Skip to main content

Installation

This package requires xraylib and compwizard. On Windows, xraylib can be installed through the Anaconda interface.

conda install -c conda-forge xraylib=4.0.0
pip instal compwizard

For further information on how to install xraylib on other operational systems, check xraylib wiki.
This module can be installed with:

pip install xfit

Usage

This module provides the "Spectrum" class. It is possible to initialize this class with a numpy nd.array or loading an *.mca or *.spt file, by giving the path. For the continuum estimation algorithm, refer to the Continuum.py file.
Test.py file provides a common *.mca file to use with the example.py script provided.

Example 1

import xfit
import numpy as np
import matplotlib.pyplot as plt
path = r"./test.mca"
pool_file = r"./pool.txt"
Spec = xfit.Spectrum(file_path=path)
Spec.calibrate() #if no arguments are passed, it gets the parameters from the mca or spt header
Spec.estimate_continuum(30, 11, 11, 3) #iterations, filter window, sav-gol window, sav-gol order
Spec.fit_fano_and_noise()
Spec.create_pool(pool_file)
Spec.fit()

#Plot ------
fig, ax = plt.subplots()
ax.plot(Spec.energyaxis, Spec.data, color="black", label="Data")
ax.plot(Spec.energyaxis, Spec.continuum, color="green", label="Continuum")
for element in Spec.areas.keys():
     ax.plot(Spec.energyaxis, 
            Spec.plots[element],
            label=element+" fit result", 
            color=ElementColors[element],
            linestyle="--")
ax.legend(loc=1, fancybox=1)
ax.set_yscale("log")
plt.show()

0.11400000005960464 80.00951851146041 (Fano and Noise values found, respectively)
Output

Example 2

import xfit
import numpy as np
ydata = np.arange(1024)
fit_pool = {}
fit_pool["elements"] = {}
fit_pool["elements"]["Cu"] = ["KA1","KA2","KB1","KB3"]
fit_pool["bg"] = 1 #Forces the use of continuum estimation for the fit
Spec = xfit.Spectrum(array=ydata)
Spec.calibrate(x=channels, y=energies)
Spec.estimate_continuum(30, 11, 11, 3)
Spec.fit_fano_and_noise()
Spec.pool = fit_pool
Spec.fit()
#or simply: Spec.fit(pool=fit_pool)

#Plot ------
fig, ax = plt.subplots()
ax.plot(Spec.energyaxis, Spec.data, color="black", label="Data")
ax.plot(Spec.energyaxis, Spec.continuum, color="green", label="Continuum")
for element in Spec.areas.keys():
     ax.plot(Spec.energyaxis, 
            Spec.plots[element],
            label=element+" fit result", 
            color=ElementColors[element],
            linestyle="--")
ax.legend(loc=1, fancybox=1)
ax.set_yscale("log")
plt.show()

Metadata

Release files for xfit 0.1.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for xfit 0.1.1.0
File Size Uploaded Provenance
xfit-0.1.1.0.tar.gz 12.1 kB Without provenance Details

Built distribution (wheel)

Table of built distributions (wheels) for xfit 0.1.1.0
File Interpreter ABI Platform
xfit-0.1.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 24.7 kB

Release files / xfit-0.1.1.0.tar.gz

Download URL xfit-0.1.1.0.tar.gz
Size 12.1 kB
Tags Source
SHA-256 checksum
How to use checksums
00e7f067ff001b658456953f2874b6ab1b3fdf97f6da4909d00a7ff8e418f96b
BLAKE2b-256 checksum
How to use checksums
87aaf48930b8da2f79ba83b1c36e060c84ef035ea1b8e01d5ebb95a9c8aea1c8
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/54.1.2 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.6

Release files / xfit-0.1.1.0-py3-none-any.whl

Download URL xfit-0.1.1.0-py3-none-any.whl
Size 12.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f1e7fea44ce729969e2d1cb0917351888ede5c184f595c03ed3b3dedcc821788
BLAKE2b-256 checksum
How to use checksums
8d73858e746ff5be46899d0fd603201b5145de60914c3298b7f60f002f2812fc
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/3.3.0 pkginfo/1.7.0 requests/2.23.0 setuptools/54.1.2 requests-toolbelt/0.9.1 tqdm/4.43.0 CPython/3.7.6

Security for xfit 0.1.1.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page