API Reference

This page contains the API reference for PlotEZ.

Main Plotting Functions

PlotEZ - Mundane plotting made easy.

This module provides simplified plotting functions for common visualization tasks.

plotez.plotez.n_plotter(x_data, y_data, n_rows, n_cols, x_labels=None, y_labels=None, data_labels=None, plot_title=None, subplot_titles=None, is_scatter=False, plot_config=None, figure_kwargs=None)[source]

Plot multiple subplots in a grid with optional customization for each subplot.

Parameters:

x_data (ArrayLike | list[ArrayLike]) – List of x-axis data arrays for each subplot.
y_data (ArrayLike | list[ArrayLike]) – List of y-axis data arrays for each subplot.
n_rows (int) – Number of rows in the subplot grid.
n_cols (int) – Number of columns in the subplot grid.
x_labels (list[str] | None) – List of labels for the x-axes of each subplot.
y_labels (list[str] | None) – List of labels for the y-axes of each subplot.
data_labels (list[str] | None) – List of labels for the data series in each subplot.
plot_title (str | None) – Title of the plot.
subplot_titles (list[str] | None) – Titles for the individual subplots, if required.
is_scatter (bool) – If True, plots data as scatter plots; otherwise, plots as line plots.
plot_config (LinePlotConfig | ScatterPlotConfig | None) – Configuration object for line or scatter styling. If None, a default LinePlotConfig is used.
figure_kwargs (dict | None) – Keyword arguments for creating the figure and axes. Passed directly to plt.subplots.

Returns:

A shaped (n_rows, n_cols) array of Matplotlib Axes objects.

Return type:

NDArray

plotez.plotez.plot_density(x_data, x_label='X', y_label='Density', plot_title='Density Plot', data_label=None, hist_config=None, axis=None, figure_kwargs=None)[source]

Plot a density histogram based on the given data and configuration.

Parameters:

x_data (ArrayLike) – The data array used for generating the density plot.
x_label (str) – The label for the x-axis. Default is “X”.
y_label (str) – The label for the y-axis. Default is “Density”.
plot_title (str) – The title of the density plot. Default is “Density Plot”.
data_label (str | None) – The optional label for the dataset being visualized. Default is None.
hist_config (HistogramConfig | dict | None) – The histogram configuration, either as an instance of HistogramConfig, a dictionary, or None. If provided, it is used to configure the histogram and ensures that density=True is set. Default is None.
axis (Axes | None) – The Matplotlib Axes object on which to draw the plot. If None, a new set of axes is created. Default is None.
figure_kwargs (dict | None) – Optional keyword arguments passed when creating a new Matplotlib figure. These arguments are ignored if an existing axis is provided. Default is None.

Returns:

The Matplotlib Axes on which the density plot was drawn.

Return type:

Axes

plotez.plotez.plot_errorband(x_data, y_data, y_lower=None, y_upper=None, x_label='X', y_label='Y', plot_title='XY ErrorBand', data_label='X vs. Y', line=True, band_config=None, line_config=None, axis=None, figure_kwargs=None)[source]

Plot a line graph with a shaded error band representing uncertainty.

Parameters:

x_data (ArrayLike) – The independent variable values to plot.
y_data (ArrayLike) – The central values to plot.
y_lower (int | float | ArrayLike | None) – The lower bound of the error band. If None, it is inferred as a symmetric reflection of y_upper through y_data. At least one of y_lower or y_upper must be provided.
y_upper (int | float | ArrayLike | None) – The upper bound of the error band. If None, it is inferred as a symmetric reflection of y_lower through y_data. At least one of y_lower or y_upper must be provided.
x_label (str) – The label for the x-axis.
y_label (str) – The label for the y-axis.
plot_title (str) – The title of the plot.
data_label (str) – The label for the data series, used in the legend. If line=True, the label is attached to the line. If line=False, it is attached to the band.
line (bool) – Whether to draw a line through the central values over the error band.
band_config (ErrorBandConfig | None) – Configuration for the error band styling. If None, defaults are used.
line_config (LinePlotConfig | dict | None) – Configuration for the line styling. If None, defaults are used.
axis (Axes | None) – Pre-existing Matplotlib axes to draw on. If provided, figure_kwargs is ignored.
figure_kwargs (dict | None) – Keyword arguments passed to plt.subplots when creating a new figure. Ignored if axis is provided.

Returns:

The Matplotlib Axes on which the plot was drawn.

