def plot_pseudoSection(Tx,Rx,data,z0, 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)
midl = []
midz = []
rho = []
for ii in range(len(Tx)):
# Get distances between each poles
rC1P1 = np.abs(Tx[ii][0] - Rx[ii][:,0])
rC2P1 = np.abs(Tx[ii][1] - Rx[ii][:,0])
rC1P2 = np.abs(Tx[ii][1] - Rx[ii][:,1])
rC2P2 = np.abs(Tx[ii][0] - Rx[ii][:,1])
rP1P2 = np.abs(Rx[ii][:,1] - Rx[ii][:,0])
# Compute apparent resistivity
if re.match(stype,'pdp'):
rho = np.hstack([rho, data[ii] * 2*np.pi * rC1P1 * ( rC1P1 + rP1P2 ) / rP1P2] )
elif re.match(stype,'dpdp'):
rho = np.hstack([rho, data[ii] * 2*np.pi / ( 1/rC1P1 - 1/rC2P1 - 1/rC1P2 + 1/rC2P2 ) ])
Cmid = (Tx[ii][0] + Tx[ii][1])/2
Pmid = (Rx[ii][:,0] + Rx[ii][:,1])/2
midl = np.hstack([midl, ( Cmid + Pmid )/2 ])
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
# Grid points
grid_x, grid_z = np.mgrid[np.min(midl):np.max(midl), np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midl,midz], np.log10(abs(1/rho.T)), (grid_x, grid_z), method='linear')
#plt.subplot(2,1,2)
plt.imshow(grid_rho.T, extent = (np.min(midl),np.max(midl),np.min(midz),np.max(midz)), origin='lower', alpha=0.8)
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
# Plot apparent resistivity
plt.scatter(midl,midz,s=50,c=np.log10(abs(1/rho.T)))
def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
"""
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)
:switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
Output:
:figure scatter plot overlayed on image
Edited Feb 17th, 2016
@author: dominiquef
"""
from SimPEG import np
from scipy.interpolate import griddata
import pylab as plt
# Set depth to 0 for now
z0 = 0.
# Pre-allocate
midx = []
midz = []
rho = []
LEG = []
count = 0 # Counter for data
for ii in range(DCsurvey.nSrc):
Tx = DCsurvey.srcList[ii].loc
Rx = DCsurvey.srcList[ii].rxList[0].locs
nD = DCsurvey.srcList[ii].rxList[0].nD
data = DCsurvey.dobs[count:count + nD]
count += nD
# Get distances between each poles A-B-M-N
if stype == 'pdp':
MA = np.abs(Tx[0] - Rx[0][:, 0])
NA = np.abs(Tx[0] - Rx[1][:, 0])
MN = np.abs(Rx[1][:, 0] - Rx[0][:, 0])
# Create mid-point location
Cmid = Tx[0]
Pmid = (Rx[0][:, 0] + Rx[1][:, 0]) / 2
if DCsurvey.mesh.dim == 2:
zsrc = Tx[1]
elif DCsurvey.mesh.dim == 3:
zsrc = Tx[2]
elif stype == 'dpdp':
MA = np.abs(Tx[0][0] - Rx[0][:, 0])
MB = np.abs(Tx[1][0] - Rx[0][:, 0])
NA = np.abs(Tx[0][0] - Rx[1][:, 0])
NB = np.abs(Tx[1][0] - Rx[1][:, 0])
# Create mid-point location
Cmid = (Tx[0][0] + Tx[1][0]) / 2
Pmid = (Rx[0][:, 0] + Rx[1][:, 0]) / 2
if DCsurvey.mesh.dim == 2:
zsrc = (Tx[0][1] + Tx[1][1]) / 2
elif DCsurvey.mesh.dim == 3:
zsrc = (Tx[0][2] + Tx[1][2]) / 2
# Change output for dtype
if dtype == 'volt':
rho = np.hstack([rho, data])
else:
# Compute pant leg of apparent rho
if stype == 'pdp':
leg = data * 2 * np.pi * MA * (MA + MN) / MN
elif stype == 'dpdp':
leg = data * 2 * np.pi / (1 / MA - 1 / MB + 1 / NB - 1 / NA)
LEG.append(1. / (2 * np.pi) *
(1 / MA - 1 / MB + 1 / NB - 1 / NA))
else:
print """dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """
break
if dtype == 'appc':
leg = np.log10(abs(1. / leg))
rho = np.hstack([rho, leg])
elif dtype == 'appr':
leg = np.log10(abs(leg))
rho = np.hstack([rho, leg])
else:
print """dtype must be 'appr' | 'appc' | 'volt' """
break
