tmp
/
pip-install-ghxuqwgs
/numpy_78e94bf2b6094bf9a1f3d92042f9bf46
/numpy
/lib
/src
/_compiled_base.c
static npy_intp | |
incr_slot_(double x, double *bins, npy_intp lbins) | |
{ | |
npy_intp i; | |
for ( i = 0; i < lbins; i ++ ) { | |
if ( x < bins [i] ) { | |
return i; | |
} | |
} | |
return lbins; | |
} | |
static npy_intp | |
decr_slot_(double x, double * bins, npy_intp lbins) | |
{ | |
npy_intp i; | |
for ( i = lbins - 1; i >= 0; i -- ) { | |
if (x < bins [i]) { | |
return i + 1; | |
} | |
} | |
return 0; | |
} | |
static npy_intp | |
incr_slot_right_(double x, double *bins, npy_intp lbins) | |
{ | |
npy_intp i; | |
for ( i = 0; i < lbins; i ++ ) { | |
if ( x <= bins [i] ) { | |
return i; | |
} | |
} | |
return lbins; | |
} | |
static npy_intp | |
decr_slot_right_(double x, double * bins, npy_intp lbins) | |
{ | |
npy_intp i; | |
for ( i = lbins - 1; i >= 0; i -- ) { | |
if (x <= bins [i]) { | |
return i + 1; | |
} | |
} | |
return 0; | |
} | |
/* | |
* Returns -1 if the array is monotonic decreasing, | |
* +1 if the array is monotonic increasing, | |
* and 0 if the array is not monotonic. | |
*/ | |
static int | |
check_array_monotonic(const double *a, npy_int lena) | |
{ | |
npy_intp i; | |
double next; | |
double last = a[0]; | |
/* Skip repeated values at the beginning of the array */ | |
for (i = 1; (i < lena) && (a[i] == last); i++); | |
if (i == lena) { | |
/* all bin edges hold the same value */ | |
return 1; | |
} | |
next = a[i]; | |
if (last < next) { | |
/* Possibly monotonic increasing */ | |
for (i += 1; i < lena; i++) { | |
last = next; | |
next = a[i]; | |
if (last > next) { | |
return 0; | |
} | |
} | |
return 1; | |
} | |
else { | |
/* last > next, possibly monotonic decreasing */ | |
for (i += 1; i < lena; i++) { | |
last = next; | |
next = a[i]; | |
if (last < next) { | |
return 0; | |
} | |
} | |
return -1; | |
} | |
} | |
/* Find the minimum and maximum of an integer array */ | |
static void | |
minmax(const npy_intp *data, npy_intp data_len, npy_intp *mn, npy_intp *mx) | |
{ | |
npy_intp min = *data; | |
npy_intp max = *data; | |
while (--data_len) { | |
const npy_intp val = *(++data); | |
if (val < min) { | |
min = val; | |
} | |
else if (val > max) { | |
max = val; | |
} | |
} | |
*mn = min; | |
*mx = max; | |
} | |
/* | |
* arr_bincount is registered as bincount. | |
* | |
* bincount accepts one, two or three arguments. The first is an array of | |
* non-negative integers The second, if present, is an array of weights, | |
* which must be promotable to double. Call these arguments list and | |
* weight. Both must be one-dimensional with len(weight) == len(list). If | |
* weight is not present then bincount(list)[i] is the number of occurrences | |
* of i in list. If weight is present then bincount(self,list, weight)[i] | |
* is the sum of all weight[j] where list [j] == i. Self is not used. | |
* The third argument, if present, is a minimum length desired for the | |
* output array. | |
*/ | |
static PyObject * | |
arr_bincount(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwds) | |
{ | |
PyArray_Descr *type; | |
PyObject *list = NULL, *weight=Py_None, *mlength=Py_None; | |
PyArrayObject *lst=NULL, *ans=NULL, *wts=NULL; | |
npy_intp *numbers, *ians, len , mx, mn, ans_size, minlength; | |
int i; | |
double *weights , *dans; | |
static char *kwlist[] = {"list", "weights", "minlength", NULL}; | |
if (!PyArg_ParseTupleAndKeywords(args, kwds, "O|OO", | |
kwlist, &list, &weight, &mlength)) { | |
goto fail; | |
} | |
lst = (PyArrayObject *)PyArray_ContiguousFromAny(list, NPY_INTP, 1, 1); | |
if (lst == NULL) { | |
goto fail; | |
} | |
len = PyArray_SIZE(lst); | |
type = PyArray_DescrFromType(NPY_INTP); | |
if (mlength == Py_None) { | |
minlength = 0; | |
} | |
else { | |
minlength = PyArray_PyIntAsIntp(mlength); | |
if (minlength <= 0) { | |
if (!PyErr_Occurred()) { | |
PyErr_SetString(PyExc_ValueError, | |
"minlength must be positive"); | |
} | |
goto fail; | |
} | |
} | |
/* handle empty list */ | |
if (len == 0) { | |
if (!(ans = (PyArrayObject *)PyArray_Zeros(1, &minlength, type, 0))){ | |
goto fail; | |
} | |
Py_DECREF(lst); | |
return (PyObject *)ans; | |
} | |
numbers = (npy_intp *) PyArray_DATA(lst); | |
minmax(numbers, len, &mn, &mx); | |
if (mn < 0) { | |
PyErr_SetString(PyExc_ValueError, | |
"The first argument of bincount must be non-negative"); | |
goto fail; | |
} | |
ans_size = mx + 1; | |
if (mlength != Py_None) { | |
if (ans_size < minlength) { | |
ans_size = minlength; | |
} | |
} | |
if (weight == Py_None) { | |
ans = (PyArrayObject *)PyArray_Zeros(1, &ans_size, type, 0); | |
if (ans == NULL) { | |
goto fail; | |
} | |
ians = (npy_intp *)(PyArray_DATA(ans)); | |
NPY_BEGIN_ALLOW_THREADS; | |
for (i = 0; i < len; i++) | |
ians [numbers [i]] += 1; | |
NPY_END_ALLOW_THREADS; | |
Py_DECREF(lst); | |
} | |
else { | |
wts = (PyArrayObject *)PyArray_ContiguousFromAny( | |
weight, NPY_DOUBLE, 1, 1); | |
if (wts == NULL) { | |
goto fail; | |
} | |
weights = (double *)PyArray_DATA (wts); | |
if (PyArray_SIZE(wts) != len) { | |
PyErr_SetString(PyExc_ValueError, | |
"The weights and list don't have the same length."); | |
goto fail; | |
} | |
type = PyArray_DescrFromType(NPY_DOUBLE); | |
ans = (PyArrayObject *)PyArray_Zeros(1, &ans_size, type, 0); | |
if (ans == NULL) { | |
goto fail; | |
} | |
dans = (double *)PyArray_DATA(ans); | |
