AkvoFluo/plotHE.py

from plotdata import *

if __name__ == "__main__":
    print sys.argv
    colour = ['blue','red','green']
    ic = 0
        
    #plt.figure(2) 
    #axmine = plt.gca()
    #axmine2 = plt.twinx()
    
    for f in sys.argv[1::]:
        ORS = ORSProc(f)
        ORS.WindowAndStack()
        ORS.T2EnvelopeDetect()
        
        #mono, rfit, [a0,b0,mt2] = ORS.MonoFit()
        #env, mod, Time = ORS.DistFit( a0 )
        #env, mod, Time = ORS.DistFit(  )

        # Subtract DC term before 2D fit? Kind of kludgy but I don't see a way around it right now. 

        plt.figure(1)
        print ORS.T2T, ORS.T2D
        plt.plot((1e-6*ORS.T2T**3), np.log(np.imag(ORS.T2D)), 'o', markersize=8)
        #plt.plot(ORS.T2T, np.real(ORS.T2D))
        #plt.plot(ORS.T2T, mono, '--',label=rfit, color=colour[ic])
        #plt.plot(ORS.T2T, a0+env, '-+', color=colour[ic], label='dist')
        #plt.plot(ORS.T2T, env, '-+',color=colour[ic], label='dist')
        #plt.legend()

        #guess = np.zeros( len(Time.T2Bins ) )
        #total = np.zeros( len(Time.T2Bins ) )
        #ib = 0
        #for bins in Time.T2Bins:
        #    if bins > mt2:
        #        guess[ib] = a0 + b0
        #        total[ib] = np.sum( mod ) # TODO find log norm and plot there instead! 
        #        break
        #    ib += 1
     
        #LogMeanT2 = numpy.exp(numpy.sum(PWC*numpy.log(T2BINS), axis=1) / theta ) 
        #theta = np.sum(mod)
        #LogMeanT2 = np.exp(np.sum( mod * np.log(Time.T2Bins) ) / theta ) 

        #plt.figure(2) 
        #axmine.plot(Time.T2Bins, mod, linewidth=2, label=f, color=colour[ic])
        #axmine2.plot(Time.T2Bins, guess, '--',color=colour[ic], linewidth=2, label="guess")
        #axmine2.plot(mt2, a0+b0, 'o',color=colour[ic], markersize=8, label="guess")
        #axmine2.plot(Time.T2Bins, guess, '-',color=colour[ic], linewidth=2, label="total")
        #axmine2.plot(LogMeanT2, theta, 's',color=colour[ic], markersize=8, label="total")
        ic += 1
    #axmine2.set_ylim([0, axmine2.get_ylim()[1]])
    #leg = axmine2.legend(numpoints=1)
    plt.xlabel(r"$\tau_e^2$ [s]", color='black', fontsize=16)
    #plt.ylabel(r"$T_2$ [s]", color='black')
    plt.ylabel(r"signal [rku]", color='black', fontsize=16)
    #axmine.set_ylabel(r"$A_0$ [i]", color='black')
    
    #plt.figure(1)
    #plt.savefig(sys.argv[1].strip(".ors")+"_comp1DT2.pdf", facecolor='white', edgecolor='white', dpi=200)
    
    #plt.figure(2)
    #plt.savefig(sys.argv[1].strip(".ors")+"_comp2DT2.pdf", facecolor='white', edgecolor='white', dpi=200)
    plt.savefig("hahn.pdf")
    plt.show()
    exit()