"Direct solvers and multiple MPI processes are not currently supported."
)
else:
print(
"escript was not built with support for direct solvers, aborting."
)
elif not escript.hasFeature('gmsh'):
print("This example requires gmsh, aborting.")
else:
# Instantiate an MT_2D object with required & optional parameters:
obj_mt2d = mt2d.MT_2D(domain,
mode,
freq_def,
tags,
rho,
rho_1d,
ifc_1d,
xstep=xstep,
zstep=zstep,
maps=None,
plot=True)
# Solve for fields, apparent resistivity and phase:
mt2d_fields, arho_2d, aphi_2d = obj_mt2d.pdeSolve()
#
print(datetime.datetime.now() - startTime)
print("Done!")
else: # no finley
print("Finley module not available.")
def test_comm1(self):
# ---
# Initialisations
# ---
# Get timing:
startTime = datetime.datetime.now()
# Mode (TE includes air-layer, whereas TM does not):
mode = 'TE'
# Read the mesh file and define the 'finley' domain:
#mesh_file = "mesh/commemi-1/commemi1_te.fly"
#domain = finley.ReadMesh(mesh_file)
#mesh_file = "mesh/commemi-1/commemi1_te.msh"
#domain = finley.ReadGmsh(mesh_file, numDim=2)
domain = generateCommemi1Mesh()
# Sounding frequencies (in Hz):
freq_def = {"high": 1.0e+1, "low": 1.0e+1, "step": 1}
# Frequencies will be mapped on a log-scale from
# 'high' to 'low' with 'step' points per decade.
# (also only one frequency must be passed via dict)
# Step sizes for sampling along vertical and horizontal axis (in m):
xstep = 100
zstep = 250
# ---
# Resistivity model
# ---
# Resistivity values assigned to tagged regions (in Ohm.m):
rho = [
1.0e+14, # 0: air
100.0, # 1: host
0.5 # 2: anomaly
]
# Tags must match those in the file:
tags = ["domain_air", "domain_host", "domain_anomaly"]
# ---
# Layer definitions for 1D response at boundaries.
# ---
# List with resistivity values for left and right boundary.
rho_1d_left = [rho[0], rho[1]]
rho_1d_rght = [rho[0], rho[1]]
# Associated interfaces for 1D response left and right (must match the mesh file).
ifc_1d_left = [20000, 0, -20000]
ifc_1d_rght = [20000, 0, -20000]
# Save in dictionary with layer interfaces and resistivities left and right:
ifc_1d = {"left": ifc_1d_left, "right": ifc_1d_rght}
rho_1d = {"left": rho_1d_left, "right": rho_1d_rght}
# ---
# Adjust parameters here for TM mode
# ---
# Simply delete first element from lists:
if mode.upper() == 'TM':
tags.pop(0)
rho.pop(0)
rho_1d['left'].pop(0)
rho_1d['right'].pop(0)
ifc_1d['left'].pop(0)
ifc_1d['right'].pop(0)
# ---
# Run MT_2D
# ---
# Class options:
mt2d.MT_2D._solver = "DIRECT" #"ITERATIVE" #"CHOLEVSKY" #"CGLS " #"BICGSTAB" #"DIRECT" "ITERATIVE"
mt2d.MT_2D._debug = False
# Instantiate an MT_2D object with required & optional parameters:
obj_mt2d = mt2d.MT_2D(domain,
mode,
freq_def,
tags,
rho,
rho_1d,
ifc_1d,
xstep=xstep,
zstep=zstep,
maps=None,
plot=False)
# Solve for fields, apparent resistivity and phase:
mt2d_fields, arho_2d, aphi_2d = obj_mt2d.pdeSolve()
#import random
#mt2d_fields[0]['real']+=random.random()
#mt2d_fields[0]['imag']+=50*random.random()
#print(arho_2d[0][0])
#for i in range(len(aphi_2d[0])):
#aphi_2d[0][i]+=(50*random.random())
#for i in range(len(arho_2d[0])):
#arho_2d[0][i]-=17.8*(random.random())
# ---
# User defined plots
# ---
from scipy.interpolate import InterpolatedUnivariateSpline
# Setup abscissas/Ordinates for escript data:
x = numpy.array(obj_mt2d.loc.getX())[:, 0]
y0 = numpy.array(obj_mt2d.loc.getValue(arho_2d[0]))
y1 = numpy.array(obj_mt2d.loc.getValue(aphi_2d[0]))
