fix: add args and kwargs to all __array__ methods

CHANGELOG

@@ -1,3 +1,5 @@
+0.60.3
+ - fix: add args and kwargs to all __array__ methods
 0.60.2
  - enh: add [experiment]:timestamp (unix time) to configuration
 0.60.1

dclab/rtdc_dataset/feat_basin.py

@@ -405,13 +405,14 @@ def __init__(self, feat_obj, basinmap):
         self._cache = None
         self.is_scalar = bool(len(self.feat_obj.shape) == 1)
 
-    def __array__(self):
+    def __array__(self, dtype=None, *args, **kwargs):
         if self._cache is None and self.is_scalar:
             self._cache = self.feat_obj[:][self.basinmap]
         else:
             # This is dangerous territory in terms of memory usage
             out_arr = np.empty((len(self.basinmap),) + self.feat_obj.shape[1:],
-                               dtype=self.feat_obj.dtype)
+                               dtype=dtype or self.feat_obj.dtype,
+                               *args, **kwargs)
             for ii, idx in enumerate(self.basinmap):
                 out_arr[ii] = self.feat_obj[idx]
             return out_arr

dclab/rtdc_dataset/fmt_hdf5/events.py

@@ -140,15 +140,15 @@ def __init__(self, h5dataset):
         self.identifier = (self.h5dataset.file.filename, self.h5dataset.name)
         self.dtype = np.dtype(bool)
 
-    def __array__(self, dtype=np.bool_):
+    def __array__(self, dtype=np.bool_, *args, **kwargs):
         if dtype is not np.uint8:
             warnings.warn("Please avoid calling the `__array__` method of the "
                           "`H5MaskEvent`. It may consume a lot of memory.",
                           UserWarning)
         # One of the reasons why we implement __array__ is such that
         # the data exporter knows this object is sliceable
         # (see yield_filtered_array_stacks).
-        return self.h5dataset.__array__(dtype=dtype)
+        return self.h5dataset.__array__(dtype=dtype, *args, **kwargs)
 
     def __getitem__(self, idx):
         return np.asarray(self.h5dataset[idx], dtype=bool)
@@ -180,9 +180,9 @@ def __init__(self, h5ds):
         # attrs
         self._ufunc_attrs = dict(self.h5ds.attrs)
 
-    def __array__(self, dtype=None):
+    def __array__(self, *args, **kwargs):
         if self._array is None:
-            self._array = np.asarray(self.h5ds, dtype=dtype)
+            self._array = np.asarray(self.h5ds, *args, **kwargs)
         return self._array
 
     def __getitem__(self, idx):

dclab/rtdc_dataset/fmt_hierarchy/events.py

@@ -37,12 +37,12 @@ def __init__(self, child, feat):
         super(ChildNDArray, self).__init__(child)
         self.feat = feat
 
-    def __array__(self):
+    def __array__(self, *args, **kwargs):
         warnings.warn("Please avoid calling the `__array__` method of the "
                       "`ChildNDArray`. It may consume a lot of memory. "
                       "Consider using a generator instead.",
                       UserWarning)
-        return self[:]
+        return np.asarray(self[:], *args, **kwargs)
 
     def __getitem__(self, idx):
         pidx = map_indices_child2parent(child=self.child,
@@ -69,12 +69,12 @@ def __init__(self, child, feat):
         self._ufunc_attrs = {}
         self.ndim = 1  # matplotlib might expect this from an array
 
-    def __array__(self, dtype=None):
+    def __array__(self, *args, **kwargs):
         if self._array is None:
             hparent = self.child.hparent
             filt_arr = hparent.filter.all
             self._array = hparent[self.feat][filt_arr]
-        return self._array
+        return np.asarray(self._array, *args, **kwargs)
 
     def __getitem__(self, idx):
         return self.__array__()[idx]
@@ -121,12 +121,12 @@ def __init__(self, child, flname):
         super(ChildTraceItem, self).__init__(child)
         self.flname = flname
 
-    def __array__(self):
+    def __array__(self, *args, **kwargs):
         warnings.warn("Please avoid calling the `__array__` method of the "
                       "`ChildTraceItem`. It may consume a lot of memory. "
                       "Consider using a generator instead.",
                       UserWarning)
-        return self[:]
+        return np.asarray(self[:], *args, **kwargs)
 
     def __getitem__(self, idx):
         pidx = map_indices_child2parent(child=self.child,

tests/test_rtdc_feat_basin.py

@@ -131,6 +131,39 @@ def test_basin_cyclic_dependency_found_2():
             _ = ds["userdef1"]
 
 
+@pytest.mark.filterwarnings(
+    "ignore::dclab.rtdc_dataset.config.WrongConfigurationTypeWarning")
+@pytest.mark.filterwarnings(
+    "ignore::UserWarning")
+def test_basin_feature_image_export_from_basin_with_hierarchy(tmp_path):
+    h5path = retrieve_data("fmt-hdf5_fl_wide-channel_2023.zip")
+    epath = tmp_path / "exported.rtdc"
+    epath2 = tmp_path / "exported2.rtdc"
+    # Create a basins-only dataset using the export functionality
+    with dclab.new_dataset(h5path) as ds:
+        assert "image" in ds
+        ds.export.hdf5(path=epath,
+                       features=[],
+                       basins=True,
+                       filtered=False,
+                       )
+    # Attempt to export image data from the exported dataset
+    with dclab.new_dataset(epath) as ds:
+        ds2 = dclab.new_dataset(ds)
+        assert "image" in ds2
+        assert "image" not in ds2.features_innate
+        ds2.export.hdf5(path=epath2,
+                        features=["mask", "image"],
+                        basins=False,
+                        filtered=False,
+                        )
+
+    # Open the exported dataset and attempt to access the image feature
+    with dclab.new_dataset(epath2) as ds:
+        assert "mask" in ds
+        assert np.any(ds["mask"][0])
+
+
 @pytest.mark.filterwarnings(
     "ignore::dclab.rtdc_dataset.config.WrongConfigurationTypeWarning")
 @pytest.mark.skipif(not DCOR_AVAILABLE, reason="DCOR is not available")

tests/test_rtdc_feat_basin_mapped.py

@@ -161,6 +161,8 @@ def test_basin_mapped(basinmap):
     [1, 3, 4],  # very simple case
     [1, 1, 1, 2],  # not trivial, not realizable with hierarchy children
 ])
+@pytest.mark.filterwarnings(
+    "ignore::UserWarning")
 def test_basin_mapped_export(basinmap):
     path = retrieve_data("fmt-hdf5_image-mask-blood_2021.zip")
     with h5py.File(path, "a") as h5: