@@ -1,1321 +1,1319 | |||||
1 | import sys |
|
1 | import sys | |
2 | import numpy |
|
2 | import numpy | |
3 | from scipy import interpolate |
|
3 | from scipy import interpolate | |
4 | from schainpy import cSchain |
|
4 | from schainpy import cSchain | |
5 | from jroproc_base import ProcessingUnit, Operation |
|
5 | from jroproc_base import ProcessingUnit, Operation | |
6 | from schainpy.model.data.jrodata import Voltage |
|
6 | from schainpy.model.data.jrodata import Voltage | |
7 | from time import time |
|
7 | from time import time | |
8 |
|
8 | |||
9 | class VoltageProc(ProcessingUnit): |
|
9 | class VoltageProc(ProcessingUnit): | |
10 |
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10 | |||
11 |
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11 | |||
12 | def __init__(self, **kwargs): |
|
12 | def __init__(self, **kwargs): | |
13 |
|
13 | |||
14 | ProcessingUnit.__init__(self, **kwargs) |
|
14 | ProcessingUnit.__init__(self, **kwargs) | |
15 |
|
15 | |||
16 | # self.objectDict = {} |
|
16 | # self.objectDict = {} | |
17 | self.dataOut = Voltage() |
|
17 | self.dataOut = Voltage() | |
18 | self.flip = 1 |
|
18 | self.flip = 1 | |
19 |
|
19 | |||
20 | def run(self): |
|
20 | def run(self): | |
21 | if self.dataIn.type == 'AMISR': |
|
21 | if self.dataIn.type == 'AMISR': | |
22 | self.__updateObjFromAmisrInput() |
|
22 | self.__updateObjFromAmisrInput() | |
23 |
|
23 | |||
24 | if self.dataIn.type == 'Voltage': |
|
24 | if self.dataIn.type == 'Voltage': | |
25 | self.dataOut.copy(self.dataIn) |
|
25 | self.dataOut.copy(self.dataIn) | |
26 |
|
26 | |||
27 | # self.dataOut.copy(self.dataIn) |
|
27 | # self.dataOut.copy(self.dataIn) | |
28 |
|
28 | |||
29 | def __updateObjFromAmisrInput(self): |
|
29 | def __updateObjFromAmisrInput(self): | |
30 |
|
30 | |||
31 | self.dataOut.timeZone = self.dataIn.timeZone |
|
31 | self.dataOut.timeZone = self.dataIn.timeZone | |
32 | self.dataOut.dstFlag = self.dataIn.dstFlag |
|
32 | self.dataOut.dstFlag = self.dataIn.dstFlag | |
33 | self.dataOut.errorCount = self.dataIn.errorCount |
|
33 | self.dataOut.errorCount = self.dataIn.errorCount | |
34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime |
|
34 | self.dataOut.useLocalTime = self.dataIn.useLocalTime | |
35 |
|
35 | |||
36 | self.dataOut.flagNoData = self.dataIn.flagNoData |
|
36 | self.dataOut.flagNoData = self.dataIn.flagNoData | |
37 | self.dataOut.data = self.dataIn.data |
|
37 | self.dataOut.data = self.dataIn.data | |
38 | self.dataOut.utctime = self.dataIn.utctime |
|
38 | self.dataOut.utctime = self.dataIn.utctime | |
39 | self.dataOut.channelList = self.dataIn.channelList |
|
39 | self.dataOut.channelList = self.dataIn.channelList | |
40 | # self.dataOut.timeInterval = self.dataIn.timeInterval |
|
40 | # self.dataOut.timeInterval = self.dataIn.timeInterval | |
41 | self.dataOut.heightList = self.dataIn.heightList |
|
41 | self.dataOut.heightList = self.dataIn.heightList | |
42 | self.dataOut.nProfiles = self.dataIn.nProfiles |
|
42 | self.dataOut.nProfiles = self.dataIn.nProfiles | |
43 |
|
43 | |||
44 | self.dataOut.nCohInt = self.dataIn.nCohInt |
|
44 | self.dataOut.nCohInt = self.dataIn.nCohInt | |
45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds |
|
45 | self.dataOut.ippSeconds = self.dataIn.ippSeconds | |
46 | self.dataOut.frequency = self.dataIn.frequency |
|
46 | self.dataOut.frequency = self.dataIn.frequency | |
47 |
|
47 | |||
48 | self.dataOut.azimuth = self.dataIn.azimuth |
|
48 | self.dataOut.azimuth = self.dataIn.azimuth | |
49 | self.dataOut.zenith = self.dataIn.zenith |
|
49 | self.dataOut.zenith = self.dataIn.zenith | |
50 |
|
50 | |||
51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList |
|
51 | self.dataOut.beam.codeList = self.dataIn.beam.codeList | |
52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList |
|
52 | self.dataOut.beam.azimuthList = self.dataIn.beam.azimuthList | |
53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList |
|
53 | self.dataOut.beam.zenithList = self.dataIn.beam.zenithList | |
54 | # |
|
54 | # | |
55 | # pass# |
|
55 | # pass# | |
56 | # |
|
56 | # | |
57 | # def init(self): |
|
57 | # def init(self): | |
58 | # |
|
58 | # | |
59 | # |
|
59 | # | |
60 | # if self.dataIn.type == 'AMISR': |
|
60 | # if self.dataIn.type == 'AMISR': | |
61 | # self.__updateObjFromAmisrInput() |
|
61 | # self.__updateObjFromAmisrInput() | |
62 | # |
|
62 | # | |
63 | # if self.dataIn.type == 'Voltage': |
|
63 | # if self.dataIn.type == 'Voltage': | |
64 | # self.dataOut.copy(self.dataIn) |
|
64 | # self.dataOut.copy(self.dataIn) | |
65 | # # No necesita copiar en cada init() los atributos de dataIn |
|
65 | # # No necesita copiar en cada init() los atributos de dataIn | |
66 | # # la copia deberia hacerse por cada nuevo bloque de datos |
|
66 | # # la copia deberia hacerse por cada nuevo bloque de datos | |
67 |
|
67 | |||
68 | def selectChannels(self, channelList): |
|
68 | def selectChannels(self, channelList): | |
69 |
|
69 | |||
70 | channelIndexList = [] |
|
70 | channelIndexList = [] | |
71 |
|
71 | |||
72 | for channel in channelList: |
|
72 | for channel in channelList: | |
73 | if channel not in self.dataOut.channelList: |
|
73 | if channel not in self.dataOut.channelList: | |
74 | raise ValueError, "Channel %d is not in %s" %(channel, str(self.dataOut.channelList)) |
|
74 | raise ValueError, "Channel %d is not in %s" %(channel, str(self.dataOut.channelList)) | |
75 |
|
75 | |||
76 | index = self.dataOut.channelList.index(channel) |
|
76 | index = self.dataOut.channelList.index(channel) | |
77 | channelIndexList.append(index) |
|
77 | channelIndexList.append(index) | |
78 |
|
78 | |||
79 | self.selectChannelsByIndex(channelIndexList) |
|
79 | self.selectChannelsByIndex(channelIndexList) | |
80 |
|
80 | |||
81 | def selectChannelsByIndex(self, channelIndexList): |
|
81 | def selectChannelsByIndex(self, channelIndexList): | |
82 | """ |
|
82 | """ | |
83 | Selecciona un bloque de datos en base a canales segun el channelIndexList |
|
83 | Selecciona un bloque de datos en base a canales segun el channelIndexList | |
84 |
|
84 | |||
85 | Input: |
|
85 | Input: | |
86 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] |
|
86 | channelIndexList : lista sencilla de canales a seleccionar por ej. [2,3,7] | |
87 |
|
87 | |||
88 | Affected: |
|
88 | Affected: | |
89 | self.dataOut.data |
|
89 | self.dataOut.data | |
90 | self.dataOut.channelIndexList |
|
90 | self.dataOut.channelIndexList | |
91 | self.dataOut.nChannels |
|
91 | self.dataOut.nChannels | |
92 | self.dataOut.m_ProcessingHeader.totalSpectra |
|
92 | self.dataOut.m_ProcessingHeader.totalSpectra | |
93 | self.dataOut.systemHeaderObj.numChannels |
|
93 | self.dataOut.systemHeaderObj.numChannels | |
94 | self.dataOut.m_ProcessingHeader.blockSize |
|
94 | self.dataOut.m_ProcessingHeader.blockSize | |
95 |
|
95 | |||
96 | Return: |
|
96 | Return: | |
97 | None |
|
97 | None | |
98 | """ |
|
98 | """ | |
99 |
|
99 | |||
100 | for channelIndex in channelIndexList: |
|
100 | for channelIndex in channelIndexList: | |
101 | if channelIndex not in self.dataOut.channelIndexList: |
|
101 | if channelIndex not in self.dataOut.channelIndexList: | |
102 | print channelIndexList |
|
102 | print channelIndexList | |
103 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex |
|
103 | raise ValueError, "The value %d in channelIndexList is not valid" %channelIndex | |
104 |
|
104 | |||
105 | if self.dataOut.flagDataAsBlock: |
|
105 | if self.dataOut.flagDataAsBlock: | |
106 | """ |
|
106 | """ | |
107 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
107 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
108 | """ |
|
108 | """ | |
109 | data = self.dataOut.data[channelIndexList,:,:] |
|
109 | data = self.dataOut.data[channelIndexList,:,:] | |
110 | else: |
|
110 | else: | |
111 | data = self.dataOut.data[channelIndexList,:] |
|
111 | data = self.dataOut.data[channelIndexList,:] | |
112 |
|
112 | |||
113 | self.dataOut.data = data |
|
113 | self.dataOut.data = data | |
114 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] |
|
114 | self.dataOut.channelList = [self.dataOut.channelList[i] for i in channelIndexList] | |
115 | # self.dataOut.nChannels = nChannels |
|
115 | # self.dataOut.nChannels = nChannels | |
116 |
|
116 | |||
117 | return 1 |
|
117 | return 1 | |
118 |
|
118 | |||
119 | def selectHeights(self, minHei=None, maxHei=None): |
|
119 | def selectHeights(self, minHei=None, maxHei=None): | |
120 | """ |
|
120 | """ | |
121 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango |
|
121 | Selecciona un bloque de datos en base a un grupo de valores de alturas segun el rango | |
122 | minHei <= height <= maxHei |
|
122 | minHei <= height <= maxHei | |
123 |
|
123 | |||
124 | Input: |
|
124 | Input: | |
125 | minHei : valor minimo de altura a considerar |
|
125 | minHei : valor minimo de altura a considerar | |
126 | maxHei : valor maximo de altura a considerar |
|
126 | maxHei : valor maximo de altura a considerar | |
127 |
|
127 | |||
128 | Affected: |
|
128 | Affected: | |
129 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex |
|
129 | Indirectamente son cambiados varios valores a travez del metodo selectHeightsByIndex | |
130 |
|
130 | |||
131 | Return: |
|
131 | Return: | |
132 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
132 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
133 | """ |
|
133 | """ | |
134 |
|
134 | |||
135 | if minHei == None: |
|
135 | if minHei == None: | |
136 | minHei = self.dataOut.heightList[0] |
|
136 | minHei = self.dataOut.heightList[0] | |
137 |
|
137 | |||
138 | if maxHei == None: |
|
138 | if maxHei == None: | |
139 | maxHei = self.dataOut.heightList[-1] |
|
139 | maxHei = self.dataOut.heightList[-1] | |
140 |
|
140 | |||
141 | if (minHei < self.dataOut.heightList[0]): |
|
141 | if (minHei < self.dataOut.heightList[0]): | |
142 | minHei = self.dataOut.heightList[0] |
|
142 | minHei = self.dataOut.heightList[0] | |
143 |
|
143 | |||
144 | if (maxHei > self.dataOut.heightList[-1]): |
|
144 | if (maxHei > self.dataOut.heightList[-1]): | |
145 | maxHei = self.dataOut.heightList[-1] |
|
145 | maxHei = self.dataOut.heightList[-1] | |
146 |
|
146 | |||
147 | minIndex = 0 |
|
147 | minIndex = 0 | |
148 | maxIndex = 0 |
|
148 | maxIndex = 0 | |
149 | heights = self.dataOut.heightList |
|
149 | heights = self.dataOut.heightList | |
150 |
|
150 | |||
151 | inda = numpy.where(heights >= minHei) |
|
151 | inda = numpy.where(heights >= minHei) | |
152 | indb = numpy.where(heights <= maxHei) |
|
152 | indb = numpy.where(heights <= maxHei) | |
153 |
|
153 | |||
154 | try: |
|
154 | try: | |
