// this copies a block of memory from a numpy array to a memory address
static PyObject*
pymappedndf_numpytondf(NDFMapped *self, PyObject *args)
{
PyObject *npy, *ptrobj;
PyArrayObject *npyarray;
npy_intp el;
size_t bytes;
if(!PyArg_ParseTuple(args, "O:pyndfmapped_numpytondf",&npy))
return NULL;
void *ptr = self->_pntr;
el = self->nelem;
if (el <= 0 || ptr == NULL) {
PyErr_SetString( PyExc_ValueError,
"ndf.mapped object does not have mapped pointer or element count");
return NULL;
}
int npytype = ndftype2numpy( self->type, &bytes );
if (npytype == 0) return NULL;
npyarray = (PyArrayObject*) PyArray_FROM_OTF(npy, npytype, NPY_IN_ARRAY | NPY_FORCECAST);
if (!npyarray) return NULL;
/* Verify the number of elements */
if ( PyArray_Size(npyarray) != el ) {
PyErr_Format( PyExc_ValueError,
"Number of elements in numpy array (%zu) differs from number of elements mapped (%zu)",
(size_t)PyArray_Size(npyarray), (size_t)el );
Py_DECREF(npyarray);
return NULL;
}
memcpy(ptr,PyArray_DATA(npyarray),el*bytes);
Py_DECREF(npyarray);
Py_RETURN_NONE;
}
static PyObject *Py_table_join(PyObject *self, PyObject *args)
{
PyObject *ret = NULL;
PyObject *id1 = NULL, *id2 = NULL, *m1 = NULL, *m2 = NULL;
const char *join_type = NULL;
try
{
PyObject *id1_, *id2_, *m1_, *m2_;
if (! PyArg_ParseTuple(args, "OOOOs", &id1_, &id2_, &m1_, &m2_, &join_type)) throw E(PyExc_Exception, "Wrong number or type of args");
if ((id1 = PyArray_ContiguousFromAny(id1_, PyArray_UINT64, 1, 1)) == NULL) throw E(PyExc_Exception, "id1 is not a 1D uint64 NumPy array");
if ((id2 = PyArray_ContiguousFromAny(id2_, PyArray_UINT64, 1, 1)) == NULL) throw E(PyExc_Exception, "Could not cast the value of id2 to 1D NumPy array");
if ((m1 = PyArray_ContiguousFromAny(m1_, PyArray_UINT64, 1, 1)) == NULL) throw E(PyExc_Exception, "Could not cast the value of m1 to 1D NumPy array");
if ((m2 = PyArray_ContiguousFromAny(m2_, PyArray_UINT64, 1, 1)) == NULL) throw E(PyExc_Exception, "Could not cast the value of m2 to 1D NumPy array");
if (PyArray_DIM(m1, 0) != PyArray_DIM(m2, 0)) throw E(PyExc_Exception, "The sizes of len(m1) and len(m2) must be the same");
#define DATAPTR(type, obj) ((type*)PyArray_DATA(obj))
PyOutput o;
table_join(
o,
DATAPTR(uint64_t, id1), PyArray_Size(id1),
DATAPTR(uint64_t, id2), PyArray_Size(id2),
DATAPTR(uint64_t, m1), DATAPTR(uint64_t, m2), PyArray_Size(m2),
join_type
);
#undef DATAPTR
o.resize(o.size);
ret = PyTuple_New(4);
// because PyTuple will take ownership (and PyOutput will do a DECREF on destruction).
Py_INCREF(o.o_idx1);
Py_INCREF(o.o_idx2);
Py_INCREF(o.o_idxLink);
Py_INCREF(o.o_isnull);
PyTuple_SetItem(ret, 0, (PyObject *)o.o_idx1);
PyTuple_SetItem(ret, 1, (PyObject *)o.o_idx2);
PyTuple_SetItem(ret, 2, (PyObject *)o.o_idxLink);
PyTuple_SetItem(ret, 3, (PyObject *)o.o_isnull);
}
catch(const E& e)
{
ret = NULL;
}
Py_XDECREF(id1);
Py_XDECREF(id2);
Py_XDECREF(m1);
Py_XDECREF(m2);
return ret;
}
static PyObject * computeMean(PyObject *obj, PyObject *args)
{
PyObject *oimage;
PyArrayObject *image;
int status=0;
int numGoodPixels;
float clipmin, clipmax, mean, stddev, minValue, maxValue;
if (!PyArg_ParseTuple(args,"Off:computeMean",&oimage, &clipmin, &clipmax))
return NULL;
image = (PyArrayObject *)PyArray_ContiguousFromObject(oimage, NPY_FLOAT32, 1, 2);
if (!image) return NULL;
mean = 0;
stddev = 0;
numGoodPixels = 0;
minValue = 0;
maxValue = 0;
status = computeMean_((float *)PyArray_DATA(image), PyArray_Size((PyObject*)image),
clipmin, clipmax,
&numGoodPixels, &mean, &stddev, &minValue, &maxValue);
Py_XDECREF(image);
return Py_BuildValue("iffff",numGoodPixels,mean,stddev,minValue,maxValue);
}
static void f2py_report_on_array_copy(PyArrayObject* arr) {
const long arr_size = PyArray_Size((PyObject *)arr);
if (arr_size>F2PY_REPORT_ON_ARRAY_COPY) {
fprintf(stderr,"copied an array: size=%ld, elsize=%d\n",
arr_size, PyArray_ITEMSIZE(arr));
}
}
// =============================================================================
Epetra_Map & Epetra_NumPyVector::getMap(PyObject * pyObject)
{
if (!tmp_array) getArray(pyObject);
if (!tmp_map)
{
const int totalLength = PyArray_Size((PyObject *)tmp_array);
tmp_map = new Epetra_Map(totalLength,0,defaultComm);
}
return *tmp_map;
}
std::valarray<T> convert2valarray(boost::python::object arr)
{
import(); // ### WARNING: forgetting this will end up in segmentation fault!
std::size_t vec_size = PyArray_Size(arr.ptr());
T * data = (T *) PyArray_DATA(arr.ptr());
std::valarray<T> vec(vec_size);
memcpy(&vec[0],data, PyArray_ITEMSIZE((PyArrayObject*) arr.ptr()) * vec_size);
return vec;
}
void dump_attrs(const PyArrayObject* arr) {
int rank = arr->nd;
npy_intp size = PyArray_Size((PyObject *)arr);
printf("\trank = %d, flags = %d, size = %" NPY_INTP_FMT "\n",
rank,arr->flags,size);
printf("\tstrides = ");
dump_dims(rank,arr->strides);
printf("\tdimensions = ");
dump_dims(rank,arr->dimensions);
}
// =============================================================================
Epetra_Map & Epetra_NumPyMultiVector::getMap(PyObject * pyObject)
{
if (!tmp_array) getArray(pyObject);
if (!tmp_map)
{
const int totalLength = PyArray_Size((PyObject *)tmp_array);
const int numVectors = PyArray_DIMS(tmp_array)[0];
tmp_map = new Epetra_Map(totalLength/numVectors,0,defaultComm);
}
return *tmp_map;
}
void dump_attrs(const PyArrayObject* obj) {
const PyArrayObject_fields *arr = (const PyArrayObject_fields*) obj;
int rank = PyArray_NDIM(arr);
npy_intp size = PyArray_Size((PyObject *)arr);
printf("\trank = %d, flags = %d, size = %" NPY_INTP_FMT "\n",
rank,arr->flags,size);
printf("\tstrides = ");
dump_dims(rank,arr->strides);
printf("\tdimensions = ");
dump_dims(rank,arr->dimensions);
}
void
copy_array_to_c_double(
PyArrayObject* array,
double* dest) {
npy_intp size = 1;
double* data = NULL;
size = PyArray_Size((PyObject*)array);
data = (double*)PyArray_DATA(array);
memcpy(dest, data, size * sizeof(double));
}
void
copy_array_to_c_int(
PyArrayObject* array,
int* dest) {
npy_intp size = 1;
int* data = NULL;
size = PyArray_Size((PyObject*)array);
data = (int*)PyArray_DATA(array);
memcpy(dest, data, size * sizeof(int));
}
void
unoffset_array(
PyArrayObject* array,
int value) {
npy_intp size;
double *data;
if (value == 1) {
return;
}
size = PyArray_Size((PyObject*)array);
data = (double*)PyArray_DATA(array);
offset_c_array(data, size, (double)-(1 - value));
}
// Get sweep infornation from file header block. Returns:
// 0 ... performed normally
// 1 ... error occurred
// Arguments:
// debugMode ... debug messages flag
// sweep ... acquired sweep parameter name, new reference created
// buf ... header string
// sweepSize ... acquired number of sweep points
// sweepValues ... sweep points array, new reference created
// faSweep ... pointer to fast access structure for sweep array
int getSweepInfo(int debugMode, int postVersion, PyObject **sweep, char *buf, int *sweepSize,
PyObject **sweepValues, struct FastArray *faSweep)
{
char *sweepName = NULL;
npy_intp dims;
sweepName = strtok(NULL, " \t\n"); // Get sweep parameter name.
if(sweepName == NULL)
{
if(debugMode)
fprintf(debugFile, "HSpiceRead: failed to extract sweep name.\n");
return 1;
}
*sweep = PyString_FromString(sweepName);
if(*sweep == NULL)
{
if(debugMode)
fprintf(debugFile, "HSpiceRead: failed to create sweep name string.\n");
return 1;
}
// Get number of sweep points.
if(postVersion == 2001)
*sweepSize = atoi(&buf[sweepSizePosition1]);
else *sweepSize = atoi(&buf[sweepSizePosition2]);
// Create array for sweep parameter values.
dims=*sweepSize;
*sweepValues = PyArray_SimpleNew(1, &dims, PyArray_DOUBLE);
if(*sweepValues == NULL)
{
if(debugMode) fprintf(debugFile, "HSpiceRead: failed to create array.\n");
return 1;
}
// Prepare fast access structure.
faSweep->data = ((PyArrayObject *)(*sweepValues))->data;
faSweep->pos = ((PyArrayObject *)(*sweepValues))->data;
faSweep->stride =
((PyArrayObject *)(*sweepValues))->strides[((PyArrayObject *)(*sweepValues))->nd -
1];
faSweep->length = PyArray_Size(*sweepValues);
return 0;
}
int getSize2( void* arr ) {
return (int) PyArray_Size( (PyObject *) arr );
// return (int) (((PyArrayObject *)(arr))->nd));
}
/*
* Converts a numpy ndarray to a Java primitive array.
