Adapt validation to sonata examples

bluepysnap/circuit_validation.py

@@ -2,6 +2,7 @@
 import itertools as it
 
 import numpy as np
+import pandas as pd
 import click
 from pathlib2 import Path
 import h5py
@@ -206,6 +207,38 @@ def _get_population_groups(population_h5):
             if isinstance(population_h5[name], h5py.Group) and name.isdigit()]
 
 
+def _nodes_group_to_dataframe(group, types_file, population):
+    """Transforms hdf5 population group to pandas DataFrame.
+
+    Args:
+        group: HDF5 nodes group
+        types_file: path to 'node_types_file' of Sonata config
+        population: HDF5 nodes population
+
+    Returns:
+        pd.DataFrame: dataframe with all group attributes
+    """
+    df = pd.DataFrame(population['node_type_id'], columns=['type_id'])
+    size = df.size
+    df['id'] = population['node_id'] if 'node_id' in population else np.arange(size)
+    df['group_id'] = population['node_group_id'] if 'node_group_id' in population else 0
+    df['group_index'] = population['node_group_index'] \
+        if 'node_group_index' in population else np.arange(size)
+    df = df[df['group_id'] == int(str(_get_group_name(group)))]
+    for k, v in group.items():
+        if isinstance(v, h5py.Dataset):
+            df[k] = v[:]
+    if '@library' in group:
+        for k, v in group['@library'].items():
+            if isinstance(v, h5py.Dataset):
+                df[k] = v[:][df[k].to_numpy(dtype=int)]
+    if types_file is None:
+        return df
+    types = pd.read_csv(types_file, sep=r'\s+')
+    types.rename(columns={types.columns[0]: 'type_id'}, inplace=True)
+    return pd.merge(df, types, on='type_id', how='left')
+
+
 def _get_group_size(group_h5):
     """Gets size of an edges or nodes group."""
     for name in group_h5:
@@ -236,10 +269,11 @@ def _check_multi_groups(group_id_h5, group_index_h5, population):
     return []
 
 
-def _check_bio_nodes_group(group, config):
+def _check_bio_nodes_group(group_df, group, config):
     """Checks biophysical nodes group for errors.
 
     Args:
+        group_df (pd.DataFrame): nodes group as a dataframe
         group (h5py.Group): nodes group in nodes .h5 file
         config (dict): resolved bluepysnap config
 
@@ -250,20 +284,21 @@ def _check_bio_nodes_group(group, config):
     def _check_rotations():
         """Checks for proper rotation fields."""
         angle_fields = {'rotation_angle_xaxis', 'rotation_angle_yaxis', 'rotation_angle_zaxis'}
-        has_angle_fields = len(angle_fields - set(group)) < len(angle_fields)
-        has_rotation_fields = 'orientation' in group or has_angle_fields
+        has_angle_fields = len(angle_fields - group_attrs) < len(angle_fields)
+        has_rotation_fields = 'orientation' in group_attrs or has_angle_fields
         if not has_rotation_fields:
             errors.append(Error(Error.WARNING, 'Group {} of {} has no rotation fields'.
                                 format(group_name, group.file.filename)))
         if not has_angle_fields:
             bbp_orient_fields = {'orientation_w', 'orientation_x', 'orientation_y', 'orientation_z'}
-            if 0 < len(bbp_orient_fields - set(group)) < len(bbp_orient_fields):
+            if 0 < len(bbp_orient_fields - group_attrs) < len(bbp_orient_fields):
                 errors.append(BbpError(Error.WARNING, 'Group {} of {} has no rotation fields'.
                                        format(group_name, group.file.filename)))
 