155 | minIndex = inda[0][0] |
|
155 | minIndex = inda[0][0] | |
156 | except: |
|
156 | except: | |
157 | minIndex = 0 |
|
157 | minIndex = 0 | |
158 |
|
158 | |||
159 | try: |
|
159 | try: | |
160 | maxIndex = indb[0][-1] |
|
160 | maxIndex = indb[0][-1] | |
161 | except: |
|
161 | except: | |
162 | maxIndex = len(heights) |
|
162 | maxIndex = len(heights) | |
163 |
|
163 | |||
164 | self.selectHeightsByIndex(minIndex, maxIndex) |
|
164 | self.selectHeightsByIndex(minIndex, maxIndex) | |
165 |
|
165 | |||
166 | return 1 |
|
166 | return 1 | |
167 |
|
167 | |||
168 |
|
168 | |||
169 | def selectHeightsByIndex(self, minIndex, maxIndex): |
|
169 | def selectHeightsByIndex(self, minIndex, maxIndex): | |
170 | """ |
|
170 | """ | |
171 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango |
|
171 | Selecciona un bloque de datos en base a un grupo indices de alturas segun el rango | |
172 | minIndex <= index <= maxIndex |
|
172 | minIndex <= index <= maxIndex | |
173 |
|
173 | |||
174 | Input: |
|
174 | Input: | |
175 | minIndex : valor de indice minimo de altura a considerar |
|
175 | minIndex : valor de indice minimo de altura a considerar | |
176 | maxIndex : valor de indice maximo de altura a considerar |
|
176 | maxIndex : valor de indice maximo de altura a considerar | |
177 |
|
177 | |||
178 | Affected: |
|
178 | Affected: | |
179 | self.dataOut.data |
|
179 | self.dataOut.data | |
180 | self.dataOut.heightList |
|
180 | self.dataOut.heightList | |
181 |
|
181 | |||
182 | Return: |
|
182 | Return: | |
183 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 |
|
183 | 1 si el metodo se ejecuto con exito caso contrario devuelve 0 | |
184 | """ |
|
184 | """ | |
185 |
|
185 | |||
186 | if (minIndex < 0) or (minIndex > maxIndex): |
|
186 | if (minIndex < 0) or (minIndex > maxIndex): | |
187 | raise ValueError, "Height index range (%d,%d) is not valid" % (minIndex, maxIndex) |
|
187 | raise ValueError, "Height index range (%d,%d) is not valid" % (minIndex, maxIndex) | |
188 |
|
188 | |||
189 | if (maxIndex >= self.dataOut.nHeights): |
|
189 | if (maxIndex >= self.dataOut.nHeights): | |
190 | maxIndex = self.dataOut.nHeights |
|
190 | maxIndex = self.dataOut.nHeights | |
191 |
|
191 | |||
192 | #voltage |
|
192 | #voltage | |
193 | if self.dataOut.flagDataAsBlock: |
|
193 | if self.dataOut.flagDataAsBlock: | |
194 | """ |
|
194 | """ | |
195 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
195 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
196 | """ |
|
196 | """ | |
197 | data = self.dataOut.data[:,:, minIndex:maxIndex] |
|
197 | data = self.dataOut.data[:,:, minIndex:maxIndex] | |
198 | else: |
|
198 | else: | |
199 | data = self.dataOut.data[:, minIndex:maxIndex] |
|
199 | data = self.dataOut.data[:, minIndex:maxIndex] | |
200 |
|
200 | |||
201 | # firstHeight = self.dataOut.heightList[minIndex] |
|
201 | # firstHeight = self.dataOut.heightList[minIndex] | |
202 |
|
202 | |||
203 | self.dataOut.data = data |
|
203 | self.dataOut.data = data | |
204 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] |
|
204 | self.dataOut.heightList = self.dataOut.heightList[minIndex:maxIndex] | |
205 |
|
205 | |||
206 | if self.dataOut.nHeights <= 1: |
|
206 | if self.dataOut.nHeights <= 1: | |
207 | raise ValueError, "selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights) |
|
207 | raise ValueError, "selectHeights: Too few heights. Current number of heights is %d" %(self.dataOut.nHeights) | |
208 |
|
208 | |||
209 | return 1 |
|
209 | return 1 | |
210 |
|
210 | |||
211 |
|
211 | |||
212 | def filterByHeights(self, window): |
|
212 | def filterByHeights(self, window): | |
213 |
|
213 | |||
214 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
214 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
215 |
|
215 | |||
216 | if window == None: |
|
216 | if window == None: | |
217 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight |
|
217 | window = (self.dataOut.radarControllerHeaderObj.txA/self.dataOut.radarControllerHeaderObj.nBaud) / deltaHeight | |
218 |
|
218 | |||
219 | newdelta = deltaHeight * window |
|
219 | newdelta = deltaHeight * window | |
220 | r = self.dataOut.nHeights % window |
|
220 | r = self.dataOut.nHeights % window | |
221 | newheights = (self.dataOut.nHeights-r)/window |
|
221 | newheights = (self.dataOut.nHeights-r)/window | |
222 |
|
222 | |||
223 | if newheights <= 1: |
|
223 | if newheights <= 1: | |
224 | raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window) |
|
224 | raise ValueError, "filterByHeights: Too few heights. Current number of heights is %d and window is %d" %(self.dataOut.nHeights, window) | |
225 |
|
225 | |||
226 | if self.dataOut.flagDataAsBlock: |
|
226 | if self.dataOut.flagDataAsBlock: | |
227 | """ |
|
227 | """ | |
228 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
228 | Si la data es obtenida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
229 | """ |
|
229 | """ | |
230 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] |
|
230 | buffer = self.dataOut.data[:, :, 0:self.dataOut.nHeights-r] | |
231 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window) |
|
231 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nProfiles,self.dataOut.nHeights/window,window) | |
232 | buffer = numpy.sum(buffer,3) |
|
232 | buffer = numpy.sum(buffer,3) | |
233 |
|
233 | |||
234 | else: |
|
234 | else: | |
235 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] |
|
235 | buffer = self.dataOut.data[:,0:self.dataOut.nHeights-r] | |
236 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) |
|
236 | buffer = buffer.reshape(self.dataOut.nChannels,self.dataOut.nHeights/window,window) | |
237 | buffer = numpy.sum(buffer,2) |
|
237 | buffer = numpy.sum(buffer,2) | |
238 |
|
238 | |||
239 | self.dataOut.data = buffer |
|
239 | self.dataOut.data = buffer | |
240 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta |
|
240 | self.dataOut.heightList = self.dataOut.heightList[0] + numpy.arange( newheights )*newdelta | |
241 | self.dataOut.windowOfFilter = window |
|
241 | self.dataOut.windowOfFilter = window | |
242 |
|
242 | |||
243 | def setH0(self, h0, deltaHeight = None): |
|
243 | def setH0(self, h0, deltaHeight = None): | |
244 |
|
244 | |||
245 | if not deltaHeight: |
|
245 | if not deltaHeight: | |
246 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
246 | deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] | |
247 |
|
247 | |||
248 | nHeights = self.dataOut.nHeights |
|
248 | nHeights = self.dataOut.nHeights | |
249 |
|
249 | |||
250 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight |
|
250 | newHeiRange = h0 + numpy.arange(nHeights)*deltaHeight | |
251 |
|
251 | |||
252 | self.dataOut.heightList = newHeiRange |
|
252 | self.dataOut.heightList = newHeiRange | |
253 |
|
253 | |||
254 | def deFlip(self, channelList = []): |
|
254 | def deFlip(self, channelList = []): | |
255 |
|
255 | |||
256 | data = self.dataOut.data.copy() |
|
256 | data = self.dataOut.data.copy() | |
257 |
|
257 | |||
258 | if self.dataOut.flagDataAsBlock: |
|
258 | if self.dataOut.flagDataAsBlock: | |
259 | flip = self.flip |
|
259 | flip = self.flip | |
260 | profileList = range(self.dataOut.nProfiles) |
|
260 | profileList = range(self.dataOut.nProfiles) | |
261 |
|
261 | |||
262 | if not channelList: |
|
262 | if not channelList: | |
263 | for thisProfile in profileList: |
|
263 | for thisProfile in profileList: | |
264 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip |
|
264 | data[:,thisProfile,:] = data[:,thisProfile,:]*flip | |
265 | flip *= -1.0 |
|
265 | flip *= -1.0 | |
266 | else: |
|
266 | else: | |
267 | for thisChannel in channelList: |
|
267 | for thisChannel in channelList: | |
268 | if thisChannel not in self.dataOut.channelList: |
|
268 | if thisChannel not in self.dataOut.channelList: | |
269 | continue |
|
269 | continue | |
270 |
|
270 | |||
271 | for thisProfile in profileList: |
|
271 | for thisProfile in profileList: | |
272 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip |
|
272 | data[thisChannel,thisProfile,:] = data[thisChannel,thisProfile,:]*flip | |
273 | flip *= -1.0 |
|
273 | flip *= -1.0 | |
274 |
|
274 | |||
275 | self.flip = flip |
|
275 | self.flip = flip | |
276 |
|
276 | |||
277 | else: |
|
277 | else: | |
278 | if not channelList: |
|
278 | if not channelList: | |
279 | data[:,:] = data[:,:]*self.flip |
|
279 | data[:,:] = data[:,:]*self.flip | |
280 | else: |
|
280 | else: | |
281 | for thisChannel in channelList: |
|
281 | for thisChannel in channelList: | |
282 | if thisChannel not in self.dataOut.channelList: |
|
282 | if thisChannel not in self.dataOut.channelList: | |
283 | continue |
|
283 | continue | |
284 |
|
284 | |||
285 | data[thisChannel,:] = data[thisChannel,:]*self.flip |
|
285 | data[thisChannel,:] = data[thisChannel,:]*self.flip | |
286 |
|
286 | |||
287 | self.flip *= -1. |
|
287 | self.flip *= -1. | |
288 |
|
288 | |||
289 | self.dataOut.data = data |
|
289 | self.dataOut.data = data | |
290 |
|
290 | |||
291 | def setRadarFrequency(self, frequency=None): |
|
291 | def setRadarFrequency(self, frequency=None): | |
292 |
|
292 | |||
293 | if frequency != None: |
|
293 | if frequency != None: | |
294 | self.dataOut.frequency = frequency |
|
294 | self.dataOut.frequency = frequency | |
295 |
|
295 | |||
296 | return 1 |
|
296 | return 1 | |
297 |
|
297 | |||
298 | def interpolateHeights(self, topLim, botLim): |
|
298 | def interpolateHeights(self, topLim, botLim): | |
299 | #69 al 72 para julia |
|
299 | #69 al 72 para julia | |
300 | #82-84 para meteoros |
|
300 | #82-84 para meteoros | |
301 | if len(numpy.shape(self.dataOut.data))==2: |
|
301 | if len(numpy.shape(self.dataOut.data))==2: | |
302 | sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2 |
|
302 | sampInterp = (self.dataOut.data[:,botLim-1] + self.dataOut.data[:,topLim+1])/2 | |
303 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) |
|
303 | sampInterp = numpy.transpose(numpy.tile(sampInterp,(topLim-botLim + 1,1))) | |
304 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp |
|
304 | #self.dataOut.data[:,botLim:limSup+1] = sampInterp | |
305 | self.dataOut.data[:,botLim:topLim+1] = sampInterp |
|
305 | self.dataOut.data[:,botLim:topLim+1] = sampInterp | |
306 | else: |
|
306 | else: | |
307 | nHeights = self.dataOut.data.shape[2] |
|
307 | nHeights = self.dataOut.data.shape[2] | |
308 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) |
|
308 | x = numpy.hstack((numpy.arange(botLim),numpy.arange(topLim+1,nHeights))) | |
309 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] |
|
309 | y = self.dataOut.data[:,:,range(botLim)+range(topLim+1,nHeights)] | |