Return type:

Axes

Raises:

ConfigurationError – If both y_lower and y_upper are None.

plotez.plotez.plot_errorband_relative(x_data, y_data, y_lower=None, y_upper=None, x_label='X', y_label='Y', plot_title='XY ErrorBand', data_label='X vs. Y', line=True, band_config=None, line_config=None, axis=None, figure_kwargs=None)[source]

Plot a line graph with a shaded error band using relative (offset) errors.

A convenience wrapper around plot_errorband() where y_lower and y_upper are interpreted as offsets from y_data rather than absolute bounds. Internally, the absolute bounds are computed as y_data - y_lower and y_data + y_upper before passing to plot_errorband().

Parameters:

x_data (ArrayLike) – The independent variable values to plot.
y_data (ArrayLike) – The central values to plot.
y_lower (int | float | ArrayLike | None) – The downward offset from y_data defining the lower band edge. If None, it is inferred as equal to y_upper, implying a symmetric band. At least one of y_lower or y_upper must be provided.
y_upper (int | float | ArrayLike | None) – The upward offset from y_data defining the upper band edge. If None, it is inferred as equal to y_lower, implying a symmetric band. At least one of y_lower or y_upper must be provided.
x_label (str) – The label for the x-axis.
y_label (str) – The label for the y-axis.
plot_title (str) – The title of the plot.
data_label (str) – The label for the data series, used in the legend. If line=True, the label is attached to the line. If line=False, it is attached to the band.
line (bool) – Whether to draw a line through the central values over the error band.
band_config (ErrorBandConfig | None) – Configuration for the error band styling. If None, defaults are used.
line_config (LinePlotConfig | dict | None) – Configuration for the line styling. If None, defaults are used.
axis (Axes | None) – Pre-existing Matplotlib axes to draw on. If provided, figure_kwargs is ignored.
figure_kwargs (dict | None) – Keyword arguments passed to plt.subplots when creating a new figure. Ignored if axis is provided.

Returns:

The Matplotlib Axes on which the plot was drawn.

Return type:

Axes

Raises:

ConfigurationError – If both y_lower and y_upper are None.

Utility Classes

Parameter Classes

class plotez.backend.utilities.LinePlotConfig(color=None, linewidth=None, linestyle=None, alpha=None, marker=None, markersize=None, markerfacecolor=None, markeredgecolor=None, markeredgewidth=None, _extra=<factory>)[source]

Bases: object

Configuration class for line plots.

Parameters:

color (str | list[str] | None)
linewidth (int | float | list[int | float] | None)
linestyle (str | list[str] | None)
alpha (int | float | list[int | float] | None)
marker (str | list[str] | None)
markersize (int | float | list[int | float] | None)
markerfacecolor (str | list[str] | None)
markeredgecolor (str | list[str] | None)
markeredgewidth (int | float | list[int | float] | None)
_extra (dict[str, Any])

__repr__()[source]: Pretty repr showing both explicit and extra params.

get_dict()[source]

Get all parameters as dict for matplotlib.

Return type:: dict[str, Any]

classmethod populate(dictionary)[source]

Create a LinePlotConfig instance from a dictionary, using a mapping for shorthand keys.

Parameters:: dictionary (dict[str, Any])
Return type:: LinePlotConfig

alpha: int | float | list[int | float] | None = None

color: str | list[str] | None = None

linestyle: str | list[str] | None = None

linewidth: int | float | list[int | float] | None = None

marker: str | list[str] | None = None

markeredgecolor: str | list[str] | None = None

markeredgewidth: int | float | list[int | float] | None = None

markerfacecolor: str | list[str] | None = None

markersize: int | float | list[int | float] | None = None

class plotez.backend.utilities.ErrorPlotConfig(color=None, linewidth=None, linestyle=None, alpha=None, ecolor=None, elinewidth=None, marker=None, markersize=None, markerfacecolor=None, markeredgecolor=None, capsize=None, capthick=None, errorevery=None, _extra=<factory>)[source]

Bases: object

Configuration class for error bar plots.

Parameters:

color (str | None)
linewidth (int | float | None)
linestyle (str | None)
alpha (int | float | None)
ecolor (str | None)
elinewidth (int | float | None)
marker (str | None)
markersize (int | float | None)
markerfacecolor (str | None)
markeredgecolor (str | None)
capsize (int | float | None)
capthick (int | float | None)
errorevery (int | tuple | None)
_extra (dict[str, Any])

__repr__()[source]: Pretty repr showing both explicit and extra params.

get_dict()[source]

Get all parameters as dict for matplotlib.

