467 lines
18 KiB
Python
467 lines
18 KiB
Python
import matplotlib.pyplot as plt
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from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
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import pandas as pd
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import numpy as np
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import math
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import ipywidgets as widgets
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import beamtime.xrd as xrd
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import beamtime.auxillary as aux
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import beamtime.plotting as btp
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def plot_diffractogram(data, options={}):
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''' Plots a diffractogram.
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Input:
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data (dict): Must include path = string to diffractogram data, and plot_kind = (recx, beamline, image)'''
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# Update options
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required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim', 'normalise', 'offset', 'offset_x', 'offset_y',
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'reflections_plot', 'reflections_indices', 'reflections_data', 'plot_kind', 'palettes', 'interactive', 'rc_params', 'format_params', 'interactive_session_active']
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default_options = {
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'x_vals': '2th',
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'y_vals': 'I',
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'ylabel': 'Intensity', 'xlabel': '2theta',
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'xunit': 'deg', 'yunit': 'a.u.',
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'xlim': None, 'ylim': None,
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'normalise': True,
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'offset': True,
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'offset_x': 0,
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'offset_y': 1,
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'line': True, # whether or not to plot diffractogram as a line plot
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'scatter': False, # whether or not to plot individual data points
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'reflections_plot': False, # whether to plot reflections as a plot
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'reflections_indices': False, # whether to plot the reflection indices
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'reflections_data': None, # Should be passed as a list of dictionaries on the form {path: rel_path, reflection_indices: number of indices, colour: [r,g,b], min_alpha: 0-1]
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'plot_kind': None,
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'palettes': [('qualitative', 'Dark2_8')],
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'interactive': False,
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'interactive_session_active': False,
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'rc_params': {},
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'format_params': {},
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}
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if 'offset_y' not in options.keys():
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if len(data['path']) > 10:
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default_options['offset_y'] = 0.05
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options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
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# Convert data['path'] to list to allow iteration over this to accommodate both single and multiple diffractograms
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if not isinstance(data['path'], list):
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data['path'] = [data['path']]
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# Check if there is some data stored already, load in data if not. This speeds up replotting in interactive mode.
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if not 'diffractogram' in data.keys():
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# Initialise empty list for diffractograms and wavelengths
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data['diffractogram'] = [None for _ in range(len(data['path']))]
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data['wavelength'] = [None for _ in range(len(data['path']))]
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for index in range(len(data['path'])):
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diffractogram, wavelength = xrd.io.read_data(data=data, options=options, index=index)
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data['diffractogram'][index] = diffractogram
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data['wavelength'][index] = wavelength
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else:
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if not isinstance(data['diffractogram'], list):
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data['diffractogram'] = [data['diffractogram']]
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data['wavelength'] = [data['wavelength']]
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# Sets the xlim if this has not bee specified
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if not options['xlim']:
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options['xlim'] = [diffractogram[options['x_vals']].min(), diffractogram[options['x_vals']].max()]
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if options['interactive_session_active']:
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if options['offset']:
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if (options['offset_x'] != options['current_offset_x']) or (options['offset_y'] != options['current_offset_y']):
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for i, (diff, wl) in enumerate(zip(data['diffractogram'], data['wavelength'])):
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xrd.io.apply_offset(diff, wl, i, options)
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# Start inteactive session with ipywidgets. Disables options['interactive'] in order for the interactive loop to not start another interactive session
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if options['interactive']:
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options['interactive'] = False
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options['interactive_session_active'] = True
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plot_diffractogram_interactive(data=data, options=options)
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return
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# Makes a list out of reflections_data if it only passed as a dict, as it will be looped through later
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if options['reflections_data']:
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if not isinstance(options['reflections_data'], list):
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options['reflections_data'] = [options['reflections_data']]
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# Determine number of subplots and height ratios between them
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if len(options['reflections_data']) >= 1:
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options = determine_grid_layout(options=options)
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# Prepare plot, and read and process data
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fig, ax = btp.prepare_plot(options=options)
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# Assign the correct axes
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if options['reflections_plot'] or options['reflections_indices']:
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if options['reflections_indices']:
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indices_ax = ax[0]
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if options['reflections_plot']:
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ref_axes = [axx for axx in ax[range(1,len(options['reflections_data'])+1)]]
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else:
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ref_axes = [axx for axx in ax[range(0,len(options['reflections_data']))]]
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ax = ax[-1]
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if len(data['path']) < 10:
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colours = btp.generate_colours(options['palettes'])
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else:
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colours = btp.generate_colours(['black'], kind='single')
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for diffractogram in data['diffractogram']:
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if options['line']:
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diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, c=next(colours), zorder=1)
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if options['scatter']:
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ax.scatter(x=diffractogram[options['x_vals']], y = diffractogram[options['y_vals']], c=[(1,1,1,0)], edgecolors=[next(colours)], linewidths=plt.rcParams['lines.markeredgewidth'], zorder=2) #, edgecolors=np.array([next(colours)]))
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fig, ax = btp.adjust_plot(fig=fig, ax=ax, options=options)
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# Make the reflection plots. By default, the wavelength of the first diffractogram will be used for these.
