fit results output

fit results output

Author: dpscience

DReconvolutionInput.py

@@ -40,8 +40,8 @@
 __channelResolutionInPs = 5.0
 
 #expected lifetimes (tau) -> start values (levenberg marquardt fit)
-__expectedTau_1_in_ps = 160.0;
-__expectedTau_2_in_ps = 455.0;
+__expectedTau_1_in_ps = 260.0;
+__expectedTau_2_in_ps = 1500.0;
 __expectedTau_3_in_ps = 160.0;
 __expectedTau_4_in_ps = 160.0;
 
@@ -52,11 +52,11 @@
 #NOTE: Spectrum and IRF data vectors require equal length!!!
 
 #file path which contains the SPECTRUM data:
-__filePathSpec = 'testData/spectrum_5ps.dat'
+__filePathSpec = 'testData/spectrum2_5ps.dat'
 __specDataDelimiter = '\t'
 
 #file path which contains the IRF data:
-__filePathIRF = 'testData/irf_5ps.dat'
+__filePathIRF = 'testData/irf2_5ps.dat'
 __irfDataDelimiter = '\t'
 
 

DReconvolutionModel.py

@@ -50,16 +50,16 @@ def Gaussian(x, ampl, sigma, y0, x0, args=()):
     h=N*np.exp(-0.5*((x-x0)/sigma)**2);
     return ampl*h+y0
 
-def Lorentz_Cauchy(x, ampl, a, wing, y0, x0, args=()):
+def Lorentz_Cauchy(x, ampl, s, y0, x0, args=()):
     h=np.zeros(x.size)
-    h=wing/(np.pi*((x-x0)*(x-x0) + wing*wing))
+    h=s/(np.pi*((x-x0)*(x-x0) + s*s))
     return ampl*h+y0
 
-def Pseudovoigt1(x, ampl, a, sigma, wing, y0, x0, args=()):
+def Pseudovoigt1(x, ampl, a, sigma, s, y0, x0, args=()):
     G=np.zeros(x.size)
     L=np.zeros(x.size)
     G=(1.0/(sigma*np.sqrt(2*np.pi)))*np.exp(-0.5*((x-x0)/sigma)*((x-x0)/sigma))
-    L=wing/(np.pi*((x-x0)*(x-x0) + wing*wing))
+    L=s/(np.pi*((x-x0)*(x-x0) + s*s))
     return ampl*(a*G+(1-a)*L)+y0
 
 def Pearson7(x, ampl, alpha, m, y0, x0, args=()):