080 | correctFactor = kwargs['correctFactor'] | |
| 1703 | else: |
|
2081 | else: | |
| 1704 | correctFactor = 1 |
|
2082 | correctFactor = 1 | |
| 1705 |
|
2083 | |||
| 1706 | tau = dataOut.data_param |
|
2084 | tau = dataOut.data_param | |
| 1707 | _lambda = dataOut.C/dataOut.frequency |
|
2085 | _lambda = dataOut.C/dataOut.frequency | |
| 1708 | pairsList = dataOut.groupList |
|
2086 | pairsList = dataOut.groupList | |
| 1709 | nChannels = dataOut.nChannels |
|
2087 | nChannels = dataOut.nChannels | |
| 1710 |
|
2088 | |||
| 1711 | dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) |
|
2089 | dataOut.data_output = self.techniqueSA(pairs, pairsList, nChannels, tau, azimuth, _lambda, position_x, position_y, absc, correctFactor) | |
| 1712 | dataOut.utctimeInit = dataOut.utctime |
|
2090 | dataOut.utctimeInit = dataOut.utctime | |
| 1713 | dataOut.outputInterval = dataOut.timeInterval |
|
2091 | dataOut.outputInterval = dataOut.timeInterval | |
| 1714 |
|
2092 | |||
| 1715 | elif technique == 'Meteors': |
|
2093 | elif technique == 'Meteors': | |
| 1716 | dataOut.flagNoData = True |
|
2094 | dataOut.flagNoData = True | |
| 1717 | self.__dataReady = False |
|
2095 | self.__dataReady = False | |
| 1718 |
|
2096 | |||
| 1719 | if kwargs.has_key('nHours'): |
|
2097 | if kwargs.has_key('nHours'): | |
| 1720 | nHours = kwargs['nHours'] |
|
2098 | nHours = kwargs['nHours'] | |
| 1721 | else: |
|
2099 | else: | |
| 1722 | nHours = 1 |
|
2100 | nHours = 1 | |
| 1723 |
|
2101 | |||
| 1724 | if kwargs.has_key('meteorsPerBin'): |
|
2102 | if kwargs.has_key('meteorsPerBin'): | |
| 1725 | meteorThresh = kwargs['meteorsPerBin'] |
|
2103 | meteorThresh = kwargs['meteorsPerBin'] | |
| 1726 | else: |
|
2104 | else: | |
| 1727 | meteorThresh = 6 |
|
2105 | meteorThresh = 6 | |
| 1728 |
|
2106 | |||
| 1729 | if kwargs.has_key('hmin'): |
|
2107 | if kwargs.has_key('hmin'): | |
| 1730 | hmin = kwargs['hmin'] |
|
2108 | hmin = kwargs['hmin'] | |
| 1731 | else: hmin = 70 |
|
2109 | else: hmin = 70 | |
| 1732 | if kwargs.has_key('hmax'): |
|
2110 | if kwargs.has_key('hmax'): | |
| 1733 | hmax = kwargs['hmax'] |
|
2111 | hmax = kwargs['hmax'] | |
| 1734 | else: hmax = 110 |
|
2112 | else: hmax = 110 | |
| 1735 |
|
2113 | |||
| 1736 | dataOut.outputInterval = nHours*3600 |
|
2114 | dataOut.outputInterval = nHours*3600 | |
| 1737 |
|
2115 | |||
| 1738 | if self.__isConfig == False: |
|
2116 | if self.__isConfig == False: | |
| 1739 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2117 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 1740 | #Get Initial LTC time |
|
2118 | #Get Initial LTC time | |
| 1741 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2119 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 1742 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2120 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 1743 |
|
2121 | |||
| 1744 | self.__isConfig = True |
|
2122 | self.__isConfig = True | |
| 1745 |
|
2123 | |||
| 1746 | if self.__buffer == None: |
|
2124 | if self.__buffer == None: | |
| 1747 | self.__buffer = dataOut.data_param |
|
2125 | self.__buffer = dataOut.data_param | |
| 1748 | self.__firstdata = copy.copy(dataOut) |
|
2126 | self.__firstdata = copy.copy(dataOut) | |
| 1749 |
|
2127 | |||
| 1750 | else: |
|
2128 | else: | |
| 1751 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2129 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 1752 |
|
2130 | |||
| 1753 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2131 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 1754 |
|
2132 | |||
| 1755 | if self.__dataReady: |
|
2133 | if self.__dataReady: | |
| 1756 | dataOut.utctimeInit = self.__initime |
|
2134 | dataOut.utctimeInit = self.__initime | |
| 1757 |
|
2135 | |||
| 1758 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2136 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 1759 |
|
2137 | |||
| 1760 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) |
|
2138 | dataOut.data_output, dataOut.heightList = self.techniqueMeteors(self.__buffer, meteorThresh, hmin, hmax) | |
| 1761 | dataOut.flagNoData = False |
|
2139 | dataOut.flagNoData = False | |
| 1762 | self.__buffer = None |
|
2140 | self.__buffer = None | |
|
|
2141 | ||||
|
|
2142 | elif technique == 'Meteors1': | |||
|
|
2143 | dataOut.flagNoData = True | |||
|
|
2144 | self.__dataReady = False | |||
|
|
2145 | ||||
|
|
2146 | if kwargs.has_key('nMins'): | |||
|
|
2147 | nMins = kwargs['nMins'] | |||
|
|
2148 | else: nMins = 20 | |||
|
|
2149 | if kwargs.has_key('rx_location'): | |||
|
|
2150 | rx_location = kwargs['rx_location'] | |||
|
|
2151 | else: rx_location = [(0,1),(1,1),(1,0)] | |||
