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Beam Profile Analysing Tools

Project Description

beprof

Documentation Status

Overview

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Overv.io issue board: https://overv.io/DataMedSci/beprof/

Beam Profile Analysing Tools

Library provides methods to work with Beam Profiles which are sets of points (2-D with optional metadata) sorted by one of coordinates. cd beprof is based on nparray class from numpy, and it provides numerous tools for different computations and data analysis.

Installation

Current version available on testing PyPi server, although once a stable version is ready it will be pushed to official PyPi repo.

For now, installation can be done from this GIT repository, using:

pip install setuptools versioneer
pip install git+https://github.com/DataMedSci/beprof.git

To unistall, simply use:

pip uninstall beprof

Documentation

https://beprof.readthedocs.io/

Features

Once you install beprof, you should be able to import is as a python module Using ipython the code would be i.e.:

import beprof
from beprof import curve  #imports curve module
from beprof import profile  #imports profile module

Once you import necessary modules, you can use them to work with i.e. profiles:

from beprof import profile
dir(profile)
p = profile.Profile([[0, 1], [1, -1], [2, 3], [4, 0]])
print(p)

You can also use another modules as numpy or matplotlib to work with beprof:

#assuming you already defined p as above
import numpy as np
import matplotlib.pyplot as plt
foo = np.asarray(p)
print(foo.shape())
plt.plot(foo[:,0], foo[:,1])
plt.show()

Note that beprof is a library and end-users shouldn’t “run it”. It is also strongly discouraged to use git clone to download code. Git is only for developers, end-users should use pip installation. If you are interested in development - have a look at CONTRIBUTING section.

Credits

This package was created with Cookiecutter and the grzanka/cookiecutter-pip-docker-versioneer project template.

Release history Release notifications

This version
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0.1.3

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0.1.2

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0.1.1

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0.1.0

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beprof-0.1.3-py2.py3-none-any.whl (17.4 kB) Copy SHA256 hash SHA256 Wheel py2.py3 Aug 18, 2017

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