##// END OF EJS Templates
schain-jc
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15/08/2017
ebocanegra -
r1001:08c8d3a7a244
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@@ -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):
@@ -1199,7 +1201,7 class Parameters(Spectra):
1199 1201 time1 = self.utctimeInit - self.timeZone*60
1200 1202 else:
1201 1203 time1 = self.utctimeInit
1202
1204 print 'interval',interval
1203 1205 datatime.append(time1)
1204 1206 datatime.append(time1 + interval)
1205 1207 datatime = numpy.array(datatime)
@@ -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.")
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@@ -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 +657,14 class WindProfilerPlot(Figure):
446 657 # tmin = None
447 658 # tmax = None
448 659
449
450 x = dataOut.getTimeRange1(dataOut.outputInterval)
660 x = dataOut.getTimeRange1(dataOut.paramInterval)
451 661 y = dataOut.heightList
452 662 z = dataOut.data_output.copy()
663 print ' '
664 print 'Xvel',z[0]
665 print ' '
666 print 'Yvel',z[1]
667 print ' '
453 668 nplots = z.shape[0] #Number of wind dimensions estimated
454 669 nplotsw = nplots
455 670
@@ -559,7 +774,7 class WindProfilerPlot(Figure):
559 774 thisDatetime=thisDatetime,
560 775 update_figfile=update_figfile)
561 776
562 if dataOut.ltctime + dataOut.outputInterval >= self.xmax:
777 if dataOut.ltctime + dataOut.paramInterval >= self.xmax:
563 778 self.counter_imagwr = wr_period
564 779 self.isConfig = False
565 780 update_figfile = True
@@ -636,12 +851,12 class ParametersPlot(Figure):
636 851
637 852 counter += 1
638 853
639 def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap=True,
854 def run(self, dataOut, id, wintitle="", channelList=None, paramIndex = 0, colormap="jet",
640 855 xmin=None, xmax=None, ymin=None, ymax=None, zmin=None, zmax=None, timerange=None,
641 856 showSNR=False, SNRthresh = -numpy.inf, SNRmin=None, SNRmax=None,
642 857 save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
643 858 server=None, folder=None, username=None, password=None,
644 ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0):
859 ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, HEIGHT=None):
645 860 """
646 861
647 862 Input:
@@ -657,12 +872,11 class ParametersPlot(Figure):
657 872 zmin : None,
658 873 zmax : None
659 874 """
660
661 if colormap:
662 colormap="jet"
663 else:
664 colormap="RdBu_r"
665
875
876 if HEIGHT is not None:
877 self.HEIGHT = HEIGHT
878
879
666 880 if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
667 881 return
668 882
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@@ -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'
@@ -525,7 +522,7 class RTIPlot(Figure):
525 522 timerange=None, colormap='jet',
526 523 save=False, figpath='./', lastone=0,figfile=None, ftp=False, wr_period=1, show=True,
527 524 server=None, folder=None, username=None, password=None,
528 ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None):
525 ftp_wei=0, exp_code=0, sub_exp_code=0, plot_pos=0, normFactor=None, HEIGHT=None):
529 526
530 527 """
531 528
@@ -543,7 +540,10 class RTIPlot(Figure):
543 540 zmax : None
544 541 """
545 542
546 colormap = kwargs.get('colormap', 'jet')
543 #colormap = kwargs.get('colormap', 'jet')
544 if HEIGHT is not None:
545 self.HEIGHT = HEIGHT
546
547 547 if not isTimeInHourRange(dataOut.datatime, xmin, xmax):
548 548 return
549 549
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@@ -267,7 +267,6 def addpcolor(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap=
267 267 cmap.set_bad('white',1.)
268 268 ax.pcolormesh(x,y,z.T,vmin=zmin,vmax=zmax, cmap=matplotlib.pyplot.get_cmap(colormap))
269 269 ax.grid(True)
270 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
271 270
272 271 def addpcolorbuffer(ax, x, y, z, zmin, zmax, xlabel='', ylabel='', title='', colormap='jet'):
273 272
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@@ -1058,10 +1058,10 class JRODataReader(JRODataIO):
1058 1058
1059 1059 break
1060 1060
1061 if self.verbose:
1062 print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks,
1063 self.processingHeaderObj.dataBlocksPerFile,
1064 self.dataOut.datatime.ctime())
1061 # if self.verbose:
1062 # print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks,
1063 # self.processingHeaderObj.dataBlocksPerFile,
1064 # self.dataOut.datatime.ctime())
1065 1065 return 1
1066 1066
1067 1067 def __readFirstHeader(self):
@@ -1417,11 +1417,12 class JRODataReader(JRODataIO):
1417 1417 print "[Reading] Number of read blocks %04d" %self.nTotalBlocks
1418 1418
1419 1419 def printNumberOfBlock(self):
1420 'SPAM!'
1420 1421
1421 if self.flagIsNewBlock:
1422 print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks,
1423 self.processingHeaderObj.dataBlocksPerFile,
1424 self.dataOut.datatime.ctime())
1422 # if self.flagIsNewBlock:
1423 # print "[Reading] Block No. %d/%d -> %s" %(self.nReadBlocks,
1424 # self.processingHeaderObj.dataBlocksPerFile,
1425 # self.dataOut.datatime.ctime())
1425 1426
1426 1427 def printInfo(self):
1427 1428
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@@ -30,6 +30,7 from schainpy.model.proc.jroproc_base import ProcessingUnit, Operation
30 30 #from schainpy.model.io.jroIO_bltr import BLTRReader
31 31 from numpy import imag, shape, NaN
32 32
33 from jroIO_base import JRODataReader
33 34
34 35
35 36 class Header(object):
@@ -426,7 +427,7 class RecordHeaderBLTR(Header):
426 427 return 1
427 428
428 429
429 class BLTRReader (ProcessingUnit,FileHeaderBLTR,RecordHeaderBLTR):
430 class BLTRReader (ProcessingUnit, FileHeaderBLTR, RecordHeaderBLTR, JRODataReader):
430 431
431 432 path = None
432 433 startDate = None
@@ -450,10 +451,10 class BLTRReader (ProcessingUnit,FileHeaderBLTR,RecordHeaderBLTR):
450 451
451 452
452 453
453 def __init__(self):
454 def __init__(self, **kwargs):
454 455
455 456 #Eliminar de la base la herencia
456 ProcessingUnit.__init__(self)
457 ProcessingUnit.__init__(self, **kwargs)
457 458
458 459 # self.isConfig = False
459 460
@@ -541,7 +542,8 class BLTRReader (ProcessingUnit,FileHeaderBLTR,RecordHeaderBLTR):
541 542 timezone='utc',
542 543 code = None,
543 544 online=False,
544 ReadMode=None):
545 ReadMode=None,
546 **kwargs):
545 547
546 548 self.isConfig = True
547 549
@@ -717,8 +719,8 class BLTRReader (ProcessingUnit,FileHeaderBLTR,RecordHeaderBLTR):
717 719
718 720 self.data_block = numpy.transpose(self.data_block, (1,2,0))
719 721
720
721 spc = self.data_block.copy() * numpy.conjugate(self.data_block.copy())
722 copy = self.data_block.copy()
723 spc = copy * numpy.conjugate(copy)
722 724
723 725 self.data_spc = numpy.absolute(spc) # valor absoluto o magnitud
724 726
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@@ -416,7 +416,7 class RecordHeader(Header):
416 416 self.RadarConst = header['RadarConst'][0] #
417 417 #84
418 418
419 print 'Pointer fp RECheader', fp.tell()
419 #print 'Pointer fp RECheader', fp.tell()
420 420
421 421 #self.ipp= 0.5*(SPEED_OF_LIGHT/self.PRFhz)
422 422
@@ -456,10 +456,10 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
456 456
457 457
458 458
459 def __init__(self):
459 def __init__(self, **kwargs):
460 460
461 461 #Eliminar de la base la herencia
462 ProcessingUnit.__init__(self)
462 ProcessingUnit.__init__(self, **kwargs)
463 463 self.PointerReader = 0
464 464 self.FileHeaderFlag = False
465 465 self.utc = None
@@ -490,13 +490,14 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
490 490 self.dataOut.nRdPairs = 0
491 491 self.dataOut.pairsList = []
492 492 self.dataOut.data_spc=None
493 self.dataOut.noise=[]
493
494 494 self.dataOut.normFactor=1
495 495 self.nextfileflag = True
496 496 self.dataOut.RadarConst = 0
497 497 self.dataOut.HSDV = []
498 498 self.dataOut.NPW = []
499 499 self.dataOut.COFA = []
500 self.dataOut.noise = 0
500 501
501 502
502 503 def Files2Read(self, fp):
@@ -543,7 +544,7 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
543 544 timezone='utc',
544 545 code = None,
545 546 online=False,
546 ReadMode=None):
547 ReadMode=None, **kwargs):
547 548
548 549 self.isConfig = True
549 550
@@ -553,7 +554,7 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
553 554 self.startTime=startTime
554 555 self.endTime=endTime
555 556 self.walk=walk
556 self.ReadMode=int(ReadMode)
557 #self.ReadMode=int(ReadMode)
557 558
558 559 pass
559 560
@@ -576,9 +577,13 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
576 577 self.Files2Read(self.fp)
577 578 self.readFile(self.fp)
578 579
579 self.dataOut.data_spc = self.data_spc.copy()
580 self.dataOut.data_spc = self.dataOut_spc#self.data_spc.copy()
580 581 self.dataOut.RadarConst = self.RadarConst
581 582 self.dataOut.data_output=self.data_output
583 self.dataOut.noise = self.dataOut.getNoise()
584 #print 'ACAAAAAA', self.dataOut.noise
585 self.dataOut.data_spc = self.dataOut.data_spc+self.dataOut.noise
586 #print 'self.dataOut.noise',self.dataOut.noise
582 587
583 588
584 589 return self.dataOut.data_spc
@@ -629,7 +634,7 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
629 634 pulse_width = self.fheader.PPARpdr * 10**-9
630 635 self.__deltaHeigth = 0.5 * SPEED_OF_LIGHT * pulse_width
631 636
632 self.data_spc = numpy.zeros((self.Num_Hei, self.Num_Bins,2))
637 self.data_spc = numpy.zeros((self.Num_Hei, self.Num_Bins,2))#
633 638 self.dataOut.HSDV = numpy.zeros((self.Num_Hei, 2))
634 639
635 640 self.Ze = numpy.zeros(self.Num_Hei)
@@ -693,7 +698,7 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
693 698 npw2 = self.recordheader.npw2
694 699
695 700
696 self.dataOut.channelList = range(2)
701 self.dataOut.channelList = range(1)
697 702 self.dataOut.nIncohInt = self.Num_inCoh
698 703 self.dataOut.nProfiles = self.Num_Bins
699 704 self.dataOut.nCohInt = 1
@@ -756,7 +761,6 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
756 761
757 762 self.dataOut.COFA = numpy.array([self.COFA_Co , self.COFA_Cx])
758 763
759
760 764 print ' '
761 765 print 'SPC',numpy.shape(self.dataOut.data_spc)
762 766 #print 'SPC',self.dataOut.data_spc
@@ -764,20 +768,26 class MIRA35CReader (ProcessingUnit,FileHeaderMIRA35c,SRVIHeader,RecordHeader):
764 768 noinor1 = 713031680
765 769 noinor2 = 30
766 770
767 #print 'npw1 db' , npw1
768
769 npw1 = 10**(npw1/10) * noinor1 * noinor2
770 npw2 = 10**(npw2/10) * noinor1 * noinor2
771 npw1 = 1#0**(npw1/10) * noinor1 * noinor2
772 npw2 = 1#0**(npw2/10) * noinor1 * noinor2
771 773 self.dataOut.NPW = numpy.array([npw1, npw2])
772 774
773
774 775 print ' '
775 #print numpy.__version__
776
776 777 self.data_spc = numpy.transpose(self.data_spc, (2,1,0))
777 778 self.data_spc = numpy.fft.fftshift(self.data_spc, axes = 1)
778 779
779 780 self.data_spc = numpy.fliplr(self.data_spc)
780 781
782 self.data_spc = numpy.where(self.data_spc > 0. , self.data_spc, 0)
783 self.dataOut_spc= numpy.ones([1, self.Num_Bins , self.Num_Hei])
784 self.dataOut_spc[0,:,:] = self.data_spc[0,:,:]
785 #print 'SHAPE', self.dataOut_spc.shape
786 #For nyquist correction:
787 #fix = 20 # ~3m/s
788 #shift = self.Num_Bins/2 + fix
789 #self.data_spc = numpy.array([ self.data_spc[: , self.Num_Bins-shift+1: , :] , self.data_spc[: , 0:self.Num_Bins-shift , :]])
790
781 791
782 792
783 793 '''Block Reading, the Block Data is received and Reshape is used to give it
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1 NO CONTENT: modified file, binary diff hidden
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@@ -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 print
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
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This diff has been collapsed as it changes many lines, (568 lines changed) Show them Hide them
@@ -11,22 +11,17 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 <<<<<<< HEAD
14
15 15 """
16 16 Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura
17 17 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones)
18 =======
19 """
20 Esta clase permite leer datos de espectros desde archivos procesados (.pdata). La lectura
21 de los datos siempre se realiza por bloques. Los datos leidos (array de 3 dimensiones)
22 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
23 18 son almacenados en tres buffer's para el Self Spectra, el Cross Spectra y el DC Channel.
24 19
25 20 paresCanalesIguales * alturas * perfiles (Self Spectra)
26 21 paresCanalesDiferentes * alturas * perfiles (Cross Spectra)
27 22 canales * alturas (DC Channels)
28 23
29 <<<<<<< HEAD
24
30 25 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
31 26 RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la
32 27 cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de
@@ -81,168 +76,25 class SpectraReader(JRODataReader, ProcessingUnit):
81 76 Inicializador de la clase SpectraReader para la lectura de datos de espectros.
82 77
83 78 Inputs:
84 =======
85 Esta clase contiene instancias (objetos) de las clases BasicHeader, SystemHeader,
86 RadarControllerHeader y Spectra. Los tres primeros se usan para almacenar informacion de la
87 cabecera de datos (metadata), y el cuarto (Spectra) para obtener y almacenar un bloque de
88 datos desde el "buffer" cada vez que se ejecute el metodo "getData".
89
90 Example:
91 dpath = "/home/myuser/data"
92
93 startTime = datetime.datetime(2010,1,20,0,0,0,0,0,0)
94
95 endTime = datetime.datetime(2010,1,21,23,59,59,0,0,0)
96
97 readerObj = SpectraReader()
98
99 readerObj.setup(dpath, startTime, endTime)
100
101 while(True):
102
103 readerObj.getData()
104
105 print readerObj.data_spc
106
107 print readerObj.data_cspc
108
109 print readerObj.data_dc
110
111 if readerObj.flagNoMoreFiles:
112 break
113
114 """
115
116 pts2read_SelfSpectra = 0
117
118 pts2read_CrossSpectra = 0
119
120 pts2read_DCchannels = 0
121
122 ext = ".pdata"
123
124 optchar = "P"
125
126 dataOut = None
127
128 nRdChannels = None
129
130 nRdPairs = None
131
132 rdPairList = []
133
134 def __init__(self):
135 """
136 Inicializador de la clase SpectraReader para la lectura de datos de espectros.
137 79
138 Inputs:
139 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
140 80 dataOut : Objeto de la clase Spectra. Este objeto sera utilizado para
141 81 almacenar un perfil de datos cada vez que se haga un requerimiento
142 82 (getData). El perfil sera obtenido a partir del buffer de datos,
143 83 si el buffer esta vacio se hara un nuevo proceso de lectura de un
144 84 bloque de datos.
145 85 Si este parametro no es pasado se creara uno internamente.
