Rasmus Vester Thøgersen
GitHub Enterprise
commit
3b1d068e14
4 changed files with 384 additions and 95 deletions
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@ -1,4 +1,5 @@
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import json
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import numpy as np
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def update_options(options, required_options, default_options):
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''' Takes a dictionary of options along with a list of required options and dictionary of default options, and sets all keyval-pairs of options that is not already defined to the default values'''
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@ -37,6 +38,18 @@ def swap_values(dict, key1, key2):
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def hello_world2(a=1, b=2):
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def ceil(a, roundto=1):
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print(f'Halla, MAFAKKAS! a = {a} og b = {b}')
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fac = 1/roundto
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a = np.ceil(a*fac) / fac
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return a
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def floor(a, roundto=1):
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fac = 1/roundto
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a = np.floor(a*fac) / fac
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return a
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@ -182,7 +182,7 @@ def adjust_plot(fig, ax, options):
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ax.xaxis.set_minor_locator(MultipleLocator(options['x_tick_locators'][1]))
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# THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY!
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# FIXME THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY!
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if options['xticks']:
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ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
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ax.set_xticklabels(options['xticks'])
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@ -40,7 +40,7 @@ def integrate_1d(data, options={}, index=0):
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df: DataFrame contianing 1D diffractogram if option 'return' is True
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'''
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required_options = ['unit', 'nbins', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite']
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required_options = ['unit', 'nbins', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite', 'extract_folder']
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default_options = {
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'unit': '2th_deg',
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@ -358,9 +358,18 @@ def read_data(data, options={}, index=0):
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def apply_offset(diffractogram, wavelength, index, options):
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options['current_offset_y'] = options['offset_y']
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if 'current_offset_y' not in options.keys():
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options['current_offset_y'] = options['offset_y']
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else:
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if options['current_offset_y'] != options['offset_y']:
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options['offset_change'] = True
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options['current_offset_y'] = options['offset_y']
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options['current_offset_x'] = options['offset_x']
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#Apply offset along y-axis
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diffractogram['I'] = diffractogram['I_org'] # Reset intensities
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@ -391,7 +400,7 @@ def revert_offset(diffractogram,which=None):
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return diffractogram
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def load_reflection_table(data, options={}):
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def load_reflection_table(data: dict, reflections_params: dict, options={}):
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required_options = ['ref_wavelength', 'to_wavelength']
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@ -404,12 +413,12 @@ def load_reflection_table(data, options={}):
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# VESTA outputs the file with a header that has a space between the parameter and units - so there is some extra code to rectify the issue
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# that ensues from this formatting
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reflections = pd.read_csv(data['path'], delim_whitespace=True)
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reflections = pd.read_csv(reflections_params['path'], delim_whitespace=True)
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# Remove the extra column that appears from the headers issue
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reflections.drop(reflections.columns[-1], axis=1, inplace=True)
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with open(data['path'], 'r') as f:
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with open(reflections_params['path'], 'r') as f:
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line = f.readline()
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headers = line.split()
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@ -425,13 +434,28 @@ def load_reflection_table(data, options={}):
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reflections = translate_wavelengths(data=reflections, wavelength=options['ref_wavelength'], to_wavelength=options['to_wavelength'])
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#print(reflections)
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if 'heatmap' in data.keys():
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start_2th, stop_2th = data['diffractogram'][0]['2th'].min(), data['diffractogram'][0]['2th'].max()
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len_2th = stop_2th - start_2th
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#print(start_2th, stop_2th, len_2th)
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start_heatmap, stop_heatmap = 0, data['heatmap'].shape[1]
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len_heatmap = stop_heatmap - start_heatmap
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#print(start_heatmap, stop_heatmap, len_heatmap)
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scale = len_heatmap/len_2th
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#print(scale)
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#print(stop_2th * scale)
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reflections['heatmap'] = (reflections['2th']-start_2th) * scale
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return reflections
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def translate_wavelengths(data, wavelength, to_wavelength=None):
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def translate_wavelengths(data: pd.DataFrame, wavelength: float, to_wavelength=None) -> pd.DataFrame:
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# FIXME Somewhere here there is an invalid arcsin-argument. Not sure where.
