Welcome to maidenhair’s documentation!¶
maidenhair¶
A plugin based data load and manimupulation library.
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()