diff options
Diffstat (limited to 'numpy/random')
| -rw-r--r-- | numpy/random/__init__.py | 18 | ||||
| -rw-r--r-- | numpy/random/info.py | 55 | ||||
| -rw-r--r-- | numpy/random/mtrand/Python.pxi | 54 | ||||
| -rw-r--r-- | numpy/random/mtrand/distributions.c | 852 | ||||
| -rw-r--r-- | numpy/random/mtrand/distributions.h | 185 | ||||
| -rw-r--r-- | numpy/random/mtrand/generate_mtrand_c.py | 37 | ||||
| -rw-r--r-- | numpy/random/mtrand/initarray.c | 136 | ||||
| -rw-r--r-- | numpy/random/mtrand/initarray.h | 6 | ||||
| -rw-r--r-- | numpy/random/mtrand/mtrand.c | 10907 | ||||
| -rw-r--r-- | numpy/random/mtrand/mtrand.pyx | 1724 | ||||
| -rw-r--r-- | numpy/random/mtrand/numpy.pxi | 133 | ||||
| -rw-r--r-- | numpy/random/mtrand/randomkit.c | 365 | ||||
| -rw-r--r-- | numpy/random/mtrand/randomkit.h | 189 | ||||
| -rw-r--r-- | numpy/random/setup.py | 53 |
14 files changed, 14714 insertions, 0 deletions
diff --git a/numpy/random/__init__.py b/numpy/random/__init__.py new file mode 100644 index 000000000..5a7423208 --- /dev/null +++ b/numpy/random/__init__.py @@ -0,0 +1,18 @@ +# To get sub-modules +from info import __doc__, __all__ +from mtrand import * + +# Some aliases: +ranf = random = sample = random_sample +__all__.extend(['ranf','random','sample']) + +def __RandomState_ctor(): + """Return a RandomState instance. + + This function exists solely to assist (un)pickling. + """ + return RandomState() + +def test(level=1, verbosity=1): + from numpy.testing import NumpyTest + return NumpyTest().test(level, verbosity) diff --git a/numpy/random/info.py b/numpy/random/info.py new file mode 100644 index 000000000..8c2cae44a --- /dev/null +++ b/numpy/random/info.py @@ -0,0 +1,55 @@ +"""\ +Core Random Tools +================= + +""" + +depends = ['core'] + +__all__ = [ + 'beta', + 'binomial', + 'bytes', + 'chisquare', + 'exponential', + 'f', + 'gamma', + 'geometric', + 'get_state', + 'gumbel', + 'hypergeometric', + 'laplace', + 'logistic', + 'lognormal', + 'logseries', + 'multinomial', + 'multivariate_normal', + 'negative_binomial', + 'noncentral_chisquare', + 'noncentral_f', + 'normal', + 'pareto', + 'permutation', + 'poisson', + 'power', + 'rand', + 'randint', + 'randn', + 'random_integers', + 'random_sample', + 'rayleigh', + 'seed', + 'set_state', + 'shuffle', + 'standard_cauchy', + 'standard_exponential', + 'standard_gamma', + 'standard_normal', + 'standard_t', + 'triangular', + 'uniform', + 'vonmises', + 'wald', + 'weibull', + 'zipf' +] diff --git a/numpy/random/mtrand/Python.pxi b/numpy/random/mtrand/Python.pxi new file mode 100644 index 000000000..03018e960 --- /dev/null +++ b/numpy/random/mtrand/Python.pxi @@ -0,0 +1,54 @@ +# :Author: Robert Kern +# :Copyright: 2004, Enthought, Inc. +# :License: BSD Style + + +cdef extern from "Python.h": + # Not part of the Python API, but we might as well define it here. + # Note that the exact type doesn't actually matter for Pyrex. + ctypedef int size_t + + # String API + char* PyString_AsString(object string) + char* PyString_AS_STRING(object string) + object PyString_FromString(char* c_string) + object PyString_FromStringAndSize(char* c_string, int length) + + # Float API + double PyFloat_AsDouble(object ob) + long PyInt_AsLong(object ob) + + # Memory API + void* PyMem_Malloc(size_t n) + void* PyMem_Realloc(void* buf, size_t n) + void PyMem_Free(void* buf) + + void Py_DECREF(object obj) + void Py_XDECREF(object obj) + void Py_INCREF(object obj) + void Py_XINCREF(object obj) + + # CObject API + ctypedef void (*destructor1)(void* cobj) + ctypedef void (*destructor2)(void* cobj, void* desc) + int PyCObject_Check(object p) + object PyCObject_FromVoidPtr(void* cobj, destructor1 destr) + object PyCObject_FromVoidPtrAndDesc(void* cobj, void* desc, + destructor2 destr) + void* PyCObject_AsVoidPtr(object self) + void* PyCObject_GetDesc(object self) + int PyCObject_SetVoidPtr(object self, void* cobj) + + # TypeCheck API + int PyFloat_Check(object obj) + int PyInt_Check(object obj) + + # Error API + int PyErr_Occurred() + void PyErr_Clear() + +cdef extern from "string.h": + void *memcpy(void *s1, void *s2, int n) + +cdef extern from "math.h": + double fabs(double x) diff --git a/numpy/random/mtrand/distributions.c b/numpy/random/mtrand/distributions.c new file mode 100644 index 000000000..528d8f332 --- /dev/null +++ b/numpy/random/mtrand/distributions.c @@ -0,0 +1,852 @@ +/* Copyright 2005 Robert Kern (robert.kern@gmail.com) + * + * Permission is hereby granted, free of charge, to any person obtaining a + * copy of this software and associated documentation files (the + * "Software"), to deal in the Software without restriction, including + * without limitation the rights to use, copy, modify, merge, publish, + * distribute, sublicense, and/or sell copies of the Software, and to + * permit persons to whom the Software is furnished to do so, subject to + * the following conditions: + * + * The above copyright notice and this permission notice shall be included + * in all copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS + * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + */ + +/* The implementations of rk_hypergeometric_hyp(), rk_hypergeometric_hrua(), + * and rk_triangular() were adapted from Ivan Frohne's rv.py which has this + * license: + * + * Copyright 1998 by Ivan Frohne; Wasilla, Alaska, U.S.A. + * All Rights Reserved + * + * Permission to use, copy, modify and distribute this software and its + * documentation for any purpose, free of charge, is granted subject to the + * following conditions: + * The above copyright notice and this permission notice shall be included in + * all copies or substantial portions of the software. + * + * THE SOFTWARE AND DOCUMENTATION IS PROVIDED WITHOUT WARRANTY OF ANY KIND, + * EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO MERCHANTABILITY, FITNESS + * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHOR + * OR COPYRIGHT HOLDER BE LIABLE FOR ANY CLAIM OR DAMAGES IN A CONTRACT + * ACTION, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * SOFTWARE OR ITS DOCUMENTATION. + */ + +#include <math.h> +#include "distributions.h" +#include <stdio.h> + +#ifndef min +#define min(x,y) ((x<y)?x:y) +#define max(x,y) ((x>y)?x:y) +#endif + +#ifndef M_PI +#define M_PI 3.14159265358979323846264338328 +#endif +/* log-gamma function to support some of these distributions. The + * algorithm comes from SPECFUN by Shanjie Zhang and Jianming Jin and their + * book "Computation of Special Functions", 1996, John Wiley & Sons, Inc. + */ +extern double loggam(double x); +double loggam(double x) +{ + double x0, x2, xp, gl, gl0; + long k, n; + + static double a[10] = {8.333333333333333e-02,-2.777777777777778e-03, + 7.936507936507937e-04,-5.952380952380952e-04, + 8.417508417508418e-04,-1.917526917526918e-03, + 6.410256410256410e-03,-2.955065359477124e-02, + 1.796443723688307e-01,-1.39243221690590e+00}; + x0 = x; + n = 0; + if ((x == 1.0) || (x == 2.0)) + { + return 0.0; + } + else if (x <= 7.0) + { + n = (long)(7 - x); + x0 = x + n; + } + x2 = 1.0/(x0*x0); + xp = 2*M_PI; + gl0 = a[9]; + for (k=8; k>=0; k--) + { + gl0 *= x2; + gl0 += a[k]; + } + gl = gl0/x0 + 0.5*log(xp) + (x0-0.5)*log(x0) - x0; + if (x <= 7.0) + { + for (k=1; k<=n; k++) + { + gl -= log(x0-1.0); + x0 -= 1.0; + } + } + return gl; +} + +double rk_normal(rk_state *state, double loc, double scale) +{ + return loc + scale*rk_gauss(state); +} + +double rk_standard_exponential(rk_state *state) +{ + /* We use -log(1-U) since U is [0, 1) */ + return -log(1.0 - rk_double(state)); +} + +double rk_exponential(rk_state *state, double scale) +{ + return scale * rk_standard_exponential(state); +} + +double rk_uniform(rk_state *state, double loc, double scale) +{ + return loc + scale*rk_double(state); +} + +double rk_standard_gamma(rk_state *state, double shape) +{ + double b, c; + double U, V, X, Y; + + if (shape == 1.0) + { + return rk_standard_exponential(state); + } + else if (shape < 1.0) + { + for (;;) + { + U = rk_double(state); + V = rk_standard_exponential(state); + if (U <= 1.0 - shape) + { + X = pow(U, 1./shape); + if (X <= V) + { + return X; + } + } + else + { + Y = -log((1-U)/shape); + X = pow(1.0 - shape + shape*Y, 1./shape); + if (X <= (V + Y)) + { + return X; + } + } + } + } + else + { + b = shape - 1./3.; + c = 1./sqrt(9*b); + for (;;) + { + do + { + X = rk_gauss(state); + V = 1.0 + c*X; + } while (V <= 0.0); + + V = V*V*V; + U = rk_double(state); + if (U < 1.0 - 0.0331*(X*X)*(X*X)) return (b*V); + if (log(U) < 0.5*X*X + b*(1. - V + log(V))) return (b*V); + } + } +} + +double rk_gamma(rk_state *state, double shape, double scale) +{ + return scale * rk_standard_gamma(state, shape); +} + +double rk_beta(rk_state *state, double a, double b) +{ + double Ga, Gb; + + if ((a <= 1.0) && (b <= 1.0)) + { + double U, V, X, Y; + /* Use Jonk's algorithm */ + + while (1) + { + U = rk_double(state); + V = rk_double(state); + X = pow(U, 1.0/a); + Y = pow(V, 1.0/b); + + if ((X + Y) <= 1.0) + { + return X / (X + Y); + } + } + } + else + { + Ga = rk_standard_gamma(state, a); + Gb = rk_standard_gamma(state, b); + return Ga/(Ga + Gb); + } +} + +double rk_chisquare(rk_state *state, double df) +{ + return 2.0*rk_standard_gamma(state, df/2.0); +} + +double rk_noncentral_chisquare(rk_state *state, double df, double nonc) +{ + double Chi2, N; + + Chi2 = rk_chisquare(state, df-1); + N = rk_gauss(state) + sqrt(nonc); + return Chi2 + N*N; +} + +double rk_f(rk_state *state, double dfnum, double dfden) +{ + return rk_chisquare(state, dfnum) / rk_chisquare(state, dfden); +} + +double rk_noncentral_f(rk_state *state, double dfnum, double dfden, double nonc) +{ + return ((rk_noncentral_chisquare(state, dfnum, nonc)*dfden) / + (rk_chisquare(state, dfden)*dfnum)); +} + +long rk_binomial_btpe(rk_state *state, long n, double p) +{ + double r,q,fm,p1,xm,xl,xr,c,laml,lamr,p2,p3,p4; + double a,u,v,s,F,rho,t,A,nrq,x1,x2,f1,f2,z,z2,w,w2,x; + long m,y,k,i; + + if (!(state->has_binomial) || + (state->nsave != n) || + (state->psave != p)) + { + /* initialize */ + state->nsave = n; + state->psave = p; + state->has_binomial = 1; + state->r = r = min(p, 1.0-p); + state->q = q = 1.0 - r; + state->fm = fm = n*r+r; + state->m = m = (long)floor(state->fm); + state->p1 = p1 = floor(2.195*sqrt(n*r*q)-4.6*q) + 0.5; + state->xm = xm = m + 0.5; + state->xl = xl = xm - p1; + state->xr = xr = xm + p1; + state->c = c = 0.134 + 20.5/(15.3 + m); + a = (fm - xl)/(fm-xl*r); + state->laml = laml = a*(1.0 + a/2.0); + a = (xr - fm)/(xr*q); + state->lamr = lamr = a*(1.0 + a/2.0); + state->p2 = p2 = p1*(1.0 + 2.0*c); + state->p3 = p3 = p2 + c/laml; + state->p4 = p4 = p3 + c/lamr; + } + else + { + r = state->r; + q = state->q; + fm = state->fm; + m = state->m; + p1 = state->p1; + xm = state->xm; + xl = state->xl; + xr = state->xr; + c = state->c; + laml = state->laml; + lamr = state->lamr; + p2 = state->p2; + p3 = state->p3; + p4 = state->p4; + } + + /* sigh ... */ + Step10: + nrq = n*r*q; + u = rk_double(state)*p4; + v = rk_double(state); + if (u > p1) goto Step20; + y = (long)floor(xm - p1*v + u); + goto Step60; + + Step20: + if (u > p2) goto Step30; + x = xl + (u - p1)/c; + v = v*c + 1.0 - fabs(m - x + 0.5)/p1; + if (v > 1.0) goto Step10; + y = (long)floor(x); + goto Step50; + + Step30: + if (u > p3) goto Step40; + y = (long)floor(xl + log(v)/laml); + if (y < 0) goto Step10; + v = v*(u-p2)*laml; + goto Step50; + + Step40: + y = (int)floor(xr - log(v)/lamr); + if (y > n) goto Step10; + v = v*(u-p3)*lamr; + + Step50: + k = fabs(y - m); + if ((k > 20) && (k < ((nrq)/2.0 - 1))) goto Step52; + + s = r/q; + a = s*(n+1); + F = 1.0; + if (m < y) + { + for (i=m; i<=y; i++) + { + F *= (a/i - s); + } + } + else if (m > y) + { + for (i=y; i<=m; i++) + { + F /= (a/i - s); + } + } + else + { + if (v > F) goto Step10; + goto Step60; + } + + Step52: + rho = (k/(nrq))*((k*(k/3.0 + 0.625) + 0.16666666666666666)/nrq + 0.5); + t = -k*k/(2*nrq); + A = log(v); + if (A < (t - rho)) goto Step60; + if (A > (t + rho)) goto Step10; + + x1 = y+1; + f1 = m+1; + z = n+1-m; + w = n-y+1; + x2 = x1*x1; + f2 = f1*f1; + z2 = z*z; + w2 = w*w; + if (A > (xm*log(f1/x1) + + (n-m+0.5)*log(z/w) + + (y-m)*log(w*r/(x1*q)) + + (13680.-(462.-(132.-(99.-140./f2)/f2)/f2)/f2)/f1/166320. + + (13680.-(462.-(132.-(99.-140./z2)/z2)/z2)/z2)/z/166320. + + (13680.-(462.-(132.-(99.-140./x2)/x2)/x2)/x2)/x1/166320. + + (13680.-(462.-(132.-(99.-140./w2)/w2)/w2)/w2)/w/166320.)) + { + goto Step10; + } + + Step60: + if (p > 0.5) + { + y = n - y; + } + + return y; +} + +long rk_binomial_inversion(rk_state *state, long n, double p) +{ + double q, qn, np, px, U; + long X, bound; + + if (!(state->has_binomial) || + (state->nsave != n) || + (state->psave != p)) + { + state->nsave = n; + state->psave = p; + state->has_binomial = 1; + state->q = q = 1.0 - p; + state->r = qn = exp(n * log(q)); + state->c = np = n*p; + state->m = bound = min(n, np + 10.0*sqrt(np)); + } else + { + q = state->q; + qn = state->r; + np = state->c; + bound = state->m; + } + X = 0; + px = qn; + U = rk_double(state); + while (U > px) + { + X++; + if (X > bound) + { + X = 0; + px = qn; + U = rk_double(state); + } else + { + U -= px; + px = ((n-X+1) * p * px)/(X*q); + } + } + return X; +} + +long rk_binomial(rk_state *state, long n, double p) +{ + double q; + + if (p <= 0.5) + { + if (p*n <= 30.0) + { + return rk_binomial_inversion(state, n, p); + } + else + { + return rk_binomial_btpe(state, n, p); + } + } + else + { + q = 1.0-p; + if (q*n <= 30.0) + { + return n - rk_binomial_inversion(state, n, q); + } + else + { + return n - rk_binomial_btpe(state, n, q); + } + } + +} + +long rk_negative_binomial(rk_state *state, long n, double p) +{ + double Y; + + Y = rk_gamma(state, n, (1-p)/p); + return rk_poisson(state, Y); +} + +long rk_poisson_mult(rk_state *state, double lam) +{ + long X; + double prod, U, enlam; + + enlam = exp(-lam); + X = 0; + prod = 1.0; + while (1) + { + U = rk_double(state); + prod *= U; + if (prod > enlam) + { + X += 1; + } + else + { + return X; + } + } +} + +#define LS2PI 0.91893853320467267 +#define TWELFTH 0.083333333333333333333333 +long rk_poisson_ptrs(rk_state *state, double lam) +{ + long k; + double U, V, slam, loglam, a, b, invalpha, vr, us; + + slam = sqrt(lam); + loglam = log(lam); + b = 0.931 + 2.53*slam; + a = -0.059 + 0.02483*b; + invalpha = 1.1239 + 1.1328/(b-3.4); + vr = 0.9277 - 3.6224/(b-2); + + while (1) + { + U = rk_double(state) - 0.5; + V = rk_double(state); + us = 0.5 - fabs(U); + k = (long)floor((2*a/us + b)*U + lam + 0.43); + if ((us >= 0.07) && (V <= vr)) + { + return k; + } + if ((k < 0) || + ((us < 0.013) && (V > us))) + { + continue; + } + if ((log(V) + log(invalpha) - log(a/(us*us)+b)) <= + (-lam + k*loglam - loggam(k+1))) + { + return k; + } + + + } + +} + +long rk_poisson(rk_state *state, double lam) +{ + if (lam >= 10) + { + return rk_poisson_ptrs(state, lam); + } + else if (lam == 0) + { + return 0; + } + else + { + return rk_poisson_mult(state, lam); + } +} + +double rk_standard_cauchy(rk_state *state) +{ + return rk_gauss(state) / rk_gauss(state); +} + +double rk_standard_t(rk_state *state, double df) +{ + double N, G, X; + + N = rk_gauss(state); + G = rk_standard_gamma(state, df/2); + X = sqrt(df/2)*N/sqrt(G); + return X; +} + +double rk_vonmises(rk_state *state, double mu, double kappa) +{ + double r, rho, s; + double U, V, W, Y, Z; + double result, mod; + + if (kappa < 1e-8) + { + return M_PI * (2*rk_double(state)-1); + } + else + { + r = 1 + sqrt(1 + 4*kappa*kappa); + rho = (r - sqrt(2*r))/(2*kappa); + s = (1 + rho*rho)/(2*rho); + + while (1) + { + U = 2*rk_double(state) - 1; + V = 2*rk_double(state) - 1; + Z = cos(M_PI*U); + W = (1 + s*Z)/(s + Z); + Y = kappa * (s - W); + if ((Y*(2-Y) - V >= 0) || (log(Y/V)+1 - Y >= 0)) + { + break; + } + } + + if (U < 0) + { + result = acos(W); + } + else + { + result = -acos(W); + } + result += mu + M_PI; + mod = fmod(result, 2*M_PI); + if (mod && (mod < 0)) + { + mod += 2*M_PI; + } + return mod - M_PI; + } +} + +double rk_pareto(rk_state *state, double a) +{ + return exp(rk_standard_exponential(state)/a) - 1; +} + +double rk_weibull(rk_state *state, double a) +{ + return pow(rk_standard_exponential(state), 1./a); +} + +double rk_power(rk_state *state, double a) +{ + return pow(1 - exp(-rk_standard_exponential(state)), 1./a); +} + +double rk_laplace(rk_state *state, double loc, double scale) +{ + double U; + + U = rk_double(state); + if (U < 0.5) + { + U = loc + scale * log(U + U); + } else + { + U = loc - scale * log(2.0 - U - U); + } + return U; +} + +double rk_gumbel(rk_state *state, double loc, double scale) +{ + double U; + + U = 1.0 - rk_double(state); + return loc - scale * log(-log(U)); +} + +double rk_logistic(rk_state *state, double loc, double scale) +{ + double U; + + U = rk_double(state); + return loc + scale * log(U/(1.0 - U)); +} + +double rk_lognormal(rk_state *state, double mean, double sigma) +{ + return exp(rk_normal(state, mean, sigma)); +} + +double rk_rayleigh(rk_state *state, double mode) +{ + return mode*sqrt(-2.0 * log(1.0 - rk_double(state))); +} + +double rk_wald(rk_state *state, double mean, double scale) +{ + double U, X, Y; + double mu_2l; + + mu_2l = mean / (2*scale); + Y = rk_gauss(state); + Y = mean*Y*Y; + X = mean + mu_2l*(Y - sqrt(4*scale*Y + Y*Y)); + U = rk_double(state); + if (U <= mean/(mean+X)) + { + return X; + } else + { + return mean*mean/X; + } +} + +long rk_zipf(rk_state *state, double a) +{ + double T, U, V; + long X; + double b; + + b = pow(2.0, a-1.0); + do + { + U = rk_double(state); + V = rk_double(state); + X = (long)floor(pow(U, -1.0/(a-1.0))); + T = pow(1.0 + 1.0/X, a-1.0); + } while ((V *X*(T-1.0)/(b-1.0)) > (T/b)); + return X; +} + +long rk_geometric_search(rk_state *state, double p) +{ + double U; + long X; + double sum, prod, q; + + X = 1; + sum = prod = p; + q = 1.0 - p; + U = rk_double(state); + while (U > sum) + { + prod *= q; + sum += prod; + X++; + } + return X; +} + +long rk_geometric_inversion(rk_state *state, double p) +{ + return (long)ceil(log(1.0-rk_double(state))/log(1.0-p)); +} + +long rk_geometric(rk_state *state, double p) +{ + if (p >= 0.333333333333333333333333) + { + return rk_geometric_search(state, p); + } else + { + return rk_geometric_inversion(state, p); + } +} + +long rk_hypergeometric_hyp(rk_state *state, long good, long bad, long sample) +{ + long d1, K, Z; + double d2, U, Y; + + d1 = bad + good - sample; + d2 = (double)min(bad, good); + + Y = d2; + K = sample; + while (Y > 0.0) + { + U = rk_double(state); + Y -= (long)floor(U + Y/(d1 + K)); + K--; + if (K == 0) break; + } + Z = (long)(d2 - Y); + if (bad > good) Z = sample - Z; + return Z; +} + +/* D1 = 2*sqrt(2/e) */ +/* D2 = 3 - 2*sqrt(3/e) */ +#define D1 1.7155277699214135 +#define D2 0.8989161620588988 +long rk_hypergeometric_hrua(rk_state *state, long good, long bad, long sample) +{ + long mingoodbad, maxgoodbad, popsize, m, d9; + double d4, d5, d6, d7, d8, d10, d11; + long Z; + double T, W, X, Y; + + mingoodbad = min(good, bad); + popsize = good + bad; + maxgoodbad = max(good, bad); + m = min(sample, popsize - sample); + d4 = ((double)mingoodbad) / popsize; + d5 = 1.0 - d4; + d6 = m*d4 + 0.5; + d7 = sqrt((popsize - m) * sample * d4 *d5 / (popsize-1) + 0.5); + d8 = D1*d7 + D2; + d9 = (long)floor((double)((m+1)*(mingoodbad+1))/(popsize+2)); + d10 = (loggam(d9+1) + loggam(mingoodbad-d9+1) + loggam(m-d9+1) + + loggam(maxgoodbad-m+d9+1)); + d11 = min(min(m, mingoodbad)+1.0, floor(d6+16*d7)); + /* 16 for 16-decimal-digit precision in D1 and D2 */ + + while (1) + { + X = rk_double(state); + Y = rk_double(state); + W = d6 + d8*(Y- 0.5)/X; + + /* fast rejection: */ + if ((W < 0.0) || (W >= d11)) continue; + + Z = (long)floor(W); + T = d10 - (loggam(Z+1) + loggam(mingoodbad-Z+1) + loggam(m-Z+1) + + loggam(maxgoodbad-m+Z+1)); + + /* fast acceptance: */ + if ((X*(4.0-X)-3.0) <= T) break; + + /* fast rejection: */ + if (X*(X-T) >= 1) continue; + + if (2.0*log(X) <= T) break; /* acceptance */ + } + + /* this is a correction to HRUA* by Ivan Frohne in rv.py */ + if (bad > good) Z = m - Z; + + /* another fix from rv.py to allow sample to exceed popsize/2 */ + if (m < sample) Z = bad - Z; + + return Z; +} +#undef D1 +#undef D2 + +long rk_hypergeometric(rk_state *state, long good, long bad, long sample) +{ + if (sample > 10) + { + return rk_hypergeometric_hrua(state, good, bad, sample); + } else + { + return rk_hypergeometric_hyp(state, good, bad, sample); + } +} + +double rk_triangular(rk_state *state, double left, double mode, double right) +{ + double base, leftbase, ratio, leftprod, rightprod; + double U; + + base = right - left; + leftbase = mode - left; + ratio = leftbase / base; + leftprod = leftbase*base; + rightprod = (right - mode)*base; + + U = rk_double(state); + if (U <= ratio) + { + return left + sqrt(U*leftprod); + } else + { + return right - sqrt((1.0 - U) * rightprod); + } +} + +long rk_logseries(rk_state *state, double p) +{ + double q, r, U, V; + + r = log(1.0 - p); + + V = rk_double(state); + if (V >= p) return 1; + U = rk_double(state); + q = 1.0 - exp(r*U); + if (V <= q*q) return (long)floor(1 + log(V)/log(q)); + if (V <= q) return 1; + return 2; +} diff --git a/numpy/random/mtrand/distributions.h b/numpy/random/mtrand/distributions.h new file mode 100644 index 000000000..0d6de639d --- /dev/null +++ b/numpy/random/mtrand/distributions.h @@ -0,0 +1,185 @@ +/* Copyright 2005 Robert Kern (robert.kern@gmail.com) + * + * Permission is hereby granted, free of charge, to any person obtaining a + * copy of this software and associated documentation files (the + * "Software"), to deal in the Software without restriction, including + * without limitation the rights to use, copy, modify, merge, publish, + * distribute, sublicense, and/or sell copies of the Software, and to + * permit persons to whom the Software is furnished to do so, subject to + * the following conditions: + * + * The above copyright notice and this permission notice shall be included + * in all copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS + * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + */ + +#ifndef _RK_DISTR_ +#define _RK_DISTR_ + +#include "randomkit.h" + +#ifdef __cplusplus +extern "C" { +#endif + +/* References: + * + * Devroye, Luc. _Non-Uniform Random Variate Generation_. + * Springer-Verlag, New York, 1986. + * http://cgm.cs.mcgill.ca/~luc/rnbookindex.html + * + * Kachitvichyanukul, V. and Schmeiser, B. W. Binomial Random Variate + * Generation. Communications of the ACM, 31, 2 (February, 1988) 216. + * + * Hoermann, W. The Transformed Rejection Method for Generating Poisson Random + * Variables. Insurance: Mathematics and Economics, (to appear) + * http://citeseer.csail.mit.edu/151115.html + * + * Marsaglia, G. and Tsang, W. W. A Simple Method for Generating Gamma + * Variables. ACM Transactions on Mathematical Software, Vol. 