peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/scipy
/stats
/_rvs_sampling.py
import warnings | |
from scipy.stats.sampling import RatioUniforms | |
def rvs_ratio_uniforms(pdf, umax, vmin, vmax, size=1, c=0, random_state=None): | |
""" | |
Generate random samples from a probability density function using the | |
ratio-of-uniforms method. | |
.. deprecated:: 1.12.0 | |
`rvs_ratio_uniforms` is deprecated in favour of | |
`scipy.stats.sampling.RatioUniforms` from version 1.12.0 and will | |
be removed in SciPy 1.15.0 | |
Parameters | |
---------- | |
pdf : callable | |
A function with signature `pdf(x)` that is proportional to the | |
probability density function of the distribution. | |
umax : float | |
The upper bound of the bounding rectangle in the u-direction. | |
vmin : float | |
The lower bound of the bounding rectangle in the v-direction. | |
vmax : float | |
The upper bound of the bounding rectangle in the v-direction. | |
size : int or tuple of ints, optional | |
Defining number of random variates (default is 1). | |
c : float, optional. | |
Shift parameter of ratio-of-uniforms method, see Notes. Default is 0. | |
random_state : {None, int, `numpy.random.Generator`, | |
`numpy.random.RandomState`}, optional | |
If `seed` is None (or `np.random`), the `numpy.random.RandomState` | |
singleton is used. | |
If `seed` is an int, a new ``RandomState`` instance is used, | |
seeded with `seed`. | |
If `seed` is already a ``Generator`` or ``RandomState`` instance then | |
that instance is used. | |
Returns | |
------- | |
rvs : ndarray | |
The random variates distributed according to the probability | |
distribution defined by the pdf. | |
Notes | |
----- | |
Please refer to `scipy.stats.sampling.RatioUniforms` for the documentation. | |
""" | |
warnings.warn("Please use `RatioUniforms` from the " | |
"`scipy.stats.sampling` namespace. The " | |
"`scipy.stats.rvs_ratio_uniforms` namespace is deprecated " | |
"and will be removed in SciPy 1.15.0", | |
category=DeprecationWarning, stacklevel=2) | |
gen = RatioUniforms(pdf, umax=umax, vmin=vmin, vmax=vmax, | |
c=c, random_state=random_state) | |
return gen.rvs(size) | |