*
* @param env the JNI environment
* @param param the ndarray to convert
* @param desiredType the desired type of the resulting primitive array, or
* NULL if it should determine type based on the dtype
*
* @return a Java primitive array, or NULL if there were errors
*/
jarray convert_pyndarray_jprimitivearray(JNIEnv* env,
PyObject *param,
jclass desiredType)
{
jarray arr = NULL;
PyArrayObject *copy = NULL;
enum NPY_TYPES paType;
jsize sz;
if (!npy_array_check(param)) {
PyErr_Format(PyExc_TypeError, "convert_pyndarray must receive an ndarray");
return NULL;
}
// determine what we can about the pyarray that is to be converted
sz = (jsize) PyArray_Size(param);
paType = PyArray_TYPE((PyArrayObject *) param);
if (desiredType == NULL) {
if (paType == NPY_BOOL) {
desiredType = JBOOLEAN_ARRAY_TYPE;
} else if (paType == NPY_BYTE) {
desiredType = JBYTE_ARRAY_TYPE;
} else if (paType == NPY_INT16) {
desiredType = JSHORT_ARRAY_TYPE;
} else if (paType == NPY_INT32) {
desiredType = JINT_ARRAY_TYPE;
} else if (paType == NPY_INT64) {
desiredType = JLONG_ARRAY_TYPE;
} else if (paType == NPY_FLOAT32) {
desiredType = JFLOAT_ARRAY_TYPE;
} else if (paType == NPY_FLOAT64) {
desiredType = JDOUBLE_ARRAY_TYPE;
} else {
PyErr_Format(PyExc_TypeError,
"Unable to determine corresponding Java type for ndarray");
return NULL;
}
}
/*
* TODO we could speed this up if we could skip the copy, but the copy makes
* it safer by enforcing the correct length in bytes for the type
*/
copy = (PyArrayObject *) PyArray_CopyFromObject(param, paType, 0, 0);
if ((*env)->IsSameObject(env, desiredType, JBOOLEAN_ARRAY_TYPE)
&& (paType == NPY_BOOL)) {
arr = (*env)->NewBooleanArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JBYTE_ARRAY_TYPE)
&& (paType == NPY_BYTE)) {
arr = (*env)->NewByteArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JSHORT_ARRAY_TYPE)
&& (paType == NPY_INT16)) {
arr = (*env)->NewShortArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JINT_ARRAY_TYPE)
&& (paType == NPY_INT32)) {
arr = (*env)->NewIntArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JLONG_ARRAY_TYPE)
&& (paType == NPY_INT64)) {
arr = (*env)->NewLongArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JFLOAT_ARRAY_TYPE)
&& (paType == NPY_FLOAT32)) {
arr = (*env)->NewFloatArray(env, sz);
} else if ((*env)->IsSameObject(env, desiredType, JDOUBLE_ARRAY_TYPE)
&& (paType == NPY_FLOAT64)) {
arr = (*env)->NewDoubleArray(env, sz);
} else {
Py_XDECREF(copy);
PyErr_Format(PyExc_RuntimeError,
"Error matching ndarray.dtype to Java primitive type");
return NULL;
}
/*
* java exception could potentially be OutOfMemoryError if it
* couldn't allocate the array
*/
if (process_java_exception(env) || !arr) {
Py_XDECREF(copy);
return NULL;
}
// if arr was allocated, we already know it matched the python array type
if (paType == NPY_BOOL) {
(*env)->SetBooleanArrayRegion(env, arr, 0, sz,
(const jboolean *) PyArray_DATA(copy));
} else if (paType == NPY_BYTE) {
(*env)->SetByteArrayRegion(env, arr, 0, sz, (const jbyte *) PyArray_DATA(copy));
} else if (paType == NPY_INT16) {
(*env)->SetShortArrayRegion(env, arr, 0, sz,
(const jshort *) PyArray_DATA(copy));
} else if (paType == NPY_INT32) {
(*env)->SetIntArrayRegion(env, arr, 0, sz, (const jint *) PyArray_DATA(copy));
} else if (paType == NPY_INT64) {
(*env)->SetLongArrayRegion(env, arr, 0, sz, (const jlong *) PyArray_DATA(copy));
} else if (paType == NPY_FLOAT32) {
(*env)->SetFloatArrayRegion(env, arr, 0, sz,
(const jfloat *) PyArray_DATA(copy));
} else if (paType == NPY_FLOAT64) {
(*env)->SetDoubleArrayRegion(env, arr, 0, sz,
(const jdouble *) PyArray_DATA(copy));
}
Py_XDECREF(copy);
if (process_java_exception(env)) {
PyErr_Format(PyExc_RuntimeError, "Error setting Java primitive array region");
return NULL;
}
return arr;
}
static PyObject* ccdToQ(PyObject *self, PyObject *args, PyObject *kwargs){
static char *kwlist[] = { "angles", "mode", "ccd_size", "ccd_pixsize",
"ccd_cen", "dist", "wavelength",
"UBinv", "outarray", NULL };
PyObject *angles = NULL;
PyObject *_angles = NULL;
PyObject *_ubinv = NULL;
PyObject *ubinv = NULL;
PyObject *_outarray = NULL;
PyObject *qOut = NULL;
CCD ccd;
npy_intp dims[2];
npy_intp nimages;
int i, j, t, stride;
int ndelgam;
int mode;
_float lambda;
_float *anglesp;
_float *qOutp;
_float *ubinvp;
_float UBI[3][3];
#ifdef USE_THREADS
pthread_t thread[NTHREADS];
int iret[NTHREADS];
#endif
imageThreadData threadData[NTHREADS];
if(!PyArg_ParseTupleAndKeywords(args, kwargs, "Oi(ii)(dd)(dd)ddO|O", kwlist,
&_angles,
&mode,
&ccd.xSize, &ccd.ySize,
&ccd.xPixSize, &ccd.yPixSize,
&ccd.xCen, &ccd.yCen,
&ccd.dist,
&lambda,
&_ubinv,
&_outarray)){
return NULL;
}
angles = PyArray_FROMANY(_angles, NPY_DOUBLE, 2, 2, NPY_IN_ARRAY);
if(!angles){
PyErr_SetString(PyExc_ValueError, "angles must be a 2-D array of floats");
goto cleanup;
}
ubinv = PyArray_FROMANY(_ubinv, NPY_DOUBLE, 2, 2, NPY_IN_ARRAY);
if(!ubinv){
PyErr_SetString(PyExc_ValueError, "ubinv must be a 2-D array of floats");
goto cleanup;
}
ubinvp = (_float *)PyArray_DATA(ubinv);
for(i=0;i<3;i++){
UBI[i][0] = -1.0 * ubinvp[2];
UBI[i][1] = ubinvp[1];
UBI[i][2] = ubinvp[0];
ubinvp+=3;
}
nimages = PyArray_DIM(angles, 0);
ndelgam = ccd.xSize * ccd.ySize;
dims[0] = nimages * ndelgam;
dims[1] = 4;
if(!_outarray){
// Create new numpy array
// fprintf(stderr, "**** Creating new array\n");
qOut = PyArray_SimpleNew(2, dims, NPY_DOUBLE);
if(!qOut){
goto cleanup;
}
} else {
qOut = PyArray_FROMANY(_outarray, NPY_DOUBLE, 2, 2, NPY_INOUT_ARRAY);
if(!qOut){
PyErr_SetString(PyExc_ValueError, "outarray must be a 2-D array of floats");
goto cleanup;
}
if(PyArray_Size(qOut) != (4 * nimages * ndelgam)){
PyErr_SetString(PyExc_ValueError, "outarray is of the wrong size");
goto cleanup;
}
}
anglesp = (_float *)PyArray_DATA(angles);
qOutp = (_float *)PyArray_DATA(qOut);
stride = nimages / NTHREADS;
for(t=0;t<NTHREADS;t++){
// Setup threads
// Allocate memory for delta/gamma pairs
threadData[t].ccd = &ccd;
threadData[t].anglesp = anglesp;
threadData[t].qOutp = qOutp;
threadData[t].ndelgam = ndelgam;
threadData[t].lambda = lambda;
threadData[t].mode = mode;
threadData[t].imstart = stride * t;
for(i=0;i<3;i++){
for(j=0;j<3;j++){
threadData[t].UBI[j][i] = UBI[j][i];
}
}
if(t == (NTHREADS - 1)){
threadData[t].imend = nimages;
} else {
threadData[t].imend = stride * (t + 1);
}
#ifdef USE_THREADS
iret[t] = pthread_create( &thread[t], NULL,
processImageThread,
(void*) &threadData[t]);
#else
processImageThread((void *) &threadData[t]);
#endif
anglesp += (6 * stride);
qOutp += (ndelgam * 4 * stride);
}
#ifdef USE_THREADS
for(t=0;t<NTHREADS;t++){
if(pthread_join(thread[t], NULL)){
fprintf(stderr, "ERROR : Cannot join thread %d", t);
}
}
#endif
Py_XDECREF(ubinv);
Py_XDECREF(angles);
return Py_BuildValue("N", qOut);
cleanup:
Py_XDECREF(ubinv);
Py_XDECREF(angles);
Py_XDECREF(qOut);
return NULL;
}
DimensionDictionary::DimensionDictionary(PyObject * dim_dict)
{
// Check that dim_dict is a dictionary
if (!PyDict_Check(dim_dict))
{
PyErr_SetString(PyExc_TypeError,
"'dim_dict' element is not a dictionary");
throw PythonException();
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << "dim_dict = " << PyString_AsString(PyObject_Str(dim_dict))
<< std::endl;
#endif
////////////////////////////////
// Get the 'dist_type' attribute
////////////////////////////////
PyObject * distTypeObj = PyDict_GetItemString(dim_dict, "dist_type");
if (distTypeObj == NULL)
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' has no 'dist_type' key");
throw PythonException();
}
if (!PyString_Check(distTypeObj))
{
PyErr_SetString(PyExc_TypeError,
"'dist_type' is not a string");
throw PythonException();
}
char * distTypeStr = PyString_AsString(distTypeObj);
if (strcmp(distTypeStr, "b") == 0)
dist_type = BLOCK;
else if (strcmp(distTypeStr, "c") == 0)
dist_type = CYCLIC;
else if (strcmp(distTypeStr, "u") == 0)
dist_type = UNSTRUCTURED;
else
{
PyErr_Format(PyExc_ValueError,
"'dist_type' value '%s' is unrecognized",
distTypeStr);
throw PythonException();
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " dist_type = '" << distTypeStr << "'" << std::endl;
#endif
///////////////////////////
// Get the 'size' attribute
///////////////////////////
PyObject * sizeObj = PyDict_GetItemString(dim_dict, "size");
if (sizeObj == NULL)
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' required key 'size' not present");
throw PythonException();
}
if (!PyInt_Check(sizeObj))
{
PyErr_Format(PyExc_TypeError, "'size' is not an int");
throw PythonException();
}
size = PyInt_AsLong(sizeObj);
if (size < 0)
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'size' = %d is less "
"than zero", size);
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " size = " << size << std::endl;
#endif
/////////////////////////////////////
// Get the 'proc_grid_size' attribute
/////////////////////////////////////
PyObject * commDimObj = PyDict_GetItemString(dim_dict, "proc_grid_size");
if (commDimObj == NULL)
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' required key 'proc_grid_size' not present");
throw PythonException();
}
if (!PyInt_Check(commDimObj))
{
PyErr_Format(PyExc_TypeError,
"'proc_grid_size' is not an int");
throw PythonException();
}
