pyopmspe11.visualization.plotting module#

Create benchmark figures from pyopmspe11 CSV output.

The module reads sparse, dense, and performance data, configures shared plotting styles, creates individual case figures, and compares compatible results from multiple folders.

class PlotCase(case, tlabel, dims, tscale, lower)[source]#

Bases: object

Case-dependent settings used by all plotting functions.

Attributes:
case

SPE11 case identifier.

tlabel

Short time-unit label used in titles and filenames.

dims

Number of coordinate columns in spatial CSV files.

tscale

Factor converting simulation seconds to the displayed time unit.

lower

Whether plots represent only the lower neighbourhood.

Parameters:
case: str#
tlabel: str#
dims: int#
tscale: float#
lower: bool#
class PlotConfig(folders, generate, compare, where, dataf, colors, linestyles, props)[source]#

Bases: object

Folders, output settings, and styles shared by one plotting run.

Attributes:
folders

Case directories whose generated CSV files are plotted.

generate

Requested combination of plot types.

compare

SPE11 case selected for a multi-folder comparison.

where

Directory in which figures are saved.

dataf

Optional data subdirectory relative to each case folder.

colors, linestyles

Style sequences used to distinguish cases and quantities.

props

Matplotlib properties used for folder labels.

Parameters:
folders: list#
generate: str#
compare: str#
where: str#
dataf: str#
colors: list#
linestyles: list#
props: dict#
class PlotGrid(times, xmsh, zmsh, xmx, ymy, zmz, kinds, cmaps, dims)[source]#

Bases: object

Coordinates and display settings for dense spatial plots.

Attributes:
times

Spatial output times selected for plotting.

xmsh, zmsh

Meshgrid coordinates passed to pcolormesh.

xmx, ymy, zmz

Reporting-grid vertices along x, y, and z.

kinds

Dense data variants to plot.

cmaps

Colormaps assigned to dense quantities.

dims

Number of coordinate columns in the spatial CSV files.

Parameters:
times: list#
xmsh: ndarray#
zmsh: ndarray#
xmx: ndarray#
ymy: ndarray#
zmz: ndarray#
kinds: list#
cmaps: list#
dims: int#
configure_matplotlib()[source]#

Configure Matplotlib defaults for benchmark figures.

Return type:

None

read_csv(path)[source]#

Read a benchmark CSV file into a numeric array.

Parameters:
pathstr

Input or output path.

Returns:
NDArray

Calculated numeric values.

Parameters:

path (str)

Return type:

NDArray

load_time_series(folder, case)[source]#

Load a sparse time-series CSV file when available.

Parameters:
folderstr

Case output directory.

casestr

SPE11 case identifier.

Returns:
csvNDArray or None

Loaded sparse time-series values, or None when the file is absent.

foundbool

Whether a matching time-series file was found.

Parameters:
Return type:

tuple[NDArray | None, bool]

load_performance_series(folder, case, kind)[source]#

Load a performance time-series CSV file when available.

Parameters:
folderstr

Case output directory.

casestr

SPE11 case identifier.

kindstr

Regular or detailed data variant.

Returns:
csvNDArray or None

Loaded performance values, or None when the file is absent.

foundbool

Whether a matching performance file was found.

Parameters:
Return type:

tuple[NDArray | None, bool]

load_spatial_map(folder, dataf, case, kind, time, tlabel)[source]#

Load one dense or performance-spatial CSV map.

Parameters:
folderstr

Case output directory.

datafstr

Optional data subdirectory.

casestr

SPE11 case identifier.

kindstr

Regular or detailed data variant.

timestr

Case-dependent time conversion factor.

tlabelstr

Short time-unit label.

Returns:
NDArray

Calculated numeric values.

Parameters:
Return type:

NDArray

format_performance_label(csv, index, folder)[source]#

Format the aggregate metric shown in a performance legend.

Parameters:
csvNDArray

Loaded numeric CSV data.

indexint

Metric index.

folderstr

Case output directory.

Returns:
str

Generated filename or formatted text.

Parameters:

  • csv (NDArray)

  • index (int)

  • folder (str)

Return type:

str

build_plot_grid(folder, dataf, tlabel, dims, time)[source]#

Build plotting coordinates and select spatial output times.

Parameters:
folderstr

Case output directory.

datafstr

Optional data subdirectory.

tlabelstr

Short time-unit label.

dimsint

Number of coordinate columns.

timefloat

Case-dependent time conversion factor.

Returns:
timeslist[int]

Spatial output times selected for plotting.

xmsh, zmshNDArray

Meshgrid coordinates used by pcolormesh.

xmx, ymy, zmzNDArray

Reporting-grid vertices along x, y, and z.

Parameters:
Return type:

tuple[list, NDArray, NDArray, NDArray, NDArray, NDArray]

plot_performance(case_cfg, run_cfg)[source]#

Create regular and detailed performance figures.

Parameters:
case_cfgPlotCase

Case-dependent plotting settings.

run_cfgPlotConfig

Folders and styles for the plotting run.

Returns:
list[str]

Names of the generated regular and detailed performance figures.

Parameters:
Return type:

list[str]

plot_sparse_data(case_cfg, run_cfg)[source]#

Create the sparse benchmark figure.

Parameters:
case_cfgPlotCase

Case-dependent plotting settings.

run_cfgPlotConfig

Folders and styles for the plotting run.

Returns:
str

Generated filename or formatted text.

Parameters:
Return type:

str

plot_dense_data(case_cfg, run_cfg, grid)[source]#

Create dense spatial-map figures.

Parameters:
case_cfgPlotCase

Case-dependent plotting settings.

run_cfgPlotConfig

Folders and styles for the plotting run.

gridPlotGrid

Spatial coordinates and plot settings.

Returns:
list[str]

Names of the generated dense spatial-map figures.

Parameters:
Return type:

list[str]

plot_results(args)[source]#

Create all figures requested by the plotting configuration.

Comparison mode discovers compatible case folders, while normal mode reads data from one configured output directory.

Parameters:
argsdict

Plotting options.

Returns:
list[str]

Names of all figures generated by the selected plotting workflow.

Parameters:

args (dict)

Return type:

list[str]

main(argv=None)[source]#

Run benchmark plotting from the command line.

The function parses standalone plotting arguments and creates the requested sparse, dense, or performance figures from generated benchmark CSV files. It can also compare compatible results from multiple case directories.

Parameters:
argvlist[str], optional

Arguments to parse instead of sys.argv[1:]. This is primarily used by tests and programmatic callers.

Parameters:

argv (list[str] | None)

Return type:

None