Return type:: dict[str, Any]

classmethod populate(dictionary)[source]

Create an ErrorPlotConfig instance from a dictionary, using a mapping for shorthand keys.

Parameters:: dictionary (dict[str, Any])
Return type:: ErrorPlotConfig

alpha: int | float | None = None

capsize: int | float | None = None

capthick: int | float | None = None

color: str | None = None

ecolor: str | None = None

elinewidth: int | float | None = None

errorevery: int | tuple | None = None

linestyle: str | None = None

linewidth: int | float | None = None

marker: str | None = None

markeredgecolor: str | None = None

markerfacecolor: str | None = None

markersize: int | float | None = None

class plotez.backend.utilities.ErrorBandConfig(color=None, alpha=0.25, linewidth=None, edgecolor=None, linestyle=None, hatch=None, interpolate=None, step=None, _extra=<factory>)[source]

Bases: object

Configuration class for error bands (shaded fill regions).

Parameters:

color (str | list[str] | None)
alpha (int | float | list[int | float])
linewidth (int | float | list[int | float] | None)
edgecolor (str | list[str] | None)
linestyle (str | list[str] | None)
hatch (Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | list[~typing.Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']] | None)
interpolate (bool | None)
step (str | Literal['pre', 'post', 'mid'] | None)
_extra (dict[str, Any])

__repr__()[source]: Return a string representation of the ErrorBandConfig instance.

get_dict()[source]

Get all parameters as dict for matplotlib.

Return type:: dict[str, Any]

classmethod populate(dictionary)[source]

Create an ErrorBandConfig instance from a dictionary, using a mapping for shorthand keys.

Parameters:: dictionary (dict[str, Any])
Return type:: ErrorBandConfig

alpha: int | float | list[int | float] = 0.25

color: str | list[str] | None = None

edgecolor: str | list[str] | None = None

hatch: Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | list[Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']] | None = None

interpolate: bool | None = None

linestyle: str | list[str] | None = None

linewidth: int | float | list[int | float] | None = None

step: str | Literal['pre', 'post', 'mid'] | None = None

class plotez.backend.utilities.ScatterPlotConfig(color=None, s=None, alpha=None, marker=None, cmap=None, edgecolors=None, facecolors=None, _extra=<factory>)[source]

Bases: object

Configuration class for scatter plots.

Parameters:

color (str | list[str] | None)
s (int | float | list[int | float] | None)
alpha (int | float | list[int | float] | None)
marker (str | list[str] | None)
cmap (str | list[str] | None)
edgecolors (str | list[str] | None)
facecolors (str | list[str] | None)
_extra (dict[str, Any])

__repr__()[source]: Pretty repr showing both explicit and extra params.

get_dict()[source]

Get all parameters as dict for matplotlib.

Return type:: dict[str, Any]

classmethod populate(dictionary)[source]

Create a ScatterPlotConfig instance from a dictionary, using a mapping for shorthand keys.

Parameters:: dictionary (dict[str, Any])
Return type:: ScatterPlotConfig

alpha: int | float | list[int | float] | None = None

cmap: str | list[str] | None = None

color: str | list[str] | None = None

edgecolors: str | list[str] | None = None

facecolors: str | list[str] | None = None

marker: str | list[str] | None = None

s: int | float | list[int | float] | None = None

class plotez.backend.utilities.HistogramConfig(bins=None, density=None, histtype=None, color=None, alpha=None, edgecolor=None, facecolor=None, linewidth=None, orientation=None, cumulative=None, hatch=None, _extra=<factory>)[source]

Bases: object

Configuration class for histogram plots.

Parameters:

bins (int | None)
density (bool | None)
histtype (str | None)
color (str | None)
alpha (int | float | None)
edgecolor (str | None)
facecolor (str | None)
linewidth (int | float | None)
orientation (str | None)
cumulative (bool | None)
hatch (str | Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | None)
_extra (dict[str, Any])

__repr__()[source]: Pretty repr showing both explicit and extra params.

get_dict()[source]

Get all parameters are dict for matplotlib.

Return type:: dict[str, Any]

classmethod populate(dictionary)[source]

Create a HistogramConfig instance from a dictionary, using a mapping for shorthand keys.

