REF: Add aray fillers for multiple data types

Use template system to generate array fillers for doubles and floats
Add array filler that fills 32-bit array using 64-bit RNGs

Author: bashtage

randomstate/array_fillers.pxi.in

@@ -0,0 +1,66 @@
+ctypedef void (* random_float_fill)(aug_state* state, np.npy_intp count, float *out) nogil
+ctypedef void (* random_double_fill)(aug_state* state, np.npy_intp count, double *out) nogil
+
+{{
+py:
+ctypes = (('float64', 'double'),
+          ('float32', 'float')) 
+}}
+{{for  nptype, ctype in ctypes}}
+
+
+cdef object {{ctype}}_fill(aug_state* state, void *func, object size, object lock):
+    cdef random_{{ctype}}_fill f = <random_{{ctype}}_fill>func
+    cdef {{ctype}} out
+    cdef {{ctype}} *out_array_data
+    cdef np.ndarray out_array
+    cdef np.npy_intp n
+
+    if size is None:
+        with lock:
+            f(state, 1, &out)
+        return out
+    else:
+        out_array = <np.ndarray>np.empty(size, np.{{nptype}})
+        n = np.PyArray_SIZE(out_array)
+        out_array_data = <{{ctype}} *>np.PyArray_DATA(out_array)
+        with lock, nogil:
+            f(state, n, out_array_data)
+        return out_array
+
+{{endfor}}
+
+
+cdef object float_fill_from_double(aug_state* state, void *func, object size, object lock):
+    cdef random_double_fill f = <random_double_fill>func
+    cdef double out
+    cdef double* buffer
+    cdef float *out_array_data
+    cdef np.ndarray out_array
+    cdef np.npy_intp i, n, buffer_size, remaining, total, fetch
+
+    if size is None:
+        with lock:
+            f(state, 1, &out)
+        return <float>out
+    else:
+        out_array = <np.ndarray>np.empty(size, np.float32)
+        n = np.PyArray_SIZE(out_array)
+        buffer_size = 1000 if n > 1000 else n
+        total = 0
+        remaining = n
+        buffer = <double *> malloc(buffer_size * sizeof(double))
+
+        out_array_data = <float *>np.PyArray_DATA(out_array)
+        while remaining > 0:
+            fetch = 1000 if remaining > 1000 else remaining
+            with lock, nogil:
+                f(state, fetch, buffer)
+            for i in range(fetch):
+                out_array_data[i + total] = <float> buffer[i]
+            total += fetch
+            remaining -= fetch
+
+        free(buffer)
+
+        return out_array

randomstate/array_utilities.pxi

@@ -16,10 +16,6 @@ ctypedef uint32_t (* random_uint_1_i_32)(aug_state* state, uint32_t a) nogil
 ctypedef int32_t (* random_int_2_i_32)(aug_state* state, int32_t a, int32_t b) nogil
 ctypedef int64_t (* random_int_2_i)(aug_state* state, int64_t a, int64_t b) nogil
 
-ctypedef void (* random_float_fill)(aug_state* state, np.npy_intp count, float *out) nogil
-ctypedef void (* random_double_fill)(aug_state* state, np.npy_intp count, double *out) nogil
-
-
 cdef np.npy_intp compute_numel(size):
     cdef np.npy_intp i, n = 1
     if isinstance(size, tuple):
@@ -600,40 +596,3 @@ cdef object disc(aug_state* state, void* func, object size, object lock,
     return np.asarray(randoms).reshape(size)
 
 
-cdef object double_fill(aug_state* state, void *func, object size, object lock):
-    cdef random_double_fill f = <random_double_fill>func
-    cdef double out
-    cdef double *out_array_data
-    cdef np.ndarray out_array
-    cdef np.npy_intp n
-
-    if size is None:
-        with lock:
-            f(state, 1, &out)
-        return out
-    else:
-        out_array = <np.ndarray>np.empty(size, np.float64)
-        n = np.PyArray_SIZE(out_array)
-        out_array_data = <double *>np.PyArray_DATA(out_array)
-        with lock, nogil:
-            f(state, n, out_array_data)
-        return out_array
-
-cdef object float_fill(aug_state* state, void *func, object size, object lock):
-    cdef random_float_fill f = <random_float_fill>func
-    cdef float out
-    cdef float *out_array_data
-    cdef np.ndarray out_array
-    cdef np.npy_intp n
-
-    if size is None:
-        with lock:
-            f(state, 1, &out)
-        return out
-    else:
-        out_array = <np.ndarray>np.empty(size, np.float32)
-        n = np.PyArray_SIZE(out_array)
-        out_array_data = <float *>np.PyArray_DATA(out_array)
-        with lock, nogil:
-            f(state, n, out_array_data)
-        return out_array