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A plugin based data load and manimupulation library.

Installation

Use pip like:

$ pip install maidenhair

Usage

Assume that there are three kinds of samples and each samples have 5 indipendent experimental results. All filenames are written as the following format:

sample-type<type number>.<experiment number>.txt

And files are saved in data directory like:

+- data
    |
    +- sample-type1.001.txt
    +- sample-type1.002.txt
    +- sample-type1.003.txt
    +- sample-type1.004.txt
    +- sample-type1.005.txt
    +- sample-type2.001.txt
    +- sample-type2.002.txt
    +- sample-type2.003.txt
    +- sample-type2.004.txt
    +- sample-type2.005.txt
    +- sample-type3.001.txt
    +- sample-type3.002.txt
    +- sample-type3.003.txt
    +- sample-type3.004.txt
    +- sample-type3.005.txt

Then, the code for plotting the data will be:

>>> import matplotlib.pyplot as plt
>>> import maidenhair
>>> import maidenhair.statistics
>>> dataset = []
>>> dataset += maidenhair.load('data/sample-type1.*.txt', unite=True)
>>> dataset += maidenhair.load('data/sample-type2.*.txt', unite=True)
>>> dataset += maidenhair.load('data/sample-type3.*.txt', unite=True)
>>> nameset = ['Type1', 'Type2', 'Type3']
>>> for name, (x, y) in zip(nameset, dataset):
...     xa = maidenhair.statistics.average(x)
...     ya = maidenhair.statistics.average(y)
...     ye = maidenhair.statistics.confidential_interval(y)
...     plt.errorbar(xa, ya, yerr=ye, label=name)
...
>>> plt.show()

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Release files for maidenhair 0.3.5

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