Vous êtes un professionnel et vous avez besoin d'une formation ? Sensibilisation à
l'Intelligence Artificielle Voir le programme détaillé

Module « scipy.stats »

Fonction relfreq - module scipy.stats

Signature de la fonction relfreq

def relfreq(a, numbins=10, defaultreallimits=None, weights=None) 

Description

help(scipy.stats.relfreq)

Return a relative frequency histogram, using the histogram function.

A relative frequency  histogram is a mapping of the number of
observations in each of the bins relative to the total of observations.

Parameters
----------
a : array_like
    Input array.
numbins : int, optional
    The number of bins to use for the histogram. Default is 10.
defaultreallimits : tuple (lower, upper), optional
    The lower and upper values for the range of the histogram.
    If no value is given, a range slightly larger than the range of the
    values in a is used. Specifically ``(a.min() - s, a.max() + s)``,
    where ``s = (1/2)(a.max() - a.min()) / (numbins - 1)``.
weights : array_like, optional
    The weights for each value in `a`. Default is None, which gives each
    value a weight of 1.0

Returns
-------
frequency : ndarray
    Binned values of relative frequency.
lowerlimit : float
    Lower real limit.
binsize : float
    Width of each bin.
extrapoints : int
    Extra points.

Examples
--------
>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from scipy import stats
>>> rng = np.random.default_rng()
>>> a = np.array([2, 4, 1, 2, 3, 2])
>>> res = stats.relfreq(a, numbins=4)
>>> res.frequency
array([ 0.16666667, 0.5       , 0.16666667,  0.16666667])
>>> np.sum(res.frequency)  # relative frequencies should add up to 1
1.0

Create a normal distribution with 1000 random values

>>> samples = stats.norm.rvs(size=1000, random_state=rng)

Calculate relative frequencies

>>> res = stats.relfreq(samples, numbins=25)

Calculate space of values for x

>>> x = res.lowerlimit + np.linspace(0, res.binsize*res.frequency.size,
...                                  res.frequency.size)

Plot relative frequency histogram

>>> fig = plt.figure(figsize=(5, 4))
>>> ax = fig.add_subplot(1, 1, 1)
>>> ax.bar(x, res.frequency, width=res.binsize)
>>> ax.set_title('Relative frequency histogram')
>>> ax.set_xlim([x.min(), x.max()])

>>> plt.show()

Vous êtes un professionnel et vous avez besoin d'une formation ? Mise en oeuvre d'IHM
avec Qt et PySide6 Voir le programme détaillé