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1 | ''' | |
|
2 | ||
|
3 | $Author: murco $ | |
|
4 | $Id: JROHeaderIO.py 151 2012-10-31 19:00:51Z murco $ | |
|
5 | ''' | |
|
6 | import sys | |
|
7 | import numpy | |
|
8 | import copy | |
|
9 | import datetime | |
|
10 | from __builtin__ import None | |
|
11 | ||
|
12 | SPEED_OF_LIGHT = 299792458 | |
|
13 | SPEED_OF_LIGHT = 3e8 | |
|
14 | ||
|
15 | FILE_STRUCTURE = numpy.dtype([ #HEADER 48bytes | |
|
16 | ('FileMgcNumber','<u4'), #0x23020100 | |
|
17 | ('nFDTdataRecors','<u4'), #No Of FDT data records in this file (0 or more) | |
|
18 | ('RadarUnitId','<u4'), | |
|
19 | ('SiteName','<s32'), #Null terminated | |
|
20 | ]) | |
|
21 | ||
|
22 | RECORD_STRUCTURE = numpy.dtype([ #RECORD HEADER 180+20N bytes | |
|
23 | ('RecMgcNumber','<u4'), #0x23030001 | |
|
24 | ('RecCounter','<u4'), #Record counter(0,1, ...) | |
|
25 | ('Off2StartNxtRec','<u4'), #Offset to start of next record form start of this record | |
|
26 | ('Off2StartData','<u4'), #Offset to start of data from start of this record | |
|
27 | ('EpTimeStamp','<i4'), #Epoch time stamp of start of acquisition (seconds) | |
|
28 | ('msCompTimeStamp','<u4'), #Millisecond component of time stamp (0,...,999) | |
|
29 | ('ExpTagName','<s32'), #Experiment tag name (null terminated) | |
|
30 | ('ExpComment','<s32'), #Experiment comment (null terminated) | |
|
31 | ('SiteLatDegrees','<f4'), #Site latitude (from GPS) in degrees (positive implies North) | |
|
32 | ('SiteLongDegrees','<f4'), #Site longitude (from GPS) in degrees (positive implies East) | |
|
33 | ('RTCgpsStatus','<u4'), #RTC GPS engine status (0=SEEK, 1=LOCK, 2=NOT FITTED, 3=UNAVAILABLE) | |
|
34 | ('TransmitFrec','<u4'), #Transmit frequency (Hz) | |
|
35 | ('ReceiveFrec','<u4'), #Receive frequency | |
|
36 | ('FirstOsciFrec','<u4'), #First local oscillator frequency (Hz) | |
|
37 | ('Polarisation','<u4'), #(0="O", 1="E", 2="linear 1", 3="linear2") | |
|
38 | ('ReceiverFiltSett','<u4'), #Receiver filter settings (0,1,2,3) | |
|
39 | ('nModesInUse','<u4'), #Number of modes in use (1 or 2) | |
|
40 | ('DualModeIndex','<u4'), #Dual Mode index number for these data (0 or 1) | |
|
41 | ('DualModeRange','<u4'), #Dual Mode range correction for these data (m) | |
|
42 | ('nDigChannels','<u4'), #Number of digital channels acquired (2*N) | |
|
43 | ('SampResolution','<u4'), #Sampling resolution (meters) | |
|
44 | ('nRangeGatesSamp','<u4'), #Number of range gates sampled | |
|
45 | ('StartRangeSamp','<u4'), #Start range of sampling (meters) | |
|
46 | ('PRFhz','<u4'), #PRF (Hz) | |
|
47 | ('Integrations','<u4'), #Integrations | |
|
48 | ('nDataPointsTrsf','<u4'), #Number of data points transformed | |
|
49 | ('nReceiveBeams','<u4'), #Number of receive beams stored in file (1 or N) | |
|
50 | ('nSpectAverages','<u4'), #Number of spectral averages | |
|
51 | ('FFTwindowingInd','<u4'), #FFT windowing index (0 = no window) | |
|
52 | ('BeamAngleAzim','<f4'), #Beam steer angle (azimuth) in degrees (clockwise from true North) | |
|
53 | ('BeamAngleZen','<f4'), #Beam steer angle (zenith) in degrees (0=> vertical) | |
|
54 | ('AntennaCoord','<f24'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
55 | ('RecPhaseCalibr','<f12'), #Receiver phase calibration (degrees) - N values | |
|
56 | ('RecAmpCalibr','<f12'), #Receiver amplitude calibration (ratio relative to receiver one) - N values | |
|
57 | ('ReceiverGaindB','<u12'), #Receiver gains in dB - N values | |
|
58 | ]) | |
|
59 | ||
|
60 | ||
|
61 | class Header(object): | |
|
62 | ||
|
63 | def __init__(self): | |
|
64 | raise NotImplementedError | |
|
65 | ||
|
66 | ||
|
67 | def read(self): | |
|
68 | ||
|
69 | raise NotImplementedError | |
|
70 | ||
|
71 | def write(self): | |
|
72 | ||
|
73 | raise NotImplementedError | |
|
74 | ||
|
75 | def printInfo(self): | |
|
76 | ||
|
77 | message = "#"*50 + "\n" | |
|
78 | message += self.__class__.__name__.upper() + "\n" | |
|
79 | message += "#"*50 + "\n" | |
|
80 | ||
|
81 | keyList = self.__dict__.keys() | |
|
82 | keyList.sort() | |
|
83 | ||
|
84 | for key in keyList: | |
|
85 | message += "%s = %s" %(key, self.__dict__[key]) + "\n" | |
|
86 | ||
|
87 | if "size" not in keyList: | |
|
88 | attr = getattr(self, "size") | |
|
89 | ||
|
90 | if attr: | |
|
91 | message += "%s = %s" %("size", attr) + "\n" | |
|
92 | ||
|
93 | print message | |
|
94 | ||
|
95 | class FileHeader(Header): | |
|
96 | ||
|
97 | FileMgcNumber= None | |
|
98 | nFDTdataRecors=None #No Of FDT data records in this file (0 or more) | |
|
99 | RadarUnitId= None | |
|
100 | SiteName= None | |
|
101 | ||
|
102 | #__LOCALTIME = None | |
|
103 | ||
|
104 | def __init__(self, useLocalTime=True): | |
|
105 | ||
|
106 | self.FileMgcNumber= 0 #0x23020100 | |
|
107 | self.nFDTdataRecors=0 #No Of FDT data records in this file (0 or more) | |
|
108 | self.RadarUnitId= 0 | |
|
109 | self.SiteName= "" | |
|
110 | self.size = 48 | |
|
111 | ||
|
112 | #self.useLocalTime = useLocalTime | |
|
113 | ||
|
114 | def read(self, fp): | |
|
115 | ||
|
116 | try: | |
|
117 | header = numpy.fromfile(fp, FILE_STRUCTURE,1) | |
|
118 | ''' numpy.fromfile(file, dtype, count, sep='') | |
|
119 | file : file or str | |
|
120 | Open file object or filename. | |
|
121 | ||
|
122 | dtype : data-type | |
|
123 | Data type of the returned array. For binary files, it is used to determine | |
|
124 | the size and byte-order of the items in the file. | |
|
125 | ||
|
126 | count : int | |
|
127 | Number of items to read. -1 means all items (i.e., the complete file). | |
|
128 | ||
|
129 | sep : str | |
|
130 | Separator between items if file is a text file. Empty (“”) separator means | |
|
131 | the file should be treated as binary. Spaces (” ”) in the separator match zero | |
|
132 | or more whitespace characters. A separator consisting only of spaces must match | |
|
133 | at least one whitespace. | |
|
134 | ||
|
135 | ''' | |
|
136 | ||
|
137 | except Exception, e: | |
|
138 | print "FileHeader: " | |
|
139 | print eBasicHeader | |
|
140 | return 0 | |
|
141 | ||
|
142 | self.FileMgcNumber= byte(header['FileMgcNumber'][0]) | |
|
143 | self.nFDTdataRecors=int(header['nFDTdataRecors'][0]) #No Of FDT data records in this file (0 or more) | |
|
144 | self.RadarUnitId= int(header['RadarUnitId'][0]) | |
|
145 | self.SiteName= char(header['SiteName'][0]) | |
|
146 | ||
|
147 | ||
|
148 | if self.size <48: | |
|
149 | return 0 | |
|
150 | ||
|
151 | return 1 | |
|
152 | ||
|
153 | def write(self, fp): | |
|
154 | ||
|
155 | headerTuple = (self.FileMgcNumber, | |
|
156 | self.nFDTdataRecors, | |
|
157 | self.RadarUnitId, | |
|
158 | self.SiteName, | |
|
159 | self.size) | |
|
160 | ||
|
161 | ||
|
162 | header = numpy.array(headerTuple, FILE_STRUCTURE) | |
|
163 | # numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0) | |
|
164 | header.tofile(fp) | |
|
165 | ''' ndarray.tofile(fid, sep, format) Write array to a file as text or binary (default). | |
|
166 | ||
|
167 | fid : file or str | |
|
168 | An open file object, or a string containing a filename. | |
|
169 | ||
|
170 | sep : str | |
|
171 | Separator between array items for text output. If “” (empty), a binary file is written, | |
|
172 | equivalent to file.write(a.tobytes()). | |
|
173 | ||
|
174 | format : str | |
|
175 | Format string for text file output. Each entry in the array is formatted to text by | |
|
176 | first converting it to the closest Python type, and then using “format” % item. | |
|
177 | ||
|
178 | ''' | |
|
179 | ||
|
180 | return 1 | |
|
181 | ||
|
182 | ||
|
183 | class RecordHeader(Header): | |
|
184 | ||
|
185 | RecMgcNumber=None #0x23030001 | |
|
186 | RecCounter= None | |
|
187 | Off2StartNxtRec= None | |
|
188 | EpTimeStamp= None | |
|
189 | msCompTimeStamp= None | |
|
190 | ExpTagName= None | |
|
191 | ExpComment=None | |
|
192 | SiteLatDegrees=None | |
|
193 | SiteLongDegrees= None | |
|
194 | RTCgpsStatus= None | |
|
195 | TransmitFrec= None | |
|
196 | ReceiveFrec= None | |
|
197 | FirstOsciFrec= None | |
|
198 | Polarisation= None | |
|
199 | ReceiverFiltSett= None | |
|
200 | nModesInUse= None | |
|
201 | DualModeIndex= None | |
|
202 | DualModeRange= None | |
|
203 | nDigChannels= None | |
|
204 | SampResolution= None | |
|
205 | nRangeGatesSamp= None | |
|
206 | StartRangeSamp= None | |
|
207 | PRFhz= None | |
|
208 | Integrations= None | |
|
209 | nDataPointsTrsf= None | |
|
210 | nReceiveBeams= None | |
|
211 | nSpectAverages= None | |
|
212 | FFTwindowingInd= None | |
|
213 | BeamAngleAzim= None | |
|
214 | BeamAngleZen= None | |
|
215 | AntennaCoord= None | |
|
216 | RecPhaseCalibr= None | |
|
217 | RecAmpCalibr= None | |
|
218 | ReceiverGaindB= None | |
|
219 | ||
|
220 | '''size = None | |
|
221 | nSamples = None | |
|
222 | nProfiles = None | |
|
223 | nChannels = None | |
|
224 | adcResolution = None | |
|
225 | pciDioBusWidth = None''' | |
|
226 | ||
|
227 | def __init__(self, RecMgcNumber=None, RecCounter= 0, Off2StartNxtRec= 0, | |
|
228 | EpTimeStamp= 0, msCompTimeStamp= 0, ExpTagName= None, | |
|
229 | ExpComment=None, SiteLatDegrees=0, SiteLongDegrees= 0, | |
|
230 | RTCgpsStatus= 0, TransmitFrec= 0, ReceiveFrec= 0, | |
|
231 | FirstOsciFrec= 0, Polarisation= 0, ReceiverFiltSett= 0, | |
|
232 | nModesInUse= 0, DualModeIndex= 0, DualModeRange= 0, | |
|
233 | nDigChannels= 0, SampResolution= 0, nRangeGatesSamp= 0, | |
|
234 | StartRangeSamp= 0, PRFhz= 0, Integrations= 0, | |
|
235 | nDataPointsTrsf= 0, nReceiveBeams= 0, nSpectAverages= 0, | |
|
236 | FFTwindowingInd= 0, BeamAngleAzim= 0, BeamAngleZen= 0, | |
|
237 | AntennaCoord= 0, RecPhaseCalibr= 0, RecAmpCalibr= 0, | |
|
238 | ReceiverGaindB= 0): | |
|
239 | ||
|
240 | self.RecMgcNumber = RecMgcNumber #0x23030001 | |
|
241 | self.RecCounter = RecCounter | |
|
242 | self.Off2StartNxtRec = Off2StartNxtRec | |
|
243 | self.EpTimeStamp = EpTimeStamp | |
|
244 | self.msCompTimeStamp = msCompTimeStamp | |
|
245 | self.ExpTagName = ExpTagName | |
|
246 | self.ExpComment = ExpComment | |
|
247 | self.SiteLatDegrees = SiteLatDegrees | |
|
248 | self.SiteLongDegrees = SiteLongDegrees | |
|
249 | self.RTCgpsStatus = RTCgpsStatus | |
|
250 | self.TransmitFrec = TransmitFrec | |
|
251 | self.ReceiveFrec = ReceiveFrec | |
|
252 | self.FirstOsciFrec = FirstOsciFrec | |
|
253 | self.Polarisation = Polarisation | |
|
254 | self.ReceiverFiltSett = ReceiverFiltSett | |
|
255 | self.nModesInUse = nModesInUse | |
|
256 | self.DualModeIndex = DualModeIndex | |
|
257 | self.DualModeRange = DualModeRange | |
|
258 | self.nDigChannels = nDigChannels | |
|
259 | self.SampResolution = SampResolution | |
|
260 | self.nRangeGatesSamp = nRangeGatesSamp | |
|
261 | self.StartRangeSamp = StartRangeSamp | |
|
262 | self.PRFhz = PRFhz | |
|
263 | self.Integrations = Integrations | |
|
264 | self.nDataPointsTrsf = nDataPointsTrsf | |
|
265 | self.nReceiveBeams = nReceiveBeams | |
|
266 | self.nSpectAverages = nSpectAverages | |
|
267 | self.FFTwindowingInd = FFTwindowingInd | |
|
268 | self.BeamAngleAzim = BeamAngleAzim | |
|
269 | self.BeamAngleZen = BeamAngleZen | |
|
270 | self.AntennaCoord = AntennaCoord | |
|
271 | self.RecPhaseCalibr = RecPhaseCalibr | |
|
272 | self.RecAmpCalibr = RecAmpCalibr | |
|
273 | self.ReceiverGaindB = ReceiverGaindB | |
|
274 | ||
|
275 | ||
|
276 | def read(self, fp): | |
|
277 | ||
|
278 | startFp = fp.tell() #The method tell() returns the current position of the file read/write pointer within the file. | |
|
279 | ||
|
280 | try: | |
|
281 | header = numpy.fromfile(fp,RECORD_STRUCTURE,1) | |
|
282 | except Exception, e: | |
|
283 | print "System Header: " + e | |
|
284 | return 0 | |
|
285 | ||
|
286 | self.RecMgcNumber = header['RecMgcNumber'][0] #0x23030001 | |
|
287 | self.RecCounter = header['RecCounter'][0] | |
|
288 | self.Off2StartNxtRec = header['Off2StartNxtRec'][0] | |
|
289 | self.EpTimeStamp = header['EpTimeStamp'][0] | |
|
290 | self.msCompTimeStamp = header['msCompTimeStamp'][0] | |
|
291 | self.ExpTagName = header['ExpTagName'][0] | |
|
292 | self.ExpComment = header['ExpComment'][0] | |
|
293 | self.SiteLatDegrees = header['SiteLatDegrees'][0] | |
|
294 | self.SiteLongDegrees = header['SiteLongDegrees'][0] | |
|
295 | self.RTCgpsStatus = header['RTCgpsStatus'][0] | |
|
296 | self.TransmitFrec = header['TransmitFrec'][0] | |
|
297 | self.ReceiveFrec = header['ReceiveFrec'][0] | |
|
298 | self.FirstOsciFrec = header['FirstOsciFrec'][0] | |
|
299 | self.Polarisation = header['Polarisation'][0] | |
|
300 | self.ReceiverFiltSett = header['ReceiverFiltSett'][0] | |
|
301 | self.nModesInUse = header['nModesInUse'][0] | |
|
302 | self.DualModeIndex = header['DualModeIndex'][0] | |
|
303 | self.DualModeRange = header['DualModeRange'][0] | |
|
304 | self.nDigChannels = header['nDigChannels'][0] | |
|
305 | self.SampResolution = header['SampResolution'][0] | |
|
306 | self.nRangeGatesSamp = header['nRangeGatesSamp'][0] | |
|
307 | self.StartRangeSamp = header['StartRangeSamp'][0] | |
|
308 | self.PRFhz = header['PRFhz'][0] | |
|
309 | self.Integrations = header['Integrations'][0] | |
|
310 | self.nDataPointsTrsf = header['nDataPointsTrsf'][0] | |
|
311 | self.nReceiveBeams = header['nReceiveBeams'][0] | |
|
312 | self.nSpectAverages = header['nSpectAverages'][0] | |
|
313 | self.FFTwindowingInd = header['FFTwindowingInd'][0] | |
|
314 | self.BeamAngleAzim = header['BeamAngleAzim'][0] | |
|
315 | self.BeamAngleZen = header['BeamAngleZen'][0] | |
|
316 | self.AntennaCoord = header['AntennaCoord'][0] | |
|
317 | self.RecPhaseCalibr = header['RecPhaseCalibr'][0] | |
|
318 | self.RecAmpCalibr = header['RecAmpCalibr'][0] | |
|
319 | self.ReceiverGaindB = header['ReceiverGaindB'][0] | |
|
320 | ||
|
321 | Self.size = 180+20*3 | |
|
322 | ||
|
323 | endFp = self.size + startFp | |
|
324 | ||
|
325 | if fp.tell() > endFp: | |
|
326 | sys.stderr.write("Warning %s: Size value read from System Header is lower than it has to be\n" %fp.name) | |
|
327 | return 0 | |
|
328 | ||
|
329 | if fp.tell() < endFp: | |
|
330 | sys.stderr.write("Warning %s: Size value read from System Header size is greater than it has to be\n" %fp.name) | |
|
331 | return 0 | |
|
332 | ||
|
333 | return 1 | |
|
334 | ||
|
335 | def write(self, fp): | |
|
336 | ||
|
337 | headerTuple = (self.RecMgcNumber, | |
|
338 | self.RecCounter, | |
|
339 | self.Off2StartNxtRec, | |
|
340 | self.EpTimeStamp, | |
|
341 | self.msCompTimeStamp, | |
|
342 | self.ExpTagName, | |
|
343 | self.ExpComment, | |
|
344 | self.SiteLatDegrees, | |
|
345 | self.SiteLongDegrees, | |
|
346 | self.RTCgpsStatus, | |
|
347 | self.TransmitFrec, | |
|
348 | self.ReceiveFrec, | |
|
349 | self.FirstOsciFrec, | |
|
350 | self.Polarisation, | |
|
351 | self.ReceiverFiltSett, | |
|
352 | self.nModesInUse, | |
|
353 | self.DualModeIndex, | |
|
354 | self.DualModeRange, | |
|
355 | self.nDigChannels, | |
|
356 | self.SampResolution, | |
|
357 | self.nRangeGatesSamp, | |
|
358 | self.StartRangeSamp, | |
|
359 | self.PRFhz, | |
|
360 | self.Integrations, | |
|
361 | self.nDataPointsTrsf, | |
|
362 | self.nReceiveBeams, | |
|
363 | self.nSpectAverages, | |
|
364 | self.FFTwindowingInd, | |
|
365 | self.BeamAngleAzim, | |
|
366 | self.BeamAngleZen, | |
|
367 | self.AntennaCoord, | |
|
368 | self.RecPhaseCalibr, | |
|
369 | self.RecAmpCalibr, | |
|
370 | self.ReceiverGaindB) | |
|
371 | ||
|
372 | # self.size,self.nSamples, | |
|
373 | # self.nProfiles, | |
|
374 | # self.nChannels, | |
|
375 | # self.adcResolution, | |
|
376 | # self.pciDioBusWidth | |
|
377 | ||
|
378 | header = numpy.array(headerTuple,RECORD_STRUCTURE) | |
|
379 | header.tofile(fp) | |
|
380 | ||
|
381 | return 1 | |
|
382 | ||
|
383 | ||
|
384 | def get_dtype_index(numpy_dtype): | |
|
385 | ||
|
386 | index = None | |
|
387 | ||
|
388 | for i in range(len(NUMPY_DTYPE_LIST)): | |
|
389 | if numpy_dtype == NUMPY_DTYPE_LIST[i]: | |
|
390 | index = i | |
|
391 | break | |
|
392 | ||
|
393 | return index | |
|
394 | ||
|
395 | def get_numpy_dtype(index): | |
|
396 | ||
|
397 | #dtype4 = numpy.dtype([('real','<f4'),('imag','<f4')]) | |
|
398 | ||
|
399 | return NUMPY_DTYPE_LIST[index] | |
|
400 | ||
|
401 | ||
|
402 | def get_dtype_width(index): | |
|
403 | ||
|
404 | return DTYPE_WIDTH[index] No newline at end of file |
@@ -0,0 +1,469 | |||
|
1 | import numpy | |
|
2 | import datetime | |
|
3 | import sys | |
|
4 | import matplotlib | |
|
5 | ||
|
6 | if 'linux' in sys.platform: | |
|
7 | matplotlib.use("TKAgg") | |
|
8 | ||
|
9 | if 'darwin' in sys.platform: | |
|
10 | matplotlib.use('TKAgg') | |
|
11 | #Qt4Agg', 'GTK', 'GTKAgg', 'ps', 'agg', 'cairo', 'MacOSX', 'GTKCairo', 'WXAgg', 'template', 'TkAgg', 'GTK3Cairo', 'GTK3Agg', 'svg', 'WebAgg', 'CocoaAgg', 'emf', 'gdk', 'WX' | |
|
12 | import matplotlib.pyplot | |
|
13 | ||
|
14 | from mpl_toolkits.axes_grid1 import make_axes_locatable | |
|
15 | from matplotlib.ticker import FuncFormatter, LinearLocator | |
|
16 | ||
|
17 | ########################################### | |
|
18 | #Actualizacion de las funciones del driver | |
|
19 | ########################################### | |
|
20 | ||
|
21 | jet_values = matplotlib.pyplot.get_cmap("jet", 100)(numpy.arange(100))[10:90] | |
|
22 | blu_values = matplotlib.pyplot.get_cmap("seismic_r", 20)(numpy.arange(20))[10:15] | |
|
23 | ncmap = matplotlib.colors.LinearSegmentedColormap.from_list("jro", numpy.vstack((blu_values, jet_values))) | |
|
24 | matplotlib.pyplot.register_cmap(cmap=ncmap) | |
|
25 | ||
|
26 | def createFigure(id, wintitle, width, height, facecolor="w", show=True, dpi = 80): | |
|
27 | ||
|
28 | matplotlib.pyplot.ioff() | |
|
29 | ||
|
30 | fig = matplotlib.pyplot.figure(num=id, facecolor=facecolor, figsize=(1.0*width/dpi, 1.0*height/dpi)) | |
|
31 | fig.canvas.manager.set_window_title(wintitle) | |
|
32 | # fig.canvas.manager.resize(width, height) | |
|
33 | matplotlib.pyplot.ion() | |
|
34 | ||
|
35 | ||
|
36 | if show: | |
|
37 | matplotlib.pyplot.show() | |
|
38 | ||
|
39 | return fig | |
|
40 | ||
|
41 | def closeFigure(show=False, fig=None): | |
|
42 | ||
|
43 | # matplotlib.pyplot.ioff() | |
|
44 | # matplotlib.pyplot.pause(0) | |
|
45 | ||
|
46 | if show: | |
|
47 | matplotlib.pyplot.show() | |
|
48 | ||
|
49 | if fig != None: | |
|
50 | matplotlib.pyplot.close(fig) | |
|
51 | # matplotlib.pyplot.pause(0) | |
|
52 | # matplotlib.pyplot.ion() | |
|
53 | ||
|
54 | return | |
|
55 | ||
|
56 | matplotlib.pyplot.close("all") | |
|
57 | # matplotlib.pyplot.pause(0) | |
|
58 | # matplotlib.pyplot.ion() | |
|
59 | ||
|
60 | return | |
|
61 | ||
|
62 | def saveFigure(fig, filename): | |
|
63 | ||
|
64 | # matplotlib.pyplot.ioff() | |
|
65 | fig.savefig(filename, dpi=matplotlib.pyplot.gcf().dpi) | |
|
66 | # matplotlib.pyplot.ion() | |
|
67 | ||
|
68 | def clearFigure(fig): | |
|
69 | ||
|
70 | fig.clf() | |
|
71 | ||
|
72 | def setWinTitle(fig, title): | |
|
73 | ||
|
74 | fig.canvas.manager.set_window_title(title) | |
|
75 | ||
|
76 | def setTitle(fig, title): | |
|
77 | ||
|
78 | fig.suptitle(title) | |
|
79 | ||
|
80 | def createAxes(fig, nrow, ncol, xpos, ypos, colspan, rowspan, polar=False): | |
|
81 | ||
|
82 | matplotlib.pyplot.ioff() | |
|
83 | matplotlib.pyplot.figure(fig.number) | |
|
84 | axes = matplotlib.pyplot.subplot2grid((nrow, ncol), | |
|
85 | (xpos, ypos), | |
|
86 | colspan=colspan, | |
|
87 | rowspan=rowspan, | |
|
88 | polar=polar) | |
|
89 | ||
|
90 | axes.grid(True) | |
|
91 | matplotlib.pyplot.ion() | |
|
92 | return axes | |
|
93 | ||
|
94 | def setAxesText(ax, text): | |
|
95 | ||
|
96 | ax.annotate(text, | |
|
97 | xy = (.1, .99), | |
|
98 | xycoords = 'figure fraction', | |
|
99 | horizontalalignment = 'left', | |
|
100 | verticalalignment = 'top', | |
|
101 | fontsize = 10) | |
|
102 | ||
|
103 | def printLabels(ax, xlabel, ylabel, title): | |
|
104 | ||
|
105 | ax.set_xlabel(xlabel, size=11) | |
|
106 | ax.set_ylabel(ylabel, size=11) | |
|
107 | ax.set_title(title, size=8) | |
|
108 | ||
|
109 | def createPline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', | |
|
110 | ticksize=9, xtick_visible=True, ytick_visible=True, | |
|
111 | nxticks=4, nyticks=10, | |
|
112 | grid=None,color='blue'): | |
|
113 | ||
|
114 | """ | |
|
115 | ||
|
116 | Input: | |
|
117 | grid : None, 'both', 'x', 'y' | |
|
118 | """ | |
|
119 | ||
|
120 | matplotlib.pyplot.ioff() | |
|
121 | ||
|
122 | ax.set_xlim([xmin,xmax]) | |
|
123 | ax.set_ylim([ymin,ymax]) | |
|
124 | ||
|
125 | printLabels(ax, xlabel, ylabel, title) | |
|
126 | ||
|
127 | ###################################################### | |
|
128 | if (xmax-xmin)<=1: | |
|
129 | xtickspos = numpy.linspace(xmin,xmax,nxticks) | |
|
130 | xtickspos = numpy.array([float("%.1f"%i) for i in xtickspos]) | |
|
131 | ax.set_xticks(xtickspos) | |
|
132 | else: | |
|
133 | xtickspos = numpy.arange(nxticks)*int((xmax-xmin)/(nxticks)) + int(xmin) | |
|
134 | # xtickspos = numpy.arange(nxticks)*float(xmax-xmin)/float(nxticks) + int(xmin) | |
|
135 | ax.set_xticks(xtickspos) | |
|
136 | ||
|
137 | for tick in ax.get_xticklabels(): | |
|
138 | tick.set_visible(xtick_visible) | |
|
139 | ||
|
140 | for tick in ax.xaxis.get_major_ticks(): | |
|
141 | tick.label.set_fontsize(ticksize) | |
|
142 | ||
|
143 | ###################################################### | |
|
144 | for tick in ax.get_yticklabels(): | |
|
145 | tick.set_visible(ytick_visible) | |
|
146 | ||
|
147 | for tick in ax.yaxis.get_major_ticks(): | |
|
148 | tick.label.set_fontsize(ticksize) | |
|
149 | ||
|
150 | ax.plot(x, y, color=color) | |
|
151 | iplot = ax.lines[-1] | |
|
152 | ||
|
153 | ###################################################### | |
|
154 | if '0.' in matplotlib.__version__[0:2]: | |
|
155 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
156 | return iplot | |
|
157 | ||
|
158 | if '1.0.' in matplotlib.__version__[0:4]: | |
|
159 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
160 | return iplot | |
|
161 | ||
|
162 | if grid != None: | |
|
163 | ax.grid(b=True, which='major', axis=grid) | |
|
164 | ||
|
165 | matplotlib.pyplot.tight_layout() | |
|
166 | ||
|
167 | matplotlib.pyplot.ion() | |
|
168 | ||
|
169 | return iplot | |
|
170 | ||
|
171 | def set_linedata(ax, x, y, idline): | |
|
172 | ||
|
173 | ax.lines[idline].set_data(x,y) | |
|
174 | ||
|
175 | def pline(iplot, x, y, xlabel='', ylabel='', title=''): | |
|
176 | ||
|
177 | ax = iplot.get_axes() | |
|
178 | ||
|
179 | printLabels(ax, xlabel, ylabel, title) | |
|
180 | ||
|
181 | set_linedata(ax, x, y, idline=0) | |
|
182 | ||
|
183 | def addpline(ax, x, y, color, linestyle, lw): | |
|
184 | ||
|
185 | ax.plot(x,y,color=color,linestyle=linestyle,lw=lw) | |
|
186 | ||
|
187 | ||
|
188 | def createPcolor(ax, x, y, z, xmin, xmax, ymin, ymax, zmin, zmax, | |
|
189 | xlabel='', ylabel='', title='', ticksize = 9, | |
|
190 | colormap='jet',cblabel='', cbsize="5%", | |
|
191 | XAxisAsTime=False): | |
|
192 | ||
|
193 | matplotlib.pyplot.ioff() | |
|
194 | ||
|
195 | divider = make_axes_locatable(ax) | |
|
196 | ax_cb = divider.new_horizontal(size=cbsize, pad=0.05) | |
|
197 | fig = ax.get_figure() | |
|
198 | fig.add_axes(ax_cb) | |
|
199 | ||
|
200 | ax.set_xlim([xmin,xmax]) | |
|
201 | ax.set_ylim([ymin,ymax]) | |
|
202 | ||
|
203 | printLabels(ax, xlabel, ylabel, title) | |
|
204 | ||
|
205 | z = numpy.ma.masked_invalid(z) | |
|
206 | cmap=matplotlib.pyplot.get_cmap(colormap) | |
|
207 | cmap.set_bad('white',1.) | |
|
208 | imesh = ax.pcolormesh(x,y,z.T, vmin=zmin, vmax=zmax, cmap=cmap) | |
|
209 | cb = matplotlib.pyplot.colorbar(imesh, cax=ax_cb) | |
|
210 | cb.set_label(cblabel) | |
|
211 | ||
|
212 | # for tl in ax_cb.get_yticklabels(): | |
|
213 | # tl.set_visible(True) | |
|
214 | ||
|
215 | for tick in ax.yaxis.get_major_ticks(): | |
|
216 | tick.label.set_fontsize(ticksize) | |
|
217 | ||
|
218 | for tick in ax.xaxis.get_major_ticks(): | |
|
219 | tick.label.set_fontsize(ticksize) | |
|
220 | ||
|
221 | for tick in cb.ax.get_yticklabels(): | |
|
222 | tick.set_fontsize(ticksize) | |
|
223 | ||
|
224 | ax_cb.yaxis.tick_right() | |
|
225 | ||
|
226 | if '0.' in matplotlib.__version__[0:2]: | |
|
227 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
228 | return imesh | |
|
229 | ||
|
230 | if '1.0.' in matplotlib.__version__[0:4]: | |
|
231 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
232 | return imesh | |
|
233 | ||
|
234 | matplotlib.pyplot.tight_layout() | |
|
235 | ||
|
236 | if XAxisAsTime: | |
|
237 | ||
|
238 | func = lambda x, pos: ('%s') %(datetime.datetime.utcfromtimestamp(x).strftime("%H:%M:%S")) | |
|
239 | ax.xaxis.set_major_formatter(FuncFormatter(func)) | |
|
240 | ax.xaxis.set_major_locator(LinearLocator(7)) | |
|
241 | ax.grid(True) | |
|
242 | matplotlib.pyplot.ion() | |
|
243 | return imesh | |
|
244 | ||
|
245 | def pcolor(imesh, z, xlabel='', ylabel='', title=''): | |
|
246 | ||
|
247 | z = z.T | |
|
248 | ax = imesh.get_axes() | |
|
249 | printLabels(ax, xlabel, ylabel, title) | |
|
250 | imesh.set_array(z.ravel()) | |
|
251 | ax.grid(True) | |
|
252 | ||
|
253 | def addpcolor(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'): | |
|
254 | ||
|
255 | printLabels(ax, xlabel, ylabel, title) | |
|
256 | ax.pcolormesh(x,y,z.T,vmin=zmin,vmax=zmax, cmap=matplotlib.pyplot.get_cmap(colormap)) | |
|
257 | ax.grid(True) | |
|
258 | ||
|
259 | def addpcolorbuffer(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'): | |
|
260 | ||
|
261 | printLabels(ax, xlabel, ylabel, title) | |
|
262 | ||
|
263 | ax.collections.remove(ax.collections[0]) | |
|
264 | ||
|
265 | z = numpy.ma.masked_invalid(z) | |
|
266 | ||
|
267 | cmap=matplotlib.pyplot.get_cmap(colormap) | |
|
268 | cmap.set_bad('white',1.) | |
|
269 | ||
|
270 | ax.pcolormesh(x,y,z.T,vmin=zmin,vmax=zmax, cmap=cmap) | |
|
271 | ax.grid(True) | |
|
272 | ||
|
273 | def createPmultiline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', legendlabels=None, | |
|
274 | ticksize=9, xtick_visible=True, ytick_visible=True, | |
|
275 | nxticks=4, nyticks=10, | |
|
276 | grid=None): | |
|
277 | ||
|
278 | """ | |
|
279 | ||
|
280 | Input: | |
|
281 | grid : None, 'both', 'x', 'y' | |
|
282 | """ | |
|
283 | ||
|
284 | matplotlib.pyplot.ioff() | |
|
285 | ||
|
286 | lines = ax.plot(x.T, y) | |
|
287 | leg = ax.legend(lines, legendlabels, loc='upper right') | |
|
288 | leg.get_frame().set_alpha(0.5) | |
|
289 | ax.set_xlim([xmin,xmax]) | |
|
290 | ax.set_ylim([ymin,ymax]) | |
|
291 | printLabels(ax, xlabel, ylabel, title) | |
|
292 | ||
|
293 | xtickspos = numpy.arange(nxticks)*int((xmax-xmin)/(nxticks)) + int(xmin) | |
|
294 | ax.set_xticks(xtickspos) | |
|
295 | ||
|
296 | for tick in ax.get_xticklabels(): | |
|
297 | tick.set_visible(xtick_visible) | |
|
298 | ||
|
299 | for tick in ax.xaxis.get_major_ticks(): | |
|
300 | tick.label.set_fontsize(ticksize) | |
|
301 | ||
|
302 | for tick in ax.get_yticklabels(): | |
|
303 | tick.set_visible(ytick_visible) | |
|
304 | ||
|
305 | for tick in ax.yaxis.get_major_ticks(): | |
|
306 | tick.label.set_fontsize(ticksize) | |
|
307 | ||
|
308 | iplot = ax.lines[-1] | |
|
309 | ||
|
310 | if '0.' in matplotlib.__version__[0:2]: | |
|
311 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
312 | return iplot | |
|
313 | ||
|
314 | if '1.0.' in matplotlib.__version__[0:4]: | |
|
315 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
316 | return iplot | |
|
317 | ||
|
318 | if grid != None: | |
|
319 | ax.grid(b=True, which='major', axis=grid) | |
|
320 | ||
|
321 | matplotlib.pyplot.tight_layout() | |
|
322 | ||
|
323 | matplotlib.pyplot.ion() | |
|
324 | ||
|
325 | return iplot | |
|
326 | ||
|
327 | ||
|
328 | def pmultiline(iplot, x, y, xlabel='', ylabel='', title=''): | |
|
329 | ||
|
330 | ax = iplot.get_axes() | |
|
331 | ||
|
332 | printLabels(ax, xlabel, ylabel, title) | |
|
333 | ||
|
334 | for i in range(len(ax.lines)): | |
|
335 | line = ax.lines[i] | |
|
336 | line.set_data(x[i,:],y) | |
|
337 | ||
|
338 | def createPmultilineYAxis(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', legendlabels=None, | |
|
339 | ticksize=9, xtick_visible=True, ytick_visible=True, | |
|
340 | nxticks=4, nyticks=10, marker='.', markersize=10, linestyle="None", | |
|
341 | grid=None, XAxisAsTime=False): | |
|
342 | ||
|
343 | """ | |
|
344 | ||
|
345 | Input: | |
|
346 | grid : None, 'both', 'x', 'y' | |
|
347 | """ | |
|
348 | ||
|
349 | matplotlib.pyplot.ioff() | |
|
350 | ||
|
351 | # lines = ax.plot(x, y.T, marker=marker,markersize=markersize,linestyle=linestyle) | |
|
352 | lines = ax.plot(x, y.T) | |
|
353 | # leg = ax.legend(lines, legendlabels, loc=2, bbox_to_anchor=(1.01, 1.00), numpoints=1, handlelength=1.5, \ | |
|
354 | # handletextpad=0.5, borderpad=0.5, labelspacing=0.5, borderaxespad=0.) | |
