from SimPEG import np import BaseDC as DC import BaseDC as IP def getActiveindfromTopo(mesh, topo): # def genActiveindfromTopo(mesh, topo): """ Get active indices from topography """ from scipy.interpolate import NearestNDInterpolator if mesh.dim==3: nCxy = mesh.nCx*mesh.nCy Zcc = mesh.gridCC[:,2].reshape((nCxy, mesh.nCz), order='F') Ftopo = NearestNDInterpolator(topo[:,:2], topo[:,2]) XY = Utils.ndgrid(mesh.vectorCCx, mesh.vectorCCy) XY.shape topo = Ftopo(XY) actind = [] for ixy in range(nCxy): actind.append(topo[ixy] <= Zcc[ixy,:]) else: raise NotImplementedError("Only 3D is working") return Utils.mkvc(np.vstack(actind)) def gettopoCC(mesh, airind): # def gettopoCC(mesh, airind): """ Get topography from active indices of mesh. """ mesh2D = Mesh.TensorMesh([mesh.hx, mesh.hy], mesh.x0[:2]) zc = mesh.gridCC[:,2] AIRIND = airind.reshape((mesh.vnC[0]*mesh.vnC[1],mesh.vnC[2]), order='F') ZC = zc.reshape((mesh.vnC[0]*mesh.vnC[1], mesh.vnC[2]), order='F') topo = np.zeros(ZC.shape[0]) topoCC = np.zeros(ZC.shape[0]) for i in range(ZC.shape[0]): ind = np.argmax(ZC[i,:][~AIRIND[i,:]]) topo[i] = ZC[i,:][~AIRIND[i,:]].max() + mesh.hz[~AIRIND[i,:]][ind]*0.5 topoCC[i] = ZC[i,:][~AIRIND[i,:]].max() XY = Utils.ndgrid(mesh.vectorCCx, mesh.vectorCCy) return mesh2D, topoCC def readUBC_DC3Dobstopo(filename,mesh,topo,probType="CC"): text_file = open(filename, "r") lines = text_file.readlines() text_file.close() SRC = [] DATA = [] srcLists = [] isrc = 0 # airind = getActiveindfromTopo(mesh, topo) # mesh2D, topoCC = gettopoCC(mesh, airind) for line in lines: if "!" in line.split(): continue elif line == '\n': continue elif line == ' \n': continue temp = map(float, line.split()) # Read a line for the current electrode if len(temp) == 5: # SRC: Only X and Y are provided (assume no topography) #TODO consider topography and assign the closest cell center in the earth if isrc == 0: DATA_temp = [] else: DATA.append(np.asarray(DATA_temp)) DATA_temp = [] indM = Utils.closestPoints(mesh2D, DATA[isrc-1][:,1:3]) indN = Utils.closestPoints(mesh2D, DATA[isrc-1][:,3:5]) rx = DCIP.RxDipole(np.c_[DATA[isrc-1][:,1:3], topoCC[indM]], np.c_[DATA[isrc-1][:,3:5], topoCC[indN]]) temp = np.asarray(temp) if [SRC[isrc-1][0], SRC[isrc-1][1]] == [SRC[isrc-1][2], SRC[isrc-1][3]]: indA = Utils.closestPoints(mesh2D, [SRC[isrc-1][0], SRC[isrc-1][1]]) tx = DCIP.SrcDipole([rx], [SRC[isrc-1][0], SRC[isrc-1][1], topoCC[indA]],[mesh.vectorCCx.max(), mesh.vectorCCy.max(), topoCC[-1]]) else: indA = Utils.closestPoints(mesh2D, [SRC[isrc-1][0], SRC[isrc-1][1]]) indB = Utils.closestPoints(mesh2D, [SRC[isrc-1][2], SRC[isrc-1][3]]) tx = DCIP.SrcDipole([rx], [SRC[isrc-1][0], SRC[isrc-1][1], topoCC[indA]],[SRC[isrc-1][2], SRC[isrc-1][3], topoCC[indB]]) srcLists.append(tx) SRC.append(temp) isrc += 1 elif len(temp) == 7: # SRC: X, Y and Z are provided SRC.append(temp) isrc += 1 elif len(temp) == 6: # DATA_temp.append(np.r_[isrc, np.asarray(temp)]) elif len(temp) > 7: DATA_temp.append(np.r_[isrc, np.asarray(temp)]) DATA.append(np.asarray(DATA_temp)) DATA_temp = [] indM = Utils.closestPoints(mesh2D, DATA[isrc-1][:,1:3]) indN = Utils.closestPoints(mesh2D, DATA[isrc-1][:,3:5]) rx = DCIP.RxDipole(np.c_[DATA[isrc-1][:,1:3], topoCC[indM]], np.c_[DATA[isrc-1][:,3:5], topoCC[indN]]) temp = np.asarray(temp) if [SRC[isrc-1][0], SRC[isrc-1][1]] == [SRC[isrc-1][2], SRC[isrc-1][3]]: indA = Utils.closestPoints(mesh2D, [SRC[isrc-1][0], SRC[isrc-1][1]]) tx = DCIP.SrcDipole([rx], [SRC[isrc-1][0], SRC[isrc-1][1], topoCC[indA]],[mesh.vectorCCx.max(), mesh.vectorCCy.max(), topoCC[-1]]) else: indA = Utils.closestPoints(mesh2D, [SRC[isrc-1][0], SRC[isrc-1][1]]) indB = Utils.closestPoints(mesh2D, [SRC[isrc-1][2], SRC[isrc-1][3]]) tx = DCIP.SrcDipole([rx], [SRC[isrc-1][0], SRC[isrc-1][1], topoCC[indA]],[SRC[isrc-1][2], SRC[isrc-1][3], topoCC[indB]]) srcLists.append(tx) text_file.close() survey = DCIP.SurveyDC(srcLists) # Do we need this? SRC = np.asarray(SRC) DATA = np.vstack(DATA) survey.dobs = np.vstack(DATA)[:,-2] return {'DCsurvey':survey, 'airind':airind, 'topoCC':topoCC, 'SRC':SRC} def readUBC_DC2DModel(fileName): from SimPEG import np, mkvc """ Read UBC GIF 2DTensor model and generate 2D Tensor model in simpeg Input: :param fileName, path to the UBC GIF 2D model file Output: :param SimPEG TensorMesh 2D object :return Created on Thu Nov 12 13:14:10 2015 @author: dominiquef """ # Open fileand skip header... assume that we know the mesh already obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!') dim = np.array(obsfile[0].split(),dtype=float) temp = np.array(obsfile[1].split(),dtype=float) if len(temp) > 1: model = np.zeros(dim) for ii in range(len(obsfile)-1): mm = np.array(obsfile[ii+1].split(),dtype=float) model[:,ii] = mm model = model[:,::-1] else: if len(obsfile[1:])==1: mm = np.array(obsfile[1:].split(),dtype=float) else: mm = np.array(obsfile[1:],dtype=float) # Permute the second dimension to flip the order model = mm.reshape(dim[1],dim[0]) model = model[::-1,:] model = np.transpose(model, (1, 0)) model = mkvc(model) return model def plot_pseudoSection(DCsurvey,lineID,ID, stype): from SimPEG import np, mkvc from scipy.interpolate import griddata from matplotlib.colors import LogNorm import pylab as plt import re """ Read list of 2D tx-rx location and plot a speudo-section of apparent resistivity. Assumes flat topo for now... Input: :param d2D, z0 :switch stype -> Either 'pdp' (pole-dipole) | 'dpdp' (dipole-dipole) Output: :figure scatter plot overlayed on image Created on Mon December 7th, 2015 @author: dominiquef """ #d2D = np.asarray(d2D) z0 = 0. for jj in range(len(ID)): indx = np.where(lineID==ID[jj])[0] midx_l = [] midz_l = [] midx_r = [] midz_r = [] rho_l = [] rho_r = [] for ii in range(len(indx)): Tx = DCsurvey.srcList[indx[ii]].loc Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs data = DCsurvey.dobs[indx[ii]] # Get distances between each poles rC1P1 = np.abs(Tx[0][0,0] - Rx[0][:,0]) rC2P1 = np.abs(Tx[1][0,0] - Rx[0][:,0]) rC1P2 = np.abs(Tx[1][0,0] - Rx[1][:,0]) rC2P2 = np.abs(Tx[0][0,0] - Rx[1][:,0]) rP1P2 = np.abs(Rx[1][:,0] - Rx[0][:,0]) # Create mid-point location Cmid = (Tx[0][0,0] + Tx[1][0,0])/2 