def run(plotIt=True):
"""
PF: Magnetics: Analytics
========================
Comparing the magnetics field in Vancouver to Seoul
"""
xr = np.linspace(-300, 300, 41)
yr = np.linspace(-300, 300, 41)
X, Y = np.meshgrid(xr, yr)
Z = np.ones((np.size(xr), np.size(yr)))*150
# Bz component in Korea
inckr = -8. + 3./60
deckr = 54. + 9./60
btotkr = 50898.6
Bokr = PF.MagAnalytics.IDTtoxyz(inckr, deckr, btotkr)
bx, by, bz = PF.MagAnalytics.MagSphereAnaFunA(
X, Y, Z, 100., 0., 0., 0., 0.01, Bokr, 'secondary'
)
Bzkr = np.reshape(bz, (np.size(xr), np.size(yr)), order='F')
# Bz component in Canada
incca = 16. + 49./60
decca = 70. + 19./60
btotca = 54692.1
Boca = PF.MagAnalytics.IDTtoxyz(incca, decca, btotca)
bx, by, bz = PF.MagAnalytics.MagSphereAnaFunA(
X, Y, Z, 100., 0., 0., 0., 0.01, Boca, 'secondary'
)
Bzca = np.reshape(bz, (np.size(xr), np.size(yr)), order='F')
if plotIt:
import matplotlib.pyplot as plt
from mpl_toolkits.axes_grid1 import make_axes_locatable
fig = plt.figure(figsize=(14, 5))
ax1 = plt.subplot(121)
dat1 = plt.imshow(Bzkr, extent=[min(xr), max(xr), min(yr), max(yr)])
divider = make_axes_locatable(ax1)
cax1 = divider.append_axes("right", size="5%", pad=0.05)
ax1.set_xlabel('East-West (m)')
ax1.set_ylabel('South-North (m)')
plt.colorbar(dat1, cax=cax1)
ax1.set_title('$B_z$ field at Seoul, South Korea')
ax2 = plt.subplot(122)
dat2 = plt.imshow(Bzca, extent=[min(xr), max(xr), min(yr), max(yr)])
divider = make_axes_locatable(ax2)
cax2 = divider.append_axes("right", size="5%", pad=0.05)
ax2.set_xlabel('East-West (m)')
ax2.set_ylabel('South-North (m)')
plt.colorbar(dat2, cax=cax2)
ax2.set_title('$B_z$ field at Vancouver, Canada')
plt.show()
def magnetizationModel(self):
"""
magnetization vector
"""
if getattr(self, 'magfile', None) is None:
M = Magnetics.dipazm_2_xyz(np.ones(self.nC) *
self.survey.srcField.param[1],
np.ones(self.nC) *
self.survey.srcField.param[2])
else:
with open(self.basePath + self.magfile) as f:
magmodel = f.read()
magmodel = magmodel.splitlines()
M = []
for line in magmodel:
M.append(map(float, line.split()))
# Convert list to 2d array
M = np.vstack(M)
# Cycle through three components and permute from UBC to SimPEG
for ii in range(3):
m = np.reshape(M[:, ii],
(self.mesh.nCz, self.mesh.nCx, self.mesh.nCy),
order='F')
m = m[::-1, :, :]
m = np.transpose(m, (1, 2, 0))
M[:, ii] = Utils.mkvc(m)
self._M = M
return self._M
def readUBC_DC3Dobs(fileName):
from SimPEG import np
"""
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
Tx = []
Rx = []
d = []
wd = []
# 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])
temp = np.reshape(temp[0:-1],[2,3]).T
Tx.append(temp)
rx = []
continue
temp = np.fromstring(obsfile[ii], dtype=float,sep=' ')
rx.append(temp)
count = count -1
# Reach the end of
if count == 0:
temp = np.asarray(rx)
Rx.append(temp[:,0:6])
# Check for data + uncertainties
if temp.shape[1]==8:
d.append(temp[:,6])
wd.append(temp[:,7])
# Check for data only
elif temp.shape[1]==7:
d.append(temp[:,6])
return Tx, Rx, d, wd
indx = PF.BaseMag.gocad2vtk(topsurf, mesh, bcflag=False, inflag=True)
actv = np.zeros(mesh.nC)
actv[indx] = 1
model[actv == 0] = -100
Utils.meshutils.writeUBCTensorModel('VTKout.dat', mesh, model)
Utils.meshutils.writeUBCTensorMesh('Mesh_temp.msh', mesh)
start_time = tm.time()
d = PF.Magnetics.Intgrl_Fwr_Data(mesh, B, M, rxLoc, model, actv, 'tmi')
timer = (tm.time() - start_time)
#%% 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)
ax.set_title('Forward data')
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)
# Create array of points for interpolating from 3D to 2D mesh
xx = Tx[0][0,0] + mesh2d.vectorCCx * np.cos(azm)
yy = Tx[0][1,0] + mesh2d.vectorCCx * np.sin(azm)
zz = mesh2d.vectorCCy
[XX,ZZ] = np.meshgrid(xx,zz)
[YY,ZZ] = np.meshgrid(yy,zz)
xyz2d = np.c_[mkvc(XX),mkvc(YY),mkvc(ZZ)]
#plt.scatter(xx,yy,s=20,c='y')
F = interpolation.NearestNDInterpolator(mesh.gridCC,model)
m2D = np.reshape(F(xyz2d),[mesh2d.nCx,mesh2d.nCy]).T
#==============================================================================
# mesh2d = Mesh.TensorMesh([mesh.hx, mesh.hz], x0=(mesh.x0[0]-endl[0,0],mesh.x0[2]))
# m3D = np.reshape(model, (mesh.nCz, mesh.nCy, mesh.nCx))
# m2D = m3D[:,1,:]
#==============================================================================
plt.figure()
axs = plt.subplot(2,1,1)
plt.xlim([0,nc*dx])
plt.ylim([mesh2d.vectorNy[-1]-dl_len/2,mesh2d.vectorNy[-1]])
plt.gca().set_aspect('equal', adjustable='box')