midx = np.hstack([midx, (Cmid + Pmid) / 2])
if DCsurvey.mesh.dim == 3:
midz = np.hstack([midz, -np.abs(Cmid - Pmid) / 2 + zsrc])
elif DCsurvey.mesh.dim == 2:
midz = np.hstack([midz, -np.abs(Cmid - Pmid) / 2 + zsrc])
ax = axs
# Grid points
grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx),
np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midx, midz],
rho.T, (grid_x, grid_z),
method='linear')
if clim == None:
vmin, vmax = rho.min(), rho.max()
else:
vmin, vmax = clim[0], clim[1]
grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
ph = plt.pcolormesh(grid_x[:, 0],
grid_z[0, :],
grid_rho.T,
clim=(vmin, vmax),
vmin=vmin,
vmax=vmax)
cbar = plt.colorbar(format="$10^{%.1f}$",
fraction=0.04,
orientation="horizontal")
cmin, cmax = cbar.get_clim()
ticks = np.linspace(cmin, cmax, 3)
cbar.set_ticks(ticks)
cbar.ax.tick_params(labelsize=10)
if dtype == 'appc':
cbar.set_label("App.Cond", size=12)
elif dtype == 'appr':
cbar.set_label("App.Res.", size=12)
elif dtype == 'volt':
cbar.set_label("Potential (V)", size=12)
# Plot apparent resistivity
ax.scatter(midx,
midz,
s=10,
c=rho.T,
vmin=vmin,
vmax=vmax,
clim=(vmin, vmax))
#ax.set_xticklabels([])
#ax.set_yticklabels([])
plt.gca().set_aspect('equal', adjustable='box')
return ph, LEG
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)
def plot_pseudoSection(DCsurvey, axs, stype='dpdp', dtype="appc", clim=None):
"""
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)
:switch dtype=-> Either 'appr' (app. res) | 'appc' (app. con) | 'volt' (potential)
Output:
:figure scatter plot overlayed on image
Edited Feb 17th, 2016
@author: dominiquef
"""
from SimPEG import np
from scipy.interpolate import griddata
import pylab as plt
# Set depth to 0 for now
z0 = 0.
# Pre-allocate
midx = []
midz = []
rho = []
LEG = []
count = 0 # Counter for data
for ii in range(DCsurvey.nSrc):
Tx = DCsurvey.srcList[ii].loc
Rx = DCsurvey.srcList[ii].rxList[0].locs
nD = DCsurvey.srcList[ii].rxList[0].nD
data = DCsurvey.dobs[count:count+nD]
count += nD
# Get distances between each poles A-B-M-N
if stype == 'pdp':
MA = np.abs(Tx[0] - Rx[0][:,0])
NA = np.abs(Tx[0] - Rx[1][:,0])
MN = np.abs(Rx[1][:,0] - Rx[0][:,0])
# Create mid-point location
Cmid = Tx[0]
Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
if DCsurvey.mesh.dim == 2:
zsrc = Tx[1]
elif DCsurvey.mesh.dim ==3:
zsrc = Tx[2]
elif stype == 'dpdp':
MA = np.abs(Tx[0][0] - Rx[0][:,0])
MB = np.abs(Tx[1][0] - Rx[0][:,0])
NA = np.abs(Tx[0][0] - Rx[1][:,0])
NB = np.abs(Tx[1][0] - Rx[1][:,0])
# Create mid-point location
Cmid = (Tx[0][0] + Tx[1][0])/2
Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
if DCsurvey.mesh.dim == 2:
zsrc = (Tx[0][1] + Tx[1][1])/2
elif DCsurvey.mesh.dim ==3:
zsrc = (Tx[0][2] + Tx[1][2])/2
# Change output for dtype
if dtype == 'volt':
rho = np.hstack([rho,data])
else:
# Compute pant leg of apparent rho
if stype == 'pdp':
leg = data * 2*np.pi * MA * ( MA + MN ) / MN
elif stype == 'dpdp':
leg = data * 2*np.pi / ( 1/MA - 1/MB + 1/NB - 1/NA )
LEG.append(1./(2*np.pi) *( 1/MA - 1/MB + 1/NB - 1/NA ))
else:
print("""dtype must be 'pdp'(pole-dipole) | 'dpdp' (dipole-dipole) """)
break
if dtype == 'appc':
leg = np.log10(abs(1./leg))
rho = np.hstack([rho,leg])
elif dtype == 'appr':
leg = np.log10(abs(leg))
rho = np.hstack([rho,leg])
else:
print("""dtype must be 'appr' | 'appc' | 'volt' """)
break
midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
if DCsurvey.mesh.dim==3:
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
elif DCsurvey.mesh.dim==2:
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + zsrc ])
ax = axs
# Grid points
grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
if clim == None:
vmin, vmax = rho.min(), rho.max()
else:
vmin, vmax = clim[0], clim[1]
grid_rho = np.ma.masked_where(np.isnan(grid_rho), grid_rho)
ph = plt.pcolormesh(grid_x[:,0],grid_z[0,:],grid_rho.T, clim=(vmin, vmax), vmin=vmin, vmax=vmax)
cbar = plt.colorbar(format="$10^{%.1f}$",fraction=0.04,orientation="horizontal")
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
cbar.ax.tick_params(labelsize=10)
if dtype == 'appc':
cbar.set_label("App.Cond",size=12)
elif dtype == 'appr':
cbar.set_label("App.Res.",size=12)
elif dtype == 'volt':
cbar.set_label("Potential (V)",size=12)
# Plot apparent resistivity
ax.scatter(midx,midz,s=10,c=rho.T, vmin =vmin, vmax = vmax, clim=(vmin, vmax))
#ax.set_xticklabels([])
#ax.set_yticklabels([])
plt.gca().set_aspect('equal', adjustable='box')
return ph, LEG
def plot_pseudoSection(DCsurvey, axs, stype):
"""
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
Edited Feb 17th, 2016
@author: dominiquef
"""
from SimPEG import np
from scipy.interpolate import griddata
import pylab as plt
# Set depth to 0 for now
z0 = 0.
# Pre-allocate
midx = []
midz = []
rho = []
count = 0 # Counter for data
for ii in range(DCsurvey.nSrc):
Tx = DCsurvey.srcList[ii].loc
Rx = DCsurvey.srcList[ii].rxList[0].locs
nD = DCsurvey.srcList[ii].rxList[0].nD
data = DCsurvey.dobs[count:count+nD]
count += nD
# Get distances between each poles A-B-M-N
MA = np.abs(Tx[0][0] - Rx[0][:,0])
MB = np.abs(Tx[1][0] - Rx[0][:,0])
NB = np.abs(Tx[1][0] - Rx[1][:,0])
NA = np.abs(Tx[0][0] - Rx[1][:,0])
MN = np.abs(Rx[1][:,0] - Rx[0][:,0])
# Create mid-point location
Cmid = (Tx[0][0] + Tx[1][0])/2
Pmid = (Rx[0][:,0] + Rx[1][:,0])/2
# Compute pant leg of apparent rho
if stype == 'pdp':
leg = data * 2*np.pi * MA * ( MA + MN ) / MN
leg = np.log10(abs(1/leg))
elif stype == 'dpdp':
leg = data * 2*np.pi / ( 1/MA - 1/MB - 1/NB + 1/NA )
midx = np.hstack([midx, ( Cmid + Pmid )/2 ])
midz = np.hstack([midz, -np.abs(Cmid-Pmid)/2 + z0 ])
rho = np.hstack([rho,leg])
ax = axs
# Grid points
grid_x, grid_z = np.mgrid[np.min(midx):np.max(midx), np.min(midz):np.max(midz)]
grid_rho = griddata(np.c_[midx,midz], rho.T, (grid_x, grid_z), method='linear')
plt.imshow(grid_rho.T, extent = (np.min(midx),np.max(midx),np.min(midz),np.max(midz)), origin='lower', alpha=0.8, vmin = np.min(rho), vmax = np.max(rho))
cbar = plt.colorbar(format = '%.2f',fraction=0.04,orientation="horizontal")
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
# Plot apparent resistivity
plt.scatter(midx,midz,s=50,c=rho.T)
ax.set_xticklabels([])
ax.set_ylabel('Z')
ax.yaxis.tick_right()
ax.yaxis.set_label_position('right')
plt.gca().set_aspect('equal', adjustable='box')
return ax
dataID[count:count + nD] = ii
count += nD
# Find 2D data correspondance
IPdataID = np.zeros(IPdobs2D.nD)
count = 0
for ii in range(IPdobs2D.nSrc):
nD = IPdobs2D.srcList[ii].rxList[0].nD
IPdataID[count:count + nD] = ii
count += nD
#
#%% Create dcin2d inversion files and run
dx = 20.