proc_grid_size = PyInt_AsLong(commDimObj);
if (proc_grid_size < 1)
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'proc_grid_size' = "
"%d is less than one", proc_grid_size);
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " proc_grid_size = " << proc_grid_size << std::endl;
#endif
/////////////////////////////////////
// Get the 'proc_grid_rank' attribute
/////////////////////////////////////
PyObject * commRankObj = PyDict_GetItemString(dim_dict, "proc_grid_rank");
if (commRankObj == NULL)
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' required key 'proc_grid_rank' not present");
throw PythonException();
}
if (!PyInt_Check(commRankObj))
{
PyErr_Format(PyExc_TypeError,
"'proc_grid_rank' is not an int");
throw PythonException();
}
proc_grid_rank = PyInt_AsLong(commRankObj);
if ((proc_grid_rank < 0) || (proc_grid_rank >= proc_grid_size))
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'proc_grid_rank' = "
"%d is out of range [0, %d)", proc_grid_rank, proc_grid_size);
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " proc_grid_rank = " << proc_grid_rank << std::endl;
#endif
////////////////////////////
// Get the 'start' attribute
////////////////////////////
PyObject * startObj = PyDict_GetItemString(dim_dict, "start");
if (startObj == NULL)
{
if ((dist_type == BLOCK) || (dist_type == CYCLIC))
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' is of type BLOCK or CYCLIC but has no "
"'start' key");
throw PythonException();
}
else
{
start = -1;
}
}
else
{
if (!PyInt_Check(startObj))
{
PyErr_SetString(PyExc_TypeError,
"'start' is not an int");
throw PythonException();
}
start = PyInt_AsLong(startObj);
if ((start < 0) || (start > size))
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'start' = "
"%d is out of range [0, %d]", start, size);
}
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " start = " << start << std::endl;
#endif
///////////////////////////
// Get the 'stop' attribute
///////////////////////////
PyObject * stopObj = PyDict_GetItemString(dim_dict, "stop");
if (stopObj == NULL)
{
if (dist_type == BLOCK)
{
PyErr_SetString(PyExc_KeyError,
"'dim_dict' is of type BLOCK but has no 'stop' key");
throw PythonException();
}
else
{
stop = -1;
}
}
else
{
if (!PyInt_Check(stopObj))
{
PyErr_SetString(PyExc_TypeError,
"'stop' for axis %d is not an int");
throw PythonException();
}
stop = PyInt_AsLong(stopObj);
if ((stop < 0) || (stop > size))
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'stop' = "
"%d is out of range [0, %d]", stop, size);
}
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " stop = " << stop << std::endl;
#endif
/////////////////////////////////
// Get the 'block_size' attribute
/////////////////////////////////
PyObject * blockSizeObj = PyDict_GetItemString(dim_dict, "block_size");
if (blockSizeObj == NULL)
{
block_size = 1;
}
else
{
if (!PyInt_Check(blockSizeObj))
{
PyErr_SetString(PyExc_TypeError,
"'block_size' is not an int");
throw PythonException();
}
block_size = PyInt_AsLong(stopObj);
if (block_size < 1)
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'block_size' = "
"%d is less than one", block_size);
}
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " block_size = " << block_size << std::endl;
#endif
//////////////////////////////
// Get the 'padding' attribute
//////////////////////////////
PyObject * paddingObj = PyDict_GetItemString(dim_dict, "padding");
if (paddingObj == NULL)
{
padding[0] = 0;
padding[1] = 0;
}
else
{
if (!PySequence_Check(paddingObj))
{
PyErr_SetString(PyExc_ValueError, "'padding' attribute must be a "
"sequence of two integers");
throw PythonException();
}
if (PySequence_Size(paddingObj) != 2)
{
PyErr_SetString(PyExc_ValueError, "'padding' attribute must be a "
"sequence of two integers");
throw PythonException();
}
PyObject * padObj = PySequence_GetItem(padObj, 0);
if (!PyInt_Check(padObj))
{
PyErr_SetString(PyExc_TypeError, "Lower 'padding' object is not an "
"integer");
throw PythonException();
}
padding[0] = PyInt_AsLong(padObj);
if (padding[0] < 0)
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'padding'[0] = "
"%d is less than zero", padding[0]);
}
padObj = PySequence_GetItem(padObj, 1);
if (!PyInt_Check(padObj))
{
PyErr_SetString(PyExc_TypeError, "Upper 'padding' object is not an "
"integer");
throw PythonException();
}
padding[1] = PyInt_AsLong(padObj);
if (padding[1] < 0)
{
PyErr_Format(PyExc_ValueError, "'dim_dict' attribute 'padding'[1] = "
"%d is less than zero", padding[1]);
}
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " padding = " << padding << std::endl;
#endif
///////////////////////////////
// Get the 'periodic' attribute
///////////////////////////////
PyObject * periodicObj = PyDict_GetItemString(dim_dict, "periodic");
if (periodicObj == NULL)
{
periodic = false;
}
else
{
if (!PyBool_Check(periodicObj))
{
PyErr_SetString(PyExc_TypeError,
"'periodic' is not a bool");
throw PythonException();
}
if (periodicObj == Py_True) periodic = true;
else periodic = false;
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " periodic = " << (periodic ? "true" : "false") << std::endl;
#endif
/////////////////////////////////
// Get the 'one_to_one' attribute
/////////////////////////////////
PyObject * oneToOneObj = PyDict_GetItemString(dim_dict, "one_to_one");
if (oneToOneObj == NULL)
{
one_to_one = false;
}
else
{
if (!PyBool_Check(oneToOneObj))
{
PyErr_SetString(PyExc_TypeError,
"'one_to_one' is not a bool");
throw PythonException();
}
if (oneToOneObj == Py_True) one_to_one = true;
else one_to_one = false;
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " one_to_one = " << (one_to_one ? "true" : "false")
<< std::endl;
#endif
//////////////////////////////
// Get the 'indices' attribute
//////////////////////////////
PyObject * indicesObj = PyDict_GetItemString(dim_dict, "indices");
if (indicesObj == NULL)
{
if (dist_type == UNSTRUCTURED)
{
PyErr_SetString(PyExc_KeyError, "'dim_dict' with type UNSTRUCTURED "
"requires 'indices' key");
throw PythonException();
}
}
else
{
PyObject * indicesArray =
PyArray_ContiguousFromAny(indicesObj, NPY_INT, 1, 1);
if (indicesArray == NULL)
{
PyErr_SetString(PyExc_ValueError, "'dim_dict' attribute 'indices' "
"specified illegally");
throw PythonException();
}
npy_intp numIndices = PyArray_Size(indicesArray);
indices.resize(numIndices);
int * source = (int*) PyArray_DATA((PyArrayObject*)indicesArray);
for (IndicesType::size_type i = 0; i < numIndices; ++i)
indices[i] = *(source++);
Py_DECREF(indicesArray);
}
#ifdef PYTRILINOS_DAP_VERBOSE
std::cout << " indices = " << indices() << std::endl;
#endif
}
static PyObject * GcTrace_wrap(PyObject *self, PyObject *args)
{
long ntotal;
PyObject *oxp, *oyp, *onp;
PyArrayObject *xcpdata, *ycpdata, *npdata;
int npsize, n, p, start = 0, end = 0;
PyObject *point, *contourList, *all_contours;
if (!PyArg_ParseTuple(args,"OOO", &onp, &oxp, &oyp))
return NULL;
npdata = (PyArrayObject *) PyArray_ContiguousFromObject(onp, 'l', 1, 1);
xcpdata = (PyArrayObject *) PyArray_ContiguousFromObject(oxp, 'd', 1, 1);
ycpdata = (PyArrayObject *) PyArray_ContiguousFromObject(oyp, 'd', 1, 1 );
if (npdata->nd != 1)
{
PyErr_SetString(PyExc_ValueError, "Argument np must be a 1D array");
return NULL;
}
if (xcpdata->nd != 1)
{
PyErr_SetString(PyExc_ValueError, "Argument xp must be a 1D array");
return NULL;
}
if (ycpdata->nd != 1)
{
PyErr_SetString(PyExc_ValueError, "Argument yp must be a 1D array");
return NULL;
}
ntotal = GcTrace( (long *) npdata->data, (double *) xcpdata->data, (double *) ycpdata->data);
npsize = PyArray_Size((PyObject *) npdata);
all_contours = PyList_New(0);
for (n = 0; n<npsize; n++)
{
start = end;
end = start + ((long *) npdata->data)[n];
contourList = PyList_New(0);
for (p = start; p<end; p++)
{
point = Py_BuildValue("(d,d)", ((double *) xcpdata->data)[p],((double *) ycpdata->data)[p]);
if (PyList_Append(contourList, point))
{
printf ("Error in appending to list\n");
return NULL;
}
}
if (PyList_Append(all_contours, contourList))
{
printf ("error in appending to all_contours\n");
return NULL;
}
}
return Py_BuildValue("O", all_contours);
}
// Read one table for one sweep value. Returns:
// 0 ... performed normally
// 1 ... error occurred
// Arguments:
// f ... pointer to file for reading
// debugMode ... debug messages flag
// fileName ... name of the file
// sweep ... sweep parameter name
// numOfVariables ... number of variables in table
// type ... type of variables with exeption of scale
// numOfVectors ... number of variables and probes in table
// faSweep ... pointer to fast access structure for sweep array
// tmpArray ... array of pointers to arrays
// faPtr ... array of fast access structures for vector arrays
// scale ... scale name
// name ... array of vector names
// dataList ... list of data dictionaries
int readTable(FILE *f, int debugMode, int postVersion,
const char *fileName, PyObject *sweep,
int numOfVariables, int type, int numOfVectors,
struct FastArray *faSweep, PyObject **tmpArray,
struct FastArray *faPtr, char *scale, char **name, PyObject *dataList)
{
int i, j, num, offset = 0, numOfColumns = numOfVectors;
npy_intp dims;
float *rawDataPos, *rawData = NULL;
PyObject *data = NULL;
// Read raw data blocks.