|
|
2152 | if kwargs.has_key('azimuth'): | |||
|
|
2153 | azimuth = kwargs['azimuth'] | |||
|
|
2154 | else: azimuth = 51 | |||
|
|
2155 | if kwargs.has_key('dfactor'): | |||
|
|
2156 | dfactor = kwargs['dfactor'] | |||
|
|
2157 | if kwargs.has_key('mode'): | |||
|
|
2158 | mode = kwargs['mode'] | |||
|
|
2159 | else: mode = 'SA' | |||
|
|
2160 | ||||
|
|
2161 | #Borrar luego esto | |||
|
|
2162 | if dataOut.groupList == None: | |||
|
|
2163 | dataOut.groupList = [(0,1),(0,2),(1,2)] | |||
|
|
2164 | groupList = dataOut.groupList | |||
|
|
2165 | C = 3e8 | |||
|
|
2166 | freq = 50e6 | |||
|
|
2167 | lamb = C/freq | |||
|
|
2168 | k = 2*numpy.pi/lamb | |||
|
|
2169 | ||||
|
|
2170 | timeList = dataOut.abscissaList | |||
|
|
2171 | heightList = dataOut.heightList | |||
|
|
2172 | ||||
|
|
2173 | if self.__isConfig == False: | |||
|
|
2174 | dataOut.outputInterval = nMins*60 | |||
|
|
2175 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |||
|
|
2176 | #Get Initial LTC time | |||
|
|
2177 | initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |||
|
|
2178 | minuteAux = initime.minute | |||
|
|
2179 | minuteNew = int(numpy.floor(minuteAux/nMins)*nMins) | |||
|
|
2180 | self.__initime = (initime.replace(minute = minuteNew, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |||
|
|
2181 | ||||
|
|
2182 | self.__isConfig = True | |||
|
|
2183 | ||||
|
|
2184 | if self.__buffer == None: | |||
|
|
2185 | self.__buffer = dataOut.data_param | |||
|
|
2186 | self.__firstdata = copy.copy(dataOut) | |||
|
|
2187 | ||||
|
|
2188 | else: | |||
|
|
2189 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |||
|
|
2190 | ||||
|
|
2191 | self.__checkTime(dataOut.utctime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |||
|
|
2192 | ||||
|
|
2193 | if self.__dataReady: | |||
|
|
2194 | dataOut.utctimeInit = self.__initime | |||
|
|
2195 | self.__initime += dataOut.outputInterval #to erase time offset | |||
|
|
2196 | ||||
|
|
2197 | metArray = self.__buffer | |||
|
|
2198 | if mode == 'SA': | |||
|
|
2199 | dataOut.data_output = self.techniqueNSM_SA(rx_location=rx_location, groupList=groupList, azimuth=azimuth, dfactor=dfactor, k=k,metArray=metArray, heightList=heightList,timeList=timeList) | |||
|
|
2200 | elif mode == 'DBS': | |||
|
|
2201 | dataOut.data_output = self.techniqueNSM_DBS(metArray=metArray,heightList=heightList,timeList=timeList) | |||
|
|
2202 | dataOut.data_output = dataOut.data_output.T | |||
|
|
2203 | dataOut.flagNoData = False | |||
|
|
2204 | self.__buffer = None | |||
| 1763 |
|
2205 | |||
| 1764 | return |
|
2206 | return | |
| 1765 |
|
2207 | |||
| 1766 | class EWDriftsEstimation(Operation): |
|
2208 | class EWDriftsEstimation(Operation): | |
| 1767 |
|
2209 | |||
| 1768 |
|
||||
| 1769 | def __init__(self): |
|
2210 | def __init__(self): | |
| 1770 | Operation.__init__(self) |
|
2211 | Operation.__init__(self) | |
| 1771 |
|
2212 | |||
| 1772 | def __correctValues(self, heiRang, phi, velRadial, SNR): |
|
2213 | def __correctValues(self, heiRang, phi, velRadial, SNR): | |
| 1773 | listPhi = phi.tolist() |
|
2214 | listPhi = phi.tolist() | |
| 1774 | maxid = listPhi.index(max(listPhi)) |
|
2215 | maxid = listPhi.index(max(listPhi)) | |
| 1775 | minid = listPhi.index(min(listPhi)) |
|
2216 | minid = listPhi.index(min(listPhi)) | |
| 1776 |
|
2217 | |||
| 1777 | rango = range(len(phi)) |
|
2218 | rango = range(len(phi)) | |
| 1778 | # rango = numpy.delete(rango,maxid) |
|
2219 | # rango = numpy.delete(rango,maxid) | |
| 1779 |
|
2220 | |||
| 1780 | heiRang1 = heiRang*math.cos(phi[maxid]) |
|
2221 | heiRang1 = heiRang*math.cos(phi[maxid]) | |
| 1781 | heiRangAux = heiRang*math.cos(phi[minid]) |
|
2222 | heiRangAux = heiRang*math.cos(phi[minid]) | |
| 1782 | indOut = (heiRang1 < heiRangAux[0]).nonzero() |
|
2223 | indOut = (heiRang1 < heiRangAux[0]).nonzero() | |
| 1783 | heiRang1 = numpy.delete(heiRang1,indOut) |
|
2224 | heiRang1 = numpy.delete(heiRang1,indOut) | |
| 1784 |
|
2225 | |||
| 1785 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
2226 | velRadial1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1786 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) |
|
2227 | SNR1 = numpy.zeros([len(phi),len(heiRang1)]) | |
| 1787 |
|
2228 | |||
| 1788 | for i in rango: |
|
2229 | for i in rango: | |
| 1789 | x = heiRang*math.cos(phi[i]) |
|
2230 | x = heiRang*math.cos(phi[i]) | |
| 1790 | y1 = velRadial[i,:] |
|
2231 | y1 = velRadial[i,:] | |
| 1791 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') |
|
2232 | f1 = interpolate.interp1d(x,y1,kind = 'cubic') | |
| 1792 |
|
2233 | |||
| 1793 | x1 = heiRang1 |
|
2234 | x1 = heiRang1 | |
| 1794 | y11 = f1(x1) |
|
2235 | y11 = f1(x1) | |
| 1795 |
|
2236 | |||
| 1796 | y2 = SNR[i,:] |
|
2237 | y2 = SNR[i,:] | |
| 1797 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') |
|
2238 | f2 = interpolate.interp1d(x,y2,kind = 'cubic') | |
| 1798 | y21 = f2(x1) |
|
2239 | y21 = f2(x1) | |
| 1799 |
|
2240 | |||
| 1800 | velRadial1[i,:] = y11 |
|
2241 | velRadial1[i,:] = y11 | |
| 1801 | SNR1[i,:] = y21 |
|
2242 | SNR1[i,:] = y21 | |
| 1802 |
|
2243 | |||
| 1803 | return heiRang1, velRadial1, SNR1 |
|
2244 | return heiRang1, velRadial1, SNR1 | |
| 1804 |
|
2245 | |||
| 1805 | def run(self, dataOut, zenith, zenithCorrection): |
|
2246 | def run(self, dataOut, zenith, zenithCorrection): | |
| 1806 | heiRang = dataOut.heightList |
|
2247 | heiRang = dataOut.heightList | |
| 1807 | velRadial = dataOut.data_param[:,3,:] |
|
2248 | velRadial = dataOut.data_param[:,3,:] | |
| 1808 | SNR = dataOut.data_SNR |
|
2249 | SNR = dataOut.data_SNR | |
| 1809 |
|
2250 | |||
| 1810 | zenith = numpy.array(zenith) |
|
2251 | zenith = numpy.array(zenith) | |
| 1811 | zenith -= zenithCorrection |
|
2252 | zenith -= zenithCorrection | |
| 1812 | zenith *= numpy.pi/180 |
|
2253 | zenith *= numpy.pi/180 | |
| 1813 |
|
2254 | |||
| 1814 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) |
|
2255 | heiRang1, velRadial1, SNR1 = self.__correctValues(heiRang, numpy.abs(zenith), velRadial, SNR) | |
| 1815 |
|
2256 | |||
| 1816 | alp = zenith[0] |
|
2257 | alp = zenith[0] | |
| 1817 | bet = zenith[1] |
|
2258 | bet = zenith[1] | |
| 1818 |
|
2259 | |||
| 1819 | w_w = velRadial1[0,:] |
|
2260 | w_w = velRadial1[0,:] | |
| 1820 | w_e = velRadial1[1,:] |
|
2261 | w_e = velRadial1[1,:] | |
| 1821 |
|
2262 | |||
| 1822 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) |
|
2263 | w = (w_w*numpy.sin(bet) - w_e*numpy.sin(alp))/(numpy.cos(alp)*numpy.sin(bet) - numpy.cos(bet)*numpy.sin(alp)) | |
| 1823 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) |
|
2264 | u = (w_w*numpy.cos(bet) - w_e*numpy.cos(alp))/(numpy.sin(alp)*numpy.cos(bet) - numpy.sin(bet)*numpy.cos(alp)) | |
| 1824 |
|
2265 | |||
| 1825 | winds = numpy.vstack((u,w)) |
|
2266 | winds = numpy.vstack((u,w)) | |
| 1826 |
|
2267 | |||
| 1827 | dataOut.heightList = heiRang1 |
|
2268 | dataOut.heightList = heiRang1 | |
| 1828 | dataOut.data_output = winds |
|
2269 | dataOut.data_output = winds | |
| 1829 | dataOut.data_SNR = SNR1 |
|
2270 | dataOut.data_SNR = SNR1 | |
| 1830 |
|
2271 | |||
| 1831 | dataOut.utctimeInit = dataOut.utctime |
|
2272 | dataOut.utctimeInit = dataOut.utctime | |
| 1832 | dataOut.outputInterval = dataOut.timeInterval |
|
2273 | dataOut.outputInterval = dataOut.timeInterval | |
| 1833 | return |
|
2274 | return | |
| 1834 |
|
2275 | |||
| 1835 | class PhaseCalibration(Operation): |
|
2276 | class PhaseCalibration(Operation): | |
| 1836 |
|
2277 | |||
| 1837 | __buffer = None |
|
2278 | __buffer = None | |
| 1838 |
|
2279 | |||
| 1839 | __initime = None |
|
2280 | __initime = None | |
| 1840 |
|
2281 | |||
| 1841 | __dataReady = False |
|
2282 | __dataReady = False | |
| 1842 |
|
2283 | |||
| 1843 | __isConfig = False |
|
2284 | __isConfig = False | |
| 1844 |
|
2285 | |||
| 1845 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): |
|
2286 | def __checkTime(self, currentTime, initTime, paramInterval, outputInterval): | |
| 1846 |
|
2287 | |||
| 1847 | dataTime = currentTime + paramInterval |
|
2288 | dataTime = currentTime + paramInterval | |
| 1848 | deltaTime = dataTime - initTime |
|
2289 | deltaTime = dataTime - initTime | |
| 1849 |
|
2290 | |||
| 1850 | if deltaTime >= outputInterval or deltaTime < 0: |
|
2291 | if deltaTime >= outputInterval or deltaTime < 0: | |
| 1851 | return True |
|
2292 | return True | |
| 1852 |
|
2293 | |||
| 1853 | return False |
|
2294 | return False | |
| 1854 |
|
2295 | |||
| 1855 | def __getGammas(self, pairs, k, d, phases): |
|
2296 | def __getGammas(self, pairs, k, d, phases): | |
| 1856 | gammas = numpy.zeros(2) |
|
2297 | gammas = numpy.zeros(2) | |
| 1857 |
|
2298 | |||
| 1858 | for i in range(len(pairs)): |
|
2299 | for i in range(len(pairs)): | |
| 1859 |
|
2300 | |||
| 1860 | pairi = pairs[i] |
|
2301 | pairi = pairs[i] | |
| 1861 |
|
2302 | |||
| 1862 | #Calculating gamma |
|
2303 | #Calculating gamma | |
| 1863 | jdcos = phases[:,pairi[1]]/(k*d[pairi[1]]) |
|
2304 | jdcos = phases[:,pairi[1]]/(k*d[pairi[1]]) | |
| 1864 | jgamma = numpy.angle(numpy.exp(1j*(k*d[pairi[0]]*jdcos - phases[:,pairi[0]]))) |
|
2305 | jgamma = numpy.angle(numpy.exp(1j*(k*d[pairi[0]]*jdcos - phases[:,pairi[0]]))) | |
| 1865 |
|
2306 | |||
| 1866 | #Revised distribution |
|
2307 | #Revised distribution | |
| 1867 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) |
|
2308 | jgammaArray = numpy.hstack((jgamma,jgamma+0.5*numpy.pi,jgamma-0.5*numpy.pi)) | |
| 1868 |
|
2309 | |||
| 1869 | #Histogram |
|
2310 | #Histogram | |
| 1870 | nBins = 64.0 |
|
2311 | nBins = 64.0 | |
| 1871 | rmin = -0.5*numpy.pi |
|
2312 | rmin = -0.5*numpy.pi | |
| 1872 | rmax = 0.5*numpy.pi |
|
2313 | rmax = 0.5*numpy.pi | |
| 1873 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) |
|
2314 | phaseHisto = numpy.histogram(jgammaArray, bins=nBins, range=(rmin,rmax)) | |
| 1874 |
|
2315 | |||
| 1875 | meteorsY = phaseHisto[0] |
|
2316 | meteorsY = phaseHisto[0] | |
| 1876 | phasesX = phaseHisto[1][:-1] |
|
2317 | phasesX = phaseHisto[1][:-1] | |
| 1877 | width = phasesX[1] - phasesX[0] |
|
2318 | width = phasesX[1] - phasesX[0] | |
| 1878 | phasesX += width/2 |
|
2319 | phasesX += width/2 | |
| 1879 |
|
2320 | |||
| 1880 | #Gaussian aproximation |
|
2321 | #Gaussian aproximation | |
| 1881 | bpeak = meteorsY.argmax() |
|
2322 | bpeak = meteorsY.argmax() | |
| 1882 | peak = meteorsY.max() |
|
2323 | peak = meteorsY.max() | |
| 1883 | jmin = bpeak - 5 |
|
2324 | jmin = bpeak - 5 | |
| 1884 | jmax = bpeak + 5 + 1 |
|
2325 | jmax = bpeak + 5 + 1 | |
| 1885 |
|
2326 | |||
| 1886 | if jmin<0: |
|
2327 | if jmin<0: | |
| 1887 | jmin = 0 |
|
2328 | jmin = 0 | |
| 1888 | jmax = 6 |
|
2329 | jmax = 6 | |
| 1889 | elif jmax > meteorsY.size: |
|
2330 | elif jmax > meteorsY.size: | |
| 1890 | jmin = meteorsY.size - 6 |
|
2331 | jmin = meteorsY.size - 6 | |
| 1891 | jmax = meteorsY.size |
|
2332 | jmax = meteorsY.size | |
| 1892 |
|
2333 | |||
| 1893 | x0 = numpy.array([peak,bpeak,50]) |
|
2334 | x0 = numpy.array([peak,bpeak,50]) | |
| 1894 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) |
|
2335 | coeff = optimize.leastsq(self.__residualFunction, x0, args=(meteorsY[jmin:jmax], phasesX[jmin:jmax])) | |
| 1895 |
|
2336 | |||
| 1896 | #Gammas |
|
2337 | #Gammas | |
| 1897 | gammas[i] = coeff[0][1] |
|
2338 | gammas[i] = coeff[0][1] | |
| 1898 |
|
2339 | |||
| 1899 | return gammas |
|
2340 | return gammas | |
| 1900 |
|
2341 | |||
| 1901 | def __residualFunction(self, coeffs, y, t): |
|
2342 | def __residualFunction(self, coeffs, y, t): | |
| 1902 |
|
2343 | |||
| 1903 | return y - self.__gauss_function(t, coeffs) |
|
2344 | return y - self.__gauss_function(t, coeffs) | |
| 1904 |
|
2345 | |||
| 1905 | def __gauss_function(self, t, coeffs): |
|
2346 | def __gauss_function(self, t, coeffs): | |
| 1906 |
|
2347 | |||
| 1907 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) |
|
2348 | return coeffs[0]*numpy.exp(-0.5*((t - coeffs[1]) / coeffs[2])**2) | |
| 1908 |
|
2349 | |||
| 1909 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): |
|
2350 | def __getPhases(self, azimuth, h, pairsList, d, gammas, meteorsArray): | |
| 1910 | meteorOps = MeteorOperations() |
|
2351 | meteorOps = MeteorOperations() | |
| 1911 | nchan = 4 |
|
2352 | nchan = 4 | |
| 1912 | pairx = pairsList[0] |
|
2353 | pairx = pairsList[0] | |
| 1913 | pairy = pairsList[1] |
|
2354 | pairy = pairsList[1] | |
| 1914 | center_xangle = 0 |
|
2355 | center_xangle = 0 | |
| 1915 | center_yangle = 0 |
|
2356 | center_yangle = 0 | |
| 1916 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) |
|
2357 | range_angle = numpy.array([10*numpy.pi,numpy.pi,numpy.pi/2,numpy.pi/4]) | |
| 1917 | ntimes = len(range_angle) |
|
2358 | ntimes = len(range_angle) | |
| 1918 |
|
2359 | |||
| 1919 | nstepsx = 20.0 |
|
2360 | nstepsx = 20.0 | |
| 1920 | nstepsy = 20.0 |
|
2361 | nstepsy = 20.0 | |
| 1921 |
|
2362 | |||
| 1922 | for iz in range(ntimes): |
|
2363 | for iz in range(ntimes): | |
| 1923 | min_xangle = -range_angle[iz]/2 + center_xangle |
|
2364 | min_xangle = -range_angle[iz]/2 + center_xangle | |
| 1924 | max_xangle = range_angle[iz]/2 + center_xangle |
|
2365 | max_xangle = range_angle[iz]/2 + center_xangle | |
| 1925 | min_yangle = -range_angle[iz]/2 + center_yangle |
|
2366 | min_yangle = -range_angle[iz]/2 + center_yangle | |
| 1926 | max_yangle = range_angle[iz]/2 + center_yangle |
|
2367 | max_yangle = range_angle[iz]/2 + center_yangle | |
| 1927 |
|
2368 | |||
| 1928 | inc_x = (max_xangle-min_xangle)/nstepsx |
|
2369 | inc_x = (max_xangle-min_xangle)/nstepsx | |
| 1929 | inc_y = (max_yangle-min_yangle)/nstepsy |
|
2370 | inc_y = (max_yangle-min_yangle)/nstepsy | |
| 1930 |
|
2371 | |||
| 1931 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle |
|
2372 | alpha_y = numpy.arange(nstepsy)*inc_y + min_yangle | |
| 1932 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle |
|
2373 | alpha_x = numpy.arange(nstepsx)*inc_x + min_xangle | |
| 1933 | penalty = numpy.zeros((nstepsx,nstepsy)) |
|
2374 | penalty = numpy.zeros((nstepsx,nstepsy)) | |
| 1934 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) |
|
2375 | jph_array = numpy.zeros((nchan,nstepsx,nstepsy)) | |
| 1935 | jph = numpy.zeros(nchan) |
|
2376 | jph = numpy.zeros(nchan) | |
| 1936 |
|
2377 | |||
| 1937 | # Iterations looking for the offset |
|
2378 | # Iterations looking for the offset | |
| 1938 | for iy in range(int(nstepsy)): |
|
2379 | for iy in range(int(nstepsy)): | |
| 1939 | for ix in range(int(nstepsx)): |
|
2380 | for ix in range(int(nstepsx)): | |
| 1940 | jph[pairy[1]] = alpha_y[iy] |
|
2381 | jph[pairy[1]] = alpha_y[iy] | |
| 1941 | jph[pairy[0]] = -gammas[1] + alpha_y[iy]*d[pairy[0]]/d[pairy[1]] |
|
2382 | jph[pairy[0]] = -gammas[1] + alpha_y[iy]*d[pairy[0]]/d[pairy[1]] | |
| 1942 |
|
2383 | |||
| 1943 | jph[pairx[1]] = alpha_x[ix] |
|
2384 | jph[pairx[1]] = alpha_x[ix] | |
| 1944 | jph[pairx[0]] = -gammas[0] + alpha_x[ix]*d[pairx[0]]/d[pairx[1]] |
|
2385 | jph[pairx[0]] = -gammas[0] + alpha_x[ix]*d[pairx[0]]/d[pairx[1]] | |
| 1945 |
|
2386 | |||
| 1946 | jph_array[:,ix,iy] = jph |
|
2387 | jph_array[:,ix,iy] = jph | |
| 1947 |
|
2388 | |||
| 1948 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, jph) |
|
2389 | meteorsArray1 = meteorOps.getMeteorParams(meteorsArray, azimuth, h, pairsList, jph) | |
| 1949 | error = meteorsArray1[:,-1] |
|
2390 | error = meteorsArray1[:,-1] | |
| 1950 | ind1 = numpy.where(error==0)[0] |
|
2391 | ind1 = numpy.where(error==0)[0] | |
| 1951 | penalty[ix,iy] = ind1.size |
|
2392 | penalty[ix,iy] = ind1.size | |
| 1952 |
|
2393 | |||
| 1953 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) |
|
2394 | i,j = numpy.unravel_index(penalty.argmax(), penalty.shape) | |
| 1954 | phOffset = jph_array[:,i,j] |
|
2395 | phOffset = jph_array[:,i,j] | |
| 1955 |
|
2396 | |||
| 1956 | center_xangle = phOffset[pairx[1]] |
|
2397 | center_xangle = phOffset[pairx[1]] | |
| 1957 | center_yangle = phOffset[pairy[1]] |
|
2398 | center_yangle = phOffset[pairy[1]] | |
| 1958 |
|
2399 | |||
| 1959 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) |
|
2400 | phOffset = numpy.angle(numpy.exp(1j*jph_array[:,i,j])) | |
| 1960 | phOffset = phOffset*180/numpy.pi |
|
2401 | phOffset = phOffset*180/numpy.pi | |
| 1961 | return phOffset |
|
2402 | return phOffset | |
| 1962 |
|
2403 | |||
| 1963 |
|
2404 | |||
| 1964 | def run(self, dataOut, hmin, hmax, direction25X=-1, direction20X=1, direction25Y=-1, direction20Y=1, nHours = 1): |
|
2405 | def run(self, dataOut, hmin, hmax, direction25X=-1, direction20X=1, direction25Y=-1, direction20Y=1, nHours = 1): | |
| 1965 |
|
2406 | |||
| 1966 | dataOut.flagNoData = True |
|
2407 | dataOut.flagNoData = True | |
| 1967 | self.__dataReady = False |
|
2408 | self.__dataReady = False | |
| 1968 | dataOut.outputInterval = nHours*3600 |
|
2409 | dataOut.outputInterval = nHours*3600 | |
| 1969 |
|
2410 | |||
| 1970 | if self.__isConfig == False: |
|
2411 | if self.__isConfig == False: | |
| 1971 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) |
|
2412 | # self.__initime = dataOut.datatime.replace(minute = 0, second = 0, microsecond = 03) | |
| 1972 | #Get Initial LTC time |
|
2413 | #Get Initial LTC time | |
| 1973 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) |
|
2414 | self.__initime = datetime.datetime.utcfromtimestamp(dataOut.utctime) | |
| 1974 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() |
|
2415 | self.__initime = (self.__initime.replace(minute = 0, second = 0, microsecond = 0) - datetime.datetime(1970, 1, 1)).total_seconds() | |
| 1975 |
|
2416 | |||
| 1976 | self.__isConfig = True |
|
2417 | self.__isConfig = True | |
| 1977 |
|
2418 | |||
| 1978 | if self.__buffer == None: |
|
2419 | if self.__buffer == None: | |
| 1979 | self.__buffer = dataOut.data_param.copy() |
|
2420 | self.__buffer = dataOut.data_param.copy() | |
| 1980 |
|
2421 | |||
| 1981 | else: |
|
2422 | else: | |
| 1982 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) |
|
2423 | self.__buffer = numpy.vstack((self.__buffer, dataOut.data_param)) | |
| 1983 |
|
2424 | |||
| 1984 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready |
|
2425 | self.__dataReady = self.__checkTime(dataOut.utctime, self.__initime, dataOut.paramInterval, dataOut.outputInterval) #Check if the buffer is ready | |
| 1985 |
|
2426 | |||
| 1986 | if self.__dataReady: |
|
2427 | if self.__dataReady: | |
| 1987 | dataOut.utctimeInit = self.__initime |
|
2428 | dataOut.utctimeInit = self.__initime | |
| 1988 | self.__initime += dataOut.outputInterval #to erase time offset |
|
2429 | self.__initime += dataOut.outputInterval #to erase time offset | |
