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)