Comparing multiple PROCESS solutions (MFiles)¶

This tool plots the solution vectors (i.e. final values of optimisation parameters) for different runs of PROCESS. This allows visual comparisons of different solution points.

It can use different intra-solution optimisation parameter normalisations (e.g. initial value, parameter range) and inter-solution normalisations (e.g. normalise to a certain solution).

Known Limitations¶

• The solution vectors (optimisation parameter values at the solution) currently plotted are normalised to the initial point (from the IN.DAT) of each solution: each element of the vector is the $x_{final}/x_{initial}$, the xcmxxx values in the MFILE.DAT. This allows all optimisation parameters to be plotted on the same axis, showing the relative changes from their initial values across multiple solutions.
• Solutions being plotted together must also have the same optimisation parameters.
• The solutions plotted in this example are fictitious.

In [1]:

# Reload Process each time (keep editable install up-to-date)
%load_ext autoreload
%autoreload 2

from pathlib import Path

from process.io.plot_solutions import (
    RunMetadata,
    plot_mfile_solutions,
    plot_mfile_solutions_constraints,
)

# Reload Process each time (keep editable install up-to-date) %load_ext autoreload %autoreload 2 from pathlib import Path from process.io.plot_solutions import ( RunMetadata, plot_mfile_solutions, plot_mfile_solutions_constraints, )

Plot single solution¶

Plot a single solution, showing optimisation parameters normalised to their initial values.

In [2]:

data_dir = Path("data")
runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
]

# Figure and dataframe returned for optional further modification
fig1, df1 = plot_mfile_solutions(
    runs_metadata=runs_metadata,
    plot_title="Large tokamak solution 1",
)
df1

data_dir = Path("data") runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), ] # Figure and dataframe returned for optional further modification fig1, df1 = plot_mfile_solutions( runs_metadata=runs_metadata, plot_title="Large tokamak solution 1", ) df1

Out[2]:

	tag	minmax	objf_name	norm_objf	itvar001_name	xcm001	itvar002_name	xcm002	itvar003_name	xcm003	...	itvar039_name	xcm039	itvar040_name	xcm040	itvar041_name	xcm041	itvar042_name	xcm042	itvar043_name	xcm043
0	large tokamak 1	1.0	major radius	1.6	b_plasma_toroidal_on_axis	0.887772	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.04427	...	f_a_cs_turn_steel	0.864261	foh_stress	0.999995	f_nd_impurity_electrons(13)	1.621696	dr_tf_wp_with_insulation	1.20536	fne0	0.59638

1 rows × 90 columns

Plot two solutions¶

Plot two MFILEs together, showing normalised values of the optimisation parameters at the solution points, as well as the objective function values.

In [3]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
    RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"),
]

fig2, df2 = plot_mfile_solutions(
    runs_metadata=runs_metadata,
    plot_title="2 large tokamak solutions",
)
df2

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"), ] fig2, df2 = plot_mfile_solutions( runs_metadata=runs_metadata, plot_title="2 large tokamak solutions", ) df2

Out[3]:

	tag	minmax	objf_name	norm_objf	itvar001_name	xcm001	itvar002_name	xcm002	itvar003_name	xcm003	...	itvar039_name	xcm039	itvar040_name	xcm040	itvar041_name	xcm041	itvar042_name	xcm042	itvar043_name	xcm043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	0.887772	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.044270	...	f_a_cs_turn_steel	0.864261	foh_stress	0.999995	f_nd_impurity_electrons(13)	1.621696	dr_tf_wp_with_insulation	1.205360	fne0	0.59638
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	0.950449	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.054492	...	f_a_cs_turn_steel	0.866183	foh_stress	0.999438	f_nd_impurity_electrons(13)	1.454803	dr_tf_wp_with_insulation	1.355719	fne0	0.59638

2 rows × 90 columns

Plot one solution normalised to another¶

Normalised differences, relative to the a given solution, can also be plotted:

