source: Examples/scripts/python/plot_carbon_data.py @ 4966

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Author: Jackson O'Donnell
#   jacksonhodonnell@gmail.com

# An example script collecting data from a number of .gpx files
#   and plotting some aggregate

from __future__ import division, print_function
import glob
import matplotlib.pyplot as plt
import pandas as pd
# Add GSASII to PYTHONPATH so this can iport
import GSASIIscriptable as G2sc


def name(p):
    return int(p.filename[-9:-4])


def get_info(p):
    """Get the desired info from a project. Returns a dictionary"""
    phase = p.phases()[0]
    hist = p.histograms()[0]
    # Output unit cell information
    output = phase.get_cell()
    # Gather histogram residuals, occupancy of a given atom,
    # goodness of fit
    output.update(hist.residuals)
    output.update({'O5 occupancy': phase.atom('O5').occupancy})
    output['Rf^2'] = hist.data['data'][0]['0:0:Rf^2']
    output['chisq'] = p['Covariance']['data']['Rvals']['chisq']
    output['GOF'] = p['Covariance']['data']['Rvals']['GOF']
    return output

if __name__ == '__main__':
    files = glob.glob('carbon_output/*.gpx')
    projs = [G2sc.G2Project(f) for f in files]
    projs.sort(key=name)

    index = [name(p) for p in projs]
    df = pd.DataFrame([get_info(p) for p in projs], index=index)

    # Plot volume and occupancy together
    plt.rc('text', usetex=True)
    plt.rc('font', weight='bold', size='20')
    fig, (ax1, axbot1) = plt.subplots(2)
    df['O5 occupancy'].plot(ax=ax1, color='r')
    ax1.set_ylabel('Oxygen occupancy, [0,1]', color='r')
    ax1.tick_params('y', colors='r')

    ax2 = ax1.twinx()
    df['volume'].plot(ax=ax2, color='b')
    ax2.set_ylabel(r'Unit Cell Volume, A$^3$', color='b')
    ax2.tick_params('y', colors='b')

    # Plot residuals on same scale
    df['wR'].plot(ax=axbot1, label='wR')
    df['Rf^2'].plot(ax=axbot1, label='Rf^2')
    axbot1.set_ylabel(r'Residual (\%)')
    axbot1.set_xlabel('Data set number')

    axbot2 = axbot1.twinx()
    df['GOF'].plot(ax=axbot2, label='GOF', color='r')
    axbot2.set_ylabel(r'GOF')

    lns = axbot1.lines + axbot2.lines
    labs = [l.get_label() for l in lns]
    axbot1.legend(lns, labs, loc=0)

    fig.suptitle(r'Refined $\alpha$-MnO$_2$ at U$_{iso}$ = 0.01')

    plt.show()