def run(self, m0): """run(m0) Runs the inversion! """ self.invProb.startup(m0) self.directiveList.call('initialize') print('curModel has any nan: {:b}'.format(np.any(np.isnan(self.invProb.curModel)))) self.m = self.opt.minimize(self.invProb.evalFunction, self.invProb.curModel) self.directiveList.call('finish') return self.m
def run(self, m0): """run(m0) Runs the inversion! """ self.invProb.startup(m0) self.directiveList.call('initialize') print('model has any nan: {:b}'.format(np.any(np.isnan(self.invProb.model)))) self.m = self.opt.minimize(self.invProb.evalFunction, self.invProb.model) self.directiveList.call('finish') return self.m
def fromRecArray(cls, recArray, srcType='primary'): """ Class method that reads in a numpy record array to MTdata object. Only imports the impedance data. """ if srcType == 'primary': src = simpegMT.SurveyMT.srcMT_polxy_1Dprimary elif srcType == 'total': src = sdsimpegMT.SurveyMT.srcMT_polxy_1DhomotD else: raise NotImplementedError( '{:s} is not a valid source type for MTdata') # Find all the frequencies in recArray uniFreq = np.unique(recArray['freq']) srcList = [] dataList = [] for freq in uniFreq: # Initiate rxList rxList = [] # Find that data for freq dFreq = recArray[recArray['freq'] == freq].copy() # Find the impedance rxTypes in the recArray. rxTypes = [ comp for comp in recArray.dtype.names if (len(comp) == 4 or len(comp) == 3) and 'z' in comp ] for rxType in rxTypes: # Find index of not nan values in rxType notNaNind = ~np.isnan(dFreq[rxType]) if np.any( notNaNind): # Make sure that there is any data to add. locs = rec2ndarr(dFreq[['x', 'y', 'z']][notNaNind].copy()) if dFreq[rxType].dtype.name in 'complex128': rxList.append( simpegMT.SurveyMT.RxMT(locs, rxType + 'r')) dataList.append(dFreq[rxType][notNaNind].real.copy()) rxList.append( simpegMT.SurveyMT.RxMT(locs, rxType + 'i')) dataList.append(dFreq[rxType][notNaNind].imag.copy()) else: rxList.append(simpegMT.SurveyMT.RxMT(locs, rxType)) dataList.append(dFreq[rxType][notNaNind].copy()) srcList.append(src(rxList, freq)) # Make a survey survey = simpegMT.SurveyMT.SurveyMT(srcList) dataVec = np.hstack(dataList) return cls(survey, dataVec)
def fromRecArray(cls, recArray, srcType='primary'): """ Class method that reads in a numpy record array to MTdata object. Only imports the impedance data. """ if srcType=='primary': src = SrcMT.polxy_1Dprimary elif srcType=='total': src = SrcMT.polxy_1DhomotD else: raise NotImplementedError('{:s} is not a valid source type for MTdata') # Find all the frequencies in recArray uniFreq = np.unique(recArray['freq']) srcList = [] dataList = [] for freq in uniFreq: # Initiate rxList rxList = [] # Find that data for freq dFreq = recArray[recArray['freq'] == freq].copy() # Find the impedance rxTypes in the recArray. rxTypes = [ comp for comp in recArray.dtype.names if (len(comp)==4 or len(comp)==3) and 'z' in comp] for rxType in rxTypes: # Find index of not nan values in rxType notNaNind = ~np.isnan(dFreq[rxType]) if np.any(notNaNind): # Make sure that there is any data to add. locs = rec2ndarr(dFreq[['x','y','z']][notNaNind].copy()) if dFreq[rxType].dtype.name in 'complex128': rxList.append(Rx(locs,rxType+'r')) dataList.append(dFreq[rxType][notNaNind].real.copy()) rxList.append(Rx(locs,rxType+'i')) dataList.append(dFreq[rxType][notNaNind].imag.copy()) else: rxList.append(Rx(locs,rxType)) dataList.append(dFreq[rxType][notNaNind].copy()) srcList.append(src(rxList,freq)) # Make a survey survey = Survey(srcList) dataVec = np.hstack(dataList) return cls(survey,dataVec)
def animate(ii): #for ii in range(1): removeFrame() # Grab current line and indx = np.where(lineID == ii)[0] srcLeft = [] obs_l = [] obs = [] srcRight = [] obs_r = [] srcList = [] # Split the obs file into left and right # Split the obs file into left and right for jj in range(len(indx)): # Grab corresponding data obs = np.hstack([obs, DCdobs2D.dobs[dataID == indx[jj]]]) #std = dobs2D.std[dataID==indx[jj]] srcList.append(DCdobs2D.srcList[indx[jj]]) Tx = DCdobs2D.srcList[indx[jj]].loc Rx = DCdobs2D.srcList[indx[jj]].rxList[0].locs # Create mid-point location Cmid = (Tx[0][0] + Tx[1][0]) / 2 Pmid = (Rx[0][:, 0] + Rx[1][:, 0]) / 2 ileft = Pmid < Cmid iright = Pmid >= Cmid temp = np.zeros(len(ileft)) temp[ileft] = 1 obs_l = np.hstack([obs_l, temp]) temp = np.zeros(len(iright)) temp[iright] = 1 obs_r = np.hstack([obs_r, temp]) if np.any(ileft): rx = DC.RxDipole(Rx[0][ileft, :], Rx[1][ileft, :]) srcLeft.append(DC.SrcDipole([rx], Tx[0], Tx[1])) #std_l = np.hstack([std_l,std[ileft]]) if np.any(iright): rx = DC.RxDipole(Rx[0][iright, :], Rx[1][iright, :]) srcRight.append(DC.SrcDipole([rx], Tx[0], Tx[1])) #obs_r = np.hstack([obs_r,iright]) #std_r = np.hstack([std_r,std[iright]]) DC2D_full = DC.SurveyDC(srcList) DC2D_full.dobs = np.asarray(obs) DC2D_full.std = DC2D_full.dobs * 0. DC2D_full.std[obs_l == 1] = np.abs(DC2D_full.dobs[obs_l == 1]) * 0.02 + 2e-5 DC2D_full.std[obs_r == 1] = np.abs(DC2D_full.dobs[obs_r == 1]) * 0.06 + 4e-5 # DC2D_l = DC.SurveyDC(srcLeft) # DC2D_l.dobs = np.asarray(obs[obs_l==1]) # DC2D_l.std = np.abs(np.asarray(DC2D_l.dobs))*0.05 + 2e-5 # # DC2D_r = DC.SurveyDC(srcRight) # DC2D_r.dobs = np.asarray(obs[obs_r==1]) # DC2D_r.std = np.abs(np.asarray(DC2D_r.dobs))*0.05 + 2e-5 survey = DC2D_full # Export data file DC.writeUBC_DCobs(inv_dir + dsep + obsfile2d, survey, '2D', 'SIMPLE') # Write input file fid = open(inv_dir + dsep + inp_file, 'w') fid.write('OBS LOC_X %s \n' % obsfile2d) fid.write('MESH FILE %s \n' % mshfile2d) fid.write('CHIFACT 1 \n') fid.write('TOPO DEFAULT \n') fid.write('INIT_MOD VALUE %e\n' % ini_mod) fid.write('REF_MOD VALUE %e\n' % ref_mod) fid.write('ALPHA VALUE %f %f %F\n' % (1. / dx**4., 1, 1)) fid.write('WEIGHT DEFAULT\n') fid.write('STORE_ALL_MODELS FALSE\n') fid.write('INVMODE CG\n') #fid.write('CG_PARAM 200 1e-4\n') fid.write('USE_MREF FALSE\n') #fid.write('BOUNDS VALUE 1e-4 1e+2\n') fid.close() os.chdir(inv_dir) os.system('dcinv2d ' + inp_file) #%% Load DC model and predicted data minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con') minv = np.reshape(minv, (mesh2d.nCy, mesh2d.nCx)) #%% Repeat for IP data indx = np.where(IPlineID == ii)[0] srcLeft = [] obs_l = [] std_l = [] srcRight = [] obs_r = [] std_r = [] obs_full = [] std_full = [] srcList = [] # Split the obs file into left and right for jj in range(len(indx)): srcList.append(IPdobs2D.srcList[indx[jj]]) # Grab corresponding data obs = IPdobs2D.dobs[IPdataID == indx[jj]] std = IPdobs2D.std[IPdataID == indx[jj]] obs_full = np.hstack([obs_full, obs]) std_full = np.hstack([std_full, std]) Tx = IPdobs2D.srcList[indx[jj]].loc Rx = IPdobs2D.srcList[indx[jj]].rxList[0].locs # Create mid-point location Cmid = (Tx[0][0] + Tx[1][0]) / 2 Pmid = (Rx[0][:, 0] + Rx[1][:, 0]) / 2 ileft = Pmid < Cmid iright = Pmid >= Cmid temp = np.zeros(len(ileft)) temp[ileft] = 1 obs_l = np.hstack([obs_l, temp]) temp = np.zeros(len(iright)) temp[iright] = 1 obs_r = np.hstack([obs_r, temp]) if np.any(ileft): rx = DC.RxDipole(Rx[0][ileft, :], Rx[1][ileft, :]) srcLeft.append(DC.SrcDipole([rx], Tx[0], Tx[1])) #std_l = np.hstack([std_l,std[ileft]]) if np.any(iright): rx = DC.RxDipole(Rx[0][iright, :], Rx[1][iright, :]) srcRight.append(DC.SrcDipole([rx], Tx[0], Tx[1])) IP2D_full = DC.SurveyDC(srcList) IP2D_full.dobs = np.asarray(obs_full) IP2D_full.std = np.asarray(std_full) IP2D_l = DC.SurveyDC(srcLeft) IP2D_l.dobs = np.asarray(obs_full[obs_l == 1]) #IP2D_l.std = np.abs(np.asarray(obs_l))*0.03 + 2e-2 IP2D_r = DC.SurveyDC(srcRight) IP2D_r.dobs = np.asarray(obs_full[obs_r == 1]) #IP2D_r.std = np.abs(np.asarray(obs_r))*0.03 + 1e-2 id_lbe = int(IPsurvey.srcList[indx[jj]].loc[0][1]) mesh3d = Mesh.TensorMesh([hx, np.ones(1) * 100., hz], x0=(-np.sum(padx) + np.min(srcMat[0][:, 0]), id_lbe - 50, np.max(srcMat[0][0, 2]) - np.sum(hz))) Mesh.TensorMesh.writeUBC(mesh3d, home_dir + dsep + 'Mesh' + str(id_lbe) + '.msh') global ax1, ax2, ax3, ax5, ax6, fig ax2 = plt.subplot(3, 2, 2) ph = DC.plot_pseudoSection(IP2D_r, ax2, stype='pdp', dtype='volt', colorbar=False) ax2.set_title('Observed P-DP', fontsize=10) plt.xlim([xmin, xmax]) plt.ylim([zmin, zmax]) plt.gca().set_aspect('equal', adjustable='box') ax2.set_xticklabels([]) ax2.set_yticklabels([]) ax1 = plt.subplot(3, 2, 1) DC.plot_pseudoSection(IP2D_l, ax1, stype='pdp', dtype='volt', clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]), colorbar=False) ax1.set_title('Observed DP-P', fontsize=10) plt.xlim([xmin, xmax]) plt.ylim([zmin, zmax]) plt.gca().set_aspect('equal', adjustable='box') ax1.set_xticklabels([]) z = np.linspace(np.min(ph[2]), np.max(ph[2]), 5) z_label = np.linspace(20, 1, 5) ax1.set_yticks(map(int, z)) ax1.set_yticklabels(map(str, map(int, z_label)), size=8) ax1.set_ylabel('n-spacing', fontsize=8) #%% Add labels bbox_props = dict(boxstyle="circle,pad=0.3", fc="r", ec="k", lw=1) ax2.text(0.00, 1, 'A', transform=ax2.transAxes, ha="left", va="center", size=6, bbox=bbox_props) bbox_props = dict(boxstyle="circle,pad=0.3", fc="y", ec="k", lw=1) ax2.text(0.1, 1, 'M', transform=ax2.transAxes, ha="left", va="center", size=6, bbox=bbox_props) bbox_props = dict(boxstyle="circle,pad=0.3", fc="g", ec="k", lw=1) ax2.text(0.2, 1, 'N', transform=ax2.transAxes, ha="left", va="center", size=6, bbox=bbox_props) bbox_props = dict(boxstyle="circle,pad=0.3", fc="g", ec="k", lw=1) ax1.text(0.00, 1, 'N', transform=ax1.transAxes, ha="left", va="center", size=6, bbox=bbox_props) bbox_props = dict(boxstyle="circle,pad=0.3", fc="y", ec="k", lw=1) ax1.text(0.1, 1, 'M', transform=ax1.transAxes, ha="left", va="center", size=6, bbox=bbox_props) bbox_props = dict(boxstyle="circle,pad=0.3", fc="r", ec="k", lw=1) ax1.text(0.2, 1, 'A', transform=ax1.transAxes, ha="left", va="center", size=6, bbox=bbox_props) survey = IP2D_full # Export data file DC.writeUBC_DCobs(inv_dir + dsep + ipfile2d, survey, '2D', 'SIMPLE', iptype=1) fid = open(inv_dir + dsep + inp_file, 'w') fid.write('OBS LOC_X %s \n' % ipfile2d) fid.write('MESH FILE %s \n' % mshfile2d) fid.write('CHIFACT 4 \n') fid.write('COND FILE dcinv2d.con\n') fid.write('TOPO DEFAULT \n') fid.write('INIT_MOD VALUE %e\n' % ini_mod) fid.write('REF_MOD VALUE 0.0\n') fid.write('ALPHA VALUE %f %f %F\n' % (1. / dx**4., 1, 1)) fid.write('WEIGHT DEFAULT\n') fid.write('STORE_ALL_MODELS FALSE\n') fid.write('INVMODE CG\n') #fid.write('CG_PARAM 200 1e-4\n') fid.write('USE_MREF FALSE\n') #fid.write('BOUNDS VALUE 1e-4 1e+2\n') fid.close() os.chdir(inv_dir) os.system('ipinv2d ' + inp_file) #%% Load model and predicted data minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'ipinv2d.chg') minv = np.reshape(minv, (mesh2d.nCy, mesh2d.nCx)) Mesh.TensorMesh.writeModelUBC( mesh3d, home_dir + dsep + 'Model' + str(id_lbe) + '.chg', minv.T) dpre = DC.readUBC_DC2Dpre(inv_dir + dsep + 'ipinv2d.pre') DCpre = dpre['DCsurvey'] DCtemp = IP2D_l DCtemp.dobs = DCpre.dobs[obs_l == 1] ax5 = plt.subplot(3, 2, 3) DC.plot_pseudoSection(DCtemp, ax5, stype='pdp', dtype='volt', clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]), colorbar=False) ax5.set_title('Predicted', fontsize=10) plt.xlim([xmin, xmax]) plt.ylim([zmin, zmax]) plt.gca().set_aspect('equal', adjustable='box') ax5.set_xticklabels([]) z = np.linspace(np.min(ph[2]), np.max(ph[2]), 5) z_label = np.linspace(20, 1, 5) ax5.set_yticks(map(int, z)) ax5.set_yticklabels(map(str, map(int, z_label)), size=8) ax5.set_ylabel('n-spacing', fontsize=8) DCtemp = IP2D_r DCtemp.dobs = DCpre.dobs[obs_r == 1] ax6 = plt.subplot(3, 2, 