|
355 | ||
|
356 | leg = ax.legend(lines, legendlabels, | |
|
357 | loc='upper right', bbox_to_anchor=(1.16, 1), borderaxespad=0) | |
|
358 | ||
|
359 | for label in leg.get_texts(): label.set_fontsize(9) | |
|
360 | ||
|
361 | ax.set_xlim([xmin,xmax]) | |
|
362 | ax.set_ylim([ymin,ymax]) | |
|
363 | printLabels(ax, xlabel, ylabel, title) | |
|
364 | ||
|
365 | # xtickspos = numpy.arange(nxticks)*int((xmax-xmin)/(nxticks)) + int(xmin) | |
|
366 | # ax.set_xticks(xtickspos) | |
|
367 | ||
|
368 | for tick in ax.get_xticklabels(): | |
|
369 | tick.set_visible(xtick_visible) | |
|
370 | ||
|
371 | for tick in ax.xaxis.get_major_ticks(): | |
|
372 | tick.label.set_fontsize(ticksize) | |
|
373 | ||
|
374 | for tick in ax.get_yticklabels(): | |
|
375 | tick.set_visible(ytick_visible) | |
|
376 | ||
|
377 | for tick in ax.yaxis.get_major_ticks(): | |
|
378 | tick.label.set_fontsize(ticksize) | |
|
379 | ||
|
380 | iplot = ax.lines[-1] | |
|
381 | ||
|
382 | if '0.' in matplotlib.__version__[0:2]: | |
|
383 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
384 | return iplot | |
|
385 | ||
|
386 | if '1.0.' in matplotlib.__version__[0:4]: | |
|
387 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
388 | return iplot | |
|
389 | ||
|
390 | if grid != None: | |
|
391 | ax.grid(b=True, which='major', axis=grid) | |
|
392 | ||
|
393 | matplotlib.pyplot.tight_layout() | |
|
394 | ||
|
395 | if XAxisAsTime: | |
|
396 | ||
|
397 | func = lambda x, pos: ('%s') %(datetime.datetime.utcfromtimestamp(x).strftime("%H:%M:%S")) | |
|
398 | ax.xaxis.set_major_formatter(FuncFormatter(func)) | |
|
399 | ax.xaxis.set_major_locator(LinearLocator(7)) | |
|
400 | ||
|
401 | matplotlib.pyplot.ion() | |
|
402 | ||
|
403 | return iplot | |
|
404 | ||
|
405 | def pmultilineyaxis(iplot, x, y, xlabel='', ylabel='', title=''): | |
|
406 | ||
|
407 | ax = iplot.get_axes() | |
|
408 | ||
|
409 | printLabels(ax, xlabel, ylabel, title) | |
|
410 | ||
|
411 | for i in range(len(ax.lines)): | |
|
412 | line = ax.lines[i] | |
|
413 | line.set_data(x,y[i,:]) | |
|
414 | ||
|
415 | def createPolar(ax, x, y, | |
|
416 | xlabel='', ylabel='', title='', ticksize = 9, | |
|
417 | colormap='jet',cblabel='', cbsize="5%", | |
|
418 | XAxisAsTime=False): | |
|
419 | ||
|
420 | matplotlib.pyplot.ioff() | |
|
421 | ||
|
422 | ax.plot(x,y,'bo', markersize=5) | |
|
423 | # ax.set_rmax(90) | |
|
424 | ax.set_ylim(0,90) | |
|
425 | ax.set_yticks(numpy.arange(0,90,20)) | |
|
426 | # ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center' ,size='11') | |
|
427 | # ax.text(0, 50, ylabel, rotation='vertical', va ='center', ha = 'left' ,size='11') | |
|
428 | # ax.text(100, 100, 'example', ha='left', va='center', rotation='vertical') | |
|
429 | ax.yaxis.labelpad = 230 | |
|
430 | printLabels(ax, xlabel, ylabel, title) | |
|
431 | iplot = ax.lines[-1] | |
|
432 | ||
|
433 | if '0.' in matplotlib.__version__[0:2]: | |
|
434 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
435 | return iplot | |
|
436 | ||
|
437 | if '1.0.' in matplotlib.__version__[0:4]: | |
|
438 | print "The matplotlib version has to be updated to 1.1 or newer" | |
|
439 | return iplot | |
|
440 | ||
|
441 | # if grid != None: | |
|
442 | # ax.grid(b=True, which='major', axis=grid) | |
|
443 | ||
|
444 | matplotlib.pyplot.tight_layout() | |
|
445 | ||
|
446 | matplotlib.pyplot.ion() | |
|
447 | ||
|
448 | ||
|
449 | return iplot | |
|
450 | ||
|
451 | def polar(iplot, x, y, xlabel='', ylabel='', title=''): | |
|
452 | ||
|
453 | ax = iplot.get_axes() | |
|
454 | ||
|
455 | # ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center',size='11') | |
|
456 | printLabels(ax, xlabel, ylabel, title) | |
|
457 | ||
|
458 | set_linedata(ax, x, y, idline=0) | |
|
459 | ||
|
460 | def draw(fig): | |
|
461 | ||
|
462 | if type(fig) == 'int': | |
|
463 | raise ValueError, "Error drawing: Fig parameter should be a matplotlib figure object figure" | |
|
464 | ||
|
465 | fig.canvas.draw() | |
|
466 | ||
|
467 | def pause(interval=0.000001): | |
|
468 | ||
|
469 | matplotlib.pyplot.pause(interval) |
@@ -0,0 +1,321 | |||
|
1 | import os, sys | |
|
2 | import glob | |
|
3 | import fnmatch | |
|
4 | import datetime | |
|
5 | import time | |
|
6 | import re | |
|
7 | import h5py | |
|
8 | import numpy | |
|
9 | import matplotlib.pyplot as plt | |
|
10 | ||
|
11 | import pylab as plb | |
|
12 | from scipy.optimize import curve_fit | |
|
13 | from scipy import asarray as ar,exp | |
|
14 | from scipy import stats | |
|
15 | ||
|
16 | from duplicity.path import Path | |
|
17 | from numpy.ma.core import getdata | |
|
18 | ||
|
19 | SPEED_OF_LIGHT = 299792458 | |
|
20 | SPEED_OF_LIGHT = 3e8 | |
|
21 | ||
|
22 | try: | |
|
23 | from gevent import sleep | |
|
24 | except: | |
|
25 | from time import sleep | |
|
26 | ||
|
27 | from schainpy.model.data.jrodata import Spectra | |
|
28 | #from schainpy.model.data.BLTRheaderIO import FileHeader, RecordHeader | |
|
29 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation | |
|
30 | #from schainpy.model.io.jroIO_bltr import BLTRReader | |
|
31 | from numpy import imag, shape, NaN | |
|
32 | ||
|
33 | ||
|
34 | startFp = open('/home/erick/Documents/MIRA35C/20160117/20160117_0000.zspc',"rb") | |
|
35 | ||
|
36 | ||
|
37 | FILE_HEADER = numpy.dtype([ #HEADER 1024bytes | |
|
38 | ('Hname',numpy.str_,32), #Original file name | |
|
39 | ('Htime',numpy.str_,32), #Date and time when the file was created | |
|
40 | ('Hoper',numpy.str_,64), #Name of operator who created the file | |
|
41 | ('Hplace',numpy.str_,128), #Place where the measurements was carried out | |
|
42 | ('Hdescr',numpy.str_,256), #Description of measurements | |
|
43 | ('Hdummy',numpy.str_,512), #Reserved space | |
|
44 | #Main chunk | |
|
45 | ('Msign','<i4'), #Main chunk signature FZKF or NUIG | |
|
46 | ('MsizeData','<i4'), #Size of data block main chunk | |
|
47 | #Processing DSP parameters | |
|
48 | ('PPARsign','<i4'), #PPAR signature | |
|
49 | ('PPARsize','<i4'), #PPAR size of block | |
|
50 | ('PPARprf','<i4'), #Pulse repetition frequency | |
|
51 | ('PPARpdr','<i4'), #Pulse duration | |
|
52 | ('PPARsft','<i4'), #FFT length | |
|
53 | ('PPARavc','<i4'), #Number of spectral (in-coherent) averages | |
|
54 | ('PPARihp','<i4'), #Number of lowest range gate for moment estimation | |
|
55 | ('PPARchg','<i4'), #Count for gates for moment estimation | |
|
56 | ('PPARpol','<i4'), #switch on/off polarimetric measurements. Should be 1. | |
|
57 | #Service DSP parameters | |
|
58 | ('SPARatt','<i4'), #STC attenuation on the lowest ranges on/off | |
|
59 | ('SPARtx','<i4'), #OBSOLETE | |
|
60 | ('SPARaddGain0','<f4'), #OBSOLETE | |
|
61 | ('SPARaddGain1','<f4'), #OBSOLETE | |
|
62 | ('SPARwnd','<i4'), #Debug only. It normal mode it is 0. | |
|
63 | ('SPARpos','<i4'), #Delay between sync pulse and tx pulse for phase corr, ns | |
|
64 | ('SPARadd','<i4'), #"add to pulse" to compensate for delay between the leading edge of driver pulse and envelope of the RF signal. | |
|
65 | ('SPARlen','<i4'), #Time for measuring txn pulse phase. OBSOLETE | |
|
66 | ('SPARcal','<i4'), #OBSOLETE | |
|
67 | ('SPARnos','<i4'), #OBSOLETE | |
|
68 | ('SPARof0','<i4'), #detection threshold | |
|
69 | ('SPARof1','<i4'), #OBSOLETE | |
|
70 | ('SPARswt','<i4'), #2nd moment estimation threshold | |
|
71 | ('SPARsum','<i4'), #OBSOLETE | |
|
72 | ('SPARosc','<i4'), #flag Oscillosgram mode | |
|
73 | ('SPARtst','<i4'), #OBSOLETE | |
|
74 | ('SPARcor','<i4'), #OBSOLETE | |
|
75 | ('SPARofs','<i4'), #OBSOLETE | |
|
76 | ('SPARhsn','<i4'), #Hildebrand div noise detection on noise gate | |
|
77 | ('SPARhsa','<f4'), #Hildebrand div noise detection on all gates | |
|
78 | ('SPARcalibPow_M','<f4'), #OBSOLETE | |
|
79 | ('SPARcalibSNR_M','<f4'), #OBSOLETE | |
|
80 | ('SPARcalibPow_S','<f4'), #OBSOLETE | |
|
81 | ('SPARcalibSNR_S','<f4'), #OBSOLETE | |
|
82 | ('SPARrawGate1','<i4'), #Lowest range gate for spectra saving Raw_Gate1 >=5 | |
|
83 | ('SPARrawGate2','<i4'), #Number of range gates with atmospheric signal | |
|
84 | ('SPARraw','<i4'), #flag - IQ or spectra saving on/off | |
|
85 | ('SPARprc','<i4'),]) #flag - Moment estimation switched on/off | |
|
86 | ||
|
87 | ||
|
88 | ||
|
89 | self.Hname= None | |
|
90 | self.Htime= None | |
|
91 | self.Hoper= None | |
|
92 | self.Hplace= None | |
|
93 | self.Hdescr= None | |
|
94 | self.Hdummy= None | |
|
95 | ||
|
96 | self.Msign=None | |
|
97 | self.MsizeData=None | |
|
98 | ||
|
99 | self.PPARsign=None | |
|
100 | self.PPARsize=None | |
|
101 | self.PPARprf=None | |
|
102 | self.PPARpdr=None | |
|
103 | self.PPARsft=None | |
|
104 | self.PPARavc=None | |
|
105 | self.PPARihp=None | |
|
106 | self.PPARchg=None | |
|
107 | self.PPARpol=None | |
|
108 | #Service DSP parameters | |
|
109 | self.SPARatt=None | |
|
110 | self.SPARtx=None | |
|
111 | self.SPARaddGain0=None | |
|
112 | self.SPARaddGain1=None | |
|
113 | self.SPARwnd=None | |
|
114 | self.SPARpos=None | |
|
115 | self.SPARadd=None | |
|
116 | self.SPARlen=None | |
|
117 | self.SPARcal=None | |
|
118 | self.SPARnos=None | |
|
119 | self.SPARof0=None | |
|
120 | self.SPARof1=None | |
|
121 | self.SPARswt=None | |
|
122 | self.SPARsum=None | |
|
123 | self.SPARosc=None | |
|
124 | self.SPARtst=None | |
|
125 | self.SPARcor=None | |
|
126 | self.SPARofs=None | |
|
127 | self.SPARhsn=None | |
|
128 | self.SPARhsa=None | |
|
129 | self.SPARcalibPow_M=None | |
|
130 | self.SPARcalibSNR_M=None | |
|
131 | self.SPARcalibPow_S=None | |
|
132 | self.SPARcalibSNR_S=None | |
|
133 | self.SPARrawGate1=None | |
|
134 | self.SPARrawGate2=None | |
|
135 | self.SPARraw=None | |
|
136 | self.SPARprc=None | |
|
137 | ||
|
138 | ||
|
139 | ||
|
140 | header = numpy.fromfile(fp, FILE_HEADER,1) | |
|
141 | ''' numpy.fromfile(file, dtype, count, sep='') | |
|
142 | file : file or str | |
|
143 | Open file object or filename. | |
|
144 | ||
|
145 | dtype : data-type | |
|
146 | Data type of the returned array. For binary files, it is used to determine | |
|
147 | the size and byte-order of the items in the file. | |
|
148 | ||
|
149 | count : int | |
|
150 | Number of items to read. -1 means all items (i.e., the complete file). | |
|
151 | ||
|
152 | sep : str | |
|
153 | Separator between items if file is a text file. Empty ("") separator means | |
|
154 | the file should be treated as binary. Spaces (" ") in the separator match zero | |
|
155 | or more whitespace characters. A separator consisting only of spaces must match | |
|
156 | at least one whitespace. | |
|
157 | ||
|
158 | ''' | |
|
159 | ||
|
160 | Hname= str(header['Hname'][0]) | |
|
161 | Htime= str(header['Htime'][0]) | |
|
162 | Hoper= str(header['Hoper'][0]) | |
|
163 | Hplace= str(header['Hplace'][0]) | |
|
164 | Hdescr= str(header['Hdescr'][0]) | |
|
165 | Hdummy= str(header['Hdummy'][0]) | |
|
166 | ||
|
167 | Msign=header['Msign'][0] | |
|
168 | MsizeData=header['MsizeData'][0] | |
|
169 | ||
|
170 | PPARsign=header['PPARsign'][0] | |
|
171 | PPARsize=header['PPARsize'][0] | |
|
172 | PPARprf=header['PPARprf'][0] | |
|
173 | PPARpdr=header['PPARpdr'][0] | |
|
174 | PPARsft=header['PPARsft'][0] | |
|
175 | PPARavc=header['PPARavc'][0] | |
|
176 | PPARihp=header['PPARihp'][0] | |
|
177 | PPARchg=header['PPARchg'][0] | |
|
178 | PPARpol=header['PPARpol'][0] | |
|
179 | #Service DSP parameters | |
|
180 | SPARatt=header['SPARatt'][0] | |
|
181 | SPARtx=header['SPARtx'][0] | |
|
182 | SPARaddGain0=header['SPARaddGain0'][0] | |
|
183 | SPARaddGain1=header['SPARaddGain1'][0] | |
|
184 | SPARwnd=header['SPARwnd'][0] | |
|
185 | SPARpos=header['SPARpos'][0] | |
|
186 | SPARadd=header['SPARadd'][0] | |
|
187 | SPARlen=header['SPARlen'][0] | |
|
188 | SPARcal=header['SPARcal'][0] | |
|
189 | SPARnos=header['SPARnos'][0] | |
|
190 | SPARof0=header['SPARof0'][0] | |
|
191 | SPARof1=header['SPARof1'][0] | |
|
192 | SPARswt=header['SPARswt'][0] | |
|
193 | SPARsum=header['SPARsum'][0] | |
|
194 | SPARosc=header['SPARosc'][0] | |
|
195 | SPARtst=header['SPARtst'][0] | |
|
196 | SPARcor=header['SPARcor'][0] | |
|
197 | SPARofs=header['SPARofs'][0] | |
|
198 | SPARhsn=header['SPARhsn'][0] | |
|
199 | SPARhsa=header['SPARhsa'][0] | |
|
200 | SPARcalibPow_M=header['SPARcalibPow_M'][0] | |
|
201 | SPARcalibSNR_M=header['SPARcalibSNR_M'][0] | |
|
202 | SPARcalibPow_S=header['SPARcalibPow_S'][0] | |
|
203 | SPARcalibSNR_S=header['SPARcalibSNR_S'][0] | |
|
204 | SPARrawGate1=header['SPARrawGate1'][0] | |
|
205 | SPARrawGate2=header['SPARrawGate2'][0] | |
|
206 | SPARraw=header['SPARraw'][0] | |
|
207 | SPARprc=header['SPARprc'][0] | |
|
208 | ||
|
209 | ||
|
210 | ||
|
211 | SRVI_STRUCTURE = numpy.dtype([ | |
|
212 | ('frame_cnt','<u4'),# | |
|
213 | ('time_t','<u4'), # | |
|
214 | ('tpow','<f4'), # | |
|
215 | ('npw1','<f4'), # | |
|
216 | ('npw2','<f4'), # | |
|
217 | ('cpw1','<f4'), # | |
|
218 | ('pcw2','<f4'), # | |
|
219 | ('ps_err','<u4'), # | |
|
220 | ('te_err','<u4'), # | |
|
221 | ('rc_err','<u4'), # | |
|
222 | ('grs1','<u4'), # | |
|
223 | ('grs2','<u4'), # | |
|
224 | ('azipos','<f4'), # | |
|
225 | ('azivel','<f4'), # | |
|
226 | ('elvpos','<f4'), # | |
|
227 | ('elvvel','<f4'), # | |
|
228 | ('northAngle','<f4'), # | |
|
229 | ('microsec','<u4'), # | |
|
230 | ('azisetvel','<f4'), # | |
|
231 | ('elvsetpos','<f4'), # | |
|
232 | ('RadarConst','<f4'),]) # | |
|
233 | ||
|
234 | JUMP_STRUCTURE = numpy.dtype([ | |
|
235 | ('jump','<u140'),# | |
|
236 | ('SizeOfDataBlock1',numpy.str_,32),# | |
|
237 | ('jump','<i4'),# | |
|
238 | ('DataBlockTitleSRVI1',numpy.str_,32),# | |
|
239 | ('SizeOfSRVI1','<i4'),])# | |
|
240 | ||
|
241 | ||
|
242 | ||
|
243 | #frame_cnt=0, time_t= 0, tpow=0, npw1=0, npw2=0, | |
|
244 | #cpw1=0, pcw2=0, ps_err=0, te_err=0, rc_err=0, grs1=0, | |
|
245 | #grs2=0, azipos=0, azivel=0, elvpos=0, elvvel=0, northangle=0, | |
|
246 | #microsec=0, azisetvel=0, elvsetpos=0, RadarConst=0 | |
|
247 | ||
|
248 | ||
|
249 | frame_cnt = frame_cnt | |
|
250 | dwell = time_t | |
|
251 | tpow = tpow | |
|
252 | npw1 = npw1 | |
|
253 | npw2 = npw2 | |
|
254 | cpw1 = cpw1 | |
|
255 | pcw2 = pcw2 | |
|
256 | ps_err = ps_err | |
|
257 | te_err = te_err | |
|
258 | rc_err = rc_err | |
|
259 | grs1 = grs1 | |
|
260 | grs2 = grs2 | |
|
261 | azipos = azipos | |
|
262 | azivel = azivel | |
|
263 | elvpos = elvpos | |
|
264 | elvvel = elvvel | |
|
265 | northAngle = northAngle | |
|
266 | microsec = microsec | |
|
267 | azisetvel = azisetvel | |
|
268 | elvsetpos = elvsetpos | |
|
269 | RadarConst5 = RadarConst | |
|
270 | ||
|
271 | ||
|
272 | ||
|
273 | #print fp | |
|
274 | #startFp = open('/home/erick/Documents/Data/huancayo.20161019.22.fdt',"rb") #The method tell() returns the current position of the file read/write pointer within the file. | |
|
275 | #startFp = open(fp,"rb") #The method tell() returns the current position of the file read/write pointer within the file. | |
|
276 | #RecCounter=0 | |
|
277 | #Off2StartNxtRec=811248 | |
|
278 | #print 'OffsetStartHeader ',self.OffsetStartHeader,'RecCounter ', self.RecCounter, 'Off2StartNxtRec ' , self.Off2StartNxtRec | |
|
279 | #OffRHeader= self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec | |
|
280 | #startFp.seek(OffRHeader, os.SEEK_SET) | |
|
281 | print 'debe ser 48, RecCounter*811248', self.OffsetStartHeader,self.RecCounter,self.Off2StartNxtRec | |
|
282 | print 'Posicion del bloque: ',OffRHeader | |
|
283 | ||
|
284 | header = numpy.fromfile(startFp,SRVI_STRUCTURE,1) | |
|
285 | ||
|
286 | self.frame_cnt = header['frame_cnt'][0]# | |
|
287 | self.time_t = header['frame_cnt'][0] # | |
|
288 | self.tpow = header['frame_cnt'][0] # | |
|
289 | self.npw1 = header['frame_cnt'][0] # | |
|
290 | self.npw2 = header['frame_cnt'][0] # | |
|
291 | self.cpw1 = header['frame_cnt'][0] # | |
|
292 | self.pcw2 = header['frame_cnt'][0] # | |
|
293 | self.ps_err = header['frame_cnt'][0] # | |
|
294 | self.te_err = header['frame_cnt'][0] # | |
|
295 | self.rc_err = header['frame_cnt'][0] # | |
|
296 | self.grs1 = header['frame_cnt'][0] # | |
|
297 | self.grs2 = header['frame_cnt'][0] # | |
|
298 | self.azipos = header['frame_cnt'][0] # | |
|
299 | self.azivel = header['frame_cnt'][0] # | |
|
300 | self.elvpos = header['frame_cnt'][0] # | |
|
301 | self.elvvel = header['frame_cnt'][0] # | |
|
302 | self.northAngle = header['frame_cnt'][0] # | |
|
303 | self.microsec = header['frame_cnt'][0] # | |
|
304 | self.azisetvel = header['frame_cnt'][0] # | |
|
305 | self.elvsetpos = header['frame_cnt'][0] # | |
|
306 | self.RadarConst = header['frame_cnt'][0] # | |
|
307 | ||
|
308 | ||
|
309 | self.ipp= 0.5*(SPEED_OF_LIGHT/self.PRFhz) | |
|
310 | ||
|
311 | self.RHsize = 180+20*self.nChannels | |
|
312 | self.Datasize= self.nProfiles*self.nChannels*self.nHeights*2*4 | |
|
313 | #print 'Datasize',self.Datasize | |
|
314 | endFp = self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec | |
|
315 | ||
|
316 | print '==============================================' | |
|
317 | ||
|
318 | print '==============================================' | |
|
319 | ||
|
320 | ||
|
321 | No newline at end of file |
@@ -0,0 +1,362 | |||
|
1 | ''' | |
|
2 | Created on Nov 9, 2016 | |
|
3 | ||
|
4 | @author: roj- LouVD | |
|
5 | ''' | |
|
6 | ||
|
7 | ||
|
8 | import os | |
|
9 | import sys | |
|
10 | import time | |
|
11 | import glob | |
|
12 | import datetime | |
|
13 | ||
|
14 | import numpy | |
|
15 | ||
|
16 | from schainpy.model.proc.jroproc_base import ProcessingUnit | |
|
17 | from schainpy.model.data.jrodata import Parameters | |
|
18 | from schainpy.model.io.jroIO_base import JRODataReader, isNumber | |
|
19 | ||
|
20 | FILE_HEADER_STRUCTURE = numpy.dtype([ | |
|
21 | ('FMN', '<u4'), | |
|
22 | ('nrec', '<u4'), | |
|
23 | ('fr_offset', '<u4'), | |
|
24 | ('id', '<u4'), | |
|
25 | ('site', 'u1', (32,)) | |
|
26 | ]) | |
|
27 | ||
|
28 | REC_HEADER_STRUCTURE = numpy.dtype([ | |
|
29 | ('rmn', '<u4'), | |
|
30 | ('rcounter', '<u4'), | |
|
31 | ('nr_offset', '<u4'), | |
|
32 | ('tr_offset', '<u4'), | |
|
33 | ('time', '<u4'), | |
|
34 | ('time_msec', '<u4'), | |
|
35 | ('tag', 'u1', (32,)), | |
|
36 | ('comments', 'u1', (32,)), | |
|
37 | ('lat', '<f4'), | |
|
38 | ('lon', '<f4'), | |
|
39 | ('gps_status', '<u4'), | |
|
40 | ('freq', '<u4'), | |
|
41 | ('freq0', '<u4'), | |
|
42 | ('nchan', '<u4'), | |
|
43 | ('delta_r', '<u4'), | |
|
44 | ('nranges', '<u4'), | |
|
45 | ('r0', '<u4'), | |
|
46 | ('prf', '<u4'), | |
|
47 | ('ncoh', '<u4'), | |
|
48 | ('npoints', '<u4'), | |
|
49 | ('polarization', '<i4'), | |
|
50 | ('rx_filter', '<u4'), | |
|
51 | ('nmodes', '<u4'), | |
|
52 | ('dmode_index', '<u4'), | |
|
53 | ('dmode_rngcorr', '<u4'), | |
|
54 | ('nrxs', '<u4'), | |
|
55 | ('acf_length', '<u4'), | |
|
56 | ('acf_lags', '<u4'), | |
|
57 | ('sea_to_atmos', '<f4'), | |
|
58 | ('sea_notch', '<u4'), | |
|
59 | ('lh_sea', '<u4'), | |
|
60 | ('hh_sea', '<u4'), | |
|
61 | ('nbins_sea', '<u4'), | |
|
62 | ('min_snr', '<f4'), | |
|
63 | ('min_cc', '<f4'), | |
|
64 | ('max_time_diff', '<f4') | |
|
65 | ]) | |
|
66 | ||
|
67 | DATA_STRUCTURE = numpy.dtype([ | |
|
68 | ('range', '<u4'), | |
|
69 | ('status', '<u4'), | |
|
70 | ('zonal', '<f4'), | |
|
71 | ('meridional', '<f4'), | |
|
72 | ('vertical', '<f4'), | |
|
73 | ('zonal_a', '<f4'), | |
|
74 | ('meridional_a', '<f4'), | |
|
75 | ('corrected_fading', '<f4'), # seconds | |
|
76 | ('uncorrected_fading', '<f4'), # seconds | |
|
77 | ('time_diff', '<f4'), | |
|
78 | ('major_axis', '<f4'), | |
|
79 | ('axial_ratio', '<f4'), | |
|
80 | ('orientation', '<f4'), | |
|
81 | ('sea_power', '<u4'), | |
|
82 | ('sea_algorithm', '<u4') | |
|
83 | ]) | |
|
84 | ||
|
85 | class BLTRParamReader(JRODataReader, ProcessingUnit): | |
|
86 | ''' | |
|
87 | Boundary Layer and Tropospheric Radar (BLTR) reader, Wind velocities and SNR from *.sswma files | |
|
88 | ''' | |
|
89 | ||
|
90 | ext = '.sswma' | |
|
91 | ||
|
92 | def __init__(self, **kwargs): | |
|
93 | ||
|
94 | ProcessingUnit.__init__(self , **kwargs) | |
|
95 | ||
|
96 | self.dataOut = Parameters() | |
|
97 | self.counter_records = 0 | |
|
98 | self.flagNoMoreFiles = 0 | |
|
99 | self.isConfig = False | |
|
100 | self.filename = None | |
|
101 | ||
|
102 | def setup(self, | |
|
103 | path=None, | |
|
104 | startDate=None, | |
|
105 | endDate=None, | |
|
106 | ext=None, | |
|
107 | startTime=datetime.time(0, 0, 0), | |
|
108 | endTime=datetime.time(23, 59, 59), | |
|
109 | timezone=0, | |
|
110 | status_value=0, | |
|
111 | **kwargs): | |
|
112 | ||
|
113 | self.path = path | |
|
114 | self.startTime = startTime | |
|
115 | self.endTime = endTime | |
|
116 | self.status_value = status_value | |
|
117 | ||
|
118 | if self.path is None: | |
|
119 | raise ValueError, "The path is not valid" | |
|
120 | ||
|
121 | if ext is None: | |
|
122 | ext = self.ext | |
|
123 | ||
|
124 | self.search_files(self.path, startDate, endDate, ext) | |
|
125 | self.timezone = timezone | |
|
126 | self.fileIndex = 0 | |
|
127 | ||
|
128 | if not self.fileList: | |
|
129 | raise Warning, "There is no files matching these date in the folder: %s. \n Check 'startDate' and 'endDate' "%(path) | |
|
130 | ||
|
131 | self.setNextFile() | |
|
132 | ||
|
133 | def search_files(self, path, startDate, endDate, ext): | |
|
134 | ''' | |
|
135 | Searching for BLTR rawdata file in path | |
|
136 | Creating a list of file to proces included in [startDate,endDate] | |
|
137 | ||
|
138 | Input: | |
|
139 | path - Path to find BLTR rawdata files | |
|
140 | startDate - Select file from this date | |
|
141 | enDate - Select file until this date | |
|
142 | ext - Extension of the file to read | |
|
143 | ||
|
144 | ''' | |
|
145 | ||
|
146 | print 'Searching file in %s ' % (path) | |
|
147 | foldercounter = 0 | |
|
148 | fileList0 = glob.glob1(path, "*%s" % ext) | |
|
149 | fileList0.sort() | |
|
150 | ||
|
151 | self.fileList = [] | |
|
152 | self.dateFileList = [] | |
|
153 | ||
|
154 | for thisFile in fileList0: | |
|
155 | year = thisFile[-14:-10] | |
|
156 | if not isNumber(year): | |
|
157 | continue | |
|
158 | ||
|
159 | month = thisFile[-10:-8] | |
|
160 | if not isNumber(month): | |
|
161 | continue | |
|
162 | ||
|
163 | day = thisFile[-8:-6] | |
|
164 | if not isNumber(day): | |
|
165 | continue | |
|
166 | ||
|
167 | year, month, day = int(year), int(month), int(day) | |
|
168 | dateFile = datetime.date(year, month, day) | |
|
169 | ||
|
170 | if (startDate > dateFile) or (endDate < dateFile): | |
|
171 | continue | |
|
172 | ||
|
173 | self.fileList.append(thisFile) | |
|
174 | self.dateFileList.append(dateFile) | |
|
175 | ||
|
176 | return | |
|
177 | ||
|
178 | def setNextFile(self): | |
|
179 | ||
|
180 | file_id = self.fileIndex | |
|
181 | ||
|
182 | if file_id == len(self.fileList): | |
|
183 | print '\nNo more files in the folder' | |
|
184 | print 'Total number of file(s) read : {}'.format(self.fileIndex + 1) | |
|
185 | self.flagNoMoreFiles = 1 | |
|
186 | return 0 | |
|
187 | ||
|
188 | print '\n[Setting file] (%s) ...' % self.fileList[file_id] | |
|
189 | filename = os.path.join(self.path, self.fileList[file_id]) | |
|
190 | ||
|
191 | dirname, name = os.path.split(filename) | |
|
192 | self.siteFile = name.split('.')[0] # 'peru2' ---> Piura - 'peru1' ---> Huancayo or Porcuya | |
|
193 | if self.filename is not None: | |
|
194 | self.fp.close() | |
|
195 | self.filename = filename | |
|
196 | self.fp = open(self.filename, 'rb') | |
|
197 | self.header_file = numpy.fromfile(self.fp, FILE_HEADER_STRUCTURE, 1) | |
|
198 | self.nrecords = self.header_file['nrec'][0] | |
|
199 | self.sizeOfFile = os.path.getsize(self.filename) | |
|
200 | self.counter_records = 0 | |
|
201 | self.flagIsNewFile = 0 | |
|
202 | self.fileIndex += 1 | |
|
203 | ||
|
204 | return 1 | |
|
205 | ||
|
206 | def readNextBlock(self): | |
|
207 | ||
|
208 | while True: | |
|
209 | if self.counter_records == self.nrecords: | |
|
210 | self.flagIsNewFile = 1 | |
|
211 | if not self.setNextFile(): | |
|
212 | return 0 | |
|
213 | ||
|
214 | self.readBlock() | |
|
215 | ||
|
216 | if (self.datatime.time() < self.startTime) or (self.datatime.time() > self.endTime): | |
|
217 | print "[Reading] Record No. %d/%d -> %s [Skipping]" %( | |
|
218 | self.counter_records, | |
|
219 | self.nrecords, | |
|
220 | self.datatime.ctime()) | |
|
221 | continue | |
|
222 | break | |
|
223 | ||
|
224 | print "[Reading] Record No. %d/%d -> %s" %( | |
|
225 | self.counter_records, | |
|
226 | self.nrecords, | |
|
227 | self.datatime.ctime()) | |
|
228 | ||
|
229 | return 1 | |
|
230 | ||
|
231 | def readBlock(self): | |
|
232 | ||
|
233 | pointer = self.fp.tell() | |
|
234 | header_rec = numpy.fromfile(self.fp, REC_HEADER_STRUCTURE, 1) | |
|
235 | self.nchannels = header_rec['nchan'][0]/2 | |
|
236 | self.kchan = header_rec['nrxs'][0] | |
|
237 | self.nmodes = header_rec['nmodes'][0] | |
|
238 | self.nranges = header_rec['nranges'][0] | |
|
239 | self.fp.seek(pointer) | |
|
240 | self.height = numpy.empty((self.nmodes, self.nranges)) | |
|
241 | self.snr = numpy.empty((self.nmodes, self.nchannels, self.nranges)) | |
|
242 | self.buffer = numpy.empty((self.nmodes, 3, self.nranges)) | |
|
243 | ||
|
244 | for mode in range(self.nmodes): | |
|
245 | self.readHeader() | |
|
246 | data = self.readData() | |
|
247 | self.height[mode] = (data[0] - self.correction) / 1000. | |
|
248 | self.buffer[mode] = data[1] | |
|
249 | self.snr[mode] = data[2] | |
|
250 | ||
|
251 | self.counter_records = self.counter_records + self.nmodes | |
|
252 | ||
|
253 | return | |
|
254 | ||
|
255 | def readHeader(self): | |
|
256 | ''' | |
|
257 | RecordHeader of BLTR rawdata file | |
|
258 | ''' | |
|
259 | ||
|
260 | header_structure = numpy.dtype( | |
|
261 | REC_HEADER_STRUCTURE.descr + [ | |
|
262 | ('antenna_coord', 'f4', (2, self.nchannels)), | |
|
263 | ('rx_gains', 'u4', (self.nchannels,)), | |
|
264 | ('rx_analysis', 'u4', (self.nchannels,)) | |
|
265 | ] | |
|
266 | ) | |
|
267 | ||
|
268 | self.header_rec = numpy.fromfile(self.fp, header_structure, 1) | |
|
269 | self.lat = self.header_rec['lat'][0] | |
|
270 | self.lon = self.header_rec['lon'][0] | |
|
271 | self.delta = self.header_rec['delta_r'][0] | |
|
272 | self.correction = self.header_rec['dmode_rngcorr'][0] | |
|
273 | self.imode = self.header_rec['dmode_index'][0] | |
|
274 | self.antenna = self.header_rec['antenna_coord'] | |
|
275 | self.rx_gains = self.header_rec['rx_gains'] | |
|
276 | self.time = self.header_rec['time'][0] | |
|
277 | tseconds = self.header_rec['time'][0] | |
|
278 | local_t1 = time.localtime(tseconds) | |
|
279 | self.year = local_t1.tm_year | |
|
280 | self.month = local_t1.tm_mon | |
|
281 | self.day = local_t1.tm_mday | |
|
282 | self.t = datetime.datetime(self.year, self.month, self.day) | |
|
283 | self.datatime = datetime.datetime.utcfromtimestamp(self.time) | |
|
284 | ||
|
285 | def readData(self): | |
|
286 | ''' | |
|
287 | Reading and filtering data block record of BLTR rawdata file, filtering is according to status_value. | |
|
288 | ||
|
289 | Input: | |
|
290 | status_value - Array data is set to NAN for values that are not equal to status_value | |
|
291 | ||
|
292 | ''' | |
|
293 | ||
|
294 | data_structure = numpy.dtype( | |
|
295 | DATA_STRUCTURE.descr + [ | |
|
296 | ('rx_saturation', 'u4', (self.nchannels,)), | |
|
297 | ('chan_offset', 'u4', (2 * self.nchannels,)), | |
|
298 | ('rx_amp', 'u4', (self.nchannels,)), | |
|
299 | ('rx_snr', 'f4', (self.nchannels,)), | |
|
300 | ('cross_snr', 'f4', (self.kchan,)), | |
|
301 | ('sea_power_relative', 'f4', (self.kchan,))] | |
|
302 | ) | |
|
303 | ||
|
304 | data = numpy.fromfile(self.fp, data_structure, self.nranges) | |
|
305 | ||
|
306 | height = data['range'] | |
|
307 | winds = numpy.array((data['zonal'], data['meridional'], data['vertical'])) | |
|
308 | snr = data['rx_snr'].T | |
|
309 | ||
|
310 | winds[numpy.where(winds == -9999.)] = numpy.nan | |
|
311 | winds[:, numpy.where(data['status'] != self.status_value)] = numpy.nan | |
|
312 | snr[numpy.where(snr == -9999.)] = numpy.nan | |
|
313 | snr[:, numpy.where(data['status'] != self.status_value)] = numpy.nan | |
|
314 | snr = numpy.power(10, snr / 10) | |
|
315 | ||
|
316 | return height, winds, snr | |
|
317 | ||
|
318 | def set_output(self): | |
|
319 | ''' | |
|
320 | Storing data from databuffer to dataOut object | |
|
321 | ''' | |
|
322 | ||
|
323 | self.dataOut.data_SNR = self.snr | |
|
324 | self.dataOut.height = self.height | |
|
325 | self.dataOut.data_output = self.buffer | |
|
326 | self.dataOut.utctimeInit = self.time | |
|
327 | self.dataOut.utctime = self.dataOut.utctimeInit | |
|
328 | self.dataOut.useLocalTime = False | |
|
329 | self.dataOut.paramInterval = 157 | |
