1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
|
#include <caml/mlvalues.h>
#include <caml/memory.h>
#include <caml/fail.h>
#include <caml/alloc.h>
#include <caml/bigarray.h>
#include <caml/custom.h>
#include "pyml_stubs.h"
value
pyml_wrap(PyObject *object, bool steal);
PyObject *
pyml_unwrap(value v);
struct numpy_custom_operations {
struct custom_operations ops;
PyObject *obj;
};
static void numpy_finalize(value v)
{
struct numpy_custom_operations *ops =
(struct numpy_custom_operations *) Custom_ops_val(v);
Py_DECREF(ops->obj);
free(ops);
}
CAMLprim value
pyarray_of_bigarray_wrapper(
value numpy_api_ocaml, value bigarray_type_ocaml, value bigarray_ocaml)
{
CAMLparam3(numpy_api_ocaml, bigarray_type_ocaml, bigarray_ocaml);
pyml_assert_initialized();
PyObject *c_api = pyml_unwrap(numpy_api_ocaml);
void **PyArray_API = pyml_get_pyarray_api(c_api);
PyObject *(*PyArray_New)
(PyTypeObject *, int, npy_intp *, int, npy_intp *, void *, int, int,
PyObject *) = PyArray_API[93];
int nd = Caml_ba_array_val(bigarray_ocaml)->num_dims;
npy_intp *dims = malloc(nd * sizeof(npy_intp));
int i;
for (i = 0; i < nd; i++) {
dims[i] = Caml_ba_array_val(bigarray_ocaml)->dim[i];
}
int type_num;
intnat flags = Caml_ba_array_val(bigarray_ocaml)->flags;
switch (flags & CAML_BA_KIND_MASK) {
case CAML_BA_FLOAT32:
type_num = NPY_FLOAT;
break;
case CAML_BA_FLOAT64:
type_num = NPY_DOUBLE;
break;
case CAML_BA_SINT8:
type_num = NPY_BYTE;
break;
case CAML_BA_UINT8:
type_num = NPY_UBYTE;
break;
case CAML_BA_SINT16:
type_num = NPY_SHORT;
break;
case CAML_BA_UINT16:
type_num = NPY_USHORT;
break;
case CAML_BA_INT32:
type_num = NPY_INT;
break;
case CAML_BA_INT64:
type_num = NPY_LONGLONG;
break;
case CAML_BA_CAML_INT:
caml_failwith("Caml integers are unsupported for NumPy array");
break;
case CAML_BA_NATIVE_INT:
type_num = NPY_LONG;
break;
case CAML_BA_COMPLEX32:
type_num = NPY_CFLOAT;
break;
case CAML_BA_COMPLEX64:
type_num = NPY_CDOUBLE;
break;
#ifdef CAML_BA_CHAR /* introduced in 4.02.0 */
case CAML_BA_CHAR:
type_num = NPY_CHAR;
break;
#endif
default:
caml_failwith("Unsupported bigarray kind for NumPy array");
}
int np_flags;
switch (flags & CAML_BA_LAYOUT_MASK) {
case CAML_BA_C_LAYOUT:
np_flags = NPY_ARRAY_CARRAY;
break;
case CAML_BA_FORTRAN_LAYOUT:
np_flags = NPY_ARRAY_FARRAY;
break;
default:
caml_failwith("Unsupported bigarray layout for NumPy array");
}
void *data = Caml_ba_data_val(bigarray_ocaml);
PyTypeObject (*PyArray_SubType) =
(PyTypeObject *) pyml_unwrap(bigarray_type_ocaml);
PyObject *result = PyArray_New(
PyArray_SubType, nd, dims, type_num, NULL, data, 0,
np_flags, NULL);
free(dims);
CAMLreturn(pyml_wrap(result, true));
}
CAMLprim value
bigarray_of_pyarray_wrapper(
value numpy_api_ocaml, value pyarray_ocaml)
{
CAMLparam2(numpy_api_ocaml, pyarray_ocaml);
CAMLlocal2(bigarray, result);
pyml_assert_initialized();
PyObject *array = pyml_unwrap(pyarray_ocaml);
PyArrayObject_fields *fields =
(PyArrayObject_fields *) pyobjectdescr(array);
int nd = fields->nd;
npy_intp *shape = fields->dimensions;
intnat *dims = malloc(nd * sizeof(intnat));
int i;
for (i = 0; i < nd; i++) {
dims[i] = shape[i];
}
int type = fields->descr->type_num;
enum caml_ba_kind kind;
switch (type) {
case NPY_BYTE:
kind = CAML_BA_SINT8;
break;
case NPY_UBYTE:
kind = CAML_BA_UINT8;
break;
case NPY_SHORT:
kind = CAML_BA_SINT16;
break;
case NPY_USHORT:
kind = CAML_BA_UINT16;
break;
case NPY_INT:
kind = CAML_BA_INT32;
break;
case NPY_LONG:
kind = CAML_BA_NATIVE_INT;
break;
case NPY_LONGLONG:
kind = CAML_BA_INT64;
break;
case NPY_FLOAT:
kind = CAML_BA_FLOAT32;
break;
case NPY_DOUBLE:
kind = CAML_BA_FLOAT64;
break;
case NPY_CFLOAT:
kind = CAML_BA_COMPLEX32;
break;
case NPY_CDOUBLE:
kind = CAML_BA_COMPLEX64;
break;
case NPY_CHAR:
#ifdef CAML_BA_CHAR /* introduced in 4.02.0 */
kind = CAML_BA_CHAR;
#else
kind = CAML_BA_UINT8;
#endif
break;
default:
caml_failwith("Unsupported NumPy kind for bigarray");
}
int flags = fields->flags;
enum caml_ba_layout layout;
if (flags & NPY_ARRAY_C_CONTIGUOUS) {
layout = CAML_BA_C_LAYOUT;
}
else if (flags & NPY_ARRAY_F_CONTIGUOUS) {
layout = CAML_BA_FORTRAN_LAYOUT;
}
else {
caml_failwith("Unsupported NumPy layout for bigarray");
}
void *data = fields->data;
bigarray = caml_ba_alloc(kind | layout, nd, data, dims);
free(dims);
Py_INCREF(array);
const struct custom_operations *oldops = Custom_ops_val(bigarray);
struct numpy_custom_operations *newops = (struct numpy_custom_operations *)
malloc(sizeof(struct numpy_custom_operations));
newops->ops.identifier = oldops->identifier;
newops->ops.finalize = numpy_finalize;
newops->ops.compare = oldops->compare;
newops->ops.hash = oldops->hash;
newops->ops.serialize = oldops->serialize;
newops->ops.deserialize = oldops->deserialize;
newops->ops.compare_ext = oldops->compare_ext;
newops->obj = array;
Custom_ops_val(bigarray) = (struct custom_operations *) newops;
result = caml_alloc_tuple(3);
Store_field(result, 0, Val_int(kind));
Store_field(result, 1, Val_int(layout == CAML_BA_FORTRAN_LAYOUT ? 1 : 0));
Store_field(result, 2, bigarray);
CAMLreturn(result);
}
|
