# Utils used for the data, import numpy as np, matplotlib.pyplot as plt, sys import SimPEG as simpeg import simpegMT as simpegmt import numpy.lib.recfunctions as recFunc def getAppRes(MTdata): # Make impedance zList = [] for src in MTdata.survey.srcList: zc = [src.freq] for rx in src.rxList: if 'i' in rx.rxType: m=1j else: m = 1 zc.append(m*MTdata[src,rx]) zList.append(zc) return [appResPhs(zList[i][0],np.sum(zList[i][1:3])) for i in np.arange(len(zList))] def appResPhs(freq,z): app_res = ((1./(8e-7*np.pi**2))/freq)*np.abs(z)**2 app_phs = np.arctan2(z.imag,z.real)*(180/np.pi) return app_res, app_phs def rec2ndarr(x,dt=float): return x.view((dt, len(x.dtype.names))) def makeAnalyticSolution(mesh,model,elev,freqs): data1D = [] for freq in freqs: anaEd, anaEu, anaHd, anaHu = simpegmt.Utils.MT1Danalytic.getEHfields(mesh,model,freq,elev) anaE = anaEd+anaEu anaH = anaHd+anaHu anaZ = anaE/anaH # Add to the list data1D.append((freq,0,0,elev,anaZ[0])) dataRec = np.array(data1D,dtype=[('freq',float),('x',float),('y',float),('z',float),('zyx',complex)]) return dataRec def plotMT1DModelData(problem,models,symList=None): # Setup the figure fontSize = 15 fig = plt.figure(figsize=[9,7]) axM = fig.add_axes([0.075,.1,.25,.875]) axM.set_xlabel('Resistivity [Ohm*m]',fontsize=fontSize) axM.set_xlim(1e-1,1e5) axM.set_ylim(-10000,5000) axM.set_ylabel('Depth [km]',fontsize=fontSize) axR = fig.add_axes([0.42,.575,.5,.4]) axR.set_xscale('log') axR.set_yscale('log') axR.invert_xaxis() # axR.set_xlabel('Frequency [Hz]') axR.set_ylabel('Apparent resistivity [Ohm m]',fontsize=fontSize) axP = fig.add_axes([0.42,.1,.5,.4]) axP.set_xscale('log') axP.invert_xaxis() axP.set_ylim(0,90) axP.set_xlabel('Frequency [Hz]',fontsize=fontSize) axP.set_ylabel('Apparent phase [deg]',fontsize=fontSize) # if not symList: # symList = ['x']*len(models) import plotDataTypes as pDt # Loop through the models. modelList = [problem.survey.mtrue] modelList.extend(models) if False: modelList = [problem.mapping.sigmaMap*mod for mod in modelList] for nr, model in enumerate(modelList): # Calculate the data if nr==0: data1D = problem.dataPair(problem.survey,problem.survey.dobs).toRecArray('Complex') else: data1D = problem.dataPair(problem.survey,problem.survey.dpred(model)).toRecArray('Complex') # Plot the data and the model colRat = nr/((len(modelList)-1.999)*1.) if colRat > 1.: col = 'k' else: col = plt.cm.seismic(1-colRat) # The model - make the pts to plot meshPts = np.concatenate((problem.mesh.gridN[0:1],np.kron(problem.mesh.gridN[1::],np.ones(2))[:-1])) modelPts = np.kron(1./(problem.mapping.sigmaMap*model),np.ones(2,)) axM.semilogx(modelPts,meshPts,color=col) ## Data # Appres pDt.plotIsoStaImpedance(axR,np.array([0,0]),data1D,'zyx','res',pColor=col) # Appphs pDt.plotIsoStaImpedance(axP,np.array([0,0]),data1D,'zyx','phs',pColor=col) try: allData = np.concatenate((allData,simpeg.mkvc(data1D['zyx'],2)),1) except: allData = simpeg.mkvc(data1D['zyx'],2) freq = simpeg.mkvc(data1D['freq'],2) res, phs = appResPhs(freq,allData) stdCol = 'gray' axRtw = axR.twinx() axRtw.set_ylabel('Std of log10',color=stdCol) [(t.set_color(stdCol), t.set_rotation(-45)) for t in axRtw.get_yticklabels()] axPtw = axP.twinx() axPtw.set_ylabel('Std ',color=stdCol) [t.set_color(stdCol) for t in axPtw.get_yticklabels()] axRtw.plot(freq, np.std(np.log10(res),1),'--',color=stdCol) axPtw.plot(freq, np.std(phs,1),'--',color=stdCol) # Fix labels and ticks yMtick = [l/1000 for l in axM.get_yticks().tolist()] axM.set_yticklabels(yMtick) [ l.set_rotation(90) for l in axM.get_yticklabels()] [ l.set_rotation(90) for l in axR.get_yticklabels()] [(t.set_color(stdCol), t.set_rotation(-45)) for t in axRtw.get_yticklabels()] [t.set_color(stdCol) for t in axPtw.get_yticklabels()] for ax in [axM,axR,axP]: ax.xaxis.set_tick_params(labelsize=fontSize) ax.yaxis.set_tick_params(labelsize=fontSize) return fig def printTime(): import time print time.strftime("%a, %d %b %Y %H:%M:%S +0000", time.localtime()) def convert3Dto1Dobject(MTdata,rxType3D='zyx'): # Find the unique locations # Need to find the locations recDataTemp = MTdata.toRecArray() # Check if survey.std has been assigned. ## NEED TO: write this... # Calculte and add the DET of the tensor to the recArray if 'det' in rxType3D: Zon = (recDataTemp['zxxr']+1j*recDataTemp['zxxi'])*(recDataTemp['zyyr']+1j*recDataTemp['zyyi']) Zoff = (recDataTemp['zxyr']+1j*recDataTemp['zxyi'])*(recDataTemp['zyxr']+1j*recDataTemp['zyxi']) det = np.sqrt(Zon.data - Zoff.data) recData = recFunc.append_fields(recDataTemp,['zdetr','zdeti'],[det.real,det.imag] ) else: recData = recDataTemp uniLocs = rec2ndarr(np.unique(recData[['x','y','z']])).data mtData1DList = [] if 'zxy' in rxType3D: corr = -1 # Shift the data to comply with the quadtrature of the 1d problem else: corr = 1 for loc in uniLocs: # Make the receiver list rx1DList = [] for rxType in ['z1dr','z1di']: rx1DList.append(simpegmt.SurveyMT.RxMT(simpeg.mkvc(loc,2).T,rxType)) # Source list locrecData = recData[np.sqrt(np.sum( (rec2ndarr(recData[['x','y','z']]).data - loc )**2,axis=1)) < 1e-5] dat1DList = [] src1DList = [] for freq in locrecData['freq']: src1DList.append(simpegmt.SurveyMT.srcMT_polxy_1Dprimary(rx1DList,freq)) for comp in ['r','i']: dat1DList.append( corr * locrecData[rxType3D+comp][locrecData['freq']== freq].data ) # Make the survey sur1D = simpegmt.SurveyMT.SurveyMT(src1DList) # Make the data dataVec = np.hstack(dat1DList) dat1D = simpegmt.DataMT.DataMT(sur1D,dataVec) sur1D.dobs = dataVec # Need to take MTdata.survey.std and split it as well. std=0.05 sur1D.std = np.abs(sur1D.dobs*std) #+ 0.01*np.linalg.norm(sur1D.dobs) mtData1DList.append(dat1D) # Return the the list of data. return mtData1DList