I have several time series signals (8x8) that I would like to plot using subplot. My data are stored in a matrix called H(x, y, N) where N is the number of points in each signal. I would like to display the 64 signals using subplots.
fig = figure(figsize=(12,8)) time = np.arange(0, Nt, 1) for x in range(8): for y in range(8): subplot(8,y+1,x+1) plot(time,H[x,y,:]) What I get is 8 signals in the first row, 4 in the second one, then 2, 2, 1, 1, 1 and 1.
That's not how subplot indexing works. From the docs to subplot:
subplot(nrows, ncols, plot_number)Where nrows and ncols are used to notionally split the figure into
nrows * ncolssub-axes, and plot_number is used to identify the particular subplot that this function is to create within the notional grid. plot_number starts at 1, increments across rows first and has a maximum ofnrows * ncols.
So, you want to have nrows=8, ncols=8 and then a plot_number in the range 1-64, so something like:
nrows,ncols = 8,8 for y in range(8): for x in range(8): plot_number = 8*y + x + 1 subplot(nrows,ncols,plot_number) plot(time,H[x,y,:]) # Remove tick labels if not on the bottom/left of the grid if y<7: gca().set_xticklabels([]) if x>0: gca().set_yticklabels([]) To remove tick labels, use gca() to get the current axes, and the set the xticklabels and yticklabels to an empty list: []
xticklabels and yticklabels. Try setting them to an empty list for the subplots you want to remove tick labels on. See my edit for a suggestion