rename global_pre_comps (#518)

* fix: rename global_pre_comps

* fix: replace remaining

* fix: wrong replace fixed

* fix: make copy_nodes_to_edges work

jaxley/modules/base.py

@@ -127,8 +127,8 @@ def __init__(self):
         self.edges = pd.DataFrame(
             columns=[
                 "global_edge_index",
-                "global_pre_comp_index",
-                "global_post_comp_index",
+                "pre_global_comp_index",
+                "post_global_comp_index",
                 "pre_locs",
                 "post_locs",
                 "type",
@@ -2318,7 +2318,7 @@ def copy_node_property_to_edges(
                     self.nodes[[property_to_import, "global_comp_index"]].set_index(
                         "global_comp_index"
                     ),
-                    on=f"global_{pre_or_post_val}_comp_index",
+                    on=f"{pre_or_post_val}_global_comp_index",
                 )
                 self.edges = self.edges.rename(
                     columns={
@@ -2466,8 +2466,8 @@ def _set_inds_in_view(
             incl_comps = pointer.nodes.loc[
                 self._nodes_in_view, "global_comp_index"
             ].unique()
-            pre = base_edges["global_pre_comp_index"].isin(incl_comps).to_numpy()
-            post = base_edges["global_post_comp_index"].isin(incl_comps).to_numpy()
+            pre = base_edges["pre_global_comp_index"].isin(incl_comps).to_numpy()
+            post = base_edges["post_global_comp_index"].isin(incl_comps).to_numpy()
             possible_edges_in_view = base_edges.index.to_numpy()[(pre & post).flatten()]
             self._edges_in_view = np.intersect1d(
                 possible_edges_in_view, self._edges_in_view
@@ -2476,7 +2476,7 @@ def _set_inds_in_view(
             base_nodes = self.base.nodes
             self._edges_in_view = edges
             incl_comps = pointer.edges.loc[
-                self._edges_in_view, ["global_pre_comp_index", "global_post_comp_index"]
+                self._edges_in_view, ["pre_global_comp_index", "post_global_comp_index"]
             ]
             incl_comps = np.unique(incl_comps.to_numpy().flatten())
             where_comps = base_nodes["global_comp_index"].isin(incl_comps)

jaxley/modules/network.py

@@ -262,8 +262,8 @@ def _step_synapse_state(
         voltages = states["v"]
 
         grouped_syns = edges.groupby("type", sort=False, group_keys=False)
-        pre_syn_inds = grouped_syns["global_pre_comp_index"].apply(list)
-        post_syn_inds = grouped_syns["global_post_comp_index"].apply(list)
+        pre_syn_inds = grouped_syns["pre_global_comp_index"].apply(list)
+        post_syn_inds = grouped_syns["post_global_comp_index"].apply(list)
         synapse_names = list(grouped_syns.indices.keys())
 
         for i, synapse_type in enumerate(syn_channels):
@@ -309,8 +309,8 @@ def _synapse_currents(
         voltages = states["v"]
 
         grouped_syns = edges.groupby("type", sort=False, group_keys=False)
-        pre_syn_inds = grouped_syns["global_pre_comp_index"].apply(list)
-        post_syn_inds = grouped_syns["global_post_comp_index"].apply(list)
+        pre_syn_inds = grouped_syns["pre_global_comp_index"].apply(list)
+        post_syn_inds = grouped_syns["post_global_comp_index"].apply(list)
         synapse_names = list(grouped_syns.indices.keys())
 
         syn_voltage_terms = jnp.zeros_like(voltages)
@@ -471,10 +471,10 @@ def vis(
 
             pre_locs = self.edges["pre_locs"].to_numpy()
             post_locs = self.edges["post_locs"].to_numpy()
-            pre_comp = self.edges["global_pre_comp_index"].to_numpy()
+            pre_comp = self.edges["pre_global_comp_index"].to_numpy()
             nodes = self.nodes.set_index("global_comp_index")
             pre_branch = nodes.loc[pre_comp, "global_branch_index"].to_numpy()
-            post_comp = self.edges["global_post_comp_index"].to_numpy()
+            post_comp = self.edges["post_global_comp_index"].to_numpy()
             post_branch = nodes.loc[post_comp, "global_branch_index"].to_numpy()
 
             dims_np = np.asarray(dims)
@@ -536,10 +536,10 @@ def build_extents(*subset_sizes):
         else:
             graph.add_nodes_from(range(len(self._cells_in_view)))
 
-        pre_comp = self.edges["global_pre_comp_index"].to_numpy()
+        pre_comp = self.edges["pre_global_comp_index"].to_numpy()
         nodes = self.nodes.set_index("global_comp_index")
         pre_cell = nodes.loc[pre_comp, "global_cell_index"].to_numpy()
-        post_comp = self.edges["global_post_comp_index"].to_numpy()
+        post_comp = self.edges["post_global_comp_index"].to_numpy()
         post_cell = nodes.loc[post_comp, "global_cell_index"].to_numpy()
 
         inds = np.stack([pre_cell, post_cell]).T
@@ -583,9 +583,9 @@ def _append_multiple_synapses(self, pre_nodes, post_nodes, synapse_type):
 
         # Define new synapses. Each row is one synapse.
         pre_nodes = pre_nodes[["global_comp_index"]]
-        pre_nodes.columns = ["global_pre_comp_index"]
+        pre_nodes.columns = ["pre_global_comp_index"]
         post_nodes = post_nodes[["global_comp_index"]]
-        post_nodes.columns = ["global_post_comp_index"]
+        post_nodes.columns = ["post_global_comp_index"]
         new_rows = pd.concat(
             [
                 global_edge_index,

tests/test_connection.py

@@ -57,7 +57,7 @@ def test_connect(SimpleBranch, SimpleCell, SimpleNet):
     # check if all connections are made correctly
     first_set_edges = net2.edges.iloc[:8]
     nodes = net2.nodes.set_index("global_comp_index")
-    cols = ["global_pre_comp_index", "global_post_comp_index"]
+    cols = ["pre_global_comp_index", "post_global_comp_index"]
     comp_inds = nodes.loc[first_set_edges[cols].to_numpy().flatten()]
     branch_inds = comp_inds["global_branch_index"].to_numpy().reshape(-1, 2)
     cell_inds = comp_inds["global_cell_index"].to_numpy().reshape(-1, 2)
@@ -84,7 +84,7 @@ def test_fully_connect():
     fully_connect(net[8:12], net[12:16], TestSynapse())
 
     assert all(
-        net.edges.global_post_comp_index
+        net.edges.post_global_comp_index
         == [
             108,
             135,
@@ -171,7 +171,7 @@ def test_connectivity_matrix_connect(SimpleNet):
     )
     assert len(net.edges.index) == 4
     nodes = net.nodes.set_index("global_comp_index")
-    cols = ["global_pre_comp_index", "global_post_comp_index"]
+    cols = ["pre_global_comp_index", "post_global_comp_index"]
     comp_inds = nodes.loc[net.edges[cols].to_numpy().flatten()]
     cell_inds = comp_inds["global_cell_index"].to_numpy().reshape(-1, 2)
     assert np.all(cell_inds == incides_of_connected_cells)
@@ -192,7 +192,7 @@ def test_connectivity_matrix_connect(SimpleNet):
     )
     assert len(net.edges.index) == 5
     nodes = net.nodes.set_index("global_comp_index")
-    cols = ["global_pre_comp_index", "global_post_comp_index"]
+    cols = ["pre_global_comp_index", "post_global_comp_index"]
     comp_inds = nodes.loc[net.edges[cols].to_numpy().flatten()]
     cell_inds = comp_inds["global_cell_index"].to_numpy().reshape(-1, 2)
     assert np.all(cell_inds == incides_of_connected_cells)

tests/test_make_trainable.py

@@ -217,14 +217,14 @@ def test_copy_node_property_to_edges(SimpleNet):
     assert "post_HH_gNa" not in net.edges.columns
 
     # Query the second cell. Each cell has four compartments.
-    edges_gna_values = net.edges.query("global_pre_comp_index > 3")
-    edges_gna_values = edges_gna_values.query("global_pre_comp_index <= 7")
+    edges_gna_values = net.edges.query("pre_global_comp_index > 3")
+    edges_gna_values = edges_gna_values.query("pre_global_comp_index <= 7")
     assert np.all(edges_gna_values["pre_HH_gNa"] == 1.0)
 
     # Query the other cells. The first cell has four compartments.
-    edges_gna_values = net.edges.query("global_pre_comp_index <= 3")
+    edges_gna_values = net.edges.query("pre_global_comp_index <= 3")
     assert np.all(edges_gna_values["pre_HH_gNa"] == 0.12)
-    edges_gna_values = net.edges.query("global_pre_comp_index > 7")
+    edges_gna_values = net.edges.query("pre_global_comp_index > 7")
     assert np.all(edges_gna_values["pre_HH_gNa"] == 0.12)
 
     # Test whether multiple properties can be copied over.
@@ -234,27 +234,27 @@ def test_copy_node_property_to_edges(SimpleNet):
     assert "pre_length" in net.edges.columns
     assert "post_length" in net.edges.columns
 
-    edges_gna_values = net.edges.query("global_pre_comp_index <= 3")
+    edges_gna_values = net.edges.query("pre_global_comp_index <= 3")
     assert np.all(edges_gna_values["pre_radius"] == 0.2)
 
-    edges_gna_values = net.edges.query("global_pre_comp_index > 3")
+    edges_gna_values = net.edges.query("pre_global_comp_index > 3")
     assert np.all(edges_gna_values["pre_radius"] == 1.0)
 
     # Test whether modifying an individual compartment also takes effect.
     net.copy_node_property_to_edges(["capacitance"])
     assert "pre_capacitance" in net.edges.columns
     assert "post_capacitance" in net.edges.columns
 
-    edges_gna_values = net.edges.query("global_pre_comp_index == 4")
+    edges_gna_values = net.edges.query("pre_global_comp_index == 4")
     assert np.all(edges_gna_values["pre_capacitance"] == 0.3)
 
-    edges_gna_values = net.edges.query("global_post_comp_index == 4")
+    edges_gna_values = net.edges.query("post_global_comp_index == 4")
     assert np.all(edges_gna_values["post_capacitance"] == 0.3)
 
-    edges_gna_values = net.edges.query("global_pre_comp_index != 4")
+    edges_gna_values = net.edges.query("pre_global_comp_index != 4")
     assert np.all(edges_gna_values["pre_capacitance"] == 1.0)
 
-    edges_gna_values = net.edges.query("global_post_comp_index != 4")
+    edges_gna_values = net.edges.query("post_global_comp_index != 4")
     assert np.all(edges_gna_values["post_capacitance"] == 1.0)
 
 

tests/test_viewing.py

@@ -359,7 +359,7 @@ def test_select(SimpleNet):
 
     # check if pre and post comps of edges are in nodes
     edge_node_inds = np.unique(
-        view.edges[["global_pre_comp_index", "global_post_comp_index"]]
+        view.edges[["pre_global_comp_index", "post_global_comp_index"]]
         .to_numpy()
         .flatten()
     )