| @@ -11,6 +11,13 import numpy | |||
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11 | 11 | |
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12 | 12 | from schainpy.model.graphics.jroplot_base import Plot, plt, log |
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13 | 13 | |
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14 | from matplotlib import __version__ as plt_version | |
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15 | ||
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16 | if plt_version >='3.3.4': | |
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17 | EXTRA_POINTS = 0 | |
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18 | else: | |
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19 | EXTRA_POINTS = 1 | |
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20 | ||
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14 | 21 | |
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15 | 22 | class SpectraPlot(Plot): |
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16 | 23 | ''' |
| @@ -51,7 +58,7 class SpectraPlot(Plot): | |||
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51 | 58 | data['noise'] = 10 * numpy.log10(dataOut.getNoise() / dataOut.normFactor) |
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52 | 59 |
extrapoints = spc.shape[1] % dataOut.nFFTPoints |
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53 | 60 |
extrapoints=1 |
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54 |
meta['xrange'] = (dataOut.getFreqRange( |
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61 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
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55 | 62 | if self.CODE == 'spc_moments': |
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56 | 63 | data['moments'] = dataOut.moments |
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57 | 64 | if self.CODE == 'gaussian_fit': |
| @@ -161,7 +168,7 class SpectraObliquePlot(Plot): | |||
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161 | 168 | data['spc'] = spc |
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162 | 169 | data['rti'] = dataOut.getPower() |
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163 | 170 | data['noise'] = 10*numpy.log10(dataOut.getNoise()/dataOut.normFactor) |
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164 |
meta['xrange'] = (dataOut.getFreqRange( |
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171 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
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165 | 172 | |
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166 | 173 | data['shift1'] = dataOut.Dop_EEJ_T1[0] |
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167 | 174 | data['shift2'] = dataOut.Dop_EEJ_T2[0] |
| @@ -261,7 +268,7 class CrossSpectraPlot(Plot): | |||
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261 | 268 | spc = dataOut.data_spc |
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262 | 269 | cspc = dataOut.data_cspc |
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263 | 270 | extrapoints = spc.shape[1] % dataOut.nFFTPoints |
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264 |
meta['xrange'] = (dataOut.getFreqRange( |
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271 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
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265 | 272 | meta['pairs'] = dataOut.pairsList |
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266 | 273 | |
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267 | 274 | tmp = [] |
| @@ -765,7 +772,7 class SpectrogramPlot(Plot): | |||
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765 | 772 | z = numpy.where(numpy.isfinite(z), z, numpy.NAN) |
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766 | 773 | #buffer = 10 * numpy.log10(z) |
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767 | 774 | |
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768 |
meta['xrange'] = (dataOut.getFreqRange( |
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775 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS)/1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
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769 | 776 | |
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770 | 777 | |
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771 | 778 | #self.hei = hei |
| @@ -999,7 +1006,7 class SpectraCutPlot(Plot): | |||
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999 | 1006 | meta = {} |
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1000 | 1007 | spc = 10 * numpy.log10(dataOut.data_pre[0] / dataOut.normFactor) |
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1001 | 1008 | data['spc'] = spc |
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1002 |
meta['xrange'] = (dataOut.getFreqRange( |
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1009 | meta['xrange'] = (dataOut.getFreqRange(EXTRA_POINTS) / 1000., dataOut.getAcfRange(EXTRA_POINTS), dataOut.getVelRange(EXTRA_POINTS)) | |
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1003 | 1010 | if self.CODE == 'cut_gaussian_fit': |
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1004 | 1011 | data['gauss_fit0'] = 10 * numpy.log10(dataOut.GaussFit0 / dataOut.normFactor) |
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1005 | 1012 | data['gauss_fit1'] = 10 * numpy.log10(dataOut.GaussFit1 / dataOut.normFactor) |
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