# Values from Weaver -- Model 2D-1 (EP, T=0.1, z=0), see Zhdanov et al, 1997,
# "Methods for modelling electromagnetic fields. Results from COMMEMI -- the
# international project on the comparison of modelling results for electromag-
# netic induction", Journal of Applied Geophysics, 133-271
rte = [8.07, 14.10, 51.50, 95.71, 104.00, 100.00,
100.00] # TE rho_a (3 Canada)
rtm = [9.86, 46.40, 94.80, 98.30, 99.70, 100.00,
100.00] # TM rho_a (3 Canada)
if mode.lower() == 'te':
ra = rte
else:
ra = rtm
# Associated stations shifted to match escript coordinates:
xs = numpy.array([0, 500, 1000, 2000, 4000, 8000, 16000
]) + x.max() / 2.0
# Setup interpolation to get values at specified stations (for comparison):
fi = InterpolatedUnivariateSpline(x, y0)
# Save escript values at comparison points in text file:
# re-enable to allow comparisons
#numpy.savetxt("commemi1_"+mode.lower()+".dat", numpy.column_stack((xs,fi(xs))), fmt='%g')
# X plot-limits:
x0lim = [2000, 38000]
y1lim = [0, 120]
y2lim = [40, 85]
# Plot labels:
title = ' escript COMMEMI-1 MT-2D ' + '(' + mode.upper(
) + ')' + ' freq: ' + str(obj_mt2d.frequencies[0]) + ' Hz'
ylbl0 = r'resistivity $(\Omega m)$'
ylbl1 = r'phase $(\circ)$'
xlbl1 = 'X (m)'
# Setup the plot window with app. res. on top and phase on bottom:
if HAVE_MPL:
f, ax = pyplot.subplots(2,
figsize=(3.33, 3.33),
dpi=1200,
facecolor='w',
edgecolor='k',
sharex=True) # Mind shared axis
f.subplots_adjust(hspace=0.1,
top=0.95,
left=0.135,
bottom=0.125,
right=0.975)
f.suptitle(title, y=0.99, fontsize=8) #
# Top: apparent resistivity and points from Weaver for comparison:
ax[0].plot(x, y0, color='red', label='escript')
ax[0].plot(xs,
ra,
linestyle='',
markersize=3,
marker='o',
color='blue',
label='Weaver')
ax[0].grid(b=True, which='both', color='grey', linestyle=':')
ax[0].set_ylabel(ylbl0)
ax[0].yaxis.set_label_coords(-0.082, 0.5)
# Plot limits:
ax[0].set_xlim(x0lim)
ax[0].set_ylim(y1lim)
# Bottom: phase on linear plot
ax[1].plot(x, y1, color='blue')
ax[1].grid(b=True, which='both', color='grey', linestyle=':')
ax[1].set_xlabel(xlbl1)
ax[1].set_ylabel(ylbl1)
# Plot limits:
ax[1].set_xlim(x0lim)
ax[1].set_ylim(y2lim)
# ask matplotlib for the plotted objects and their labels
lna, la = ax[0].get_legend_handles_labels()
ax[0].legend(lna,
la,
bbox_to_anchor=(0.675, 0.325),
loc=2,
borderaxespad=0.,
prop={'size': 8},
frameon=False)
pyplot.ticklabel_format(style='sci',
axis='x',
scilimits=(0, 0),
useMathText=True)
ax[0].xaxis.major.formatter._useMathText = True
pyplot.rc('font', **{'size': 8, 'family': 'sans-serif'})
# Uncomment to inspect visually
#f.savefig("commemi1_"+mode.lower()+".png", dpi=1200)
# Now let's see if the points match
# First, we need to find correspondance between xs and x
indices = []
for i in range(len(xs)):
mindiff = 40000
mindex = 0
for j in range(len(x)):
if abs(xs[i] - x[j]) < mindiff:
mindiff = abs(xs[i] - x[j])
mindex = j
indices.append(mindex)
# The following are very simple checks based on the visual shape of the correct result
maxdiff = 0
for i in range(len(indices)):
if abs(y0[indices[i]] - ra[i]) > maxdiff:
maxdiff = abs(y0[indices[i]] - ra[i])
# Threshold is pretty arbitrary
self.assertLess(maxdiff, 5) # "Mismatch with reference data"
c = 0
for y in y1:
if y < 46:
c += 1
self.assertLess(74, escript.Lsup(y1)) # "Peak of bottom plot is off."
self.assertLess(escript.Lsup(y1), 81) # "Peak of bottom plot is off."
self.assertLess(0.78,
c / len(y1)) # "Bottom plot has too many high points"
self.assertLess(c / len(y1),
0.8) # "Bottom plot has too many high points"
#
print(datetime.datetime.now() - startTime)
print("Done!")
