spacepy.toolbox.binHisto¶
- spacepy.toolbox.binHisto(data, verbose=False)[source]¶
Calculates bin width and number of bins for histogram using Freedman-Diaconis rule, if rule fails, defaults to square-root method
- The Freedman-Diaconis method is detailed in:
Freedman, D., and P. Diaconis (1981), On the histogram as a density estimator: L2 theory, Z. Wahrscheinlichkeitstheor. Verw. Geb., 57, 453–476
- and is also described by:
Wilks, D. S. (2006), Statistical Methods in the Atmospheric Sciences, 2nd ed.
- Parameters:
- dataarray_like
list/array of data values
- verboseboolean (optional)
print out some more information
- Returns:
- outtuple
calculated width of bins using F-D rule, number of bins (nearest integer) to use for histogram
See also
Examples
>>> import numpy, spacepy >>> import matplotlib.pyplot as plt >>> numpy.random.seed(8675301) >>> data = numpy.random.randn(1000) >>> binw, nbins = spacepy.toolbox.binHisto(data) >>> print(nbins) 19 >>> p = plt.hist(data, bins=nbins, histtype='step', density=True)