Merge pull request #94 from zoj613/version

Author: zoj613

README.md

@@ -42,7 +42,7 @@ of multi-dimensional samples without specifying the size.
 existing libraries.
 - `polyagamma` is optimized for performance and tests show that it is faster
   than other implementations.
-- Pre-built wheels are provided for easy installation on `x86_64` linux systems.
+- Pre-built wheels are provided for easy installation on Linux, MacOS and Windows.
 
 
 ## Examples
@@ -165,7 +165,9 @@ and the following shell commands:
 ```shell
 $ git clone https://github.com/zoj613/polya-gamma.git
 $ cd polya-gamma/
-$ poetry install
+# install dependencies
+$ poetry install --no-root
+$ make install
 # add package to python's path
 $ export PYTHONPATH=$PWD:$PYTHONPATH 
 ```
@@ -196,7 +198,7 @@ method and also equally accurate).
 Therefore, we devise a "hybrid/default" sampler that picks a sampler based on the above guidelines.
 
 We also benchmark the hybrid sampler runtime with the sampler found in the `pypolyagamma` 
-package (version `1.2.3`). The version of NumPy we use is `1.18.5`. We compare our
+package (version `1.2.3`). The version of NumPy we use is `1.19.0`. We compare our
 sampler to the `pgdrawv` functions provided by the package. Below are runtime plots of 20000
 samples for each value of `h` and `z`. Values of `h` range from 0.1 to 50, while `z` is set
 to 0, 2.5, 5, and 10.

polyagamma/__init__.py

@@ -2,4 +2,4 @@
     polyagamma as random_polyagamma, polyagamma_pdf, polyagamma_cdf
 )
 
-__version__ = '1.3.1'
+__version__ = '1.3.2-beta.2'

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "polyagamma"
-version = "1.3.1"
+version = "1.3.2-beta.2"
 description = "Efficiently generate samples from the Polya-Gamma distribution using a NumPy/SciPy compatible interface."
 authors = ["Zolisa Bleki"]
 license = "BSD-3-Clause"
@@ -14,7 +14,9 @@ classifiers = [
     "Programming Language :: C",
     "Programming Language :: Python",
     "Programming Language :: Python :: 3 :: Only",
-    "Operating System :: Unix",
+    "Operating System :: POSIX :: Linux",
+    "Operating System :: Microsoft :: Windows :: Windows 10",
+    "Operating System :: MacOS :: MacOS X",
     "Typing :: Typed",
 ]
 packages = [{include = "polyagamma/*.py"}]

src/pgm_random.c

@@ -3,7 +3,9 @@
  * SPDX-License-Identifier: BSD-3-Clause */
 #include "../include/pgm_random.h"
 
-#if defined(__GNUC__) || defined(__clang__)
+#if defined(_MSC_VER)
+    #define PGM_INLINE __inline
+#elif defined(__GNUC__) || defined(__clang__)
     #define PGM_INLINE inline
 #else
     #define PGM_INLINE
@@ -28,13 +30,13 @@ random_polyagamma_saddle(bitgen_t* bitgen_state, double h, double z,
 
 /* libc math library forward declarations */
 double
-sinh(double __x);
+sinh(double x);
 double
-tanh(double __x);
+tanh(double x);
 double
-sqrt(double __x);
+sqrt(double x);
 double
-fabs(double __x);
+fabs(double x);
 
 /*
  * Sample from a PG(h. z) using a Normal Approximation. For sufficiently large
@@ -72,7 +74,7 @@ random_polyagamma_normal_approx(bitgen_t* bitgen_state, double h, double z,
 #endif
 
 void*
-memset(void* __s, int __c, size_t __n);
+memset(void* s, int c, size_t n);
 /*
  * Sample from PG(h, z) using the Gamma convolution approximation method.
  *
@@ -126,7 +128,7 @@ random_polyagamma_hybrid(bitgen_t* bitgen_state, double h, double z,
 typedef void
 (*pgm_func_t)(bitgen_t* bitgen_state, double h, double z, size_t n, double* out);
 
-const pgm_func_t sampling_method_table[] = {
+static const pgm_func_t sampling_method_table[] = {
     [ALTERNATE] = random_polyagamma_alternate,
     [DEVROYE] = random_polyagamma_devroye,
     [SADDLE] = random_polyagamma_saddle,
@@ -135,7 +137,7 @@ const pgm_func_t sampling_method_table[] = {
 };
 
 
-PGM_INLINE double
+double
 pgm_random_polyagamma(bitgen_t* bitgen_state, double h, double z, sampler_t method)
 {
     double out;
@@ -145,15 +147,15 @@ pgm_random_polyagamma(bitgen_t* bitgen_state, double h, double z, sampler_t meth
 }
 
 
-PGM_INLINE void
+void
 pgm_random_polyagamma_fill(bitgen_t* bitgen_state, double h, double z,
                            sampler_t method, size_t n, double* out)
 {
     sampling_method_table[method](bitgen_state, h, z, n, out);
 }
 
 
-PGM_INLINE void
+void
 pgm_random_polyagamma_fill2(bitgen_t* bitgen_state, const double* h, const double* z,
                             sampler_t method, size_t n, double* restrict out)
 {