do num = readDataBlock(f, debugMode, postVersion, fileName, &rawData, &offset);
while(num == 0);
if(num > 0) goto readTableFailed;
data = PyDict_New(); // Create an empty dictionary.
if(data == NULL)
{
if(debugMode)
fprintf(debugFile, "HSpiceRead: failed to create data dictionary.\n");
goto readTableFailed;
}
// Increase number of columns if variables with exeption of scale are complex.
if(type == complex_var) numOfColumns = numOfColumns + numOfVariables - 1;
rawDataPos = rawData;
// TODO check sweeps with postVersion == 2001
if(postVersion == 2001)
{
if(sweep == NULL) num = (offset - 1) / numOfColumns
/ 2; // Number of rows.
else
{
num = (offset - 2) / numOfColumns / 2;
*((npy_double *)(faSweep->pos)) = *((double*)rawDataPos);
// Save sweep value.
rawDataPos = rawDataPos + 2;
faSweep->pos = faSweep->pos + faSweep->stride;
}
}
else
{
if(sweep == NULL) num = (offset - 1) / numOfColumns; // Number of rows.
else
{
num = (offset - 2) / numOfColumns;
*((npy_double *)(faSweep->pos)) = *rawDataPos; // Save sweep value.
rawDataPos = rawDataPos + 1;
faSweep->pos = faSweep->pos + faSweep->stride;
}
}
if(debugMode) fprintf(debugFile, "num=%d\n", num);
for(i = 0; i < numOfVectors; i++)
{
// Create array for i-th vector.
dims=num;
if(type == complex_var && i > 0 && i < numOfVariables)
tmpArray[i] = PyArray_SimpleNew(1, &dims, PyArray_CDOUBLE);
else
tmpArray[i] = PyArray_SimpleNew(1, &dims, PyArray_DOUBLE);
if(tmpArray[i] == NULL)
{
if(debugMode)
fprintf(debugFile, "HSpiceRead: failed to create array.\n");
for(j = 0; j < i + 1; j++) Py_XDECREF(tmpArray[j]);
goto readTableFailed;
}
}
for(i = 0; i < numOfVectors; i++) // Prepare fast access structures.
{
faPtr[i].data = ((PyArrayObject *)(tmpArray[i]))->data;
faPtr[i].pos = ((PyArrayObject *)(tmpArray[i]))->data;
faPtr[i].stride =
((PyArrayObject *)(tmpArray[i]))->strides[((PyArrayObject *)(tmpArray[i]))->nd -
1];
faPtr[i].length = PyArray_Size(tmpArray[i]);
}
if(postVersion == 2001)
{
for(i = 0; i < num; i++) // Save raw data.
{
struct FastArray *faPos = faPtr;
for(j = 0; j < numOfVectors; j++)
{
if(type == complex_var && j > 0 && j < numOfVariables)
{
((npy_cdouble *)(faPos->pos))->real = *((double *)rawDataPos);
rawDataPos = rawDataPos + 2;
((npy_cdouble *)(faPos->pos))->imag = *((double *)rawDataPos);
} else *((npy_double *)(faPos->pos)) = *((double *)rawDataPos);
rawDataPos = rawDataPos + 2;
faPos->pos = faPos->pos + faPos->stride;
faPos = faPos + 1;
}
}
}
else
{
for(i = 0; i < num; i++) // Save raw data.
{
struct FastArray *faPos = faPtr;
for(j = 0; j < numOfVectors; j++)
{
if(type == complex_var && j > 0 && j < numOfVariables)
{
((npy_cdouble *)(faPos->pos))->real = *rawDataPos;
rawDataPos = rawDataPos + 1;
((npy_cdouble *)(faPos->pos))->imag = *rawDataPos;
} else *((npy_double *)(faPos->pos)) = *rawDataPos;
rawDataPos = rawDataPos + 1;
faPos->pos = faPos->pos + faPos->stride;
faPos = faPos + 1;
}
}
}
PyMem_Free(rawData);
rawData = NULL;
// Insert vectors into dictionary.
num = PyDict_SetItemString(data, scale, tmpArray[0]);
i = -1;
if(num == 0) for(i = 0; i < numOfVectors - 1; i++)
{
num = PyDict_SetItemString(data, name[i], tmpArray[i + 1]);
if(num != 0) break;
}
for(j = 0; j < numOfVectors; j++) Py_XDECREF(tmpArray[j]);
if(num)
{
if(debugMode) {
if(i == -1) fprintf(debugFile,
"HSpiceRead: failed to insert vector %s into dictionary.\n",
scale);
else fprintf(debugFile,
"HSpiceRead: failed to insert vector %s into dictionary.\n",
name[i]);
}
goto readTableFailed;
}
// Insert table into the list of data dictionaries.
num = PyList_Append(dataList, data);
if(num)
{
if(debugMode) fprintf(debugFile,
"HSpiceRead: failed to append table to the list of data dictionaries.\n");
goto readTableFailed;
}
Py_XDECREF(data);
data = NULL;
return 0;
readTableFailed:
PyMem_Free(rawData);
Py_XDECREF(data);
return 1;
}
static PyObject *
odepack_odeint(PyObject *dummy, PyObject *args, PyObject *kwdict)
{
PyObject *fcn, *y0, *p_tout, *o_rtol = NULL, *o_atol = NULL;
PyArrayObject *ap_y = NULL, *ap_yout = NULL;
PyArrayObject *ap_rtol = NULL, *ap_atol = NULL;
PyArrayObject *ap_tout = NULL;
PyObject *extra_args = NULL;
PyObject *Dfun = Py_None;
int neq, itol = 1, itask = 1, istate = 1, iopt = 0, lrw, *iwork, liw, jt = 4;
double *y, t, *tout, *rtol, *atol, *rwork;
double h0 = 0.0, hmax = 0.0, hmin = 0.0;
int ixpr = 0, mxstep = 0, mxhnil = 0, mxordn = 12, mxords = 5, ml = -1, mu = -1;
PyObject *o_tcrit = NULL;
PyArrayObject *ap_tcrit = NULL;
PyArrayObject *ap_hu = NULL, *ap_tcur = NULL, *ap_tolsf = NULL, *ap_tsw = NULL;
PyArrayObject *ap_nst = NULL, *ap_nfe = NULL, *ap_nje = NULL, *ap_nqu = NULL;
PyArrayObject *ap_mused = NULL;
int imxer = 0, lenrw = 0, leniw = 0, col_deriv = 0;
npy_intp out_sz = 0, dims[2];
int k, ntimes, crit_ind = 0;
int allocated = 0, full_output = 0, numcrit = 0;
double *yout, *yout_ptr, *tout_ptr, *tcrit;
double *wa;
static char *kwlist[] = {"fun", "y0", "t", "args", "Dfun", "col_deriv",
"ml", "mu", "full_output", "rtol", "atol", "tcrit",
"h0", "hmax", "hmin", "ixpr", "mxstep", "mxhnil",
"mxordn", "mxords", NULL};
odepack_params save_params;
if (!PyArg_ParseTupleAndKeywords(args, kwdict, "OOO|OOiiiiOOOdddiiiii", kwlist,
&fcn, &y0, &p_tout, &extra_args, &Dfun,
&col_deriv, &ml, &mu, &full_output, &o_rtol, &o_atol,
&o_tcrit, &h0, &hmax, &hmin, &ixpr, &mxstep, &mxhnil,
&mxordn, &mxords)) {
return NULL;
}
if (o_tcrit == Py_None) {
o_tcrit = NULL;
}
if (o_rtol == Py_None) {
o_rtol = NULL;
}
if (o_atol == Py_None) {
o_atol = NULL;
}
/* Set up jt, ml, and mu */
if (Dfun == Py_None) {
/* set jt for internally generated */
jt++;
}
if (ml < 0 && mu < 0) {
/* neither ml nor mu given, mark jt for full jacobian */
jt -= 3;
}
if (ml < 0) {
/* if one but not both are given */
ml = 0;
}
if (mu < 0) {
mu = 0;
}
/* Stash the current global_params in save_params. */
memcpy(&save_params, &global_params, sizeof(save_params));
if (extra_args == NULL) {
if ((extra_args = PyTuple_New(0)) == NULL) {
goto fail;
}
}
else {
Py_INCREF(extra_args); /* We decrement on exit. */
}
if (!PyTuple_Check(extra_args)) {
PYERR(odepack_error, "Extra arguments must be in a tuple");
}
if (!PyCallable_Check(fcn) || (Dfun != Py_None && !PyCallable_Check(Dfun))) {
PYERR(odepack_error, "The function and its Jacobian must be callable functions.");
}
/* Set global_params from the function arguments. */
global_params.python_function = fcn;
global_params.extra_arguments = extra_args;
global_params.python_jacobian = Dfun;
global_params.jac_transpose = !(col_deriv);
global_params.jac_type = jt;
/* Initial input vector */
ap_y = (PyArrayObject *) PyArray_ContiguousFromObject(y0, NPY_DOUBLE, 0, 0);
if (ap_y == NULL) {
goto fail;
}
if (PyArray_NDIM(ap_y) > 1) {
PyErr_SetString(PyExc_ValueError, "Initial condition y0 must be one-dimensional.");
goto fail;
}
y = (double *) PyArray_DATA(ap_y);
neq = PyArray_Size((PyObject *) ap_y);
dims[1] = neq;
/* Set of output times for integration */
ap_tout = (PyArrayObject *) PyArray_ContiguousFromObject(p_tout, NPY_DOUBLE, 0, 0);
if (ap_tout == NULL) {
goto fail;
}
if (PyArray_NDIM(ap_tout) > 1) {
PyErr_SetString(PyExc_ValueError, "Output times t must be one-dimensional.");
goto fail;
}
tout = (double *) PyArray_DATA(ap_tout);
ntimes = PyArray_Size((PyObject *)ap_tout);
dims[0] = ntimes;
t = tout[0];
/* Setup array to hold the output evaluations*/
ap_yout= (PyArrayObject *) PyArray_SimpleNew(2,dims,NPY_DOUBLE);
if (ap_yout== NULL) {
goto fail;
}
yout = (double *) PyArray_DATA(ap_yout);
/* Copy initial vector into first row of output */
memcpy(yout, y, neq*sizeof(double)); /* copy initial value to output */
yout_ptr = yout + neq; /* set output pointer to next position */
itol = setup_extra_inputs(&ap_rtol, o_rtol, &ap_atol, o_atol, &ap_tcrit,
o_tcrit, &numcrit, neq);
if (itol < 0 ) {
goto fail; /* Something didn't work */
}
rtol = (double *) PyArray_DATA(ap_rtol);
atol = (double *) PyArray_DATA(ap_atol);
if (o_tcrit != NULL) {
tcrit = (double *)(PyArray_DATA(ap_tcrit));
}
/* Find size of working arrays*/
if (compute_lrw_liw(&lrw, &liw, neq, jt, ml, mu, mxordn, mxords) < 0) {
goto fail;
}
if ((wa = (double *)malloc(lrw*sizeof(double) + liw*sizeof(int)))==NULL) {
PyErr_NoMemory();
goto fail;
}
allocated = 1;
rwork = wa;
iwork = (int *)(wa + lrw);
iwork[0] = ml;
iwork[1] = mu;
if (h0 != 0.0 || hmax != 0.0 || hmin != 0.0 || ixpr != 0 || mxstep != 0 ||
mxhnil != 0 || mxordn != 0 || mxords != 0) {
rwork[4] = h0;
rwork[5] = hmax;
rwork[6] = hmin;
iwork[4] = ixpr;
iwork[5] = mxstep;
