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MNT: use compat functions for accessing dtype state #475

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MNT: use compat functions for accessing dtype state #475

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16 changes: 8 additions & 8 deletions numexpr/interpreter.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@
#define fmin min
#define NE_INFINITY (DBL_MAX+DBL_MAX)
#define NE_NAN (INFINITY-INFINITY)
#else
#else
#define NE_INFINITY INFINITY
#define NE_NAN NAN
#endif
Expand Down Expand Up @@ -1203,7 +1203,7 @@ NumExpr_run(NumExprObject *self, PyObject *args, PyObject *kwds)
Py_INCREF(dtypes[0]);
} else { // constant, like in '"foo"'
dtypes[0] = PyArray_DescrNewFromType(NPY_STRING);
dtypes[0]->elsize = (int)self->memsizes[1];
PyDataType_SET_ELSIZE(dtypes[0], (int)self->memsizes[1]);
} // no string temporaries, so no third case
}
if (dtypes[0] == NULL) {
Expand Down Expand Up @@ -1254,7 +1254,7 @@ NumExpr_run(NumExprObject *self, PyObject *args, PyObject *kwds)
PyArrayObject *singleton;
bool writeback;
// NOTE: cannot assign on declaration due to `goto` statements
singleton = NULL;
singleton = NULL;
writeback = false;
if (n_inputs == 0) {
char retsig = get_return_sig(self->program);
Expand Down Expand Up @@ -1313,10 +1313,10 @@ NumExpr_run(NumExprObject *self, PyObject *args, PyObject *kwds)
/* Allocate the iterator or nested iterators */
if (reduction_size < 0 || full_reduction) {
/* When there's no reduction, reduction_size is 1 as well */
// RAM: in issue #277 this was also the case for reductions on arrays
// with axis=0 having singleton dimension, i.e. such ops were interpreted
// as full_reductions when they weren't in Numpy. As such, the default
// reduction_size is now -1 and we add the flag for full_reduction,
// RAM: in issue #277 this was also the case for reductions on arrays
// with axis=0 having singleton dimension, i.e. such ops were interpreted
// as full_reductions when they weren't in Numpy. As such, the default
// reduction_size is now -1 and we add the flag for full_reduction,
// e.g. ne.evaluate("sum(a)")"
iter = NpyIter_AdvancedNew(n_inputs+1, operands,
NPY_ITER_BUFFERED|
Expand Down Expand Up @@ -1449,7 +1449,7 @@ NumExpr_run(NumExprObject *self, PyObject *args, PyObject *kwds)
/* Get the sizes of all the operands */
dtypes_tmp = NpyIter_GetDescrArray(iter);
for (i = 0; i < n_inputs+1; ++i) {
self->memsizes[i] = dtypes_tmp[i]->elsize;
self->memsizes[i] = PyDataType_ELSIZE(dtypes_tmp[i]);
}

/* For small calculations, just use 1 thread */
Expand Down
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