diff options
Diffstat (limited to 'numpy/random/mtrand/mtrand.pyx')
| -rw-r--r-- | numpy/random/mtrand/mtrand.pyx | 168 |
1 files changed, 83 insertions, 85 deletions
diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx index 95b0accdc..21bc73e54 100644 --- a/numpy/random/mtrand/mtrand.pyx +++ b/numpy/random/mtrand/mtrand.pyx @@ -22,8 +22,8 @@ # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. include "Python.pxi" -include "randint_helpers.pxi" include "numpy.pxd" +include "randint_helpers.pxi" include "cpython/pycapsule.pxd" from libc cimport string @@ -573,21 +573,21 @@ def _shape_from_size(size, d): shape = tuple(size) + (d,) return shape -# Look up table for randint functions keyed by type name. The stored data -# is a tuple (lbnd, ubnd, func), where lbnd is the smallest value for the -# type, ubnd is one greater than the largest value, and func is the +# Look up table for randint functions keyed by dtype. +# The stored data is a tuple (lbnd, ubnd, func), where lbnd is the smallest +# value for the type, ubnd is one greater than the largest value, and func is the # function to call. _randint_type = { - 'bool': (0, 2, _rand_bool), - 'int8': (-2**7, 2**7, _rand_int8), - 'int16': (-2**15, 2**15, _rand_int16), - 'int32': (-2**31, 2**31, _rand_int32), - 'int64': (-2**63, 2**63, _rand_int64), - 'uint8': (0, 2**8, _rand_uint8), - 'uint16': (0, 2**16, _rand_uint16), - 'uint32': (0, 2**32, _rand_uint32), - 'uint64': (0, 2**64, _rand_uint64) - } + np.dtype(np.bool_): (0, 2, _rand_bool), + np.dtype(np.int8): (-2**7, 2**7, _rand_int8), + np.dtype(np.int16): (-2**15, 2**15, _rand_int16), + np.dtype(np.int32): (-2**31, 2**31, _rand_int32), + np.dtype(np.int64): (-2**63, 2**63, _rand_int64), + np.dtype(np.uint8): (0, 2**8, _rand_uint8), + np.dtype(np.uint16): (0, 2**16, _rand_uint16), + np.dtype(np.uint32): (0, 2**32, _rand_uint32), + np.dtype(np.uint64): (0, 2**64, _rand_uint64) +} cdef class RandomState: @@ -969,13 +969,12 @@ cdef class RandomState: high = low low = 0 - # '_randint_type' is defined in - # 'generate_randint_helpers.py' - key = np.dtype(dtype).name - if key not in _randint_type: - raise TypeError('Unsupported dtype "%s" for randint' % key) - - lowbnd, highbnd, randfunc = _randint_type[key] + raw_dtype = dtype + dtype = np.dtype(dtype) + try: + lowbnd, highbnd, randfunc = _randint_type[dtype] + except KeyError: + raise TypeError('Unsupported dtype "%s" for randint' % dtype) # TODO: Do not cast these inputs to Python int # @@ -986,20 +985,20 @@ cdef class RandomState: ihigh = int(high) if ilow < lowbnd: - raise ValueError("low is out of bounds for %s" % (key,)) + raise ValueError("low is out of bounds for %s" % dtype) if ihigh > highbnd: - raise ValueError("high is out of bounds for %s" % (key,)) - if ilow >= ihigh: - raise ValueError("low >= high") - + raise ValueError("high is out of bounds for %s" % dtype) + if ilow >= ihigh and np.prod(size) != 0: + raise ValueError("Range cannot be empty (low >= high) unless no samples are taken") + with self.lock: ret = randfunc(ilow, ihigh - 1, size, self.state_address) - if size is None: - if dtype in (np.bool, np.int, np.long): - return dtype(ret) + # back-compat: keep python scalars when a python type is passed + if size is None and raw_dtype in (bool, int, np.long): + return raw_dtype(ret) - return ret + return ret def bytes(self, npy_intp length): """ @@ -1115,15 +1114,15 @@ cdef class RandomState: # __index__ must return an integer by python rules. pop_size = operator.index(a.item()) except TypeError: - raise ValueError("a must be 1-dimensional or an integer") - if pop_size <= 0: - raise ValueError("a must be greater than 0") + raise ValueError("'a' must be 1-dimensional or an integer") + if pop_size <= 0 and np.prod(size) != 0: + raise ValueError("'a' must be greater than 0 unless no samples are taken") elif a.ndim != 1: - raise ValueError("a must be 1-dimensional") + raise ValueError("'a' must be 1-dimensional") else: pop_size = a.shape[0] - if pop_size is 0: - raise ValueError("a must be non-empty") + if pop_size is 0 and np.prod(size) != 0: + raise ValueError("'a' cannot be empty unless no samples are taken") if p is not None: d = len(p) @@ -1137,9 +1136,9 @@ cdef class RandomState: pix = <double*>PyArray_DATA(p) if p.ndim != 1: - raise ValueError("p must be 1-dimensional") + raise ValueError("'p' must be 1-dimensional") if p.size != pop_size: - raise ValueError("a and p must have same size") + raise ValueError("'a' and 'p' must have same size") if np.logical_or.reduce(p < 0): raise ValueError("probabilities are not non-negative") if abs(kahan_sum(pix, d) - 1.) > atol: @@ -1607,7 +1606,7 @@ cdef class RandomState: References ---------- .. [1] Wikipedia, "Normal distribution", - http://en.wikipedia.org/wiki/Normal_distribution + https://en.wikipedia.org/wiki/Normal_distribution .. [2] P. R. Peebles Jr., "Central Limit Theorem" in "Probability, Random Variables and Random Signal Principles", 4th ed., 2001, pp. 51, 51, 125. @@ -1680,9 +1679,9 @@ cdef class RandomState: Parameters ---------- a : float or array_like of floats - Alpha, non-negative. + Alpha, positive (>0). b : float or array_like of floats - Beta, non-negative. + Beta, positive (>0). size : int or tuple of ints, optional Output shape. If the given shape is, e.g., ``(m, n, k)``, then ``m * n * k`` samples are drawn. If size is ``None`` (default), @@ -1759,9 +1758,9 @@ cdef class RandomState: .. [1] Peyton Z. Peebles Jr., "Probability, Random Variables and Random Signal Principles", 4th ed, 2001, p. 57. .. [2] Wikipedia, "Poisson process", - http://en.wikipedia.org/wiki/Poisson_process + https://en.wikipedia.org/wiki/Poisson_process .. [3] Wikipedia, "Exponential distribution", - http://en.wikipedia.org/wiki/Exponential_distribution + https://en.wikipedia.org/wiki/Exponential_distribution """ cdef ndarray oscale @@ -1860,7 +1859,7 @@ cdef class RandomState: Wolfram Web Resource. http://mathworld.wolfram.com/GammaDistribution.html .. [2] Wikipedia, "Gamma distribution", - http://en.wikipedia.org/wiki/Gamma_distribution + https://en.wikipedia.org/wiki/Gamma_distribution Examples -------- @@ -1950,7 +1949,7 @@ cdef class RandomState: Wolfram Web Resource. http://mathworld.wolfram.com/GammaDistribution.html .. [2] Wikipedia, "Gamma distribution", - http://en.wikipedia.org/wiki/Gamma_distribution + https://en.wikipedia.org/wiki/Gamma_distribution Examples -------- @@ -2047,7 +2046,7 @@ cdef class RandomState: .. [1] Glantz, Stanton A. "Primer of Biostatistics.", McGraw-Hill, Fifth Edition, 2002. .. [2] Wikipedia, "F-distribution", - http://en.wikipedia.org/wiki/F-distribution + https://en.wikipedia.org/wiki/F-distribution Examples -------- @@ -2150,7 +2149,7 @@ cdef class RandomState: From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/NoncentralF-Distribution.html .. [2] Wikipedia, "Noncentral F-distribution", - http://en.wikipedia.org/wiki/Noncentral_F-distribution + https://en.wikipedia.org/wiki/Noncentral_F-distribution Examples -------- @@ -2257,7 +2256,7 @@ cdef class RandomState: References ---------- .. [1] NIST "Engineering Statistics Handbook" - http://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm + https://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm Examples -------- @@ -2333,8 +2332,8 @@ cdef class RandomState: .. [1] Delhi, M.S. Holla, "On a noncentral chi-square distribution in the analysis of weapon systems effectiveness", Metrika, Volume 15, Number 1 / December, 1970. - .. [2] Wikipedia, "Noncentral chi-square distribution" - http://en.wikipedia.org/wiki/Noncentral_chi-square_distribution + .. [2] Wikipedia, "Noncentral chi-squared distribution" + https://en.wikipedia.org/wiki/Noncentral_chi-squared_distribution Examples -------- @@ -2433,12 +2432,12 @@ cdef class RandomState: ---------- .. [1] NIST/SEMATECH e-Handbook of Statistical Methods, "Cauchy Distribution", - http://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm + https://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm .. [2] Weisstein, Eric W. "Cauchy Distribution." From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/CauchyDistribution.html .. [3] Wikipedia, "Cauchy distribution" - http://en.wikipedia.org/wiki/Cauchy_distribution + https://en.wikipedia.org/wiki/Cauchy_distribution Examples -------- @@ -2501,12 +2500,12 @@ cdef class RandomState: .. [1] Dalgaard, Peter, "Introductory Statistics With R", Springer, 2002. .. [2] Wikipedia, "Student's t-distribution" - http://en.wikipedia.org/wiki/Student's_t-distribution + https://en.wikipedia.org/wiki/Student's_t-distribution Examples -------- From Dalgaard page 83 [1]_, suppose the daily energy intake for 11 - women in Kj is: + women in kilojoules (kJ) is: >>> intake = np.array([5260., 5470, 5640, 6180, 6390, 6515, 6805, 7515, \\ ... 7515, 8230, 8770]) @@ -2731,7 +2730,7 @@ cdef class RandomState: .. [3] Reiss, R.D., Thomas, M.(2001), Statistical Analysis of Extreme Values, Birkhauser Verlag, Basel, pp 23-30. .. [4] Wikipedia, "Pareto distribution", - http://en.wikipedia.org/wiki/Pareto_distribution + https://en.wikipedia.org/wiki/Pareto_distribution Examples -------- @@ -2786,7 +2785,7 @@ cdef class RandomState: Parameters ---------- a : float or array_like of floats - Shape of the distribution. Should be greater than zero. + Shape parameter of the distribution. Must be nonnegative. size : int or tuple of ints, optional Output shape. If the given shape is, e.g., ``(m, n, k)``, then ``m * n * k`` samples are drawn. If size is ``None`` (default), @@ -2836,7 +2835,7 @@ cdef class RandomState: Wide Applicability", Journal Of Applied Mechanics ASME Paper 1951. .. [3] Wikipedia, "Weibull distribution", - http://en.wikipedia.org/wiki/Weibull_distribution + https://en.wikipedia.org/wiki/Weibull_distribution Examples -------- @@ -2927,7 +2926,7 @@ cdef class RandomState: Dataplot Reference Manual, Volume 2: Let Subcommands and Library Functions", National Institute of Standards and Technology Handbook Series, June 2003. - http://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/powpdf.pdf + https://www.itl.nist.gov/div898/software/dataplot/refman2/auxillar/powpdf.pdf Examples -------- @@ -3042,7 +3041,7 @@ cdef class RandomState: From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/LaplaceDistribution.html .. [4] Wikipedia, "Laplace distribution", - http://en.wikipedia.org/wiki/Laplace_distribution + https://en.wikipedia.org/wiki/Laplace_distribution Examples -------- @@ -3272,7 +3271,7 @@ cdef class RandomState: MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/LogisticDistribution.html .. [3] Wikipedia, "Logistic-distribution", - http://en.wikipedia.org/wiki/Logistic_distribution + https://en.wikipedia.org/wiki/Logistic_distribution Examples -------- @@ -3366,7 +3365,7 @@ cdef class RandomState: .. [1] Limpert, E., Stahel, W. A., and Abbt, M., "Log-normal Distributions across the Sciences: Keys and Clues," BioScience, Vol. 51, No. 5, May, 2001. - http://stat.ethz.ch/~stahel/lognormal/bioscience.pdf + https://stat.ethz.ch/~stahel/lognormal/bioscience.pdf .. [2] Reiss, R.D. and Thomas, M., "Statistical Analysis of Extreme Values," Basel: Birkhauser Verlag, 2001, pp. 31-32. @@ -3472,9 +3471,9 @@ cdef class RandomState: References ---------- .. [1] Brighton Webs Ltd., "Rayleigh Distribution," - http://www.brighton-webs.co.uk/distributions/rayleigh.asp + https://web.archive.org/web/20090514091424/http://brighton-webs.co.uk:80/distributions/rayleigh.asp .. [2] Wikipedia, "Rayleigh distribution" - http://en.wikipedia.org/wiki/Rayleigh_distribution + https://en.wikipedia.org/wiki/Rayleigh_distribution Examples -------- @@ -3560,12 +3559,12 @@ cdef class RandomState: References ---------- .. [1] Brighton Webs Ltd., Wald Distribution, - http://www.brighton-webs.co.uk/distributions/wald.asp + https://web.archive.org/web/20090423014010/http://www.brighton-webs.co.uk:80/distributions/wald.asp .. [2] Chhikara, Raj S., and Folks, J. Leroy, "The Inverse Gaussian Distribution: Theory : Methodology, and Applications", CRC Press, 1988. - .. [3] Wikipedia, "Wald distribution" - http://en.wikipedia.org/wiki/Wald_distribution + .. [3] Wikipedia, "Inverse Gaussian