26, No. 3, + * September 2000, Pages 363–372. + */ + +/* Normal distribution with mean=loc and standard deviation=scale. */ +extern double rk_normal(rk_state *state, double loc, double scale); + +/* Standard exponential distribution (mean=1) computed by inversion of the + * CDF. */ +extern double rk_standard_exponential(rk_state *state); + +/* Exponential distribution with mean=scale. */ +extern double rk_exponential(rk_state *state, double scale); + +/* Uniform distribution on interval [loc, loc+scale). */ +extern double rk_uniform(rk_state *state, double loc, double scale); + +/* Standard gamma distribution with shape parameter. + * When shape < 1, the algorithm given by (Devroye p. 304) is used. + * When shape == 1, a Exponential variate is generated. + * When shape > 1, the small and fast method of (Marsaglia and Tsang 2000) + * is used. + */ +extern double rk_standard_gamma(rk_state *state, double shape); + +/* Gamma distribution with shape and scale. */ +extern double rk_gamma(rk_state *state, double shape, double scale); + +/* Beta distribution computed by combining two gamma variates (Devroye p. 432). + */ +extern double rk_beta(rk_state *state, double a, double b); + +/* Chi^2 distribution computed by transforming a gamma variate (it being a + * special case Gamma(df/2, 2)). */ +extern double rk_chisquare(rk_state *state, double df); + +/* Noncentral Chi^2 distribution computed by modifying a Chi^2 variate. */ +extern double rk_noncentral_chisquare(rk_state *state, double df, double nonc); + +/* F distribution computed by taking the ratio of two Chi^2 variates. */ +extern double rk_f(rk_state *state, double dfnum, double dfden); + +/* Noncentral F distribution computed by taking the ratio of a noncentral Chi^2 + * and a Chi^2 variate. */ +extern double rk_noncentral_f(rk_state *state, double dfnum, double dfden, double nonc); + +/* Binomial distribution with n Bernoulli trials with success probability p. + * When n*p <= 30, the "Second waiting time method" given by (Devroye p. 525) is + * used. Otherwise, the BTPE algorithm of (Kachitvichyanukul and Schmeiser 1988) + * is used. */ +extern long rk_binomial(rk_state *state, long n, double p); + +/* Binomial distribution using BTPE. */ +extern long rk_binomial_btpe(rk_state *state, long n, double p); + +/* Binomial distribution using inversion and chop-down */ +extern long rk_binomial_inversion(rk_state *state, long n, double p); + +/* Negative binomial distribution computed by generating a Gamma(n, (1-p)/p) + * variate Y and returning a Poisson(Y) variate (Devroye p. 543). */ +extern long rk_negative_binomial(rk_state *state, long n, double p); + +/* Poisson distribution with mean=lam. + * When lam < 10, a basic algorithm using repeated multiplications of uniform + * variates is used (Devroye p. 504). + * When lam >= 10, algorithm PTRS from (Hoermann 1992) is used. + */ +extern long rk_poisson(rk_state *state, double lam); + +/* Poisson distribution computed by repeated multiplication of uniform variates. + */ +extern long rk_poisson_mult(rk_state *state, double lam); + +/* Poisson distribution computer by the PTRS algorithm. */ +extern long rk_poisson_ptrs(rk_state *state, double lam); + +/* Standard Cauchy distribution computed by dividing standard gaussians + * (Devroye p. 451). */ +extern double rk_standard_cauchy(rk_state *state); + +/* Standard t-distribution with df degrees of freedom (Devroye p. 445 as + * corrected in the Errata). */ +extern double rk_standard_t(rk_state *state, double df); + +/* von Mises circular distribution with center mu and shape kappa on [-pi,pi] + * (Devroye p. 476 as corrected in the Errata). */ +extern double rk_vonmises(rk_state *state, double mu, double kappa); + +/* Pareto distribution via inversion (Devroye p. 262) */ +extern double rk_pareto(rk_state *state, double a); + +/* Weibull distribution via inversion (Devroye p. 262) */ +extern double rk_weibull(rk_state *state, double a); + +/* Power distribution via inversion (Devroye p. 262) */ +extern double rk_power(rk_state *state, double a); + +/* Laplace distribution */ +extern double rk_laplace(rk_state *state, double loc, double scale); + +/* Gumbel distribution */ +extern double rk_gumbel(rk_state *state, double loc, double scale); + +/* Logistic distribution */ +extern double rk_logistic(rk_state *state, double loc, double scale); + +/* Log-normal distribution */ +extern double rk_lognormal(rk_state *state, double mean, double sigma); + +/* Rayleigh distribution */ +extern double rk_rayleigh(rk_state *state, double mode); + +/* Wald distribution */ +extern double rk_wald(rk_state *state, double mean, double scale); + +/* Zipf distribution */ +extern long rk_zipf(rk_state *state, double a); + +/* Geometric distribution */ +extern long rk_geometric(rk_state *state, double p); +extern long rk_geometric_search(rk_state *state, double p); +extern long rk_geometric_inversion(rk_state *state, double p); + +/* Hypergeometric distribution */ +extern long rk_hypergeometric(rk_state *state, long good, long bad, long sample); +extern long rk_hypergeometric_hyp(rk_state *state, long good, long bad, long sample); +extern long rk_hypergeometric_hrua(rk_state *state, long good, long bad, long sample); + +/* Triangular distribution */ +extern double rk_triangular(rk_state *state, double left, double mode, double right); + +/* Logarithmic series distribution */ +extern long rk_logseries(rk_state *state, double p); + +#ifdef __cplusplus +} +#endif + + +#endif /* _RK_DISTR_ */ diff --git a/numpy/random/mtrand/generate_mtrand_c.py b/numpy/random/mtrand/generate_mtrand_c.py new file mode 100644 index 000000000..8eb6254f2 --- /dev/null +++ b/numpy/random/mtrand/generate_mtrand_c.py @@ -0,0 +1,37 @@ +#!/usr/bin/env python +import sys +import re +import os + +unused_internal_funcs = ['__Pyx_PrintItem', + '__Pyx_PrintNewline', + '__Pyx_ReRaise', + #'__Pyx_GetExcValue', + '__Pyx_ArgTypeTest', + '__Pyx_SetVtable', + '__Pyx_GetVtable', + '__Pyx_CreateClass'] + +if __name__ == '__main__': + os.system('pyrexc mtrand.pyx') + mtrand_c = open('mtrand.c', 'r') + processed = open('mtrand_pp.c', 'w') + unused_funcs_str = '(' + '|'.join(unused_internal_funcs) + ')' + uifpat = re.compile(r'static \w+ \*?'+unused_funcs_str+r'.*/\*proto\*/') + for linenum, line in enumerate(mtrand_c): + m = re.match(r'^(\s+arrayObject\w*\s*=\s*[(])[(]PyObject\s*[*][)]', + line) + if m: + line = '%s(PyArrayObject *)%s' % (m.group(1), line[m.end():]) + m = uifpat.match(line) + if m: + line = '' + m = re.search(unused_funcs_str, line) + if m: + print >>sys.stderr, \ + "%s was declared unused, but is used at line %d" % (m.group(), + linenum+1) + processed.write(line) + mtrand_c.close() + processed.close() + os.rename('mtrand_pp.c', 'mtrand.c') diff --git a/numpy/random/mtrand/initarray.c b/numpy/random/mtrand/initarray.c new file mode 100644 index 000000000..07ad2cc4f --- /dev/null +++ b/numpy/random/mtrand/initarray.c @@ -0,0 +1,136 @@ +/* These function have been adapted from Python 2.4.1's _randommodule.c + + The following changes have been made to it in 2005 by Robert Kern: + + * init_by_array has been declared extern, has a void return, and uses the + rk_state structure to hold its data. + + The original file has the following verbatim comments: + + ------------------------------------------------------------------ + The code in this module was based on a download from: + http://www.math.keio.ac.jp/~matumoto/MT2002/emt19937ar.html + + It was modified in 2002 by Raymond Hettinger as follows: + + * the principal computational lines untouched except for tabbing. + + * renamed genrand_res53() to random_random() and wrapped + in python calling/return code. + + * genrand_int32() and the helper functions, init_genrand() + and init_by_array(), were declared static, wrapped in + Python calling/return code. also, their global data + references were replaced with structure references. + + * unused functions from the original were deleted. + new, original C python code was added to implement the + Random() interface. + + The following are the verbatim comments from the original code: + + A C-program for MT19937, with initialization improved 2002/1/26. + Coded by Takuji Nishimura and Makoto Matsumoto. + + Before using, initialize the state by using init_genrand(seed) + or init_by_array(init_key, key_length). + + Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, + All rights reserved. + + Redistribution and use in source and binary forms, with or without + modification, are permitted provided that the following conditions + are met: + + 1. Redistributions of source code must retain the above copyright + notice, this list of conditions and the following disclaimer. + + 2. Redistributions in binary form must reproduce the above copyright + notice, this list of conditions and the following disclaimer in the + documentation and/or other materials provided with the distribution. + + 3. The names of its contributors may not be used to endorse or promote + products derived from this software without specific prior written + permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR + CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF + LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING + NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + + Any feedback is very welcome. + http://www.math.keio.ac.jp/matumoto/emt.html + email: matumoto@math.keio.ac.jp +*/ + +#include "initarray.h" + +static void +init_genrand(rk_state *self, unsigned long s); + +/* initializes mt[RK_STATE_LEN] with a seed */ +static void +init_genrand(rk_state *self, unsigned long s) +{ + int mti; + unsigned long *mt; + + mt = self->key; + mt[0]= s & 0xffffffffUL; + for (mti=1; mti<RK_STATE_LEN; mti++) { + mt[mti] = + (1812433253UL * (mt[mti-1] ^ (mt[mti-1] >> 30)) + mti); + /* See Knuth TAOCP Vol2. 3rd Ed. P.106 for multiplier. */ + /* In the previous versions, MSBs of the seed affect */ + /* only MSBs of the array mt[]. */ + /* 2002/01/09 modified by Makoto Matsumoto */ + mt[mti] &= 0xffffffffUL; + /* for >32 bit machines */ + } + self->pos = mti; + return; +} + + +/* initialize by an array with array-length */ +/* init_key is the array for initializing keys */ +/* key_length is its length */ +extern void +init_by_array(rk_state *self, unsigned long init_key[], unsigned long key_length) +{ + unsigned int i, j, k; /* was signed in the original code. RDH 12/16/2002 */ + unsigned long *mt; + + mt = self->key; + init_genrand(self, 19650218UL); + i=1; j=0; + k = (RK_STATE_LEN>key_length ? RK_STATE_LEN : key_length); + for (; k; k--) { + mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1664525UL)) + + init_key[j] + j; /* non linear */ + mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ + i++; j++; + if (i>=RK_STATE_LEN) { mt[0] = mt[RK_STATE_LEN-1]; i=1; } + if (j>=key_length) j=0; + } + for (k=RK_STATE_LEN-1; k; k--) { + mt[i] = (mt[i] ^ ((mt[i-1] ^ (mt[i-1] >> 30)) * 1566083941UL)) + - i; /* non linear */ + mt[i] &= 0xffffffffUL; /* for WORDSIZE > 32 machines */ + i++; + if (i>=RK_STATE_LEN) { mt[0] = mt[RK_STATE_LEN-1]; i=1; } + } + + mt[0] = 0x80000000UL; /* MSB is 1; assuring non-zero initial array */ + self->has_gauss = 0; + self->has_binomial = 0; +} + diff --git a/numpy/random/mtrand/initarray.h b/numpy/random/mtrand/initarray.h new file mode 100644 index 000000000..a4ac210f4 --- /dev/null +++ b/numpy/random/mtrand/initarray.h @@ -0,0 +1,6 @@ +#include "randomkit.h" + +extern void +init_by_array(rk_state *self, unsigned long init_key[], + unsigned long key_length); + diff --git a/numpy/random/mtrand/mtrand.c b/numpy/random/mtrand/mtrand.c new file mode 100644 index 000000000..17aaeb4bf --- /dev/null +++ b/numpy/random/mtrand/mtrand.c @@ -0,0 +1,10907 @@ +/* Generated by Pyrex 0.9.5.1a on Mon Apr 2 09:24:19 2007 */ + +#include "Python.h" +#include "structmember.h" +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifdef __cplusplus +#define __PYX_EXTERN_C extern "C" +#else +#define __PYX_EXTERN_C extern +#endif +__PYX_EXTERN_C double pow(double, double); +#include "string.h" +#include "math.h" +#include "numpy/arrayobject.h" +#include "randomkit.h" +#include "distributions.h" +#include "initarray.h" + + +typedef struct {PyObject **p; char *s;} __Pyx_InternTabEntry; /*proto*/ +typedef struct {PyObject **p; char *s; long n;} __Pyx_StringTabEntry; /*proto*/ + +static PyObject *__pyx_m; +static PyObject *__pyx_b; +static int __pyx_lineno; +static char *__pyx_filename; +static char **__pyx_f; + +static int __Pyx_GetStarArgs(PyObject **args, PyObject **kwds, char *kwd_list[], int nargs, PyObject **args2, PyObject **kwds2); /*proto*/ + +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list); /*proto*/ + +static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name); /*proto*/ + +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb); /*proto*/ + +static PyObject *__Pyx_UnpackItem(PyObject *); /*proto*/ +static int __Pyx_EndUnpack(PyObject *); /*proto*/ + +static PyObject *__Pyx_GetExcValue(void); /*proto*/ + +static int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /*proto*/ + +static int __Pyx_InternStrings(__Pyx_InternTabEntry *t); /*proto*/ + +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); /*proto*/ + +static PyTypeObject *__Pyx_ImportType(char *module_name, char *class_name, long size); /*proto*/ + +static void __Pyx_AddTraceback(char *funcname); /*proto*/ + +/* Declarations from mtrand */ + + +struct __pyx_obj_6mtrand_RandomState { + PyObject_HEAD + rk_state (*internal_state); +}; + +static PyTypeObject *__pyx_ptype_6mtrand_dtype = 0; +static PyTypeObject *__pyx_ptype_6mtrand_ndarray = 0; +static PyTypeObject *__pyx_ptype_6mtrand_flatiter = 0; +static PyTypeObject *__pyx_ptype_6mtrand_broadcast = 0; +static PyTypeObject *__pyx_ptype_6mtrand_RandomState = 0; +static PyObject *__pyx_k2; +static PyObject *__pyx_k3; +static PyObject *__pyx_k4; +static PyObject *__pyx_k5; +static PyObject *__pyx_k6; +static PyObject *__pyx_k7; +static PyObject *__pyx_k8; +static PyObject *__pyx_k9; +static PyObject *__pyx_k10; +static PyObject *__pyx_k11; +static PyObject *__pyx_k12; +static PyObject *__pyx_k13; +static PyObject *__pyx_k14; +static PyObject *__pyx_k15; +static PyObject *__pyx_k16; +static PyObject *__pyx_k17; +static PyObject *__pyx_k18; +static PyObject *__pyx_k19; +static PyObject *__pyx_k20; +static PyObject *__pyx_k21; +static PyObject *__pyx_k22; +static PyObject *__pyx_k23; +static PyObject *__pyx_k24; +static PyObject *__pyx_k25; +static PyObject *__pyx_k26; +static PyObject *__pyx_k27; +static PyObject *__pyx_k28; +static PyObject *__pyx_k29; +static PyObject *__pyx_k30; +static PyObject *__pyx_k31; +static PyObject *__pyx_k32; +static PyObject *__pyx_k33; +static PyObject *__pyx_k34; +static PyObject *__pyx_k35; +static PyObject *__pyx_k36; +static PyObject *__pyx_k37; +static PyObject *__pyx_k38; +static PyObject *__pyx_k39; +static PyObject *__pyx_k40; +static PyObject *__pyx_k41; +static PyObject *__pyx_k42; +static PyObject *__pyx_k43; +static PyObject *__pyx_k44; +static PyObject *__pyx_k45; +static PyObject *__pyx_k46; +static PyObject *__pyx_k47; +static PyObject *__pyx_k48; +static PyObject *__pyx_k49; +static PyObject *__pyx_k50; +static PyObject *__pyx_k51; +static PyObject *__pyx_k52; +static PyObject *__pyx_k53; +static PyObject *__pyx_k54; +static PyObject *__pyx_k55; +static PyObject *__pyx_k56; +static PyObject *__pyx_k57; +static PyObject *__pyx_k58; +static PyObject *__pyx_k59; +static PyObject *__pyx_k60; +static PyObject *(__pyx_f_6mtrand_cont0_array(rk_state (*),double ((*)(rk_state (*))),PyObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont1_array_sc(rk_state (*),double ((*)(rk_state (*),double )),PyObject *,double )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont1_array(rk_state (*),double ((*)(rk_state (*),double )),PyObject *,PyArrayObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont2_array_sc(rk_state (*),double ((*)(rk_state (*),double ,double )),PyObject *,double ,double )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont2_array(rk_state (*),double ((*)(rk_state (*),double ,double )),PyObject *,PyArrayObject *,PyArrayObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont3_array_sc(rk_state (*),double ((*)(rk_state (*),double ,double ,double )),PyObject *,double ,double ,double )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_cont3_array(rk_state (*),double ((*)(rk_state (*),double ,double ,double )),PyObject *,PyArrayObject *,PyArrayObject *,PyArrayObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_disc0_array(rk_state (*),long ((*)(rk_state (*))),PyObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discnp_array_sc(rk_state (*),long ((*)(rk_state (*),long ,double )),PyObject *,long ,double )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discnp_array(rk_state (*),long ((*)(rk_state (*),long ,double )),PyObject *,PyArrayObject *,PyArrayObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discnmN_array_sc(rk_state (*),long ((*)(rk_state (*),long ,long ,long )),PyObject *,long ,long ,long )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discnmN_array(rk_state (*),long ((*)(rk_state (*),long ,long ,long )),PyObject *,PyArrayObject *,PyArrayObject *,PyArrayObject *)); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discd_array_sc(rk_state (*),long ((*)(rk_state (*),double )),PyObject *,double )); /*proto*/ +static PyObject *(__pyx_f_6mtrand_discd_array(rk_state (*),long ((*)(rk_state (*),double )),PyObject *,PyArrayObject *)); /*proto*/ +static double (__pyx_f_6mtrand_kahan_sum(double (*),long )); /*proto*/ + + +/* Implementation of mtrand */ + + +static PyObject *__pyx_n__sp; +static PyObject *__pyx_n__rand; +static PyObject *__pyx_n_seed; +static PyObject *__pyx_n_get_state; +static PyObject *__pyx_n_set_state; 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; goto __pyx_L1;} + __pyx_4 = PyObject_GetAttr(__pyx_2, __pyx_n_float64); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_2 = PyTuple_New(2); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; goto __pyx_L1;} + Py_INCREF(__pyx_v_size); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_size); + PyTuple_SET_ITEM(__pyx_2, 1, __pyx_4); + __pyx_4 = 0; + __pyx_4 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 132; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_4))); + Py_DECREF(((PyObject *)arrayObject)); + arrayObject = ((PyArrayObject *)__pyx_4); + Py_DECREF(__pyx_4); __pyx_4 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":133 */ + __pyx_v_length = PyArray_SIZE(arrayObject); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":134 */ + __pyx_v_array_data = ((double (*))arrayObject->data); 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 166; goto __pyx_L1;} + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_2))); + Py_DECREF(((PyObject *)arrayObject)); + arrayObject = ((PyArrayObject *)__pyx_2); + Py_DECREF(__pyx_2); __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":167 */ + __pyx_v_length = PyArray_SIZE(arrayObject); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":168 */ + __pyx_v_array_data = ((double (*))arrayObject->data); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":169 */ + __pyx_2 = PyArray_IterNew(((PyObject *)__pyx_v_oa)); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 169; goto __pyx_L1;} + Py_INCREF(((PyObject *)((PyArrayIterObject *)__pyx_2))); + Py_DECREF(((PyObject *)__pyx_v_itera)); + __pyx_v_itera = ((PyArrayIterObject *)__pyx_2); + Py_DECREF(__pyx_2); __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":170 */ + for (__pyx_v_i = 0; 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_1, __pyx_n_empty); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PyInt_FromLong(624); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + __pyx_3 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + __pyx_4 = PyObject_GetAttr(__pyx_3, __pyx_n_uint); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyTuple_New(2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_1); + PyTuple_SET_ITEM(__pyx_3, 1, __pyx_4); + __pyx_1 = 0; + __pyx_4 = 0; + __pyx_1 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 525; goto __pyx_L1;} + Py_DECREF(__pyx_2); 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 527; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_4 = PyTuple_New(2); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 527; goto __pyx_L1;} + Py_INCREF(((PyObject *)arrayObject_state)); + PyTuple_SET_ITEM(__pyx_4, 0, ((PyObject *)arrayObject_state)); + PyTuple_SET_ITEM(__pyx_4, 1, __pyx_1); + __pyx_1 = 0; + __pyx_3 = PyObject_CallObject(__pyx_2, __pyx_4); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 527; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_4); __pyx_4 = 0; + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_3))); + Py_DECREF(((PyObject *)arrayObject_state)); + arrayObject_state = ((PyArrayObject *)__pyx_3); + Py_DECREF(__pyx_3); __pyx_3 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":528 */ + __pyx_1 = PyInt_FromLong(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state->pos); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; 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/*proto*/ +static char __pyx_doc_6mtrand_11RandomState_set_state[] = "Set the state from a tuple.\n\n state = (\'MT19937\', int key[624], int pos)\n\n set_state(state)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_set_state(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_state = 0; + PyArrayObject *arrayObject_obj; + int __pyx_v_pos; + PyObject *__pyx_v_algorithm_name; + PyObject *__pyx_v_key; + PyObject *__pyx_r; + PyObject *__pyx_1 = 0; + PyObject *__pyx_2 = 0; + int __pyx_3; + PyObject *__pyx_4 = 0; + static char *__pyx_argnames[] = {"state",0}; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "O", __pyx_argnames, &__pyx_v_state)) return 0; + Py_INCREF(__pyx_v_self); + Py_INCREF(__pyx_v_state); + arrayObject_obj = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); + __pyx_v_algorithm_name = Py_None; Py_INCREF(Py_None); + __pyx_v_key = Py_None; Py_INCREF(Py_None); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":539 */ + __pyx_1 = PyInt_FromLong(0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 539; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_state, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 539; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_v_algorithm_name); + __pyx_v_algorithm_name = __pyx_2; + __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":540 */ + if (PyObject_Cmp(__pyx_v_algorithm_name, __pyx_n_MT19937, &__pyx_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 540; goto __pyx_L1;} + __pyx_3 = __pyx_3 != 0; + if (__pyx_3) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":541 */ + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 541; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 541; goto __pyx_L1;} + Py_INCREF(__pyx_k69p); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_k69p); 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If you want an\n interface that takes a tuple as the first argument\n use numpy.random.random_sample(shape_tuple).