Generalise prepare_plot and adjust_plot
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rasmusvt
parent
d993663c7c
commit
67ea048380
2 changed files with 107 additions and 74 deletions
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@ -1,4 +1,5 @@
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import beamtime.auxillary as aux
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import matplotlib.pyplot as plt
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from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
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from mpl_toolkits.axes_grid.inset_locator import (inset_axes, InsetPosition, mark_inset)
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@ -10,20 +11,23 @@ from cycler import cycler
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import itertools
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import numpy as np
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def prepare_plot(options={}):
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''' Prepares plot based on contents of options['rc_params'] and options['format_params'].
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''' A general function to prepare a plot based on contents of options['rc_params'] and options['format_params'].
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rc_params is a dictionary with keyval-pairs corresponding to rcParams in matplotlib
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rc_params is a dictionary with keyval-pairs corresponding to rcParams in matplotlib, to give the user full control over this. Please consult the matplotlib-documentation
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format_params will determine the size and aspect ratios of '''
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format_params will determine the size, aspect ratio, resolution etc. of the figure. Should be modified to conform with any requirements from a journal.'''
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rc_params = options['rc_params']
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format_params = options['format_params']
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required_options = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi']
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required_format_params = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi']
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default_options = {
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default_format_params = {
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'single_column_width': 8.3,
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'double_column_width': 17.1,
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'column_type': 'single',
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@ -35,7 +39,7 @@ def prepare_plot(options={}):
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'dpi': 600,
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}
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options = aux.update_options(format_params, required_options, default_options)
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format_params = aux.update_options(format_params, required_format_params, default_format_params)
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# Reset run commands
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@ -44,54 +48,50 @@ def prepare_plot(options={}):
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# Update run commands if any is passed (will pass an empty dictionary if not passed)
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update_rc_params(rc_params)
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width = determine_width(options)
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height = determine_height(options, width)
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width, height = scale_figure(options=options, width=width, height=height)
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width = determine_width(format_params=format_params)
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height = determine_height(format_params=format_params, width=width)
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width, height = scale_figure(format_params=format_params, width=width, height=height)
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fig, ax = plt.subplots(figsize=(width, height), dpi=options['dpi'])
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fig, ax = plt.subplots(figsize=(width, height), dpi=format_params['dpi'])
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return fig, ax
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def prettify_plot(fig, ax, plot_data, options):
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def adjust_plot(fig, ax, options):
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''' A general function to adjust plot according to contents of the options-dictionary '''
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required_options = ['plot_kind',
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required_options = [
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'plot_kind',
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'hide_x_labels', 'hide_y_labels',
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'rotation_x_ticks', 'rotation_y_ticks',
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'xlim', 'ylim',
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'hide_x_ticklabels', 'hide_y_ticklabels',
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'hide_x_ticks', 'hide_y_ticks',
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'x_tick_locators', 'y_tick_locators',
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'xticks', 'hide_x_ticks', 'hide_y_ticks', 'hide_x_ticklabels', 'hide_y_ticklabels',
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'colours', 'palettes', 'title', 'legend', 'legend_position', 'subplots_adjust', 'text', 'legend_ncol']
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'rotation_x_ticks', 'rotation_y_ticks',
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'xticks', 'yticks',
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'xlim', 'ylim',
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'title',
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'legend', 'legend_position', 'legend_ncol',
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'subplots_adjust',
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'text']
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default_options = {
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'plot_kind': None, # defaults to None, but should be utilised when requiring special formatting for a particular plot
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'hide_x_labels': False, # Whether x labels should be hidden
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'hide_x_ticklabels': False,
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'hide_x_ticks': False,
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'rotation_x_ticks': 0,
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'hide_y_labels': False, # whether y labels should be hidden
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'hide_y_ticklabels': False,
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'hide_y_ticks': False,
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'rotation_y_ticks': 0,
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'xlim': None,
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'ylim': None,
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'x_tick_locators': [.5, .25], # Major and minor tick locators
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'y_tick_locators': [.5, .25],
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'xticks': None,
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'labels': None,
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'colours': None,
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'palettes': [('qualitative', 'Dark2_8'), ('qualitative', 'Paired_12')],
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'title': None,
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'legend': False,
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'legend_position': ['lower center', (0.5, -0.1)], # the position of the legend passed as arguments to loc and bbox_to_anchor respectively
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'legend_ncol': 1,
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'subplots_adjust': [0.1, 0.1, 0.9, 0.9],
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'text': None
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'hide_x_labels': False, 'hide_y_labels': False, # Whether the main labels on the x- and/or y-axes should be hidden
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'hide_x_ticklabels': False, 'hide_y_ticklabels': False, # Whether ticklabels on the x- and/or y-axes should be hidden
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'hide_x_ticks': False, 'hide_y_ticks': False, # Whether the ticks on the x- and/or y-axes should be hidden
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'x_tick_locators': None, 'y_tick_locators': None, # The major and minor tick locators for the x- and y-axes
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'rotation_x_ticks': 0, 'rotation_y_ticks': 0, # Degrees the x- and/or y-ticklabels should be rotated
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'xticks': None, 'yticks': None, # Custom definition of the xticks and yticks. This is not properly implemented now.
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'xlim': None, 'ylim': None, # Limits to the x- and y-axes
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'title': None, # Title of the plot
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'legend': False, 'legend_position': ['lower center', (0.5, -0.1)], 'legend_ncol': 1, # Toggles on/off legend. Specifices legend position and the number of columns the legend should appear as.
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'subplots_adjust': [0.1, 0.1, 0.9, 0.9], # Adjustment of the Axes-object within the Figure-object. Fraction of the Figure-object the left, bottom, right and top edges of the Axes-object will start.