146 <<<<<<< HEAD
147 86
148 Affected:
149 =======
150 87
151 88 Affected:
152 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
89
153 90 self.dataOut
154 91
155 92 Return : None
156 93 """
157 <<<<<<< HEAD
158
159 #Eliminar de la base la herencia
160 ProcessingUnit.__init__(self, **kwargs)
161
162 # self.isConfig = False
163
164 self.pts2read_SelfSpectra = 0
165
166 self.pts2read_CrossSpectra = 0
167
168 self.pts2read_DCchannels = 0
169
170 self.datablock = None
171
172 self.utc = None
173
174 self.ext = ".pdata"
175
176 self.optchar = "P"
177
178 self.basicHeaderObj = BasicHeader(LOCALTIME)
179
180 self.systemHeaderObj = SystemHeader()
181
182 self.radarControllerHeaderObj = RadarControllerHeader()
183
184 self.processingHeaderObj = ProcessingHeader()
185
186 self.online = 0
187
188 self.fp = None
189
190 self.idFile = None
191
192 self.dtype = None
193
194 self.fileSizeByHeader = None
195
196 self.filenameList = []
197
198 self.filename = None
199
200 self.fileSize = None
201
202 self.firstHeaderSize = 0
203
204 self.basicHeaderSize = 24
205
206 self.pathList = []
207
208 self.lastUTTime = 0
209
210 self.maxTimeStep = 30
211
212 self.flagNoMoreFiles = 0
213
214 self.set = 0
215
216 self.path = None
217
218 self.delay = 60 #seconds
219
220 self.nTries = 3 #quantity tries
221
222 self.nFiles = 3 #number of files for searching
223
224 self.nReadBlocks = 0
225
226 self.flagIsNewFile = 1
227
228 self.__isFirstTimeOnline = 1
229
230 # self.ippSeconds = 0
231
232 self.flagDiscontinuousBlock = 0
233
234 self.flagIsNewBlock = 0
235 94
236 self.nTotalBlocks = 0
237
238 self.blocksize = 0
239
240 self.dataOut = self.createObjByDefault()
241
242 =======
243 95
244 96 #Eliminar de la base la herencia
245 ProcessingUnit.__init__(self)
97 ProcessingUnit.__init__(self, **kwargs)
246 98
247 99 # self.isConfig = False
248 100
@@ -324,24 +176,15 class SpectraReader(JRODataReader, ProcessingUnit):
324 176
325 177 self.dataOut = self.createObjByDefault()
326 178
327 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
328 179 self.profileIndex = 1 #Always
329 180
330 181
331 182 def createObjByDefault(self):
332 <<<<<<< HEAD
333
334 dataObj = Spectra()
335
336 return dataObj
337
338 =======
339 183
340 184 dataObj = Spectra()
341 185
342 186 return dataObj
343 187
344 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
345 188 def __hasNotDataInBuffer(self):
346 189 return 1
347 190
@@ -349,11 +192,7 class SpectraReader(JRODataReader, ProcessingUnit):
349 192 def getBlockDimension(self):
350 193 """
351 194 Obtiene la cantidad de puntos a leer por cada bloque de datos
352 <<<<<<< HEAD
353
354 =======
355 195
356 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
357 196 Affected:
358 197 self.nRdChannels
359 198 self.nRdPairs
@@ -370,40 +209,16 class SpectraReader(JRODataReader, ProcessingUnit):
370 209 self.nRdChannels = 0
371 210 self.nRdPairs = 0
372 211 self.rdPairList = []
373 <<<<<<< HEAD
374 212
375 213 for i in range(0, self.processingHeaderObj.totalSpectra*2, 2):
376 214 if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]:
377 self.nRdChannels = self.nRdChannels + 1 #par de canales iguales
378 =======
379
380
381 for i in range(0, self.processingHeaderObj.totalSpectra*2, 2):
382 if self.processingHeaderObj.spectraComb[i] == self.processingHeaderObj.spectraComb[i+1]:
383 215 self.nRdChannels = self.nRdChannels + 1 #par de canales iguales
384 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
216
385 217 else:
386 218 self.nRdPairs = self.nRdPairs + 1 #par de canales diferentes
387 219 self.rdPairList.append((self.processingHeaderObj.spectraComb[i], self.processingHeaderObj.spectraComb[i+1]))
388 220
389 221 pts2read = self.processingHeaderObj.nHeights * self.processingHeaderObj.profilesPerBlock
390 <<<<<<< HEAD
391
392 self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read)
393 self.blocksize = self.pts2read_SelfSpectra
394
395 if self.processingHeaderObj.flag_cspc:
396 self.pts2read_CrossSpectra = int(self.nRdPairs * pts2read)
397 self.blocksize += self.pts2read_CrossSpectra
398
399 if self.processingHeaderObj.flag_dc:
400 self.pts2read_DCchannels = int(self.systemHeaderObj.nChannels * self.processingHeaderObj.nHeights)
401 self.blocksize += self.pts2read_DCchannels
402
403 # self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels
404
405
406 =======
407 222
408 223 self.pts2read_SelfSpectra = int(self.nRdChannels * pts2read)
409 224 self.blocksize = self.pts2read_SelfSpectra
@@ -419,26 +234,18 class SpectraReader(JRODataReader, ProcessingUnit):
419 234 # self.blocksize = self.pts2read_SelfSpectra + self.pts2read_CrossSpectra + self.pts2read_DCchannels
420 235
421 236
422 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
423 237 def readBlock(self):
424 238 """
425 239 Lee el bloque de datos desde la posicion actual del puntero del archivo
426 240 (self.fp) y actualiza todos los parametros relacionados al bloque de datos
427 241 (metadata + data). La data leida es almacenada en el buffer y el contador del buffer
428 242 es seteado a 0
429 <<<<<<< HEAD
430
431 Return: None
432
433 Variables afectadas:
434
435 =======
436 243
437 244 Return: None
438 245
439 246 Variables afectadas:
440 247
441 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
248
442 249 self.flagIsNewFile
443 250 self.flagIsNewBlock
444 251 self.nTotalBlocks
@@ -446,11 +253,6 class SpectraReader(JRODataReader, ProcessingUnit):
446 253 self.data_cspc
447 254 self.data_dc
448 255
449 <<<<<<< HEAD
450 Exceptions:
451 Si un bloque leido no es un bloque valido
452 """
453 =======
454 256 Exceptions:
455 257 Si un bloque leido no es un bloque valido
456 258 """
@@ -463,25 +265,13 class SpectraReader(JRODataReader, ProcessingUnit):
463 265 print ' '
464 266 print ' ======================================================== '
465 267
466 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
268
467 269 blockOk_flag = False
468 270 fpointer = self.fp.tell()
469 271
470 272 spc = numpy.fromfile( self.fp, self.dtype[0], self.pts2read_SelfSpectra )
471 273 spc = spc.reshape( (self.nRdChannels, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
472 <<<<<<< HEAD
473
474 if self.processingHeaderObj.flag_cspc:
475 cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra )
476 cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
477
478 if self.processingHeaderObj.flag_dc:
479 dc = numpy.fromfile( self.fp, self.dtype, self.pts2read_DCchannels ) #int(self.processingHeaderObj.nHeights*self.systemHeaderObj.nChannels) )
480 dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D
481
482 274
483 =======
484
485 275 if self.processingHeaderObj.flag_cspc:
486 276 cspc = numpy.fromfile( self.fp, self.dtype, self.pts2read_CrossSpectra )
487 277 cspc = cspc.reshape( (self.nRdPairs, self.processingHeaderObj.nHeights, self.processingHeaderObj.profilesPerBlock) ) #transforma a un arreglo 3D
@@ -491,23 +281,10 class SpectraReader(JRODataReader, ProcessingUnit):
491 281 dc = dc.reshape( (self.systemHeaderObj.nChannels, self.processingHeaderObj.nHeights) ) #transforma a un arreglo 2D
492 282
493 283
494 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
495 284 if not(self.processingHeaderObj.shif_fft):
496 285 #desplaza a la derecha en el eje 2 determinadas posiciones
497 286 shift = int(self.processingHeaderObj.profilesPerBlock/2)
498 287 spc = numpy.roll( spc, shift , axis=2 )
499 <<<<<<< HEAD
500
501 if self.processingHeaderObj.flag_cspc:
502 #desplaza a la derecha en el eje 2 determinadas posiciones
503 cspc = numpy.roll( cspc, shift, axis=2 )
504
505 #Dimensions : nChannels, nProfiles, nSamples
506 spc = numpy.transpose( spc, (0,2,1) )
507 self.data_spc = spc
508
509 if self.processingHeaderObj.flag_cspc:
510 =======
511 288
512 289 if self.processingHeaderObj.flag_cspc:
513 290 #desplaza a la derecha en el eje 2 determinadas posiciones
@@ -518,16 +295,13 class SpectraReader(JRODataReader, ProcessingUnit):
518 295 self.data_spc = spc
519 296
520 297 if self.processingHeaderObj.flag_cspc:
521 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
298
522 299 cspc = numpy.transpose( cspc, (0,2,1) )
523 300 self.data_cspc = cspc['real'] + cspc['imag']*1j
524 301 else:
525 302 self.data_cspc = None
526 <<<<<<< HEAD
527
528 =======
529 303
530 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
304
531 305 if self.processingHeaderObj.flag_dc:
532 306 self.data_dc = dc['real'] + dc['imag']*1j
533 307 else:
@@ -540,62 +314,6 class SpectraReader(JRODataReader, ProcessingUnit):
540 314 self.nReadBlocks += 1
541 315
542 316 return 1
543 <<<<<<< HEAD
544
545 def getFirstHeader(self):
546
547 self.getBasicHeader()
548
549 self.dataOut.systemHeaderObj = self.systemHeaderObj.copy()
550
551 self.dataOut.radarControllerHeaderObj = self.radarControllerHeaderObj.copy()
552
553 # self.dataOut.ippSeconds = self.ippSeconds
554
555 # self.dataOut.timeInterval = self.radarControllerHeaderObj.ippSeconds * self.processingHeaderObj.nCohInt * self.processingHeaderObj.nIncohInt * self.processingHeaderObj.profilesPerBlock
556
557 self.dataOut.dtype = self.dtype
558
559 # self.dataOut.nPairs = self.nPairs
560
561 self.dataOut.pairsList = self.rdPairList
562
563 self.dataOut.nProfiles = self.processingHeaderObj.profilesPerBlock
564
565 self.dataOut.nFFTPoints = self.processingHeaderObj.profilesPerBlock
566
567 self.dataOut.nCohInt = self.processingHeaderObj.nCohInt
568
569 self.dataOut.nIncohInt = self.processingHeaderObj.nIncohInt
570
571 xf = self.processingHeaderObj.firstHeight + self.processingHeaderObj.nHeights*self.processingHeaderObj.deltaHeight
572
573 self.dataOut.heightList = numpy.arange(self.processingHeaderObj.firstHeight, xf, self.processingHeaderObj.deltaHeight)
574
575 self.dataOut.channelList = range(self.systemHeaderObj.nChannels)
576
577 self.dataOut.flagShiftFFT = True #Data is always shifted
578
579 self.dataOut.flagDecodeData = self.processingHeaderObj.flag_decode #asumo q la data no esta decodificada
580
581 self.dataOut.flagDeflipData = self.processingHeaderObj.flag_deflip #asumo q la data esta sin flip
582
583 def getData(self):
584 """
585 First method to execute before "RUN" is called.
586
587 Copia el buffer de lectura a la clase "Spectra",
588 con todos los parametros asociados a este (metadata). cuando no hay datos en el buffer de
589 lectura es necesario hacer una nueva lectura de los bloques de datos usando "readNextBlock"
590
591 Return:
592 0 : Si no hay mas archivos disponibles
593 1 : Si hizo una buena copia del buffer
594
595 Affected:
596 self.dataOut
597
598 =======
599 317
600 318 def getFirstHeader(self):
601 319
@@ -650,7 +368,6 class SpectraReader(JRODataReader, ProcessingUnit):
650 368 Affected:
651 369 self.dataOut
652 370
653 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
654 371 self.flagDiscontinuousBlock
655 372 self.flagIsNewBlock
656 373 """
@@ -659,82 +376,22 class SpectraReader(JRODataReader, ProcessingUnit):
659 376 self.dataOut.flagNoData = True
660 377 print 'Process finished'
661 378 return 0
662 <<<<<<< HEAD
663
664 self.flagDiscontinuousBlock = 0
665 self.flagIsNewBlock = 0
666
667 if self.__hasNotDataInBuffer():
668 =======
669 379
670 380 self.flagDiscontinuousBlock = 0
671 381 self.flagIsNewBlock = 0
672 382
673 383 if self.__hasNotDataInBuffer():
674 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
675 384
676 385 if not( self.readNextBlock() ):
677 386 self.dataOut.flagNoData = True
678 387 return 0
679 <<<<<<< HEAD
680
681 =======
682 388
683 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
389
684 390 #data es un numpy array de 3 dmensiones (perfiles, alturas y canales)
685 391
686 392 if self.data_spc is None:
687 393 self.dataOut.flagNoData = True
688 394 return 0
689 <<<<<<< HEAD
690
691 self.getBasicHeader()
692
693 self.getFirstHeader()
694
695 self.dataOut.data_spc = self.data_spc
696
697 self.dataOut.data_cspc = self.data_cspc
698
699 self.dataOut.data_dc = self.data_dc
700
701 self.dataOut.flagNoData = False
702
703 self.dataOut.realtime = self.online
704
705 return self.dataOut.data_spc
706
707 class SpectraWriter(JRODataWriter, Operation):
708
709 """
710 Esta clase permite escribir datos de espectros a archivos procesados (.pdata). La escritura
711 de los datos siempre se realiza por bloques.
712 """
713
714 ext = ".pdata"
715
716 optchar = "P"
717
718 shape_spc_Buffer = None
719
720 shape_cspc_Buffer = None
721
722 shape_dc_Buffer = None
723
724 data_spc = None
725
726 data_cspc = None
727
728 data_dc = None
729
730 # dataOut = None
731
732 def __init__(self, **kwargs):
733 """
734 Inicializador de la clase SpectraWriter para la escritura de datos de espectros.
735
736 Affected:
737 =======
738 395
739 396 self.getBasicHeader()
740 397
@@ -782,7 +439,7 class SpectraWriter(JRODataWriter, Operation):
782 439 Inicializador de la clase SpectraWriter para la escritura de datos de espectros.
