|  |  |  | @ -11,10 +11,13 @@ | 
			
		
	
		
			
				
					|  |  |  |  | wpylib.math.fitting.funcs_pec module | 
			
		
	
		
			
				
					|  |  |  |  | A library of simple f(x) functions for PEC fitting | 
			
		
	
		
			
				
					|  |  |  |  | 
 | 
			
		
	
		
			
				
					|  |  |  |  | For use with OO-style x-y curve fitting interface. | 
			
		
	
		
			
				
					|  |  |  |  | For use with the OO-style x-y curve fitting interface | 
			
		
	
		
			
				
					|  |  |  |  | (fit_func_base). | 
			
		
	
		
			
				
					|  |  |  |  | """ | 
			
		
	
		
			
				
					|  |  |  |  | 
 | 
			
		
	
		
			
				
					|  |  |  |  | import numpy | 
			
		
	
		
			
				
					|  |  |  |  | from wpylib.math.fitting import fit_func_base | 
			
		
	
		
			
				
					|  |  |  |  | from wpylib.math.fitting.funcs_simple import fit_harm | 
			
		
	
		
			
				
					|  |  |  |  | 
 | 
			
		
	
		
			
				
					|  |  |  |  | 
 | 
			
		
	
		
			
				
					|  |  |  |  | class harm_fit_func(fit_func_base): | 
			
		
	
	
		
			
				
					|  |  |  | @ -99,7 +102,7 @@ class morse2_fit_func(fit_func_base): | 
			
		
	
		
			
				
					|  |  |  |  |     imin = numpy.argmin(y) | 
			
		
	
		
			
				
					|  |  |  |  |     harm_params = fit_harm(x[0], y) | 
			
		
	
		
			
				
					|  |  |  |  |     if self.debug >= 10: | 
			
		
	
		
			
				
					|  |  |  |  |       print "Initial guess by fit_harm gives: ", harm_params | 
			
		
	
		
			
				
					|  |  |  |  |       print("Initial guess by fit_harm gives: %s" % (harm_params,)) | 
			
		
	
		
			
				
					|  |  |  |  |     self.guess_params = (y[imin], harm_params[0][1], x[0][imin], 0.01 * harm_params[0][1]) | 
			
		
	
		
			
				
					|  |  |  |  |     return self.guess_params | 
			
		
	
		
			
				
					|  |  |  |  |   def Guess_xy_old(self, x, y): | 
			
		
	
	
		
			
				
					|  |  |  | @ -134,7 +137,7 @@ class ext3Bmorse2_fit_func(fit_func_base): | 
			
		
	
		
			
				
					|  |  |  |  |     imin = numpy.argmin(y) | 
			
		
	
		
			
				
					|  |  |  |  |     harm_params = fit_harm(x[0], y) | 
			
		
	
		
			
				
					|  |  |  |  |     if self.debug >= 10: | 
			
		
	
		
			
				
					|  |  |  |  |       print "Initial guess by fit_harm gives: ", harm_params | 
			
		
	
		
			
				
					|  |  |  |  |       print("Initial guess by fit_harm gives: %s " % (harm_params,)) | 
			
		
	
		
			
				
					|  |  |  |  |     self.guess_params = (y[imin], harm_params[0][1], x[0][imin], 0.01 * harm_params[0][1], 0) | 
			
		
	
		
			
				
					|  |  |  |  |     return self.guess_params | 
			
		
	
		
			
				
					|  |  |  |  | 
 | 
			
		
	
	
		
			
				
					|  |  |  | 
 |