Propagate changes from libsonata ElementReport

bluepysnap/_plotting.py

@@ -23,6 +23,7 @@
 from bluepysnap.sonata_constants import Node
 from bluepysnap.utils import roundrobin
 
+
 L = logging.getLogger(__name__)
 
 
@@ -359,9 +360,13 @@ def frame_trace(filtered_report, plot_type='mean', ax=None):  # pragma: no cover
     elif plot_type == "all":
         max_per_pop = 15
         levels = filtered_report.report.columns.levels
-        slicer = tuple(slice(None) if i != len(levels) - 1 else slice(None, max_per_pop)
-                       for i in range(len(levels)))
-        data = filtered_report.report.loc[:, slicer].T
+        slicer = []
+        # create a slicer that will slice only on the last level of the columns
+        # that is, node_id for the soma report, element_id for the compartment report
+        for i, _ in enumerate(levels):
+            max_ = levels[i][:max_per_pop][-1]
+            slicer.append(slice(None) if i != len(levels) - 1 else slice(None, max_))
+        data = filtered_report.report.loc[:, tuple(slicer)].T
         # create [[(pop1, id1), (pop1, id2),...], [(pop2, id1), (pop2, id2),...]]
         indexes = [[(pop, idx) for idx in data.loc[pop].index] for pop in levels[0]]
         # try to keep the maximum of ids from each population

bluepysnap/frame_report.py

@@ -21,15 +21,14 @@
 from pathlib2 import Path
 import numpy as np
 import pandas as pd
-from libsonata import ElementReportReader
+from libsonata import ElementReportReader, SonataError
 
 import bluepysnap._plotting
 from bluepysnap.exceptions import BluepySnapError
-from bluepysnap.utils import fix_libsonata_empty_list, ensure_list
+from bluepysnap.utils import ensure_list
 
 L = logging.getLogger(__name__)
 
-
 FORMAT_TO_EXT = {"ASCII": ".txt", "HDF5": ".h5", "BIN": ".bbp"}
 
 
@@ -98,22 +97,36 @@ def get(self, group=None, t_start=None, t_stop=None):
         Returns:
             pandas.DataFrame: frame as columns indexed by timestamps.
         """
-        ids = [] if group is None else self._resolve(group).tolist()
-        t_start = -1 if t_start is None else t_start
-        t_stop = -1 if t_stop is None else t_stop
+        ids = self._resolve(group).tolist()
+        try:
+            view = self._frame_population.get(node_ids=ids, tstart=t_start, tstop=t_stop)
+        except SonataError as e:
+            raise BluepySnapError(e)
 
-        view = self._frame_population.get(node_ids=ids, tstart=t_start, tstop=t_stop)
-        if not view.data:
+        if len(view.ids) == 0:
             return pd.DataFrame()
-        res = pd.DataFrame(data=view.data, index=view.index)
+
+        res = pd.DataFrame(data=view.data,
+                           columns=pd.MultiIndex.from_arrays(np.asarray(view.ids).T),
+                           index=view.times).sort_index(axis=1)
+
         # rename from multi index to index cannot be achieved easily through df.rename
         res.columns = self._wrap_columns(res.columns)
-        res.sort_index(inplace=True)
         return res
 
+    @cached_property
+    def node_ids(self):
+        """Returns the node ids present in the report.
+
+        Returns:
+            np.Array: Numpy array containing the node_ids included in the report
+        """
+        return np.sort(np.asarray(self._frame_population.get_node_ids(), dtype=np.int64))
+
 
 class FilteredFrameReport(object):
     """Access to filtered FrameReport data."""
+
     def __init__(self, frame_report, group=None, t_start=None, t_stop=None):
         """Initialize a FilteredFrameReport.
 
@@ -237,7 +250,7 @@ def simulation(self):
     @cached_property
     def population_names(self):
         """Returns the population names included in this report."""
-        return sorted(self._frame_reader.get_populations_names())
+        return sorted(self._frame_reader.get_population_names())
 
     @cached_property
     def _population_report(self):
@@ -282,8 +295,6 @@ def nodes(self):
 
     def _resolve(self, group):
         """Transform a group into a node_id array."""
-        if isinstance(group, (np.ndarray, list, tuple)) and len(group) == 0:
-            return fix_libsonata_empty_list()
         return self.nodes.ids(group=group)
 
 

bluepysnap/nodes.py

@@ -505,7 +505,7 @@ def positions(self, group=None):
         return result.astype(float)
 
     def orientations(self, group=None):
-        """Node orientation(s) as a pandas Series or DataFrame.
+        """Node orientation(s) as a pandas numpy array or pandas Series.
 