iwork[6] = mxhnil;
iwork[7] = mxordn;
iwork[8] = mxords;
iopt = 1;
}
istate = 1;
k = 1;
/* If full output make some useful output arrays */
if (full_output) {
out_sz = ntimes-1;
ap_hu = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_DOUBLE);
ap_tcur = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_DOUBLE);
ap_tolsf = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_DOUBLE);
ap_tsw = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_DOUBLE);
ap_nst = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_INT);
ap_nfe = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_INT);
ap_nje = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_INT);
ap_nqu = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_INT);
ap_mused = (PyArrayObject *) PyArray_SimpleNew(1, &out_sz, NPY_INT);
if (ap_hu == NULL || ap_tcur == NULL || ap_tolsf == NULL ||
ap_tsw == NULL || ap_nst == NULL || ap_nfe == NULL ||
ap_nje == NULL || ap_nqu == NULL || ap_mused == NULL) {
goto fail;
}
}
if (o_tcrit != NULL) {
/* There are critical points */
itask = 4;
rwork[0] = *tcrit;
}
while (k < ntimes && istate > 0) { /* loop over desired times */
tout_ptr = tout + k;
/* Use tcrit if relevant */
if (itask == 4 && *tout_ptr > *(tcrit + crit_ind)) {
crit_ind++;
rwork[0] = *(tcrit+crit_ind);
}
if (crit_ind >= numcrit) {
itask = 1; /* No more critical values */
}
LSODA(ode_function, &neq, y, &t, tout_ptr, &itol, rtol, atol, &itask,
&istate, &iopt, rwork, &lrw, iwork, &liw,
ode_jacobian_function, &jt);
if (full_output) {
*((double *)PyArray_DATA(ap_hu) + (k-1)) = rwork[10];
*((double *)PyArray_DATA(ap_tcur) + (k-1)) = rwork[12];
*((double *)PyArray_DATA(ap_tolsf) + (k-1)) = rwork[13];
*((double *)PyArray_DATA(ap_tsw) + (k-1)) = rwork[14];
*((int *)PyArray_DATA(ap_nst) + (k-1)) = iwork[10];
*((int *)PyArray_DATA(ap_nfe) + (k-1)) = iwork[11];
*((int *)PyArray_DATA(ap_nje) + (k-1)) = iwork[12];
*((int *)PyArray_DATA(ap_nqu) + (k-1)) = iwork[13];
if (istate == -5 || istate == -4) {
imxer = iwork[15];
}
else {
imxer = -1;
}
lenrw = iwork[16];
leniw = iwork[17];
*((int *)PyArray_DATA(ap_mused) + (k-1)) = iwork[18];
}
if (PyErr_Occurred()) {
goto fail;
}
memcpy(yout_ptr, y, neq*sizeof(double)); /* copy integration result to output*/
yout_ptr += neq;
k++;
}
/* Restore global_params from the previously stashed save_params. */
memcpy(&global_params, &save_params, sizeof(save_params));
Py_DECREF(extra_args);
Py_DECREF(ap_atol);
Py_DECREF(ap_rtol);
Py_XDECREF(ap_tcrit);
Py_DECREF(ap_y);
Py_DECREF(ap_tout);
free(wa);
/* Do Full output */
if (full_output) {
return Py_BuildValue("N{s:N,s:N,s:N,s:N,s:N,s:N,s:N,s:N,s:i,s:i,s:i,s:N}i",
PyArray_Return(ap_yout),
"hu", PyArray_Return(ap_hu),
"tcur", PyArray_Return(ap_tcur),
"tolsf", PyArray_Return(ap_tolsf),
"tsw", PyArray_Return(ap_tsw),
"nst", PyArray_Return(ap_nst),
"nfe", PyArray_Return(ap_nfe),
"nje", PyArray_Return(ap_nje),
"nqu", PyArray_Return(ap_nqu),
"imxer", imxer,
"lenrw", lenrw,
"leniw", leniw,
"mused", PyArray_Return(ap_mused),
istate);
}
else {
return Py_BuildValue("Ni", PyArray_Return(ap_yout), istate);
}
fail:
/* Restore global_params from the previously stashed save_params. */
memcpy(&global_params, &save_params, sizeof(save_params));
Py_XDECREF(extra_args);
Py_XDECREF(ap_y);
Py_XDECREF(ap_rtol);
Py_XDECREF(ap_atol);
Py_XDECREF(ap_tcrit);
Py_XDECREF(ap_tout);
Py_XDECREF(ap_yout);
if (allocated) {
free(wa);
}
if (full_output) {
Py_XDECREF(ap_hu);
Py_XDECREF(ap_tcur);
Py_XDECREF(ap_tolsf);
Py_XDECREF(ap_tsw);
Py_XDECREF(ap_nst);
Py_XDECREF(ap_nfe);
Py_XDECREF(ap_nje);
Py_XDECREF(ap_nqu);
Py_XDECREF(ap_mused);
}
return NULL;
}
static PyObject *
_pylm_dlevmar_generic(PyObject *mod, PyObject *args, PyObject *kwds,
char *argstring, char *kwlist[],
int jacobian, int bounds) {
PyObject *func = NULL;
PyObject *jacf = NULL;
PyObject *initial = NULL, *initial_npy = NULL;
PyObject *measurements = NULL, *measurements_npy = NULL;
PyObject *lower = NULL, *lower_npy = NULL;
PyObject *upper = NULL, *upper_npy = NULL;
PyObject *opts = NULL, *opts_npy = NULL;
PyObject *covar = NULL;
PyObject *retval = NULL;
PyObject *info = NULL;
pylm_callback_data *pydata = NULL;
double *c_initial = NULL;
double *c_measurements = NULL;
double *c_opts = NULL;
double *c_lower = NULL;
double *c_upper = NULL;
double *c_covar = NULL;
int max_iter = 0;
int run_iter = 0;
int m = 0, n = 0;
double c_info[LM_INFO_SZ];
int nopts;
// If finite-difference approximate Jacobians are used, we
// need 5 optional params; otherwise 4.
if (jacobian){
nopts = 4;
} else {
nopts = 5;
}
// parse arguments
if (!bounds) {
if (jacobian) {
if (!PyArg_ParseTupleAndKeywords(args, kwds, argstring, kwlist,
&func, &jacf, &initial,
&measurements, &max_iter,
&opts, &covar)){
return NULL;
}
} else {
if (!PyArg_ParseTupleAndKeywords(args, kwds, argstring, kwlist,
&func, &initial,
&measurements, &max_iter,
&opts, &covar)){
return NULL;
}
}
} else {
if (jacobian) {
if (!PyArg_ParseTupleAndKeywords(args, kwds, argstring, kwlist,
&func, &jacf, &initial,
&measurements, &lower, &upper, &max_iter,
&opts, &covar)){
return NULL;
}
} else {
if (!PyArg_ParseTupleAndKeywords(args, kwds, argstring, kwlist,
&func, &initial,
&measurements, &lower, &upper, &max_iter,
&opts, &covar)){
return NULL;
}
}
}
// Check each variable type
if (!PyCallable_Check(func)) {
PyErr_SetString(PyExc_TypeError, "func must be a callable object");
return NULL;
}
if (!PyArray_Check(initial)) {
PyErr_SetString(PyExc_TypeError, "initial must be a numpy array");
return NULL;
}
if (!PyArray_Check(measurements)) {
PyErr_SetString(PyExc_TypeError, "measurements must be a numpy array");
return NULL;
}
if (jacobian && !PyCallable_Check(jacf)) {
PyErr_SetString(PyExc_TypeError, "jacf must be a callable object");
return NULL;
}
if (lower && !PyArray_Check(lower)) {
PyErr_SetString(PyExc_TypeError, "lower bounds must be a numpy array");
return NULL;
}
if (upper && !PyArray_Check(upper)) {
PyErr_SetString(PyExc_TypeError, "upper bounds must be a numpy array");
return NULL;
}
if (opts && !PyArray_Check(opts) && (PyArray_Size(opts) != nopts)) {
if (nopts == 4){
PyErr_SetString(PyExc_TypeError,
"opts must be a numpy vector of length 4.");
} else {
PyErr_SetString(PyExc_TypeError,
"opts must be a numpy vector of length 5.");
}
return NULL;
}
// convert python types into C
pydata = PyMem_Malloc(sizeof(pydata));
if(!pydata){
PyErr_SetString(PyExc_RuntimeError,
"Error in allocating memory for data.");
return NULL;
}
pydata->func = func;
pydata->jacf = jacf;
initial_npy = PyArray_FROMANY(initial, NPY_DOUBLE, 0, 0, NPY_INOUT_ARRAY);
measurements_npy = PyArray_FROMANY(measurements, NPY_DOUBLE, 0, 0, NPY_IN_ARRAY);
if(!initial_npy || !measurements_npy){
// Cannot create array
PyErr_SetString(PyExc_RuntimeError,
"Error in creating arrays from input data.");
//Py_XDECREF(initial_npy);
//Py_XDECREF(measurements_npy);
return NULL;
}
c_initial = (double *)PyArray_DATA(initial_npy);
c_measurements = (double *)PyArray_DATA(measurements_npy);
m = PyArray_SIZE(initial_npy);
n = PyArray_SIZE(measurements_npy);
npy_intp dims[2] = {m, m};
covar = PyArray_SimpleNew(2, dims, NPY_DOUBLE);
c_covar = PyArray_DATA(covar);
if (lower){
lower_npy = PyArray_FROMANY(lower, PyArray_DOUBLE, 0, 0, NPY_IN_ARRAY);
c_lower = PyArray_DATA(lower_npy);
// TODO check dims
}
if (upper){
upper_npy = PyArray_FROMANY(upper, PyArray_DOUBLE, 0, 0, NPY_IN_ARRAY);
c_upper = PyArray_DATA(upper_npy);
// TODO check dims
}
if (opts) {
opts_npy = PyArray_FROMANY(opts, PyArray_DOUBLE, 0, 0, NPY_IN_ARRAY);
c_opts = PyArray_DATA(opts_npy);
// TODO check dims
}
// call function to do the fitting
if (!bounds) {
if (jacobian) {
run_iter = dlevmar_der(_pylm_func_callback, _pylm_jacf_callback,
c_initial, c_measurements, m, n,
max_iter, c_opts, c_info, NULL, c_covar, pydata);
} else {
run_iter = dlevmar_dif(_pylm_func_callback, c_initial, c_measurements,
m, n, max_iter, c_opts, c_info, NULL, c_covar, pydata);
}
} else {
if (jacobian) {
run_iter = dlevmar_bc_der(_pylm_func_callback, _pylm_jacf_callback,
c_initial, c_measurements, m, n,
c_lower, c_upper,
max_iter, c_opts, c_info, NULL, c_covar, pydata);
} else {
run_iter = dlevmar_bc_dif(_pylm_func_callback, c_initial, c_measurements,
m, n, c_lower, c_upper,
max_iter, c_opts, c_info, NULL, c_covar, pydata);
}
}
// convert results back into python
if (run_iter > 0) {
npy_intp dims[1] = {m};
retval = PyArray_SimpleNewFromData(1, dims, PyArray_DOUBLE, c_initial);
} else {
retval = Py_None;
Py_INCREF(Py_None);