783 440
784 441 Affected:
785 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
442
786 443 self.dataOut
787 444 self.basicHeaderObj
788 445 self.systemHeaderObj
@@ -791,19 +448,6 class SpectraWriter(JRODataWriter, Operation):
791 448
792 449 Return: None
793 450 """
794 <<<<<<< HEAD
795
796 Operation.__init__(self, **kwargs)
797
798 self.isConfig = False
799
800 self.nTotalBlocks = 0
801
802 self.data_spc = None
803
804 self.data_cspc = None
805
806 =======
807 451
808 452 Operation.__init__(self)
809 453
@@ -815,42 +459,12 class SpectraWriter(JRODataWriter, Operation):
815 459
816 460 self.data_cspc = None
817 461
818 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
462
819 463 self.data_dc = None
820 464
821 465 self.fp = None
822 466
823 467 self.flagIsNewFile = 1
824 <<<<<<< HEAD
825
826 self.nTotalBlocks = 0
827
828 self.flagIsNewBlock = 0
829
830 self.setFile = None
831
832 self.dtype = None
833
834 self.path = None
835
836 self.noMoreFiles = 0
837
838 self.filename = None
839
840 self.basicHeaderObj = BasicHeader(LOCALTIME)
841
842 self.systemHeaderObj = SystemHeader()
843
844 self.radarControllerHeaderObj = RadarControllerHeader()
845
846 self.processingHeaderObj = ProcessingHeader()
847
848
849 def hasAllDataInBuffer(self):
850 return 1
851
852
853 =======
854 468
855 469 self.nTotalBlocks = 0
856 470
@@ -879,7 +493,7 class SpectraWriter(JRODataWriter, Operation):
879 493 return 1
880 494
881 495
882 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
496
883 497 def setBlockDimension(self):
884 498 """
885 499 Obtiene las formas dimensionales del los subbloques de datos que componen un bloque
@@ -898,17 +512,6 class SpectraWriter(JRODataWriter, Operation):
898 512 self.shape_cspc_Buffer = (self.dataOut.nPairs,
899 513 self.processingHeaderObj.nHeights,
900 514 self.processingHeaderObj.profilesPerBlock)
901 <<<<<<< HEAD
902
903 self.shape_dc_Buffer = (self.dataOut.nChannels,
904 self.processingHeaderObj.nHeights)
905
906
907 def writeBlock(self):
908 """
909 Escribe el buffer en el file designado
910
911 =======
912 515
913 516 self.shape_dc_Buffer = (self.dataOut.nChannels,
914 517 self.processingHeaderObj.nHeights)
@@ -918,7 +521,7 class SpectraWriter(JRODataWriter, Operation):
918 521 """
919 522 Escribe el buffer en el file designado
920 523
921 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
524
922 525 Affected:
923 526 self.data_spc
924 527 self.data_cspc
@@ -926,19 +529,11 class SpectraWriter(JRODataWriter, Operation):
926 529 self.flagIsNewFile
927 530 self.flagIsNewBlock
928 531 self.nTotalBlocks
929 <<<<<<< HEAD
930 self.nWriteBlocks
931
932 Return: None
933 """
934
935 =======
936 532 self.nWriteBlocks
937 533
938 534 Return: None
939 535 """
940 536
941 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
942 537 spc = numpy.transpose( self.data_spc, (0,2,1) )
943 538 if not( self.processingHeaderObj.shif_fft ):
944 539 spc = numpy.roll( spc, self.processingHeaderObj.profilesPerBlock/2, axis=2 ) #desplaza a la derecha en el eje 2 determinadas posiciones
@@ -955,11 +550,8 class SpectraWriter(JRODataWriter, Operation):
955 550 data['imag'] = cspc.imag
956 551 data = data.reshape((-1))
957 552 data.tofile(self.fp)
958 <<<<<<< HEAD
959
960 =======
961 553
962 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
554
963 555 if self.data_dc is not None:
964 556 data = numpy.zeros( self.shape_dc_Buffer, self.dtype )
965 557 dc = self.data_dc
@@ -969,15 +561,6 class SpectraWriter(JRODataWriter, Operation):
969 561 data.tofile(self.fp)
970 562
971 563 # self.data_spc.fill(0)
972 <<<<<<< HEAD
973 #
974 # if self.data_dc is not None:
975 # self.data_dc.fill(0)
976 #
977 # if self.data_cspc is not None:
978 # self.data_cspc.fill(0)
979
980 =======
981 564 #
982 565 # if self.data_dc is not None:
983 566 # self.data_dc.fill(0)
@@ -985,21 +568,12 class SpectraWriter(JRODataWriter, Operation):
985 568 # if self.data_cspc is not None:
986 569 # self.data_cspc.fill(0)
987 570
988 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
571
989 572 self.flagIsNewFile = 0
990 573 self.flagIsNewBlock = 1
991 574 self.nTotalBlocks += 1
992 575 self.nWriteBlocks += 1
993 576 self.blockIndex += 1
994 <<<<<<< HEAD
995
996 # print "[Writing] Block = %d04" %self.blockIndex
997
998 def putData(self):
999 """
1000 Setea un bloque de datos y luego los escribe en un file
1001
1002 =======
1003 577
1004 578 # print "[Writing] Block = %d04" %self.blockIndex
1005 579
@@ -1007,43 +581,12 class SpectraWriter(JRODataWriter, Operation):
1007 581 """
1008 582 Setea un bloque de datos y luego los escribe en un file
1009 583
1010 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
584
1011 585 Affected:
1012 586 self.data_spc
1013 587 self.data_cspc
1014 588 self.data_dc
1015 589
1016 <<<<<<< HEAD
1017 Return:
1018 0 : Si no hay data o no hay mas files que puedan escribirse
1019 1 : Si se escribio la data de un bloque en un file
1020 """
1021
1022 if self.dataOut.flagNoData:
1023 return 0
1024
1025 self.flagIsNewBlock = 0
1026
1027 if self.dataOut.flagDiscontinuousBlock:
1028 self.data_spc.fill(0)
1029 if self.dataOut.data_cspc is not None:
1030 self.data_cspc.fill(0)
1031 if self.dataOut.data_dc is not None:
1032 self.data_dc.fill(0)
1033 self.setNextFile()
1034
1035 if self.flagIsNewFile == 0:
1036 self.setBasicHeader()
1037
1038 self.data_spc = self.dataOut.data_spc.copy()
1039
1040 if self.dataOut.data_cspc is not None:
1041 self.data_cspc = self.dataOut.data_cspc.copy()
1042
1043 if self.dataOut.data_dc is not None:
1044 self.data_dc = self.dataOut.data_dc.copy()
1045
1046 =======
1047 590 Return:
1048 591 0 : Si no hay data o no hay mas files que puedan escribirse
1049 592 1 : Si se escribio la data de un bloque en un file
@@ -1071,51 +614,18 class SpectraWriter(JRODataWriter, Operation):
1071 614 if self.dataOut.data_dc is not None:
1072 615 self.data_dc = self.dataOut.data_dc.copy()
1073 616
1074 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1075 617 # #self.processingHeaderObj.dataBlocksPerFile)
1076 618 if self.hasAllDataInBuffer():
1077 619 # self.setFirstHeader()
1078 620 self.writeNextBlock()
1079 <<<<<<< HEAD
1080
1081 return 1
1082
1083 =======
1084 621
1085 622 return 1
1086 623
1087 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
624
1088 625 def __getBlockSize(self):
1089 626 '''
1090 627 Este metodos determina el cantidad de bytes para un bloque de datos de tipo Spectra
1091 628 '''
1092 <<<<<<< HEAD
1093
1094 dtype_width = self.getDtypeWidth()
1095
1096 pts2write = self.dataOut.nHeights * self.dataOut.nFFTPoints
1097
1098 pts2write_SelfSpectra = int(self.dataOut.nChannels * pts2write)
1099 blocksize = (pts2write_SelfSpectra*dtype_width)
1100
1101 if self.dataOut.data_cspc is not None:
1102 pts2write_CrossSpectra = int(self.dataOut.nPairs * pts2write)
1103 blocksize += (pts2write_CrossSpectra*dtype_width*2)
1104
1105 if self.dataOut.data_dc is not None:
1106 pts2write_DCchannels = int(self.dataOut.nChannels * self.dataOut.nHeights)
1107 blocksize += (pts2write_DCchannels*dtype_width*2)
1108
1109 # blocksize = blocksize #* datatypeValue * 2 #CORREGIR ESTO
1110
1111 return blocksize
1112
1113 def setFirstHeader(self):
1114
1115 """
1116 Obtiene una copia del First Header
1117
1118 =======
1119 629
1120 630 dtype_width = self.getDtypeWidth()
1121 631
@@ -1141,22 +651,11 class SpectraWriter(JRODataWriter, Operation):
1141 651 """
1142 652 Obtiene una copia del First Header
1143 653
1144 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1145 654 Affected:
1146 655 self.systemHeaderObj
1147 656 self.radarControllerHeaderObj
1148 657 self.dtype
1149 658
1150 <<<<<<< HEAD
1151 Return:
1152 None
1153 """
1154
1155 self.systemHeaderObj = self.dataOut.systemHeaderObj.copy()
1156 self.systemHeaderObj.nChannels = self.dataOut.nChannels
1157 self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
1158
1159 =======
1160 659 Return:
1161 660 None
1162 661 """
@@ -1165,73 +664,44 class SpectraWriter(JRODataWriter, Operation):
1165 664 self.systemHeaderObj.nChannels = self.dataOut.nChannels
1166 665 self.radarControllerHeaderObj = self.dataOut.radarControllerHeaderObj.copy()
1167 666
1168 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1169 667 self.processingHeaderObj.dtype = 1 # Spectra
1170 668 self.processingHeaderObj.blockSize = self.__getBlockSize()
1171 669 self.processingHeaderObj.profilesPerBlock = self.dataOut.nFFTPoints
1172 670 self.processingHeaderObj.dataBlocksPerFile = self.blocksPerFile
1173 671 self.processingHeaderObj.nWindows = 1 #podria ser 1 o self.dataOut.processingHeaderObj.nWindows
1174 672 self.processingHeaderObj.nCohInt = self.dataOut.nCohInt# Se requiere para determinar el valor de timeInterval
1175 <<<<<<< HEAD
1176 self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt
1177 self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels
1178 self.processingHeaderObj.shif_fft = self.dataOut.flagShiftFFT
1179
1180 =======
1181 673 self.processingHeaderObj.nIncohInt = self.dataOut.nIncohInt
1182 674 self.processingHeaderObj.totalSpectra = self.dataOut.nPairs + self.dataOut.nChannels
1183 675 self.processingHeaderObj.shif_fft = self.dataOut.flagShiftFFT
1184 676
1185 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
677
1186 678 if self.processingHeaderObj.totalSpectra > 0:
1187 679 channelList = []
1188 680 for channel in range(self.dataOut.nChannels):
1189 681 channelList.append(channel)
1190 682 channelList.append(channel)
1191 <<<<<<< HEAD
1192
1193 =======
1194 683
1195 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1196 684 pairsList = []
1197 685 if self.dataOut.nPairs > 0:
1198 686 for pair in self.dataOut.pairsList:
1199 687 pairsList.append(pair[0])
1200 688 pairsList.append(pair[1])
1201 <<<<<<< HEAD
1202
1203 spectraComb = channelList + pairsList
1204 spectraComb = numpy.array(spectraComb, dtype="u1")
1205 self.processingHeaderObj.spectraComb = spectraComb
1206
1207 =======
1208 689
1209 690 spectraComb = channelList + pairsList
1210 691 spectraComb = numpy.array(spectraComb, dtype="u1")
1211 692 self.processingHeaderObj.spectraComb = spectraComb
1212 693
1213 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1214 694 if self.dataOut.code is not None:
1215 695 self.processingHeaderObj.code = self.dataOut.code
1216 696 self.processingHeaderObj.nCode = self.dataOut.nCode
1217 697 self.processingHeaderObj.nBaud = self.dataOut.nBaud
1218 <<<<<<< HEAD
1219
1220 =======
1221 698
1222 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1223 699 if self.processingHeaderObj.nWindows != 0:
1224 700 self.processingHeaderObj.firstHeight = self.dataOut.heightList[0]
1225 701 self.processingHeaderObj.deltaHeight = self.dataOut.heightList[1] - self.dataOut.heightList[0]
1226 702 self.processingHeaderObj.nHeights = self.dataOut.nHeights
1227 703 self.processingHeaderObj.samplesWin = self.dataOut.nHeights
1228 <<<<<<< HEAD
1229
1230 self.processingHeaderObj.processFlags = self.getProcessFlags()
1231
1232 =======
1233 704
1234 705 self.processingHeaderObj.processFlags = self.getProcessFlags()
1235 706
1236 >>>>>>> 08c4507d6c3c48f6c52326d5dedfa1972fb26356
1237 707 self.setBasicHeader()
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@@ -427,10 +427,16 class VoltageReader(JRODataReader, ProcessingUnit):
427 427 self.dataOut.flagNoData = False
428 428
429 429 self.getBasicHeader()
430
430
431 #print self.basicHeaderObj.printInfo()
432 #print self.systemHeaderObj.printInfo()
433 #print self.radarControllerHeaderObj.printInfo()
434 #print self.processingHeaderObj.printInfo()
435
431 436 self.dataOut.realtime = self.online
432 437
433 438 return self.dataOut.data
439
434 440
435 441 class VoltageWriter(JRODataWriter, Operation):
436 442 """
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This diff has been collapsed as it changes many lines, (965 lines changed) Show them Hide them
@@ -1,20 +1,62
1 1 import numpy
2 2 import math
3 3 from scipy import optimize, interpolate, signal, stats, ndimage
4 import scipy
4 5 import re
5 6 import datetime
6 7 import copy
7 8 import sys
8 9 import importlib
9 10 import itertools
11 from multiprocessing import Pool, TimeoutError
12 from multiprocessing.pool import ThreadPool
13 import copy_reg
14 import cPickle
15 import types
16 from functools import partial
17 import time
18 #from sklearn.cluster import KMeans
10 19
20 import matplotlib.pyplot as plt
21
22 from scipy.optimize import fmin_l_bfgs_b #optimize with bounds on state papameters
11 23 from jroproc_base import ProcessingUnit, Operation
12 24 from schainpy.model.data.jrodata import Parameters, hildebrand_sekhon
13 25 from scipy import asarray as ar,exp
14 26 from scipy.optimize import curve_fit
15 27
28 import warnings
29 from numpy import NaN
30 warnings.filterwarnings('ignore')
31
16 32 SPEED_OF_LIGHT = 299792458
17 33
34
35 '''solving pickling issue'''
36
37 def _pickle_method(method):
38 func_name = method.im_func.__name__
39 obj = method.im_self
40 cls = method.im_class
41 return _unpickle_method, (func_name, obj, cls)
42
43 def _unpickle_method(func_name, obj, cls):
44 for cls in cls.mro():
45 try:
46 func = cls.__dict__[func_name]
47 except KeyError:
48 pass
49 else:
50 break
51 return func.__get__(obj, cls)
52
53
54
55
56
57
58
59
18 60 class ParametersProc(ProcessingUnit):
19 61
20 62 nSeconds = None
@@ -57,11 +99,13 class ParametersProc(ProcessingUnit):
57 99 # self.dataOut.nIncohInt = 1
58 100 self.dataOut.ippSeconds = self.dataIn.ippSeconds
59 101 # self.dataOut.windowOfFilter = self.dataIn.windowOfFilter
60 self.dataOut.timeInterval = self.dataIn.timeInterval
102 self.dataOut.timeInterval1 = self.dataIn.timeInterval
61 103 self.dataOut.heightList = self.dataIn.getHeiRange()
62 104 self.dataOut.frequency = self.dataIn.frequency
63 105 self.dataOut.noise = self.dataIn.noise
64 106
107
108
65 109 def run(self):
66 110
67 111 #---------------------- Voltage Data ---------------------------
@@ -80,18 +124,25 class ParametersProc(ProcessingUnit):
80 124 if self.dataIn.type == "Spectra":
81 125
82 126 self.dataOut.data_pre = (self.dataIn.data_spc,self.dataIn.data_cspc)
127 print 'self.dataIn.data_spc', self.dataIn.data_spc.shape
83 128 self.dataOut.abscissaList = self.dataIn.getVelRange(1)
84 self.dataOut.noise = self.dataIn.getNoise()
129 self.dataOut.spc_noise = self.dataIn.getNoise()
130 self.dataOut.spc_range = (self.dataIn.getFreqRange(1)/1000. , self.dataIn.getAcfRange(1) , self.dataIn.getVelRange(1) )
131
85 132 self.dataOut.normFactor = self.dataIn.normFactor
86 self.dataOut.outputInterval = self.dataIn.outputInterval
133 #self.dataOut.outputInterval = self.dataIn.outputInterval
87 134 self.dataOut.groupList = self.dataIn.pairsList
88 135 self.dataOut.flagNoData = False
89
136 #print 'datain chandist ',self.dataIn.ChanDist
90 137 if hasattr(self.dataIn, 'ChanDist'): #Distances of receiver channels
91 138 self.dataOut.ChanDist = self.dataIn.ChanDist
139 else: self.dataOut.ChanDist = None
140
141 print 'datain chandist ',self.dataOut.ChanDist
92 142
93 143 if hasattr(self.dataIn, 'VelRange'): #Velocities range
94 144 self.dataOut.VelRange = self.dataIn.VelRange
145 else: self.dataOut.VelRange = None
95 146
96 147 if hasattr(self.dataIn, 'RadarConst'): #Radar Constant
97 148 self.dataOut.RadarConst = self.dataIn.RadarConst
@@ -132,71 +183,843 class ParametersProc(ProcessingUnit):
132 183 self.dataOut.paramInterval = self.dataIn.timeInterval
133 184
134 185 return
186
187
188 def target(tups):
189
190 obj, args = tups
191 #print 'TARGETTT', obj, args
192 return obj.FitGau(args)
193
194 class GaussianFit(Operation):
195
196 '''
197 Function that fit of one and two generalized gaussians (gg) based
198 on the PSD shape across an "power band" identified from a cumsum of
199 the measured spectrum - noise.