         Args:
             group (int/sequence/str/mapping/None): Which nodes will have their positions

bluepysnap/spike_report.py

@@ -22,14 +22,13 @@
 from cached_property import cached_property
 import pandas as pd
 import numpy as np
+from libsonata import SpikeReader, SonataError
 
 from bluepysnap.exceptions import BluepySnapError
-from bluepysnap.utils import fix_libsonata_empty_list
 import bluepysnap._plotting
 
 
 def _get_reader(spike_report):
-    from libsonata import SpikeReader
     path = str(Path(spike_report.config["output_dir"]) / spike_report.config["spikes_file"])
     return SpikeReader(path)
 
@@ -86,8 +85,6 @@ def nodes(self):
 
     def _resolve_nodes(self, group):
         """Transform a node group into a node_id array."""
-        if isinstance(group, (np.ndarray, list, tuple)) and len(group) == 0:
-            return fix_libsonata_empty_list()
         return self.nodes.ids(group=group)
 
     def get(self, group=None, t_start=None, t_stop=None):
@@ -101,23 +98,35 @@ def get(self, group=None, t_start=None, t_stop=None):
         Returns:
             pandas.Series: return spiking node_ids indexed by sorted spike time.
         """
-        node_ids = [] if group is None else self._resolve_nodes(group).tolist()
+        node_ids = self._resolve_nodes(group).tolist()
 
-        t_start = -1 if t_start is None else t_start
-        t_stop = -1 if t_stop is None else t_stop
         series_name = "ids"
-        res = self._spike_population.get(node_ids=node_ids, tstart=t_start, tstop=t_stop)
+        try:
+            res = self._spike_population.get(node_ids=node_ids, tstart=t_start, tstop=t_stop)
+        except SonataError as e:
+            raise BluepySnapError(e)
+
         if not res:
             return pd.Series(data=[], index=pd.Index([], name="times"), name=series_name)
 
         res = pd.DataFrame(data=res, columns=[series_name, "times"]).set_index("times")[series_name]
         if self._sorted_by != "by_time":
             res.sort_index(inplace=True)
-        return res
+        return res.astype(np.int64)
+
+    @cached_property
+    def node_ids(self):
+        """Returns the node ids present in the report.
+
+        Returns:
+            np.Array: Numpy array containing the node_ids included in the report
+        """
+        return np.unique(self.get())
 
 
 class FilteredSpikeReport(object):
     """Access to filtered SpikeReport data."""
+
     def __init__(self, spike_report, group=None, t_start=None, t_stop=None):
         """Initialize a FilteredSpikeReport.
 
@@ -227,7 +236,7 @@ def _spike_reader(self):
     @cached_property
     def population_names(self):
         """Returns the population names included in this report."""
-        return sorted(self._spike_reader.get_populations_names())
+        return sorted(self._spike_reader.get_population_names())
 
     @cached_property
     def _population(self):

bluepysnap/utils.py

@@ -72,14 +72,6 @@ def roundrobin(*iterables):
             nexts = itertools.cycle(itertools.islice(nexts, num_active))
 
 
-def fix_libsonata_empty_list():
-    """Temporary solution to return empty list from libsonata report readers `.get` functions.
-
-    see: https://github.com/BlueBrain/libsonata/issues/84
-    """
-    return np.array([-2])
-
-
 def add_dynamic_prefix(properties):
     """Add the dynamic prefix to a list of properties."""
     return [DYNAMICS_PREFIX + name for name in list(properties)]

setup.py

@@ -44,7 +44,7 @@ def __init__(self, *args, **kwargs):
         'cached_property>=1.0',
         'functools32;python_version<"3.2"',
         'h5py>=2.2',
-        'libsonata>=0.1.3',
+        'libsonata>=0.1.4',
         'neurom>=1.3',
         'numpy>=1.8',
         'pandas>=0.17',

tests/data/reporting/create_reports.py

@@ -64,15 +64,16 @@ def write_element_report(filepath):
     population_names = ['default', 'default2']
     node_ids = np.arange(0, 3)
     index_pointers = np.arange(0, 8, 2)
-    element_ids = np.array([0, 1] * 3)
+    index_pointers[-1] = index_pointers[-1] + 1
+    element_ids = np.array([0, 1] * 3 + [1])
 
     times = (0.0, 1, 0.1)
 
     string_dtype = h5py.special_dtype(vlen=str)
     with h5py.File(filepath, 'w') as h5f:
         h5f.create_group('report')
         gpop_element = h5f.create_group('/report/' + population_names[0])
-        d1 = np.array([np.arange(6) + j*0.1 for j in range(10)])
+        d1 = np.array([np.arange(7) + j*0.1 for j in range(10)])
         ddata = gpop_element.create_dataset('data', data=d1, dtype=np.float32)
         ddata.attrs.create('units', data="mV", dtype=string_dtype)
         gmapping = h5f.create_group('/report/' + population_names[0] + '/mapping')
@@ -85,7 +86,7 @@ def write_element_report(filepath):
         dtimes.attrs.create('units', data="ms", dtype=string_dtype)
 
