static PyObject* dtw_extension(PyObject *dummy, PyObject *args) {
PyObject *arg1 = NULL;
PyObject *arr1 = NULL;
PyObject *arg2 = NULL;
PyObject *arr2 = NULL;
if (!PyArg_ParseTuple(args, "OO", &arg1, &arg2)) {
return NULL;
}
arr1 = PyArray_FROM_OTF(arg1, NPY_DOUBLE, NPY_ARRAY_IN_ARRAY);
if (arr1 == NULL) {
return NULL;
}
arr2 = PyArray_FROM_OTF(arg2, NPY_DOUBLE, NPY_ARRAY_IN_ARRAY);
if (arr2 == NULL) {
return NULL;
}
// Number of dimensions
int nd1 = PyArray_NDIM((PyArrayObject*)arr1);
int arr_type1 = PyArray_TYPE((PyArrayObject*)arr1);
npy_intp *dims1 = PyArray_DIMS((PyArrayObject*)arr1);
int nd2 = PyArray_NDIM((PyArrayObject*)arr2);
int arr_type2 = PyArray_TYPE((PyArrayObject*)arr2);
npy_intp *dims2 = PyArray_DIMS((PyArrayObject*)arr2);
int r = 0;
npy_double **input1 = NULL;
r = PyArray_AsCArray((PyObject**)&arr1, (void**)&input1, dims1, nd1, PyArray_DescrFromType(arr_type1));
if (r < 0) {
PyErr_SetString(PyExc_RuntimeError, "Could not convert input to C array");
return NULL;
}
npy_double **input2 = NULL;
r = PyArray_AsCArray((PyObject**)&arr2, (void**)&input2, dims2, nd2, PyArray_DescrFromType(arr_type2));
if (r < 0) {
PyErr_SetString(PyExc_RuntimeError, "Could not convert input to C array");
return NULL;
}
// DTW
matrix_t mat_a = { input1, dims1[0], dims1[1] };
matrix_t mat_b = { input2, dims2[0], dims2[1] };
double dist = dtw_distance(&mat_a, &mat_b);
PyObject *value = PyFloat_FromDouble(dist);
if (value == NULL) {
PyErr_SetString(PyExc_RuntimeError, "Could not convert double to object");
return NULL;
}
Py_DECREF(arr1);
Py_DECREF(arr2);
PyArray_Free(arr1, (void*)input1);
PyArray_Free(arr2, (void*)input2);
return value;
}
PyObject *punwrap2D_Unwrap2D(PyObject *self, PyObject *args) {
PyObject *op1, *op2;
PyArrayObject *phsArray, *mskArray, *retArray;
float *wr_phs, *uw_phs;
BYTE *bmask;
int typenum_phs, typenum_msk, ndim;
npy_intp *dims;
PyArray_Descr *dtype_phs;
if(!PyArg_ParseTuple(args, "OO", &op1, &op2)) {
PyErr_SetString(PyExc_Exception,"Unwrap2D: Couldn't parse the arguments");
return NULL;
}
if(op1==NULL || op2==NULL) {
PyErr_SetString(PyExc_Exception,"Unwrap2D: Arguments not read correctly");
return NULL;
}
typenum_phs = PyArray_TYPE(op1);
typenum_msk = PyArray_TYPE(op2);
ndim = PyArray_NDIM(op1);
dims = PyArray_DIMS(op2);
/* This stuff is technically enforced in punwrap/__init__.py */
if(typenum_phs != PyArray_FLOAT) {
PyErr_SetString(PyExc_Exception, "Unwrap2D: I can only handle single-precision floating point numbers");
return NULL;
}
if(typenum_msk != PyArray_UBYTE) {
PyErr_SetString(PyExc_Exception, "Unwrap2D: The mask should be type uint8");
return NULL;
}
if(ndim != 2) {
PyErr_SetString(PyExc_Exception, "Unwrap2D: I can only unwrap 2D arrays");
return NULL;
}
dtype_phs = PyArray_DescrFromType(typenum_phs);
/* increasing references here */
phsArray = (PyArrayObject *)PyArray_FROM_OTF(op1, typenum_phs, NPY_IN_ARRAY);
mskArray = (PyArrayObject *)PyArray_FROM_OTF(op2, typenum_msk, NPY_IN_ARRAY);
/* create a new, empty ndarray with floats */
retArray = (PyArrayObject *)PyArray_SimpleNewFromDescr(ndim, dims, dtype_phs);
wr_phs = (float *)PyArray_DATA(phsArray);
uw_phs = (float *)PyArray_DATA(retArray);
bmask = (BYTE *)PyArray_DATA(mskArray);
phase_unwrap_2D(wr_phs, uw_phs, bmask, (int) dims[0], (int) dims[1]);
Py_DECREF(phsArray);
Py_DECREF(mskArray);
return PyArray_Return(retArray);
}
static PyObject *inverse_subtraction_inplace(PyObject *self, PyObject *args)
{
PyObject* a = NULL;
PyObject* b = NULL;
npy_intp sz = 0, i;
npy_complex64* tmp_sp = NULL;
npy_complex64* a_data_sp = NULL;
npy_float32* b_data_sp = NULL;
npy_complex128* tmp_dp = NULL;
npy_complex128* a_data_dp = NULL;
npy_float64* b_data_dp = NULL;
double c;
if (!PyArg_ParseTuple(args, "OOd", &a, &b, &c))
return NULL;
if (!(PyArray_Check(a) && PyArray_Check(b)))
{
