Converted the to_*_array() functions into generics.

This should make it more extensible, for subclasses that are able to
avoid block processing for more efficient coercion.

Author: LTLA

src/delayedarray/DelayedArray.py

@@ -13,7 +13,8 @@
 from .UnaryIsometricOpSimple import UnaryIsometricOpSimple
 from .UnaryIsometricOpWithArgs import UnaryIsometricOpWithArgs
 
-from .extract_dense_array import extract_dense_array, to_dense_array
+from .extract_dense_array import extract_dense_array
+from .to_dense_array import to_dense_array
 from .extract_sparse_array import extract_sparse_array
 from .apply_over_blocks import apply_over_blocks, choose_block_shape_for_iteration
 from .create_dask_array import create_dask_array

src/delayedarray/__init__.py

@@ -27,8 +27,11 @@
 from .UnaryIsometricOpWithArgs import UnaryIsometricOpWithArgs
 from .SparseNdarray import SparseNdarray
 
-from .extract_dense_array import extract_dense_array, to_dense_array
-from .extract_sparse_array import extract_sparse_array, to_sparse_array
+from .extract_dense_array import extract_dense_array
+from .extract_sparse_array import extract_sparse_array
+from .to_dense_array import to_dense_array
+from .to_sparse_array import to_sparse_array
+
 from .create_dask_array import create_dask_array
 from .is_sparse import is_sparse
 from .is_masked import is_masked

src/delayedarray/extract_dense_array.py

@@ -3,7 +3,7 @@
 from typing import Any, Tuple, Sequence
 from biocutils.package_utils import is_package_installed
 
-from ._subset import _spawn_indices, _is_subset_noop
+from ._subset import _is_subset_noop
 from .SparseNdarray import SparseNdarray, _extract_dense_array_from_SparseNdarray
 
 __author__ = "ltla"
@@ -91,18 +91,3 @@ def extract_dense_array_sparse_array(x, subset: Tuple[Sequence[int], ...]) -> nu
         extract_dense_array.register(sp.sparray, extract_dense_array_sparse_array)
     except Exception:
         pass
-
-
-def to_dense_array(x: Any) -> numpy.ndarray:
-    """
-    Convenience function that extracts the entirety of ``x`` as a dense NumPy
-    array. This simply calls :py:func:`~extract_dense_array` with ``subset``
-    set to the full extent of all dimensions.
-
-    Args:
-        x: Any array-like object.
-
-    Returns:
-        NumPy array contains the full contents of ``x``. This may be masked.
-    """
-    return extract_dense_array(x, _spawn_indices(x.shape))

src/delayedarray/extract_sparse_array.py

@@ -217,19 +217,3 @@ def extract_sparse_array_coo_matrix(x: sp.coo_matrix, subset: Tuple[Sequence[int
             new_contents = _set_empty_contents(new_contents)
 
         return SparseNdarray((*final_shape,), new_contents, dtype=x.dtype, index_dtype=x.row.dtype, is_masked=False, check=False)
-
-
-def to_sparse_array(x: Any) -> numpy.ndarray:
-    """
-    Convenience function that extracts the entirety of ``x`` as a
-    :py:class:`~delayedarray.SparseNdarray.SparseNdarray`. This simply calls
-    :py:func:`~extract_sparse_array` with ``subset`` set to the full extent of
-    all dimensions.
-
-    Args:
-        x: Any array-like object containing sparse data.
-
-    Returns:
-        ``SparseNdarray`` with the full contents of ``x``.
-    """
-    return extract_sparse_array(x, _spawn_indices(x.shape))

src/delayedarray/to_dense_array.py

@@ -0,0 +1,22 @@
+from functools import singledispatch
+from typing import Any
+import numpy
+
+from .extract_dense_array import extract_dense_array
+from ._subset import _spawn_indices
+
+
+@singledispatch
+def to_dense_array(x: Any) -> numpy.ndarray:
+    """
+    Extract ``x`` as a dense NumPy array. The default method simply calls
+    :py:func:`~delayedarray.extract_dense_array.extract_dense_array` with
+    ``subset`` set to the full extent of all dimensions.
+
+    Args:
+        x: Any array-like object.
+
+    Returns:
+        NumPy array contains the full contents of ``x``. This may be masked.
+    """
+    return extract_dense_array(x, _spawn_indices(x.shape))

src/delayedarray/to_sparse_array.py

@@ -0,0 +1,23 @@
+from functools import singledispatch
+from typing import Any
+import numpy
+
+from ._subset import _spawn_indices
+from .extract_sparse_array import extract_sparse_array
+from .SparseNdarray import SparseNdarray
+
+
+@singledispatch
+def to_sparse_array(x: Any) -> SparseNdarray:
+    """
+    Convert ``x`` to a :py:class:`~delayedarray.SparseNdarray.SparseNdarray`.
+    This calls :py:func:`~delayedarray.delayedarray.extract_sparse_array` with
+    ``subset`` set to the full extent of all dimensions.
+
+    Args:
+        x: Any array-like object containing sparse data.
+
+    Returns:
+        ``SparseNdarray`` with the full contents of ``x``.
+    """
+    return extract_sparse_array(x, _spawn_indices(x.shape))