In [4]:

fig3, df3 = plot_mfile_solutions(
    runs_metadata=runs_metadata,
    plot_title="Large tokamak 2 solution, relative to large tokamak 1",
    normalising_tag="large tokamak 1",
)
df3

fig3, df3 = plot_mfile_solutions( runs_metadata=runs_metadata, plot_title="Large tokamak 2 solution, relative to large tokamak 1", normalising_tag="large tokamak 1", ) df3

/home/runner/work/PROCESS/PROCESS/process/io/plot_solutions.py:111: UserWarning: Double-normalising: using opt params normalised to each solution and normalising again to another solution. Are you sure?
  warn(

Out[4]:

	tag	minmax	objf_name	norm_objf	itvar001_name	xcm001	itvar002_name	xcm002	itvar003_name	xcm003	...	itvar039_name	xcm039	itvar040_name	xcm040	itvar041_name	xcm041	itvar042_name	xcm042	itvar043_name	xcm043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	0.887772	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.044270	...	f_a_cs_turn_steel	0.864261	foh_stress	0.999995	f_nd_impurity_electrons(13)	1.621696	dr_tf_wp_with_insulation	1.205360	fne0	0.59638
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	0.950449	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.054492	...	f_a_cs_turn_steel	0.866183	foh_stress	0.999438	f_nd_impurity_electrons(13)	1.454803	dr_tf_wp_with_insulation	1.355719	fne0	0.59638

2 rows × 90 columns

Plot multiple solutions normalised by one¶

Plot two MFILEs, normalised by a third MFILE.

In [5]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
    RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"),
    RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"),
]

fig4, df4 = plot_mfile_solutions(
    runs_metadata,
    "2 large tokamak solutions, relative to large tokamak 1",
    normalising_tag="large tokamak 1",
)
df4

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"), RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"), ] fig4, df4 = plot_mfile_solutions( runs_metadata, "2 large tokamak solutions, relative to large tokamak 1", normalising_tag="large tokamak 1", ) df4

/home/runner/work/PROCESS/PROCESS/process/io/plot_solutions.py:111: UserWarning: Double-normalising: using opt params normalised to each solution and normalising again to another solution. Are you sure?
  warn(

Out[5]:

	tag	minmax	objf_name	norm_objf	itvar001_name	xcm001	itvar002_name	xcm002	itvar003_name	xcm003	...	itvar039_name	xcm039	itvar040_name	xcm040	itvar041_name	xcm041	itvar042_name	xcm042	itvar043_name	xcm043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	0.887772	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.044270	...	f_a_cs_turn_steel	0.864261	foh_stress	0.999995	f_nd_impurity_electrons(13)	1.621696	dr_tf_wp_with_insulation	1.205360	fne0	0.59638
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	0.950449	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.054492	...	f_a_cs_turn_steel	0.866183	foh_stress	0.999438	f_nd_impurity_electrons(13)	1.454803	dr_tf_wp_with_insulation	1.355719	fne0	0.59638
2	large tokamak 3	1.0	major radius	1.68	b_plasma_toroidal_on_axis	1.001950	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.065104	...	f_a_cs_turn_steel	0.875111	foh_stress	0.991054	f_nd_impurity_electrons(13)	1.339160	dr_tf_wp_with_insulation	1.464856	fne0	0.59638

3 rows × 90 columns

RMS Errors¶

Plot RMS errors of multiple solutions relative to a reference solution.