PyErr_SetString(PyExc_TypeError,"arguments must be array objects");
return NULL;
}
sz = PyArray_SIZE(a);
if (sz != PyArray_SIZE(b))
{
PyErr_SetString(PyExc_TypeError,"argument sizes must be equal");
return NULL;
}
if ((PyArray_TYPE(a) == PyArray_COMPLEX64) && (PyArray_TYPE(b) == PyArray_FLOAT32))
{
a_data_sp = (npy_complex64*)PyArray_DATA(a);
b_data_sp = (npy_float32*)PyArray_DATA(b);
for (i=0; i<sz; ++i)
{
tmp_sp = a_data_sp + i;
tmp_sp->real = b_data_sp[i] - tmp_sp->real * c;
}
}
else if ((PyArray_TYPE(a) == PyArray_COMPLEX128) && (PyArray_TYPE(b) == PyArray_FLOAT64))
{
a_data_dp = (npy_complex128*)PyArray_DATA(a);
b_data_dp = (npy_float64*)PyArray_DATA(b);
for (i=0; i<sz; ++i)
{
tmp_dp = a_data_dp + i;
tmp_dp->real = b_data_dp[i] - tmp_dp->real * c;
}
}
else
{
PyErr_SetString(PyExc_TypeError,"argument types must be complex64 and float32");
return NULL;
}
return Py_BuildValue("");
}
// ========================================================================
// class vec<double>
//
// constructor from a python array
vec<double>::vec(array& boost_array)
{ // get array info
PyArrayObject* py_array_p=reinterpret_cast<PyArrayObject*>(boost_array.ptr());
npy_intp* dims_ptr = PyArray_DIMS(py_array_p);
int length = dims_ptr[0];
// check array info
PYCPPAD_ASSERT(
PyArray_NDIM(py_array_p) == 1 ,
"array is not a vector"
);
PYCPPAD_ASSERT(
length >= 0 ,
"array length is <= zero"
);
// set private data
length_ = static_cast<size_t>( length );
if( PyArray_TYPE(py_array_p) == NPY_DOUBLE )
{ pointer_ = static_cast<double*>(
PyArray_DATA(py_array_p)
);
allocated_ = false;
}
else if( PyArray_TYPE(py_array_p) == NPY_INT )
{ pointer_ = CPPAD_TRACK_NEW_VEC(length, pointer_);
int* data = static_cast<int*>(
PyArray_DATA(py_array_p)
);
for(size_t i = 0; i < length_; i++)
pointer_[i] = static_cast<double>( data[i] );
allocated_ = true;
}
else if( PyArray_TYPE(py_array_p) == NPY_LONG )
{ pointer_ = CPPAD_TRACK_NEW_VEC(length, pointer_);
long* data = static_cast<long*>(
PyArray_DATA(py_array_p)
);
for(size_t i = 0; i < length_; i++)
pointer_[i] = static_cast<double>( data[i] );
allocated_ = true;
}
else PYCPPAD_ASSERT(
0,
"expected an array with int or float elements"
);
return;
}
vec<Scalar>::vec(array& boost_array)
{
// get array info
PyArrayObject* py_array_p=reinterpret_cast<PyArrayObject*>(boost_array.ptr());
npy_intp* dims_ptr = PyArray_DIMS(py_array_p);
int length = dims_ptr[0];
// check array info
PYCPPAD_ASSERT(
PyArray_NDIM(py_array_p) == 1 ,
"array is not a vector"
);
PYCPPAD_ASSERT(
PyArray_TYPE(py_array_p) == NPY_OBJECT ,
"expected array elements of type object"
);
PYCPPAD_ASSERT(
length >= 0 ,
"array length is <= zero"
);
// pointer to object
object *obj_ptr = static_cast<object*>(
PyArray_DATA(py_array_p)
);
// set private data
length_ = static_cast<size_t>(length);
pointer_ = 0;
handle_ = CPPAD_TRACK_NEW_VEC(length_, handle_);
for(size_t i = 0; i < length_; i++) handle_[i] =
& extract<Scalar&>(obj_ptr[i])();
return;
}
static PyObject *
Py_gstrf(PyObject *self, PyObject *args, PyObject *keywds)
{
/* default value for SuperLU parameters*/
int N, nnz;
PyArrayObject *rowind, *colptr, *nzvals;
SuperMatrix A;
PyObject *result;
PyObject *option_dict = NULL;
int type;
int ilu = 0;
static char *kwlist[] = {"N","nnz","nzvals","colind","rowptr",
"options", "ilu",
NULL};
int res = PyArg_ParseTupleAndKeywords(
args, keywds, "iiO!O!O!|Oi", kwlist,
&N, &nnz,
&PyArray_Type, &nzvals,
&PyArray_Type, &rowind,
&PyArray_Type, &colptr,
&option_dict,
&ilu);
if (!res)
return NULL;
if (!_CHECK_INTEGER(colptr) || !_CHECK_INTEGER(rowind)) {
PyErr_SetString(PyExc_TypeError,
"rowind and colptr must be of type cint");
return NULL;
}
type = PyArray_TYPE(nzvals);
if (!CHECK_SLU_TYPE(type)) {
PyErr_SetString(PyExc_TypeError,
"nzvals is not of a type supported by SuperLU");
return NULL;