\n \n "; +static PyObject *__pyx_f_6mtrand_11RandomState_rand(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_args = 0; + PyObject *__pyx_r; + PyObject *__pyx_1 = 0; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + int __pyx_4; + PyObject *__pyx_5 = 0; + static char *__pyx_argnames[] = {0}; + if (__Pyx_GetStarArgs(&__pyx_args, &__pyx_kwds, __pyx_argnames, 0, &__pyx_v_args, 0) < 0) return 0; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "", __pyx_argnames)) { + Py_XDECREF(__pyx_args); + Py_XDECREF(__pyx_kwds); + Py_XDECREF(__pyx_v_args); + return 0; + } + Py_INCREF(__pyx_v_self); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":656 */ + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_len); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 656; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 656; goto __pyx_L1;} + Py_INCREF(__pyx_v_args); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_args); + __pyx_3 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 656; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyInt_FromLong(0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 656; goto __pyx_L1;} + if (PyObject_Cmp(__pyx_3, __pyx_1, &__pyx_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 656; goto __pyx_L1;} + __pyx_4 = __pyx_4 == 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + if (__pyx_4) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":657 */ + __pyx_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_random_sample); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 657; goto __pyx_L1;} + __pyx_3 = PyObject_CallObject(__pyx_2, 0); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 657; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_r = __pyx_3; + __pyx_3 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + /*else*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":659 */ + __pyx_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_random_sample); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 659; goto __pyx_L1;} + __pyx_2 = PyTuple_New(0); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 659; goto __pyx_L1;} + __pyx_3 = PyDict_New(); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 659; goto __pyx_L1;} + if (PyDict_SetItem(__pyx_3, __pyx_n_size, __pyx_v_args) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 659; goto __pyx_L1;} + __pyx_5 = PyEval_CallObjectWithKeywords(__pyx_1, __pyx_2, __pyx_3); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 659; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_r = __pyx_5; + __pyx_5 = 0; + goto __pyx_L0; + } + __pyx_L2:; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_1); + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + Py_XDECREF(__pyx_5); + __Pyx_AddTraceback("mtrand.RandomState.rand"); + __pyx_r = 0; + __pyx_L0:; + Py_XDECREF(__pyx_v_args); + Py_DECREF(__pyx_v_self); + Py_XDECREF(__pyx_args); + Py_XDECREF(__pyx_kwds); + return __pyx_r; +} + +static PyObject *__pyx_f_6mtrand_11RandomState_randn(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_randn[] = "Returns zero-mean, unit-variance Gaussian random numbers in an \n array of shape (d0, d1, ..., dn).\n\n randn(d0, d1, ..., dn) -> random values\n\n Note: This is a convenience function. 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__pyx_lineno = 671; goto __pyx_L1;} + Py_INCREF(__pyx_v_args); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_args); + __pyx_3 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 671; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyInt_FromLong(0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 671; goto __pyx_L1;} + if (PyObject_Cmp(__pyx_3, __pyx_1, &__pyx_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 671; goto __pyx_L1;} + __pyx_4 = __pyx_4 == 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + if (__pyx_4) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":672 */ + __pyx_2 = PyObject_GetAttr(__pyx_v_self, __pyx_n_standard_normal); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 672; goto __pyx_L1;} + __pyx_3 = PyObject_CallObject(__pyx_2, 0); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 672; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_r = __pyx_3; + __pyx_3 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + /*else*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":674 */ + __pyx_1 = PyObject_GetAttr(__pyx_v_self, __pyx_n_standard_normal); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 674; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 674; goto __pyx_L1;} + Py_INCREF(__pyx_v_args); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_args); + __pyx_3 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 674; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_r = __pyx_3; + __pyx_3 = 0; + goto __pyx_L0; + } + __pyx_L2:; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_1); + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + __Pyx_AddTraceback("mtrand.RandomState.randn"); + __pyx_r = 0; + __pyx_L0:; 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 694; goto __pyx_L1;} + __pyx_r = __pyx_1; + __pyx_1 = 0; + goto __pyx_L0; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_1); + __Pyx_AddTraceback("mtrand.RandomState.standard_normal"); + __pyx_r = 0; + __pyx_L0:; + Py_DECREF(__pyx_v_self); + Py_DECREF(__pyx_v_size); + return __pyx_r; +} + +static PyObject *__pyx_n_any; +static PyObject *__pyx_n_less_equal; + +static PyObject *__pyx_k73p; +static PyObject *__pyx_k74p; + +static char (__pyx_k73[]) = "scale <= 0"; +static char (__pyx_k74[]) = "scale <= 0"; + +static PyObject *__pyx_f_6mtrand_11RandomState_normal(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_normal[] = "Normal distribution (mean=loc, stdev=scale).\n\n normal(loc=0.0, scale=1.0, size=None) -> random values\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_normal(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_loc = 0; 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__pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 785; goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":786 */ + __pyx_2 = __pyx_f_6mtrand_cont1_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_standard_gamma,__pyx_v_size,__pyx_v_fshape); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 786; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":788 */ + PyErr_Clear(); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":789 */ + __pyx_3 = PyArray_FROM_OTF(__pyx_v_shape,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 789; goto __pyx_L1;} + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_3))); 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 832; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 832; goto __pyx_L1;} + Py_INCREF(__pyx_k87p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k87p); + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 832; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 832; goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":833 */ + __pyx_1 = (__pyx_v_fdfden <= 0); + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":834 */ + __pyx_2 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 834; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 834; goto __pyx_L1;} + Py_INCREF(__pyx_k88p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k88p); + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 834; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 834; goto __pyx_L1;} + goto __pyx_L4; + } + __pyx_L4:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":835 */ + __pyx_2 = __pyx_f_6mtrand_cont2_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_f,__pyx_v_size,__pyx_v_fdfnum,__pyx_v_fdfden); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 835; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":837 */ + PyErr_Clear(); 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goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_5); __pyx_5 = 0; + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 841; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_4); + __pyx_4 = 0; + __pyx_5 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 841; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyObject_IsTrue(__pyx_5); if (__pyx_1 < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 841; goto __pyx_L1;} + Py_DECREF(__pyx_5); __pyx_5 = 0; + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":842 */ + __pyx_4 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 842; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 842; goto __pyx_L1;} + Py_INCREF(__pyx_k89p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k89p); 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 915; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 915; goto __pyx_L1;} + Py_INCREF(__pyx_k99p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k99p); + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 915; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 915; goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":916 */ + __pyx_1 = (__pyx_v_fnonc <= 0); + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":917 */ + __pyx_2 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 917; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 917; goto __pyx_L1;} + Py_INCREF(__pyx_k100p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k100p); + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 917; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 917; goto __pyx_L1;} + goto __pyx_L4; + } + __pyx_L4:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":918 */ + __pyx_2 = __pyx_f_6mtrand_cont2_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_noncentral_chisquare,__pyx_v_size,__pyx_v_fdf,__pyx_v_fnonc); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 918; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":921 */ + PyErr_Clear(); 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goto __pyx_L1;} + __pyx_3 = PyObject_GetAttr(__pyx_2, __pyx_n_any); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_4 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_4, __pyx_n_less_equal); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_4 = PyFloat_FromDouble(0.0); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + __pyx_5 = PyTuple_New(2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + Py_INCREF(((PyObject *)__pyx_v_odf)); + PyTuple_SET_ITEM(__pyx_5, 0, ((PyObject *)__pyx_v_odf)); + PyTuple_SET_ITEM(__pyx_5, 1, __pyx_4); + __pyx_4 = 0; + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_5); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 925; goto __pyx_L1;} + Py_DECREF(__pyx_2); 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/*proto*/ +static char __pyx_doc_6mtrand_11RandomState_weibull[] = "Weibull distribution.\n\n weibull(a, size=None)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_weibull(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_a = 0; + PyObject *__pyx_v_size = 0; + PyArrayObject *__pyx_v_oa; + double __pyx_v_fa; + PyObject *__pyx_r; + int __pyx_1; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + PyObject *__pyx_4 = 0; + PyObject *__pyx_5 = 0; + static char *__pyx_argnames[] = {"a","size",0}; + __pyx_v_size = __pyx_k32; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "O|O", __pyx_argnames, &__pyx_v_a, &__pyx_v_size)) return 0; + Py_INCREF(__pyx_v_self); + Py_INCREF(__pyx_v_a); + Py_INCREF(__pyx_v_size); + __pyx_v_oa = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1013 */ + __pyx_v_fa = PyFloat_AsDouble(__pyx_v_a); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1014 */ + __pyx_1 = (!PyErr_Occurred()); 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if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1089; goto __pyx_L1;} + __pyx_r = __pyx_5; + __pyx_5 = 0; + goto __pyx_L0; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + Py_XDECREF(__pyx_4); + Py_XDECREF(__pyx_5); + __Pyx_AddTraceback("mtrand.RandomState.gumbel"); + __pyx_r = 0; + __pyx_L0:; + Py_DECREF(__pyx_v_oloc); + Py_DECREF(__pyx_v_oscale); + Py_DECREF(__pyx_v_self); + Py_DECREF(__pyx_v_loc); + Py_DECREF(__pyx_v_scale); + Py_DECREF(__pyx_v_size); + return __pyx_r; +} + +static PyObject *__pyx_k117p; +static PyObject *__pyx_k118p; + +static char (__pyx_k117[]) = "scale <= 0"; +static char (__pyx_k118[]) = "scale <= 0"; + +static PyObject *__pyx_f_6mtrand_11RandomState_logistic(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_logistic[] = "Logistic distribution.\n \n logistic(loc=0.0, scale=1.0, size=None)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_logistic(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_loc = 0; 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goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1104 */ + __pyx_2 = __pyx_f_6mtrand_cont2_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_logistic,__pyx_v_size,__pyx_v_floc,__pyx_v_fscale); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1104; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1106 */ + PyErr_Clear(); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1107 */ + __pyx_3 = PyArray_FROM_OTF(__pyx_v_loc,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1107; goto __pyx_L1;} + if (!__Pyx_TypeTest(__pyx_3, __pyx_ptype_6mtrand_ndarray)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1107; goto __pyx_L1;} + Py_DECREF(((PyObject *)__pyx_v_oloc)); + __pyx_v_oloc = ((PyArrayObject *)__pyx_3); 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_4 = PyFloat_FromDouble(0.0); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + __pyx_5 = PyTuple_New(2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + Py_INCREF(((PyObject *)__pyx_v_oscale)); + PyTuple_SET_ITEM(__pyx_5, 0, ((PyObject *)__pyx_v_oscale)); + PyTuple_SET_ITEM(__pyx_5, 1, __pyx_4); + __pyx_4 = 0; + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_5); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_5); __pyx_5 = 0; + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_4); + __pyx_4 = 0; + __pyx_5 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyObject_IsTrue(__pyx_5); if (__pyx_1 < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1109; goto __pyx_L1;} + Py_DECREF(__pyx_5); __pyx_5 = 0; + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1110 */ + __pyx_4 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; goto __pyx_L1;} + Py_INCREF(__pyx_k118p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k118p); + __pyx_2 = PyObject_CallObject(__pyx_4, __pyx_3); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_2, 0, 0); + Py_DECREF(__pyx_2); __pyx_2 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1110; goto __pyx_L1;} + goto __pyx_L4; + } + __pyx_L4:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1111 */ + __pyx_5 = __pyx_f_6mtrand_cont2_array(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_logistic,__pyx_v_size,__pyx_v_oloc,__pyx_v_oscale); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1111; goto __pyx_L1;} + __pyx_r = __pyx_5; + __pyx_5 = 0; + goto __pyx_L0; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + Py_XDECREF(__pyx_4); + Py_XDECREF(__pyx_5); + __Pyx_AddTraceback("mtrand.RandomState.logistic"); + __pyx_r = 0; + __pyx_L0:; + Py_DECREF(__pyx_v_oloc); + Py_DECREF(__pyx_v_oscale); + Py_DECREF(__pyx_v_self); + Py_DECREF(__pyx_v_loc); + Py_DECREF(__pyx_v_scale); + Py_DECREF(__pyx_v_size); + return __pyx_r; +} + +static PyObject *__pyx_k119p; +static PyObject *__pyx_k120p; + +static char (__pyx_k119[]) = "sigma <= 0"; +static char (__pyx_k120[]) = "sigma <= 0.0"; + +static PyObject *__pyx_f_6mtrand_11RandomState_lognormal(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_lognormal[] = "Log-normal distribution.\n \n Note that the mean parameter is not the mean of this distribution, but \n the underlying normal distribution.\n \n lognormal(mean, sigma) <=> exp(normal(mean, sigma))\n \n lognormal(mean=0.0, sigma=1.0, size=None)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_lognormal(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_mean = 0; + PyObject *__pyx_v_sigma = 0; + PyObject *__pyx_v_size = 0; + PyArrayObject *__pyx_v_omean; + PyArrayObject *__pyx_v_osigma; + double __pyx_v_fmean; + double __pyx_v_fsigma; + PyObject *__pyx_r; + int __pyx_1; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + PyObject *__pyx_4 = 0; + PyObject *__pyx_5 = 0; + static char *__pyx_argnames[] = {"mean","sigma","size",0}; + __pyx_v_mean = __pyx_k43; + __pyx_v_sigma = __pyx_k44; + __pyx_v_size = __pyx_k45; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "|OOO", __pyx_argnames, &__pyx_v_mean, &__pyx_v_sigma, &__pyx_v_size)) return 0; + Py_INCREF(__pyx_v_self); + Py_INCREF(__pyx_v_mean); + Py_INCREF(__pyx_v_sigma); + Py_INCREF(__pyx_v_size); + __pyx_v_omean = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); + __pyx_v_osigma = ((PyArrayObject *)Py_None); Py_INCREF(Py_None); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1126 */ + __pyx_v_fmean = PyFloat_AsDouble(__pyx_v_mean); 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__pyx_lineno = 1136; goto __pyx_L1;} + Py_DECREF(((PyObject *)__pyx_v_omean)); + __pyx_v_omean = ((PyArrayObject *)__pyx_3); + __pyx_3 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1137 */ + __pyx_4 = PyArray_FROM_OTF(__pyx_v_sigma,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1137; goto __pyx_L1;} + if (!__Pyx_TypeTest(__pyx_4, __pyx_ptype_6mtrand_ndarray)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1137; goto __pyx_L1;} + Py_DECREF(((PyObject *)__pyx_v_osigma)); + __pyx_v_osigma = ((PyArrayObject *)__pyx_4); + __pyx_4 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1138 */ + __pyx_2 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + __pyx_3 = PyObject_GetAttr(__pyx_2, __pyx_n_any); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_4 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_4, __pyx_n_less_equal); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_4 = PyFloat_FromDouble(0.0); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + __pyx_5 = PyTuple_New(2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + Py_INCREF(((PyObject *)__pyx_v_osigma)); + PyTuple_SET_ITEM(__pyx_5, 0, ((PyObject *)__pyx_v_osigma)); + PyTuple_SET_ITEM(__pyx_5, 1, __pyx_4); + __pyx_4 = 0; + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_5); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_5); __pyx_5 = 0; + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1138; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_4); + __pyx_4 = 0; 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__pyx_lineno = 1154; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1154; goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1155 */ + __pyx_2 = __pyx_f_6mtrand_cont1_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_rayleigh,__pyx_v_size,__pyx_v_fscale); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1155; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1157 */ + PyErr_Clear(); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1159 */ + __pyx_3 = PyArray_FROM_OTF(__pyx_v_scale,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1159; goto __pyx_L1;} + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_3))); + Py_DECREF(((PyObject *)__pyx_v_oscale)); + __pyx_v_oscale = ((PyArrayObject *)__pyx_3); + Py_DECREF(__pyx_3); __pyx_3 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1160 */ + __pyx_4 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1160; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_4, __pyx_n_any); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1160; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_3 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1160; goto __pyx_L1;} + __pyx_4 = PyObject_GetAttr(__pyx_3, __pyx_n_less_equal); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1160; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyFloat_FromDouble(0.0); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1160; goto __pyx_L1;} + __pyx_5 = PyTuple_New(2); 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1179; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1181 */ + PyErr_Clear(); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1182 */ + __pyx_3 = PyArray_FROM_OTF(__pyx_v_mean,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; goto __pyx_L1;} + if (!__Pyx_TypeTest(__pyx_3, __pyx_ptype_6mtrand_ndarray)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1182; goto __pyx_L1;} + Py_DECREF(((PyObject *)__pyx_v_omean)); + __pyx_v_omean = ((PyArrayObject *)__pyx_3); + __pyx_3 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1183 */ + __pyx_4 = PyArray_FROM_OTF(__pyx_v_scale,NPY_DOUBLE,NPY_ALIGNED); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1183; goto __pyx_L1;} + if (!