In [6]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
    RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"),
    RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"),
    RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"),
]

fig5, df5 = plot_mfile_solutions(
    runs_metadata,
    "3 large tokamak solutions with RMS errors normalised to large tokamak 1",
    normalising_tag="large tokamak 1",
    rmse=True,
)
df5

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"), RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"), RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"), ] fig5, df5 = plot_mfile_solutions( runs_metadata, "3 large tokamak solutions with RMS errors normalised to large tokamak 1", normalising_tag="large tokamak 1", rmse=True, ) df5

/home/runner/work/PROCESS/PROCESS/process/io/plot_solutions.py:111: UserWarning: Double-normalising: using opt params normalised to each solution and normalising again to another solution. Are you sure?
  warn(

Out[6]:

	tag	minmax	objf_name	norm_objf	itvar001_name	xcm001	itvar002_name	xcm002	itvar003_name	xcm003	...	itvar039_name	xcm039	itvar040_name	xcm040	itvar041_name	xcm041	itvar042_name	xcm042	itvar043_name	xcm043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	0.887772	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.044270	...	f_a_cs_turn_steel	0.864261	foh_stress	0.999995	f_nd_impurity_electrons(13)	1.621696	dr_tf_wp_with_insulation	1.205360	fne0	0.59638
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	0.950449	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.054492	...	f_a_cs_turn_steel	0.866183	foh_stress	0.999438	f_nd_impurity_electrons(13)	1.454803	dr_tf_wp_with_insulation	1.355719	fne0	0.59638
2	large tokamak 3	1.0	major radius	1.68	b_plasma_toroidal_on_axis	1.001950	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.065104	...	f_a_cs_turn_steel	0.875111	foh_stress	0.991054	f_nd_impurity_electrons(13)	1.339160	dr_tf_wp_with_insulation	1.464856	fne0	0.59638
3	large tokamak 4	1.0	major radius	1.72	b_plasma_toroidal_on_axis	1.002129	rmajor	1.0	temp_plasma_electron_vol_avg_kev	1.032701	...	f_a_cs_turn_steel	0.904825	foh_stress	0.979912	f_nd_impurity_electrons(13)	1.351687	dr_tf_wp_with_insulation	1.451062	fne0	0.59638

4 rows × 90 columns

Solutions normalised by range¶

Use nitvar values instead; the solution optimisation parameters are normalised to the range of their upper and lower bounds.

In [7]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
    RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"),
    RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"),
    RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"),
]

fig6, df6 = plot_mfile_solutions(
    runs_metadata,
    "4 large tokamak solutions normalised to the range of the optimisation parameters",
    normalisation_type="range",
)
df6

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"), RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"), RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"), ] fig6, df6 = plot_mfile_solutions( runs_metadata, "4 large tokamak solutions normalised to the range of the optimisation parameters", normalisation_type="range", ) df6

Out[7]:

	tag	minmax	objf_name	norm_objf	itvar001_name	nitvar001	itvar002_name	nitvar002	itvar003_name	nitvar003	...	itvar039_name	nitvar039	itvar040_name	nitvar040	itvar041_name	nitvar041	itvar042_name	nitvar042	itvar043_name	nitvar043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	0.168400	rmajor	1.781757e-10	temp_plasma_electron_vol_avg_kev	0.074351	...	f_a_cs_turn_steel	0.727512	foh_stress	0.999995	f_nd_impurity_electrons(13)	0.061624	dr_tf_wp_with_insulation	0.126675	fne0	0.595976
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	0.180312	rmajor	5.562212e-11	temp_plasma_electron_vol_avg_kev	0.075649	...	f_a_cs_turn_steel	0.729132	foh_stress	0.999437	f_nd_impurity_electrons(13)	0.055282	dr_tf_wp_with_insulation	0.173662	fne0	0.595976
2	large tokamak 3	1.0	major radius	1.68	b_plasma_toroidal_on_axis	0.190101	rmajor	7.485879e-11	temp_plasma_electron_vol_avg_kev	0.076997	...	f_a_cs_turn_steel	0.736658	foh_stress	0.991045	f_nd_impurity_electrons(13)	0.050887	dr_tf_wp_with_insulation	0.207768	fne0	0.595976
3	large tokamak 4	1.0	major radius	1.72	b_plasma_toroidal_on_axis	0.190135	rmajor	1.155775e-11	temp_plasma_electron_vol_avg_kev	0.072882	...	f_a_cs_turn_steel	0.761707	foh_stress	0.979892	f_nd_impurity_electrons(13)	0.051363	dr_tf_wp_with_insulation	0.203457	fne0	0.595976

