Console Output
+ diff --exclude=.git --exclude=version_clubb_core.txt --exclude=version_silhs.txt -r clubb clubb_release
diff '--exclude=.git' '--exclude=version_clubb_core.txt' '--exclude=version_silhs.txt' -r clubb/utilities/sens_matrix/create_figs.py clubb_release/utilities/sens_matrix/create_figs.py
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< # Remove selected metrics from plots
< maskMetricsNames = (metricsNames == 'PRECT_GLB') | (metricsNames == 'LWCF_GLB') \
< | (metricsNames == 'SWCF_LBA') | (metricsNames == 'SWCF_EP') \
< | (metricsNames == 'SWCF_WP') | (metricsNames == 'SWCF_NP') \
< | (metricsNames == 'SWCF_VOCAL') | (metricsNames == 'SWCF_HAWAII') \
< | (metricsNames == 'SWCF_SP') | (metricsNames == 'SWCF_GLB')
<
< maskParamsNames = (paramsNames == 'clubb_c_k10') | (paramsNames == 'clubb_altitude_threshold') \
< | (paramsNames == 'clubb_c_invrs_tau_shear') | (paramsNames == 'clubb_c_invrs_tau_bkgnd') \
< | (paramsNames == 'clubb_c_invrs_tau_n2_wp2') | (paramsNames == 'clubb_c_invrs_tau_n2_wp2') \
< | (paramsNames == 'clubb_c_invrs_tau_n2')
<
< maskMetricsParamsNames = np.outer(maskMetricsNames,maskParamsNames)
<
< # #maskMetricsNames = np.logical_not(maskMetricsNames) # get rid of named elements
< # Apply mask
< metricsNamesMasked = np.ma.masked_array(metricsNames, maskMetricsNames).compressed()
< paramsNamesMasked = np.ma.masked_array(paramsNames, maskParamsNames).compressed()
< # normMetricValsColMasked = np.ma.masked_array(normMetricValsCol, maskMetricsNames).compressed()
< # normMetricValsColMasked = normMetricValsColMasked[np.newaxis].T # turn into column array
< # defaultBiasesColMasked = np.ma.masked_array(defaultBiasesCol, maskMetricsNames).compressed()
< # defaultBiasesColMasked = defaultBiasesColMasked[np.newaxis].T
< normMetricValsColMasked = normMetricValsCol[~maskMetricsNames]
< defaultBiasesColMasked = defaultBiasesCol[~maskMetricsNames]
< normlzdSensMatrixPolyMasked = normlzdSensMatrixPoly[~maskMetricsNames].T[~maskParamsNames].T
< normlzdLinplusSensMatrixPolyMasked = normlzdLinplusSensMatrixPoly[~maskMetricsNames].T[~maskParamsNames].T
<
< metricsWeightsMasked = metricsWeights[~maskMetricsNames]
<
< obsMetricValsColMasked = obsMetricValsCol[~maskMetricsNames]
< normlzdCurvMatrixMasked = normlzdCurvMatrix[~maskMetricsNames].T[~maskParamsNames].T
< normlzdConstMatrixMasked = normlzdConstMatrix[~maskMetricsNames].T[~maskParamsNames].T
< normlzdOrdDparamsMinMasked = normlzdOrdDparamsMin[~maskMetricsNames].T[~maskParamsNames].T
< normlzdOrdDparamsMaxMasked = normlzdOrdDparamsMax[~maskMetricsNames].T[~maskParamsNames].T
<
< magParamValsRowMasked = magParamValsRow.T[~maskParamsNames].T
<
< sensNcFilenamesMasked = np.ma.masked_array(sensNcFilenames, maskParamsNames).compressed()
< sensNcFilenamesExtMasked = np.ma.masked_array(sensNcFilenamesExt, maskParamsNames).compressed()
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< # threeDotFig = \
< # createThreeDotFig(metricsNames, paramsNames, transformedParamsNames,
< # metricsWeights, obsMetricValsCol, normMetricValsCol, magParamValsRow,
< # normlzdCurvMatrix, normlzdSensMatrixPoly, normlzdConstMatrix,
< # normlzdOrdDparamsMin, normlzdOrdDparamsMax,
< # sensNcFilenames, sensNcFilenamesExt, defaultNcFilename)
<
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< createThreeDotFig(metricsNamesMasked, paramsNamesMasked, transformedParamsNames,
< metricsWeightsMasked, obsMetricValsColMasked, normMetricValsColMasked, magParamValsRowMasked,
< normlzdCurvMatrixMasked, normlzdSensMatrixPolyMasked, normlzdConstMatrixMasked,