__Pyx_TypeTest(__pyx_4, __pyx_ptype_6mtrand_ndarray)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1183; goto __pyx_L1;} + Py_DECREF(((PyObject *)__pyx_v_oscale)); + __pyx_v_oscale = ((PyArrayObject *)__pyx_4); + __pyx_4 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1184 */ + __pyx_2 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + __pyx_3 = PyObject_GetAttr(__pyx_2, __pyx_n_any); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_4 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_4, __pyx_n_less_equal); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_4 = PyFloat_FromDouble(0.0); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + __pyx_5 = PyTuple_New(2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_INCREF(((PyObject *)__pyx_v_omean)); + PyTuple_SET_ITEM(__pyx_5, 0, ((PyObject *)__pyx_v_omean)); + PyTuple_SET_ITEM(__pyx_5, 1, __pyx_4); + __pyx_4 = 0; + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_5); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_5); __pyx_5 = 0; + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_4); + __pyx_4 = 0; + __pyx_5 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyObject_IsTrue(__pyx_5); if (__pyx_1 < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1184; goto __pyx_L1;} + Py_DECREF(__pyx_5); __pyx_5 = 0; + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1185 */ + __pyx_4 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); 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if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1312; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_4); __pyx_4 = 0; + __pyx_1 = PyObject_IsTrue(__pyx_5); if (__pyx_1 < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1312; goto __pyx_L1;} + Py_DECREF(__pyx_5); __pyx_5 = 0; + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1313 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1313; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1313; goto __pyx_L1;} + Py_INCREF(__pyx_k146p); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_k146p); + __pyx_4 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1313; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; 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goto __pyx_L1;} + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1383 */ + __pyx_2 = PyInt_FromLong(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1383; goto __pyx_L1;} + if (PyObject_Cmp(__pyx_v_nbad, __pyx_2, &__pyx_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1383; goto __pyx_L1;} + __pyx_1 = __pyx_1 < 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + if (__pyx_1) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1384 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1384; goto __pyx_L1;} + __pyx_4 = PyTuple_New(1); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1384; goto __pyx_L1;} + Py_INCREF(__pyx_k154p); + PyTuple_SET_ITEM(__pyx_4, 0, __pyx_k154p); + __pyx_2 = PyObject_CallObject(__pyx_3, __pyx_4); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1384; goto __pyx_L1;} + Py_DECREF(__pyx_3); 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goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1388; goto __pyx_L1;} + Py_INCREF(__pyx_k156p); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_k156p); + __pyx_4 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1388; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_4, 0, 0); + Py_DECREF(__pyx_4); __pyx_4 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1388; goto __pyx_L1;} + goto __pyx_L6; + } + __pyx_L6:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1389 */ + __pyx_2 = __pyx_f_6mtrand_discnmN_array_sc(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,rk_hypergeometric,__pyx_v_size,__pyx_v_lngood,__pyx_v_lnbad,__pyx_v_lnsample); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1389; goto __pyx_L1;} + __pyx_r = __pyx_2; + __pyx_2 = 0; + goto __pyx_L0; + goto __pyx_L2; + } + __pyx_L2:; 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if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1397; goto __pyx_L1;} + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_2))); + Py_DECREF(((PyObject *)__pyx_v_onsample)); + __pyx_v_onsample = ((PyArrayObject *)__pyx_2); + Py_DECREF(__pyx_2); __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1398 */ + __pyx_3 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1398; goto __pyx_L1;} + __pyx_4 = PyObject_GetAttr(__pyx_3, __pyx_n_any); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1398; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_2 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1398; goto __pyx_L1;} + __pyx_3 = PyObject_GetAttr(__pyx_2, __pyx_n_less); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1398; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_2 = PyInt_FromLong(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1456; goto __pyx_L1;} + Py_DECREF(__pyx_v_shape); + __pyx_v_shape = __pyx_1; + __pyx_1 = 0; + goto __pyx_L2; + } + /*else*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1458 */ + Py_INCREF(__pyx_v_size); + Py_DECREF(__pyx_v_shape); + __pyx_v_shape = __pyx_v_size; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1459 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_len); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1459; goto __pyx_L1;} + __pyx_2 = PyObject_GetAttr(__pyx_v_mean, __pyx_n_shape); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1459; goto __pyx_L1;} + __pyx_1 = PyTuple_New(1); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1459; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_1, 0, __pyx_2); + __pyx_2 = 0; + __pyx_2 = PyObject_CallObject(__pyx_3, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1459; 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if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1461; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + if (PyObject_Cmp(__pyx_1, __pyx_5, &__pyx_4) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1461; goto __pyx_L1;} + __pyx_4 = __pyx_4 != 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_5); __pyx_5 = 0; + } + if (__pyx_4) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1462 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_ValueError); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1462; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1462; goto __pyx_L1;} + Py_INCREF(__pyx_k166p); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_k166p); + __pyx_1 = PyObject_CallObject(__pyx_3, __pyx_2); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1462; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __Pyx_Raise(__pyx_1, 0, 0); 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1468; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_v_final_shape); + __pyx_v_final_shape = __pyx_1; + __pyx_1 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1469 */ + __pyx_5 = PyObject_GetAttr(__pyx_v_final_shape, __pyx_n_append); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1469; goto __pyx_L1;} + __pyx_3 = PyObject_GetAttr(__pyx_v_mean, __pyx_n_shape); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1469; goto __pyx_L1;} + __pyx_2 = PyInt_FromLong(0); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1469; goto __pyx_L1;} + __pyx_1 = PyObject_GetItem(__pyx_3, __pyx_2); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1469; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1469; 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if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1514; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __Pyx_Raise(__pyx_1, 0, 0); + Py_DECREF(__pyx_1); __pyx_1 = 0; + {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1514; goto __pyx_L1;} + goto __pyx_L2; + } + __pyx_L2:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1516 */ + __pyx_5 = __pyx_v_size == Py_None; + if (__pyx_5) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1517 */ + __pyx_2 = PyInt_FromLong(__pyx_v_d); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1517; goto __pyx_L1;} + __pyx_3 = PyTuple_New(1); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1517; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_2); + __pyx_2 = 0; + Py_DECREF(__pyx_v_shape); + __pyx_v_shape = __pyx_3; + __pyx_3 = 0; + goto __pyx_L3; + } + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_type); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; 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A \n Dirichlet-distributed random variable can be seen as a multivariate \n generalization of a Beta distribution. Dirichlet pdf is the conjugate\n prior of a multinomial in Bayesian inference.\n \n :Parameters:\n alpha : array\n parameter of the distribution (k dimension\n for sample of dimension k).\n size : array\n number of samples to draw.\n\n $X \approx \\prod_{i=1}^{k}{x^{\alpha_i-1}_i}$\n \n Uses the following property for computation: for each dimension,\n draw a random sample y_i from a standard gamma generator of shape \n alpha_i, then X = \frac{1}{\\sum_{i=1}^k{y_i}} (y_1, ..., y_n) is \n Dirichlet distributed. \n \n Reference:\n - David Mc Kay : Information Theory, inference and Learning \n algorithms, chapter 23. the book is available for free at \n http://www.inference.phy.cam.ac.uk/mackay/\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_dirichlet(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_alpha = 0; + PyObject *__pyx_v_size = 0; + long __pyx_v_k; + long __pyx_v_totsize; + PyArrayObject *__pyx_v_alpha_arr; + PyArrayObject 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(!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1604; goto __pyx_L1;} + Py_INCREF(__pyx_v_size); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_size); + __pyx_3 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1604; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_int); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1604; goto __pyx_L1;} + __pyx_5 = __pyx_3 == __pyx_1; + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + if (__pyx_5) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1605 */ + __pyx_2 = PyInt_FromLong(__pyx_v_k); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1605; goto __pyx_L1;} + __pyx_3 = PyTuple_New(2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1605; goto __pyx_L1;} + Py_INCREF(__pyx_v_size); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_v_size); + 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__pyx_2 = PyObject_GetAttr(__pyx_1, __pyx_n_zeros); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1609; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_3 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1609; goto __pyx_L1;} + __pyx_1 = PyObject_GetAttr(__pyx_3, __pyx_n_float64); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1609; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyTuple_New(2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1609; goto __pyx_L1;} + Py_INCREF(__pyx_v_shape); + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_v_shape); + PyTuple_SET_ITEM(__pyx_3, 1, __pyx_1); + __pyx_1 = 0; + __pyx_1 = PyObject_CallObject(__pyx_2, __pyx_3); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1609; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_v_diric); + __pyx_v_diric = __pyx_1; + __pyx_1 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1610 */ + Py_INCREF(((PyObject *)((PyArrayObject *)__pyx_v_diric))); + Py_DECREF(((PyObject *)__pyx_v_val_arr)); + __pyx_v_val_arr = ((PyArrayObject *)__pyx_v_diric); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1611 */ + __pyx_v_val_data = ((double (*))__pyx_v_val_arr->data); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1613 */ + __pyx_v_i = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1614 */ + __pyx_v_totsize = PyArray_SIZE(__pyx_v_val_arr); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1615 */ + while (1) { + __pyx_5 = (__pyx_v_i < __pyx_v_totsize); + if (!__pyx_5) break; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1616 */ + __pyx_v_acc = 0.0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1617 */ + for (__pyx_v_j = 0; __pyx_v_j < __pyx_v_k; ++__pyx_v_j) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1618 */ + (__pyx_v_val_data[(__pyx_v_i + __pyx_v_j)]) = rk_standard_gamma(((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state,(__pyx_v_alpha_data[__pyx_v_j])); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1619 */ + __pyx_v_acc = (__pyx_v_acc + (__pyx_v_val_data[(__pyx_v_i + __pyx_v_j)])); + } + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1620 */ + __pyx_v_invacc = (1 / __pyx_v_acc); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1621 */ + for (__pyx_v_j = 0; __pyx_v_j < __pyx_v_k; ++__pyx_v_j) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1622 */ + (__pyx_v_val_data[(__pyx_v_i + __pyx_v_j)]) = ((__pyx_v_val_data[(__pyx_v_i + __pyx_v_j)]) * __pyx_v_invacc); + } + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1623 */ + __pyx_v_i = (__pyx_v_i + __pyx_v_k); + } + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1625 */ + Py_INCREF(__pyx_v_diric); + __pyx_r = __pyx_v_diric; + goto __pyx_L0; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_1); + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + __Pyx_AddTraceback("mtrand.RandomState.dirichlet"); + __pyx_r = 0; + __pyx_L0:; + Py_DECREF(__pyx_v_alpha_arr); + Py_DECREF(__pyx_v_val_arr); + Py_DECREF(__pyx_v_shape); + Py_DECREF(__pyx_v_diric); + Py_DECREF(__pyx_v_self); + Py_DECREF(__pyx_v_alpha); + Py_DECREF(__pyx_v_size); + return __pyx_r; +} + +static PyObject *__pyx_n_hasattr; +static PyObject *__pyx_n_copy; + + +static PyObject *__pyx_f_6mtrand_11RandomState_shuffle(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_shuffle[] = "Modify a sequence in-place by shuffling its contents.\n \n shuffle(x)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_shuffle(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_x = 0; + long __pyx_v_i; + long __pyx_v_j; + int __pyx_v_copy; + PyObject *__pyx_r; + PyObject *__pyx_1 = 0; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + long __pyx_4; + int __pyx_5; + static char *__pyx_argnames[] = {"x",0}; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "O", __pyx_argnames, &__pyx_v_x)) return 0; + Py_INCREF(__pyx_v_self); + Py_INCREF(__pyx_v_x); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1636 */ + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_len); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + __pyx_2 = PyTuple_New(1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + Py_INCREF(__pyx_v_x); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_x); + __pyx_3 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyInt_FromLong(1); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + __pyx_2 = PyNumber_Subtract(__pyx_3, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_4 = PyInt_AsLong(__pyx_2); if (PyErr_Occurred()) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1636; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_v_i = __pyx_4; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1637 */ + /*try:*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1638 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_len); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + __pyx_1 = PyInt_FromLong(0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PyTuple_New(1); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + PyTuple_SET_ITEM(__pyx_1, 0, __pyx_2); + __pyx_2 = 0; + __pyx_2 = PyObject_CallObject(__pyx_3, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_4 = PyInt_AsLong(__pyx_2); if (PyErr_Occurred()) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1638; goto __pyx_L2;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_v_j = __pyx_4; + } + goto __pyx_L3; + __pyx_L2:; + Py_XDECREF(__pyx_3); __pyx_3 = 0; + Py_XDECREF(__pyx_1); __pyx_1 = 0; + Py_XDECREF(__pyx_2); __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1639 */ + /*except:*/ { + __Pyx_AddTraceback("mtrand.shuffle"); + __pyx_3 = __Pyx_GetExcValue(); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1639; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1640 */ + __pyx_v_j = 0; + goto __pyx_L3; + } + __pyx_L3:; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1642 */ + __pyx_5 = (__pyx_v_j == 0); + if (__pyx_5) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1644 */ + while (1) { + __pyx_5 = (__pyx_v_i > 0); + if (!__pyx_5) break; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1645 */ + __pyx_v_j = rk_interval(__pyx_v_i,((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1646 */ + __pyx_1 = PyInt_FromLong(__pyx_v_j); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_3 = PyInt_FromLong(__pyx_v_i); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + __pyx_1 = PyObject_GetItem(__pyx_v_x, __pyx_3); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyInt_FromLong(__pyx_v_i); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_3, __pyx_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_2 = PyInt_FromLong(__pyx_v_j); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_2, __pyx_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1646; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1647 */ + __pyx_v_i = (__pyx_v_i - 1); + } + goto __pyx_L4; + } + /*else*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1650 */ + __pyx_3 = __Pyx_GetName(__pyx_b, __pyx_n_hasattr); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + __pyx_1 = PyInt_FromLong(0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PyTuple_New(2); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_1, 0, __pyx_2); + Py_INCREF(__pyx_n_copy); + PyTuple_SET_ITEM(__pyx_1, 1, __pyx_n_copy); + __pyx_2 = 0; + __pyx_2 = PyObject_CallObject(__pyx_3, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_5 = PyInt_AsLong(__pyx_2); if (PyErr_Occurred()) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1650; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_v_copy = __pyx_5; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1651 */ + __pyx_5 = __pyx_v_copy; + if (__pyx_5) { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1652 */ + while (1) { + __pyx_5 = (__pyx_v_i > 0); + if (!__pyx_5) break; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1653 */ + __pyx_v_j = rk_interval(__pyx_v_i,((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1654 */ + __pyx_3 = PyInt_FromLong(__pyx_v_j); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + __pyx_1 = PyObject_GetItem(__pyx_v_x, __pyx_3); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_2 = PyObject_GetAttr(__pyx_1, __pyx_n_copy); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_3 = PyObject_CallObject(__pyx_2, 0); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyInt_FromLong(__pyx_v_i); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PyObject_GetAttr(__pyx_2, __pyx_n_copy); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_2 = PyObject_CallObject(__pyx_1, 0); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PyInt_FromLong(__pyx_v_i); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_1, __pyx_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyInt_FromLong(__pyx_v_j); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_3, __pyx_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1654; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1655 */ + __pyx_v_i = (__pyx_v_i - 1); + } + goto __pyx_L7; + } + /*else*/ { + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1657 */ + while (1) { + __pyx_5 = (__pyx_v_i > 0); + if (!__pyx_5) break; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1658 */ + __pyx_v_j = rk_interval(__pyx_v_i,((struct __pyx_obj_6mtrand_RandomState *)__pyx_v_self)->internal_state); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1659 */ + __pyx_1 = PyInt_FromLong(__pyx_v_j); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_3 = PySequence_GetSlice(__pyx_2, 0, 0x7fffffff); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_1 = PyInt_FromLong(__pyx_v_i); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + __pyx_2 = PyObject_GetItem(__pyx_v_x, __pyx_1); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + __pyx_1 = PySequence_GetSlice(__pyx_2, 0, 0x7fffffff); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_2 = PyInt_FromLong(__pyx_v_i); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_2, __pyx_3) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_2); __pyx_2 = 0; + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyInt_FromLong(__pyx_v_j); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + if (PyObject_SetItem(__pyx_v_x, __pyx_3, __pyx_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1659; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + Py_DECREF(__pyx_1); __pyx_1 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1660 */ + __pyx_v_i = (__pyx_v_i - 1); + } + } + __pyx_L7:; + } + __pyx_L4:; + + __pyx_r = Py_None; Py_INCREF(Py_None); + goto __pyx_L0; + __pyx_L1:; + Py_XDECREF(__pyx_1); + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + __Pyx_AddTraceback("mtrand.RandomState.shuffle"); + __pyx_r = 0; + __pyx_L0:; + Py_DECREF(__pyx_v_self); + Py_DECREF(__pyx_v_x); + return __pyx_r; +} + +static PyObject *__pyx_n_integer; +static PyObject *__pyx_n_arange; + +static PyObject *__pyx_f_6mtrand_11RandomState_permutation(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/ +static char __pyx_doc_6mtrand_11RandomState_permutation[] = "Given an integer, return a shuffled sequence of integers >= 0 and \n < x; given a sequence, return a shuffled array copy.