36 lines
896 B
Python
36 lines
896 B
Python
|
import h5py
|
||
|
import pandas as pd
|
||
|
import re
|
||
|
|
||
|
from Model import Model
|
||
|
from fitter import Fitter
|
||
|
from Data import Data
|
||
|
|
||
|
|
||
|
def fit_data():
|
||
|
filename = "ltcc_current.h5"
|
||
|
with h5py.File(filename, "r") as h5:
|
||
|
eids = list(h5.keys())
|
||
|
|
||
|
for eid in eids:
|
||
|
data = Data(filename, group_key=eid)
|
||
|
fit = Fitter(Model, data)
|
||
|
fit.optimize()
|
||
|
res, fig = fit.optimize()
|
||
|
|
||
|
fit_hist = pd.DataFrame.from_dict(fit.fit_results, orient="index").T
|
||
|
fit_hist.index.name = "Iterations"
|
||
|
|
||
|
res_filename = f"fit_results_{eid}.csv"
|
||
|
res_filename = res_filename.replace(" ", "_").replace(":", "-")
|
||
|
fit_hist.to_csv(res_filename, index=True)
|
||
|
|
||
|
eid_cleaned = re.sub(
|
||
|
r"[^\w.-]", "", eid
|
||
|
) # Eemaldab kõik eritähed
|
||
|
fig.savefig(f"plot_{eid_cleaned}.png")
|
||
|
fig.savefig(f"plot_{eid_cleaned}.pdf")
|
||
|
|
||
|
|
||
|
fit_data()
|