epyr.eprplot

Simple plotting module for EPR data from eprload.

This module provides simple plotting functions for data obtained with eprload(): - plot_1d: Plot 1D EPR spectra - plot_2d_map: Plot 2D data as color map - plot_2d_waterfall: Plot 2D data as waterfall plot

Based on the _plot_data function from eprload.py

Functions

plot_1d(x, y[, params, title, ax])

Plot 1D EPR data.

plot_2d_map(x, y[, params, title, ax, cmap, ...])

Plot 2D EPR data as a color map.

plot_2d_slicer(x, y[, params, title, ...])

Interactive 2D EPR data slicer with a slider control.

plot_2d_waterfall(x, y[, params, title, ax, ...])

Plot 2D EPR data as a waterfall plot.
epyr.eprplot.plot_1d(x, y, params=None, title=None, ax=None)[source]

Plot 1D EPR data.

Parameters:

  • x (np.ndarray, list, or None) – X-axis data from eprload. Falls back to point index if None or shape mismatch.

  • y (np.ndarray) – 1D EPR signal array.

  • params (dict, optional) – Parameter dictionary from eprload, used to extract axis labels and units.

  • title (str, optional) – Plot title.

  • ax (matplotlib.axes.Axes, optional) – Axes to draw on. A new figure is created if not provided.

Returns:

  • fig (matplotlib.figure.Figure)

  • ax (matplotlib.axes.Axes)

Return type:

Tuple[Figure, Axes]

Examples

>>> from epyr import eprload, plot_1d
>>> x, y, params, _ = eprload("examples/data/130406SB_CaWO4_Er_CW_5K_20.DSC")
>>> fig, ax = plot_1d(x, y, params, title="CaWO4:Er, 5 K")

Reuse an existing axes (subplot composition):

>>> import matplotlib.pyplot as plt
>>> fig, axes = plt.subplots(1, 2)
>>> plot_1d(x, y, params, ax=axes[0])
epyr.eprplot.plot_2d_map(x, y, params=None, title=None, ax=None, cmap='magma', vmin=None, vmax=None)[source]

Plot 2D EPR data as a color map.

Parameters:

  • x (np.ndarray, list, or None) – Axis data from eprload. A list of two arrays sets both x and y axes.

  • y (np.ndarray) – 2D EPR signal array, shape (ny, nx).

  • params (dict, optional) – Parameter dictionary from eprload, used to extract axis labels and units.

  • title (str, optional) – Plot title.

  • ax (matplotlib.axes.Axes, optional) – Axes to draw on. A new figure is created if not provided.

  • cmap (str, optional) – Matplotlib colormap name (default: “magma”).

  • vmin (float, optional) – Lower bound of the color scale. Defaults to data minimum.

  • vmax (float, optional) – Upper bound of the color scale. Defaults to data maximum.

Returns:

  • fig (matplotlib.figure.Figure)

  • ax (matplotlib.axes.Axes)

Return type:

Tuple[Figure, Axes]

Examples

>>> fig, ax = plot_2d_map(x, y, params, vmin=-100, vmax=100)
>>> fig, ax = plot_2d_map(x, y, params, vmin=0)  # clip negatives
epyr.eprplot.plot_2d_waterfall(x, y, params=None, title=None, ax=None, offset_factor=0.5, max_traces=20, cmap='viridis', lw=0.75, clip_factor=None)[source]

Plot 2D EPR data as a waterfall plot.

Parameters:

  • x (np.ndarray, list, or None) – Axis data from eprload. A list of two arrays sets both x and y axes.

  • y (np.ndarray) – 2D EPR signal array, shape (ny, nx).

  • params (dict, optional) – Parameter dictionary from eprload, used to extract axis labels and units.

  • title (str, optional) – Plot title.

  • ax (matplotlib.axes.Axes, optional) – Axes to draw on. A new figure is created if not provided.

  • offset_factor (float, optional) – Vertical spacing between traces as a fraction of the total data range (default: 0.5).

  • max_traces (int, optional) – Maximum number of traces to display. If ny > max_traces, traces are subsampled uniformly (default: 20).

  • cmap (str, optional) – Matplotlib colormap used to color-code traces (default: “viridis”).

  • lw (float, optional) – Line width for each trace (default: 0.75).

  • clip_factor (float, optional) – Clip each trace at clip_factor * max(|trace|) before adding the vertical offset. None disables clipping (default). A value of 0.5 clips at 50% of the trace maximum.

Returns:

  • fig (matplotlib.figure.Figure)

  • ax (matplotlib.axes.Axes)

Return type:

Tuple[Figure, Axes]

Examples

>>> from epyr import eprload, plot_2d_waterfall
>>> x, y, params, _ = eprload("examples/data/Rabi2D_GdCaWO4_13dB_3057G.DSC")
>>> fig, ax = plot_2d_waterfall(x, y, params, max_traces=10)

Tighter spacing with strong clipping (useful for noisy backgrounds):

>>> fig, ax = plot_2d_waterfall(x, y, params, offset_factor=0.2, clip_factor=0.3)
epyr.eprplot.plot_2d_slicer(x, y, params=None, title=None, slice_direction='horizontal', cmap='magma')[source]

Interactive 2D EPR data slicer with a slider control.

Parameters:

  • x (np.ndarray, list, or None) – Axis data from eprload. A list of two arrays sets both x and y axes.

  • y (np.ndarray) – 2D EPR signal array, shape (ny, nx).

  • params (dict, optional) – Parameter dictionary from eprload, used to extract axis labels and units.

  • title (str, optional) – Plot title shown above the active slice panel.

  • slice_direction ({'horizontal', 'vertical'}, optional) – Axis along which to slice (default: ‘horizontal’).

  • cmap (str, optional) – Matplotlib colormap name for the overview panel (default: “magma”).

Returns:

Keys: ‘figure’, ‘ax_main’, ‘ax_overview’, ‘slider’, ‘line’, ‘slice_line’.

Return type:

dict

Notes

Requires an interactive matplotlib backend. In Jupyter, activate with %matplotlib widget or %matplotlib notebook before calling.

Examples

>>> from epyr import eprload, plot_2d_slicer
>>> x, y, params, _ = eprload("examples/data/Rabi2D_GdCaWO4_13dB_3057G.DSC")
>>> handles = plot_2d_slicer(x, y, params, slice_direction="vertical")
>>> handles["slider"].set_val(50)  # programmatic slider control