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pd.options.mode.chained_assignment = None
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@ -1,3 +1,4 @@
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import seaborn as sns
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import matplotlib.pyplot as plt
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from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
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@ -19,8 +20,8 @@ def plot_diffractogram(data, options={}):
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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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required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim', 'normalise', 'offset', 'offset_x', 'offset_y', 'offset_change',
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'reflections_plot', 'reflections_indices', 'reflections_data', 'heatmap', 'cmap', '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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@ -32,11 +33,14 @@ def plot_diffractogram(data, options={}):
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'offset': True,
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'offset_x': 0,
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'offset_y': 1,
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'offset_change': False,
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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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'heatmap': False,
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'cmap': 'viridis',
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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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@ -50,6 +54,7 @@ def plot_diffractogram(data, options={}):
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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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#options['current_offset_y'] = options['offset_y']
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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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@ -69,16 +74,22 @@ def plot_diffractogram(data, options={}):
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data['diffractogram'][index] = diffractogram
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data['wavelength'][index] = 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'] = [data['diffractogram'][0][options['x_vals']].min(), data['diffractogram'][0][options['x_vals']].max()]
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# Generate heatmap data
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data['heatmap'], data['heatmap_xticks'], data['heatmap_xticklabels'] = generate_heatmap(data=data, options=options)
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options['heatmap_loaded'] = True
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if options['heatmap']:
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options['xlim'] = options['heatmap_xlim']
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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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@ -129,13 +140,19 @@ def plot_diffractogram(data, options={}):
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else:
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colours = btp.generate_colours(['black'], kind='single')
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if options['heatmap']:
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sns.heatmap(data['heatmap'], cmap=options['cmap'], cbar=False, ax=ax)
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ax.set_xticks(data['heatmap_xticks'][options['x_vals']])
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ax.set_xticklabels(data['heatmap_xticklabels'][options['x_vals']])
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ax.tick_params(axis='x', which='minor', bottom=False, top=False)
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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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else:
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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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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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@ -148,27 +165,102 @@ def plot_diffractogram(data, options={}):
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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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for reflections_params, axis in zip(options['reflections_data'], ref_axes):
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plot_reflection_table(data=data, reflections_params=reflections_params, 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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for reflections_params in options['reflections_data']:
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plot_reflection_indices(data=data, reflections_params=reflections_params, 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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options['current_y_offset'] = options['widget'].kwargs['offset_y']
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update_widgets(data=data, options=options)
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return data['diffractogram'], fig, ax
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def generate_heatmap(data, options={}):
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required_options = ['x_tick_locators']
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default_options = {
