mirror of
https://github.com/wassname/simpeg.git
synced 2026-06-28 23:58:09 +08:00
GudniRos
417 lines
16 KiB
Python
417 lines
16 KiB
Python
from matplotlib import pyplot as plt, colors, numpy as np
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def rec2nd(structArray):
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""" Converts a structured/record array to ndarray to do operations on."""
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return structArray.view((np.float,len(structArray.dtype.names)))
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def plotIsoFreqNSimpedance(ax,freq,array,flag,par='abs',colorbar=True,colorNorm='SymLog',cLevel=True,contour=True):
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indUniFreq = np.where(freq==array['freq'])
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x, y = array['x'][indUniFreq],array['y'][indUniFreq]
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if par == 'abs':
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zPlot = np.abs(array[flag][indUniFreq])
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cmap = plt.get_cmap('OrRd_r')#seismic')
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level = np.logspace(0,-5,31)
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clevel = np.logspace(0,-4,5)
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plotNorm = colors.LogNorm()
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elif par == 'real':
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zPlot = np.real(array[flag][indUniFreq])
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cmap = plt.get_cmap('RdYlBu')
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if cLevel:
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level = np.concatenate((-np.logspace(0,-10,31),np.logspace(-10,0,31)))
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clevel = np.concatenate((-np.logspace(0,-8,5),np.logspace(-8,0,5)))
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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if colorNorm=='SymLog':
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plotNorm = colors.SymLogNorm(1e-10,linscale=2)
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else:
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plotNorm = colors.Normalize()
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elif par == 'imag':
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zPlot = np.imag(array[flag][indUniFreq])
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cmap = plt.get_cmap('RdYlBu')
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level = np.concatenate((-np.logspace(0,-10,31),np.logspace(-10,0,31)))
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clevel = np.concatenate((-np.logspace(0,-8,5),np.logspace(-8,0,5)))
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plotNorm = colors.SymLogNorm(1e-10,linscale=2)
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if cLevel:
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level = np.concatenate((-np.logspace(0,-10,31),np.logspace(-10,0,31)))
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clevel = np.concatenate((-np.logspace(0,-8,5),np.logspace(-8,0,5)))
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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if colorNorm=='SymLog':
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plotNorm = colors.SymLogNorm(1e-10,linscale=2)
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elif colorNorm=='Lin':
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plotNorm = colors.Normalize()
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if contour:
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cs = ax.tricontourf(x,y,zPlot,levels=level,cmap=cmap,norm=plotNorm)#,extend='both')
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else:
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uniX,uniY = np.unique(x),np.unique(y)
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X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
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cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),cmap=cmap,norm=plotNorm)
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if colorbar:
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plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
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ax.set_title(flag+' '+par,fontsize=8)
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return cs
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def plotIsoFreqNSDiff(ax,freq,arrayList,flag,par='abs',colorbar=True,cLevel=True,mask=None,contourLine=True,useLog=False):
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indUniFreq0 = np.where(freq==arrayList[0]['freq'])
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indUniFreq1 = np.where(freq==arrayList[1]['freq'])
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seicmap = plt.get_cmap('RdYlBu')#seismic')
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x, y = arrayList[0]['x'][indUniFreq0],arrayList[0]['y'][indUniFreq0]
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if par == 'abs':
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if useLog:
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zPlot = (np.log10(np.abs(arrayList[0][flag][indUniFreq0])) - np.log10(np.abs(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs(arrayList[1][flag][indUniFreq1]))
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else:
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zPlot = (np.abs(arrayList[0][flag][indUniFreq0]) - np.abs(arrayList[1][flag][indUniFreq1]))/np.abs(arrayList[1][flag][indUniFreq1])
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if mask:
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maskInd = np.logical_or(np.abs(arrayList[0][flag][indUniFreq0])< 1e-3,np.abs(arrayList[1][flag][indUniFreq1]) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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if cLevel:
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level = np.arange(-200,201,10)