310 | f = interpolate.interp1d(x, y, axis = 2) |
|
310 | f = interpolate.interp1d(x, y, axis = 2) | |
311 | xnew = numpy.arange(botLim,topLim+1) |
|
311 | xnew = numpy.arange(botLim,topLim+1) | |
312 | ynew = f(xnew) |
|
312 | ynew = f(xnew) | |
313 |
|
313 | |||
314 | self.dataOut.data[:,:,botLim:topLim+1] = ynew |
|
314 | self.dataOut.data[:,:,botLim:topLim+1] = ynew | |
315 |
|
315 | |||
316 | # import collections |
|
316 | # import collections | |
317 |
|
317 | |||
318 | class CohInt(Operation): |
|
318 | class CohInt(Operation): | |
319 |
|
319 | |||
320 | isConfig = False |
|
320 | isConfig = False | |
321 | __profIndex = 0 |
|
321 | __profIndex = 0 | |
322 | __byTime = False |
|
322 | __byTime = False | |
323 | __initime = None |
|
323 | __initime = None | |
324 | __lastdatatime = None |
|
324 | __lastdatatime = None | |
325 | __integrationtime = None |
|
325 | __integrationtime = None | |
326 | __buffer = None |
|
326 | __buffer = None | |
327 | __bufferStride = [] |
|
327 | __bufferStride = [] | |
328 | __dataReady = False |
|
328 | __dataReady = False | |
329 | __profIndexStride = 0 |
|
329 | __profIndexStride = 0 | |
330 | __dataToPutStride = False |
|
330 | __dataToPutStride = False | |
331 | n = None |
|
331 | n = None | |
332 |
|
332 | |||
333 | def __init__(self, **kwargs): |
|
333 | def __init__(self, **kwargs): | |
334 |
|
334 | |||
335 | Operation.__init__(self, **kwargs) |
|
335 | Operation.__init__(self, **kwargs) | |
336 |
|
336 | |||
337 | # self.isConfig = False |
|
337 | # self.isConfig = False | |
338 |
|
338 | |||
339 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): |
|
339 | def setup(self, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False): | |
340 | """ |
|
340 | """ | |
341 | Set the parameters of the integration class. |
|
341 | Set the parameters of the integration class. | |
342 |
|
342 | |||
343 | Inputs: |
|
343 | Inputs: | |
344 |
|
344 | |||
345 | n : Number of coherent integrations |
|
345 | n : Number of coherent integrations | |
346 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work |
|
346 | timeInterval : Time of integration. If the parameter "n" is selected this one does not work | |
347 | overlapping : |
|
347 | overlapping : | |
348 | """ |
|
348 | """ | |
349 |
|
349 | |||
350 | self.__initime = None |
|
350 | self.__initime = None | |
351 | self.__lastdatatime = 0 |
|
351 | self.__lastdatatime = 0 | |
352 | self.__buffer = None |
|
352 | self.__buffer = None | |
353 | self.__dataReady = False |
|
353 | self.__dataReady = False | |
354 | self.byblock = byblock |
|
354 | self.byblock = byblock | |
355 | self.stride = stride |
|
355 | self.stride = stride | |
356 |
|
356 | |||
357 | if n == None and timeInterval == None: |
|
357 | if n == None and timeInterval == None: | |
358 | raise ValueError, "n or timeInterval should be specified ..." |
|
358 | raise ValueError, "n or timeInterval should be specified ..." | |
359 |
|
359 | |||
360 | if n != None: |
|
360 | if n != None: | |
361 | self.n = n |
|
361 | self.n = n | |
362 | self.__byTime = False |
|
362 | self.__byTime = False | |
363 | else: |
|
363 | else: | |
364 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line |
|
364 | self.__integrationtime = timeInterval #* 60. #if (type(timeInterval)!=integer) -> change this line | |
365 | self.n = 9999 |
|
365 | self.n = 9999 | |
366 | self.__byTime = True |
|
366 | self.__byTime = True | |
367 |
|
367 | |||
368 | if overlapping: |
|
368 | if overlapping: | |
369 | self.__withOverlapping = True |
|
369 | self.__withOverlapping = True | |
370 | self.__buffer = None |
|
370 | self.__buffer = None | |
371 | else: |
|
371 | else: | |
372 | self.__withOverlapping = False |
|
372 | self.__withOverlapping = False | |
373 | self.__buffer = 0 |
|
373 | self.__buffer = 0 | |
374 |
|
374 | |||
375 | self.__profIndex = 0 |
|
375 | self.__profIndex = 0 | |
376 |
|
376 | |||
377 | def putData(self, data): |
|
377 | def putData(self, data): | |
378 |
|
378 | |||
379 | """ |
|
379 | """ | |
380 | Add a profile to the __buffer and increase in one the __profileIndex |
|
380 | Add a profile to the __buffer and increase in one the __profileIndex | |
381 |
|
381 | |||
382 | """ |
|
382 | """ | |
383 |
|
383 | |||
384 | if not self.__withOverlapping: |
|
384 | if not self.__withOverlapping: | |
385 | self.__buffer += data.copy() |
|
385 | self.__buffer += data.copy() | |
386 | self.__profIndex += 1 |
|
386 | self.__profIndex += 1 | |
387 | return |
|
387 | return | |
388 |
|
388 | |||
389 | #Overlapping data |
|
389 | #Overlapping data | |
390 | nChannels, nHeis = data.shape |
|
390 | nChannels, nHeis = data.shape | |
391 | data = numpy.reshape(data, (1, nChannels, nHeis)) |
|
391 | data = numpy.reshape(data, (1, nChannels, nHeis)) | |
392 |
|
392 | |||
393 | #If the buffer is empty then it takes the data value |
|
393 | #If the buffer is empty then it takes the data value | |
394 | if self.__buffer is None: |
|
394 | if self.__buffer is None: | |
395 | self.__buffer = data |
|
395 | self.__buffer = data | |
396 | self.__profIndex += 1 |
|
396 | self.__profIndex += 1 | |
397 | return |
|
397 | return | |
398 |
|
398 | |||
399 | #If the buffer length is lower than n then stakcing the data value |
|
399 | #If the buffer length is lower than n then stakcing the data value | |
400 | if self.__profIndex < self.n: |
|
400 | if self.__profIndex < self.n: | |
401 | self.__buffer = numpy.vstack((self.__buffer, data)) |
|
401 | self.__buffer = numpy.vstack((self.__buffer, data)) | |
402 | self.__profIndex += 1 |
|
402 | self.__profIndex += 1 | |
403 | return |
|
403 | return | |
404 |
|
404 | |||
405 | #If the buffer length is equal to n then replacing the last buffer value with the data value |
|
405 | #If the buffer length is equal to n then replacing the last buffer value with the data value | |
406 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) |
|
406 | self.__buffer = numpy.roll(self.__buffer, -1, axis=0) | |
407 | self.__buffer[self.n-1] = data |
|
407 | self.__buffer[self.n-1] = data | |
408 | self.__profIndex = self.n |
|
408 | self.__profIndex = self.n | |
409 | return |
|
409 | return | |
410 |
|
410 | |||
411 |
|
411 | |||
412 | def pushData(self): |
|
412 | def pushData(self): | |
413 | """ |
|
413 | """ | |
414 | Return the sum of the last profiles and the profiles used in the sum. |
|
414 | Return the sum of the last profiles and the profiles used in the sum. | |
415 |
|
415 | |||
416 | Affected: |
|
416 | Affected: | |
417 |
|
417 | |||
418 | self.__profileIndex |
|
418 | self.__profileIndex | |
419 |
|
419 | |||
420 | """ |
|
420 | """ | |
421 |
|
421 | |||
422 | if not self.__withOverlapping: |
|
422 | if not self.__withOverlapping: | |
423 | data = self.__buffer |
|
423 | data = self.__buffer | |
424 | n = self.__profIndex |
|
424 | n = self.__profIndex | |
425 |
|
425 | |||
426 | self.__buffer = 0 |
|
426 | self.__buffer = 0 | |
427 | self.__profIndex = 0 |
|
427 | self.__profIndex = 0 | |
428 |
|
428 | |||
429 | return data, n |
|
429 | return data, n | |
430 |
|
430 | |||
431 | #Integration with Overlapping |
|
431 | #Integration with Overlapping | |
432 | data = numpy.sum(self.__buffer, axis=0) |
|
432 | data = numpy.sum(self.__buffer, axis=0) | |
433 | # print data |
|
433 | # print data | |
434 | # raise |
|
434 | # raise | |
435 | n = self.__profIndex |
|
435 | n = self.__profIndex | |
436 |
|
436 | |||
437 | return data, n |
|
437 | return data, n | |
438 |
|
438 | |||
439 | def byProfiles(self, data): |
|
439 | def byProfiles(self, data): | |
440 |
|
440 | |||
441 | self.__dataReady = False |
|
441 | self.__dataReady = False | |
442 | avgdata = None |
|
442 | avgdata = None | |
443 | # n = None |
|
443 | # n = None | |
444 | # print data |
|
444 | # print data | |
445 | # raise |
|
445 | # raise | |
446 | self.putData(data) |
|
446 | self.putData(data) | |
447 |
|
447 | |||
448 | if self.__profIndex == self.n: |
|
448 | if self.__profIndex == self.n: | |
449 | avgdata, n = self.pushData() |
|
449 | avgdata, n = self.pushData() | |
450 | self.__dataReady = True |
|
450 | self.__dataReady = True | |
451 |
|
451 | |||
452 | return avgdata |
|
452 | return avgdata | |
453 |
|
453 | |||
454 | def byTime(self, data, datatime): |
|
454 | def byTime(self, data, datatime): | |
455 |
|
455 | |||
456 | self.__dataReady = False |
|
456 | self.__dataReady = False | |
457 | avgdata = None |
|
457 | avgdata = None | |
458 | n = None |
|
458 | n = None | |
459 |
|
459 | |||
460 | self.putData(data) |
|
460 | self.putData(data) | |
461 |
|
461 | |||
462 | if (datatime - self.__initime) >= self.__integrationtime: |
|
462 | if (datatime - self.__initime) >= self.__integrationtime: | |
463 | avgdata, n = self.pushData() |
|
463 | avgdata, n = self.pushData() | |
464 | self.n = n |
|
464 | self.n = n | |
465 | self.__dataReady = True |
|
465 | self.__dataReady = True | |
466 |
|
466 | |||
467 | return avgdata |
|
467 | return avgdata | |
468 |
|
468 | |||
469 | def integrateByStride(self, data, datatime): |
|
469 | def integrateByStride(self, data, datatime): | |
470 | # print data |
|
470 | # print data | |
471 | if self.__profIndex == 0: |
|
471 | if self.__profIndex == 0: | |
472 | self.__buffer = [[data.copy(), datatime]] |
|
472 | self.__buffer = [[data.copy(), datatime]] | |
473 | else: |
|
473 | else: | |
474 |
self.__buffer.append([data.copy(), |
|
474 | self.__buffer.append([data.copy(),datatime]) | |
475 | self.__profIndex += 1 |
|
475 | self.__profIndex += 1 | |
476 | self.__dataReady = False |
|
476 | self.__dataReady = False | |
477 |
|
477 | |||
478 | if self.__profIndex == self.n * self.stride : |
|
478 | if self.__profIndex == self.n * self.stride : | |
479 | self.__dataToPutStride = True |
|
479 | self.__dataToPutStride = True | |
480 | self.__profIndexStride = 0 |
|
480 | self.__profIndexStride = 0 | |
481 | self.__profIndex = 0 |
|
481 | self.__profIndex = 0 | |
482 | self.__bufferStride = [] |
|
482 | self.__bufferStride = [] | |
483 | for i in range(self.stride): |
|
483 | for i in range(self.stride): | |
484 | current = self.__buffer[i::self.stride] |
|
484 | current = self.__buffer[i::self.stride] | |
485 | data = numpy.sum([t[0] for t in current], axis=0) |
|
485 | data = numpy.sum([t[0] for t in current], axis=0) | |
486 | avgdatatime = numpy.average([t[1] for t in current]) |
|
486 | avgdatatime = numpy.average([t[1] for t in current]) | |
487 | # print data |
|
487 | # print data | |
488 | self.__bufferStride.append((data, avgdatatime)) |
|
488 | self.__bufferStride.append((data, avgdatatime)) | |
489 |
|
489 | |||
490 | if self.__dataToPutStride: |
|
490 | if self.__dataToPutStride: | |
491 |
self.__dataReady = |
|
491 | self.__dataReady = True | |
492 | self.__profIndexStride += 1 |
|
492 | self.__profIndexStride += 1 | |
493 | if self.__profIndexStride == self.stride: |
|
493 | if self.__profIndexStride == self.stride: | |
494 | self.__dataReady = True |
|
|||
495 | self.__dataToPutStride = False |
|
494 | self.__dataToPutStride = False | |
496 | self.__profIndexStride = 0 |
|
|||
497 | # print self.__bufferStride[self.__profIndexStride - 1] |
|
495 | # print self.__bufferStride[self.__profIndexStride - 1] | |
498 | # raise |
|
496 | # raise | |
499 | return (numpy.sum([t[0] for t in self.__bufferStride], axis=0), numpy.average([t[1] for t in self.__bufferStride])) |
|
497 | return self.__bufferStride[self.__profIndexStride - 1] | |
500 |
|
498 | |||
501 |
|
499 | |||
502 | return None, None |
|
500 | return None, None | |
503 |
|
501 | |||
504 | def integrate(self, data, datatime=None): |
|
502 | def integrate(self, data, datatime=None): | |
505 |
|
503 | |||
506 | if self.__initime == None: |
|
504 | if self.__initime == None: | |
507 | self.__initime = datatime |
|
505 | self.__initime = datatime | |
508 |
|
506 | |||
509 | if self.__byTime: |
|
507 | if self.__byTime: | |
510 | avgdata = self.byTime(data, datatime) |
|
508 | avgdata = self.byTime(data, datatime) | |
511 | else: |
|
509 | else: | |
512 | avgdata = self.byProfiles(data) |
|
510 | avgdata = self.byProfiles(data) | |
513 |
|
511 | |||
514 |
|
512 | |||
515 | self.__lastdatatime = datatime |
|
513 | self.__lastdatatime = datatime | |
516 |
|
514 | |||
517 | if avgdata is None: |
|
515 | if avgdata is None: | |
518 | return None, None |
|
516 | return None, None | |
519 |
|
517 | |||
520 | avgdatatime = self.__initime |
|
518 | avgdatatime = self.__initime | |
521 |
|
519 | |||
522 | deltatime = datatime - self.__lastdatatime |
|
520 | deltatime = datatime - self.__lastdatatime | |
523 |
|
521 | |||
524 | if not self.__withOverlapping: |
|
522 | if not self.__withOverlapping: | |
525 | self.__initime = datatime |
|
523 | self.__initime = datatime | |
526 | else: |
|
524 | else: | |
527 | self.__initime += deltatime |
|
525 | self.__initime += deltatime | |
528 |
|
526 | |||
529 | return avgdata, avgdatatime |
|
527 | return avgdata, avgdatatime | |
530 |
|
528 | |||
531 | def integrateByBlock(self, dataOut): |
|
529 | def integrateByBlock(self, dataOut): | |
532 |
|
530 | |||
533 | times = int(dataOut.data.shape[1]/self.n) |
|
531 | times = int(dataOut.data.shape[1]/self.n) | |
534 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) |
|
532 | avgdata = numpy.zeros((dataOut.nChannels, times, dataOut.nHeights), dtype=numpy.complex) | |
535 |
|
533 | |||
536 | id_min = 0 |
|
534 | id_min = 0 | |
537 | id_max = self.n |
|
535 | id_max = self.n | |
538 |
|
536 | |||
539 | for i in range(times): |
|
537 | for i in range(times): | |
540 | junk = dataOut.data[:,id_min:id_max,:] |
|
538 | junk = dataOut.data[:,id_min:id_max,:] | |
541 | avgdata[:,i,:] = junk.sum(axis=1) |
|
539 | avgdata[:,i,:] = junk.sum(axis=1) | |
542 | id_min += self.n |
|
540 | id_min += self.n | |
543 | id_max += self.n |
|
541 | id_max += self.n | |
544 |
|
542 | |||
545 | timeInterval = dataOut.ippSeconds*self.n |
|
543 | timeInterval = dataOut.ippSeconds*self.n | |
546 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime |
|
544 | avgdatatime = (times - 1) * timeInterval + dataOut.utctime | |
547 | self.__dataReady = True |
|
545 | self.__dataReady = True | |
548 | return avgdata, avgdatatime |
|
546 | return avgdata, avgdatatime | |
549 |
|
547 | |||
550 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): |
|
548 | def run(self, dataOut, n=None, timeInterval=None, stride=None, overlapping=False, byblock=False, **kwargs): | |
551 | if not self.isConfig: |
|
549 | if not self.isConfig: | |
552 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) |
|
550 | self.setup(n=n, stride=stride, timeInterval=timeInterval, overlapping=overlapping, byblock=byblock, **kwargs) | |
553 | self.isConfig = True |
|
551 | self.isConfig = True | |
554 |
|
552 | |||
555 | if dataOut.flagDataAsBlock: |
|
553 | if dataOut.flagDataAsBlock: | |
556 | """ |
|
554 | """ | |
557 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] |
|
555 | Si la data es leida por bloques, dimension = [nChannels, nProfiles, nHeis] | |
558 | """ |
|
556 | """ | |
559 | avgdata, avgdatatime = self.integrateByBlock(dataOut) |
|
557 | avgdata, avgdatatime = self.integrateByBlock(dataOut) | |
560 | dataOut.nProfiles /= self.n |
|
558 | dataOut.nProfiles /= self.n | |
561 | else: |
|
559 | else: | |
562 | if stride is None: |
|
560 | if stride is None: | |
563 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) |
|
561 | avgdata, avgdatatime = self.integrate(dataOut.data, dataOut.utctime) | |
564 | else: |
|
562 | else: | |
565 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) |
|
563 | avgdata, avgdatatime = self.integrateByStride(dataOut.data, dataOut.utctime) | |
566 |
|
564 | |||
567 |
|
565 | |||
568 | # dataOut.timeInterval *= n |
|
566 | # dataOut.timeInterval *= n | |
569 | dataOut.flagNoData = True |
|
567 | dataOut.flagNoData = True | |
570 |
|
568 | |||
571 | if self.__dataReady: |
|
569 | if self.__dataReady: | |
572 | dataOut.data = avgdata |
|
570 | dataOut.data = avgdata | |
573 | dataOut.nCohInt *= self.n |
|
571 | dataOut.nCohInt *= self.n | |
574 | dataOut.utctime = avgdatatime |
|
572 | dataOut.utctime = avgdatatime | |
575 | # print avgdata, avgdatatime |
|
573 | # print avgdata, avgdatatime | |
576 | # raise |
|
574 | # raise | |
577 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt |
|
575 | # dataOut.timeInterval = dataOut.ippSeconds * dataOut.nCohInt | |
578 | dataOut.flagNoData = False |
|
576 | dataOut.flagNoData = False | |
579 |
|
577 | |||
580 | class Decoder(Operation): |
|
578 | class Decoder(Operation): | |
581 |
|
579 | |||
582 | isConfig = False |
|
580 | isConfig = False | |
583 | __profIndex = 0 |
|
581 | __profIndex = 0 | |
584 |
|
582 | |||
585 | code = None |
|
583 | code = None | |
586 |
|
584 | |||
587 | nCode = None |
|
585 | nCode = None | |
588 | nBaud = None |
|
586 | nBaud = None | |
589 |
|
587 | |||
590 | def __init__(self, **kwargs): |
|
588 | def __init__(self, **kwargs): | |
591 |
|
589 | |||
592 | Operation.__init__(self, **kwargs) |
|
590 | Operation.__init__(self, **kwargs) | |
593 |
|
591 | |||
594 | self.times = None |
|
592 | self.times = None | |
595 | self.osamp = None |
|
593 | self.osamp = None | |
596 | # self.__setValues = False |
|
594 | # self.__setValues = False | |
597 | self.isConfig = False |
|
595 | self.isConfig = False | |
598 |
|
596 | |||
599 | def setup(self, code, osamp, dataOut): |
|
597 | def setup(self, code, osamp, dataOut): | |
600 |
|
598 | |||
601 | self.__profIndex = 0 |
|
599 | self.__profIndex = 0 | |
602 |
|
600 | |||
603 | self.code = code |
|
601 | self.code = code | |
604 |
|
602 | |||
605 | self.nCode = len(code) |
|
603 | self.nCode = len(code) | |
606 | self.nBaud = len(code[0]) |
|
604 | self.nBaud = len(code[0]) | |
607 |
|
605 | |||
608 | if (osamp != None) and (osamp >1): |
|
606 | if (osamp != None) and (osamp >1): | |
609 | self.osamp = osamp |
|
607 | self.osamp = osamp | |
610 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) |
|
608 | self.code = numpy.repeat(code, repeats=self.osamp, axis=1) | |
611 | self.nBaud = self.nBaud*self.osamp |
|
609 | self.nBaud = self.nBaud*self.osamp | |
612 |
|
610 | |||
613 | self.__nChannels = dataOut.nChannels |
|
611 | self.__nChannels = dataOut.nChannels | |
614 | self.__nProfiles = dataOut.nProfiles |
|
612 | self.__nProfiles = dataOut.nProfiles | |
615 | self.__nHeis = dataOut.nHeights |
|
613 | self.__nHeis = dataOut.nHeights | |
616 |
|
614 | |||
617 | if self.__nHeis < self.nBaud: |
|
615 | if self.__nHeis < self.nBaud: | |
618 | raise ValueError, 'Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud) |
|
616 | raise ValueError, 'Number of heights (%d) should be greater than number of bauds (%d)' %(self.__nHeis, self.nBaud) | |
619 |
|
617 | |||
620 | #Frequency |
|
618 | #Frequency | |
621 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) |
|
619 | __codeBuffer = numpy.zeros((self.nCode, self.__nHeis), dtype=numpy.complex) | |
622 |
|
620 | |||
623 | __codeBuffer[:,0:self.nBaud] = self.code |
|
621 | __codeBuffer[:,0:self.nBaud] = self.code | |
624 |
|
622 | |||
625 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) |
|
623 | self.fft_code = numpy.conj(numpy.fft.fft(__codeBuffer, axis=1)) | |
626 |
|
624 | |||
627 | if dataOut.flagDataAsBlock: |
|
625 | if dataOut.flagDataAsBlock: | |
628 |
|
626 | |||
629 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
627 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
630 |
|
628 | |||
631 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) |
|
629 | self.datadecTime = numpy.zeros((self.__nChannels, self.__nProfiles, self.ndatadec), dtype=numpy.complex) | |
632 |
|
630 | |||
633 | else: |
|
631 | else: | |
634 |
|
632 | |||
635 | #Time |
|
633 | #Time | |
636 | self.ndatadec = self.__nHeis #- self.nBaud + 1 |
|
634 | self.ndatadec = self.__nHeis #- self.nBaud + 1 | |
637 |
|
635 | |||
638 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) |
|
636 | self.datadecTime = numpy.zeros((self.__nChannels, self.ndatadec), dtype=numpy.complex) | |
639 |
|
637 | |||
640 | def __convolutionInFreq(self, data): |
|
638 | def __convolutionInFreq(self, data): | |
641 |
|
639 | |||
642 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
640 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
643 |
|
641 | |||
644 | fft_data = numpy.fft.fft(data, axis=1) |
|
642 | fft_data = numpy.fft.fft(data, axis=1) | |
645 |
|
643 | |||
646 | conv = fft_data*fft_code |
|
644 | conv = fft_data*fft_code | |
647 |
|
645 | |||
648 | data = numpy.fft.ifft(conv,axis=1) |
|
646 | data = numpy.fft.ifft(conv,axis=1) | |
649 |
|
647 | |||
650 | return data |
|
648 | return data | |
651 |
|
649 | |||
652 | def __convolutionInFreqOpt(self, data): |
|
650 | def __convolutionInFreqOpt(self, data): | |
653 |
|
651 | |||
654 | raise NotImplementedError |
|
652 | raise NotImplementedError | |
655 |
|
653 | |||
656 | def __convolutionInTime(self, data): |
|
654 | def __convolutionInTime(self, data): | |
657 |
|
655 | |||
658 | code = self.code[self.__profIndex] |
|
656 | code = self.code[self.__profIndex] | |
659 | for i in range(self.__nChannels): |
|
657 | for i in range(self.__nChannels): | |
660 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] |
|
658 | self.datadecTime[i,:] = numpy.correlate(data[i,:], code, mode='full')[self.nBaud-1:] | |
661 |
|
659 | |||
