# fwd_only=1,
# result_folder=result_folder_fwd,
# starting_model_file=jp(cwd, 'rho1.dat'))
# myfwd.run()
# %% Run CRTOMO
# This will make your Crtomo object run the inversion. The configuration files are
# automatically saved in the results folder
myinv.run()
# %% Import results
if dc == 0: # If you have IP results to load
res, ip = import_res(result_folder=result_folder)
m2p = mtophase(ncycles=1, pulse_l=3.5, tmin=0.02, tmax=2.83)
ipt = ip[:] * m2p
else: # if you only have resistivity data to load
res, files = import_res(result_folder=result_folder, return_file=1)
rest = np.copy(res[0])
# If you want to convert a crtomo result file in a prior model for future inversions for example:
# modf = res2mod(files[0])
# Let's plot the results:
# Remove outliers (arbitrary)
cut = np.log10(4500)
rest[rest > cut] = cut
# Define a linear space for the color map
res_levels = 10**np.linspace(min(rest), cut, 10)
mesh_dir = jp(cwd, "mesh", sub_folder_name) # Mesh files directory
mshf = jp(mesh_dir, "Mesh.dat")
results_dir = jp(cwd, "results", sub_folder_name,
"FM1B") # Results files directory
subs = ""
result_folder = jp(results_dir, subs)
ncol, nlin, nelem, blocks, centerxy, nodes = crc.mesh_geometry(mshf)
# %% Load results
try:
m2p = crc.mtophase(ncycles=1, pulse_l=3.5, tmin=0.02, tmax=2.83)
res, ip, s = crc.import_res(result_folder=result_folder)
rest = np.copy(res)
ipt = np.copy(ip[:] / m2p)
ss = [si[-1] for si in s]
# res, files = import_res(result_folder=result_folder, return_file=1)
# rest = np.copy(res[0])
res_levels = 10**np.linspace(min(rest), max(rest), 8)
rtp = 10**np.copy(rest)
figname = jp(results_dir, result_folder + "_res.png")
model_map(
polygons=blocks,
vals=rtp,
log=1,
figname=None,
extension="pdf",
)
plt.show()
results_dir = jp("/Users/robin/PycharmProjects/MGS",
"results/paper/scenario/WFB")
# %% STEPI Smooth
# Load solution
results_dir = jp("/Users/robin/PycharmProjects/MGS",
"results/paper/scenario/WFB")
subs = "STEPI"
result_folder = jp(results_dir, subs)
sol, files = crc.import_res(result_folder=result_folder, return_file=1)
# Res plot
res = sol[0]
# res_levels = 10**np.array(sorted(set(resmod)))
rtp = 10**np.copy(res)
model_map(
polygons=blocks,
vals=rtp,
log=1,
cbpos=bpos,
levels=res_levels,
folder=result_folder,
figname=None,