zdc_lyso: set maxfev=10000 for curve_fit (#77)

eic · Oct 7, 2024 · 8116047 · 8116047
1 parent cff85ab
commit 8116047
Showing 1 changed file with 3 additions and 3 deletions.
diff --git a/benchmarks/zdc_lyso/analysis/analysis.py b/benchmarks/zdc_lyso/analysis/analysis.py
@@ -82,7 +82,7 @@ def rotateY(xdata, zdata, angle):
     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 @@ def rotateY(xdata, zdata, angle):
     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 @@ def rotateY(xdata, zdata, angle):
     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])