662 | return self.datadecTime |
|
660 | return self.datadecTime | |
663 |
|
661 | |||
664 | def __convolutionByBlockInTime(self, data): |
|
662 | def __convolutionByBlockInTime(self, data): | |
665 |
|
663 | |||
666 | repetitions = self.__nProfiles / self.nCode |
|
664 | repetitions = self.__nProfiles / self.nCode | |
667 |
|
665 | |||
668 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) |
|
666 | junk = numpy.lib.stride_tricks.as_strided(self.code, (repetitions, self.code.size), (0, self.code.itemsize)) | |
669 | junk = junk.flatten() |
|
667 | junk = junk.flatten() | |
670 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) |
|
668 | code_block = numpy.reshape(junk, (self.nCode*repetitions, self.nBaud)) | |
671 | profilesList = xrange(self.__nProfiles) |
|
669 | profilesList = xrange(self.__nProfiles) | |
672 |
|
670 | |||
673 | for i in range(self.__nChannels): |
|
671 | for i in range(self.__nChannels): | |
674 | for j in profilesList: |
|
672 | for j in profilesList: | |
675 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] |
|
673 | self.datadecTime[i,j,:] = numpy.correlate(data[i,j,:], code_block[j,:], mode='full')[self.nBaud-1:] | |
676 | return self.datadecTime |
|
674 | return self.datadecTime | |
677 |
|
675 | |||
678 | def __convolutionByBlockInFreq(self, data): |
|
676 | def __convolutionByBlockInFreq(self, data): | |
679 |
|
677 | |||
680 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" |
|
678 | raise NotImplementedError, "Decoder by frequency fro Blocks not implemented" | |
681 |
|
679 | |||
682 |
|
680 | |||
683 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) |
|
681 | fft_code = self.fft_code[self.__profIndex].reshape(1,-1) | |
684 |
|
682 | |||
685 | fft_data = numpy.fft.fft(data, axis=2) |
|
683 | fft_data = numpy.fft.fft(data, axis=2) | |
686 |
|
684 | |||
687 | conv = fft_data*fft_code |
|
685 | conv = fft_data*fft_code | |
688 |
|
686 | |||
689 | data = numpy.fft.ifft(conv,axis=2) |
|
687 | data = numpy.fft.ifft(conv,axis=2) | |
690 |
|
688 | |||
691 | return data |
|
689 | return data | |
692 |
|
690 | |||
693 |
|
691 | |||
694 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): |
|
692 | def run(self, dataOut, code=None, nCode=None, nBaud=None, mode = 0, osamp=None, times=None): | |
695 |
|
693 | |||
696 | if dataOut.flagDecodeData: |
|
694 | if dataOut.flagDecodeData: | |
697 | print "This data is already decoded, recoding again ..." |
|
695 | print "This data is already decoded, recoding again ..." | |
698 |
|
696 | |||
699 | if not self.isConfig: |
|
697 | if not self.isConfig: | |
700 |
|
698 | |||
701 | if code is None: |
|
699 | if code is None: | |
702 | if dataOut.code is None: |
|
700 | if dataOut.code is None: | |
703 | raise ValueError, "Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type |
|
701 | raise ValueError, "Code could not be read from %s instance. Enter a value in Code parameter" %dataOut.type | |
704 |
|
702 | |||
705 | code = dataOut.code |
|
703 | code = dataOut.code | |
706 | else: |
|
704 | else: | |
707 | code = numpy.array(code).reshape(nCode,nBaud) |
|
705 | code = numpy.array(code).reshape(nCode,nBaud) | |
708 | self.setup(code, osamp, dataOut) |
|
706 | self.setup(code, osamp, dataOut) | |
709 |
|
707 | |||
710 | self.isConfig = True |
|
708 | self.isConfig = True | |
711 |
|
709 | |||
712 | if mode == 3: |
|
710 | if mode == 3: | |
713 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) |
|
711 | sys.stderr.write("Decoder Warning: mode=%d is not valid, using mode=0\n" %mode) | |
714 |
|
712 | |||
715 | if times != None: |
|
713 | if times != None: | |
716 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") |
|
714 | sys.stderr.write("Decoder Warning: Argument 'times' in not used anymore\n") | |
717 |
|
715 | |||
718 | if self.code is None: |
|
716 | if self.code is None: | |
719 | print "Fail decoding: Code is not defined." |
|
717 | print "Fail decoding: Code is not defined." | |
720 | return |
|
718 | return | |
721 |
|
719 | |||
722 | self.__nProfiles = dataOut.nProfiles |
|
720 | self.__nProfiles = dataOut.nProfiles | |
723 | datadec = None |
|
721 | datadec = None | |
724 |
|
722 | |||
725 | if mode == 3: |
|
723 | if mode == 3: | |
726 | mode = 0 |
|
724 | mode = 0 | |
727 |
|
725 | |||
728 | if dataOut.flagDataAsBlock: |
|
726 | if dataOut.flagDataAsBlock: | |
729 | """ |
|
727 | """ | |
730 | Decoding when data have been read as block, |
|
728 | Decoding when data have been read as block, | |
731 | """ |
|
729 | """ | |
732 |
|
730 | |||
733 | if mode == 0: |
|
731 | if mode == 0: | |
734 | datadec = self.__convolutionByBlockInTime(dataOut.data) |
|
732 | datadec = self.__convolutionByBlockInTime(dataOut.data) | |
735 | if mode == 1: |
|
733 | if mode == 1: | |
736 | datadec = self.__convolutionByBlockInFreq(dataOut.data) |
|
734 | datadec = self.__convolutionByBlockInFreq(dataOut.data) | |
737 | else: |
|
735 | else: | |
738 | """ |
|
736 | """ | |
739 | Decoding when data have been read profile by profile |
|
737 | Decoding when data have been read profile by profile | |
740 | """ |
|
738 | """ | |
741 | if mode == 0: |
|
739 | if mode == 0: | |
742 | datadec = self.__convolutionInTime(dataOut.data) |
|
740 | datadec = self.__convolutionInTime(dataOut.data) | |
743 |
|
741 | |||
744 | if mode == 1: |
|
742 | if mode == 1: | |
745 | datadec = self.__convolutionInFreq(dataOut.data) |
|
743 | datadec = self.__convolutionInFreq(dataOut.data) | |
746 |
|
744 | |||
747 | if mode == 2: |
|
745 | if mode == 2: | |
748 | datadec = self.__convolutionInFreqOpt(dataOut.data) |
|
746 | datadec = self.__convolutionInFreqOpt(dataOut.data) | |
749 |
|
747 | |||
750 | if datadec is None: |
|
748 | if datadec is None: | |
751 | raise ValueError, "Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode |
|
749 | raise ValueError, "Codification mode selected is not valid: mode=%d. Try selecting 0 or 1" %mode | |
752 |
|
750 | |||
753 | dataOut.code = self.code |
|
751 | dataOut.code = self.code | |
754 | dataOut.nCode = self.nCode |
|
752 | dataOut.nCode = self.nCode | |
755 | dataOut.nBaud = self.nBaud |
|
753 | dataOut.nBaud = self.nBaud | |
756 |
|
754 | |||
757 | dataOut.data = datadec |
|
755 | dataOut.data = datadec | |
758 |
|
756 | |||
759 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] |
|
757 | dataOut.heightList = dataOut.heightList[0:datadec.shape[-1]] | |
760 |
|
758 | |||
761 | dataOut.flagDecodeData = True #asumo q la data esta decodificada |
|
759 | dataOut.flagDecodeData = True #asumo q la data esta decodificada | |
762 |
|
760 | |||
763 | if self.__profIndex == self.nCode-1: |
|
761 | if self.__profIndex == self.nCode-1: | |
764 | self.__profIndex = 0 |
|
762 | self.__profIndex = 0 | |
765 | return 1 |
|
763 | return 1 | |
766 |
|
764 | |||
767 | self.__profIndex += 1 |
|
765 | self.__profIndex += 1 | |
768 |
|
766 | |||
769 | return 1 |
|
767 | return 1 | |
770 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip |
|
768 | # dataOut.flagDeflipData = True #asumo q la data no esta sin flip | |
771 |
|
769 | |||
772 |
|
770 | |||
773 | class ProfileConcat(Operation): |
|
771 | class ProfileConcat(Operation): | |
774 |
|
772 | |||
775 | isConfig = False |
|
773 | isConfig = False | |
776 | buffer = None |
|
774 | buffer = None | |
777 |
|
775 | |||
778 | def __init__(self, **kwargs): |
|
776 | def __init__(self, **kwargs): | |
779 |
|
777 | |||
780 | Operation.__init__(self, **kwargs) |
|
778 | Operation.__init__(self, **kwargs) | |
781 | self.profileIndex = 0 |
|
779 | self.profileIndex = 0 | |
782 |
|
780 | |||
783 | def reset(self): |
|
781 | def reset(self): | |
784 | self.buffer = numpy.zeros_like(self.buffer) |
|
782 | self.buffer = numpy.zeros_like(self.buffer) | |
785 | self.start_index = 0 |
|
783 | self.start_index = 0 | |
786 | self.times = 1 |
|
784 | self.times = 1 | |
787 |
|
785 | |||
788 | def setup(self, data, m, n=1): |
|
786 | def setup(self, data, m, n=1): | |
789 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) |
|
787 | self.buffer = numpy.zeros((data.shape[0],data.shape[1]*m),dtype=type(data[0,0])) | |
790 | self.nHeights = data.shape[1]#.nHeights |
|
788 | self.nHeights = data.shape[1]#.nHeights | |
791 | self.start_index = 0 |
|
789 | self.start_index = 0 | |
792 | self.times = 1 |
|
790 | self.times = 1 | |
793 |
|
791 | |||
794 | def concat(self, data): |
|
792 | def concat(self, data): | |
795 |
|
793 | |||
796 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() |
|
794 | self.buffer[:,self.start_index:self.nHeights*self.times] = data.copy() | |
797 | self.start_index = self.start_index + self.nHeights |
|
795 | self.start_index = self.start_index + self.nHeights | |
798 |
|
796 | |||
799 | def run(self, dataOut, m): |
|
797 | def run(self, dataOut, m): | |
800 |
|
798 | |||
801 | dataOut.flagNoData = True |
|
799 | dataOut.flagNoData = True | |
802 |
|
800 | |||
803 | if not self.isConfig: |
|
801 | if not self.isConfig: | |
804 | self.setup(dataOut.data, m, 1) |
|
802 | self.setup(dataOut.data, m, 1) | |
805 | self.isConfig = True |
|
803 | self.isConfig = True | |
806 |
|
804 | |||
807 | if dataOut.flagDataAsBlock: |
|
805 | if dataOut.flagDataAsBlock: | |
808 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" |
|
806 | raise ValueError, "ProfileConcat can only be used when voltage have been read profile by profile, getBlock = False" | |
809 |
|
807 | |||
810 | else: |
|
808 | else: | |
811 | self.concat(dataOut.data) |
|
809 | self.concat(dataOut.data) | |
812 | self.times += 1 |
|
810 | self.times += 1 | |
813 | if self.times > m: |
|
811 | if self.times > m: | |
814 | dataOut.data = self.buffer |
|
812 | dataOut.data = self.buffer | |
815 | self.reset() |
|
813 | self.reset() | |
816 | dataOut.flagNoData = False |
|
814 | dataOut.flagNoData = False | |
817 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas |
|
815 | # se deben actualizar mas propiedades del header y del objeto dataOut, por ejemplo, las alturas | |
818 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
816 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
819 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m |
|
817 | xf = dataOut.heightList[0] + dataOut.nHeights * deltaHeight * m | |
820 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) |
|
818 | dataOut.heightList = numpy.arange(dataOut.heightList[0], xf, deltaHeight) | |
821 | dataOut.ippSeconds *= m |
|
819 | dataOut.ippSeconds *= m | |
822 |
|
820 | |||
823 | class ProfileSelector(Operation): |
|
821 | class ProfileSelector(Operation): | |
824 |
|
822 | |||
825 | profileIndex = None |
|
823 | profileIndex = None | |
826 | # Tamanho total de los perfiles |
|
