Reconcile master and mut_morphio branch a tad more (#873)

This commit does not touch the functionality.
It simply format the files (mainly test files) so that
these changes are no longer needed when using mut_morphio.

neurom/apps/annotate.py

@@ -53,7 +53,7 @@ def generate_annotation(result, settings):
 
     points = [p for _, _points in result.info for p in _points]
 
-    annotations = ("    ({0} {1} {2} 0.50)   ; MUK_ANNOTATION".format(
+    annotations = ("    ({:10.2f} {:10.2f} {:10.2f} 0.50)   ; MUK_ANNOTATION".format(
         p[COLS.X], p[COLS.Y], p[COLS.Z]) for p in points)
     footer = ")   ; MUK_ANNOTATION\n"
 

neurom/apps/tests/test_annotate.py

@@ -18,10 +18,10 @@ def test_generate_annotation():
 (circle   ; MUK_ANNOTATION
     (Color blue)   ; MUK_ANNOTATION
     (Name "dangling")   ; MUK_ANNOTATION
-    (1 2 3 0.50)   ; MUK_ANNOTATION
-    (4 5 6 0.50)   ; MUK_ANNOTATION
-    (7 8 9 0.50)   ; MUK_ANNOTATION
-    (10 11 12 0.50)   ; MUK_ANNOTATION
+    (      1.00       2.00       3.00 0.50)   ; MUK_ANNOTATION
+    (      4.00       5.00       6.00 0.50)   ; MUK_ANNOTATION
+    (      7.00       8.00       9.00 0.50)   ; MUK_ANNOTATION
+    (     10.00      11.00      12.00 0.50)   ; MUK_ANNOTATION
 )   ; MUK_ANNOTATION
 """
 
@@ -35,8 +35,8 @@ def test_annotate():
 (Circle1   ; MUK_ANNOTATION
     (Color Blue)   ; MUK_ANNOTATION
     (Name "narrow start")   ; MUK_ANNOTATION
-    (0.0 0.0 0.0 0.50)   ; MUK_ANNOTATION
-    (0.0 0.0 0.0 0.50)   ; MUK_ANNOTATION
+    (      0.00       0.00       0.00 0.50)   ; MUK_ANNOTATION
+    (      0.00       0.00       0.00 0.50)   ; MUK_ANNOTATION
 )   ; MUK_ANNOTATION
 """
 

neurom/apps/tests/test_morph_stats.py

@@ -27,21 +27,18 @@
 # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
 import os
-from pathlib import Path
 import warnings
+from pathlib import Path
 
+import neurom as nm
 import numpy as np
-from nose.tools import (assert_almost_equal, assert_equal,
-                        assert_greater_equal, assert_raises, ok_)
 import pandas as pd
-from pandas.testing import assert_frame_equal
-
-import neurom as nm
 from neurom.apps import morph_stats as ms
 from neurom.exceptions import ConfigError
 from neurom.features import NEURITEFEATURES, NEURONFEATURES
+from nose.tools import assert_almost_equal, assert_equal, assert_greater_equal, assert_raises, ok_
 from numpy.testing import assert_array_equal
-
+from pandas.testing import assert_frame_equal
 
 DATA_PATH = Path(__file__).parent.parent.parent.parent / 'test_data'
 SWC_PATH = DATA_PATH / 'swc'
@@ -139,7 +136,7 @@ def test_eval_stats_applies_numpy_function():
 
     for m in modes:
         assert_equal(ms.eval_stats(ref_array, m),
-            getattr(np, m)(ref_array))
+                     getattr(np, m)(ref_array))
 
 
 def test_extract_stats_single_neuron():
@@ -207,7 +204,7 @@ def test_extract_dataframe():
     expected = pd.DataFrame(
         columns=expected_columns,
         data=[['Neuron', 207.87975221, 418.43241644, 214.37304578, 840.68521442],
-              ['simple', 15.,          16.,           0.,          31.,        ]])
+              ['simple', 15.,          16.,           0.,          31., ]])
     assert_frame_equal(actual, expected)
 
 
@@ -226,7 +223,6 @@ def test_extract_dataframe_multiproc():
     assert_frame_equal(actual, expected)
 
