From 89c8682bb736143aef08b2daea6c560177def569 Mon Sep 17 00:00:00 2001
From: Dmitry Kalinkin <dmitry.kalinkin@gmail.com>
Date: Wed, 23 Oct 2024 00:42:32 -0400
Subject: [PATCH] femc_*: use maxfev=10000
---
benchmarks/femc_electron/analysis/femc_electron_plots.py | 6 +++---
benchmarks/femc_photon/analysis/femc_photon_plots.py | 6 +++---
benchmarks/femc_pi0/analysis/femc_pi0_plots.py | 6 +++---
3 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/benchmarks/femc_electron/analysis/femc_electron_plots.py b/benchmarks/femc_electron/analysis/femc_electron_plots.py
index cc34633d..8979e0c7 100644
--- a/benchmarks/femc_electron/analysis/femc_electron_plots.py
+++ b/benchmarks/femc_electron/analysis/femc_electron_plots.py
@@ -132,7 +132,7 @@ for p in arrays_sim:
sigma=np.sqrt(y[slc])+0.5*(y[slc]==0)
p0=(100, p, 3)
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
#res=np.abs(coeff[2]/coeff[1])
if p==50:
xx=np.linspace(15*p/20,22*p/20, 100)
@@ -151,7 +151,7 @@ plt.sca(axs[1])
plt.errorbar(pvals, 100*np.array(res), 100*np.array(dres), ls='', marker='o')
fnc = lambda E, a, b: np.hypot(a,b/np.sqrt(E))
p0=(.05, .12)
-coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0,sigma=dres)
+coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0, sigma=dres, maxfev=10000)
xx=np.linspace(7, 85, 100)
plt.plot(xx, 100*fnc(xx,*coeff), label=f'fit:{100*coeff[0]:.1f}%$\\oplus\\frac{{{100*coeff[1]:.0f}\\%}}{{\\sqrt{{E}}}}$')
plt.legend()
@@ -190,7 +190,7 @@ for eta_min, eta_max in zip(partitions[:-1], partitions[1:]):
p0=(100, p, 3)
try:
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
if abs(coeff[1])>100 or np.sqrt(var_matrix[1][1])>100:
continue
pvals.append(p)
diff --git a/benchmarks/femc_photon/analysis/femc_photon_plots.py b/benchmarks/femc_photon/analysis/femc_photon_plots.py
index 8170f4a1..176eb663 100644
--- a/benchmarks/femc_photon/analysis/femc_photon_plots.py
+++ b/benchmarks/femc_photon/analysis/femc_photon_plots.py
@@ -131,7 +131,7 @@ for p in arrays_sim:
sigma=np.sqrt(y[slc])+0.5*(y[slc]==0)
p0=(100, p, 3)
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
#res=np.abs(coeff[2]/coeff[1])
if p==50:
xx=np.linspace(15*p/20,22*p/20, 100)
@@ -150,7 +150,7 @@ plt.sca(axs[1])
plt.errorbar(pvals, 100*np.array(res), 100*np.array(dres), ls='', marker='o')
fnc = lambda E, a, b: np.hypot(a,b/np.sqrt(E))
p0=(.05, .12)
-coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0,sigma=dres)
+coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0, sigma=dres, maxfev=10000)
xx=np.linspace(7, 85, 100)
plt.plot(xx, 100*fnc(xx,*coeff), label=f'fit:{100*coeff[0]:.1f}%$\\oplus\\frac{{{100*coeff[1]:.0f}\\%}}{{\\sqrt{{E}}}}$')
plt.legend()
@@ -188,7 +188,7 @@ for eta_min, eta_max in zip(partitions[:-1], partitions[1:]):
sigma=np.sqrt(y[slc])+0.5*(y[slc]==0)
p0=(100, p, 3)
try:
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
if abs(coeff[1])>100 or np.sqrt(var_matrix[1][1])>100:
continue
pvals.append(p)
diff --git a/benchmarks/femc_pi0/analysis/femc_pi0_plots.py b/benchmarks/femc_pi0/analysis/femc_pi0_plots.py
index cdf9d231..0bdf26e3 100644
--- a/benchmarks/femc_pi0/analysis/femc_pi0_plots.py
+++ b/benchmarks/femc_pi0/analysis/femc_pi0_plots.py
@@ -167,7 +167,7 @@ for p in arrays_sim:
sigma=np.sqrt(y[slc])+0.5*(y[slc]==0)
p0=(100, p, 3)
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
#res=np.abs(coeff[2]/coeff[1])
if p==50:
xx=np.linspace(15*p/20,22*p/20, 100)
@@ -186,7 +186,7 @@ plt.sca(axs[1])
plt.errorbar(pvals, 100*np.array(res), 100*np.array(dres), ls='', marker='o')
fnc = lambda E, a, b: np.hypot(a,b/np.sqrt(E))
p0=(.05, .12)
-coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0,sigma=dres)
+coeff, var_matrix = curve_fit(fnc, pvals, res, p0=p0, sigma=dres, maxfev=10000)
xx=np.linspace(15, 85, 100)
plt.plot(xx, 100*fnc(xx,*coeff), label=f'fit:{100*coeff[0]:.1f}%$\\oplus\\frac{{{100*coeff[1]:.0f}\\%}}{{\\sqrt{{E}}}}$')
plt.legend()
@@ -225,7 +225,7 @@ for eta_min, eta_max in zip(partitions[:-1], partitions[1:]):
p0=(100, p, 3)
try:
- coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0,sigma=list(sigma))
+ coeff, var_matrix = curve_fit(fnc, list(bcs[slc]), list(y[slc]), p0=p0, sigma=list(sigma), maxfev=10000)
if abs(coeff[1])>100 or np.sqrt(var_matrix[1][1])>100:
continue
pvals.append(p)
--
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