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'x_tick_locators': [0.5, 0.1]
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}
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options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
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twotheta = []
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intensities = []
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scans = []
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for i, d in enumerate(data['diffractogram']):
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twotheta = np.append(twotheta, d['2th'].to_numpy())
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intensities = np.append(intensities, d['I'].to_numpy())
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scans = np.append(scans, np.full(len(d['2th'].to_numpy()), int(i)))
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heatmap = pd.DataFrame({'2th': twotheta, 'scan': scans, 'I': intensities})
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xrd.io.translate_wavelengths(data=heatmap, wavelength=data['wavelength'][0])
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min_dict = {'2th': heatmap['2th'].min(), '2th_cuka': heatmap['2th_cuka'].min(), '2th_moka': heatmap['2th_moka'].min(),
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'q': heatmap['q'].min(), 'q2': heatmap['q2'].min(), 'q4': heatmap['q4'].min(), '1/d': heatmap['1/d'].min()}
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max_dict = {'2th': heatmap['2th'].max(), '2th_cuka': heatmap['2th_cuka'].max(), '2th_moka': heatmap['2th_moka'].max(),
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'q': heatmap['q'].max(), 'q2': heatmap['q2'].max(), 'q4': heatmap['q4'].max(), '1/d': heatmap['1/d'].max()}
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ndatapoints = len(data['diffractogram'][0]['2th'])
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xlims = [0, ndatapoints, 0, ndatapoints] # 0: xmin, 1: xmax, 2: xmin_start, 3: xmax_start
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xticks = {}
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xticklabels = {}
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for xval in min_dict.keys():
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# Add xticks labels
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label_max = aux.floor(max_dict[xval], roundto=options['x_tick_locators'][0])
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label_min = aux.ceil(min_dict[xval], roundto=options['x_tick_locators'][0])
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label_steps = (label_max - label_min)/options['x_tick_locators'][0]
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xticklabels[xval] = np.linspace(label_min, label_max, num=int(label_steps)+1)
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# Add xticks
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xval_span = max_dict[xval] - min_dict[xval]
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steps = xval_span / ndatapoints
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xticks_xval = []
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for tick in xticklabels[xval]:
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xticks_xval.append((tick-min_dict[xval])/steps)
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xticks[xval] = xticks_xval
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options['x_tick_locators'] = None
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heatmap = heatmap.reset_index().pivot_table(index='scan', columns='2th', values='I')
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options['heatmap_xlim'] = xlims
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return heatmap, xticks, xticklabels
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return diffractogram, fig, ax
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# #results = np.transpose(np.vstack([twotheta, scans, intensities]))
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def determine_grid_layout(options):
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@ -187,57 +279,76 @@ def determine_grid_layout(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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# Format here is xminmax[0]: xmin, xminmax[1]: xmax, xminmax[2]: xmin_start, xminmax[3]: xmax_start, where "_start" denotes starting value of the slider
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xminmax = { '2th': [None, None, None, None], '2th_cuka': [None, None, None, None], '2th_moka': [None, None, None, None],
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'd': [None, None, None, None], '1/d': [None, None, None, None],
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'q': [None, None, None, None], 'q2': [None, None, None, None], 'q4': [None, None, None, None],
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'heatmap': [None, None, None, None], 'start': [None, None, None, None]}
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update_minmax(minmax, data)
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yminmax = { 'diff': [None, None, None, None], 'heatmap': [None, None, None, None], 'start': [None, None, None, None]}
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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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update_xminmax(xminmax=xminmax, data=data, options=options)
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update_yminmax(yminmax=yminmax, data=data, options=options)
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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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options['xminmax'], options['yminmax'] = xminmax, yminmax
