22 lines
1.2 KiB
Python
22 lines
1.2 KiB
Python
import os
|
|
import pandas as pd
|
|
|
|
|
|
df = pd.DataFrame([i for i in os.listdir() if i.endswith(".txt")], columns=["file"])
|
|
df["strain"] = df.apply(lambda x: x.file[:4].upper(), axis=1)
|
|
df["replica"] = df.apply(lambda x: x.file.split("_")[0][-1], axis=1)
|
|
df["replica"] = df.apply(lambda x: int(x.replica) if x.replica.isnumeric() else None, axis=1)
|
|
df["phase"] = df.apply(lambda x: x.file.split("_")[0].replace("SampleSpectra", "")[4:-1 if x.replica is not None else None].casefold(), axis=1)
|
|
df["objective"] = df.apply(lambda x: int(x.file.split("_")[1].replace("x", "")), axis=1)
|
|
df["substrate"] = df.apply(lambda x: x.file.split("_")[4].casefold(), axis=1)
|
|
df["laser_power[%]"] = df.apply(lambda x: int(x.file.split("_")[5].replace("percent", "")), axis=1)
|
|
df["grating"] = df.apply(lambda x: int(x.file.split("_")[6].replace("gr", "")), axis=1)
|
|
df["exposition[sec]"] = df.apply(lambda x: int(x.file.split("_")[7].replace("sec", "")), axis=1)
|
|
df["confocalhigh"] = df.apply(lambda x: x.file.split("_")[8] == "confocalhigh", axis=1)
|
|
df["accumulations"] = df.apply(lambda x: int(x.file.split("_")[9].replace("."," ").replace("(", " ").split()[0].replace("accu", "")), axis=1)
|
|
df.set_index("file", inplace=True)
|
|
df.to_csv("metadata.csv")
|
|
|
|
|
|
print(df)
|