'figure.subplot.bottom':0.15, 'figure.subplot.top':0.95, 'figure.subplot.left':0.15, 'figure.subplot.right':0.92} hexcols = ['#332288', '#88CCEE', '#44AA99', '#117733', '#999933', '#DDCC77',\ '#CC6677', '#882255', '#AA4499', '#661100', '#6699CC', '#AA4466','#4477AA'] mpl.rcParams.update(params) import colormaps as cmaps plt.register_cmap(name='viridis', cmap=cmaps.viridis) plt.set_cmap(cmaps.viridis) data = np.loadtxt("kick.dataNS") orbit = kicks.post_kick_parameters_P(11.9,12.4,56.4,1.4,0,0,0) norm = mpl.colors.Normalize(vmin=0,vmax=16) fig, axes= plt.subplots(1) scatter = axes.scatter(data[:,3][np.logical_and(data[:,5]>0,True)],\ data[:,4][np.logical_and(data[:,5]>0,True)], c=data[:,5][np.logical_and(data[:,5]>0,True)],\ marker="o", s=5, linewidth='0', cmap = "viridis", norm=norm, rasterized = True) axes.scatter(orbit[0], orbit[1], marker="s", s=20, linewidth='0') for kickv in [100,200,300,400]: orbit = [kicks.post_kick_parameters_P(11.9,12.4,56.4,1.4,kickv,theta,0) \ for theta in np.linspace(0,math.pi,50)] orbit = np.array(orbit) axes.plot(orbit[:,0],orbit[:,1],"k-",linewidth=0.5)
'figure.subplot.bottom':0.15, 'figure.subplot.top':0.95, 'figure.subplot.left':0.15, 'figure.subplot.right':0.92} hexcols = ['#332288', '#88CCEE', '#44AA99', '#117733', '#999933', '#DDCC77',\ '#CC6677', '#882255', '#AA4499', '#661100', '#6699CC', '#AA4466','#4477AA'] mpl.rcParams.update(params) import colormaps as cmaps plt.register_cmap(name='viridis', cmap=cmaps.viridis) plt.set_cmap(cmaps.viridis) data = np.loadtxt("kick.dataNS") orbit = kicks.post_kick_parameters_P(2.348553e+01, 5.486435e+00, 5.504611e+01, 1.4,0,0,0) norm = mpl.colors.Normalize(vmin=0,vmax=16) fig, axes= plt.subplots(1) scatter = axes.scatter(data[:,3][np.logical_and(data[:,5]>0,True)],\ data[:,4][np.logical_and(data[:,5]>0,True)], c=data[:,5][np.logical_and(data[:,5]>0,True)],\ marker="o", s=5, linewidth='0', cmap = "viridis", norm=norm, rasterized = True) axes.scatter(orbit[0], orbit[1], marker="s", s=20, linewidth='0') print("fraction below 1Gyr", \ np.sum(data[:,6][np.logical_and(data[:,5]>0,data[:,5]<1)])\ /np.sum(data[:,6][np.logical_and(data[:,5]>0,data[:,5]<13.8)]), np.sum(data[:,6][np.logical_and(data[:,5]>0,True)]), np.sum(data[:,6][np.logical_and(data[:,5]>0,data[:,5]<13.8)]))
'figure.subplot.bottom':0.15, 'figure.subplot.top':0.95, 'figure.subplot.left':0.15, 'figure.subplot.right':0.92} hexcols = ['#332288', '#88CCEE', '#44AA99', '#117733', '#999933', '#DDCC77',\ '#CC6677', '#882255', '#AA4499', '#661100', '#6699CC', '#AA4466','#4477AA'] mpl.rcParams.update(params) import colormaps as cmaps plt.register_cmap(name='viridis', cmap=cmaps.viridis) plt.set_cmap(cmaps.viridis) data = np.loadtxt("kick.dataBH2") orbit = kicks.post_kick_parameters_P(1.391271e+01, 3.635118e+01, 1.331844e+02, 3.635118e+01*0.9,0,0,0) norm = mpl.colors.Normalize(vmin=0,vmax=16) fig, axes= plt.subplots(1) scatter = axes.scatter(data[:,3][np.logical_and(data[:,5]>0,True)],\ data[:,4][np.logical_and(data[:,5]>0,True)], c=data[:,5][np.logical_and(data[:,5]>0,True)],\ marker="o", s=10, linewidth='0', cmap = "viridis", norm=norm, rasterized = True) axes.scatter(orbit[0], orbit[1], marker="s", s=40, linewidth='0') for kickv in [50,100]: orbit = [kicks.post_kick_parameters_P(1.391271e+01, 3.635118e+01, 1.331844e+02, 3.635118e+01*0.9,kickv,theta,0) \ for theta in np.linspace(0,math.pi,50)] orbit = np.array(orbit) axes.plot(orbit[:,0],orbit[:,1],"k-",linewidth=0.5)
'figure.subplot.bottom':0.15, 'figure.subplot.top':0.95, 'figure.subplot.left':0.15, 'figure.subplot.right':0.92} hexcols = ['#332288', '#88CCEE', '#44AA99', '#117733', '#999933', '#DDCC77',\ '#CC6677', '#882255', '#AA4499', '#661100', '#6699CC', '#AA4466','#4477AA'] mpl.rcParams.update(params) import colormaps as cmaps plt.register_cmap(name='viridis', cmap=cmaps.viridis) plt.set_cmap(cmaps.viridis) data = np.loadtxt("kick.dataBH") orbit = kicks.post_kick_parameters_P(12.7,48.8,136,43.9,0,0,0) norm = mpl.colors.Normalize(vmin=0,vmax=16) fig, axes= plt.subplots(1) scatter = axes.scatter(data[:,3][np.logical_and(data[:,5]>0,True)],\ data[:,4][np.logical_and(data[:,5]>0,True)], c=data[:,5][np.logical_and(data[:,5]>0,True)],\ marker="o", s=5, linewidth='0', cmap = "viridis", norm=norm, rasterized = True) axes.scatter(orbit[0], orbit[1], marker="s", s=20, linewidth='0') for kickv in [40,80]: orbit = [kicks.post_kick_parameters_P(12.7,48.8,136,43.9,kickv,theta,0) \ for theta in np.linspace(0,math.pi,50)] orbit = np.array(orbit) axes.plot(orbit[:,0],orbit[:,1],"k-",linewidth=0.5)