}
if (NCFormat_from_spMatrix(&A, N, N, nnz, nzvals, rowind, colptr,
type)) {
goto fail;
}
result = newSciPyLUObject(&A, option_dict, type, ilu);
if (result == NULL) {
goto fail;
}
/* arrays of input matrix will not be freed */
Destroy_SuperMatrix_Store(&A);
return result;
fail:
/* arrays of input matrix will not be freed */
Destroy_SuperMatrix_Store(&A);
return NULL;
}
static double*
check_double_image(PyObject* image, size_t *nrows, size_t *ncols)
{
double* ptr=NULL;
npy_intp *dims=NULL;
if (!PyArray_Check(image)) {
PyErr_SetString(PyExc_ValueError,
"image must be a 2D numpy array of type 64-bit float");
return NULL;
}
if (2 != PyArray_NDIM((PyArrayObject*)image)) {
PyErr_Format(PyExc_ValueError,
"image must be a 2D numpy array of type 64-bit float");
return NULL;
}
if (NPY_DOUBLE != PyArray_TYPE((PyArrayObject*)image)) {
PyErr_Format(PyExc_ValueError,
"image must be a 2D numpy array of type 64-bit float");
return NULL;
}
ptr = PyArray_DATA((PyArrayObject*)image);
dims = PyArray_DIMS((PyArrayObject*)image);
*nrows = dims[0];
*ncols = dims[1];
return ptr;
}
static int
check_object(PyObject *ob, int t, char *obname,
char *tname, char *funname)
{
if (!PyArray_Check(ob)) {
PyErr_Format(LapackError,
"Expected an array for parameter %s in lapack_lite.%s",
obname, funname);
return 0;
}
else if (!PyArray_IS_C_CONTIGUOUS((PyArrayObject *)ob)) {
PyErr_Format(LapackError,
"Parameter %s is not contiguous in lapack_lite.%s",
obname, funname);
return 0;
}
else if (!(PyArray_TYPE((PyArrayObject *)ob) == t)) {
PyErr_Format(LapackError,
"Parameter %s is not of type %s in lapack_lite.%s",
obname, tname, funname);
return 0;
}
else if (PyArray_ISBYTESWAPPED((PyArrayObject *)ob)) {
PyErr_Format(LapackError,
"Parameter %s has non-native byte order in lapack_lite.%s",
obname, funname);
return 0;
}
else {
return 1;
}
}
static PyObject* gse_checksum(PyObject *dummy, PyObject *args) {
int checksum, length, i;
PyObject *array = NULL;
PyArrayObject *carray = NULL;
int *data;
if (!PyArg_ParseTuple(args, "O", &array )) {
PyErr_SetString(GSEError, "usage checksum(array)" );
return NULL;
}
if (!PyArray_Check(array)) {
PyErr_SetString(GSEError, "Data must be given as NumPy array." );
return NULL;
}
if (PyArray_TYPE(array) != NPY_INT32) {
PyErr_SetString(GSEError, "Data must be 32-bit integers.");
return NULL;
}
carray = PyArray_GETCONTIGUOUS((PyArrayObject*)array);
length = PyArray_SIZE(carray);
data = (int*)PyArray_DATA(carray);
checksum = 0;
for (i=0; i<length; i++) {
checksum += data[i] % MODULUS;
checksum %= MODULUS;
}
return Py_BuildValue("i", abs(checksum));
}
/* setData */
PyObject *
Image_setData(PyObject *obj, PyObject *args, PyObject *kwargs)
{
ImageObject *self = (ImageObject*) obj;
PyArrayObject * arr = NULL;
if (self != NULL && PyArg_ParseTuple(args, "O", &arr))
{
try
{
ImageGeneric & image = Image_Value(self);
DataType dt = npyType2Datatype(PyArray_TYPE(arr));
int nd = PyArray_NDIM(arr);
//Setup of image
image.setDatatype(dt);
ArrayDim adim;
adim.ndim = (nd == 4 ) ? PyArray_DIM(arr, 0) : 1;
adim.zdim = (nd > 2 ) ? PyArray_DIM(arr, nd - 3) : 1;
adim.ydim = PyArray_DIM(arr, nd - 2);
adim.xdim = PyArray_DIM(arr, nd - 1);
MULTIDIM_ARRAY_GENERIC(image).resize(adim, false);
void *mymem = image().getArrayPointer();
void * data = PyArray_DATA(arr);
memcpy(mymem, data, adim.nzyxdim * gettypesize(dt));
Py_RETURN_NONE;
}
catch (XmippError &xe)
{
PyErr_SetString(PyXmippError, xe.msg.c_str());
}
}
return NULL;
}//function Image_setData
static PyObject* PyTesseract_set_image(PyTesseract *self, PyObject *array) {
if (!PyArray_Check(array)) {
PyErr_SetString(PyExc_TypeError, "Image must be a NumPy array");
return NULL;
}
PyArrayObject *np_array = (PyArrayObject *)array;
npy_intp *shape = PyArray_DIMS(np_array);
int dimension_count = PyArray_NDIM(np_array);
int channels = 0;
