`numpy.lib._histograms_impl:_hist_bin_fd`

source: build-install/usr/lib/python3.14/site-packages/numpy/lib/_histograms_impl.py :200

Signature

def _hist_bin_fd ( x , range )

Summary

The Freedman-Diaconis histogram bin estimator.

Extended Summary

The Freedman-Diaconis rule uses interquartile range (IQR) to estimate binwidth. It is considered a variation of the Scott rule with more robustness as the IQR is less affected by outliers than the standard deviation. However, the IQR depends on fewer points than the standard deviation, so it is less accurate, especially for long tailed distributions.

If the IQR is 0, this function returns 0 for the bin width. Binwidth is inversely proportional to the cube root of data size (asymptotically optimal).

Parameters

x : array_like: Input data that is to be histogrammed, trimmed to range. May not be empty.

Returns

h : An estimate of the optimal bin width for the given data.

Aliases

numpy.lib._histograms_impl._hist_bin_fd