4 rows × 90 columns

Actual values¶

In [8]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"),
    RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"),
    RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"),
    RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"),
]

fig7, df7 = plot_mfile_solutions(
    runs_metadata,
    "Actual values of optimisation parameters for 4 large tokamak solutions",
    normalisation_type=None,
)
df7

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_1_MFILE.DAT", "large tokamak 1"), RunMetadata(data_dir / "large_tokamak_2_MFILE.DAT", "large tokamak 2"), RunMetadata(data_dir / "large_tokamak_3_MFILE.DAT", "large tokamak 3"), RunMetadata(data_dir / "large_tokamak_4_MFILE.DAT", "large tokamak 4"), ] fig7, df7 = plot_mfile_solutions( runs_metadata, "Actual values of optimisation parameters for 4 large tokamak solutions", normalisation_type=None, ) df7

Out[8]:

	tag	minmax	objf_name	norm_objf	itvar001_name	itvar001	itvar002_name	itvar002	itvar003_name	itvar003	...	itvar039_name	itvar039	itvar040_name	itvar040	itvar041_name	itvar041	itvar042_name	itvar042	itvar043_name	itvar043
0	large tokamak 1	1.0	major radius	1.60	b_plasma_toroidal_on_axis	5.060301	rmajor	8.0	temp_plasma_electron_vol_avg_kev	12.531239	...	f_a_cs_turn_steel	0.691409	foh_stress	0.999995	f_nd_impurity_electrons(13)	0.000616	dr_tf_wp_with_insulation	0.602680	fne0	0.59638
1	large tokamak 2	1.0	major radius	1.64	b_plasma_toroidal_on_axis	5.417557	rmajor	8.2	temp_plasma_electron_vol_avg_kev	12.653898	...	f_a_cs_turn_steel	0.692946	foh_stress	0.999438	f_nd_impurity_electrons(13)	0.000553	dr_tf_wp_with_insulation	0.677859	fne0	0.59638
2	large tokamak 3	1.0	major radius	1.68	b_plasma_toroidal_on_axis	5.711117	rmajor	8.4	temp_plasma_electron_vol_avg_kev	12.781252	...	f_a_cs_turn_steel	0.700089	foh_stress	0.991054	f_nd_impurity_electrons(13)	0.000509	dr_tf_wp_with_insulation	0.732428	fne0	0.59638
3	large tokamak 4	1.0	major radius	1.72	b_plasma_toroidal_on_axis	5.712135	rmajor	8.6	temp_plasma_electron_vol_avg_kev	12.392409	...	f_a_cs_turn_steel	0.723860	foh_stress	0.979912	f_nd_impurity_electrons(13)	0.000514	dr_tf_wp_with_insulation	0.725531	fne0	0.59638

4 rows × 90 columns

Plot constraints¶

Plot constraint values for 2 output mfiles.

In [9]:

runs_metadata = [
    RunMetadata(data_dir / "large_tokamak_nof_MFILE.DAT", "large tokamak"),
    RunMetadata(data_dir / "large_tokamak_nof_2_MFILE.DAT", "large tokamak 2"),
]

fig, eval_df = plot_mfile_solutions_constraints(
    runs_metadata=runs_metadata,
    title="Constraint values at large tokamak solution",
)

runs_metadata = [ RunMetadata(data_dir / "large_tokamak_nof_MFILE.DAT", "large tokamak"), RunMetadata(data_dir / "large_tokamak_nof_2_MFILE.DAT", "large tokamak 2"), ] fig, eval_df = plot_mfile_solutions_constraints( runs_metadata=runs_metadata, title="Constraint values at large tokamak solution", )

The constraint values are the actual constraint values, where a positive value corresponds to a satisfied constraint.