93 lines
2.6 KiB
Python
93 lines
2.6 KiB
Python
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#!/usr/bin/python
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import sys
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import os.path
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import time
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import numpy as np
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import os
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from cbx.dynamics import CBXDynamic, CBO
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localtime = time.asctime( time.localtime(time.time()) )
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print(localtime)
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sys.path.append("/home/semeraro/Programming/PythonStuff/python_tools")
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from Tools import Reading
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from Tools import ReadData
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from Tools import PlotData
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import FitTools
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import TSA_algorithm
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############################################################
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############################################################
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############################################################
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def X2function(Q,IDATA,I,ERR,N):
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'X^2 calculation'
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X2 = np.sum( ( ( IDATA-I ) / ERR )**2 )
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return X2/(Q.shape[0]-(N-1))
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############################################################
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t0=time.time()
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############################################################ Read Options & Parameters
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############### Read File & Options
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print("\n-- Reading File:")
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read_par = Reading(sys.argv)
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iters = int(sys.argv[2])
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print("\n-- Reading Options")
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options = read_par.Options()
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############### Read Function, from the MODEL parameter
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"-- Reading Function"
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(function, pltOptions) = FitTools.ChooseFunction( options['function'] )
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############### Read Parameters
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print("\n-- Reading Parameters\n")
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(NAME, PAR, FIX, PRIOR, L_LIM, H_LIM) = read_par.Parameters()
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############################################################ Read & Select Data
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(Q, IDATA ,ERR) = ReadData( options['datafile'] ).SelectColumns( options['qmin'],
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options['qmax'],
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options['bing'],
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options['err_mul'] )
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lo_bounds = np.array(L_LIM)
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hi_bounds = np.array(H_LIM)
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free_idx = np.array(FIX) == '-'
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params = np.array(PAR)
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N_free = sum(free_idx)
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x_init = np.array(params[free_idx])
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print("# params: " + str(len(params)))
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print("# fixed : " + str(sum(~free_idx)))
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print("# free : " + str(sum(free_idx)))
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print("# len(x): " + str(len(x_init)))
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def set_params_vector(x):
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params[free_idx] = x
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def check_bounds(x):
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return (lo_bounds <= x).all() and (x <= hi_bounds).all()
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def objective(x):
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print(x)
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set_params_vector(x)
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if not check_bounds(params): return 1e10
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I_pre = function(Q, params)
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I = np.array(I_pre.intensity())
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print(I.max())
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return X2function(Q,IDATA,I,ERR,N_free)
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dyn = CBXDynamic(objective, d = N_free)
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dyn.optimize()
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# cbo = CBO(objective, x=x_init)
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# cbo = CBO(objective, x=x_init, d=N_free, sigma=0.1, dt=0.01)
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# cbo.optimize()
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