diff options
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/random/__init__.pxd | 14 | ||||
| -rw-r--r-- | numpy/random/_bounded_integers.pxd.in | 2 | ||||
| -rw-r--r-- | numpy/random/_common.pxd | 2 | ||||
| -rw-r--r-- | numpy/random/_examples/cython/extending.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/_examples/cython/extending_distributions.pyx | 4 | ||||
| -rw-r--r-- | numpy/random/_generator.pyx | 14 | ||||
| -rw-r--r-- | numpy/random/_mt19937.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/_pcg64.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/_philox.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/_sfc64.pyx | 2 | ||||
| -rw-r--r-- | numpy/random/mtrand.pyx | 293 | ||||
| -rw-r--r-- | numpy/random/setup.py | 1 |
12 files changed, 315 insertions, 25 deletions
diff --git a/numpy/random/__init__.pxd b/numpy/random/__init__.pxd new file mode 100644 index 000000000..05e073876 --- /dev/null +++ b/numpy/random/__init__.pxd @@ -0,0 +1,14 @@ +cimport numpy as np +from libc.stdint cimport uint32_t, uint64_t + +cdef extern from "numpy/random/bitgen.h": + struct bitgen: + void *state + uint64_t (*next_uint64)(void *st) nogil + uint32_t (*next_uint32)(void *st) nogil + double (*next_double)(void *st) nogil + uint64_t (*next_raw)(void *st) nogil + + ctypedef bitgen bitgen_t + +from numpy.random._bit_generator cimport BitGenerator, SeedSequence diff --git a/numpy/random/_bounded_integers.pxd.in b/numpy/random/_bounded_integers.pxd.in index 320d35774..5ae5a8067 100644 --- a/numpy/random/_bounded_integers.pxd.in +++ b/numpy/random/_bounded_integers.pxd.in @@ -4,7 +4,7 @@ import numpy as np cimport numpy as np ctypedef np.npy_bool bool_t -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t cdef inline uint64_t _gen_mask(uint64_t max_val) nogil: """Mask generator for use in bounded random numbers""" diff --git a/numpy/random/_common.pxd b/numpy/random/_common.pxd index 74bebca83..588f613ae 100644 --- a/numpy/random/_common.pxd +++ b/numpy/random/_common.pxd @@ -5,7 +5,7 @@ from libc.stdint cimport uint32_t, uint64_t, int32_t, int64_t import numpy as np cimport numpy as np -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t cdef double POISSON_LAM_MAX cdef double LEGACY_POISSON_LAM_MAX diff --git a/numpy/random/_examples/cython/extending.pyx b/numpy/random/_examples/cython/extending.pyx index d12c0b919..7a0dfe078 100644 --- a/numpy/random/_examples/cython/extending.pyx +++ b/numpy/random/_examples/cython/extending.pyx @@ -8,7 +8,7 @@ import numpy as np cimport numpy as np cimport cython -from numpy.random._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t from numpy.random import PCG64 np.import_array() diff --git a/numpy/random/_examples/cython/extending_distributions.pyx b/numpy/random/_examples/cython/extending_distributions.pyx index 3f342c475..1bef506ef 100644 --- a/numpy/random/_examples/cython/extending_distributions.pyx +++ b/numpy/random/_examples/cython/extending_distributions.pyx @@ -8,8 +8,7 @@ cimport numpy as np cimport cython from cpython.pycapsule cimport PyCapsule_IsValid, PyCapsule_GetPointer from libc.stdint cimport uint16_t, uint64_t -from numpy.random._bit_generator cimport bitgen_t - +from numpy.random cimport bitgen_t from numpy.random import PCG64 @@ -72,3 +71,4 @@ def uint10_uniforms(Py_ssize_t n): randoms = np.asarray(random_values) return randoms + diff --git a/numpy/random/_generator.pyx b/numpy/random/_generator.pyx index 2d8455982..64ec73986 100644 --- a/numpy/random/_generator.pyx +++ b/numpy/random/_generator.pyx @@ -19,7 +19,7 @@ from ._bounded_integers cimport (_rand_bool, _rand_int32, _rand_int64, _rand_uint8, _gen_mask) from ._bounded_integers import _integers_types from ._pcg64 import PCG64 -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, CONS_NON_NEGATIVE, CONS_BOUNDED_0_1, CONS_BOUNDED_GT_0_1, CONS_GT_1, CONS_POSITIVE_NOT_NAN, CONS_POISSON, @@ -1004,6 +1004,12 @@ cdef class Generator: A floating-point array of shape ``size`` of drawn samples, or a single sample if ``size`` was not specified. + See Also + -------- + normal : + Equivalent function with additional ``loc`` and ``scale`` arguments + for setting the mean and standard deviation. + Notes ----- For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: @@ -1011,12 +1017,6 @@ cdef class Generator: mu + sigma * gen.standard_normal(size=...) gen.normal(mu, sigma, size=...) - See Also - -------- - normal : - Equivalent function with additional ``loc`` and ``scale`` arguments - for setting the mean and standard deviation. - Examples -------- >>> rng = np.random.default_rng() diff --git a/numpy/random/_mt19937.pyx b/numpy/random/_mt19937.pyx index e99652b73..919a96a4c 100644 --- a/numpy/random/_mt19937.pyx +++ b/numpy/random/_mt19937.pyx @@ -4,7 +4,7 @@ import numpy as np cimport numpy as np from libc.stdint cimport uint32_t, uint64_t -from ._bit_generator cimport BitGenerator, SeedSequence +from numpy.random cimport BitGenerator, SeedSequence __all__ = ['MT19937'] diff --git a/numpy/random/_pcg64.pyx b/numpy/random/_pcg64.pyx index 1a5d852a2..05d27db5c 100644 --- a/numpy/random/_pcg64.pyx +++ b/numpy/random/_pcg64.pyx @@ -3,7 +3,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double, wrap_int -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['PCG64'] diff --git a/numpy/random/_philox.pyx b/numpy/random/_philox.pyx index 9f136c32f..7e8880490 100644 --- a/numpy/random/_philox.pyx +++ b/numpy/random/_philox.pyx @@ -10,7 +10,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double, int_to_array, wrap_int -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['Philox'] diff --git a/numpy/random/_sfc64.pyx b/numpy/random/_sfc64.pyx index 1633669d5..1daee34f8 100644 --- a/numpy/random/_sfc64.pyx +++ b/numpy/random/_sfc64.pyx @@ -3,7 +3,7 @@ cimport numpy as np from libc.stdint cimport uint32_t, uint64_t from ._common cimport uint64_to_double -from ._bit_generator cimport BitGenerator +from numpy.random cimport BitGenerator __all__ = ['SFC64'] diff --git a/numpy/random/mtrand.pyx b/numpy/random/mtrand.pyx index 691a6e6e7..e6cd9b87e 100644 --- a/numpy/random/mtrand.pyx +++ b/numpy/random/mtrand.pyx @@ -17,7 +17,7 @@ from ._bounded_integers cimport (_rand_bool, _rand_int32, _rand_int64, _rand_uint8,) from ._bounded_integers import _integers_types from ._mt19937 import MT19937 as _MT19937 -from ._bit_generator cimport bitgen_t +from numpy.random cimport bitgen_t from ._common cimport (POISSON_LAM_MAX, CONS_POSITIVE, CONS_NONE, CONS_NON_NEGATIVE, CONS_BOUNDED_0_1, CONS_BOUNDED_GT_0_1, CONS_GTE_1, CONS_GT_1, LEGACY_CONS_POISSON, @@ -379,6 +379,10 @@ cdef class RandomState: (b - a) * random_sample() + a + .. note:: + New code should use ``default_rng().random`` (see + `random-quick-start`) instead. + Parameters ---------- size : int or tuple of ints, optional @@ -392,6 +396,10 @@ cdef class RandomState: Array of random floats of shape `size` (unless ``size=None``, in which case a single float is returned). + See also + -------- + Generator.random: which should be used for new code. + Examples -------- >>> np.random.random_sample() @@ -441,6 +449,10 @@ cdef class RandomState: It is often seen in Bayesian inference and order statistics. + .. note:: + New code should use ``default_rng().beta`` (see + `random-quick-start`) instead. + Parameters ---------- a : float or array_like of floats @@ -458,6 +470,9 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized beta distribution. + See also + -------- + Generator.beta: which should be used for new code. """ return cont(&legacy_beta, &self._aug_state, size, self.lock, 2, a, 'a', CONS_POSITIVE, @@ -484,6 +499,10 @@ cdef class RandomState: the size of raindrops measured over many rainstorms [1]_, or the time between page requests to Wikipedia [2]_. + .. note:: + New code should use ``default_rng().exponential`` (see + `random-quick-start`) instead. + Parameters ---------- scale : float or array_like of floats @@ -500,6 +519,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized exponential distribution. + See also + -------- + Generator.exponential: which should be used for new code. + References ---------- .. [1] Peyton Z. Peebles Jr., "Probability, Random Variables and @@ -525,6 +548,10 @@ cdef class RandomState: `standard_exponential` is identical to the exponential distribution with a scale parameter of 1. + .. note:: + New code should use ``default_rng().standard_exponential`` (see + `random-quick-start`) instead. + Parameters ---------- size : int or tuple of ints, optional @@ -537,6 +564,10 @@ cdef class RandomState: out : float or ndarray Drawn samples. + See also + -------- + Generator.standard_exponential: which should be used for new code. + Examples -------- Output a 3x8000 array: @@ -618,6 +649,10 @@ cdef class RandomState: the specified dtype in the "half-open" interval [`low`, `high`). If `high` is None (the default), then results are from [0, `low`). + .. note:: + New code should use ``default_rng().integers`` (see + `random-quick-start`) instead. + Parameters ---------- low : int or array-like of ints @@ -651,6 +686,7 @@ cdef class RandomState: random_integers : similar to `randint`, only for the closed interval [`low`, `high`], and 1 is the lowest value if `high` is omitted. + Generator.integers: which should be used for new code. Examples -------- @@ -735,6 +771,10 @@ cdef class RandomState: Return random bytes. + .. note:: + New code should use ``default_rng().bytes`` (see + `random-quick-start`) instead. + Parameters ---------- length : int @@ -745,11 +785,14 @@ cdef class RandomState: out : str String of length `length`. + See also + -------- + Generator.bytes: which should be used for new code. + Examples -------- >>> np.random.bytes(10) ' eh\\x85\\x022SZ\\xbf\\xa4' #random - """ cdef Py_ssize_t n_uint32 = ((length - 1) // 4 + 1) # Interpret the uint32s as little-endian to convert them to bytes @@ -766,6 +809,10 @@ cdef class RandomState: .. versionadded:: 1.7.0 + .. note:: + New code should use ``default_rng().choice`` (see + `random-quick-start`) instead. + Parameters ---------- a : 1-D array-like or int @@ -799,6 +846,7 @@ cdef class RandomState: See Also -------- randint, shuffle, permutation + Generator.choice: which should be used in new code Examples -------- @@ -958,6 +1006,10 @@ cdef class RandomState: any value within the given interval is equally likely to be drawn by `uniform`. + .. note:: + New code should use ``default_rng().uniform`` (see + `random-quick-start`) instead. + Parameters ---------- low : float or array_like of floats, optional @@ -987,6 +1039,7 @@ cdef class RandomState: rand : Convenience function that accepts dimensions as input, e.g., ``rand(2,2)`` would generate a 2-by-2 array of floats, uniformly distributed over ``[0, 1)``. + Generator.uniform: which should be used for new code. Notes ----- @@ -1114,6 +1167,10 @@ cdef class RandomState: tuple to specify the size of the output, which is consistent with other NumPy functions like `numpy.zeros` and `numpy.ones`. + .. note:: + New code should use ``default_rng().standard_normal`` (see + `random-quick-start`) instead. + If positive int_like arguments are provided, `randn` generates an array of shape ``(d0, d1, ..., dn)``, filled with random floats sampled from a univariate "normal" (Gaussian) @@ -1137,6 +1194,7 @@ cdef class RandomState: -------- standard_normal : Similar, but takes a tuple as its argument. normal : Also accepts mu and sigma arguments. + Generator.standard_normal: which should be used for new code. Notes ----- @@ -1263,6 +1321,10 @@ cdef class RandomState: Draw samples from a standard Normal distribution (mean=0, stdev=1). + .. note:: + New code should use ``default_rng().standard_normal`` (see + `random-quick-start`) instead. + Parameters ---------- size : int or tuple of ints, optional @@ -1276,6 +1338,13 @@ cdef class RandomState: A floating-point array of shape ``size`` of drawn samples, or a single sample if ``size`` was not specified. + See Also + -------- + normal : + Equivalent function with additional ``loc`` and ``scale`` arguments + for setting the mean and standard deviation. + Generator.standard_normal: which should be used for new code. + Notes ----- For random samples from :math:`N(\\mu, \\sigma^2)`, use one of:: @@ -1283,12 +1352,6 @@ cdef class RandomState: mu + sigma * np.random.standard_normal(size=...) np.random.normal(mu, sigma, size=...) - See Also - -------- - normal : - Equivalent function with additional ``loc`` and ``scale`` arguments - for setting the mean and standard deviation. - Examples -------- >>> np.random.standard_normal() @@ -1333,6 +1396,10 @@ cdef class RandomState: by a large number of tiny, random disturbances, each with its own unique distribution [2]_. + .. note:: + New code should use ``default_rng().normal`` (see + `random-quick-start`) instead. + Parameters ---------- loc : float or array_like of floats @@ -1355,6 +1422,7 @@ cdef class RandomState: -------- scipy.stats.norm : probability density function, distribution or cumulative density