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clevel = np.arange(-200,201,25)
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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elif par == 'real':
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if useLog:
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zPlot = (np.log10(np.real(arrayList[0][flag][indUniFreq0])) -np.log10(np.real(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.real(arrayList[1][flag][indUniFreq1]))))
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else:
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zPlot = (np.real(arrayList[0][flag][indUniFreq0]) -np.real(arrayList[1][flag][indUniFreq1]))/np.abs((np.real(arrayList[1][flag][indUniFreq1])))
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if mask:
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maskInd = np.logical_or(np.abs(np.real(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.real(arrayList[1][flag][indUniFreq1])) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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if cLevel:
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level = np.arange(-200,201,10)
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clevel = np.arange(-200,201,25)
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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elif par == 'imag':
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if useLog:
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zPlot = (np.log10(np.imag(arrayList[0][flag][indUniFreq0])) -np.log10(np.imag(arrayList[1][flag][indUniFreq1])))/np.log10(np.abs((np.imag(arrayList[1][flag][indUniFreq1]))))
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else:
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zPlot = (np.imag(arrayList[0][flag][indUniFreq0]) -np.imag(arrayList[1][flag][indUniFreq1]))/np.abs((np.imag(arrayList[1][flag][indUniFreq1])))
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if mask:
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maskInd = np.logical_or(np.abs(np.imag(arrayList[0][flag][indUniFreq0])) < 1e-3,np.abs(np.imag(arrayList[1][flag][indUniFreq1])) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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if cLevel:
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level = np.arange(-200,201,10)
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clevel = np.arange(-200,201,25)
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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cs = ax.tricontourf(x,y,zPlot*100,levels=level*100,cmap=seicmap,extend='both') #,norm=colors.SymLogNorm(1e-2,linscale=2))
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if contourLine:
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csl = ax.tricontour(x,y,zPlot*100,levels=clevel*100,colors='k')
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plt.clabel(csl, fontsize=7, inline=1,fmt='%1.1e',inline_spacing=10)
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if colorbar:
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cb = plt.colorbar(cs,cax=ax.cax,ticks=clevel*100,format='%1.1e')
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for t in cb.ax.get_yticklabels():
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t.set_rotation(60)
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t.set_fontsize(8)
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ax.set_title(flag+' '+par,fontsize=8)
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def plotIsoFreqNStipper(ax,freq,array,flag,par='abs',colorbar=True,colorNorm='SymLog',cLevel=True,contour=True):
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indUniFreq = np.where(freq==array['freq'])
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x, y = array['x'][indUniFreq],array['y'][indUniFreq]
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if par == 'abs':
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cmap = plt.get_cmap('OrRd_r')#seismic')
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zPlot = np.abs(array[flag][indUniFreq])
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if cLevel:
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level = np.logspace(-4,0,33)
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clevel = np.logspace(-4,0,5)
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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if colorNorm=='SymLog':
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plotNorm = colors.LogNorm()
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else:
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plotNorm = colors.Normalize()
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elif par == 'real':
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cmap = plt.get_cmap('RdYlBu')
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zPlot = np.real(array[flag][indUniFreq])
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if cLevel:
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level = np.concatenate((-np.logspace(0,-4,33),np.logspace(-4,0,33)))
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clevel = np.concatenate((-np.logspace(0,-4,5),np.logspace(-4,0,5)))
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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if colorNorm=='SymLog':
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plotNorm = colors.SymLogNorm(1e-4,linscale=2)
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else:
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plotNorm = colors.Normalize()
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elif par == 'imag':
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cmap = plt.get_cmap('RdYlBu')
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zPlot = np.imag(array[flag][indUniFreq])
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if cLevel:
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level = np.concatenate((-np.logspace(0,-4,33),np.logspace(-4,0,33)))
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clevel = np.concatenate((-np.logspace(0,-4,5),np.logspace(-4,0,5)))