200
201 Input:
202 self.dataOut.data_pre : SelfSpectra
203
204 Output:
205 self.dataOut.GauSPC : SPC_ch1, SPC_ch2
206
207 '''
208 def __init__(self, **kwargs):
209 Operation.__init__(self, **kwargs)
210 self.i=0
211
212
213 def run(self, dataOut, num_intg=7, pnoise=1., vel_arr=None, SNRlimit=-9): #num_intg: Incoherent integrations, pnoise: Noise, vel_arr: range of velocities, similar to the ftt points
214 """This routine will find a couple of generalized Gaussians to a power spectrum
215 input: spc
216 output:
217 Amplitude0,shift0,width0,p0,Amplitude1,shift1,width1,p1,noise
218 """
219
220 self.spc = dataOut.data_pre[0].copy()
221
222
223 print 'SelfSpectra Shape', numpy.asarray(self.spc).shape
224
225
226 #plt.figure(50)
227 #plt.subplot(121)
228 #plt.plot(self.spc,'k',label='spc(66)')
229 #plt.plot(xFrec,ySamples[1],'g',label='Ch1')
230 #plt.plot(xFrec,ySamples[2],'r',label='Ch2')
231 #plt.plot(xFrec,FitGauss,'yo:',label='fit')
232 #plt.legend()
233 #plt.title('DATOS A ALTURA DE 7500 METROS')
234 #plt.show()
235
236 self.Num_Hei = self.spc.shape[2]
237 #self.Num_Bin = len(self.spc)
238 self.Num_Bin = self.spc.shape[1]
239 self.Num_Chn = self.spc.shape[0]
240
241 Vrange = dataOut.abscissaList
242
243 #print 'self.spc2', numpy.asarray(self.spc).shape
244
245 GauSPC = numpy.empty([2,self.Num_Bin,self.Num_Hei])
246 SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei])
247 SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei])
248 SPC_ch1[:] = numpy.NaN
249 SPC_ch2[:] = numpy.NaN
250
251
252 start_time = time.time()
253
254 noise_ = dataOut.spc_noise[0].copy()
255
256
257
258 pool = Pool(processes=self.Num_Chn)
259 args = [(Vrange, Ch, pnoise, noise_, num_intg, SNRlimit) for Ch in range(self.Num_Chn)]
260 objs = [self for __ in range(self.Num_Chn)]
261 attrs = zip(objs, args)
262 gauSPC = pool.map(target, attrs)
263 dataOut.GauSPC = numpy.asarray(gauSPC)
264 # ret = []
265 # for n in range(self.Num_Chn):
266 # self.FitGau(args[n])
267 # dataOut.GauSPC = ret
268
269
270
271 # for ch in range(self.Num_Chn):
272 #
273 # for ht in range(self.Num_Hei):
274 # #print (numpy.asarray(self.spc).shape)
275 # spc = numpy.asarray(self.spc)[ch,:,ht]
276 #
277 # #############################################
278 # # normalizing spc and noise
279 # # This part differs from gg1
280 # spc_norm_max = max(spc)
281 # spc = spc / spc_norm_max
282 # pnoise = pnoise / spc_norm_max
283 # #############################################
284 #
285 # if abs(vel_arr[0])<15.0: # this switch is for spectra collected with different length IPP's
286 # fatspectra=1.0
287 # else:
288 # fatspectra=0.5
289 #
290 # wnoise = noise_ / spc_norm_max
291 # #print 'wnoise', noise_, dataOut.spc_noise[0], wnoise
292 # #wnoise,stdv,i_max,index =enoise(spc,num_intg) #noise estimate using Hildebrand Sekhon, only wnoise is used
293 # #if wnoise>1.1*pnoise: # to be tested later
294 # # wnoise=pnoise
295 # noisebl=wnoise*0.9; noisebh=wnoise*1.1
296 # spc=spc-wnoise
297 #
298 # minx=numpy.argmin(spc)
299 # spcs=numpy.roll(spc,-minx)
300 # cum=numpy.cumsum(spcs)
301 # tot_noise=wnoise * self.Num_Bin #64;
302 # #tot_signal=sum(cum[-5:])/5.; ''' How does this line work? '''
303 # #snr=tot_signal/tot_noise
304 # #snr=cum[-1]/tot_noise
305 #
306 # #print 'spc' , spcs[5:8] , 'tot_noise', tot_noise
307 #
308 # snr = sum(spcs)/tot_noise
309 # snrdB=10.*numpy.log10(snr)
310 #
311 # #if snrdB < -9 :
312 # # snrdB = numpy.NaN
313 # # continue
314 #
315 # #print 'snr',snrdB # , sum(spcs) , tot_noise
316 #
317 #
318 # #if snrdB<-18 or numpy.isnan(snrdB) or num_intg<4:
319 # # return [None,]*4,[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None
320 #
321 # cummax=max(cum); epsi=0.08*fatspectra # cumsum to narrow down the energy region
322 # cumlo=cummax*epsi;
323 # cumhi=cummax*(1-epsi)
324 # powerindex=numpy.array(numpy.where(numpy.logical_and(cum>cumlo, cum<cumhi))[0])
325 #
326 # #if len(powerindex)==1:
327 # ##return [numpy.mod(powerindex[0]+minx,64),None,None,None,],[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None
328 # #return [numpy.mod(powerindex[0]+minx, self.Num_Bin ),None,None,None,],[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None
329 # #elif len(powerindex)<4*fatspectra:
330 # #return [None,]*4,[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None
331 #
332 # if len(powerindex) < 1:# case for powerindex 0
333 # continue
334 # powerlo=powerindex[0]
335 # powerhi=powerindex[-1]
336 # powerwidth=powerhi-powerlo
337 #
338 # firstpeak=powerlo+powerwidth/10.# first gaussian energy location
339 # secondpeak=powerhi-powerwidth/10.#second gaussian energy location
340 # midpeak=(firstpeak+secondpeak)/2.
341 # firstamp=spcs[int(firstpeak)]
342 # secondamp=spcs[int(secondpeak)]
343 # midamp=spcs[int(midpeak)]
344 # #x=numpy.spc.shape[1]
345 #
346 # #x=numpy.arange(64)
347 # x=numpy.arange( self.Num_Bin )
348 # y_data=spc+wnoise
349 #
350 # # single gaussian
351 # #shift0=numpy.mod(midpeak+minx,64)
352 # shift0=numpy.mod(midpeak+minx, self.Num_Bin )
353 # width0=powerwidth/4.#Initialization entire power of spectrum divided by 4
354 # power0=2.
355 # amplitude0=midamp
356 # state0=[shift0,width0,amplitude0,power0,wnoise]
357 # #bnds=((0,63),(1,powerwidth),(0,None),(0.5,3.),(noisebl,noisebh))
358 # bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth),(0,None),(0.5,3.),(noisebl,noisebh))
359 # #bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth),(0,None),(0.5,3.),(0.1,0.5))
360 # # bnds = range of fft, power width, amplitude, power, noise
361 # lsq1=fmin_l_bfgs_b(self.misfit1,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True)
362 #
363 # chiSq1=lsq1[1];
364 # jack1= self.y_jacobian1(x,lsq1[0])
365 #
366 #
367 # try:
368 # sigmas1=numpy.sqrt(chiSq1*numpy.diag(numpy.linalg.inv(numpy.dot(jack1.T,jack1))))
369 # except:
370 # std1=32.; sigmas1=numpy.ones(5)
371 # else:
372 # std1=sigmas1[0]
373 #
374 #
375 # if fatspectra<1.0 and powerwidth<4:
376 # choice=0
377 # Amplitude0=lsq1[0][2]
378 # shift0=lsq1[0][0]
379 # width0=lsq1[0][1]
380 # p0=lsq1[0][3]
381 # Amplitude1=0.
382 # shift1=0.
383 # width1=0.
384 # p1=0.
385 # noise=lsq1[0][4]
386 # #return (numpy.array([shift0,width0,Amplitude0,p0]),
387 # # numpy.array([shift1,width1,Amplitude1,p1]),noise,snrdB,chiSq1,6.,sigmas1,[None,]*9,choice)
388 #
389 # # two gaussians
390 # #shift0=numpy.mod(firstpeak+minx,64); shift1=numpy.mod(secondpeak+minx,64)
391 # shift0=numpy.mod(firstpeak+minx, self.Num_Bin );
392 # shift1=numpy.mod(secondpeak+minx, self.Num_Bin )
393 # width0=powerwidth/6.;
394 # width1=width0
395 # power0=2.;
396 # power1=power0
397 # amplitude0=firstamp;
398 # amplitude1=secondamp
399 # state0=[shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,wnoise]
400 # #bnds=((0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh))
401 # bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh))
402 # #bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(0.1,0.5))
403 #
404 # lsq2=fmin_l_bfgs_b(self.misfit2,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True)
405 #
406 #
407 # chiSq2=lsq2[1]; jack2=self.y_jacobian2(x,lsq2[0])
408 #
409 #
410 # try:
411 # sigmas2=numpy.sqrt(chiSq2*numpy.diag(numpy.linalg.inv(numpy.dot(jack2.T,jack2))))
412 # except:
413 # std2a=32.; std2b=32.; sigmas2=numpy.ones(9)
414 # else:
415 # std2a=sigmas2[0]; std2b=sigmas2[4]
416 #
417 #
418 #
419 # oneG=(chiSq1<5 and chiSq1/chiSq2<2.0) and (abs(lsq2[0][0]-lsq2[0][4])<(lsq2[0][1]+lsq2[0][5])/3. or abs(lsq2[0][0]-lsq2[0][4])<10)
420 #
421 # if snrdB>-9: # when SNR is strong pick the peak with least shift (LOS velocity) error
422 # if oneG:
423 # choice=0
424 # else:
425 # w1=lsq2[0][1]; w2=lsq2[0][5]
426 # a1=lsq2[0][2]; a2=lsq2[0][6]
427 # p1=lsq2[0][3]; p2=lsq2[0][7]
428 # s1=(2**(1+1./p1))*scipy.special.gamma(1./p1)/p1; s2=(2**(1+1./p2))*scipy.special.gamma(1./p2)/p2;
429 # gp1=a1*w1*s1; gp2=a2*w2*s2 # power content of each ggaussian with proper p scaling
430 #
431 # if gp1>gp2:
432 # if a1>0.7*a2:
433 # choice=1
434 # else:
435 # choice=2
436 # elif gp2>gp1:
437 # if a2>0.7*a1:
438 # choice=2
439 # else:
440 # choice=1
441 # else:
442 # choice=numpy.argmax([a1,a2])+1
443 # #else:
444 # #choice=argmin([std2a,std2b])+1
445 #
446 # else: # with low SNR go to the most energetic peak
447 # choice=numpy.argmax([lsq1[0][2]*lsq1[0][1],lsq2[0][2]*lsq2[0][1],lsq2[0][6]*lsq2[0][5]])
448 #
449 # #print 'choice',choice
450 #
451 # if choice==0: # pick the single gaussian fit
452 # Amplitude0=lsq1[0][2]
453 # shift0=lsq1[0][0]
454 # width0=lsq1[0][1]
455 # p0=lsq1[0][3]
456 # Amplitude1=0.
457 # shift1=0.
458 # width1=0.
459 # p1=0.
460 # noise=lsq1[0][4]
461 # elif choice==1: # take the first one of the 2 gaussians fitted
462 # Amplitude0 = lsq2[0][2]
463 # shift0 = lsq2[0][0]
464 # width0 = lsq2[0][1]
465 # p0 = lsq2[0][3]
466 # Amplitude1 = lsq2[0][6] # This is 0 in gg1
467 # shift1 = lsq2[0][4] # This is 0 in gg1
468 # width1 = lsq2[0][5] # This is 0 in gg1
469 # p1 = lsq2[0][7] # This is 0 in gg1
470 # noise = lsq2[0][8]
471 # else: # the second one
472 # Amplitude0 = lsq2[0][6]
473 # shift0 = lsq2[0][4]
474 # width0 = lsq2[0][5]
475 # p0 = lsq2[0][7]
476 # Amplitude1 = lsq2[0][2] # This is 0 in gg1
477 # shift1 = lsq2[0][0] # This is 0 in gg1
478 # width1 = lsq2[0][1] # This is 0 in gg1
479 # p1 = lsq2[0][3] # This is 0 in gg1
480 # noise = lsq2[0][8]
481 #
482 # #print len(noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0)
483 # SPC_ch1[:,ht] = noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0
484 # SPC_ch2[:,ht] = noise + Amplitude1*numpy.exp(-0.5*(abs(x-shift1))/width1)**p1
485 # #print 'SPC_ch1.shape',SPC_ch1.shape
486 # #print 'SPC_ch2.shape',SPC_ch2.shape
487 # #dataOut.data_param = SPC_ch1
488 # GauSPC[0] = SPC_ch1
489 # GauSPC[1] = SPC_ch2
490
491 # #plt.gcf().clear()
492 # plt.figure(50+self.i)
493 # self.i=self.i+1
494 # #plt.subplot(121)
495 # plt.plot(self.spc,'k')#,label='spc(66)')
496 # plt.plot(SPC_ch1[ch,ht],'b')#,label='gg1')
497 # #plt.plot(SPC_ch2,'r')#,label='gg2')
498 # #plt.plot(xFrec,ySamples[1],'g',label='Ch1')
499 # #plt.plot(xFrec,ySamples[2],'r',label='Ch2')
500 # #plt.plot(xFrec,FitGauss,'yo:',label='fit')
501 # plt.legend()
502 # plt.title('DATOS A ALTURA DE 7500 METROS')
503 # plt.show()
504 # print 'shift0', shift0
505 # print 'Amplitude0', Amplitude0
506 # print 'width0', width0
507 # print 'p0', p0
508 # print '========================'
509 # print 'shift1', shift1
510 # print 'Amplitude1', Amplitude1
511 # print 'width1', width1
512 # print 'p1', p1
513 # print 'noise', noise
514 # print 's_noise', wnoise
515
516 print '========================================================'
517 print 'total_time: ', time.time()-start_time
518
519 # re-normalizing spc and noise
520 # This part differs from gg1
521
522
523
524 ''' Parameters:
525 1. Amplitude
526 2. Shift
527 3. Width
528 4. Power
529 '''
530
531
532 ###############################################################################
533 def FitGau(self, X):
534
535 Vrange, ch, pnoise, noise_, num_intg, SNRlimit = X
536 #print 'VARSSSS', ch, pnoise, noise, num_intg
537
538 #print 'HEIGHTS', self.Num_Hei
539
540 GauSPC = []
541 SPC_ch1 = numpy.empty([self.Num_Bin,self.Num_Hei])
542 SPC_ch2 = numpy.empty([self.Num_Bin,self.Num_Hei])
543 SPC_ch1[:] = 0#numpy.NaN
544 SPC_ch2[:] = 0#numpy.NaN
545
546
547
548 for ht in range(self.Num_Hei):
549 #print (numpy.asarray(self.spc).shape)
550
551 #print 'TTTTT', ch , ht
552 #print self.spc.shape
553
554
555 spc = numpy.asarray(self.spc)[ch,:,ht]
556
557 #############################################
558 # normalizing spc and noise
559 # This part differs from gg1
560 spc_norm_max = max(spc)
561 spc = spc / spc_norm_max
562 pnoise = pnoise / spc_norm_max
563 #############################################
564
565 fatspectra=1.0
566
567 wnoise = noise_ / spc_norm_max
568 #wnoise,stdv,i_max,index =enoise(spc,num_intg) #noise estimate using Hildebrand Sekhon, only wnoise is used
569 #if wnoise>1.1*pnoise: # to be tested later
570 # wnoise=pnoise
571 noisebl=wnoise*0.9; noisebh=wnoise*1.1
572 spc=spc-wnoise
573 # print 'wnoise', noise_[0], spc_norm_max, wnoise
574 minx=numpy.argmin(spc)
575 spcs=numpy.roll(spc,-minx)
576 cum=numpy.cumsum(spcs)
577 tot_noise=wnoise * self.Num_Bin #64;
578 #print 'spc' , spcs[5:8] , 'tot_noise', tot_noise
579 #tot_signal=sum(cum[-5:])/5.; ''' How does this line work? '''
580 #snr=tot_signal/tot_noise
581 #snr=cum[-1]/tot_noise
582 snr = sum(spcs)/tot_noise
583 snrdB=10.*numpy.log10(snr)
584
585 if snrdB < SNRlimit :
586 snr = numpy.NaN
587 SPC_ch1[:,ht] = 0#numpy.NaN
588 SPC_ch1[:,ht] = 0#numpy.NaN
589 GauSPC = (SPC_ch1,SPC_ch2)
590 continue
591 #print 'snr',snrdB #, sum(spcs) , tot_noise
592
593
594
595 #if snrdB<-18 or numpy.isnan(snrdB) or num_intg<4:
596 # return [None,]*4,[None,]*4,None,snrdB,None,None,[None,]*5,[None,]*9,None
597
598 cummax=max(cum); epsi=0.08*fatspectra # cumsum to narrow down the energy region
599 cumlo=cummax*epsi;
600 cumhi=cummax*(1-epsi)
601 powerindex=numpy.array(numpy.where(numpy.logical_and(cum>cumlo, cum<cumhi))[0])
602
603
604 if len(powerindex) < 1:# case for powerindex 0
605 continue
606 powerlo=powerindex[0]
607 powerhi=powerindex[-1]
608 powerwidth=powerhi-powerlo
609
610 firstpeak=powerlo+powerwidth/10.# first gaussian energy location
611 secondpeak=powerhi-powerwidth/10.#second gaussian energy location
612 midpeak=(firstpeak+secondpeak)/2.
613 firstamp=spcs[int(firstpeak)]
614 secondamp=spcs[int(secondpeak)]
615 midamp=spcs[int(midpeak)]
616
617 x=numpy.arange( self.Num_Bin )
618 y_data=spc+wnoise
619
620 # single gaussian
621 shift0=numpy.mod(midpeak+minx, self.Num_Bin )
622 width0=powerwidth/4.#Initialization entire power of spectrum divided by 4
623 power0=2.
