scatter_plot_matrix module¶

Draw a scatter matrix from a Dataset.

The ScatterMatrix class implements the scatter plot matrix, which is a way to visualize \(n\) samples of a multi-dimensional vector

\[x=(x_1,x_2,\ldots,x_d)\in\mathbb{R}^d\]

in several 2D subplots where the (i,j) subplot represents the cloud of points

\[\left(x_i^{(k)},x_j^{(k)}\right)_{1\leq k \leq n}\]

while the (i,i) subplot represents the empirical distribution of the samples

\[x_i^{(1)},\ldots,x_i^{(n)}\]

by means of an histogram or a kernel density estimator.

A variable name can be passed to the DatasetPlot.execute() method by means of the classifier keyword in order to color the curves according to the value of the variable name. This is useful when the data is labeled.

class gemseo.post.dataset.scatter_plot_matrix.ScatterMatrix(dataset, variable_names=None, classifier=None, kde=False, size=25, marker='o', plot_lower=True, plot_upper=True, trend=Trend.NONE, **options)[source]¶

Bases: DatasetPlot

Scatter plot matrix.

Parameters:

dataset (Dataset) – The dataset containing the data to plot.
variable_names (Iterable[str] | None) – The names of the variables to consider. If None, consider all the variables of the dataset.
classifier (str | None) – The name of the variable to build the cluster.
kde (bool) –
The type of the distribution representation. If True, plot kernel-density estimator on the diagonal. Otherwise, use histograms.

By default it is set to False.
size (int) –
The size of the points.

By default it is set to 25.
marker (str) –
The marker for the points.

By default it is set to “o”.
plot_lower (bool) –
Whether to plot the lower part.

By default it is set to True.
plot_upper (bool) –
Whether to plot the upper part.

By default it is set to True.
trend (Trend | TrendFunctionCreator) –
The trend function to be added on the scatter plots or a function creating a trend function from a set of xy-points.

By default it is set to “none”.
**options (Any) – The options of the underlying pandas scatter matrix.

Raises:

ValueError – If the dataset is empty.

class PlotEngine(value)¶

Bases: StrEnum

An engine of plots.

MATPLOTLIB = 'MatplotlibPlotFactory'¶

PLOTLY = 'PlotlyPlotFactory'¶

class Trend(value)¶

Bases: StrEnum

A type of trend.

CUBIC = 'cubic'¶

LINEAR = 'linear'¶

NONE = 'none'¶

QUADRATIC = 'quadratic'¶

RBF = 'rbf'¶

execute(save=True, show=False, file_path='', directory_path=None, file_name=None, file_format='png', file_name_suffix='', **engine_parameters)¶

Execute the post-processing.

Parameters:

save (bool) –
If True, save the plot.

By default it is set to True.
show (bool) –
If True, display the plot.

By default it is set to False.
file_path (str | Path) –
The path of the file to save the figures. If empty, create a file path from directory_path, file_name and file_format.

By default it is set to “”.
directory_path (str | Path | None) – The path of the directory to save the figures. If None, use the current working directory.
file_name (str | None) – The name of the file to save the figures. If None, use a default one generated by the post-processing.
file_format (str) –
A file format, e.g. ‘png’, ‘pdf’, ‘svg’, …

By default it is set to “png”.
file_name_suffix (str) –
The suffix to be added to the file name.

By default it is set to “”.
**engine_parameters (Any) – The parameters specific to the plot engine.

Returns:

The figures.

Return type:

list[Figure]

DEFAULT_PLOT_ENGINE: ClassVar[PlotEngine] = 'MatplotlibPlotFactory'¶: The default engine of plots.

FILE_FORMATS_TO_PLOT_ENGINES: ClassVar[dict[str, PlotEngine]] = {'html': PlotEngine.PLOTLY}¶

The file formats bound to the engines of plots.

The method execute() uses this dictionary to select the engine of plots associated with its file_format argument. If missing, the method uses the DEFAULT_PLOT_ENGINE.

property color: str | list[str]¶: The colors for the series; if empty, use a default one.

property colormap: str¶: The color map.

property dataset: Dataset¶: The dataset.

property fig_size: FigSizeType¶: The figure size.

property fig_size_x: float¶: The x-component of figure size.

property fig_size_y: float¶: The y-component of figure size.

property font_size: int¶: The font size.

property labels: Mapping[str, str]¶: The labels for the variables.

property legend_location: str¶: The location of the legend.

property linestyle: str | list[str]¶: The line style for the series; if empty, use a default one.

property marker: str | list[str]¶: The marker for the series; if empty, use a default one.

property output_files: list[str]¶: The paths to the output files.

property rmax: float | None¶: The maximum value on the r-axis; if None, compute it from data.

property rmin: float | None¶: The minimum value on the r-axis; if None, compute it from data.

property title: str¶: The title of the plot.

property xlabel: str¶: The label for the x-axis.

property xmax: float | None¶: The maximum value on the x-axis; if None, compute it from data.

property xmin: float | None¶: The minimum value on the x-axis; if None, compute it from data.

property xtick_rotation: str¶: The rotation angle in degrees for the x-ticks.

property ylabel: str¶: The label for the y-axis.

property ymax: float | None¶: The maximum value on the y-axis; if None, compute it from data.

property ymin: float | None¶: The minimum value on the y-axis; if None, compute it from data.

property zlabel: str¶: The label for the z-axis.

property zmax: float | None¶: The maximum value on the z-axis; if None, compute it from data.

property zmin: float | None¶: The minimum value on the z-axis; if None, compute it from data.

Examples using ScatterMatrix¶

Parameter space

Diagonal design of experiments