         gpop_element2 = h5f.create_group('/report/' + population_names[1])
-        d1 = np.array([np.arange(6) + j * 0.1 for j in range(10)])
+        d1 = np.array([np.arange(7) + j * 0.1 for j in range(10)])
         ddata = gpop_element2.create_dataset('data', data=d1, dtype=np.float32)
         ddata.attrs.create('units', data="mR", dtype=string_dtype)
         gmapping = h5f.create_group('/report/' + population_names[1] + '/mapping')

tests/test_frame_report.py

@@ -102,7 +102,10 @@ def test_filter(self):
         assert filtered.report.columns.tolist() == [("default2", 1, 0), ("default2", 1, 1)]
 
         filtered = self.test_obj.filter(group={"population": "default2"}, t_start=0.3, t_stop=0.6)
-        assert filtered.report.columns.tolist() == [("default2", 0, 0), ("default2", 0, 1), ("default2", 1, 0), ("default2", 1, 1), ("default2", 2, 0), ("default2", 2, 1)]
+        assert filtered.report.columns.tolist() == [("default2", 0, 0), ("default2", 0, 1),
+                                                    ("default2", 1, 0), ("default2", 1, 1),
+                                                    ("default2", 2, 0), ("default2", 2, 1),
+                                                    ("default2", 2, 1)]
 
         filtered = self.test_obj.filter(group={"population": "default3"}, t_start=0.3, t_stop=0.6)
         pdt.assert_frame_equal(filtered.report, pd.DataFrame())
@@ -163,11 +166,9 @@ def setup(self):
         self.simulation = Simulation(str(TEST_DATA_DIR / 'simulation_config.json'))
         self.test_obj = test_module.CompartmentReport(self.simulation, "section_report")["default"]
         timestamps = np.linspace(0, 0.9, 10)
-        data = np.array([np.arange(6) + j * 0.1 for j in range(10)])
-
-        data = {(0, 0): data[:, 0], (0, 1): data[:, 1], (1, 0): data[:, 2], (1, 1): data[:, 3],
-                (2, 0): data[:, 4], (2, 1): data[:, 5]}
-        self.df = pd.DataFrame(data=data, index=timestamps)
+        data = np.array([np.arange(7) + j * 0.1 for j in range(10)], dtype=np.float32)
+        ids = [(0, 0), (0, 1), (1, 0), (1, 1), (2, 0), (2, 1), (2, 1)]
+        self.df = pd.DataFrame(data=data, columns=pd.MultiIndex.from_tuples(ids), index=timestamps)
 
     def test__resolve(self):
         npt.assert_array_equal(self.test_obj._resolve({Cell.MTYPE: "L6_Y"}), [1, 2])
@@ -213,8 +214,6 @@ def test_get(self):
         pdt.assert_frame_equal(
             self.test_obj.get([2, 1], t_start=0.2, t_stop=0.8), self.df.iloc[2:9].loc[:, [1, 2]])
 
-        pdt.assert_frame_equal(self.test_obj.get([0, 2], t_start=15), pd.DataFrame())
-
         pdt.assert_frame_equal(
             self.test_obj.get(group={Cell.MTYPE: "L6_Y"}, t_start=0.2, t_stop=0.8),
             self.df.iloc[2:9].loc[:, [1, 2]])
@@ -225,12 +224,28 @@ def test_get(self):
         pdt.assert_frame_equal(
             self.test_obj.get(group="Layer23"), self.df.loc[:, [0]])
 
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get(-1, t_start=0.2)
+
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get(0, t_start=-1)
+
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get([0, 2], t_start=15)
+
         with pytest.raises(BluepySnapError):
             self.test_obj.get(4)
 
+    def test_get_partially_not_in_report(self):
+        with patch.object(self.test_obj.__class__, "_resolve", return_value=np.asarray([0, 4])):
+            pdt.assert_frame_equal(self.test_obj.get([0, 4]),  self.df.loc[:, [0]])
+
     def test_get_not_in_report(self):
         with patch.object(self.test_obj.__class__, "_resolve", return_value=np.asarray([4])):
-            pdt.assert_frame_equal(self.test_obj.get(4), pd.DataFrame())
+            pdt.assert_frame_equal(self.test_obj.get([4]), pd.DataFrame())
+
+    def test_node_ids(self):
+        npt.assert_array_equal(self.test_obj.node_ids, np.array(sorted([0, 1, 2]), dtype=np.int64))
 