Parameters:: dictionary (dict[str, Any])

alpha: int | float | None = None

bins: int | None = None

color: str | None = None

cumulative: bool | None = None

density: bool | None = None

edgecolor: str | None = None

facecolor: str | None = None

hatch: str | Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | None = None

histtype: str | None = None

linewidth: int | float | None = None

orientation: str | None = None

Utility Functions

plotez.backend.utilities.plot_or_scatter(axes, scatter)[source]

Return the plot or scatter method based on the specified plot type.

Parameters:

axes – The matplotlib axis on which to apply the plot or scatter method.
scatter (bool) – If True, returns the scatter method; otherwise, returns the plot method.

Returns:

The matplotlib plotting method (axes.scatter if scatter is True, otherwise axes.plot).

Return type:

function

plotez.backend.utilities.split_dictionary(plot_instance)[source]

Split a config instance’s parameters into two separate instances.

Parameters:: plot_instance (LSE) – An instance with parameters stored as lists or tuples. Each parameter should be a list or tuple containing exactly two values, corresponding to settings for the two resulting instances.
Returns:: Two instances of the same type as plot_instance, with parameters split based on the values in plot_instance. The first instance (instance1) and second instance (instance2) will have their attributes set according to the first and second elements, respectively, from each list or tuple in plot_instance.
Return type:: Tuple
Raises:: ValueError – If any parameter in plot_instance is not a list or tuple with exactly two elements.

Notes

The parameters with only one element are broadcast to both instances rather than raising an error.

plotez.backend.utilities.dual_axes_data_validation(x1_data, x2_data, y1_data, y2_data, use_twin_x, axis_labels)[source]

Validate the data and parameters for dual-axes plotting.

Parameters:

x1_data (ArrayLike) – Data for the primary x-axis.
x2_data (ArrayLike | None) – Data for the secondary x-axis (used in dual x-axis plots). Should be None if use_twin_x is True.
y1_data (ArrayLike) – Data for the primary y-axis.
y2_data (ArrayLike | None) – Data for the secondary y-axis (used in dual y-axis plots). Should be None if use_twin_x is False.
use_twin_x (bool) – If True, a dual y-axis plot is expected; otherwise, a dual x-axis plot is expected.
axis_labels (list[str | None]) – List of axis labels. Must have exactly three elements: - Label for the x-axis of the primary plot. - Label for the y-axis of the primary plot. - Label for the secondary axis (x or y).

Raises:

AxisLabelError – If axis_labels does not have exactly three elements.
EmptyDataError – If x1_data or y1_data is empty.
TwinXDataError – If x2_data is provided when use_twin_x is True.
TwinYDataError – If y2_data is provided when use_twin_x is False.

Return type:

tuple[NDArray, NDArray, NDArray | None, NDArray | None]

Convenience / Wrapper Functions

These factory functions provide a concise, keyword-driven way to build config objects without importing the dataclass names directly. All are available at the top-level plotez namespace.

Each function also has a short alias that can be used interchangeably:

Long-form function	Short alias
`line_plot_configuration`	`lpc`
`error_plot_configuration`	`epc`
`error_band_configuration`	`ebc`
scatter_plot_configuration``\| ``spc
`histogram_config`	`hgc`

plotez.backend._wrappers.line_plot_configuration(c=None, lw=None, ls=None, alpha=None, marker=None, ms=None, mfc=None, mec=None, mew=None, **kwargs)[source]

Create a configuration object for line plots.

Parameters:

c (str | list[str] | None) – Line color.
lw (int | float | list[int | float] | None) – Line width.
ls (str | list[str] | None) – Line style (e.g., ‘-’, ‘–’, ‘-.’, ‘:’).
alpha (int | float | list[int | float] | None) – Transparency level (0.0 to 1.0).
marker (str | list[str] | None) – Marker style (e.g., ‘o’, ‘s’, ‘^’).
ms (int | float | list[int | float] | None) – Marker size.
mfc (str | list[str] | None) – Marker face color.
mec (str | list[str] | None) – Marker-edge color.
mew (int | float | list[int | float] | None) – Marker-edge width.
**kwargs – Additional keyword arguments passed to the underlying plot function.

Returns:

Configuration object for line plots.

Return type:

LinePlotConfig

plotez.backend._wrappers.error_plot_configuration(c=None, lw=None, ls=None, alpha=None, ecolor=None, elinewidth=None, marker=None, ms=None, mfc=None, mec=None, capsize=None, capthick=None, errorevery=None, **kwargs)[source]

Create a configuration object for error bar plots.