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if options['reflections_plot'] and options['reflections_data']:
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options['xlim'] = ax.get_xlim()
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options['to_wavelength'] = data['wavelength'][0]
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for reference, axis in zip(options['reflections_data'], ref_axes):
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plot_reflection_table(data=reference, ax=axis, options=options)
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# Print the reflection indices. By default, the wavelength of the first diffractogram will be used for this.
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if options['reflections_indices'] and options['reflections_data']:
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options['xlim'] = ax.get_xlim()
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options['to_wavelength'] = data['wavelength'][0]
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for reference in options['reflections_data']:
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plot_reflection_indices(data=reference, ax=indices_ax, options=options)
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if options['interactive_session_active']:
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btp.update_widgets(options=options)
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return diffractogram, fig, ax
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def determine_grid_layout(options):
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nrows = 1 if not options['reflections_indices'] else 2
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if options['reflections_plot']:
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for reference in options['reflections_data']:
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nrows += 1
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options['format_params']['nrows'] = nrows
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options['format_params']['grid_ratio_height'] = [1 for i in range(nrows-1)]+[10]
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return options
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def plot_diffractogram_interactive(data, options):
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minmax = {'2th': [None, None], '2th_cuka': [None, None], '2th_moka': [None, None], 'd': [None, None], '1/d': [None, None], 'q': [None, None], 'q2': [None, None], 'q4': [None, None]}
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update_minmax(minmax, data)
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ymin, ymax = None, None
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for index, diffractogram in enumerate(data['diffractogram']):
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if not ymin or (ymin > (diffractogram['I'].min())): #+index*options['offset_y'])):
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ymin = diffractogram['I'].min()#+index*options['offset_y']
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if not ymax or (ymax < (diffractogram['I'].max())):#+index*options['offset_y'])):
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ymax = diffractogram['I'].max()#+index*options['offset_y']
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ymin_start = ymin - 0.1*ymax
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ymax_start = ymax+0.2*ymax
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ymin = ymin - 5*ymax
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ymax = ymax*5
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options['widgets'] = {
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'xlim': {
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'w': widgets.FloatRangeSlider(value=[minmax['2th'][0], minmax['2th'][1]], min=minmax['2th'][0], max=minmax['2th'][1], step=0.5, layout=widgets.Layout(width='95%')),
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'state': '2th',
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'2th_default': {'min': minmax['2th'][0], 'max': minmax['2th'][1], 'value': [minmax['2th'][0], minmax['2th'][1]], 'step': 0.5},
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'2th_cuka_default': {'min': minmax['2th_cuka'][0], 'max': minmax['2th_cuka'][1], 'value': [minmax['2th_cuka'][0], minmax['2th_cuka'][1]], 'step': 0.5},
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'2th_moka_default': {'min': minmax['2th_moka'][0], 'max': minmax['2th_moka'][1], 'value': [minmax['2th_moka'][0], minmax['2th_moka'][1]], 'step': 0.5},
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'd_default': {'min': minmax['d'][0], 'max': minmax['d'][1], 'value': [minmax['d'][0], minmax['d'][1]], 'step': 0.5},
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'1/d_default': {'min': minmax['1/d'][0], 'max': minmax['1/d'][1], 'value': [minmax['1/d'][0], minmax['1/d'][1]], 'step': 0.5},
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'q_default': {'min': minmax['q'][0], 'max': minmax['q'][1], 'value': [minmax['q'][0], minmax['q'][1]], 'step': 0.5},
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'q2_default': {'min': minmax['q2'][0], 'max': minmax['q2'][1], 'value': [minmax['q2'][0], minmax['q2'][1]], 'step': 0.5},
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'q4_default': {'min': minmax['q4'][0], 'max': minmax['q4'][1], 'value': [minmax['q4'][0], minmax['q4'][1]], 'step': 0.5}
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}
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}
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if options['reflections_data']:
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w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options),
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scatter=widgets.ToggleButton(value=False),
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line=widgets.ToggleButton(value=True),
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reflections_plot=widgets.ToggleButton(value=True),
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reflections_indices=widgets.ToggleButton(value=False),
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x_vals=widgets.Dropdown(options=['2th', 'd', '1/d', 'q', 'q2', 'q4', '2th_cuka', '2th_moka'], value='2th', description='X-values'),
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xlim=options['widgets']['xlim']['w'],
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ylim=widgets.FloatRangeSlider(value=[ymin_start, ymax_start], min=ymin, max=ymax, step=0.5, layout=widgets.Layout(width='95%')),
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offset_y=widgets.BoundedFloatText(value=options['offset_y'], min=-5, max=5, step=0.01),
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offset_x=widgets.BoundedFloatText(value=options['offset_x'], min=-1, max=1, step=0.01)
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)
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else:
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w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options),
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scatter=widgets.ToggleButton(value=False),
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line=widgets.ToggleButton(value=True),
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xlim=options['widgets']['xlim']['w'])
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display(w)
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def update_minmax(minmax, data):
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''' Finds minimum and maximum values of each column and updates the minmax dictionary to contain the correct values.
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Input:
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minmax (dict): contains '''
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for index, diffractogram in enumerate(data['diffractogram']):
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if not minmax['2th'][0] or diffractogram['2th'].min() < minmax['2th'][0]:
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minmax['2th'][0] = diffractogram['2th'].min()
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min_index = index
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if not minmax['2th'][1] or diffractogram['2th'].max() > minmax['2th'][1]:
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minmax['2th'][1] = diffractogram['2th'].max()
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max_index = index
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minmax['2th_cuka'][0], minmax['2th_cuka'][1] = data['diffractogram'][min_index]['2th_cuka'].min(), data['diffractogram'][max_index]['2th_cuka'].max()
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minmax['2th_moka'][0], minmax['2th_moka'][1] = data['diffractogram'][min_index]['2th_moka'].min(), data['diffractogram'][max_index]['2th_moka'].max()
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minmax['d'][0], minmax['d'][1] = data['diffractogram'][max_index]['d'].min(), data['diffractogram'][min_index]['d'].max() # swapped, intended
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minmax['1/d'][0], minmax['1/d'][1] = data['diffractogram'][min_index]['1/d'].min(), data['diffractogram'][max_index]['1/d'].max()
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minmax['q'][0], minmax['q'][1] = data['diffractogram'][min_index]['q'].min(), data['diffractogram'][max_index]['q'].max()
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minmax['q2'][0], minmax['q2'][1] = data['diffractogram'][min_index]['q2'].min(), data['diffractogram'][max_index]['q2'].max()
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minmax['q4'][0], minmax['q4'][1] = data['diffractogram'][min_index]['q4'].min(), data['diffractogram'][max_index]['q4'].max()
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def update_widgets(options):
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for widget in options['widgets'].values():
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if widget['state'] != options['x_vals']:
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for arg in widget[f'{options["x_vals"]}_default']:
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setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
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widget['state'] = options['x_vals']
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def plot_reflection_indices(data, ax, options={}):
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''' Print reflection indices from output generated by VESTA.
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Required contents of data:
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path (str): relative path to reflection table file'''
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required_options = ['reflection_indices', 'text_colour', 'hide_indices']
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default_options = {
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'reflection_indices': 3, # Number of reflection indices to plot, from highest intensity and working its way down
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'text_colour': 'black',
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'hide_indices': False
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}
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data = aux.update_options(options=data, required_options=required_options, default_options=default_options)
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if not data['hide_indices']:
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reflection_table = xrd.io.load_reflection_table(data=data, options=options)
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if data['reflection_indices'] > 0:
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# Get the data['reflection_indices'] number of highest reflections within the subrange options['xlim']
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reflection_indices = reflection_table.loc[(reflection_table[options['x_vals']] > options['xlim'][0]) & (reflection_table[options['x_vals']] < options['xlim'][1])].nlargest(options['reflection_indices'], 'I')
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# Plot the indices
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for i in range(data['reflection_indices']):
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if reflection_indices.shape[0] > i:
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ax.text(s=f'({reflection_indices["h"].iloc[i]} {reflection_indices["k"].iloc[i]} {reflection_indices["l"].iloc[i]})', x=reflection_indices[options['x_vals']].iloc[i], y=0, fontsize=2.5, rotation=90, va='bottom', ha='center', c=data['text_colour'])
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if options['xlim']:
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ax.set_xlim(options['xlim'])
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ax.axis('off')
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return
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def plot_reflection_table(data, ax=None, options={}):
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''' Plots a reflection table from output generated by VESTA.
