Example for processing field data from Sycal

Note

This example is work in progress!!!

import matplotlib.pyplot as plt

import crtomo
import reda.exporters.crtomo as crto
import reda.utils.norrec as NR
import reda

Daten einlesen und berechnen

# reda container erstellen
ert = reda.ERT()
# normal und reciproke Daten einlesen
ert.import_syscal_bin('data_nor.bin')
ert.import_syscal_bin('data_rec.bin', reciprocals=48)
# K-Faktor berechnen
K = reda.utils.geometric_factors.compute_K_analytical(ert.data, spacing=2.5)
# Rho_a berechnen
reda.utils.geometric_factors.apply_K(ert.data, K)
# negative Widerstände bei negativen K umdrehen
reda.utils.fix_sign_with_K.fix_sign_with_K(ert.data)
# calculate diffeence between nor and rec measurement
ert.data = NR.assign_norrec_diffs(ert.data, ('r', 'rho_a'))

Histogramme plotten

fig = ert.histogram(('r', 'rdiff', 'rho_a', 'rho_adiff', 'Iab'))
plt.savefig('histogramms.png')

plot pseudosection

fig = ert.pseudosection('r')
plt.savefig('pseudo_r.png')
fig = ert.pseudosection('rdiff')
plt.savefig('pseudo_rdiff.png')
fig = ert.pseudosection('rho_a')
plt.savefig('pseudo_rhoa.png')
fig = ert.pseudosection('rho_adiff')
plt.savefig('pseudo_rhoadiff.png')
fig = ert.pseudosection('Iab')
plt.savefig('pseudo_I.png')

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apply data filters

ert.filter('norrec == "rec"')
ert.filter('r < 0 or r > 1')
ert.filter('rho_a < 0 or rho_a > 60')
ert.filter('rdiff > 0.2 or rdiff < -0.2')

Datenfile in CRTomo Format ausgeben (volt.dat)

crto.write_files_to_directory(ert.data, '.')

Arbeiten im Tomodir

Gitter und Daten einlesen

grid = crtomo.crt_grid.create_surface_grid(
    electrodes_x=list(range(30, 174, 3)),
    char_lengths=[1.5, 10, 10, 10],
)

td_obj = crtomo.tdMan(grid=grid)
td_obj.read_voltages('volt.dat')

This grid was sorted using CutMcK. The nodes were resorted!
Triangular grid found

Inversionseinstellungen

td_obj.crtomo_cfg['robust_inv'] = 'F'
td_obj.crtomo_cfg['dc_inv'] = 'F'
td_obj.crtomo_cfg['cells_z'] = '-1'
td_obj.crtomo_cfg['mag_rel'] = '10'
td_obj.crtomo_cfg['mag_abs'] = '0.5'
td_obj.crtomo_cfg['fpi_inv'] = 'F'
# td_obj.crtomo_cfg['pha_a1'] = '10'
# td_obj.crtomo_cfg['pha_b'] = '-1.5'
# td_obj.crtomo_cfg['pha_rel'] = '10'
# td_obj.crtomo_cfg['pha_abs'] = '0'

invert

td_obj.invert(cores=4)

Attempting inversion in directory: /tmp/tmp0x882ols
Using binary: /usr/bin/CRTomo_dev
Calling CRTomo
Inversion attempt finished
Attempting to import the results
Reading inversion results
is robust False
Info: res_m.diag not found: /tmp/tmp0x882ols/inv/res_m.diag
/home/runner/work/crtomo_tools/crtomo_tools/examples/06_field_data_processing
Info: ata.diag not found: /tmp/tmp0x882ols/inv/ata.diag
/home/runner/work/crtomo_tools/crtomo_tools/examples/06_field_data_processing
Statistics of last iteration:
iteration               1
main_iteration          1
it_type             DC/IP
type                 main
dataRMS            0.1137
magRMS             0.1137
phaRMS                NaN
lambda             7739.0
roughness             0.0
cgsteps             194.0
nrdata              624.0
steplength          0.001
stepsize          0.00726
l1ratio               NaN
Name: 8, dtype: object

save tomodir

td_obj.save_to_tomodir('td')