}
if (pydata) {
PyMem_Free(pydata);
}
// convert additional information into python
info = Py_BuildValue("{s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d,s:d}",
"initial_e2", c_info[0],
"estimate_e2", c_info[1],
"estimate_Jt", c_info[2],
"estimate_Dp2", c_info[3],
"estimate_mu", c_info[4],
"iterations", c_info[5],
"termination", c_info[6],
"function_evaluations", c_info[7],
"jacobian_evaluations", c_info[8]);
//Py_XDECREF(measurements_npy);
//Py_XDECREF(initial_npy);
//Py_XDECREF(lower_npy);
//Py_XDECREF(upper_npy);
//Py_XDECREF(opts_npy);
return Py_BuildValue("(OOiO)", retval, covar, run_iter, info, NULL);
}
void
ode_function(int *n, double *t, double *y, double *ydot)
{
/*
This is the function called from the Fortran code it should
-- use call_python_function to get a multiarrayobject result
-- check for errors and set *n to -1 if any
-- otherwise place result of calculation in ydot
*/
PyArrayObject *result_array = NULL;
PyObject *arg1, *arglist;
/* Append t to argument list */
if ((arg1 = PyTuple_New(1)) == NULL) {
*n = -1;
return;
}
PyTuple_SET_ITEM(arg1, 0, PyFloat_FromDouble(*t));
/* arg1 now owns newly created reference */
if ((arglist = PySequence_Concat(arg1, global_params.extra_arguments)) == NULL) {
*n = -1;
Py_DECREF(arg1);
return;
}
Py_DECREF(arg1); /* arglist has reference */
result_array = (PyArrayObject *)call_python_function(global_params.python_function,
*n, y, arglist, odepack_error);
if (result_array == NULL) {
*n = -1;
Py_DECREF(arglist);
return;
}
if (PyArray_NDIM(result_array) > 1) {
*n = -1;
PyErr_Format(PyExc_RuntimeError,
"The array return by func must be one-dimensional, but got ndim=%d.",
PyArray_NDIM(result_array));
Py_DECREF(arglist);
Py_DECREF(result_array);
return;
}
if (PyArray_Size((PyObject *)result_array) != *n) {
PyErr_Format(PyExc_RuntimeError,
"The size of the array returned by func (%ld) does not match "
"the size of y0 (%d).",
PyArray_Size((PyObject *)result_array), *n);
*n = -1;
Py_DECREF(arglist);
Py_DECREF(result_array);
return;
}
memcpy(ydot, PyArray_DATA(result_array), (*n)*sizeof(double));
Py_DECREF(result_array);
Py_DECREF(arglist);
return;
}
int
setup_extra_inputs(PyArrayObject **ap_rtol, PyObject *o_rtol,
PyArrayObject **ap_atol, PyObject *o_atol,
PyArrayObject **ap_tcrit, PyObject *o_tcrit,
int *numcrit, int neq)
{
int itol = 0;
double tol = 1.49012e-8;
npy_intp one = 1;
/* Setup tolerances */
if (o_rtol == NULL) {
*ap_rtol = (PyArrayObject *) PyArray_SimpleNew(1, &one, NPY_DOUBLE);
if (*ap_rtol == NULL) {
PYERR2(odepack_error,"Error constructing relative tolerance.");
}
*(double *) PyArray_DATA(*ap_rtol) = tol; /* Default */
}
else {
*ap_rtol = (PyArrayObject *) PyArray_ContiguousFromObject(o_rtol,
NPY_DOUBLE, 0, 1);
if (*ap_rtol == NULL) {
PYERR2(odepack_error,"Error converting relative tolerance.");
}
/* XXX Fix the following. */
if (PyArray_NDIM(*ap_rtol) == 0); /* rtol is scalar */
else if (PyArray_DIMS(*ap_rtol)[0] == neq) {
itol |= 2; /* Set rtol array flag */
}
else {
PYERR(odepack_error, "Tolerances must be an array of the same length as the\n number of equations or a scalar.");
}
}
if (o_atol == NULL) {
*ap_atol = (PyArrayObject *) PyArray_SimpleNew(1, &one, NPY_DOUBLE);
if (*ap_atol == NULL) {
PYERR2(odepack_error,"Error constructing absolute tolerance");
}
*(double *)PyArray_DATA(*ap_atol) = tol;
}
else {
*ap_atol = (PyArrayObject *) PyArray_ContiguousFromObject(o_atol, NPY_DOUBLE, 0, 1);
if (*ap_atol == NULL) {
PYERR2(odepack_error,"Error converting absolute tolerance.");
}
/* XXX Fix the following. */
if (PyArray_NDIM(*ap_atol) == 0); /* atol is scalar */
else if (PyArray_DIMS(*ap_atol)[0] == neq) {
itol |= 1; /* Set atol array flag */
}
else {
PYERR(odepack_error,"Tolerances must be an array of the same length as the\n number of equations or a scalar.");
}
}
itol++; /* increment to get correct value */
/* Setup t-critical */
if (o_tcrit != NULL) {
*ap_tcrit = (PyArrayObject *) PyArray_ContiguousFromObject(o_tcrit, NPY_DOUBLE, 0, 1);
if (*ap_tcrit == NULL) {
PYERR2(odepack_error,"Error constructing critical times.");
}
*numcrit = PyArray_Size((PyObject *) (*ap_tcrit));
}
return itol;
fail: /* Needed for use of PYERR */
return -1;
}
PyObject *wrap_vis_sim(PyObject *self, PyObject *args){
PyArrayObject *baseline, *src_dir, *src_int, *src_index, *freqs, *mfreqs, *beam_arr;
PyArrayObject *vis_array;
npy_intp N_fq, N_src, d0, d1, N_beam_fq, l, m;
npy_float lmin, lmax, mmin, mmax, beamfqmin, beamfqmax;
if(!PyArg_ParseTuple(args, "O!O!O!O!O!O!O!ffffff", &PyArray_Type, &baseline,
&PyArray_Type, &src_dir,
&PyArray_Type, &src_int,
&PyArray_Type, &src_index,
&PyArray_Type, &freqs,
&PyArray_Type, &mfreqs,
&PyArray_Type, &beam_arr,
&lmin, &lmax, &mmin, &mmax,
&beamfqmin, &beamfqmax)){
return NULL;
}
N_fq = PyArray_Size((PyObject *)freqs);
N_src = PyArray_Size((PyObject *)src_int);
//if the baseline is not 3 numbers, raise an error
if (PyArray_Size((PyObject *)baseline) != 3){
PyErr_Format(PyExc_ValueError, "Baseline vector length must be 3");
return NULL;
}
//Check that there is one src_index for each source
if (PyArray_Size((PyObject *)src_index) != N_src){
PyErr_Format(PyExc_ValueError, "src_index.size != src_int.size");
return NULL;
}
//Check that the length of mfreqs = the number of sources
if (PyArray_Size((PyObject *)mfreqs) != N_src){
PyErr_Format(PyExc_ValueError, "mfreqs.size != src_int.size");
return NULL;
}
//Check that src_dir is 2 dimensional, and one dimension is 3 long and the other is equal to N_src
if (PyArray_NDIM(src_dir) != 2){
PyErr_Format(PyExc_ValueError, "src_dir must be 2 dimensional");
return NULL;
}
else{
d0 = PyArray_DIM(src_dir, 0);
d1 = PyArray_DIM(src_dir, 1);
}
if (!((d0 == N_src) && (d1 == (npy_intp) 3))){
PyErr_Format(PyExc_ValueError, "src_dir must have 0th dimension = the length of src_int, and 1st dimension = 3");
return NULL;
}
//Check that beam_arr is 3 dimensional. If it is, set l, m, and N_beam_fq
if (PyArray_NDIM(beam_arr) != 3){
PyErr_Format(PyExc_ValueError, "beam_arr must be 3 dimensional");
return NULL;
}
else{
l = PyArray_DIM(beam_arr, 0);
m = PyArray_DIM(beam_arr, 1);
N_beam_fq = PyArray_DIM(beam_arr, 2);
}
//Check the type of the array inputs
if (! (PyArray_ISFLOAT((PyObject *) baseline) && (PyArray_ISFLOAT((PyObject *) src_dir)) && (PyArray_ISFLOAT((PyObject *) src_int)) && (PyArray_ISFLOAT((PyObject *) src_index)) && (PyArray_ISFLOAT((PyObject *) freqs)) && (PyArray_ISFLOAT((PyObject *) mfreqs)) && (PyArray_ISFLOAT((PyObject *) beam_arr)))){
PyErr_Format(PyExc_ValueError, "All arrays must be of floats");
return NULL;
}
//Create the array to hold the output
vis_array = (PyArrayObject *) PyArray_SimpleNew(PyArray_NDIM(freqs), PyArray_DIMS(freqs), NPY_CFLOAT);
vis_sim(
(float *)PyArray_DATA(baseline), // access pointer to data buffer, cast as floats
(float *)PyArray_DATA(src_dir),
(float *)PyArray_DATA(src_int),
(float *)PyArray_DATA(src_index),
(float *)PyArray_DATA(freqs),
(float *)PyArray_DATA(mfreqs),
(float *)PyArray_DATA(vis_array),
(float *)PyArray_DATA(beam_arr),
l, m, N_beam_fq, lmin, lmax, mmin, mmax, beamfqmin, beamfqmax,
N_fq, N_src // pass pointer to sum buffer to hold result
);
return PyArray_Return(vis_array);
}
static PyObject *AscanfCall( ascanf_Function *af, PyObject *arglist, long repeats, int asarray, int deref,
PAO_Options *opts, char *caller )
{ int fargs= 0, aargc= 0, volatile_args= 0;
double result= 0, *aresult=NULL;
static double *AARGS= NULL;
static char *ATYPE= NULL;
static ascanf_Function *LAF= NULL;
static size_t LAFN= 0;
double *aargs= NULL;
char *atype= NULL;
ascanf_Function *laf= NULL, *af_array= NULL;
size_t lafN= 0;
PyObject *ret= NULL;
static ascanf_Function *nDindex= NULL;
int aV = ascanf_verbose;
if( arglist ){
if( PyList_Check(arglist) ){
if( !(arglist= PyList_AsTuple(arglist)) ){
PyErr_SetString( XG_PythonError, "unexpected failure converting argument list to tuple" );
// PyErr_SetString( PyExc_RuntimeError, "unexpected failure converting argument list to tuple" );
return(NULL);
}
}
if( !PyTuple_Check(arglist) ){
PyErr_SetString(
XG_PythonError,
// PyExc_SyntaxError,
"arguments to the ascanf method should be passed as a tuple or list\n"
" NB: a 1-element tuple is specified as (value , ) !!\n"
);
return(NULL);
}
aargc= PyTuple_Size(arglist);
}
else{
aargc= 0;
}
if( !af ){
goto PAC_ESCAPE;
}
if( af->type!= _ascanf_procedure && af->Nargs> 0 ){
/* procedures can have as many arguments as MaxArguments, which is probably too much to allocate here.