624 amplitude0=midamp
625 state0=[shift0,width0,amplitude0,power0,wnoise]
626 bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth),(0,None),(0.5,3.),(noisebl,noisebh))
627 lsq1=fmin_l_bfgs_b(self.misfit1,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True)
628
629 chiSq1=lsq1[1];
630 jack1= self.y_jacobian1(x,lsq1[0])
631
632
633 try:
634 sigmas1=numpy.sqrt(chiSq1*numpy.diag(numpy.linalg.inv(numpy.dot(jack1.T,jack1))))
635 except:
636 std1=32.; sigmas1=numpy.ones(5)
637 else:
638 std1=sigmas1[0]
639
640
641 if fatspectra<1.0 and powerwidth<4:
642 choice=0
643 Amplitude0=lsq1[0][2]
644 shift0=lsq1[0][0]
645 width0=lsq1[0][1]
646 p0=lsq1[0][3]
647 Amplitude1=0.
648 shift1=0.
649 width1=0.
650 p1=0.
651 noise=lsq1[0][4]
652 #return (numpy.array([shift0,width0,Amplitude0,p0]),
653 # numpy.array([shift1,width1,Amplitude1,p1]),noise,snrdB,chiSq1,6.,sigmas1,[None,]*9,choice)
654
655 # two gaussians
656 #shift0=numpy.mod(firstpeak+minx,64); shift1=numpy.mod(secondpeak+minx,64)
657 shift0=numpy.mod(firstpeak+minx, self.Num_Bin );
658 shift1=numpy.mod(secondpeak+minx, self.Num_Bin )
659 width0=powerwidth/6.;
660 width1=width0
661 power0=2.;
662 power1=power0
663 amplitude0=firstamp;
664 amplitude1=secondamp
665 state0=[shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,wnoise]
666 #bnds=((0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(0,63),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh))
667 bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(noisebl,noisebh))
668 #bnds=(( 0,(self.Num_Bin-1) ),(1,powerwidth/2.),(0,None),(0.5,3.),( 0,(self.Num_Bin-1)),(1,powerwidth/2.),(0,None),(0.5,3.),(0.1,0.5))
669
670 lsq2=fmin_l_bfgs_b(self.misfit2,state0,args=(y_data,x,num_intg),bounds=bnds,approx_grad=True)
671
672
673 chiSq2=lsq2[1]; jack2=self.y_jacobian2(x,lsq2[0])
674
675
676 try:
677 sigmas2=numpy.sqrt(chiSq2*numpy.diag(numpy.linalg.inv(numpy.dot(jack2.T,jack2))))
678 except:
679 std2a=32.; std2b=32.; sigmas2=numpy.ones(9)
680 else:
681 std2a=sigmas2[0]; std2b=sigmas2[4]
682
683
684
685 oneG=(chiSq1<5 and chiSq1/chiSq2<2.0) and (abs(lsq2[0][0]-lsq2[0][4])<(lsq2[0][1]+lsq2[0][5])/3. or abs(lsq2[0][0]-lsq2[0][4])<10)
686
687 if snrdB>-6: # when SNR is strong pick the peak with least shift (LOS velocity) error
688 if oneG:
689 choice=0
690 else:
691 w1=lsq2[0][1]; w2=lsq2[0][5]
692 a1=lsq2[0][2]; a2=lsq2[0][6]
693 p1=lsq2[0][3]; p2=lsq2[0][7]
694 s1=(2**(1+1./p1))*scipy.special.gamma(1./p1)/p1;
695 s2=(2**(1+1./p2))*scipy.special.gamma(1./p2)/p2;
696 gp1=a1*w1*s1; gp2=a2*w2*s2 # power content of each ggaussian with proper p scaling
697
698 if gp1>gp2:
699 if a1>0.7*a2:
700 choice=1
701 else:
702 choice=2
703 elif gp2>gp1:
704 if a2>0.7*a1:
705 choice=2
706 else:
707 choice=1
708 else:
709 choice=numpy.argmax([a1,a2])+1
710 #else:
711 #choice=argmin([std2a,std2b])+1
712
713 else: # with low SNR go to the most energetic peak
714 choice=numpy.argmax([lsq1[0][2]*lsq1[0][1],lsq2[0][2]*lsq2[0][1],lsq2[0][6]*lsq2[0][5]])
715
716
717 shift0=lsq2[0][0]; vel0=Vrange[0] + shift0*(Vrange[1]-Vrange[0])
718 shift1=lsq2[0][4]; vel1=Vrange[0] + shift1*(Vrange[1]-Vrange[0])
719
720 max_vel = 20
721
722 #first peak will be 0, second peak will be 1
723 if vel0 > 0 and vel0 < max_vel : #first peak is in the correct range
724 shift0=lsq2[0][0]
725 width0=lsq2[0][1]
726 Amplitude0=lsq2[0][2]
727 p0=lsq2[0][3]
728
729 shift1=lsq2[0][4]
730 width1=lsq2[0][5]
731 Amplitude1=lsq2[0][6]
732 p1=lsq2[0][7]
733 noise=lsq2[0][8]
734 else:
735 shift1=lsq2[0][0]
736 width1=lsq2[0][1]
737 Amplitude1=lsq2[0][2]
738 p1=lsq2[0][3]
739
740 shift0=lsq2[0][4]
741 width0=lsq2[0][5]
742 Amplitude0=lsq2[0][6]
743 p0=lsq2[0][7]
744 noise=lsq2[0][8]
745
746 if Amplitude0<0.1: # in case the peak is noise
747 shift0,width0,Amplitude0,p0 = 4*[numpy.NaN]
748 if Amplitude1<0.1:
749 shift1,width1,Amplitude1,p1 = 4*[numpy.NaN]
750
751
752 # if choice==0: # pick the single gaussian fit
753 # Amplitude0=lsq1[0][2]
754 # shift0=lsq1[0][0]
755 # width0=lsq1[0][1]
756 # p0=lsq1[0][3]
757 # Amplitude1=0.
758 # shift1=0.
759 # width1=0.
760 # p1=0.
761 # noise=lsq1[0][4]
762 # elif choice==1: # take the first one of the 2 gaussians fitted
763 # Amplitude0 = lsq2[0][2]
764 # shift0 = lsq2[0][0]
765 # width0 = lsq2[0][1]
766 # p0 = lsq2[0][3]
767 # Amplitude1 = lsq2[0][6] # This is 0 in gg1
768 # shift1 = lsq2[0][4] # This is 0 in gg1
769 # width1 = lsq2[0][5] # This is 0 in gg1
770 # p1 = lsq2[0][7] # This is 0 in gg1
771 # noise = lsq2[0][8]
772 # else: # the second one
773 # Amplitude0 = lsq2[0][6]
774 # shift0 = lsq2[0][4]
775 # width0 = lsq2[0][5]
776 # p0 = lsq2[0][7]
777 # Amplitude1 = lsq2[0][2] # This is 0 in gg1
778 # shift1 = lsq2[0][0] # This is 0 in gg1
779 # width1 = lsq2[0][1] # This is 0 in gg1
780 # p1 = lsq2[0][3] # This is 0 in gg1
781 # noise = lsq2[0][8]
782
783 #print len(noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0)
784 SPC_ch1[:,ht] = noise + Amplitude0*numpy.exp(-0.5*(abs(x-shift0))/width0)**p0
785 SPC_ch2[:,ht] = noise + Amplitude1*numpy.exp(-0.5*(abs(x-shift1))/width1)**p1
786 #print 'SPC_ch1.shape',SPC_ch1.shape
787 #print 'SPC_ch2.shape',SPC_ch2.shape
788 #dataOut.data_param = SPC_ch1
789 GauSPC = (SPC_ch1,SPC_ch2)
790 #GauSPC[1] = SPC_ch2
791
792 # print 'shift0', shift0
793 # print 'Amplitude0', Amplitude0
794 # print 'width0', width0
795 # print 'p0', p0
796 # print '========================'
797 # print 'shift1', shift1
798 # print 'Amplitude1', Amplitude1
799 # print 'width1', width1
800 # print 'p1', p1
801 # print 'noise', noise
802 # print 's_noise', wnoise
803
804 return GauSPC
805
806
807 def y_jacobian1(self,x,state): # This function is for further analysis of generalized Gaussians, it is not too importan for the signal discrimination.
808 y_model=self.y_model1(x,state)
809 s0,w0,a0,p0,n=state
810 e0=((x-s0)/w0)**2;
811
812 e0u=((x-s0-self.Num_Bin)/w0)**2;
813
814 e0d=((x-s0+self.Num_Bin)/w0)**2
815 m0=numpy.exp(-0.5*e0**(p0/2.));
816 m0u=numpy.exp(-0.5*e0u**(p0/2.));
817 m0d=numpy.exp(-0.5*e0d**(p0/2.))
818 JA=m0+m0u+m0d
819 JP=(-1/4.)*a0*m0*e0**(p0/2.)*numpy.log(e0)+(-1/4.)*a0*m0u*e0u**(p0/2.)*numpy.log(e0u)+(-1/4.)*a0*m0d*e0d**(p0/2.)*numpy.log(e0d)
820
821 JS=(p0/w0/2.)*a0*m0*e0**(p0/2.-1)*((x-s0)/w0)+(p0/w0/2.)*a0*m0u*e0u**(p0/2.-1)*((x-s0- self.Num_Bin )/w0)+(p0/w0/2.)*a0*m0d*e0d**(p0/2.-1)*((x-s0+ self.Num_Bin )/w0)
822
823 JW=(p0/w0/2.)*a0*m0*e0**(p0/2.-1)*((x-s0)/w0)**2+(p0/w0/2.)*a0*m0u*e0u**(p0/2.-1)*((x-s0- self.Num_Bin )/w0)**2+(p0/w0/2.)*a0*m0d*e0d**(p0/2.-1)*((x-s0+ self.Num_Bin )/w0)**2
824 jack1=numpy.sqrt(7)*numpy.array([JS/y_model,JW/y_model,JA/y_model,JP/y_model,1./y_model])
825 return jack1.T
826
827 def y_jacobian2(self,x,state):
828 y_model=self.y_model2(x,state)
829 s0,w0,a0,p0,s1,w1,a1,p1,n=state
830 e0=((x-s0)/w0)**2;
831
832 e0u=((x-s0- self.Num_Bin )/w0)**2;
833
834 e0d=((x-s0+ self.Num_Bin )/w0)**2
835 e1=((x-s1)/w1)**2;
836
837 e1u=((x-s1- self.Num_Bin )/w1)**2;
838
839 e1d=((x-s1+ self.Num_Bin )/w1)**2
840 m0=numpy.exp(-0.5*e0**(p0/2.));
841 m0u=numpy.exp(-0.5*e0u**(p0/2.));
842 m0d=numpy.exp(-0.5*e0d**(p0/2.))
843 m1=numpy.exp(-0.5*e1**(p1/2.));
844 m1u=numpy.exp(-0.5*e1u**(p1/2.));
845 m1d=numpy.exp(-0.5*e1d**(p1/2.))
846 JA=m0+m0u+m0d
847 JA1=m1+m1u+m1d
848 JP=(-1/4.)*a0*m0*e0**(p0/2.)*numpy.log(e0)+(-1/4.)*a0*m0u*e0u**(p0/2.)*numpy.log(e0u)+(-1/4.)*a0*m0d*e0d**(p0/2.)*numpy.log(e0d)
849 JP1=(-1/4.)*a1*m1*e1**(p1/2.)*numpy.log(e1)+(-1/4.)*a1*m1u*e1u**(p1/2.)*numpy.log(e1u)+(-1/4.)*a1*m1d*e1d**(p1/2.)*numpy.log(e1d)
850
851 JS=(p0/w0/2.)*a0*m0*e0**(p0/2.-1)*((x-s0)/w0)+(p0/w0/2.)*a0*m0u*e0u**(p0/2.-1)*((x-s0- self.Num_Bin )/w0)+(p0/w0/2.)*a0*m0d*e0d**(p0/2.-1)*((x-s0+ self.Num_Bin )/w0)
852
853 JS1=(p1/w1/2.)*a1*m1*e1**(p1/2.-1)*((x-s1)/w1)+(p1/w1/2.)*a1*m1u*e1u**(p1/2.-1)*((x-s1- self.Num_Bin )/w1)+(p1/w1/2.)*a1*m1d*e1d**(p1/2.-1)*((x-s1+ self.Num_Bin )/w1)
854
855 JW=(p0/w0/2.)*a0*m0*e0**(p0/2.-1)*((x-s0)/w0)**2+(p0/w0/2.)*a0*m0u*e0u**(p0/2.-1)*((x-s0- self.Num_Bin )/w0)**2+(p0/w0/2.)*a0*m0d*e0d**(p0/2.-1)*((x-s0+ self.Num_Bin )/w0)**2
856
857 JW1=(p1/w1/2.)*a1*m1*e1**(p1/2.-1)*((x-s1)/w1)**2+(p1/w1/2.)*a1*m1u*e1u**(p1/2.-1)*((x-s1- self.Num_Bin )/w1)**2+(p1/w1/2.)*a1*m1d*e1d**(p1/2.-1)*((x-s1+ self.Num_Bin )/w1)**2
858 jack2=numpy.sqrt(7)*numpy.array([JS/y_model,JW/y_model,JA/y_model,JP/y_model,JS1/y_model,JW1/y_model,JA1/y_model,JP1/y_model,1./y_model])
859 return jack2.T
860
861 def y_model1(self,x,state):
862 shift0,width0,amplitude0,power0,noise=state
863 model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0)
864
865 model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0)
866
867 model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0)
868 return model0+model0u+model0d+noise
869
870 def y_model2(self,x,state): #Equation for two generalized Gaussians with Nyquist
871 shift0,width0,amplitude0,power0,shift1,width1,amplitude1,power1,noise=state
872 model0=amplitude0*numpy.exp(-0.5*abs((x-shift0)/width0)**power0)
873
874 model0u=amplitude0*numpy.exp(-0.5*abs((x-shift0- self.Num_Bin )/width0)**power0)
875
876 model0d=amplitude0*numpy.exp(-0.5*abs((x-shift0+ self.Num_Bin )/width0)**power0)
877 model1=amplitude1*numpy.exp(-0.5*abs((x-shift1)/width1)**power1)
878
879 model1u=amplitude1*numpy.exp(-0.5*abs((x-shift1- self.Num_Bin )/width1)**power1)
880
881 model1d=amplitude1*numpy.exp(-0.5*abs((x-shift1+ self.Num_Bin )/width1)**power1)
882 return model0+model0u+model0d+model1+model1u+model1d+noise
883
884 def misfit1(self,state,y_data,x,num_intg): # This function compares how close real data is with the model data, the close it is, the better it is.
885
886 return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model1(x,state)))**2)#/(64-5.) # /(64-5.) can be commented
887
888 def misfit2(self,state,y_data,x,num_intg):
889 return num_intg*sum((numpy.log(y_data)-numpy.log(self.y_model2(x,state)))**2)#/(64-9.)
