85 lines
2.1 KiB
Python
85 lines
2.1 KiB
Python
import h5py
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import os
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import pandas as pd
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h5_file = 'ltcc_current.h5'
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sobiv_eid_list = []
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ttx_eid_list = []
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teised_eid_list = []
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with h5py.File(h5_file, 'r') as h5_file:
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for eid in h5_file.keys():
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if 'tag' in h5_file[eid].attrs:
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tag_val = h5_file[eid].attrs['tag']
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if isinstance(tag_val, bytes):
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tag_val = tag_val.decode('utf-8')
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puhas_eid = eid.replace(" ", "_").replace(":", "-")
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fit_result_eid = "fit_results_" + puhas_eid
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if tag_val == 'iso':
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sobiv_eid_list.append(fit_result_eid)
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elif tag_val == 'ttx':
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ttx_eid_list.append(fit_result_eid)
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else:
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teised_eid_list.append(fit_result_eid)
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file = 'ltcc_current.h5'
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with h5py.File(file, 'r') as h5_file:
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for eid in h5_file.keys():
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puhastatud_eid = eid.replace(" ", "_").replace(":", "-")
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atribuudid = h5_file[eid].attrs
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sex = atribuudid.get('sex')
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spid = atribuudid.get('spid')
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csv_file_name = f"fit_results_{puhastatud_eid}.csv"
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if os.path.exists(csv_file_name):
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df = pd.read_csv(csv_file_name)
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df['sex'] = sex
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df['spid'] = spid.replace("Mouse AGAT", "")
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df['eid'] = eid
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df.to_csv(csv_file_name, index=False)
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for fail in os.listdir():
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if fail.endswith('.csv'):
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eksperiment_id = fail.replace(".csv", "")
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if eksperiment_id in sobiv_eid_list:
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df = pd.read_csv(fail)
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df['tag'] = 'iso'
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df.to_csv(fail, index=False)
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elif eksperiment_id in ttx_eid_list:
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df = pd.read_csv(fail)
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df['tag'] = 'ttx'
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df.to_csv(fail, index=False)
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else:
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df = pd.read_csv(fail)
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df['tag'] = 'teised'
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df.to_csv(fail, index=False)
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comb_df = pd.DataFrame()
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for filename in os.listdir():
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if filename.endswith('.csv'):
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df = pd.read_csv(filename)
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if 'tag' in df.columns and df['tag'].isin(['iso', 'ttx']).all():
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comb_df = pd.concat([comb_df, df], ignore_index=True)
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print(comb_df)
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