Reorganize

python/build_pyqmckl.sh

@@ -5,6 +5,8 @@ set -x
 
 cp ../include/qmckl.h .
 
+cd src/
+
 # check if qmckl header exists
 if [[ ! -f 'qmckl.h' ]]; then
   echo "qmckl.h NOT FOUND"
@@ -12,7 +14,7 @@ if [[ ! -f 'qmckl.h' ]]; then
 fi
 
 # process the qmckl header file to get patterns for SWIG
-python process.py
+python process_header.py
 
 # check if SWIG files exist
 SWIG_LIST='pyqmckl.i pyqmckl_include.i numpy.i'
@@ -32,8 +34,10 @@ cc -c -fPIC `pkg-config --cflags qmckl` -I/usr/include/python3.8 pyqmckl_wrap.c
 # link against the previously installed QMCkl library (as detected by pkg-config)
 cc -shared pyqmckl_wrap.o `pkg-config --libs qmckl` -o _pyqmckl.so
 
+cd ..
+
 # test
-cp _pyqmckl.so pyqmckl.py -- test/
+cp src/_pyqmckl.so src/pyqmckl.py -- test/
 cd test 
 python test_api.py
 

python/pytrexio.i

@@ -1,141 +0,0 @@
-%module pytrexio
-/* Define SWIGWORDSIZE in order to properly align long integers on 64-bit system */
-#define SWIGWORDSIZE64
-%{
-#define SWIG_FILE_WITH_INIT
-/* Include the headers in the wrapper code */
-#include "trexio_s.h"
-#include "trexio.h"
-%}
-
-/* Include stdint to recognize types from stdint.h */
-%include <stdint.i>
-
-/* NOTE:
-   carrays was useful before numpy.i was introduced.
-   For Python interface it's better to use numpy arrays instead of carrays, because the latter are less python-ic.
-   On the other hand, carrays might be more portable to other target languages.
-// Include carrays to work with C pointers to arrays
-%include "carrays.i"
-// Include classes that correspond to integer and float arrays
-%array_class(double, doubleArray);
-%array_class(float, floatArray);
-%array_class(int32_t, int32Array);
-%array_class(int64_t, int64Array);
-*/
-
-/* Include typemaps to play with input/output re-casting
-   Useful when working with C pointers
-*/
-%include typemaps.i
-/* Redefine the [int32_t*, int64_t*, float*, double*] num
-   pattern to be appended to the output tuple.
-   Useful for TREXIO read_num functions where the
-   num variable is modified by address
-*/
-/* Return num variables as part of the output tuple */
-%apply int *OUTPUT { int32_t* const num};
-%apply int *OUTPUT { int64_t* const num};
-%apply int *OUTPUT { int32_t* const num_up};
-%apply int *OUTPUT { int32_t* const num_dn};
-%apply int *OUTPUT { int64_t* const num_up};
-%apply int *OUTPUT { int64_t* const num_dn};
-%apply float *OUTPUT { float* const num};
-%apply float *OUTPUT { double* const num};
-/* Return TREXIO exit code from trexio_open as part of the output tuple */
-%apply int *OUTPUT { trexio_exit_code* const rc_open};
-/* Return number of sparse data points stored in the file as part of the output tuple */
-%apply int *OUTPUT { int64_t* const size_max};
-/* Return number of sparse data points read from the file as part of the output tuple */
-%apply int *INOUT { int64_t* const buffer_size_read};
-
-/* Does not work for arrays (SIGSEGV) */
-
-/* This enables access to trexio_[...]_read_dset_str_low set of functions
-   in order to return one long string with TREXIO_DELIM delimeter as 2-nd argument of output tuple
-   */
-%include <cstring.i>
-/* This enables read of long strings with TREXIO_DELIM delimeters that can be further converted into an array of string */
-%cstring_bounded_output(char* dset_out, 4096);
-/* This enables read of single string attributes with pre-defined max_str_len
-   for Python we pre-define max_str_len = PYTREXIO_MAX_STR_LENGTH everywhere for simplicity
-*/
-%cstring_output_maxsize(char* const str_out, const int32_t max_str_len);
-
-
-/* This block is needed make SWIG treat (double * dset_out|_in, int64_t dim_out|_in) pattern
-   as a special case in order to return the NumPy array to Python from C pointer to array
-   provided by trexio_read_safe_[dset_num] function.
-   NOTE: numpy.i is currently not part of SWIG but included in the numpy distribution (under numpy/tools/swig/numpy.i)
-*/
-%include "numpy.i"
-
-%init %{
-import_array();
-%}
-
-/* Typemaps below change the type of numpy array dimensions from int to int64_t */
-%numpy_typemaps(double, NPY_DOUBLE, int64_t)
-%numpy_typemaps(float, NPY_FLOAT, int64_t)
-%numpy_typemaps(int32_t, NPY_INT32, int64_t)
-%numpy_typemaps(int64_t, NPY_INT64, int64_t)
-%numpy_typemaps(bitfield_t, NPY_INT64, int64_t)
-/* Enable write|read_safe functions to convert numpy arrays from/to double arrays */
-%apply (double* ARGOUT_ARRAY1, int64_t DIM1) {(double* const dset_out, const int64_t dim_out)};
-%apply (double* IN_ARRAY1, int64_t DIM1) {(const double* dset_in, const int64_t dim_in)};
-/* Enable write|read_safe functions to convert numpy arrays from/to float arrays */
-%apply (float* ARGOUT_ARRAY1, int64_t DIM1) {(float* const dset_out, const int64_t dim_out)};
-%apply (float* IN_ARRAY1, int64_t DIM1) {(const float* dset_in, const int64_t dim_in)};
-/* Enable write|read_safe functions to convert numpy arrays from/to int32 arrays */
-%apply (int32_t* ARGOUT_ARRAY1, int64_t DIM1) {(int32_t* const dset_out, const int64_t dim_out)};
-%apply (int32_t* IN_ARRAY1, int64_t DIM1) {(const int32_t* dset_in, const int64_t dim_in)};
-/* Enable write|read_safe functions to convert numpy arrays from/to int64 arrays */
-%apply (int64_t* ARGOUT_ARRAY1, int64_t DIM1) {(int64_t* const dset_out, const int64_t dim_out)};
-%apply (int64_t* IN_ARRAY1, int64_t DIM1) {(const int64_t* dset_in, const int64_t dim_in)};
-/* Enable write|read_safe functions to convert numpy arrays from/to sparse arrays */
-%apply (double* IN_ARRAY1, int64_t DIM1) {(const double* value_sparse_write, const int64_t size_value_write)};
-%apply (int32_t* IN_ARRAY1, int64_t DIM1) {(const int32_t* index_sparse_write, const int64_t size_index_write)};
-
-%apply (double* ARGOUT_ARRAY1, int64_t DIM1) {(double* const value_sparse_read, const int64_t size_value_read)};
-%apply (int32_t* ARGOUT_ARRAY1, int64_t DIM1) {(int32_t* const index_sparse_read, const int64_t size_index_read)};
-/* Enable write|read_safe functions to convert numpy arrays from orbital list arrays */
-%apply (int32_t* ARGOUT_ARRAY1, int64_t DIM1) {(int32_t* const dset_up_out, const int64_t dim_up_out)};
-%apply (int32_t* ARGOUT_ARRAY1, int64_t DIM1) {(int32_t* const dset_dn_out, const int64_t dim_dn_out)};
-%apply (int64_t* ARGOUT_ARRAY1, int64_t DIM1) {(int64_t* const dset_up_out, const int64_t dim_up_out)};
-%apply (int64_t* ARGOUT_ARRAY1, int64_t DIM1) {(int64_t* const dset_dn_out, const int64_t dim_dn_out)};
-%apply (bitfield_t* IN_ARRAY1, int64_t DIM1) {(const bitfield_t* dset_in, const int64_t dim_in)};
-
-/* This tells SWIG to treat char ** dset_in pattern as a special case
-   Enables access to trexio_[...]_write_dset_str set of functions directly, i.e.
-   by converting input list of strings from Python into char ** of C
-*/
-%typemap(in) char** dset_in {
-  /* Check if is a list */
-  if (PyList_Check($input)) {
-    int size = PyList_Size($input);
-    Py_ssize_t i = 0;
-    $1 = (char **) malloc((size+1)*sizeof(char *));
-    for (i = 0; i < size; i++) {
-      PyObject *o = PyList_GetItem($input, i);
-      if (PyUnicode_Check(o)) {
-        $1[i] = PyUnicode_AsUTF8(PyList_GetItem($input,i));
-      } else {
-        PyErr_Format(PyExc_TypeError, "list must contain strings. %d/%d element was not string.", i, size);
-        free($1);
-        return NULL;
-      }
-    }
-    $1[i] = 0;
-  } else {
-    PyErr_SetString(PyExc_TypeError, "not a list");
-    return NULL;
-  }
-}
-/* This cleans up the char ** array we malloc-ed before */
-%typemap(freearg) char** dset_in {
-  free((char *) $1);
-}
-
-/* Parse the header files to generate wrappers */
-%include "trexio_s.h"
-%include "trexio.h"