\ However, we know how many arguments a function can get (if all's well...), and we can assure that
\ it will have space for those arguments
\ 20061015: unless it also has MaxArguments, i.e. Nargs<0 ...
*/
fargs= af->Nargs;
}
{ long n= (aargc+fargs+1)*2;
if( opts->call_reentrant ){
lafN= n;
aargs= (double*) calloc( lafN, sizeof(double) );
atype= (char*) calloc( lafN, sizeof(char) );
if( !aargs || !atype || !(laf= (ascanf_Function*) calloc( lafN, sizeof(ascanf_Function) )) ){
PyErr_NoMemory();
return(NULL);
}
}
else{
if( !LAF ){
LAFN= n;
AARGS= (double*) calloc( LAFN, sizeof(double) );
ATYPE= (char*) calloc( LAFN, sizeof(char) );
if( !AARGS || !ATYPE || !(LAF= (ascanf_Function*) calloc( LAFN, sizeof(ascanf_Function) )) ){
PyErr_NoMemory();
return(NULL);
}
}
else if( n> LAFN ){
AARGS= (double*) realloc( AARGS, n * sizeof(double) );
ATYPE= (char*) realloc( ATYPE, n * sizeof(char) );
if( !AARGS || !ATYPE || !(LAF= (ascanf_Function*) realloc( LAF, n * sizeof(ascanf_Function) )) ){
PyErr_NoMemory();
return(NULL);
}
else{
for( ; LAFN< n; LAFN++ ){
AARGS[LAFN]= 0;
memset( &LAF[LAFN], 0, sizeof(ascanf_Function) );
}
}
LAFN= n;
}
aargs= AARGS;
atype= ATYPE;
laf= LAF;
lafN= LAFN;
}
}
{ int a= 0, i;
if( opts->verbose > 1 ){
ascanf_verbose = 1;
}
if( af->type== _ascanf_array ){
if( !nDindex ){
nDindex= Py_getNamedAscanfVariable("nDindex");
}
if( nDindex ){
af_array= af;
aargs[a]= (af->own_address)? af->own_address : take_ascanf_address(af);
af= nDindex;
a+= 1;
}
}
for( i= 0; i< aargc; i++, a++ ){
PyObject *arg= PyTuple_GetItem(arglist, i);
ascanf_Function *aaf;
if( PyFloat_Check(arg) ){
aargs[a]= PyFloat_AsDouble(arg);
atype[a]= 1;
}
#ifdef USE_COBJ
else if( PyCObject_Check(arg) ){
if( (aaf= PyCObject_AsVoidPtr(arg)) && (PyCObject_GetDesc(arg)== aaf->function) ){
aargs[a]= (aaf->own_address)? aaf->own_address : take_ascanf_address(aaf);
atype[a]= 2;
}
else{
PyErr_SetString( XG_PythonError, "unsupported PyCObject type does not contain ascanf pointer" );
// PyErr_SetString( PyExc_TypeError, "unsupported PyCObject type does not contain ascanf pointer" );
goto PAC_ESCAPE;
}
}
#else
else if( PyAscanfObject_Check(arg) ){
if( (aaf= PyAscanfObject_AsAscanfFunction(arg)) ){
aargs[a]= (aaf->own_address)? aaf->own_address : take_ascanf_address(aaf);
atype[a]= 2;
}
else{
PyErr_SetString( XG_PythonError, "invalid PyAscanfObject type does not contain ascanf pointer" );
// PyErr_SetString( PyExc_TypeError, "invalid PyAscanfObject type does not contain ascanf pointer" );
goto PAC_ESCAPE;
}
}
#endif
else if( PyInt_Check(arg) || PyLong_Check(arg) ){
aargs[a]= PyInt_AsLong(arg);
atype[a]= 3;
}
else if( PyBytes_Check(arg)
#ifdef IS_PY3K
|| PyUnicode_Check(arg)
#endif
){
static char *AFname= "AscanfCall-Static-StringPointer";
ascanf_Function *saf= &laf[a];
memset( saf, 0, sizeof(ascanf_Function) );
saf->type= _ascanf_variable;
saf->function= ascanf_Variable;
if( !(saf->name= PyObject_Name(arg)) ){
saf->name= XGstrdup(AFname);
}
saf->is_address= saf->take_address= True;
saf->is_usage= saf->take_usage= True;
saf->internal= True;
#ifdef IS_PY3K
if( PyUnicode_Check(arg) ){
PyObject *bytes = NULL;
char *str = NULL;
PYUNIC_TOSTRING( arg, bytes, str );
if( !str ){
if( bytes ){
Py_XDECREF(bytes);
}
goto PAC_ESCAPE;
}
saf->usage= parse_codes( XGstrdup(str) );
Py_XDECREF(bytes);
}
else
#endif
{
saf->usage= parse_codes( XGstrdup( PyBytes_AsString(arg) ) );
}
aargs[a]= take_ascanf_address(saf);
atype[a]= 4;
if( i && af_array ){
volatile_args+= 1;
}
}
else if( PyArray_Check(arg)
|| PyTuple_Check(arg)
|| PyList_Check(arg)
){
static char *AFname= "AscanfCall-Static-ArrayPointer";
ascanf_Function *saf= &laf[a];
PyArrayObject *parray;
atype[a]= 6;
if( PyList_Check(arg) ){
if( !(arg= PyList_AsTuple(arg)) ){
PyErr_SetString( XG_PythonError, "unexpected failure converting argument to tuple" );
// PyErr_SetString( PyExc_RuntimeError, "unexpected failure converting argument to tuple" );
goto PAC_ESCAPE;
/* return(NULL); */
}
else{
atype[a]= 5;
}
}
memset( saf, 0, sizeof(ascanf_Function) );
saf->type= _ascanf_array;
saf->function= ascanf_Variable;
if( !(saf->name= PyObject_Name(arg)) ){
saf->name= XGstrdup(AFname);
}
saf->is_address= saf->take_address= True;
saf->internal= True;
if( a ){
saf->car= &laf[a-1];
}
else{
saf->car= &laf[lafN-1];
}
if( PyTuple_Check(arg) ){
saf->N= PyTuple_Size(arg);
parray= NULL;
}
else{
saf->N= PyArray_Size(arg);
parray= (PyArrayObject*) arg;
atype[a]= 7;
}
if( (saf->array= (double*) malloc( saf->N * sizeof(double) )) ){
int j;
if( parray ){
PyArrayObject* xd= NULL;
double *PyArrayBuf= NULL;
PyArrayIterObject *it;
if( (xd = (PyArrayObject*) PyArray_ContiguousFromObject( (PyObject*) arg, PyArray_DOUBLE, 0, 0 )) ){
PyArrayBuf= (double*)PyArray_DATA(xd); /* size would be N*sizeof(double) */
}
else{
it= (PyArrayIterObject*) PyArray_IterNew(arg);
}
if( PyArrayBuf ){
// for( j= 0; j< saf->N; j++ ){
// /* 20061016: indices used to be i?!?! */
// saf->array[j]= PyArrayBuf[j];
// }
if( saf->array != PyArrayBuf ){
memcpy( saf->array, PyArrayBuf, saf->N * sizeof(double) );
}
}
else{
for( j= 0; j< saf->N; j++ ){
saf->array[j]= PyFloat_AsDouble( PyArray_DESCR(parray)->f->getitem( it->dataptr, arg) );
PyArray_ITER_NEXT(it);
}
}
if( xd ){
Py_XDECREF(xd);
}
else{
Py_DECREF(it);
}
}
else{
for( j= 0; j< saf->N; j++ ){
saf->array[j]= PyFloat_AsDouble( PyTuple_GetItem(arg,j) );
}
}
aargs[a]= take_ascanf_address(saf);
if( i && af_array ){
volatile_args+= 1;
}
}
else{
PyErr_NoMemory();
goto PAC_ESCAPE;
}
}
#if 0
else{
PyErr_SetString( XG_PythonError, "arguments should be scalars, strings, arrays or ascanf pointers" );
// PyErr_SetString( PyExc_SyntaxError, "arguments should be scalars, strings, arrays or ascanf pointers" );
goto PAC_ESCAPE;
}
#else
else{
static char *AFname= "AscanfCall-Static-PyObject";
ascanf_Function *saf= &laf[a];
memset( saf, 0, sizeof(ascanf_Function) );
saf->function= ascanf_Variable;
saf->internal= True;
saf= make_ascanf_python_object( saf, arg, "AscanfCall" );
if( !saf->name ){
if( saf->PyObject_Name ){
saf->name= XGstrdup(saf->PyObject_Name);
}
else{
saf->name= XGstrdup(AFname);
}
}
aargs[a]= take_ascanf_address(saf);
atype[a]= 4;
if( i && af_array ){
volatile_args+= 1;
}
}
#endif
}
if( a> aargc ){
aargc= a;
}
}
const unsigned size() { return PyArray_Size(obj.get()); }
int getSize1( void* arr ) {
return (int) PyArray_Size( (PyObject *) arr );
}
// =============================================================================
int Epetra_NumPyMultiVector::getRangeLen(PyObject * range,
const Epetra_MultiVector & source)
{
if (!tmp_range) getRange(range, source);
return PyArray_Size((PyObject*)tmp_range);
}
static PyObject * enz_vnmpocnp(PyObject *self, PyObject *args,
PyObject *keywds)
{
static char *kwlist[] = { "r", "f", "n", "m", "L_max",
"bessel_name", "ncpus", "verb", NULL };