|
330 | self.dataOut.timezone = self.timezone | |
|
331 | self.dataOut.site = self.siteFile | |
|
332 | self.dataOut.nrecords = self.nrecords/self.nmodes | |
|
333 | self.dataOut.sizeOfFile = self.sizeOfFile | |
|
334 | self.dataOut.lat = self.lat | |
|
335 | self.dataOut.lon = self.lon | |
|
336 | self.dataOut.channelList = range(self.nchannels) | |
|
337 | self.dataOut.kchan = self.kchan | |
|
338 | # self.dataOut.nHeights = self.nranges | |
|
339 | self.dataOut.delta = self.delta | |
|
340 | self.dataOut.correction = self.correction | |
|
341 | self.dataOut.nmodes = self.nmodes | |
|
342 | self.dataOut.imode = self.imode | |
|
343 | self.dataOut.antenna = self.antenna | |
|
344 | self.dataOut.rx_gains = self.rx_gains | |
|
345 | self.dataOut.flagNoData = False | |
|
346 | ||
|
347 | def getData(self): | |
|
348 | ''' | |
|
349 | Storing data from databuffer to dataOut object | |
|
350 | ''' | |
|
351 | if self.flagNoMoreFiles: | |
|
352 | self.dataOut.flagNoData = True | |
|
353 | print 'No file left to process' | |
|
354 | return 0 | |
|
355 | ||
|
356 | if not self.readNextBlock(): | |
|
357 | self.dataOut.flagNoData = True | |
|
358 | return 0 | |
|
359 | ||
|
360 | self.set_output() | |
|
361 | ||
|
362 | return 1 |
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|
1 | import os, sys | |
|
2 | import glob | |
|
3 | import fnmatch | |
|
4 | import datetime | |
|
5 | import time | |
|
6 | import re | |
|
7 | import h5py | |
|
8 | import numpy | |
|
9 | import matplotlib.pyplot as plt | |
|
10 | ||
|
11 | import pylab as plb | |
|
12 | from scipy.optimize import curve_fit | |
|
13 | from scipy import asarray as ar, exp | |
|
14 | from scipy import stats | |
|
15 | ||
|
16 | from numpy.ma.core import getdata | |
|
17 | ||
|
18 | SPEED_OF_LIGHT = 299792458 | |
|
19 | SPEED_OF_LIGHT = 3e8 | |
|
20 | ||
|
21 | try: | |
|
22 | from gevent import sleep | |
|
23 | except: | |
|
24 | from time import sleep | |
|
25 | ||
|
26 | from schainpy.model.data.jrodata import Spectra | |
|
27 | #from schainpy.model.data.BLTRheaderIO import FileHeader, RecordHeader | |
|
28 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation | |
|
29 | #from schainpy.model.io.jroIO_bltr import BLTRReader | |
|
30 | from numpy import imag, shape, NaN | |
|
31 | ||
|
32 | from jroIO_base import JRODataReader | |
|
33 | ||
|
34 | ||
|
35 | class Header(object): | |
|
36 | ||
|
37 | def __init__(self): | |
|
38 | raise NotImplementedError | |
|
39 | ||
|
40 | ||
|
41 | def read(self): | |
|
42 | ||
|
43 | raise NotImplementedError | |
|
44 | ||
|
45 | def write(self): | |
|
46 | ||
|
47 | raise NotImplementedError | |
|
48 | ||
|
49 | def printInfo(self): | |
|
50 | ||
|
51 | message = "#"*50 + "\n" | |
|
52 | message += self.__class__.__name__.upper() + "\n" | |
|
53 | message += "#"*50 + "\n" | |
|
54 | ||
|
55 | keyList = self.__dict__.keys() | |
|
56 | keyList.sort() | |
|
57 | ||
|
58 | for key in keyList: | |
|
59 | message += "%s = %s" %(key, self.__dict__[key]) + "\n" | |
|
60 | ||
|
61 | if "size" not in keyList: | |
|
62 | attr = getattr(self, "size") | |
|
63 | ||
|
64 | if attr: | |
|
65 | message += "%s = %s" %("size", attr) + "\n" | |
|
66 | ||
|
67 | #print message | |
|
68 | ||
|
69 | ||
|
70 | ||
|
71 | ||
|
72 | ||
|
73 | FILE_STRUCTURE = numpy.dtype([ #HEADER 48bytes | |
|
74 | ('FileMgcNumber','<u4'), #0x23020100 | |
|
75 | ('nFDTdataRecors','<u4'), #No Of FDT data records in this file (0 or more) | |
|
76 | ('OffsetStartHeader','<u4'), | |
|
77 | ('RadarUnitId','<u4'), | |
|
78 | ('SiteName',numpy.str_,32), #Null terminated | |
|
79 | ]) | |
|
80 | ||
|
81 | class FileHeaderBLTR(Header): | |
|
82 | ||
|
83 | def __init__(self): | |
|
84 | ||
|
85 | self.FileMgcNumber= 0 #0x23020100 | |
|
86 | self.nFDTdataRecors=0 #No Of FDT data records in this file (0 or more) | |
|
87 | self.RadarUnitId= 0 | |
|
88 | self.OffsetStartHeader=0 | |
|
89 | self.SiteName= "" | |
|
90 | self.size = 48 | |
|
91 | ||
|
92 | def FHread(self, fp): | |
|
93 | #try: | |
|
94 | startFp = open(fp,"rb") | |
|
95 | ||
|
96 | header = numpy.fromfile(startFp, FILE_STRUCTURE,1) | |
|
97 | ||
|
98 | print ' ' | |
|
99 | print 'puntero file header', startFp.tell() | |
|
100 | print ' ' | |
|
101 | ||
|
102 | ||
|
103 | ''' numpy.fromfile(file, dtype, count, sep='') | |
|
104 | file : file or str | |
|
105 | Open file object or filename. | |
|
106 | ||
|
107 | dtype : data-type | |
|
108 | Data type of the returned array. For binary files, it is used to determine | |
|
109 | the size and byte-order of the items in the file. | |
|
110 | ||
|
111 | count : int | |
|
112 | Number of items to read. -1 means all items (i.e., the complete file). | |
|
113 | ||
|
114 | sep : str | |
|
115 | Separator between items if file is a text file. Empty ("") separator means | |
|
116 | the file should be treated as binary. Spaces (" ") in the separator match zero | |
|
117 | or more whitespace characters. A separator consisting only of spaces must match | |
|
118 | at least one whitespace. | |
|
119 | ||
|
120 | ''' | |
|
121 | ||
|
122 | ||
|
123 | ||
|
124 | self.FileMgcNumber= hex(header['FileMgcNumber'][0]) | |
|
125 | self.nFDTdataRecors=int(header['nFDTdataRecors'][0]) #No Of FDT data records in this file (0 or more) | |
|
126 | self.RadarUnitId= int(header['RadarUnitId'][0]) | |
|
127 | self.OffsetStartHeader= int(header['OffsetStartHeader'][0]) | |
|
128 | self.SiteName= str(header['SiteName'][0]) | |
|
129 | ||
|
130 | #print 'Numero de bloques', self.nFDTdataRecors | |
|
131 | ||
|
132 | ||
|
133 | if self.size <48: | |
|
134 | return 0 | |
|
135 | ||
|
136 | return 1 | |
|
137 | ||
|
138 | ||
|
139 | def write(self, fp): | |
|
140 | ||
|
141 | headerTuple = (self.FileMgcNumber, | |
|
142 | self.nFDTdataRecors, | |
|
143 | self.RadarUnitId, | |
|
144 | self.SiteName, | |
|
145 | self.size) | |
|
146 | ||
|
147 | ||
|
148 | header = numpy.array(headerTuple, FILE_STRUCTURE) | |
|
149 | # numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0) | |
|
150 | header.tofile(fp) | |
|
151 | ''' ndarray.tofile(fid, sep, format) Write array to a file as text or binary (default). | |
|
152 | ||
|
153 | fid : file or str | |
|
154 | An open file object, or a string containing a filename. | |
|
155 | ||
|
156 | sep : str | |
|
157 | Separator between array items for text output. If "" (empty), a binary file is written, | |
|
158 | equivalent to file.write(a.tobytes()). | |
|
159 | ||
|
160 | format : str | |
|
161 | Format string for text file output. Each entry in the array is formatted to text by | |
|
162 | first converting it to the closest Python type, and then using "format" % item. | |
|
163 | ||
|
164 | ''' | |
|
165 | ||
|
166 | return 1 | |
|
167 | ||
|
168 | ||
|
169 | ||
|
170 | ||
|
171 | ||
|
172 | RECORD_STRUCTURE = numpy.dtype([ #RECORD HEADER 180+20N bytes | |
|
173 | ('RecMgcNumber','<u4'), #0x23030001 | |
|
174 | ('RecCounter','<u4'), #Record counter(0,1, ...) | |
|
175 | ('Off2StartNxtRec','<u4'), #Offset to start of next record form start of this record | |
|
176 | ('Off2StartData','<u4'), #Offset to start of data from start of this record | |
|
177 | ('nUtime','<i4'), #Epoch time stamp of start of acquisition (seconds) | |
|
178 | ('nMilisec','<u4'), #Millisecond component of time stamp (0,...,999) | |
|
179 | ('ExpTagName',numpy.str_,32), #Experiment tag name (null terminated) | |
|
180 | ('ExpComment',numpy.str_,32), #Experiment comment (null terminated) | |
|
181 | ('SiteLatDegrees','<f4'), #Site latitude (from GPS) in degrees (positive implies North) | |
|
182 | ('SiteLongDegrees','<f4'), #Site longitude (from GPS) in degrees (positive implies East) | |
|
183 | ('RTCgpsStatus','<u4'), #RTC GPS engine status (0=SEEK, 1=LOCK, 2=NOT FITTED, 3=UNAVAILABLE) | |
|
184 | ('TransmitFrec','<u4'), #Transmit frequency (Hz) | |
|
185 | ('ReceiveFrec','<u4'), #Receive frequency | |
|
186 | ('FirstOsciFrec','<u4'), #First local oscillator frequency (Hz) | |
|
187 | ('Polarisation','<u4'), #(0="O", 1="E", 2="linear 1", 3="linear2") | |
|
188 | ('ReceiverFiltSett','<u4'), #Receiver filter settings (0,1,2,3) | |
|
189 | ('nModesInUse','<u4'), #Number of modes in use (1 or 2) | |
|
190 | ('DualModeIndex','<u4'), #Dual Mode index number for these data (0 or 1) | |
|
191 | ('DualModeRange','<u4'), #Dual Mode range correction for these data (m) | |
|
192 | ('nDigChannels','<u4'), #Number of digital channels acquired (2*N) | |
|
193 | ('SampResolution','<u4'), #Sampling resolution (meters) | |
|
194 | ('nHeights','<u4'), #Number of range gates sampled | |
|
195 | ('StartRangeSamp','<u4'), #Start range of sampling (meters) | |
|
196 | ('PRFhz','<u4'), #PRF (Hz) | |
|
197 | ('nCohInt','<u4'), #Integrations | |
|
198 | ('nProfiles','<u4'), #Number of data points transformed | |
|
199 | ('nChannels','<u4'), #Number of receive beams stored in file (1 or N) | |
|
200 | ('nIncohInt','<u4'), #Number of spectral averages | |
|
201 | ('FFTwindowingInd','<u4'), #FFT windowing index (0 = no window) | |
|
202 | ('BeamAngleAzim','<f4'), #Beam steer angle (azimuth) in degrees (clockwise from true North) | |
|
203 | ('BeamAngleZen','<f4'), #Beam steer angle (zenith) in degrees (0=> vertical) | |
|
204 | ('AntennaCoord0','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
205 | ('AntennaAngl0','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
206 | ('AntennaCoord1','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
207 | ('AntennaAngl1','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
208 | ('AntennaCoord2','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
209 | ('AntennaAngl2','<f4'), #Antenna coordinates (Range(meters), Bearing(degrees)) - N pairs | |
|
210 | ('RecPhaseCalibr0','<f4'), #Receiver phase calibration (degrees) - N values | |
|
211 | ('RecPhaseCalibr1','<f4'), #Receiver phase calibration (degrees) - N values | |
|
212 | ('RecPhaseCalibr2','<f4'), #Receiver phase calibration (degrees) - N values | |
|
213 | ('RecAmpCalibr0','<f4'), #Receiver amplitude calibration (ratio relative to receiver one) - N values | |
|
214 | ('RecAmpCalibr1','<f4'), #Receiver amplitude calibration (ratio relative to receiver one) - N values | |
|
215 | ('RecAmpCalibr2','<f4'), #Receiver amplitude calibration (ratio relative to receiver one) - N values | |
|
216 | ('ReceiverGaindB0','<i4'), #Receiver gains in dB - N values | |
|
217 | ('ReceiverGaindB1','<i4'), #Receiver gains in dB - N values | |
|
218 | ('ReceiverGaindB2','<i4'), #Receiver gains in dB - N values | |
|
219 | ]) | |
|
220 | ||
|
221 | ||
|
222 | class RecordHeaderBLTR(Header): | |
|
223 | ||
|
224 | def __init__(self, RecMgcNumber=None, RecCounter= 0, Off2StartNxtRec= 811248, | |
|
225 | nUtime= 0, nMilisec= 0, ExpTagName= None, | |
|
226 | ExpComment=None, SiteLatDegrees=0, SiteLongDegrees= 0, | |
|
227 | RTCgpsStatus= 0, TransmitFrec= 0, ReceiveFrec= 0, | |
|
228 | FirstOsciFrec= 0, Polarisation= 0, ReceiverFiltSett= 0, | |
|
229 | nModesInUse= 0, DualModeIndex= 0, DualModeRange= 0, | |
|
230 | nDigChannels= 0, SampResolution= 0, nHeights= 0, | |
|
231 | StartRangeSamp= 0, PRFhz= 0, nCohInt= 0, | |
|
232 | nProfiles= 0, nChannels= 0, nIncohInt= 0, | |
|
233 | FFTwindowingInd= 0, BeamAngleAzim= 0, BeamAngleZen= 0, | |
|
234 | AntennaCoord0= 0, AntennaCoord1= 0, AntennaCoord2= 0, | |
|
235 | RecPhaseCalibr0= 0, RecPhaseCalibr1= 0, RecPhaseCalibr2= 0, | |
|
236 | RecAmpCalibr0= 0, RecAmpCalibr1= 0, RecAmpCalibr2= 0, | |
|
237 | AntennaAngl0=0, AntennaAngl1=0, AntennaAngl2=0, | |
|
238 | ReceiverGaindB0= 0, ReceiverGaindB1= 0, ReceiverGaindB2= 0, Off2StartData=0, OffsetStartHeader=0): | |
|
239 | ||
|
240 | self.RecMgcNumber = RecMgcNumber #0x23030001 | |
|
241 | self.RecCounter = RecCounter | |
|
242 | self.Off2StartNxtRec = Off2StartNxtRec | |
|
243 | self.Off2StartData = Off2StartData | |
|
244 | self.nUtime = nUtime | |
|
245 | self.nMilisec = nMilisec | |
|
246 | self.ExpTagName = ExpTagName | |
|
247 | self.ExpComment = ExpComment | |
|
248 | self.SiteLatDegrees = SiteLatDegrees | |
|
249 | self.SiteLongDegrees = SiteLongDegrees | |
|
250 | self.RTCgpsStatus = RTCgpsStatus | |
|
251 | self.TransmitFrec = TransmitFrec | |
|
252 | self.ReceiveFrec = ReceiveFrec | |
|
253 | self.FirstOsciFrec = FirstOsciFrec | |
|
254 | self.Polarisation = Polarisation | |
|
255 | self.ReceiverFiltSett = ReceiverFiltSett | |
|
256 | self.nModesInUse = nModesInUse | |
|
257 | self.DualModeIndex = DualModeIndex | |
|
258 | self.DualModeRange = DualModeRange | |
|
259 | self.nDigChannels = nDigChannels | |
|
260 | self.SampResolution = SampResolution | |
|
261 | self.nHeights = nHeights | |
|
262 | self.StartRangeSamp = StartRangeSamp | |
|
263 | self.PRFhz = PRFhz | |
|
264 | self.nCohInt = nCohInt | |
|
265 | self.nProfiles = nProfiles | |
|
266 | self.nChannels = nChannels | |
|
267 | self.nIncohInt = nIncohInt | |
|
268 | self.FFTwindowingInd = FFTwindowingInd | |
|
269 | self.BeamAngleAzim = BeamAngleAzim | |
|
270 | self.BeamAngleZen = BeamAngleZen | |
|
271 | self.AntennaCoord0 = AntennaCoord0 | |
|
272 | self.AntennaAngl0 = AntennaAngl0 | |
|
273 | self.AntennaAngl1 = AntennaAngl1 | |
|
274 | self.AntennaAngl2 = AntennaAngl2 | |
|
275 | self.AntennaCoord1 = AntennaCoord1 | |
|
276 | self.AntennaCoord2 = AntennaCoord2 | |
|
277 | self.RecPhaseCalibr0 = RecPhaseCalibr0 | |
|
278 | self.RecPhaseCalibr1 = RecPhaseCalibr1 | |
|
279 | self.RecPhaseCalibr2 = RecPhaseCalibr2 | |
|
280 | self.RecAmpCalibr0 = RecAmpCalibr0 | |
|
281 | self.RecAmpCalibr1 = RecAmpCalibr1 | |
|
282 | self.RecAmpCalibr2 = RecAmpCalibr2 | |
|
283 | self.ReceiverGaindB0 = ReceiverGaindB0 | |
|
284 | self.ReceiverGaindB1 = ReceiverGaindB1 | |
|
285 | self.ReceiverGaindB2 = ReceiverGaindB2 | |
|
286 | self.OffsetStartHeader = 48 | |
|
287 | ||
|
288 | ||
|
289 | ||
|
290 | def RHread(self, fp): | |
|
291 | #print fp | |
|
292 | #startFp = open('/home/erick/Documents/Data/huancayo.20161019.22.fdt',"rb") #The method tell() returns the current position of the file read/write pointer within the file. | |
|
293 | startFp = open(fp,"rb") #The method tell() returns the current position of the file read/write pointer within the file. | |
|
294 | #RecCounter=0 | |
|
295 | #Off2StartNxtRec=811248 | |
|
296 | OffRHeader= self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec | |
|
297 | print ' ' | |
|
298 | print 'puntero Record Header', startFp.tell() | |
|
299 | print ' ' | |
|
300 | ||
|
301 | ||
|
302 | startFp.seek(OffRHeader, os.SEEK_SET) | |
|
303 | ||
|
304 | print ' ' | |
|
305 | print 'puntero Record Header con seek', startFp.tell() | |
|
306 | print ' ' | |
|
307 | ||
|
308 | #print 'Posicion del bloque: ',OffRHeader | |
|
309 | ||
|
310 | header = numpy.fromfile(startFp,RECORD_STRUCTURE,1) | |
|
311 | ||
|
312 | print ' ' | |
|
313 | print 'puntero Record Header con seek', startFp.tell() | |
|
314 | print ' ' | |
|
315 | ||
|
316 | print ' ' | |
|
317 | # | |
|
318 | #print 'puntero Record Header despues de seek', header.tell() | |
|
319 | print ' ' | |
|
320 | ||
|
321 | self.RecMgcNumber = hex(header['RecMgcNumber'][0]) #0x23030001 | |
|
322 | self.RecCounter = int(header['RecCounter'][0]) | |
|
323 | self.Off2StartNxtRec = int(header['Off2StartNxtRec'][0]) | |
|
324 | self.Off2StartData = int(header['Off2StartData'][0]) | |
|
325 | self.nUtime = header['nUtime'][0] | |
|
326 | self.nMilisec = header['nMilisec'][0] | |
|
327 | self.ExpTagName = str(header['ExpTagName'][0]) | |
|
328 | self.ExpComment = str(header['ExpComment'][0]) | |
|
329 | self.SiteLatDegrees = header['SiteLatDegrees'][0] | |
|
330 | self.SiteLongDegrees = header['SiteLongDegrees'][0] | |
|
331 | self.RTCgpsStatus = header['RTCgpsStatus'][0] | |
|
332 | self.TransmitFrec = header['TransmitFrec'][0] | |
|
333 | self.ReceiveFrec = header['ReceiveFrec'][0] | |
|
334 | self.FirstOsciFrec = header['FirstOsciFrec'][0] | |
|
335 | self.Polarisation = header['Polarisation'][0] | |
|
336 | self.ReceiverFiltSett = header['ReceiverFiltSett'][0] | |
|
337 | self.nModesInUse = header['nModesInUse'][0] | |
|
338 | self.DualModeIndex = header['DualModeIndex'][0] | |
|
339 | self.DualModeRange = header['DualModeRange'][0] | |
|
340 | self.nDigChannels = header['nDigChannels'][0] | |
|
341 | self.SampResolution = header['SampResolution'][0] | |
|
342 | self.nHeights = header['nHeights'][0] | |
|
343 | self.StartRangeSamp = header['StartRangeSamp'][0] | |
|
344 | self.PRFhz = header['PRFhz'][0] | |
|
345 | self.nCohInt = header['nCohInt'][0] | |
|
346 | self.nProfiles = header['nProfiles'][0] | |
|
347 | self.nChannels = header['nChannels'][0] | |
|
348 | self.nIncohInt = header['nIncohInt'][0] | |
|
349 | self.FFTwindowingInd = header['FFTwindowingInd'][0] | |
|
350 | self.BeamAngleAzim = header['BeamAngleAzim'][0] | |
|
351 | self.BeamAngleZen = header['BeamAngleZen'][0] | |
|
352 | self.AntennaCoord0 = header['AntennaCoord0'][0] | |
|
353 | self.AntennaAngl0 = header['AntennaAngl0'][0] | |
|
354 | self.AntennaCoord1 = header['AntennaCoord1'][0] | |
|
355 | self.AntennaAngl1 = header['AntennaAngl1'][0] | |
|
356 | self.AntennaCoord2 = header['AntennaCoord2'][0] | |
|
357 | self.AntennaAngl2 = header['AntennaAngl2'][0] | |
|
358 | self.RecPhaseCalibr0 = header['RecPhaseCalibr0'][0] | |
|
359 | self.RecPhaseCalibr1 = header['RecPhaseCalibr1'][0] | |
|
360 | self.RecPhaseCalibr2 = header['RecPhaseCalibr2'][0] | |
|
361 | self.RecAmpCalibr0 = header['RecAmpCalibr0'][0] | |
|
362 | self.RecAmpCalibr1 = header['RecAmpCalibr1'][0] | |
|
363 | self.RecAmpCalibr2 = header['RecAmpCalibr2'][0] | |
|
364 | self.ReceiverGaindB0 = header['ReceiverGaindB0'][0] | |
|
365 | self.ReceiverGaindB1 = header['ReceiverGaindB1'][0] | |
|
366 | self.ReceiverGaindB2 = header['ReceiverGaindB2'][0] | |
|
367 | ||
|
368 | self.ipp= 0.5*(SPEED_OF_LIGHT/self.PRFhz) | |
|
369 | ||
|
370 | self.RHsize = 180+20*self.nChannels | |
|
371 | self.Datasize= self.nProfiles*self.nChannels*self.nHeights*2*4 | |
|
372 | #print 'Datasize',self.Datasize | |
|
373 | endFp = self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec | |
|
374 | ||
|
375 | print '==============================================' | |
|
376 | print 'RecMgcNumber ',self.RecMgcNumber | |
|
377 | print 'RecCounter ',self.RecCounter | |
|
378 | print 'Off2StartNxtRec ',self.Off2StartNxtRec | |
|
379 | print 'Off2StartData ',self.Off2StartData | |
|
380 | print 'Range Resolution ',self.SampResolution | |
|
381 | print 'First Height ',self.StartRangeSamp | |
|
382 | print 'PRF (Hz) ',self.PRFhz | |
|
383 | print 'Heights (K) ',self.nHeights | |
|
384 | print 'Channels (N) ',self.nChannels | |
|
385 | print 'Profiles (J) ',self.nProfiles | |
|
386 | print 'iCoh ',self.nCohInt | |
|
387 | print 'iInCoh ',self.nIncohInt | |
|
388 | print 'BeamAngleAzim ',self.BeamAngleAzim | |
|
389 | print 'BeamAngleZen ',self.BeamAngleZen | |
|
390 | ||
|
391 | #print 'ModoEnUso ',self.DualModeIndex | |
|
392 | #print 'UtcTime ',self.nUtime | |
|
393 | #print 'MiliSec ',self.nMilisec | |
|
394 | #print 'Exp TagName ',self.ExpTagName | |
|
395 | #print 'Exp Comment ',self.ExpComment | |
|
396 | #print 'FFT Window Index ',self.FFTwindowingInd | |
|
397 | #print 'N Dig. Channels ',self.nDigChannels | |
|
398 | print 'Size de bloque ',self.RHsize | |
|
399 | print 'DataSize ',self.Datasize | |
|
400 | print 'BeamAngleAzim ',self.BeamAngleAzim | |
|
401 | #print 'AntennaCoord0 ',self.AntennaCoord0 | |
|
402 | #print 'AntennaAngl0 ',self.AntennaAngl0 | |
|
403 | #print 'AntennaCoord1 ',self.AntennaCoord1 | |
|
404 | #print 'AntennaAngl1 ',self.AntennaAngl1 | |
|
405 | #print 'AntennaCoord2 ',self.AntennaCoord2 | |
|
406 | #print 'AntennaAngl2 ',self.AntennaAngl2 | |
|
407 | print 'RecPhaseCalibr0 ',self.RecPhaseCalibr0 | |
|
408 | print 'RecPhaseCalibr1 ',self.RecPhaseCalibr1 | |
|
409 | print 'RecPhaseCalibr2 ',self.RecPhaseCalibr2 | |
|
410 | print 'RecAmpCalibr0 ',self.RecAmpCalibr0 | |
|
411 | print 'RecAmpCalibr1 ',self.RecAmpCalibr1 | |
|
412 | print 'RecAmpCalibr2 ',self.RecAmpCalibr2 | |
|
413 | print 'ReceiverGaindB0 ',self.ReceiverGaindB0 | |
|
414 | print 'ReceiverGaindB1 ',self.ReceiverGaindB1 | |
|
415 | print 'ReceiverGaindB2 ',self.ReceiverGaindB2 | |
|
416 | print '==============================================' | |
|
417 | ||
|
418 | if OffRHeader > endFp: | |
|
419 | sys.stderr.write("Warning %s: Size value read from System Header is lower than it has to be\n" %fp) | |
|
420 | return 0 | |
|
421 | ||
|
422 | if OffRHeader < endFp: | |
|
423 | sys.stderr.write("Warning %s: Size value read from System Header size is greater than it has to be\n" %fp) | |
|
424 | return 0 | |
|
425 | ||
|
426 | return 1 | |
|
427 | ||
|
428 | ||
|
429 | class BLTRSpectraReader (ProcessingUnit, FileHeaderBLTR, RecordHeaderBLTR, JRODataReader): | |
|
430 | ||
|
431 | path = None | |
|
432 | startDate = None | |
|
433 | endDate = None | |
|
434 | startTime = None | |
|
435 | endTime = None | |
|
436 | walk = None | |
|
437 | isConfig = False | |
|
438 | ||
|
439 | ||
|
440 | fileList= None | |
|
441 | ||
|
442 | #metadata | |
|
443 | TimeZone= None | |
|
444 | Interval= None | |
|
445 | heightList= None | |
|
446 | ||
|
447 | #data | |
|
448 | data= None | |
|
449 | utctime= None | |
|
450 | ||
|
451 | ||
|
452 | ||
|
453 | def __init__(self, **kwargs): | |
|
454 | ||
|
455 | #Eliminar de la base la herencia | |
|
456 | ProcessingUnit.__init__(self, **kwargs) | |
|
457 | ||
|
458 | #self.isConfig = False | |
|
459 | ||
|
460 | #self.pts2read_SelfSpectra = 0 | |
|
461 | #self.pts2read_CrossSpectra = 0 | |
|
462 | #self.pts2read_DCchannels = 0 | |
|
463 | #self.datablock = None | |
|
464 | self.utc = None | |
|
465 | self.ext = ".fdt" | |
|
466 | self.optchar = "P" | |
|
467 | self.fpFile=None | |
|
468 | self.fp = None | |
|
469 | self.BlockCounter=0 | |
|
470 | self.dtype = None | |
|
471 | self.fileSizeByHeader = None | |
|
472 | self.filenameList = [] | |
|
473 | self.fileSelector = 0 | |
|
474 | self.Off2StartNxtRec=0 | |
|
475 | self.RecCounter=0 | |
|
476 | self.flagNoMoreFiles = 0 | |
|
477 | self.data_spc=None | |
|
478 | self.data_cspc=None | |
|
479 | self.data_output=None | |
|
480 | self.path = None | |
|
481 | self.OffsetStartHeader=0 | |
|
482 | self.Off2StartData=0 | |
|
483 | self.ipp = 0 | |
|
484 | self.nFDTdataRecors=0 | |
|
485 | self.blocksize = 0 | |
|
486 | self.dataOut = Spectra() | |
|
487 | self.profileIndex = 1 #Always | |
|
488 | self.dataOut.flagNoData=False | |
|
489 | self.dataOut.nRdPairs = 0 | |
|
490 | self.dataOut.pairsList = [] | |
|
491 | self.dataOut.data_spc=None | |
|
492 | self.dataOut.noise=[] | |
|
493 | self.dataOut.velocityX=[] | |
|
494 | self.dataOut.velocityY=[] | |
|
495 | self.dataOut.velocityV=[] | |
|
496 | ||
|
497 | ||
|
498 | ||
|
499 | def Files2Read(self, fp): | |
|
500 | ''' | |
|
501 | Function that indicates the number of .fdt files that exist in the folder to be read. | |
|
502 | It also creates an organized list with the names of the files to read. | |
|
503 | ''' | |
|
504 | #self.__checkPath() | |
|
505 | ||
|
506 | ListaData=os.listdir(fp) #Gets the list of files within the fp address | |
|
507 | ListaData=sorted(ListaData) #Sort the list of files from least to largest by names | |
|
508 | nFiles=0 #File Counter | |
|
509 | FileList=[] #A list is created that will contain the .fdt files | |
|
510 | for IndexFile in ListaData : | |
|
511 | if '.fdt' in IndexFile: | |
|
512 | FileList.append(IndexFile) | |
|
513 | nFiles+=1 | |
|
514 | ||
|
515 | #print 'Files2Read' | |
|
516 | #print 'Existen '+str(nFiles)+' archivos .fdt' | |
|
517 | ||
|
518 | self.filenameList=FileList #List of files from least to largest by names | |
|
519 | ||
|
520 | ||
|
521 | def run(self, **kwargs): | |
|
522 | ''' | |
|
523 | This method will be the one that will initiate the data entry, will be called constantly. | |
|
524 | You should first verify that your Setup () is set up and then continue to acquire | |
|
525 | the data to be processed with getData (). | |
|
526 | ''' | |
|
527 | if not self.isConfig: | |
|
528 | self.setup(**kwargs) | |
|
529 | self.isConfig = True | |
|
530 | ||
|
531 | self.getData() | |
|
532 | #print 'running' | |
|
533 | ||
|
534 | ||
|
535 | def setup(self, path=None, | |
|
536 | startDate=None, | |
|
537 | endDate=None, | |
|
538 | startTime=None, | |
|
539 | endTime=None, | |
|
540 | walk=True, | |
|
541 | timezone='utc', | |
|
542 | code = None, | |
|
543 | online=False, | |
|
544 | ReadMode=None, | |
|
545 | **kwargs): | |
|
546 | ||
|
547 | self.isConfig = True | |
|
548 | ||
|
549 | self.path=path | |
|
550 | self.startDate=startDate | |
|
551 | self.endDate=endDate | |
|
552 | self.startTime=startTime | |
|
553 | self.endTime=endTime | |
|
554 | self.walk=walk | |
|
555 | self.ReadMode=int(ReadMode) | |
|
556 | ||
|
557 | pass | |
|
558 | ||
|
559 | ||
|
560 | def getData(self): | |
|
561 | ''' | |
|
562 | Before starting this function, you should check that there is still an unread file, | |
|
563 | If there are still blocks to read or if the data block is empty. | |
|
564 | ||
|
565 | You should call the file "read". | |
|
566 | ||
|
567 | ''' | |
|
568 | ||
|
569 | if self.flagNoMoreFiles: | |
|
570 | self.dataOut.flagNoData = True | |
|
571 | print 'NoData se vuelve true' | |
|
572 | return 0 | |
|
573 | ||
|
574 | self.fp=self.path | |
|
575 | self.Files2Read(self.fp) | |
|
576 | self.readFile(self.fp) | |
|
577 | self.dataOut.data_spc = self.data_spc | |
|
578 | self.dataOut.data_cspc =self.data_cspc | |
|
579 | self.dataOut.data_output=self.data_output | |
|
580 | ||
|
581 | print 'self.dataOut.data_output', shape(self.dataOut.data_output) | |
|
582 | ||
|
583 | #self.removeDC() | |
|
584 | return self.dataOut.data_spc | |
|
585 | ||
|
586 | ||
|
587 | def readFile(self,fp): | |
|
588 | ''' | |
|
589 | You must indicate if you are reading in Online or Offline mode and load the | |
|
590 | The parameters for this file reading mode. | |
|
591 | ||
|
592 | Then you must do 2 actions: | |
|
593 | ||
|
594 | 1. Get the BLTR FileHeader. | |
|
595 | 2. Start reading the first block. | |
|
596 | ''' | |
|
597 | ||
|
598 | #The address of the folder is generated the name of the .fdt file that will be read | |
|
599 | print "File: ",self.fileSelector+1 | |
|
600 | ||
|
601 | if self.fileSelector < len(self.filenameList): | |
|
602 | ||
|
603 | self.fpFile=str(fp)+'/'+str(self.filenameList[self.fileSelector]) | |
|
604 | #print self.fpFile | |
|
605 | fheader = FileHeaderBLTR() | |
|
606 | fheader.FHread(self.fpFile) #Bltr FileHeader Reading | |
|
607 | self.nFDTdataRecors=fheader.nFDTdataRecors | |
|
608 | ||
|
609 | self.readBlock() #Block reading | |
|
610 | else: | |
|
611 | print 'readFile FlagNoData becomes true' | |
|
612 | self.flagNoMoreFiles=True | |
|
613 | self.dataOut.flagNoData = True | |
|
614 | return 0 | |
|
615 | ||
|
616 | def getVelRange(self, extrapoints=0): | |
|
617 | Lambda= SPEED_OF_LIGHT/50000000 | |
|
618 | PRF = self.dataOut.PRF#1./(self.dataOut.ippSeconds * self.dataOut.nCohInt) | |
|
619 | Vmax=-Lambda/(4.*(1./PRF)*self.dataOut.nCohInt*2.) | |
|
620 | deltafreq = PRF / (self.nProfiles) | |
|
621 | deltavel = (Vmax*2) / (self.nProfiles) | |
|
622 | freqrange = deltafreq*(numpy.arange(self.nProfiles)-self.nProfiles/2.) - deltafreq/2 | |
|
623 | velrange = deltavel*(numpy.arange(self.nProfiles)-self.nProfiles/2.) | |
|
624 | return velrange | |
|
625 | ||
|
626 | def readBlock(self): | |
|
627 | ''' | |
|
628 | It should be checked if the block has data, if it is not passed to the next file. | |
|
629 | ||
|
630 | Then the following is done: | |
|
631 | ||
|
632 | 1. Read the RecordHeader | |
|
633 | 2. Fill the buffer with the current block number. | |
|
634 | ||
|
635 | ''' | |
|
636 | ||
|
637 | if self.BlockCounter < self.nFDTdataRecors-2: | |
|
638 | print self.nFDTdataRecors, 'CONDICION!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!' | |
|
639 | if self.ReadMode==1: | |
|
640 | rheader = RecordHeaderBLTR(RecCounter=self.BlockCounter+1) | |
|
641 | elif self.ReadMode==0: | |
|
642 | rheader = RecordHeaderBLTR(RecCounter=self.BlockCounter) | |
|
643 | ||
|
644 | rheader.RHread(self.fpFile) #Bltr FileHeader Reading | |
|
645 | ||
|
646 | self.OffsetStartHeader=rheader.OffsetStartHeader | |
|
647 | self.RecCounter=rheader.RecCounter | |
|
648 | self.Off2StartNxtRec=rheader.Off2StartNxtRec | |
|
649 | self.Off2StartData=rheader.Off2StartData | |
|
650 | self.nProfiles=rheader.nProfiles | |
|
651 | self.nChannels=rheader.nChannels | |
|
652 | self.nHeights=rheader.nHeights | |
|
653 | self.frequency=rheader.TransmitFrec | |
|
654 | self.DualModeIndex=rheader.DualModeIndex | |
|
655 | ||
|
