Add test for base attributes

scripts/attributes/master.py

@@ -4,6 +4,7 @@ import h5py
 from .base_attributes import base_attributes
 from .map_objects import map_objects
 from .genes import write_genes_table
+from .morphology import write_morphology_cells, write_morphology_nuclei
 from ..files import get_h5_path_from_xml
 
 
@@ -49,7 +50,11 @@ def make_cell_tables(folder, name, tmp_folder, resolution,
     if not os.path.exists(aux_gene_path):
         raise RuntimeError("Can't find auxiliary gene file")
     gene_out = os.path.join(table_folder, 'genes.csv')
-    write_genes_table(seg_path, aux_gene_path, gene_out, label_ids)
+    # write_genes_table(seg_path, aux_gene_path, gene_out, label_ids)
+
+    # make table with morphology
+    morpho_out = os.path.join(table_folder, 'morphology.csv')
+    write_morphology_cells(seg_path, base_out, map_out, morpho_out)
 
     # TODO additional tables:
     # regions / semantics
@@ -71,10 +76,9 @@ def make_nucleus_tables(folder, name, tmp_folder, resolution,
                     tmp_folder, target=target, max_jobs=max_jobs,
                     correct_anchors=True)
 
-    # TODO do we need this for nuclei as well ?
-    # make table with mapping to other objects
-    # cells, ...
+    # make the morphology attribute table
+    morpho_out = os.path.join(table_folder, 'morphology.csv')
+    write_morphology_nuclei(seg_path, base_out, morpho_out)
 
     # TODO additional tables:
-    # kimberly's nucleus attributes
     # ???

test/attributes/test_base.py

+import unittest
+import sys
+import os
+import pandas
+import h5py
+from shutil import rmtree
+sys.path.append('../..')
+
+
+# check new version of gene mapping against original
+class TestGeneAttributes(unittest.TestCase):
+    tmp_folder = 'tmp'
+
+    def tearDown(self):
+        try:
+            rmtree(self.tmp_folder)
+        except OSError:
+            pass
+
+    def test_genes(self):
+        from scripts.attributes.base_attributes import base_attributes
+
+        input_path = '../../data/0.0.0/segmentations/em-segmented-nuclei-labels.h5'
+        input_key = 't00000/s00/0/cells'
+        output_path = os.path.join(self.tmp_folder, 'table-test.csv')
+        target = 'local'
+        max_jobs = 32
+        resolution = [0.1, 0.08, 0.08]
+        base_attributes(input_path, input_key, output_path, resolution,
+                        self.tmp_folder, target, max_jobs, correct_anchors=False)
+
+        table = pandas.read_csv(output_path, sep='\t')
+        print("Checking attributes ...")
+        with h5py.File(input_path, 'r') as f:
+            ds = f[input_key]
+            for row in table.itertuples(index=False):
+                label_id = int(row.label_id)
+                if label_id == 0:
+                    continue
+
+                # NOTE we increase the bounding box by 1 due to potential rounding artifacts
+                # check bounding box
+                bb_min = [row.bb_min_z, row.bb_min_y, row.bb_min_x]
+                bb_max = [row.bb_max_z, row.bb_max_y, row.bb_max_x]
+                bb = tuple(slice(int(min_ / res) - 1, int(max_ / res) + 2)
+                           for min_, max_, res in zip(bb_min, bb_max, resolution))
+                seg = ds[bb]
+
+                # TODO check anchor once we have anchor correction
+                # anchor = [row.anchor_z, row.anchor_y, row.anchor_x]
+                # anchor = tuple(anch // res - b.start for anch, res, b in zip(anchor, resolution, bb))
+                # anchor_id = seg[anchor]
+                # self.assertEqual(anchor_id, label_id)
+
+                label_mask = seg == label_id
+                n_pixels = label_mask.sum()
+                self.assertGreater(n_pixels, 0)
+
+                # check the pixel size
+                pixel_size = int(row.n_pixels)
+                self.assertEqual(pixel_size, n_pixels)
+
+
+if __name__ == '__main__':
+    unittest.main()