| 1989 |
|
2430 | |||
| 1990 | freq = dataOut.frequency |
|
2431 | freq = dataOut.frequency | |
| 1991 | c = dataOut.C #m/s |
|
2432 | c = dataOut.C #m/s | |
| 1992 | lamb = c/freq |
|
2433 | lamb = c/freq | |
| 1993 | k = 2*numpy.pi/lamb |
|
2434 | k = 2*numpy.pi/lamb | |
| 1994 | azimuth = 0 |
|
2435 | azimuth = 0 | |
| 1995 | h = (hmin, hmax) |
|
2436 | h = (hmin, hmax) | |
| 1996 | pairs = ((0,1),(2,3)) |
|
2437 | pairs = ((0,1),(2,3)) | |
| 1997 | distances = [direction25X*2.5*lamb, direction20X*2*lamb, direction25Y*2.5*lamb, direction20Y*2*lamb] |
|
2438 | distances = [direction25X*2.5*lamb, direction20X*2*lamb, direction25Y*2.5*lamb, direction20Y*2*lamb] | |
| 1998 |
|
2439 | |||
| 1999 | meteorsArray = self.__buffer |
|
2440 | meteorsArray = self.__buffer | |
| 2000 | error = meteorsArray[:,-1] |
|
2441 | error = meteorsArray[:,-1] | |
| 2001 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) |
|
2442 | boolError = (error==0)|(error==3)|(error==4)|(error==13)|(error==14) | |
| 2002 | ind1 = numpy.where(boolError)[0] |
|
2443 | ind1 = numpy.where(boolError)[0] | |
| 2003 | meteorsArray = meteorsArray[ind1,:] |
|
2444 | meteorsArray = meteorsArray[ind1,:] | |
| 2004 | meteorsArray[:,-1] = 0 |
|
2445 | meteorsArray[:,-1] = 0 | |
| 2005 | phases = meteorsArray[:,8:12] |
|
2446 | phases = meteorsArray[:,8:12] | |
| 2006 |
|
2447 | |||
| 2007 | #Calculate Gammas |
|
2448 | #Calculate Gammas | |
| 2008 | gammas = self.__getGammas(pairs, k, distances, phases) |
|
2449 | gammas = self.__getGammas(pairs, k, distances, phases) | |
| 2009 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 |
|
2450 | # gammas = numpy.array([-21.70409463,45.76935864])*numpy.pi/180 | |
| 2010 | #Calculate Phases |
|
2451 | #Calculate Phases | |
| 2011 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) |
|
2452 | phasesOff = self.__getPhases(azimuth, h, pairs, distances, gammas, meteorsArray) | |
| 2012 | phasesOff = phasesOff.reshape((1,phasesOff.size)) |
|
2453 | phasesOff = phasesOff.reshape((1,phasesOff.size)) | |
| 2013 | dataOut.data_output = -phasesOff |
|
2454 | dataOut.data_output = -phasesOff | |
| 2014 | dataOut.flagNoData = False |
|
2455 | dataOut.flagNoData = False | |
| 2015 | self.__buffer = None |
|
2456 | self.__buffer = None | |
| 2016 |
|
2457 | |||
| 2017 |
|
2458 | |||
| 2018 | return |
|
2459 | return | |
| 2019 |
|
2460 | |||
| 2020 | class MeteorOperations(): |
|
2461 | class MeteorOperations(): | |
| 2021 |
|
2462 | |||
| 2022 | def __init__(self): |
|
2463 | def __init__(self): | |
| 2023 |
|
2464 | |||
| 2024 | return |
|
2465 | return | |
| 2025 |
|
2466 | |||
| 2026 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, jph): |
|
2467 | def getMeteorParams(self, arrayParameters0, azimuth, h, pairsList, jph): | |
| 2027 |
|
2468 | |||
| 2028 | arrayParameters = arrayParameters0.copy() |
|
2469 | arrayParameters = arrayParameters0.copy() | |
| 2029 | hmin = h[0] |
|
2470 | hmin = h[0] | |
| 2030 | hmax = h[1] |
|
2471 | hmax = h[1] | |
| 2031 |
|
2472 | |||
| 2032 | #Calculate AOA (Error N 3, 4) |
|
2473 | #Calculate AOA (Error N 3, 4) | |
| 2033 | #JONES ET AL. 1998 |
|
2474 | #JONES ET AL. 1998 | |
| 2034 | AOAthresh = numpy.pi/8 |
|
2475 | AOAthresh = numpy.pi/8 | |
| 2035 | error = arrayParameters[:,-1] |
|
2476 | error = arrayParameters[:,-1] | |
| 2036 | phases = -arrayParameters[:,8:12] + jph |
|
2477 | phases = -arrayParameters[:,8:12] + jph | |
| 2037 | # phases = numpy.unwrap(phases) |
|
2478 | # phases = numpy.unwrap(phases) | |
| 2038 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, error, AOAthresh, azimuth) |
|
2479 | arrayParameters[:,3:6], arrayParameters[:,-1] = self.__getAOA(phases, pairsList, error, AOAthresh, azimuth) | |
| 2039 |
|
2480 | |||
| 2040 | #Calculate Heights (Error N 13 and 14) |
|
2481 | #Calculate Heights (Error N 13 and 14) | |
| 2041 | error = arrayParameters[:,-1] |
|
2482 | error = arrayParameters[:,-1] | |
| 2042 | Ranges = arrayParameters[:,1] |
|
2483 | Ranges = arrayParameters[:,1] | |
| 2043 | zenith = arrayParameters[:,4] |
|
2484 | zenith = arrayParameters[:,4] | |
| 2044 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) |
|
2485 | arrayParameters[:,2], arrayParameters[:,-1] = self.__getHeights(Ranges, zenith, error, hmin, hmax) | |
| 2045 |
|
2486 | |||
| 2046 | #----------------------- Get Final data ------------------------------------ |
|
2487 | #----------------------- Get Final data ------------------------------------ | |
| 2047 | # error = arrayParameters[:,-1] |
|
2488 | # error = arrayParameters[:,-1] | |
| 2048 | # ind1 = numpy.where(error==0)[0] |
|
2489 | # ind1 = numpy.where(error==0)[0] | |