\n\n permutation(x)\n "; +static PyObject *__pyx_f_6mtrand_11RandomState_permutation(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) { + PyObject *__pyx_v_x = 0; + PyObject *__pyx_v_arr; + PyObject *__pyx_r; + PyObject *__pyx_1 = 0; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + PyObject *__pyx_4 = 0; + int __pyx_5; + static char *__pyx_argnames[] = {"x",0}; + if (!PyArg_ParseTupleAndKeywords(__pyx_args, __pyx_kwds, "O", __pyx_argnames, &__pyx_v_x)) return 0; + Py_INCREF(__pyx_v_self); + Py_INCREF(__pyx_v_x); + __pyx_v_arr = Py_None; Py_INCREF(Py_None); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1668 */ + __pyx_1 = __Pyx_GetName(__pyx_b, __pyx_n_isinstance); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + __pyx_2 = __Pyx_GetName(__pyx_b, __pyx_n_int); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + __pyx_3 = __Pyx_GetName(__pyx_m, __pyx_n__sp); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + __pyx_4 = PyObject_GetAttr(__pyx_3, __pyx_n_integer); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + Py_DECREF(__pyx_3); __pyx_3 = 0; + __pyx_3 = PyTuple_New(2); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + PyTuple_SET_ITEM(__pyx_3, 0, __pyx_2); + PyTuple_SET_ITEM(__pyx_3, 1, __pyx_4); + __pyx_2 = 0; + __pyx_4 = 0; + __pyx_2 = PyTuple_New(2); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + Py_INCREF(__pyx_v_x); + PyTuple_SET_ITEM(__pyx_2, 0, __pyx_v_x); + PyTuple_SET_ITEM(__pyx_2, 1, __pyx_3); + __pyx_3 = 0; + __pyx_4 = PyObject_CallObject(__pyx_1, __pyx_2); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + Py_DECREF(__pyx_2); __pyx_2 = 0; + __pyx_5 = PyObject_IsTrue(__pyx_4); if (__pyx_5 < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1668; 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__pyx_doc_6mtrand_11RandomState_gamma}, + {"f", (PyCFunction)__pyx_f_6mtrand_11RandomState_f, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_f}, + {"noncentral_f", (PyCFunction)__pyx_f_6mtrand_11RandomState_noncentral_f, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_noncentral_f}, + {"chisquare", (PyCFunction)__pyx_f_6mtrand_11RandomState_chisquare, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_chisquare}, + {"noncentral_chisquare", (PyCFunction)__pyx_f_6mtrand_11RandomState_noncentral_chisquare, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_noncentral_chisquare}, + {"standard_cauchy", (PyCFunction)__pyx_f_6mtrand_11RandomState_standard_cauchy, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_standard_cauchy}, + {"standard_t", (PyCFunction)__pyx_f_6mtrand_11RandomState_standard_t, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_standard_t}, + {"vonmises", (PyCFunction)__pyx_f_6mtrand_11RandomState_vonmises, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_vonmises}, + {"pareto", (PyCFunction)__pyx_f_6mtrand_11RandomState_pareto, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_pareto}, + {"weibull", (PyCFunction)__pyx_f_6mtrand_11RandomState_weibull, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_weibull}, + {"power", (PyCFunction)__pyx_f_6mtrand_11RandomState_power, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_power}, + {"laplace", (PyCFunction)__pyx_f_6mtrand_11RandomState_laplace, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_laplace}, + {"gumbel", (PyCFunction)__pyx_f_6mtrand_11RandomState_gumbel, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_gumbel}, + {"logistic", (PyCFunction)__pyx_f_6mtrand_11RandomState_logistic, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_logistic}, + {"lognormal", (PyCFunction)__pyx_f_6mtrand_11RandomState_lognormal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_lognormal}, + {"rayleigh", (PyCFunction)__pyx_f_6mtrand_11RandomState_rayleigh, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_rayleigh}, + {"wald", (PyCFunction)__pyx_f_6mtrand_11RandomState_wald, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_wald}, + {"triangular", (PyCFunction)__pyx_f_6mtrand_11RandomState_triangular, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_triangular}, + {"binomial", (PyCFunction)__pyx_f_6mtrand_11RandomState_binomial, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_binomial}, + {"negative_binomial", (PyCFunction)__pyx_f_6mtrand_11RandomState_negative_binomial, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_negative_binomial}, + {"poisson", (PyCFunction)__pyx_f_6mtrand_11RandomState_poisson, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_poisson}, + {"zipf", (PyCFunction)__pyx_f_6mtrand_11RandomState_zipf, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_zipf}, + {"geometric", (PyCFunction)__pyx_f_6mtrand_11RandomState_geometric, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_geometric}, + {"hypergeometric", (PyCFunction)__pyx_f_6mtrand_11RandomState_hypergeometric, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_hypergeometric}, + {"logseries", (PyCFunction)__pyx_f_6mtrand_11RandomState_logseries, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_logseries}, + {"multivariate_normal", (PyCFunction)__pyx_f_6mtrand_11RandomState_multivariate_normal, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_multivariate_normal}, + {"multinomial", (PyCFunction)__pyx_f_6mtrand_11RandomState_multinomial, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_multinomial}, + {"dirichlet", (PyCFunction)__pyx_f_6mtrand_11RandomState_dirichlet, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_dirichlet}, + {"shuffle", (PyCFunction)__pyx_f_6mtrand_11RandomState_shuffle, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_shuffle}, + {"permutation", (PyCFunction)__pyx_f_6mtrand_11RandomState_permutation, METH_VARARGS|METH_KEYWORDS, __pyx_doc_6mtrand_11RandomState_permutation}, + {0, 0, 0, 0} +}; + +static PyNumberMethods __pyx_tp_as_number_RandomState = { + 0, /*nb_add*/ + 0, /*nb_subtract*/ + 0, /*nb_multiply*/ + 0, /*nb_divide*/ + 0, /*nb_remainder*/ + 0, /*nb_divmod*/ + 0, /*nb_power*/ + 0, /*nb_negative*/ + 0, /*nb_positive*/ + 0, /*nb_absolute*/ + 0, /*nb_nonzero*/ + 0, /*nb_invert*/ + 0, /*nb_lshift*/ + 0, /*nb_rshift*/ + 0, /*nb_and*/ + 0, /*nb_xor*/ + 0, /*nb_or*/ + 0, /*nb_coerce*/ + 0, /*nb_int*/ + 0, /*nb_long*/ + 0, /*nb_float*/ + 0, /*nb_oct*/ + 0, /*nb_hex*/ + 0, /*nb_inplace_add*/ + 0, /*nb_inplace_subtract*/ + 0, /*nb_inplace_multiply*/ + 0, /*nb_inplace_divide*/ + 0, /*nb_inplace_remainder*/ + 0, /*nb_inplace_power*/ + 0, /*nb_inplace_lshift*/ + 0, /*nb_inplace_rshift*/ + 0, /*nb_inplace_and*/ + 0, /*nb_inplace_xor*/ + 0, /*nb_inplace_or*/ + 0, /*nb_floor_divide*/ + 0, /*nb_true_divide*/ + 0, /*nb_inplace_floor_divide*/ + 0, /*nb_inplace_true_divide*/ +}; + +static PySequenceMethods __pyx_tp_as_sequence_RandomState = { + 0, /*sq_length*/ + 0, /*sq_concat*/ + 0, /*sq_repeat*/ + 0, /*sq_item*/ + 0, /*sq_slice*/ + 0, /*sq_ass_item*/ + 0, /*sq_ass_slice*/ + 0, /*sq_contains*/ + 0, /*sq_inplace_concat*/ + 0, /*sq_inplace_repeat*/ +}; + +static PyMappingMethods __pyx_tp_as_mapping_RandomState = { + 0, /*mp_length*/ + 0, /*mp_subscript*/ + 0, /*mp_ass_subscript*/ +}; + +static PyBufferProcs __pyx_tp_as_buffer_RandomState = { + 0, /*bf_getreadbuffer*/ + 0, /*bf_getwritebuffer*/ + 0, /*bf_getsegcount*/ + 0, /*bf_getcharbuffer*/ +}; + +PyTypeObject __pyx_type_6mtrand_RandomState = { + PyObject_HEAD_INIT(0) + 0, /*ob_size*/ + "mtrand.RandomState", /*tp_name*/ + sizeof(struct __pyx_obj_6mtrand_RandomState), /*tp_basicsize*/ + 0, /*tp_itemsize*/ + __pyx_tp_dealloc_6mtrand_RandomState, /*tp_dealloc*/ + 0, /*tp_print*/ + 0, /*tp_getattr*/ + 0, /*tp_setattr*/ + 0, /*tp_compare*/ + 0, /*tp_repr*/ + &__pyx_tp_as_number_RandomState, /*tp_as_number*/ + &__pyx_tp_as_sequence_RandomState, /*tp_as_sequence*/ + &__pyx_tp_as_mapping_RandomState, /*tp_as_mapping*/ + 0, /*tp_hash*/ + 0, /*tp_call*/ + 0, /*tp_str*/ + 0, /*tp_getattro*/ + 0, /*tp_setattro*/ + &__pyx_tp_as_buffer_RandomState, /*tp_as_buffer*/ + Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_BASETYPE|Py_TPFLAGS_HAVE_GC, /*tp_flags*/ + "Container for the Mersenne Twister PRNG.\n\n Constructor\n -----------\n RandomState(seed=None): initializes the PRNG with the given seed. See the\n seed() method for details.\n\n Distribution Methods\n -----------------\n RandomState exposes a number of methods for generating random numbers drawn\n from a variety of probability distributions. In addition to the\n distribution-specific arguments, each method takes a keyword argument\n size=None. If size is None, then a single value is generated and returned.\n If size is an integer, then a 1-D numpy array filled with generated values\n is returned. If size is a tuple, then a numpy array with that shape is\n filled and returned.\n ", /*tp_doc*/ + __pyx_tp_traverse_6mtrand_RandomState, /*tp_traverse*/ + __pyx_tp_clear_6mtrand_RandomState, /*tp_clear*/ + 0, /*tp_richcompare*/ + 0, /*tp_weaklistoffset*/ + 0, /*tp_iter*/ + 0, /*tp_iternext*/ + __pyx_methods_6mtrand_RandomState, /*tp_methods*/ + 0, /*tp_members*/ + 0, /*tp_getset*/ + 0, /*tp_base*/ + 0, /*tp_dict*/ + 0, /*tp_descr_get*/ + 0, /*tp_descr_set*/ + 0, /*tp_dictoffset*/ + __pyx_f_6mtrand_11RandomState___init__, /*tp_init*/ + 0, /*tp_alloc*/ + __pyx_tp_new_6mtrand_RandomState, /*tp_new*/ + 0, /*tp_free*/ + 0, /*tp_is_gc*/ + 0, /*tp_bases*/ + 0, /*tp_mro*/ + 0, /*tp_cache*/ + 0, /*tp_subclasses*/ + 0, /*tp_weaklist*/ +}; + +static struct PyMethodDef __pyx_methods[] = { + {0, 0, 0, 0} +}; + +static void __pyx_init_filenames(void); /*proto*/ + +PyMODINIT_FUNC initmtrand(void); /*proto*/ +PyMODINIT_FUNC initmtrand(void) { + PyObject *__pyx_1 = 0; + PyObject *__pyx_2 = 0; + PyObject *__pyx_3 = 0; + PyObject *__pyx_4 = 0; + PyObject *__pyx_5 = 0; + PyObject *__pyx_6 = 0; + PyObject *__pyx_7 = 0; + PyObject *__pyx_8 = 0; + PyObject *__pyx_9 = 0; + PyObject *__pyx_10 = 0; + PyObject *__pyx_11 = 0; + PyObject *__pyx_12 = 0; + PyObject *__pyx_13 = 0; + PyObject *__pyx_14 = 0; + PyObject *__pyx_15 = 0; + PyObject *__pyx_16 = 0; + PyObject *__pyx_17 = 0; + PyObject *__pyx_18 = 0; + __pyx_init_filenames(); + __pyx_m = Py_InitModule4("mtrand", __pyx_methods, 0, 0, PYTHON_API_VERSION); + if (!__pyx_m) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; goto __pyx_L1;}; + __pyx_b = PyImport_AddModule("__builtin__"); + if (!__pyx_b) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; goto __pyx_L1;}; + if (PyObject_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; goto __pyx_L1;}; + if (__Pyx_InternStrings(__pyx_intern_tab) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; goto __pyx_L1;}; + if (__Pyx_InitStrings(__pyx_string_tab) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 25; goto __pyx_L1;}; + __pyx_ptype_6mtrand_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr)); if (!__pyx_ptype_6mtrand_dtype) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 74; goto __pyx_L1;} + __pyx_ptype_6mtrand_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject)); if (!__pyx_ptype_6mtrand_ndarray) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 79; goto __pyx_L1;} + __pyx_ptype_6mtrand_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject)); if (!__pyx_ptype_6mtrand_flatiter) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 88; goto __pyx_L1;} + __pyx_ptype_6mtrand_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject)); if (!__pyx_ptype_6mtrand_broadcast) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 94; goto __pyx_L1;} + if (PyType_Ready(&__pyx_type_6mtrand_RandomState) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 468; goto __pyx_L1;} + if (PyObject_SetAttrString(__pyx_m, "RandomState", (PyObject *)&__pyx_type_6mtrand_RandomState) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 468; goto __pyx_L1;} + __pyx_ptype_6mtrand_RandomState = &__pyx_type_6mtrand_RandomState; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":119 */ + import_array(); + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":121 */ + __pyx_1 = __Pyx_Import(__pyx_n_numpy, 0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; goto __pyx_L1;} + if (PyObject_SetAttr(__pyx_m, __pyx_n__sp, __pyx_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; goto __pyx_L1;} + Py_DECREF(__pyx_1); __pyx_1 = 0; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":488 */ + Py_INCREF(Py_None); + __pyx_k2 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":498 */ + Py_INCREF(Py_None); + __pyx_k3 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":564 */ + Py_INCREF(Py_None); + __pyx_k4 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":571 */ + Py_INCREF(Py_None); + __pyx_k5 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":578 */ + Py_INCREF(Py_None); + __pyx_k6 = Py_None; + Py_INCREF(Py_None); + __pyx_k7 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":623 */ + __pyx_1 = PyFloat_FromDouble(0.0); if (!__pyx_1) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 623; goto __pyx_L1;} + __pyx_k8 = __pyx_1; + __pyx_1 = 0; + __pyx_2 = PyFloat_FromDouble(1.0); if (!__pyx_2) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 623; goto __pyx_L1;} + __pyx_k9 = __pyx_2; + __pyx_2 = 0; + Py_INCREF(Py_None); + __pyx_k10 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":676 */ + Py_INCREF(Py_None); + __pyx_k11 = Py_None; + Py_INCREF(Py_None); + __pyx_k12 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":689 */ + Py_INCREF(Py_None); + __pyx_k13 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":696 */ + __pyx_3 = PyFloat_FromDouble(0.0); if (!__pyx_3) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 696; goto __pyx_L1;} + __pyx_k14 = __pyx_3; + __pyx_3 = 0; + __pyx_4 = PyFloat_FromDouble(1.0); if (!__pyx_4) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 696; goto __pyx_L1;} + __pyx_k15 = __pyx_4; + __pyx_4 = 0; + Py_INCREF(Py_None); + __pyx_k16 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":719 */ + Py_INCREF(Py_None); + __pyx_k17 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":746 */ + __pyx_5 = PyFloat_FromDouble(1.0); if (!__pyx_5) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 746; goto __pyx_L1;} + __pyx_k18 = __pyx_5; + __pyx_5 = 0; + Py_INCREF(Py_None); + __pyx_k19 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":767 */ + Py_INCREF(Py_None); + __pyx_k20 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":774 */ + Py_INCREF(Py_None); + __pyx_k21 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":794 */ + __pyx_6 = PyFloat_FromDouble(1.0); if (!__pyx_6) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 794; goto __pyx_L1;} + __pyx_k22 = __pyx_6; + __pyx_6 = 0; + Py_INCREF(Py_None); + __pyx_k23 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":820 */ + Py_INCREF(Py_None); + __pyx_k24 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":847 */ + Py_INCREF(Py_None); + __pyx_k25 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":883 */ + Py_INCREF(Py_None); + __pyx_k26 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":904 */ + Py_INCREF(Py_None); + __pyx_k27 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":932 */ + Py_INCREF(Py_None); + __pyx_k28 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":939 */ + Py_INCREF(Py_None); + __pyx_k29 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":960 */ + Py_INCREF(Py_None); + __pyx_k30 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":984 */ + Py_INCREF(Py_None); + __pyx_k31 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1005 */ + Py_INCREF(Py_None); + __pyx_k32 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1026 */ + Py_INCREF(Py_None); + __pyx_k33 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1047 */ + __pyx_7 = PyFloat_FromDouble(0.0); if (!__pyx_7) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1047; goto __pyx_L1;} + __pyx_k34 = __pyx_7; + __pyx_7 = 0; + __pyx_8 = PyFloat_FromDouble(1.0); if (!__pyx_8) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1047; goto __pyx_L1;} + __pyx_k35 = __pyx_8; + __pyx_8 = 0; + Py_INCREF(Py_None); + __pyx_k36 = Py_None; + + /* "/Users/dave/Stuff/Projects/numpy/trunk/numpy/random/mtrand/mtrand.pyx":1069 */ + __pyx_9 = PyFloat_FromDouble(0.0); if (!__pyx_9) {__pyx_filename = __pyx_f[0]; 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if (!__pyx_17) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1724; goto __pyx_L1;} + __pyx_18 = PyObject_GetAttr(__pyx_17, __pyx_n_permutation); if (!__pyx_18) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1724; goto __pyx_L1;} + Py_DECREF(__pyx_17); __pyx_17 = 0; + if (PyObject_SetAttr(__pyx_m, __pyx_n_permutation, __pyx_18) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1724; goto __pyx_L1;} + Py_DECREF(__pyx_18); __pyx_18 = 0; + return; + __pyx_L1:; + Py_XDECREF(__pyx_1); + Py_XDECREF(__pyx_2); + Py_XDECREF(__pyx_3); + Py_XDECREF(__pyx_4); + Py_XDECREF(__pyx_5); + Py_XDECREF(__pyx_6); + Py_XDECREF(__pyx_7); + Py_XDECREF(__pyx_8); + Py_XDECREF(__pyx_9); + Py_XDECREF(__pyx_10); + Py_XDECREF(__pyx_11); + Py_XDECREF(__pyx_12); + Py_XDECREF(__pyx_13); + Py_XDECREF(__pyx_14); + Py_XDECREF(__pyx_15); + Py_XDECREF(__pyx_16); + Py_XDECREF(__pyx_17); + Py_XDECREF(__pyx_18); + __Pyx_AddTraceback("mtrand"); +} + +static char *__pyx_filenames[] = { + "mtrand.pyx", + "numpy.pxi", +}; + +/* Runtime support code */ + +static void __pyx_init_filenames(void) { + __pyx_f = __pyx_filenames; +} + +static int __Pyx_GetStarArgs( + PyObject **args, + PyObject **kwds, + char *kwd_list[], + int nargs, + PyObject **args2, + PyObject **kwds2) +{ + PyObject *x = 0, *args1 = 0, *kwds1 = 0; + + if (args2) + *args2 = 0; + if (kwds2) + *kwds2 = 0; + + if (args2) { + args1 = PyTuple_GetSlice(*args, 0, nargs); + if (!args1) + goto bad; + *args2 = PyTuple_GetSlice(*args, nargs, PyTuple_Size(*args)); + if (!*args2) + goto bad; + } + else { + args1 = *args; + Py_INCREF(args1); + } + + if (kwds2) { + if (*kwds) { + char **p; + kwds1 = PyDict_New(); + if (!kwds) + goto bad; + *kwds2 = PyDict_Copy(*kwds); + if (!*kwds2) + goto bad; + for (p = kwd_list; *p; p++) { + x = PyDict_GetItemString(*kwds, *p); + if (x) { + if (PyDict_SetItemString(kwds1, *p, x) < 0) + goto bad; + if (PyDict_DelItemString(*kwds2, *p) < 0) + goto bad; + } + } + } + else { + *kwds2 = PyDict_New(); + if (!*kwds2) + goto bad; + } + } + else { + kwds1 = *kwds; + Py_XINCREF(kwds1); + } + + *args = args1; + *kwds = kwds1; + return 0; +bad: + Py_XDECREF(args1); + Py_XDECREF(kwds1); + if (*args2) { + Py_XDECREF(*args2); + } + if (*kwds2) { + Py_XDECREF(*kwds2); + } + return -1; +} + +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list) { + PyObject *__import__ = 0; + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + __import__ = PyObject_GetAttrString(__pyx_b, "__import__"); + if (!__import__) + goto bad; + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + module = PyObject_CallFunction(__import__, "OOOO", + name, global_dict, empty_dict, list); +bad: + Py_XDECREF(empty_list); + Py_XDECREF(__import__); + Py_XDECREF(empty_dict); + return module; +} + +static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name) { + PyObject *result; + result = PyObject_GetAttr(dict, name); + if (!result) + PyErr_SetObject(PyExc_NameError, name); + return result; +} + +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb) { + Py_XINCREF(type); + Py_XINCREF(value); + Py_XINCREF(tb); + /* First, check the traceback argument, replacing None with NULL. */ + if (tb == Py_None) { + Py_DECREF(tb); + tb = 0; + } + else if (tb != NULL && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + /* Next, replace a missing value with None */ + if (value == NULL) { + value = Py_None; + Py_INCREF(value); + } + /* Next, repeatedly, replace a tuple exception with its first item */ + while (PyTuple_Check(type) && PyTuple_Size(type) > 0) { + PyObject *tmp = type; + type = PyTuple_GET_ITEM(type, 0); + Py_INCREF(type); + Py_DECREF(tmp); + } + if (PyString_Check(type)) { + if (PyErr_Warn(PyExc_DeprecationWarning, + "raising a string exception is deprecated")) + goto raise_error; + } + else if (PyType_Check(type) || PyClass_Check(type)) + ; /*PyErr_NormalizeException(&type, &value, &tb);*/ + else { + /* Raising an instance. The value should be a dummy. */ + if (value != Py_None) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + /* Normalize to raise <class>, <instance> */ + Py_DECREF(value); + value = type; + if (PyInstance_Check(type)) + type = (PyObject*) ((PyInstanceObject*)type)->in_class; + else + type = (PyObject*) type->ob_type; + Py_INCREF(type); + } + PyErr_Restore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} + +static void __Pyx_UnpackError(void) { + PyErr_SetString(PyExc_ValueError, "unpack sequence of wrong size"); +} + +static PyObject *__Pyx_UnpackItem(PyObject *iter) { + PyObject *item; + if (!(item = PyIter_Next(iter))) { + if (!PyErr_Occurred()) + __Pyx_UnpackError(); + } + return item; +} + +static int __Pyx_EndUnpack(PyObject *iter) { + PyObject *item; + if ((item = PyIter_Next(iter))) { + Py_DECREF(item); + __Pyx_UnpackError(); + return -1; + } + else if (!PyErr_Occurred()) + return 0; + else + return -1; +} + +static PyObject *__Pyx_GetExcValue(void) { + PyObject *type = 0, *value = 0, *tb = 0; + PyObject *result = 0; + PyThreadState *tstate = PyThreadState_Get(); + PyErr_Fetch(&type, &value, &tb); + PyErr_NormalizeException(&type, &value, &tb); + if (PyErr_Occurred()) + goto bad; + if (!value) { + value = Py_None; + Py_INCREF(value); + } + Py_XDECREF(tstate->exc_type); + Py_XDECREF(tstate->exc_value); + Py_XDECREF(tstate->exc_traceback); + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + result = value; + Py_XINCREF(result); + type = 0; + value = 0; + tb = 0; +bad: + Py_XDECREF(type); + Py_XDECREF(value); + Py_XDECREF(tb); + return result; +} + +static int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (!type) { + PyErr_Format(PyExc_SystemError, "Missing type object"); + return 0; + } + if (obj == Py_None || PyObject_TypeCheck(obj, type)) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %s to %s", + obj->ob_type->tp_name, type->tp_name); + return 0; +} + +static int __Pyx_InternStrings(__Pyx_InternTabEntry *t) { + while (t->p) { + *t->p = PyString_InternFromString(t->s); + if (!*t->p) + return -1; + ++t; + } + return 0; +} + +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) { + while (t->p) { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + if (!*t->p) + return -1; + ++t; + } + return 0; +} + +static PyTypeObject *__Pyx_ImportType(char *module_name, char *class_name, + long size) +{ + PyObject *py_module_name = 0; + PyObject *py_class_name = 0; + PyObject *py_name_list = 0; + PyObject *py_module = 0; + PyObject *result = 0; + + py_module_name = PyString_FromString(module_name); + if (!py_module_name) + goto bad; + py_class_name = PyString_FromString(class_name); + if (!py_class_name) + goto bad; + py_name_list = PyList_New(1); + if (!py_name_list) + goto bad; + Py_INCREF(py_class_name); + if (PyList_SetItem(py_name_list, 0, py_class_name) < 0) + goto bad; + py_module = __Pyx_Import(py_module_name, py_name_list); + if (!py_module) + goto bad; + result = PyObject_GetAttr(py_module, py_class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%s.%s is not a type object", + module_name, class_name); + goto bad; + } + if (((PyTypeObject *)result)->tp_basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%s.%s does not appear to be the correct type object", + module_name, class_name); + goto bad; + } + goto done; +bad: + Py_XDECREF(result); + result = 0; +done: + Py_XDECREF(py_module_name); + Py_XDECREF(py_class_name); + Py_XDECREF(py_name_list); + return (PyTypeObject *)result; +} + +#include "compile.h" +#include "frameobject.h" +#include "traceback.h" + +static void __Pyx_AddTraceback(char *funcname) { + PyObject *py_srcfile = 0; + PyObject *py_funcname = 0; + PyObject *py_globals = 0; + PyObject *empty_tuple = 0; + PyObject *empty_string = 0; + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + + py_srcfile = PyString_FromString(__pyx_filename); + if (!py_srcfile) goto bad; + py_funcname = PyString_FromString(funcname); + if (!py_funcname) goto bad; + py_globals = PyModule_GetDict(__pyx_m); + if (!py_globals) goto bad; + empty_tuple = PyTuple_New(0); + if (!empty_tuple) goto bad; + empty_string = PyString_FromString(""); + if (!empty_string) goto bad; + py_code = PyCode_New( + 0, /*int argcount,*/ + 0, /*int nlocals,*/ + 0, /*int stacksize,*/ + 0, /*int flags,*/ + empty_string, /*PyObject *code,*/ + empty_tuple, /*PyObject *consts,*/ + empty_tuple, /*PyObject *names,*/ + empty_tuple, /*PyObject *varnames,*/ + empty_tuple, /*PyObject *freevars,*/ + empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + __pyx_lineno, /*int firstlineno,*/ + empty_string /*PyObject *lnotab*/ + ); + if (!py_code) goto bad; + py_frame = PyFrame_New( + PyThreadState_Get(), /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + py_globals, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + py_frame->f_lineno = __pyx_lineno; + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_srcfile); + Py_XDECREF(py_funcname); + Py_XDECREF(empty_tuple); + Py_XDECREF(empty_string); + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} diff --git a/numpy/random/mtrand/mtrand.pyx b/numpy/random/mtrand/mtrand.pyx new file mode 100644 index 000000000..f27bc3c94 --- /dev/null +++ b/numpy/random/mtrand/mtrand.pyx @@ -0,0 +1,1724 @@ + +# mtrand.pyx -- A Pyrex wrapper of Jean-Sebastien Roy's RandomKit +# +# Copyright 2005 Robert Kern (robert.kern@gmail.com) +# +# Permission is hereby granted, free of charge, to any person obtaining a +# copy of this software and associated documentation files (the +# "Software"), to deal in the Software without restriction, including +# without limitation the rights to use, copy, modify, merge, publish, +# distribute, sublicense, and/or sell copies of the Software, and to +# permit persons to whom the Software is furnished to do so, subject to +# the following conditions: +# +# The above copyright notice and this permission notice shall be included +# in all copies or substantial portions of the Software. +# +# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS +# OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +# MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. +# IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY +# CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, +# TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE +# SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +include "Python.pxi" +include "numpy.pxi" + +cdef extern from "math.h": + double exp(double x) + double log(double x) + double floor(double x) + double sin(double x) + double cos(double x) + +cdef extern from "randomkit.h": + + ctypedef struct rk_state: + unsigned long key[624] + int pos + + ctypedef enum rk_error: + RK_NOERR = 0 + RK_ENODEV = 1 + RK_ERR_MAX = 2 + + char *rk_strerror[2] + + # 0xFFFFFFFFUL + unsigned long RK_MAX + + void rk_seed(unsigned long seed, rk_state *state) + rk_error rk_randomseed(rk_state *state) + unsigned long rk_random(rk_state *state) + long rk_long(rk_state *state) + unsigned long rk_ulong(rk_state *state) + unsigned long rk_interval(unsigned long max, rk_state *state) + double rk_double(rk_state *state) + void rk_fill(void *buffer, size_t size, rk_state *state) + rk_error rk_devfill(void *buffer, size_t size, int strong) + rk_error rk_altfill(void *buffer, size_t size, int strong, + rk_state *state) + double rk_gauss(rk_state *state) + +cdef extern from "distributions.h": + + double rk_normal(rk_state *state, double loc, double scale) + double rk_standard_exponential(rk_state *state) + double rk_exponential(rk_state *state, double scale) + double rk_uniform(rk_state *state, double loc, double scale) + double rk_standard_gamma(rk_state *state, double shape) + double rk_gamma(rk_state *state, double shape, double scale) + double rk_beta(rk_state *state, double a, double b) + double rk_chisquare(rk_state *state, double df) + double rk_noncentral_chisquare(rk_state *state, double df, double nonc) + double rk_f(rk_state *state, double dfnum, double dfden) + double rk_noncentral_f(rk_state *state, double dfnum, double dfden, double nonc) + double rk_standard_cauchy(rk_state *state) + double rk_standard_t(rk_state *state, double df) + double rk_vonmises(rk_state *state, double mu, double kappa) + double rk_pareto(rk_state *state, double a) + double rk_weibull(rk_state *state, double a) + double rk_power(rk_state *state, double a) + double rk_laplace(rk_state *state, double loc, double scale) + double rk_gumbel(rk_state *state, double loc, double scale) + double rk_logistic(rk_state *state, double loc, double scale) + double rk_lognormal(rk_state *state, double mode, double sigma) + double rk_rayleigh(rk_state *state, double mode) + double rk_wald(rk_state *state, double mean, double scale) + double rk_triangular(rk_state *state, double left, double mode, double right) + + long rk_binomial(rk_state *state, long n, double p) + long rk_binomial_btpe(rk_state *state, long n, double p) + long rk_binomial_inversion(rk_state *state, long n, double p) + long rk_negative_binomial(rk_state *state, long n, double p) + long rk_poisson(rk_state *state, double lam) + long rk_poisson_mult(rk_state *state, double lam) + long rk_poisson_ptrs(rk_state *state, double lam) + long rk_zipf(rk_state *state, double a) + long rk_geometric(rk_state *state, double p) + long rk_hypergeometric(rk_state *state, long good, long bad, long sample) + long rk_logseries(rk_state *state, double p) + +ctypedef double (* rk_cont0)(rk_state *state) +ctypedef double (* rk_cont1)(rk_state *state, double a) +ctypedef double (* rk_cont2)(rk_state *state, double a, double b) +ctypedef double (* rk_cont3)(rk_state *state, double a, double b, double c) + +ctypedef long (* rk_disc0)(rk_state *state) +ctypedef long (* rk_discnp)(rk_state *state, long n, double p) +ctypedef long (* rk_discnmN)(rk_state *state, long n, long m, long N) +ctypedef long (* rk_discd)(rk_state *state, double a) + + +cdef extern from "initarray.h": + void init_by_array(rk_state *self, unsigned long *init_key, + unsigned long key_length) + +# Initialize numpy +import_array() + +import numpy as _sp + +cdef object cont0_array(rk_state *state, rk_cont0 func, object size): + cdef double *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + length = PyArray_SIZE(array) + array_data = <double *>array.data + for i from 0 <= i < length: + array_data[i] = func(state) + return array + + +cdef object cont1_array_sc(rk_state *state, rk_cont1 func, object size, double a): + cdef double *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, a) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + length = PyArray_SIZE(array) + array_data = <double *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, a) + return array + +cdef object cont1_array(rk_state *state, rk_cont1 func, object size, ndarray oa): + cdef double *array_data + cdef double *oa_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef flatiter itera + cdef broadcast multi + + if size is None: + array = <ndarray>PyArray_SimpleNew(oa.nd, oa.dimensions, NPY_DOUBLE) + length = PyArray_SIZE(array) + array_data = <double *>array.data + itera = <flatiter>PyArray_IterNew(<object>oa) + for i from 0 <= i < length: + array_data[i] = func(state, (<double *>(itera.dataptr))[0]) + PyArray_ITER_NEXT(itera) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + array_data = <double *>array.data + multi = <broadcast>PyArray_MultiIterNew(2, <void *>array, + <void *>oa) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 1) + array_data[i] = func(state, oa_data[0]) + PyArray_MultiIter_NEXTi(multi, 1) + return array + +cdef object cont2_array_sc(rk_state *state, rk_cont2 func, object size, double a, + double b): + cdef double *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, a, b) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + length = PyArray_SIZE(array) + array_data = <double *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, a, b) + return array + + +cdef object cont2_array(rk_state *state, rk_cont2 func, object size, + ndarray oa, ndarray ob): + cdef double *array_data + cdef double *oa_data + cdef double *ob_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef broadcast multi + + if size is None: + multi = <broadcast> PyArray_MultiIterNew(2, <void *>oa, <void *>ob) + array = <ndarray> PyArray_SimpleNew(multi.nd, multi.dimensions, NPY_DOUBLE) + array_data = <double *>array.data + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 0) + ob_data = <double *>PyArray_MultiIter_DATA(multi, 1) + array_data[i] = func(state, oa_data[0], ob_data[0]) + PyArray_MultiIter_NEXT(multi) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + array_data = <double *>array.data + multi = <broadcast>PyArray_MultiIterNew(3, <void*>array, <void *>oa, <void *>ob) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 1) + ob_data = <double *>PyArray_MultiIter_DATA(multi, 2) + array_data[i] = func(state, oa_data[0], ob_data[0]) + PyArray_MultiIter_NEXTi(multi, 1) + PyArray_MultiIter_NEXTi(multi, 2) + return array + +cdef object cont3_array_sc(rk_state *state, rk_cont3 func, object size, double a, + double b, double c): + + cdef double *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, a, b, c) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + length = PyArray_SIZE(array) + array_data = <double *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, a, b, c) + return array + +cdef object cont3_array(rk_state *state, rk_cont3 func, object size, ndarray oa, + ndarray ob, ndarray oc): + + cdef double *array_data + cdef double *oa_data + cdef double *ob_data + cdef double *oc_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef broadcast multi + + if size is None: + multi = <broadcast> PyArray_MultiIterNew(3, <void *>oa, <void *>ob, <void *>oc) + array = <ndarray> PyArray_SimpleNew(multi.nd, multi.dimensions, NPY_DOUBLE) + array_data = <double *>array.data + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 0) + ob_data = <double *>PyArray_MultiIter_DATA(multi, 1) + oc_data = <double *>PyArray_MultiIter_DATA(multi, 2) + array_data[i] = func(state, oa_data[0], ob_data[0], oc_data[0]) + PyArray_MultiIter_NEXT(multi) + else: + array = <ndarray>_sp.empty(size, _sp.float64) + array_data = <double *>array.data + multi = <broadcast>PyArray_MultiIterNew(4, <void*>array, <void *>oa, + <void *>ob, <void *>oc) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 1) + ob_data = <double *>PyArray_MultiIter_DATA(multi, 2) + oc_data = <double *>PyArray_MultiIter_DATA(multi, 3) + array_data[i] = func(state, oa_data[0], ob_data[0], oc_data[0]) + PyArray_MultiIter_NEXT(multi) + return array + +cdef object disc0_array(rk_state *state, rk_disc0 func, object size): + cdef long *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state) + else: + array = <ndarray>_sp.empty(size, int) + length = PyArray_SIZE(array) + array_data = <long *>array.data + for i from 0 <= i < length: + array_data[i] = func(state) + return array + +cdef object discnp_array_sc(rk_state *state, rk_discnp func, object size, long n, double p): + cdef long *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, n, p) + else: + array = <ndarray>_sp.empty(size, int) + length = PyArray_SIZE(array) + array_data = <long *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, n, p) + return array + +cdef object discnp_array(rk_state *state, rk_discnp func, object size, ndarray on, ndarray op): + cdef long *array_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef double *op_data + cdef long *on_data + cdef broadcast multi + + if size is None: + multi = <broadcast> PyArray_MultiIterNew(2, <void *>on, <void *>op) + array = <ndarray> PyArray_SimpleNew(multi.nd, multi.dimensions, NPY_LONG) + array_data = <long *>array.data + for i from 0 <= i < multi.size: + on_data = <long *>PyArray_MultiIter_DATA(multi, 0) + op_data = <double *>PyArray_MultiIter_DATA(multi, 1) + array_data[i] = func(state, on_data[0], op_data[0]) + PyArray_MultiIter_NEXT(multi) + else: + array = <ndarray>_sp.empty(size, int) + array_data = <long *>array.data + multi = <broadcast>PyArray_MultiIterNew(3, <void*>array, <void *>on, <void *>op) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + on_data = <long *>PyArray_MultiIter_DATA(multi, 1) + op_data = <double *>PyArray_MultiIter_DATA(multi, 2) + array_data[i] = func(state, on_data[0], op_data[0]) + PyArray_MultiIter_NEXTi(multi, 1) + PyArray_MultiIter_NEXTi(multi, 2) + + return array + +cdef object discnmN_array_sc(rk_state *state, rk_discnmN func, object size, + long n, long m, long N): + cdef long *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, n, m, N) + else: + array = <ndarray>_sp.empty(size, int) + length = PyArray_SIZE(array) + array_data = <long *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, n, m, N) + return array + +cdef object discnmN_array(rk_state *state, rk_discnmN func, object size, + ndarray on, ndarray om, ndarray oN): + cdef long *array_data + cdef long *on_data + cdef long *om_data + cdef long *oN_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef broadcast multi + + if size is None: + multi = <broadcast> PyArray_MultiIterNew(3, <void *>on, <void *>om, <void *>oN) + array = <ndarray> PyArray_SimpleNew(multi.nd, multi.dimensions, NPY_LONG) + array_data = <long *>array.data + for i from 0 <= i < multi.size: + on_data = <long *>PyArray_MultiIter_DATA(multi, 0) + om_data = <long *>PyArray_MultiIter_DATA(multi, 1) + oN_data = <long *>PyArray_MultiIter_DATA(multi, 2) + array_data[i] = func(state, on_data[0], om_data[0], oN_data[0]) + PyArray_MultiIter_NEXT(multi) + else: + array = <ndarray>_sp.empty(size, int) + array_data = <long *>array.data + multi = <broadcast>PyArray_MultiIterNew(4, <void*>array, <void *>on, <void *>om, + <void *>oN) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + on_data = <long *>PyArray_MultiIter_DATA(multi, 1) + om_data = <long *>PyArray_MultiIter_DATA(multi, 2) + oN_data = <long *>PyArray_MultiIter_DATA(multi, 3) + array_data[i] = func(state, on_data[0], om_data[0], oN_data[0]) + PyArray_MultiIter_NEXT(multi) + + return array + +cdef object discd_array_sc(rk_state *state, rk_discd func, object size, double a): + cdef long *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if size is None: + return func(state, a) + else: + array = <ndarray>_sp.empty(size, int) + length = PyArray_SIZE(array) + array_data = <long *>array.data + for i from 0 <= i < length: + array_data[i] = func(state, a) + return array + +cdef object discd_array(rk_state *state, rk_discd func, object size, ndarray oa): + cdef long *array_data + cdef double *oa_data + cdef ndarray array "arrayObject" + cdef npy_intp length + cdef npy_intp i + cdef broadcast multi + cdef flatiter itera + + if size is None: + array = <ndarray>PyArray_SimpleNew(oa.nd, oa.dimensions, NPY_LONG) + length = PyArray_SIZE(array) + array_data = <long *>array.data + itera = <flatiter>PyArray_IterNew(<object>oa) + for i from 0 <= i < length: + array_data[i] = func(state, (<double *>(itera.dataptr))[0]) + PyArray_ITER_NEXT(itera) + else: + array = <ndarray>_sp.empty(size, int) + array_data = <long *>array.data + multi = <broadcast>PyArray_MultiIterNew(2, <void *>array, <void *>oa) + if (multi.size != PyArray_SIZE(array)): + raise ValueError("size is not compatible with inputs") + for i from 0 <= i < multi.size: + oa_data = <double *>PyArray_MultiIter_DATA(multi, 1) + array_data[i] = func(state, oa_data[0]) + PyArray_MultiIter_NEXTi(multi, 1) + return array + +cdef double kahan_sum(double *darr, long n): + cdef double c, y, t, sum + cdef long i + sum = darr[0] + c = 0.0 + for i from 1 <= i < n: + y = darr[i] - c + t = sum + y + c = (t-sum) - y + sum = t + return sum + +cdef class RandomState: + """Container for the Mersenne Twister PRNG. + + Constructor + ----------- + RandomState(seed=None): initializes the PRNG with the given seed. See the + seed() method for details. + + Distribution Methods + ----------------- + RandomState exposes a number of methods for generating random numbers drawn + from a variety of probability distributions. In addition to the + distribution-specific arguments, each method takes a keyword argument + size=None. If size is None, then a single value is generated and returned. + If size is an integer, then a 1-D numpy array filled with generated values + is returned. If size is a tuple, then a numpy array with that shape is + filled and returned. + """ + cdef rk_state *internal_state + + def __init__(self, seed=None): + self.internal_state = <rk_state*>PyMem_Malloc(sizeof(rk_state)) + + self.seed(seed) + + def __dealloc__(self): + if self.internal_state != NULL: + PyMem_Free(self.internal_state) + self.internal_state = NULL + + def seed(self, seed=None): + """Seed the generator. + + seed(seed=None) + + seed can be an integer, an array (or other sequence) of integers of any + length, or None. If seed is None, then RandomState will try to read data + from /dev/urandom (or the Windows analogue) if available or seed from + the clock otherwise. + """ + cdef rk_error errcode + cdef ndarray obj "arrayObject_obj" + if seed is None: + errcode = rk_randomseed(self.internal_state) + elif type(seed) is int: + rk_seed(seed, self.internal_state) + else: + obj = <ndarray>PyArray_ContiguousFromObject(seed, NPY_LONG, 1, 1) + init_by_array(self.internal_state, <unsigned long *>(obj.data), + obj.dimensions[0]) + + def get_state(self): + """Return a tuple representing the internal state of the generator. + + get_state() -> ('MT19937', int key[624], int pos) + """ + cdef ndarray state "arrayObject_state" + state = <ndarray>_sp.empty(624, _sp.uint) + memcpy(<void*>(state.data), <void*>(self.internal_state.key), 624*sizeof(long)) + state = <ndarray>_sp.asarray(state, _sp.uint32) + return ('MT19937', state, self.internal_state.pos) + + def set_state(self, state): + """Set the state from a tuple. + + state = ('MT19937', int key[624], int pos) + + set_state(state) + """ + cdef ndarray obj "arrayObject_obj" + cdef int pos + algorithm_name = state[0] + if algorithm_name != 'MT19937': + raise ValueError("algorithm must be 'MT19937'") + key, pos = state[1:] + try: + obj = <ndarray>PyArray_ContiguousFromObject(key, NPY_ULONG, 1, 1) + except TypeError: + # compatibility -- could be an older pickle + obj = <ndarray>PyArray_ContiguousFromObject(key, NPY_LONG, 1, 1) + if obj.dimensions[0] != 624: + raise ValueError("state must be 624 longs") + memcpy(<void*>(self.internal_state.key), <void*>(obj.data), 624*sizeof(long)) + self.internal_state.pos = pos + + # Pickling support: + def __getstate__(self): + return self.get_state() + + def __setstate__(self, state): + self.set_state(state) + + def __reduce__(self): + return (_sp.random.__RandomState_ctor, (), self.get_state()) + + # Basic distributions: + def random_sample(self, size=None): + """Return random floats in the half-open interval [0.0, 1.0). + + random_sample(size=None) -> random values + """ + return cont0_array(self.internal_state, rk_double, size) + + def tomaxint(self, size=None): + """Returns random integers x such that 0 <= x <= sys.maxint. + + tomaxint(size=None) -> random values + """ + return disc0_array(self.internal_state, rk_long, size) + + def randint(self, low, high=None, size=None): + """Return random integers x such that low <= x < high. + + randint(low, high=None, size=None) -> random values + + If high is None, then 0 <= x < low. + """ + cdef long lo, hi, diff + cdef long *array_data + cdef ndarray array "arrayObject" + cdef long length + cdef long i + + if high is None: + lo = 0 + hi = low + else: + lo = low + hi = high + + diff = hi - lo - 1 + if diff < 0: + raise ValueError("low >= high") + + if size is None: + return rk_interval(diff, self.internal_state) + lo + else: + array = <ndarray>_sp.empty(size, int) + length = PyArray_SIZE(array) + array_data = <long *>array.data + for i from 0 <= i < length: + array_data[i] = lo + <long>rk_interval(diff, self.internal_state) + return array + + def bytes(self, unsigned int length): + """Return random bytes. + + bytes(length) -> str + """ + cdef void *bytes + bytestring = PyString_FromStringAndSize(NULL, length) + bytes = PyString_AS_STRING(bytestring) + rk_fill(bytes, length, self.internal_state) + return bytestring + + def uniform(self, low=0.0, high=1.0, size=None): + """Uniform distribution over [low, high). + + uniform(low=0.0, high=1.0, size=None) -> random values + """ + cdef ndarray olow, ohigh, odiff + cdef double flow, fhigh + cdef object temp + + flow = PyFloat_AsDouble(low) + fhigh = PyFloat_AsDouble(high) + if not PyErr_Occurred(): + return cont2_array_sc(self.internal_state, rk_uniform, size, flow, fhigh-flow) + PyErr_Clear() + olow = <ndarray>PyArray_FROM_OTF(low, NPY_DOUBLE, NPY_ALIGNED) + ohigh = <ndarray>PyArray_FROM_OTF(high, NPY_DOUBLE, NPY_ALIGNED) + temp = _sp.subtract(ohigh, olow) + Py_INCREF(temp) # needed to get around Pyrex's automatic reference-counting + # rules because EnsureArray steals a reference + odiff = <ndarray>PyArray_EnsureArray(temp) + return cont2_array(self.internal_state, rk_uniform, size, olow, odiff) + + def rand(self, *args): + """Return an array of the given dimensions which is initialized to + random numbers from a uniform distribution in the range [0,1). + + rand(d0, d1, ..., dn) -> random values + + Note: This is a convenience function. If you want an + interface that takes a tuple as the first argument + use numpy.random.random_sample(shape_tuple). + + """ + if len(args) == 0: + return self.random_sample() + else: + return self.random_sample(size=args) + + def randn(self, *args): + """Returns zero-mean, unit-variance Gaussian random numbers in an + array of shape (d0, d1, ..., dn). + + randn(d0, d1, ..., dn) -> random values + + Note: This is a convenience function. If you want an + interface that takes a tuple as the first argument + use numpy.random.standard_normal(shape_tuple). + """ + if len(args) == 0: + return self.standard_normal() + else: + return self.standard_normal(args) + + def random_integers(self, low, high=None, size=None): + """Return random integers x such that low <= x <= high. + + random_integers(low, high=None, size=None) -> random values. + + If high is None, then 1 <= x <= low. + """ + if high is None: + high = low + low = 1 + return self.randint(low, high+1, size) + + # Complicated, continuous distributions: + def standard_normal(self, size=None): + """Standard Normal distribution (mean=0, stdev=1). + + standard_normal(size=None) -> random values + """ + return cont0_array(self.internal_state, rk_gauss, size) + + def normal(self, loc=0.0, scale=1.0, size=None): + """Normal distribution (mean=loc, stdev=scale). + + normal(loc=0.0, scale=1.0, size=None) -> random values + """ + cdef ndarray oloc, oscale + cdef double floc, fscale + + floc = PyFloat_AsDouble(loc) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_normal, size, floc, fscale) + + PyErr_Clear() + + oloc = <ndarray>PyArray_FROM_OTF(loc, NPY_DOUBLE, NPY_ALIGNED) + oscale = <ndarray>PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0)): + raise ValueError("scale <= 0") + return cont2_array(self.internal_state, rk_normal, size, oloc, oscale) + + def beta(self, a, b, size=None): + """Beta distribution over [0, 1]. + + beta(a, b, size=None) -> random values + """ + cdef ndarray oa, ob + cdef double fa, fb + + fa = PyFloat_AsDouble(a) + fb = PyFloat_AsDouble(b) + if not PyErr_Occurred(): + if fa <= 0: + raise ValueError("a <= 0") + if fb <= 0: + raise ValueError("b <= 0") + return cont2_array_sc(self.internal_state, rk_beta, size, fa, fb) + + PyErr_Clear() + + oa = <ndarray>PyArray_FROM_OTF(a, NPY_DOUBLE, NPY_ALIGNED) + ob = <ndarray>PyArray_FROM_OTF(b, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oa, 0)): + raise ValueError("a <= 0") + if _sp.any(_sp.less_equal(ob, 0)): + raise ValueError("b <= 0") + return cont2_array(self.internal_state, rk_beta, size, oa, ob) + + def exponential(self, scale=1.0, size=None): + """Exponential distribution. + + exponential(scale=1.0, size=None) -> random values + """ + cdef ndarray oscale + cdef double fscale + + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont1_array_sc(self.internal_state, rk_exponential, size, fscale) + + PyErr_Clear() + + oscale = <ndarray> PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0") + return cont1_array(self.internal_state, rk_exponential, size, oscale) + + def standard_exponential(self, size=None): + """Standard exponential