switch (dimension_count) {
case 2:
channels = 1;
break;
case 3:
channels = (int)shape[2];
break;
default:
PyErr_SetString(PyExc_TypeError, "Invalid array format");
return NULL;
}
int bytes_per_channel = 0;
switch (PyArray_TYPE(np_array)) {
case NPY_BYTE:
case NPY_UBYTE:
bytes_per_channel = 1;
break;
case NPY_SHORT:
case NPY_USHORT:
bytes_per_channel = 2;
break;
case NPY_FLOAT:
bytes_per_channel = 4;
break;
case NPY_DOUBLE:
bytes_per_channel = 8;
break;
default:
PyErr_SetString(PyExc_TypeError, "Invalid array format");
return NULL;
}
int rows = (int)shape[0];
int cols = (int)shape[1];
Py_INCREF(array);
self->image = array;
int bytes_per_pixel = bytes_per_channel * channels;
self->tess->SetImage((unsigned char *)PyArray_BYTES(np_array), cols, rows, bytes_per_pixel, bytes_per_pixel * cols);
PyTesseract_invalidate_iterators(self);
if (self->page) {
delete self->page;
self->page = NULL;
}
Py_INCREF(Py_None);
return Py_None;
}
static PyObject *poisson_hist_factor_estimate(PyObject *self, PyObject *args)
{
PyObject* a = NULL;
PyObject* b = NULL;
npy_intp sz = 0, i;
npy_float32 tmp;
npy_float32* a_data = NULL;
npy_float32* b_data = NULL;
double c;
double unstable = 0.0, stable = 0.0;
if (!PyArg_ParseTuple(args, "OOd", &a, &b, &c))
return NULL;
if (c<0 || c>0.5)
{
PyErr_SetString(PyExc_TypeError,"third argument must be non-negative and less than 0.5");
return NULL;
}
if (!(PyArray_Check(a) && PyArray_Check(b)))
{
PyErr_SetString(PyExc_TypeError,"first two arguments must be array objects");
return NULL;
}
sz = PyArray_SIZE(a);
if (sz != PyArray_SIZE(b))
{
PyErr_SetString(PyExc_TypeError,"array argument sizes must be equal");
return NULL;
}
if (! ((PyArray_TYPE(a) == PyArray_FLOAT32) && (PyArray_TYPE(b) == PyArray_FLOAT32)))
{
PyErr_SetString(PyExc_TypeError,"array argument types must be float32");
return NULL;
}
a_data = (npy_float32*)PyArray_DATA(a);
b_data = (npy_float32*)PyArray_DATA(b);
for (i=0; i<sz; ++i)
{
tmp = a_data[i];
if (((tmp>-c) && (tmp<c)) || ((tmp<1.0+c) && (tmp>1.0-c)))
stable += tmp * b_data[i];
else
{
unstable += tmp * b_data[i];
}
}
return Py_BuildValue("dd",stable, unstable);
}
td_tag_t td_py_get_eltype(void *v)
{
if (PyArray_Check( (PyObject *) v)){
PyArrayObject *arr = (PyArrayObject *)v;
return numpy_type_to_td(PyArray_TYPE(v));
}
return TD_UNKNOWN;
}
static PyObject* write_coords(PyObject* self, PyObject* args)
{
oskar_MeasurementSet* h = 0;
PyObject *capsule = 0;
PyObject *obj[] = {0, 0, 0};
PyArrayObject *uu = 0, *vv = 0, *ww = 0;
int start_row = 0, num_baselines = 0;
double exposure_sec = 0.0, interval_sec = 0.0, time_stamp = 0.0;
if (!PyArg_ParseTuple(args, "OiiOOOddd", &capsule,
&start_row, &num_baselines, &obj[0], &obj[1], &obj[2],
&exposure_sec, &interval_sec, &time_stamp))
return 0;
if (!(h = (oskar_MeasurementSet*) get_handle(capsule, name))) return 0;
/* Make sure input objects are arrays. Convert if required. */
uu = (PyArrayObject*) PyArray_FROM_OF(obj[0], NPY_ARRAY_IN_ARRAY);
vv = (PyArrayObject*) PyArray_FROM_OF(obj[1], NPY_ARRAY_IN_ARRAY);
ww = (PyArrayObject*) PyArray_FROM_OF(obj[2], NPY_ARRAY_IN_ARRAY);
if (!uu || !vv || !ww)
goto fail;
/* Check dimensions. */
if (num_baselines != (int) PyArray_SIZE(uu) ||
num_baselines != (int) PyArray_SIZE(vv) ||
num_baselines != (int) PyArray_SIZE(ww))
{
PyErr_SetString(PyExc_RuntimeError, "Input data dimension mismatch.");
goto fail;
}
/* Write the coordinates. */
Py_BEGIN_ALLOW_THREADS
if (PyArray_TYPE(uu) == NPY_DOUBLE)
oskar_ms_write_coords_d(h, start_row, num_baselines,
(const double*)PyArray_DATA(uu),
(const double*)PyArray_DATA(vv),
(const double*)PyArray_DATA(ww),
exposure_sec, interval_sec, time_stamp);
else
oskar_ms_write_coords_f(h, start_row, num_baselines,
(const float*)PyArray_DATA(uu),
(const float*)PyArray_DATA(vv),
(const float*)PyArray_DATA(ww),