dl_len = np.max(srcMat[lineID == 0, 0, 0]) - np.min(srcMat[lineID == 0, 0, 0])
nc = np.ceil(dl_len / dx) + 10
padx = dx * np.power(1.4, range(1, padc))
# Creating padding cells
hx = np.r_[padx[::-1], np.ones(nc) * dx, padx]
hz = np.r_[padx[::-1], np.ones(int(nc / 5)) * dx]
# Create mesh with 0 coordinate centerer on the ginput points in cell center
mesh2d = Mesh.TensorMesh([hx, hz],
x0=(-np.sum(padx) + np.min(srcMat[0][:, 0]),
np.ceil(np.max(srcMat[0][0, 2])) - np.sum(hz)))
inv_dir = home_dir + '\Inv2D'
if not os.path.exists(inv_dir):
actvMap * np.ones(len(actv))) # Load in observation file survey = PF.Magnetics.readUBCmagObs(obsfile) rxLoc = survey.srcField.rxList[0].locs d = None #rxLoc[:,2] += 5 # Temporary change for test ndata = rxLoc.shape[0] #%% Subdivide the forward data locations into tiles PF.Magnetics.plot_obs_2D(rxLoc) xmin = np.min(rxLoc[:, 0]) xmax = np.max(rxLoc[:, 0]) ymin = np.min(rxLoc[:, 1]) ymax = np.max(rxLoc[:, 1]) var = np.c_[np.r_[xmin, ymin], np.r_[xmax, ymin], np.r_[xmin, ymax]] var = np.c_[var.T, np.ones(3) * mesh.vectorCCz[-1]] # First put a tile on both corners of the mesh indx = Utils.closestPoints(mesh, var) endl = np.c_[mesh.gridCC[indx, 0], mesh.gridCC[indx, 1]] dx = np.median(mesh.hx) # Add intermediate tiles until the min_Olap is respected # First in the x-direction
def branchdepth(self):
return np.max([node.branchdepth for node in self.children.flatten('F')])
def branchdepth(self):
if self.isleaf:
return self.depth
else:
return np.max([node.branchdepth for node in self.children.flatten('F')])
model = np.zeros(mesh.nC)
model[indx] = chibkg
Utils.meshutils.writeUBCTensorModel('VTKout' + str(ii) + '.dat', mesh,
model)
Utils.meshutils.writeUBCTensorMesh('Mesh_temp' + str(ii) + '.msh', mesh)
start_time = tm.time()
d_temp = PF.Magnetics.Intgrl_Fwr_Data(mesh, B, M, rxLoc, model, actv,
'tmi')
timer = (tm.time() - start_time)
ddata = np.max(abs(d - d_temp))
d = d_temp
#%% Plot data
plt.figure()
ax = plt.subplot()
plt.imshow(np.reshape(d, X.shape),
interpolation="bicubic",
extent=[xr.min(), xr.max(),
yr.min(), yr.max()],
origin='lower')
plt.clim(0, 25)
plt.colorbar(fraction=0.02)
plt.contour(X, Y, np.reshape(d, X.shape), 10)
plt.scatter(X, Y, c=np.reshape(d, X.shape), s=20)
os.chdir(inv_dir)
os.system('dcinv2d ' + inp_file)
#%%
#Load model
minv = DC.readUBC_DC2DModel(inv_dir + dsep + 'dcinv2d.con')
#plt.figure()
axs = plt.subplot(2,1,2)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')
minv = np.reshape(minv,(mesh2d.nCy,mesh2d.nCx))
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(m2D),alpha=0.5, cmap='gray')
plt.pcolormesh(mesh2d.vectorNx,mesh2d.vectorNy,np.log10(minv),alpha=0.5, clim=(np.min(np.log10(m2D)),np.max(np.log10(m2D))))
cbar = plt.colorbar(format = '%.2f',fraction=0.02)
cmin,cmax = cbar.get_clim()
ticks = np.linspace(cmin,cmax,3)
cbar.set_ticks(ticks)
#%% Othrwise it is a gradient array, plot surface of apparent resisitivty
elif re.match(stype,'gradient'):
rC1P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC2P1 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,0:2])**2, axis=1 ))
rC1P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC2P2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,1],Rx[0].shape[0], 1) - Rx[0][:,3:5])**2, axis=1 ))
rC1C2 = np.sqrt( np.sum( (npm.repmat(Tx[0][0:2,0]-Tx[0][0:2,1],Rx[0].shape[0], 1) )**2, axis=1 ))
rP1P2 = np.sqrt( np.sum( (Rx[0][:,0:2] - Rx[0][:,3:5])**2, axis=1 ))