distribution (scale=1). + + standard_exponential(size=None) -> random values + """ + return cont0_array(self.internal_state, rk_standard_exponential, size) + + def standard_gamma(self, shape, size=None): + """Standard Gamma distribution. + + standard_gamma(shape, size=None) -> random values + """ + cdef ndarray oshape + cdef double fshape + + fshape = PyFloat_AsDouble(shape) + if not PyErr_Occurred(): + if fshape <= 0: + raise ValueError("shape <= 0") + return cont1_array_sc(self.internal_state, rk_standard_gamma, size, fshape) + + PyErr_Clear() + oshape = <ndarray> PyArray_FROM_OTF(shape, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oshape, 0.0)): + raise ValueError("shape <= 0") + return cont1_array(self.internal_state, rk_standard_gamma, size, oshape) + + def gamma(self, shape, scale=1.0, size=None): + """Gamma distribution. + + gamma(shape, scale=1.0, size=None) -> random values + """ + cdef ndarray oshape, oscale + cdef double fshape, fscale + + fshape = PyFloat_AsDouble(shape) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fshape <= 0: + raise ValueError("shape <= 0") + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_gamma, size, fshape, fscale) + + PyErr_Clear() + oshape = <ndarray>PyArray_FROM_OTF(shape, NPY_DOUBLE, NPY_ALIGNED) + oscale = <ndarray>PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oshape, 0.0)): + raise ValueError("shape <= 0") + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0") + return cont2_array(self.internal_state, rk_gamma, size, oshape, oscale) + + def f(self, dfnum, dfden, size=None): + """F distribution. + + f(dfnum, dfden, size=None) -> random values + """ + cdef ndarray odfnum, odfden + cdef double fdfnum, fdfden + + fdfnum = PyFloat_AsDouble(dfnum) + fdfden = PyFloat_AsDouble(dfden) + if not PyErr_Occurred(): + if fdfnum <= 0: + raise ValueError("shape <= 0") + if fdfden <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_f, size, fdfnum, fdfden) + + PyErr_Clear() + + odfnum = <ndarray>PyArray_FROM_OTF(dfnum, NPY_DOUBLE, NPY_ALIGNED) + odfden = <ndarray>PyArray_FROM_OTF(dfden, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(odfnum, 0.0)): + raise ValueError("dfnum <= 0") + if _sp.any(_sp.less_equal(odfden, 0.0)): + raise ValueError("dfden <= 0") + return cont2_array(self.internal_state, rk_f, size, odfnum, odfden) + + def noncentral_f(self, dfnum, dfden, nonc, size=None): + """Noncentral F distribution. + + noncentral_f(dfnum, dfden, nonc, size=None) -> random values + """ + cdef ndarray odfnum, odfden, ononc + cdef double fdfnum, fdfden, fnonc + + fdfnum = PyFloat_AsDouble(dfnum) + fdfden = PyFloat_AsDouble(dfden) + fnonc = PyFloat_AsDouble(nonc) + if not PyErr_Occurred(): + if fdfnum <= 1: + raise ValueError("dfnum <= 1") + if fdfden <= 0: + raise ValueError("dfden <= 0") + if fnonc < 0: + raise ValueError("nonc < 0") + return cont3_array_sc(self.internal_state, rk_noncentral_f, size, + fdfnum, fdfden, fnonc) + + PyErr_Clear() + + odfnum = <ndarray>PyArray_FROM_OTF(dfnum, NPY_DOUBLE, NPY_ALIGNED) + odfden = <ndarray>PyArray_FROM_OTF(dfden, NPY_DOUBLE, NPY_ALIGNED) + ononc = <ndarray>PyArray_FROM_OTF(nonc, NPY_DOUBLE, NPY_ALIGNED) + + if _sp.any(_sp.less_equal(odfnum, 1.0)): + raise ValueError("dfnum <= 1") + if _sp.any(_sp.less_equal(odfden, 0.0)): + raise ValueError("dfden <= 0") + if _sp.any(_sp.less(ononc, 0.0)): + raise ValueError("nonc < 0") + return cont3_array(self.internal_state, rk_noncentral_f, size, odfnum, + odfden, ononc) + + def chisquare(self, df, size=None): + """Chi^2 distribution. + + chisquare(df, size=None) -> random values + """ + cdef ndarray odf + cdef double fdf + + fdf = PyFloat_AsDouble(df) + if not PyErr_Occurred(): + if fdf <= 0: + raise ValueError("df <= 0") + return cont1_array_sc(self.internal_state, rk_chisquare, size, fdf) + + PyErr_Clear() + + odf = <ndarray>PyArray_FROM_OTF(df, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(odf, 0.0)): + raise ValueError("df <= 0") + return cont1_array(self.internal_state, rk_chisquare, size, odf) + + def noncentral_chisquare(self, df, nonc, size=None): + """Noncentral Chi^2 distribution. + + noncentral_chisquare(df, nonc, size=None) -> random values + """ + cdef ndarray odf, ononc + cdef double fdf, fnonc + fdf = PyFloat_AsDouble(df) + fnonc = PyFloat_AsDouble(nonc) + if not PyErr_Occurred(): + if fdf <= 1: + raise ValueError("df <= 0") + if fnonc <= 0: + raise ValueError("nonc <= 0") + return cont2_array_sc(self.internal_state, rk_noncentral_chisquare, + size, fdf, fnonc) + + PyErr_Clear() + + odf = <ndarray>PyArray_FROM_OTF(df, NPY_DOUBLE, NPY_ALIGNED) + ononc = <ndarray>PyArray_FROM_OTF(nonc, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(odf, 0.0)): + raise ValueError("df <= 1") + if _sp.any(_sp.less_equal(ononc, 0.0)): + raise ValueError("nonc < 0") + return cont2_array(self.internal_state, rk_noncentral_chisquare, size, + odf, ononc) + + def standard_cauchy(self, size=None): + """Standard Cauchy with mode=0. + + standard_cauchy(size=None) + """ + return cont0_array(self.internal_state, rk_standard_cauchy, size) + + def standard_t(self, df, size=None): + """Standard Student's t distribution with df degrees of freedom. + + standard_t(df, size=None) + """ + cdef ndarray odf + cdef double fdf + + fdf = PyFloat_AsDouble(df) + if not PyErr_Occurred(): + if fdf <= 0: + raise ValueError("df <= 0") + return cont1_array_sc(self.internal_state, rk_standard_t, size, fdf) + + PyErr_Clear() + + odf = <ndarray> PyArray_FROM_OTF(df, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(odf, 0.0)): + raise ValueError("df <= 0") + return cont1_array(self.internal_state, rk_standard_t, size, odf) + + def vonmises(self, mu, kappa, size=None): + """von Mises circular distribution with mode mu and dispersion parameter + kappa on [-pi, pi]. + + vonmises(mu, kappa, size=None) + """ + cdef ndarray omu, okappa + cdef double fmu, fkappa + + fmu = PyFloat_AsDouble(mu) + fkappa = PyFloat_AsDouble(kappa) + if not PyErr_Occurred(): + if fkappa < 0: + raise ValueError("kappa < 0") + return cont2_array_sc(self.internal_state, rk_vonmises, size, fmu, fkappa) + + PyErr_Clear() + + omu = <ndarray> PyArray_FROM_OTF(mu, NPY_DOUBLE, NPY_ALIGNED) + okappa = <ndarray> PyArray_FROM_OTF(kappa, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less(okappa, 0.0)): + raise ValueError("kappa < 0") + return cont2_array(self.internal_state, rk_vonmises, size, omu, okappa) + + def pareto(self, a, size=None): + """Pareto distribution. + + pareto(a, size=None) + """ + cdef ndarray oa + cdef double fa + + fa = PyFloat_AsDouble(a) + if not PyErr_Occurred(): + if fa <= 0: + raise ValueError("a <= 0") + return cont1_array_sc(self.internal_state, rk_pareto, size, fa) + + PyErr_Clear() + + oa = <ndarray>PyArray_FROM_OTF(a, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oa, 0.0)): + raise ValueError("a <= 0") + return cont1_array(self.internal_state, rk_pareto, size, oa) + + def weibull(self, a, size=None): + """Weibull distribution. + + weibull(a, size=None) + """ + cdef ndarray oa + cdef double fa + + fa = PyFloat_AsDouble(a) + if not PyErr_Occurred(): + if fa <= 0: + raise ValueError("a <= 0") + return cont1_array_sc(self.internal_state, rk_weibull, size, fa) + + PyErr_Clear() + + oa = <ndarray>PyArray_FROM_OTF(a, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oa, 0.0)): + raise ValueError("a <= 0") + return cont1_array(self.internal_state, rk_weibull, size, oa) + + def power(self, a, size=None): + """Power distribution. + + power(a, size=None) + """ + cdef ndarray oa + cdef double fa + + fa = PyFloat_AsDouble(a) + if not PyErr_Occurred(): + if fa <= 0: + raise ValueError("a <= 0") + return cont1_array_sc(self.internal_state, rk_power, size, fa) + + PyErr_Clear() + + oa = <ndarray>PyArray_FROM_OTF(a, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oa, 0.0)): + raise ValueError("a <= 0") + return cont1_array(self.internal_state, rk_power, size, oa) + + def laplace(self, loc=0.0, scale=1.0, size=None): + """Laplace distribution. + + laplace(loc=0.0, scale=1.0, size=None) + """ + cdef ndarray oloc, oscale + cdef double floc, fscale + + floc = PyFloat_AsDouble(loc) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_laplace, size, floc, fscale) + + PyErr_Clear() + oloc = PyArray_FROM_OTF(loc, NPY_DOUBLE, NPY_ALIGNED) + oscale = PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0") + return cont2_array(self.internal_state, rk_laplace, size, oloc, oscale) + + def gumbel(self, loc=0.0, scale=1.0, size=None): + """Gumbel distribution. + + gumbel(loc=0.0, scale=1.0, size=None) + """ + cdef ndarray oloc, oscale + cdef double floc, fscale + + floc = PyFloat_AsDouble(loc) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_gumbel, size, floc, fscale) + + PyErr_Clear() + oloc = PyArray_FROM_OTF(loc, NPY_DOUBLE, NPY_ALIGNED) + oscale = PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0") + return cont2_array(self.internal_state, rk_gumbel, size, oloc, oscale) + + def logistic(self, loc=0.0, scale=1.0, size=None): + """Logistic distribution. + + logistic(loc=0.0, scale=1.0, size=None) + """ + cdef ndarray oloc, oscale + cdef double floc, fscale + + floc = PyFloat_AsDouble(loc) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_logistic, size, floc, fscale) + + PyErr_Clear() + oloc = PyArray_FROM_OTF(loc, NPY_DOUBLE, NPY_ALIGNED) + oscale = PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0") + return cont2_array(self.internal_state, rk_logistic, size, oloc, oscale) + + def lognormal(self, mean=0.0, sigma=1.0, size=None): + """Log-normal distribution. + + Note that the mean parameter is not the mean of this distribution, but + the underlying normal distribution. + + lognormal(mean, sigma) <=> exp(normal(mean, sigma)) + + lognormal(mean=0.0, sigma=1.0, size=None) + """ + cdef ndarray omean, osigma + cdef double fmean, fsigma + + fmean = PyFloat_AsDouble(mean) + fsigma = PyFloat_AsDouble(sigma) + + if not PyErr_Occurred(): + if fsigma <= 0: + raise ValueError("sigma <= 0") + return cont2_array_sc(self.internal_state, rk_lognormal, size, fmean, fsigma) + + PyErr_Clear() + + omean = PyArray_FROM_OTF(mean, NPY_DOUBLE, NPY_ALIGNED) + osigma = PyArray_FROM_OTF(sigma, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(osigma, 0.0)): + raise ValueError("sigma <= 0.0") + return cont2_array(self.internal_state, rk_lognormal, size, omean, osigma) + + def rayleigh(self, scale=1.0, size=None): + """Rayleigh distribution. + + rayleigh(scale=1.0, size=None) + """ + cdef ndarray oscale + cdef double fscale + + fscale = PyFloat_AsDouble(scale) + + if not PyErr_Occurred(): + if fscale <= 0: + raise ValueError("scale <= 0") + return cont1_array_sc(self.internal_state, rk_rayleigh, size, fscale) + + PyErr_Clear() + + oscale = <ndarray>PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oscale, 0.0)): + raise ValueError("scale <= 0.0") + return cont1_array(self.internal_state, rk_rayleigh, size, oscale) + + def wald(self, mean, scale, size=None): + """Wald (inverse Gaussian) distribution. + + wald(mean, scale, size=None) + """ + cdef ndarray omean, oscale + cdef double fmean, fscale + + fmean = PyFloat_AsDouble(mean) + fscale = PyFloat_AsDouble(scale) + if not PyErr_Occurred(): + if fmean <= 0: + raise ValueError("mean <= 0") + if fscale <= 0: + raise ValueError("scale <= 0") + return cont2_array_sc(self.internal_state, rk_wald, size, fmean, fscale) + + PyErr_Clear() + omean = PyArray_FROM_OTF(mean, NPY_DOUBLE, NPY_ALIGNED) + oscale = PyArray_FROM_OTF(scale, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(omean,0.0)): + raise ValueError("mean <= 0.0") + elif _sp.any(_sp.less_equal(oscale,0.0)): + raise ValueError("scale <= 0.0") + return cont2_array(self.internal_state, rk_wald, size, omean, oscale) + + + + def triangular(self, left, mode, right, size=None): + """Triangular distribution starting at left, peaking at mode, and + ending at right (left <= mode <= right). + + triangular(left, mode, right, size=None) + """ + cdef ndarray oleft, omode, oright + cdef double fleft, fmode, fright + + fleft = PyFloat_AsDouble(left) + fright = PyFloat_AsDouble(right) + fmode = PyFloat_AsDouble(mode) + if not PyErr_Occurred(): + if fleft > fmode: + raise ValueError("left > mode") + if fmode > fright: + raise ValueError("mode > right") + if fleft == fright: + raise ValueError("left == right") + return cont3_array_sc(self.internal_state, rk_triangular, size, fleft, + fmode, fright) + + PyErr_Clear() + oleft = <ndarray>PyArray_FROM_OTF(left, NPY_DOUBLE, NPY_ALIGNED) + omode = <ndarray>PyArray_FROM_OTF(mode, NPY_DOUBLE, NPY_ALIGNED) + oright = <ndarray>PyArray_FROM_OTF(right, NPY_DOUBLE, NPY_ALIGNED) + + if _sp.any(_sp.greater(oleft, omode)): + raise ValueError("left > mode") + if _sp.any(_sp.greater(omode, oright)): + raise ValueError("mode > right") + if _sp.any(_sp.equal(oleft, oright)): + raise ValueError("left == right") + return cont3_array(self.internal_state, rk_triangular, size, oleft, + omode, oright) + + # Complicated, discrete distributions: + def binomial(self, n, p, size=None): + """Binomial distribution of n trials and p probability of success. + + binomial(n, p, size=None) -> random values + """ + cdef ndarray on, op + cdef long ln + cdef double fp + + fp = PyFloat_AsDouble(p) + ln = PyInt_AsLong(n) + if not PyErr_Occurred(): + if ln <= 0: + raise ValueError("n <= 0") + if fp < 0: + raise ValueError("p < 0") + elif fp > 1: + raise ValueError("p > 1") + return discnp_array_sc(self.internal_state, rk_binomial, size, ln, fp) + + PyErr_Clear() + + on = <ndarray>PyArray_FROM_OTF(n, NPY_LONG, NPY_ALIGNED) + op = <ndarray>PyArray_FROM_OTF(p, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(n, 0)): + raise ValueError("n <= 0") + if _sp.any(_sp.less(p, 0)): + raise ValueError("p < 0") + if _sp.any(_sp.greater(p, 1)): + raise ValueError("p > 1") + return discnp_array(self.internal_state, rk_binomial, size, on, op) + + def negative_binomial(self, n, p, size=None): + """Negative Binomial distribution. + + negative_binomial(n, p, size=None) -> random values + """ + cdef ndarray on + cdef ndarray op + cdef long ln + cdef double fp + + fp = PyFloat_AsDouble(p) + ln = PyInt_AsLong(n) + if not PyErr_Occurred(): + if ln <= 0: + raise ValueError("n <= 0") + if fp < 0: + raise ValueError("p < 0") + elif fp > 1: + raise ValueError("p > 1") + return discnp_array_sc(self.internal_state, rk_negative_binomial, + size, ln, fp) + + PyErr_Clear() + + on = <ndarray>PyArray_FROM_OTF(n, NPY_LONG, NPY_ALIGNED) + op = <ndarray>PyArray_FROM_OTF(p, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(n, 0)): + raise ValueError("n <= 0") + if _sp.any(_sp.less(p, 0)): + raise ValueError("p < 0") + if _sp.any(_sp.greater(p, 1)): + raise ValueError("p > 1") + return discnp_array(self.internal_state, rk_negative_binomial, size, + on, op) + + def poisson(self, lam=1.0, size=None): + """Poisson distribution. + + poisson(lam=1.0, size=None) -> random values + """ + cdef ndarray olam + cdef double flam + flam = PyFloat_AsDouble(lam) + if not PyErr_Occurred(): + if lam < 0: + raise ValueError("lam < 0") + return discd_array_sc(self.internal_state, rk_poisson, size, flam) + + PyErr_Clear() + + olam = <ndarray>PyArray_FROM_OTF(lam, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less(olam, 0)): + raise ValueError("lam < 0") + return discd_array(self.internal_state, rk_poisson, size, olam) + + def zipf(self, a, size=None): + """Zipf distribution. + + zipf(a, size=None) + """ + cdef ndarray oa + cdef double fa + + fa = PyFloat_AsDouble(a) + if not PyErr_Occurred(): + if fa <= 1.0: + raise ValueError("a <= 1.0") + return discd_array_sc(self.internal_state, rk_zipf, size, fa) + + PyErr_Clear() + + oa = <ndarray>PyArray_FROM_OTF(a, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less_equal(oa, 1.0)): + raise ValueError("a <= 1.0") + return discd_array(self.internal_state, rk_zipf, size, oa) + + def geometric(self, p, size=None): + """Geometric distribution with p being the probability of "success" on + an individual trial. + + geometric(p, size=None) + """ + cdef ndarray op + cdef double fp + + fp = PyFloat_AsDouble(p) + if not PyErr_Occurred(): + 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) + + PyErr_Clear() + + + op = <ndarray>PyArray_FROM_OTF(p, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less(op, 0.0)): + raise ValueError("p < 0.0") + if _sp.any(_sp.greater(op, 1.0)): + raise ValueError("p > 1.0") + return discd_array(self.internal_state, rk_geometric, size, op) + + def hypergeometric(self, ngood, nbad, nsample, size=None): + """Hypergeometric distribution. + + Consider an urn with ngood "good" balls and nbad "bad" balls. If one + were to draw nsample balls from the urn without replacement, then + the hypergeometric distribution describes the distribution of "good" + balls in the sample. + + hypergeometric(ngood, nbad, nsample, size=None) + """ + cdef ndarray ongood, onbad, onsample + cdef long lngood, lnbad, lnsample + + lngood = PyInt_AsLong(ngood) + lnbad = PyInt_AsLong(nbad) + lnsample = PyInt_AsLong(nsample) + if not PyErr_Occurred(): + if ngood < 1: + raise ValueError("ngood < 1") + if nbad < 1: + raise ValueError("nbad < 1") + if nsample < 1: + raise ValueError("nsample < 1") + if ngood + nbad < nsample: + raise ValueError("ngood + nbad < nsample") + return discnmN_array_sc(self.internal_state, rk_hypergeometric, size, + lngood, lnbad, lnsample) + + + PyErr_Clear() + + ongood = <ndarray>PyArray_FROM_OTF(ngood, NPY_LONG, NPY_ALIGNED) + onbad = <ndarray>PyArray_FROM_OTF(nbad, NPY_LONG, NPY_ALIGNED) + onsample = <ndarray>PyArray_FROM_OTF(nsample, NPY_LONG, NPY_ALIGNED) + if _sp.any(_sp.less(ongood, 1)): + raise ValueError("ngood < 1") + if _sp.any(_sp.less(onbad, 1)): + raise ValueError("nbad < 1") + if _sp.any(_sp.less(onsample, 1)): + raise ValueError("nsample < 1") + if _sp.any(_sp.less(_sp.add(ongood, onbad),onsample)): + raise ValueError("ngood + nbad < nsample") + return discnmN_array(self.internal_state, rk_hypergeometric, size, + ongood, onbad, onsample) + + def logseries(self, p, size=None): + """Logarithmic series distribution. + + logseries(p, size=None) + """ + cdef ndarray op + cdef double fp + + fp = PyFloat_AsDouble(p) + if not PyErr_Occurred(): + 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_logseries, size, fp) + + PyErr_Clear() + + op = <ndarray>PyArray_FROM_OTF(p, NPY_DOUBLE, NPY_ALIGNED) + if _sp.any(_sp.less(op, 0.0)): + raise ValueError("p < 0.0") + if _sp.any(_sp.greater(op, 1.0)): + raise ValueError("p > 1.0") + return discd_array(self.internal_state, rk_logseries, size, op) + + # Multivariate distributions: + def multivariate_normal(self, mean, cov, size=None): + """Return an array containing multivariate normally distributed random numbers + with specified mean and covariance. + + multivariate_normal(mean, cov) -> random values + multivariate_normal(mean, cov, [m, n, ...]) -> random values + + mean must be a 1 dimensional array. cov must be a square two dimensional + array with the same number of rows and columns as mean has elements. + + The first form returns a single 1-D array containing a multivariate + normal. + + The second form returns an array of shape (m, n, ..., cov.shape[0]). + In this case, output[i,j,...,:] is a 1-D array containing a multivariate + normal. + """ + # Check preconditions on arguments + mean = _sp.array(mean) + cov = _sp.array(cov) + if size is None: + shape = [] + else: + shape = size + if len(mean.shape) != 1: + raise ValueError("mean must be 1 dimensional") + if (len(cov.shape) != 2) or (cov.shape[0] != cov.shape[1]): + raise ValueError("cov must be 2 dimensional and square") + if mean.shape[0] != cov.shape[0]: + raise ValueError("mean and cov must have same length") + # Compute shape of output + if isinstance(shape, int): + shape = [shape] + final_shape = list(shape[:]) + final_shape.append(mean.shape[0]) + # Create a matrix of independent standard normally distributed random + # numbers. The matrix has rows with the same length as mean and as + # many rows are necessary to form a matrix of shape final_shape. + x = standard_normal(_sp.multiply.reduce(final_shape)) + x.shape = (_sp.multiply.reduce(final_shape[0:len(final_shape)-1]), + mean.shape[0]) + # Transform matrix of standard normals into matrix where each row + # contains multivariate normals with the desired covariance. + # Compute A such that dot(transpose(A),A) == cov. + # Then the matrix products of the rows of x and A has the desired + # covariance. Note that sqrt(s)*v where (u,s,v) is the singular value + # decomposition of cov is such an A. + + from numpy.dual import svd + # XXX: we really should be doing this by Cholesky decomposition + (u,s,v) = svd(cov) + x = _sp.dot(x*_sp.sqrt(s),v) + # The rows of x now have the correct covariance but mean 0. Add + # mean to each row. Then each row will have mean mean. + _sp.add(mean,x,x) + x.shape = tuple(final_shape) + return x + + def multinomial(self, long n, object pvals, size=None): + """Multinomial distribution. + + multinomial(n, pvals, size=None) -> random values + + pvals is a sequence of probabilities that should sum to 1 (however, the + last element is always assumed to account for the remaining probability + as long as sum(pvals[:-1]) <= 1). + """ + cdef long d + cdef ndarray parr "arrayObject_parr", mnarr "arrayObject_mnarr" + cdef double *pix + cdef long *mnix + cdef long i, j, dn + cdef double Sum + + d = len(pvals) + parr = <ndarray>PyArray_ContiguousFromObject(pvals, NPY_DOUBLE, 1, 1) + pix = <double*>parr.data + + if kahan_sum(pix, d-1) > 1.0: + raise ValueError("sum(pvals) > 1.0") + + if size is None: + shape = (d,) + elif type(size) is int: + shape = (size, d) + else: + shape = size + (d,) + + multin = _sp.zeros(shape, int) + mnarr = <ndarray>multin + mnix = <long*>mnarr.data + i = 0 + while i < PyArray_SIZE(mnarr): + Sum = 1.0 + dn = n + for j from 0 <= j < d-1: + mnix[i+j] = rk_binomial(self.internal_state, dn, pix[j]/Sum) + dn = dn - mnix[i+j] + if dn <= 0: + break + Sum = Sum - pix[j] + if dn > 0: + mnix[i+d-1] = dn + + i = i + d + + return multin + + def dirichlet(self, object alpha, size=None): + """dirichlet(alpha, size=None) + + Draw `size` samples of dimension k from a Dirichlet distribution. A + Dirichlet-distributed random variable can be seen as a multivariate + generalization of a Beta distribution. Dirichlet pdf is the conjugate + prior of a multinomial in Bayesian inference. + + :Parameters: + alpha : array + parameter of the distribution (k dimension + for sample of dimension k). + size : array + number of samples to draw. + + $X \approx \prod_{i=1}^{k}{x^{\alpha_i-1}_i}$ + + Uses the following property for computation: for each dimension, + draw a random sample y_i from a standard gamma generator of shape + alpha_i, then X = \frac{1}{\sum_{i=1}^k{y_i}} (y_1, ..., y_n) is + Dirichlet distributed. + + Reference: + - David