Honor the contiguous param

Author: FrancescAlted

blosc2/core.py

@@ -598,15 +598,15 @@ def pack_tensor(tensor, chunksize=None, **kwargs):
     arr = np.asarray(tensor)
     # If not passed, set a sensible typesize
     if 'cparams' in kwargs and 'typesize' not in kwargs['cparams']:
-        cparams = kwargs.pop('cparams')
-        cparams = cparams.copy()
+        cparams = kwargs.pop('cparams').copy()
         cparams['typesize'] = arr.itemsize
         kwargs['cparams'] = cparams
     elif 'typesize' not in kwargs:
         kwargs['typesize'] = arr.itemsize
 
     urlpath = kwargs.get('urlpath', None)
-    contiguous = False if urlpath is None else True
+    if 'contiguous' not in kwargs:
+        kwargs['contiguous'] = False if urlpath is None else True
 
     if chunksize is None:
         chunksize = arr.size * arr.itemsize
@@ -615,7 +615,7 @@ def pack_tensor(tensor, chunksize=None, **kwargs):
             chunksize = 2 ** 28
     # Make that a multiple of typesize
     chunksize = chunksize // arr.itemsize * arr.itemsize
-    schunk = blosc2.SChunk(chunksize=chunksize, contiguous=contiguous, data=arr, **kwargs)
+    schunk = blosc2.SChunk(chunksize=chunksize, data=arr, **kwargs)
     # Guess the kind of tensor / array
     repr_tensor = repr(tensor)
     if "tensor" in repr_tensor:

tests/test_tensor.py

@@ -5,6 +5,7 @@
 ########################################################################
 
 
+import os
 import numpy as np
 import pytest
 import blosc2
@@ -170,3 +171,18 @@ def test_save_tensor_torch(size, dtype, urlpath):
     tensor2 = blosc2.load_tensor(urlpath)
     blosc2.remove_urlpath(urlpath)
     assert np.array_equal(nparray, np.asarray(tensor2))
+
+@pytest.mark.parametrize(
+    "size, sparse, urlpath", [
+    (1e6, True, "test.bl2"),
+    (1e6, False, "test.bl2"),
+    ])
+def test_save_tensor_sparse(size, sparse, urlpath):
+    nparray = np.arange(size, dtype=np.int32)
+    serial_size = blosc2.save_tensor(nparray, urlpath, mode="w", contiguous=not sparse)
+    assert serial_size < nparray.size * nparray.itemsize
+
+    a2 = blosc2.load_tensor(urlpath)
+    assert os.path.isdir(urlpath) == sparse
+    blosc2.remove_urlpath(urlpath)
+    assert np.array_equal(nparray, a2)