Merge branch 'main' into ome-ngff

.github/workflows/black.yaml

@@ -1,4 +1,4 @@
-name: Python Black
+name: black
 
 on: [push, pull_request]
 

.github/workflows/mypy.yaml

@@ -1,4 +1,4 @@
-name: Python mypy
+name: mypy
 
 on: [push, pull_request]
 

.github/workflows/publish.yaml

@@ -1,4 +1,4 @@
-name: Publish
+name: pypi
 
 on:
   push:

.github/workflows/tests.yaml

@@ -1,4 +1,4 @@
-name: Test
+name: tests
 
 on:
   push:

README.md

@@ -1,13 +1,15 @@
 [![tests](https://github.com/funkelab/funlib.persistence/actions/workflows/tests.yaml/badge.svg)](https://github.com/funkelab/funlib.persistence/actions/workflows/tests.yaml)
 [![black](https://github.com/funkelab/funlib.persistence/actions/workflows/black.yaml/badge.svg)](https://github.com/funkelab/funlib.persistence/actions/workflows/black.yaml)
 [![mypy](https://github.com/funkelab/funlib.persistence/actions/workflows/mypy.yaml/badge.svg)](https://github.com/funkelab/funlib.persistence/actions/workflows/mypy.yaml)
+[![pypi](https://github.com/funkelab/funlib.persistence/actions/workflows/publish.yaml/badge.svg)](https://pypi.org/project/funlib.persistence/)
 
 # funlib.persistence
 Interfaces for data (arrays and graphs) and storage formats (databases and file formats)
 
 # installation
-regular installation for usage:
-`pip install .`
-developer installation including pytest etc.:
-`pip install ".[dev]"`
+Regular installation for usage:
+`pip install funlib.persistence`
+
+Developer installation including pytest etc.:
+`pip install funlib.persistence[dev]`
 

funlib/persistence/arrays/array.py

@@ -323,6 +323,13 @@ def __setitem__(self, key, value: np.ndarray):
 
                 self._source_data[region_slices] = value
 
+            # If the source data is an in-memory numpy array, writing to the numpy
+            # array does not always result in the dask array reading the new data.
+            # It seems to be a caching issue. To work around this, we create a new
+            # dask array from the source data.
+            if isinstance(self._source_data, np.ndarray):
+                self.data = da.from_array(self._source_data)
+
         else:
             raise RuntimeError(
                 "This array is not writeable since you have applied a custom callable "

tests/test_array.py

@@ -73,13 +73,14 @@ def test_setitem():
 
     a = Array(np.zeros((2, 5)), (0, 0), (1, 1))
 
-    a[Roi((0, 0), (2, 5))] = np.arange(0, 10).reshape(2, 5)
-    assert a[Coordinate((0, 0))] == 0
-    assert a[Coordinate((0, 1))] == 1
-    assert a[Coordinate((0, 2))] == 2
-    assert a[Coordinate((1, 0))] == 5
-    assert a[Coordinate((1, 1))] == 6
-    assert a[Coordinate((1, 4))] == 9
+    data = np.arange(0, 10).reshape(2, 5)
+    a[Roi((0, 0), (2, 5))] = data
+    assert a[Coordinate((0, 0))] == a._source_data[0, 0] == 0
+    assert a[Coordinate((0, 1))] == a._source_data[0, 1] == 1
+    assert a[Coordinate((0, 2))] == a._source_data[0, 2] == 2
+    assert a[Coordinate((1, 0))] == a._source_data[1, 0] == 5
+    assert a[Coordinate((1, 1))] == a._source_data[1, 1] == 6
+    assert a[Coordinate((1, 4))] == a._source_data[1, 4] == 9
 
     # set entirely with numpy array and channels