Pmid = (Rx[0][:,0] + Rx[1][:,0])/2 # Seperate left/right tx-rx configurations ileft = Pmid < Cmid iright = Pmid >= Cmid # Compute apparent resistivity if re.match(stype,'pdp'): rho = data * 2*np.pi * rC1P1 * ( rC1P1 + rP1P2 ) / rP1P2 rho = np.log10(abs(1/rho)) elif re.match(stype,'dpdp'): rho = data * 2*np.pi / ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 ) if np.any(ileft): midx_l = np.hstack([midx_l, ( Cmid + Pmid[ileft] )/2 ]) midz_l = np.hstack([midz_l, -np.abs(Cmid-Pmid[ileft])/2 + z0 ]) rho_l = np.hstack([rho_l,rho[ileft]]) if np.any(iright): midx_r = np.hstack([midx_r, ( Cmid + Pmid[iright] )/2 ]) midz_r = np.hstack([midz_r, -np.abs(Cmid-Pmid[iright])/2 + z0 ]) rho_r = np.hstack([rho_r,rho[iright]]) #plt.figure(figsize=(10, 4)) if np.any(midx_l): ax1 = plt.subplot(1,2,1) # Grid points grid_x, grid_z = np.mgrid[np.min(midx_l):np.max(midx_l), np.min(midz_l):np.max(midz_l)] grid_rho = griddata(np.c_[midx_l,midz_l], rho_l.T, (grid_x, grid_z), method='linear') plt.imshow(grid_rho.T, extent = (np.min(midx_l),np.max(midx_l),np.min(midz_l),np.max(midz_l)), origin='lower', alpha=0.8, vmin = np.min(np.r_[rho_l,rho_r]), vmax = np.max(np.r_[rho_l,rho_r])) cbar = plt.colorbar(format = '%.2f',fraction=0.02,orientation="horizontal") cbar.set_label('App Cond (S/m)',verticalalignment='bottom',labelpad=-25.) cmin,cmax = cbar.get_clim() ticks = np.linspace(cmin,cmax,3) cbar.set_ticks(ticks) # Plot apparent resistivity plt.scatter(midx_l,midz_l,s=50,c=rho_l.T) ax1.set_ylabel('Pseudo-Z (m)') ax1.xaxis.tick_top() ax1.set_xlabel('X (m)') ax1.xaxis.set_label_position('top') if np.any(midx_r): ax2 = plt.subplot(1,2,2) # Grid points grid_x, grid_z = np.mgrid[np.min(midx_r):np.max(midx_r), np.min(midz_r):np.max(midz_r)] grid_rho = griddata(np.c_[midx_r,midz_r], rho_r.T, (grid_x, grid_z), method='linear') plt.imshow(grid_rho.T, extent = (np.min(midx_r),np.max(midx_r),np.min(midz_r),np.max(midz_r)), origin='lower', alpha=0.8, vmin = np.min(np.r_[rho_l,rho_r]), vmax = np.max(np.r_[rho_l,rho_r])) cbar = plt.colorbar(format = '%.2f',fraction=0.02,orientation="horizontal") cbar.set_label('App Cond (S/m)',verticalalignment='bottom',labelpad=-25.) cmin,cmax = cbar.get_clim() ticks = np.linspace(cmin,cmax,3) cbar.set_ticks(ticks) # Plot apparent resistivity plt.scatter(midx_r,midz_r,s=50,c=rho_r.T) ax2.set_yticklabels([]) ax2.xaxis.tick_top() ax2.set_xlabel('X (m)') ax2.xaxis.set_label_position('top') return ax1, ax2 def gen_DCIPsurvey(endl, mesh, stype, a, b, n): from SimPEG import np import re """ Load in endpoints and survey specifications to generate Tx, Rx location stations. Assumes flat topo for now... Input: :param endl -> input endpoints [x1, y1, z1, x2, y2, z2] :object mesh -> SimPEG mesh object :switch stype -> "dpdp" (dipole-dipole) | "pdp" (pole-dipole) | 'gradient' : param a, n -> pole seperation, number of rx dipoles per tx Output: :param Tx, Rx -> List objects for each tx location Lines: P1x, P1y, P1z, P2x, P2y, P2z Created on Wed December 9th, 2015 @author: dominiquef """ def xy_2_r(x1,x2,y1,y2): r = np.sqrt( np.sum((x2 - x1)**2 + (y2 - y1)**2) ) return r ## Evenly distribute electrodes and put on surface # Mesure survey length and direction dl_len = xy_2_r(endl[0,0],endl[1,0],endl[0,1],endl[1,1]) dl_x = ( endl[1,0] - endl[0,0] ) / dl_len dl_y = ( endl[1,1] - endl[0,1] ) / dl_len nstn = np.floor( dl_len / a ) # Compute discrete pole location along line stn_x = endl[0,0] + np.array(range(int(nstn)))*dl_x*a stn_y = endl[0,1] + np.array(range(int(nstn)))*dl_y*a # Create line of P1 locations M = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]] # Create line of P2 locations N = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]] ## Build list of Tx-Rx locations depending on survey type # Dipole-dipole: Moving tx with [a] spacing -> [AB a MN1 a MN2 ... a MNn] # Pole-dipole: Moving pole on one end -> [A a MN1 a MN2 ... MNn a B] Tx = [] Rx = [] if not re.match(stype,'gradient'): for ii in range(0, int(nstn)-1): if re.match(stype,'dpdp'): tx = np.c_[M[ii,:],N[ii,:]] elif re.match(stype,'pdp'): tx = np.c_[M[ii,:],M[ii,:]] #Rx.append(np.c_[M[ii+1:indx,:],N[ii+1:indx,:]]) # Current elctrode seperation AB = xy_2_r(tx[0,1],endl[1,0],tx[1,1],endl[1,1]) # Number of receivers to fit nstn = np.min([np.floor( (AB - b) / a ) , n]) # Check if there is enough space, else break the loop if nstn <= 0: continue # Compute discrete pole location along line stn_x = N[ii,0] + dl_x*b + np.array(range(int(nstn)))*dl_x*a stn_y = N[ii,1] + dl_y*b + np.array(range(int(nstn)))*dl_y*a # Create receiver poles # Create line of P1 locations P1 = np.c_[stn_x, stn_y, np.ones(nstn).T*mesh.vectorNz[-1]] # Create line of P2 locations P2 = np.c_[stn_x+a*dl_x, stn_y+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]] Rx.append(np.c_[P1,P2]) Tx.append(tx) #============================================================================== # elif re.match(stype,'dpdp'): # # for ii in range(0, int(nstn)-2): # # indx = np.min([ii+n+1,nstn]) # Tx.append(np.c_[M[ii,:],N[ii,:]]) # Rx.append(np.c_[M[ii+2:indx,:],N[ii+2:indx,:]]) #============================================================================== elif re.match(stype,'gradient'): # Gradient survey only requires Tx at end of line and creates a square # grid of receivers at in the middle at a pre-set minimum distance Tx.append(np.c_[M[0,:],N[-1,:]]) # Get the edge limit of survey area min_x = endl[0,0] + dl_x * b min_y = endl[0,1] + dl_y * b max_x = endl[1,0] - dl_x * b max_y = endl[1,1] - dl_y * b box_l = np.sqrt( (min_x - max_x)**2 + (min_y - max_y)**2 ) box_w = box_l/2. nstn = np.floor( box_l / a ) # Compute discrete pole location along line stn_x = min_x + np.array(range(int(nstn)))*dl_x*a stn_y = min_y + np.array(range(int(nstn)))*dl_y*a # Define number of cross lines nlin = int(np.floor( box_w / a )) lind = range(-nlin,nlin+1) ngrad = nstn * len(lind) rx = np.zeros([ngrad,6]) for ii in range( len(lind) ): # Move line in perpendicular direction by dipole spacing lxx = stn_x - lind[ii]*a*dl_y lyy = stn_y + lind[ii]*a*dl_x M = np.c_[ lxx, lyy , np.ones(nstn).T*mesh.vectorNz[-1]] N = np.c_[ lxx+a*dl_x, lyy+a*dl_y, np.ones(nstn).T*mesh.vectorNz[-1]] rx[(ii*nstn):((ii+1)*nstn),:] = np.c_[M,N] Rx.append(rx) else: print """stype must be either 'pdp', 'dpdp' or 'gradient'. """ return Tx, Rx def writeUBC_DCobs(fileName,Tx,Rx,d,wd, dtype): from SimPEG import np, mkvc import re """ Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location Input: :param fileName, path to the UBC GIF 3D obs file Output: :param rx, tx, d, wd :return Created on Mon December 7th, 2015 @author: dominiquef """ fid = open(fileName,'w') fid.write('! GENERAL FORMAT\n') for ii in range(len(Tx)): tx = np.asarray(Tx[ii]) rx = np.asarray(Rx[ii]) nrx = rx.shape[0] fid.write('\n') if re.match(dtype,'2D'): for jj in range(nrx): fid.writelines("%e " % ii for ii in mkvc(tx)) fid.writelines("%e " % ii for ii in mkvc(rx[jj])) fid.write('%e %e\n'% (d[ii][jj],wd[ii][jj])) #np.savetxt(fid, np.c_[ rx ,np.asarray(d[ii]), np.asarray(wd[ii]) ], fmt='%e',delimiter=' ',newline='\n') elif re.match(dtype,'3D'): fid.write('\n') fid.writelines("%e " % ii for ii in mkvc(tx)) fid.write('%i\n'% nrx) np.savetxt(fid, np.c_[ rx ,np.asarray(d[ii]), np.asarray(wd[ii]) ], fmt='%e',delimiter=' ',newline='\n') fid.close() def convertObs_DC3D_to_2D(DCsurvey,lineID): from SimPEG import np import numpy.matlib as npm """ Read DC survey and data and change coordinate system to distance along line assuming all data is acquired along line. First transmitter pole is assumed to be at the origin Assumes flat topo for now... Input: :param Tx, Rx Output: :figure Tx2d, Rx2d Created on Mon December 7th, 2015 @author: dominiquef """ def stn_id(v0,v1,r): """ Compute station ID along line """ dl = int(v0.dot(v1)) * r return dl srcLists = [] srcMat = getSrc_locs(DCsurvey) uniqueID = np.unique(lineID) for jj in range(len(uniqueID)): indx = np.where(lineID==uniqueID[jj])[0] # Find origin of survey r = 1e+8 # Initialize to some large number Tx = srcMat[indx] x0 = Tx[0][0,0:2] # Define station zero along line vecTx, r1 = r_unit(x0,Tx[-1][1,0:2]) for ii in range(len(indx)): Rx = DCsurvey.srcList[indx[ii]].rxList[0].locs nrx = Rx[0].shape[0] vec, r = r_unit(x0,Tx[ii][0,0:2]) rP1 = stn_id(vecTx,vec,r) vec, r = r_unit(x0,Tx[ii][1,0:2]) rP2 = stn_id(vecTx,vec,r) rC1 = np.zeros(nrx) rC2 = np.zeros(nrx) for kk in range(nrx): vec, r = r_unit(x0,Rx[0][kk,0:2]) rC1[kk] = stn_id(vecTx,vec,r) vec, r = r_unit(x0,Rx[1][kk,0:2]) rC2[kk] = stn_id(vecTx,vec,r) #rC1 = np.sqrt( np.sum( ( npm.repmat(endp.T,nrx,1) - Rx[0][:,0:2] )**2 , axis=1)) #rC2 = np.sqrt( np.sum( ( npm.repmat(endp.T,nrx,1) - Rx[1][:,0:2] )**2 , axis=1)) Rx = DC.RxDipole(np.c_[rC1,np.zeros(nrx),Rx[0][:,2]],np.c_[rC2,np.zeros(nrx),Rx[1][:,2]]) #np.savetxt(fid, data, fmt='%e',delimiter=' ',newline='\n') srcLists.append( DC.SrcDipole( [Rx], np.c_[rP1,0,Tx[ii][0,2]],np.c_[rP2,0,Tx[ii][1,2]] ) ) srvy2D = DC.SurveyDC(srcLists) srvy2D.dobs = np.asarray(DCsurvey.dobs) srvy2D.std = np.asarray(DCsurvey.std) return srvy2D def readUBC_DC3Dobs(fileName): """ Read UBC GIF DCIP 3D observation file and generate arrays for tx-rx location Input: :param fileName, path to the UBC GIF 