From 4ea2369958416c4eb21b997ceb6e7052cf10075f Mon Sep 17 00:00:00 2001
From: "Antonello, Dr. Massimiliano" <massimiliano.antonello@uni-hamburg.de>
Date: Wed, 23 Oct 2024 09:45:12 +0200
Subject: [PATCH] Added the prefit_only oiption in sumlab_auto
---
.gitignore | 4 +++-
user/sumlab_auto.py | 22 +++++++++++-----------
2 files changed, 14 insertions(+), 12 deletions(-)
diff --git a/.gitignore b/.gitignore
index 5ba68f2..c6ff415 100644
--- a/.gitignore
+++ b/.gitignore
@@ -2,4 +2,6 @@ Results
data
.DS_Store
__pycache__
-user
\ No newline at end of file
+user
+Icon*
+peakotron_logo.icns
\ No newline at end of file
diff --git a/user/sumlab_auto.py b/user/sumlab_auto.py
index 74ae8ee..8801a5f 100644
--- a/user/sumlab_auto.py
+++ b/user/sumlab_auto.py
@@ -85,12 +85,10 @@ for i, (file, path) in enumerate(files_to_fit):
tau_R=f_tau_hmt*tau,
bin_0=bin_0,
truncate_nsigma0_up=truncate_nsigma0_up,
- truncate_nsigma0_do=truncate_nsigma0_do
+ truncate_nsigma0_do=truncate_nsigma0_do,
+ prefit_only=prefit_only
)
- f_data.PlotFit(plot_in_bins=True, display=False,
- save_directory=f"{folder}/{file[:-4]}_fit.png")
-
fit_out = {}
prefit_val, prefit_err = f_data.GetPrefitResults(bin_units=False)
print("\033[95m"+rf"Prefit: G = {prefit_val.get('G')} d_G = {prefit_err.get('G')}"+"\033[0m")
@@ -99,13 +97,15 @@ for i, (file, path) in enumerate(files_to_fit):
for key, value in prefit_err.items():
fit_out["prefit_d_{:s}".format(key)] = value
- #if not prefit_only:
- fit_val, fit_err = f_data.GetFitResults(bin_units=False)
- print("\033[95m"+rf"Fit: G = {fit_val.get('G')} d_G = {fit_err.get('G')}"+"\033[0m")
- for key, value in fit_val.items():
- fit_out["{:s}".format(key)] = value
- for key, value in fit_err.items():
- fit_out["d_{:s}".format(key)] = value
+ if not prefit_only:
+ fit_val, fit_err = f_data.GetFitResults(bin_units=False)
+ print("\033[95m"+rf"Fit: G = {fit_val.get('G')} d_G = {fit_err.get('G')}"+"\033[0m")
+ for key, value in fit_val.items():
+ fit_out["{:s}".format(key)] = value
+ for key, value in fit_err.items():
+ fit_out["d_{:s}".format(key)] = value
+ f_data.PlotFit(plot_in_bins=True, display=False,
+ save_directory=f"{folder}/{file[:-4]}_fit.png")
df = pd.DataFrame.from_dict([fit_out])
df.to_csv("{}/fit_results_{:s}.csv".format(folder, file[:-4]))
--
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