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Generalise prepare_plot and adjust_plot

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rasmusvt 2022-03-11 17:52:01 +01:00
parent d993663c7c
commit 67ea048380
2 changed files with 107 additions and 74 deletions
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139
beamtime/plotting.py
View file

@ -1,4 +1,5 @@
import beamtime.auxillary as aux import beamtime.auxillary as aux
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator) from matplotlib.ticker import (MultipleLocator, FormatStrFormatter,AutoMinorLocator)
from mpl_toolkits.axes_grid.inset_locator import (inset_axes, InsetPosition, mark_inset) from mpl_toolkits.axes_grid.inset_locator import (inset_axes, InsetPosition, mark_inset)
@ -10,20 +11,23 @@ from cycler import cycler
import itertools import itertools
import numpy as np
def prepare_plot(options={}): def prepare_plot(options={}):
''' Prepares plot based on contents of options['rc_params'] and options['format_params']. ''' A general function to prepare a plot based on contents of options['rc_params'] and options['format_params'].
rc_params is a dictionary with keyval-pairs corresponding to rcParams in matplotlib 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
format_params will determine the size and aspect ratios of ''' format_params will determine the size, aspect ratio, resolution etc. of the figure. Should be modified to conform with any requirements from a journal.'''
rc_params = options['rc_params'] rc_params = options['rc_params']
format_params = options['format_params'] format_params = options['format_params']
required_options = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi'] required_format_params = ['single_column_width', 'double_column_width', 'column_type', 'width_ratio', 'aspect_ratio', 'compress_width', 'compress_height', 'upscaling_factor', 'dpi']
default_options = { default_format_params = {
'single_column_width': 8.3, 'single_column_width': 8.3,
'double_column_width': 17.1, 'double_column_width': 17.1,
'column_type': 'single', 'column_type': 'single',
@ -35,7 +39,7 @@ def prepare_plot(options={}):
'dpi': 600, 'dpi': 600,
} }
options = aux.update_options(format_params, required_options, default_options) format_params = aux.update_options(format_params, required_format_params, default_format_params)
# Reset run commands # Reset run commands
@ -44,54 +48,50 @@ def prepare_plot(options={}):
# Update run commands if any is passed (will pass an empty dictionary if not passed) # Update run commands if any is passed (will pass an empty dictionary if not passed)
update_rc_params(rc_params) update_rc_params(rc_params)
width = determine_width(options) width = determine_width(format_params=format_params)
height = determine_height(options, width) height = determine_height(format_params=format_params, width=width)
width, height = scale_figure(options=options, width=width, height=height) width, height = scale_figure(format_params=format_params, width=width, height=height)
fig, ax = plt.subplots(figsize=(width, height), dpi=options['dpi']) fig, ax = plt.subplots(figsize=(width, height), dpi=format_params['dpi'])
return fig, ax return fig, ax
def prettify_plot(fig, ax, plot_data, options): def adjust_plot(fig, ax, options):
''' A general function to adjust plot according to contents of the options-dictionary '''
required_options = ['plot_kind', required_options = [
'plot_kind',
'hide_x_labels', 'hide_y_labels', 'hide_x_labels', 'hide_y_labels',
'rotation_x_ticks', 'rotation_y_ticks', 'hide_x_ticklabels', 'hide_y_ticklabels',
'xlim', 'ylim', 'hide_x_ticks', 'hide_y_ticks',
'x_tick_locators', 'y_tick_locators', 'x_tick_locators', 'y_tick_locators',
'xticks', 'hide_x_ticks', 'hide_y_ticks', 'hide_x_ticklabels', 'hide_y_ticklabels', 'rotation_x_ticks', 'rotation_y_ticks',
'colours', 'palettes', 'title', 'legend', 'legend_position', 'subplots_adjust', 'text', 'legend_ncol'] 'xticks', 'yticks',
'xlim', 'ylim',
'title',
'legend', 'legend_position', 'legend_ncol',
'subplots_adjust',
'text']
default_options = { default_options = {
'plot_kind': None, # defaults to None, but should be utilised when requiring special formatting for a particular plot 'plot_kind': None, # defaults to None, but should be utilised when requiring special formatting for a particular plot
'hide_x_labels': False, # Whether x labels should be hidden 'hide_x_labels': False, 'hide_y_labels': False, # Whether the main labels on the x- and/or y-axes should be hidden
'hide_x_ticklabels': False, 'hide_x_ticklabels': False, 'hide_y_ticklabels': False, # Whether ticklabels on the x- and/or y-axes should be hidden
'hide_x_ticks': False, 'hide_x_ticks': False, 'hide_y_ticks': False, # Whether the ticks on the x- and/or y-axes should be hidden
'rotation_x_ticks': 0, 'x_tick_locators': None, 'y_tick_locators': None, # The major and minor tick locators for the x- and y-axes
'hide_y_labels': False, # whether y labels should be hidden 'rotation_x_ticks': 0, 'rotation_y_ticks': 0, # Degrees the x- and/or y-ticklabels should be rotated
'hide_y_ticklabels': False, 'xticks': None, 'yticks': None, # Custom definition of the xticks and yticks. This is not properly implemented now.
