powerxrd 2.1.0

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(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(show=True,xrange=[18,22])
    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(tol=0.2,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: 10.842851187995 deg - Sch width: 8.941734253261906 nm
2-theta: 19.91162984576907 deg - Sch width: 19.506346638418783 nm
2-theta: 27.037098791162983 deg - Sch width: 10.82238857760865 nm
2-theta: 29.19633180491872 deg - Sch width: 12.19498841711745 nm
2-theta: 35.488953730721136 deg - Sch width: 16.215930196133126 nm
2-theta: 38.45018757815757 deg - Sch width: 14.81225507944928 nm
2-theta: 40.45518966235932 deg - Sch width: 50.49857930719013 nm
2-theta: 47.704043351396415 deg - Sch width: 20.034855818080402 nm
2-theta: 75.52730304293456 deg - Sch width: 9.010130859537554 nm
'''

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