diff --git a/beamtime/auxillary.py b/beamtime/auxillary.py index 76ec551..68785f7 100644 --- a/beamtime/auxillary.py +++ b/beamtime/auxillary.py @@ -1,4 +1,5 @@ import json +import numpy as np def update_options(options, required_options, default_options): ''' 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''' @@ -37,6 +38,18 @@ def swap_values(dict, key1, key2): -def hello_world2(a=1, b=2): +def ceil(a, roundto=1): - print(f'Halla, MAFAKKAS! a = {a} og b = {b}') \ No newline at end of file + fac = 1/roundto + + a = np.ceil(a*fac) / fac + + return a + +def floor(a, roundto=1): + + fac = 1/roundto + + a = np.floor(a*fac) / fac + + return a \ No newline at end of file diff --git a/beamtime/plotting.py b/beamtime/plotting.py index 4e058ac..500f532 100644 --- a/beamtime/plotting.py +++ b/beamtime/plotting.py @@ -182,7 +182,7 @@ def adjust_plot(fig, ax, options): ax.xaxis.set_minor_locator(MultipleLocator(options['x_tick_locators'][1])) - # THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY! + # FIXME THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY! if options['xticks']: ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1)) ax.set_xticklabels(options['xticks']) diff --git a/beamtime/xrd/io.py b/beamtime/xrd/io.py index dc53b29..c2447d8 100644 --- a/beamtime/xrd/io.py +++ b/beamtime/xrd/io.py @@ -40,7 +40,7 @@ def integrate_1d(data, options={}, index=0): df: DataFrame contianing 1D diffractogram if option 'return' is True ''' - required_options = ['unit', 'nbins', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite'] + required_options = ['unit', 'nbins', 'save', 'save_filename', 'save_extension', 'save_folder', 'overwrite', 'extract_folder'] default_options = { 'unit': '2th_deg', @@ -358,9 +358,18 @@ def read_data(data, options={}, index=0): def apply_offset(diffractogram, wavelength, index, options): - options['current_offset_y'] = options['offset_y'] + if 'current_offset_y' not in options.keys(): + options['current_offset_y'] = options['offset_y'] + else: + if options['current_offset_y'] != options['offset_y']: + options['offset_change'] = True + + options['current_offset_y'] = options['offset_y'] + options['current_offset_x'] = options['offset_x'] + + #Apply offset along y-axis diffractogram['I'] = diffractogram['I_org'] # Reset intensities @@ -391,7 +400,7 @@ def revert_offset(diffractogram,which=None): return diffractogram -def load_reflection_table(data, options={}): +def load_reflection_table(data: dict, reflections_params: dict, options={}): required_options = ['ref_wavelength', 'to_wavelength'] @@ -404,12 +413,12 @@ def load_reflection_table(data, options={}): # 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 # that ensues from this formatting - reflections = pd.read_csv(data['path'], delim_whitespace=True) + reflections = pd.read_csv(reflections_params['path'], delim_whitespace=True) # Remove the extra column that appears from the headers issue reflections.drop(reflections.columns[-1], axis=1, inplace=True) - with open(data['path'], 'r') as f: + with open(reflections_params['path'], 'r') as f: line = f.readline() headers = line.split() @@ -425,13 +434,28 @@ def load_reflection_table(data, options={}): reflections = translate_wavelengths(data=reflections, wavelength=options['ref_wavelength'], to_wavelength=options['to_wavelength']) - #print(reflections) + if 'heatmap' in data.keys(): + + start_2th, stop_2th = data['diffractogram'][0]['2th'].min(), data['diffractogram'][0]['2th'].max() + len_2th = stop_2th - start_2th + #print(start_2th, stop_2th, len_2th) + + start_heatmap, stop_heatmap = 0, data['heatmap'].shape[1] + len_heatmap = stop_heatmap - start_heatmap + #print(start_heatmap, stop_heatmap, len_heatmap) + + scale = len_heatmap/len_2th + + #print(scale) + #print(stop_2th * scale) + + reflections['heatmap'] = (reflections['2th']-start_2th) * scale return reflections -def translate_wavelengths(data, wavelength, to_wavelength=None): +def translate_wavelengths(data: pd.DataFrame, wavelength: float, to_wavelength=None) -> pd.DataFrame: # FIXME Somewhere here there is an invalid arcsin-argument. Not sure where. pd.options.mode.chained_assignment = None diff --git a/beamtime/xrd/plot.py b/beamtime/xrd/plot.py index 012e9b8..cc6baa3 100644 --- a/beamtime/xrd/plot.py +++ b/beamtime/xrd/plot.py @@ -1,3 +1,4 @@ +import seaborn as sns import matplotlib.pyplot as plt from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator) @@ -19,8 +20,8 @@ def plot_diffractogram(data, options={}): data (dict): Must include path = string to diffractogram data, and plot_kind = (recx, beamline, image)''' # Update options - required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim', 'normalise', 