656 | self.pairsList =[(0,1),(0,2),(1,2)] | |
|
657 | self.dataOut.pairsList = self.pairsList | |
|
658 | ||
|
659 | self.nRdPairs=len(self.dataOut.pairsList) | |
|
660 | self.dataOut.nRdPairs = self.nRdPairs | |
|
661 | ||
|
662 | self.__firstHeigth=rheader.StartRangeSamp | |
|
663 | self.__deltaHeigth=rheader.SampResolution | |
|
664 | self.dataOut.heightList= self.__firstHeigth + numpy.array(range(self.nHeights))*self.__deltaHeigth | |
|
665 | self.dataOut.channelList = range(self.nChannels) | |
|
666 | self.dataOut.nProfiles=rheader.nProfiles | |
|
667 | self.dataOut.nIncohInt=rheader.nIncohInt | |
|
668 | self.dataOut.nCohInt=rheader.nCohInt | |
|
669 | self.dataOut.ippSeconds= 1/float(rheader.PRFhz) | |
|
670 | self.dataOut.PRF=rheader.PRFhz | |
|
671 | self.dataOut.nFFTPoints=rheader.nProfiles | |
|
672 | self.dataOut.utctime=rheader.nUtime | |
|
673 | self.dataOut.timeZone=0 | |
|
674 | self.dataOut.normFactor= self.dataOut.nProfiles*self.dataOut.nIncohInt*self.dataOut.nCohInt | |
|
675 | self.dataOut.outputInterval= self.dataOut.ippSeconds * self.dataOut.nCohInt * self.dataOut.nIncohInt * self.nProfiles | |
|
676 | ||
|
677 | self.data_output=numpy.ones([3,rheader.nHeights])*numpy.NaN | |
|
678 | print 'self.data_output', shape(self.data_output) | |
|
679 | self.dataOut.velocityX=[] | |
|
680 | self.dataOut.velocityY=[] | |
|
681 | self.dataOut.velocityV=[] | |
|
682 | ||
|
683 | '''Block Reading, the Block Data is received and Reshape is used to give it | |
|
684 | shape. | |
|
685 | ''' | |
|
686 | ||
|
687 | #Procedure to take the pointer to where the date block starts | |
|
688 | startDATA = open(self.fpFile,"rb") | |
|
689 | OffDATA= self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec+self.Off2StartData | |
|
690 | startDATA.seek(OffDATA, os.SEEK_SET) | |
|
691 | ||
|
692 | def moving_average(x, N=2): | |
|
693 | return numpy.convolve(x, numpy.ones((N,))/N)[(N-1):] | |
|
694 | ||
|
695 | def gaus(xSamples,a,x0,sigma): | |
|
696 | return a*exp(-(xSamples-x0)**2/(2*sigma**2)) | |
|
697 | ||
|
698 | def Find(x,value): | |
|
699 | for index in range(len(x)): | |
|
700 | if x[index]==value: | |
|
701 | return index | |
|
702 | ||
|
703 | def pol2cart(rho, phi): | |
|
704 | x = rho * numpy.cos(phi) | |
|
705 | y = rho * numpy.sin(phi) | |
|
706 | return(x, y) | |
|
707 | ||
|
708 | ||
|
709 | ||
|
710 | ||
|
711 | if self.DualModeIndex==self.ReadMode: | |
|
712 | ||
|
713 | self.data_fft = numpy.fromfile( startDATA, [('complex','<c8')],self.nProfiles*self.nChannels*self.nHeights ) | |
|
714 | ||
|
715 | self.data_fft=self.data_fft.astype(numpy.dtype('complex')) | |
|
716 | ||
|
717 | self.data_block=numpy.reshape(self.data_fft,(self.nHeights, self.nChannels, self.nProfiles )) | |
|
718 | ||
|
719 | self.data_block = numpy.transpose(self.data_block, (1,2,0)) | |
|
720 | ||
|
721 | copy = self.data_block.copy() | |
|
722 | spc = copy * numpy.conjugate(copy) | |
|
723 | ||
|
724 | self.data_spc = numpy.absolute(spc) # valor absoluto o magnitud | |
|
725 | ||
|
726 | factor = self.dataOut.normFactor | |
|
727 | ||
|
728 | ||
|
729 | z = self.data_spc.copy()#/factor | |
|
730 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
|
731 | #zdB = 10*numpy.log10(z) | |
|
732 | print ' ' | |
|
733 | print 'Z: ' | |
|
734 | print shape(z) | |
|
735 | print ' ' | |
|
736 | print ' ' | |
|
737 | ||
|
738 | self.dataOut.data_spc=self.data_spc | |
|
739 | ||
|
740 | self.noise = self.dataOut.getNoise(ymin_index=80, ymax_index=132)#/factor | |
|
741 | #noisedB = 10*numpy.log10(self.noise) | |
|
742 | ||
|
743 | ||
|
744 | ySamples=numpy.ones([3,self.nProfiles]) | |
|
745 | phase=numpy.ones([3,self.nProfiles]) | |
|
746 | CSPCSamples=numpy.ones([3,self.nProfiles],dtype=numpy.complex_) | |
|
747 | coherence=numpy.ones([3,self.nProfiles]) | |
|
748 | PhaseSlope=numpy.ones(3) | |
|
749 | PhaseInter=numpy.ones(3) | |
|
750 | ||
|
751 | '''****** Getting CrossSpectra ******''' | |
|
752 | cspc=self.data_block.copy() | |
|
753 | self.data_cspc=self.data_block.copy() | |
|
754 | ||
|
755 | xFrec=self.getVelRange(1) | |
|
756 | VelRange=self.getVelRange(1) | |
|
757 | self.dataOut.VelRange=VelRange | |
|
758 | #print ' ' | |
|
759 | #print ' ' | |
|
760 | #print 'xFrec',xFrec | |
|
761 | #print ' ' | |
|
762 | #print ' ' | |
|
763 | #Height=35 | |
|
764 | for i in range(self.nRdPairs): | |
|
765 | ||
|
766 | chan_index0 = self.dataOut.pairsList[i][0] | |
|
767 | chan_index1 = self.dataOut.pairsList[i][1] | |
|
768 | ||
|
769 | self.data_cspc[i,:,:]=cspc[chan_index0,:,:] * numpy.conjugate(cspc[chan_index1,:,:]) | |
|
770 | ||
|
771 | ||
|
772 | '''Getting Eij and Nij''' | |
|
773 | (AntennaX0,AntennaY0)=pol2cart(rheader.AntennaCoord0, rheader.AntennaAngl0*numpy.pi/180) | |
|
774 | (AntennaX1,AntennaY1)=pol2cart(rheader.AntennaCoord1, rheader.AntennaAngl1*numpy.pi/180) | |
|
775 | (AntennaX2,AntennaY2)=pol2cart(rheader.AntennaCoord2, rheader.AntennaAngl2*numpy.pi/180) | |
|
776 | ||
|
777 | E01=AntennaX0-AntennaX1 | |
|
778 | N01=AntennaY0-AntennaY1 | |
|
779 | ||
|
780 | E02=AntennaX0-AntennaX2 | |
|
781 | N02=AntennaY0-AntennaY2 | |
|
782 | ||
|
783 | E12=AntennaX1-AntennaX2 | |
|
784 | N12=AntennaY1-AntennaY2 | |
|
785 | ||
|
786 | self.ChanDist= numpy.array([[E01, N01],[E02,N02],[E12,N12]]) | |
|
787 | ||
|
788 | self.dataOut.ChanDist = self.ChanDist | |
|
789 | ||
|
790 | ||
|
791 | # for Height in range(self.nHeights): | |
|
792 | # | |
|
793 | # for i in range(self.nRdPairs): | |
|
794 | # | |
|
795 | # '''****** Line of Data SPC ******''' | |
|
796 | # zline=z[i,:,Height] | |
|
797 | # | |
|
798 | # '''****** DC is removed ******''' | |
|
799 | # DC=Find(zline,numpy.amax(zline)) | |
|
800 | # zline[DC]=(zline[DC-1]+zline[DC+1])/2 | |
|
801 | # | |
|
802 | # | |
|
803 | # '''****** SPC is normalized ******''' | |
|
804 | # FactNorm= zline.copy() / numpy.sum(zline.copy()) | |
|
805 | # FactNorm= FactNorm/numpy.sum(FactNorm) | |
|
806 | # | |
|
807 | # SmoothSPC=moving_average(FactNorm,N=3) | |
|
808 | # | |
|
809 | # xSamples = ar(range(len(SmoothSPC))) | |
|
810 | # ySamples[i] = SmoothSPC-self.noise[i] | |
|
811 | # | |
|
812 | # for i in range(self.nRdPairs): | |
|
813 | # | |
|
814 | # '''****** Line of Data CSPC ******''' | |
|
815 | # cspcLine=self.data_cspc[i,:,Height].copy() | |
|
816 | # | |
|
817 | # | |
|
818 | # | |
|
819 | # '''****** CSPC is normalized ******''' | |
|
820 | # chan_index0 = self.dataOut.pairsList[i][0] | |
|
821 | # chan_index1 = self.dataOut.pairsList[i][1] | |
|
822 | # CSPCFactor= numpy.sum(ySamples[chan_index0]) * numpy.sum(ySamples[chan_index1]) | |
|
823 | # | |
|
824 | # | |
|
825 | # CSPCNorm= cspcLine.copy() / numpy.sqrt(CSPCFactor) | |
|
826 | # | |
|
827 | # | |
|
828 | # CSPCSamples[i] = CSPCNorm-self.noise[i] | |
|
829 | # coherence[i] = numpy.abs(CSPCSamples[i]) / numpy.sqrt(CSPCFactor) | |
|
830 | # | |
|
831 | # '''****** DC is removed ******''' | |
|
832 | # DC=Find(coherence[i],numpy.amax(coherence[i])) | |
|
833 | # coherence[i][DC]=(coherence[i][DC-1]+coherence[i][DC+1])/2 | |
|
834 | # coherence[i]= moving_average(coherence[i],N=2) | |
|
835 | # | |
|
836 | # phase[i] = moving_average( numpy.arctan2(CSPCSamples[i].imag, CSPCSamples[i].real),N=1)#*180/numpy.pi | |
|
837 | # | |
|
838 | # | |
|
839 | # '''****** Getting fij width ******''' | |
|
840 | # | |
|
841 | # yMean=[] | |
|
842 | # yMean2=[] | |
|
843 | # | |
|
844 | # for j in range(len(ySamples[1])): | |
|
845 | # yMean=numpy.append(yMean,numpy.average([ySamples[0,j],ySamples[1,j],ySamples[2,j]])) | |
|
846 | # | |
|
847 | # '''******* Getting fitting Gaussian ******''' | |
|
848 | # meanGauss=sum(xSamples*yMean) / len(xSamples) | |
|
849 | # sigma=sum(yMean*(xSamples-meanGauss)**2) / len(xSamples) | |
|
850 | # #print 'Height',Height,'SNR', meanGauss/sigma**2 | |
|
851 | # | |
|
852 | # if (abs(meanGauss/sigma**2) > 0.0001) : | |
|
853 | # | |
|
854 | # try: | |
|
855 | # popt,pcov = curve_fit(gaus,xSamples,yMean,p0=[1,meanGauss,sigma]) | |
|
856 | # | |
|
857 | # if numpy.amax(popt)>numpy.amax(yMean)*0.3: | |
|
858 | # FitGauss=gaus(xSamples,*popt) | |
|
859 | # | |
|
860 | # else: | |
|
861 | # FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) | |
|
862 | # print 'Verificador: Dentro', Height | |
|
863 | # except RuntimeError: | |
|
864 | # | |
|
865 | # try: | |
|
866 | # for j in range(len(ySamples[1])): | |
|
867 | # yMean2=numpy.append(yMean2,numpy.average([ySamples[1,j],ySamples[2,j]])) | |
|
868 | # popt,pcov = curve_fit(gaus,xSamples,yMean2,p0=[1,meanGauss,sigma]) | |
|
869 | # FitGauss=gaus(xSamples,*popt) | |
|
870 | # print 'Verificador: Exepcion1', Height | |
|
871 | # except RuntimeError: | |
|
872 | # | |
|
873 | # try: | |
|
874 | # popt,pcov = curve_fit(gaus,xSamples,ySamples[1],p0=[1,meanGauss,sigma]) | |
|
875 | # FitGauss=gaus(xSamples,*popt) | |
|
876 | # print 'Verificador: Exepcion2', Height | |
|
877 | # except RuntimeError: | |
|
878 | # FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) | |
|
879 | # print 'Verificador: Exepcion3', Height | |
|
880 | # else: | |
|
881 | # FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean) | |
|
882 | # #print 'Verificador: Fuera', Height | |
|
883 | # | |
|
884 | # | |
|
885 | # | |
|
886 | # Maximun=numpy.amax(yMean) | |
|
887 | # eMinus1=Maximun*numpy.exp(-1) | |
|
888 | # | |
|
889 | # HWpos=Find(FitGauss,min(FitGauss, key=lambda value:abs(value-eMinus1))) | |
|
890 | # HalfWidth= xFrec[HWpos] | |
|
891 | # GCpos=Find(FitGauss, numpy.amax(FitGauss)) | |
|
892 | # Vpos=Find(FactNorm, numpy.amax(FactNorm)) | |
|
893 | # #Vpos=numpy.sum(FactNorm)/len(FactNorm) | |
|
894 | # #Vpos=Find(FactNorm, min(FactNorm, key=lambda value:abs(value- numpy.mean(FactNorm) ))) | |
|
895 | # #print 'GCpos',GCpos, numpy.amax(FitGauss), 'HWpos',HWpos | |
|
896 | # '''****** Getting Fij ******''' | |
|
897 | # | |
|
898 | # GaussCenter=xFrec[GCpos] | |
|
899 | # if (GaussCenter<0 and HalfWidth>0) or (GaussCenter>0 and HalfWidth<0): | |
|
900 | # Fij=abs(GaussCenter)+abs(HalfWidth)+0.0000001 | |
|
901 | # else: | |
|
902 | # Fij=abs(GaussCenter-HalfWidth)+0.0000001 | |
|
903 | # | |
|
904 | # '''****** Getting Frecuency range of significant data ******''' | |
|
905 | # | |
|
906 | # Rangpos=Find(FitGauss,min(FitGauss, key=lambda value:abs(value-Maximun*0.10))) | |
|
907 | # | |
|
908 | # if Rangpos<GCpos: | |
|
909 | # Range=numpy.array([Rangpos,2*GCpos-Rangpos]) | |
|
910 | # else: | |
|
911 | # Range=numpy.array([2*GCpos-Rangpos,Rangpos]) | |
|
912 | # | |
|
913 | # FrecRange=xFrec[Range[0]:Range[1]] | |
|
914 | # | |
|
915 | # #print 'FrecRange', FrecRange | |
|
916 | # '''****** Getting SCPC Slope ******''' | |
|
917 | # | |
|
918 | # for i in range(self.nRdPairs): | |
|
919 | # | |
|
920 | # if len(FrecRange)>5 and len(FrecRange)<self.nProfiles*0.5: | |
|
921 | # PhaseRange=moving_average(phase[i,Range[0]:Range[1]],N=3) | |
|
922 | # | |
|
923 | # slope, intercept, r_value, p_value, std_err = stats.linregress(FrecRange,PhaseRange) | |
|
924 | # PhaseSlope[i]=slope | |
|
925 | # PhaseInter[i]=intercept | |
|
926 | # else: | |
|
927 | # PhaseSlope[i]=0 | |
|
928 | # PhaseInter[i]=0 | |
|
929 | # | |
|
930 | # # plt.figure(i+15) | |
|
931 | # # plt.title('FASE ( CH%s*CH%s )' %(self.dataOut.pairsList[i][0],self.dataOut.pairsList[i][1])) | |
|
932 | # # plt.xlabel('Frecuencia (KHz)') | |
|
933 | # # plt.ylabel('Magnitud') | |
|
934 | # # #plt.subplot(311+i) | |
|
935 | # # plt.plot(FrecRange,PhaseRange,'b') | |
|
936 | # # plt.plot(FrecRange,FrecRange*PhaseSlope[i]+PhaseInter[i],'r') | |
|
937 | # | |
|
938 | # #plt.axis([-0.6, 0.2, -3.2, 3.2]) | |
|
939 | # | |
|
940 | # | |
|
941 | # '''Getting constant C''' | |
|
942 | # cC=(Fij*numpy.pi)**2 | |
|
943 | # | |
|
944 | # # '''Getting Eij and Nij''' | |
|
945 | # # (AntennaX0,AntennaY0)=pol2cart(rheader.AntennaCoord0, rheader.AntennaAngl0*numpy.pi/180) | |
|
946 | # # (AntennaX1,AntennaY1)=pol2cart(rheader.AntennaCoord1, rheader.AntennaAngl1*numpy.pi/180) | |
|
947 | # # (AntennaX2,AntennaY2)=pol2cart(rheader.AntennaCoord2, rheader.AntennaAngl2*numpy.pi/180) | |
|
948 | # # | |
|
949 | # # E01=AntennaX0-AntennaX1 | |
|
950 | # # N01=AntennaY0-AntennaY1 | |
|
951 | # # | |
|
952 | # # E02=AntennaX0-AntennaX2 | |
|
953 | # # N02=AntennaY0-AntennaY2 | |
|
954 | # # | |
|
955 | # # E12=AntennaX1-AntennaX2 | |
|
956 | # # N12=AntennaY1-AntennaY2 | |
|
957 | # | |
|
958 | # '''****** Getting constants F and G ******''' | |
|
959 | # MijEijNij=numpy.array([[E02,N02], [E12,N12]]) | |
|
960 | # MijResult0=(-PhaseSlope[1]*cC) / (2*numpy.pi) | |
|
961 | # MijResult1=(-PhaseSlope[2]*cC) / (2*numpy.pi) | |
|
962 | # MijResults=numpy.array([MijResult0,MijResult1]) | |
|
963 | # (cF,cG) = numpy.linalg.solve(MijEijNij, MijResults) | |
|
964 | # | |
|
965 | # '''****** Getting constants A, B and H ******''' | |
|
966 | # W01=numpy.amax(coherence[0]) | |
|
967 | # W02=numpy.amax(coherence[1]) | |
|
968 | # W12=numpy.amax(coherence[2]) | |
|
969 | # | |
|
970 | # WijResult0=((cF*E01+cG*N01)**2)/cC - numpy.log(W01 / numpy.sqrt(numpy.pi/cC)) | |
|
971 | # WijResult1=((cF*E02+cG*N02)**2)/cC - numpy.log(W02 / numpy.sqrt(numpy.pi/cC)) | |
|
972 | # WijResult2=((cF*E12+cG*N12)**2)/cC - numpy.log(W12 / numpy.sqrt(numpy.pi/cC)) | |
|
973 | # | |
|
974 | # WijResults=numpy.array([WijResult0, WijResult1, WijResult2]) | |
|
975 | # | |
|
976 | # WijEijNij=numpy.array([ [E01**2, N01**2, 2*E01*N01] , [E02**2, N02**2, 2*E02*N02] , [E12**2, N12**2, 2*E12*N12] ]) | |
|
977 | # (cA,cB,cH) = numpy.linalg.solve(WijEijNij, WijResults) | |
|
978 | # | |
|
979 | # VxVy=numpy.array([[cA,cH],[cH,cB]]) | |
|
980 | # | |
|
981 | # VxVyResults=numpy.array([-cF,-cG]) | |
|
982 | # (Vx,Vy) = numpy.linalg.solve(VxVy, VxVyResults) | |
|
983 | # Vzon = Vy | |
|
984 | # Vmer = Vx | |
|
985 | # Vmag=numpy.sqrt(Vzon**2+Vmer**2) | |
|
986 | # Vang=numpy.arctan2(Vmer,Vzon) | |
|
987 | # | |
|
988 | # if abs(Vy)<100 and abs(Vy)> 0.: | |
|
989 | # self.dataOut.velocityX=numpy.append(self.dataOut.velocityX, Vzon) #Vmag | |
|
990 | # #print 'Vmag',Vmag | |
|
991 | # else: | |
|
992 | # self.dataOut.velocityX=numpy.append(self.dataOut.velocityX, NaN) | |
|
993 | # | |
|
994 | # if abs(Vx)<100 and abs(Vx) > 0.: | |
|
995 | # self.dataOut.velocityY=numpy.append(self.dataOut.velocityY, Vmer) #Vang | |
|
996 | # #print 'Vang',Vang | |
|
997 | # else: | |
|
998 | # self.dataOut.velocityY=numpy.append(self.dataOut.velocityY, NaN) | |
|
999 | # | |
|
1000 | # if abs(GaussCenter)<2: | |
|
1001 | # self.dataOut.velocityV=numpy.append(self.dataOut.velocityV, xFrec[Vpos]) | |
|
1002 | # | |
|
1003 | # else: | |
|
1004 | # self.dataOut.velocityV=numpy.append(self.dataOut.velocityV, NaN) | |
|
1005 | # | |
|
1006 | # | |
|
1007 | # # print '********************************************' | |
|
1008 | # # print 'HalfWidth ', HalfWidth | |
|
1009 | # # print 'Maximun ', Maximun | |
|
1010 | # # print 'eMinus1 ', eMinus1 | |
|
1011 | # # print 'Rangpos ', Rangpos | |
|
1012 | # # print 'GaussCenter ',GaussCenter | |
|
1013 | # # print 'E01 ',E01 | |
|
1014 | # # print 'N01 ',N01 | |
|
1015 | # # print 'E02 ',E02 | |
|
1016 | # # print 'N02 ',N02 | |
|
1017 | # # print 'E12 ',E12 | |
|
1018 | # # print 'N12 ',N12 | |
|
1019 | # #print 'self.dataOut.velocityX ', self.dataOut.velocityX | |
|
1020 | # # print 'Fij ', Fij | |
|
1021 | # # print 'cC ', cC | |
|
1022 | # # print 'cF ', cF | |
|
1023 | # # print 'cG ', cG | |
|
1024 | # # print 'cA ', cA | |
|
1025 | # # print 'cB ', cB | |
|
1026 | # # print 'cH ', cH | |
|
1027 | # # print 'Vx ', Vx | |
|
1028 | # # print 'Vy ', Vy | |
|
1029 | # # print 'Vmag ', Vmag | |
|
1030 | # # print 'Vang ', Vang*180/numpy.pi | |
|
1031 | # # print 'PhaseSlope ',PhaseSlope[0] | |
|
1032 | # # print 'PhaseSlope ',PhaseSlope[1] | |
|
1033 | # # print 'PhaseSlope ',PhaseSlope[2] | |
|
1034 | # # print '********************************************' | |
|
1035 | # #print 'data_output',shape(self.dataOut.velocityX), shape(self.dataOut.velocityY) | |
|
1036 | # | |
|
1037 | # #print 'self.dataOut.velocityX', len(self.dataOut.velocityX) | |
|
1038 | # #print 'self.dataOut.velocityY', len(self.dataOut.velocityY) | |
|
1039 | # #print 'self.dataOut.velocityV', self.dataOut.velocityV | |
|
1040 | # | |
|
1041 | # self.data_output[0]=numpy.array(self.dataOut.velocityX) | |
|
1042 | # self.data_output[1]=numpy.array(self.dataOut.velocityY) | |
|
1043 | # self.data_output[2]=numpy.array(self.dataOut.velocityV) | |
|
1044 | # | |
|
1045 | # prin= self.data_output[0][~numpy.isnan(self.data_output[0])] | |
|
1046 | # print ' ' | |
|
1047 | # print 'VmagAverage',numpy.mean(prin) | |
|
1048 | # print ' ' | |
|
1049 | # # plt.figure(5) | |
|
1050 | # # plt.subplot(211) | |
|
1051 | # # plt.plot(self.dataOut.velocityX,'yo:') | |
|
1052 | # # plt.subplot(212) | |
|
1053 | # # plt.plot(self.dataOut.velocityY,'yo:') | |
|
1054 | # | |
|
1055 | # # plt.figure(1) | |
|
1056 | # # # plt.subplot(121) | |
|
1057 | # # # plt.plot(xFrec,ySamples[0],'k',label='Ch0') | |
|
1058 | # # # plt.plot(xFrec,ySamples[1],'g',label='Ch1') | |
|
1059 | # # # plt.plot(xFrec,ySamples[2],'r',label='Ch2') | |
|
1060 | # # # plt.plot(xFrec,FitGauss,'yo:',label='fit') | |
|
1061 | # # # plt.legend() | |
|
1062 | # # plt.title('DATOS A ALTURA DE 2850 METROS') | |
|
1063 | # # | |
|
1064 | # # plt.xlabel('Frecuencia (KHz)') | |
|
1065 | # # plt.ylabel('Magnitud') | |
|
1066 | # # # plt.subplot(122) | |
|
1067 | # # # plt.title('Fit for Time Constant') | |
|
1068 | # # #plt.plot(xFrec,zline) | |
|
1069 | # # #plt.plot(xFrec,SmoothSPC,'g') | |
|
1070 | # # plt.plot(xFrec,FactNorm) | |
|
1071 | # # plt.axis([-4, 4, 0, 0.15]) | |
|
1072 | # # # plt.xlabel('SelfSpectra KHz') | |
|
1073 | # # | |
|
1074 | # # plt.figure(10) | |
|
1075 | # # # plt.subplot(121) | |
|
1076 | # # plt.plot(xFrec,ySamples[0],'b',label='Ch0') | |
|
1077 | # # plt.plot(xFrec,ySamples[1],'y',label='Ch1') | |
|
1078 | # # plt.plot(xFrec,ySamples[2],'r',label='Ch2') | |
|
1079 | # # # plt.plot(xFrec,FitGauss,'yo:',label='fit') | |
|
1080 | # # plt.legend() | |
|
1081 | # # plt.title('SELFSPECTRA EN CANALES') | |
|
1082 | # # | |
|
1083 | # # plt.xlabel('Frecuencia (KHz)') | |
|
1084 | # # plt.ylabel('Magnitud') | |
|
1085 | # # # plt.subplot(122) | |
|
1086 | # # # plt.title('Fit for Time Constant') | |
|
1087 | # # #plt.plot(xFrec,zline) | |
|
1088 | # # #plt.plot(xFrec,SmoothSPC,'g') | |
|
1089 | # # # plt.plot(xFrec,FactNorm) | |
|
1090 | # # # plt.axis([-4, 4, 0, 0.15]) | |
|
1091 | # # # plt.xlabel('SelfSpectra KHz') | |
|
1092 | # # | |
|
1093 | # # plt.figure(9) | |
|
1094 | # # | |
|
1095 | # # | |
|
1096 | # # plt.title('DATOS SUAVIZADOS') | |
|
1097 | # # plt.xlabel('Frecuencia (KHz)') | |
|
1098 | # # plt.ylabel('Magnitud') | |
|
1099 | # # plt.plot(xFrec,SmoothSPC,'g') | |
|
1100 | # # | |
|
1101 | # # #plt.plot(xFrec,FactNorm) | |
|
1102 | # # plt.axis([-4, 4, 0, 0.15]) | |
|
1103 | # # # plt.xlabel('SelfSpectra KHz') | |
|
1104 | # # # | |
|
1105 | # # plt.figure(2) | |
|
1106 | # # # #plt.subplot(121) | |
|
1107 | # # plt.plot(xFrec,yMean,'r',label='Mean SelfSpectra') | |
|
1108 | # # plt.plot(xFrec,FitGauss,'yo:',label='Ajuste Gaussiano') | |
|
1109 | # # # plt.plot(xFrec[Rangpos],FitGauss[Find(FitGauss,min(FitGauss, key=lambda value:abs(value-Maximun*0.1)))],'bo') | |
|
1110 | # # # #plt.plot(xFrec,phase) | |
|
1111 | # # # plt.xlabel('Suavizado, promediado KHz') | |
|
1112 | # # plt.title('SELFSPECTRA PROMEDIADO') | |
|
1113 | # # # #plt.subplot(122) | |
|
1114 | # # # #plt.plot(xSamples,zline) | |
|
1115 | # # plt.xlabel('Frecuencia (KHz)') | |
|
1116 | # # plt.ylabel('Magnitud') | |
|
1117 | # # plt.legend() | |
|
1118 | # # # | |
|
1119 | # # # plt.figure(3) | |
|
1120 | # # # plt.subplot(311) | |
|
1121 | # # # #plt.plot(xFrec,phase[0]) | |
|
1122 | # # # plt.plot(xFrec,phase[0],'g') | |
|
1123 | # # # plt.subplot(312) | |
|
1124 | # # # plt.plot(xFrec,phase[1],'g') | |
|
1125 | # # # plt.subplot(313) | |
|
1126 | # # # plt.plot(xFrec,phase[2],'g') | |
|
1127 | # # # #plt.plot(xFrec,phase[2]) | |
|
1128 | # # # | |
|
1129 | # # # plt.figure(4) | |
|
1130 | # # # | |
|
1131 | # # # plt.plot(xSamples,coherence[0],'b') | |
|
1132 | # # # plt.plot(xSamples,coherence[1],'r') | |
|
1133 | # # # plt.plot(xSamples,coherence[2],'g') | |
|
1134 | # # plt.show() | |
|
1135 | # # # | |
|
1136 | # # # plt.clf() | |
|
1137 | # # # plt.cla() | |
|
1138 | # # # plt.close() | |
|
1139 | # | |
|
1140 | # print ' ' | |
|
1141 | ||
|
1142 | ||
|
1143 | ||
|
1144 | self.BlockCounter+=2 | |
|
1145 | ||
|
1146 | else: | |
|
1147 | self.fileSelector+=1 | |
|
1148 | self.BlockCounter=0 | |
|
1149 | print "Next File" | |
|
1150 | ||
|
1151 | ||
|
1152 | ||
|
1153 | ||
|
1154 |
@@ -0,0 +1,243 | |||
|
1 | ''' | |
|
2 | Created on Aug 1, 2017 | |
|
3 | ||
|
4 | @author: Juan C. Espinoza | |
|
5 | ''' | |
|
6 | ||
|
7 | import os | |
|
8 | import sys | |
|
9 | import time | |
|
10 | import json | |
|
11 | import datetime | |
|
12 | ||
|
13 | import numpy | |
|
14 | ||
|
15 | try: | |
|
16 | import madrigal | |
|
17 | import madrigal.cedar | |
|
18 | except: | |
|
19 | print 'You should install "madrigal library" module if you want to read/write Madrigal data' | |
|
20 | ||
|
21 | from schainpy.model.proc.jroproc_base import Operation | |
|
22 | from schainpy.model.data.jrodata import Parameters | |
|
23 | ||
|
24 | MISSING = -32767 | |
|
25 | DEF_CATALOG = { | |
|
26 | 'principleInvestigator': 'Marco Milla', | |
|
27 | 'expPurpose': None, | |
|
28 | 'expMode': None, | |
|
29 | 'cycleTime': None, | |
|
30 | 'correlativeExp': None, | |
|
31 | 'sciRemarks': None, | |
|
32 | 'instRemarks': None | |
|
33 | } | |
|
34 | DEF_HEADER = { | |
|
35 | 'kindatDesc': None, | |
|
36 | 'analyst': 'Jicamarca User', | |
|
37 | 'comments': None, | |
|
38 | 'history': None | |
|
39 | } | |
|
40 | MNEMONICS = { | |
|
41 | 10: 'jro', | |
|
42 | 11: 'jbr', | |
|
43 | 840: 'jul', | |
|
44 | 13: 'jas', | |
|
45 | 1000: 'pbr', | |
|
46 | 1001: 'hbr', | |
|
47 | 1002: 'obr', | |
|
48 | } | |
|
49 | ||
|
50 | def load_json(obj): | |
|
51 | ''' | |
|
52 | Parse json as string instead of unicode | |
|
53 | ''' | |
|
54 | ||
|
55 | if isinstance(obj, str): | |
|
56 | obj = json.loads(obj) | |
|
57 | ||
|
58 | return {str(k): load_json(v) if isinstance(v, dict) else str(v) if isinstance(v, unicode) else v | |
|
59 | for k, v in obj.items()} | |
|
60 | ||
|
61 | ||
|
62 | class MAD2Writer(Operation): | |
|
63 | ||
|
64 | def __init__(self, **kwargs): | |
|
65 | ||
|
66 | Operation.__init__(self, **kwargs) | |
|
67 | self.dataOut = Parameters() | |
|
68 | self.path = None | |
|
69 | self.dataOut = None | |
|
70 | self.ext = '.dat' | |
|
71 | ||
|
72 | return | |
|
73 | ||
|
74 | def run(self, dataOut, path, oneDList, twoDParam='', twoDList='{}', metadata='{}', **kwargs): | |
|
75 | ''' | |
|
76 | Inputs: | |
|
77 | path - path where files will be created | |
|
78 | oneDList - json of one-dimensional parameters in record where keys | |
|
79 | are Madrigal codes (integers or mnemonics) and values the corresponding | |
|
80 | dataOut attribute e.g: { | |
|
81 | 'gdlatr': 'lat', | |
|
82 | 'gdlonr': 'lon', | |
|
83 | 'gdlat2':'lat', | |
|
84 | 'glon2':'lon'} | |
|
85 | twoDParam - independent parameter to get the number of rows e.g: | |
|
86 | heighList | |
|
87 | twoDList - json of two-dimensional parameters in record where keys | |
|
88 | are Madrigal codes (integers or mnemonics) and values the corresponding | |
|
89 | dataOut attribute if multidimensional array specify as tupple | |
|
90 | ('attr', pos) e.g: { | |
|
91 | 'gdalt': 'heightList', | |
|
92 | 'vn1p2': ('data_output', 0), | |
|
93 | 'vn2p2': ('data_output', 1), | |
|
94 | 'vn3': ('data_output', 2), | |
|
95 | 'snl': ('data_SNR', 'db') | |
|
96 | } | |
|
97 | metadata - json of madrigal metadata (kinst, kindat, catalog and header) | |
|
98 | ''' | |
|
99 | if not self.isConfig: | |
|
100 | self.setup(dataOut, path, oneDList, twoDParam, twoDList, metadata, **kwargs) | |
|
101 | self.isConfig = True | |
|
102 | ||
|
103 | self.putData() | |
|
104 | return | |
|
105 | ||
|
106 | def setup(self, dataOut, path, oneDList, twoDParam, twoDList, metadata, **kwargs): | |
|
107 | ''' | |
|
108 | Configure Operation | |
|
109 | ''' | |
|
110 | ||
|
111 | self.dataOut = dataOut | |
|
112 | self.nmodes = self.dataOut.nmodes | |
|
113 | self.path = path | |
|
114 | self.blocks = kwargs.get('blocks', None) | |
|
115 | self.counter = 0 | |
|
116 | self.oneDList = load_json(oneDList) | |
|
117 | self.twoDList = load_json(twoDList) | |
|
118 | self.twoDParam = twoDParam | |
|
119 | meta = load_json(metadata) | |
|
120 | self.kinst = meta.get('kinst') | |
|
121 | self.kindat = meta.get('kindat') | |
|
122 | self.catalog = meta.get('catalog', DEF_CATALOG) | |
|
123 | self.header = meta.get('header', DEF_HEADER) | |
|
124 | ||
|
125 | return | |
|
126 | ||
|
127 | def setFile(self): | |
|
128 | ''' | |
|
129 | Create new cedar file object | |
|
130 | ''' | |
|
131 | ||
|
132 | self.mnemonic = MNEMONICS[self.kinst] #TODO get mnemonic from madrigal | |
|
133 | date = datetime.datetime.utcfromtimestamp(self.dataOut.utctime) | |
|
134 | ||
|
135 | filename = '%s%s_%s%s' % (self.mnemonic, | |
|
136 | date.strftime('%Y%m%d_%H%M%S'), | |
|
137 | self.dataOut.mode, | |
|
138 | self.ext) | |
|
139 | ||
|
140 | self.fullname = os.path.join(self.path, filename) | |
|
141 | ||
|
142 | if os.path.isfile(self.fullname) : | |
|
143 | print "Destination path '%s' already exists. Previous file deleted. " %self.fullname | |
|
144 | os.remove(self.fullname) | |
|
145 | ||
|
146 | try: | |
|
147 | print '[Writing] creating file : %s' % (self.fullname) | |
|
148 | self.cedarObj = madrigal.cedar.MadrigalCedarFile(self.fullname, True) | |
|
149 | except ValueError, e: | |
|
150 | print '[Error]: Impossible to create a cedar object with "madrigal.cedar.MadrigalCedarFile" ' | |
|
151 | return | |
|
152 | ||
|
153 | return 1 | |
|
154 | ||
|
155 | def writeBlock(self): | |
|
156 | ''' | |
|
157 | Add data records to cedar file taking data from oneDList and twoDList | |
|
158 | attributes. | |
|
159 | Allowed parameters in: parcodes.tab | |
|
160 | ''' | |
|
161 | ||
|
162 | startTime = datetime.datetime.utcfromtimestamp(self.dataOut.utctime) | |
|
163 | endTime = startTime + datetime.timedelta(seconds=self.dataOut.paramInterval) | |
|
164 | nrows = len(getattr(self.dataOut, self.twoDParam)) | |
|
165 | ||
|
166 | rec = madrigal.cedar.MadrigalDataRecord( | |
|
167 | self.kinst, | |
|
168 | self.kindat, | |
|
169 | startTime.year, | |
|
170 | startTime.month, | |
|
171 | startTime.day, | |
|
172 | startTime.hour, | |
|
173 | startTime.minute, | |
|
174 | startTime.second, | |
|
175 | startTime.microsecond/10000, | |
|
176 | endTime.year, | |
|
177 | endTime.month, | |
|
178 | endTime.day, | |
|
179 | endTime.hour, | |
|
180 | endTime.minute, | |
|
181 | endTime.second, | |
|
182 | endTime.microsecond/10000, | |
|
183 | self.oneDList.keys(), | |
|
184 | self.twoDList.keys(), | |
|
185 | nrows | |
|
186 | ) | |
|
187 | ||
|
188 | # Setting 1d values | |
|
189 | for key in self.oneDList: | |
|
190 | rec.set1D(key, getattr(self.dataOut, self.oneDList[key])) | |
|
191 | ||
|
192 | # Setting 2d values | |
|
193 | invalid = numpy.isnan(self.dataOut.data_output) | |
|
194 | self.dataOut.data_output[invalid] = MISSING | |
|
195 | out = {} | |
|
196 | for key, value in self.twoDList.items(): | |
|
197 | if isinstance(value, str): | |
|
198 | out[key] = getattr(self.dataOut, value) | |
|
199 | elif isinstance(value, tuple): | |
|
200 | attr, x = value | |
|
201 | if isinstance(x, (int, float)): | |
|
202 | out[key] = getattr(self.dataOut, attr)[int(x)] | |
|
203 | elif x.lower()=='db': | |
|
204 | tmp = getattr(self.dataOut, attr) | |
|
205 | SNRavg = numpy.average(tmp, axis=0) | |
|
206 | out[key] = 10*numpy.log10(SNRavg) | |
|
207 | ||
|
208 | for n in range(nrows): | |
|
209 | for key in out: | |
|
210 | rec.set2D(key, n, out[key][n]) | |
|
211 | ||
|
212 | self.cedarObj.append(rec) | |
|
213 | self.cedarObj.dump() | |
|
214 | print '[Writing] Record No. {} (mode {}).'.format( | |
|
215 | self.counter, | |
|
216 | self.dataOut.mode | |
|
217 | ) | |
|
218 | ||
|
219 | def setHeader(self): | |
|
220 | ''' | |
|
221 | Create an add catalog and header to cedar file | |
|
222 | ''' | |
|
223 | ||
|
224 | header = madrigal.cedar.CatalogHeaderCreator(self.fullname) | |
|
225 | header.createCatalog(**self.catalog) | |
|
226 | header.createHeader(**self.header) | |
|
227 | header.write() | |
|
228 | ||
|
229 | def putData(self): | |
|
230 | ||
|
231 | if self.dataOut.flagNoData: | |
|
232 | return 0 | |
