powerxrd 2.1.2

Simple tools to handle powder XRD (and XRD) data with Python.

powerxrd

Simple tools to handle powder XRD (and XRD) data

Installation

pip install powerxrd

Usage

On your Terminal ("command line"), copy-paste the following lines:

cd Desktop   		# go to your Desktop
mkdir pxrd		# create a folder called pxrd

cd pxrd 		# go inside that folder
touch example.py  	# create example.py file
wget https://raw.githubusercontent.com/andrewrgarcia/powerxrd/main/sample1.xy	# download sample1.xy file

Plots from tests/test_module

Code shows basic application of this module. On a blank Python file, type the following:

import powerxrd as xrd
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

def test_backsub():
    
    data = xrd.Data('sample1.xy').importfile()
    chart = xrd.Chart(*data)

    chart.emission_lines(xrange_Ka=[10,20], show=True)
    plt.plot(*data,label='no backsub')
    plt.plot(*chart.backsub(),label='backsub')
    plt.xlabel('2 $\\theta$')
    plt.legend()
    plt.show()

def test_sch():
    
    data = xrd.Data('sample1.xy').importfile()
    chart = xrd.Chart(*data)

    chart.backsub(tol=1.0,show=True)
    chart.SchPeak(xrange=[18,22],show=True)
    plt.xlabel('2 $\\theta$')
    plt.title('backsub and Scherrer width calculation')
    plt.show()

'''[OUT]
SchPeak: Scherrer width calc. for peak in range of [18,22]

-Gaussian fit results-
y-shift 10071.343657500349
amplitude 498186.5044519722
mean 19.921493157135924
sigma 0.1692913723155234
covariance matrix 
[[ 2.20553363e+07 -1.98537382e+07 -3.73304414e-08 -4.49772395e+00]
 [-1.98537382e+07  7.90011550e+07 -2.89541102e-09  1.78971558e+01]
 [-3.73304414e-08 -2.89541102e-09  9.41177383e-06 -8.26802823e-12]
 [-4.49772395e+00  1.78971558e+01 -8.26802823e-12  1.03289908e-05]]

FWHM == sigma*2*sqrt(2*ln(2)): 0.39865071697939203 degrees
K (shape factor): 0.9
K-alpha: 0.15406 nm 
max 2-theta: 19.91162984576907 degrees
Scherrer Width == K*lmda / (FWHM*cos(theta))

SCHERRER WIDTH: 20.23261907915097 nm
'''

def test_allpeaks():
    
    data = xrd.Data('sample1.xy').importfile()
    chart = xrd.Chart(*data)

    chart.backsub(tol=1.0,show=True)
    chart.allpeaks(tols=(0.2,0.8),show=True)
    plt.xlabel('2 $\\theta$')
    plt.suptitle('backsub & Automated Scherrer width calculation of all peaks*')
    plt.show()

'''[OUT]

.
.
.

allpeaks : Automated Scherrer width calculation of all peaks [within a certain tolerance]
SUMMARY:
2-theta / deg, 	 Intensity, 	 Sch width / nm
10.842851187995, 	  168253.24331045512, 	  9.441628912735878 
19.91162984576907, 	  1173162.1712873918, 	  20.135492565092957 
27.037098791162983, 	  106100.29651133435, 	  11.637934653748315 
29.19633180491872, 	  612236.4986085768, 	  14.141811760734479 
35.488953730721136, 	  85476.80399923288, 	  18.062742760350677 
38.45018757815757, 	  878296.1296163809, 	  16.688459614982563 
40.45518966235932, 	  72528.3080639828, 	  861.4498530251062 
47.704043351396415, 	  1311776.3933334802, 	  20.745821993861888 
75.52730304293456, 	  167210.87548438687, 	  11.141240095107339 
'''

def test_mav():
    
    data = xrd.Data('sample1.xy').importfile()
    chart = xrd.Chart(*data)

    chart.backsub()
    n = 20
    plt.plot(*chart.mav(n))
    plt.xlabel('2 $\\theta$')
    plt.title('backsub and {}-point moving average'.format(n))
    plt.show()

Contributors

• Andrew Garcia - creator and maintainer

Contributing

1. Fork it (https://github.com/your-github-user/tensorscout/fork)
2. Create your feature branch (git checkout -b my-new-feature)
3. Commit your changes (git commit -am 'Add some feature')
4. Push to the branch (git push origin my-new-feature)
5. Create a new Pull Request