def stashcsv(df, name, **kws):
savecsv(df, name)
def stashcsv(df, name, **kws):
savecsv(df, name, foldername=FNAME, save_on=True, **kws)
for p in pair_meta["Pair ID"].unique():
pm = pair_meta[pair_meta["Pair ID"] == p]
uni_lin = pm["lineage"].unique()
if ("unk" in uni_lin) and len(uni_lin) > 1:
print(str(uni_lin) + " unk")
pair_unk += 1
unk.append(pm.index.values)
elif len(uni_lin) > 1:
print(str(uni_lin) + " mismatch")
pair_mismatch += 1
mismatch.append(pm.index.values)
from src.io import savecsv
mismatch = pd.DataFrame(mismatch)
savecsv(mismatch, "mismatch")
unk = pd.DataFrame(unk)
savecsv(unk, "unk")
#%%
input_counts_path = data_path / data_date_graphs / (input_counts_file + ".csv")
input_counts_df = pd.read_csv(input_counts_path, index_col=0)
cols = input_counts_df.columns.values
cols = [str(c).strip(" ") for c in cols]
input_counts_df.columns = cols
meta.loc[input_counts_df.index, "dendrite_input"] = input_counts_df["dendrite_inputs"]
meta.loc[input_counts_df.index, "axon_input"] = input_counts_df["axon_inputs"]
#%% Import the raw graphs
def stashcsv(df, name, **kws):
savecsv(df, name, foldername=FNAME, **kws)
def stashcsv(df, name, **kws):
savecsv(df, name, foldername=FNAME, save_on=SAVEFIGS, **kws)