     errors = []
+    group_attrs = set(group_df.columns)
     group_name = _get_group_name(group, parents=1)
-    missing_fields = sorted({'morphology', 'x', 'y', 'z'} - set(group))
+    missing_fields = sorted({'morphology', 'x', 'y', 'z'} - group_attrs)
     if missing_fields:
         errors.append(fatal('Group {} of {} misses biophysical fields: {}'.
                             format(group_name, group.file.filename, missing_fields)))
@@ -273,52 +308,37 @@ def _check_rotations():
     errors += _check_components_dir('biophysical_neuron_models_dir', components)
     if errors:
         return errors
-    morph_files = group['morphology'] if _get_h5_data(group, '@library/morphology') is None \
-        else group['@library/morphology']
     errors += _check_files(
         'morphology: {}[{}]'.format(group_name, group.file.filename),
-        (Path(components['morphologies_dir'], m + '.swc') for m in morph_files),
+        (Path(components['morphologies_dir'], m + '.swc') for m in group_df['morphology']),
         Error.WARNING)
-    bio_files = group['model_template'] if _get_h5_data(group, '@library/model_template') is None \
-        else group['@library/model_template']
     bio_path = Path(components['biophysical_neuron_models_dir'])
     errors += _check_files(
         'model_template: {}[{}]'.format(group_name, group.file.filename),
-        (bio_path / _get_model_template_file(m) for m in bio_files),
+        (bio_path / _get_model_template_file(m) for m in group_df['model_template']),
         Error.WARNING)
     return errors
 
 
-def _is_biophysical(group):
-    """Check if a group contains biophysical nodes."""
-    if group['model_type'][0] == 'biophysical':
-        return True
-    if "@library/model_type" in group:
-        model_type_int = group['model_type'][0]
-        model_type = group["@library/model_type"][model_type_int]
-        if six.ensure_str(model_type) == 'biophysical':
-            return True
-    return False
-
-
-def _check_nodes_group(group, config):
+def _check_nodes_group(group_df, group, config):
     """Validates nodes group in nodes population.
 
     Args:
+        group_df (pd.DataFrame): nodes group in nodes .h5 file
         group (h5py.Group): nodes group in nodes .h5 file
         config (dict): resolved bluepysnap config
 
     Returns:
         list: List of errors, empty if no errors
     """
     REQUIRED_GROUP_NAMES = ['model_type', 'model_template']
-    missing_fields = sorted(set(REQUIRED_GROUP_NAMES) - set(group))
+    missing_fields = sorted(set(REQUIRED_GROUP_NAMES) - set(group_df.columns.tolist()))
     if missing_fields:
         return [fatal('Group {} of {} misses required fields: {}'
                       .format(_get_group_name(group, parents=1), group.file.filename,
                               missing_fields))]
-    elif _is_biophysical(group):
-        return _check_bio_nodes_group(group, config)
+    elif group_df['model_type'][0] == 'biophysical':
+        return _check_bio_nodes_group(group_df, group, config)
     return []
 
 
@@ -335,25 +355,28 @@ def _check_nodes_population(nodes_dict, config):
     required_datasets = ['node_type_id']
     errors = []
     nodes_file = nodes_dict.get('nodes_file')
+    node_types_file = nodes_dict.get('node_types_file', None)
     with h5py.File(nodes_file, 'r') as h5f:
         nodes = _get_h5_data(h5f, 'nodes')
         if not nodes or len(nodes) == 0:
-            errors.append(fatal('No "nodes" in {}.'.format(nodes_file)))
-            return errors
+            return [fatal('No "nodes" in {}.'.format(nodes_file))]
         for population_name in nodes:
             population = nodes[population_name]
             groups = _get_population_groups(population)
             if len(groups) > 1:
                 required_datasets += ['node_group_id', 'node_group_index']
             missing_datasets = sorted(set(required_datasets) - set(population))
             if missing_datasets:
-                errors.append(fatal('Population {} of {} misses datasets {}'.
-                                    format(population_name, nodes_file, missing_datasets)))
-            elif 'node_group_id' in population:
-                errors += _check_multi_groups(
-                    population['node_group_id'], population['node_group_index'], population)
+                return [fatal('Population {} of {} misses datasets {}'.
+                              format(population_name, nodes_file, missing_datasets))]
+            if len(groups) > 1:
+                m_errors = _check_multi_groups(population['node_group_id'],
+                                               population['node_group_index'], population)
+                if len(m_errors) > 0:
+                    return m_errors
             for group in groups:
-                errors += _check_nodes_group(group, config)
+                group_df = _nodes_group_to_dataframe(group, node_types_file, population)
+                errors += _check_nodes_group(group_df, group, config)
     return errors
 