distribution" + https://en.wikipedia.org/wiki/Inverse_Gaussian_distribution Examples -------- @@ -3651,7 +3650,7 @@ cdef class RandomState: References ---------- .. [1] Wikipedia, "Triangular distribution" - http://en.wikipedia.org/wiki/Triangular_distribution + https://en.wikipedia.org/wiki/Triangular_distribution Examples -------- @@ -3758,7 +3757,7 @@ cdef class RandomState: Wolfram Web Resource. http://mathworld.wolfram.com/BinomialDistribution.html .. [5] Wikipedia, "Binomial distribution", - http://en.wikipedia.org/wiki/Binomial_distribution + https://en.wikipedia.org/wiki/Binomial_distribution Examples -------- @@ -3861,7 +3860,7 @@ cdef class RandomState: MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/NegativeBinomialDistribution.html .. [2] Wikipedia, "Negative binomial distribution", - http://en.wikipedia.org/wiki/Negative_binomial_distribution + https://en.wikipedia.org/wiki/Negative_binomial_distribution Examples -------- @@ -3955,7 +3954,7 @@ cdef class RandomState: From MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/PoissonDistribution.html .. [2] Wikipedia, "Poisson distribution", - http://en.wikipedia.org/wiki/Poisson_distribution + https://en.wikipedia.org/wiki/Poisson_distribution Examples -------- @@ -4144,15 +4143,15 @@ cdef class RandomState: if op.shape == (): fp = PyFloat_AsDouble(p) - if fp < 0.0: - raise ValueError("p < 0.0") + if fp <= 0.0: + raise ValueError("p <= 0.0") if fp > 1.0: raise ValueError("p > 1.0") return discd_array_sc(self.internal_state, rk_geometric, size, fp, self.lock) - if np.any(np.less(op, 0.0)): - raise ValueError("p < 0.0") + if np.any(np.less_equal(op, 0.0)): + raise ValueError("p <= 0.0") if np.any(np.greater(op, 1.0)): raise ValueError("p > 1.0") return discd_array(self.internal_state, rk_geometric, size, op, @@ -4199,12 +4198,12 @@ cdef class RandomState: ----- The probability density for the Hypergeometric distribution is - .. math:: P(x) = \\frac{\\binom{m}{n}\\binom{N-m}{n-x}}{\\binom{N}{n}}, + .. math:: P(x) = \\frac{\\binom{g}{x}\\binom{b}{n-x}}{\\binom{g+b}{n}}, - where :math:`0 \\le x \\le m` and :math:`n+m-N \\le x \\le n` + where :math:`0 \\le x \\le n` and :math:`n-b \\le x \\le g` - for P(x) the probability of x successes, n = ngood, m = nbad, and - N = number of samples. + for P(x) the probability of x successes, g = ngood, b = nbad, and + n = number of samples. Consider an urn with black and white marbles in it, ngood of them black and nbad are white. If you draw nsample balls without @@ -4225,7 +4224,7 @@ cdef class RandomState: MathWorld--A Wolfram Web Resource. http://mathworld.wolfram.com/HypergeometricDistribution.html .. [3] Wikipedia, "Hypergeometric distribution", - http://en.wikipedia.org/wiki/Hypergeometric_distribution + https://en.wikipedia.org/wiki/Hypergeometric_distribution Examples -------- @@ -4335,7 +4334,7 @@ cdef class RandomState: .. [3] D. J. Hand, F. Daly, D. Lunn, E. Ostrowski, A Handbook of Small Data Sets, CRC Press, 1994. .. [4] Wikipedia, "Logarithmic distribution", - http://en.wikipedia.org/wiki/Logarithmic_distribution + https://en.wikipedia.org/wiki/Logarithmic_distribution Examples -------- @@ -4697,9 +4696,9 @@ cdef class RandomState: ---------- .. [1] David McKay, "Information Theory, Inference and Learning Algorithms," chapter 23, - http://www.inference.phy.cam.ac.uk/mackay/ + http://www.inference.org.uk/mackay/itila/ .. [2] Wikipedia, "Dirichlet distribution", - http://en.wikipedia.org/wiki/Dirichlet_distribution + https://en.wikipedia.org/wiki/Dirichlet_distribution Examples -------- @@ -4837,9 +4836,8 @@ cdef class RandomState: self._shuffle_raw(n, sizeof(npy_intp), stride, x_ptr, buf_ptr) else: self._shuffle_raw(n, itemsize, stride, x_ptr, buf_ptr) - elif isinstance(x, np.ndarray) and x.ndim > 1 and x.size: - # Multidimensional ndarrays require a bounce buffer. - buf = np.empty_like(x[0]) + elif isinstance(x, np.ndarray) and x.ndim and x.size: + buf = np.empty_like(x[0,...]) with self.lock: for i in reversed(range(1, n)): j = rk_interval(i, self.internal_state) |