def test_comm4(self):
# ---
# Initialisations
# ---
# Get timing:
startTime = datetime.datetime.now()
# Mode (TE includes air-layer, whereas TM does not):
mode = 'TE'
# Read the mesh file and define the 'finley' domain:
#mesh_file = "mesh/commemi-4/commemi4_tm.msh"
#domain = finley.ReadGmsh(mesh_file, numDim=2)
domain = generateCommemi4Mesh()
#mesh_file = "mesh/commemi-4/commemi4_tm.fly"
#domain = finley.ReadMesh(mesh_file)
# Sounding frequencies (in Hz):
freq_def = {"high":1.0e+0,"low":1.0e-0,"step":1}
# Frequencies will be mapped on a log-scale from
# 'high' to 'low' with 'step' points per decade.
# (also only one frequency must be passed via dict)
# Step sizes for sampling along vertical and horizontal axis (in m):
xstep=100
zstep=100
# ---
# Resistivity model
# ---
# Resistivity values assigned to tagged regions (in Ohm.m):
rho = [
1.0e+14, # 0: air 1.0e-30
25.0 , # 1: lyr1 0.04
10.0 , # 2: slab 0.1
2.5 , # 3: basin 0.4
1000.0 , # 4: lyr2 0.001
5.0 # 5: lyr3 0.2
]
# Tags must match those in the file:
tags = ["air", "lyr1", "slab", "basin", "lyr2", "lyr3"]
# Optional user defined map of resistivity:
def f4(x,z,r): return escript.sqrt(escript.sqrt(x*x+z*z))/r
maps = [None, None, None, None, f4, None]
# ---
# Layer definitions for 1D response at boundaries.
# ---
# List with resistivity values for left and right boundary.
rho_1d_left = [ rho[0], rho[1], rho[2], rho[4], rho[5] ]
rho_1d_rght = [ rho[0], rho[1], rho[3], rho[4], rho[5] ]
# Associated interfaces for 1D response left and right (must match the mesh file).
ifc_1d_left = [ 50000, 0, -500, -2000, -25000, -50000]
ifc_1d_rght = [ 50000, 0, -500, -1000, -25000, -50000]
# Save in dictionary with layer interfaces and resistivities left and right:
ifc_1d = {"left":ifc_1d_left , "right":ifc_1d_rght}
rho_1d = {"left":rho_1d_left , "right":rho_1d_rght}
# ---
# Adjust parameters here for TM mode
# ---
# Simply delete first element from lists:
if mode.upper() == 'TM':
tags.pop(0)
rho.pop(0)
rho_1d['left'].pop(0)
rho_1d['right'].pop(0)
ifc_1d['left'].pop(0)
ifc_1d['right'].pop(0)
if maps is not None:
maps.pop(0)
# ---
# Run MT_2D
# ---
# Class options:
mt2d.MT_2D._solver = "DIRECT" #"ITERATIVE" #"CHOLEVSKY" #"CGLS " #"BICGSTAB" #"DIRECT" "ITERATIVE"
mt2d.MT_2D._debug = False
# Instantiate an MT_2D object with required & optional parameters:
obj_mt2d = mt2d.MT_2D(domain, mode, freq_def, tags, rho, rho_1d, ifc_1d,
xstep=xstep ,zstep=zstep, maps=None, plot=False)
# Solve for fields, apparent resistivity and phase:
mt2d_fields, arho_2d, aphi_2d = obj_mt2d.pdeSolve()
#import random
#mt2d_fields[0]['real']+=random.random()
#mt2d_fields[0]['imag']+=50*random.random()
#print(arho_2d[0][0])
#for i in range(len(aphi_2d[0])):
#aphi_2d[0][i]+=(50*random.random())
#for i in range(len(arho_2d[0])):
#arho_2d[0][i]-=7*(random.random())
# ---
# User defined plots
# ---
# Setup abscissas/Ordinates for escript data:
x = numpy.array( obj_mt2d.loc.getX() )[:,0]
y0 = numpy.array( obj_mt2d.loc.getValue(arho_2d[0]) )
y1 = numpy.array( obj_mt2d.loc.getValue(aphi_2d[0]) )
# Sort these arrays and delete any duplicates to prevent the call to
# InterpolatedUnivariateSpline below from returning an error
indices = numpy.argsort(x,kind='quicksort')
x = x[indices]
y0 = y0[indices]
y1 = y1[indices]
indices = numpy.unique(x,return_index=True)
x = x[indices[1]]
y0 = y0[indices[1]]
y1 = y1[indices[1]]
