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Update speudo plot and allow app_res, app_con, volt

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D Fournier
2016-04-06 22:17:34 -07:00
parent f799733a9d
commit 16c6cc8d74
2 changed files with 80 additions and 54 deletions
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SimPEG/Examples/DC_Forward_PseudoSection.py
+28 -26
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@@ -2,19 +2,27 @@ from SimPEG import Mesh, Utils, np, sp
import SimPEG.DCIP as DC
import time
def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', dtype='appc', plotIt=True):
"""
DC Forward Simulation
=====================
Forward model conductive spheres in a half-space and plot a pseudo-section
Forward model two conductive spheres in a half-space and plot a
pseudo-section. Assumes an infinite line source and measures along the
center of the spheres.
INPUT:
loc = Location of spheres [[x1,y1,z1],[x2,y2,z2]]
radi = Radius of spheres [r1,r2]
param = Conductivity of background and two spheres [m0,m1,m2]
stype = survey type "pdp" (pole dipole) or "dpdp" (dipole dipole)
dtype = Data type "appr" (app res) | "appc" (app cond) | "volt" (potential)
Created by @fourndo on Mon Feb 01 19:28:06 2016
"""
assert stype in ['pdp', 'dpdp'], "Source type (stype) must be pdp or dpdp (pole dipole or dipole dipole)"
assert dtype in ['appr', 'appc', 'volt'], "Data type (dtype) must be appr (app res) or appc (app cond) or volt (potential)"
if loc is None:
loc = np.c_[[-50.,0.,-50.],[50.,0.,-50.]]
@@ -27,7 +35,6 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
# First we need to create a mesh and a model.
# This is our mesh
dx = 5.
@@ -52,15 +59,11 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
# Get index of the center
indy = int(mesh.nCy/2)
# Plot the model for reference
# Define core mesh extent
xlim = 200
zlim = 100
# Specify the survey type: "pdp" | "dpdp"
# Then specify the end points of the survey. Let's keep it simple for now and survey above the anomalies, top of the mesh
ends = [(-175,0),(175,0)]
ends = np.c_[np.asarray(ends),np.ones(2).T*mesh.vectorNz[-1]]
@@ -82,7 +85,8 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
#Set boundary conditions
mesh.setCellGradBC('neumann')
# Define the differential operators needed for the DC problem
# Define the linear system needed for the DC problem. We assume an infitite
# line source for simplicity.
Div = mesh.faceDiv
Grad = mesh.cellGrad
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
@@ -145,10 +149,9 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
print 'Forward completed'
# Let's just convert the 3D format into 2D (distance along line) and plot
# [Tx2d, Rx2d] = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc))
survey2D = DC.convertObs_DC3D_to_2D(survey, np.ones(survey.nSrc) , 'Xloc')
survey2D.dobs =np.hstack(data)
# Here is an example for the first tx-rx array
if plotIt:
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(7,7))
@@ -158,29 +161,29 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
ax.add_artist(circle1)
ax.add_artist(circle2)
dat = mesh.plotSlice(np.log10(model), ax =ax, normal = 'Y',
ind = indy,grid=True, clim = np.log10([sig.min(),sig.max()]))
ax.set_title('3-D model')
plt.gca().set_aspect('equal', adjustable='box')
plt.scatter(Tx[0][0,:],Tx[0][2,:],s=40,c='g', marker='v')
plt.scatter(Rx[0][:,0::3],Rx[0][:,2::3],s=40,c='y')
plt.xlim([-xlim,xlim])
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
pos = ax.get_position()
pos = ax.get_position()
ax.set_position([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height])
pos = ax.get_position()
cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height * 0.04]) ## the parameters are the specified position you set
cbarax = fig.add_axes([pos.x0 , pos.y0 + 0.025 , pos.width, pos.height * 0.04]) ## the parameters are the specified position you set
cb = fig.colorbar(dat[0],cax=cbarax, orientation="horizontal",
ax = ax, ticks=np.linspace(np.log10(sig.min()),
np.log10(sig.max()), 3), format="$10^{%.1f}$")
cb.set_label("Conductivity (S/m)",size=12)
cb.ax.tick_params(labelsize=12)
cb.ax.tick_params(labelsize=12)
# Second plot for the predicted apparent resistivity data
ax2 = plt.subplot(2,1,2, aspect='equal')
@@ -189,16 +192,15 @@ def run(loc=None, sig=None, radi=None, param=None, stype='dpdp', plotIt=True):
circle2=plt.Circle((loc[0,1],loc[2,1]),radi[1],color='k',fill=False, lw=3)
ax2.add_artist(circle1)
ax2.add_artist(circle2)
# Add the speudo section
dat = DC.plot_pseudoSection(survey2D,ax2,stype)
dat = DC.plot_pseudoSection(survey2D,ax2,stype=stype, dtype = dtype)
# plt.scatter(Tx2d[0][:],Tx[0][2,:],s=40,c='g', marker='v')
# plt.scatter(Rx2d[0][:],Rx[0][:,2::3],s=40,c='y')
# plt.plot(np.r_[Tx2d[0][0],Rx2d[-1][-1,-1]],np.ones(2)*mesh.vectorNz[-1], color='k')
ax2.set_title('Apparent Conductivity data')
ax2.set_title('Apparent Conductivity data')
plt.ylim([-zlim,mesh.vectorNz[-1]+dx])
plt.show()