Parameters:

c (str | None) – Line color.
lw (float | None) – Line width.
ls (str | None) – Line style (e.g., ‘-’, ‘–’, ‘-.’, ‘:’).
alpha (float | None) – Transparency level (0.0 to 1.0).
ecolor (str | None) – Error bar color.
elinewidth (float | None) – Error bar line width.
marker (str | None) – Marker style (e.g., ‘o’, ‘s’, ‘^’).
ms (float | None) – Marker size.
mfc (str | None) – Marker face color.
mec (str | None) – Marker edge color.
capsize (float | None) – Length of the error bar caps in points.
capthick (float | None) – Thickness of error bar caps.
errorevery (int | tuple | None) – Draw error bars on a subset of data points.
**kwargs – Additional keyword arguments passed to the underlying errorbar function.

Returns:

Configuration object for error bar plots.

Return type:

ErrorPlotConfig

plotez.backend._wrappers.error_band_configuration(c=None, alpha=0.25, lw=None, ec=None, ls=None, hatch=None, interpolate=None, step=None, **kwargs)[source]

Create a configuration object for error bands.

Parameters:

c (str | None) – Fill color for the error band.
alpha (float) – Transparency level (0.0 to 1.0).
lw (float | None) – Edge line width.
ec (str | None) – Edge color.
ls (str | None) – Edge line style (e.g., ‘-’, ‘–’, ‘-.’, ‘:’).
hatch (Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | list[~typing.Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*']] | None) – Hatching pattern (e.g., ‘/’, ‘|’, ‘-’, ‘+’, ‘x’).
interpolate (bool | None) – Whether to interpolate the error band.
step (str | Literal['pre', 'post', 'mid'] | None) – Step mode for the band (e.g., ‘pre’, ‘post’, ‘mid’).
**kwargs – Additional keyword arguments passed to the underlying fill function.

Returns:

Configuration object for error bands.

Return type:

ErrorBandConfig

plotez.backend._wrappers.scatter_plot_configuration(c=None, s=None, alpha=None, marker=None, cmap=None, ec=None, fc=None, **kwargs)[source]

Create a configuration object for scatter plots.

Parameters:

c (str | list[str] | None) – Marker color(s).
s (int | float | list[int | float] | None) – Marker size(s) in points squared.
alpha (int | float | list[int | float] | None) – Transparency level (0.0 to 1.0).
marker (str | list[str] | None) – Marker style (e.g., ‘o’, ‘s’, ‘^’).
cmap (str | list[str] | None) – Colormap name or object.
ec (str | list[str] | None) – Edge color(s).
fc (str | list[str] | None) – Face color(s).
**kwargs – Additional keyword arguments passed to the underlying scatter function.

Returns:

Configuration object for scatter plots.

Return type:

ScatterPlotConfig

plotez.backend._wrappers.histogram_config(bins=None, density=None, histtype=None, color=None, alpha=None, edgecolor=None, facecolor=None, linewidth=None, orientation=None, cumulative=None, hatch=None, **kwargs)[source]

Create a HistogramConfig instance with the given parameters.

Parameters:

bins (int | None)
density (bool | None)
histtype (str | None)
color (str | None)
alpha (float | None)
edgecolor (str | None)
facecolor (str | None)
linewidth (float | None)
orientation (str | None)
cumulative (bool | None)
hatch (str | Literal['/', '\\', '|', '-', '+', 'x', 'o', 'O', '.', '*'] | None)

Shorthand Key Reference

All populate() class methods and wrapper functions accept shorthand aliases in place of full matplotlib parameter names. The tables below list every recognised alias.

Line / Error-bar parameters

Alias	Full parameter name
`ls`	`linestyle`
`lw`	`linewidth`
`c`	`color`
`ms`	`markersize`
`mec`	`markeredgecolor`
`mfc`	`markerfacecolor`
`mew`	`markeredgewidth`

Error-bar-only parameters

The ErrorPlotConfig / epc wrapper also accepts all line aliases above, plus:

Alias	Full parameter name
`ecolor`	`ecolor`
`elinewidth`	`elinewidth`
`capsize`	`capsize`
`capthick`	`capthick`

Scatter parameters

Alias	Full parameter name
`c`	`color`
`s`	`size`
`ec`	`edgecolors`
`fc`	`facecolors`

Error band parameters

The ErrorBandConfig / ebc wrapper accepts the following shorthand aliases:

Alias	Full parameter name
`c`	`color`
`ec`	`edgecolor`
`lw`	`linewidth`
`ls`	`linestyle`

hatch, interpolate, and step are passed through under their own names.