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10)
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if colorNorm=='SymLog':
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plotNorm = colors.SymLogNorm(1e-4,linscale=2)
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else:
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plotNorm = colors.Normalize()
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if contour:
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cs = ax.tricontourf(x,y,zPlot,levels=level,cmap=cmap,norm=plotNorm)#,extend='both')
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else:
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uniX,uniY = np.unique(x),np.unique(y)
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X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
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cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),levels=level,cmap=cmap,norm=plotNorm,edgecolors='k', linewidths=0.5)
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if colorbar:
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plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
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ax.set_title(flag+' '+par,fontsize=8)
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def plotIsoStaImpedance(ax,loc,array,flag,par='abs',pSym='s',pColor=None):
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appResFact = 1/(8*np.pi**2*10**(-7))
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treshold = 1.0 # 1 meter
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indUniSta = np.sqrt(np.sum((rec2nd(array[['x','y']])-loc)**2,axis=1)) < treshold
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freq = array['freq'][indUniSta]
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if par == 'abs':
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zPlot = np.abs(array[flag][indUniSta])
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elif par == 'real':
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zPlot = np.real(array[flag][indUniSta])
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elif par == 'imag':
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zPlot = np.imag(array[flag][indUniSta])
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elif par == 'res':
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zPlot = (appResFact/freq)*np.abs(array[flag][indUniSta])**2
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elif par == 'phs':
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zPlot = np.arctan2(array[flag][indUniSta].imag,array[flag][indUniSta].real)*(180/np.pi)
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if not pColor:
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if 'xx' in flag:
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lab = 'XX'
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pColor = 'g'
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elif 'xy' in flag:
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lab = 'XY'
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pColor = 'r'
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elif 'yx' in flag:
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lab = 'YX'
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pColor = 'b'
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elif 'yy' in flag:
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lab = 'YY'
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pColor = 'y'
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ax.plot(freq,zPlot,color=pColor,marker=pSym,label=flag)
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def plotPsudoSectNSimpedance(ax,sectDict,array,flag,par='abs',colorbar=True,colorNorm='None',cLevel=None,contour=True):
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indSect = np.where(sectDict.values()[0]==array[sectDict.keys()[0]])
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# Define the plot axes
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if 'x' in sectDict.keys()[0]:
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x = array['y'][indSect]
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else:
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x = array['x'][indSect]
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y = array['freq'][indSect]
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if par == 'abs':
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zPlot = np.abs(array[flag][indSect])
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cmap = plt.get_cmap('OrRd_r')#seismic')
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if cLevel:
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level = np.logspace(0,-5,31,endpoint=True)
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clevel = np.logspace(0,-4,5,endpoint=True)
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else:
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level = np.linspace(zPlot.min(),zPlot.max(),100,endpoint=True)
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clevel = np.linspace(zPlot.min(),zPlot.max(),10,endpoint=True)
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elif par == 'ares':
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zPlot = np.abs(array[flag][indSect])**2/(8*np.pi**2*10**(-7)*array['freq'][indSect])
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cmap = plt.get_cmap('RdYlBu')#seismic)
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if cLevel:
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zMax = np.log10(cLevel[1])
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zMin = np.log10(cLevel[0])
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else:
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zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
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zMin = (np.floor(np.log10(np.abs(zPlot).min())))
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level = np.logspace(zMin,zMax,(zMax-zMin)*8+1,endpoint=True)
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clevel = np.logspace(zMin,zMax,(zMax-zMin)*2+1,endpoint=True)
