@@ -160,7 +160,7 class CorrelationPlot(Figure): | |||
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160 | 160 | |
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161 | 161 | for i in range(self.nplots): |
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162 | 162 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
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163 |
title = "Channel %d and %d: : %s" %(dataOut.pairsList[i][0] |
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163 | title = "Channel %d and %d: : %s" %(dataOut.pairsList[i][0],dataOut.pairsList[i][1] , str_datetime) | |
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164 | 164 | axes = self.axesList[i*self.__nsubplots] |
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165 | 165 | axes.pcolor(x, y, zdB[i,:,:], |
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166 | 166 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
@@ -159,7 +159,7 class MomentsPlot(Figure): | |||
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159 | 159 | |
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160 | 160 | for i in range(self.nplots): |
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161 | 161 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
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162 |
title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i] |
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162 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime) | |
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163 | 163 | axes = self.axesList[i*self.__nsubplots] |
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164 | 164 | axes.pcolor(x, y, zdB[i,:,:], |
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165 | 165 | xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax, zmin=zmin, zmax=zmax, |
@@ -759,7 +759,7 class ParametersPlot(Figure): | |||
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759 | 759 | ticksize=9, cblabel=zlabel, cbsize="1%") |
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760 | 760 | |
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761 | 761 | if DOP: |
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762 |
title = "%s Channel %d: %s" %(parameterName, channelIndexList[i] |
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762 | title = "%s Channel %d: %s" %(parameterName, channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
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763 | 763 | |
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764 | 764 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
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765 | 765 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
@@ -771,7 +771,7 class ParametersPlot(Figure): | |||
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771 | 771 | ticksize=9, cblabel=zlabel, cbsize="1%") |
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772 | 772 | |
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773 | 773 | if SNR: |
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774 |
title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i] |
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774 | title = "Channel %d Signal Noise Ratio (SNR): %s" %(channelIndexList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
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775 | 775 | axes = self.axesList[(j)*self.__nsubplots] |
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776 | 776 | if not onlySNR: |
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777 | 777 | axes = self.axesList[(j + 1)*self.__nsubplots] |
@@ -951,7 +951,7 class SpectralFittingPlot(Figure): | |||
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951 | 951 | self.setWinTitle(title) |
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952 | 952 | for i in range(self.nplots): |
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953 | 953 | # title = "Channel %d: %4.2fdB" %(dataOut.channelList[i]+1, noisedB[i]) |
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954 |
title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i] |
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954 | title = "Height %4.1f km\nChannel %d:" %(cutHeight, listChannels[i]) | |
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955 | 955 | axes = self.axesList[i*self.__nsubplots] |
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956 | 956 | if fit == False: |
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957 | 957 | axes.pline(x, zdB[i,:], |
@@ -168,7 +168,7 class SpectraPlot(Figure): | |||
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168 | 168 | |
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169 | 169 | for i in range(self.nplots): |
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170 | 170 | str_datetime = '%s %s'%(thisDatetime.strftime("%Y/%m/%d"),thisDatetime.strftime("%H:%M:%S")) |
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171 |
title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i] |
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171 | title = "Channel %d: %4.2fdB: %s" %(dataOut.channelList[i], noisedB[i], str_datetime) | |
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172 | 172 | if len(dataOut.beam.codeList) != 0: |
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173 | 173 | title = "Ch%d:%4.2fdB,%2.2f,%2.2f:%s" %(dataOut.channelList[i]+1, noisedB[i], dataOut.beam.azimuthList[i], dataOut.beam.zenithList[i], str_datetime) |
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174 | 174 | |
@@ -575,7 +575,7 class RTIPlot(Figure): | |||
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575 | 575 | x[1] = self.xmax |
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576 | 576 | |
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577 | 577 | for i in range(self.nplots): |
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578 |
title = "Channel %d: %s" %(dataOut.channelList[i] |
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578 | title = "Channel %d: %s" %(dataOut.channelList[i], thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) | |
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579 | 579 | if ((dataOut.azimuth!=None) and (dataOut.zenith!=None)): |
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580 | 580 | title = title + '_' + 'azimuth,zenith=%2.2f,%2.2f'%(dataOut.azimuth, dataOut.zenith) |
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581 | 581 | axes = self.axesList[i*self.__nsubplots] |
@@ -1088,7 +1088,7 class Noise(Figure): | |||
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1088 | 1088 | |
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1089 | 1089 | title = "Noise %s" %(thisDatetime.strftime("%Y/%m/%d %H:%M:%S")) |
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1090 | 1090 | |
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1091 |
legendlabels = ["channel %d"%(idchannel |
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1091 | legendlabels = ["channel %d"%(idchannel) for idchannel in channelList] | |
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1092 | 1092 | axes = self.axesList[0] |
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1093 | 1093 | |
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1094 | 1094 | self.xdata = numpy.hstack((self.xdata, x[0:1])) |
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