function, etc. + Generator.normal: which should be used for new code. Notes ----- @@ -1428,6 +1496,10 @@ cdef class RandomState: Samples are drawn from a Gamma distribution with specified parameters, shape (sometimes designated "k") and scale=1. + .. note:: + New code should use ``default_rng().standard_gamma`` (see + `random-quick-start`) instead. + Parameters ---------- shape : float or array_like of floats @@ -1447,6 +1519,7 @@ cdef class RandomState: -------- scipy.stats.gamma : probability density function, distribution or cumulative density function, etc. + Generator.standard_gamma: which should be used for new code. Notes ----- @@ -1504,6 +1577,10 @@ cdef class RandomState: `shape` (sometimes designated "k") and `scale` (sometimes designated "theta"), where both parameters are > 0. + .. note:: + New code should use ``default_rng().gamma`` (see + `random-quick-start`) instead. + Parameters ---------- shape : float or array_like of floats @@ -1526,6 +1603,7 @@ cdef class RandomState: -------- scipy.stats.gamma : probability density function, distribution or cumulative density function, etc. + Generator.gamma: which should be used for new code. Notes ----- @@ -1588,6 +1666,10 @@ cdef class RandomState: that arises in ANOVA tests, and is the ratio of two chi-square variates. + .. note:: + New code should use ``default_rng().f`` (see + `random-quick-start`) instead. + Parameters ---------- dfnum : float or array_like of floats @@ -1609,6 +1691,7 @@ cdef class RandomState: -------- scipy.stats.f : probability density function, distribution or cumulative density function, etc. + Generator.f: which should be used for new code. Notes ----- @@ -1671,6 +1754,10 @@ cdef class RandomState: freedom in denominator), where both parameters > 1. `nonc` is the non-centrality parameter. + .. note:: + New code should use ``default_rng().noncentral_f`` (see + `random-quick-start`) instead. + Parameters ---------- dfnum : float or array_like of floats @@ -1695,6 +1782,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized noncentral Fisher distribution. + See also + -------- + Generator.noncentral_f: which should be used for new code. + Notes ----- When calculating the power of an experiment (power = probability of @@ -1748,6 +1839,10 @@ cdef class RandomState: resulting distribution is chi-square (see Notes). This distribution is often used in hypothesis testing. + .. note:: + New code should use ``default_rng().chisquare`` (see + `random-quick-start`) instead. + Parameters ---------- df : float or array_like of floats @@ -1769,6 +1864,10 @@ cdef class RandomState: When `df` <= 0 or when an inappropriate `size` (e.g. ``size=-1``) is given. + See also + -------- + Generator.chisquare: which should be used for new code. + Notes ----- The variable obtained by summing the squares of `df` independent, @@ -1798,7 +1897,6 @@ cdef class RandomState: -------- >>> np.random.chisquare(2,4) array([ 1.89920014, 9.00867716, 3.13710533, 5.62318272]) # random - """ return cont(&legacy_chisquare, &self._aug_state, size, self.lock, 1, df, 'df', CONS_POSITIVE, @@ -1814,6 +1912,10 @@ cdef class RandomState: The noncentral :math:`\\chi^2` distribution is a generalization of the :math:`\\chi^2` distribution. + .. note:: + New code should use ``default_rng().noncentral_chisquare`` (see + `random-quick-start`) instead. + Parameters ---------- df : float or array_like of floats @@ -1834,6 +1936,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized noncentral chi-square distribution. + See also + -------- + Generator.noncentral_chisquare: which should be used for new code. + Notes ----- The probability density function for the noncentral Chi-square @@ -1892,6 +1998,10 @@ cdef class RandomState: Also known as the Lorentz distribution. + .. note:: + New code should use ``default_rng().standard_cauchy`` (see + `random-quick-start`) instead. + Parameters ---------- size : int or tuple of ints, optional @@ -1904,6 +2014,10 @@ cdef class RandomState: samples : ndarray or scalar The drawn samples. + See also + -------- + Generator.standard_cauchy: which should be used for new code. + Notes ----- The probability density function for the full Cauchy distribution is @@ -1960,6 +2074,10 @@ cdef class RandomState: large, the result resembles that of the standard normal distribution (`standard_normal`). + .. note:: + New code should