[FIX] Forgot to massage kwargs for concatenate

Author: FrancescAlted

bench/ndarray/concatenate.py

@@ -50,7 +50,7 @@ def run_benchmark(num_arrays=10, size=500, aligned_chunks=False, axis=0):
     arrays = []
     for i, (shape, chunk_shape) in enumerate(zip(shapes, chunk_shapes)):
         arr = blosc2.arange(
-            i * np.prod(shape), (i + 1) * np.prod(shape), 1, dtype="i4", shape=shape, chunks=chunk_shape
+            i * np.prod(shape), (i + 1) * np.prod(shape), 1, dtype="i4", shape=shape, chunks=chunk_shape,
         )
         arrays.append(arr)
 
@@ -60,7 +60,7 @@ def run_benchmark(num_arrays=10, size=500, aligned_chunks=False, axis=0):
 
     # Time the concatenation
     start_time = time.time()
-    result = blosc2.concatenate(arrays, axis=axis)
+    result = blosc2.concatenate(arrays, axis=axis, cparams=blosc2.CParams(codec=blosc2.Codec.BLOSCLZ))
     duration = time.time() - start_time
 
     return duration, result.shape, data_size_gb
@@ -198,7 +198,7 @@ def main():
     print(f"{'=' * 60}")
 
     # Parameters
-    sizes = [500, 1000, 2000, 4000] #, 10000]  # must be divisible by 4 for aligned chunks
+    sizes = [500, 1000] #, 2000, 4000] #, 10000]  # must be divisible by 4 for aligned chunks
     num_arrays = 10
 
     # Lists to store results for both axes
@@ -211,7 +211,8 @@ def main():
 
     for axis in [0, 1]:
         print(f"\nConcatenating {num_arrays} arrays along axis {axis}")
-        print(f"{'Size':<10} {'NumPy (GB/s)':<14} {'Unaligned (GB/s)':<18} {'Aligned (GB/s)':<16} {'Alig vs Unalig':<16} {'Alig vs NumPy':<16}")
+        print(f"{'Size':<10} {'NumPy (GB/s)':<14} {'Unaligned (GB/s)':<18} "
+              f"{'Aligned (GB/s)':<16} {'Alig vs Unalig':<16} {'Alig vs NumPy':<16}")
         print(f"{'-' * 90}")
 
         for size in sizes:

src/blosc2/ndarray.py

@@ -3577,6 +3577,7 @@ def concatenate(arrays: list[NDArray], /, axis=0, **kwargs: Any) -> NDArray:  #
                 f"{arr1.shape} vs {arr2.shape}"
             )
 
+    kwargs = _check_ndarray_kwargs(**kwargs)
     # Proceed with the actual concatenation
     copy = True
     for arr2 in arrays[1:]:

tests/ndarray/test_concatenate.py

@@ -32,7 +32,8 @@
 def test_concat2(shape1, shape2, dtype, axis):
     ndarr1 = blosc2.arange(0, int(np.prod(shape1)), 1, dtype=dtype, shape=shape1)
     ndarr2 = blosc2.arange(0, int(np.prod(shape2)), 1, dtype=dtype, shape=shape2)
-    result = blosc2.concatenate([ndarr1, ndarr2], axis=axis)
+    cparams = blosc2.CParams(clevel=1)
+    result = blosc2.concatenate([ndarr1, ndarr2], axis=axis, cparams=cparams)
     nparray = np.concatenate([ndarr1[:], ndarr2[:]], axis=axis)
     np.testing.assert_almost_equal(result[:], nparray)
 
@@ -57,6 +58,7 @@ def test_concat3(shape1, shape2, shape3, dtype, axis):
     ndarr1 = blosc2.arange(0, int(np.prod(shape1)), 1, dtype=dtype, shape=shape1)
     ndarr2 = blosc2.arange(0, int(np.prod(shape2)), 1, dtype=dtype, shape=shape2)
     ndarr3 = blosc2.arange(0, int(np.prod(shape3)), 1, dtype=dtype, shape=shape3)
-    result = blosc2.concatenate([ndarr1, ndarr2, ndarr3], axis=axis)
+    cparams = blosc2.CParams(codec=blosc2.Codec.BLOSCLZ)
+    result = blosc2.concatenate([ndarr1, ndarr2, ndarr3], axis=axis, cparams=cparams)
     nparray = np.concatenate([ndarr1[:], ndarr2[:], ndarr3[:]], axis=axis)
     np.testing.assert_almost_equal(result[:], nparray)