|
233 | ||
|
234 | if self.counter == 0: | |
|
235 | self.setFile() | |
|
236 | ||
|
237 | if self.counter <= self.dataOut.nrecords: | |
|
238 | self.writeBlock() | |
|
239 | self.counter += 1 | |
|
240 | ||
|
241 | if self.counter == self.dataOut.nrecords or self.counter == self.blocks: | |
|
242 | self.setHeader() | |
|
243 | self.counter = 0 |
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|
1 | import os, sys | |
|
2 | import glob | |
|
3 | import fnmatch | |
|
4 | import datetime | |
|
5 | import time | |
|
6 | import re | |
|
7 | import h5py | |
|
8 | import numpy | |
|
9 | import matplotlib.pyplot as plt | |
|
10 | ||
|
11 | import pylab as plb | |
|
12 | from scipy.optimize import curve_fit | |
|
13 | from scipy import asarray as ar,exp | |
|
14 | from scipy import stats | |
|
15 | ||
|
16 | from numpy.ma.core import getdata | |
|
17 | ||
|
18 | SPEED_OF_LIGHT = 299792458 | |
|
19 | SPEED_OF_LIGHT = 3e8 | |
|
20 | ||
|
21 | try: | |
|
22 | from gevent import sleep | |
|
23 | except: | |
|
24 | from time import sleep | |
|
25 | ||
|
26 | from schainpy.model.data.jrodata import Spectra | |
|
27 | #from schainpy.model.data.BLTRheaderIO import FileHeader, RecordHeader | |
|
28 | from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation | |
|
29 | #from schainpy.model.io.jroIO_bltr import BLTRReader | |
|
30 | from numpy import imag, shape, NaN, empty | |
|
31 | ||
|
32 | ||
|
33 | ||
|
34 | class Header(object): | |
|
35 | ||
|
36 | def __init__(self): | |
|
37 | raise NotImplementedError | |
|
38 | ||
|
39 | ||
|
40 | def read(self): | |
|
41 | ||
|
42 | raise NotImplementedError | |
|
43 | ||
|
44 | def write(self): | |
|
45 | ||
|
46 | raise NotImplementedError | |
|
47 | ||
|
48 | def printInfo(self): | |
|
49 | ||
|
50 | message = "#"*50 + "\n" | |
|
51 | message += self.__class__.__name__.upper() + "\n" | |
|
52 | message += "#"*50 + "\n" | |
|
53 | ||
|
54 | keyList = self.__dict__.keys() | |
|
55 | keyList.sort() | |
|
56 | ||
|
57 | for key in keyList: | |
|
58 | message += "%s = %s" %(key, self.__dict__[key]) + "\n" | |
|
59 | ||
|
60 | if "size" not in keyList: | |
|
61 | attr = getattr(self, "size") | |
|
62 | ||
|
63 | if attr: | |
|
64 | message += "%s = %s" %("size", attr) + "\n" | |
|
65 | ||
|
66 | #print message | |
|
67 | ||
|
68 | ||
|
69 | FILE_HEADER = numpy.dtype([ #HEADER 1024bytes | |
|
70 | ('Hname','a32'), #Original file name | |
|
71 | ('Htime',numpy.str_,32), #Date and time when the file was created | |
|
72 | ('Hoper',numpy.str_,64), #Name of operator who created the file | |
|
73 | ('Hplace',numpy.str_,128), #Place where the measurements was carried out | |
|
74 | ('Hdescr',numpy.str_,256), #Description of measurements | |
|
75 | ('Hdummy',numpy.str_,512), #Reserved space | |
|
76 | #Main chunk 8bytes | |
|
77 | ('Msign',numpy.str_,4), #Main chunk signature FZKF or NUIG | |
|
78 | ('MsizeData','<i4'), #Size of data block main chunk | |
|
79 | #Processing DSP parameters 36bytes | |
|
80 | ('PPARsign',numpy.str_,4), #PPAR signature | |
|
81 | ('PPARsize','<i4'), #PPAR size of block | |
|
82 | ('PPARprf','<i4'), #Pulse repetition frequency | |
|
83 | ('PPARpdr','<i4'), #Pulse duration | |
|
84 | ('PPARsft','<i4'), #FFT length | |
|
85 | ('PPARavc','<i4'), #Number of spectral (in-coherent) averages | |
|
86 | ('PPARihp','<i4'), #Number of lowest range gate for moment estimation | |
|
87 | ('PPARchg','<i4'), #Count for gates for moment estimation | |
|
88 | ('PPARpol','<i4'), #switch on/off polarimetric measurements. Should be 1. | |
|
89 | #Service DSP parameters 112bytes | |
|
90 | ('SPARatt','<i4'), #STC attenuation on the lowest ranges on/off | |
|
91 | ('SPARtx','<i4'), #OBSOLETE | |
|
92 | ('SPARaddGain0','<f4'), #OBSOLETE | |
|
93 | ('SPARaddGain1','<f4'), #OBSOLETE | |
|
94 | ('SPARwnd','<i4'), #Debug only. It normal mode it is 0. | |
|
95 | ('SPARpos','<i4'), #Delay between sync pulse and tx pulse for phase corr, ns | |
|
96 | ('SPARadd','<i4'), #"add to pulse" to compensate for delay between the leading edge of driver pulse and envelope of the RF signal. | |
|
97 | ('SPARlen','<i4'), #Time for measuring txn pulse phase. OBSOLETE | |
|
98 | ('SPARcal','<i4'), #OBSOLETE | |
|
99 | ('SPARnos','<i4'), #OBSOLETE | |
|
100 | ('SPARof0','<i4'), #detection threshold | |
|
101 | ('SPARof1','<i4'), #OBSOLETE | |
|
102 | ('SPARswt','<i4'), #2nd moment estimation threshold | |
|
103 | ('SPARsum','<i4'), #OBSOLETE | |
|
104 | ('SPARosc','<i4'), #flag Oscillosgram mode | |
|
105 | ('SPARtst','<i4'), #OBSOLETE | |
|
106 | ('SPARcor','<i4'), #OBSOLETE | |
|
107 | ('SPARofs','<i4'), #OBSOLETE | |
|
108 | ('SPARhsn','<i4'), #Hildebrand div noise detection on noise gate | |
|
109 | ('SPARhsa','<f4'), #Hildebrand div noise detection on all gates | |
|
110 | ('SPARcalibPow_M','<f4'), #OBSOLETE | |
|
111 | ('SPARcalibSNR_M','<f4'), #OBSOLETE | |
|
112 | ('SPARcalibPow_S','<f4'), #OBSOLETE | |
|
113 | ('SPARcalibSNR_S','<f4'), #OBSOLETE | |
|
114 | ('SPARrawGate1','<i4'), #Lowest range gate for spectra saving Raw_Gate1 >=5 | |
|
115 | ('SPARrawGate2','<i4'), #Number of range gates with atmospheric signal | |
|
116 | ('SPARraw','<i4'), #flag - IQ or spectra saving on/off | |
|
117 | ('SPARprc','<i4'),]) #flag - Moment estimation switched on/off | |
|
118 | ||
|
119 | ||
|
120 | ||
|
121 | class FileHeaderMIRA35c(Header): | |
|
122 | ||
|
123 | def __init__(self): | |
|
124 | ||
|
125 | self.Hname= None | |
|
126 | self.Htime= None | |
|
127 | self.Hoper= None | |
|
128 | self.Hplace= None | |
|
129 | self.Hdescr= None | |
|
130 | self.Hdummy= None | |
|
131 | ||
|
132 | self.Msign=None | |
|
133 | self.MsizeData=None | |
|
134 | ||
|
135 | self.PPARsign=None | |
|
136 | self.PPARsize=None | |
|
137 | self.PPARprf=None | |
|
138 | self.PPARpdr=None | |
|
139 | self.PPARsft=None | |
|
140 | self.PPARavc=None | |
|
141 | self.PPARihp=None | |
|
142 | self.PPARchg=None | |
|
143 | self.PPARpol=None | |
|
144 | #Service DSP parameters | |
|
145 | self.SPARatt=None | |
|
146 | self.SPARtx=None | |
|
147 | self.SPARaddGain0=None | |
|
148 | self.SPARaddGain1=None | |
|
149 | self.SPARwnd=None | |
|
150 | self.SPARpos=None | |
|
151 | self.SPARadd=None | |
|
152 | self.SPARlen=None | |
|
153 | self.SPARcal=None | |
|
154 | self.SPARnos=None | |
|
155 | self.SPARof0=None | |
|
156 | self.SPARof1=None | |
|
157 | self.SPARswt=None | |
|
158 | self.SPARsum=None | |
|
159 | self.SPARosc=None | |
|
160 | self.SPARtst=None | |
|
161 | self.SPARcor=None | |
|
162 | self.SPARofs=None | |
|
163 | self.SPARhsn=None | |
|
164 | self.SPARhsa=None | |
|
165 | self.SPARcalibPow_M=None | |
|
166 | self.SPARcalibSNR_M=None | |
|
167 | self.SPARcalibPow_S=None | |
|
168 | self.SPARcalibSNR_S=None | |
|
169 | self.SPARrawGate1=None | |
|
170 | self.SPARrawGate2=None | |
|
171 | self.SPARraw=None | |
|
172 | self.SPARprc=None | |
|
173 | ||
|
174 | self.FHsize=1180 | |
|
175 | ||
|
176 | def FHread(self, fp): | |
|
177 | ||
|
178 | header = numpy.fromfile(fp, FILE_HEADER,1) | |
|
179 | ''' numpy.fromfile(file, dtype, count, sep='') | |
|
180 | file : file or str | |
|
181 | Open file object or filename. | |
|
182 | ||
|
183 | dtype : data-type | |
|
184 | Data type of the returned array. For binary files, it is used to determine | |
|
185 | the size and byte-order of the items in the file. | |
|
186 | ||
|
187 | count : int | |
|
188 | Number of items to read. -1 means all items (i.e., the complete file). | |
|
189 | ||
|
190 | sep : str | |
|
191 | Separator between items if file is a text file. Empty ("") separator means | |
|
192 | the file should be treated as binary. Spaces (" ") in the separator match zero | |
|
193 | or more whitespace characters. A separator consisting only of spaces must match | |
|
194 | at least one whitespace. | |
|
195 | ||
|
196 | ''' | |
|
197 | ||
|
198 | ||
|
199 | self.Hname= str(header['Hname'][0]) | |
|
200 | self.Htime= str(header['Htime'][0]) | |
|
201 | self.Hoper= str(header['Hoper'][0]) | |
|
202 | self.Hplace= str(header['Hplace'][0]) | |
|
203 | self.Hdescr= str(header['Hdescr'][0]) | |
|
204 | self.Hdummy= str(header['Hdummy'][0]) | |
|
205 | #1024 | |
|
206 | ||
|
207 | self.Msign=str(header['Msign'][0]) | |
|
208 | self.MsizeData=header['MsizeData'][0] | |
|
209 | #8 | |
|
210 | ||
|
211 | self.PPARsign=str(header['PPARsign'][0]) | |
|
212 | self.PPARsize=header['PPARsize'][0] | |
|
213 | self.PPARprf=header['PPARprf'][0] | |
|
214 | self.PPARpdr=header['PPARpdr'][0] | |
|
215 | self.PPARsft=header['PPARsft'][0] | |
|
216 | self.PPARavc=header['PPARavc'][0] | |
|
217 | self.PPARihp=header['PPARihp'][0] | |
|
218 | self.PPARchg=header['PPARchg'][0] | |
|
219 | self.PPARpol=header['PPARpol'][0] | |
|
220 | #Service DSP parameters | |
|
221 | #36 | |
|
222 | ||
|
223 | self.SPARatt=header['SPARatt'][0] | |
|
224 | self.SPARtx=header['SPARtx'][0] | |
|
225 | self.SPARaddGain0=header['SPARaddGain0'][0] | |
|
226 | self.SPARaddGain1=header['SPARaddGain1'][0] | |
|
227 | self.SPARwnd=header['SPARwnd'][0] | |
|
228 | self.SPARpos=header['SPARpos'][0] | |
|
229 | self.SPARadd=header['SPARadd'][0] | |
|
230 | self.SPARlen=header['SPARlen'][0] | |
|
231 | self.SPARcal=header['SPARcal'][0] | |
|
232 | self.SPARnos=header['SPARnos'][0] | |
|
233 | self.SPARof0=header['SPARof0'][0] | |
|
234 | self.SPARof1=header['SPARof1'][0] | |
|
235 | self.SPARswt=header['SPARswt'][0] | |
|
236 | self.SPARsum=header['SPARsum'][0] | |
|
237 | self.SPARosc=header['SPARosc'][0] | |
|
238 | self.SPARtst=header['SPARtst'][0] | |
|
239 | self.SPARcor=header['SPARcor'][0] | |
|
240 | self.SPARofs=header['SPARofs'][0] | |
|
241 | self.SPARhsn=header['SPARhsn'][0] | |
|
242 | self.SPARhsa=header['SPARhsa'][0] | |
|
243 | self.SPARcalibPow_M=header['SPARcalibPow_M'][0] | |
|
244 | self.SPARcalibSNR_M=header['SPARcalibSNR_M'][0] | |
|
245 | self.SPARcalibPow_S=header['SPARcalibPow_S'][0] | |
|
246 | self.SPARcalibSNR_S=header['SPARcalibSNR_S'][0] | |
|
247 | self.SPARrawGate1=header['SPARrawGate1'][0] | |
|
248 | self.SPARrawGate2=header['SPARrawGate2'][0] | |
|
249 | self.SPARraw=header['SPARraw'][0] | |
|
250 | self.SPARprc=header['SPARprc'][0] | |
|
251 | #112 | |
|
252 | #1180 | |
|
253 | #print 'Pointer fp header', fp.tell() | |
|
254 | #print ' ' | |
|
255 | #print 'SPARrawGate' | |
|
256 | #print self.SPARrawGate2 - self.SPARrawGate1 | |
|
257 | ||
|
258 | #print ' ' | |
|
259 | #print 'Hname' | |
|
260 | #print self.Hname | |
|
261 | ||
|
262 | #print ' ' | |
|
263 | #print 'Msign' | |
|
264 | #print self.Msign | |
|
265 | ||
|
266 | def write(self, fp): | |
|
267 | ||
|
268 | headerTuple = (self.Hname, | |
|
269 | self.Htime, | |
|
270 | self.Hoper, | |
|
271 | self.Hplace, | |
|
272 | self.Hdescr, | |
|
273 | self.Hdummy) | |
|
274 | ||
|
275 | ||
|
276 | header = numpy.array(headerTuple, FILE_HEADER) | |
|
277 | # numpy.array(object, dtype=None, copy=True, order=None, subok=False, ndmin=0) | |
|
278 | header.tofile(fp) | |
|
279 | ''' ndarray.tofile(fid, sep, format) Write array to a file as text or binary (default). | |
|
280 | ||
|
281 | fid : file or str | |
|
282 | An open file object, or a string containing a filename. | |
|
283 | ||
|
284 | sep : str | |
|
285 | Separator between array items for text output. If "" (empty), a binary file is written, | |
|
286 | equivalent to file.write(a.tobytes()). | |
|
287 | ||
|
288 | format : str | |
|
289 | Format string for text file output. Each entry in the array is formatted to text by | |
|
290 | first converting it to the closest Python type, and then using "format" % item. | |
|
291 | ||
|
292 | ''' | |
|
293 | ||
|
294 | return 1 | |
|
295 | ||
|
296 | SRVI_HEADER = numpy.dtype([ | |
|
297 | ('SignatureSRVI1',numpy.str_,4),# | |
|
298 | ('SizeOfDataBlock1','<i4'),# | |
|
299 | ('DataBlockTitleSRVI1',numpy.str_,4),# | |
|
300 | ('SizeOfSRVI1','<i4'),])# | |
|
301 | ||
|
302 | class SRVIHeader(Header): | |
|
303 | def __init__(self, SignatureSRVI1=0, SizeOfDataBlock1=0, DataBlockTitleSRVI1=0, SizeOfSRVI1=0): | |
|
304 | ||
|
305 | self.SignatureSRVI1 = SignatureSRVI1 | |
|
306 | self.SizeOfDataBlock1 = SizeOfDataBlock1 | |
|
307 | self.DataBlockTitleSRVI1 = DataBlockTitleSRVI1 | |
|
308 | self.SizeOfSRVI1 = SizeOfSRVI1 | |
|
309 | ||
|
310 | self.SRVIHsize=16 | |
|
311 | ||
|
312 | def SRVIread(self, fp): | |
|
313 | ||
|
314 | header = numpy.fromfile(fp, SRVI_HEADER,1) | |
|
315 | ||
|
316 | self.SignatureSRVI1 = str(header['SignatureSRVI1'][0]) | |
|
317 | self.SizeOfDataBlock1 = header['SizeOfDataBlock1'][0] | |
|
318 | self.DataBlockTitleSRVI1 = str(header['DataBlockTitleSRVI1'][0]) | |
|
319 | self.SizeOfSRVI1 = header['SizeOfSRVI1'][0] | |
|
320 | #16 | |
|
321 | print 'Pointer fp SRVIheader', fp.tell() | |
|
322 | ||
|
323 | ||
|
324 | SRVI_STRUCTURE = numpy.dtype([ | |
|
325 | ('frame_cnt','<u4'),# | |
|
326 | ('time_t','<u4'), # | |
|
327 | ('tpow','<f4'), # | |
|
328 | ('npw1','<f4'), # | |
|
329 | ('npw2','<f4'), # | |
|
330 | ('cpw1','<f4'), # | |
|
331 | ('pcw2','<f4'), # | |
|
332 | ('ps_err','<u4'), # | |
|
333 | ('te_err','<u4'), # | |
|
334 | ('rc_err','<u4'), # | |
|
335 | ('grs1','<u4'), # | |
|
336 | ('grs2','<u4'), # | |
|
337 | ('azipos','<f4'), # | |
|
338 | ('azivel','<f4'), # | |
|
339 | ('elvpos','<f4'), # | |
|
340 | ('elvvel','<f4'), # | |
|
341 | ('northAngle','<f4'), # | |
|
342 | ('microsec','<u4'), # | |
|
343 | ('azisetvel','<f4'), # | |
|
344 | ('elvsetpos','<f4'), # | |
|
345 | ('RadarConst','<f4'),]) # | |
|
346 | ||
|
347 | ||
|
348 | ||
|
349 | ||
|
350 | class RecordHeader(Header): | |
|
351 | ||
|
352 | ||
|
353 | def __init__(self, frame_cnt=0, time_t= 0, tpow=0, npw1=0, npw2=0, | |
|
354 | cpw1=0, pcw2=0, ps_err=0, te_err=0, rc_err=0, grs1=0, | |
|
355 | grs2=0, azipos=0, azivel=0, elvpos=0, elvvel=0, northangle=0, | |
|
356 | microsec=0, azisetvel=0, elvsetpos=0, RadarConst=0 , RecCounter=0, Off2StartNxtRec=0): | |
|
357 | ||
|
358 | ||
|
359 | self.frame_cnt = frame_cnt | |
|
360 | self.dwell = time_t | |
|
361 | self.tpow = tpow | |
|
362 | self.npw1 = npw1 | |
|
363 | self.npw2 = npw2 | |
|
364 | self.cpw1 = cpw1 | |
|
365 | self.pcw2 = pcw2 | |
|
366 | self.ps_err = ps_err | |
|
367 | self.te_err = te_err | |
|
368 | self.rc_err = rc_err | |
|
369 | self.grs1 = grs1 | |
|
370 | self.grs2 = grs2 | |
|
371 | self.azipos = azipos | |
|
372 | self.azivel = azivel | |
|
373 | self.elvpos = elvpos | |
|
374 | self.elvvel = elvvel | |
|
375 | self.northAngle = northangle | |
|
376 | self.microsec = microsec | |
|
377 | self.azisetvel = azisetvel | |
|
378 | self.elvsetpos = elvsetpos | |
|
379 | self.RadarConst = RadarConst | |
|
380 | self.RHsize=84 | |
|
381 | self.RecCounter = RecCounter | |
|
382 | self.Off2StartNxtRec=Off2StartNxtRec | |
|
383 | ||
|
384 | def RHread(self, fp): | |
|
385 | ||
|
386 | #startFp = open(fp,"rb") #The method tell() returns the current position of the file read/write pointer within the file. | |
|
387 | ||
|
388 | #OffRHeader= 1180 + self.RecCounter*(self.Off2StartNxtRec) | |
|
389 | #startFp.seek(OffRHeader, os.SEEK_SET) | |
|
390 | ||
|
391 | #print 'Posicion del bloque: ',OffRHeader | |
|
392 | ||
|
393 | header = numpy.fromfile(fp,SRVI_STRUCTURE,1) | |
|
394 | ||
|
395 | self.frame_cnt = header['frame_cnt'][0]# | |
|
396 | self.time_t = header['time_t'][0] # | |
|
397 | self.tpow = header['tpow'][0] # | |
|
398 | self.npw1 = header['npw1'][0] # | |
|
399 | self.npw2 = header['npw2'][0] # | |
|
400 | self.cpw1 = header['cpw1'][0] # | |
|
401 | self.pcw2 = header['pcw2'][0] # | |
|
402 | self.ps_err = header['ps_err'][0] # | |
|
403 | self.te_err = header['te_err'][0] # | |
|
404 | self.rc_err = header['rc_err'][0] # | |
|
405 | self.grs1 = header['grs1'][0] # | |
|
406 | self.grs2 = header['grs2'][0] # | |
|
407 | self.azipos = header['azipos'][0] # | |
|
408 | self.azivel = header['azivel'][0] # | |
|
409 | self.elvpos = header['elvpos'][0] # | |
|
410 | self.elvvel = header['elvvel'][0] # | |
|
411 | self.northAngle = header['northAngle'][0] # | |
|
412 | self.microsec = header['microsec'][0] # | |
|
413 | self.azisetvel = header['azisetvel'][0] # | |
|
414 | self.elvsetpos = header['elvsetpos'][0] # | |
|
415 | self.RadarConst = header['RadarConst'][0] # | |
|
416 | #84 | |
|
417 | ||
|
418 | #print 'Pointer fp RECheader', fp.tell() | |
|
419 | ||
|
420 | #self.ipp= 0.5*(SPEED_OF_LIGHT/self.PRFhz) | |
|
421 | ||
|
422 | #self.RHsize = 180+20*self.nChannels | |
|
423 | #self.Datasize= self.nProfiles*self.nChannels*self.nHeights*2*4 | |
|
424 | #print 'Datasize',self.Datasize | |
|
425 | #endFp = self.OffsetStartHeader + self.RecCounter*self.Off2StartNxtRec | |
|
426 | ||
|
427 | print '==============================================' | |
|
428 | ||
|
429 | print '==============================================' | |
|
430 | ||
|
431 | ||
|
432 | return 1 | |
|
433 | ||
|
434 | class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader): | |
|
435 | ||
|
436 | path = None | |
|
437 | startDate = None | |
|
438 | endDate = None | |
|
439 | startTime = None | |
|
440 | endTime = None | |
|
441 | walk = None | |
|
442 | isConfig = False | |
|
443 | ||
|
444 | ||
|
445 | fileList= None | |
|
446 | ||
|
447 | #metadata | |
|
448 | TimeZone= None | |
|
449 | Interval= None | |
|
450 | heightList= None | |
|
451 | ||
|
452 | #data | |
|
453 | data= None | |
|
454 | utctime= None | |
|
455 | ||
|
456 | ||
|
457 | ||
|
458 | def __init__(self, **kwargs): | |
|
459 | ||
|
460 | #Eliminar de la base la herencia | |
|
461 | ProcessingUnit.__init__(self, **kwargs) | |
|
462 | self.PointerReader = 0 | |
|
463 | self.FileHeaderFlag = False | |
|
464 | self.utc = None | |
|
465 | self.ext = ".zspca" | |
|
466 | self.optchar = "P" | |
|
467 | self.fpFile=None | |
|
468 | self.fp = None | |
|
469 | self.BlockCounter=0 | |
|
470 | self.dtype = None | |
|
471 | self.fileSizeByHeader = None | |
|
472 | self.filenameList = [] | |
|
473 | self.fileSelector = 0 | |
|
474 | self.Off2StartNxtRec=0 | |
|
475 | self.RecCounter=0 | |
|
476 | self.flagNoMoreFiles = 0 | |
|
477 | self.data_spc=None | |
|
478 | #self.data_cspc=None | |
|
479 | self.data_output=None | |
|
480 | self.path = None | |
|
481 | self.OffsetStartHeader=0 | |
|
482 | self.Off2StartData=0 | |
|
483 | self.ipp = 0 | |
|
484 | self.nFDTdataRecors=0 | |
|
485 | self.blocksize = 0 | |
|
486 | self.dataOut = Spectra() | |
|
487 | self.profileIndex = 1 #Always | |
|
488 | self.dataOut.flagNoData=False | |
|
489 | self.dataOut.nRdPairs = 0 | |
|
490 | self.dataOut.pairsList = [] | |
|
491 | self.dataOut.data_spc=None | |
|
492 | ||
|
493 | self.dataOut.normFactor=1 | |
|
494 | self.nextfileflag = True | |
|
495 | self.dataOut.RadarConst = 0 | |
|
496 | self.dataOut.HSDV = [] | |
|
497 | self.dataOut.NPW = [] | |
|
498 | self.dataOut.COFA = [] | |
|
499 | self.dataOut.noise = 0 | |
|
500 | ||
|
501 | ||
|
502 | def Files2Read(self, fp): | |
|
503 | ''' | |
|
504 | Function that indicates the number of .fdt files that exist in the folder to be read. | |
|
505 | It also creates an organized list with the names of the files to read. | |
|
506 | ''' | |
|
507 | #self.__checkPath() | |
|
508 | ||
|
509 | ListaData=os.listdir(fp) #Gets the list of files within the fp address | |
|
510 | ListaData=sorted(ListaData) #Sort the list of files from least to largest by names | |
|
511 | nFiles=0 #File Counter | |
|
512 | FileList=[] #A list is created that will contain the .fdt files | |
|
513 | for IndexFile in ListaData : | |
|
514 | if '.zspca' in IndexFile and '.gz' not in IndexFile: | |
|
515 | FileList.append(IndexFile) | |
|
516 | nFiles+=1 | |
|
517 | ||
|
518 | #print 'Files2Read' | |
|
519 | #print 'Existen '+str(nFiles)+' archivos .fdt' | |
|
520 | ||
|
521 | self.filenameList=FileList #List of files from least to largest by names | |
|
522 | ||
|
523 | ||
|
524 | def run(self, **kwargs): | |
|
525 | ''' | |
|
526 | This method will be the one that will initiate the data entry, will be called constantly. | |
|
527 | You should first verify that your Setup () is set up and then continue to acquire | |
|
528 | the data to be processed with getData (). | |
|
529 | ''' | |
|
530 | if not self.isConfig: | |
|
531 | self.setup(**kwargs) | |
|
532 | self.isConfig = True | |
|
533 | ||
|
534 | self.getData() | |
|
535 | ||
|
536 | ||
|
537 | def setup(self, path=None, | |
|
538 | startDate=None, | |
|
539 | endDate=None, | |
|
540 | startTime=None, | |
|
541 | endTime=None, | |
|
542 | walk=True, | |
|
543 | timezone='utc', | |
|
544 | code = None, | |
|
545 | online=False, | |
|
546 | ReadMode=None, **kwargs): | |
|
547 | ||
|
548 | self.isConfig = True | |
|
549 | ||
|
550 | self.path=path | |
|
551 | self.startDate=startDate | |
|
552 | self.endDate=endDate | |
|
553 | self.startTime=startTime | |
|
554 | self.endTime=endTime | |
|
555 | self.walk=walk | |
|
556 | #self.ReadMode=int(ReadMode) | |
|
557 | ||
|
558 | pass | |
|
559 | ||
|
560 | ||
|
561 | def getData(self): | |
|
562 | ''' | |
|
563 | Before starting this function, you should check that there is still an unread file, | |
|
564 | If there are still blocks to read or if the data block is empty. | |
|
565 | ||
|
566 | You should call the file "read". | |
|
567 | ||
|
568 | ''' | |
|
569 | ||
|
570 | if self.flagNoMoreFiles: | |
|
571 | self.dataOut.flagNoData = True | |
|
572 | print 'NoData se vuelve true' | |
|
573 | return 0 | |
|
574 | ||
|
575 | self.fp=self.path | |
|
576 | self.Files2Read(self.fp) | |
|
577 | self.readFile(self.fp) | |
|
578 | ||
|
579 | self.dataOut.data_spc = self.dataOut_spc#self.data_spc.copy() | |
|
580 | self.dataOut.RadarConst = self.RadarConst | |
|
581 | self.dataOut.data_output=self.data_output | |
|
582 | self.dataOut.noise = self.dataOut.getNoise() | |
|
583 | #print 'ACAAAAAA', self.dataOut.noise | |
|
584 | self.dataOut.data_spc = self.dataOut.data_spc+self.dataOut.noise | |
|
585 | #print 'self.dataOut.noise',self.dataOut.noise | |
|
586 | ||
|
587 | ||
|
588 | return self.dataOut.data_spc | |
|
589 | ||
|
590 | ||
|
591 | def readFile(self,fp): | |
|
592 | ''' | |
|
593 | You must indicate if you are reading in Online or Offline mode and load the | |
|
594 | The parameters for this file reading mode. | |
|
595 | ||
|
596 | Then you must do 2 actions: | |
|
597 | ||
|
598 | 1. Get the BLTR FileHeader. | |
|
599 | 2. Start reading the first block. | |
|
600 | ''' | |
|
601 | ||
|
602 | #The address of the folder is generated the name of the .fdt file that will be read | |
|
603 | print "File: ",self.fileSelector+1 | |
|
604 | ||
|
605 | if self.fileSelector < len(self.filenameList): | |
|
606 | ||
|
607 | self.fpFile=str(fp)+'/'+str(self.filenameList[self.fileSelector]) | |
|
608 | ||
|
609 | if self.nextfileflag==True: | |
|
610 | self.fp = open(self.fpFile,"rb") | |
|
611 | self.nextfileflag==False | |
|
612 | ||
|
613 | '''HERE STARTING THE FILE READING''' | |
|
614 | ||
|
615 | ||
|
616 | self.fheader = FileHeaderMIRA35c() | |
|
617 | self.fheader.FHread(self.fp) #Bltr FileHeader Reading | |
|
618 | ||
|
619 | ||
|
620 | self.SPARrawGate1 = self.fheader.SPARrawGate1 | |
|
621 | self.SPARrawGate2 = self.fheader.SPARrawGate2 | |
|
622 | self.Num_Hei = self.SPARrawGate2 - self.SPARrawGate1 | |
|
623 | self.Num_Bins = self.fheader.PPARsft | |
|
624 | self.dataOut.nFFTPoints = self.fheader.PPARsft | |
|
625 | ||
|
626 | ||
|
627 | self.Num_inCoh = self.fheader.PPARavc | |
|
628 | self.dataOut.PRF = self.fheader.PPARprf | |
|
629 | self.dataOut.frequency = 34.85*10**9 | |
|
630 | self.Lambda = SPEED_OF_LIGHT/self.dataOut.frequency | |
|
631 | self.dataOut.ippSeconds= 1./float(self.dataOut.PRF) | |
|
632 | ||
|
633 | pulse_width = self.fheader.PPARpdr * 10**-9 | |
|
634 | self.__deltaHeigth = 0.5 * SPEED_OF_LIGHT * pulse_width | |
|
635 | ||
|
636 | self.data_spc = numpy.zeros((self.Num_Hei, self.Num_Bins,2))# | |
|
637 | self.dataOut.HSDV = numpy.zeros((self.Num_Hei, 2)) | |
|
638 | ||
|
639 | self.Ze = numpy.zeros(self.Num_Hei) | |
|
640 | self.ETA = numpy.zeros(([2,self.Num_Hei])) | |
|
641 | ||
|
642 | ||
|
643 | ||
|
644 | self.readBlock() #Block reading | |
|
645 | ||
|
646 | else: | |
|
647 | print 'readFile FlagNoData becomes true' | |
|
648 | self.flagNoMoreFiles=True | |
|
649 | self.dataOut.flagNoData = True | |
|
650 | self.FileHeaderFlag == True | |
|
651 | return 0 | |
|
652 | ||
|
653 | ||
|
654 | ||
|
655 | def readBlock(self): | |
|
656 | ''' | |
|
657 | It should be checked if the block has data, if it is not passed to the next file. | |
|
658 | ||
|
659 | Then the following is done: | |
|
660 | ||
|
661 | 1. Read the RecordHeader | |
|
662 | 2. Fill the buffer with the current block number. | |
|
663 | ||
|
664 | ''' | |
|
665 | ||
|
666 | if self.PointerReader > 1180: | |
|
667 | self.fp.seek(self.PointerReader , os.SEEK_SET) | |
|
668 | self.FirstPoint = self.PointerReader | |
|
669 | ||
|
670 | else : | |
|
671 | self.FirstPoint = 1180 | |
|
672 | ||
|
673 | ||
|
674 | ||
|
675 | self.srviHeader = SRVIHeader() | |
|
676 | ||
|
677 | self.srviHeader.SRVIread(self.fp) #Se obtiene la cabecera del SRVI | |
|
678 | ||
|
679 | self.blocksize = self.srviHeader.SizeOfDataBlock1 # Se obtiene el tamao del bloque | |
|
680 | ||
|
681 | if self.blocksize == 148: | |
|
682 | print 'blocksize == 148 bug' | |
|
683 | jump = numpy.fromfile(self.fp,[('jump',numpy.str_,140)] ,1) | |
|
684 | ||
|
685 | self.srviHeader.SRVIread(self.fp) #Se obtiene la cabecera del SRVI | |
|
686 | ||
|
687 | if not self.srviHeader.SizeOfSRVI1: | |
|
688 | self.fileSelector+=1 | |
|
689 | self.nextfileflag==True | |
|
690 | self.FileHeaderFlag == True | |
|
691 | ||
|
692 | self.recordheader = RecordHeader() | |
|
693 | self.recordheader.RHread(self.fp) | |
|
694 | self.RadarConst = self.recordheader.RadarConst | |
|
695 | dwell = self.recordheader.time_t | |
|
696 | npw1 = self.recordheader.npw1 | |
|
697 | npw2 = self.recordheader.npw2 | |
|
698 | ||
|
699 | ||
|
700 | self.dataOut.channelList = range(1) | |
|
701 | self.dataOut.nIncohInt = self.Num_inCoh | |
|
702 | self.dataOut.nProfiles = self.Num_Bins | |
|
703 | self.dataOut.nCohInt = 1 | |
|
704 | self.dataOut.windowOfFilter = 1 | |
|
705 | self.dataOut.utctime = dwell | |
|
706 | self.dataOut.timeZone=0 | |
|
707 | ||
|
708 | self.dataOut.outputInterval = self.dataOut.getTimeInterval() | |
|
709 | self.dataOut.heightList = self.SPARrawGate1*self.__deltaHeigth + numpy.array(range(self.Num_Hei))*self.__deltaHeigth | |
|
710 | ||
|
711 | ||
|
712 | ||
|
713 | self.HSDVsign = numpy.fromfile( self.fp, [('HSDV',numpy.str_,4)],1) | |
|
714 | self.SizeHSDV = numpy.fromfile( self.fp, [('SizeHSDV','<i4')],1) | |
|
715 | self.HSDV_Co = numpy.fromfile( self.fp, [('HSDV_Co','<f4')],self.Num_Hei) | |
|
716 | self.HSDV_Cx = numpy.fromfile( self.fp, [('HSDV_Cx','<f4')],self.Num_Hei) | |
|
717 | ||
|
718 | self.COFAsign = numpy.fromfile( self.fp, [('COFA',numpy.str_,4)],1) | |
|
719 | self.SizeCOFA = numpy.fromfile( self.fp, [('SizeCOFA','<i4')],1) | |
|
720 | self.COFA_Co = numpy.fromfile( self.fp, [('COFA_Co','<f4')],self.Num_Hei) | |
|
721 | self.COFA_Cx = numpy.fromfile( self.fp, [('COFA_Cx','<f4')],self.Num_Hei) | |
|
722 | ||
|
723 | self.ZSPCsign = numpy.fromfile(self.fp, [('ZSPCsign',numpy.str_,4)],1) | |
|
724 | self.SizeZSPC = numpy.fromfile(self.fp, [('SizeZSPC','<i4')],1) | |
|
725 | ||
|
726 | self.dataOut.HSDV[0]=self.HSDV_Co[:][0] | |
|
727 | self.dataOut.HSDV[1]=self.HSDV_Cx[:][0] | |
|
728 | ||
|
729 | for irg in range(self.Num_Hei): | |
|
730 | nspc = numpy.fromfile(self.fp, [('nspc','int16')],1)[0][0] # Number of spectral sub pieces containing significant power | |
|
731 | ||
|
732 | for k in range(nspc): | |
|
733 | binIndex = numpy.fromfile(self.fp, [('binIndex','int16')],1)[0][0] # Index of the spectral bin where the piece is beginning | |
|
734 | nbins = numpy.fromfile(self.fp, [('nbins','int16')],1)[0][0] # Number of bins of the piece | |
|
735 | ||
|
736 | #Co_Channel | |
|
737 | jbin = numpy.fromfile(self.fp, [('jbin','uint16')],nbins)[0][0] # Spectrum piece to be normaliced | |
|
738 | jmax = numpy.fromfile(self.fp, [('jmax','float32')],1)[0][0] # Maximun piece to be normaliced | |
|
739 | ||
|
740 | ||
|
741 | self.data_spc[irg,binIndex:binIndex+nbins,0] = self.data_spc[irg,binIndex:binIndex+nbins,0]+jbin/65530.*jmax | |
|
742 | ||
|
743 | #Cx_Channel | |
|
744 | jbin = numpy.fromfile(self.fp, [('jbin','uint16')],nbins)[0][0] | |
|
745 | jmax = numpy.fromfile(self.fp, [('jmax','float32')],1)[0][0] | |
|
746 | ||
|
747 | ||
|
748 | self.data_spc[irg,binIndex:binIndex+nbins,1] = self.data_spc[irg,binIndex:binIndex+nbins,1]+jbin/65530.*jmax | |
|
749 | ||
|
750 | for bin in range(self.Num_Bins): | |
|
751 | ||
|