'hide_y_ticks': False, 'xlim': None, 'ylim': None, # Limits to the x- and y-axes
'rotation_y_ticks': 0, 'title': None, # Title of the plot
'xlim': None, '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.
'ylim': None, '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.
'x_tick_locators': [.5, .25], # Major and minor tick locators '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.
'y_tick_locators': [.5, .25],
'xticks': None,
'labels': None,
'colours': None,
'palettes': [('qualitative', 'Dark2_8'), ('qualitative', 'Paired_12')],
'title': None,
'legend': False,
'legend_position': ['lower center', (0.5, -0.1)], # the position of the legend passed as arguments to loc and bbox_to_anchor respectively
'legend_ncol': 1,
'subplots_adjust': [0.1, 0.1, 0.9, 0.9],
'text': None
} }
options = update_options(options=options, required_options=required_options, default_options=default_options) options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
# Set labels on x- and y-axes # Set labels on x- and y-axes
if not options['hide_y_labels']: if not options['hide_y_labels']:
@ -106,18 +106,22 @@ def prettify_plot(fig, ax, plot_data, options):
# Set multiple locators # Set multiple locators
ax.yaxis.set_major_locator(MultipleLocator(options['y_tick_locators'][0])) if options['y_tick_locators']:
ax.yaxis.set_minor_locator(MultipleLocator(options['y_tick_locators'][1])) ax.yaxis.set_major_locator(MultipleLocator(options['y_tick_locators'][0]))
ax.yaxis.set_minor_locator(MultipleLocator(options['y_tick_locators'][1]))
ax.xaxis.set_major_locator(MultipleLocator(options['x_tick_locators'][0])) if options['x_tick_locators']:
ax.xaxis.set_minor_locator(MultipleLocator(options['x_tick_locators'][1])) ax.xaxis.set_major_locator(MultipleLocator(options['x_tick_locators'][0]))
ax.xaxis.set_minor_locator(MultipleLocator(options['x_tick_locators'][1]))
# THIS NEEDS REWORK FOR IT TO FUNCTION PROPERLY!
if options['xticks']: if options['xticks']:
ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1)) ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
ax.set_xticklabels(options['xticks']) ax.set_xticklabels(options['xticks'])
else: # else:
ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1)) # ax.set_xticks(np.arange(plot_data['start'], plot_data['end']+1))
ax.set_xticklabels([x/2 for x in np.arange(plot_data['start'], plot_data['end']+1)]) # ax.set_xticklabels([x/2 for x in np.arange(plot_data['start'], plot_data['end']+1)])
# Hide x- and y- ticklabels # Hide x- and y- ticklabels
if options['hide_y_ticklabels']: if options['hide_y_ticklabels']:
@ -202,7 +206,14 @@ def prettify_plot(fig, ax, plot_data, options):
# Add custom text # Add custom text
if options['text']: if options['text']:
plt.text(x=options['text'][1][0], y=options['text'][1][1], s=options['text'][0])
# If only a single element, put it into a list so the below for-loop works.
if isinstance(options['text'][0], str):
options['text'] = [options['text']]
# Plot all passed texts
for text in options['text']:
plt.text(x=text[1][0], y=text[1][1], s=text[0])
return fig, ax return fig, ax
@ -210,28 +221,40 @@ def prettify_plot(fig, ax, plot_data, options):
def ipywidgets_update(func, plot_data, options={}, **kwargs): def ipywidgets_update(func, plot_data, options={}, **kwargs):
''' A general ipywidgets update function that can be passed to ipywidgets.interactive. To use this, you can run:
import ipywidgets as widgets
import beamtime.plotting as btp
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)
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)
'''
# Update the options-dictionary with the values from the widgets
for key in kwargs: for key in kwargs:
options[key] = kwargs[key] options[key] = kwargs[key]
# Call the function with the plot_data and options-dictionaries
func(plot_data=plot_data, options=options) func(plot_data=plot_data, options=options)
def determine_width(options): def determine_width(format_params):
''' '''
conversion_cm_inch = 0.3937008 # cm to inch conversion_cm_inch = 0.3937008 # cm to inch
if options['column_type'] == 'single': if format_params['column_type'] == 'single':
column_width = options['single_column_width'] column_width = format_params['single_column_width']
elif options['column_type'] == 'double': elif format_params['column_type'] == 'double':
column_width = options['double_column_width'] column_width = format_params['double_column_width']
column_width *= conversion_cm_inch column_width *= conversion_cm_inch
width_ratio = [float(num) for num in options['width_ratio'].split(':')] width_ratio = [float(num) for num in format_params['width_ratio'].split(':')]
width = column_width * width_ratio[0]/width_ratio[1] width = column_width * width_ratio[0]/width_ratio[1]
@ -240,18 +263,18 @@ def determine_width(options):
return width return width
def determine_height(options, width): def determine_height(format_params, width):
aspect_ratio = [float(num) for num in options['aspect_ratio'].split(':')] aspect_ratio = [float(num) for num in format_params['aspect_ratio'].split(':')]
height = width/(aspect_ratio[0] / aspect_ratio[1]) height = width/(aspect_ratio[0] / aspect_ratio[1])
return height return height
def scale_figure(options, width, height): def scale_figure(format_params, width, height):
width = width * options['upscaling_factor'] * options['compress_width'] width = width * format_params['upscaling_factor'] * format_params['compress_width']
height = height * options['upscaling_factor'] * options['compress_height'] height = height * format_params['upscaling_factor'] * format_params['compress_height']
return width, height return width, height

36
beamtime/xrd/plot.py
View file

@ -7,38 +7,48 @@ import math
import beamtime.xrd as xrd import beamtime.xrd as xrd
import beamtime.auxillary as aux
import beamtime.plotting as btp
def plot_diffractogram(plot_data, options={}):
''' Plots a diffractogram.
def plot_diffractogram(path, kind, options=None): Input:
plot_data (dict): Must include path = string to diffractogram data, and plot_kind = (recx, beamline, image)'''
# Prepare plot, and read and process data
fig, ax = prepare_diffractogram_plot(options=options)
diffractogram = xrd.io.read_data(path=path, kind=kind, options=options)
# Update options # Update options
required_options = ['x_vals', 'y_vals', 'scatter'] required_options = ['x_vals', 'y_vals', 'ylabel', 'xlabel', 'xunit', 'yunit', 'scatter', 'plot_kind', 'rc_params', 'format_params']
default_options = { default_options = {
'x_vals': '2th', 'x_vals': '2th',
'y_vals': 'I', 'y_vals': 'I',
'scatter': False 'ylabel': 'Intensity', 'xlabel': '2theta',
'xunit': 'deg', 'yunit': 'a.u.',
'scatter': False,
'plot_kind': None,
'rc_params': {},
'format_params': {}
} }
options = update_options(options=options, required_options=required_options, default_options=default_options) options = aux.update_options(options=options, required_options=required_options, default_options=default_options)
# Prepare plot, and read and process data
fig, ax = btp.prepare_plot(options=options)
diffractogram = xrd.io.read_data(path=plot_data['path'], kind=plot_data['plot_kind'], options=options)
if options['scatter']: if options['scatter']:
diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, kind='scatter') ax.scatter(x= diffractogram[options['x_vals']], y = diffractogram[options['y_vals']])
#diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax, kind='scatter')
else: else:
diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax) diffractogram.plot(x=options['x_vals'], y=options['y_vals'], ax=ax)
fig, ax = prettify_diffractogram_plot(fig=fig, ax=ax, options=options) fig, ax = btp.adjust_plot(fig=fig, ax=ax, options=options)
return diffractogram, fig, ax return diffractogram, fig, ax