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plotNorm = colors.LogNorm()
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elif par == 'aphs':
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zPlot = np.arctan2(array[flag][indSect].imag,array[flag][indSect].real)*(180/np.pi)
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cmap = plt.get_cmap('RdYlBu')#seismic)
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if cLevel:
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zMax = cLevel[1]
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zMin = cLevel[0]
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else:
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zMax = (np.ceil(zPlot).max())
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zMin = (np.floor(zPlot).min())
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level = np.arange(zMin,zMax+.1,1)
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clevel = np.arange(zMin,zMax+.1,10)
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plotNorm = colors.Normalize()
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elif par == 'real':
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zPlot = np.real(array[flag][indSect])
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cmap = plt.get_cmap('Spectral') #('RdYlBu')
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if cLevel:
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zMax = np.log10(cLevel[1])
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zMin = np.log10(cLevel[0])
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else:
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zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
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zMin = (np.floor(np.log10(np.abs(zPlot).min())))
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level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
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clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
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plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
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elif par == 'imag':
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zPlot = np.imag(array[flag][indSect])
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cmap = plt.get_cmap('Spectral') #('RdYlBu')
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if cLevel:
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zMax = np.log10(cLevel[1])
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zMin = np.log10(cLevel[0])
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else:
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zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
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zMin = (np.floor(np.log10(np.abs(zPlot).min())))
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level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
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clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
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plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
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if colorNorm=='SymLog':
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plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
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elif colorNorm=='Lin':
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plotNorm = colors.Normalize()
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elif colorNorm=='Log':
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plotNorm = colors.LogNorm()
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if contour:
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cs = ax.tricontourf(x,y,zPlot,levels=level,cmap=cmap,norm=plotNorm)#,extend='both')
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else:
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uniX,uniY = np.unique(x),np.unique(y)
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X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
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cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),cmap=cmap,norm=plotNorm)
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if colorbar:
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csB = plt.colorbar(cs,cax=ax.cax,ticks=clevel,format='%1.2e')
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# csB.on_mappable_changed(cs)
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ax.set_title(flag+' '+par,fontsize=8)
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return cs, csB
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return cs,None
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def plotPsudoSectNSDiff(ax,sectDict,arrayList,flag,par='abs',colorbar=True,colorNorm='SymLog',cLevel=None,contour=True,mask=None,useLog=False):
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def sortInArr(arr):
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return np.sort(arr,order=['freq','x','y','z'])
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# Find the index for the slice
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indSect0 = np.where(sectDict.values()[0]==arrayList[0][sectDict.keys()[0]])
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indSect1 = np.where(sectDict.values()[0]==arrayList[1][sectDict.keys()[0]])
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# Extract and sort the mats
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arr0 = sortInArr(arrayList[0][indSect0])
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arr1 = sortInArr(arrayList[1][indSect1])
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# Define the plot axes
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if 'x' in sectDict.keys()[0]:
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x0 = arr0['y']
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x1 = arr1['y']
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else:
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x0 = arr0['x']
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x1 = arr1['x']
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y0 = arr0['freq']
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y1 = arr1['freq']
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if par == 'abs':
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if useLog:
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zPlot = (np.log10(np.abs(arr0[flag])) - np.log10(np.abs(arr1[flag])))/np.log10(np.abs(arr1[flag]))
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else:
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zPlot = (np.abs(arr0[flag]) - np.abs(arr1[flag]))/np.abs(arr1[flag])
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if mask:
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maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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cmap = plt.get_cmap('RdYlBu')#seismic)
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elif par == 'ares':
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arF = 1/(8*np.pi**2*10**(-7))
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if useLog:
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zPlot = (np.log10((arF/arr0['freq'])*np.abs(arr0[flag])**2) - np.log10((arF/arr1['freq'])*np.abs(arr1[flag])**2))/np.log10((arF/arr1['freq'])*np.abs(arr1[flag])**2)
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else:
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zPlot = ((arF/arr0['freq'])*np.abs(arr0[flag])**2 - (arF/arr1['freq'])*np.abs(arr1[flag])**2)/((arF/arr1['freq'])*np.abs(arr1[flag])**2)
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if mask:
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maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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cmap = plt.get_cmap('Spectral')#seismic)
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|
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elif par == 'aphs':
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if useLog:
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zPlot = (np.log10(np.arctan2(arr0[flag].imag,arr0[flag].real)*(180/np.pi)) - np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi)) )/np.log10(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi))
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else:
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zPlot = ( np.arctan2(arr0[flag].imag,arr0[flag].real)*(180/np.pi) - np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi) )/(np.arctan2(arr1[flag].imag,arr1[flag].real)*(180/np.pi))
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if mask:
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maskInd = np.logical_or(np.abs(arr0[flag])< 1e-3,np.abs(arr1[flag]) < 1e-3)
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zPlot = np.ma.array(zPlot)
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zPlot[maskInd] = mask
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cmap = plt.get_cmap('Spectral')#seismic)
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elif par == 'real':
|
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if useLog:
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zPlot = (np.log10(arr0[flag].real) - np.log10(arr1[flag].real))/np.log10(arr1[flag].real)
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else:
|
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zPlot = (arr0[flag].real - arr1[flag].real)/arr1[flag].real
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if mask:
|
|
maskInd = np.logical_or(arr0[flag].real< 1e-3,arr1[flag].real < 1e-3)
|
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zPlot = np.ma.array(zPlot)
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|
zPlot[maskInd] = mask
|
|
cmap = plt.get_cmap('Spectral') #('Spectral')
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|
|
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elif par == 'imag':
|
|
if useLog:
|
|
zPlot = (np.log10(arr0[flag].imag) - np.log10(arr1[flag].imag))/np.log10(arr1[flag].imag)
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else:
|
|
zPlot = (arr0[flag].imag - arr1[flag].imag)/arr1[flag].imag
|
|
if mask:
|
|
maskInd = np.logical_or(arr0[flag].imag< 1e-3,arr1[flag].imag < 1e-3)
|
|
zPlot = np.ma.array(zPlot)
|
|
zPlot[maskInd] = mask
|
|
cmap = plt.get_cmap('Spectral') #('RdYlBu')
|
|
|
|
if cLevel:
|
|
zMax = np.log10(cLevel[1])
|
|
zMin = np.log10(cLevel[0])
|
|
else:
|
|
zMax = (np.ceil(np.log10(np.abs(zPlot).max())))
|
|
zMin = (np.floor(np.log10(np.abs(zPlot).min())))
|
|
|
|
|
|
if colorNorm=='SymLog':
|
|
level = np.concatenate((-np.logspace(zMax,zMin-.125,(zMax-zMin)*8+1,endpoint=True),np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)))
|
|
clevel = np.concatenate((-np.logspace(zMax,zMin,(zMax-zMin)*1+1,endpoint=True),np.logspace(zMin,zMax,(zMax-zMin)*1+1,endpoint=True)))
|
|
plotNorm = colors.SymLogNorm(np.abs(level).min(),linscale=0.1)
|
|
elif colorNorm=='Lin':
|
|
if cLevel:
|
|
level = np.arange(cLevel[0],cLevel[1]+.1,(cLevel[1] - cLevel[0])/50.)
|
|
clevel = np.arange(cLevel[0],cLevel[1]+.1,(cLevel[1] - cLevel[0])/10.)
|
|
else:
|
|
level = np.arange(zPlot.min(),zPlot.max(),(zPlot.max() - zPlot.min())/50.)
|
|
clevel = np.arange(zPlot.min(),zPlot.max(),(zPlot.max() - zPlot.min())/10.)
|
|
plotNorm = colors.Normalize()
|
|
elif colorNorm=='Log':
|
|
level = np.logspace(zMin-.125,zMax,(zMax-zMin)*8+1,endpoint=True)
|
|
clevel = np.logspace(zMin,zMax,(zMax-zMin)*2+1,endpoint=True)
|
|
plotNorm = colors.LogNorm()
|
|
if contour:
|
|
cs = ax.tricontourf(x0,y0,zPlot*100,levels=level*100,cmap=cmap,norm=plotNorm,extend='both')#,extend='both')
|
|
else:
|
|
uniX,uniY = np.unique(x0),np.unique(y0)
|
|
X,Y = np.meshgrid(np.append(uniX-25,uniX[-1]+25),np.append(uniY-25,uniY[-1]+25))
|
|
cs = ax.pcolor(X,Y,np.reshape(zPlot,(len(uniY),len(uniX))),cmap=cmap,norm=plotNorm)
|
|
if colorbar:
|
|
csB = plt.colorbar(cs,cax=ax.cax,ticks=clevel*100,format='%1.2e')
|
|
# csB.on_mappable_changed(cs)
|
|
ax.set_title(flag+' '+par + ' diff',fontsize=8)
|
|
return cs, csB
|
|
return cs,None
|