3D obs file Output: :param rx, tx, d, wd :return Created on Mon December 7th, 2015 @author: dominiquef """ # Load file obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!') # Pre-allocate srcLists = [] Rx = [] d = [] wd = [] zflag = True # Flag for z value provided # Countdown for number of obs/tx count = 0 for ii in range(obsfile.shape[0]): if not obsfile[ii]: continue # First line is transmitter with number of receivers if count==0: temp = (np.fromstring(obsfile[ii], dtype=float,sep=' ').T) count = int(temp[-1]) # Check if z value is provided, if False -> nan if len(temp)==5: tx = np.r_[temp[0:2],np.nan,temp[0:2],np.nan] zflag = False else: tx = temp[:-1] rx = [] continue temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') if zflag: rx.append(temp[:-2]) # Check if there is data with the location if len(temp)==8: d.append(temp[-2]) wd.append(temp[-1]) else: rx.append(np.r_[temp[0:2],np.nan,temp[0:2],np.nan] ) # Check if there is data with the location if len(temp)==6: d.append(temp[-2]) wd.append(temp[-1]) count = count -1 # Reach the end of transmitter block if count == 0: rx = np.asarray(rx) Rx = DC.RxDipole(rx[:,:3],rx[:,3:]) srcLists.append( DC.SrcDipole( [Rx], tx[:3],tx[3:]) ) survey = DC.SurveyDC(srcLists) survey.dobs = np.asarray(d) survey.std = np.asarray(wd) # DCdata[src0, src0.rxList[0]] return {'DCsurvey':survey} def readUBC_DC2DLoc(fileName): from SimPEG import np """ Read UBC GIF 2D observation file and generate arrays for tx-rx location Input: :param fileName, path to the UBC GIF 2D model file Output: :param rx, tx :return Created on Thu Nov 12 13:14:10 2015 @author: dominiquef """ # Open fileand skip header... assume that we know the mesh already #============================================================================== # fopen = open(fileName,'r') # lines = fopen.readlines() # fopen.close() #============================================================================== # Load file obsfile = np.genfromtxt(fileName,delimiter=' \n',dtype=np.str,comments='!') # Check first line and figure out if 2D or 3D file format line = np.array(obsfile[0].split(),dtype=float) tx_A = [] tx_B = [] rx_M = [] rx_N = [] d = [] wd = [] for ii in range(obsfile.shape[0]): # If len==3, then simple format where tx-rx is listed on each line if len(line) == 4: temp = np.fromstring(obsfile[ii], dtype=float,sep=' ') tx_A = np.hstack((tx_A,temp[0])) tx_B = np.hstack((tx_B,temp[1])) rx_M = np.hstack((rx_M,temp[2])) rx_N = np.hstack((rx_N,temp[3])) rx = np.transpose(np.array((rx_M,rx_N))) tx = np.transpose(np.array((tx_A,tx_B))) return tx, rx, d, wd def readUBC_DC2DMesh(fileName): from SimPEG import np """ Read UBC GIF 2DTensor mesh and generate 2D Tensor mesh in simpeg Input: :param fileName, path to the UBC GIF mesh file Output: :param SimPEG TensorMesh 2D object :return Created on Thu Nov 12 13:14:10 2015 @author: dominiquef """ # Open file fopen = open(fileName,'r') # Read down the file and unpack dx vector def unpackdx(fid,nrows): for ii in range(nrows): line = fid.readline() var = np.array(line.split(),dtype=float) if