stats — Statistics functions module.¶
This module contains utility functions used for statistics in ADMIT.
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admit.util.stats.mystats(data)[source]¶ return raw and robust statistics for a distribution
Parameters: data : array
The data array for which the statistics is returned.
Returns: returns: N, mean, std for the raw and robust resp.
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admit.util.stats.reducedchisquared(data, model, numpar, noise=None)[source]¶ Method to compute the reduced chi squared of a fit to data.
Parameters: data : array like
The raw data the fit is based on, acceptable data types are numpy array, masked array, and list
model : array like
The fit to the data, acceptable data types are numpy array, masked array, and list. Must be of the same length as data, no error checking is done
dof : int
Number of free parameters (degrees of freedom) in the model
noise : float
The noise/uncertainty of the data
Returns: Float containing the reduced chi squared value, the closer to 1.0
the better
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admit.util.stats.rejecto1(data, f=1.5)[source]¶ reject outliers from a distribution using a hinges-fences style rejection, using a mean.
Parameters: data : array
f : float
The factor f, such that only data is retained between mean - f*std and mean + f*std
Returns: returns: an array with only data between
mean - f*std and mean + f*std
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admit.util.stats.rejecto2(data, f=1.5)[source]¶ - reject outliers from a distribution
- using a hinges-fences style rejection, using a median.
Parameters: data : array
f : float
The factor f, such that only data is retained between median - f*std and median + f*std
Returns: returns: an array with only data between
median - f*std and median + f*std