Spherical statistics in Python
Project description
spherical_stats
Spherical statistics in Python
Installation
pip install spherical_stats
Documentation
Refer to the online documentation for examples and API reference.
Features:
- Visualization helper functions to quickly generate data to be plotted with plotly/matplotlib/ipyvolume:
- Sphere creation and evaluation of a function over its surface
- Spherical histogram
- Descriptive statistics:
- Spherical mean and spherical variance
- Orientation tensor
- Parametric distributions with scipy.stats like API:
- Modeling axial data: Angular central gaussian distribution (ACG)
- Modeling vector data: Elliptically symmetrical angular gausian distribution (ESAG), Von Mises-Fisher distribution (VMF)
Example usage of the distributions:
from spherical_stats import ESAG
import numpy as np
esag_params = np.array([1,3,5,2,6])
#Instantiate ESAG class with known parameters
esag_known = ESAG(esag_params)
#generate 500 ESAG samples and calculate their PDF vals
samples = esag_known.rvs(500)
pdf_vals = esag.pdf(samples)
#Instantiate ESAG class and fit distribution parameters given samples
esag_unknown = ESAG()
esag_unknown.fit(samples, verbose = True)
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