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# Get start values for ylim slider based on choice (FIXME This can be impleneted into update_yminmax). Can also make a 'start' item that stores the start values, instead of having 4 items in 'diff' as it is now.
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if options['heatmap']:
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ymin = yminmax['heatmap'][0]
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ymax = yminmax['heatmap'][1]
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ymin_start = yminmax['heatmap'][0]
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ymax_start = yminmax['heatmap'][1]
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elif not options['heatmap']:
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ymin = yminmax['diff'][0]
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ymax = yminmax['diff'][1]
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ymin_start = yminmax['diff'][2]
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ymax_start = yminmax['diff'][3]
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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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# FIXME The start values for xlim should probably also be decided by initial value of x_vals, and can likewise be implemented in update_xminmax()
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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},
|
||||
'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},
|
||||
'd_default': {'min': minmax['d'][0], 'max': minmax['d'][1], 'value': [minmax['d'][0], minmax['d'][1]], 'step': 0.5},
|
||||
'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},
|
||||
'q_default': {'min': minmax['q'][0], 'max': minmax['q'][1], 'value': [minmax['q'][0], minmax['q'][1]], 'step': 0.5},
|
||||
'q2_default': {'min': minmax['q2'][0], 'max': minmax['q2'][1], 'value': [minmax['q2'][0], minmax['q2'][1]], 'step': 0.5},
|
||||
'q4_default': {'min': minmax['q4'][0], 'max': minmax['q4'][1], 'value': [minmax['q4'][0], minmax['q4'][1]], 'step': 0.5}
|
||||
'w': widgets.FloatRangeSlider(value=[xminmax['start'][2], xminmax['start'][3]], min=xminmax['start'][0], max=xminmax['start'][1], step=0.5, layout=widgets.Layout(width='95%')),
|
||||
'state': options['x_vals'],
|
||||
'2th_default': {'min': xminmax['2th'][0], 'max': xminmax['2th'][1], 'value': [xminmax['2th'][0], xminmax['2th'][1]], 'step': 0.5},
|
||||
'2th_cuka_default': {'min': xminmax['2th_cuka'][0], 'max': xminmax['2th_cuka'][1], 'value': [xminmax['2th_cuka'][0], xminmax['2th_cuka'][1]], 'step': 0.5},
|
||||
'2th_moka_default': {'min': xminmax['2th_moka'][0], 'max': xminmax['2th_moka'][1], 'value': [xminmax['2th_moka'][0], xminmax['2th_moka'][1]], 'step': 0.5},
|
||||
'd_default': {'min': xminmax['d'][0], 'max': xminmax['d'][1], 'value': [xminmax['d'][0], xminmax['d'][1]], 'step': 0.5},
|
||||
'1/d_default': {'min': xminmax['1/d'][0], 'max': xminmax['1/d'][1], 'value': [xminmax['1/d'][0], xminmax['1/d'][1]], 'step': 0.5},
|
||||
'q_default': {'min': xminmax['q'][0], 'max': xminmax['q'][1], 'value': [xminmax['q'][0], xminmax['q'][1]], 'step': 0.5},
|
||||
'q2_default': {'min': xminmax['q2'][0], 'max': xminmax['q2'][1], 'value': [xminmax['q2'][0], xminmax['q2'][1]], 'step': 0.5},
|
||||
'q4_default': {'min': xminmax['q4'][0], 'max': xminmax['q4'][1], 'value': [xminmax['q4'][0], xminmax['q4'][1]], 'step': 0.5},
|
||||
'heatmap_default': {'min': xminmax['heatmap'][0], 'max': xminmax['heatmap'][1], 'value': [xminmax['heatmap'][0], xminmax['heatmap'][1]], 'step': 10}
|
||||
},
|
||||
'ylim': {
|
||||
'w': widgets.FloatRangeSlider(value=[yminmax['start'][2], yminmax['start'][3]], min=yminmax['start'][0], max=yminmax['start'][1], step=0.5, layout=widgets.Layout(width='95%')),
|
||||
'state': 'heatmap' if options['heatmap'] else 'diff',
|
||||
'diff_default': {'min': yminmax['diff'][0], 'max': yminmax['diff'][1], 'value': [yminmax['diff'][2], yminmax['diff'][3]], 'step': 0.1},
|
||||
'heatmap_default': {'min': yminmax['heatmap'][0], 'max': yminmax['heatmap'][1], 'value': [yminmax['heatmap'][0], yminmax['heatmap'][1]], 'step': 0.1}
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
if options['reflections_data']:
|
||||
w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(plot_diffractogram), data=widgets.fixed(data), options=widgets.fixed(options),
|
||||
scatter=widgets.ToggleButton(value=False),
|
||||
line=widgets.ToggleButton(value=True),
|
||||
reflections_plot=widgets.ToggleButton(value=True),
|
||||
reflections_indices=widgets.ToggleButton(value=False),
|
||||
heatmap=widgets.ToggleButton(value=options['heatmap']),
|
||||
x_vals=widgets.Dropdown(options=['2th', 'd', '1/d', 'q', 'q2', 'q4', '2th_cuka', '2th_moka'], value='2th', description='X-values'),
|
||||
xlim=options['widgets']['xlim']['w'],
|
||||
ylim=widgets.FloatRangeSlider(value=[ymin_start, ymax_start], min=ymin, max=ymax, step=0.5, layout=widgets.Layout(width='95%')),
|
||||
offset_y=widgets.BoundedFloatText(value=options['offset_y'], min=-5, max=5, step=0.01),
|
||||
offset_x=widgets.BoundedFloatText(value=options['offset_x'], min=-1, max=1, step=0.01)
|
||||
ylim=options['widgets']['ylim']['w'],
|
||||
offset_y=widgets.BoundedFloatText(value=options['offset_y'], min=-5, max=5, step=0.01, description='offset_y'),
|
||||
offset_x=widgets.BoundedFloatText(value=options['offset_x'], min=-1, max=1, step=0.01, description='offset_x')
|
||||
)
|
||||
|
||||
else:
|
||||
|
|
@ -247,45 +358,184 @@ def plot_diffractogram_interactive(data, options):
|
|||
xlim=options['widgets']['xlim']['w'])
|
||||
|
||||
|
||||
options['widget'] = w
|
||||
|
||||
display(w)
|
||||
|
||||
|
||||
def update_minmax(minmax, data):
|
||||
def update_xminmax(xminmax, data, options={}):
|
||||
''' Finds minimum and maximum values of each column and updates the minmax dictionary to contain the correct values.