752 | self.data_spc[:,bin,0] = self.data_spc[:,bin,0] - self.dataOut.HSDV[:,0] | |
|
753 | ||
|
754 | self.data_spc[:,bin,1] = self.data_spc[:,bin,1] - self.dataOut.HSDV[:,1] | |
|
755 | ||
|
756 | ||
|
757 | numpy.set_printoptions(threshold='nan') | |
|
758 | ||
|
759 | self.data_spc = numpy.where(self.data_spc > 0. , self.data_spc, 0) | |
|
760 | ||
|
761 | self.dataOut.COFA = numpy.array([self.COFA_Co , self.COFA_Cx]) | |
|
762 | ||
|
763 | print ' ' | |
|
764 | print 'SPC',numpy.shape(self.dataOut.data_spc) | |
|
765 | #print 'SPC',self.dataOut.data_spc | |
|
766 | ||
|
767 | noinor1 = 713031680 | |
|
768 | noinor2 = 30 | |
|
769 | ||
|
770 | npw1 = 1#0**(npw1/10) * noinor1 * noinor2 | |
|
771 | npw2 = 1#0**(npw2/10) * noinor1 * noinor2 | |
|
772 | self.dataOut.NPW = numpy.array([npw1, npw2]) | |
|
773 | ||
|
774 | print ' ' | |
|
775 | ||
|
776 | self.data_spc = numpy.transpose(self.data_spc, (2,1,0)) | |
|
777 | self.data_spc = numpy.fft.fftshift(self.data_spc, axes = 1) | |
|
778 | ||
|
779 | self.data_spc = numpy.fliplr(self.data_spc) | |
|
780 | ||
|
781 | self.data_spc = numpy.where(self.data_spc > 0. , self.data_spc, 0) | |
|
782 | self.dataOut_spc= numpy.ones([1, self.Num_Bins , self.Num_Hei]) | |
|
783 | self.dataOut_spc[0,:,:] = self.data_spc[0,:,:] | |
|
784 | #print 'SHAPE', self.dataOut_spc.shape | |
|
785 | #For nyquist correction: | |
|
786 | #fix = 20 # ~3m/s | |
|
787 | #shift = self.Num_Bins/2 + fix | |
|
788 | #self.data_spc = numpy.array([ self.data_spc[: , self.Num_Bins-shift+1: , :] , self.data_spc[: , 0:self.Num_Bins-shift , :]]) | |
|
789 | ||
|
790 | ||
|
791 | ||
|
792 | '''Block Reading, the Block Data is received and Reshape is used to give it | |
|
793 | shape. | |
|
794 | ''' | |
|
795 | ||
|
796 | self.PointerReader = self.fp.tell() | |
|
797 | ||
|
798 | ||
|
799 | ||
|
800 | ||
|
801 | ||
|
802 | ||
|
803 | No newline at end of file |
@@ -0,0 +1,403 | |||
|
1 | ''' | |
|
2 | Created on Oct 24, 2016 | |
|
3 | ||
|
4 | @author: roj- LouVD | |
|
5 | ''' | |
|
6 | ||
|
7 | import numpy | |
|
8 | import copy | |
|
9 | import datetime | |
|
10 | import time | |
|
11 | from time import gmtime | |
|
12 | ||
|
13 | from numpy import transpose | |
|
14 | ||
|
15 | from jroproc_base import ProcessingUnit, Operation | |
|
16 | from schainpy.model.data.jrodata import Parameters | |
|
17 | ||
|
18 | ||
|
19 | class BLTRParametersProc(ProcessingUnit): | |
|
20 | ''' | |
|
21 | Processing unit for BLTR parameters data (winds) | |
|
22 | ||
|
23 | Inputs: | |
|
24 | self.dataOut.nmodes - Number of operation modes | |
|
25 | self.dataOut.nchannels - Number of channels | |
|
26 | self.dataOut.nranges - Number of ranges | |
|
27 | ||
|
28 | self.dataOut.data_SNR - SNR array | |
|
29 | self.dataOut.data_output - Zonal, Vertical and Meridional velocity array | |
|
30 | self.dataOut.height - Height array (km) | |
|
31 | self.dataOut.time - Time array (seconds) | |
|
32 | ||
|
33 | self.dataOut.fileIndex -Index of the file currently read | |
|
34 | self.dataOut.lat - Latitude coordinate of BLTR location | |
|
35 | ||
|
36 | self.dataOut.doy - Experiment doy (number of the day in the current year) | |
|
37 | self.dataOut.month - Experiment month | |
|
38 | self.dataOut.day - Experiment day | |
|
39 | self.dataOut.year - Experiment year | |
|
40 | ''' | |
|
41 | ||
|
42 | def __init__(self, **kwargs): | |
|
43 | ''' | |
|
44 | Inputs: None | |
|
45 | ''' | |
|
46 | ProcessingUnit.__init__(self, **kwargs) | |
|
47 | self.dataOut = Parameters() | |
|
48 | self.isConfig = False | |
|
49 | ||
|
50 | def setup(self, mode): | |
|
51 | ''' | |
|
52 | ''' | |
|
53 | self.dataOut.mode = mode | |
|
54 | ||
|
55 | def run(self, mode, snr_threshold=None): | |
|
56 | ''' | |
|
57 | Inputs: | |
|
58 | mode = High resolution (0) or Low resolution (1) data | |
|
59 | snr_threshold = snr filter value | |
|
60 | ''' | |
|
61 | ||
|
62 | if not self.isConfig: | |
|
63 | self.setup(mode) | |
|
64 | self.isConfig = True | |
|
65 | ||
|
66 | if self.dataIn.type == 'Parameters': | |
|
67 | self.dataOut.copy(self.dataIn) | |
|
68 | ||
|
69 | self.dataOut.data_output = self.dataOut.data_output[mode] | |
|
70 | self.dataOut.heightList = self.dataOut.height[0] | |
|
71 | self.dataOut.data_SNR = self.dataOut.data_SNR[mode] | |
|
72 | ||
|
73 | if snr_threshold is not None: | |
|
74 | SNRavg = numpy.average(self.dataOut.data_SNR, axis=0) | |
|
75 | SNRavgdB = 10*numpy.log10(SNRavg) | |
|
76 | for i in range(3): | |
|
77 | self.dataOut.data_output[i][SNRavgdB <= snr_threshold] = numpy.nan | |
|
78 | ||
|
79 | # TODO | |
|
80 | class OutliersFilter(Operation): | |
|
81 | ||
|
82 | def __init__(self, **kwargs): | |
|
83 | ''' | |
|
84 | ''' | |
|
85 | Operation.__init__(self, **kwargs) | |
|
86 | ||
|
87 | def run(self, svalue2, method, factor, filter, npoints=9): | |
|
88 | ''' | |
|
89 | Inputs: | |
|
90 | svalue - string to select array velocity | |
|
91 | svalue2 - string to choose axis filtering | |
|
92 | method - 0 for SMOOTH or 1 for MEDIAN | |
|
93 | factor - number used to set threshold | |
|
94 | filter - 1 for data filtering using the standard deviation criteria else 0 | |
|
95 | npoints - number of points for mask filter | |
|
96 | ''' | |
|
97 | ||
|
98 | print ' Outliers Filter {} {} / threshold = {}'.format(svalue, svalue, factor) | |
|
99 | ||
|
100 | ||
|
101 | yaxis = self.dataOut.heightList | |
|
102 | xaxis = numpy.array([[self.dataOut.utctime]]) | |
|
103 | ||
|
104 | # Zonal | |
|
105 | value_temp = self.dataOut.data_output[0] | |
|
106 | ||
|
107 | # Zonal | |
|
108 | value_temp = self.dataOut.data_output[1] | |
|
109 | ||
|
110 | # Vertical | |
|
111 | value_temp = numpy.transpose(self.dataOut.data_output[2]) | |
|
112 | ||
|
113 | htemp = yaxis | |
|
114 | std = value_temp | |
|
115 | for h in range(len(htemp)): | |
|
116 | nvalues_valid = len(numpy.where(numpy.isfinite(value_temp[h]))[0]) | |
|
117 | minvalid = npoints | |
|
118 | ||
|
119 | #only if valid values greater than the minimum required (10%) | |
|
120 | if nvalues_valid > minvalid: | |
|
121 | ||
|
122 | if method == 0: | |
|
123 | #SMOOTH | |
|
124 | w = value_temp[h] - self.Smooth(input=value_temp[h], width=npoints, edge_truncate=1) | |
|
125 | ||
|
126 | ||
|
127 | if method == 1: | |
|
128 | #MEDIAN | |
|
129 | w = value_temp[h] - self.Median(input=value_temp[h], width = npoints) | |
|
130 | ||
|
131 | dw = numpy.std(w[numpy.where(numpy.isfinite(w))],ddof = 1) | |
|
132 | ||
|
133 | threshold = dw*factor | |
|
134 | value_temp[numpy.where(w > threshold),h] = numpy.nan | |
|
135 | value_temp[numpy.where(w < -1*threshold),h] = numpy.nan | |
|
136 | ||
|
137 | ||
|
138 | #At the end | |
|
139 | if svalue2 == 'inHeight': | |
|
140 | value_temp = numpy.transpose(value_temp) | |
|
141 | output_array[:,m] = value_temp | |
|
142 | ||
|
143 | if svalue == 'zonal': | |
|
144 | self.dataOut.data_output[0] = output_array | |
|
145 | ||
|
146 | elif svalue == 'meridional': | |
|
147 | self.dataOut.data_output[1] = output_array | |
|
148 | ||
|
149 | elif svalue == 'vertical': | |
|
150 | self.dataOut.data_output[2] = output_array | |
|
151 | ||
|
152 | return self.dataOut.data_output | |
|
153 | ||
|
154 | ||
|
155 | def Median(self,input,width): | |
|
156 | ''' | |
|
157 | Inputs: | |
|
158 | input - Velocity array | |
|
159 | width - Number of points for mask filter | |
|
160 | ||
|
161 | ''' | |
|
162 | ||
|
163 | if numpy.mod(width,2) == 1: | |
|
164 | pc = int((width - 1) / 2) | |
|
165 | cont = 0 | |
|
166 | output = [] | |
|
167 | ||
|
168 | for i in range(len(input)): | |
|
169 | if i >= pc and i < len(input) - pc: | |
|
170 | new2 = input[i-pc:i+pc+1] | |
|
171 | temp = numpy.where(numpy.isfinite(new2)) | |
|
172 | new = new2[temp] | |
|
173 | value = numpy.median(new) | |
|
174 | output.append(value) | |
|
175 | ||
|
176 | output = numpy.array(output) | |
|
177 | output = numpy.hstack((input[0:pc],output)) | |
|
178 | output = numpy.hstack((output,input[-pc:len(input)])) | |
|
179 | ||
|
180 | return output | |
|
181 | ||
|
182 | def Smooth(self,input,width,edge_truncate = None): | |
|
183 | ''' | |
|
184 | Inputs: | |
|
185 | input - Velocity array | |
|
186 | width - Number of points for mask filter | |
|
187 | edge_truncate - 1 for truncate the convolution product else | |
|
188 | ||
|
189 | ''' | |
|
190 | ||
|
191 | if numpy.mod(width,2) == 0: | |
|
192 | real_width = width + 1 | |
|
193 | nzeros = width / 2 | |
|
194 | else: | |
|
195 | real_width = width | |
|
196 | nzeros = (width - 1) / 2 | |
|
197 | ||
|
198 | half_width = int(real_width)/2 | |
|
199 | length = len(input) | |
|
200 | ||
|
201 | gate = numpy.ones(real_width,dtype='float') | |
|
202 | norm_of_gate = numpy.sum(gate) | |
|
203 | ||
|
204 | nan_process = 0 | |
|
205 | nan_id = numpy.where(numpy.isnan(input)) | |
|
206 | if len(nan_id[0]) > 0: | |
|
207 | nan_process = 1 | |
|
208 | pb = numpy.zeros(len(input)) | |
|
209 | pb[nan_id] = 1. | |
|
210 | input[nan_id] = 0. | |
|
211 | ||
|
212 | if edge_truncate == True: | |
|
213 | output = numpy.convolve(input/norm_of_gate,gate,mode='same') | |
|
214 | elif edge_truncate == False or edge_truncate == None: | |
|
215 | output = numpy.convolve(input/norm_of_gate,gate,mode='valid') | |
|
216 | output = numpy.hstack((input[0:half_width],output)) | |
|
217 | output = numpy.hstack((output,input[len(input)-half_width:len(input)])) | |
|
218 | ||
|
219 | if nan_process: | |
|
220 | pb = numpy.convolve(pb/norm_of_gate,gate,mode='valid') | |
|
221 | pb = numpy.hstack((numpy.zeros(half_width),pb)) | |
|
222 | pb = numpy.hstack((pb,numpy.zeros(half_width))) | |
|
223 | output[numpy.where(pb > 0.9999)] = numpy.nan | |
|
224 | input[nan_id] = numpy.nan | |
|
225 | return output | |
|
226 | ||
|
227 | def Average(self,aver=0,nhaver=1): | |
|
228 | ''' | |
|
229 | Inputs: | |
|
230 | aver - Indicates the time period over which is averaged or consensus data | |
|
231 | nhaver - Indicates the decimation factor in heights | |
|
232 | ||
|
233 | ''' | |
|
234 | nhpoints = 48 | |
|
235 | ||
|
236 | lat_piura = -5.17 | |
|
237 | lat_huancayo = -12.04 | |
|
238 | lat_porcuya = -5.8 | |
|
239 | ||
|
240 | if '%2.2f'%self.dataOut.lat == '%2.2f'%lat_piura: | |
|
241 | hcm = 3. | |
|
242 | if self.dataOut.year == 2003 : | |
|
243 | if self.dataOut.doy >= 25 and self.dataOut.doy < 64: | |
|
244 | nhpoints = 12 | |
|
245 | ||
|
246 | elif '%2.2f'%self.dataOut.lat == '%2.2f'%lat_huancayo: | |
|
247 | hcm = 3. | |
|
248 | if self.dataOut.year == 2003 : | |
|
249 | if self.dataOut.doy >= 25 and self.dataOut.doy < 64: | |
|
250 | nhpoints = 12 | |
|
251 | ||
|
252 | ||
|
253 | elif '%2.2f'%self.dataOut.lat == '%2.2f'%lat_porcuya: | |
|
254 | hcm = 5.#2 | |
|
255 | ||
|
256 | pdata = 0.2 | |
|
257 | taver = [1,2,3,4,6,8,12,24] | |
|
258 | t0 = 0 | |
|
259 | tf = 24 | |
|
260 | ntime =(tf-t0)/taver[aver] | |
|
261 | ti = numpy.arange(ntime) | |
|
262 | tf = numpy.arange(ntime) + taver[aver] | |
|
263 | ||
|
264 | ||
|
265 | old_height = self.dataOut.heightList | |
|
266 | ||
|
267 | if nhaver > 1: | |
|
268 | num_hei = len(self.dataOut.heightList)/nhaver/self.dataOut.nmodes | |
|
269 | deltha = 0.05*nhaver | |
|
270 | minhvalid = pdata*nhaver | |
|
271 | for im in range(self.dataOut.nmodes): | |
|
272 | new_height = numpy.arange(num_hei)*deltha + self.dataOut.height[im,0] + deltha/2. | |
|
273 | ||
|
274 | ||
|
275 | data_fHeigths_List = [] | |
|
276 | data_fZonal_List = [] | |
|
277 | data_fMeridional_List = [] | |
|
278 | data_fVertical_List = [] | |
|
279 | startDTList = [] | |
|
280 | ||
|
281 | ||
|
282 | for i in range(ntime): | |
|
283 | height = old_height | |
|
284 | ||
|
285 | start = datetime.datetime(self.dataOut.year,self.dataOut.month,self.dataOut.day) + datetime.timedelta(hours = int(ti[i])) - datetime.timedelta(hours = 5) | |
|
286 | stop = datetime.datetime(self.dataOut.year,self.dataOut.month,self.dataOut.day) + datetime.timedelta(hours = int(tf[i])) - datetime.timedelta(hours = 5) | |
|
287 | ||
|
288 | ||
|
289 | limit_sec1 = time.mktime(start.timetuple()) | |
|
290 | limit_sec2 = time.mktime(stop.timetuple()) | |
|
291 | ||
|
292 | t1 = numpy.where(self.f_timesec >= limit_sec1) | |
|
293 | t2 = numpy.where(self.f_timesec < limit_sec2) | |
|
294 | time_select = [] | |
|
295 | for val_sec in t1[0]: | |
|
296 | if val_sec in t2[0]: | |
|
297 | time_select.append(val_sec) | |
|
298 | ||
|
299 | ||
|
300 | time_select = numpy.array(time_select,dtype = 'int') | |
|
301 | minvalid = numpy.ceil(pdata*nhpoints) | |
|
302 | ||
|
303 | zon_aver = numpy.zeros([self.dataOut.nranges,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
304 | mer_aver = numpy.zeros([self.dataOut.nranges,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
305 | ver_aver = numpy.zeros([self.dataOut.nranges,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
306 | ||
|
307 | if nhaver > 1: | |
|
308 | new_zon_aver = numpy.zeros([num_hei,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
309 | new_mer_aver = numpy.zeros([num_hei,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
310 | new_ver_aver = numpy.zeros([num_hei,self.dataOut.nmodes],dtype='f4') + numpy.nan | |
|
311 | ||
|
312 | if len(time_select) > minvalid: | |
|
313 | time_average = self.f_timesec[time_select] | |
|
314 | ||
|
315 | for im in range(self.dataOut.nmodes): | |
|
316 | ||
|
317 | for ih in range(self.dataOut.nranges): | |
|
318 | if numpy.sum(numpy.isfinite(self.f_zon[time_select,ih,im])) >= minvalid: | |
|
319 | zon_aver[ih,im] = numpy.nansum(self.f_zon[time_select,ih,im]) / numpy.sum(numpy.isfinite(self.f_zon[time_select,ih,im])) | |
|
320 | ||
|
321 | if numpy.sum(numpy.isfinite(self.f_mer[time_select,ih,im])) >= minvalid: | |
|
322 | mer_aver[ih,im] = numpy.nansum(self.f_mer[time_select,ih,im]) / numpy.sum(numpy.isfinite(self.f_mer[time_select,ih,im])) | |
|
323 | ||
|
324 | if numpy.sum(numpy.isfinite(self.f_ver[time_select,ih,im])) >= minvalid: | |
|
325 | ver_aver[ih,im] = numpy.nansum(self.f_ver[time_select,ih,im]) / numpy.sum(numpy.isfinite(self.f_ver[time_select,ih,im])) | |
|
326 | ||
|
327 | if nhaver > 1: | |
|
328 | for ih in range(num_hei): | |
|
329 | hvalid = numpy.arange(nhaver) + nhaver*ih | |
|
330 | ||
|
331 | if numpy.sum(numpy.isfinite(zon_aver[hvalid,im])) >= minvalid: | |
|
332 | new_zon_aver[ih,im] = numpy.nansum(zon_aver[hvalid,im]) / numpy.sum(numpy.isfinite(zon_aver[hvalid,im])) | |
|
333 | ||
|
334 | if numpy.sum(numpy.isfinite(mer_aver[hvalid,im])) >= minvalid: | |
|
335 | new_mer_aver[ih,im] = numpy.nansum(mer_aver[hvalid,im]) / numpy.sum(numpy.isfinite(mer_aver[hvalid,im])) | |
|
336 | ||
|
337 | if numpy.sum(numpy.isfinite(ver_aver[hvalid,im])) >= minvalid: | |
|
338 | new_ver_aver[ih,im] = numpy.nansum(ver_aver[hvalid,im]) / numpy.sum(numpy.isfinite(ver_aver[hvalid,im])) | |
|
339 | if nhaver > 1: | |
|
340 | zon_aver = new_zon_aver | |
|
341 | mer_aver = new_mer_aver | |
|
342 | ver_aver = new_ver_aver | |
|
343 | height = new_height | |
|
344 | ||
|
345 | ||
|
346 | tstart = time_average[0] | |
|
347 | tend = time_average[-1] | |
|
348 | startTime = time.gmtime(tstart) | |
|
349 | ||
|
350 | year = startTime.tm_year | |
|
351 | month = startTime.tm_mon | |
|
352 | day = startTime.tm_mday | |
|
353 | hour = startTime.tm_hour | |
|
354 | minute = startTime.tm_min | |
|
355 | second = startTime.tm_sec | |
|
356 | ||
|
357 | startDTList.append(datetime.datetime(year,month,day,hour,minute,second)) | |
|
358 | ||
|
359 | ||
|
360 | o_height = numpy.array([]) | |
|
361 | o_zon_aver = numpy.array([]) | |
|
362 | o_mer_aver = numpy.array([]) | |
|
363 | o_ver_aver = numpy.array([]) | |
|
364 | if self.dataOut.nmodes > 1: | |
|
365 | for im in range(self.dataOut.nmodes): | |
|
366 | ||
|
367 | if im == 0: | |
|
368 | h_select = numpy.where(numpy.bitwise_and(height[0,:] >=0,height[0,:] <= hcm,numpy.isfinite(height[0,:]))) | |
|
369 | else: | |
|
370 | h_select = numpy.where(numpy.bitwise_and(height[1,:] > hcm,height[1,:] < 20,numpy.isfinite(height[1,:]))) | |
|
371 | ||
|
372 | ||
|
373 | ht = h_select[0] | |
|
374 | ||
|
375 | o_height = numpy.hstack((o_height,height[im,ht])) | |
|
376 | o_zon_aver = numpy.hstack((o_zon_aver,zon_aver[ht,im])) | |
|
377 | o_mer_aver = numpy.hstack((o_mer_aver,mer_aver[ht,im])) | |
|
378 | o_ver_aver = numpy.hstack((o_ver_aver,ver_aver[ht,im])) | |
|
379 | ||
|
380 | data_fHeigths_List.append(o_height) | |
|
381 | data_fZonal_List.append(o_zon_aver) | |
|
382 | data_fMeridional_List.append(o_mer_aver) | |
|
383 | data_fVertical_List.append(o_ver_aver) | |
|
384 | ||
|
385 | ||
|
386 | else: | |
|
387 | h_select = numpy.where(numpy.bitwise_and(height[0,:] <= hcm,numpy.isfinite(height[0,:]))) | |
|
388 | ht = h_select[0] | |
|
389 | o_height = numpy.hstack((o_height,height[im,ht])) | |
|
390 | o_zon_aver = numpy.hstack((o_zon_aver,zon_aver[ht,im])) | |
|
391 | o_mer_aver = numpy.hstack((o_mer_aver,mer_aver[ht,im])) | |
|
392 | o_ver_aver = numpy.hstack((o_ver_aver,ver_aver[ht,im])) | |
|
393 | ||
|
394 | data_fHeigths_List.append(o_height) | |
|
395 | data_fZonal_List.append(o_zon_aver) | |
|
396 | data_fMeridional_List.append(o_mer_aver) | |
|
397 | data_fVertical_List.append(o_ver_aver) | |
|
398 | ||
|
399 | ||
|
400 | return startDTList, data_fHeigths_List, data_fZonal_List, data_fMeridional_List, data_fVertical_List | |
|
401 | ||
|
402 | ||
|
403 | No newline at end of file |
@@ -1179,6 +1179,8 class Parameters(Spectra): | |||
|
1179 | 1179 | nAvg = None |
|
1180 | 1180 | |
|
1181 | 1181 | noise_estimation = None |
|
1182 | ||
|
1183 | GauSPC = None #Fit gaussian SPC | |
|
1182 | 1184 | |
|
1183 | 1185 | |
|
1184 | 1186 | def __init__(self): |
@@ -1213,8 +1215,15 class Parameters(Spectra): | |||
|
1213 | 1215 | else: |
|
1214 | 1216 | return self.paramInterval |
|
1215 | 1217 | |
|
1218 | def setValue(self, value): | |
|
1219 | ||
|
1220 | print "This property should not be initialized" | |
|
1221 | ||
|
1222 | return | |
|
1223 | ||
|
1216 | 1224 | def getNoise(self): |
|
1217 | 1225 | |
|
1218 | 1226 | return self.spc_noise |
|
1219 | 1227 | |
|
1220 | 1228 | timeInterval = property(getTimeInterval) |
|
1229 | noise = property(getNoise, setValue, "I'm the 'Noise' property.") |
@@ -6,81 +6,81 import copy | |||
|
6 | 6 | from figure import Figure, isRealtime |
|
7 | 7 | |
|
8 | 8 | class CorrelationPlot(Figure): |
|
9 | ||
|
9 | ||
|
10 | 10 | isConfig = None |
|
11 | 11 | __nsubplots = None |
|
12 | ||
|
12 | ||
|
13 | 13 | WIDTHPROF = None |
|
14 | 14 | HEIGHTPROF = None |
|
15 | 15 | PREFIX = 'corr' |
|
16 | ||
|
17 |
def __init__(self |
|
|
18 | Figure.__init__(self, **kwargs) | |
|
16 | ||
|
17 | def __init__(self): | |
|
18 | ||
|
19 | 19 | self.isConfig = False |
|
20 | 20 | self.__nsubplots = 1 |
|
21 | ||
|
21 | ||
|
22 | 22 | self.WIDTH = 280 |
|
23 | 23 | self.HEIGHT = 250 |
|
24 | 24 | self.WIDTHPROF = 120 |
|
25 | 25 | self.HEIGHTPROF = 0 |
|
26 | 26 | self.counter_imagwr = 0 |
|
27 | ||
|
27 | ||
|
28 | 28 | self.PLOT_CODE = 1 |
|
29 | 29 | self.FTP_WEI = None |
|
30 | 30 | self.EXP_CODE = None |
|
31 | 31 | self.SUB_EXP_CODE = None |
|
32 | 32 | self.PLOT_POS = None |
|
33 | ||
|
33 | ||
|
34 | 34 | def getSubplots(self): |
|
35 | ||
|
35 | ||
|
36 | 36 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
37 | 37 | nrow = int(self.nplots*1./ncol + 0.9) |
|
38 | ||
|
38 | ||
|
39 | 39 | return nrow, ncol |
|
40 | ||
|
40 | ||
|
41 | 41 | def setup(self, id, nplots, wintitle, showprofile=False, show=True): |
|
42 | ||
|
43 | showprofile = False | |
|
42 | ||
|
43 | showprofile = False | |
|
44 | 44 | self.__showprofile = showprofile |
|
45 | 45 | self.nplots = nplots |
|
46 | ||
|
46 | ||
|
47 | 47 | ncolspan = 1 |
|
48 | 48 | colspan = 1 |
|
49 | 49 | if showprofile: |
|
50 | 50 | ncolspan = 3 |
|
51 | 51 | colspan = 2 |
|
52 | 52 | self.__nsubplots = 2 |
|
53 | ||
|
53 | ||
|
54 | 54 | self.createFigure(id = id, |
|
55 | 55 | wintitle = wintitle, |
|
56 | 56 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
57 | 57 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
58 | 58 | show=show) |
|
59 | ||
|
59 | ||
|
60 | 60 | nrow, ncol = self.getSubplots() |
|
61 | ||
|
61 | ||
|
62 | 62 | counter = 0 |
|
63 | 63 | for y in range(nrow): |
|
64 | 64 | for x in range(ncol): |
|
65 | ||
|
65 | ||
|
66 | 66 | if counter >= self.nplots: |
|
67 | 67 | break |
|
68 | ||
|
68 | ||
|
69 | 69 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
70 | ||
|
70 | ||
|
71 | 71 | if showprofile: |
|
72 | 72 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
73 | ||
|
73 | ||
|
74 | 74 | counter += 1 |
|
75 | ||
|
75 | ||
|
76 | 76 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=False, |
|
77 | 77 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
78 | 78 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
79 | 79 | server=None, folder=None, username=None, password=None, |
|
80 | 80 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False): |
|
81 | ||
|
81 | ||
|
82 | 82 |
|
|
83 | ||
|
83 | ||
|
84 | 84 | Input: |
|
85 | 85 | dataOut : |
|
86 | 86 | id : |
@@ -94,15 +94,15 class CorrelationPlot(Figure): | |||
|
94 | 94 | zmin : None, |
|
95 | 95 | zmax : None |
|
96 | 96 | """ |
|
97 | ||
|
97 | ||
|
98 | 98 | if dataOut.flagNoData: |
|
99 | 99 | return None |
|
100 | ||
|
100 | ||
|
101 | 101 | if realtime: |
|
102 | 102 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
103 | 103 | print 'Skipping this plot function' |
|
104 | 104 | return |
|
105 | ||
|
105 | ||
|
106 | 106 | if channelList == None: |
|
107 | 107 | channelIndexList = dataOut.channelIndexList |
|
108 | 108 | else: |
@@ -111,53 +111,53 class CorrelationPlot(Figure): | |||
|
111 | 111 | if channel not in dataOut.channelList: |
|
112 | 112 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
113 | 113 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
114 | ||
|
114 | ||
|
115 | 115 | factor = dataOut.normFactor |
|
116 | 116 | lenfactor = factor.shape[1] |
|
117 | 117 | x = dataOut.getLagTRange(1) |
|
118 | 118 | y = dataOut.getHeiRange() |
|
119 | ||
|
119 | ||
|
120 | 120 | z = copy.copy(dataOut.data_corr[:,:,0,:]) |
|
121 | 121 | for i in range(dataOut.data_corr.shape[0]): |
|
122 | z[i,:,:] = z[i,:,:]/factor[i,:] | |
|
122 | z[i,:,:] = z[i,:,:]/factor[i,:] | |
|
123 | 123 | zdB = numpy.abs(z) |
|
124 | ||
|
124 | ||
|
125 | 125 | avg = numpy.average(z, axis=1) |
|
126 | 126 | # avg = numpy.nanmean(z, axis=1) |
|
127 | 127 | # noise = dataOut.noise/factor |
|
128 | ||
|
128 | ||
|
129 | 129 | #thisDatetime = dataOut.datatime |
|
130 | 130 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
131 | title = wintitle + " Correlation" | |
|
131 | title = wintitle + " Correlation" | |
|
132 | 132 | xlabel = "Lag T (s)" |
|
133 | 133 | ylabel = "Range (Km)" |
|
134 | ||
|
134 | ||
|
135 | 135 | if not self.isConfig: |
|
136 | ||
|
137 | nplots = dataOut.data_corr.shape[0] | |
|
138 | ||
|
136 | ||
|
137 | nplots = dataOut.data_corr.shape[0] | |
|
138 | ||
|
139 | 139 | self.setup(id=id, |
|
140 | 140 | nplots=nplots, |
|
141 | 141 | wintitle=wintitle, |
|
142 | 142 | showprofile=showprofile, |
|
143 | 143 | show=show) |
|
144 | ||
|
144 | ||
|
145 | 145 | if xmin == None: xmin = numpy.nanmin(x) |
|
146 | 146 | if xmax == None: xmax = numpy.nanmax(x) |
|
147 | 147 | if ymin == None: ymin = numpy.nanmin(y) |
|
148 | 148 | if ymax == None: ymax = numpy.nanmax(y) |
|
149 | 149 | if zmin == None: zmin = 0 |
|
150 | 150 | if zmax == None: zmax = 1 |
|
151 | ||
|
151 | ||
|
152 | 152 | self.FTP_WEI = ftp_wei |
|
153 | 153 | self.EXP_CODE = exp_code |
|
154 | 154 | self.SUB_EXP_CODE = sub_exp_code |
|
155 | 155 | self.PLOT_POS = plot_pos |
|
156 | ||
|
156 | ||
|
157 | 157 | self.isConfig = True |
|
158 | ||
|
158 | ||
|
159 | 159 | self.setWinTitle(title) |
|
160 | ||
|
160 | ||
|
161 | 161 | for i in range(self.nplots): |
|
162 | 162 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
|
163 | 163 | title = "Channel %d and %d: : %s" %(dataOut.pairsList[i][0],dataOut.pairsList[i][1] , str_datetime) |
@@ -166,7 +166,7 class CorrelationPlot(Figure): | |||
|
166 | 166 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
|
167 | 167 | xlabel=xlabel, ylabel=ylabel, title=title, |
|
168 | 168 | ticksize=9, cblabel='') |
|
169 | ||
|
169 | ||
|
170 | 170 | # if self.__showprofile: |
|
171 | 171 | # axes = self.axesList[i*self.__nsubplots +1] |
|
172 | 172 | # axes.pline(avgdB[i], y, |
@@ -174,15 +174,15 class CorrelationPlot(Figure): | |||
|
174 | 174 | # xlabel='dB', ylabel='', title='', |
|
175 | 175 | # ytick_visible=False, |
|
176 | 176 | # grid='x') |
|
177 | # | |
|
177 | # | |
|
178 | 178 | # noiseline = numpy.repeat(noisedB[i], len(y)) |
|
179 | 179 | # axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) |
|
180 | ||
|
180 | ||
|
181 | 181 | self.draw() |
|
182 | ||
|
182 | ||
|
183 | 183 | self.save(figpath=figpath, |
|
184 | 184 | figfile=figfile, |
|
185 | 185 | save=save, |
|
186 | 186 | ftp=ftp, |
|
187 | 187 | wr_period=wr_period, |
|
188 | thisDatetime=thisDatetime) | |
|
188 | thisDatetime=thisDatetime) |
@@ -11,80 +11,79 from figure import Figure, isRealtime | |||
|
11 | 11 | from plotting_codes import * |
|
12 | 12 | |
|
13 | 13 | class SpectraHeisScope(Figure): |
|
14 | ||
|
15 | ||
|
14 | ||
|
15 | ||
|
16 | 16 | isConfig = None |
|
17 | 17 | __nsubplots = None |
|
18 | ||
|
18 | ||
|
19 | 19 | WIDTHPROF = None |
|
20 | 20 | HEIGHTPROF = None |
|
21 | 21 | PREFIX = 'spc' |
|
22 | ||
|
23 |
def __init__(self |
|
|
24 | ||
|
25 | Figure.__init__(self, **kwargs) | |
|
22 | ||
|
23 | def __init__(self): | |
|
24 | ||
|
26 | 25 | self.isConfig = False |
|
27 | 26 | self.__nsubplots = 1 |
|
28 | ||
|
27 | ||
|
29 | 28 | self.WIDTH = 230 |
|
30 | 29 | self.HEIGHT = 250 |
|
31 | 30 | self.WIDTHPROF = 120 |
|
32 | 31 | self.HEIGHTPROF = 0 |
|
33 | 32 | self.counter_imagwr = 0 |
|
34 | ||
|
33 | ||
|
35 | 34 | self.PLOT_CODE = SPEC_CODE |
|
36 | ||
|
35 | ||
|
37 | 36 | def getSubplots(self): |
|
38 | ||
|
37 | ||
|
39 | 38 | ncol = int(numpy.sqrt(self.nplots)+0.9) |
|
40 | 39 | nrow = int(self.nplots*1./ncol + 0.9) |
|
41 | ||
|
40 | ||
|
42 | 41 | return nrow, ncol |
|
43 | ||
|
42 | ||
|
44 | 43 | def setup(self, id, nplots, wintitle, show): |
|
45 | ||
|
44 | ||
|
46 | 45 | showprofile = False |
|
47 | 46 | self.__showprofile = showprofile |
|
48 | 47 | self.nplots = nplots |
|
49 | ||
|
48 | ||
|
50 | 49 | ncolspan = 1 |
|
51 | 50 | colspan = 1 |
|
52 | 51 | if showprofile: |
|
53 | 52 | ncolspan = 3 |
|
54 | 53 | colspan = 2 |
|
55 | 54 | self.__nsubplots = 2 |
|
56 | ||
|
55 | ||
|
57 | 56 | self.createFigure(id = id, |
|
58 | 57 | wintitle = wintitle, |
|
59 | 58 | widthplot = self.WIDTH + self.WIDTHPROF, |
|
60 | 59 | heightplot = self.HEIGHT + self.HEIGHTPROF, |
|
61 | 60 | show = show) |
|
62 | ||
|
61 | ||
|
63 | 62 | nrow, ncol = self.getSubplots() |
|
64 | ||
|
63 | ||
|
65 | 64 | counter = 0 |
|
66 | 65 | for y in range(nrow): |
|
67 | 66 | for x in range(ncol): |
|
68 | ||
|
67 | ||
|
69 | 68 | if counter >= self.nplots: |
|
70 | 69 | break |
|
71 | ||
|
70 | ||
|
72 | 71 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) |
|
73 | ||
|
72 | ||
|
74 | 73 | if showprofile: |
|
75 | 74 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) |
|
76 | ||
|
75 | ||
|
77 | 76 | counter += 1 |
|
78 | 77 | |
|
79 | ||
|
78 | ||
|
80 | 79 | def run(self, dataOut, id, wintitle="", channelList=None, |
|
81 | 80 | xmin=None, xmax=None, ymin=None, ymax=None, save=False, |
|
82 | 81 | figpath='./', figfile=None, ftp=False, wr_period=1, show=True, |
|
83 | 82 | server=None, folder=None, username=None, password=None, |
|
84 | 83 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
85 | ||
|
84 | ||
|
86 | 85 |
|
|
87 | ||
|
86 | ||
|
88 | 87 | Input: |
|
89 | 88 | dataOut : |
|
90 | 89 | id : |
@@ -95,12 +94,12 class SpectraHeisScope(Figure): | |||
|
95 | 94 | ymin : None, |
|
96 | 95 | ymax : None, |
|
97 | 96 | """ |
|
98 | ||
|
97 | ||
|
99 | 98 | if dataOut.realtime: |
|
100 | 99 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
101 | 100 | print 'Skipping this plot function' |
|
102 | 101 | return |
|
103 | ||
|
102 | ||
|
104 | 103 | if channelList == None: |
|
105 | 104 | channelIndexList = dataOut.channelIndexList |
|
106 | 105 | else: |
@@ -109,9 +108,9 class SpectraHeisScope(Figure): | |||
|
109 | 108 | if channel not in dataOut.channelList: |
|
110 | 109 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
111 | 110 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
112 | ||
|
111 | ||
|
113 | 112 | # x = dataOut.heightList |
|
114 | c = 3E8 | |
|
113 | c = 3E8 | |
|
115 | 114 | deltaHeight = dataOut.heightList[1] - dataOut.heightList[0] |
|