 
@@ -417,7 +440,7 @@ def _check_edges_node_ids(nodes_ds, nodes):
         list: List of errors, empty if no errors
     """
     errors = []
-    node_population_name = nodes_ds.attrs['node_population']
+    node_population_name = six.ensure_str(nodes_ds.attrs['node_population'])
     nodes_dict = _find_nodes_population(node_population_name, nodes)
     if not nodes_dict:
         errors.append(fatal('No node population for "{}"'.format(nodes_ds.name)))

tests/data/circuit_config.json

@@ -13,7 +13,7 @@
     "nodes": [
       {
         "nodes_file": "$NETWORK_DIR/nodes.h5",
-        "node_types_file": null
+        "node_types_file": "$NETWORK_DIR/node_types.csv"
       }
     ],
     "edges": [

tests/data/node_types.csv

@@ -0,0 +1,2 @@
+node_type_id model_processing
+1 perisomatic

tests/test_circuit.py

@@ -18,7 +18,7 @@ def test_all():
             circuit.config['networks']['nodes'][0] ==
             {
                 'nodes_file': str(TEST_DATA_DIR / 'nodes.h5'),
-                'node_types_file': None,
+                'node_types_file': str(TEST_DATA_DIR / 'node_types.csv'),
             }
     )
     assert isinstance(circuit.nodes, dict)

tests/test_circuit_validation.py

@@ -37,6 +37,12 @@ def test_ok_circuit():
     errors = test_module.validate(str(TEST_DATA_DIR / 'circuit_config.json'))
     assert errors == []
 
+    with copy_circuit() as (_, config_copy_path):
+        with edit_config(config_copy_path) as config:
+            config['networks']['nodes'][0]['node_types_file'] = None
+        errors = test_module.validate(str(config_copy_path))
+        assert errors == []
+
 
 def test_no_config_components():
     with copy_circuit() as (_, config_copy_path):
@@ -163,6 +169,17 @@ def test_no_required_node_multi_group_datasets():
                                     format(nodes_file, [ds]))]
 
 
+def test_nodes_multi_group_wrong_group_id():
+    with copy_circuit() as (circuit_copy_path, config_copy_path):
+        nodes_file = circuit_copy_path / 'nodes.h5'
+        with h5py.File(nodes_file, 'r+') as h5f:
+            h5f.copy('nodes/default/0', 'nodes/default/1')
+            h5f['nodes/default/node_group_id'][-1] = 2
+        errors = test_module.validate(str(config_copy_path))
+        assert errors == [Error(Error.FATAL, 'Population /nodes/default of {} misses group(s): {}'.
+                                format(nodes_file, {2}))]
+
+
 def test_no_required_node_group_datasets():
     required_datasets = ['model_template', 'model_type']
     with copy_circuit() as (circuit_copy_path, config_copy_path):
@@ -230,8 +247,9 @@ def test_no_rotation_bbp_node_group_datasets():
         nodes_file = circuit_copy_path / 'nodes.h5'
         with h5py.File(nodes_file, 'r+') as h5f:
             for ds in angle_datasets:
+                shape = h5f['nodes/default/0/' + ds].shape
                 del h5f['nodes/default/0/' + ds]
-            h5f['nodes/default/0/orientation_w'] = 0
+            h5f['nodes/default/0/'].create_dataset('orientation_w', shape, fillvalue=0)
         errors = test_module.validate(str(config_copy_path), bbp_check=True)
         assert errors == [
             Error(Error.WARNING, 'Group default/0 of {} has no rotation fields'.format(nodes_file)),
@@ -538,8 +556,6 @@ def test_no_edge_all_node_ids():
             del h5f['nodes/default/0']
         errors = test_module.validate(str(config_copy_path))
         assert errors == [
-            Error(Error.FATAL, 'Population /nodes/default of {} misses group(s): {}'.
-                  format(nodes_file, {0})),
             Error(Error.FATAL,
                   '/edges/default/source_node_id does not have node ids in its node population'),
             Error(Error.FATAL,