def get_merged_basin():
# todo: replace "system" with "circuit"
cho_basin_g = get_data(Circuit.CHO_BASIN)
nx.set_edge_attributes(cho_basin_g, 1, "drive")
nx.set_edge_attributes(cho_basin_g, "chordotonal-Basin", "system")
ln_basin_g = get_data(Circuit.LN_BASIN)
nx.set_edge_attributes(ln_basin_g, -1, "drive")
nx.set_edge_attributes(ln_basin_g, "LN-Basin", "system")
return merge_multi(cho_basin_g, ln_basin_g)
def syn_area_distribution():
n = len(list(Circuit))
for circuit in Circuit:
g = get_data(circuit)
data = [data["area"] for _, _, data in g.edges(data=True)]
# bonferroni-corrected p-value
print(f"{circuit}: {NormalVsLognormal.from_data(data, 0.05/n)}")
def all_plots_for_system(circuit: Circuit, directory=None, ext=DEFAULT_EXT, show=False, **kwargs):
logger.info("creating plots for " + str(circuit))
multi_g = get_data(circuit)
for plot_class in circuit_plot_classes:
with plot_class(multi_g, circuit).plot(**kwargs) as plot:
if directory:
plot.save(directory, ext)
if show:
plt.show()
def plot(self, tgt_path=None, increment=False, **kwargs):
tgt_path = tgt_path or self.layout_path
for circuit in Circuit:
multi_g = get_data(circuit)
for plot_cls in [ContactNumberHeatMap, DendriticFractionHeatMap]:
fig_ax_arr = self._fig_ax_arr(f"{circuit} {plot_cls.__name__}")
with plot_cls(multi_g, circuit).plot(fig_ax_arr, **kwargs) as plot:
ax = plot.ax_arr[0, 0]
ax.set_title('')
# self.layout.insert_figures(self.layer_name)
if increment:
tgt_path = increment_filename(tgt_path)
self.layout.write_svg(tgt_path)
done_edges.add((pre, post))
done_edges.add((post, pre))
erroneous_edges = set()
for pre_post in g_auto.edges:
if pre_post not in done_edges:
erroneous_edges.add(pre_post)
print(f"{len(erroneous_edges)} erroneous edges found: ")
for pre, post in sorted(erroneous_edges):
print(f"\t{pre} -> {post}")
fig, ax_arr = plt.subplots(1, 2)
count_ax, area_ax = ax_arr.flatten()
manual_auto_scatter(manual_counts, auto_counts, "Contact number", count_ax)
manual_auto_scatter(manual_areas, auto_areas, "Contact area", area_ax)
if __name__ == "__main__":
catmaid = get_catmaid()
multi_g = get_data("ORN-PN")
g_manual = multidigraph_to_digraph(multi_g)
skids = list(g_manual.nodes)
detected_df = catmaid.get_detected_synapses_between(*skids)
g_auto = df_to_graph(detected_df)
compare_edges(g_manual, g_auto)
plt.show()
data_dir = TABLES_DIR / "out" / "count_frac_area"
data_dir.mkdir(parents=True, exist_ok=True)
HEADERS = ("circuit", "pre_id", "pre_name", "pre_side", "pre_segment",
"post_id", "post_name", "post_side", "post_segment",
"contact_number", "contact_fraction", "synaptic_area")
all_data = []
tgt_total_counts_df = pd.read_csv(CATMAID_CSV_DIR /
"dendritic_synapse_counts.csv",
index_col=0)
for circuit in Circuit:
g = multidigraph_to_digraph(get_data(circuit))
rows = []
total_count = 0
for pre, post, edata in iter_data(g):
row = [str(circuit)]
for node in (pre, post):
row.extend([node.id, node.name, str(node.side), str(node.segment)])
row.append(edata["count"])
frac = edata["count"] / tgt_total_counts_df["post_count"].loc[post.id]
row.append(frac)
row.append(edata["area"])
rows.append(row)
from clefts.manual_label.common import get_data
from clefts.manual_label.constants import Circuit, TABLES_DIR
from clefts.manual_label.make_tables.common import iter_data, write_rows
data_dir = TABLES_DIR / "out" / "areas"
data_dir.mkdir(parents=True, exist_ok=True)
HEADERS = ("circuit", "pre_id", "pre_name", "pre_side", "pre_segment",
"post_id", "post_name", "post_side", "post_segment", "connector_id",
"synaptic_area")
all_data = []
for circuit in Circuit:
g = get_data(circuit)
rows = []
total_count = 0
for pre, post, edata in iter_data(g):
row = [str(circuit)]
for node in (pre, post):
row.extend([node.id, node.name, str(node.side), str(node.segment)])
row.append(edata["conn_id"])
row.append(edata["area"])
rows.append(row)
total_count += 1
print(f"Total synapse count for {circuit}: {total_count}")
rows = sorted(rows)
write_rows(data_dir / f"{circuit}.csv", rows, HEADERS)