From 8116047447bcfa6aa493ea3dd4f6ab3e724b5c7f Mon Sep 17 00:00:00 2001
From: Dmitry Kalinkin <dmitry.kalinkin@gmail.com>
Date: Mon, 7 Oct 2024 10:50:28 -0400
Subject: [PATCH] zdc_lyso: set maxfev=10000 for curve_fit (#77)
---
benchmarks/zdc_lyso/analysis/analysis.py | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git a/benchmarks/zdc_lyso/analysis/analysis.py b/benchmarks/zdc_lyso/analysis/analysis.py
index eace6112..8994fa24 100644
--- a/benchmarks/zdc_lyso/analysis/analysis.py
+++ b/benchmarks/zdc_lyso/analysis/analysis.py
@@ -82,7 +82,7 @@ for i in range(6):
hist, x = np.histogram(temp,bins=np.linspace(min(temp),max(temp)+np.std(abs(temp)),2*int(np.sqrt(len(temp)))))
x = x[1:]/2 + x[:-1]/2
plt.errorbar(x,hist,yerr=np.sqrt(hist),fmt='-o',label='Cluster')
- coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])))
+ coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])),maxfev=10000)
#plt.plot(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),gaussian(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),*coeff))
mu.append(coeff[1])
sigma.append(coeff[2])
@@ -91,7 +91,7 @@ for i in range(6):
hist, x = np.histogram(temp,bins=np.linspace(min(temp),max(temp)+np.std(abs(temp)),2*int(np.sqrt(len(temp)))))
x = x[1:]/2 + x[:-1]/2
plt.errorbar(x,hist,yerr=np.sqrt(hist),fmt='-o',label='Digitization')
- coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])))
+ coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])),maxfev=10000)
#plt.plot(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),gaussian(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),*coeff))
mu.append(coeff[1])
sigma.append(coeff[2])
@@ -100,7 +100,7 @@ for i in range(6):
hist, x = np.histogram(temp,bins=np.linspace(min(temp),max(temp)+np.std(abs(temp)),2*int(np.sqrt(len(temp)))))
x = x[1:]/2 + x[:-1]/2
plt.errorbar(x,hist,yerr=np.sqrt(hist),fmt='-o',label='Simulation')
- coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])))
+ coeff, covar = curve_fit(gaussian,x[1:],hist[1:],p0=(max(hist[x>=np.std(abs(temp))]),np.mean(temp[temp!=0]),np.std(temp[temp!=0])),maxfev=10000)
#plt.plot(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),gaussian(np.linspace(coeff[1]-3*coeff[2],coeff[1]+3*coeff[2],50),*coeff))
mu.append(coeff[1])
sigma.append(coeff[2])
--
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