Importing Syscal ERT data from roll-a-long scheme

import reda

create an ERT container and import first dataset The ‘elecs_transform_reg_spacing_x’ parameter transforms the spacing in x direction from the spacing stored in the data file (here 1 m) to the true spacing of 0.2 m. This is useful if the spacing on the measurement system is not changed between measurements and only changed in the postprocessing (this is common practice in some work groups).

ert_p1 = reda.ERT()
ert_p1.import_syscal_bin(
    'data_syscal_rollalong/profile_1.bin',
    elecs_transform_reg_spacing_x=(1, 0.2),
)
ert_p1.compute_K_analytical(spacing=0.2)
with reda.CreateEnterDirectory('output_02_rollalong'):
    ert_p1.pseudosection(
        filename='profile1_pseudosection.pdf',
        column='r', log10=True
    )

found duplicate coordinates!

Print statistics

ert_p1.print_data_journal()

--- Data Journal Start ---
2024-04-29 07:58:36.094338
Data was imported from file  (1460 data points)
--- Data Journal End ---

This here is an activity list

ert_p1.print_log()

2024-04-29 07:58:35,004 - reda.containers.BaseContainer - INFO - IRIS Syscal Pro bin import
2024-04-29 07:58:35,825 - reda.containers.BaseContainer - INFO - Data sized changed from 0 to 1460

create an ERT container and import second dataset

ert_p2 = reda.ERT()
ert_p2.import_syscal_bin(
    'data_syscal_rollalong/profile_2.bin',
    elecs_transform_reg_spacing_x=(1, 0.2),
)
ert_p2.compute_K_analytical(spacing=0.2)
with reda.CreateEnterDirectory('output_02_rollalong'):
    ert_p2.pseudosection(
        filename='profile2_pseudosection.pdf',
        column='r',
        log10=True
    )

found duplicate coordinates!

Again print the data journal to see what changed in terms of imported data points

ert_p2.print_data_journal()

--- Data Journal Start ---
2024-04-29 07:58:37.174876
Data was imported from file  (1460 data points)
--- Data Journal End ---

Now we start over again and fix the coordinates of the second profile by using the ‘shift_by_xyz’ parameter, which can be used to move the electrode positions by a fixed offset. In our case this offset amounts to the position of the 25th position (first electrode starts at 0, therefore 24 * 0.25 m).

ert = reda.ERT()

# first profile
ert.import_syscal_bin(
    'data_syscal_rollalong/profile_1.bin',
    elecs_transform_reg_spacing_x=(1, 0.2),
)

ert2 = reda.ERT()
# second profile
ert2.import_syscal_bin(
    'data_syscal_rollalong/profile_2.bin',
    elecs_transform_reg_spacing_x=(1, 0.2),
    shift_by_xyz=[24 * 0.2],
)

Electrode positions of first dataset

with reda.CreateEnterDirectory('output_02_rollalong'):
    fig, ax = ert.plot_electrode_positions_2d()
    fig.show()

Electrode positions of second dataset

with reda.CreateEnterDirectory('output_02_rollalong'):
    fig, ax = ert2.plot_electrode_positions_2d()
    fig.show()

Now we merge the datasets and plot the electrode positions

ert.merge_container(ert2)

with reda.CreateEnterDirectory('output_02_rollalong'):
    fig, ax = ert.plot_electrode_positions_2d()
    fig.show()

compute geometric factors

ert.compute_K_analytical(spacing=0.2)

array([ -3.76991118,  -3.76991118, -15.07964474, ...,  15.07964474,
        -3.76991118,   3.76991118])

Plot Pseudosection

with reda.CreateEnterDirectory('output_02_rollalong'):
    ert.pseudosection(filename='pseudosection_both_profiles.pdf',
                      column='r', log10=True)

found duplicate coordinates!

with reda.CreateEnterDirectory('output_02_rollalong'):
    ert.histogram(filename='hist_both_profiles.pdf',
                  column=['r', 'rho_a', 'Iab', ])

Generating histogram plot for key: r
Generating histogram plot for key: rho_a
Generating histogram plot for key: Iab