Source code for matador.plotting.pxrd_plotting

# coding: utf-8
# Distributed under the terms of the MIT License.

""" This file implements plotting routines specifically
for the PXRD objects defined in the
matador.fingerprints.pxrd module.


from matador.plotting.plotting import plotting_function
from matador.utils.cell_utils import get_space_group_label_latex
from matador.crystal import Crystal

__all__ = ['plot_pxrd']

[docs]@plotting_function def plot_pxrd( pxrds, two_theta_range=None, rug=False, rug_height=0.05, rug_offset=0.04, offset=None, ax=None, labels=None, figsize=None, text_offset=0.1, filename=None, **kwargs ): """ Plot PXRD or PXRDs. Parameters: pxrds (list or matador.fingerprints.pxrd.PXRD): the PXRD or list of PXRDs to plot. Keyword arguments: two_theta_range (tuple): plotting limits for 2theta rug (bool): whether to provide a rug plot of all peaks. rug_height (float): size of rug ticks. rug_offset (float): offset of rug ticks. offset (float): extra space added between patterns (as fraction of max intensity). Default 0.1. labels (list of str): list of labels to plot alongside pattern. figsize (tuple): specify a figure size, the default scales with the number of PXRDs to be plotted. ax (matplotlib.Axis): optional axis object to plot on. text_offset (float): amount by which to offset the labels. filename (str): optional filename for saving. """ import matplotlib.pyplot as plt if not isinstance(pxrds, list): pxrds = [pxrds] if labels is not None and not isinstance(labels, list): labels = [labels] if figsize is None: _user_default_figsize = plt.rcParams.get('figure.figsize', (8, 6)) height = len(pxrds) * max(0.5, _user_default_figsize[1] / 1.5 / len(pxrds)) figsize = (_user_default_figsize[0], height) if ax is None: fig, ax = plt.subplots(figsize=figsize) if offset is None and rug: offset = 0.2 elif offset is None: offset = 0.1 colour_cycle = ax._get_lines.prop_cycler for ind, pxrd in enumerate(pxrds): if isinstance(pxrd, Crystal): pxrd = pxrd.pxrd elif isinstance(pxrd, dict) and 'pxrd' in pxrd: pxrd = pxrd['pxrd'] c = next(colour_cycle).get('color') if labels: label = labels[ind] else: label = get_space_group_label_latex(pxrd.spg) + '-' + pxrd.formula ax.plot(pxrd.two_thetas, (1 - offset) * pxrd.pattern + ind, c=c) ax.text(0.95, ind+text_offset, label, transform=ax.get_yaxis_transform(), horizontalalignment='right') if rug: import numpy as np peaks = np.unique(pxrd.peak_positions) for peak in peaks: ax.plot([peak, peak], [ind-rug_height-rug_offset, ind-rug_offset], c=c, alpha=0.5) if len(pxrds) > 1: ax.set_yticks([]) else: import numpy as np ax.set_yticks(np.linspace(0, 1, 5, endpoint=True)) ax.set_ylim(-0.2, len(pxrds)+0.1) if two_theta_range is not None: ax.set_xlim(*two_theta_range) ax.set_ylabel('Relative intensity') ax.set_xlabel('$2\\theta$ (degrees)') if any([kwargs.get('pdf'), kwargs.get('svg'), kwargs.get('png')]): bbox_extra_artists = None if filename is None: filename = '-'.join([pxrd.formula for pxrd in pxrds]) + '_pxrd' if kwargs.get('pdf'): plt.savefig('{}.pdf'.format(filename), bbox_inches='tight', transparent=True, bbox_extra_artists=bbox_extra_artists) if kwargs.get('svg'): plt.savefig('{}.svg'.format(filename), bbox_inches='tight', transparent=True, bbox_extra_artists=bbox_extra_artists) if kwargs.get('png'): plt.savefig('{}.png'.format(filename), bbox_inches='tight', transparent=True, bbox_extra_artists=bbox_extra_artists)