python_utilities #958

Closed jonmaddock closed 1 year ago

In GitLab by @asbrown on Nov 21, 2019, 13:28

Summary

There are a number of python utilities available in PROCESS and a review of them is required to know which are still being used and need to be maintained and which are not being used and can be archived.

A number of the utilities have no documentation associated with them which needs to be written and included on GitPages.

List of python utilities

[x] a_to_b.py (Thomas Miller)
Scans from one IN.DAT(A.DAT) to another IN.DAT(B.DAT). Useful when creating a new reactor model and having trouble finding a feasible solution.
[ ] build_index.py (Hanni Lux)
Creates an index of all PROCESS run comments, after they have been created by run_process.py in a series of subfolders.
[x] cad_output.py (James Morris)
The PROCESS utility cad_output.py takes the mfile.py and produces an output file suitable for using in CAD programs.
[ ] compare_radials.py (Katy Ellis)
Radial plot comparison tool using PLASMOD-type input (expand)
[ ] convert_in_dat.py (James Morris)
Takes an old format IN.DAT (~pre-2014) ad converts it into the newer format.
[x] cost_bar.py (Stuart Muldrew)
Plots the cost breakdown as a bar chart giving the cost of each component.
[x] cost_pie.py (Stuart Muldrew)
Plots the cost breakdown as a pie chart giving each component as a percentage.
[ ] create_csv4database.py (FRANCESCO MAVIGLIA / Hanni Lux)
Output a set of data very similar to plot_proc.py, but to a comma-delimited format for inclusion in spreadsheets.
[x] create_dicts.py (Tom Miller)
Automatically generates the process_dicts.py file used by PROCESS utility programs
[x] diagnose_process.py (Hanni Lux)
To interpret PROCESS runs that do not find a feasible solution. Reads the MFILE.DAT and plots the normalised iteration variables and the normalised constraint residuals.
[x] diagnose_uncertainties.py (Hanni Lux)
Display the input parameter distributions in the final runs vs. the ones specified in the input file.
[x] display_uncertainties.py (Hanni Lux)
Display the output file uncertainties.nc created by the evaluate_uncertainties.py tool.
[x] evaluate_uncertainties.py (Hanni Lux)
Evaluates the uncertainties of a single PROCESS design point by use of Monte Carlo method.
[ ] fit_profile.py (Hanni Lux)
Fit a general temperature or density profile as given by the pedestalised profile parameterisation (ipedestal=1) to an ascii table.
[x] in_dat_comparison.py (James Morris)
Compares two IN.DATs and outputting inputs in one file and not the other, inputs in both with different values and inputs in both with the same value.
[ ] kallenbach_plotting.py (?)
NO DESCRIPTION
[x] kallenbach_plotting2.py (?)
NO DESCRIPTION
[x] line_length_standard.py (James Morris)
Script to check line length of repository files (expand)
[ ] make_plot_dat.py (James Morris)
Creates a PLOT.DAT-type file from MFILE.DAT. This is required by plot_sweep.py.
[ ] mcnp_output.py (James Morris)
Makes a MFILE.DAT and converts it to a suitable format for MCNP runs.
[x] mfile_comparison.py (James Morris)
Comparing two MFILEs and outputting significant differences in numerical values.
[x] ndscan.py (Adam Brown)
Multidimensional scanning tool.
[x] ndscan_and_package.py (S. Torrisi)
Creates a NetCDF output file from a previous Nd-scan run.
[x] ndscan_package_only.py (S. Torrisi)
Executes the Nd-scan and creates the NetCDF output file
[x] ndscan_visualisation.py (S. Torrisi)
Visualises the NetCDF output.
[ ] output_data.py (Richard Kemp)
Outputs a comma-delimited format dataset similar to plot_proc.py.
[x] output_detailed.py (James Morris)
Takes a configuration file called output_detailed.json to configure the output html of output.summary.py.
[ ] output_summary.py (James Morris)
Outputs a general uncustomisable summary.
[ ] plot_comparison.py (Hanni Lux)
Display the evolution of two variables in a selection of MFILEs.
[ ] plot_mfile_sweep.py (James Morris)
Plots normalised values of the iteration variables output by a parameter scan.
[x] plot_opti_process.py (?)
Macro plotting a set of information about the VMCON optimisation from an output file called OPT.DAT.
[x] plot_proc.py (Michael Kovari)
Produce a two-page summary of the output, including the major parameters, poloidal and toroidal cross-sections, and temperature and density profiles.
[ ] plot_profiles.py (James Morris)
Plotting of the temperature and density profiles of a number of MFILEs.
[x] plot_sankey.py (Adam Brown)
The power flows of the power plant will be extracted from MFILE.DAT and used to populate a Sankey diagram.
[ ] popcon.py (Stuart Muldrew)
Generates a POPCON plot from an MFILE that can be saved with the -s argument.
[ ] ref_check.py (James Morris)
Tool for comparing a PROCESS MFILE output file to a JSON reference file for a certain type of machine.
[x] run_process.py (Hanni Lux)
Runs PROCESS many times, randomly varying the initial values of the iteration variables until a feasible solution is found.
[x] test_process.py (Hanni Lux)
Similar structure to the 'run_process.py' program, but varies the iteration variable start parameters for as many iterations as requested by the configuration file.
[x] xls_create.py (Michael Kovari)
Append summary data to a spreadsheet data_summary.xlsx or name specified.
[x] write_new_in_dat.py (James Morris)
Creates a new IN.DAT file with the initial values of all the iteration variables replaced by their results in OUT.DAT, if that output is a feasible solution.

In GitLab by @asbrown on Nov 21, 2019, 13:32

The utilities that people have mentioned they are using on Slack:

Jonathan Maddock: run_process.py, plot_proc.py, create_dicts
Stuart Muldrew: diagnose_uncertainties.py, display_uncertainties.py, evaluate_uncertainties.py, in_dat_comparison.py, cost_bar.py, cost_pie.py
Alex Pearce: write_new_in_dat.py, xls_create.py

In GitLab by @asbrown on Nov 21, 2019, 13:32

marked the task run_process.py (Hanni Lux)
as completed

In GitLab by @asbrown on Nov 21, 2019, 13:32

marked the task plot_proc.py (Michael Kovari)
as completed