| 2049 | # arrayParameters = arrayParameters[ind1,:] |
|
2490 | # arrayParameters = arrayParameters[ind1,:] | |
| 2050 |
|
2491 | |||
| 2051 | return arrayParameters |
|
2492 | return arrayParameters | |
| 2052 |
|
2493 | |||
| 2053 |
def |
|
2494 | def getAOA(self, phases, pairsList, error, AOAthresh, azimuth): | |
| 2054 |
|
2495 | |||
| 2055 | arrayAOA = numpy.zeros((phases.shape[0],3)) |
|
2496 | arrayAOA = numpy.zeros((phases.shape[0],3)) | |
| 2056 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) |
|
2497 | cosdir0, cosdir = self.__getDirectionCosines(phases, pairsList) | |
| 2057 |
|
2498 | |||
| 2058 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) |
|
2499 | arrayAOA[:,:2] = self.__calculateAOA(cosdir, azimuth) | |
| 2059 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) |
|
2500 | cosDirError = numpy.sum(numpy.abs(cosdir0 - cosdir), axis = 1) | |
| 2060 | arrayAOA[:,2] = cosDirError |
|
2501 | arrayAOA[:,2] = cosDirError | |
| 2061 |
|
2502 | |||
| 2062 | azimuthAngle = arrayAOA[:,0] |
|
2503 | azimuthAngle = arrayAOA[:,0] | |
| 2063 | zenithAngle = arrayAOA[:,1] |
|
2504 | zenithAngle = arrayAOA[:,1] | |
| 2064 |
|
2505 | |||
| 2065 | #Setting Error |
|
2506 | #Setting Error | |
| 2066 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] |
|
2507 | indError = numpy.where(numpy.logical_or(error == 3, error == 4))[0] | |
| 2067 | error[indError] = 0 |
|
2508 | error[indError] = 0 | |
| 2068 | #Number 3: AOA not fesible |
|
2509 | #Number 3: AOA not fesible | |
| 2069 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] |
|
2510 | indInvalid = numpy.where(numpy.logical_and((numpy.logical_or(numpy.isnan(zenithAngle), numpy.isnan(azimuthAngle))),error == 0))[0] | |
| 2070 | error[indInvalid] = 3 |
|
2511 | error[indInvalid] = 3 | |
| 2071 | #Number 4: Large difference in AOAs obtained from different antenna baselines |
|
2512 | #Number 4: Large difference in AOAs obtained from different antenna baselines | |
| 2072 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] |
|
2513 | indInvalid = numpy.where(numpy.logical_and(cosDirError > AOAthresh,error == 0))[0] | |
| 2073 | error[indInvalid] = 4 |
|
2514 | error[indInvalid] = 4 | |
| 2074 | return arrayAOA, error |
|
2515 | return arrayAOA, error | |
| 2075 |
|
2516 | |||
| 2076 | def __getDirectionCosines(self, arrayPhase, pairsList): |
|
2517 | def __getDirectionCosines(self, arrayPhase, pairsList): | |
| 2077 |
|
2518 | |||
| 2078 | #Initializing some variables |
|
2519 | #Initializing some variables | |
| 2079 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi |
|
2520 | ang_aux = numpy.array([-8,-7,-6,-5,-4,-3,-2,-1,0,1,2,3,4,5,6,7,8])*2*numpy.pi | |
| 2080 | ang_aux = ang_aux.reshape(1,ang_aux.size) |
|
2521 | ang_aux = ang_aux.reshape(1,ang_aux.size) | |
| 2081 |
|
2522 | |||
| 2082 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) |
|
2523 | cosdir = numpy.zeros((arrayPhase.shape[0],2)) | |
| 2083 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) |
|
2524 | cosdir0 = numpy.zeros((arrayPhase.shape[0],2)) | |
| 2084 |
|
2525 | |||
| 2085 |
|
2526 | |||
| 2086 | for i in range(2): |
|
2527 | for i in range(2): | |
| 2087 | #First Estimation |
|
2528 | #First Estimation | |
| 2088 | phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] |
|
2529 | phi0_aux = arrayPhase[:,pairsList[i][0]] + arrayPhase[:,pairsList[i][1]] | |
| 2089 | #Dealias |
|
2530 | #Dealias | |
| 2090 | indcsi = numpy.where(phi0_aux > numpy.pi) |
|
2531 | indcsi = numpy.where(phi0_aux > numpy.pi) | |
| 2091 | phi0_aux[indcsi] -= 2*numpy.pi |
|
2532 | phi0_aux[indcsi] -= 2*numpy.pi | |
| 2092 | indcsi = numpy.where(phi0_aux < -numpy.pi) |
|
2533 | indcsi = numpy.where(phi0_aux < -numpy.pi) | |
| 2093 | phi0_aux[indcsi] += 2*numpy.pi |
|
2534 | phi0_aux[indcsi] += 2*numpy.pi | |
| 2094 | #Direction Cosine 0 |
|
2535 | #Direction Cosine 0 | |
| 2095 | cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) |
|
2536 | cosdir0[:,i] = -(phi0_aux)/(2*numpy.pi*0.5) | |
| 2096 |
|
2537 | |||
| 2097 | #Most-Accurate Second Estimation |
|
2538 | #Most-Accurate Second Estimation | |
| 2098 | phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] |
|
2539 | phi1_aux = arrayPhase[:,pairsList[i][0]] - arrayPhase[:,pairsList[i][1]] | |
| 2099 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) |
|
2540 | phi1_aux = phi1_aux.reshape(phi1_aux.size,1) | |
| 2100 | #Direction Cosine 1 |
|
2541 | #Direction Cosine 1 | |
| 2101 | cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) |
|
2542 | cosdir1 = -(phi1_aux + ang_aux)/(2*numpy.pi*4.5) | |
| 2102 |
|
2543 | |||
| 2103 | #Searching the correct Direction Cosine |
|
2544 | #Searching the correct Direction Cosine | |