 
 class TestPopulationSomaReport(TestPopulationCompartmentReport):
@@ -239,4 +254,4 @@ def setup(self):
         self.test_obj = test_module.SomaReport(self.simulation, "soma_report")["default"]
         timestamps = np.linspace(0, 0.9, 10)
         data = {0: timestamps, 1: timestamps + 1, 2: timestamps + 2}
-        self.df = pd.DataFrame(data=data, index=timestamps, columns=[0, 1, 2])
+        self.df = pd.DataFrame(data=data, index=timestamps, columns=[0, 1, 2]).astype(np.float32)

tests/test_morph.py

@@ -10,7 +10,6 @@
 
 import bluepysnap.morph as test_module
 from bluepysnap.circuit import Circuit
-from bluepysnap.nodes import NodeStorage
 from bluepysnap.sonata_constants import Node
 from bluepysnap.exceptions import BluepySnapError
 

tests/test_spike_report.py

@@ -17,6 +17,7 @@
 def _create_series(node_ids, index, name="ids"):
     def _get_index(ids):
         return pd.Index(ids, name="times")
+
     return pd.Series(node_ids, index=_get_index(index), name=name)
 
 
@@ -132,8 +133,10 @@ def test_get(self):
         pdt.assert_series_equal(self.test_obj.get(2), _create_series([2, 2], [0.1, 0.7]))
         pdt.assert_series_equal(self.test_obj.get(0, t_start=1.), _create_series([0], [1.3]))
         pdt.assert_series_equal(self.test_obj.get(0, t_stop=1.), _create_series([0], [0.2]))
-        pdt.assert_series_equal(self.test_obj.get(0, t_start=1., t_stop=12), _create_series([0], [1.3]))
-        pdt.assert_series_equal(self.test_obj.get(0, t_start=0.1, t_stop=12), _create_series([0, 0], [0.2, 1.3]))
+        pdt.assert_series_equal(self.test_obj.get(0, t_start=1., t_stop=12),
+                                _create_series([0], [1.3]))
+        pdt.assert_series_equal(self.test_obj.get(0, t_start=0.1, t_stop=12),
+                                _create_series([0, 0], [0.2, 1.3]))
 
         pdt.assert_series_equal(self.test_obj.get([2, 0]),
                                 _create_series([2, 0, 2, 0], [0.1, 0.2, 0.7, 1.3]))
@@ -157,8 +160,6 @@ def test_get(self):
         pdt.assert_series_equal(self.test_obj.get([2, 1], t_start=0.2, t_stop=0.8),
                                 _create_series([1, 2], [0.3, 0.7]))
 
-        pdt.assert_series_equal(self.test_obj.get([0, 2], t_start=12), _create_series([], []))
-
         pdt.assert_series_equal(
             self.test_obj.get(group={Cell.MTYPE: "L6_Y"}, t_start=0.2, t_stop=0.8),
             _create_series([1, 2], [0.3, 0.7]))
@@ -169,6 +170,15 @@ def test_get(self):
         pdt.assert_series_equal(
             self.test_obj.get(group="Layer23"), _create_series([0, 0], [0.2, 1.3]))
 
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get([-1], t_start=0.2)
+
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get([0, 2], t_start=-1)
+
+        with pytest.raises(BluepySnapError):
+            self.test_obj.get([0, 2], t_start=12)
+
         with pytest.raises(BluepySnapError):
             self.test_obj.get(4)
 
@@ -188,3 +198,12 @@ def test_get2(self):
     def test_get_not_in_report(self, mock):
         pdt.assert_series_equal(self.test_obj.get(4),
                                 _create_series([], []))
+
+    @patch(test_module.__name__ + '.PopulationSpikeReport._resolve_nodes',
+           return_value=np.asarray([0, 4]))
+    def test_get_not_in_report(self, mock):
+        pdt.assert_series_equal(self.test_obj.get([0, 4]),
+                                _create_series([0, 0], [0.2, 1.3]))
+
+    def test_node_ids(self):
+        npt.assert_array_equal(self.test_obj.node_ids, np.array(sorted([0, 1, 2]), dtype=np.int64))

tests/test_utils.py

@@ -34,10 +34,6 @@ def test_roundrobin():
     assert list(test_module.roundrobin(*a)) == [1, 4, 5, 2, 6, 3]
 
 
-def test_fix_libsonata_empty_list():
-    npt.assert_array_equal(test_module.fix_libsonata_empty_list(), np.array([-2]))
-
-
 def test_add_dynamic_prefix():
     assert test_module.add_dynamic_prefix(["a", "b"]) == [DYNAMICS_PREFIX + "a",
                                                           DYNAMICS_PREFIX + "b"]