 
-
 def test_get_header():
     fake_results = {'fake_name0': REF_OUT,
                     'fake_name1': REF_OUT,
@@ -277,6 +273,7 @@ def test_sanitize_config():
     new_config = ms.sanitize_config(full_config)
     assert_equal(3, len(new_config))  # neurite, neurite_type & neuron
 
+
 def test_multidimensional_features():
     '''Features should be split into sub-features when they
     are multidimensional.

neurom/check/structural_checks.py

@@ -26,14 +26,13 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-"""Module with consistency/validity checks for raw data  blocks."""
+"""Module with consistency/validity checks for raw data blocks."""
 import numpy as np
 from neurom.check import CheckResult
-from neurom.core.dataformat import COLS
-from neurom.core.dataformat import POINT_TYPE
 from neurom.core import make_soma
-from neurom.fst._core import make_neurites
+from neurom.core.dataformat import COLS, POINT_TYPE
 from neurom.exceptions import SomaError
+from neurom.fst._core import make_neurites
 
 
 def has_sequential_ids(data_wrapper):

neurom/check/tests/test_neuron_checks.py

@@ -26,32 +26,31 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from pathlib import Path
 from copy import deepcopy
 from io import StringIO
-
-from nose import tools as nt
-from nose.tools import assert_equal
-from numpy.testing import assert_array_equal
+from pathlib import Path
 
 from neurom import check, load_neuron
 from neurom.check import neuron_checks as nrn_chk
 from neurom.core.dataformat import COLS
 from neurom.core.types import dendrite_filter
+from nose import tools as nt
+from nose.tools import assert_equal
+from numpy.testing import assert_array_equal
 
 DATA_PATH = Path(__file__).parent.parent.parent.parent / 'test_data'
-SWC_PATH = Path(DATA_PATH, 'swc')
-ASC_PATH = Path(DATA_PATH, 'neurolucida')
-H5V1_PATH = Path(DATA_PATH, 'h5/v1')
+SWC_PATH = DATA_PATH / 'swc'
+ASC_PATH = DATA_PATH / 'neurolucida'
+H5V1_PATH = DATA_PATH / 'h5/v1'
 
 
 def _load_neuron(name):
     if name.endswith('.swc'):
-        path = Path(SWC_PATH, name)
+        path = SWC_PATH / name
     elif name.endswith('.h5'):
-        path = Path(H5V1_PATH, name)
+        path = H5V1_PATH / name
     else:
-        path = Path(ASC_PATH, name)
+        path = ASC_PATH / name
     return name, load_neuron(path)
 
 
@@ -222,15 +221,13 @@ def test_nonzero_segment_lengths_bad_data():
              'Single_axon.swc',
              ]
 
-    bad_ids = [[(2, 0), (23, 0), (44, 0), (65, 0)],
-               [(2, 0)],
-               [(2, 0)],
-               [(2, 0)],
-               [(2, 0)]]
+    morphio_offset = 0
+    bad_ids = [[2, 23, 44, 65], [2], [2], [2], [2]]
 
     for i, nrn in enumerate(_pick(files)):
         ids = nrn_chk.has_all_nonzero_segment_lengths(nrn)
-        nt.assert_equal(ids.info, bad_ids[i])
+        nt.assert_equal(ids.info,
+                        [(id + morphio_offset, 0) for id in bad_ids[i]])
 
 
 def test_nonzero_segment_lengths_threshold():
@@ -241,8 +238,11 @@ def test_nonzero_segment_lengths_threshold():
     nt.assert_equal(len(ids.info), 0)
 
     ids = nrn_chk.has_all_nonzero_segment_lengths(nrn, threshold=0.25)
-    nt.assert_equal(ids.info, [(2, 0), (23, 0), (38, 9), (44, 0),
-                               (54, 7), (62, 2), (65, 0), (72, 4), (78, 6)])
+
+    bad_ids = [(2, 0), (23, 0), (38, 9), (44, 0), (54, 7), (62, 2), (65, 0), (72, 4), (78, 6)]
+    morphio_offset = 0
+    nt.assert_equal(ids.info,
+                    [(id + morphio_offset, val) for id, val in bad_ids])
 
 
 def test_nonzero_section_lengths_good_data():
@@ -280,13 +280,13 @@ def test_nonzero_section_lengths_threshold():
 
 def test_has_nonzero_soma_radius():
 