|
||||
|
||||
Input:
|
||||
minmax (dict): contains '''
|
||||
|
||||
xminmax['2th'] = [None, None, None, None]
|
||||
for index, diffractogram in enumerate(data['diffractogram']):
|
||||
if not minmax['2th'][0] or diffractogram['2th'].min() < minmax['2th'][0]:
|
||||
minmax['2th'][0] = diffractogram['2th'].min()
|
||||
|
||||
if not xminmax['2th'][0] or diffractogram['2th'].min() < xminmax['2th'][0]:
|
||||
xminmax['2th'][0] = diffractogram['2th'].min()
|
||||
min_index = index
|
||||
|
||||
if not minmax['2th'][1] or diffractogram['2th'].max() > minmax['2th'][1]:
|
||||
minmax['2th'][1] = diffractogram['2th'].max()
|
||||
if not xminmax['2th'][1] or diffractogram['2th'].max() > xminmax['2th'][1]:
|
||||
xminmax['2th'][1] = diffractogram['2th'].max()
|
||||
max_index = index
|
||||
|
||||
minmax['2th_cuka'][0], minmax['2th_cuka'][1] = data['diffractogram'][min_index]['2th_cuka'].min(), data['diffractogram'][max_index]['2th_cuka'].max()
|
||||
minmax['2th_moka'][0], minmax['2th_moka'][1] = data['diffractogram'][min_index]['2th_moka'].min(), data['diffractogram'][max_index]['2th_moka'].max()
|
||||
minmax['d'][0], minmax['d'][1] = data['diffractogram'][max_index]['d'].min(), data['diffractogram'][min_index]['d'].max() # swapped, intended
|
||||
minmax['1/d'][0], minmax['1/d'][1] = data['diffractogram'][min_index]['1/d'].min(), data['diffractogram'][max_index]['1/d'].max()
|
||||
minmax['q'][0], minmax['q'][1] = data['diffractogram'][min_index]['q'].min(), data['diffractogram'][max_index]['q'].max()
|
||||
minmax['q2'][0], minmax['q2'][1] = data['diffractogram'][min_index]['q2'].min(), data['diffractogram'][max_index]['q2'].max()
|
||||
minmax['q4'][0], minmax['q4'][1] = data['diffractogram'][min_index]['q4'].min(), data['diffractogram'][max_index]['q4'].max()
|
||||
|
||||
def update_widgets(options):
|
||||
xminmax['2th'][2], xminmax['2th'][3] = xminmax['2th'][0], xminmax['2th'][1]
|
||||
|
||||
for widget in options['widgets'].values():
|
||||
xminmax['2th_cuka'][0], xminmax['2th_cuka'][1] = data['diffractogram'][min_index]['2th_cuka'].min(), data['diffractogram'][max_index]['2th_cuka'].max()
|
||||
xminmax['2th_cuka'][2], xminmax['2th_cuka'][3] = xminmax['2th_cuka'][0], xminmax['2th_cuka'][1]
|
||||
|
||||
if widget['state'] != options['x_vals']:
|
||||
for arg in widget[f'{options["x_vals"]}_default']:
|
||||
setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
|
||||
xminmax['2th_moka'][0], xminmax['2th_moka'][1] = data['diffractogram'][min_index]['2th_moka'].min(), data['diffractogram'][max_index]['2th_moka'].max()
|
||||
xminmax['2th_moka'][2], xminmax['2th_moka'][3] = xminmax['2th_moka'][0], xminmax['2th_moka'][1]
|
||||
|
||||
widget['state'] = options['x_vals']
|
||||
xminmax['d'][0], xminmax['d'][1] = data['diffractogram'][max_index]['d'].min(), data['diffractogram'][min_index]['d'].max() # swapped, intended
|
||||
xminmax['d'][2], xminmax['d'][3] = xminmax['d'][0], xminmax['d'][1]
|
||||
|
||||
xminmax['1/d'][0], xminmax['1/d'][1] = data['diffractogram'][min_index]['1/d'].min(), data['diffractogram'][max_index]['1/d'].max()
|
||||
xminmax['1/d'][2], xminmax['1/d'][3] = xminmax['1/d'][0], xminmax['1/d'][1]
|
||||
|
||||
xminmax['q'][0], xminmax['q'][1] = data['diffractogram'][min_index]['q'].min(), data['diffractogram'][max_index]['q'].max()
|
||||
xminmax['q'][2], xminmax['q'][3] = xminmax['q'][0], xminmax['q'][1]
|
||||
|
