Matplotlib subplot using nested for loop to plot timeseries (trajectory) - matplotlib

Question

I want to plot 5 timetable series using nested for loop. here is my code attached and the results of the plots. I use the first loop to generate each when I put plt.show() outside the first loop, it will just plot the fifth series, and when I put the plt.show() outside the inside (second) loop, it will just plot the first series.
How can I plot all five series using the nested loop?
How can I plot all of the same y variables with the same bound (shared y) in the loop?
fig = plt.figure(figsize=(38, 55))
for i in range(len(Traj_List)): # first loop for creating subplots for each of timeseries data (Trajectory of some states like joint angle and joint speed and muscle activations)
# States.
stateNames = list(Traj_List[i].getStateNames()) # Traj_List is a list of timeseries data
numStates = len(stateNames)
dim = np.sqrt(numStates)
if dim == np.ceil(dim):
numRows = int(dim)
numCols = int(dim)
else:
numCols = int(np.min([numStates, 4]))
numRows = int(np.floor(numStates / 4))
if not numStates % 4 == 0:
numRows += 1
# color = iter(plt.rainbow(np.linspace(0, 1, 5)))
color = ['r', 'b', 'g', 'y', 'm']
lines = ["-", "--", "-.", ":", "-."]
linewidth = [3, 2.5, 3.5, 2, 3]
for j in np.arange(numStates): # the second loop plots each time series data (states) against time.
ax = fig.add_subplot(numRows, numCols, int(j + 1))
ax.plot(Traj_List[i].getTimeMat(),
Traj_List[i].getStateMat(stateNames[j]), linestyle=lines[i], color=color[i],
linewidth=linewidth[i], label=Label_List[i])
stateName = stateNames[j]
ax.set_title(stateName)
ax.set_xlabel('time (s)')
# ax.set_xlim(0, 1)
ax.legend(loc='best')
if 'value' in stateName:
ax.set_ylabel('position (rad)')
elif 'speed' in stateName:
ax.set_ylabel('speed (rad/s)')
elif 'activation' in stateName:
ax.set_ylabel('activation (-)')
ax.set_ylim(0, 1)
# plt.show()
fig.tight_layout()
plt.show()
plt.close()

Answer 1

Try to only make the figure once, and save the axes. In pseudo code, because I can't run your code anyway:
for i in range(N):
M, N = size(data)
if i == 0:
# only make the axes once!
fig, axs = plt.subplots(M, N)
for j in range(M*N):
axs.flat[j].plot(yourdata)
I'm sure my ranges are not correct for your data, but that is easy to sort out. The point is don't keep recreating the axes using plt.add_subplot. Just create them once, and then plot on them.