135 890
136 891
137 892 class PrecipitationProc(Operation):
138 893
139 894 '''
140 Funtion that uses Reflectivity factor (Z), and estimates rainfall Rate
895 Operator that estimates Reflectivity factor (Z), and estimates rainfall Rate (R)
141 896
142 897 Input:
143 898 self.dataOut.data_pre : SelfSpectra
144 899
145
146
147 Output:
900 Output:
148 901
149 902 self.dataOut.data_output : Reflectivity factor, rainfall Rate
150 903
151 904
152 Parameters affected: Winds, height range, SNR
905 Parameters affected:
153 906 '''
907
154 908
155 def run(self, dataOut):
909 def run(self, dataOut, radar=None, Pt=None, Gt=None, Gr=None, Lambda=None, aL=None,
910 tauW=None, ThetaT=None, ThetaR=None, Km = 0.93, Altitude=None):
156 911
157 #numpy.set_printoptions(threshold=numpy.NaN)
912 self.spc = dataOut.data_pre[0].copy()
913 self.Num_Hei = self.spc.shape[2]
914 self.Num_Bin = self.spc.shape[1]
915 self.Num_Chn = self.spc.shape[0]
158 916
159 spc = dataOut.data_pre[0].copy()
160 NPW = dataOut.NPW
161 COFA = dataOut.COFA
162 #print 'COFA',COFA.shape
163 #spc = numpy.where(spc<0,spc, numpy.NaN )
917 Velrange = dataOut.abscissaList
918
919 if radar == "MIRA35C" :
920
921 Ze = self.dBZeMODE2(dataOut)
922
923 else:
924
925 self.Pt = Pt
926 self.Gt = Gt
927 self.Gr = Gr
928 self.Lambda = Lambda
929 self.aL = aL
930 self.tauW = tauW
931 self.ThetaT = ThetaT
932 self.ThetaR = ThetaR
933
934 RadarConstant = GetRadarConstant()
935 SPCmean = numpy.mean(self.spc,0)
936 ETA = numpy.zeros(self.Num_Hei)
937 Pr = numpy.sum(SPCmean,0)
938
939 #for R in range(self.Num_Hei):
940 # ETA[R] = RadarConstant * Pr[R] * R**2 #Reflectivity (ETA)
941
942 D_range = numpy.zeros(self.Num_Hei)
943 EqSec = numpy.zeros(self.Num_Hei)
944 del_V = numpy.zeros(self.Num_Hei)
945
946 for R in range(self.Num_Hei):
947 ETA[R] = RadarConstant * Pr[R] * R**2 #Reflectivity (ETA)
948
949 h = R + Altitude #Range from ground to radar pulse altitude
950 del_V[R] = 1 + 3.68 * 10**-5 * h + 1.71 * 10**-9 * h**2 #Density change correction for velocity
951
952 D_range[R] = numpy.log( (9.65 - (Velrange[R]/del_V[R])) / 10.3 ) / -0.6 #Range of Diameter of drops related to velocity
953 SIGMA[R] = numpy.pi**5 / Lambda**4 * Km * D_range[R]**6 #Equivalent Section of drops (sigma)
954
955 N_dist[R] = ETA[R] / SIGMA[R]
956
957 Ze = (ETA * Lambda**4) / (numpy.pi * Km)
958 Z = numpy.sum( N_dist * D_range**6 )
959 RR = 6*10**-4*numpy.pi * numpy.sum( D_range**3 * N_dist * Velrange ) #Rainfall rate
164 960
165 SNR = numpy.array([spc[0,:,:] / NPW[0] , spc[1,:,:] / NPW[1]])
166 961
962 RR = (Ze/200)**(1/1.6)
963 dBRR = 10*numpy.log10(RR)
167 964
168 #print 'SNR',SNR.shape
169 #print ' '
965 dBZe = 10*numpy.log10(Ze)
966 dataOut.data_output = Ze
967 dataOut.data_param = numpy.ones([2,self.Num_Hei])
968 dataOut.channelList = [0,1]
969 print 'channelList', dataOut.channelList
970 dataOut.data_param[0]=dBZe
971 dataOut.data_param[1]=dBRR
972 print 'RR SHAPE', dBRR.shape
973 print 'Ze SHAPE', dBZe.shape
974 print 'dataOut.data_param SHAPE', dataOut.data_param.shape
975
976
977 def dBZeMODE2(self, dataOut): # Processing for MIRA35C
978
979 NPW = dataOut.NPW
980 COFA = dataOut.COFA
981
982 SNR = numpy.array([self.spc[0,:,:] / NPW[0]]) #, self.spc[1,:,:] / NPW[1]])
170 983 RadarConst = dataOut.RadarConst
171 984 #frequency = 34.85*10**9
172 #Lambda = SPEED_OF_LIGHT/frequency
173
174 Num_Hei = spc.shape[2]
175 Num_Bin = spc.shape[1]
176 Num_Chn = spc.shape[0]
177 ETA = numpy.zeros(([Num_Chn ,Num_Hei]))
178 data_output = numpy.ones([Num_Chn ,Num_Hei])*numpy.NaN
179 985
180 Km = 0.93
986 ETA = numpy.zeros(([self.Num_Chn ,self.Num_Hei]))
987 data_output = numpy.ones([self.Num_Chn , self.Num_Hei])*numpy.NaN
181 988
182 989 ETA = numpy.sum(SNR,1)
183 ETA = numpy.where(ETA > 0. , ETA, numpy.NaN)
990 print 'ETA' , ETA
991 ETA = numpy.where(ETA is not 0. , ETA, numpy.NaN)
184 992
185 Ze = numpy.ones([Num_Chn,Num_Hei] )
993 Ze = numpy.ones([self.Num_Chn, self.Num_Hei] )
186 994
187 for r in range(Num_Hei):
995 for r in range(self.Num_Hei):
188 996
189 997 Ze[0,r] = ( ETA[0,r] ) * COFA[0,r][0] * RadarConst * ((r/5000.)**2)
190 Ze[1,r] = ( ETA[1,r] ) * COFA[1,r][0] * RadarConst * ((r/5000.)**2)
998 #Ze[1,r] = ( ETA[1,r] ) * COFA[1,r][0] * RadarConst * ((r/5000.)**2)
191 999
1000 return Ze
1001
1002 def GetRadarConstant(self):
1003
1004 """
1005 Constants:
192 1006
193 dBZe = 10*numpy.log10(Ze)
194 dataOut.data_output = Ze
195 dataOut.data_param = dBZe
1007 Pt: Transmission Power dB
1008 Gt: Transmission Gain dB
1009 Gr: Reception Gain dB
1010 Lambda: Wavelenght m
1011 aL: Attenuation loses dB
1012 tauW: Width of transmission pulse s
1013 ThetaT: Transmission antenna bean angle rad
1014 ThetaR: Reception antenna beam angle rad
196 1015
197 print 'dBZe',dBZe[0,:]
1016 """
1017 Numerator = ( (4*numpy.pi)**3 * aL**2 * 16 * numpy.log(2) )
1018 Denominator = ( Pt * Gt * Gr * Lambda**2 * SPEED_OF_LIGHT * TauW * numpy.pi * ThetaT * TheraR)
1019 RadarConstant = Numerator / Denominator
1020
1021 return RadarConstant
198 1022
199
200 1023
201 1024
202 1025 class FullSpectralAnalysis(Operation):
@@ -218,7 +1041,7 class FullSpectralAnalysis(Operation):
218 1041 Parameters affected: Winds, height range, SNR
219 1042
220 1043 """
221 def run(self, dataOut):
1044 def run(self, dataOut, E01=None, E02=None, E12=None, N01=None, N02=None, N12=None):
222 1045
223 1046 spc = dataOut.data_pre[0].copy()
224 1047 cspc = dataOut.data_pre[1].copy()
@@ -227,9 +1050,18 class FullSpectralAnalysis(Operation):
227 1050 nProfiles = spc.shape[1]
228 1051 nHeights = spc.shape[2]
229 1052
230 pairsList = dataOut.groupList
231 ChanDist = dataOut.ChanDist
232 VelRange= dataOut.VelRange
1053 pairsList = dataOut.groupList
1054 if dataOut.ChanDist is not None :
1055 ChanDist = dataOut.ChanDist
1056 else:
1057 ChanDist = numpy.array([[E01, N01],[E02,N02],[E12,N12]])
1058
1059 #print 'ChanDist', ChanDist
1060
1061 if dataOut.VelRange is not None:
1062 VelRange= dataOut.VelRange
1063 else:
1064 VelRange= dataOut.abscissaList
233 1065
234 1066 ySamples=numpy.ones([nChannel,nProfiles])
235 1067 phase=numpy.ones([nChannel,nProfiles])
@@ -240,6 +1072,7 class FullSpectralAnalysis(Operation):
240 1072
241 1073 data = dataOut.data_pre
242 1074 noise = dataOut.noise
1075 print 'noise',noise
243 1076 SNRdB = 10*numpy.log10(dataOut.data_SNR)
244 1077
245 1078 FirstMoment = []
@@ -257,20 +1090,20 class FullSpectralAnalysis(Operation):
257 1090
258 1091 for Height in range(nHeights):
259 1092
260
261
262 1093 [Vzon,Vmer,Vver, GaussCenter]= self.WindEstimation(spc, cspc, pairsList, ChanDist, Height, noise, VelRange)
263 1094
264 if abs(Vzon)<100 and abs(Vzon)> 0.:
1095 if abs(Vzon)<100. and abs(Vzon)> 0.:
265 1096 velocityX=numpy.append(velocityX, Vzon)#Vmag
266 1097
267 1098 else:
1099 print 'Vzon',Vzon
268 1100 velocityX=numpy.append(velocityX, numpy.NaN)
269
270 if abs(Vmer)<100 and abs(Vmer) > 0.:
1101
1102 if abs(Vmer)<100. and abs(Vmer) > 0.:
271 1103 velocityY=numpy.append(velocityY, Vmer)#Vang
272 1104
273 1105 else:
1106 print 'Vmer',Vmer
274 1107 velocityY=numpy.append(velocityY, numpy.NaN)
275 1108
276 1109 if abs(GaussCenter)<10:
@@ -278,10 +1111,10 class FullSpectralAnalysis(Operation):
278 1111 else:
279 1112 velocityV=numpy.append(velocityV, numpy.NaN)
280 1113 #FirstMoment[Height]= numpy.NaN
281 if SNRdBMean[Height] <12:
282 FirstMoment[Height] = numpy.NaN
283 velocityX[Height] = numpy.NaN
284 velocityY[Height] = numpy.NaN
1114 # if SNRdBMean[Height] <12:
1115 # FirstMoment[Height] = numpy.NaN
1116 # velocityX[Height] = numpy.NaN
1117 # velocityY[Height] = numpy.NaN
285 1118
286 1119
287 1120 data_output[0]=numpy.array(velocityX)
@@ -291,8 +1124,9 class FullSpectralAnalysis(Operation):
291 1124 print ' '
292 1125 #print 'FirstMoment'
293 1126 #print FirstMoment
1127 print 'velocityX',data_output[0]
294 1128 print ' '
295 #print 'velocityY'
1129 print 'velocityY',data_output[1]
296 1130 #print numpy.array(velocityY)
297 1131 print ' '
298 1132 #print 'SNR'
@@ -309,7 +1143,7 class FullSpectralAnalysis(Operation):
309 1143 return numpy.convolve(x, numpy.ones((N,))/N)[(N-1):]
310 1144
311 1145 def gaus(self,xSamples,a,x0,sigma):
312 return a*exp(-(xSamples-x0)**2/(2*sigma**2))
1146 return a*numpy.exp(-(xSamples-x0)**2/(2*sigma**2))
313 1147
314 1148 def Find(self,x,value):
315 1149 for index in range(len(x)):
@@ -353,9 +1187,17 class FullSpectralAnalysis(Operation):
353 1187
354 1188 xSamples = ar(range(len(SmoothSPC)))
355 1189 ySamples[i] = SmoothSPC-noise[i]
356
1190
1191 print ' '
1192 print ' '
1193 print ' '
1194 print 'SmoothSPC',SmoothSPC
1195 print 'noise',noise
1196 print'zline',zline
1197 print'FactNorm',FactNorm
1198
357 1199 for i in range(spc.shape[0]):
358
1200
359 1201 '''****** Line of Data CSPC ******'''
360 1202 cspcLine=cspc[i,:,Height].copy()
361 1203
@@ -372,6 +1214,8 class FullSpectralAnalysis(Operation):
372 1214 coherence[i]= self.moving_average(coherence[i],N=2)
373 1215
374 1216 phase[i] = self.moving_average( numpy.arctan2(CSPCSamples[i].imag, CSPCSamples[i].real),N=1)#*180/numpy.pi
1217
1218 print 'CSPCSamples', CSPCSamples
375 1219
376 1220 '''****** Getting fij width ******'''
377 1221
@@ -385,7 +1229,15 class FullSpectralAnalysis(Operation):
385 1229 meanGauss=sum(xSamples*yMean) / len(xSamples)
386 1230 sigma=sum(yMean*(xSamples-meanGauss)**2) / len(xSamples)
387 1231
388 if (abs(meanGauss/sigma**2) > 0.00001) :
1232 print '****************************'
1233 print 'len(xSamples): ',len(xSamples)
1234 print 'yMean: ', yMean
1235 print 'ySamples', ySamples
1236 print 'xSamples: ',xSamples
1237
1238 print 'meanGauss',meanGauss
1239 print 'sigma',sigma
1240 if (abs(meanGauss/sigma**2) > 0.000000001):#0.00001) :
389 1241
390 1242 try:
391 1243 popt,pcov = curve_fit(self.gaus,xSamples,yMean,p0=[1,meanGauss,sigma])
@@ -399,7 +1251,7 class FullSpectralAnalysis(Operation):
399 1251 except RuntimeError:
400 1252 FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean)
401 1253
402 #
1254
403 1255 else:
404 1256 FitGauss=numpy.ones(len(xSamples))*numpy.mean(yMean)
405 1257
@@ -474,12 +1326,13 class FullSpectralAnalysis(Operation):
474 1326
475 1327 VxVyResults=numpy.array([-cF,-cG])
476 1328 (Vx,Vy) = numpy.linalg.solve(VxVy, VxVyResults)
1329
477 1330 Vzon = Vy
478 1331 Vmer = Vx
479 1332 Vmag=numpy.sqrt(Vzon**2+Vmer**2)
480 1333 Vang=numpy.arctan2(Vmer,Vzon)
481 1334 Vver=xFrec[Vpos]
482
1335 print 'vzon y vmer', Vzon, Vmer
483 1336 return Vzon, Vmer, Vver, GaussCenter
484 1337
485 1338 class SpectralMoments(Operation):
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@@ -902,3 +902,4 class IncohInt(Operation):
902 902 dataOut.nIncohInt *= self.n
903 903 dataOut.utctime = avgdatatime
904 904 dataOut.flagNoData = False
905
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@@ -1,1 +1,1
1 <Project description="Reader/Writer experiment" id="196" name="test01"><ReadUnit datatype="BLTRReader" id="1961" inputId="0" name="BLTRReader"><Operation id="19611" name="run" priority="1" type="self"><Parameter format="str" id="196111" name="datatype" value="BLTRReader" /><Parameter format="str" id="196112" name="path" value="/home/erick/Documents/Data" /><Parameter format="date" id="196113" name="startDate" value="2016/10/19" /><Parameter format="date" id="196114" name="endDate" value="2016/10/19" /><Parameter format="time" id="196115" name="startTime" value="00:00:00" /><Parameter format="time" id="196116" name="endTime" value="23:59:59" /><Parameter format="int" id="196117" name="walk" value="1" /></Operation></ReadUnit><ProcUnit datatype="BLTRProc" id="1962" inputId="1961" name="BLTRProc"><Operation id="19621" name="run" priority="1" type="self" /><Operation id="19622" name="PrintInfo" priority="2" type="other" /></ProcUnit></Project> No newline at end of file
1 <Project description="Reader/Writer experiment" id="196" name="test01"><ReadUnit datatype="BLTRReader" id="1961" inputId="0" name="BLTRReader"><Operation id="19611" name="run" priority="1" type="self"><Parameter format="str" id="196111" name="datatype" value="BLTRReader" /><Parameter format="str" id="196112" name="path" value="/home/erick/Documents/Data" /><Parameter format="date" id="196113" name="startDate" value="2016/10/19" /><Parameter format="date" id="196114" name="endDate" value="2016/10/19" /><Parameter format="time" id="196115" name="startTime" value="00:00:00" /><Parameter format="time" id="196116" name="endTime" value="23:59:59" /><Parameter format="int" id="196118" name="walk" value="1" /></Operation></ReadUnit><ProcUnit datatype="BLTRProc" id="1962" inputId="1961" name="BLTRProc"><Operation id="19621" name="run" priority="1" type="self" /><Operation id="19622" name="PrintInfo" priority="2" type="other" /></ProcUnit></Project> No newline at end of file
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@@ -83,7 +83,7 opObj11.addParameter(name='n', value='6', format='float')
83 83
84 84 opObj11 = procUnitConfObj1.addOperation(name='SpectraWriter', optype='other')
85 85 opObj11.addParameter(name='path', value='/home/alex/Downloads/pdata_hf')
86 opObj11.addParameter(name='blocksPerFile', value='1', format='int')
86 opObj11.addParameter(name='blocksPerFile', value='1000', format='int')
87 87 #
88 88 #
89 89 # # opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
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@@ -14,30 +14,36 if __name__ == '__main__':
14 14 controllerObj = Project()
15 15 controllerObj.setup(id='191', name='test01', description=desc)
16 16
17 proc1 = controllerObj.addProcUnit(name='ReceiverData')
17 proc1 = controllerObj.addProcUnit(name='PlotterReceiver')
18 18 proc1.addParameter(name='realtime', value='0', format='bool')
19 proc1.addParameter(name='plottypes', value='rti,coh,phase', format='str')
20 proc1.addParameter(name='throttle', value='10', format='int')
21 proc1.addParameter(name='interactive', value='0', format='bool')
19 proc1.addParameter(name='plottypes', value='rti', format='str')
20 proc1.addParameter(name='throttle', value='2', format='int')
21 proc1.addParameter(name='server', value='erick2', format='str')
22 # proc1.addParameter(name='interactive', value='0', format='bool')
22 23 # proc1.addParameter(name='server', value='tcp://10.10.10.82:7000', format='str')
23 24 ## TODO Agregar direccion de server de publicacion a graficos como variable
24 25
25 26 op1 = proc1.addOperation(name='PlotRTIData', optype='other')
26 op1.addParameter(name='wintitle', value='Julia 150Km', format='str')
27 op1.addParameter(name='save', value='/home/nanosat/Pictures', format='str')
27 op1.addParameter(name='wintitle', value='MIRA35c RTI', format='str')
28 op1.addParameter(name='save', value='/home/erick/Pictures', format='str')
28 29 op1.addParameter(name='show', value='0', format='bool')
29 30 op1.addParameter(name='colormap', value='jet', format='str')
31 op1.addParameter(name='zmin', value='-90', format='int')
32 op1.addParameter(name='zmax', value='-40', format='int')
33 #op1.addParameter(name='xrange', value='1', format='int')
34 #op1.addParameter(name='xmin', value='23', format='int')
35 #op1.addParameter(name='xmax', value='3', format='int')
30 36 #
31 op2 = proc1.addOperation(name='PlotCOHData', optype='other')
32 op2.addParameter(name='wintitle', value='Julia 150Km', format='str')
33 op2.addParameter(name='save', value='/home/nanosat/Pictures', format='str')