| 2104 | cosdir0_aux = cosdir0[:,i] |
|
2545 | cosdir0_aux = cosdir0[:,i] | |
| 2105 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) |
|
2546 | cosdir0_aux = cosdir0_aux.reshape(cosdir0_aux.size,1) | |
| 2106 | #Minimum Distance |
|
2547 | #Minimum Distance | |
| 2107 | cosDiff = (cosdir1 - cosdir0_aux)**2 |
|
2548 | cosDiff = (cosdir1 - cosdir0_aux)**2 | |
| 2108 | indcos = cosDiff.argmin(axis = 1) |
|
2549 | indcos = cosDiff.argmin(axis = 1) | |
| 2109 | #Saving Value obtained |
|
2550 | #Saving Value obtained | |
| 2110 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] |
|
2551 | cosdir[:,i] = cosdir1[numpy.arange(len(indcos)),indcos] | |
| 2111 |
|
2552 | |||
| 2112 | return cosdir0, cosdir |
|
2553 | return cosdir0, cosdir | |
| 2113 |
|
2554 | |||
| 2114 | def __calculateAOA(self, cosdir, azimuth): |
|
2555 | def __calculateAOA(self, cosdir, azimuth): | |
| 2115 | cosdirX = cosdir[:,0] |
|
2556 | cosdirX = cosdir[:,0] | |
| 2116 | cosdirY = cosdir[:,1] |
|
2557 | cosdirY = cosdir[:,1] | |
| 2117 |
|
2558 | |||
| 2118 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi |
|
2559 | zenithAngle = numpy.arccos(numpy.sqrt(1 - cosdirX**2 - cosdirY**2))*180/numpy.pi | |
| 2119 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east |
|
2560 | azimuthAngle = numpy.arctan2(cosdirX,cosdirY)*180/numpy.pi + azimuth #0 deg north, 90 deg east | |
| 2120 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() |
|
2561 | angles = numpy.vstack((azimuthAngle, zenithAngle)).transpose() | |
| 2121 |
|
2562 | |||
| 2122 | return angles |
|
2563 | return angles | |
| 2123 |
|
2564 | |||
| 2124 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): |
|
2565 | def __getHeights(self, Ranges, zenith, error, minHeight, maxHeight): | |
| 2125 |
|
2566 | |||
| 2126 | Ramb = 375 #Ramb = c/(2*PRF) |
|
2567 | Ramb = 375 #Ramb = c/(2*PRF) | |
| 2127 | Re = 6371 #Earth Radius |
|
2568 | Re = 6371 #Earth Radius | |
| 2128 | heights = numpy.zeros(Ranges.shape) |
|
2569 | heights = numpy.zeros(Ranges.shape) | |
| 2129 |
|
2570 | |||
| 2130 | R_aux = numpy.array([0,1,2])*Ramb |
|
2571 | R_aux = numpy.array([0,1,2])*Ramb | |
| 2131 | R_aux = R_aux.reshape(1,R_aux.size) |
|
2572 | R_aux = R_aux.reshape(1,R_aux.size) | |
| 2132 |
|
2573 | |||
| 2133 | Ranges = Ranges.reshape(Ranges.size,1) |
|
2574 | Ranges = Ranges.reshape(Ranges.size,1) | |
| 2134 |
|
2575 | |||
| 2135 | Ri = Ranges + R_aux |
|
2576 | Ri = Ranges + R_aux | |
| 2136 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re |
|
2577 | hi = numpy.sqrt(Re**2 + Ri**2 + (2*Re*numpy.cos(zenith*numpy.pi/180)*Ri.transpose()).transpose()) - Re | |
| 2137 |
|
2578 | |||
| 2138 | #Check if there is a height between 70 and 110 km |
|
2579 | #Check if there is a height between 70 and 110 km | |
| 2139 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) |
|
2580 | h_bool = numpy.sum(numpy.logical_and(hi > minHeight, hi < maxHeight), axis = 1) | |
| 2140 | ind_h = numpy.where(h_bool == 1)[0] |
|
2581 | ind_h = numpy.where(h_bool == 1)[0] | |
| 2141 |
|
2582 | |||
| 2142 | hCorr = hi[ind_h, :] |
|
2583 | hCorr = hi[ind_h, :] | |
| 2143 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) |
|
2584 | ind_hCorr = numpy.where(numpy.logical_and(hi > minHeight, hi < maxHeight)) | |
| 2144 |
|
2585 | |||
| 2145 | hCorr = hi[ind_hCorr] |
|
2586 | hCorr = hi[ind_hCorr] | |
| 2146 | heights[ind_h] = hCorr |
|
2587 | heights[ind_h] = hCorr | |
| 2147 |
|
2588 | |||
| 2148 | #Setting Error |
|
2589 | #Setting Error | |
| 2149 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km |
|
2590 | #Number 13: Height unresolvable echo: not valid height within 70 to 110 km | |
| 2150 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km |
|
2591 | #Number 14: Height ambiguous echo: more than one possible height within 70 to 110 km | |
| 2151 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] |
|
2592 | indError = numpy.where(numpy.logical_or(error == 13, error == 14))[0] | |
| 2152 | error[indError] = 0 |
|
2593 | error[indError] = 0 | |
| 2153 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] |
|
2594 | indInvalid2 = numpy.where(numpy.logical_and(h_bool > 1, error == 0))[0] | |
| 2154 | error[indInvalid2] = 14 |
|
2595 | error[indInvalid2] = 14 | |
| 2155 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] |
|
2596 | indInvalid1 = numpy.where(numpy.logical_and(h_bool == 0, error == 0))[0] | |
| 2156 | error[indInvalid1] = 13 |
|
2597 | error[indInvalid1] = 13 | |
| 2157 |
|
2598 | |||
| 2158 | return heights, error No newline at end of file |
|
2599 | return heights, error | |
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