From 36796d675f91fb4637a8530f7e89bfaa319fd02e Mon Sep 17 00:00:00 2001
From: Constantin Pape <constantin.pape@iwr.uni-heidelberg.de>
Date: Fri, 21 Jun 2019 21:52:55 +0200
Subject: [PATCH] Add test for region attributes
---
test/attributes/test_regions.py | 124 ++++++++++++++++++++++++++++++++
1 file changed, 124 insertions(+)
create mode 100644 test/attributes/test_regions.py
diff --git a/test/attributes/test_regions.py b/test/attributes/test_regions.py
new file mode 100644
index 0000000..66209d6
--- /dev/null
+++ b/test/attributes/test_regions.py
@@ -0,0 +1,124 @@
+import unittest
+import sys
+import os
+import json
+from shutil import rmtree
+
+import numpy as np
+import pandas
+import h5py
+from cluster_tools.node_labels import NodeLabelWorkflow
+sys.path.append('../..')
+
+
+# check new version of gene mapping against original
+class TestRegions(unittest.TestCase):
+ tmp_folder = 'tmp'
+
+ def tearDown(self):
+ try:
+ rmtree(self.tmp_folder)
+ except OSError:
+ pass
+
+ def check_result(self, table, base_table,
+ seg_path, seg_key,
+ tissue_path, tissue_key):
+
+ resolution = [.1, .08, .08]
+
+ with h5py.File(seg_path, 'r') as fseg, h5py.File(tissue_path, 'r') as ftis:
+ ds_seg = fseg[seg_key]
+ ds_tis = ftis[tissue_key]
+ assert ds_seg.shape == ds_tis.shape, "%s, %s" % (str(ds_seg.shape),
+ str(ds_tis.shape))
+
+ names = ftis['semantic_names'][:]
+ mapped_ids = ftis['semantic_mapping'][:]
+
+ for name, tis_ids in zip(names, mapped_ids):
+
+ # these are too big
+ if name in ('cuticle', 'neuropil'):
+ continue
+ print("Checking", name)
+
+ col = table[name].values
+ seg_ids = np.where(col == 1.)[0]
+ for seg_id in seg_ids:
+ row = base_table.iloc[seg_id]
+ bb_start = [row.bb_min_z, row.bb_min_y, row.bb_min_x]
+ bb_stop = [row.bb_max_z, row.bb_max_y, row.bb_max_x]
+ bb = tuple(slice(int(mi / re), int(ma / re))
+ for mi, ma, re in zip(bb_start, bb_stop, resolution))
+
+ seg = ds_seg[bb]
+ tis = ds_tis[bb]
+
+ seg_mask = seg == seg_id
+ self.assertGreater(np.in1d(tis[seg_mask], tis_ids).sum(), 0)
+
+ def test_regions(self):
+ from scripts.attributes.region_attributes import region_attributes
+
+ segmentation_folder = '../../data/0.0.0/segmentations'
+ seg_path = os.path.join(segmentation_folder,
+ 'sbem-6dpf-1-whole-segmented-cells-labels.h5')
+ seg_key = 't00000/s00/0/cells'
+ with h5py.File(seg_path, 'r') as f:
+ max_id = f[seg_key].attrs['maxId']
+
+ output_path = os.path.join(self.tmp_folder, 'table-test.csv')
+ label_ids = np.arange(max_id + 1, dtype='uint64')
+
+ # write the global config
+ config_folder = os.path.join(self.tmp_folder, 'configs')
+ os.makedirs(config_folder, exist_ok=True)
+ conf = NodeLabelWorkflow.get_config()['global']
+ shebang = '#! /g/kreshuk/pape/Work/software/conda/miniconda3/envs/cluster_env37/bin/python'
+ conf.update({'shebang': shebang})
+ with open(os.path.join(config_folder, 'global.config'), 'w') as f:
+ json.dump(conf, f)
+
+ target = 'local'
+ max_jobs = 32
+ region_attributes(seg_path, output_path, segmentation_folder,
+ label_ids, self.tmp_folder, target, max_jobs)
+
+ table = pandas.read_csv(output_path, sep='\t')
+ assert len(table) == max_id + 1
+
+ base_path = '../../data/0.0.0/tables/sbem-6dpf-1-whole-segmented-cells-labels/default.csv'
+ base_table = pandas.read_csv(base_path, sep='\t')
+
+ seg_key = 't00000/s00/2/cells'
+ tissue_path = '../../data/rawdata/sbem-6dpf-1-whole-segmented-tissue-labels.h5'
+ tissue_key = 't00000/s00/0/cells'
+ self.check_result(table, base_table,
+ seg_path, seg_key,
+ tissue_path, tissue_key)
+
+
+# this indeed fails for the glands, whereas the unittest above passes
+def check_external():
+ t = TestRegions()
+
+ base_table_path = '/g/arendt/EM_6dpf_segmentation/EM-Prospr/tables/em-segmented-cells-20190520-labels.csv'
+ base_table = pandas.read_csv(base_table_path, sep='\t')
+
+ table_path = '/g/kreshuk/pape/Work/my_projects/py_platy_browser/experiments/segmentation/tissue/regions.csv'
+ table = pandas.read_csv(table_path, sep='\t')
+
+ seg_path = '/g/arendt/EM_6dpf_segmentation/EM-Prospr/em-segmented-cells-20190520-labels.h5'
+ tissue_path = '/g/arendt/EM_6dpf_segmentation/EM-Prospr/em-segmented-tissue-labels.h5'
+ seg_key = 't00000/s00/2/cells'
+ tissue_key = 't00000/s00/0/cells'
+
+ t.check_result(table, base_table,
+ seg_path, seg_key,
+ tissue_path, tissue_key)
+
+
+if __name__ == '__main__':
+ # check_external()
+ unittest.main()
--
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