`scipy.stats._distribution_infrastructure:exp`

source: build-install/usr/lib/python3.14/site-packages/scipy/stats/_distribution_infrastructure.py:5735

Signature

def exp(X, /)

Summary

Natural exponential of a random variable.

Parameters

X : `ContinuousDistribution`: The random variable $X$ .

Returns

Y : `ContinuousDistribution`: A random variable $Y = exp (X)$ .

Examples

Suppose we have a normally distributed random variable :math:`X`:

import numpy as np
from scipy import stats
X = stats.Normal()

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We wish to have a lognormally distributed random variable :math:`Y`, a random variable whose natural logarithm is :math:`X`. If :math:`X` is to be the natural logarithm of :math:`Y`, then we must take :math:`Y` to be the natural exponential of :math:`X`.

Y = stats.exp(X)

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To demonstrate that ``X`` represents the logarithm of ``Y``, we plot a normalized histogram of the logarithm of observations of ``Y`` against the PDF underlying ``X``.

import matplotlib.pyplot as plt
rng = np.random.default_rng(435383595582522)
y = Y.sample(shape=10000, rng=rng)
ax = plt.gca()

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ax.hist(np.log(y), bins=50, density=True)
X.plot(ax=ax)
plt.legend(('PDF of `X`', 'histogram of `log(y)`'))

✗

<matplotlib.legend.Legend object at 0x7f3f68cd0590>

plt.show()

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`scipy.stats._distribution_infrastructure:exp`

Signature

Summary

Parameters

Returns

Examples

Aliases

Referenced by

This package