use ``default_rng().standard_t`` (see + `random-quick-start`) instead. + Parameters ---------- df : float or array_like of floats @@ -1975,6 +2093,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized standard Student's t distribution. + See also + -------- + Generator.standard_t: which should be used for new code. + Notes ----- The probability density function for the t distribution is @@ -2057,6 +2179,10 @@ cdef class RandomState: circle. It may be thought of as the circular analogue of the normal distribution. + .. note:: + New code should use ``default_rng().vonmises`` (see + `random-quick-start`) instead. + Parameters ---------- mu : float or array_like of floats @@ -2078,6 +2204,7 @@ cdef class RandomState: -------- scipy.stats.vonmises : probability density function, distribution, or cumulative density function, etc. + Generator.vonmises: which should be used for new code. Notes ----- @@ -2150,6 +2277,10 @@ cdef class RandomState: 20 percent of the range, while the other 20 percent fill the remaining 80 percent of the range. + .. note:: + New code should use ``default_rng().pareto`` (see + `random-quick-start`) instead. + Parameters ---------- a : float or array_like of floats @@ -2171,6 +2302,7 @@ cdef class RandomState: cumulative density function, etc. scipy.stats.genpareto : probability density function, distribution or cumulative density function, etc. + Generator.pareto: which should be used for new code. Notes ----- @@ -2239,6 +2371,10 @@ cdef class RandomState: The more common 2-parameter Weibull, including a scale parameter :math:`\\lambda` is just :math:`X = \\lambda(-ln(U))^{1/a}`. + .. note:: + New code should use ``default_rng().weibull`` (see + `random-quick-start`) instead. + Parameters ---------- a : float or array_like of floats @@ -2260,6 +2396,7 @@ cdef class RandomState: scipy.stats.weibull_min scipy.stats.genextreme gumbel + Generator.weibull: which should be used for new code. Notes ----- @@ -2330,6 +2467,10 @@ cdef class RandomState: Also known as the power function distribution. + .. note:: + New code should use ``default_rng().power`` (see + `random-quick-start`) instead. + Parameters ---------- a : float or array_like of floats @@ -2350,6 +2491,10 @@ cdef class RandomState: ValueError If a < 1. + See also + -------- + Generator.power: which should be used for new code. + Notes ----- The probability density function is @@ -2433,6 +2578,10 @@ cdef class RandomState: difference between two independent, identically distributed exponential random variables. + .. note:: + New code should use ``default_rng().laplace`` (see + `random-quick-start`) instead. + Parameters ---------- loc : float or array_like of floats, optional @@ -2451,6 +2600,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Laplace distribution. + See also + -------- + Generator.laplace: which should be used for new code. + Notes ----- It has the probability density function @@ -2516,6 +2669,10 @@ cdef class RandomState: scale. For more information on the Gumbel distribution, see Notes and References below. + .. note:: + New code should use ``default_rng().gumbel`` (see + `random-quick-start`) instead. + Parameters ---------- loc : float or array_like of floats, optional @@ -2540,6 +2697,7 @@ cdef class RandomState: scipy.stats.gumbel_r scipy.stats.genextreme weibull + Generator.gumbel: which should be used for new code. Notes ----- @@ -2633,6 +2791,10 @@ cdef class RandomState: Samples are drawn from a logistic distribution with specified parameters, loc (location or mean, also median), and scale (>0). + .. note:: + New code should use ``default_rng().logistic`` (see + `random-quick-start`) instead. + Parameters ---------- loc : float or array_like of floats, optional @@ -2655,6 +2817,7 @@ cdef class RandomState: -------- scipy.stats.logistic : probability density function, distribution or cumulative density function, etc. + Generator.logistic: which should be used for new code. Notes ----- @@ -2715,6 +2878,10 @@ cdef class RandomState: deviation are not the values for the distribution itself, but of the underlying normal distribution it is derived from. + .. note:: + New code should use ``default_rng().lognormal`` (see + `random-quick-start`) instead. + Parameters ---------- mean : float or array_like of floats, optional @@ -2737,6 +2904,7 @@ cdef class RandomState: -------- scipy.stats.lognorm : probability density function, distribution, cumulative density function, etc. + Generator.lognormal: which should be used for new code. Notes ----- @@ -2823,6 +2991,10 @@ cdef class RandomState: The :math:`\\chi` and Weibull distributions are generalizations of the Rayleigh. + .. note:: + New code should use ``default_rng().rayleigh`` (see + `random-quick-start`) instead. + Parameters ---------- scale : float or array_like of floats, optional @@ -2838,6 +3010,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Rayleigh distribution. + See also + -------- + Generator.rayleigh: which should be used for new code. + Notes ----- The probability density function for the Rayleigh distribution is @@ -2897,6 +3073,10 @@ cdef class RandomState: because there is an inverse relationship between the time to cover a unit distance and distance covered in unit time. + .. note:: + New code should use ``default_rng().wald`` (see + `random-quick-start`) instead. + Parameters ---------- mean : float or array_like of floats @@ -2914,6 +3094,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Wald distribution. + See also + -------- + Generator.wald: which should be used for new code. + Notes ----- The probability density function for the Wald distribution is @@ -2962,6 +3146,10 @@ cdef class RandomState: limit right. Unlike the other distributions, these parameters directly define the shape of the pdf. + .. note:: + New code should use ``default_rng().triangular`` (see + `random-quick-start`) instead. + Parameters ---------- left : float or array_like of floats @@ -2983,6 +3171,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized triangular distribution. + See also + -------- + Generator.triangular: which should be used for new code. + Notes ----- The probability density function for the triangular distribution is @@ -3061,6 +3253,10 @@ cdef class RandomState: n an integer >= 0 and p is in the interval [0,1]. (n may be input as a float, but it is truncated to an integer in use) + .. note:: + New code should use ``default_rng().binomial`` (see + `random-quick-start`) instead. + Parameters ---------- n : int or array_like of ints @@ -3084,6 +3280,7 @@ cdef class RandomState: -------- scipy.stats.binom : probability density function, distribution or cumulative density function, etc. + Generator.binomial: which should be used for new code. Notes ----- @@ -3206,6 +3403,10 @@ cdef class RandomState: parameters, `n` successes and `p` probability of success where `n` is > 0 and `p` is in the interval [0, 1]. + .. note:: + New code should use ``default_rng().negative_binomial`` (see + `random-quick-start`) instead. + Parameters ---------- n : float or array_like of floats @@ -3225,6 +3426,10 @@ cdef class RandomState: where each sample is equal to N, the number of failures that occurred before a total of n successes was reached. + See also + -------- + Generator.negative_binomial: which should be used for new code. + Notes ----- The probability mass function of the negative binomial distribution is @@ -3283,6 +3488,10 @@ cdef class RandomState: The Poisson distribution is the limit of the binomial distribution for large N. + .. note:: + New code should use ``default_rng().poisson`` (see + `random-quick-start`) instead. + Parameters ---------- lam : float or array_like of floats @@ -3299,6 +3508,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized Poisson distribution. + See also + -------- + Generator.poisson: which should be used for new code. + Notes ----- The Poisson distribution @@ -3361,6 +3574,10 @@ cdef class RandomState: frequency of an item is inversely proportional to its rank in a frequency table. + .. note:: + New code should use ``default_rng().zipf`` (see + `random-quick-start`) instead. + Parameters ---------- a : float or array_like of floats @@ -3380,6 +3597,7 @@ cdef class RandomState: -------- scipy.stats.zipf : probability density function, distribution, or cumulative density function, etc. + Generator.zipf: which should be used for new code. Notes ----- @@ -3446,6 +3664,10 @@ cdef class RandomState: where `p` is the probability of success of an individual trial. + .. note:: + New code should use ``default_rng().geometric`` (see + `random-quick-start`) instead. + Parameters ---------- p : float or array_like of floats @@ -3461,6 +3683,10 @@ cdef class RandomState: out : ndarray or scalar Drawn samples from the parameterized geometric distribution. + See also + -------- + Generator.geometric: which should be used for new code. + Examples -------- Draw ten thousand values from the geometric distribution, @@ -3492,6 +3718,10 @@ cdef class RandomState: a bad selection), and `nsample` (number of items sampled, which is less than or equal to the sum ``ngood + nbad``). + .. note:: + New code should use ``default_rng().hypergeometric`` (see + `random-quick-start`) instead. + Parameters ---------- ngood : int or array_like of ints @@ -3519,6 +3749,7 @@ cdef class RandomState: -------- scipy.stats.hypergeom : probability density function, distribution or cumulative density function, etc. + Generator.hypergeometric: which should be used for new code. Notes ----- @@ -3618,6 +3849,10 @@ cdef class RandomState: Samples are drawn from a log series distribution with specified shape parameter, 0 < ``p`` < 1. + .. note:: + New code should use ``default_rng().logseries`` (see + `random-quick-start`) instead. + Parameters ---------- p : float or array_like of floats @@ -3637,6 +3872,7 @@ cdef class RandomState: -------- scipy.stats.logser : probability density function, distribution or cumulative density function, etc. + Generator.logseries: which should be used for new code. Notes ----- @@ -3706,6 +3942,10 @@ cdef class RandomState: (average or "center") and variance (standard deviation, or "width," squared) of the one-dimensional normal distribution. + .. note:: + New code should use ``default_rng().multivariate_normal`` (see + `random-quick-start`) instead. + Parameters ---------- mean : 1-D array_like, of length N @@ -3733,6 +3973,10 @@ cdef class RandomState: In other words, each entry ``out[i,j,...,:]`` is an N-dimensional value drawn from the distribution. + See also + -------- + Generator.multivariate_normal: which should be used for new code. + Notes ----- The mean is a coordinate in N-dimensional space, which represents the @@ -3872,6 +4116,10 @@ cdef class RandomState: ``X_i = [X_0, X_1, ..., X_p]``, represent the number of times the outcome was ``i``. + .. note:: + New code should use ``default_rng().multinomial`` (see + `random-quick-start`) instead. + Parameters ---------- n : int @@ -3895,6 +4143,10 @@ cdef class RandomState: In other words, each entry ``out[i,j,...,:]`` is an N-dimensional value drawn from the distribution. + See also + -------- + Generator.multinomial: which should be used for new code. + Examples -------- Throw a dice 20 times: @@ -3982,6 +4234,10 @@ cdef class RandomState: is a conjugate prior of a multinomial distribution in Bayesian inference. + .. note:: + New code should use ``default_rng().dirichlet`` (see + `random-quick-start`) instead. + Parameters ---------- alpha : array @@ -4002,6 +4258,10 @@ cdef class RandomState: ValueError If any value in alpha is less than or equal to zero + See also + -------- + Generator.dirichlet: which should be used for new code. + Notes ----- The Dirichlet distribution is a distribution over vectors @@ -4119,6 +4379,10 @@ cdef class RandomState: multi-dimensional array. The order of sub-arrays is changed but their contents remains the same. + .. note:: + New code should use ``default_rng().shuffle`` (see + `random-quick-start`) instead. + Parameters ---------- x : array_like @@ -4128,6 +4392,10 @@ cdef class RandomState: ------- None + See also + -------- + Generator.shuffle: which should be used for new code. + Examples -------- >>> arr = np.arange(10) @@ -4206,6 +4474,10 @@ cdef class RandomState: If `x` is a multi-dimensional array, it is only shuffled along its first index. + .. note:: + New code should use ``default_rng().permutation`` (see + `random-quick-start`) instead. + Parameters ---------- x : int or array_like @@ -4218,6 +4490,9 @@ cdef class RandomState: out : ndarray Permuted sequence or array range. + See also + -------- + Generator.permutation: which should be used for new code. Examples -------- diff --git a/numpy/random/setup.py b/numpy/random/setup.py index 776a018bc..64e1b5b92 100644 --- a/numpy/random/setup.py +++ b/numpy/random/setup.py @@ -125,6 +125,7 @@ def configuration(parent_package='', top_path=None): depends=['mtrand.pyx'], define_macros=defs + LEGACY_DEFS, ) + config.add_data_files('__init__.pxd') return config |