||||
xminmax['q2'][0], xminmax['q2'][1] = data['diffractogram'][min_index]['q2'].min(), data['diffractogram'][max_index]['q2'].max()
|
||||
xminmax['q2'][2], xminmax['q2'][3] = xminmax['q2'][0], xminmax['q2'][1]
|
||||
|
||||
xminmax['q4'][0], xminmax['q4'][1] = data['diffractogram'][min_index]['q4'].min(), data['diffractogram'][max_index]['q4'].max()
|
||||
xminmax['q4'][2], xminmax['q4'][3] = xminmax['q4'][0], xminmax['q4'][1]
|
||||
|
||||
|
||||
xminmax['heatmap'] = options['heatmap_xlim'] # This value is set in the generate_heatmap()-function
|
||||
|
||||
|
||||
xminmax['start'][0], xminmax['start'][1] = xminmax[options['x_vals']][0], xminmax[options['x_vals']][1]
|
||||
xminmax['start'][2], xminmax['start'][3] = xminmax[options['x_vals']][2], xminmax[options['x_vals']][3]
|
||||
|
||||
|
||||
def update_yminmax(yminmax: dict, data: dict, options={}) -> None:
|
||||
|
||||
yminmax['diff'] = [None, None, None, None]
|
||||
# Go through diffractograms and find the minimum and maximum intensity values
|
||||
for diffractogram in data['diffractogram']:
|
||||
if not yminmax['diff'][0] or (yminmax['diff'][0] > (diffractogram['I'].min())):
|
||||
yminmax['diff'][0] = diffractogram['I'].min()
|
||||
|
||||
if not yminmax['diff'][1] or (yminmax['diff'][1] < (diffractogram['I'].max())):
|
||||
yminmax['diff'][1] = diffractogram['I'].max()
|
||||
|
||||
|
||||
# Set start values of ymin and ymax to be slightly below lowest data points and slightly above highest data points to give some whitespace around the plot
|
||||
yminmax['diff'][2] = yminmax['diff'][0] - 0.1*yminmax['diff'][1]
|
||||
yminmax['diff'][3] = yminmax['diff'][1] + 0.2*yminmax['diff'][1]
|
||||
|
||||
# Allow for adjustment up to five times ymax above and below data
|
||||
yminmax['diff'][0] = yminmax['diff'][0] - 5*yminmax['diff'][1]
|
||||
yminmax['diff'][1] = yminmax['diff'][1]*5
|
||||
|
||||
|
||||
# Set start values to the edges of the dataset
|
||||
yminmax['heatmap'][0], yminmax['heatmap'][1] = 0, data['heatmap'].shape[0]
|
||||
yminmax['heatmap'][2], yminmax['heatmap'][3] = yminmax['heatmap'][0], yminmax['heatmap'][1]
|
||||
|
||||
|
||||
if options['heatmap']:
|
||||
yminmax['start'][0], yminmax['start'][1] = yminmax['heatmap'][0], yminmax['heatmap'][1]
|
||||
yminmax['start'][2], yminmax['start'][3] = yminmax['heatmap'][0], yminmax['heatmap'][1]
|
||||
|
||||
else:
|
||||
# The third and fourth index are different here to not be zoomed completely out to begin with.
|
||||
yminmax['start'][0], yminmax['start'][1] = yminmax['diff'][0], yminmax['diff'][1]
|
||||
yminmax['start'][2], yminmax['start'][3] = yminmax['diff'][2], yminmax['diff'][3]
|
||||
|
||||
|
||||
def update_defaults(widget: dict, minmax: dict) -> None:
|
||||
''' Updates the default x- or y-limits of a given widget. Refer to plot_diffractogram_interactive() to see the form of the widget that is passed in. An update of the min/max-values is done just prior to calling this function.
|
||||
Changes dictionaries in place.
|
||||
|
||||
Input:
|
||||
widget (dict): A dictionary containing the widget itself (widget['w']) and all its default-values (e.g. widget['2th_default'])
|
||||
minmax (dict): A dictionary containing min and max values, as well as min_start and max_start values. (e.g. minmax['2th'] is a list with four elements: [xmin, xmax, xmin_start, xmax_start])
|
||||
|
||||
Output:
|
||||
None.'''