34 op2.addParameter(name='colormap', value='jet', format='str')
35 op2.addParameter(name='show', value='0', format='bool')
36 # # #
37 op6 = proc1.addOperation(name='PlotPHASEData', optype='other')
38 op6.addParameter(name='wintitle', value='Julia 150Km', format='str')
39 op6.addParameter(name='save', value='/home/nanosat/Pictures', format='str')
40 op6.addParameter(name='show', value='1', format='bool')
37 # op2 = proc1.addOperation(name='PlotCOHData', optype='other')
38 # op2.addParameter(name='wintitle', value='Julia 150Km', format='str')
39 # op2.addParameter(name='save', value='/home/nanosat/Pictures', format='str')
40 # op2.addParameter(name='colormap', value='jet', format='str')
41 # op2.addParameter(name='show', value='0', format='bool')
42 # # # #
43 # op6 = proc1.addOperation(name='PlotPHASEData', optype='other')
44 # op6.addParameter(name='wintitle', value='Julia 150Km', format='str')
45 # op6.addParameter(name='save', value='/home/nanosat/Pictures', format='str')
46 # op6.addParameter(name='show', value='1', format='bool')
41 47 # #
42 48 # # proc2 = controllerObj.addProcUnit(name='ReceiverData')
43 49 # # proc2.addParameter(name='server', value='juanca', format='str')
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@@ -1,1 +1,1
1 <Project description="HF_EXAMPLE" id="191" name="test01"><ReadUnit datatype="Spectra" id="1911" inputId="0" name="SpectraReader"><Operation id="19111" name="run" priority="1" type="self"><Parameter format="str" id="191111" name="datatype" value="SpectraReader" /><Parameter format="str" id="191112" name="path" value="/home/nanosat/data/sp1_f0" /><Parameter format="date" id="191113" name="startDate" value="2017/01/28" /><Parameter format="date" id="191114" name="endDate" value="2017/01/28" /><Parameter format="time" id="191115" name="startTime" value="00:00:00" /><Parameter format="time" id="191116" name="endTime" value="23:59:59" /><Parameter format="int" id="191118" name="cursor" value="5" /><Parameter format="int" id="191119" name="skip" value="177" /><Parameter format="int" id="191120" name="walk" value="1" /><Parameter format="int" id="191121" name="verbose" value="1" /><Parameter format="int" id="191122" name="online" value="0" /></Operation></ReadUnit><ProcUnit datatype="Parameters" id="1913" inputId="1911" name="ParametersProc"><Operation id="19131" name="run" priority="1" type="self" /><Operation id="19132" name="SpectralMoments" priority="2" type="other" /><Operation id="19133" name="PublishData" priority="3" type="other"><Parameter format="int" id="191331" name="zeromq" value="1" /><Parameter format="bool" id="191332" name="verbose" value="0" /><Parameter format="int" id="191333" name="delay" value="0" /></Operation></ProcUnit><ProcUnit datatype="Spectra" id="1912" inputId="1911" name="SpectraProc"><Operation id="19121" name="run" priority="1" type="self" /></ProcUnit></Project> No newline at end of file
1 <Project description="Segundo Test" id="191" name="test01"><ReadUnit datatype="VoltageReader" id="1911" inputId="0" name="VoltageReader"><Operation id="19111" name="run" priority="1" type="self"><Parameter format="str" id="191111" name="datatype" value="VoltageReader" /><Parameter format="str" id="191112" name="path" value="/home/erick/Documents/Data/Claire_Data/raw" /><Parameter format="date" id="191113" name="startDate" value="2017/07/26" /><Parameter format="date" id="191114" name="endDate" value="2017/10/28" /><Parameter format="time" id="191115" name="startTime" value="09:40:00" /><Parameter format="time" id="191116" name="endTime" value="23:59:00" /><Parameter format="int" id="191118" name="online" value="0" /><Parameter format="int" id="191119" name="walk" value="1" /></Operation><Operation id="19112" name="printNumberOfBlock" priority="2" type="self" /></ReadUnit><ProcUnit datatype="SpectraProc" id="1913" inputId="1912" name="SpectraProc"><Operation id="19131" name="run" priority="1" type="self"><Parameter format="int" id="191311" name="nFFTPoints" value="256" /><Parameter format="pairslist" id="191312" name="pairsList" value="(0,1),(0,2),(1,2)" /></Operation><Operation id="19132" name="removeDC" priority="2" type="self" /><Operation id="19133" name="IncohInt" priority="3" type="external"><Parameter format="float" id="191331" name="n" value="30" /></Operation><Operation id="19134" name="SpectraPlot" priority="4" type="external"><Parameter format="int" id="191341" name="id" value="11" /><Parameter format="str" id="191342" name="wintitle" value="SpectraPlot" /><Parameter format="str" id="191343" name="xaxis" value="velocity" /><Parameter format="int" id="191344" name="zmin" value="0" /><Parameter format="float" id="191345" name="ymin" value="1.5" /><Parameter format="int" id="191346" name="ymax" value="7" /><Parameter format="int" id="191347" name="zmax" value="40" /><Parameter format="int" id="191348" name="save" value="1" /></Operation><Operation id="19135" name="RTIPlot" priority="5" type="other"><Parameter format="int" id="191351" name="id" value="30" /><Parameter format="str" id="191352" name="wintitle" value="RTI" /><Parameter format="int" id="191353" name="zmin" value="0" /><Parameter format="int" id="191354" name="zmax" value="40" /><Parameter format="float" id="191355" name="ymin" value="1.5" /><Parameter format="int" id="191356" name="ymax" value="8" /><Parameter format="int" id="191357" name="showprofile" value="1" /><Parameter format="float" id="191358" name="xmin" value="0" /><Parameter format="float" id="191359" name="xmax" value="23.9" /><Parameter format="int" id="191360" name="save" value="1" /></Operation><Operation id="19136" name="CrossSpectraPlot" priority="6" type="other"><Parameter format="str" id="191361" name="phase_cmap" value="bwr" /><Parameter format="int" id="191362" name="id" value="2005" /><Parameter format="str" id="191363" name="wintitle" value="CrossSpectraPlot_ShortPulse" /><Parameter format="str" id="191364" name="xaxis" value="Velocity" /><Parameter format="float" id="191365" name="ymin" value="1.5" /><Parameter format="int" id="191366" name="ymax" value="7" /></Operation></ProcUnit><ProcUnit datatype="VoltageProc" id="1912" inputId="1911" name="VoltageProc"><Operation id="19121" name="run" priority="1" type="self" /><Operation id="19122" name="setRadarFrequency" priority="2" type="self"><Parameter format="float" id="191221" name="frequency" value="445.09e6" /></Operation><Operation id="19123" name="selectHeights" priority="3" type="self"><Parameter format="float" id="191231" name="minHei" value="0" /><Parameter format="float" id="191232" name="maxHei" value="64" /></Operation></ProcUnit><ProcUnit datatype="Parameters" id="1914" inputId="1913" name="ParametersProc"><Operation id="19141" name="run" priority="1" type="self" /><Operation id="19142" name="SpectralMoments" priority="2" type="other" /><Operation id="19143" name="FullSpectralAnalysis" priority="3" type="other"><Parameter format="float" id="191431" name="E01" value="1.5" /><Parameter format="float" id="191432" name="E02" value="1.5" /><Parameter format="float" id="191433" name="E12" value="0" /><Parameter format="float" id="191434" name="N01" value="0.875" /><Parameter format="float" id="191435" name="N02" value="-0.875" /><Parameter format="float" id="191436" name="N12" value="-1.75" /></Operation><Operation id="19144" name="WindProfilerPlot" priority="4" type="other"><Parameter format="int" id="191441" name="id" value="4" /><Parameter format="str" id="191442" name="wintitle" value="Wind Profiler" /><Parameter format="bool" id="191443" name="save" value="1" /><Parameter format="float" id="191444" name="ymin" value="1.5" /><Parameter format="int" id="191445" name="ymax" value="7" /><Parameter format="float" id="191446" name="zmin" value="-0.00" /><Parameter format="float" id="191447" name="zmax" value="1.1" /></Operation></ProcUnit></Project> No newline at end of file
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@@ -1,11 +1,11
1 1 #!/usr/bin/env python
2 2 import os, sys
3 3
4 path = os.path.dirname(os.getcwd())
5 path = os.path.join(path, 'source')
6 sys.path.insert(0, '../')
4 # path = os.path.dirname(os.getcwd())
5 # path = os.path.join(path, 'source')
6 # sys.path.insert(0, '../')
7 7
8 from controller import Project
8 from schainpy.controller import Project
9 9
10 10 xmin = '15.5'
11 11 xmax = '24'
@@ -16,42 +16,42 filename = "ProcBLTR.xml"
16 16 controllerObj = Project()
17 17
18 18
19 controllerObj.setup(id = '191', name='test01', description=desc)
19 controllerObj.setup(id='191', name='test01', description=desc)
20 20
21 21 readUnitConfObj = controllerObj.addReadUnit(datatype='BLTRReader',
22 path='/home/erick/Documents/Data/BLTR_Data/fdt/',
23 startDate='2016/11/8',
22 path='/home/erick/Documents/Data/BLTR_Data/fdt/',
23
24 24 endDate='2017/10/19',
25 25 startTime='13:00:00',
26
26 startDate='2016/11/8',
27 27 endTime='23:59:59',
28 28
29 29
30 30 online=0,
31 31 walk=0,
32 32 ReadMode='1')
33 #expLabel='')
33 # expLabel='')
34 34
35 #opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
35 # opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
36 36
37 37 procUnitConfObj1 = controllerObj.addProcUnit(datatype='Spectra', inputId=readUnitConfObj.getId())
38 38
39 39
40 40
41 41 opObj11 = procUnitConfObj1.addOperation(name='IncohInt', optype='other')
42 opObj11.addParameter(name='n', value='1', format='float')
42 opObj11.addParameter(name='n', value='2', format='float')
43 43
44 44 opObj10 = procUnitConfObj1.addOperation(name='removeDC')
45 45
46 #opObj10 = procUnitConfObj1.addOperation(name='calcMag')
46 # opObj10 = procUnitConfObj1.addOperation(name='calcMag')
47 47
48 opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
49 opObj11.addParameter(name='id', value='21', format='int')
50 opObj11.addParameter(name='wintitle', value='SpectraCutPlot', format='str')
51 opObj11.addParameter(name='xaxis', value='frequency', format='str')
52 opObj11.addParameter(name='colormap', value='winter', format='str')
53 opObj11.addParameter(name='xmin', value='-0.005', format='float')
54 opObj11.addParameter(name='xmax', value='0.005', format='float')
48 # opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
49 # opObj11.addParameter(name='id', value='21', format='int')
50 # opObj11.addParameter(name='wintitle', value='SpectraCutPlot', format='str')
51 # opObj11.addParameter(name='xaxis', value='frequency', format='str')
52 # opObj11.addParameter(name='colormap', value='winter', format='str')
53 # opObj11.addParameter(name='xmin', value='-0.005', format='float')
54 # opObj11.addParameter(name='xmax', value='0.005', format='float')
55 55 # #opObj10 = procUnitConfObj1.addOperation(name='selectChannels')
56 56 # #opObj10.addParameter(name='channelList', value='0,1', format='intlist')
57 57 # opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
@@ -59,53 +59,53 opObj11.addParameter(name='xmax', value='0.005', format='float')
59 59 # opObj11.addParameter(name='wintitle', value='SpectraPlot', format='str')
60 60 # #opObj11.addParameter(name='xaxis', value='Velocity', format='str')
61 61
62 #opObj11.addParameter(name='xaxis', value='velocity', format='str')
63 #opObj11.addParameter(name='xmin', value='-0.005', format='float')
64 #opObj11.addParameter(name='xmax', value='0.005', format='float')
62 # opObj11.addParameter(name='xaxis', value='velocity', format='str')
63 # opObj11.addParameter(name='xmin', value='-0.005', format='float')
64 # opObj11.addParameter(name='xmax', value='0.005', format='float')
65 65
66 #opObj11.addParameter(name='ymin', value='225', format='float')
67 #opObj11.addParameter(name='ymax', value='3000', format='float')
66 # opObj11.addParameter(name='ymin', value='225', format='float')
67 # opObj11.addParameter(name='ymax', value='3000', format='float')
68 68 # opObj11.addParameter(name='zmin', value='-100', format='int')
69 69 # opObj11.addParameter(name='zmax', value='-65', format='int')
70 70
71 #opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other')
72 #opObj11.addParameter(name='id', value='10', format='int')
73 #opObj11.addParameter(name='wintitle', value='RTI', format='str')
71 # opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other')
72 # opObj11.addParameter(name='id', value='10', format='int')
73 # opObj11.addParameter(name='wintitle', value='RTI', format='str')
74 74 # opObj11.addParameter(name='ymin', value='0', format='float')
75 75 # opObj11.addParameter(name='ymax', value='4000', format='float')
76 ##opObj11.addParameter(name='zmin', value='-100', format='int')
77 ##opObj11.addParameter(name='zmax', value='-70', format='int')
76 # #opObj11.addParameter(name='zmin', value='-100', format='int')
77 # #opObj11.addParameter(name='zmax', value='-70', format='int')
78 78 # opObj11.addParameter(name='zmin', value='-90', format='int')
79 79 # opObj11.addParameter(name='zmax', value='-40', format='int')
80 #opObj11.addParameter(name='showprofile', value='1', format='int')
81 #opObj11.addParameter(name='timerange', value=str(2*60*60), format='int')
82
83 # opObj11 = procUnitConfObj1.addOperation(name='CrossSpectraPlot', optype='other')
84 # #procUnitConfObj1.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList')
85 # opObj11.addParameter(name='id', value='2005', format='int')
86 # opObj11.addParameter(name='wintitle', value='CrossSpectraPlot_ShortPulse', format='str')
87 # # opObj11.addParameter(name='exp_code', value='13', format='int')
88 # opObj11.addParameter(name='xaxis', value='Velocity', format='str')
89 # #opObj11.addParameter(name='xmin', value='-10', format='float')
90 # #opObj11.addParameter(name='xmax', value='10', format='float')
91 # #opObj11.addParameter(name='ymin', value='225', format='float')
92 # #opObj11.addParameter(name='ymax', value='3000', format='float')
93 # #opObj11.addParameter(name='phase_min', value='-4', format='int')
94 # #opObj11.addParameter(name='phase_max', value='4', format='int')
95
96 #procUnitConfObj2 = controllerObj.addProcUnit(datatype='CorrelationProc', inputId=procUnitConfObj1.getId())
97 #procUnitConfObj2.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList')
98
99 procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=readUnitConfObj.getId())
80 # opObj11.addParameter(name='showprofile', value='1', format='int')
81 # opObj11.addParameter(name='timerange', value=str(2*60*60), format='int')
82
83 opObj11 = procUnitConfObj1.addOperation(name='CrossSpectraPlot', optype='other')
84 procUnitConfObj1.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList')
85 opObj11.addParameter(name='id', value='2005', format='int')
86 opObj11.addParameter(name='wintitle', value='CrossSpectraPlot_ShortPulse', format='str')
87 # opObj11.addParameter(name='exp_code', value='13', format='int')
88 opObj11.addParameter(name='xaxis', value='Velocity', format='str')
89 #opObj11.addParameter(name='xmin', value='-10', format='float')
90 #opObj11.addParameter(name='xmax', value='10', format='float')
91 #opObj11.addParameter(name='ymin', value='225', format='float')
92 #opObj11.addParameter(name='ymax', value='3000', format='float')
93 #opObj11.addParameter(name='phase_min', value='-4', format='int')
94 #opObj11.addParameter(name='phase_max', value='4', format='int')
95
96 # procUnitConfObj2 = controllerObj.addProcUnit(datatype='CorrelationProc', inputId=procUnitConfObj1.getId())
