histogram#
- class histogram(values=None, bins=None, density=False, data=None, **kwargs)[source]#
Bases:
Dist
Sample from a histogram with defined bins
Note: unlike other distributions, the parameters of this distribution can’t be modified after creation.
- Parameters:
values (array) – the probability (or count) of each bin
bins (array) – the edges of each bin
density (bool) – treat the histogram as a density instead of counts; only matters with unequal bin widths, see numpy.histogram and scipy.stats.rv_histogram for more information
data (array) – if supplied, compute the values and bin edges using this data and np.histogram() instead
Note: if the length of bins is equal to the length of values, they will be interpreted as left bin edges, and one additional right-bin edge will be added based on the difference between the last two bins (e.g. if the last two bins are 40 and 50, the final right edge will be added at 60). If no bins are supplied, then they will be created as integers matching the length of the values.
The values can be supplied in either normalized (sum to 1) or un-normalized format.
Examples:
# Sample from an age distribution age_bins = [0, 10, 20, 40, 65, 100] age_vals = [0.1, 0.1, 0.3, 0.3, 0.2] h1 = ss.histogram(values=age_vals, bins=age_bins, strict=False) h1.plot_hist() # Create a histogram from data data = np.random.randn(10_000)*2+5 h2 = ss.histogram(data=data, strict=False) h2.plot_hist(bins=100)
Attributes
bitgen
state
Get the current state
state_int
Get the integer corresponding to the current state
Methods