# Zhdanov et al, 1997, -- Model 2D-1 Table B.33. Model2D-4 (T=1.0, z=0), see
# "Methods for modelling electromagnetic fields. Results from COMMEMI -- the
# international project on the comparison of modelling results for electromag-
# netic induction", Journal of Applied Geophysics, 133-271
rte = [12.70, 12.00, 8.80, 6.84, 6.67, 6.25] # TE rho_a (3 Canada)
rtm = [11.40, 11.50, 9.03, 6.78, 6.80, 5.71] # TM rho_a (3 Canada)
if mode.lower() == 'te':
ra = rte
else:
ra = rtm
# Associated stations shifted to match escript coordinates:
xs = numpy.array( [-10, -7, -6, -5, 2, 5] )*1000 + x.max()/2.0
# Setup interpolation to get values at specified stations (for comparison):
fi = InterpolatedUnivariateSpline(x, y0)
# Save esscript values at comparison points in text file:
# uncomment to investigate
#numpy.savetxt("mesh/commemi-4/commemi4_"+mode.lower()+".dat", numpy.column_stack((xs,fi(xs))), fmt='%g')
# X plot-limits:
x0lim = [2000,38000]
#y1lim = [0,120]
#y2lim = [40,85]
# Plot labels:
title = ' escript COMMEMI-4 MT-2D ' + '(' + mode.upper() + ')' + ' freq: ' + str(obj_mt2d.frequencies[0]) + ' Hz'
ylbl0 = r'resistivity $(\Omega m)$'
ylbl1 = r'phase $(\circ)$'
xlbl1 = 'X (m)'
if HAVE_MPL:
# Setup the plot window with app. res. on top and phase on bottom:
f, ax = pyplot.subplots(2, figsize=(3.33,3.33), dpi=1200,
facecolor='w', edgecolor='k', sharex=True) # Mind shared axis
f.subplots_adjust(hspace=0.1, top=0.95, left=0.135, bottom=0.125, right=0.975)
f.suptitle(title, y=0.99,fontsize=8) #
# Top: apparent resistivity and points from Weaver for comparison:
ax[0].plot(x, y0, color='red', label = 'escript')
ax[0].plot(xs,ra, linestyle='', markersize=3, marker='o',
color='blue', label = 'Weaver')
ax[0].grid(b=True, which='both', color='grey',linestyle=':')
ax[0].set_ylabel( ylbl0)
ax[0].yaxis.set_label_coords(-0.082, 0.5)
# Plot limits:
ax[0].set_xlim(x0lim)
#ax[0].set_ylim(y1lim)
# Bottom: phase on linear plot
ax[1].plot(x,y1, color='blue')
ax[1].grid(b=True, which='both', color='grey',linestyle=':')
ax[1].set_xlabel( xlbl1 )
ax[1].set_ylabel( ylbl1 )
# Plot limits:
ax[1].set_xlim(x0lim)
#ax[1].set_ylim(y2lim)
# ask matplotlib for the plotted objects and their labels
lna, la = ax[0].get_legend_handles_labels()
ax[0].legend(lna, la, bbox_to_anchor=(0.02, 0.325), loc=2,
borderaxespad=0.,prop={'size':8}, frameon=False)
pyplot.ticklabel_format(style='sci', axis='x', scilimits=(0,0),
useMathText=True)
ax[0].xaxis.major.formatter._useMathText = True
pyplot.rc('font', **{'size': 8,'family':'sans-serif'})
#uncomment to allow visual inspection
#f.savefig("mesh/commemi-4/commemi4_"+mode.lower()+".png", dpi=1200)
# Now let's see if the points match
# First, we need to find correspondance between xs and x
indices=[]
for i in range(len(xs)):
mindiff=40000
mindex=0
for j in range(len(x)):
if abs(xs[i]-x[j]) < mindiff:
mindiff=abs(xs[i]-x[j])
mindex=j
indices.append(mindex)
# The following are very simple checks based on the visual shape of the correct result
maxdiff=0
for i in range(len(indices)):
if abs(y0[indices[i]]-ra[i])>maxdiff:
maxdiff=abs(y0[indices[i]]-ra[i])
if maxdiff>5: #Threshold is pretty arbitrary
raise RuntimeError("Mismatch with reference data")
c=0
for y in y1:
if y<46:
c+=1
if not (62 < escript.Lsup(y1) < 64):
raise RuntimeError("Peak of bottom plot is off.")
if not (0.61 < c/len(y1) < 0.65):
print(c/len(y1))
raise RuntimeError("Bottom plot has too many high points")
#
print("Runtime:", datetime.datetime.now()-startTime)
print("Done!")