NPY_BEGIN_ALLOW_THREADS; | |
for (i = 0; i < len; i++) { | |
dans[numbers[i]] += weights[i]; | |
} | |
NPY_END_ALLOW_THREADS; | |
Py_DECREF(lst); | |
Py_DECREF(wts); | |
} | |
return (PyObject *)ans; | |
fail: | |
Py_XDECREF(lst); | |
Py_XDECREF(wts); | |
Py_XDECREF(ans); | |
return NULL; | |
} | |
/* | |
* digitize (x, bins, right=False) returns an array of python integers the same | |
* length of x. The values i returned are such that bins [i - 1] <= x < | |
* bins [i] if bins is monotonically increasing, or bins [i - 1] > x >= | |
* bins [i] if bins is monotonically decreasing. Beyond the bounds of | |
* bins, returns either i = 0 or i = len (bins) as appropriate. | |
* if right == True the comparison is bins [i - 1] < x <= bins[i] | |
* or bins [i - 1] >= x > bins[i] | |
*/ | |
static PyObject * | |
arr_digitize(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwds) | |
{ | |
/* self is not used */ | |
PyObject *ox, *obins; | |
PyArrayObject *ax = NULL, *abins = NULL, *aret = NULL; | |
double *dx, *dbins; | |
npy_intp lbins, lx; /* lengths */ | |
npy_intp right = 0; /* whether right or left is inclusive */ | |
npy_intp *iret; | |
int m, i; | |
static char *kwlist[] = {"x", "bins", "right", NULL}; | |
PyArray_Descr *type; | |
char bins_non_monotonic = 0; | |
if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO|i", kwlist, &ox, &obins, | |
&right)) { | |
goto fail; | |
} | |
type = PyArray_DescrFromType(NPY_DOUBLE); | |
ax = (PyArrayObject *)PyArray_FromAny(ox, type, | |
1, 1, NPY_ARRAY_CARRAY, NULL); | |
if (ax == NULL) { | |
goto fail; | |
} | |
Py_INCREF(type); | |
abins = (PyArrayObject *)PyArray_FromAny(obins, type, | |
1, 1, NPY_ARRAY_CARRAY, NULL); | |
if (abins == NULL) { | |
goto fail; | |
} | |
lx = PyArray_SIZE(ax); | |
dx = (double *)PyArray_DATA(ax); | |
lbins = PyArray_SIZE(abins); | |
dbins = (double *)PyArray_DATA(abins); | |
aret = (PyArrayObject *)PyArray_SimpleNew(1, &lx, NPY_INTP); | |
if (aret == NULL) { | |
goto fail; | |
} | |
iret = (npy_intp *)PyArray_DATA(aret); | |
if (lx <= 0 || lbins < 0) { | |
PyErr_SetString(PyExc_ValueError, | |
"Both x and bins must have non-zero length"); | |
goto fail; | |
} | |
NPY_BEGIN_ALLOW_THREADS; | |
if (lbins == 1) { | |
if (right == 0) { | |
for (i = 0; i < lx; i++) { | |
if (dx [i] >= dbins[0]) { | |
iret[i] = 1; | |
} | |
else { | |
iret[i] = 0; | |
} | |
} | |
} | |
else { | |
for (i = 0; i < lx; i++) { | |
if (dx [i] > dbins[0]) { | |
iret[i] = 1; | |
} | |
else { | |
iret[i] = 0; | |
} | |
} | |
} | |
} | |
else { | |
m = check_array_monotonic(dbins, lbins); | |
if (right == 0) { | |
if ( m == -1 ) { | |
for ( i = 0; i < lx; i ++ ) { | |
iret [i] = decr_slot_ ((double)dx[i], dbins, lbins); | |
} | |
} | |
else if ( m == 1 ) { | |
for ( i = 0; i < lx; i ++ ) { | |
iret [i] = incr_slot_ ((double)dx[i], dbins, lbins); | |
} | |
} | |
else { | |
/* defer PyErr_SetString until after NPY_END_ALLOW_THREADS */ | |
bins_non_monotonic = 1; | |
} | |
} | |
else { | |
if ( m == -1 ) { | |
for ( i = 0; i < lx; i ++ ) { | |
iret [i] = decr_slot_right_ ((double)dx[i], dbins, | |
lbins); | |
} | |
} | |
else if ( m == 1 ) { | |
for ( i = 0; i < lx; i ++ ) { | |
iret [i] = incr_slot_right_ ((double)dx[i], dbins, | |
lbins); | |
} | |
} | |
else { | |
/* defer PyErr_SetString until after NPY_END_ALLOW_THREADS */ | |
bins_non_monotonic = 1; | |
} | |
} | |
} | |
NPY_END_ALLOW_THREADS; | |
if (bins_non_monotonic) { | |
PyErr_SetString(PyExc_ValueError, | |
"The bins must be monotonically increasing or decreasing"); | |
goto fail; | |
} | |
Py_DECREF(ax); | |
Py_DECREF(abins); | |
return (PyObject *)aret; | |
fail: | |
Py_XDECREF(ax); | |
Py_XDECREF(abins); | |
Py_XDECREF(aret); | |
return NULL; | |
} | |
static char arr_insert__doc__[] = "Insert vals sequentially into equivalent 1-d positions indicated by mask."; | |
/* | |
* Insert values from an input array into an output array, at positions | |
* indicated by a mask. If the arrays are of dtype object (indicated by | |
* the objarray flag), take care of reference counting. | |
* | |
* This function implements the copying logic of arr_insert() defined | |
* below. | |
*/ | |
static void | |
arr_insert_loop(char *mptr, char *vptr, char *input_data, char *zero, | |
char *avals_data, int melsize, int delsize, int objarray, | |
int totmask, int numvals, int nd, npy_intp *instrides, | |
npy_intp *inshape) | |
{ | |
int mindx, rem_indx, indx, i, copied; | |
/* | |
* Walk through mask array, when non-zero is encountered | |
* copy next value in the vals array to the input array. | |
* If we get through the value array, repeat it as necessary. | |
*/ | |
copied = 0; | |
for (mindx = 0; mindx < totmask; mindx++) { | |
if (memcmp(mptr,zero,melsize) != 0) { | |
/* compute indx into input array */ | |
rem_indx = mindx; | |
indx = 0; | |
for (i = nd - 1; i > 0; --i) { | |
indx += (rem_indx % inshape[i]) * instrides[i]; | |
rem_indx /= inshape[i]; | |
} | |
indx += rem_indx * instrides[0]; | |
/* fprintf(stderr, "mindx = %d, indx=%d\n", mindx, indx); */ | |
/* Copy value element over to input array */ | |
memcpy(input_data+indx,vptr,delsize); | |
if (objarray) { | |
Py_INCREF(*((PyObject **)vptr)); | |
} | |
vptr += delsize; | |
copied += 1; | |
/* If we move past value data. Reset */ | |
if (copied >= numvals) { | |
vptr = avals_data; | |
} | |
} | |
mptr += melsize; | |
} | |
} | |
/* | |
* Returns input array with values inserted sequentially into places | |
* indicated by the mask | |
*/ | |
static PyObject * | |
arr_insert(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwdict) | |
{ | |
PyObject *mask = NULL, *vals = NULL; | |
PyArrayObject *ainput = NULL, *amask = NULL, *avals = NULL, *tmp = NULL; | |
int numvals, totmask, sameshape; | |
char *input_data, *mptr, *vptr, *zero = NULL; | |
int melsize, delsize, nd, objarray, k; | |
npy_intp *instrides, *inshape; | |
static char *kwlist[] = {"input", "mask", "vals", NULL}; | |
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "O&OO", kwlist, | |
PyArray_Converter, &ainput, | |
&mask, &vals)) { | |
goto fail; | |
} | |
amask = (PyArrayObject *)PyArray_FROM_OF(mask, NPY_ARRAY_CARRAY); | |
if (amask == NULL) { | |
goto fail; | |
} | |
/* Cast an object array */ | |
if (PyArray_DESCR(amask)->type_num == NPY_OBJECT) { | |
tmp = (PyArrayObject *)PyArray_Cast(amask, NPY_INTP); | |
if (tmp == NULL) { | |
goto fail; | |
} | |
Py_DECREF(amask); | |
amask = tmp; | |
} | |
sameshape = 1; | |
if (PyArray_NDIM(amask) == PyArray_NDIM(ainput)) { | |
for (k = 0; k < PyArray_NDIM(amask); k++) { | |
if (PyArray_DIMS(amask)[k] != PyArray_DIMS(ainput)[k]) { | |
sameshape = 0; | |
} | |
} | |
} | |
else { | |
/* Test to see if amask is 1d */ | |
if (PyArray_NDIM(amask) != 1) { | |
sameshape = 0; | |
} | |
else if ((PyArray_SIZE(ainput)) != PyArray_SIZE(amask)) { | |
sameshape = 0; | |
} | |
} | |
if (!sameshape) { | |
PyErr_SetString(PyExc_TypeError, | |
"mask array must be 1-d or same shape as input array"); | |
goto fail; | |
} | |
avals = (PyArrayObject *)PyArray_FromObject(vals, | |
PyArray_DESCR(ainput)->type_num, 0, 1); | |
if (avals == NULL) { | |
goto fail; | |
} | |
numvals = PyArray_SIZE(avals); | |
nd = PyArray_NDIM(ainput); | |
input_data = PyArray_DATA(ainput); | |
mptr = PyArray_DATA(amask); | |
melsize = PyArray_DESCR(amask)->elsize; | |
vptr = PyArray_DATA(avals); | |
delsize = PyArray_DESCR(avals)->elsize; | |
zero = PyArray_Zero(amask); | |
if (zero == NULL) { | |
goto fail; | |
} | |
objarray = (PyArray_DESCR(ainput)->type_num == NPY_OBJECT); | |
/* Handle zero-dimensional case separately */ | |
if (nd == 0) { | |
if (memcmp(mptr,zero,melsize) != 0) { | |
/* Copy value element over to input array */ | |
memcpy(input_data,vptr,delsize); | |
if (objarray) { | |
Py_INCREF(*((PyObject **)vptr)); | |
} | |
} | |
Py_DECREF(amask); | |
Py_DECREF(avals); | |
PyDataMem_FREE(zero); | |
Py_DECREF(ainput); | |
Py_INCREF(Py_None); | |
return Py_None; | |
} | |
totmask = (int) PyArray_SIZE(amask); | |
instrides = PyArray_STRIDES(ainput); | |
inshape = PyArray_DIMS(ainput); | |
if (objarray) { | |
/* object array, need to refcount, can't release the GIL */ | |
arr_insert_loop(mptr, vptr, input_data, zero, PyArray_DATA(avals), | |
melsize, delsize, objarray, totmask, numvals, nd, | |
instrides, inshape); | |
} | |
else { | |
/* No increfs take place in arr_insert_loop, so release the GIL */ | |
NPY_BEGIN_ALLOW_THREADS; | |
arr_insert_loop(mptr, vptr, input_data, zero, PyArray_DATA(avals), | |
melsize, delsize, objarray, totmask, numvals, nd, | |
instrides, inshape); | |
NPY_END_ALLOW_THREADS; | |
} | |
Py_DECREF(amask); | |
Py_DECREF(avals); | |
PyDataMem_FREE(zero); | |
Py_DECREF(ainput); | |
Py_INCREF(Py_None); | |
return Py_None; | |
fail: | |
PyDataMem_FREE(zero); | |
Py_XDECREF(ainput); | |
Py_XDECREF(amask); | |
Py_XDECREF(avals); | |
return NULL; | |
} | |
/** @brief Use bisection on a sorted array to find first entry > key. | |
* | |
* Use bisection to find an index i s.t. arr[i] <= key < arr[i + 1]. If there is | |
* no such i the error returns are: | |
* key < arr[0] -- -1 | |
* key == arr[len - 1] -- len - 1 | |
* key > arr[len - 1] -- len | |
* The array is assumed contiguous and sorted in ascending order. | |
* | |
* @param key key value. | |
* @param arr contiguous sorted array to be searched. | |
* @param len length of the array. | |
* @return index | |
*/ | |
static npy_intp | |
binary_search(double key, double arr [], npy_intp len) | |
{ | |
npy_intp imin = 0; | |
npy_intp imax = len; | |
if (key > arr[len - 1]) { | |
return len; | |
} | |
while (imin < imax) { | |
npy_intp imid = imin + ((imax - imin) >> 1); | |
if (key >= arr[imid]) { | |
imin = imid + 1; | |
} | |
else { | |
imax = imid; | |
} | |
} | |
return imin - 1; | |
} | |
static PyObject * | |
arr_interp(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwdict) | |
{ | |
PyObject *fp, *xp, *x; | |
PyObject *left = NULL, *right = NULL; | |
PyArrayObject *afp = NULL, *axp = NULL, *ax = NULL, *af = NULL; | |
npy_intp i, lenx, lenxp; | |
double lval, rval; | |
double *dy, *dx, *dz, *dres, *slopes; | |
static char *kwlist[] = {"x", "xp", "fp", "left", "right", NULL}; | |
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "OOO|OO", kwlist, | |
&x, &xp, &fp, &left, &right)) { | |
return NULL; | |
} | |
afp = (PyArrayObject *)PyArray_ContiguousFromAny(fp, NPY_DOUBLE, 1, 1); | |
if (afp == NULL) { | |
return NULL; | |
} | |
axp = (PyArrayObject *)PyArray_ContiguousFromAny(xp, NPY_DOUBLE, 1, 1); | |
if (axp == NULL) { | |
goto fail; | |
} | |
ax = (PyArrayObject *)PyArray_ContiguousFromAny(x, NPY_DOUBLE, 1, 0); | |
if (ax == NULL) { | |
goto fail; | |
} | |
lenxp = PyArray_DIMS(axp)[0]; | |
if (lenxp == 0) { | |
PyErr_SetString(PyExc_ValueError, | |
"array of sample points is empty"); | |
goto fail; | |
} | |
if (PyArray_DIMS(afp)[0] != lenxp) { | |
PyErr_SetString(PyExc_ValueError, | |
"fp and xp are not of the same length."); | |
goto fail; | |
} | |
af = (PyArrayObject *)PyArray_SimpleNew(PyArray_NDIM(ax), | |
PyArray_DIMS(ax), NPY_DOUBLE); | |
if (af == NULL) { | |
goto fail; | |
} | |
lenx = PyArray_SIZE(ax); | |
dy = (double *)PyArray_DATA(afp); | |
dx = (double *)PyArray_DATA(axp); | |
dz = (double *)PyArray_DATA(ax); | |
dres = (double *)PyArray_DATA(af); | |
/* Get left and right fill values. */ | |
if ((left == NULL) || (left == Py_None)) { | |
lval = dy[0]; | |
} | |
else { | |
lval = PyFloat_AsDouble(left); | |
if ((lval == -1) && PyErr_Occurred()) { | |
goto fail; | |
} | |
} | |
if ((right == NULL) || (right == Py_None)) { | |
rval = dy[lenxp-1]; | |
} | |
else { | |
rval = PyFloat_AsDouble(right); | |
if ((rval == -1) && PyErr_Occurred()) { | |
goto fail; | |
} | |
} | |
/* only pre-calculate slopes if there are relatively few of them. */ | |
if (lenxp <= lenx) { | |
slopes = (double *) PyArray_malloc((lenxp - 1)*sizeof(double)); | |
if (! slopes) { | |
goto fail; | |
} | |
NPY_BEGIN_ALLOW_THREADS; | |
for (i = 0; i < lenxp - 1; i++) { | |
slopes[i] = (dy[i + 1] - dy[i])/(dx[i + 1] - dx[i]); | |
} | |
for (i = 0; i < lenx; i++) { | |
const double x = dz[i]; | |
npy_intp j; | |
if (npy_isnan(x)) { | |
dres[i] = x; | |
continue; | |
} | |
j = binary_search(x, dx, lenxp); | |
if (j == -1) { | |
dres[i] = lval; | |
} | |
else if (j == lenxp - 1) { | |
dres[i] = dy[j]; | |
} | |
else if (j == lenxp) { | |
dres[i] = rval; | |
} | |
else { | |
dres[i] = slopes[j]*(x - dx[j]) + dy[j]; | |
} | |
} | |
NPY_END_ALLOW_THREADS; | |
PyArray_free(slopes); | |
} | |
else { | |
NPY_BEGIN_ALLOW_THREADS; | |
for (i = 0; i < lenx; i++) { | |
const double x = dz[i]; | |
npy_intp j; | |
if (npy_isnan(x)) { | |
dres[i] = x; | |
continue; | |
} | |
j = binary_search(x, dx, lenxp); | |
if (j == -1) { | |
dres[i] = lval; | |
} | |
else if (j == lenxp - 1) { | |
dres[i] = dy[j]; | |
} | |
else if (j == lenxp) { | |
dres[i] = rval; | |
} | |
else { | |
const double slope = (dy[j + 1] - dy[j])/(dx[j + 1] - dx[j]); | |
dres[i] = slope*(x - dx[j]) + dy[j]; | |
} | |
} | |
NPY_END_ALLOW_THREADS; | |
} | |
Py_DECREF(afp); | |
Py_DECREF(axp); | |
Py_DECREF(ax); | |
return (PyObject *)af; | |
fail: | |
Py_XDECREF(afp); | |
Py_XDECREF(axp); | |
Py_XDECREF(ax); | |
Py_XDECREF(af); | |
return NULL; | |
} | |
/* | |
* Converts a Python sequence into 'count' PyArrayObjects | |
* | |
* seq - Input Python object, usually a tuple but any sequence works. | |
* op - Where the arrays are placed. | |
* count - How many arrays there should be (errors if it doesn't match). | |
* paramname - The name of the parameter that produced 'seq'. | |
*/ | |
static int sequence_to_arrays(PyObject *seq, | |
PyArrayObject **op, int count, | |
char *paramname) | |
{ | |
int i; | |
if (!PySequence_Check(seq) || PySequence_Size(seq) != count) { | |
PyErr_Format(PyExc_ValueError, | |
"parameter %s must be a sequence of length %d", | |
paramname, count); | |
return -1; | |
} | |
for (i = 0; i < count; ++i) { | |
PyObject *item = PySequence_GetItem(seq, i); | |
if (item == NULL) { | |
while (--i >= 0) { | |
Py_DECREF(op[i]); | |
op[i] = NULL; | |
} | |
return -1; | |
} | |
op[i] = (PyArrayObject *)PyArray_FromAny(item, NULL, 0, 0, 0, NULL); | |
if (op[i] == NULL) { | |
while (--i >= 0) { | |
Py_DECREF(op[i]); | |
op[i] = NULL; | |
} | |
Py_DECREF(item); | |
return -1; | |
} | |
Py_DECREF(item); | |
} | |
return 0; | |
} | |
/* Inner loop for unravel_index */ | |
static int | |
ravel_multi_index_loop(int ravel_ndim, npy_intp *ravel_dims, | |
npy_intp *ravel_strides, | |
npy_intp count, | |
NPY_CLIPMODE *modes, | |
char **coords, npy_intp *coords_strides) | |
{ | |
int i; | |
char invalid; | |
npy_intp j, m; | |
NPY_BEGIN_ALLOW_THREADS; | |
invalid = 0; | |
while (count--) { | |
npy_intp raveled = 0; | |
for (i = 0; i < ravel_ndim; ++i) { | |
m = ravel_dims[i]; | |
j = *(npy_intp *)coords[i]; | |
switch (modes[i]) { | |
case NPY_RAISE: | |
if (j < 0 || j >= m) { | |
invalid = 1; | |
goto end_while; | |
} | |
break; | |
case NPY_WRAP: | |
if (j < 0) { | |
j += m; | |
if (j < 0) { | |
j = j % m; | |
if (j != 0) { | |
j += m; | |
} | |
} | |
} | |
else if (j >= m) { | |
j -= m; | |
if (j >= m) { | |
j = j % m; | |
} | |
} | |
break; | |
case NPY_CLIP: | |
if (j < 0) { | |
j = 0; | |
} | |
else if (j >= m) { | |
j = m - 1; | |
} | |
break; | |
} | |
raveled += j * ravel_strides[i]; | |
coords[i] += coords_strides[i]; | |
} | |
*(npy_intp *)coords[ravel_ndim] = raveled; | |
coords[ravel_ndim] += coords_strides[ravel_ndim]; | |
} | |
end_while: | |
NPY_END_ALLOW_THREADS; | |
if (invalid) { | |
PyErr_SetString(PyExc_ValueError, | |
"invalid entry in coordinates array"); | |
return NPY_FAIL; | |
} | |
return NPY_SUCCEED; | |
} | |
/* ravel_multi_index implementation - see add_newdocs.py */ | |
static PyObject * | |
arr_ravel_multi_index(PyObject *self, PyObject *args, PyObject *kwds) | |
{ | |
int i, s; | |
PyObject *mode0=NULL, *coords0=NULL; | |
PyArrayObject *ret = NULL; | |
PyArray_Dims dimensions={0,0}; | |
npy_intp ravel_strides[NPY_MAXDIMS]; | |
NPY_ORDER order = NPY_CORDER; | |
NPY_CLIPMODE modes[NPY_MAXDIMS]; | |
PyArrayObject *op[NPY_MAXARGS]; | |
PyArray_Descr *dtype[NPY_MAXARGS]; | |
npy_uint32 op_flags[NPY_MAXARGS]; | |
NpyIter *iter = NULL; | |
char *kwlist[] = {"multi_index", "dims", "mode", "order", NULL}; | |
memset(op, 0, sizeof(op)); | |
dtype[0] = NULL; | |
if (!PyArg_ParseTupleAndKeywords(args, kwds, | |
"OO&|OO&:ravel_multi_index", kwlist, | |
&coords0, | |
PyArray_IntpConverter, &dimensions, | |
&mode0, | |
PyArray_OrderConverter, &order)) { | |
goto fail; | |
} | |
if (dimensions.len+1 > NPY_MAXARGS) { | |
PyErr_SetString(PyExc_ValueError, | |
"too many dimensions passed to ravel_multi_index"); | |
goto fail; | |
} | |
if (!PyArray_ConvertClipmodeSequence(mode0, modes, dimensions.len)) { | |
goto fail; | |
} | |
switch (order) { | |
case NPY_CORDER: | |
s = 1; | |
for (i = dimensions.len-1; i >= 0; --i) { | |
ravel_strides[i] = s; | |
s *= dimensions.ptr[i]; | |
} | |
break; | |
case NPY_FORTRANORDER: | |
s = 1; | |
for (i = 0; i < dimensions.len; ++i) { | |
ravel_strides[i] = s; | |
s *= dimensions.ptr[i]; | |
} | |
break; | |
default: | |
PyErr_SetString(PyExc_ValueError, | |
"only 'C' or 'F' order is permitted"); | |
goto fail; | |
} | |
/* Get the multi_index into op */ | |
if (sequence_to_arrays(coords0, op, dimensions.len, "multi_index") < 0) { | |
goto fail; | |
} | |
for (i = 0; i < dimensions.len; ++i) { | |
op_flags[i] = NPY_ITER_READONLY| | |
NPY_ITER_ALIGNED; | |
} | |
op_flags[dimensions.len] = NPY_ITER_WRITEONLY| | |
NPY_ITER_ALIGNED| | |
NPY_ITER_ALLOCATE; | |
dtype[0] = PyArray_DescrFromType(NPY_INTP); | |
for (i = 1; i <= dimensions.len; ++i) { | |
dtype[i] = dtype[0]; | |
} | |
iter = NpyIter_MultiNew(dimensions.len+1, op, NPY_ITER_BUFFERED| | |
NPY_ITER_EXTERNAL_LOOP| | |
NPY_ITER_ZEROSIZE_OK, | |
NPY_KEEPORDER, | |
NPY_SAME_KIND_CASTING, | |
op_flags, dtype); | |
if (iter == NULL) { | |
goto fail; | |
} | |
if (NpyIter_GetIterSize(iter) != 0) { | |
NpyIter_IterNextFunc *iternext; | |
char **dataptr; | |
npy_intp *strides; | |
npy_intp *countptr; | |
iternext = NpyIter_GetIterNext(iter, NULL); | |
if (iternext == NULL) { | |
goto fail; | |
} | |
dataptr = NpyIter_GetDataPtrArray(iter); | |
strides = NpyIter_GetInnerStrideArray(iter); | |
countptr = NpyIter_GetInnerLoopSizePtr(iter); | |
do { | |
if (ravel_multi_index_loop(dimensions.len, dimensions.ptr, | |
ravel_strides, *countptr, modes, | |
dataptr, strides) != NPY_SUCCEED) { | |
goto fail; | |
} | |
} while(iternext(iter)); | |
} | |
ret = NpyIter_GetOperandArray(iter)[dimensions.len]; | |
Py_INCREF(ret); | |
Py_DECREF(dtype[0]); | |
for (i = 0; i < dimensions.len; ++i) { | |
Py_XDECREF(op[i]); | |
} | |
PyDimMem_FREE(dimensions.ptr); | |
NpyIter_Deallocate(iter); | |
return PyArray_Return(ret); | |
fail: | |
Py_XDECREF(dtype[0]); | |
for (i = 0; i < dimensions.len; ++i) { | |
Py_XDECREF(op[i]); | |
} | |
PyDimMem_FREE(dimensions.ptr); | |
NpyIter_Deallocate(iter); | |
return NULL; | |
} | |
/* C-order inner loop for unravel_index */ | |
static int | |
unravel_index_loop_corder(int unravel_ndim, npy_intp *unravel_dims, | |
npy_intp unravel_size, npy_intp count, | |
char *indices, npy_intp indices_stride, | |
npy_intp *coords) | |
{ | |
int i; | |
char invalid; | |
npy_intp val; | |
NPY_BEGIN_ALLOW_THREADS; | |
invalid = 0; | |
while (count--) { | |
val = *(npy_intp *)indices; | |
if (val < 0 || val >= unravel_size) { | |
invalid = 1; | |
break; | |
} | |
for (i = unravel_ndim-1; i >= 0; --i) { | |
coords[i] = val % unravel_dims[i]; | |
val /= unravel_dims[i]; | |
} | |
coords += unravel_ndim; | |
indices += indices_stride; | |
} | |
NPY_END_ALLOW_THREADS; | |
if (invalid) { | |
PyErr_SetString(PyExc_ValueError, | |
"invalid entry in index array"); | |
return NPY_FAIL; | |
} | |
return NPY_SUCCEED; | |
} | |
/* Fortran-order inner loop for unravel_index */ | |
static int | |
unravel_index_loop_forder(int unravel_ndim, npy_intp *unravel_dims, | |
npy_intp unravel_size, npy_intp count, | |
char *indices, npy_intp indices_stride, | |
npy_intp *coords) | |
{ | |
int i; | |
char invalid; | |
npy_intp val; | |
NPY_BEGIN_ALLOW_THREADS; | |
invalid = 0; | |
while (count--) { | |
val = *(npy_intp *)indices; | |
if (val < 0 || val >= unravel_size) { | |
invalid = 1; | |
break; | |
} | |
for (i = 0; i < unravel_ndim; ++i) { | |
*coords++ = val % unravel_dims[i]; | |
val /= unravel_dims[i]; | |
} | |
indices += indices_stride; | |
} | |
NPY_END_ALLOW_THREADS; | |
if (invalid) { | |
PyErr_SetString(PyExc_ValueError, | |
"invalid entry in index array"); | |
return NPY_FAIL; | |
} | |
return NPY_SUCCEED; | |
} | |
/* unravel_index implementation - see add_newdocs.py */ | |
static PyObject * | |
arr_unravel_index(PyObject *self, PyObject *args, PyObject *kwds) | |
{ | |
PyObject *indices0 = NULL, *ret_tuple = NULL; | |
PyArrayObject *ret_arr = NULL; | |
PyArrayObject *indices = NULL; | |
PyArray_Descr *dtype = NULL; | |
PyArray_Dims dimensions={0,0}; | |
NPY_ORDER order = NPY_CORDER; | |
npy_intp unravel_size; | |
NpyIter *iter = NULL; | |
int i, ret_ndim; | |
npy_intp ret_dims[NPY_MAXDIMS], ret_strides[NPY_MAXDIMS]; | |
char *kwlist[] = {"indices", "dims", "order", NULL}; | |
if (!PyArg_ParseTupleAndKeywords(args, kwds, "OO&|O&:unravel_index", | |
kwlist, | |
&indices0, | |
PyArray_IntpConverter, &dimensions, | |
PyArray_OrderConverter, &order)) { | |
goto fail; | |
} | |
if (dimensions.len == 0) { | |
PyErr_SetString(PyExc_ValueError, | |
"dims must have at least one value"); | |
goto fail; | |
} | |
unravel_size = PyArray_MultiplyList(dimensions.ptr, dimensions.len); | |
if (!PyArray_Check(indices0)) { | |
indices = (PyArrayObject*)PyArray_FromAny(indices0, | |
NULL, 0, 0, 0, NULL); | |
if (indices == NULL) { | |
goto fail; | |
} | |
} | |
else { | |
indices = (PyArrayObject *)indices0; | |
Py_INCREF(indices); | |
} | |
dtype = PyArray_DescrFromType(NPY_INTP); | |
if (dtype == NULL) { | |
goto fail; | |
} | |
iter = NpyIter_New(indices, NPY_ITER_READONLY| | |
NPY_ITER_ALIGNED| | |
NPY_ITER_BUFFERED| | |
NPY_ITER_ZEROSIZE_OK| | |
NPY_ITER_DONT_NEGATE_STRIDES| | |
NPY_ITER_MULTI_INDEX, | |
NPY_KEEPORDER, NPY_SAME_KIND_CASTING, | |
dtype); | |
if (iter == NULL) { | |
goto fail; | |
} | |
/* | |
* Create the return array with a layout compatible with the indices | |
* and with a dimension added to the end for the multi-index | |
*/ | |
ret_ndim = PyArray_NDIM(indices) + 1; | |
if (NpyIter_GetShape(iter, ret_dims) != NPY_SUCCEED) { | |
goto fail; | |
} | |
ret_dims[ret_ndim-1] = dimensions.len; | |
if (NpyIter_CreateCompatibleStrides(iter, | |
dimensions.len*sizeof(npy_intp), ret_strides) != NPY_SUCCEED) { | |
goto fail; | |
} | |
ret_strides[ret_ndim-1] = sizeof(npy_intp); | |
/* Remove the multi-index and inner loop */ | |
if (NpyIter_RemoveMultiIndex(iter) != NPY_SUCCEED) { | |
goto fail; | |
} | |
if (NpyIter_EnableExternalLoop(iter) != NPY_SUCCEED) { | |
goto fail; | |
} | |
ret_arr = (PyArrayObject *)PyArray_NewFromDescr(&PyArray_Type, dtype, | |
ret_ndim, ret_dims, ret_strides, NULL, 0, NULL); | |
dtype = NULL; | |
if (ret_arr == NULL) { | |
goto fail; | |
} | |
if (order == NPY_CORDER) { | |
if (NpyIter_GetIterSize(iter) != 0) { | |
NpyIter_IterNextFunc *iternext; | |
char **dataptr; | |
npy_intp *strides; | |
npy_intp *countptr, count; | |
npy_intp *coordsptr = (npy_intp *)PyArray_DATA(ret_arr); | |
iternext = NpyIter_GetIterNext(iter, NULL); | |
if (iternext == NULL) { | |
goto fail; | |
} | |
dataptr = NpyIter_GetDataPtrArray(iter); | |
strides = NpyIter_GetInnerStrideArray(iter); | |
countptr = NpyIter_GetInnerLoopSizePtr(iter); | |
do { | |
count = *countptr; | |
if (unravel_index_loop_corder(dimensions.len, dimensions.ptr, | |
unravel_size, count, *dataptr, *strides, | |
coordsptr) != NPY_SUCCEED) { | |
goto fail; | |
} | |
coordsptr += count*dimensions.len; | |
} while(iternext(iter)); | |
} | |
} | |
else if (order == NPY_FORTRANORDER) { | |
if (NpyIter_GetIterSize(iter) != 0) { | |
NpyIter_IterNextFunc *iternext; | |
char **dataptr; | |
npy_intp *strides; | |
npy_intp *countptr, count; | |
npy_intp *coordsptr = (npy_intp *)PyArray_DATA(ret_arr); | |
iternext = NpyIter_GetIterNext(iter, NULL); | |
if (iternext == NULL) { | |
goto fail; | |
} | |
dataptr = NpyIter_GetDataPtrArray(iter); | |
strides = NpyIter_GetInnerStrideArray(iter); | |
countptr = NpyIter_GetInnerLoopSizePtr(iter); | |
do { | |
count = *countptr; | |
if (unravel_index_loop_forder(dimensions.len, dimensions.ptr, | |
unravel_size, count, *dataptr, *strides, | |
coordsptr) != NPY_SUCCEED) { | |
goto fail; | |
} | |
coordsptr += count*dimensions.len; | |
} while(iternext(iter)); | |
} | |
} | |
else { | |
PyErr_SetString(PyExc_ValueError, | |
"only 'C' or 'F' order is permitted"); | |
goto fail; | |
} | |
/* Now make a tuple of views, one per index */ | |
ret_tuple = PyTuple_New(dimensions.len); | |
if (ret_tuple == NULL) { | |
goto fail; | |
} | |
for (i = 0; i < dimensions.len; ++i) { | |
PyArrayObject *view; | |
view = (PyArrayObject *)PyArray_New(&PyArray_Type, ret_ndim-1, | |
ret_dims, NPY_INTP, | |
ret_strides, | |
PyArray_BYTES(ret_arr) + i*sizeof(npy_intp), | |
0, 0, NULL); | |
if (view == NULL) { | |
goto fail; | |
} | |
Py_INCREF(ret_arr); | |
if (PyArray_SetBaseObject(view, (PyObject *)ret_arr) < 0) { | |
Py_DECREF(view); | |
goto fail; | |
} | |
PyTuple_SET_ITEM(ret_tuple, i, PyArray_Return(view)); | |
} | |
Py_DECREF(ret_arr); | |
Py_XDECREF(indices); | |
PyDimMem_FREE(dimensions.ptr); | |
NpyIter_Deallocate(iter); | |
return ret_tuple; | |
fail: | |
Py_XDECREF(ret_tuple); | |
Py_XDECREF(ret_arr); | |
Py_XDECREF(dtype); | |
Py_XDECREF(indices); | |
PyDimMem_FREE(dimensions.ptr); | |
NpyIter_Deallocate(iter); | |
return NULL; | |
} | |
static PyTypeObject *PyMemberDescr_TypePtr = NULL; | |
static PyTypeObject *PyGetSetDescr_TypePtr = NULL; | |
static PyTypeObject *PyMethodDescr_TypePtr = NULL; | |
/* Can only be called if doc is currently NULL */ | |
static PyObject * | |
arr_add_docstring(PyObject *NPY_UNUSED(dummy), PyObject *args) | |
{ | |
PyObject *obj; | |
PyObject *str; | |
char *docstr; | |
static char *msg = "already has a docstring"; | |
/* Don't add docstrings */ | |
if (Py_OptimizeFlag > 1) { | |
Py_INCREF(Py_None); | |
return Py_None; | |
} | |
if (!PyArg_ParseTuple(args, "OO!", &obj, &PyUnicode_Type, &str)) { | |
return NULL; | |
} | |
docstr = PyBytes_AS_STRING(PyUnicode_AsUTF8String(str)); | |
if (!PyArg_ParseTuple(args, "OO!", &obj, &PyString_Type, &str)) { | |
return NULL; | |
} | |
docstr = PyString_AS_STRING(str); | |
if (_TESTDOC1(CFunction)) { | |
_ADDDOC(CFunction, new->m_ml->ml_doc, new->m_ml->ml_name); | |
} | |
else if (_TESTDOC1(Type)) { | |
_ADDDOC(Type, new->tp_doc, new->tp_name); | |
} | |
else if (_TESTDOC2(MemberDescr)) { | |
_ADDDOC(MemberDescr, new->d_member->doc, new->d_member->name); | |
} | |
else if (_TESTDOC2(GetSetDescr)) { | |
_ADDDOC(GetSetDescr, new->d_getset->doc, new->d_getset->name); | |
} | |
else if (_TESTDOC2(MethodDescr)) { | |
_ADDDOC(MethodDescr, new->d_method->ml_doc, new->d_method->ml_name); | |
} | |
else { | |
PyObject *doc_attr; | |
doc_attr = PyObject_GetAttrString(obj, "__doc__"); | |
if (doc_attr != NULL && doc_attr != Py_None) { | |
PyErr_Format(PyExc_RuntimeError, "object %s", msg); | |
return NULL; | |
} | |
Py_XDECREF(doc_attr); | |
if (PyObject_SetAttrString(obj, "__doc__", str) < 0) { | |
PyErr_SetString(PyExc_TypeError, | |
"Cannot set a docstring for that object"); | |
return NULL; | |
} | |
Py_INCREF(Py_None); | |
return Py_None; | |
} | |
Py_INCREF(str); | |
Py_INCREF(Py_None); | |
return Py_None; | |
} | |
/* docstring in numpy.add_newdocs.py */ | |
static PyObject * | |
add_newdoc_ufunc(PyObject *NPY_UNUSED(dummy), PyObject *args) | |
{ | |
PyUFuncObject *ufunc; | |
PyObject *str; | |
char *docstr, *newdocstr; | |
if (!PyArg_ParseTuple(args, "O!O!", &PyUFunc_Type, &ufunc, | |
&PyUnicode_Type, &str)) { | |
return NULL; | |
} | |
docstr = PyBytes_AS_STRING(PyUnicode_AsUTF8String(str)); | |
if (!PyArg_ParseTuple(args, "O!O!", &PyUFunc_Type, &ufunc, | |
&PyString_Type, &str)) { | |
return NULL; | |
} | |
docstr = PyString_AS_STRING(str); | |
if (NULL != ufunc->doc) { | |
PyErr_SetString(PyExc_ValueError, | |
"Cannot change docstring of ufunc with non-NULL docstring"); | |
return NULL; | |
} | |
/* | |
* This introduces a memory leak, as the memory allocated for the doc | |
* will not be freed even if the ufunc itself is deleted. In practice | |
* this should not be a problem since the user would have to | |
* repeatedly create, document, and throw away ufuncs. | |
*/ | |
newdocstr = malloc(strlen(docstr) + 1); | |
strcpy(newdocstr, docstr); | |
ufunc->doc = newdocstr; | |
Py_INCREF(Py_None); | |
return Py_None; | |
} | |
/* PACKBITS | |
* | |
* This function packs binary (0 or 1) 1-bit per pixel arrays | |
* into contiguous bytes. | |
* | |
*/ | |
static void | |
_packbits( void *In, | |
int element_size, /* in bytes */ | |
npy_intp in_N, | |
npy_intp in_stride, | |
void *Out, | |
npy_intp out_N, | |
npy_intp out_stride | |
) | |
{ | |
char build; | |
int i, index; | |
npy_intp out_Nm1; | |
int maxi, remain, nonzero, j; | |
char *outptr,*inptr; | |
NPY_BEGIN_THREADS_DEF; | |
NPY_BEGIN_THREADS_THRESHOLDED(out_N); | |
outptr = Out; /* pointer to output buffer */ | |
inptr = In; /* pointer to input buffer */ | |
/* | |
* Loop through the elements of In | |
* Determine whether or not it is nonzero. | |
* Yes: set correspdoning bit (and adjust build value) | |
* No: move on | |
* Every 8th value, set the value of build and increment the outptr | |
*/ | |
remain = in_N % 8; /* uneven bits */ | |
if (remain == 0) { | |
remain = 8; | |
} | |
out_Nm1 = out_N - 1; | |
for (index = 0; index < out_N; index++) { | |
build = 0; | |
maxi = (index != out_Nm1 ? 8 : remain); | |
for (i = 0; i < maxi; i++) { | |
build <<= 1; | |
nonzero = 0; | |
for (j = 0; j < element_size; j++) { | |
nonzero += (*(inptr++) != 0); | |
} | |
inptr += (in_stride - element_size); | |
build += (nonzero != 0); | |
} | |
if (index == out_Nm1) build <<= (8-remain); | |
/* printf("Here: %d %d %d %d\n",build,slice,index,maxi); */ | |
*outptr = build; | |
outptr += out_stride; | |
} | |
NPY_END_THREADS; | |
return; | |
} | |
static void | |
_unpackbits(void *In, | |
int NPY_UNUSED(el_size), /* unused */ | |
npy_intp in_N, | |
npy_intp in_stride, | |
void *Out, | |
npy_intp NPY_UNUSED(out_N), | |
npy_intp out_stride | |
) | |
{ | |
unsigned char mask; | |
int i, index; | |
char *inptr, *outptr; | |
NPY_BEGIN_THREADS_DEF; | |
NPY_BEGIN_THREADS_THRESHOLDED(in_N); | |
outptr = Out; | |
inptr = In; | |
for (index = 0; index < in_N; index++) { | |
mask = 128; | |
for (i = 0; i < 8; i++) { | |
*outptr = ((mask & (unsigned char)(*inptr)) != 0); | |
outptr += out_stride; | |
mask >>= 1; | |
} | |
inptr += in_stride; | |
} | |
NPY_END_THREADS; | |
return; | |
} | |
/* Fixme -- pack and unpack should be separate routines */ | |
static PyObject * | |
pack_or_unpack_bits(PyObject *input, int axis, int unpack) | |
{ | |
PyArrayObject *inp; | |
PyArrayObject *new = NULL; | |
PyArrayObject *out = NULL; | |
npy_intp outdims[NPY_MAXDIMS]; | |
int i; | |
void (*thefunc)(void *, int, npy_intp, npy_intp, void *, npy_intp, npy_intp); | |
PyArrayIterObject *it, *ot; | |
inp = (PyArrayObject *)PyArray_FROM_O(input); | |
if (inp == NULL) { | |
return NULL; | |
} | |
if (unpack) { | |
if (PyArray_TYPE(inp) != NPY_UBYTE) { | |
PyErr_SetString(PyExc_TypeError, | |
"Expected an input array of unsigned byte data type"); | |
goto fail; | |
} | |
} | |
else if (!PyArray_ISINTEGER(inp)) { | |
PyErr_SetString(PyExc_TypeError, | |
"Expected an input array of integer data type"); | |
goto fail; | |
} | |
new = (PyArrayObject *)PyArray_CheckAxis(inp, &axis, 0); | |
Py_DECREF(inp); | |
if (new == NULL) { | |
return NULL; | |
} | |
/* Handle zero-dim array separately */ | |
if (PyArray_SIZE(new) == 0) { | |
return PyArray_Copy(new); | |
} | |
if (PyArray_NDIM(new) == 0) { | |
if (unpack) { | |
/* Handle 0-d array by converting it to a 1-d array */ | |
PyArrayObject *temp; | |
PyArray_Dims newdim = {NULL, 1}; | |
npy_intp shape = 1; | |
newdim.ptr = &shape; | |
temp = (PyArrayObject *)PyArray_Newshape(new, &newdim, NPY_CORDER); | |
if (temp == NULL) { | |
goto fail; | |
} | |
Py_DECREF(new); | |
new = temp; | |
} | |
else { | |
char *optr, *iptr; | |
out = (PyArrayObject *)PyArray_New(Py_TYPE(new), 0, NULL, NPY_UBYTE, | |
NULL, NULL, 0, 0, NULL); | |
if (out == NULL) { | |
goto fail; | |
} | |
optr = PyArray_DATA(out); | |
iptr = PyArray_DATA(new); | |
*optr = 0; | |
for (i = 0; i<PyArray_ITEMSIZE(new); i++) { | |
if (*iptr != 0) { | |
*optr = 1; | |
break; | |
} | |
iptr++; | |
} | |
goto finish; | |
} | |
} | |
/* Setup output shape */ | |
for (i=0; i<PyArray_NDIM(new); i++) { | |
outdims[i] = PyArray_DIM(new, i); | |
} | |
if (unpack) { | |
/* Multiply axis dimension by 8 */ | |
outdims[axis] <<= 3; | |
thefunc = _unpackbits; | |
} | |
else { | |
/* | |
* Divide axis dimension by 8 | |
* 8 -> 1, 9 -> 2, 16 -> 2, 17 -> 3 etc.. | |
*/ | |
outdims[axis] = ((outdims[axis] - 1) >> 3) + 1; | |
thefunc = _packbits; | |
} | |
/* Create output array */ | |
out = (PyArrayObject *)PyArray_New(Py_TYPE(new), | |
PyArray_NDIM(new), outdims, NPY_UBYTE, | |
NULL, NULL, 0, PyArray_ISFORTRAN(new), NULL); | |
if (out == NULL) { | |
goto fail; | |
} | |
/* Setup iterators to iterate over all but given axis */ | |
it = (PyArrayIterObject *)PyArray_IterAllButAxis((PyObject *)new, &axis); | |
ot = (PyArrayIterObject *)PyArray_IterAllButAxis((PyObject *)out, &axis); | |
if (it == NULL || ot == NULL) { | |
Py_XDECREF(it); | |
Py_XDECREF(ot); | |
goto fail; | |
} | |
while(PyArray_ITER_NOTDONE(it)) { | |
thefunc(PyArray_ITER_DATA(it), PyArray_ITEMSIZE(new), | |
PyArray_DIM(new, axis), PyArray_STRIDE(new, axis), | |
PyArray_ITER_DATA(ot), PyArray_DIM(out, axis), | |
PyArray_STRIDE(out, axis)); | |
PyArray_ITER_NEXT(it); | |
PyArray_ITER_NEXT(ot); | |
} | |
Py_DECREF(it); | |
Py_DECREF(ot); | |
finish: | |
Py_DECREF(new); | |
return (PyObject *)out; | |
fail: | |
Py_XDECREF(new); | |
Py_XDECREF(out); | |
return NULL; | |
} | |
static PyObject * | |
io_pack(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwds) | |
{ | |
PyObject *obj; | |
int axis = NPY_MAXDIMS; | |
static char *kwlist[] = {"in", "axis", NULL}; | |
if (!PyArg_ParseTupleAndKeywords( args, kwds, "O|O&" , kwlist, | |
&obj, PyArray_AxisConverter, &axis)) { | |
return NULL; | |
} | |
return pack_or_unpack_bits(obj, axis, 0); | |
} | |
static PyObject * | |
io_unpack(PyObject *NPY_UNUSED(self), PyObject *args, PyObject *kwds) | |
{ | |
PyObject *obj; | |
int axis = NPY_MAXDIMS; | |
static char *kwlist[] = {"in", "axis", NULL}; | |
if (!PyArg_ParseTupleAndKeywords( args, kwds, "O|O&" , kwlist, | |
&obj, PyArray_AxisConverter, &axis)) { | |
return NULL; | |
} | |
return pack_or_unpack_bits(obj, axis, 1); | |
} | |
/* The docstrings for many of these methods are in add_newdocs.py. */ | |
static struct PyMethodDef methods[] = { | |
{"_insert", (PyCFunction)arr_insert, | |
METH_VARARGS | METH_KEYWORDS, arr_insert__doc__}, | |
{"bincount", (PyCFunction)arr_bincount, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"digitize", (PyCFunction)arr_digitize, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"interp", (PyCFunction)arr_interp, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"ravel_multi_index", (PyCFunction)arr_ravel_multi_index, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"unravel_index", (PyCFunction)arr_unravel_index, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"add_docstring", (PyCFunction)arr_add_docstring, | |
METH_VARARGS, NULL}, | |
{"add_newdoc_ufunc", (PyCFunction)add_newdoc_ufunc, | |
METH_VARARGS, NULL}, | |
{"packbits", (PyCFunction)io_pack, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{"unpackbits", (PyCFunction)io_unpack, | |
METH_VARARGS | METH_KEYWORDS, NULL}, | |
{NULL, NULL, 0, NULL} /* sentinel */ | |
}; | |
static void | |
define_types(void) | |
{ | |
PyObject *tp_dict; | |
PyObject *myobj; | |
tp_dict = PyArrayDescr_Type.tp_dict; | |
/* Get "subdescr" */ | |
myobj = PyDict_GetItemString(tp_dict, "fields"); | |
if (myobj == NULL) { | |
return; | |
} | |
PyGetSetDescr_TypePtr = Py_TYPE(myobj); | |
myobj = PyDict_GetItemString(tp_dict, "alignment"); | |
if (myobj == NULL) { | |
return; | |
} | |
PyMemberDescr_TypePtr = Py_TYPE(myobj); | |
myobj = PyDict_GetItemString(tp_dict, "newbyteorder"); | |
if (myobj == NULL) { | |
return; | |
} | |
PyMethodDescr_TypePtr = Py_TYPE(myobj); | |
return; | |
} | |
static struct PyModuleDef moduledef = { | |
PyModuleDef_HEAD_INIT, | |
"_compiled_base", | |
NULL, | |
-1, | |
methods, | |
NULL, | |
NULL, | |
NULL, | |
NULL | |
}; | |
PyMODINIT_FUNC PyInit__compiled_base(void) | |
PyMODINIT_FUNC | |
init_compiled_base(void) | |
{ | |
PyObject *m, *d; | |
m = PyModule_Create(&moduledef); | |
m = Py_InitModule("_compiled_base", methods); | |
if (!m) { | |
return RETVAL; | |
} | |
/* Import the array objects */ | |
import_array(); | |
import_umath(); | |
/* Add some symbolic constants to the module */ | |
d = PyModule_GetDict(m); | |
/* | |
* PyExc_Exception should catch all the standard errors that are | |
* now raised instead of the string exception "numpy.lib.error". | |
* This is for backward compatibility with existing code. | |
*/ | |
PyDict_SetItemString(d, "error", PyExc_Exception); | |
/* define PyGetSetDescr_Type and PyMemberDescr_Type */ | |
define_types(); | |
return RETVAL; | |
} | |