116 | 115 | #deberia cambiar para el caso de 1Mhz y 100KHz |
|
117 | 116 | x = numpy.arange(-1*dataOut.nHeights/2.,dataOut.nHeights/2.)*(c/(2*deltaHeight*dataOut.nHeights*1000)) |
@@ -123,7 +122,7 class SpectraHeisScope(Figure): | |||
|
123 | 122 | data = dataOut.data_spc / factor |
|
124 | 123 | datadB = 10.*numpy.log10(data) |
|
125 | 124 | y = datadB |
|
126 | ||
|
125 | ||
|
127 | 126 | #thisDatetime = dataOut.datatime |
|
128 | 127 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
129 | 128 | title = wintitle + " Scope: %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
@@ -131,29 +130,29 class SpectraHeisScope(Figure): | |||
|
131 | 130 | #para 1Mhz descomentar la siguiente linea |
|
132 | 131 | #xlabel = "Frequency x 10000" |
|
133 | 132 | ylabel = "Intensity (dB)" |
|
134 | ||
|
133 | ||
|
135 | 134 | if not self.isConfig: |
|
136 | 135 | nplots = len(channelIndexList) |
|
137 | ||
|
136 | ||
|
138 | 137 | self.setup(id=id, |
|
139 | 138 | nplots=nplots, |
|
140 | 139 | wintitle=wintitle, |
|
141 | 140 | show=show) |
|
142 | ||
|
141 | ||
|
143 | 142 | if xmin == None: xmin = numpy.nanmin(x) |
|
144 | 143 | if xmax == None: xmax = numpy.nanmax(x) |
|
145 | 144 | if ymin == None: ymin = numpy.nanmin(y) |
|
146 | 145 | if ymax == None: ymax = numpy.nanmax(y) |
|
147 | ||
|
146 | ||
|
148 | 147 | self.FTP_WEI = ftp_wei |
|
149 | 148 | self.EXP_CODE = exp_code |
|
150 | 149 | self.SUB_EXP_CODE = sub_exp_code |
|
151 | 150 | self.PLOT_POS = plot_pos |
|
152 | ||
|
151 | ||
|
153 | 152 | self.isConfig = True |
|
154 | ||
|
153 | ||
|
155 | 154 | self.setWinTitle(title) |
|
156 | ||
|
155 | ||
|
157 | 156 | for i in range(len(self.axesList)): |
|
158 | 157 | ychannel = y[i,:] |
|
159 | 158 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
@@ -162,10 +161,10 class SpectraHeisScope(Figure): | |||
|
162 | 161 | axes.pline(x, ychannel, |
|
163 | 162 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, |
|
164 | 163 | xlabel=xlabel, ylabel=ylabel, title=title, grid='both') |
|
165 | ||
|
166 | ||
|
164 | ||
|
165 | ||
|
167 | 166 | self.draw() |
|
168 | ||
|
167 | ||
|
169 | 168 | self.save(figpath=figpath, |
|
170 | 169 | figfile=figfile, |
|
171 | 170 | save=save, |
@@ -174,18 +173,18 class SpectraHeisScope(Figure): | |||
|
174 | 173 | thisDatetime=thisDatetime) |
|
175 | 174 | |
|
176 | 175 | class RTIfromSpectraHeis(Figure): |
|
177 | ||
|
176 | ||
|
178 | 177 | isConfig = None |
|
179 | 178 | __nsubplots = None |
|
180 | 179 | |
|
181 | 180 | PREFIX = 'rtinoise' |
|
182 | ||
|
183 |
def __init__(self |
|
|
184 | Figure.__init__(self, **kwargs) | |
|
181 | ||
|
182 | def __init__(self): | |
|
183 | ||
|
185 | 184 | self.timerange = 24*60*60 |
|
186 | 185 | self.isConfig = False |
|
187 | 186 | self.__nsubplots = 1 |
|
188 | ||
|
187 | ||
|
189 | 188 | self.WIDTH = 820 |
|
190 | 189 | self.HEIGHT = 200 |
|
191 | 190 | self.WIDTHPROF = 120 |
@@ -194,43 +193,43 class RTIfromSpectraHeis(Figure): | |||
|
194 | 193 | self.xdata = None |
|
195 | 194 | self.ydata = None |
|
196 | 195 | self.figfile = None |
|
197 | ||
|
196 | ||
|
198 | 197 | self.PLOT_CODE = RTI_CODE |
|
199 | ||
|
198 | ||
|
200 | 199 | def getSubplots(self): |
|
201 | ||
|
200 | ||
|
202 | 201 | ncol = 1 |
|
203 | 202 | nrow = 1 |
|
204 | ||
|
203 | ||
|
205 | 204 | return nrow, ncol |
|
206 | ||
|
205 | ||
|
207 | 206 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): |
|
208 | ||
|
207 | ||
|
209 | 208 | self.__showprofile = showprofile |
|
210 | 209 | self.nplots = nplots |
|
211 | ||
|
210 | ||
|
212 | 211 | ncolspan = 7 |
|
213 | 212 | colspan = 6 |
|
214 | 213 | self.__nsubplots = 2 |
|
215 | ||
|
214 | ||
|
216 | 215 | self.createFigure(id = id, |
|
217 | 216 | wintitle = wintitle, |
|
218 | 217 | widthplot = self.WIDTH+self.WIDTHPROF, |
|
219 | 218 | heightplot = self.HEIGHT+self.HEIGHTPROF, |
|
220 | 219 | show = show) |
|
221 | ||
|
220 | ||
|
222 | 221 | nrow, ncol = self.getSubplots() |
|
223 | ||
|
222 | ||
|
224 | 223 | self.addAxes(nrow, ncol*ncolspan, 0, 0, colspan, 1) |
|
225 | ||
|
226 | ||
|
224 | ||
|
225 | ||
|
227 | 226 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
228 | 227 | xmin=None, xmax=None, ymin=None, ymax=None, |
|
229 | 228 | timerange=None, |
|
230 | 229 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, show=True, |
|
231 | 230 | server=None, folder=None, username=None, password=None, |
|
232 | 231 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): |
|
233 | ||
|
232 | ||
|
234 | 233 | if channelList == None: |
|
235 | 234 | channelIndexList = dataOut.channelIndexList |
|
236 | 235 | channelList = dataOut.channelList |
@@ -240,86 +239,86 class RTIfromSpectraHeis(Figure): | |||
|
240 | 239 | if channel not in dataOut.channelList: |
|
241 | 240 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
242 | 241 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
243 | ||
|
242 | ||
|
244 | 243 | if timerange != None: |
|
245 | 244 | self.timerange = timerange |
|
246 | ||
|
245 | ||
|
247 | 246 | x = dataOut.getTimeRange() |
|
248 | 247 | y = dataOut.getHeiRange() |
|
249 | ||
|
248 | ||
|
250 | 249 | factor = dataOut.normFactor |
|
251 | 250 | data = dataOut.data_spc / factor |
|
252 | 251 | data = numpy.average(data,axis=1) |
|
253 | 252 | datadB = 10*numpy.log10(data) |
|
254 | ||
|
253 | ||
|
255 | 254 | # factor = dataOut.normFactor |
|
256 | 255 | # noise = dataOut.getNoise()/factor |
|
257 | 256 | # noisedB = 10*numpy.log10(noise) |
|
258 | ||
|
257 | ||
|
259 | 258 | #thisDatetime = dataOut.datatime |
|
260 | 259 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
|
261 | 260 | title = wintitle + " RTI: %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
262 | 261 | xlabel = "Local Time" |
|
263 | 262 | ylabel = "Intensity (dB)" |
|
264 | ||
|
263 | ||
|
265 | 264 | if not self.isConfig: |
|
266 | ||
|
265 | ||
|
267 | 266 | nplots = 1 |
|
268 | ||
|
267 | ||
|
269 | 268 | self.setup(id=id, |
|
270 | 269 | nplots=nplots, |
|
271 | 270 | wintitle=wintitle, |
|
272 | 271 | showprofile=showprofile, |
|
273 | 272 | show=show) |
|
274 | ||
|
273 | ||
|
275 | 274 | self.tmin, self.tmax = self.getTimeLim(x, xmin, xmax) |
|
276 | ||
|
275 | ||
|
277 | 276 | if ymin == None: ymin = numpy.nanmin(datadB) |
|
278 | 277 | if ymax == None: ymax = numpy.nanmax(datadB) |
|
279 | ||
|
278 | ||
|
280 | 279 | self.name = thisDatetime.strftime("%Y%m%d_%H%M%S") |
|
281 | 280 | self.isConfig = True |
|
282 | 281 | self.figfile = figfile |
|
283 | 282 | self.xdata = numpy.array([]) |
|
284 | 283 | self.ydata = numpy.array([]) |
|
285 | ||
|
284 | ||
|
286 | 285 | self.FTP_WEI = ftp_wei |
|
287 | 286 | self.EXP_CODE = exp_code |
|
288 | 287 | self.SUB_EXP_CODE = sub_exp_code |
|
289 | 288 | self.PLOT_POS = plot_pos |
|
290 | ||
|
289 | ||
|
291 | 290 | self.setWinTitle(title) |
|
292 | ||
|
293 | ||
|
291 | ||
|
292 | ||
|
294 | 293 | # title = "RTI %s" %(thisDatetime.strftime("%d-%b-%Y")) |
|
295 | 294 | title = "RTI - %s" %(thisDatetime.strftime("%d-%b-%Y %H:%M:%S")) |
|
296 | ||
|
295 | ||
|
297 | 296 | legendlabels = ["channel %d"%idchannel for idchannel in channelList] |
|
298 | 297 | axes = self.axesList[0] |
|
299 | ||
|
298 | ||
|
300 | 299 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
|
301 | ||
|
300 | ||
|
302 | 301 | if len(self.ydata)==0: |
|
303 | 302 | self.ydata = datadB[channelIndexList].reshape(-1,1) |
|
304 | 303 | else: |
|
305 | 304 | self.ydata = numpy.hstack((self.ydata, datadB[channelIndexList].reshape(-1,1))) |
|
306 | ||
|
307 | ||
|
305 | ||
|
306 | ||
|
308 | 307 | axes.pmultilineyaxis(x=self.xdata, y=self.ydata, |
|
309 | 308 | xmin=self.tmin, xmax=self.tmax, ymin=ymin, ymax=ymax, |
|
310 | 309 | xlabel=xlabel, ylabel=ylabel, title=title, legendlabels=legendlabels, marker='.', markersize=8, linestyle="solid", grid='both', |
|
311 | 310 | XAxisAsTime=True |
|
312 | 311 | ) |
|
313 | ||
|
312 | ||
|
314 | 313 | self.draw() |
|
315 | ||
|
314 | ||
|
316 | 315 | update_figfile = False |
|
317 | ||
|
316 | ||
|
318 | 317 | if dataOut.ltctime >= self.tmax: |
|
319 | 318 | self.counter_imagwr = wr_period |
|
320 | 319 | self.isConfig = False |
|
321 | 320 | update_figfile = True |
|
322 | ||
|
321 | ||
|
323 | 322 | self.save(figpath=figpath, |
|
324 | 323 | figfile=figfile, |
|
325 | 324 | save=save, |
@@ -6,6 +6,217 from figure import Figure, isRealtime, isTimeInHourRange | |||
|
6 | 6 | from plotting_codes import * |
|
7 | 7 | |
|
8 | 8 | |
|
9 | class FitGauPlot(Figure): | |
|
10 | ||
|
11 | isConfig = None | |
|
12 | __nsubplots = None | |
|
13 | ||
|
14 | WIDTHPROF = None | |
|
15 | HEIGHTPROF = None | |
|
16 | PREFIX = 'fitgau' | |
|
17 | ||
|
18 | def __init__(self, **kwargs): | |
|
19 | Figure.__init__(self, **kwargs) | |
|
20 | self.isConfig = False | |
|
21 | self.__nsubplots = 1 | |
|
22 | ||
|
23 | self.WIDTH = 250 | |
|
24 | self.HEIGHT = 250 | |
|
25 | self.WIDTHPROF = 120 | |
|
26 | self.HEIGHTPROF = 0 | |
|
27 | self.counter_imagwr = 0 | |
|
28 | ||
|
29 | self.PLOT_CODE = SPEC_CODE | |
|
30 | ||
|
31 | self.FTP_WEI = None | |
|
32 | self.EXP_CODE = None | |
|
33 | self.SUB_EXP_CODE = None | |
|
34 | self.PLOT_POS = None | |
|
35 | ||
|
36 | self.__xfilter_ena = False | |
|
37 | self.__yfilter_ena = False | |
|
38 | ||
|
39 | def getSubplots(self): | |
|
40 | ||
|
41 | ncol = int(numpy.sqrt(self.nplots)+0.9) | |
|
42 | nrow = int(self.nplots*1./ncol + 0.9) | |
|
43 | ||
|
44 | return nrow, ncol | |
|
45 | ||
|
46 | def setup(self, id, nplots, wintitle, showprofile=True, show=True): | |
|
47 | ||
|
48 | self.__showprofile = showprofile | |
|
49 | self.nplots = nplots | |
|
50 | ||
|
51 | ncolspan = 1 | |
|
52 | colspan = 1 | |
|
53 | if showprofile: | |
|
54 | ncolspan = 3 | |
|
55 | colspan = 2 | |
|
56 | self.__nsubplots = 2 | |
|
57 | ||
|
58 | self.createFigure(id = id, | |
|
59 | wintitle = wintitle, | |
|
60 | widthplot = self.WIDTH + self.WIDTHPROF, | |
|
61 | heightplot = self.HEIGHT + self.HEIGHTPROF, | |
|
62 | show=show) | |
|
63 | ||
|
64 | nrow, ncol = self.getSubplots() | |
|
65 | ||
|
66 | counter = 0 | |
|
67 | for y in range(nrow): | |
|
68 | for x in range(ncol): | |
|
69 | ||
|
70 | if counter >= self.nplots: | |
|
71 | break | |
|
72 | ||
|
73 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan, colspan, 1) | |
|
74 | ||
|
75 | if showprofile: | |
|
76 | self.addAxes(nrow, ncol*ncolspan, y, x*ncolspan+colspan, 1, 1) | |
|
77 | ||
|
78 | counter += 1 | |
|
79 | ||
|
80 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile=True, | |
|
81 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, | |
|
82 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, | |
|
83 | server=None, folder=None, username=None, password=None, | |
|
84 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, | |
|
85 | xaxis="frequency", colormap='jet', normFactor=None , GauSelector = 1): | |
|
86 | ||
|
87 | """ | |
|
88 | ||
|
89 | Input: | |
|
90 | dataOut : | |
|
91 | id : | |
|
92 | wintitle : | |
|
93 | channelList : | |
|
94 | showProfile : | |
|
95 | xmin : None, | |
|
96 | xmax : None, | |
|
97 | ymin : None, | |
|
98 | ymax : None, | |
|
99 | zmin : None, | |
|
100 | zmax : None | |
|
101 | """ | |
|
102 | if realtime: | |
|
103 | if not(isRealtime(utcdatatime = dataOut.utctime)): | |
|
104 | print 'Skipping this plot function' | |
|
105 | return | |
|
106 | ||
|
107 | if channelList == None: | |
|
108 | channelIndexList = dataOut.channelIndexList | |
|
109 | else: | |
|
110 | channelIndexList = [] | |
|
111 | for channel in channelList: | |
|
112 | if channel not in dataOut.channelList: | |
|
113 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel | |
|
114 | channelIndexList.append(dataOut.channelList.index(channel)) | |
|
115 | ||
|
116 | # if normFactor is None: | |
|
117 | # factor = dataOut.normFactor | |
|
118 | # else: | |
|
119 | # factor = normFactor | |
|
120 | if xaxis == "frequency": | |
|
121 | x = dataOut.spc_range[0] | |
|
122 | xlabel = "Frequency (kHz)" | |
|
123 | ||
|
124 | elif xaxis == "time": | |
|
125 | x = dataOut.spc_range[1] | |
|
126 | xlabel = "Time (ms)" | |
|
127 | ||
|
128 | else: | |
|
129 | x = dataOut.spc_range[2] | |
|
130 | xlabel = "Velocity (m/s)" | |
|
131 | ||
|
132 | ylabel = "Range (Km)" | |
|
133 | ||
|
134 | y = dataOut.getHeiRange() | |
|
135 | ||
|
136 | z = dataOut.GauSPC[:,GauSelector,:,:] #GauSelector] #dataOut.data_spc/factor | |
|
137 | print 'GausSPC', z[0,32,10:40] | |
|
138 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
|
139 | zdB = 10*numpy.log10(z) | |
|
140 | ||
|
141 | avg = numpy.average(z, axis=1) | |
|
142 | avgdB = 10*numpy.log10(avg) | |
|
143 | ||
|
144 | noise = dataOut.spc_noise | |
|
145 | noisedB = 10*numpy.log10(noise) | |
|
146 | ||
|
147 | thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) | |
|
148 | title = wintitle + " Spectra" | |
|
149 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
|
150 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) | |
|
151 | ||
|
152 | if not self.isConfig: | |
|
153 | ||
|
154 | nplots = len(channelIndexList) | |
|
155 | ||
|
156 | self.setup(id=id, | |
|
157 | nplots=nplots, | |
|
158 | wintitle=wintitle, | |
|
159 | showprofile=showprofile, | |
|
160 | show=show) | |
|
161 | ||
|
162 | if xmin == None: xmin = numpy.nanmin(x) | |
|
163 | if xmax == None: xmax = numpy.nanmax(x) | |
|
164 | if ymin == None: ymin = numpy.nanmin(y) | |
|
165 | if ymax == None: ymax = numpy.nanmax(y) | |
|
166 | if zmin == None: zmin = numpy.floor(numpy.nanmin(noisedB)) - 3 | |
|
167 | if zmax == None: zmax = numpy.ceil(numpy.nanmax(avgdB)) + 3 | |
|
168 | ||
|
169 | self.FTP_WEI = ftp_wei | |
|
170 | self.EXP_CODE = exp_code | |
|
171 | self.SUB_EXP_CODE = sub_exp_code | |
|
172 | self.PLOT_POS = plot_pos | |
|
173 | ||
|
174 | self.isConfig = True | |
|
175 | ||
|
176 | self.setWinTitle(title) | |
|
177 | ||
|
178 | for i in range(self.nplots): | |
|
179 | index = channelIndexList[i] | |
|
180 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) | |
|
181 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[index], noisedB[index], str_datetime) | |
|
182 | if len(dataOut.beam.codeList) != 0: | |
|
183 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[index], noisedB[index], dataOut.beam.azimuthList[index], dataOut.beam.zenithList[index], str_datetime) | |
|
184 | ||
|
185 | axes = self.axesList[i*self.__nsubplots] | |
|
186 | axes.pcolor(x, y, zdB[index,:,:], | |
|
187 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, | |
|
188 | xlabel=xlabel, ylabel=ylabel, title=title, colormap=colormap, | |
|
189 | ticksize=9, cblabel='') | |
|
190 | ||
|
191 | if self.__showprofile: | |
|
192 | axes = self.axesList[i*self.__nsubplots +1] | |
|
193 | axes.pline(avgdB[index,:], y, | |
|
194 | xmin=zmin, xmax=zmax, ymin=ymin, ymax=ymax, | |
|
195 | xlabel='dB', ylabel='', title='', | |
|
196 | ytick_visible=False, | |
|
197 | grid='x') | |
|
198 | ||
|
199 | noiseline = numpy.repeat(noisedB[index], len(y)) | |
|
200 | axes.addpline(noiseline, y, idline=1, color="black", linestyle="dashed", lw=2) | |
|
201 | ||
|
202 | self.draw() | |
|
203 | ||
|
204 | if figfile == None: | |
|
205 | str_datetime = thisDatetime.strftime("%Y%m%d_%H%M%S") | |
|
206 | name = str_datetime | |
|
207 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): | |
|
208 | name = name + '_az' + '_%2.2f'%(dataOut.azimuth) + '_zn' + '_%2.2f'%(dataOut.zenith) | |
|
209 | figfile = self.getFilename(name) | |
|
210 | ||
|
211 | self.save(figpath=figpath, | |
|
212 | figfile=figfile, | |
|
213 | save=save, | |
|
214 | ftp=ftp, | |
|
215 | wr_period=wr_period, | |
|
216 | thisDatetime=thisDatetime) | |
|
217 | ||
|
218 | ||
|
219 | ||
|
9 | 220 | class MomentsPlot(Figure): |
|
10 | 221 | |
|
11 | 222 | isConfig = None |
@@ -446,10 +657,9 class WindProfilerPlot(Figure): | |||
|
446 | 657 | # tmin = None |
|
447 | 658 | # tmax = None |
|
448 | 659 | |
|
449 | ||
|
450 | x = dataOut.getTimeRange1(dataOut.outputInterval) | |
|
451 | y = dataOut.heightList | |
|
452 | z = dataOut.data_output.copy() | |
|
660 | x = dataOut.getTimeRange1(dataOut.paramInterval) | |
|
661 | y = dataOut.heightList | |
|
662 | z = dataOut.data_output.copy() | |
|
453 | 663 | nplots = z.shape[0] #Number of wind dimensions estimated |
|
454 | 664 | nplotsw = nplots |
|
455 | 665 | |
@@ -559,7 +769,7 class WindProfilerPlot(Figure): | |||
|
559 | 769 | thisDatetime=thisDatetime, |
|
560 | 770 | update_figfile=update_figfile) |
|
561 | 771 | |
|
562 |
if dataOut.ltctime + dataOut. |
|
|
772 | if dataOut.ltctime + dataOut.paramInterval >= self.xmax: | |
|
563 | 773 | self.counter_imagwr = wr_period |
|
564 | 774 | self.isConfig = False |
|
565 | 775 | update_figfile = True |
@@ -636,12 +846,12 class ParametersPlot(Figure): | |||
|
636 | 846 | |
|
637 | 847 | counter += 1 |
|
638 | 848 | |
|
639 |
def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap= |
|
|
849 | def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap="jet", | |
|
640 | 850 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None, |
|
641 | 851 | showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None, |
|
642 | 852 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
643 | 853 | server=None, folder=None, username=None, password=None, |
|
644 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0): | |
|
854 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, HEIGHT=None): | |
|
645 | 855 | """ |
|
646 | 856 | |
|
647 | 857 | Input: |
@@ -657,12 +867,11 class ParametersPlot(Figure): | |||
|
657 | 867 | zmin : None, |
|
658 | 868 | zmax : None |
|
659 | 869 | """ |
|
660 | ||
|
661 | if colormap: | |
|
662 | colormap="jet" | |
|
663 |
|
|
|
664 | colormap="RdBu_r" | |
|
665 | ||
|
870 | ||
|
871 | if HEIGHT is not None: | |
|
872 | self.HEIGHT = HEIGHT | |
|
873 | ||
|
874 | ||
|
666 | 875 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
667 | 876 | return |
|
668 | 877 |
@@ -86,7 +86,7 class SpectraPlot(Figure): | |||
|
86 | 86 | save=False, figpath='./', figfile=None, show=True, ftp=False, wr_period=1, |
|
87 | 87 | server=None, folder=None, username=None, password=None, |
|
88 | 88 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, realtime=False, |
|
89 | xaxis="velocity", **kwargs): | |
|
89 | xaxis="frequency", colormap='jet', normFactor=None): | |
|
90 | 90 | |
|
91 | 91 | """ |
|
92 | 92 | |
@@ -103,9 +103,6 class SpectraPlot(Figure): | |||
|
103 | 103 | zmin : None, |
|
104 | 104 | zmax : None |
|
105 | 105 | """ |
|
106 | ||
|
107 | colormap = kwargs.get('colormap','jet') | |
|
108 | ||
|
109 | 106 | if realtime: |
|
110 | 107 | if not(isRealtime(utcdatatime = dataOut.utctime)): |
|
111 | 108 | print 'Skipping this plot function' |
@@ -120,8 +117,10 class SpectraPlot(Figure): | |||
|
120 | 117 | raise ValueError, "Channel %d is not in dataOut.channelList" %channel |
|
121 | 118 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
122 | 119 | |
|
123 |
f |
|
|
124 | ||
|
120 | if normFactor is None: | |
|
121 | factor = dataOut.normFactor | |
|
122 | else: | |
|
123 | factor = normFactor | |
|
125 | 124 | if xaxis == "frequency": |
|
126 | 125 | x = dataOut.getFreqRange(1)/1000. |
|
127 | 126 | xlabel = "Frequency (kHz)" |
@@ -282,7 +281,7 class CrossSpectraPlot(Figure): | |||
|
282 | 281 | save=False, figpath='./', figfile=None, ftp=False, wr_period=1, |
|
283 | 282 | power_cmap='jet', coherence_cmap='jet', phase_cmap='RdBu_r', show=True, |
|
284 | 283 | server=None, folder=None, username=None, password=None, |
|
285 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, | |
|
284 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, | |
|
286 | 285 | xaxis='frequency'): |
|
287 | 286 | |
|
288 | 287 | """ |
@@ -315,8 +314,11 class CrossSpectraPlot(Figure): | |||
|
315 | 314 | |
|
316 | 315 | if len(pairsIndexList) > 4: |
|
317 | 316 | pairsIndexList = pairsIndexList[0:4] |
|
318 | ||
|
319 |
f |
|
|
317 | ||
|
318 | if normFactor is None: | |
|
319 | factor = dataOut.normFactor | |
|
320 | else: | |
|
321 | factor = normFactor | |
|
320 | 322 | x = dataOut.getVelRange(1) |
|
321 | 323 | y = dataOut.getHeiRange() |
|
322 | 324 | z = dataOut.data_spc[:,:,:]/factor |
@@ -517,10 +519,10 class RTIPlot(Figure): | |||
|
517 | 519 | |
|
518 | 520 | def run(self, dataOut, id, wintitle="", channelList=None, showprofile='True', |
|
519 | 521 | xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, |
|
520 | timerange=None, | |
|
522 | timerange=None, colormap='jet', | |
|
521 | 523 | save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True, |
|
522 | 524 | server=None, folder=None, username=None, password=None, |
|
523 |
ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, |
|
|
525 | ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None): | |
|
524 | 526 | |
|
525 | 527 | """ |
|
526 | 528 | |
@@ -538,7 +540,10 class RTIPlot(Figure): | |||
|
538 | 540 | zmax : None |
|
539 | 541 | """ |
|
540 | 542 | |
|
541 | colormap = kwargs.get('colormap', 'jet') | |
|
543 | #colormap = kwargs.get('colormap', 'jet') | |
|
544 | if HEIGHT is not None: | |
|
545 | self.HEIGHT = HEIGHT | |
|
546 | ||
|
542 | 547 | if not isTimeInHourRange(dataOut.datatime, xmin, xmax): |
|
543 | 548 | return |
|
544 | 549 | |
@@ -551,20 +556,21 class RTIPlot(Figure): | |||
|
551 | 556 | raise ValueError, "Channel %d is not in dataOut.channelList" |
|
552 | 557 | channelIndexList.append(dataOut.channelList.index(channel)) |
|
553 | 558 | |
|
554 |
if |
|
|
559 | if normFactor is None: | |
|
555 | 560 | factor = dataOut.normFactor |
|
556 | 561 | else: |
|
557 |
factor = |
|
|
562 | factor = normFactor | |
|
558 | 563 | |
|
559 | 564 | # factor = dataOut.normFactor |
|
560 | 565 | x = dataOut.getTimeRange() |
|
561 | 566 | y = dataOut.getHeiRange() |
|
562 | 567 | |
|
563 |
|
|
|
564 |
|
|
|
565 |
|
|
|
566 |
|
|
|
567 | avgdB = dataOut.getPower() | |
|
568 | z = dataOut.data_spc/factor | |
|
569 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) | |
|
570 | avg = numpy.average(z, axis=1) | |
|
571 | avgdB = 10.*numpy.log10(avg) | |
|
572 | # avgdB = dataOut.getPower() | |
|
573 | ||
|
568 | 574 | |
|
569 | 575 | thisDatetime = dataOut.datatime |
|
570 | 576 | # thisDatetime = datetime.datetime.utcfromtimestamp(dataOut.getTimeRange()[0]) |
@@ -1111,6 +1117,7 class Noise(Figure): | |||
|
1111 | 1117 | |
|
1112 | 1118 | PREFIX = 'noise' |
|
1113 | 1119 | |
|
1120 | ||
|
1114 | 1121 | def __init__(self, **kwargs): |
|
1115 | 1122 | Figure.__init__(self, **kwargs) |
|
1116 | 1123 | self.timerange = 24*60*60 |
@@ -88,6 +88,8 def createAxes(fig, nrow, ncol, xpos, ypos, colspan, rowspan, polar=False): | |||
|
88 | 88 | rowspan=rowspan, |
|
89 | 89 | polar=polar) |
|
90 | 90 | |
|
91 | axes.grid(True) | |
|
92 | ||
|
91 | 93 | matplotlib.pyplot.ion() |
|
92 | 94 | return axes |
|
93 | 95 | |
@@ -174,7 +176,7 def set_linedata(ax, x, y, idline): | |||
|
174 | 176 | |
|
175 | 177 | def pline(iplot, x, y, xlabel='', ylabel='', title=''): |
|
176 | 178 | |
|
177 | ax = iplot.axes | |
|
179 | ax = iplot.get_axes() | |
|
178 | 180 | |
|
179 | 181 | printLabels(ax, xlabel, ylabel, title) |
|
180 | 182 | |
@@ -204,7 +206,7 def createPcolor(ax, x, y, z, xmin, xmax, ymin, ymax, zmin, zmax, | |||
|
204 | 206 | |
|
205 | 207 | z = numpy.ma.masked_invalid(z) |
|
206 | 208 | cmap=matplotlib.pyplot.get_cmap(colormap) |
|
207 |
cmap.set_bad(' |
|
|
209 | cmap.set_bad('white',1.) | |
|
208 | 210 | imesh = ax.pcolormesh(x,y,z.T, vmin=zmin, vmax=zmax, cmap=cmap) |
|
209 | 211 | cb = matplotlib.pyplot.colorbar(imesh, cax=ax_cb) |
|
210 | 212 | cb.set_label(cblabel) |
@@ -239,21 +241,32 def createPcolor(ax, x, y, z, xmin, xmax, ymin, ymax, zmin, zmax, | |||
|
239 | 241 | ax.xaxis.set_major_formatter(FuncFormatter(func)) |
|
240 | 242 | ax.xaxis.set_major_locator(LinearLocator(7)) |
|
241 | 243 | |
|
244 | ax.grid(True) | |
|
242 | 245 | matplotlib.pyplot.ion() |
|
243 | 246 | return imesh |
|
244 | 247 | |
|
245 | 248 | def pcolor(imesh, z, xlabel='', ylabel='', title=''): |
|
246 | 249 | |
|
250 | z = numpy.ma.masked_invalid(z) | |
|
251 | ||
|
252 | cmap=matplotlib.pyplot.get_cmap('jet') | |
|
253 | cmap.set_bad('white',1.) | |
|
254 | ||
|
247 | 255 | z = z.T |
|
248 | ax = imesh.axes | |
|
256 | ax = imesh.get_axes() | |
|
249 | 257 | printLabels(ax, xlabel, ylabel, title) |
|
250 | 258 | imesh.set_array(z.ravel()) |
|
259 | ax.grid(True) | |
|
260 | ||
|
251 | 261 | |
|
252 | 262 | def addpcolor(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'): |
|
253 | 263 | |
|
254 | 264 | printLabels(ax, xlabel, ylabel, title) |
|
255 | ||
|
265 | z = numpy.ma.masked_invalid(z) | |
|
266 | cmap=matplotlib.pyplot.get_cmap(colormap) | |
|
267 | cmap.set_bad('white',1.) | |
|
256 | 268 | ax.pcolormesh(x,y,z.T,vmin=zmin,vmax=zmax, cmap=matplotlib.pyplot.get_cmap(colormap)) |
|
269 | ax.grid(True) | |
|
257 | 270 | |
|
258 | 271 | def addpcolorbuffer(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'): |
|
259 | 272 | |
@@ -262,12 +275,13 def addpcolorbuffer(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', col | |||
|
262 | 275 | ax.collections.remove(ax.collections[0]) |
|
263 | 276 | |
|
264 | 277 | z = numpy.ma.masked_invalid(z) |
|
265 | ||
|
278 | ||
|
266 | 279 | cmap=matplotlib.pyplot.get_cmap(colormap) |
|
267 |
cmap.set_bad(' |
|
|
268 | ||
|
280 | cmap.set_bad('white',1.) | |
|
269 | 281 | |
|
270 | 282 | ax.pcolormesh(x,y,z.T,vmin=zmin,vmax=zmax, cmap=cmap) |
|
283 | ax.grid(True) | |
|
284 | ||
|
271 | 285 | |
|
272 | 286 | def createPmultiline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', title='', legendlabels=None, |
|
273 | 287 | ticksize=9, xtick_visible=True, ytick_visible=True, |
@@ -326,7 +340,7 def createPmultiline(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='', tit | |||
|
326 | 340 | |
|
327 | 341 | def pmultiline(iplot, x, y, xlabel='', ylabel='', title=''): |
|
328 | 342 | |
|
329 | ax = iplot.axes | |
|
343 | ax = iplot.get_axes() | |
|
330 | 344 | |
|
331 | 345 | printLabels(ax, xlabel, ylabel, title) |
|
332 | 346 | |
@@ -403,8 +417,7 def createPmultilineYAxis(ax, x, y, xmin, xmax, ymin, ymax, xlabel='', ylabel='' | |||
|
403 | 417 | |
|
404 | 418 | def pmultilineyaxis(iplot, x, y, xlabel='', ylabel='', title=''): |
|
405 | 419 | |
|
406 | ax = iplot.axes | |
|
407 | ||
|
420 | ax = iplot.get_axes() | |
|
408 | 421 | printLabels(ax, xlabel, ylabel, title) |
|
409 | 422 | |
|
410 | 423 | for i in range(len(ax.lines)): |
@@ -425,7 +438,7 def createPolar(ax, x, y, | |||
|
425 | 438 | # ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center' ,size='11') |
|
426 | 439 | # ax.text(0, 50, ylabel, rotation='vertical', va ='center', ha = 'left' ,size='11') |
|
427 | 440 | # ax.text(100, 100, 'example', ha='left', va='center', rotation='vertical') |
|
428 |
ax.yaxis.labelpad = |
|
|
441 | ax.yaxis.labelpad = 230 | |
|
429 | 442 | printLabels(ax, xlabel, ylabel, title) |
|
430 | 443 | iplot = ax.lines[-1] |
|
431 | 444 | |
@@ -449,7 +462,7 def createPolar(ax, x, y, | |||
|
449 | 462 | |
|
450 | 463 | def polar(iplot, x, y, xlabel='', ylabel='', title=''): |
|
451 | 464 | |
|
452 | ax = iplot.axes | |
|
465 | ax = iplot.get_axes() | |
|
453 | 466 | |
|
454 | 467 | # ax.text(0, -110, ylabel, rotation='vertical', va ='center', ha = 'center',size='11') |
|
455 | 468 | printLabels(ax, xlabel, ylabel, title) |
@@ -12,3 +12,10 from jroIO_usrp import * | |||
|
12 | 12 | from jroIO_kamisr import * |
|
13 | 13 | from jroIO_param import * |
|
14 | 14 | from jroIO_hf import * |
|
15 | ||
|
16 | from jroIO_madrigal import * | |
|
17 | ||
|
18 | from bltrIO_param import * | |
|
19 | from jroIO_bltr import * | |
|
20 | from jroIO_mira35c import * | |
|
21 |
@@ -1432,11 +1432,12 class JRODataReader(JRODataIO): | |||
|
1432 | 1432 | print "[Reading] Number of read blocks %04d" %self.nTotalBlocks |
|
1433 | 1433 | |
|
1434 | 1434 | def printNumberOfBlock(self): |
|
1435 | 'SPAM!' | |
|
1435 | 1436 | |
|
1436 | if self.flagIsNewBlock: | |
|
1437 | print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks, | |
|
1438 | self.processingHeaderObj.dataBlocksPerFile, | |
|
1439 | self.dataOut.datatime.ctime()) | |
|
1437 | # if self.flagIsNewBlock: | |
|
1438 | # print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks, | |
|
1439 | # self.processingHeaderObj.dataBlocksPerFile, | |
|
1440 | # self.dataOut.datatime.ctime()) | |
|
1440 | 1441 | |
|
1441 | 1442 | def printInfo(self): |
|
1442 | 1443 |
@@ -178,8 +178,8 class ParamReader(ProcessingUnit): | |||
|
178 | 178 | print "[Reading] %d file(s) was(were) found in time range: %s - %s" %(len(filenameList), startTime, endTime) |
|
179 | 179 | |
|
180 | 180 | |
|
181 | for i in range(len(filenameList)): | |
