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A few small bug fixes #54

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d6d6843
Properly show all selected attributes in the interactive graph and ad…
Dominic-DallOsto Apr 11, 2025
e5242ae
Fix `ConnectomeReader.get_neurons_from_class` bug
Dominic-DallOsto Apr 11, 2025
8d720e0
Fix bug in `FAFBReader.get_neuron_bodyids`
Dominic-DallOsto Apr 11, 2025
ea871f5
Fix some tiny type hinting problems in connectome_reader
Dominic-DallOsto Apr 11, 2025
e291cc4
Fix bug with `Connections.get_neuron_ids` not working when providing …
Dominic-DallOsto Apr 11, 2025
60d1db4
Define the `nt_weights` dict in the base `ConnectomeReader` class to …
Dominic-DallOsto Apr 11, 2025
669f9d0
Make `specific_neuron_class` throw a `KeyError` instead of a `ValueEr…
Dominic-DallOsto Apr 11, 2025
ab01e74
Add `root_side` parameter to MANC connectome reader
Dominic-DallOsto Apr 11, 2025
8881230
Merge pull request #53 from NeLy-EPFL:Dominic-DallOsto/issue52
Dominic-DallOsto Apr 24, 2025
25a53e7
Add notebook investigating missing synapses in FAFB graph
Dominic-DallOsto Apr 24, 2025
1cf21a3
Add function to get neuron and synapse counts by neuropil
Dominic-DallOsto Apr 24, 2025
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595 changes: 595 additions & 0 deletions scripts/fafb_missing_some_synapses.ipynb
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192 changes: 192 additions & 0 deletions tests/test_local/test_data_loading.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,9 @@
"""


from vnc_networks.params import SelectionDict


class TestDataLoading:
"""
Test the data loading functions.
Expand Down Expand Up @@ -58,3 +61,192 @@ def test_connections_instantiation_MANCv1_2(self):

df_2 = df[(df["start_bid"] == 10725) & (df["end_bid"] == 10439)]
assert df_2["eff_weight"].values[0] == -1080, "Incorrect nt_type handling"

def test_connections_getting_neuron_ids_MANCv1_2(self):
"""
Test that we get the same results if we get uids or bodyids and convert between the two.
"""
import vnc_networks
from vnc_networks.connections import Connections

# Instantiate a Connections object
connections = Connections(vnc_networks.connectome_reader.MANC("v1.2"))

# test a few different selection_dicts
selection_dicts: list[SelectionDict | None] = [
None,
{},
{"class_1": "descending"},
{"class_1": "ascending", "nt_type": "GABA"},
]
for selection_dict in selection_dicts:
body_ids = connections.get_neuron_bodyids(selection_dict)
uids = connections.get_neuron_ids(selection_dict)
assert (
set(connections.get_uids_from_bodyids(body_ids)) == set(uids)
), f"Getting bodyids and converting to uids doesn't match with selection_dict {selection_dict}."
assert (
set(connections.get_bodyids_from_uids(uids)) == set(body_ids)
), f"Getting uids and converting to bodyids doesn't match with selection_dict {selection_dict}."

def test_getting_counts_by_neuropil_MANCv1_2(self):
"""
Test that we can get neuron and synapse counts by neuropil
"""
import pandas as pd

import vnc_networks

# Instantiate a Connections object
connectome_reader = vnc_networks.connectome_reader.MANC("v1.2")

# check that this matches what we expect
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"downstream", [10000, 23458]
),
pd.DataFrame(
{
"body_id": [10000, 23458],
"CV": [703, 0],
"IntTct": [313, 0],
"LTct": [3181, 0],
"LegNp(T3)(R)": [0, 1688],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"upstream", [10000, 23458]
),
pd.DataFrame(
{
"body_id": [10000, 23458],
"CV": [224, 0],
"IntTct": [185, 0],
"LTct": [1462, 0],
"LegNp(T3)(R)": [0, 685],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil("pre", [10000, 23458]),
pd.DataFrame(
{
"body_id": [10000, 23458],
"CV": [138, 0],
"IntTct": [73, 0],
"LTct": [752, 0],
"LegNp(T3)(R)": [0, 207],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil("post", [10000, 23458]),
pd.DataFrame(
{
"body_id": [10000, 23458],
"CV": [224, 0],
"IntTct": [185, 0],
"LTct": [1462, 0],
"LegNp(T3)(R)": [0, 685],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"total_synapses", [10000, 23458]
),
pd.DataFrame(
{
"body_id": [10000, 23458],
"CV": [927, 0],
"IntTct": [498, 0],
"LTct": [4643, 0],
"LegNp(T3)(R)": [0, 2373],
}
),
)

def test_getting_counts_by_neuropil_FAFBv783(self):
"""
Test that we can get neuron and synapse counts by neuropil
"""
import pandas as pd

import vnc_networks

# Instantiate a Connections object
connectome_reader = vnc_networks.connectome_reader.FAFB_v783()

# check that this matches what we expect
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"downstream", [720575940627036426, 720575940633587552]
),
pd.DataFrame(
{
"body_id": [720575940627036426, 720575940633587552],
"LOP_L": [9, 0],
"LO_L": [2, 0],
"SLP_R": [0, 2],
"SMP_R": [0, 31],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"upstream", [720575940627036426, 720575940633587552]
),
pd.DataFrame(
{
"body_id": [720575940627036426, 720575940633587552],
"LOP_L": [3, 0],
"LO_L": [9, 0],
"SLP_R": [0, 11],
"SMP_R": [0, 13],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"pre", [720575940627036426, 720575940633587552]
),
pd.DataFrame(
{
"body_id": [720575940627036426, 720575940633587552],
"LOP_L": [14, 0],
"LO_L": [83, 0],
"SLP_R": [0, 33],
"SMP_R": [0, 75],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"post", [720575940627036426, 720575940633587552]
),
pd.DataFrame(
{
"body_id": [720575940627036426, 720575940633587552],
"LOP_L": [100, 0],
"LO_L": [8, 0],
"SLP_R": [0, 4],
"SMP_R": [0, 284],
}
),
)
pd.testing.assert_frame_equal(
connectome_reader.get_synapse_counts_by_neuropil(
"total_synapses", [720575940627036426, 720575940633587552]
),
pd.DataFrame(
{
"body_id": [720575940627036426, 720575940633587552],
"LOP_L": [114, 0],
"LO_L": [91, 0],
"SLP_R": [0, 37],
"SMP_R": [0, 359],
}
),
)
5 changes: 3 additions & 2 deletions vnc_networks/connections.py
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Original file line number Diff line number Diff line change
Expand Up @@ -977,8 +977,9 @@ def get_neuron_ids(
Get the neuron IDs from the nodes dataframe as loaded in the initial
dataset, based on a selection dictionary.
"""
nodes = self.get_nodes(type="body_id")
body_ids = self.CR.get_neuron_bodyids(selection_dict, nodes)
body_ids = self.get_nodes(type="body_id")
if selection_dict is not None:
body_ids = self.CR.get_neuron_bodyids(selection_dict, body_ids)
return self.__get_uids_from_bodyids(body_ids)

def get_neurons_pre(self):
Expand Down
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