exposure_sec, interval_sec, time_stamp);
Py_END_ALLOW_THREADS
Py_XDECREF(uu);
Py_XDECREF(vv);
Py_XDECREF(ww);
return Py_BuildValue("");
fail:
Py_XDECREF(uu);
Py_XDECREF(vv);
Py_XDECREF(ww);
return 0;
}
static void to_td_val(td_val_t *out, PyObject *pVal)
{
PyObject *pStr;
td_array_t *arr;
PyArrayObject *pArr;
td_tag_t tag = py_type_to_td(pVal);
switch (tag) {
case TD_INT32:
out->tag = TD_INT32;
if (PyInt_Check(pVal))
out->int32_val = PyInt_AS_LONG(pVal);
else
out->int32_val = PyLong_AsLong(pVal);
break;
case TD_UINT32:
out->tag = TD_UINT32;
out->uint32_val = PyLong_AsUnsignedLong(pVal);
break;
case TD_INT64:
out->tag = TD_INT64;
out->int64_val = PyLong_AsLongLong(pVal);
break;
case TD_UINT64:
out->tag = TD_UINT64;
out->uint64_val = PyLong_AsUnsignedLongLong(pVal);
break;
case TD_DOUBLE:
out->tag = TD_DOUBLE;
out->double_val = PyFloat_AsDouble(pVal);
break;
case TD_UTF8:
pStr = pVal;
if (PyUnicode_Check(pStr)) pStr = PyUnicode_AsUTF8String(pStr);
size_t len = PyString_Size(pStr);
char* data = malloc((len+1)*sizeof(char));
strcpy(PyString_AsString(pStr), data);
td_string_t *obj = malloc(sizeof(td_string_t));
obj->length = len;
obj->data = (void*) data;
out->tag = TD_UTF8;
out->object = (void*) obj;
break;
case TD_ARRAY:
arr = (td_array_t *)malloc(sizeof(td_array_t));
pArr = (PyArrayObject *) pVal;
arr->data = PyArray_DATA(pArr);
arr->length = PyArray_SIZE(pArr);
arr->eltype = numpy_type_to_td(PyArray_TYPE(pArr));
arr->ndims = PyArray_NDIM(pArr);
break;
default:
out->tag = TD_OBJECT;
out->owner = td_env_python(NULL, NULL);
out->object = pVal;
}
}
static PyObject* write_vis(PyObject* self, PyObject* args)
{
oskar_MeasurementSet* h = 0;
PyObject *capsule = 0;
PyObject *obj = 0;
PyArrayObject *vis = 0;
int start_row = 0, start_channel = 0;
int num_channels = 0, num_baselines = 0, num_pols = 0;
if (!PyArg_ParseTuple(args, "OiiiiO", &capsule, &start_row,
&start_channel, &num_channels, &num_baselines, &obj))
return 0;
if (!(h = get_handle(capsule))) return 0;
/* Make sure input objects are arrays. Convert if required. */
vis = (PyArrayObject*) PyArray_FROM_OF(obj, NPY_ARRAY_IN_ARRAY);
if (!vis)
goto fail;
/* Get precision of complex visibility data. */
if (!PyArray_ISCOMPLEX(vis))
{
PyErr_SetString(PyExc_RuntimeError,
"Input visibility data must be complex.");
goto fail;
}
/* Check dimensions. */
num_pols = oskar_ms_num_pols(h);
if (num_baselines * num_channels * num_pols != (int) PyArray_SIZE(vis))
{
PyErr_SetString(PyExc_RuntimeError, "Input data dimension mismatch.");
goto fail;
}
/* Allow threads. */
Py_BEGIN_ALLOW_THREADS
/* Write the visibilities. */
if (PyArray_TYPE(vis) == NPY_DOUBLE)
oskar_ms_write_vis_d(h, start_row, start_channel, num_channels,
num_baselines, (const double*)PyArray_DATA(vis));
else
oskar_ms_write_vis_f(h, start_row, start_channel, num_channels,
num_baselines, (const float*)PyArray_DATA(vis));
/* Disallow threads. */
Py_END_ALLOW_THREADS
Py_XDECREF(vis);
return Py_BuildValue("");
fail:
Py_XDECREF(vis);
return 0;
}
/* Fetch vector data from an iterator (view or copy) */
void _fff_vector_sync_with_PyArrayIter(fff_vector* y, const PyArrayIterObject* it, npy_intp axis)
{
if (y->owner) {
PyArrayObject* ao = (PyArrayObject*) it->ao;
COPY_BUFFER(y, PyArray_ITER_DATA(it), PyArray_STRIDE(ao, axis),
PyArray_TYPE(ao), PyArray_ITEMSIZE(ao));
}
else
y->data = (double*) PyArray_ITER_DATA(it);
return;
}
fff_array* fff_array_fromPyArray(const PyArrayObject* x)
{
fff_array* y;
fff_datatype datatype;
unsigned int nbytes;
size_t dimX = 1, dimY = 1, dimZ = 1, dimT = 1;
size_t offX = 0, offY = 0, offZ = 0, offT = 0;
size_t ndims = (size_t)PyArray_NDIM(x);
/* Check that the input array has less than four dimensions */
if (ndims > 4) {
FFF_ERROR("Input array has more than four dimensions", EINVAL);
return NULL;
}
/* Check that the input array is aligned */