ii==0: x0= var[0] xvec = np.ones(int(var[2])) * (var[1] - var[0]) / int(var[2]) xend = var[1] else: xvec = np.hstack((xvec,np.ones(int(var[1])) * (var[0] - xend) / int(var[1]))) xend = var[0] return x0, xvec #%% Start with dx block # First line specifies the number of rows for x-cells line = fopen.readline() nl = np.array(line.split(),dtype=float) [x0, dx] = unpackdx(fopen,nl) #%% Move down the file until reaching the z-block line = fopen.readline() if not line: line = fopen.readline() #%% End with dz block # First line specifies the number of rows for z-cells line = fopen.readline() nl = np.array(line.split(),dtype=float) [z0, dz] = unpackdx(fopen,nl) # Flip z0 to be the bottom of the mesh for SimPEG z0 = z0 - sum(dz) dz = dz[::-1] #%% Make the mesh using SimPEG from SimPEG import Mesh tensMsh = Mesh.TensorMesh([dx,dz],(x0, z0)) return tensMsh def xy_2_lineID(DCsurvey): """ Read DC survey class and append line ID. Assumes that the locations are listed in the order they were collected. May need to generalize for random point locations, but will be more expensive Input: :param DCdict Vectors of station location Output: :param LineID Vector of integers :return Created on Thu Feb 11, 2015 @author: dominiquef """ # Compute unit vector between two points nstn = DCsurvey.nSrc # Pre-allocate space lineID = np.zeros(nstn) linenum = 0 indx = 0 for ii in range(nstn): if ii == 0: A = DCsurvey.srcList[ii].loc[0] B = DCsurvey.srcList[ii].loc[1] xout = np.mean([A[0:2],B[0:2]], axis = 0) xy0 = A[:2] xym = xout # Deal with replicate pole location if np.all(xy0==xym): xym[0] = xym[0] + 1e-3 continue A = DCsurvey.srcList[ii].loc[0] B = DCsurvey.srcList[ii].loc[1] xin = np.mean([A[0:2],B[0:2]], axis = 0) # Compute vector between neighbours vec1, r1 = r_unit(xout,xin) # Compute vector between current stn and mid-point vec2, r2 = r_unit(xym,xin) # Compute vector between current stn and start line vec3, r3 = r_unit(xy0,xin) # Compute vector between mid-point and start line vec4, r4 = r_unit(xym,xy0) # Compute dot product ang1 = np.abs(vec1.dot(vec2)) ang2 = np.abs(vec3.dot(vec4)) # If the angles are smaller then 45d, than next point is on a new line if ((ang1 < np.cos(np.pi/4.)) | (ang2 < np.cos(np.pi/4.))) & (np.all(np.r_[r1,r2,r3,r4] > 0)): # Re-initiate start and mid-point location xy0 = A[:2] xym = xin # Deal with replicate pole location if np.all(xy0==xym): xym[0] = xym[0] + 1e-3 linenum += 1 indx = ii else: xym = np.mean([xy0,xin], axis = 0) lineID[ii] = linenum xout = xin return lineID def r_unit(p1,p2): """ r_unit(x,y) : Function computes the unit vector between two points with coordinates p1(x1,y1) and p2(x2,y2) """ assert len(p1)==len(p2), 'locs must be the same shape.' dx = [] for ii in range(len(p1)): dx.append((p2[ii] - p1[ii])) # Compute length of vector r = np.linalg.norm(np.asarray(dx)) if r!=0: vec = dx/r else: vec = np.zeros(len(p1)) return vec, r def getSrc_locs(DCsurvey): """ """ srcMat = np.zeros((DCsurvey.nSrc,2,3)) for ii in range(DCsurvey.nSrc): srcMat[ii][:,:] = np.asarray(DCsurvey.srcList[ii].loc) return srcMat