824 | # Tamanho total de los perfiles | |
827 | nProfiles = None |
|
825 | nProfiles = None | |
828 |
|
826 | |||
829 | def __init__(self, **kwargs): |
|
827 | def __init__(self, **kwargs): | |
830 |
|
828 | |||
831 | Operation.__init__(self, **kwargs) |
|
829 | Operation.__init__(self, **kwargs) | |
832 | self.profileIndex = 0 |
|
830 | self.profileIndex = 0 | |
833 |
|
831 | |||
834 | def incProfileIndex(self): |
|
832 | def incProfileIndex(self): | |
835 |
|
833 | |||
836 | self.profileIndex += 1 |
|
834 | self.profileIndex += 1 | |
837 |
|
835 | |||
838 | if self.profileIndex >= self.nProfiles: |
|
836 | if self.profileIndex >= self.nProfiles: | |
839 | self.profileIndex = 0 |
|
837 | self.profileIndex = 0 | |
840 |
|
838 | |||
841 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): |
|
839 | def isThisProfileInRange(self, profileIndex, minIndex, maxIndex): | |
842 |
|
840 | |||
843 | if profileIndex < minIndex: |
|
841 | if profileIndex < minIndex: | |
844 | return False |
|
842 | return False | |
845 |
|
843 | |||
846 | if profileIndex > maxIndex: |
|
844 | if profileIndex > maxIndex: | |
847 | return False |
|
845 | return False | |
848 |
|
846 | |||
849 | return True |
|
847 | return True | |
850 |
|
848 | |||
851 | def isThisProfileInList(self, profileIndex, profileList): |
|
849 | def isThisProfileInList(self, profileIndex, profileList): | |
852 |
|
850 | |||
853 | if profileIndex not in profileList: |
|
851 | if profileIndex not in profileList: | |
854 | return False |
|
852 | return False | |
855 |
|
853 | |||
856 | return True |
|
854 | return True | |
857 |
|
855 | |||
858 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): |
|
856 | def run(self, dataOut, profileList=None, profileRangeList=None, beam=None, byblock=False, rangeList = None, nProfiles=None): | |
859 |
|
857 | |||
860 | """ |
|
858 | """ | |
861 | ProfileSelector: |
|
859 | ProfileSelector: | |
862 |
|
860 | |||
863 | Inputs: |
|
861 | Inputs: | |
864 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) |
|
862 | profileList : Index of profiles selected. Example: profileList = (0,1,2,7,8) | |
865 |
|
863 | |||
866 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) |
|
864 | profileRangeList : Minimum and maximum profile indexes. Example: profileRangeList = (4, 30) | |
867 |
|
865 | |||
868 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) |
|
866 | rangeList : List of profile ranges. Example: rangeList = ((4, 30), (32, 64), (128, 256)) | |
869 |
|
867 | |||
870 | """ |
|
868 | """ | |
871 |
|
869 | |||
872 | if rangeList is not None: |
|
870 | if rangeList is not None: | |
873 | if type(rangeList[0]) not in (tuple, list): |
|
871 | if type(rangeList[0]) not in (tuple, list): | |
874 | rangeList = [rangeList] |
|
872 | rangeList = [rangeList] | |
875 |
|
873 | |||
876 | dataOut.flagNoData = True |
|
874 | dataOut.flagNoData = True | |
877 |
|
875 | |||
878 | if dataOut.flagDataAsBlock: |
|
876 | if dataOut.flagDataAsBlock: | |
879 | """ |
|
877 | """ | |
880 | data dimension = [nChannels, nProfiles, nHeis] |
|
878 | data dimension = [nChannels, nProfiles, nHeis] | |
881 | """ |
|
879 | """ | |
882 | if profileList != None: |
|
880 | if profileList != None: | |
883 | dataOut.data = dataOut.data[:,profileList,:] |
|
881 | dataOut.data = dataOut.data[:,profileList,:] | |
884 |
|
882 | |||
885 | if profileRangeList != None: |
|
883 | if profileRangeList != None: | |
886 | minIndex = profileRangeList[0] |
|
884 | minIndex = profileRangeList[0] | |
887 | maxIndex = profileRangeList[1] |
|
885 | maxIndex = profileRangeList[1] | |
888 | profileList = range(minIndex, maxIndex+1) |
|
886 | profileList = range(minIndex, maxIndex+1) | |
889 |
|
887 | |||
890 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] |
|
888 | dataOut.data = dataOut.data[:,minIndex:maxIndex+1,:] | |
891 |
|
889 | |||
892 | if rangeList != None: |
|
890 | if rangeList != None: | |
893 |
|
891 | |||
894 | profileList = [] |
|
892 | profileList = [] | |
895 |
|
893 | |||
896 | for thisRange in rangeList: |
|
894 | for thisRange in rangeList: | |
897 | minIndex = thisRange[0] |
|
895 | minIndex = thisRange[0] | |
898 | maxIndex = thisRange[1] |
|
896 | maxIndex = thisRange[1] | |
899 |
|
897 | |||
900 | profileList.extend(range(minIndex, maxIndex+1)) |
|
898 | profileList.extend(range(minIndex, maxIndex+1)) | |
901 |
|
899 | |||
902 | dataOut.data = dataOut.data[:,profileList,:] |
|
900 | dataOut.data = dataOut.data[:,profileList,:] | |
903 |
|
901 | |||
904 | dataOut.nProfiles = len(profileList) |
|
902 | dataOut.nProfiles = len(profileList) | |
905 | dataOut.profileIndex = dataOut.nProfiles - 1 |
|
903 | dataOut.profileIndex = dataOut.nProfiles - 1 | |
906 | dataOut.flagNoData = False |
|
904 | dataOut.flagNoData = False | |
907 |
|
905 | |||
908 | return True |
|
906 | return True | |
909 |
|
907 | |||
910 | """ |
|
908 | """ | |
911 | data dimension = [nChannels, nHeis] |
|
909 | data dimension = [nChannels, nHeis] | |
912 | """ |
|
910 | """ | |
913 |
|
911 | |||
914 | if profileList != None: |
|
912 | if profileList != None: | |
915 |
|
913 | |||
916 | if self.isThisProfileInList(dataOut.profileIndex, profileList): |
|
914 | if self.isThisProfileInList(dataOut.profileIndex, profileList): | |
917 |
|
915 | |||
918 | self.nProfiles = len(profileList) |
|
916 | self.nProfiles = len(profileList) | |
919 | dataOut.nProfiles = self.nProfiles |
|
917 | dataOut.nProfiles = self.nProfiles | |
920 | dataOut.profileIndex = self.profileIndex |
|
918 | dataOut.profileIndex = self.profileIndex | |
921 | dataOut.flagNoData = False |
|
919 | dataOut.flagNoData = False | |
922 |
|
920 | |||
923 | self.incProfileIndex() |
|
921 | self.incProfileIndex() | |
924 | return True |
|
922 | return True | |
925 |
|
923 | |||
926 | if profileRangeList != None: |
|
924 | if profileRangeList != None: | |
927 |
|
925 | |||
928 | minIndex = profileRangeList[0] |
|
926 | minIndex = profileRangeList[0] | |
929 | maxIndex = profileRangeList[1] |
|
927 | maxIndex = profileRangeList[1] | |
930 |
|
928 | |||
931 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
929 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
932 |
|
930 | |||
933 | self.nProfiles = maxIndex - minIndex + 1 |
|
931 | self.nProfiles = maxIndex - minIndex + 1 | |
934 | dataOut.nProfiles = self.nProfiles |
|
932 | dataOut.nProfiles = self.nProfiles | |
935 | dataOut.profileIndex = self.profileIndex |
|
933 | dataOut.profileIndex = self.profileIndex | |
936 | dataOut.flagNoData = False |
|
934 | dataOut.flagNoData = False | |
937 |
|
935 | |||
938 | self.incProfileIndex() |
|
936 | self.incProfileIndex() | |
939 | return True |
|
937 | return True | |
940 |
|
938 | |||
941 | if rangeList != None: |
|
939 | if rangeList != None: | |
942 |
|
940 | |||
943 | nProfiles = 0 |
|
941 | nProfiles = 0 | |
944 |
|
942 | |||
945 | for thisRange in rangeList: |
|
943 | for thisRange in rangeList: | |
946 | minIndex = thisRange[0] |
|
944 | minIndex = thisRange[0] | |
947 | maxIndex = thisRange[1] |
|
945 | maxIndex = thisRange[1] | |
948 |
|
946 | |||
949 | nProfiles += maxIndex - minIndex + 1 |
|
947 | nProfiles += maxIndex - minIndex + 1 | |
950 |
|
948 | |||
951 | for thisRange in rangeList: |
|
949 | for thisRange in rangeList: | |
952 |
|
950 | |||
953 | minIndex = thisRange[0] |
|
951 | minIndex = thisRange[0] | |
954 | maxIndex = thisRange[1] |
|
952 | maxIndex = thisRange[1] | |
955 |
|
953 | |||
956 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): |
|
954 | if self.isThisProfileInRange(dataOut.profileIndex, minIndex, maxIndex): | |
957 |
|
955 | |||
958 | self.nProfiles = nProfiles |
|
956 | self.nProfiles = nProfiles | |
959 | dataOut.nProfiles = self.nProfiles |
|
957 | dataOut.nProfiles = self.nProfiles | |
960 | dataOut.profileIndex = self.profileIndex |
|
958 | dataOut.profileIndex = self.profileIndex | |
961 | dataOut.flagNoData = False |
|
959 | dataOut.flagNoData = False | |
962 |
|
960 | |||
963 | self.incProfileIndex() |
|
961 | self.incProfileIndex() | |
964 |
|
962 | |||
965 | break |
|
963 | break | |
966 |
|
964 | |||
967 | return True |
|
965 | return True | |
968 |
|
966 | |||
969 |
|
967 | |||
970 | if beam != None: #beam is only for AMISR data |
|
968 | if beam != None: #beam is only for AMISR data | |
971 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): |
|
969 | if self.isThisProfileInList(dataOut.profileIndex, dataOut.beamRangeDict[beam]): | |
972 | dataOut.flagNoData = False |
|
970 | dataOut.flagNoData = False | |
973 | dataOut.profileIndex = self.profileIndex |
|
971 | dataOut.profileIndex = self.profileIndex | |
974 |
|
972 | |||
975 | self.incProfileIndex() |
|
973 | self.incProfileIndex() | |
976 |
|
974 | |||
977 | return True |
|
975 | return True | |
978 |
|
976 | |||
979 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" |
|
977 | raise ValueError, "ProfileSelector needs profileList, profileRangeList or rangeList parameter" | |
980 |
|
978 | |||
981 | return False |
|
979 | return False | |
982 |
|
980 | |||
983 | class Reshaper(Operation): |
|
981 | class Reshaper(Operation): | |
984 |
|
982 | |||
985 | def __init__(self, **kwargs): |
|
983 | def __init__(self, **kwargs): | |
986 |
|
984 | |||
987 | Operation.__init__(self, **kwargs) |
|
985 | Operation.__init__(self, **kwargs) | |
988 |
|
986 | |||
989 | self.__buffer = None |
|
987 | self.__buffer = None | |
990 | self.__nitems = 0 |
|
988 | self.__nitems = 0 | |
991 |
|
989 | |||
992 | def __appendProfile(self, dataOut, nTxs): |
|
990 | def __appendProfile(self, dataOut, nTxs): | |
993 |
|
991 | |||
994 | if self.__buffer is None: |
|
992 | if self.__buffer is None: | |
995 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) |
|
993 | shape = (dataOut.nChannels, int(dataOut.nHeights/nTxs) ) | |
996 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) |
|
994 | self.__buffer = numpy.empty(shape, dtype = dataOut.data.dtype) | |
997 |
|
995 | |||
998 | ini = dataOut.nHeights * self.__nitems |
|
996 | ini = dataOut.nHeights * self.__nitems | |
999 | end = ini + dataOut.nHeights |
|
997 | end = ini + dataOut.nHeights | |
1000 |
|
998 | |||
1001 | self.__buffer[:, ini:end] = dataOut.data |
|
999 | self.__buffer[:, ini:end] = dataOut.data | |
1002 |
|
1000 | |||
1003 | self.__nitems += 1 |
|
1001 | self.__nitems += 1 | |
1004 |
|
1002 | |||
1005 | return int(self.__nitems*nTxs) |
|
1003 | return int(self.__nitems*nTxs) | |
1006 |
|
1004 | |||
1007 | def __getBuffer(self): |
|
1005 | def __getBuffer(self): | |
1008 |
|
1006 | |||
1009 | if self.__nitems == int(1./self.__nTxs): |
|
1007 | if self.__nitems == int(1./self.__nTxs): | |
1010 |
|
1008 | |||
1011 | self.__nitems = 0 |
|