Mc Kay : Information Theory, inference and Learning + algorithms, chapter 23. the book is available for free at + http://www.inference.phy.cam.ac.uk/mackay/ + """ + + #================= + # Pure python algo + #================= + #alpha = N.atleast_1d(alpha) + #k = alpha.size + + #if n == 1: + # val = N.zeros(k) + # for i in range(k): + # val[i] = sgamma(alpha[i], n) + # val /= N.sum(val) + #else: + # val = N.zeros((k, n)) + # for i in range(k): + # val[i] = sgamma(alpha[i], n) + # val /= N.sum(val, axis = 0) + # val = val.T + + #return val + + cdef long k + cdef long totsize + cdef ndarray alpha_arr, val_arr + cdef double *alpha_data, *val_data + cdef long i, j + cdef double acc, invacc + + k = len(alpha) + alpha_arr = <ndarray>PyArray_ContiguousFromObject(alpha, NPY_DOUBLE, 1, 1) + alpha_data = <double*>alpha_arr.data + + if size is None: + shape = (k,) + elif type(size) is int: + shape = (size, k) + else: + shape = size + (k,) + + diric = _sp.zeros(shape, _sp.float64) + val_arr = <ndarray>diric + val_data= <double*>val_arr.data + + i = 0 + totsize = PyArray_SIZE(val_arr) + while i < totsize: + acc = 0.0 + for j from 0 <= j < k: + val_data[i+j] = rk_standard_gamma(self.internal_state, alpha_data[j]) + acc = acc + val_data[i+j] + invacc = 1/acc + for j from 0 <= j < k: + val_data[i+j] = val_data[i+j] * invacc + i = i + k + + return diric + + # Shuffling and permutations: + def shuffle(self, object x): + """Modify a sequence in-place by shuffling its contents. + + shuffle(x) + """ + cdef long i, j + cdef int copy + + i = len(x) - 1 + try: + j = len(x[0]) + except: + j = 0 + + if (j == 0): + # adaptation of random.shuffle() + while i > 0: + j = rk_interval(i, self.internal_state) + x[i], x[j] = x[j], x[i] + i = i - 1 + else: + # make copies + copy = hasattr(x[0], 'copy') + if copy: + while(i > 0): + j = rk_interval(i, self.internal_state) + x[i], x[j] = x[j].copy(), x[i].copy() + i = i - 1 + else: + while(i > 0): + j = rk_interval(i, self.internal_state) + x[i], x[j] = x[j][:], x[i][:] + i = i - 1 + + def permutation(self, object x): + """Given an integer, return a shuffled sequence of integers >= 0 and + < x; given a sequence, return a shuffled array copy. + + permutation(x) + """ + if isinstance(x, (int, _sp.integer)): + arr = _sp.arange(x) + else: + arr = _sp.array(x) + self.shuffle(arr) + return arr + +_rand = RandomState() +seed = _rand.seed +get_state = _rand.get_state +set_state = _rand.set_state +random_sample = _rand.random_sample +randint = _rand.randint +bytes = _rand.bytes +uniform = _rand.uniform +rand = _rand.rand +randn = _rand.randn +random_integers = _rand.random_integers +standard_normal = _rand.standard_normal +normal = _rand.normal +beta = _rand.beta +exponential = _rand.exponential +standard_exponential = _rand.standard_exponential +standard_gamma = _rand.standard_gamma +gamma = _rand.gamma +f = _rand.f +noncentral_f = _rand.noncentral_f +chisquare = _rand.chisquare +noncentral_chisquare = _rand.noncentral_chisquare +standard_cauchy = _rand.standard_cauchy +standard_t = _rand.standard_t +vonmises = _rand.vonmises +pareto = _rand.pareto +weibull = _rand.weibull +power = _rand.power +laplace = _rand.laplace +gumbel = _rand.gumbel +logistic = _rand.logistic +lognormal = _rand.lognormal +rayleigh = _rand.rayleigh +wald = _rand.wald +triangular = _rand.triangular + +binomial = _rand.binomial +negative_binomial = _rand.negative_binomial +poisson = _rand.poisson +zipf = _rand.zipf +geometric = _rand.geometric +hypergeometric = _rand.hypergeometric +logseries = _rand.logseries + +multivariate_normal = _rand.multivariate_normal +multinomial = _rand.multinomial +dirichlet = _rand.dirichlet + +shuffle = _rand.shuffle +permutation = _rand.permutation diff --git a/numpy/random/mtrand/numpy.pxi b/numpy/random/mtrand/numpy.pxi new file mode 100644 index 000000000..11cb8fac9 --- /dev/null +++ b/numpy/random/mtrand/numpy.pxi @@ -0,0 +1,133 @@ +# :Author: Travis Oliphant + +cdef extern from "numpy/arrayobject.h": + + cdef enum NPY_TYPES: + NPY_BOOL + NPY_BYTE + NPY_UBYTE + NPY_SHORT + NPY_USHORT + NPY_INT + NPY_UINT + NPY_LONG + NPY_ULONG + NPY_LONGLONG + NPY_ULONGLONG + NPY_FLOAT + NPY_DOUBLE + NPY_LONGDOUBLE + NPY_CFLOAT + NPY_CDOUBLE + NPY_CLONGDOUBLE + NPY_OBJECT + NPY_STRING + NPY_UNICODE + NPY_VOID + NPY_NTYPES + NPY_NOTYPE + + cdef enum requirements: + NPY_CONTIGUOUS + NPY_FORTRAN + NPY_OWNDATA + NPY_FORCECAST + NPY_ENSURECOPY + NPY_ENSUREARRAY + NPY_ELEMENTSTRIDES + NPY_ALIGNED + NPY_NOTSWAPPED + NPY_WRITEABLE + NPY_UPDATEIFCOPY + NPY_ARR_HAS_DESCR + + NPY_BEHAVED + NPY_BEHAVED_NS + NPY_CARRAY + NPY_CARRAY_RO + NPY_FARRAY + NPY_FARRAY_RO + NPY_DEFAULT + + NPY_IN_ARRAY + NPY_OUT_ARRAY + NPY_INOUT_ARRAY + NPY_IN_FARRAY + NPY_OUT_FARRAY + NPY_INOUT_FARRAY + + NPY_UPDATE_ALL + + cdef enum defines: + NPY_MAXDIMS + + ctypedef struct npy_cdouble: + double real + double imag + + ctypedef struct npy_cfloat: + double real + double imag + + ctypedef int npy_intp + + ctypedef extern class numpy.dtype [object PyArray_Descr]: + cdef int type_num, elsize, alignment + cdef char type, kind, byteorder, hasobject + cdef object fields, typeobj + + ctypedef extern class numpy.ndarray [object PyArrayObject]: + cdef char *data + cdef int nd + cdef npy_intp *dimensions + cdef npy_intp *strides + cdef object base + cdef dtype descr + cdef int flags + + ctypedef extern class numpy.flatiter [object PyArrayIterObject]: + cdef int nd_m1 + cdef npy_intp index, size + cdef ndarray ao + cdef char *dataptr + + ctypedef extern class numpy.broadcast [object PyArrayMultiIterObject]: + cdef int numiter + cdef npy_intp size, index + cdef int nd + cdef npy_intp *dimensions + cdef void **iters + + object PyArray_ZEROS(int ndims, npy_intp* dims, NPY_TYPES type_num, int fortran) + object PyArray_EMPTY(int ndims, npy_intp* dims, NPY_TYPES type_num, int fortran) + dtype PyArray_DescrFromTypeNum(NPY_TYPES type_num) + object PyArray_SimpleNew(int ndims, npy_intp* dims, NPY_TYPES type_num) + int PyArray_Check(object obj) + object PyArray_ContiguousFromAny(object obj, NPY_TYPES type, + int mindim, int maxdim) + object PyArray_ContiguousFromObject(object obj, NPY_TYPES type, + int mindim, int maxdim) + npy_intp PyArray_SIZE(ndarray arr) + npy_intp PyArray_NBYTES(ndarray arr) + void *PyArray_DATA(ndarray arr) + object PyArray_FromAny(object obj, dtype newtype, int mindim, int maxdim, + int requirements, object context) + object PyArray_FROMANY(object obj, NPY_TYPES type_num, int min, + int max, int requirements) + object PyArray_NewFromDescr(object subtype, dtype newtype, int nd, + npy_intp* dims, npy_intp* strides, void* data, + int flags, object parent) + + object PyArray_FROM_OTF(object obj, NPY_TYPES type, int flags) + object PyArray_EnsureArray(object) + + object PyArray_MultiIterNew(int n, ...) + + char *PyArray_MultiIter_DATA(broadcast multi, int i) + void PyArray_MultiIter_NEXTi(broadcast multi, int i) + void PyArray_MultiIter_NEXT(broadcast multi) + + object PyArray_IterNew(object arr) + void PyArray_ITER_NEXT(flatiter it) + + void import_array() diff --git a/numpy/random/mtrand/randomkit.c b/numpy/random/mtrand/randomkit.c new file mode 100644 index 000000000..56f52c0b4 --- /dev/null +++ b/numpy/random/mtrand/randomkit.c @@ -0,0 +1,365 @@ +/* Random kit 1.3 */ + +/* + * Copyright (c) 2003-2005, Jean-Sebastien Roy (js@jeannot.org) + * + * The rk_random and rk_seed functions algorithms and the original design of + * the Mersenne Twister RNG: + * + * Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, + * All rights reserved. + * + * Redistribution and use in source and binary forms, with or without + * modification, are permitted provided that the following conditions + * are met: + * + * 1. Redistributions of source code must retain the above copyright + * notice, this list of conditions and the following disclaimer. + * + * 2. Redistributions in binary form must reproduce the above copyright + * notice, this list of conditions and the following disclaimer in the + * documentation and/or other materials provided with the distribution. + * + * 3. The names of its contributors may not be used to endorse or promote + * products derived from this software without specific prior written + * permission. + * + * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS + * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT + * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR + * A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR + * CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, + * EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, + * PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR + * PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF + * LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING + * NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + * SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + * + * Original algorithm for the implementation of rk_interval function from + * Richard J. Wagner's implementation of the Mersenne Twister RNG, optimised by + * Magnus Jonsson. + * + * Constants used in the rk_double implementation by Isaku Wada. + * + * Permission is hereby granted, free of charge, to any person obtaining a + * copy of this software and associated documentation files (the + * "Software"), to deal in the Software without restriction, including + * without limitation the rights to use, copy, modify, merge, publish, + * distribute, sublicense, and/or sell copies of the Software, and to + * permit persons to whom the Software is furnished to do so, subject to + * the following conditions: + * + * The above copyright notice and this permission notice shall be included + * in all copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS + * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + */ + +/* static char const rcsid[] = + "@(#) $Jeannot: randomkit.c,v 1.28 2005/07/21 22:14:09 js Exp $"; */ + +#include <stddef.h> +#include <stdio.h> +#include <stdlib.h> +#include <errno.h> +#include <time.h> +#include <limits.h> +#include <math.h> + +#ifdef _WIN32 +/* Windows */ +#include <sys/timeb.h> +#ifndef RK_NO_WINCRYPT +/* Windows crypto */ +#ifndef _WIN32_WINNT +#define _WIN32_WINNT 0x0400 +#endif +#include <windows.h> +#include <wincrypt.h> +#endif +#else +/* Unix */ +#include <sys/time.h> +#include <unistd.h> +#endif + +#include "randomkit.h" + +#ifndef RK_DEV_URANDOM +#define RK_DEV_URANDOM "/dev/urandom" +#endif + +#ifndef RK_DEV_RANDOM +#define RK_DEV_RANDOM "/dev/random" +#endif + +char *rk_strerror[RK_ERR_MAX] = +{ + "no error", + "random device unvavailable" +}; + +/* static functions */ +static unsigned long rk_hash(unsigned long key); + +void rk_seed(unsigned long seed, rk_state *state) +{ + int pos; + seed &= 0xffffffffUL; + + /* Knuth's PRNG as used in the Mersenne Twister reference implementation */ + for (pos=0; pos<RK_STATE_LEN; pos++) + { + state->key[pos] = seed; + seed = (1812433253UL * (seed ^ (seed >> 30)) + pos + 1) & 0xffffffffUL; + } + + state->pos = RK_STATE_LEN; + state->has_gauss = 0; + state->has_binomial = 0; +} + +/* Thomas Wang 32 bits integer hash function */ +unsigned long rk_hash(unsigned long key) +{ + key += ~(key << 15); + key ^= (key >> 10); + key += (key << 3); + key ^= (key >> 6); + key += ~(key << 11); + key ^= (key >> 16); + return key; +} + +rk_error rk_randomseed(rk_state *state) +{ +#ifndef _WIN32 + struct timeval tv; +#else + struct _timeb tv; +#endif + int i; + + if(rk_devfill(state->key, sizeof(state->key), 0) == RK_NOERR) + { + state->key[0] |= 0x80000000UL; /* ensures non-zero key */ + state->pos = RK_STATE_LEN; + state->has_gauss = 0; + state->has_binomial = 0; + + for (i=0; i<624; i++) + { + state->key[i] &= 0xffffffffUL; + } + + return RK_NOERR; + } + +#ifndef _WIN32 + gettimeofday(&tv, NULL); + rk_seed(rk_hash(getpid()) ^ rk_hash(tv.tv_sec) ^ rk_hash(tv.tv_usec) + ^ rk_hash(clock()), state); +#else + _ftime(&tv); + rk_seed(rk_hash(tv.time) ^ rk_hash(tv.millitm) ^ rk_hash(clock()), state); +#endif + + return RK_ENODEV; +} + +/* Magic Mersenne Twister constants */ +#define N 624 +#define M 397 +#define MATRIX_A 0x9908b0dfUL +#define UPPER_MASK 0x80000000UL +#define LOWER_MASK 0x7fffffffUL + +/* Slightly optimised reference implementation of the Mersenne Twister */ +unsigned long rk_random(rk_state *state) +{ + unsigned long y; + + if (state->pos == RK_STATE_LEN) + { + int i; + + for (i=0;i<N-M;i++) + { + y = (state->key[i] & UPPER_MASK) | (state->key[i+1] & LOWER_MASK); + state->key[i] = state->key[i+M] ^ (y>>1) ^ (-(y & 1) & MATRIX_A); + } + for (;i<N-1;i++) + { + y = (state->key[i] & UPPER_MASK) | (state->key[i+1] & LOWER_MASK); + state->key[i] = state->key[i+(M-N)] ^ (y>>1) ^ (-(y & 1) & MATRIX_A); + } + y = (state->key[N-1] & UPPER_MASK) | (state->key[0] & LOWER_MASK); + state->key[N-1] = state->key[M-1] ^ (y>>1) ^ (-(y & 1) & MATRIX_A); + + state->pos = 0; + } + + y = state->key[state->pos++]; + + /* Tempering */ + y ^= (y >> 11); + y ^= (y << 7) & 0x9d2c5680UL; + y ^= (y << 15) & 0xefc60000UL; + y ^= (y >> 18); + + return y; +} + +long rk_long(rk_state *state) +{ + return rk_ulong(state) >> 1; +} + +unsigned long rk_ulong(rk_state *state) +{ +#if ULONG_MAX <= 0xffffffffUL + return rk_random(state); +#else + return (rk_random(state) << 32) | (rk_random(state)); +#endif +} + +unsigned long rk_interval(unsigned long max, rk_state *state) +{ + unsigned long mask = max, value; + + if (max == 0) return 0; + + /* Smallest bit mask >= max */ + mask |= mask >> 1; + mask |= mask >> 2; + mask |= mask >> 4; + mask |= mask >> 8; + mask |= mask >> 16; +#if ULONG_MAX > 0xffffffffUL + mask |= mask >> 32; +#endif + + /* Search a random value in [0..mask] <= max */ +#if ULONG_MAX > 0xffffffffUL + if (max <= 0xffffffffUL) { + while ((value = (rk_random(state) & mask)) > max); + } else { + while ((value = (rk_ulong(state) & mask)) > max); + } +#else + while ((value = (rk_ulong(state) & mask)) > max); +#endif + + return value; +} + +double rk_double(rk_state *state) +{ + /* shifts : 67108864 = 0x4000000, 9007199254740992 = 0x20000000000000 */ + long a = rk_random(state) >> 5, b = rk_random(state) >> 6; + return (a * 67108864.0 + b) / 9007199254740992.0; +} + +void rk_fill(void *buffer, size_t size, rk_state *state) +{ + unsigned long r; + unsigned char *buf = buffer; + + for (; size >= 4; size -= 4) + { + r = rk_random(state); + *(buf++) = r & 0xFF; + *(buf++) = (r >> 8) & 0xFF; + *(buf++) = (r >> 16) & 0xFF; + *(buf++) = (r >> 24) & 0xFF; + } + + if (!size) return; + + r = rk_random(state); + + for (; size; r >>= 8, size --) + *(buf++) = (unsigned char)(r & 0xFF); +} + +rk_error rk_devfill(void *buffer, size_t size, int strong) +{ +#ifndef _WIN32 + FILE *rfile; + int done; + + if (strong) + rfile = fopen(RK_DEV_RANDOM, "rb"); + else + rfile = fopen(RK_DEV_URANDOM, "rb"); + if (rfile == NULL) + return RK_ENODEV; + done = fread(buffer, size, 1, rfile); + fclose(rfile); + if (done) + return RK_NOERR; +#else + +#ifndef RK_NO_WINCRYPT + HCRYPTPROV hCryptProv; + BOOL done; + + if (!CryptAcquireContext(&hCryptProv, NULL, NULL, PROV_RSA_FULL, + CRYPT_VERIFYCONTEXT) || !hCryptProv) + return RK_ENODEV; + done = CryptGenRandom(hCryptProv, size, (unsigned char *)buffer); + CryptReleaseContext(hCryptProv, 0); + if (done) + return RK_NOERR; +#endif + +#endif + + return RK_ENODEV; +} + +rk_error rk_altfill(void *buffer, size_t size, int strong, rk_state *state) +{ + rk_error err; + + err = rk_devfill(buffer, size, strong); + if (err) + rk_fill(buffer, size, state); + + return err; +} + +double rk_gauss(rk_state *state) +{ + if (state->has_gauss) + { + state->has_gauss = 0; + return state->gauss; + } + else + { + double f, x1, x2, r2; + do + { + x1 = 2.0*rk_double(state) - 1.0; + x2 = 2.0*rk_double(state) - 1.0; + r2 = x1*x1 + x2*x2; + } + while (r2 >= 1.0 || r2 == 0.0); + + f = sqrt(-2.0*log(r2)/r2); /* Box-Muller transform */ + state->has_gauss = 1; + state->gauss = f*x1; /* Keep for next call */ + return f*x2; + } +} + + diff --git a/numpy/random/mtrand/randomkit.h b/numpy/random/mtrand/randomkit.h new file mode 100644 index 000000000..389666854 --- /dev/null +++ b/numpy/random/mtrand/randomkit.h @@ -0,0 +1,189 @@ +/* Random kit 1.3 */ + +/* + * Copyright (c) 2003-2005, Jean-Sebastien Roy (js@jeannot.org) + * + * Permission is hereby granted, free of charge, to any person obtaining a + * copy of this software and associated documentation files (the + * "Software"), to deal in the Software without restriction, including + * without limitation the rights to use, copy, modify, merge, publish, + * distribute, sublicense, and/or sell copies of the Software, and to + * permit persons to whom the Software is furnished to do so, subject to + * the following conditions: + * + * The above copyright notice and this permission notice shall be included + * in all copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS + * OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF + * MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. + * IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY + * CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, + * TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE + * SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + */ + +/* @(#) $Jeannot: randomkit.h,v 1.24 2005/07/21 22:14:09 js Exp $ */ + +/* + * Typical use: + * + * { + * rk_state state; + * unsigned long seed = 1, random_value; + * + * rk_seed(seed, &state); // Initialize the RNG + * ... + * random_value = rk_random(&state); // Generate random values in [0..RK_MAX] + * } + * + * Instead of rk_seed, you can use rk_randomseed which will get a random seed + * from /dev/urandom (or the clock, if /dev/urandom is unavailable): + * + * { + * rk_state state; + * unsigned long random_value; + * + * rk_randomseed(&state); // Initialize the RNG with a random seed + * ... + * random_value = rk_random(&state); // Generate random values in [0..RK_MAX] + * } + */ + +/* + * Useful macro: + * RK_DEV_RANDOM: the device used for random seeding. + * defaults to "/dev/urandom" + */ + +#include <stddef.h> + +#ifndef _RANDOMKIT_ +#define _RANDOMKIT_ + +#define RK_STATE_LEN 624 + +typedef struct rk_state_ +{ + unsigned long key[RK_STATE_LEN]; + int pos; + int has_gauss; /* !=0: gauss contains a gaussian deviate */ + double gauss; + + /* The rk_state structure has been extended to store the following + * information for the binomial generator. If the input values of n or p + * are different than nsave and psave, then the other parameters will be + * recomputed. RTK 2005-09-02 */ + + int has_binomial; /* !=0: following parameters initialized for + binomial */ + double psave; + long nsave; + double r; + double q; + double fm; + long m; + double p1; + double xm; + double xl; + double xr; + double c; + double laml; + double lamr; + double p2; + double p3; + double p4; + +} +rk_state; + +typedef enum { + RK_NOERR = 0, /* no error */ + RK_ENODEV = 1, /* no RK_DEV_RANDOM device */ + RK_ERR_MAX = 2 +} rk_error; + +/* error strings */ +extern char *rk_strerror[RK_ERR_MAX]; + +/* Maximum generated random value */ +#define RK_MAX 0xFFFFFFFFUL + +#ifdef __cplusplus +extern "C" { +#endif + +/* + * Initialize the RNG state using the given seed. + */ +extern void rk_seed(unsigned long seed, rk_state *state); + +/* + * Initialize the RNG state using a random seed. + * Uses /dev/random or, when unavailable, the clock (see randomkit.c). + * Returns RK_NOERR when no errors occurs. + * Returns RK_ENODEV when the use of RK_DEV_RANDOM failed (for example because + * there is no such device). In this case, the RNG was initialized using the + * clock. + */ +extern rk_error rk_randomseed(rk_state *state); + +/* + * Returns a random unsigned long between 0 and RK_MAX inclusive + */ +extern unsigned long rk_random(rk_state *state); + +/* + * Returns a random long between 0 and LONG_MAX inclusive + */ +extern long rk_long(rk_state *state); + +/* + * Returns a random unsigned long between 0 and ULONG_MAX inclusive + */ +extern unsigned long rk_ulong(rk_state *state); + +/* + * Returns a random unsigned long between 0 and max inclusive. + */ +extern unsigned long rk_interval(unsigned long max, rk_state *state); + +/* + * Returns a random double between 0.0 and 1.0, 1.0 excluded. + */ +extern double rk_double(rk_state *state); + +/* + * fill the buffer with size random bytes + */ +extern void rk_fill(void *buffer, size_t size, rk_state *state); + +/* + * fill the buffer with randombytes from the random device + * Returns RK_ENODEV if the device is unavailable, or RK_NOERR if it is + * On Unix, if strong is defined, RK_DEV_RANDOM is used. If not, RK_DEV_URANDOM + * is used instead. This parameter has no effect on Windows. + * Warning: on most unixes RK_DEV_RANDOM will wait for enough entropy to answer + * which can take a very long time on quiet systems. + */ +extern rk_error rk_devfill(void *buffer, size_t size, int strong); + +/* + * fill the buffer using rk_devfill if the random device is available and using + * rk_fill if is is not + * parameters have the same meaning as rk_fill and rk_devfill + * Returns RK_ENODEV if the device is unavailable, or RK_NOERR if it is + */ +extern rk_error rk_altfill(void *buffer, size_t size, int strong, + rk_state *state); + +/* + * return a random gaussian deviate with variance unity and zero mean. + */ +extern double rk_gauss(rk_state *state); + +#ifdef __cplusplus +} +#endif + +#endif /* _RANDOMKIT_ */ diff --git a/numpy/random/setup.py b/numpy/random/setup.py new file mode 100644 index 000000000..6525034a8 --- /dev/null +++ b/numpy/random/setup.py @@ -0,0 +1,53 @@ +from os.path import join, split + +def configuration(parent_package='',top_path=None): + from numpy.distutils.misc_util import Configuration, get_mathlibs + config = Configuration('random',parent_package,top_path) + + def generate_libraries(ext, build_dir): + config_cmd = config.get_config_cmd() + if top_path is None: + libs = get_mathlibs() + else: + path = join(split(build_dir)[0],'core') + libs = get_mathlibs(path) + tc = testcode_wincrypt() + if config_cmd.try_run(tc): + libs.append('Advapi32') + ext.libraries.extend(libs) + return None + + libs = [] + # Configure mtrand + config.add_extension('mtrand', + sources=[join('mtrand', x) for x in + ['mtrand.c', 'randomkit.c', 'initarray.c', + 'distributions.c']]+[generate_libraries], + libraries=libs, + depends = [join('mtrand','*.h'), + join('mtrand','*.pyx'), + join('mtrand','*.pxi'), + ] + ) + + config.add_data_files(('.', join('mtrand', 'randomkit.h'))) + + return config + +def testcode_wincrypt(): + return """\ +/* check to see if _WIN32 is defined */ +int main(int argc, char *argv[]) +{ +#ifdef _WIN32 + return 0; +#else +#error No _WIN32 +#endif + return -1; +} +""" + +if __name__ == '__main__': + from numpy.distutils.core import setup + setup(configuration=configuration) |