Histogram parameters

The HistogramConfig / hgc wrapper accepts the following shorthand aliases (via populate() and the hgc factory function):

Alias	Full parameter name
`c`	`color`
`lw`	`linewidth`
`ec`	`edgecolor`

bins, density, histtype, alpha, facecolor, orientation, cumulative, and hatch are passed through under their own names.

Error Handling

PlotEZ Error Handling.

Custom exceptions for plotting operations.

exception plotez.backend.error_handling.AxisLabelError[source]

Bases: ConfigurationError

Raised when the axis_labels sequence does not contain exactly three elements.

Notes

Dual-axes functions require labels for three axes: primary x, primary y, and the secondary axis (either x or y).

exception plotez.backend.error_handling.ColumnCountError[source]

Bases: DataError

Raised when a data file does not contain exactly two columns.

Notes

plot_two_column_file expects files with exactly one x-column and one y-column. Any other column count triggers this error.

exception plotez.backend.error_handling.ConfigurationError[source]

Bases: PlotError

Base class for plot configuration and parameter errors.

Notes

Inherit from this class for errors that arise from incorrect or conflicting plot configuration options rather than from the data itself.

exception plotez.backend.error_handling.DataError[source]

Bases: PlotError

Base class for data-related plotting errors.

Notes

Inherit from this class for any error that stems from invalid, malformed, or incompatible input data arrays or files.

exception plotez.backend.error_handling.EmptyDataError[source]

Bases: DataError

Raised when required primary x or y data is empty.

Notes

At least one data point must be present in the primary x and y arrays before a plot can be constructed.

exception plotez.backend.error_handling.LabelConflictWarning[source]

Bases: UserWarning

Issued when auto_label=True overrides user-provided labels.

Notes

When auto_label is enabled, it silently replaces any explicitly supplied axis labels, data labels, or plot titles with auto-generated defaults. This warning is raised to make that substitution visible to the caller. Use warnings.filterwarnings to suppress or escalate it as needed.

exception plotez.backend.error_handling.OrientationError[source]

Bases: PlotError

Raised when an invalid or unexpected orientation is used in a plot.

Notes

This error occurs when the orientation parameter for a plot is set incorrectly or does not match the expected format.

exception plotez.backend.error_handling.PlotError[source]

Bases: Exception

Base class for exceptions related to plotting operations.

Notes

This serves as the parent class for all plotting-related errors. Specific exceptions related to plot configuration or data issues should inherit from this class.

exception plotez.backend.error_handling.ShapeError[source]

Bases: DataError

Raised when an array has an unexpected or incompatible shape.

Notes

Typically raised when an error array intended for asymmetric error bars does not satisfy the required (2, N) shape contract.

exception plotez.backend.error_handling.TwinXDataError[source]

Bases: ConfigurationError

Is raised when x2_data is supplied for a dual-Y-axis (use_twin_x=True) plot.

Notes

A dual-Y-axis plot shares the x-axis between both datasets; providing a separate x2_data is therefore contradictory and not permitted.

exception plotez.backend.error_handling.TwinYDataError[source]

Bases: ConfigurationError

Is raised when y2_data is supplied for a dual-X-axis (use_twin_x=False) plot.

Notes

A dual-X-axis plot shares the y-axis between both datasets; providing a separate y2_data is therefore contradictory and not permitted.

Type Aliases

Note

AxesFigReturn is deprecated as of v0.3.2 and kept only as a backward-compatible alias for AxesReturn. It will be removed in a future release. Use AxesReturn (Axes | tuple[Axes, Axes] | NDArray) for all new code.

Type aliases used throughout PlotEZ.

Public aliases
Name	Description
`NDArray`	Re-export of `numpy.ndarray` but as a typehint – any array-like input accepted by NumPy.
`AxesReturn`	`Axes \| tuple[Axes, Axes] \| NDArray` – unified return type for all plot functions. Single-axis functions return `Axes`; dual-axis functions return `tuple[Axes, Axes]`; grid functions (`n_plotter`, `two_subplots`) return a shaped `NDArray` of `Axes`.