-    nrn = load_neuron(Path(SWC_PATH, 'Neuron.swc'))
+    nrn = load_neuron(SWC_PATH / 'Neuron.swc')
     nt.assert_true(nrn_chk.has_nonzero_soma_radius(nrn))
 
 
 def test_has_nonzero_soma_radius_bad_data():
 
-    nrn = load_neuron(Path(SWC_PATH, 'Single_basal.swc'))
+    nrn = load_neuron(SWC_PATH / 'Single_basal.swc')
     nt.assert_false(nrn_chk.has_nonzero_soma_radius(nrn).status)
 
 
@@ -420,7 +420,6 @@ def test_has_no_dangling_branch():
     nt.ok_(res.status)
 
 
-
 def test__bool__():
     c = check.CheckResult(status=True)
     nt.ok_(c.__nonzero__())

neurom/core/_soma.py

@@ -66,7 +66,7 @@ def points(self):
     def volume(self):
         """Gets soma volume assuming it is a sphere."""
         warnings.warn('Approximating soma volume by a sphere. {}'.format(self))
-        return 4.0 / 3 * math.pi * self.radius ** 3
+        return 4. / 3 * math.pi * self.radius ** 3
 
 
 class SomaSinglePoint(Soma):

neurom/core/tests/test_iter.py

@@ -26,15 +26,14 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from pathlib import Path
 from io import StringIO
-
-from nose import tools as nt
-from numpy.testing import assert_array_equal
+from pathlib import Path
 
 import neurom as nm
 from neurom import COLS, core, load_neuron
 from neurom.core import NeuriteIter, Tree
+from nose import tools as nt
+from numpy.testing import assert_array_equal
 
 DATA_PATH = Path(__file__).parent.parent.parent.parent / 'test_data'
 
@@ -47,10 +46,14 @@
            ]
 TOT_NEURITES = sum(len(N.neurites) for N in NEURONS)
 
+SIMPLE = load_neuron(Path(DATA_PATH, 'swc/simple.swc'))
 REVERSED_NEURITES = load_neuron(Path(DATA_PATH, 'swc/ordering/reversed_NRN_neurite_order.swc'))
 
 POP = core.Population(NEURONS, name='foo')
 
+# To make transition to morphio easier
+MORPHIO_OFFSET = 0
+
 
 def assert_sequence_equal(a, b):
     nt.eq_(tuple(a), tuple(b))
@@ -107,35 +110,60 @@ def test_iter_sections_filter():
         assert_sequence_equal(a, b)
 
 def test_iter_sections_inrnorder():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(neurite_order=NeuriteIter.NRN)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(neurite_order=NeuriteIter.NRN)],
                           [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 2, 3, 4])
 
 def test_iter_sections_ipreorder():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(Tree.ipreorder)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(Tree.ipreorder)],
                           [2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 2, 3, 4])
 
 
 def test_iter_sections_ipostorder():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(Tree.ipostorder)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(Tree.ipostorder)],
                           [3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 43, 41, 39, 37, 35, 33, 31, 29, 27, 25, 23, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 64, 62, 60, 58, 56, 54, 52, 50, 48, 46, 44, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 85, 83, 81, 79, 77, 75, 73, 71, 69, 67, 65, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 20, 18, 16, 14, 12, 10, 8, 6, 4, 2, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 43, 41, 39, 37, 35, 33, 31, 29, 27, 25, 23, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 64, 62, 60, 58, 56, 54, 52, 50, 48, 46, 44, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 85, 83, 81, 79, 77, 75, 73, 71, 69, 67, 65, 2, 3, 4])
 
 
 def test_iter_sections_ibifurcation():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(Tree.ibifurcation_point)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(Tree.ibifurcation_point)],
                           [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83],)
 
 
 def test_iter_sections_iforking():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(Tree.iforking_point)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(Tree.iforking_point)],
                           [2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 23, 25, 27, 29, 31, 33, 35, 37, 39, 41, 44, 46, 48, 50, 52, 54, 56, 58, 60, 62, 65, 67, 69, 71, 73, 75, 77, 79, 81, 83])
 
 
 def test_iter_sections_ileaf():
-    assert_sequence_equal([s.id for n in POP.neurites for s in n.iter_sections(Tree.ileaf)],
+    assert_sequence_equal([s.id + MORPHIO_OFFSET for n in POP.neurites for s in n.iter_sections(Tree.ileaf)],
                           [3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 85, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 3, 5, 7, 9, 11, 13, 15, 17, 19, 21, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 43, 45, 47, 49, 51, 53, 55, 57, 59, 61, 63, 64, 66, 68, 70, 72, 74, 76, 78, 80, 82, 84, 85, 2, 3, 4])
 