|
||||
|
||||
for name, attr in widget.items():
|
||||
if name.endswith('default'):
|
||||
attr['min'] = minmax[name.replace('_default', '')][0]
|
||||
attr['max'] = minmax[name.replace('_default', '')][1]
|
||||
attr['value'] = [minmax[name.replace('_default', '')][2], minmax[name.replace('_default', '')][3]]
|
||||
|
||||
|
||||
def update_widgets(data, options):
|
||||
|
||||
|
||||
for widget_name, widget in options['widgets'].items():
|
||||
|
||||
# Make changes to xlim-widget
|
||||
if widget_name == 'xlim':
|
||||
# First update the min and max values
|
||||
update_xminmax(xminmax=options['xminmax'], data=data, options=options)
|
||||
update_defaults(widget=widget, minmax=options['xminmax'])
|
||||
|
||||
|
||||
if options['heatmap'] and (widget['state'] != 'heatmap'):
|
||||
|
||||
|
||||
setattr(widget['w'], 'min', widget['heatmap_default']['min'])
|
||||
setattr(widget['w'], 'max', widget['heatmap_default']['max'])
|
||||
setattr(widget['w'], 'value', widget['heatmap_default']['value'])
|
||||
setattr(widget['w'], 'step', widget['heatmap_default']['step'])
|
||||
|
||||
widget['state'] = 'heatmap'
|
||||
|
||||
elif not options['heatmap'] and (widget['state'] != options['x_vals']):
|
||||
# Then loop through all attributes in the widget and change to current mode.
|
||||
for arg in widget[f'{options["x_vals"]}_default']:
|
||||
|
||||
# If new min value is larger than previous max, or new max value is smaller than previous min, set the opposite first
|
||||
if arg == 'min':
|
||||
if widget[f'{options["x_vals"]}_default']['min'] > getattr(widget['w'], 'max'):
|
||||
setattr(widget['w'], 'max', widget[f'{options["x_vals"]}_default']['max'])
|
||||
|
||||
elif arg == 'max':
|
||||
if widget[f'{options["x_vals"]}_default']['max'] < getattr(widget['w'], 'min'):
|
||||
setattr(widget['w'], 'min', widget[f'{options["x_vals"]}_default']['min'])
|
||||
|
||||
|
||||
setattr(widget['w'], arg, widget[f'{options["x_vals"]}_default'][arg])
|
||||
|
||||
|
||||
widget['state'] = options['x_vals']
|
||||
|
||||
# Make changes to ylim-widget
|
||||
elif widget_name == 'ylim':
|
||||
update_yminmax(yminmax=options['yminmax'], data=data, options=options)
|
||||
update_defaults(widget=widget, minmax=options['yminmax'])
|
||||
|
||||
state = 'heatmap' if options['heatmap'] else 'diff'
|
||||
|
||||
if widget['state'] != state or options['offset_change']:
|
||||
|
||||
for arg in widget[f'{state}_default']:
|
||||
# If new min value is larger than previous max, or new max value is smaller than previous min, set the opposite first
|
||||
if arg == 'min':
|
||||
if widget[f'{state}_default']['min'] > getattr(widget['w'], 'max'):
|
||||
setattr(widget['w'], 'max', widget[f'{state}_default']['max'])
|
||||
|
||||
elif arg == 'max':
|
||||
if widget[f'{state}_default']['max'] < getattr(widget['w'], 'min'):
|
||||
setattr(widget['w'], 'min', widget[f'{state}_default']['min'])
|
||||
|
||||
|
||||
setattr(widget['w'], arg, widget[f'{state}_default'][arg])
|
||||
|
||||
options['offset_change'] = False
|
||||
widget['state'] = state
|
||||
|
||||
|
||||
|
||||
def plot_reflection_indices(data, ax, options={}):
|
||||
|
||||
def plot_reflection_indices(data, reflections_params, ax, options={}):
|
||||
''' Print reflection indices from output generated by VESTA.