if (! PyArray_ISALIGNED(x)) {
FFF_ERROR("Input array is not aligned", EINVAL);
return NULL;
}
/* Match the data type */
datatype = fff_datatype_fromNumPy(PyArray_TYPE(x));
if (datatype == FFF_UNKNOWN_TYPE) {
FFF_ERROR("Unrecognized data type", EINVAL);
return NULL;
}
/* Dimensions and offsets */
nbytes = fff_nbytes(datatype);
dimX = PyArray_DIM(x, 0);
offX = PyArray_STRIDE(x, 0)/nbytes;
if (ndims > 1) {
dimY = PyArray_DIM(x, 1);
offY = PyArray_STRIDE(x, 1)/nbytes;
if (ndims > 2) {
dimZ = PyArray_DIM(x, 2);
offZ = PyArray_STRIDE(x, 2)/nbytes;
if (ndims > 3) {
dimT = PyArray_DIM(x, 3);
offT = PyArray_STRIDE(x, 3)/nbytes;
}
}
}
/* Create array (not owner) */
y = (fff_array*)malloc(sizeof(fff_array));
*y = fff_array_view(datatype,
(void*) PyArray_DATA(x),
dimX, dimY, dimZ, dimT,
offX, offY, offZ, offT);
return y;
}
void local_histogram(double* H,
unsigned int clamp,
PyArrayIterObject* iter,
const unsigned int* size)
{
PyArrayObject *block, *im = iter->ao;
PyArrayIterObject* block_iter;
unsigned int i, left, right, center, halfsize, dim, offset=0;
npy_intp block_dims[3];
UPDATE_ITERATOR_COORDS(iter);
/* Compute block corners */
for (i=0; i<3; i++) {
center = iter->coordinates[i];
halfsize = size[i]/2;
dim = PyArray_DIM(im, i);
/* Left handside corner */
if (center<halfsize)
left = 0;
else
left = center-halfsize;
/* Right handside corner (plus one)*/
right = center+halfsize+1;
if (right>dim)
right = dim;
/* Block properties */
offset += left*PyArray_STRIDE(im, i);
block_dims[i] = right-left;
}
/* Create the block as a vew and the block iterator */
block = (PyArrayObject*)PyArray_New(&PyArray_Type, 3, block_dims,
PyArray_TYPE(im), PyArray_STRIDES(im),
(void*)(PyArray_DATA(im)+offset),
PyArray_ITEMSIZE(im),
NPY_BEHAVED, NULL);
block_iter = (PyArrayIterObject*)PyArray_IterNew((PyObject*)block);
/* Compute block histogram */
histogram(H, clamp, block_iter);
/* Free memory */
Py_XDECREF(block_iter);
Py_XDECREF(block);
return;
}
MPI_Datatype type_map(PyArrayObject *x, int *count) {
/* Return the MPI Datatype corresponding to
the Python data type as follows
TYPE py_type mpi_type bytes symbol
----------------------------------------
INT 4 6 4 'i'
LONG 5 8 8 'l'
FLOAT 6 10 4 'f'
DOUBLE 12 11 8 'd'
Also return the total number of elements in the array
The Python datatype COMPLEX ('F') and COMPLEX_DOUBLE ('D')
is treated as a special case to the absence of an
MPI_COMPLEX datatype:
Complex arrays are mapped to float or double arrays with real
and imaginary parts alternating and count is updated. */
int py_type;
MPI_Datatype mpi_type;
*count = length(x);
py_type = PyArray_TYPE(x);
if (py_type == NPY_DOUBLE)
mpi_type = MPI_DOUBLE;
else if (py_type == NPY_INT)
mpi_type = MPI_INT;
else if (py_type == NPY_CDOUBLE) {
mpi_type = MPI_DOUBLE;
(*count) *= 2;
} else if (py_type == NPY_FLOAT)
mpi_type = MPI_FLOAT;
else if (py_type == NPY_LONG)
mpi_type = MPI_LONG;
else if (py_type == NPY_CFLOAT) {
mpi_type = MPI_FLOAT;
(*count) *= 2;
} else {
/* FIXME: Should let caller decide about setting Python exception */
PyErr_Format(PyExc_ValueError,
"Array must be of type int or float. I got py_type == %d", py_type);
/* FIXME: consider MPI_DATATYPE_NULL */
return (MPI_Datatype) NULL;
}
//printf("Types: py_type=%d, mpi_type=%d\n", py_type, (int) mpi_type);
return mpi_type;
}
static double*
coerce_ndarray_double(PyArrayObject *in, PyArrayObject **out)
{
int pcm_type = PyArray_TYPE(in);
if (pcm_type==NPY_DOUBLE)
return ((double *) PyArray_DATA(in));
else if (PyArray_CanCastSafely(pcm_type, NPY_DOUBLE)) {
*out = (PyArrayObject*)PyArray_Cast(in, NPY_DOUBLE);
return ((double *) PyArray_DATA(*out));
}
else
return NULL;
}
/* Create an fff_vector from a PyArrayIter object */
fff_vector* _fff_vector_new_from_PyArrayIter(const PyArrayIterObject* it, npy_intp axis)
{
fff_vector* y;