1009 | self.__nitems = 0 | |
1012 |
|
1010 | |||
1013 | return self.__buffer.copy() |
|
1011 | return self.__buffer.copy() | |
1014 |
|
1012 | |||
1015 | return None |
|
1013 | return None | |
1016 |
|
1014 | |||
1017 | def __checkInputs(self, dataOut, shape, nTxs): |
|
1015 | def __checkInputs(self, dataOut, shape, nTxs): | |
1018 |
|
1016 | |||
1019 | if shape is None and nTxs is None: |
|
1017 | if shape is None and nTxs is None: | |
1020 | raise ValueError, "Reshaper: shape of factor should be defined" |
|
1018 | raise ValueError, "Reshaper: shape of factor should be defined" | |
1021 |
|
1019 | |||
1022 | if nTxs: |
|
1020 | if nTxs: | |
1023 | if nTxs < 0: |
|
1021 | if nTxs < 0: | |
1024 | raise ValueError, "nTxs should be greater than 0" |
|
1022 | raise ValueError, "nTxs should be greater than 0" | |
1025 |
|
1023 | |||
1026 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: |
|
1024 | if nTxs < 1 and dataOut.nProfiles % (1./nTxs) != 0: | |
1027 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) |
|
1025 | raise ValueError, "nProfiles= %d is not divisibled by (1./nTxs) = %f" %(dataOut.nProfiles, (1./nTxs)) | |
1028 |
|
1026 | |||
1029 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] |
|
1027 | shape = [dataOut.nChannels, dataOut.nProfiles*nTxs, dataOut.nHeights/nTxs] | |
1030 |
|
1028 | |||
1031 | return shape, nTxs |
|
1029 | return shape, nTxs | |
1032 |
|
1030 | |||
1033 | if len(shape) != 2 and len(shape) != 3: |
|
1031 | if len(shape) != 2 and len(shape) != 3: | |
1034 | raise ValueError, "shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights) |
|
1032 | raise ValueError, "shape dimension should be equal to 2 or 3. shape = (nProfiles, nHeis) or (nChannels, nProfiles, nHeis). Actually shape = (%d, %d, %d)" %(dataOut.nChannels, dataOut.nProfiles, dataOut.nHeights) | |
1035 |
|
1033 | |||
1036 | if len(shape) == 2: |
|
1034 | if len(shape) == 2: | |
1037 | shape_tuple = [dataOut.nChannels] |
|
1035 | shape_tuple = [dataOut.nChannels] | |
1038 | shape_tuple.extend(shape) |
|
1036 | shape_tuple.extend(shape) | |
1039 | else: |
|
1037 | else: | |
1040 | shape_tuple = list(shape) |
|
1038 | shape_tuple = list(shape) | |
1041 |
|
1039 | |||
1042 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles |
|
1040 | nTxs = 1.0*shape_tuple[1]/dataOut.nProfiles | |
1043 |
|
1041 | |||
1044 | return shape_tuple, nTxs |
|
1042 | return shape_tuple, nTxs | |
1045 |
|
1043 | |||
1046 | def run(self, dataOut, shape=None, nTxs=None): |
|
1044 | def run(self, dataOut, shape=None, nTxs=None): | |
1047 |
|
1045 | |||
1048 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) |
|
1046 | shape_tuple, self.__nTxs = self.__checkInputs(dataOut, shape, nTxs) | |
1049 |
|
1047 | |||
1050 | dataOut.flagNoData = True |
|
1048 | dataOut.flagNoData = True | |
1051 | profileIndex = None |
|
1049 | profileIndex = None | |
1052 |
|
1050 | |||
1053 | if dataOut.flagDataAsBlock: |
|
1051 | if dataOut.flagDataAsBlock: | |
1054 |
|
1052 | |||
1055 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) |
|
1053 | dataOut.data = numpy.reshape(dataOut.data, shape_tuple) | |
1056 | dataOut.flagNoData = False |
|
1054 | dataOut.flagNoData = False | |
1057 |
|
1055 | |||
1058 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 |
|
1056 | profileIndex = int(dataOut.nProfiles*self.__nTxs) - 1 | |
1059 |
|
1057 | |||
1060 | else: |
|
1058 | else: | |
1061 |
|
1059 | |||
1062 | if self.__nTxs < 1: |
|
1060 | if self.__nTxs < 1: | |
1063 |
|
1061 | |||
1064 | self.__appendProfile(dataOut, self.__nTxs) |
|
1062 | self.__appendProfile(dataOut, self.__nTxs) | |
1065 | new_data = self.__getBuffer() |
|
1063 | new_data = self.__getBuffer() | |
1066 |
|
1064 | |||
1067 | if new_data is not None: |
|
1065 | if new_data is not None: | |
1068 | dataOut.data = new_data |
|
1066 | dataOut.data = new_data | |
1069 | dataOut.flagNoData = False |
|
1067 | dataOut.flagNoData = False | |
1070 |
|
1068 | |||
1071 | profileIndex = dataOut.profileIndex*nTxs |
|
1069 | profileIndex = dataOut.profileIndex*nTxs | |
1072 |
|
1070 | |||
1073 | else: |
|
1071 | else: | |
1074 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" |
|
1072 | raise ValueError, "nTxs should be greater than 0 and lower than 1, or use VoltageReader(..., getblock=True)" | |
1075 |
|
1073 | |||
1076 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1074 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
1077 |
|
1075 | |||
1078 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] |
|
1076 | dataOut.heightList = numpy.arange(dataOut.nHeights/self.__nTxs) * deltaHeight + dataOut.heightList[0] | |
1079 |
|
1077 | |||
1080 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) |
|
1078 | dataOut.nProfiles = int(dataOut.nProfiles*self.__nTxs) | |
1081 |
|
1079 | |||
1082 | dataOut.profileIndex = profileIndex |
|
1080 | dataOut.profileIndex = profileIndex | |
1083 |
|
1081 | |||
1084 | dataOut.ippSeconds /= self.__nTxs |
|
1082 | dataOut.ippSeconds /= self.__nTxs | |
1085 |
|
1083 | |||
1086 | class SplitProfiles(Operation): |
|
1084 | class SplitProfiles(Operation): | |
1087 |
|
1085 | |||
1088 | def __init__(self, **kwargs): |
|
1086 | def __init__(self, **kwargs): | |
1089 |
|
1087 | |||
1090 | Operation.__init__(self, **kwargs) |
|
1088 | Operation.__init__(self, **kwargs) | |
1091 |
|
1089 | |||
1092 | def run(self, dataOut, n): |
|
1090 | def run(self, dataOut, n): | |
1093 |
|
1091 | |||
1094 | dataOut.flagNoData = True |
|
1092 | dataOut.flagNoData = True | |
1095 | profileIndex = None |
|
1093 | profileIndex = None | |
1096 |
|
1094 | |||
1097 | if dataOut.flagDataAsBlock: |
|
1095 | if dataOut.flagDataAsBlock: | |
1098 |
|
1096 | |||
1099 | #nchannels, nprofiles, nsamples |
|
1097 | #nchannels, nprofiles, nsamples | |
1100 | shape = dataOut.data.shape |
|
1098 | shape = dataOut.data.shape | |
1101 |
|
1099 | |||
1102 | if shape[2] % n != 0: |
|
1100 | if shape[2] % n != 0: | |
1103 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) |
|
1101 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[2]) | |
1104 |
|
1102 | |||
1105 | new_shape = shape[0], shape[1]*n, shape[2]/n |
|
1103 | new_shape = shape[0], shape[1]*n, shape[2]/n | |
1106 |
|
1104 | |||
1107 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1105 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
1108 | dataOut.flagNoData = False |
|
1106 | dataOut.flagNoData = False | |
1109 |
|
1107 | |||
1110 | profileIndex = int(dataOut.nProfiles/n) - 1 |
|
1108 | profileIndex = int(dataOut.nProfiles/n) - 1 | |
1111 |
|
1109 | |||
1112 | else: |
|
1110 | else: | |
1113 |
|
1111 | |||
1114 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" |
|
1112 | raise ValueError, "Could not split the data when is read Profile by Profile. Use VoltageReader(..., getblock=True)" | |
1115 |
|
1113 | |||
1116 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1114 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
1117 |
|
1115 | |||
1118 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] |
|
1116 | dataOut.heightList = numpy.arange(dataOut.nHeights/n) * deltaHeight + dataOut.heightList[0] | |
1119 |
|
1117 | |||
1120 | dataOut.nProfiles = int(dataOut.nProfiles*n) |
|
1118 | dataOut.nProfiles = int(dataOut.nProfiles*n) | |
1121 |
|
1119 | |||
1122 | dataOut.profileIndex = profileIndex |
|
1120 | dataOut.profileIndex = profileIndex | |
1123 |
|
1121 | |||
1124 | dataOut.ippSeconds /= n |
|
1122 | dataOut.ippSeconds /= n | |
1125 |
|
1123 | |||
1126 | class CombineProfiles(Operation): |
|
1124 | class CombineProfiles(Operation): | |
1127 | def __init__(self, **kwargs): |
|
1125 | def __init__(self, **kwargs): | |
1128 |
|
1126 | |||
1129 | Operation.__init__(self, **kwargs) |
|
1127 | Operation.__init__(self, **kwargs) | |
1130 |
|
1128 | |||
1131 | self.__remData = None |
|
1129 | self.__remData = None | |
1132 | self.__profileIndex = 0 |
|
1130 | self.__profileIndex = 0 | |
1133 |
|
1131 | |||
1134 | def run(self, dataOut, n): |
|
1132 | def run(self, dataOut, n): | |
1135 |
|
1133 | |||
1136 | dataOut.flagNoData = True |
|
1134 | dataOut.flagNoData = True | |
1137 | profileIndex = None |
|
1135 | profileIndex = None | |
1138 |
|
1136 | |||
1139 | if dataOut.flagDataAsBlock: |
|
1137 | if dataOut.flagDataAsBlock: | |
1140 |
|
1138 | |||
1141 | #nchannels, nprofiles, nsamples |
|
1139 | #nchannels, nprofiles, nsamples | |
1142 | shape = dataOut.data.shape |
|
1140 | shape = dataOut.data.shape | |
1143 | new_shape = shape[0], shape[1]/n, shape[2]*n |
|
1141 | new_shape = shape[0], shape[1]/n, shape[2]*n | |
1144 |
|
1142 | |||
1145 | if shape[1] % n != 0: |
|
1143 | if shape[1] % n != 0: | |
1146 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) |
|
1144 | raise ValueError, "Could not split the data, n=%d has to be multiple of %d" %(n, shape[1]) | |
1147 |
|
1145 | |||
1148 | dataOut.data = numpy.reshape(dataOut.data, new_shape) |
|
1146 | dataOut.data = numpy.reshape(dataOut.data, new_shape) | |
1149 | dataOut.flagNoData = False |
|
1147 | dataOut.flagNoData = False | |
1150 |
|
1148 | |||
1151 | profileIndex = int(dataOut.nProfiles*n) - 1 |
|
1149 | profileIndex = int(dataOut.nProfiles*n) - 1 | |
1152 |
|
1150 | |||
1153 | else: |
|
1151 | else: | |
1154 |
|
1152 | |||
1155 | #nchannels, nsamples |
|
1153 | #nchannels, nsamples | |
1156 | if self.__remData is None: |
|
1154 | if self.__remData is None: | |
1157 | newData = dataOut.data |
|
1155 | newData = dataOut.data | |
1158 | else: |
|
1156 | else: | |
1159 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) |
|
1157 | newData = numpy.concatenate((self.__remData, dataOut.data), axis=1) | |
1160 |
|
1158 | |||
1161 | self.__profileIndex += 1 |
|
1159 | self.__profileIndex += 1 | |
1162 |
|
1160 | |||
1163 | if self.__profileIndex < n: |
|
1161 | if self.__profileIndex < n: | |
1164 | self.__remData = newData |
|
1162 | self.__remData = newData | |
1165 | #continue |
|
1163 | #continue | |
1166 | return |
|
1164 | return | |
1167 |
|
1165 | |||
1168 | self.__profileIndex = 0 |
|
1166 | self.__profileIndex = 0 | |
1169 | self.__remData = None |
|
1167 | self.__remData = None | |
1170 |
|
1168 | |||
1171 | dataOut.data = newData |
|
1169 | dataOut.data = newData | |
1172 | dataOut.flagNoData = False |
|
1170 | dataOut.flagNoData = False | |
1173 |
|
1171 | |||
1174 | profileIndex = dataOut.profileIndex/n |
|
1172 | profileIndex = dataOut.profileIndex/n | |
1175 |
|
1173 | |||
1176 |
|
1174 | |||
1177 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1175 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
1178 |
|
1176 | |||
1179 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] |
|