long syscpus = sysconf(_SC_NPROCESSORS_ONLN);
PyObject *r_o, *f_o, *n_o, *m_o;
PyObject *r = NULL;
PyObject *f = NULL;
PyObject *n = NULL;
PyObject *m = NULL;
const char *error = NULL;
npy_intp r_n, f_n, beta_n;
PyObject *vnm = NULL;
npy_intp vnm_dims[3];
double *datar = NULL;
complex double *dataf = NULL;
int *datan = NULL;
int *datam = NULL;
complex double *datap = NULL;
int kL_max = 35;
int kncpus = -1;
int kverb = 0;
char *kbessel_name = "jn";
int ret;
if (syscpus <= 0)
syscpus = 1;
if (!PyArg_ParseTupleAndKeywords(args, keywds, "O!O!O!O!|isii",
kwlist,
&PyArray_Type, &r_o,
&PyArray_Type, &f_o,
&PyArray_Type, &n_o,
&PyArray_Type, &m_o,
&kL_max, &kbessel_name, &kncpus, &kverb)) {
PyErr_SetString(PyExc_SyntaxError, "failed to parse args");
return NULL;
}
r = PyArray_FROM_OTF(r_o, NPY_FLOAT64, NPY_ARRAY_IN_ARRAY);
f = PyArray_FROM_OTF(f_o, NPY_COMPLEX128, NPY_ARRAY_IN_ARRAY);
n = PyArray_FROM_OTF(n_o, NPY_INT64, NPY_ARRAY_IN_ARRAY);
m = PyArray_FROM_OTF(m_o, NPY_INT64, NPY_ARRAY_IN_ARRAY);
if (!r) {
PyErr_SetString(PyExc_ValueError, "cannot convert r to PyArray");
return NULL;
}
if (!f) {
PyErr_SetString(PyExc_ValueError, "cannot convert f to PyArray");
return NULL;
}
if (!n) {
PyErr_SetString(PyExc_ValueError, "cannot convert n to PyArray");
return NULL;
}
if (!m) {
PyErr_SetString(PyExc_ValueError, "cannot convert m to PyArray");
return NULL;
}
if (!r || not_vect(r) || PyArray_TYPE((PyArrayObject*)r) != NPY_FLOAT64) {
error = "r is not a vector of doubles";
goto exit_decrement;
}
r_n = PyArray_DIM((PyArrayObject*)r, 0);
if (!f || not_vect(f) ||
PyArray_TYPE((PyArrayObject*)f) != NPY_COMPLEX128) {
error = "f is not a vector of complex numbers";
goto exit_decrement;
}
f_n = PyArray_DIM((PyArrayObject*)f, 0);
if (!n || not_vect(n) || PyArray_TYPE((PyArrayObject*)n) != NPY_INT64) {
error = "n is not a vector of integers";
goto exit_decrement;
}
if (!m || not_vect(m) || PyArray_TYPE((PyArrayObject*)m) != NPY_INT64) {
error = "m is not a vector of integers";
goto exit_decrement;
}
if (PyArray_DIM((PyArrayObject*)n, 0) !=
PyArray_DIM((PyArrayObject*)m, 0)) {
error = "n and m must have the same length";
goto exit_decrement;
}
beta_n = PyArray_DIM((PyArrayObject*)n, 0);
vnm_dims[0] = r_n;
vnm_dims[1] = f_n;
vnm_dims[2] = beta_n;
vnm = PyArray_New(&PyArray_Type, 3, vnm_dims, NPY_COMPLEX128, NULL, NULL,
0, NPY_ARRAY_F_CONTIGUOUS | NPY_ARRAY_ALIGNED, NULL);
if (!vnm) {
error = "cannot create vnm";
goto exit_decrement;
}
PyArray_CLEARFLAGS((PyArrayObject*)vnm, NPY_ARRAY_C_CONTIGUOUS);
assert(PyArray_Size(vnm) == (r_n * f_n * beta_n));
assert(PyArray_NBYTES(vnm) == (r_n * f_n * beta_n * sizeof(double complex)));
datap = PyArray_DATA((PyArrayObject*)vnm);
if (kncpus < 0)
kncpus = beta_n < syscpus ? beta_n : syscpus;
else
kncpus = kncpus > syscpus ? syscpus : kncpus;
if ((r_n * f_n * beta_n) != 0) {
datar = PyArray_DATA((PyArrayObject*)r);
dataf = PyArray_DATA((PyArrayObject*)f);
datan = PyArray_DATA((PyArrayObject*)n);
datam = PyArray_DATA((PyArrayObject*)m);
Py_BEGIN_ALLOW_THREADS
ret = vnmpocnp(r_n, datar,
f_n, dataf,
beta_n,
datan, datam,
kL_max, kbessel_name,
kncpus,
kverb, datap, &error);
Py_END_ALLOW_THREADS
if (ret) {
Py_XDECREF(vnm);
goto exit_decrement;
}
}
static
int check_and_fix_dimensions(const PyArrayObject* arr,const int rank,npy_intp *dims) {
/*
This function fills in blanks (that are -1\'s) in dims list using
the dimensions from arr. It also checks that non-blank dims will
match with the corresponding values in arr dimensions.
*/
const npy_intp arr_size = (PyArray_NDIM(arr))?PyArray_Size((PyObject *)arr):1;
#ifdef DEBUG_COPY_ND_ARRAY
dump_attrs(arr);
printf("check_and_fix_dimensions:init: dims=");
dump_dims(rank,dims);
#endif
if (rank > PyArray_NDIM(arr)) { /* [1,2] -> [[1],[2]]; 1 -> [[1]] */
npy_intp new_size = 1;
int free_axe = -1;
int i;
npy_intp d;
/* Fill dims where -1 or 0; check dimensions; calc new_size; */
for(i=0;i<PyArray_NDIM(arr);++i) {
d = PyArray_DIM(arr,i);
if (dims[i] >= 0) {
if (d>1 && dims[i]!=d) {
fprintf(stderr,"%d-th dimension must be fixed to %" NPY_INTP_FMT
" but got %" NPY_INTP_FMT "\n",
i,dims[i], d);
return 1;
}
if (!dims[i]) dims[i] = 1;
} else {
dims[i] = d ? d : 1;
}
new_size *= dims[i];
}
for(i=PyArray_NDIM(arr);i<rank;++i)
if (dims[i]>1) {
fprintf(stderr,"%d-th dimension must be %" NPY_INTP_FMT
" but got 0 (not defined).\n",
i,dims[i]);
return 1;
} else if (free_axe<0)
free_axe = i;
else
dims[i] = 1;
if (free_axe>=0) {
dims[free_axe] = arr_size/new_size;
new_size *= dims[free_axe];
}
if (new_size != arr_size) {
fprintf(stderr,"unexpected array size: new_size=%" NPY_INTP_FMT
", got array with arr_size=%" NPY_INTP_FMT " (maybe too many free"
" indices)\n", new_size,arr_size);
return 1;
}
} else if (rank==PyArray_NDIM(arr)) {
npy_intp new_size = 1;
int i;
npy_intp d;
for (i=0; i<rank; ++i) {
d = PyArray_DIM(arr,i);
if (dims[i]>=0) {
if (d > 1 && d!=dims[i]) {
fprintf(stderr,"%d-th dimension must be fixed to %" NPY_INTP_FMT
" but got %" NPY_INTP_FMT "\n",
i,dims[i],d);
return 1;
}
if (!dims[i]) dims[i] = 1;
} else dims[i] = d;
new_size *= dims[i];
}
if (new_size != arr_size) {
fprintf(stderr,"unexpected array size: new_size=%" NPY_INTP_FMT
", got array with arr_size=%" NPY_INTP_FMT "\n", new_size,arr_size);
return 1;
}
} else { /* [[1,2]] -> [[1],[2]] */
int i,j;
npy_intp d;
int effrank;
npy_intp size;
for (i=0,effrank=0;i<PyArray_NDIM(arr);++i)
if (PyArray_DIM(arr,i)>1) ++effrank;
if (dims[rank-1]>=0)
if (effrank>rank) {
fprintf(stderr,"too many axes: %d (effrank=%d), expected rank=%d\n",
PyArray_NDIM(arr),effrank,rank);
return 1;
}
for (i=0,j=0;i<rank;++i) {
while (j<PyArray_NDIM(arr) && PyArray_DIM(arr,j)<2) ++j;
if (j>=PyArray_NDIM(arr)) d = 1;
else d = PyArray_DIM(arr,j++);
if (dims[i]>=0) {
if (d>1 && d!=dims[i]) {
fprintf(stderr,"%d-th dimension must be fixed to %" NPY_INTP_FMT
" but got %" NPY_INTP_FMT " (real index=%d)\n",
i,dims[i],d,j-1);
return 1;
}
if (!dims[i]) dims[i] = 1;
} else
dims[i] = d;
}
for (i=rank;i<PyArray_NDIM(arr);++i) { /* [[1,2],[3,4]] -> [1,2,3,4] */
while (j<PyArray_NDIM(arr) && PyArray_DIM(arr,j)<2) ++j;
if (j>=PyArray_NDIM(arr)) d = 1;
else d = PyArray_DIM(arr,j++);
dims[rank-1] *= d;
}
for (i=0,size=1;i<rank;++i) size *= dims[i];
if (size != arr_size) {
fprintf(stderr,"unexpected array size: size=%" NPY_INTP_FMT ", arr_size=%" NPY_INTP_FMT
", rank=%d, effrank=%d, arr.nd=%d, dims=[",
size,arr_size,rank,effrank,PyArray_NDIM(arr));
for (i=0;i<rank;++i) fprintf(stderr," %" NPY_INTP_FMT,dims[i]);
fprintf(stderr," ], arr.dims=[");
for (i=0;i<PyArray_NDIM(arr);++i) fprintf(stderr," %" NPY_INTP_FMT,PyArray_DIM(arr,i));
fprintf(stderr," ]\n");
return 1;
}
}
#ifdef DEBUG_COPY_ND_ARRAY
printf("check_and_fix_dimensions:end: dims=");
dump_dims(rank,dims);
#endif
return 0;
}