LoadingsPlot#

class chemotools.plotting.LoadingsPlot(loadings: ndarray, *, feature_names: ndarray | list | None = None, components: int | list[int] = 0, component_label: str = 'PC')[ソース]

ベースクラス: BasePlot

Loadings plot implementing Display protocol for model inspection.

This class creates line plots of model loadings (feature weights), following the same design pattern as SpectraPlot and ScoresPlot. Supports plotting single or multiple components overlaid on the same plot.

パラメータ:

  • loadings (np.ndarray) -- Loadings array with shape (n_features, n_components).

  • feature_names (np.ndarray or list, optional) -- Names/values for features (x-axis). Can be wavelengths, wavenumbers, feature indices, etc. If None, uses feature indices [0, 1, 2, ...].

  • components (int or list[int], optional) -- Which component(s) to plot. Can be: - Single int (default 0): plots one component - List of ints: plots multiple components overlaid with legend Uses 0-based indexing.

  • component_label (str, optional) -- Prefix for component naming in legend and titles (default "PC"). Use "LV" for PLS models, "PC" for PCA models, "IC" for ICA, etc.

例外:

ValueError -- If component index exceeds the available components in the loadings array.

サンプル

Basic usage with single component:

>>> loadings = model.components_.T  # Shape: (n_features, n_components)
>>> wavenumbers = np.linspace(400, 2500, n_features)
>>> plot = LoadingsPlot(loadings, feature_names=wavenumbers, components=0)
>>> fig = plot.show(title="PC1 Loadings")

Plot multiple components overlaid:

>>> plot = LoadingsPlot(
...     loadings,
...     feature_names=wavenumbers,
...     components=[0, 1, 2],  # Plot PC1, PC2, PC3 together
... )
>>> fig = plot.show(
...     title="First 3 Principal Components",
...     xlabel='Wavenumber (cm⁻¹)',
...     ylabel='Loading Coefficient'
... )

With custom axis labels:

>>> plot = LoadingsPlot(
...     loadings,
...     feature_names=wavenumbers,
...     components=0
... )
>>> fig = plot.show(
...     title="PLS LV1 Loadings",
...     xlabel="Wavenumber (cm⁻¹)",
...     ylabel="Loading Coefficient"
... )

Zoom into a spectral region:

>>> plot = LoadingsPlot(loadings, feature_names=wavenumbers, components=[0, 1])
>>> fig = plot.show(title="C-H Region", xlim=(2800, 3000))

Create subplots for different component groups:

>>> fig, axes = plt.subplots(2, 1, figsize=(12, 8))
>>> plot1 = LoadingsPlot(loadings, feature_names=wavelengths, components=[0, 1])
>>> plot1.render(ax=axes[0])
>>> plot2 = LoadingsPlot(loadings, feature_names=wavelengths, components=[0, 1])
>>> plot2.render(ax=axes[1], xlim=(2800, 3000))
>>> plt.tight_layout()

Custom styling:

>>> plot.show(
...     title="Styled Loadings",
...     linewidth=2,
...     alpha=0.8
... )
show(figsize=(12, 4), title=None, xlabel='X-axis', ylabel='Y-axis', xlim=None, ylim=None, **kwargs) → Figure[ソース]

Show the loadings plot with optional customization.

パラメータ:

  • figsize (tuple, optional) -- Figure size as (width, height) in inches. Default is (12, 4).

  • title (str, optional) -- Title for the plot. If None, a default title is generated.

  • xlabel (str, optional) -- X-axis label. Default is "X-axis".

  • ylabel (str, optional) -- Y-axis label. Default is "Y-axis".

  • xlim (tuple, optional) -- X-axis limits as (xmin, xmax). Default is None (auto).

  • ylim (tuple, optional) -- Y-axis limits as (ymin, ymax). Default is None (auto).

  • **kwargs (Any) -- Additional keyword arguments passed to the plot function.

戻り値:

The matplotlib Figure object containing the plot.

戻り値の型:

Figure

render(ax: Axes | None = None, *, xlabel: str | None = None, ylabel: str | None = None, xlim: tuple[float, float] | None = None, ylim: tuple[float, float] | None = None, **kwargs: Any) → tuple[Figure, Axes][ソース]

Render the plot on the given axes or create new ones.

パラメータ:

  • ax (Axes, optional) -- Matplotlib axes to plot on. If None, creates new figure and axes.

  • xlabel (str, optional) -- X-axis label. Default is "Feature".

  • ylabel (str, optional) -- Y-axis label. Default is "Loading".

  • xlim (tuple[float, float], optional) -- X-axis limits as (xmin, xmax).

  • ylim (tuple[float, float], optional) -- Y-axis limits as (ymin, ymax).

  • **kwargs (Any) -- Additional keyword arguments passed to the plot function.

戻り値:

  • fig (Figure) -- The matplotlib Figure object.

  • ax (Axes) -- The matplotlib Axes object with the rendered plot.

サンプル

Render on existing axes:

>>> fig, ax = plt.subplots()
>>> plot.render(ax=ax)

Create subplots:

>>> fig, axes = plt.subplots(2, 1, figsize=(12, 8))
>>> plot1.render(ax=axes[0])
>>> plot2.render(ax=axes[1])

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