< normlzdOrdDparamsMinMasked, normlzdOrdDparamsMaxMasked,
< sensNcFilenamesMasked, sensNcFilenamesExtMasked, defaultNcFilename)
---
> createThreeDotFig(metricsNames, paramsNames, transformedParamsNames,
> metricsWeights, obsMetricValsCol, normMetricValsCol, magParamValsRow,
> normlzdCurvMatrix, normlzdSensMatrixPoly, normlzdConstMatrix,
> normlzdOrdDparamsMin, normlzdOrdDparamsMax,
> sensNcFilenames, sensNcFilenamesExt, defaultNcFilename)
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<
<
---
> maskMetricsNames = np.logical_or(metricsNames[:] == 'PRECT_GLB', metricsNames[:] == 'LWCF_GLB')
> # #maskMetricsNames = np.logical_not(maskMetricsNames) # get rid of named elements
> # Apply mask
> metricsNamesMasked = np.ma.masked_array(metricsNames, maskMetricsNames).compressed()
> # normMetricValsColMasked = np.ma.masked_array(normMetricValsCol, maskMetricsNames).compressed()
> # normMetricValsColMasked = normMetricValsColMasked[np.newaxis].T # turn into column array
> # defaultBiasesColMasked = np.ma.masked_array(defaultBiasesCol, maskMetricsNames).compressed()
> # defaultBiasesColMasked = defaultBiasesColMasked[np.newaxis].T
> normMetricValsColMasked = normMetricValsCol[~maskMetricsNames]
> defaultBiasesColMasked = defaultBiasesCol[~maskMetricsNames]
> normlzdSensMatrixPolyMasked = normlzdSensMatrixPoly[~maskMetricsNames]
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< createDpMin2PtFig( normlzdLinplusSensMatrixPolyMasked, defaultBiasesColMasked,
---
> createDpMin2PtFig( normlzdSensMatrixPolyMasked, defaultBiasesColMasked,
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< metricsWeights, obsMetricValsCol, normMetricValsCol, magParamValsRow,
< normlzdCurvMatrix, normlzdSensMatrixPoly, normlzdConstMatrix,
< normlzdOrdDparamsMin, normlzdOrdDparamsMax,
< sens1NcFilenames, sens2NcFilenames, defaultNcFilename):
---
> metricsWeights, obsMetricValsCol, normMetricValsCol, magParamValsRow,
> normlzdCurvMatrix, normlzdSensMatrixPoly, normlzdConstMatrix,
> normlzdOrdDparamsMin, normlzdOrdDparamsMax,
> sens1NcFilenames, sens2NcFilenames, defaultNcFilename):
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< # if ( len(paramsNames) != len(sens1NcFilenames) ):
< # print("Number of parameters must equal number of netcdf files.")
< # quit()
---
> if ( len(paramsNames) != len(sens1NcFilenames) ):
> print("Number of parameters must equal number of netcdf files.")
> quit()
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< marker=dict(color='black', size=16)),
---
> marker=dict(color='black', size=5)),
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< line=dict(color='blue', width=4)),
---
> line=dict(color='blue', width=2)),
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< line=dict(color='red', width=4)),
---
> line=dict(color='red', width=2)),
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< title_font_size=36,
< #font=dict(size=50),
---
> #title_font_size=8,
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< title_font_size=36
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< threeDotFig.update_yaxes(title_text=metricsNames[arrayRow], row=arrayRow+1, col=arrayCol+1,
< title_font_size=36)
---
> threeDotFig.update_yaxes(title_text=metricsNames[arrayRow], row=arrayRow+1, col=arrayCol+1)
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< title_text='Minimum size of parameter perturbation between 2 metrics',
---
> title_text='dpMin between 2 metrics (i.e., rows of sens matrix)',
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