MAINT: Implement API changes for randomgen-derived code

remove numpy.random.gen, BRNG.generator, pcg*, rand, randn
remove use_mask and Lemire's method, fix benchmarks for PCG removal
convert brng to bitgen (in C) and bit_generator (in python)
convert base R{NG,andom.*} to BitGenerator, fix last commit
randint -> integers, remove rand, randn, random_integers
RandomGenerator -> Generator, more "basic RNG" -> BitGenerator
random_sample -> random, jump -> jumped, resync with randomgen
Remove derived code from entropy
Port over changes accepted in upstream to protect log(0.0) where relevant
fix doctests for jumped, better document choice
Remove Python 2.7 shims
Use NPY_INLINE to simplify
Fix performance.py to work
Renam directory brng to bit_generators
Fix examples wiht new directory structure
Clarify relationship to historical RandomState
Remove references to .generator
Rename xoshiro256/512starstar

3 files changed, 47 insertions, 77 deletions

diff --git a/numpy/random/src/legacy/LICENSE.md b/numpy/random/src/legacy/LICENSE.md
deleted file mode 100644
index 88b1791b2..000000000
--- a/numpy/random/src/legacy/LICENSE.md
+++ /dev/null
@@ -1,30 +0,0 @@
-Copyright (c) 2005-2017, NumPy Developers.
-All rights reserved.
-
-Redistribution and use in source and binary forms, with or without
-modification, are permitted provided that the following conditions are
-met:
-
-* Redistributions of source code must retain the above copyright
-   notice, this list of conditions and the following disclaimer.
-
-* 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.
-
-* Neither the name of the NumPy Developers nor the names of any
-   contributors may 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.
diff --git a/numpy/random/src/legacy/distributions-boxmuller.c b/numpy/random/src/legacy/distributions-boxmuller.c
index 5d3ba27f8..2c715799f 100644
--- a/numpy/random/src/legacy/distributions-boxmuller.c
+++ b/numpy/random/src/legacy/distributions-boxmuller.c
@@ -1,10 +1,10 @@
 #include "distributions-boxmuller.h"
 
-static NPY_INLINE double legacy_double(aug_brng_t *aug_state) {
-  return aug_state->basicrng->next_double(aug_state->basicrng->state);
+static NPY_INLINE double legacy_double(aug_bitgen_t *aug_state) {
+  return aug_state->bit_generator->next_double(aug_state->bit_generator->state);
 }
 
-double legacy_gauss(aug_brng_t *aug_state) {
+double legacy_gauss(aug_bitgen_t *aug_state) {
   if (aug_state->has_gauss) {
     const double temp = aug_state->gauss;
     aug_state->has_gauss = false;
@@ -28,12 +28,12 @@ double legacy_gauss(aug_brng_t *aug_state) {
   }
 }
 
-double legacy_standard_exponential(aug_brng_t *aug_state) {
+double legacy_standard_exponential(aug_bitgen_t *aug_state) {
   /* We use -log(1-U) since U is [0, 1) */
   return -log(1.0 - legacy_double(aug_state));
 }
 
-double legacy_standard_gamma(aug_brng_t *aug_state, double shape) {
+double legacy_standard_gamma(aug_bitgen_t *aug_state, double shape) {
   double b, c;
   double U, V, X, Y;
 
@@ -78,30 +78,30 @@ double legacy_standard_gamma(aug_brng_t *aug_state, double shape) {
   }
 }
 
-double legacy_gamma(aug_brng_t *aug_state, double shape, double scale) {
+double legacy_gamma(aug_bitgen_t *aug_state, double shape, double scale) {
   return scale * legacy_standard_gamma(aug_state, shape);
 }
 
-double legacy_pareto(aug_brng_t *aug_state, double a) {
+double legacy_pareto(aug_bitgen_t *aug_state, double a) {
   return exp(legacy_standard_exponential(aug_state) / a) - 1;
 }
 
-double legacy_weibull(aug_brng_t *aug_state, double a) {
+double legacy_weibull(aug_bitgen_t *aug_state, double a) {
   if (a == 0.0) {
     return 0.0;
   }
   return pow(legacy_standard_exponential(aug_state), 1. / a);
 }
 
-double legacy_power(aug_brng_t *aug_state, double a) {
+double legacy_power(aug_bitgen_t *aug_state, double a) {
   return pow(1 - exp(-legacy_standard_exponential(aug_state)), 1. / a);
 }
 
