spacepy.toolbox.poisson_fit

spacepy.toolbox.poisson_fit(data, initial=None, method='Powell')[source]

Fit a Poisson distribution to data using the method and initial guess provided.

Parameters
dataarray-like

Data to fit a Poisson distribution to.

initialint or None

initial guess for the fit, if None np.median(data) is used

methodstr

method passed to scipy.optimize.minimize, default=’Powell’

Returns
resultscipy.optimize.optimize.OptimizeResult

Resulting fit results from scipy.optimize, answer is result.x, user should likely round.

Examples

>>> import spacepy.toolbox as tb
>>> from scipy.stats import poisson
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> data = poisson.rvs(20, size=1000)
>>> res = tb.poisson_fit(data)
>>> print(res.x)
19.718000038769095
>>> xvals = np.arange(0, np.max(data)+5)
>>> plt.hist(data, bins=xvals, normed=True)
>>> plt.plot(xvals, poisson.pmf(xvals, np.round(res.x)))