4) DC.plot_pseudoSection(DCtemp, ax6, stype='pdp', dtype='volt', clim=(ph[0].get_clim()[0], ph[0].get_clim()[1]), colorbar=False) ax6.set_title('Predicted', fontsize=10) plt.xlim([xmin, xmax]) plt.ylim([zmin, zmax]) plt.gca().set_aspect('equal', adjustable='box') ax6.set_xticklabels([]) ax6.set_yticklabels([]) pos = ax6.get_position() cbarax = fig.add_axes([ pos.x0 + 0.325, pos.y0 + 0.2, pos.width * 0.1, pos.height * 0.5 ]) ## the parameters are the specified position you set cb = fig.colorbar(ph[0], cax=cbarax, orientation="vertical", ax=ax6, ticks=np.linspace(ph[0].get_clim()[0], ph[0].get_clim()[1], 4), format="$10^{%.1f}$") cb.set_label("App. Charg.", size=8) ax3 = plt.subplot(3, 1, 3) ax3.set_title('2-D Model (S/m)', fontsize=10) ax3.set_xticks(map(int, x)) ax3.set_xticklabels(map(str, map(int, x))) ax3.set_xlabel('Easting (m)', fontsize=8) ax3.set_yticks(map(int, z)) ax3.set_yticklabels(map(str, map(int, z)), rotation='vertical') ax3.set_ylabel('Depth (m)', fontsize=8) plt.xlim([xmin, xmax]) plt.ylim([zmin / 2, zmax]) plt.gca().set_aspect('equal', adjustable='box') ph2 = plt.pcolormesh(mesh2d.vectorNx, mesh2d.vectorNy, (minv), vmin=vmin, vmax=vmax) plt.gca().tick_params(axis='both', which='major', labelsize=8) plt.draw() for ss in range(survey.nSrc): Tx = survey.srcList[ss].loc[0] plt.scatter(Tx[0], mesh2d.vectorNy[-1] + 10, s=10) pos = ax3.get_position() ax3.set_position([pos.x0 + 0.025, pos.y0, pos.width, pos.height]) pos = ax3.get_position() cbarax = fig.add_axes([ pos.x0 + 0.65, pos.y0 + 0.01, pos.width * 0.05, pos.height * 0.75 ]) ## the parameters are the specified position you set cb = fig.colorbar(ph2, cax=cbarax, orientation="vertical", ax=ax3, ticks=np.linspace(vmin, vmax, 4), format="%4.1f") cb.set_label("Chargeability", size=8) pos = ax1.get_position() ax1.set_position([pos.x0 + 0.03, pos.y0, pos.width, pos.height]) pos = ax5.get_position() ax5.set_position([pos.x0 + 0.03, pos.y0, pos.width, pos.height]) pos = ax2.get_position() ax2.set_position([pos.x0 - 0.03, pos.y0, pos.width, pos.height]) pos = ax6.get_position() ax6.set_position([pos.x0 - 0.03, pos.y0, pos.width, pos.height]) #%% Add the extra bbox_props = dict(boxstyle="rarrow,pad=0.3", fc="w", ec="k", lw=2) ax2.text(0.01, (float(ii) + 1.) / (len(uniqueID) + 2), 'N: ' + str(id_lbe), transform=fig.transFigure, ha="left", va="center", size=8, bbox=bbox_props) mrk_props = dict(boxstyle="square,pad=0.3", fc="w", ec="k", lw=2) ax2.text(0.01, 0.9, 'Line ID#', transform=fig.transFigure, ha="left", va="center", size=8, bbox=mrk_props) mrk_props = dict(boxstyle="square,pad=0.3", fc="b", ec="k", lw=2) for jj in range(len(uniqueID)): ax2.text(0.1, (float(jj) + 1.) / (len(uniqueID) + 2), ".", transform=fig.transFigure, ha="right", va="center", size=8, bbox=mrk_props) mrk_props = dict(boxstyle="square,pad=0.3", fc="r", ec="k", lw=2) ax2.text(0.1, (float(ii) + 1.) / (len(uniqueID) + 2), ".", transform=fig.transFigure, ha="right", va="center", size=8, bbox=mrk_props)