-double legacy_chisquare(aug_brng_t *aug_state, double df) {
+double legacy_chisquare(aug_bitgen_t *aug_state, double df) {
   return 2.0 * legacy_standard_gamma(aug_state, df / 2.0);
 }
 
-double legacy_noncentral_chisquare(aug_brng_t *aug_state, double df,
+double legacy_noncentral_chisquare(aug_bitgen_t *aug_state, double df,
                                    double nonc) {
   double out;
   if (nonc == 0) {
@@ -112,7 +112,7 @@ double legacy_noncentral_chisquare(aug_brng_t *aug_state, double df,
     const double n = legacy_gauss(aug_state) + sqrt(nonc);
     return Chi2 + n * n;
   } else {
-    const long i = random_poisson(aug_state->basicrng, nonc / 2.0);
+    const long i = random_poisson(aug_state->bit_generator, nonc / 2.0);
     out = legacy_chisquare(aug_state, df + 2 * i);
     /* Insert nan guard here to avoid changing the stream */
     if (npy_isnan(nonc)){
@@ -123,13 +123,13 @@ double legacy_noncentral_chisquare(aug_brng_t *aug_state, double df,
   }
 }
 
-double legacy_noncentral_f(aug_brng_t *aug_state, double dfnum, double dfden,
+double legacy_noncentral_f(aug_bitgen_t *aug_state, double dfnum, double dfden,
                            double nonc) {
   double t = legacy_noncentral_chisquare(aug_state, dfnum, nonc) * dfden;
   return t / (legacy_chisquare(aug_state, dfden) * dfnum);
 }
 
-double legacy_wald(aug_brng_t *aug_state, double mean, double scale) {
+double legacy_wald(aug_bitgen_t *aug_state, double mean, double scale) {
   double U, X, Y;
   double mu_2l;
 
@@ -145,15 +145,15 @@ double legacy_wald(aug_brng_t *aug_state, double mean, double scale) {
   }
 }
 
-double legacy_normal(aug_brng_t *aug_state, double loc, double scale) {
+double legacy_normal(aug_bitgen_t *aug_state, double loc, double scale) {
   return loc + scale * legacy_gauss(aug_state);
 }
 
-double legacy_lognormal(aug_brng_t *aug_state, double mean, double sigma) {
+double legacy_lognormal(aug_bitgen_t *aug_state, double mean, double sigma) {
   return exp(legacy_normal(aug_state, mean, sigma));
 }
 
-double legacy_standard_t(aug_brng_t *aug_state, double df) {
+double legacy_standard_t(aug_bitgen_t *aug_state, double df) {
   double num, denom;
 
   num = legacy_gauss(aug_state);
@@ -161,16 +161,16 @@ double legacy_standard_t(aug_brng_t *aug_state, double df) {
   return sqrt(df / 2) * num / sqrt(denom);
 }
 
-int64_t legacy_negative_binomial(aug_brng_t *aug_state, double n, double p) {
+int64_t legacy_negative_binomial(aug_bitgen_t *aug_state, double n, double p) {
   double Y = legacy_gamma(aug_state, n, (1 - p) / p);
-  return random_poisson(aug_state->basicrng, Y);
+  return random_poisson(aug_state->bit_generator, Y);
 }
 
-double legacy_standard_cauchy(aug_brng_t *aug_state) {
+double legacy_standard_cauchy(aug_bitgen_t *aug_state) {
   return legacy_gauss(aug_state) / legacy_gauss(aug_state);
 }
 
-double legacy_beta(aug_brng_t *aug_state, double a, double b) {
+double legacy_beta(aug_bitgen_t *aug_state, double a, double b) {
   double Ga, Gb;
 
   if ((a <= 1.0) && (b <= 1.0)) {
@@ -204,11 +204,11 @@ double legacy_beta(aug_brng_t *aug_state, double a, double b) {
   }
 }
 
-double legacy_f(aug_brng_t *aug_state, double dfnum, double dfden) {
+double legacy_f(aug_bitgen_t *aug_state, double dfnum, double dfden) {
   return ((legacy_chisquare(aug_state, dfnum) * dfden) /
           (legacy_chisquare(aug_state, dfden) * dfnum));
 }
 
