Update supported python versions to 3.8, 3.9, 3.10, & 3.11 (drop pyth…

…on 3.7) (#284)

* Supported python versions should match main dask/dask repo

* Update python versions mentioned in pull request template

* Drop python 3.7 env, add envs for python 3.10 & 3.11

* np.bool & np.int deprecated, replace with np.bool_ & int

* threshold_local doesn't raise error for gaussians with nan block size in later versions

.github/PULL_REQUEST_TEMPLATE.md

@@ -4,4 +4,4 @@ Before you submit a pull request, check that it meets these guidelines:
 2. If the pull request adds functionality, the docs should be updated. Put
    your new functionality into a function with a docstring, and add the
    feature to the list in README.rst.
-3. The pull request should work for Python 3.7, 3.8, and 3.9.
+3. The pull request should work for Python 3.8, 3.9, 3.10 and 3.1.

.github/workflows/test.yml

@@ -13,7 +13,7 @@ jobs:
       fail-fast: true
       matrix:
         os: ["windows-latest", "ubuntu-latest", "macos-latest"]
-        python-version: ["3.7", "3.8", "3.9"]
+        python-version: ["3.8", "3.9", "3.10", "3.11"]
 
     steps:
       - name: Checkout source

continuous_integration/environment-3.10.yml

@@ -0,0 +1,20 @@
+name: dask-image-testenv
+
+channels:
+  - conda-forge
+
+dependencies:
+  - python=3.10.*
+  - pip==23.0.1
+  - wheel==0.38.4
+  - coverage==7.2.1
+  - flake8==6.0.0
+  - pytest==7.2.2
+  - pytest-cov==4.0.0
+  - pytest-flake8==1.1.1
+  - dask==2023.3.1
+  - numpy==1.24.2
+  - scipy==1.10.1
+  - scikit-image==0.19.3
+  - pims==0.6.1
+  - slicerator==1.1.0

continuous_integration/environment-3.11.yml

@@ -0,0 +1,20 @@
+name: dask-image-testenv-py311
+
+channels:
+  - conda-forge
+
+dependencies:
+  - python=3.11.*
+  - pip
+  - wheel
+  - coverage
+  - flake8
+  - pytest
+  - pytest-cov
+  - pytest-flake8
+  - dask
+  - numpy
+  - scipy
+  - scikit-image
+  - pims
+  - slicerator

tests/test_dask_image/test_ndfilters/test__threshold.py

@@ -100,7 +100,6 @@ def setup(self):
              [4, 5, 1, 0, 0]], dtype=int), chunks=(5, 5))
 
     @pytest.mark.parametrize("method, block_size, error_type", [
-        ('gaussian', np.nan, ValueError),
         ('median', np.nan, TypeError),
     ])
     def test_nan_blocksize(self, method, block_size, error_type):

tests/test_dask_image/test_ndmeasure/test_core.py

@@ -53,7 +53,7 @@ def test_measure_props_err(funcname):
     "datatype", [
         int,
         float,
-        np.bool,
+        np.bool_,
         np.uint8,
         np.uint16,
         np.uint32,
@@ -445,7 +445,7 @@ def test_labeled_comprehension_struct(shape, chunks, ind):
     )
     d_lbls = da.from_array(lbls, chunks=d.chunks)
 
-    dtype = np.dtype([("val", np.float64), ("pos", np.int)])
+    dtype = np.dtype([("val", np.float64), ("pos", int)])
     default = np.array((np.nan, -1), dtype=dtype)
 
     def func_max(val):