garbage collect array after generating

fftma_module/gen/lib_src/clean_real.c

@@ -15,13 +15,13 @@ void clean_real(struct realization_mod* realin, int n[3], struct grid_mod grid,
     /*is the output realization already allocated?*/
     /*if not, memory allocation*/
 
-    /*if (realout->vector == NULL || realout->n != realin->n) {
+    if (realout->vector == NULL || realout->n != realin->n) {
         realout->vector = (double*)malloc(realin->n * sizeof(double));
         if (realout->vector == NULL) {
             printf("Clean_real.c:  No memory available\n");
             exit;
         }
-    }*/
+    }
 
     realout->n = realin->n;
     realout->code = 1;

fftma_module/gen/moduleFFTMA.c

@@ -28,12 +28,9 @@ static PyObject* genFunc(PyObject* self, PyObject* args)
     struct vario_mod variogram;
     long seed;
     struct statistic_mod stat;
-    PyArrayObject* out_array;
+    PyObject* out_array;
     npy_intp out_dims[NPY_MAXDIMS];
 
-    out_array = (PyArrayObject *) PyArray_FromDims(NDIMENSIONS,out_dims,NPY_DOUBLE);
-    Y.vector = (double *) out_array->data;
-
     if (!Py_getvalues(args, &seed, &grid, &variogram, &stat))
         return NULL;
     Py_kgeneration(seed, grid, stat, variogram, &Z, &Y, n);
@@ -42,12 +39,11 @@ static PyObject* genFunc(PyObject* self, PyObject* args)
     out_dims[1] = grid.NY;
     out_dims[2] = grid.NX;
 
-    out_array = (PyArrayObject*)PyArray_SimpleNewFromData(NDIMENSIONS, out_dims, NPY_DOUBLE, Y.vector);
+    out_array = PyArray_SimpleNewFromData(NDIMENSIONS, out_dims, NPY_DOUBLE, Y.vector);
     if (out_array == NULL)
         return NULL;
-    // PyArray_ENABLEFLAGS(out_array, NPY_ARRAY_OWNDATA);
 
-    // out_array->flags |= NPY_ARRAY_OWNDATA;
+    PyArray_ENABLEFLAGS(out_array, NPY_ARRAY_OWNDATA);
 
     free(stat.mean);
     free(stat.variance);

fftma_module/gen/test.py

@@ -1,7 +1,8 @@
 from FFTMA import gen
 import numpy as np
+import gc
 
-N=128
+N=512
 
 nx, ny, nz = N,N,N
 dx, dy, dz = 1.0, 1.0, 1.0
@@ -24,8 +25,12 @@ variograms = [v1]
 
 mean=15.3245987
 variance=3.5682389
-typ=1
+typ=3
 
-k=gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
+for i in range(2):
+    k=gen(nx, ny, nz, dx, dy, dz, seed, variograms, mean, variance, typ)
 
-np.save("out.npy",k)
+    np.save(f"out_{i}.npy",k)
+
+    del k
+    gc.collect()