'offset', 'offset_x', 'offset_y', - 'reflections_plot', 'reflections_indices', 'reflections_data', 'plot_kind', 'palettes', 'interactive', 'rc_params', 'format_params', 'interactive_session_active'] + required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'line', 'scatter', 'xlim', 'ylim', 'normalise', 'offset', 'offset_x', 'offset_y', 'offset_change', + 'reflections_plot', 'reflections_indices', 'reflections_data', 'heatmap', 'cmap', 'plot_kind', 'palettes', 'interactive', 'rc_params', 'format_params', 'interactive_session_active'] default_options = { 'x_vals': '2th', @@ -32,11 +33,14 @@ def plot_diffractogram(data, options={}): 'offset': True, 'offset_x': 0, 'offset_y': 1, + 'offset_change': False, 'line': True, # whether or not to plot diffractogram as a line plot 'scatter': False, # whether or not to plot individual data points 'reflections_plot': False, # whether to plot reflections as a plot 'reflections_indices': False, # whether to plot the reflection indices '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] + 'heatmap': False, + 'cmap': 'viridis', 'plot_kind': None, 'palettes': [('qualitative', 'Dark2_8')], 'interactive': False, @@ -50,6 +54,7 @@ def plot_diffractogram(data, options={}): default_options['offset_y'] = 0.05 options = aux.update_options(options=options, required_options=required_options, default_options=default_options) + #options['current_offset_y'] = options['offset_y'] # Convert data['path'] to list to allow iteration over this to accommodate both single and multiple diffractograms if not isinstance(data['path'], list): @@ -69,16 +74,22 @@ def plot_diffractogram(data, options={}): data['diffractogram'][index] = diffractogram data['wavelength'][index] = wavelength - + # Sets the xlim if this has not bee specified + if not options['xlim']: + options['xlim'] = [data['diffractogram'][0][options['x_vals']].min(), data['diffractogram'][0][options['x_vals']].max()] + + # Generate heatmap data + data['heatmap'], data['heatmap_xticks'], data['heatmap_xticklabels'] = generate_heatmap(data=data, options=options) + options['heatmap_loaded'] = True + + if options['heatmap']: + options['xlim'] = options['heatmap_xlim'] else: if not isinstance(data['diffractogram'], list): data['diffractogram'] = [data['diffractogram']] data['wavelength'] = [data['wavelength']] - # Sets the xlim if this has not bee specified - if not options['xlim']: - options['xlim'] = [diffractogram[options['x_vals']].min(), diffractogram[options['x_vals']].max()] if options['interactive_session_active']: @@ -129,13 +140,19 @@ def plot_diffractogram(data, options={}): else: colours = btp.generate_colours(['black'], kind='single') + if options['heatmap']: + sns.heatmap(data['heatmap'], cmap=options['cmap'], cbar=False, ax=ax) + ax.set_xticks(data['heatmap_xticks'][options['x_vals']]) + ax.set_xticklabels(data['heatmap_xticklabels'][options['x_vals']]) + ax.tick_params(axis='x', which='minor', bottom=False, top=False) - for diffractogram in data['diffractogram']: - if options['line']: - diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, c=next(colours), zorder=1) - - if options['scatter']: - 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)])) + else: + for diffractogram in data['diffractogram']: + if options['line']: + diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, c=next(colours), zorder=1) + + if options['scatter']: + 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)])) @@ -148,27 +165,102 @@ def plot_diffractogram(data, options={}): options['xlim'] = ax.get_xlim() options['to_wavelength'] = data['wavelength'][0] - for reference, axis in zip(options['reflections_data'], ref_axes): - plot_reflection_table(data=reference, ax=axis, options=options) + for reflections_params, axis in zip(options['reflections_data'], ref_axes): + plot_reflection_table(data=data, reflections_params=reflections_params, ax=axis, options=options) # Print the reflection indices. By default, the wavelength of the first diffractogram will be used for this. if options['reflections_indices'] and options['reflections_data']: options['xlim'] = ax.get_xlim() options['to_wavelength'] = data['wavelength'][0] - for reference in options['reflections_data']: - plot_reflection_indices(data=reference, ax=indices_ax, options=options) + for reflections_params in options['reflections_data']: + plot_reflection_indices(data=data, reflections_params=reflections_params, ax=indices_ax, options=options) if options['interactive_session_active']: - btp.update_widgets(options=options) + options['current_y_offset'] = options['widget'].kwargs['offset_y'] + update_widgets(data=data, options=options) + + + return data['diffractogram'], fig, ax + + + +def generate_heatmap(data, options={}): + + required_options = ['x_tick_locators'] + + default_options = { + 'x_tick_locators': [0.5, 0.1] + } + + options = aux.update_options(options=options, required_options=required_options, default_options=default_options) + + twotheta = [] + intensities = [] + scans = [] + + for i, d in enumerate(data['diffractogram']): + twotheta = np.append(twotheta, d['2th'].to_numpy()) + intensities = np.append(intensities, d['I'].to_numpy()) + scans = np.append(scans, np.full(len(d['2th'].to_numpy()), int(i))) + + + heatmap = pd.DataFrame({'2th': twotheta, 'scan': scans, 'I': intensities}) + xrd.io.translate_wavelengths(data=heatmap, wavelength=data['wavelength'][0]) + min_dict = {'2th': heatmap['2th'].min(), '2th_cuka': heatmap['2th_cuka'].min(), '2th_moka': heatmap['2th_moka'].min(), + 'q': heatmap['q'].min(), 'q2': heatmap['q2'].min(), 'q4': heatmap['q4'].min(), '1/d': heatmap['1/d'].min()} + + max_dict = {'2th': heatmap['2th'].max(), '2th_cuka': heatmap['2th_cuka'].max(), '2th_moka': heatmap['2th_moka'].max(), + 'q': heatmap['q'].max(), 'q2': heatmap['q2'].max(), 'q4': heatmap['q4'].max(), '1/d': heatmap['1/d'].max()} + + + ndatapoints = len(data['diffractogram'][0]['2th']) + + xlims = [0, ndatapoints, 0, ndatapoints] # 0: xmin, 1: xmax, 2: xmin_start, 3: xmax_start + xticks = {} + xticklabels = {} + + for xval in min_dict.keys(): + + # Add xticks labels + label_max = aux.floor(max_dict[xval], roundto=options['x_tick_locators'][0]) + label_min = aux.ceil(min_dict[xval], roundto=options['x_tick_locators'][0]) + label_steps = (label_max - label_min)/options['x_tick_locators'][0] + + xticklabels[xval] = np.linspace(label_min, label_max, num=int(label_steps)+1) + + # Add xticks + xval_span = max_dict[xval] - min_dict[xval] + steps = xval_span / ndatapoints + + + xticks_xval = [] + + for tick in xticklabels[xval]: + xticks_xval.append((tick-min_dict[xval])/steps) + + xticks[xval] = xticks_xval + + + options['x_tick_locators'] = None + + heatmap = heatmap.reset_index().pivot_table(index='scan', columns='2th', values='I') + + options['heatmap_xlim'] = xlims + + + return heatmap, xticks, xticklabels - return diffractogram, fig, ax + + + +# #results = np.transpose(np.vstack([twotheta, scans, intensities])) def determine_grid_layout(options): @@ -187,57 +279,76 @@ def determine_grid_layout(options): + + def plot_diffractogram_interactive(data, options): - 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]} + # 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 + xminmax = { '2th': [None, None, None, None], '2th_cuka': [None, None, None, None], '2th_moka': [None, None, None, None], + 'd': [None, None, None, None], '1/d': [None, None, None, None], + 'q': [None, None, None, None], 'q2': [None, None, None, None], 'q4': [None, None, None, None], + 'heatmap': [None, None, None, None], 'start': [None, None, None, None]} + + yminmax = { 'diff': [None, None, None, None], 'heatmap': [None, None, None, None], 'start': [None, None, None, None]} - update_minmax(minmax, data) + update_xminmax(xminmax=xminmax, data=data, options=options) + update_yminmax(yminmax=yminmax, data=data, options=options) - ymin, ymax = None, None - for index, diffractogram in enumerate(data['diffractogram']): - if not ymin or (ymin > (diffractogram['I'].min())): #+index*options['offset_y'])): - ymin = diffractogram['I'].min()#+index*options['offset_y'] + options['xminmax'], options['yminmax'] = xminmax, yminmax - if not ymax or (ymax < (diffractogram['I'].max())):#+index*options['offset_y'])): - ymax = diffractogram['I'].max()#+index*options['offset_y'] + # 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. + if options['heatmap']: + ymin = yminmax['heatmap'][0] + ymax = yminmax['heatmap'][1] + ymin_start = yminmax['heatmap'][0] + ymax_start = yminmax['heatmap'][1] + elif not options['heatmap']: + ymin = yminmax['diff'][0] + ymax = yminmax['diff'][1] + ymin_start = yminmax['diff'][2] + ymax_start = yminmax['diff'][3] + + + # 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() - ymin_start = ymin - 0.1*ymax - ymax_start = ymax+0.2*ymax - ymin = ymin - 5*ymax - ymax = ymax*5 - - options['widgets'] = { 'xlim': { - '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%')), - 'state': '2th', - '2th_default': {'min': minmax['2th'][0], 'max': minmax['2th'][1], 'value': [minmax['2th'][0], minmax['2th'][1]], 'step': 0.5}, - '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] + + 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' - widget['state'] = options['x_vals'] + 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'] - if 'min_alpha' in data.keys(): - 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')