def plot_replication_program():
from sampling_KJMA_kinetics import get_oriter_from_oris
from sampling_KJMA_kinetics import get_origins_from_phantoms
from sampling_KJMA_kinetics import get_timing_from_oris
lim = {'y':np.arange(100),'u':np.arange(100),'v':1,'dy':1,'Ny':100,'du':1,'Nu':100}
phantoms = [(10,20), (20,25), (60,30)]
phantoms = np.array(phantoms, dtype=[('y',float),('u',float)])
oris = get_origins_from_phantoms(phantoms, lim)
oriter = get_oriter_from_oris(oris, lim)
timing = get_timing_from_oris(oris, lim)
fig, ax = plt.subplots(figsize=(5,5))
remove_junk_xyplot(ax)
ax.set_ylim([0, 100])
ax.set_xlim([0, 100])
ax.set_yticks([0,100])
ax.set_xticks([0,100])
ax.plot(oriter['y'],oriter['u'],color='k', linewidth=2)
ax.set_xlabel('position')
ax.set_ylabel('time')
delta_y = 1
ax.text(x=10,y=20-delta_y,s=r'$O_1$', color='gray',
verticalalignment='top', horizontalalignment='center')
ax.text(x=20,y=25-delta_y,s=r'$O_2$', color='gray',
verticalalignment='top', horizontalalignment='center')
ax.text(x=60,y=30-delta_y,s=r'$O_3$', color='gray',
verticalalignment='top', horizontalalignment='center')
ax.text(x=17.5,y=27.5+delta_y,s=r'$T_1$', color='gray',
verticalalignment='bottom', horizontalalignment='center')
ax.text(x=42.5,y=47.5+delta_y,s=r'$T_2$', color='gray',
verticalalignment='bottom', horizontalalignment='center')
def animation_replication_program():
from sampling_KJMA_kinetics import get_oriter_from_oris
from sampling_KJMA_kinetics import get_origins_from_phantoms
from sampling_KJMA_kinetics import get_timing_from_oris
lim = {'y':np.arange(100),'u':np.arange(100),'v':1,'dy':1,'Ny':100,'du':1,'Nu':100}
phantoms = [(10,20), (20,25), (60,30)]
phantoms = np.array(phantoms, dtype=[('y',float),('u',float)])
oris = get_origins_from_phantoms(phantoms, lim)
oriter = get_oriter_from_oris(oris, lim)
timing = get_timing_from_oris(oris, lim)
dark_color = [(0.10588235294117647, 0.6196078431372549, 0.4666666666666667),
(0.8509803921568627, 0.37254901960784315, 0.00784313725490196)]
from matplotlib import animation
tmin, tmax, x = 0, 100, np.arange(100)
t = np.linspace(tmin,tmax,200) # time coordinates
replicated = np.zeros((len(t), len(x)), dtype=int)
for i, t_i in enumerate(t):
replicated[i,:] = (timing['u'] < t_i)
fig, ax = plt.subplots(figsize=(5,5))
ax.spines['top'].set_visible(False) # no top or right spine
ax.spines['right'].set_visible(False)
ax.spines['left'].set_visible(False) # no top or right spine
ax.spines['bottom'].set_visible(False)
ax.set_ylim([tmin, tmax])
ax.set_xlim([0, 100])
ax.set_xticks([])
ax.set_yticks([])
ax.set_xlabel('position')
ax.set_ylabel('time')
ax.plot(oriter['y'],oriter['u'],color='k', linewidth=2)
timeline, = ax.plot([],[],color='gray',alpha=0.5, linewidth=2)
DNA, = ax.plot([],[],color=dark_color[0])
ax.hlines(y=tmin+2,xmin=x.min(),xmax=x.max(),color=dark_color[1])
def init():
timeline.set_data([0,99], [0,0])
DNA.set_data([], [])
def update(n):
# n = frame counter
timeline.set_data([0,100],[t[n],t[n]])
DNA.set_data(x, tmin+2+2*replicated[n,:])
anim = animation.FuncAnimation(fig, update, init_func=init, frames=len(t), interval=40, blit=True)
return anim
