def analyseSim(cRes): v = cRes.v #v = (v>0)*1.0 delta = SND.getDelta(v) Omega = SND.getOmega(delta) redHom = SND.getHomo(v) OmegaM = Omega.mean() redHomM = redHom.mean() cRes.OmegaM = OmegaM cRes.redHomM = redHomM return cRes
def analyseSim(cRes): v = cRes.imI v =(v>0)*1.0 #Binarizing the data #plt.imshow(v) delta = SND.getDelta(v) Omega = SND.getOmega(delta) redHom = SND.getHomo(v) OmegaM = Omega.mean() redHomM = redHom.mean() cRes.OmegaM = OmegaM cRes.redHomM = redHomM return cRes
#v = resDat.v; v = np.asanyarray(Image.open('testBild_Streifen_Noise.tif'),float) v = (v>1)*1.0 # test f1 = plt.figure() ax = f1.add_axes([0, 0, 1, 1]) plt.imshow(v) plt.title('Spatiotemporal') plt.xlabel('t') plt.ylabel('s') f1.show() delta = SND.getDelta(v) Omega = SND.getOmega(delta) redHom = SND.getHomo(v) f2 = plt.figure() plt.plot(Omega) plt.title('Omega') plt.xlabel('t') plt.ylabel('Omega') f2.show() f3 = plt.figure() plt.title('Reduced homogeneity') plt.xlabel('t') plt.ylabel('h') plt.plot(redHom)