Merge branch 'dev'

.github/workflows/cibuildwheel.yml

@@ -43,7 +43,7 @@ jobs:
           CIBW_BUILD: "cp3?-*"
           CIBW_SKIP: "cp35-*"
           # install fork of 'delocate' to work around bug
-          CIBW_BEFORE_BUILD: python -m pip install git+https://github.com/uschmidt83/delocate.git@patch-1
+          # CIBW_BEFORE_BUILD: python -m pip install git+https://github.com/uschmidt83/delocate.git@patch-1
            # TODO: make it work for 10.9 (required libstdc++.dylib and libgomp.dylib from gcc compiled for 10.15)
           MACOSX_DEPLOYMENT_TARGET: 10.15
           CIBW_BUILD_VERBOSITY: 1

.github/workflows/tests.yml

@@ -1,6 +1,13 @@
 name: Test
 
-on: [push, pull_request]
+on:
+  push:
+    branches-ignore:
+      - wheels
+  pull_request:
+    branches:
+      - master
+      - dev
 
 jobs:
   test:

pyproject.toml

@@ -1,3 +1,3 @@
 [build-system]
-requires = ["setuptools>=40.8.0", "wheel", "numpy==1.19.3"]
+requires = ["setuptools>=40.8.0", "wheel", "oldest-supported-numpy"]
 build-backend = "setuptools.build_meta"

setup.py

@@ -97,6 +97,8 @@ def build_extension(self, ext):
         'Topic :: Scientific/Engineering',
         'License :: OSI Approved :: BSD License',
 
+        'Operating System :: OS Independent',
+
         'Programming Language :: Python :: 3.6',
         'Programming Language :: Python :: 3.7',
         'Programming Language :: Python :: 3.8',

stardist/__init__.py

@@ -1,9 +1,11 @@
 from __future__ import absolute_import, print_function
+
 import warnings
-import pathlib
-def format_Warning(message, category, filename, lineno, line=''):
+def format_warning(message, category, filename, lineno, line=''):
+    import pathlib
     return f"{pathlib.Path(filename).name} ({lineno}): {message}\n"
-warnings.formatwarning = format_Warning
+warnings.formatwarning = format_warning
+del warnings
 
 from .version import __version__
 

stardist/models/model2d.py

@@ -59,18 +59,18 @@ def __getitem__(self, i):
 
         X, Y = tuple(zip(*tuple(self.augmenter(_x, _y) for _x, _y in zip(X,Y))))
 
-        
+
         prob = np.stack([edt_prob(lbl[self.b][self.ss_grid[1:3]]) for lbl in Y])
         # prob = np.stack([edt_prob(lbl[self.b]) for lbl in Y])
         # prob = prob[self.ss_grid]
 
         if self.shape_completion:
             Y_cleared = [clear_border(lbl) for lbl in Y]
-            _dist      = np.stack([star_dist(lbl,self.n_rays,mode=self.sd_mode)[self.b+(slice(None),)] for lbl in Y_cleared])
-            dist      = dist[self.ss_grid]
+            _dist     = np.stack([star_dist(lbl,self.n_rays,mode=self.sd_mode)[self.b+(slice(None),)] for lbl in Y_cleared])
+            dist      = _dist[self.ss_grid]
             dist_mask = np.stack([edt_prob(lbl[self.b][self.ss_grid[1:3]]) for lbl in Y_cleared])
         else:
-            # directly subsample with grid 
+            # directly subsample with grid
             dist      = np.stack([star_dist(lbl,self.n_rays,mode=self.sd_mode, grid=self.grid) for lbl in Y])
             dist_mask = prob
 

stardist/utils.py

@@ -13,6 +13,7 @@
 from skimage.measure import regionprops
 from csbdeep.utils import _raise
 from csbdeep.utils.six import Path
+from collections.abc import Iterable
 
 from .matching import matching_dataset, _check_label_array
 
@@ -178,7 +179,7 @@ def sample_points(n_samples, mask, prob=None, b=2):
 
 def calculate_extents(lbl, func=np.median):
     """ Aggregate bounding box sizes of objects in label images. """
-    if isinstance(lbl,(tuple,list)) or (isinstance(lbl,np.ndarray) and lbl.ndim==4):
+    if (isinstance(lbl,np.ndarray) and lbl.ndim==4) or (not isinstance(lbl,np.ndarray) and  isinstance(lbl,Iterable)):
         return func(np.stack([calculate_extents(_lbl,func) for _lbl in lbl], axis=0), axis=0)
 
     n = lbl.ndim

stardist/version.py

@@ -1 +1 @@
-__version__ = '0.7.1'
+__version__ = '0.7.2'

tests/test_model2D.py

@@ -113,13 +113,16 @@ def test_optimize_thresholds(model2d):
     np.testing.assert_almost_equal(res["nms"] , 0.3, decimal=3)
 
 
-def test_stardistdata(n_classes = None, classes = 1):
+@pytest.mark.parametrize('n_classes, classes', [(None,(1,1)),(2,(1,2))])
+@pytest.mark.parametrize('shape_completion',(False,True))
+def test_stardistdata(shape_completion, n_classes, classes):
     np.random.seed(42)
     from stardist.models import StarDistData2D
     img, mask = real_image2d()
     s = StarDistData2D([img, img], [mask, mask],
                        grid = (2,2),
-                       n_classes = n_classes, classes = (classes,classes),
+                       n_classes = n_classes, classes = classes,
+                       shape_completion = shape_completion, b = 8,
                        batch_size=1, patch_size=(30, 40), n_rays=32, length=1)
     a, b = s[0]
     return a,b, s