pyopmspe11.visualization.data module

” Script to write the benchmark data

pyopmspe11.visualization.data.compute_m_c(dig, dil)

Normalized total variation of the concentration field within Box C

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.create_from_summary(dig, dil)

Use the summary arrays for the sparse data interpolation

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.dense_data(dig)

Generate the dense data within the benchmark format

Args:

dig (dict): Global dictionary

Returns:

None

pyopmspe11.visualization.data.generate_arrays(dig, dil, names, t_n)

Arrays for the dense data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

names (list): Strings with the quantities for the spatial maps

t_n (int): Index for the number of restart file

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.generate_arrays_performance_spatial(dig, dil, t_n)

Arrays for the performance spatial data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

t_n (int): Index for the number of restart file

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.get_corners(dig, dil)

Get the cell corners from the simulation grid

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.get_header(dig, i)

Get the right csv file header

Args:

dig (dict): Global dictionary

i (int): Number of csv file

Returns:

name_t (str): Name of the csv file

text (str): Header for the csv file

pyopmspe11.visualization.data.handle_fipnums(dig, dil)

Set the fipnum groups to compute the sparse data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.handle_inactive_mapping(dig, dil)

Set to inf the inactive grid centers in the reporting grid

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.handle_performance_spatial(dig, dil)

Create the performance spatial maps

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

None

pyopmspe11.visualization.data.handle_yaxis_mapping_extensive(dig, dil)

Extend the indices accounting for the y direction (extensive quantities)

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.handle_yaxis_mapping_intensive(dig, dil)

Extend the indices accounting for the y direction

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.main()

Postprocessing to generate the benchmark data

pyopmspe11.visualization.data.map_to_report_grid(dig, dil, names)

Map the simulation grid to the reporting grid

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

names (list): Strings with the quantities for the spatial maps

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.map_to_report_grid_performance_spatial(dig, dil, names, d_t)

Map the simulation grid to the reporting grid

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

names (list): Strings with the quantities for the spatial maps

d_t (float): Time step size

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.max_xcw(dig, dil)

Get the maximum CO2 mass fraction in the liquid phase

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.opm_files(dig)

Read some of the data from the simulation output files

Args:

dig (dict): Global dictionary

Returns:

dig (dict): Modified global dictionary

pyopmspe11.visualization.data.performance(dig)

Generate the performance within the benchmark format

Args:

dig (dict): Global dictionary

Returns:

None

pyopmspe11.visualization.data.read_opm(dig)

Read the simulation files using OPM

Args:

dig (dict): Global dictionary

Returns:

dig (dict): Modified global dictionary

pyopmspe11.visualization.data.read_resdata(dig)

Read the simulation files using resdata

Args:

dig (dict): Global dictionary

Returns:

dig (dict): Modified global dictionary

pyopmspe11.visualization.data.read_times(dig)

Get the time for injection and restart number

Args:

dig (dict): Global dictionary

Returns:

dig (dict): Modified global dictionary

pyopmspe11.visualization.data.resdata_summary(dig, dil, names, sort)

Read the summary arrays using resdata

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

names (list): Strings with the sensors ijk locations

sort (list): Integers with the right order for the sensors

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.sparse_data(dig)

Generate the sparse data within the benchmark format

Args:

dig (dict): Global dictionary

Returns:

None

pyopmspe11.visualization.data.static_map_to_report_grid_performance_spatial(dig, dil)

Map the no dynamic quantities to the reporting grid

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

dil (dict): Modified local dictionary

pyopmspe11.visualization.data.write_dense_data(dig, dil, i)

Map the quantities to the cells

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

i (int): Number of csv file

Returns:

None

pyopmspe11.visualization.data.write_dense_data_performance_spatial(dig, dil, i)

Write the dense performance data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

i (int): Number of csv file

Returns:

None

pyopmspe11.visualization.data.write_performance(dig, dil, interp_fgip, tcpu, infotimes)

Write the performance data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

interp_fgip (object): Interpolator (time) for the CO2 mass

tcpu (array): Floats with the simulation times

infotimes (array): Floats with the simulation time steps

Returns:

None

pyopmspe11.visualization.data.write_sparse_data(dig, dil)

Write the sparse data

Args:

dig (dict): Global dictionary

dil (dict): Local dictionary

Returns:

None