|
182 | print "[Reading] %s -> [%s]" %(filenameList[i], datetimeList[i].ctime()) | |
|
181 | # for i in range(len(filenameList)): | |
|
182 | # print "[Reading] %s -> [%s]" %(filenameList[i], datetimeList[i].ctime()) | |
|
183 | 183 | |
|
184 | 184 | self.filenameList = filenameList |
|
185 | 185 | self.datetimeList = datetimeList |
@@ -11,6 +11,7 from schainpy.model.data.jroheaderIO import PROCFLAG, BasicHeader, SystemHeader, | |||
|
11 | 11 | from schainpy.model.data.jrodata import Spectra |
|
12 | 12 | |
|
13 | 13 | class SpectraReader(JRODataReader, ProcessingUnit): |
|
14 | ||
|
14 | 15 | """ |
|
15 | 16 | Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura |
|
16 | 17 | de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones) |
@@ -20,6 +21,7 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
20 | 21 | paresCanalesDiferentes * alturas * perfiles (Cross Spectra) |
|
21 | 22 | canales * alturas (DC Channels) |
|
22 | 23 | |
|
24 | ||
|
23 | 25 | Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader, |
|
24 | 26 | RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la |
|
25 | 27 | cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de |
@@ -74,6 +76,7 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
74 | 76 | Inicializador de la clase SpectraReader para la lectura de datos de espectros. |
|
75 | 77 | |
|
76 | 78 | Inputs: |
|
79 | ||
|
77 | 80 | dataOut : Objeto de la clase Spectra. Este objeto sera utilizado para |
|
78 | 81 | almacenar un perfil de datos cada vez que se haga un requerimiento |
|
79 | 82 | (getData). El perfil sera obtenido a partir del buffer de datos, |
@@ -81,104 +84,107 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
81 | 84 | bloque de datos. |
|
82 | 85 | Si este parametro no es pasado se creara uno internamente. |
|
83 | 86 | |
|
84 |
|
|
|
87 | ||
|
88 | Affected: | |
|
89 | ||
|
85 | 90 | self.dataOut |
|
86 | 91 | |
|
87 | 92 | Return : None |
|
88 | 93 | """ |
|
89 | 94 | |
|
95 | ||
|
90 | 96 | #Eliminar de la base la herencia |
|
91 | 97 | ProcessingUnit.__init__(self, **kwargs) |
|
92 | ||
|
98 | ||
|
93 | 99 | # self.isConfig = False |
|
94 | ||
|
100 | ||
|
95 | 101 | self.pts2read_SelfSpectra = 0 |
|
96 | ||
|
102 | ||
|
97 | 103 | self.pts2read_CrossSpectra = 0 |
|
98 | ||
|
104 | ||
|
99 | 105 | self.pts2read_DCchannels = 0 |
|
100 | ||
|
106 | ||
|
101 | 107 | self.datablock = None |
|
102 | ||
|
108 | ||
|
103 | 109 | self.utc = None |
|
104 | ||
|
110 | ||
|
105 | 111 | self.ext = ".pdata" |
|
106 | ||
|
112 | ||
|
107 | 113 | self.optchar = "P" |
|
108 | ||
|
114 | ||
|
109 | 115 | self.basicHeaderObj = BasicHeader(LOCALTIME) |
|
110 | ||
|
116 | ||
|
111 | 117 | self.systemHeaderObj = SystemHeader() |
|
112 | ||
|
118 | ||
|
113 | 119 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
114 | ||
|
120 | ||
|
115 | 121 | self.processingHeaderObj = ProcessingHeader() |
|
116 | ||
|
122 | ||
|
117 | 123 | self.online = 0 |
|
118 | ||
|
124 | ||
|
119 | 125 | self.fp = None |
|
120 | ||
|
126 | ||
|
121 | 127 | self.idFile = None |
|
122 | ||
|
128 | ||
|
123 | 129 | self.dtype = None |
|
124 | ||
|
130 | ||
|
125 | 131 | self.fileSizeByHeader = None |
|
126 | ||
|
132 | ||
|
127 | 133 | self.filenameList = [] |
|
128 | ||
|
134 | ||
|
129 | 135 | self.filename = None |
|
130 | ||
|
136 | ||
|
131 | 137 | self.fileSize = None |
|
132 | ||
|
138 | ||
|
133 | 139 | self.firstHeaderSize = 0 |
|
134 | ||
|
140 | ||
|
135 | 141 | self.basicHeaderSize = 24 |
|
136 | ||
|
142 | ||
|
137 | 143 | self.pathList = [] |
|
138 | 144 | |
|
139 | 145 | self.lastUTTime = 0 |
|
140 | ||
|
146 | ||
|
141 | 147 | self.maxTimeStep = 30 |
|
142 | ||
|
148 | ||
|
143 | 149 | self.flagNoMoreFiles = 0 |
|
144 | ||
|
150 | ||
|
145 | 151 | self.set = 0 |
|
146 | ||
|
152 | ||
|
147 | 153 | self.path = None |
|
148 | 154 | |
|
149 | 155 | self.delay = 60 #seconds |
|
150 | ||
|
156 | ||
|
151 | 157 | self.nTries = 3 #quantity tries |
|
152 | ||
|
158 | ||
|
153 | 159 | self.nFiles = 3 #number of files for searching |
|
154 | ||
|
160 | ||
|
155 | 161 | self.nReadBlocks = 0 |
|
156 | ||
|
162 | ||
|
157 | 163 | self.flagIsNewFile = 1 |
|
158 | ||
|
164 | ||
|
159 | 165 | self.__isFirstTimeOnline = 1 |
|
160 | ||
|
166 | ||
|
161 | 167 | # self.ippSeconds = 0 |
|
162 | ||
|
163 | self.flagDiscontinuousBlock = 0 | |
|
164 | ||
|
168 | ||
|
169 | self.flagDiscontinuousBlock = 0 | |
|
170 | ||
|
165 | 171 | self.flagIsNewBlock = 0 |
|
166 | ||
|
172 | ||
|
167 | 173 | self.nTotalBlocks = 0 |
|
168 | ||
|
174 | ||
|
169 | 175 | self.blocksize = 0 |
|
170 | ||
|
176 | ||
|
171 | 177 | self.dataOut = self.createObjByDefault() |
|
172 | ||
|
178 | ||
|
173 | 179 | self.profileIndex = 1 #Always |
|
174 | 180 | |
|
175 | 181 | |
|
176 | 182 | def createObjByDefault(self): |
|
177 | ||
|
183 | ||
|
178 | 184 | dataObj = Spectra() |
|
179 | ||
|
185 | ||
|
180 | 186 | return dataObj |
|
181 | ||
|
187 | ||
|
182 | 188 | def __hasNotDataInBuffer(self): |
|
183 | 189 | return 1 |
|
184 | 190 | |
@@ -186,7 +192,7 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
186 | 192 | def getBlockDimension(self): |
|
187 | 193 | """ |
|
188 | 194 | Obtiene la cantidad de puntos a leer por cada bloque de datos |
|
189 | ||
|
195 | ||
|
190 | 196 | Affected: |
|
191 | 197 | self.nRdChannels |
|
192 | 198 | self.nRdPairs |
@@ -206,37 +212,39 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
206 | 212 | |
|
207 | 213 | for i in range(0, self.processingHeaderObj.totalSpectra*2, 2): |
|
208 | 214 | if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]: |
|
209 | self.nRdChannels = self.nRdChannels + 1 #par de canales iguales | |
|
215 | self.nRdChannels = self.nRdChannels + 1 #par de canales iguales | |
|
216 | ||
|
210 | 217 | else: |
|
211 | 218 | self.nRdPairs = self.nRdPairs + 1 #par de canales diferentes |
|
212 | 219 | self.rdPairList.append((self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1])) |
|
213 | 220 | |
|
214 | 221 | pts2read = self.processingHeaderObj.nHeights * self.processingHeaderObj.profilesPerBlock |
|
215 | ||
|
222 | ||
|
216 | 223 | self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read) |
|
217 | 224 | self.blocksize = self.pts2read_SelfSpectra |
|
218 | ||
|
225 | ||
|
219 | 226 | if self.processingHeaderObj.flag_cspc: |
|
220 | 227 | self.pts2read_CrossSpectra = int(self.nRdPairs * pts2read) |
|
221 | 228 | self.blocksize += self.pts2read_CrossSpectra |
|
222 | ||
|
229 | ||
|
223 | 230 | if self.processingHeaderObj.flag_dc: |
|
224 | 231 | self.pts2read_DCchannels = int(self.systemHeaderObj.nChannels * self.processingHeaderObj.nHeights) |
|
225 | 232 | self.blocksize += self.pts2read_DCchannels |
|
226 | ||
|
233 | ||
|
227 | 234 | # self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels |
|
228 | 235 | |
|
229 | ||
|
236 | ||
|
230 | 237 | def readBlock(self): |
|
231 | 238 | """ |
|
232 | 239 | Lee el bloque de datos desde la posicion actual del puntero del archivo |
|
233 | 240 | (self.fp) y actualiza todos los parametros relacionados al bloque de datos |
|
234 | 241 | (metadata + data). La data leida es almacenada en el buffer y el contador del buffer |
|
235 | 242 | es seteado a 0 |
|
236 | ||
|
243 | ||
|
237 | 244 | Return: None |
|
238 | ||
|
245 | ||
|
239 | 246 | Variables afectadas: |
|
247 | ||
|
240 | 248 | |
|
241 | 249 | self.flagIsNewFile |
|
242 | 250 | self.flagIsNewBlock |
@@ -245,9 +253,19 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
245 | 253 | self.data_cspc |
|
246 | 254 | self.data_dc |
|
247 | 255 | |
|
248 | Exceptions: | |
|
256 | Exceptions: | |
|
249 | 257 | Si un bloque leido no es un bloque valido |
|
250 | 258 | """ |
|
259 | print ' ======================================================== ' | |
|
260 | print ' ' | |
|
261 | print ' ' | |
|
262 | print self.processingHeaderObj.totalSpectra, 'TotalSpectra', type(self.processingHeaderObj.totalSpectra) | |
|
263 | print self.processingHeaderObj.spectraComb, 'SpectraComb', type(self.processingHeaderObj.spectraComb) | |
|
264 | print ' ' | |
|
265 | print ' ' | |
|
266 | print ' ======================================================== ' | |
|
267 | ||
|
268 | ||
|
251 | 269 | blockOk_flag = False |
|
252 | 270 | fpointer = self.fp.tell() |
|
253 | 271 | |
@@ -257,30 +275,32 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
257 | 275 | if self.processingHeaderObj.flag_cspc: |
|
258 | 276 | cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra ) |
|
259 | 277 | cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D |
|
260 | ||
|
278 | ||
|
261 | 279 | if self.processingHeaderObj.flag_dc: |
|
262 | 280 | dc = numpy.fromfile( self.fp, self.dtype, self.pts2read_DCchannels ) #int(self.processingHeaderObj.nHeights*self.systemHeaderObj.nChannels) ) |
|
263 | 281 | dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D |
|
264 | ||
|
265 | ||
|
282 | ||
|
283 | ||
|
266 | 284 | if not(self.processingHeaderObj.shif_fft): |
|
267 | 285 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
268 | 286 | shift = int(self.processingHeaderObj.profilesPerBlock/2) |
|
269 | 287 | spc = numpy.roll( spc, shift , axis=2 ) |
|
270 | ||
|
288 | ||
|
271 | 289 | if self.processingHeaderObj.flag_cspc: |
|
272 | 290 | #desplaza a la derecha en el eje 2 determinadas posiciones |
|
273 | 291 | cspc = numpy.roll( cspc, shift, axis=2 ) |
|
274 | ||
|
292 | ||
|
275 | 293 | #Dimensions : nChannels, nProfiles, nSamples |
|
276 | 294 | spc = numpy.transpose( spc, (0,2,1) ) |
|
277 | 295 | self.data_spc = spc |
|
296 | ||
|
297 | if self.processingHeaderObj.flag_cspc: | |
|
278 | 298 | |
|
279 | if self.processingHeaderObj.flag_cspc: | |
|
280 | 299 | cspc = numpy.transpose( cspc, (0,2,1) ) |
|
281 | 300 | self.data_cspc = cspc['real'] + cspc['imag']*1j |
|
282 | 301 | else: |
|
283 | 302 | self.data_cspc = None |
|
303 | ||
|
284 | 304 | |
|
285 | 305 | if self.processingHeaderObj.flag_dc: |
|
286 | 306 | self.data_dc = dc['real'] + dc['imag']*1j |
@@ -294,60 +314,60 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
294 | 314 | self.nReadBlocks += 1 |
|
295 | 315 | |
|
296 | 316 | return 1 |
|
297 | ||
|
317 | ||
|
298 | 318 | def getFirstHeader(self): |
|
299 | ||
|
319 | ||
|
300 | 320 | self.getBasicHeader() |
|
301 | ||
|
321 | ||
|
302 | 322 | self.dataOut.systemHeaderObj = self.systemHeaderObj.copy() |
|
303 | ||
|
323 | ||
|
304 | 324 | self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy() |
|
305 | ||
|
325 | ||
|
306 | 326 | # self.dataOut.ippSeconds = self.ippSeconds |
|
307 | ||
|
327 | ||
|
308 | 328 | # self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt * self.processingHeaderObj.nIncohInt * self.processingHeaderObj.profilesPerBlock |
|
309 | 329 | |
|
310 | 330 | self.dataOut.dtype = self.dtype |
|
311 | ||
|
331 | ||
|
312 | 332 | # self.dataOut.nPairs = self.nPairs |
|
313 | ||
|
333 | ||
|
314 | 334 | self.dataOut.pairsList = self.rdPairList |
|
315 | ||
|
335 | ||
|
316 | 336 | self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock |
|
317 | ||
|
337 | ||
|
318 | 338 | self.dataOut.nFFTPoints = self.processingHeaderObj.profilesPerBlock |
|
319 | ||
|
339 | ||
|
320 | 340 | self.dataOut.nCohInt = self.processingHeaderObj.nCohInt |
|
321 | ||
|
341 | ||
|
322 | 342 | self.dataOut.nIncohInt = self.processingHeaderObj.nIncohInt |
|
323 | ||
|
343 | ||
|
324 | 344 | xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight |
|
325 | 345 | |
|
326 | self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight) | |
|
327 | ||
|
346 | self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight) | |
|
347 | ||
|
328 | 348 | self.dataOut.channelList = range(self.systemHeaderObj.nChannels) |
|
329 | ||
|
349 | ||
|
330 | 350 | self.dataOut.flagShiftFFT = True #Data is always shifted |
|
331 | ||
|
351 | ||
|
332 | 352 | self.dataOut.flagDecodeData = self.processingHeaderObj.flag_decode #asumo q la data no esta decodificada |
|
333 | ||
|
334 | self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip #asumo q la data esta sin flip | |
|
335 | ||
|
353 | ||
|
354 | self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip #asumo q la data esta sin flip | |
|
355 | ||
|
336 | 356 | def getData(self): |
|
337 | 357 | """ |
|
338 | 358 | First method to execute before "RUN" is called. |
|
339 | ||
|
359 | ||
|
340 | 360 | Copia el buffer de lectura a la clase "Spectra", |
|
341 | 361 | con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de |
|
342 | 362 | lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock" |
|
343 | ||
|
363 | ||
|
344 | 364 | Return: |
|
345 | 365 | 0 : Si no hay mas archivos disponibles |
|
346 | 366 | 1 : Si hizo una buena copia del buffer |
|
347 | ||
|
367 | ||
|
348 | 368 | Affected: |
|
349 | 369 | self.dataOut |
|
350 | ||
|
370 | ||
|
351 | 371 | self.flagDiscontinuousBlock |
|
352 | 372 | self.flagIsNewBlock |
|
353 | 373 | """ |
@@ -356,68 +376,70 class SpectraReader(JRODataReader, ProcessingUnit): | |||
|
356 | 376 | self.dataOut.flagNoData = True |
|
357 | 377 | print 'Process finished' |
|
358 | 378 | return 0 |
|
359 | ||
|
379 | ||
|
360 | 380 | self.flagDiscontinuousBlock = 0 |
|
361 | 381 | self.flagIsNewBlock = 0 |
|
362 | ||
|
363 | if self.__hasNotDataInBuffer(): | |
|
382 | ||
|
383 | if self.__hasNotDataInBuffer(): | |
|
364 | 384 | |
|
365 | 385 | if not( self.readNextBlock() ): |
|
366 | 386 | self.dataOut.flagNoData = True |
|
367 | 387 | return 0 |
|
388 | ||
|
368 | 389 | |
|
369 | 390 | #data es un numpy array de 3 dmensiones (perfiles, alturas y canales) |
|
370 | 391 | |
|
371 | 392 | if self.data_spc is None: |
|
372 | 393 | self.dataOut.flagNoData = True |
|
373 | 394 | return 0 |
|
374 | ||
|
395 | ||
|
375 | 396 | self.getBasicHeader() |
|
376 | ||
|
397 | ||
|
377 | 398 | self.getFirstHeader() |
|
378 | 399 | |
|
379 | 400 | self.dataOut.data_spc = self.data_spc |
|
380 | ||
|
401 | ||
|
381 | 402 | self.dataOut.data_cspc = self.data_cspc |
|
382 | ||
|
403 | ||
|
383 | 404 | self.dataOut.data_dc = self.data_dc |
|
384 | ||
|
405 | ||
|
385 | 406 | self.dataOut.flagNoData = False |
|
386 | ||
|
407 | ||
|
387 | 408 | self.dataOut.realtime = self.online |
|
388 | ||
|
409 | ||
|
389 | 410 | return self.dataOut.data_spc |
|
390 | 411 | |
|
391 | 412 | class SpectraWriter(JRODataWriter, Operation): |
|
392 | ||
|
393 |
|
|
|
413 | ||
|
414 | """ | |
|
394 | 415 | Esta clase permite escribir datos de espectros a archivos procesados (.pdata). La escritura |
|
395 | de los datos siempre se realiza por bloques. | |
|
416 | de los datos siempre se realiza por bloques. | |
|
396 | 417 | """ |
|
397 | ||
|
418 | ||
|
398 | 419 | ext = ".pdata" |
|
399 | ||
|
420 | ||
|
400 | 421 | optchar = "P" |
|
401 | ||
|
422 | ||
|
402 | 423 | shape_spc_Buffer = None |
|
403 | ||
|
424 | ||
|
404 | 425 | shape_cspc_Buffer = None |
|
405 | ||
|
426 | ||
|
406 | 427 | shape_dc_Buffer = None |
|
407 | ||
|
428 | ||
|
408 | 429 | data_spc = None |
|
409 | ||
|
430 | ||
|
410 | 431 | data_cspc = None |
|
411 | ||
|
432 | ||
|
412 | 433 | data_dc = None |
|
413 | ||
|
434 | ||
|
414 | 435 | # dataOut = None |
|
415 | ||
|
416 |
def __init__(self |
|
|
417 | """ | |
|
436 | ||
|
437 | def __init__(self): | |
|
438 | """ | |
|
418 | 439 | Inicializador de la clase SpectraWriter para la escritura de datos de espectros. |
|
440 | ||
|
441 | Affected: | |
|
419 | 442 | |
|
420 | Affected: | |
|
421 | 443 | self.dataOut |
|
422 | 444 | self.basicHeaderObj |
|
423 | 445 | self.systemHeaderObj |
@@ -426,49 +448,51 class SpectraWriter(JRODataWriter, Operation): | |||
|
426 | 448 | |
|
427 | 449 | Return: None |
|
428 | 450 | """ |
|
429 | ||
|
430 |
Operation.__init__(self |
|
|
431 | ||
|
451 | ||
|
452 | Operation.__init__(self) | |
|
453 | ||
|
432 | 454 | self.isConfig = False |
|
433 | ||
|
455 | ||
|
434 | 456 | self.nTotalBlocks = 0 |
|
435 | ||
|
457 | ||
|
436 | 458 | self.data_spc = None |
|
437 | ||
|
459 | ||
|
438 | 460 | self.data_cspc = None |
|
461 | ||
|
439 | 462 | |
|
440 | 463 | self.data_dc = None |
|
441 | 464 | |
|
442 | 465 | self.fp = None |
|
443 | 466 | |
|
444 | 467 | self.flagIsNewFile = 1 |
|
445 | ||
|
446 | self.nTotalBlocks = 0 | |
|
447 | ||
|
468 | ||
|
469 | self.nTotalBlocks = 0 | |
|
470 | ||
|
448 | 471 | self.flagIsNewBlock = 0 |
|
449 | 472 | |
|
450 | 473 | self.setFile = None |
|
451 | ||
|
474 | ||
|
452 | 475 | self.dtype = None |
|
453 | ||
|
476 | ||
|
454 | 477 | self.path = None |
|
455 | ||
|
478 | ||
|
456 | 479 | self.noMoreFiles = 0 |
|
457 | ||
|
480 | ||
|
458 | 481 | self.filename = None |
|
459 | ||
|
482 | ||
|
460 | 483 | self.basicHeaderObj = BasicHeader(LOCALTIME) |
|
461 | ||
|
484 | ||
|
462 | 485 | self.systemHeaderObj = SystemHeader() |
|
463 | ||
|
486 | ||
|
464 | 487 | self.radarControllerHeaderObj = RadarControllerHeader() |
|
465 | ||
|
488 | ||
|
466 | 489 | self.processingHeaderObj = ProcessingHeader() |
|
467 | 490 | |
|
468 | ||
|
491 | ||
|
469 | 492 | def hasAllDataInBuffer(self): |
|
470 | 493 | return 1 |
|
471 | 494 | |
|
495 | ||
|
472 | 496 | |
|
473 | 497 | def setBlockDimension(self): |
|
474 | 498 | """ |
@@ -488,14 +512,15 class SpectraWriter(JRODataWriter, Operation): | |||
|
488 | 512 | self.shape_cspc_Buffer = (self.dataOut.nPairs, |
|
489 | 513 | self.processingHeaderObj.nHeights, |
|
490 | 514 | self.processingHeaderObj.profilesPerBlock) |
|
491 | ||
|
515 | ||
|
492 | 516 | self.shape_dc_Buffer = (self.dataOut.nChannels, |
|
493 | 517 | self.processingHeaderObj.nHeights) |
|
494 | 518 | |
|
495 | ||
|
519 | ||
|
496 | 520 | def writeBlock(self): |
|
497 | 521 | """ |
|
498 | 522 | Escribe el buffer en el file designado |
|
523 | ||
|
499 | 524 | |
|
500 | 525 | Affected: |
|
501 | 526 | self.data_spc |
@@ -504,11 +529,11 class SpectraWriter(JRODataWriter, Operation): | |||
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504 | 529 | self.flagIsNewFile |
|
505 | 530 | self.flagIsNewBlock |
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506 | 531 | self.nTotalBlocks |
|
507 | self.nWriteBlocks | |
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508 | ||
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532 | self.nWriteBlocks | |
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533 | ||
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509 | 534 | Return: None |
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510 | 535 | """ |
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511 | ||
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536 | ||
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512 | 537 | spc = numpy.transpose( self.data_spc, (0,2,1) ) |
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513 | 538 | if not( self.processingHeaderObj.shif_fft ): |
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514 | 539 | spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones |
@@ -525,6 +550,7 class SpectraWriter(JRODataWriter, Operation): | |||
|
525 | 550 | data['imag'] = cspc.imag |
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526 | 551 | data = data.reshape((-1)) |
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527 | 552 | data.tofile(self.fp) |
|
553 | ||
|
528 | 554 | |
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529 | 555 | if self.data_dc is not None: |
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530 | 556 | data = numpy.zeros( self.shape_dc_Buffer, self.dtype ) |
@@ -535,145 +561,147 class SpectraWriter(JRODataWriter, Operation): | |||
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535 | 561 | data.tofile(self.fp) |
|
536 | 562 | |
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537 | 563 | # self.data_spc.fill(0) |
|
538 | # | |
|
564 | # | |
|
539 | 565 | # if self.data_dc is not None: |
|
540 | 566 | # self.data_dc.fill(0) |
|
541 | # | |
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567 | # | |
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542 | 568 | # if self.data_cspc is not None: |
|
543 | 569 | # self.data_cspc.fill(0) |
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570 | ||
|
544 | 571 | |
|
545 | 572 | self.flagIsNewFile = 0 |
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546 | 573 | self.flagIsNewBlock = 1 |
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547 | 574 | self.nTotalBlocks += 1 |
|
548 | 575 | self.nWriteBlocks += 1 |
|
549 | 576 | self.blockIndex += 1 |
|
550 | ||
|
577 | ||
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551 | 578 | # print "[Writing] Block = %d04" %self.blockIndex |
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552 | ||
|
579 | ||
|
553 | 580 | def putData(self): |
|
554 | 581 | """ |
|
555 | Setea un bloque de datos y luego los escribe en un file | |
|
582 | Setea un bloque de datos y luego los escribe en un file | |
|
583 | ||
|
556 | 584 | |
|
557 | 585 | Affected: |
|
558 | 586 | self.data_spc |
|
559 | 587 | self.data_cspc |
|
560 | 588 | self.data_dc |
|
561 | 589 | |
|
562 | Return: | |
|
563 | 0 : Si no hay data o no hay mas files que puedan escribirse | |
|
590 | Return: | |
|
591 | 0 : Si no hay data o no hay mas files que puedan escribirse | |
|
564 | 592 | 1 : Si se escribio la data de un bloque en un file |
|
565 | 593 | """ |
|
566 | ||
|
594 | ||
|
567 | 595 | if self.dataOut.flagNoData: |
|
568 | 596 | return 0 |
|
569 | ||
|
597 | ||
|
570 | 598 | self.flagIsNewBlock = 0 |
|
571 | ||
|
599 | ||
|
572 | 600 | if self.dataOut.flagDiscontinuousBlock: |
|
573 | 601 | self.data_spc.fill(0) |
|
574 |
|
|
|
575 |
|
|
|
576 | if self.dataOut.data_dc is not None: | |
|
577 | self.data_dc.fill(0) | |
|
602 | self.data_cspc.fill(0) | |
|
603 | self.data_dc.fill(0) | |
|
578 | 604 | self.setNextFile() |
|
579 | ||
|
605 | ||
|
580 | 606 | if self.flagIsNewFile == 0: |
|
581 | 607 | self.setBasicHeader() |
|
582 | ||
|
608 | ||
|
583 | 609 | self.data_spc = self.dataOut.data_spc.copy() |
|
584 | ||
|
610 | ||
|
585 | 611 | if self.dataOut.data_cspc is not None: |
|
586 | 612 | self.data_cspc = self.dataOut.data_cspc.copy() |
|
587 | ||
|
613 | ||
|
588 | 614 | if self.dataOut.data_dc is not None: |
|
589 | 615 | self.data_dc = self.dataOut.data_dc.copy() |
|
590 | ||
|
616 | ||
|
591 | 617 | # #self.processingHeaderObj.dataBlocksPerFile) |
|
592 | 618 | if self.hasAllDataInBuffer(): |
|
593 | 619 | # self.setFirstHeader() |
|
594 | 620 | self.writeNextBlock() |
|
595 | ||
|
621 | ||
|
596 | 622 | return 1 |
|
623 | ||
|
597 | 624 | |
|
598 | 625 | def __getBlockSize(self): |
|
599 | 626 | ''' |
|
600 | 627 | Este metodos determina el cantidad de bytes para un bloque de datos de tipo Spectra |
|
601 | 628 | ''' |
|
602 | ||
|
629 | ||
|
603 | 630 | dtype_width = self.getDtypeWidth() |
|
604 | ||
|
631 | ||
|
605 | 632 | pts2write = self.dataOut.nHeights * self.dataOut.nFFTPoints |
|
606 | ||
|
633 | ||
|
607 | 634 | pts2write_SelfSpectra = int(self.dataOut.nChannels * pts2write) |
|
608 | 635 | blocksize = (pts2write_SelfSpectra*dtype_width) |
|
609 | ||
|
636 | ||
|
610 | 637 | if self.dataOut.data_cspc is not None: |
|
611 | 638 | pts2write_CrossSpectra = int(self.dataOut.nPairs * pts2write) |
|
612 | 639 | blocksize += (pts2write_CrossSpectra*dtype_width*2) |
|
613 | ||
|
640 | ||
|
614 | 641 | if self.dataOut.data_dc is not None: |
|
615 | 642 | pts2write_DCchannels = int(self.dataOut.nChannels * self.dataOut.nHeights) |
|
616 | 643 | blocksize += (pts2write_DCchannels*dtype_width*2) |
|
617 | ||
|
644 | ||
|
618 | 645 | # blocksize = blocksize #* datatypeValue * 2 #CORREGIR ESTO |
|
619 | 646 | |
|
620 | 647 | return blocksize |
|
621 | ||
|
648 | ||
|
622 | 649 | def setFirstHeader(self): |
|
623 | ||
|
650 | ||
|
624 | 651 |
|
|
625 | 652 | Obtiene una copia del First Header |
|
626 | ||
|
653 | ||
|
627 | 654 | Affected: |
|
628 | 655 | self.systemHeaderObj |
|
629 | 656 | self.radarControllerHeaderObj |
|
630 | 657 | self.dtype |
|
631 | 658 | |
|
632 | Return: | |
|
659 | Return: | |
|
633 | 660 | None |
|
634 | 661 | """ |
|
635 | ||
|
662 | ||
|
636 | 663 | self.systemHeaderObj = self.dataOut.systemHeaderObj.copy() |
|
637 | 664 | self.systemHeaderObj.nChannels = self.dataOut.nChannels |
|
638 | 665 | self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy() |
|
639 | ||
|
666 | ||
|
640 | 667 | self.processingHeaderObj.dtype = 1 # Spectra |
|
641 | 668 | self.processingHeaderObj.blockSize = self.__getBlockSize() |
|
642 | 669 | self.processingHeaderObj.profilesPerBlock = self.dataOut.nFFTPoints |
|
643 | 670 | self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile |
|
644 | 671 | self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows |
|
645 | 672 | self.processingHeaderObj.nCohInt = self.dataOut.nCohInt# Se requiere para determinar el valor de timeInterval |
|
646 | self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt | |
|
673 | self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt | |
|
647 | 674 | self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels |
|
648 | 675 | self.processingHeaderObj.shif_fft = self.dataOut.flagShiftFFT |
|
676 | ||
|
649 | 677 | |
|
650 | 678 | if self.processingHeaderObj.totalSpectra > 0: |
|
651 | 679 | channelList = [] |
|
652 | 680 | for channel in range(self.dataOut.nChannels): |
|
653 | 681 | channelList.append(channel) |
|
654 | 682 | channelList.append(channel) |
|
655 | ||
|
683 | ||
|
656 | 684 | pairsList = [] |
|
657 | 685 | if self.dataOut.nPairs > 0: |
|
658 | 686 | for pair in self.dataOut.pairsList: |
|
659 | 687 | pairsList.append(pair[0]) |
|
660 | 688 | pairsList.append(pair[1]) |
|
661 | ||
|
689 | ||
|
662 | 690 | spectraComb = channelList + pairsList |
|
663 | 691 | spectraComb = numpy.array(spectraComb, dtype="u1") |
|
664 | 692 | self.processingHeaderObj.spectraComb = spectraComb |
|
665 | ||
|
693 | ||
|
666 | 694 | if self.dataOut.code is not None: |
|
667 | 695 | self.processingHeaderObj.code = self.dataOut.code |
|
668 | 696 | self.processingHeaderObj.nCode = self.dataOut.nCode |
|
669 | 697 | self.processingHeaderObj.nBaud = self.dataOut.nBaud |
|
670 | ||
|
698 | ||
|
671 | 699 | if self.processingHeaderObj.nWindows != 0: |
|
672 | 700 | self.processingHeaderObj.firstHeight = self.dataOut.heightList[0] |
|
673 | 701 | self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0] |
|
674 | 702 | self.processingHeaderObj.nHeights = self.dataOut.nHeights |
|
675 | 703 | self.processingHeaderObj.samplesWin = self.dataOut.nHeights |
|
676 | ||
|
704 | ||
|
677 | 705 | self.processingHeaderObj.processFlags = self.getProcessFlags() |
|
678 | ||
|
706 | ||
|
679 | 707 | self.setBasicHeader() |
@@ -527,10 +527,16 class VoltageReader(JRODataReader, ProcessingUnit): | |||
|
527 | 527 | self.dataOut.flagNoData = False |
|
528 | 528 | |
|
529 | 529 | self.getBasicHeader() |
|
530 | ||
|
530 | ||
|
531 | #print self.basicHeaderObj.printInfo() | |
|
532 | #print self.systemHeaderObj.printInfo() | |
|
533 | #print self.radarControllerHeaderObj.printInfo() | |
|
534 | #print self.processingHeaderObj.printInfo() | |
|
535 | ||
|
531 | 536 | self.dataOut.realtime = self.online |
|
532 | 537 | |
|
533 | 538 | return self.dataOut.data |
|
539 | ||
|
534 | 540 | |
|
535 | 541 | class VoltageWriter(JRODataWriter, Operation): |
|
536 | 542 | """ |
@@ -11,4 +11,5 from jroproc_amisr import * | |||
|
11 | 11 | from jroproc_correlation import * |
|
12 | 12 | from jroproc_parameters import * |
|
13 | 13 | from jroproc_spectra_lags import * |
|
14 | from jroproc_spectra_acf import * No newline at end of file | |
|
14 | from jroproc_spectra_acf import * | |
|
15 | from bltrproc_parameters import * |
|
1 | NO CONTENT: modified file | |
The requested commit or file is too big and content was truncated. Show full diff |
@@ -902,3 +902,4 class IncohInt(Operation): | |||
|
902 | 902 | dataOut.nIncohInt *= self.n |
|
903 | 903 | dataOut.utctime = avgdatatime |
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904 | 904 | dataOut.flagNoData = False |
|
905 |
@@ -42,7 +42,7 setup(name="schainpy", | |||
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42 | 42 | scripts=['schainpy/gui/schainGUI'], |
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43 | 43 | ext_modules=[Extension("cSchain", ["schainpy/model/proc/extensions.c"], include_dirs=[numpy.get_include()])], |
|
44 | 44 | install_requires=[ |
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45 |
"scipy >= 0.1 |
|
|
45 | "scipy >= 0.13.0", | |
|
46 | 46 | "h5py >= 2.2.1", |
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47 | 47 | "matplotlib >= 1.4.2", |
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48 | 48 | "pyfits >= 3.4", |
|
1 | NO CONTENT: file was removed |
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