1177 | dataOut.heightList = numpy.arange(dataOut.nHeights*n) * deltaHeight + dataOut.heightList[0] | |
1180 |
|
1178 | |||
1181 | dataOut.nProfiles = int(dataOut.nProfiles/n) |
|
1179 | dataOut.nProfiles = int(dataOut.nProfiles/n) | |
1182 |
|
1180 | |||
1183 | dataOut.profileIndex = profileIndex |
|
1181 | dataOut.profileIndex = profileIndex | |
1184 |
|
1182 | |||
1185 | dataOut.ippSeconds *= n |
|
1183 | dataOut.ippSeconds *= n | |
1186 |
|
1184 | |||
1187 | # import collections |
|
1185 | # import collections | |
1188 | # from scipy.stats import mode |
|
1186 | # from scipy.stats import mode | |
1189 | # |
|
1187 | # | |
1190 | # class Synchronize(Operation): |
|
1188 | # class Synchronize(Operation): | |
1191 | # |
|
1189 | # | |
1192 | # isConfig = False |
|
1190 | # isConfig = False | |
1193 | # __profIndex = 0 |
|
1191 | # __profIndex = 0 | |
1194 | # |
|
1192 | # | |
1195 | # def __init__(self, **kwargs): |
|
1193 | # def __init__(self, **kwargs): | |
1196 | # |
|
1194 | # | |
1197 | # Operation.__init__(self, **kwargs) |
|
1195 | # Operation.__init__(self, **kwargs) | |
1198 | # # self.isConfig = False |
|
1196 | # # self.isConfig = False | |
1199 | # self.__powBuffer = None |
|
1197 | # self.__powBuffer = None | |
1200 | # self.__startIndex = 0 |
|
1198 | # self.__startIndex = 0 | |
1201 | # self.__pulseFound = False |
|
1199 | # self.__pulseFound = False | |
1202 | # |
|
1200 | # | |
1203 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): |
|
1201 | # def __findTxPulse(self, dataOut, channel=0, pulse_with = None): | |
1204 | # |
|
1202 | # | |
1205 | # #Read data |
|
1203 | # #Read data | |
1206 | # |
|
1204 | # | |
1207 | # powerdB = dataOut.getPower(channel = channel) |
|
1205 | # powerdB = dataOut.getPower(channel = channel) | |
1208 | # noisedB = dataOut.getNoise(channel = channel)[0] |
|
1206 | # noisedB = dataOut.getNoise(channel = channel)[0] | |
1209 | # |
|
1207 | # | |
1210 | # self.__powBuffer.extend(powerdB.flatten()) |
|
1208 | # self.__powBuffer.extend(powerdB.flatten()) | |
1211 | # |
|
1209 | # | |
1212 | # dataArray = numpy.array(self.__powBuffer) |
|
1210 | # dataArray = numpy.array(self.__powBuffer) | |
1213 | # |
|
1211 | # | |
1214 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") |
|
1212 | # filteredPower = numpy.correlate(dataArray, dataArray[0:self.__nSamples], "same") | |
1215 | # |
|
1213 | # | |
1216 | # maxValue = numpy.nanmax(filteredPower) |
|
1214 | # maxValue = numpy.nanmax(filteredPower) | |
1217 | # |
|
1215 | # | |
1218 | # if maxValue < noisedB + 10: |
|
1216 | # if maxValue < noisedB + 10: | |
1219 | # #No se encuentra ningun pulso de transmision |
|
1217 | # #No se encuentra ningun pulso de transmision | |
1220 | # return None |
|
1218 | # return None | |
1221 | # |
|
1219 | # | |
1222 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] |
|
1220 | # maxValuesIndex = numpy.where(filteredPower > maxValue - 0.1*abs(maxValue))[0] | |
1223 | # |
|
1221 | # | |
1224 | # if len(maxValuesIndex) < 2: |
|
1222 | # if len(maxValuesIndex) < 2: | |
1225 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX |
|
1223 | # #Solo se encontro un solo pulso de transmision de un baudio, esperando por el siguiente TX | |
1226 | # return None |
|
1224 | # return None | |
1227 | # |
|
1225 | # | |
1228 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples |
|
1226 | # phasedMaxValuesIndex = maxValuesIndex - self.__nSamples | |
1229 | # |
|
1227 | # | |
1230 | # #Seleccionar solo valores con un espaciamiento de nSamples |
|
1228 | # #Seleccionar solo valores con un espaciamiento de nSamples | |
1231 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) |
|
1229 | # pulseIndex = numpy.intersect1d(maxValuesIndex, phasedMaxValuesIndex) | |
1232 | # |
|
1230 | # | |
1233 | # if len(pulseIndex) < 2: |
|
1231 | # if len(pulseIndex) < 2: | |
1234 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1232 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
1235 | # return None |
|
1233 | # return None | |
1236 | # |
|
1234 | # | |
1237 | # spacing = pulseIndex[1:] - pulseIndex[:-1] |
|
1235 | # spacing = pulseIndex[1:] - pulseIndex[:-1] | |
1238 | # |
|
1236 | # | |
1239 | # #remover senales que se distancien menos de 10 unidades o muestras |
|
1237 | # #remover senales que se distancien menos de 10 unidades o muestras | |
1240 | # #(No deberian existir IPP menor a 10 unidades) |
|
1238 | # #(No deberian existir IPP menor a 10 unidades) | |
1241 | # |
|
1239 | # | |
1242 | # realIndex = numpy.where(spacing > 10 )[0] |
|
1240 | # realIndex = numpy.where(spacing > 10 )[0] | |
1243 | # |
|
1241 | # | |
1244 | # if len(realIndex) < 2: |
|
1242 | # if len(realIndex) < 2: | |
1245 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 |
|
1243 | # #Solo se encontro un pulso de transmision con ancho mayor a 1 | |
1246 | # return None |
|
1244 | # return None | |
1247 | # |
|
1245 | # | |
1248 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) |
|
1246 | # #Eliminar pulsos anchos (deja solo la diferencia entre IPPs) | |
1249 | # realPulseIndex = pulseIndex[realIndex] |
|
1247 | # realPulseIndex = pulseIndex[realIndex] | |
1250 | # |
|
1248 | # | |
1251 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] |
|
1249 | # period = mode(realPulseIndex[1:] - realPulseIndex[:-1])[0][0] | |
1252 | # |
|
1250 | # | |
1253 | # print "IPP = %d samples" %period |
|
1251 | # print "IPP = %d samples" %period | |
1254 | # |
|
1252 | # | |
1255 | # self.__newNSamples = dataOut.nHeights #int(period) |
|
1253 | # self.__newNSamples = dataOut.nHeights #int(period) | |
1256 | # self.__startIndex = int(realPulseIndex[0]) |
|
1254 | # self.__startIndex = int(realPulseIndex[0]) | |
1257 | # |
|
1255 | # | |
1258 | # return 1 |
|
1256 | # return 1 | |
1259 | # |
|
1257 | # | |
1260 | # |
|
1258 | # | |
1261 | # def setup(self, nSamples, nChannels, buffer_size = 4): |
|
1259 | # def setup(self, nSamples, nChannels, buffer_size = 4): | |
1262 | # |
|
1260 | # | |
1263 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), |
|
1261 | # self.__powBuffer = collections.deque(numpy.zeros( buffer_size*nSamples,dtype=numpy.float), | |
1264 | # maxlen = buffer_size*nSamples) |
|
1262 | # maxlen = buffer_size*nSamples) | |
1265 | # |
|
1263 | # | |
1266 | # bufferList = [] |
|
1264 | # bufferList = [] | |
1267 | # |
|
1265 | # | |
1268 | # for i in range(nChannels): |
|
1266 | # for i in range(nChannels): | |
1269 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, |
|
1267 | # bufferByChannel = collections.deque(numpy.zeros( buffer_size*nSamples, dtype=numpy.complex) + numpy.NAN, | |
1270 | # maxlen = buffer_size*nSamples) |
|
1268 | # maxlen = buffer_size*nSamples) | |
1271 | # |
|
1269 | # | |
1272 | # bufferList.append(bufferByChannel) |
|
1270 | # bufferList.append(bufferByChannel) | |
1273 | # |
|
1271 | # | |
1274 | # self.__nSamples = nSamples |
|
1272 | # self.__nSamples = nSamples | |
1275 | # self.__nChannels = nChannels |
|
1273 | # self.__nChannels = nChannels | |
1276 | # self.__bufferList = bufferList |
|
1274 | # self.__bufferList = bufferList | |
1277 | # |
|
1275 | # | |
1278 | # def run(self, dataOut, channel = 0): |
|
1276 | # def run(self, dataOut, channel = 0): | |
1279 | # |
|
1277 | # | |
1280 | # if not self.isConfig: |
|
1278 | # if not self.isConfig: | |
1281 | # nSamples = dataOut.nHeights |
|
1279 | # nSamples = dataOut.nHeights | |
1282 | # nChannels = dataOut.nChannels |
|
1280 | # nChannels = dataOut.nChannels | |
1283 | # self.setup(nSamples, nChannels) |
|
1281 | # self.setup(nSamples, nChannels) | |
1284 | # self.isConfig = True |
|
1282 | # self.isConfig = True | |
1285 | # |
|
1283 | # | |
1286 | # #Append new data to internal buffer |
|
1284 | # #Append new data to internal buffer | |
1287 | # for thisChannel in range(self.__nChannels): |
|
1285 | # for thisChannel in range(self.__nChannels): | |
1288 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1286 | # bufferByChannel = self.__bufferList[thisChannel] | |
1289 | # bufferByChannel.extend(dataOut.data[thisChannel]) |
|
1287 | # bufferByChannel.extend(dataOut.data[thisChannel]) | |
1290 | # |
|
1288 | # | |
1291 | # if self.__pulseFound: |
|
1289 | # if self.__pulseFound: | |
1292 | # self.__startIndex -= self.__nSamples |
|
1290 | # self.__startIndex -= self.__nSamples | |
1293 | # |
|
1291 | # | |
1294 | # #Finding Tx Pulse |
|
1292 | # #Finding Tx Pulse | |
1295 | # if not self.__pulseFound: |
|
1293 | # if not self.__pulseFound: | |
1296 | # indexFound = self.__findTxPulse(dataOut, channel) |
|
1294 | # indexFound = self.__findTxPulse(dataOut, channel) | |
1297 | # |
|
1295 | # | |
1298 | # if indexFound == None: |
|
1296 | # if indexFound == None: | |
1299 | # dataOut.flagNoData = True |
|
1297 | # dataOut.flagNoData = True | |
1300 | # return |
|
1298 | # return | |
1301 | # |
|
1299 | # | |
1302 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) |
|
1300 | # self.__arrayBuffer = numpy.zeros((self.__nChannels, self.__newNSamples), dtype = numpy.complex) | |
1303 | # self.__pulseFound = True |
|
1301 | # self.__pulseFound = True | |
1304 | # self.__startIndex = indexFound |
|
1302 | # self.__startIndex = indexFound | |
1305 | # |
|
1303 | # | |
1306 | # #If pulse was found ... |
|
1304 | # #If pulse was found ... | |
1307 | # for thisChannel in range(self.__nChannels): |
|
1305 | # for thisChannel in range(self.__nChannels): | |
1308 | # bufferByChannel = self.__bufferList[thisChannel] |
|
1306 | # bufferByChannel = self.__bufferList[thisChannel] | |
1309 | # #print self.__startIndex |
|
1307 | # #print self.__startIndex | |
1310 | # x = numpy.array(bufferByChannel) |
|
1308 | # x = numpy.array(bufferByChannel) | |
1311 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] |
|
1309 | # self.__arrayBuffer[thisChannel] = x[self.__startIndex:self.__startIndex+self.__newNSamples] | |
1312 | # |
|
1310 | # | |
1313 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
1311 | # deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] | |
1314 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight |
|
1312 | # dataOut.heightList = numpy.arange(self.__newNSamples)*deltaHeight | |
1315 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 |
|
1313 | # # dataOut.ippSeconds = (self.__newNSamples / deltaHeight)/1e6 | |
1316 | # |
|
1314 | # | |
1317 | # dataOut.data = self.__arrayBuffer |
|
1315 | # dataOut.data = self.__arrayBuffer | |
1318 | # |
|
1316 | # | |
1319 | # self.__startIndex += self.__newNSamples |
|
1317 | # self.__startIndex += self.__newNSamples | |
1320 | # |
|
1318 | # | |
1321 | # return |
|
1319 | # return |
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