X-Git-Url: http://mmka.chem.univ.gda.pl/gitweb/?a=blobdiff_plain;f=files%2Fmatplotlib_fit_hist.py;h=b31025e51bdfc67879fdf30e65ebc743177b4fba;hb=d03bf58e6dc3d690486f8eb7a8f18ad34938c71f;hp=e08d110c30d3dd2f15165156ea9c42678fcc2553;hpb=3cd10cb73439c774e87c98f6873b12eff8109ffa;p=django_unres.git diff --git a/files/matplotlib_fit_hist.py b/files/matplotlib_fit_hist.py index e08d110..b31025e 100755 --- a/files/matplotlib_fit_hist.py +++ b/files/matplotlib_fit_hist.py @@ -11,9 +11,11 @@ import sys def prob_T(x,a): gg=np.float128(g) - aa=np.float128(10**(-gg-2)*a) +# aa=np.float128(10**(-gg-2)*a) + aa=np.float128(a) Tr=np.float128(t_bath) - return np.exp( np.log(aa) + (gg-2)/2*np.log(x) - gg*x/(2*Tr) ) + return np.exp( aa + (gg-2)/2*np.log(x) - gg*x/(2*Tr) ) +# return np.exp( np.log(aa) + (gg-2)/2*np.log(x) - gg*x/(2*Tr) ) # return aa * ( x**((gg-2)/2) * np.exp( -gg*x/(2*Tr) ) ) #x,y= np.loadtxt('1L2Y_L_GB000.stat',usecols=(0,10),skiprows=30,unpack=True) @@ -27,11 +29,14 @@ with open('md.stat','r') as f: ncolumns=len(line.split()) if ncolumns==14: - x,y= np.loadtxt('md.stat',usecols=(0,10),skiprows=10,unpack=True) - x1,e,r,gy,nc= np.loadtxt('md.stat',usecols=(0,3,5,12,6),skiprows=0,unpack=True) + x,y= np.loadtxt('md.stat',usecols=(1,10),skiprows=10,unpack=True) + x1,e,r,gy,nc= np.loadtxt('md.stat',usecols=(1,3,5,12,6),skiprows=0,unpack=True) else: - x,y= np.loadtxt('md.stat',usecols=(0,6),skiprows=10,unpack=True) - x1,e,gy= np.loadtxt('md.stat',usecols=(0,3,8),skiprows=0,unpack=True) + x,y= np.loadtxt('md.stat',usecols=(1,6),skiprows=10,unpack=True) + x1,e,gy= np.loadtxt('md.stat',usecols=(1,3,8),skiprows=0,unpack=True) + +x=x*0.0489 +x1=x1*0.0489 h,bin=np.histogram(y,bins=50,density=True) @@ -44,7 +49,8 @@ plt.xlabel('temperature') center = (bin[:-1] + bin[1:]) / 2 #print bin #print center -popt, pcov = curve_fit(prob_T, center, h) +start = (g-2)/2*np.log(t_bath) - g*t_bath/(2*t_bath) +popt, pcov = curve_fit(prob_T, center, h, p0=-start) xfine = np.linspace(min(bin), max(bin), 100) #print popt @@ -58,26 +64,26 @@ plt.savefig('temp_hist.png') #plt.show() plt.clf() -plt.xlabel('step') +plt.xlabel('time [ps]') plt.ylabel('potential energy') plt.plot(x1,e,'.') plt.savefig('md_ene.png') plt.clf() -plt.xlabel('step') +plt.xlabel('time [ps]') plt.ylabel('radius of gyration') plt.plot(x1,gy,'.') plt.savefig('md_gyr.png') if ncolumns==14: plt.clf() - plt.xlabel('step') + plt.xlabel('time [ps]') plt.ylabel('RMSD') plt.plot(x1,r,'.') plt.savefig('md_rms.png') plt.clf() - plt.xlabel('step') + plt.xlabel('time [ps]') plt.ylabel('fraction of native side-chain concacts') plt.plot(x1,nc,'.') plt.savefig('md_fracn.png')