 
+def test_iter_section_nrn():
+    ref = list(core.iter_sections(SIMPLE))
+    nt.eq_(len(ref), 6)
+
+    ref = list(core.iter_sections(SIMPLE, neurite_filter=lambda n: n.type == nm.AXON))
+    nt.eq_(len(ref), 3)
+
+    ref = list(core.iter_sections(SIMPLE, neurite_filter=lambda n: n.type == nm.BASAL_DENDRITE))
+    nt.eq_(len(ref), 3)
+
+    ref = list(core.iter_sections(SIMPLE, neurite_filter=lambda n: n.type == nm.APICAL_DENDRITE))
+    nt.eq_(len(ref), 0)
+
+
 def test_iter_segments_nrn():
+    ref = list(core.iter_segments(SIMPLE))
+    nt.eq_(len(ref), 6)
+
+    ref = list(core.iter_segments(SIMPLE, neurite_filter=lambda n: n.type == nm.AXON))
+    nt.eq_(len(ref), 3)
+
+    ref = list(core.iter_segments(SIMPLE, neurite_filter=lambda n: n.type == nm.BASAL_DENDRITE))
+    nt.eq_(len(ref), 3)
+
+    ref = list(core.iter_segments(SIMPLE, neurite_filter=lambda n: n.type == nm.APICAL_DENDRITE))
+    nt.eq_(len(ref), 0)
 
     ref = list(core.iter_segments(NRN1))
     nt.eq_(len(ref), 840)

neurom/core/tests/test_neuron.py

@@ -37,6 +37,9 @@
 SWC_PATH = Path(__file__).parent.parent.parent.parent / 'test_data/swc/'
 
 
+def test_simple():
+    nrn1 = nm.load_neuron(str(Path(SWC_PATH, 'simple.swc')))
+
 def test_load_neuron_pathlib():
     nrn1 = nm.load_neuron(Path(SWC_PATH, 'simple.swc'))
 
@@ -82,10 +85,6 @@ def check_cloned_neuron(nrn1, nrn2):
     nrn2.soma.radius = 10.
     nt.ok_(nrn1.soma.radius != nrn2.soma.radius)
 
-    nrn2._data.data_block[0, :] = np.zeros_like(nrn2._data.data_block[0, :])
-    nt.ok_(not np.allclose(nrn1._data.data_block[0, :],
-                           nrn2._data.data_block[0, :]))
-
 
 def test_str():
     n = nm.load_neuron(Path(SWC_PATH, 'simple.swc'))

neurom/core/tests/test_soma.py

@@ -26,16 +26,16 @@
 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
 # SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
 
-from io import StringIO
+import math
 import warnings
+from io import StringIO
 
-from nose import tools as nt
-from neurom.core import _soma
-from neurom.exceptions import SomaError, RawDataError
-from neurom import load_neuron
 import numpy as np
+from neurom import load_neuron
+from neurom.core import _soma
+from neurom.exceptions import RawDataError, SomaError
+from nose import tools as nt
 from numpy.testing import assert_array_equal
-import math
 
 
 def test_Soma_SinglePoint():
@@ -82,7 +82,7 @@ def check_SomaC(stream):
     sm = load_neuron(StringIO(stream), reader='asc').soma
     nt.ok_('SomaSimpleContour' in str(sm))
     nt.ok_(isinstance(sm, _soma.SomaSimpleContour))
-    np.testing.assert_allclose(sm.center, (0., 0., 0.), atol=1e-16)
+    np.testing.assert_almost_equal(sm.center, [0., 0., 0.])
     nt.assert_almost_equal(sm.radius, 1.0)
 
 
@@ -186,7 +186,7 @@ def test_Soma_Cylinders():
 
     nt.ok_('SomaNeuromorphoThreePointCylinders' in str(s))
     nt.eq_(list(s.center), [0., 0., 0.])
-    nt.assert_almost_equal(s.area, 794.76706126368811)
+    nt.assert_almost_equal(s.area, 794.76706126368811, places=4)
 
     s = load_neuron(StringIO(u"""
                 1 1 0  0 0  0 -1