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'text': None # Text to show in the plot. Should be a list where the first element is the string, and the second is a tuple with x- and y-coordinates. Could also be a list of lists to show more strings of text.
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}
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options = update_options(options=options, required_options=required_options, default_options=default_options)
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options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
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# Set labels on x- and y-axes
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if not options['hide_y_labels']:
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@ -106,18 +106,22 @@ def prettify_plot(fig, ax, plot_data, options):
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# Set multiple locators
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if options['y_tick_locators']:
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ax.yaxis.set_major_locator(MultipleLocator(options['y_tick_locators'][0]))
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ax.yaxis.set_minor_locator(MultipleLocator(options['y_tick_locators'][1]))
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if options['x_tick_locators']:
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ax.xaxis.set_major_locator(MultipleLocator(options['x_tick_locators'][0]))
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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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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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else:
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ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
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ax.set_xticklabels([x/2 for x in np.arange(plot_data['start'], plot_data['end']+1)])
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# else:
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# ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
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# ax.set_xticklabels([x/2 for x in np.arange(plot_data['start'], plot_data['end']+1)])
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# Hide x- and y- ticklabels
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if options['hide_y_ticklabels']:
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@ -202,7 +206,14 @@ def prettify_plot(fig, ax, plot_data, options):
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# Add custom text
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if options['text']:
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plt.text(x=options['text'][1][0], y=options['text'][1][1], s=options['text'][0])
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# If only a single element, put it into a list so the below for-loop works.
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if isinstance(options['text'][0], str):
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options['text'] = [options['text']]
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# Plot all passed texts
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for text in options['text']:
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plt.text(x=text[1][0], y=text[1][1], s=text[0])
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return fig, ax
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@ -210,28 +221,40 @@ def prettify_plot(fig, ax, plot_data, options):
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def ipywidgets_update(func, plot_data, options={}, **kwargs):
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''' A general ipywidgets update function that can be passed to ipywidgets.interactive. To use this, you can run:
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import ipywidgets as widgets
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import beamtime.plotting as btp
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w = widgets.interactive(btp.ipywidgets_update, func=widgets.fixed(my_func), plot_data=widgets.fixed(plot_data), options=widgets.fixed(options), key1=widget1, key2=widget2, key3=widget3)
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where key1, key2, key3 etc. are the values in the options-dictionary you want widget control of, and widget1, widget2, widget3 etc. are widgets to control these values, e.g. widgets.IntSlider(value=1, min=0, max=10)
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'''
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# Update the options-dictionary with the values from the widgets
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for key in kwargs:
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options[key] = kwargs[key]
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# Call the function with the plot_data and options-dictionaries
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func(plot_data=plot_data, options=options)
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def determine_width(options):
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def determine_width(format_params):
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''' '''
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conversion_cm_inch = 0.3937008 # cm to inch
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if options['column_type'] == 'single':
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column_width = options['single_column_width']
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elif options['column_type'] == 'double':
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column_width = options['double_column_width']
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if format_params['column_type'] == 'single':
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column_width = format_params['single_column_width']
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elif format_params['column_type'] == 'double':
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column_width = format_params['double_column_width']
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column_width *= conversion_cm_inch
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width_ratio = [float(num) for num in options['width_ratio'].split(':')]
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width_ratio = [float(num) for num in format_params['width_ratio'].split(':')]
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width = column_width * width_ratio[0]/width_ratio[1]
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@ -240,18 +263,18 @@ def determine_width(options):
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return width
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def determine_height(options, width):
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def determine_height(format_params, width):
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aspect_ratio = [float(num) for num in options['aspect_ratio'].split(':')]
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aspect_ratio = [float(num) for num in format_params['aspect_ratio'].split(':')]
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height = width/(aspect_ratio[0] / aspect_ratio[1])
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return height
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def scale_figure(options, width, height):
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width = width * options['upscaling_factor'] * options['compress_width']
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height = height * options['upscaling_factor'] * options['compress_height']
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def scale_figure(format_params, width, height):
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width = width * format_params['upscaling_factor'] * format_params['compress_width']
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height = height * format_params['upscaling_factor'] * format_params['compress_height']
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return width, height
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@ -7,38 +7,48 @@ import math
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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(plot_data, options={}):
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''' Plots a diffractogram.
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def plot_diffractogram(path, kind, options=None):
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# Prepare plot, and read and process data
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fig, ax = prepare_diffractogram_plot(options=options)
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diffractogram = xrd.io.read_data(path=path, kind=kind, options=options)
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Input:
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plot_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', 'scatter']
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required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'scatter', 'plot_kind', 'rc_params', 'format_params']
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default_options = {
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'x_vals': '2th',
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'y_vals': 'I',
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'scatter': False
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'ylabel': 'Intensity', 'xlabel': '2theta',
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'xunit': 'deg', 'yunit': 'a.u.',
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'scatter': False,
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'plot_kind': None,
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'rc_params': {},
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'format_params': {}
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}
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options = update_options(options=options, required_options=required_options, default_options=default_options)
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options = aux.update_options(options=options, required_options=required_options, default_options=default_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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diffractogram = xrd.io.read_data(path=plot_data['path'], kind=plot_data['plot_kind'], options=options)
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if options['scatter']:
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diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, kind='scatter')
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ax.scatter(x= diffractogram[options['x_vals']], y = diffractogram[options['y_vals']])
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#diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, kind='scatter')
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else:
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diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax)
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fig, ax = prettify_diffractogram_plot(fig=fig, ax=ax, options=options)
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fig, ax = btp.adjust_plot(fig=fig, ax=ax, options=options)
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return diffractogram, fig, ax
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