char* data = PyArray_ITER_DATA(it);
PyArrayObject* ao = (PyArrayObject*) it->ao;
npy_intp dim = PyArray_DIM(ao, axis);
npy_intp stride = PyArray_STRIDE(ao, axis);
int type = PyArray_TYPE(ao);
int itemsize = PyArray_ITEMSIZE(ao);
y = _fff_vector_new_from_buffer(data, dim, stride, type, itemsize);
return y;
}
static PyObject *zero_if_zero_inplace(PyObject *self, PyObject *args)
{
PyObject* a = NULL;
PyObject* b = NULL;
npy_intp sz = 0, i;
npy_complex64* tmp = NULL;
npy_complex64* a_data = NULL;
npy_float32* b_data = NULL;
if (!PyArg_ParseTuple(args, "OO", &a, &b))
return NULL;
if (!(PyArray_Check(a) && PyArray_Check(b)))
{
PyErr_SetString(PyExc_TypeError,"arguments must be array objects");
return NULL;
}
sz = PyArray_SIZE(a);
if (sz != PyArray_SIZE(b))
{
PyErr_SetString(PyExc_TypeError,"argument sizes must be equal");
return NULL;
}
if (! ((PyArray_TYPE(a) == PyArray_COMPLEX64) && (PyArray_TYPE(b) == PyArray_FLOAT32)))
{
PyErr_SetString(PyExc_TypeError,"argument types must be complex64 and float32");
return NULL;
}
a_data = (npy_complex64*)PyArray_DATA(a);
b_data = (npy_float32*)PyArray_DATA(b);
for (i=0; i<sz; ++i)
{
if (b_data[i]==0)
{
tmp = a_data + i;
tmp->real = tmp->imag = 0.0;
}
}
return Py_BuildValue("");
}
fvec_t *
PyAubio_ArrayToCFvec (PyObject *input) {
PyObject *array;
fvec_t *vec;
if (input == NULL) {
PyErr_SetString (PyExc_ValueError, "input array is not a python object");
goto fail;
}
// parsing input object into a Py_fvec
if (PyArray_Check(input)) {
// we got an array, convert it to an fvec
if (PyArray_NDIM (input) == 0) {
PyErr_SetString (PyExc_ValueError, "input array is a scalar");
goto fail;
} else if (PyArray_NDIM (input) > 1) {
PyErr_SetString (PyExc_ValueError,
"input array has more than one dimensions");
goto fail;
}
if (!PyArray_ISFLOAT (input)) {
PyErr_SetString (PyExc_ValueError, "input array should be float");
goto fail;
} else if (PyArray_TYPE (input) != AUBIO_NPY_SMPL) {
PyErr_SetString (PyExc_ValueError, "input array should be float32");
goto fail;
} else {
// input data type is float32, nothing else to do
array = input;
}
// vec = new_fvec (vec->length);
// no need to really allocate fvec, just its struct member
vec = (fvec_t *)malloc(sizeof(fvec_t));
vec->length = PyArray_SIZE (array);
vec->data = (smpl_t *) PyArray_GETPTR1 (array, 0);
} else if (PyObject_TypeCheck (input, &PyList_Type)) {
PyErr_SetString (PyExc_ValueError, "does not convert from list yet");
return NULL;
} else {
PyErr_SetString (PyExc_ValueError, "can only accept vector of float as input");
return NULL;
}
return vec;
fail:
return NULL;
}
int not_doublevector(PyArrayObject *vec)
{
if (PyArray_TYPE(vec) != NPY_DOUBLE) {
PyErr_SetString(PyExc_ValueError,
"Vector is not a float or double vector.");
return 1;
}
if (PyArray_NDIM(vec) != 1) {
PyErr_Format(PyExc_ValueError,
"Vector is not a 1 dimensional vector (%d).", PyArray_NDIM(vec));
return 1;
}
return 0;
}
static PyObject *_eclipse(PyObject *self, PyObject *args)
{
int nthreads;
double d, p, kap0, kap1, fp, alpha_t, alpha_o;
PyArrayObject *ds, *flux;
npy_intp i, dims[1];
if(!PyArg_ParseTuple(args, "Oddi", &ds, &p, &fp, &nthreads)) return NULL; //parses function input
dims[0] = PyArray_DIMS(ds)[0];
flux = (PyArrayObject *) PyArray_SimpleNew(1, dims, PyArray_TYPE(ds)); //creates numpy array to store return flux values
double *f_array = PyArray_DATA(flux);
double *d_array = PyArray_DATA(ds);
if(fabs(p - 0.5) < 1.e-3) p = 0.5;
#if defined (_OPENMP)
omp_set_num_threads(nthreads);
#endif
#if defined (_OPENMP)
#pragma omp parallel for private(d, kap1, kap0)
#endif
for(i=0; i<dims[0]; i++)
{
d = d_array[i]; // separation of centers
if(d >= 1. + p)
{
f_array[i] = 1. + fp; //planet fully visible
}
else if(d < 1. - p)
{
f_array[i] = 1.; //planet fully occulted
}
else //planet is crossing the limb
{
kap1=acos(fmin((1. - p*p + d*d)/2./d, 1.));
kap0=acos(fmin((p*p + d*d - 1.)/2./p/d, 1.));
alpha_t = (p*p*kap0 + kap1 - 0.5*sqrt(fmax(4.*d*d \
- pow(1. + d*d - p*p, 2.), 0.)))/M_PI; //transit depth
alpha_o = alpha_t/p/p; //fraction of planet disk that is eclipsed by the star
f_array[i] = 1. + fp*(1. - alpha_o); //planet partially occulted
}
}
return PyArray_Return((PyArrayObject *)flux);
}
int PyUFunc_PipelinedFunction(PyUFuncObject *ufunc, PyArrayObject **args, size_t start, size_t end) {
int retval = 0;
int i, nin = ufunc->nin, nout = ufunc->nout;
int nop = nin + nout;
PyArray_Descr *dtypes[NPY_MAXARGS];
PyArrayObject *op[NPY_MAXARGS];
NPY_ORDER order = NPY_KEEPORDER;
NPY_CASTING casting = NPY_DEFAULT_ASSIGN_CASTING;
int trivial_loop_ok = 1;
for (i = 0; i < NPY_MAXARGS; ++i) {
op[i] = NULL;
dtypes[i] = NULL;
}
retval = ufunc->type_resolver(ufunc, casting, args, NULL, dtypes);
if (retval < 0) {
goto fail;
}
for(i = 0; i < nop; ++i) {
size_t size = PyArray_SIZE(args[i]);
if (size > 1) {
npy_intp elements[1] = { end - start };
Py_XINCREF(PyArray_DESCR(args[i]));
op[i] = (PyArrayObject*) PyArray_NewFromDescr(&PyArray_Type, PyArray_DESCR(args[i]), 1, elements, NULL, PyArray_ElementPointer(args[i], start), NPY_ARRAY_CARRAY | !NPY_ARRAY_OWNDATA, NULL);
} else {
Py_XINCREF(args[i]);
op[i] = args[i];
}
if (PyArray_TYPE(args[i]) != dtypes[i]->type_num) {
assert(i < nin); // Casting makes no sense for output arrays, only for input arrays. If we have to cast the output array something went wrong
PyArrayObject *converted = (PyArrayObject*) PyArray_CastToType(op[i], dtypes[i], 0);
Py_XDECREF(op[i]);
op[i] = converted;
}
}
retval = execute_legacy_ufunc_loop(ufunc, trivial_loop_ok, op, dtypes, order);
for(i = 0; i < nop; ++i) {
Py_XDECREF(op[i]);
}
fail:
return retval;
}
fff_vector* fff_vector_fromPyArray(const PyArrayObject* x)
{
fff_vector* y;
int ok;
npy_intp axis = _PyArray_main_axis(x, &ok);
if (!ok) {
FFF_ERROR("Input array is not a vector", EINVAL);
return NULL;
}
y = _fff_vector_new_from_buffer(PyArray_DATA(x),
PyArray_DIM(x, axis),
PyArray_STRIDE(x, axis),
PyArray_TYPE(x),
PyArray_ITEMSIZE(x));
return y;
}
int good_array(PyObject* o, int typenum) {
if (!PyArray_Check(o)) {
PyErr_SetString(PyExc_ValueError, "not a NumPy array" );
return 0;
}
if (PyArray_TYPE((PyArrayObject*)o) != typenum) {
PyErr_SetString(PyExc_ValueError, "array of unexpected type");
return 0;
}
if (!PyArray_ISCARRAY((PyArrayObject*)o)) {
PyErr_SetString(PyExc_ValueError, "array is not contiguous or not well behaved");
return 0;
}
return 1;
}
PyObject *punwrap3D_Unwrap3D(PyObject *self, PyObject *args) {
PyObject *op;
PyArrayObject *phsArray, *retArray;
float *wr_phs, *uw_phs;
npy_intp *dims;
int typenum_phs, ndim;
PyArray_Descr *dtype_phs;
if(!PyArg_ParseTuple(args, "O", &op)) {
PyErr_SetString(PyExc_Exception, "Unwrap3D: Couldn't parse any args");
return NULL;
}
if(op==NULL) {
PyErr_SetString(PyExc_Exception, "Unwrap3D: Arguments not read correctly");
return NULL;
}
typenum_phs = PyArray_TYPE(op);
ndim = PyArray_NDIM(op);
dims = PyArray_DIMS(op);
if(typenum_phs != PyArray_FLOAT) {
PyErr_SetString(PyExc_Exception, "Unwrap3D: I can only handle single-precision floating point numbers");
return NULL;
}
if(ndim < 3) {
PyErr_SetString(PyExc_Exception, "Unwrap3D: I can only unwrap 3D arrays");
return NULL;
}
dtype_phs = PyArray_DescrFromType(typenum_phs);
/* increasing reference here */
phsArray = (PyArrayObject *)PyArray_FROM_OTF(op, typenum_phs, NPY_IN_ARRAY);
/* create a new, empty ndarray with floats */
retArray = (PyArrayObject *)PyArray_SimpleNewFromDescr(ndim, dims, dtype_phs);
wr_phs = (float *)PyArray_DATA(phsArray);
uw_phs = (float *)PyArray_DATA(retArray);
unwrap_phs(wr_phs, uw_phs, (int) dims[0], (int) dims[1], (int) dims[2]);
Py_DECREF(phsArray);
return PyArray_Return(retArray);
}