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Required contents of data:
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path (str): relative path to reflection table file'''
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required_options = ['reflection_indices', 'reflections_colour', 'min_alpha', 'wavelength', 'format_params', 'rc_params', 'label']
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default_options = {
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'reflection_indices': 0, # Number of indices to print
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'reflections_colour': [0,0,0],
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'min_alpha': 0,
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'wavelength': 1.54059, # CuKalpha, [Å]
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'format_params': {},
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'rc_params': {},
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'label': None
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}
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if 'colour' in data.keys():
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options['reflections_colour'] = data['colour']
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if 'min_alpha' in data.keys():
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options['min_alpha'] = data['min_alpha']
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if 'reflection_indices' in data.keys():
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options['reflection_indices'] = data['reflection_indices']
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if 'label' in data.keys():
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options['label'] = data['label']
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if 'wavelength' in data.keys():
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options['wavelength'] = data['wavelength']
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options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
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if not ax:
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_, ax = btp.prepare_plot(options)
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reflection_table = xrd.io.load_reflection_table(data=data, options=options)
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reflections, intensities = reflection_table[options['x_vals']], reflection_table['I']
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colours = []
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for ref, intensity in zip(reflections, intensities):
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colour = list(options['reflections_colour'])
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rel_intensity = (intensity / intensities.max())*(1-options['min_alpha']) + options['min_alpha']
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colour.append(rel_intensity)
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colours.append(colour)
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ax.vlines(x=reflections, ymin=-1, ymax=1, colors=colours, lw=0.5)
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ax.set_ylim([-0.5,0.5])
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ax.tick_params(which='both', bottom=False, labelbottom=False, right=False, labelright=False, left=False, labelleft=False, top=False, labeltop=False)
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if options['xlim']:
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ax.set_xlim(options['xlim'])
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if options['label']:
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xlim_range = ax.get_xlim()[1] - ax.get_xlim()[0]
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ylim_avg = (ax.get_ylim()[0]+ax.get_ylim()[1])/2
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ax.text(s=data['label'], x=(ax.get_xlim()[0]-0.01*xlim_range), y=ylim_avg, ha = 'right', va = 'center')
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def prettify_labels(label):
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labels_dict = {
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'2th': '2$\\theta$',
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'I': 'Intensity'
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}
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return labels_dict[label]
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def plot_diffractograms(paths, kind, options=None):
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fig, ax = prepare_diffractogram_plot(options=options)
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diffractograms = []
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for path in paths:
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diffractogram = xrd.io.read_data(path=path, kind=kind, options=options)
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diffractograms.append(diffractogram)
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required_options = ['type', 'xvals', 'yvals', 'x_offset', 'y_offset', 'normalise', 'normalise_around', 'reverse_order']
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default_options = {
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'type': 'stacked',
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'xvals': '2th',
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'yvals': 'I',
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'x_offset': 0,
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'y_offset': 0.2,
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'normalise': True,
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'normalise_around': None,
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'reverse_order': False
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}
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# If reverse_order is enabled, reverse the order
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if options['reverse_order']:
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diffractograms = reverse_diffractograms(diffractograms)
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|
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# If normalise is enbaled, normalise all the diffractograms
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if options['normalise']:
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if not options['normalise_around']:
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for diffractogram in diffractograms:
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diffractogram["I"] = diffractogram["I"]/diffractogram["I"].max()
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else:
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diffractogram["I"] = diffractogram["I"]/diffractogram["I"].loc[(diffractogram['2th'] > options['normalise_around'][0]) & (diffractogram['2th'] < options['normalise_around'][1])].max()
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|
|
|
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if options['type'] == 'stacked':
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for diffractogram in diffractograms:
|
|
diffractogram.plot(x=options['xvals'], y=options['yvals'], ax=ax)
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|
|
|
|
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fig, ax = prettify_diffractogram_plot(fig=fig, ax=ax, options=options)
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|
|
|
|
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return diffractogram, fig, ax
|
|
|
|
|
|
def reverse_diffractograms(diffractograms):
|
|
|
|
rev_diffractograms = []
|
|
|
|
for i in len(diffractograms):
|
|
rev_diffractograms.append(diffractograms.pop())
|
|
|
|
return rev_diffractograms
|
|
|
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#def plot_heatmap():
|