97 # procUnitConfObj2.addParameter(name='pairsList', value='(0,1),(0,2),(1,2)', format='pairsList')
98
99 procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=procUnitConfObj1.getId())
100 100 opObj11 = procUnitConfObj2.addOperation(name='SpectralMoments', optype='other')
101 101 opObj22 = procUnitConfObj2.addOperation(name='FullSpectralAnalysis', optype='other')
102
102 #
103 103 opObj22 = procUnitConfObj2.addOperation(name='WindProfilerPlot', optype='other')
104 104 opObj22.addParameter(name='id', value='4', format='int')
105 105 opObj22.addParameter(name='wintitle', value='Wind Profiler', format='str')
106 106 opObj22.addParameter(name='save', value='1', format='bool')
107 107 # opObj22.addParameter(name='figpath', value = '/home/erick/Pictures', format='str')
108
108
109 109 opObj22.addParameter(name='zmin', value='-20', format='int')
110 110 opObj22.addParameter(name='zmax', value='20', format='int')
111 111 opObj22.addParameter(name='zmin_ver', value='-250', format='float')
@@ -115,29 +115,32 opObj22.addParameter(name='SNRmax', value='30', format='int')
115 115 # opObj22.addParameter(name='SNRthresh', value='-3.5', format='float')
116 116 opObj22.addParameter(name='xmin', value=0, format='float')
117 117 opObj22.addParameter(name='xmax', value=24, format='float')
118 #opObj22.addParameter(name='ymin', value='225', format='float')
118 opObj22.addParameter(name='ymin', value='225', format='float')
119 119 #opObj22.addParameter(name='ymax', value='2000', format='float')
120
121
122 # opObj11.addParameter(name='pairlist', value='(1,0),(0,2),(1,2)', format='pairsList')
123 #opObj10 = procUnitConfObj1.addOperation(name='selectHeights')
124 #opObj10.addParameter(name='minHei', value='225', format='float')
125 #opObj10.addParameter(name='maxHei', value='1000', format='float')
126
127 # opObj11 = procUnitConfObj1.addOperation(name='CoherenceMap', optype='other')
128 # opObj11.addParameter(name='id', value='102', format='int')
129 # opObj11.addParameter(name='wintitle', value='Coherence', format='str')
130 # opObj11.addParameter(name='ymin', value='225', format='float')
131 # opObj11.addParameter(name='ymax', value='4000', format='float')
132
133 # opObj11.addParameter(name='phase_cmap', value='jet', format='str')
134 # opObj11.addParameter(name='xmin', value='8.5', format='float')
135 # opObj11.addParameter(name='xmax', value='9.5', format='float')
136 # opObj11.addParameter(name='figpath', value=figpath, format='str')
137 # opObj11.addParameter(name='save', value=1, format='bool')
138 # opObj11.addParameter(name='pairsList', value='(1,0),(3,2)', format='pairsList')
139
140 # opObj12 = procUnitConfObj1.addOperation(name='PublishData', optype='other')
141 # opObj12.addParameter(name='zeromq', value=1, format='int')
142 # opObj12.addParameter(name='verbose', value=0, format='bool')
143 # opObj12.addParameter(name='server', value='erick2', format='str')
144 controllerObj.start()
120 145
121 146
122 # # opObj11.addParameter(name='pairlist', value='(1,0),(0,2),(1,2)', format='pairsList')
123 # #opObj10 = procUnitConfObj1.addOperation(name='selectHeights')
124 # #opObj10.addParameter(name='minHei', value='225', format='float')
125 # #opObj10.addParameter(name='maxHei', value='1000', format='float')
126
127 #opObj11 = procUnitConfObj1.addOperation(name='CoherenceMap', optype='other')
128 #opObj11.addParameter(name='id', value='102', format='int')
129 #opObj11.addParameter(name='wintitle', value='Coherence', format='str')
130 #opObj11.addParameter(name='ymin', value='225', format='float')
131 #opObj11.addParameter(name='ymax', value='4000', format='float')
132
133 # # opObj11.addParameter(name='phase_cmap', value='jet', format='str')
134 # # opObj11.addParameter(name='xmin', value='8.5', format='float')
135 # # opObj11.addParameter(name='xmax', value='9.5', format='float')
136 # # opObj11.addParameter(name='figpath', value=figpath, format='str')
137 # # opObj11.addParameter(name='save', value=1, format='bool')
138 # # opObj11.addParameter(name='pairsList', value='(1,0),(3,2)', format='pairsList')
139
140
141 controllerObj.createObjects()
142 controllerObj.connectObjects()
143 controllerObj.run()
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@@ -17,9 +17,9 def main():
17 17 controllerObj.setup(id = '191', name='test01', description=desc)
18 18
19 19 readUnitConfObj = controllerObj.addReadUnit(datatype='Spectra',
20 path='../data/pdata/',
20 path='/home/erick/Documents/Data/d2015106',
21 21 startDate='2010/12/18',
22 endDate='2015/12/22',
22 endDate='2017/12/22',
23 23 startTime='00:00:00',
24 24 endTime='23:59:59',
25 25 online=0,
@@ -30,32 +30,70 def main():
30 30
31 31 opObj10 = procUnitConfObj1.addOperation(name='selectChannels')
32 32 opObj10.addParameter(name='channelList', value='0,1', format='intlist')
33
34 opObj10 = procUnitConfObj1.addOperation(name='selectHeights')
35 opObj10.addParameter(name='minHei', value='90', format='float')
36 opObj10.addParameter(name='maxHei', value='180', format='float')
33
34 #opObj10 = procUnitConfObj1.addOperation(name='selectHeights')
35 #opObj10.addParameter(name='minHei', value='90', format='float')
36 #opObj10.addParameter(name='maxHei', value='180', format='float')
37 37
38 38 opObj10 = procUnitConfObj1.addOperation(name='removeDC')
39 39
40 opObj12 = procUnitConfObj1.addOperation(name='IncohInt', optype='other')
41 opObj12.addParameter(name='n', value='1', format='int')
40 #opObj12 = procUnitConfObj1.addOperation(name='IncohInt', optype='other')
41 #opObj12.addParameter(name='n', value='1', format='int')
42 42
43 43 opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
44 44 opObj11.addParameter(name='id', value='1', format='int')
45 45 opObj11.addParameter(name='wintitle', value='SpectraPlot0', format='str')
46 opObj11.addParameter(name='xaxis', value='velocity', format='str')
46 47 opObj11.addParameter(name='showprofile', value='1', format='int')
47 opObj11.addParameter(name='save', value='0', format='int')
48 opObj11.addParameter(name='figpath', value='/Users/miguel/Data/JULIA/pdata/graphs')
49
50 opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other')
51 opObj11.addParameter(name='id', value='10', format='int')
52 opObj11.addParameter(name='wintitle', value='RTI', format='str')
48 opObj11.addParameter(name='save', value='1', format='int')
49 opObj11.addParameter(name='figpath', value='/home/erick/Documents/Data/d2015106')
50
51 #opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other')
52 #opObj11.addParameter(name='id', value='10', format='int')
53 #opObj11.addParameter(name='wintitle', value='RTI', format='str')
53 54 # opObj11.addParameter(name='xmin', value='21', format='float')
54 55 # opObj11.addParameter(name='xmax', value='22', format='float')
55 opObj11.addParameter(name='zmin', value='12', format='int')
56 opObj11.addParameter(name='zmax', value='32', format='int')
57 opObj11.addParameter(name='showprofile', value='1', format='int')
58 opObj11.addParameter(name='timerange', value=str(2*60*60), format='int')
56 #opObj11.addParameter(name='zmin', value='12', format='int')
57 #opObj11.addParameter(name='zmax', value='32', format='int')
58 #opObj11.addParameter(name='showprofile', value='1', format='int')
59 #opObj11.addParameter(name='timerange', value=str(2*60*60), format='int')
60
61 procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=readUnitConfObj.getId())
62 opObj11 = procUnitConfObj2.addOperation(name='GaussianFit', optype='other')
63 opObj11.addParameter(name='vel_arr', value='32,0,0,0', format='intList')
64 opObj11.addParameter(name='SNRlimit', value='-3', format='int')
65
66 #opObj12 = procUnitConfObj2.addOperation(name='ParametersPlot', optype='other')
67 #opObj12.addParameter(name='id',value='4',format='int')
68 #opObj12.addParameter(name='wintitle',value='First_gg',format='str')
69
70 opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other')
71 opObj11.addParameter(name='id', value='21', format='int')
72 opObj11.addParameter(name='wintitle', value='FitGauPlot', format='str')
73 opObj11.addParameter(name='xaxis', value='frequency', format='str')
74 opObj11.addParameter(name='showprofile', value='1', format='int')
75 opObj11.addParameter(name='zmin', value='-20', format='int')
76 opObj11.addParameter(name='zmax', value='20', format='int')
77 opObj11.addParameter(name='GauSelector', value='1', format='int')
78 #opObj11.addParameter(name='save', value='1', format='int')
79 #opObj11.addParameter(name='figpath', value='/home/erick/Documents/Data/d2015106')
80
81 opObj11 = procUnitConfObj2.addOperation(name='FitGauPlot', optype='other')
82 opObj11.addParameter(name='id', value='22', format='int')
83 opObj11.addParameter(name='wintitle', value='FitGauPlot', format='str')
84 opObj11.addParameter(name='xaxis', value='frequency', format='str')
85 opObj11.addParameter(name='showprofile', value='1', format='int')
86 opObj11.addParameter(name='zmin', value='-20', format='int')
87 opObj11.addParameter(name='zmax', value='20', format='int')
88 opObj11.addParameter(name='GauSelector', value='0', format='int')
89
90 #opObj11 = procUnitConfObj2.addOperation(name='SpectraPlot', optype='other')
91 #opObj11.addParameter(name='id', value='55', format='int')
92 #opObj11.addParameter(name='wintitle', value='SpectraPlot1', format='str')
93 #opObj11.addParameter(name='xaxis', value='velocity', format='str')
94 #opObj11.addParameter(name='showprofile', value='1', format='int')
95 #opObj11.addParameter(name='save', value='1', format='int')
96 #opObj11.addParameter(name='figpath', value='/home/erick/Documents/Data/d2015106')
59 97
60 98 controllerObj.start()
61 99
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@@ -14,26 +14,25 desc = "ProcBLTR Test"
14 14
15 15
16 16 filename = "ProcBLTR.xml"
17
17
18 18 controllerObj = Project()
19
20
19
20
21 21 controllerObj.setup(id = '191', name='test01', description=desc)
22
22
23 23 readUnitConfObj = controllerObj.addReadUnit(datatype='MIRA35CReader',
24 24 path='/home/erick/Documents/MIRA35C/20160117',
25 25 startDate='2016/11/8',
26 26 endDate='2017/10/19',
27 27 startTime='13:00:00',
28
28
29 29 endTime='23:59:59',
30
31
30
31
32 32 online=0,
33 walk=0,
34 ReadMode='1')
35 #expLabel='')
36
33 walk=0)
34
35
37 36 #opObj11 = readUnitConfObj.addOperation(name='printNumberOfBlock')
38 37
39 38 procUnitConfObj1 = controllerObj.addProcUnit(datatype='Spectra', inputId=readUnitConfObj.getId())
@@ -55,7 +54,7 opObj11 = procUnitConfObj1.addOperation(name='SpectraPlot', optype='other')
55 54 opObj11.addParameter(name='id', value='21', format='int')
56 55 opObj11.addParameter(name='wintitle', value='SpectraCutPlot', format='str')
57 56 opObj11.addParameter(name='xaxis', value='velocity', format='str')
58 opObj11.addParameter(name='colormap', value='winter', format='str')
57 opObj11.addParameter(name='colormap', value='nipy_spectral', format='str')
59 58 opObj11.addParameter(name='normFactor', value='1', format='float')
60 59 #opObj11.addParameter(name='xaxis', value='velocity', format='str')
61 60 #opObj11.addParameter(name='xmin', value='-1.', format='float')
@@ -67,7 +66,6 opObj11.addParameter(name='normFactor', value='1', format='float')
67 66 opObj11.addParameter(name='zmin', value='-20', format='int')
68 67 opObj11.addParameter(name='zmax', value='20', format='int')
69 68
70
71 69 opObj11 = procUnitConfObj1.addOperation(name='RTIPlot', optype='other')
72 70 opObj11.addParameter(name='id', value='10', format='int')
73 71 opObj11.addParameter(name='wintitle', value='RTI', format='str')
@@ -79,6 +77,8 opObj11.addParameter(name='normFactor', value='1', format='float')
79 77 #opObj11.addParameter(name='xmax', value='24', format='float')
80 78 opObj11.addParameter(name='zmin', value='-20', format='int')
81 79 opObj11.addParameter(name='zmax', value='20', format='int')
80 opObj11.addParameter(name='timerange', value='10800', format='int')
81 opObj11.addParameter(name='HEIGHT', value='400', format='int')
82 82 # opObj11.addParameter(name='zmin', value='-90', format='int')
83 83 # opObj11.addParameter(name='zmax', value='-40', format='int')
84 84 #opObj11.addParameter(name='showprofile', value='1', format='int')
@@ -87,27 +87,35 opObj11.addParameter(name='zmax', value='20', format='int')
87 87 procUnitConfObj2 = controllerObj.addProcUnit(datatype='Parameters', inputId=readUnitConfObj.getId())
88 88 #opObj11 = procUnitConfObj2.addOperation(name='SpectralMoments', optype='other')
89 89 opObj22 = procUnitConfObj2.addOperation(name='PrecipitationProc', optype='other')
90 opObj22.addParameter(name='radar', value='MIRA35C', format='str')
90 91
91 92 opObj22 = procUnitConfObj2.addOperation(name='ParametersPlot', optype='other')
92 93 opObj22.addParameter(name='id', value='4', format='int')
93 94 opObj22.addParameter(name='wintitle', value='PrecipitationProc', format='str')
94 95 opObj22.addParameter(name='save', value='1', format='bool')
95 opObj22.addParameter(name='colormap', value='jet', format='str')
96 opObj22.addParameter(name='colormap', value='nipy_spectral', format='str')
96 97 # opObj22.addParameter(name='figpath', value = '/home/erick/Pictures', format='str')
97 opObj22.addParameter(name='zmin', value='-70', format='int')
98 opObj22.addParameter(name='zmax', value='0', format='int')
98 opObj22.addParameter(name='zmin', value='-60', format='int')
99 opObj22.addParameter(name='zmax', value='-20', format='int')
100 opObj22.addParameter(name='timerange', value='10800', format='int')
101 #opObj22.addParameter(name='channelList', value='0', format='intlist')
102 #opObj22.addParameter(name='colormap', value='nipy_spectral', format='str')
103 opObj22.addParameter(name='HEIGHT', value='500', format='int')
99 104 #opObj22.addParameter(name='zmin_ver', value='-250', format='float')
100 105 #opObj22.addParameter(name='zmax_ver', value='250', format='float')
101 106 #opObj22.addParameter(name='SNRmin', value='-5', format='int')
102 107 #opObj22.addParameter(name='SNRmax', value='30', format='int')
103 108 # opObj22.addParameter(name='SNRthresh', value='-3.5', format='float')
104 opObj22.addParameter(name='xmin', value=0, format='float')
105 opObj22.addParameter(name='xmax', value=2, format='float')
109 #opObj22.addParameter(name='xmin', value=0, format='float')
110 #opObj22.addParameter(name='xmax', value=2, format='float')
106 111 #opObj22.addParameter(name='ymin', value='225', format='float')
107 112 #opObj22.addParameter(name='ymax', value='5000', format='float')
108 113
114 # opObj12 = procUnitConfObj1.addOperation(name='PublishData', optype='other')
115 # opObj12.addParameter(name='zeromq', value=1, format='int')
116 # opObj12.addParameter(name='verbose', value=0, format='bool')
117 # opObj12.addParameter(name='server', value='Jose', format='str')
109 118
110
111 controllerObj.createObjects()
112 controllerObj.connectObjects()
113 controllerObj.run()
119 #controllerObj.createObjects()
120 #controllerObj.connectObjects()
121 controllerObj.start()
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@@ -41,7 +41,7 setup(name="schainpy",
41 41 scripts=['schainpy/gui/schainGUI'],
42 42 ext_modules=[Extension("cSchain", ["schainpy/model/proc/extensions.c"])],
43 43 install_requires=[
44 "scipy >= 0.14.0",
44 "scipy >= 0.13.0",
45 45 "h5py >= 2.2.1",
46 46 "matplotlib >= 1.4.2",
47 47 "pyfits >= 3.4",
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