|
||||
|
||||
Required contents of data:
|
||||
|
|
@ -299,20 +549,21 @@ def plot_reflection_indices(data, ax, options={}):
|
|||
'hide_indices': False
|
||||
}
|
||||
|
||||
data = aux.update_options(options=data, required_options=required_options, default_options=default_options)
|
||||
reflections_params = aux.update_options(options=reflections_params, required_options=required_options, default_options=default_options)
|
||||
|
||||
if not data['hide_indices']:
|
||||
reflection_table = xrd.io.load_reflection_table(data=data, options=options)
|
||||
if not reflections_params['hide_indices']:
|
||||
reflection_table = xrd.io.load_reflection_table(data=data, reflections_params=reflections_params, options=options)
|
||||
|
||||
if data['reflection_indices'] > 0:
|
||||
if reflections_params['reflection_indices'] > 0:
|
||||
|
||||
# Get the data['reflection_indices'] number of highest reflections within the subrange options['xlim']
|
||||
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')
|
||||
x_vals = 'heatmap' if options['heatmap'] else options['x_vals']
|
||||
reflection_indices = reflection_table.loc[(reflection_table[x_vals] > options['xlim'][0]) & (reflection_table[x_vals] < options['xlim'][1])].nlargest(options['reflection_indices'], 'I')
|
||||
|
||||
# Plot the indices
|
||||
for i in range(data['reflection_indices']):
|
||||
for i in range(reflections_params['reflection_indices']):
|
||||
if reflection_indices.shape[0] > i:
|
||||
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'])
|
||||
ax.text(s=f'({reflection_indices["h"].iloc[i]} {reflection_indices["k"].iloc[i]} {reflection_indices["l"].iloc[i]})', x=reflection_indices[x_vals].iloc[i], y=0, fontsize=2.5, rotation=90, va='bottom', ha='center', c=reflections_params['text_colour'])
|
||||
|
||||
|
||||
if options['xlim']:
|
||||
|
|
@ -323,7 +574,7 @@ def plot_reflection_indices(data, ax, options={}):
|
|||
|
||||
return
|
||||
|
||||
def plot_reflection_table(data, ax=None, options={}):
|
||||
def plot_reflection_table(data, reflections_params, ax=None, options={}):
|
||||
''' Plots a reflection table from output generated by VESTA.
|
||||
|
||||
Required contents of data:
|
||||
|
|
@ -342,15 +593,15 @@ def plot_reflection_table(data, ax=None, options={}):
|
|||
}
|
||||
|
||||
if 'colour' in data.keys():
|
||||
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']
|
||||
if 'reflection_indices' in data.keys():
|
||||
options['reflection_indices'] = data['reflection_indices']
|
||||
if 'label' in data.keys():
|
||||
options['label'] = data['label']
|
||||
if 'wavelength' in data.keys():
|
||||
options['wavelength'] = data['wavelength']
|
||||
options['reflections_colour'] = reflections_params['colour']
|
||||
if 'min_alpha' in reflections_params.keys():
|
||||
options['min_alpha'] = reflections_params['min_alpha']
|
||||
if 'reflection_indices' in reflections_params.keys():
|
||||
options['reflection_indices'] = reflections_params['reflection_indices']
|
||||
if 'label' in reflections_params.keys():
|
||||
options['label'] = reflections_params['label']
|
||||
if 'wavelength' in reflections_params.keys():
|
||||
options['wavelength'] = reflections_params['wavelength']
|
||||
|
||||
options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
|
||||
|
||||
|
|
@ -358,9 +609,10 @@ def plot_reflection_table(data, ax=None, options={}):
|
|||
if not ax:
|
||||
_, ax = btp.prepare_plot(options)
|
||||
|
||||
reflection_table = xrd.io.load_reflection_table(data=data, options=options)
|
||||
x_vals = 'heatmap' if options['heatmap'] else options['x_vals']
|
||||
|
||||
reflections, intensities = reflection_table[options['x_vals']], reflection_table['I']
|
||||
reflection_table = xrd.io.load_reflection_table(data=data, reflections_params=reflections_params, options=options)
|
||||
reflections, intensities = reflection_table[x_vals], reflection_table['I']
|
||||
|
||||
|
||||
|
||||
|
|
@ -390,7 +642,7 @@ def plot_reflection_table(data, ax=None, options={}):
|
|||
xlim_range = ax.get_xlim()[1] - ax.get_xlim()[0]
|
||||
ylim_avg = (ax.get_ylim()[0]+ax.get_ylim()[1])/2
|
||||
|
||||
ax.text(s=data['label'], x=(ax.get_xlim()[0]-0.01*xlim_range), y=ylim_avg, ha = 'right', va = 'center')
|
||||
ax.text(s=reflections_params['label'], x=(ax.get_xlim()[0]-0.01*xlim_range), y=ylim_avg, ha = 'right', va = 'center')
|
||||
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue