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fixed iso to tag as is in the file, added function to print out attributes

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ralf 2024-08-05 13:27:23 +03:00
parent 05656c85d6
commit a999da570e
1 changed files with 21 additions and 11 deletions
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32
h5_data_organizer.py
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@ -3,31 +3,41 @@ import pandas as pd
file = "ltcc_current.h5"
# Dict to hold DFs 'sex', 'iso' & 'spid'
dfs_by_sex_iso_spid = {}
def print_attrs(name, obj):
print(f"\nAttributes for {name}:")
for key, val in obj.attrs.items():
print(f" {key}: {val}")
with h5py.File(file, "r") as h5_file:
h5_file.visititems(print_attrs)
# Dict to hold DFs 'sex', 'tag' & 'spid'
dfs_by_sex_tag_spid = {}
with h5py.File(file, "r") as h5_file:
for eid in h5_file.keys():
attributes = h5_file[eid].attrs
sex = attributes.get("sex")
iso = attributes.get("iso")
tag = attributes.get("tag")
spid = attributes.get("spid")
# Creates a unique key for dict based on sex, iso & spid
key = f"{sex}_{iso}_{spid}"
# Creates a unique key for dict based on sex, tag & spid
key = f"{sex}_{tag}_{spid}"
if key not in dfs_by_sex_iso_spid:
dfs_by_sex_iso_spid[key] = pd.DataFrame()
if key not in dfs_by_sex_tag_spid:
dfs_by_sex_tag_spid[key] = pd.DataFrame()
row_data = {"experiment_id": eid, "sex": sex, "iso": iso, "spid": spid}
row_data = {"experiment_id": eid, "sex": sex, "tag": tag, "spid": spid}
temp_df = pd.DataFrame([row_data])
# Append the DF to the appropriate dict entry
dfs_by_sex_iso_spid[key] = pd.concat(
[dfs_by_sex_iso_spid[key], temp_df], ignore_index=True
dfs_by_sex_tag_spid[key] = pd.concat(
[dfs_by_sex_tag_spid[key], temp_df], ignore_index=True
)
for key, df in dfs_by_sex_iso_spid.items():
for key, df in dfs_by_sex_tag_spid.items():
print(f"DataFrame for {key}:")
print(df)
print()