-double legacy_exponential(aug_brng_t *aug_state, double scale) {
+double legacy_exponential(aug_bitgen_t *aug_state, double scale) {
   return scale * legacy_standard_exponential(aug_state);
 }
diff --git a/numpy/random/src/legacy/distributions-boxmuller.h b/numpy/random/src/legacy/distributions-boxmuller.h
index 445686e6c..07e093b26 100644
--- a/numpy/random/src/legacy/distributions-boxmuller.h
+++ b/numpy/random/src/legacy/distributions-boxmuller.h
@@ -4,37 +4,37 @@
 
 #include "../distributions/distributions.h"
 
-typedef struct aug_brng {
-  brng_t *basicrng;
+typedef struct aug_bitgen {
+  bitgen_t *bit_generator;
   int has_gauss;
   double gauss;
-} aug_brng_t;
+} aug_bitgen_t;
 
-extern double legacy_gauss(aug_brng_t *aug_state);
-extern double legacy_standard_exponential(aug_brng_t *aug_state);
-extern double legacy_pareto(aug_brng_t *aug_state, double a);
-extern double legacy_weibull(aug_brng_t *aug_state, double a);
-extern double legacy_power(aug_brng_t *aug_state, double a);
-extern double legacy_gamma(aug_brng_t *aug_state, double shape, double scale);
-extern double legacy_pareto(aug_brng_t *aug_state, double a);
-extern double legacy_weibull(aug_brng_t *aug_state, double a);
-extern double legacy_chisquare(aug_brng_t *aug_state, double df);
-extern double legacy_noncentral_chisquare(aug_brng_t *aug_state, double df,
+extern double legacy_gauss(aug_bitgen_t *aug_state);
+extern double legacy_standard_exponential(aug_bitgen_t *aug_state);
+extern double legacy_pareto(aug_bitgen_t *aug_state, double a);
+extern double legacy_weibull(aug_bitgen_t *aug_state, double a);
+extern double legacy_power(aug_bitgen_t *aug_state, double a);
+extern double legacy_gamma(aug_bitgen_t *aug_state, double shape, double scale);
+extern double legacy_pareto(aug_bitgen_t *aug_state, double a);
+extern double legacy_weibull(aug_bitgen_t *aug_state, double a);
+extern double legacy_chisquare(aug_bitgen_t *aug_state, double df);
+extern double legacy_noncentral_chisquare(aug_bitgen_t *aug_state, double df,
                                           double nonc);
 
-extern double legacy_noncentral_f(aug_brng_t *aug_state, double dfnum,
+extern double legacy_noncentral_f(aug_bitgen_t *aug_state, double dfnum,
                                   double dfden, double nonc);
-extern double legacy_wald(aug_brng_t *aug_state, double mean, double scale);
-extern double legacy_lognormal(aug_brng_t *aug_state, double mean,
+extern double legacy_wald(aug_bitgen_t *aug_state, double mean, double scale);
+extern double legacy_lognormal(aug_bitgen_t *aug_state, double mean,
                                double sigma);
-extern double legacy_standard_t(aug_brng_t *aug_state, double df);
-extern int64_t legacy_negative_binomial(aug_brng_t *aug_state, double n,
+extern double legacy_standard_t(aug_bitgen_t *aug_state, double df);
+extern int64_t legacy_negative_binomial(aug_bitgen_t *aug_state, double n,
                                         double p);
-extern double legacy_standard_cauchy(aug_brng_t *state);
-extern double legacy_beta(aug_brng_t *aug_state, double a, double b);
-extern double legacy_f(aug_brng_t *aug_state, double dfnum, double dfden);
-extern double legacy_normal(aug_brng_t *aug_state, double loc, double scale);
-extern double legacy_standard_gamma(aug_brng_t *aug_state, double shape);
-extern double legacy_exponential(aug_brng_t *aug_state, double scale);
+extern double legacy_standard_cauchy(aug_bitgen_t *state);
+extern double legacy_beta(aug_bitgen_t *aug_state, double a, double b);
+extern double legacy_f(aug_bitgen_t *aug_state, double dfnum, double dfden);
+extern double legacy_normal(aug_bitgen_t *aug_state, double loc, double scale);
+extern double legacy_standard_gamma(aug_bitgen_t *aug_state, double shape);
+extern double legacy_exponential(aug_bitgen_t *aug_state, double scale);
 
 #endif