X0_low, _, width_low, height_low = ss.get_position(fig).boundsĪx.set_position(pos=) If (row % 2 = 0) and (col = 0): # upper-half row (first subplot)Įlif (row % 2 = 1): # lower-half row (all subplots)
Row, col = ss.num1 // n_cols, ss.num1 % n_cols The spacing between vertical pairs is reduced to zero by moving all lower-half subplots up. The upper-half's first subplot (column 0) should always be present So make sure the subplots have been added in this order. fig.axes should be ordered top to bottom (ascending row number). n_cols: number of columns in the figure Here's a solution with getting into tedious low-level hacks: import matplotlib.pyplot as plt Note that you can change the number of rows also, you can adjust the size of the blank space compared to the subplots by tweaking the row_height/ space_height ratio (both must be integers). Grid_row = row_height*ind_row + space_height*num_sep_rows(ind_row+1)Īx_list += Grid = (row_height*num_rows + space_height*num_sep_rows(num_rows), num_cols) I tried this: import matplotlib.pyplot as plt # set xlabel outside of for loop so only the last axis get an xlabelįig.Without going to tedious low-level hacks like adjusting the position of the axes manually, I would suggest using a grid but just leaving some of the rows blank. (NOTE: I created fake data for illustrative purposes.) fig, axes = plt.subplots(3,1, figsize=(12,5), dpi=80, facecolor='w',Įdgecolor='k', sharex=True) # sharex shares the x-axisįor i, ax in enumerate(axes): # need to enumerate to slice the data In this case it is a 1-D array because we only call for 1 column. What's the difference? plt.subplots(3,1) returns a tuple of a figure object and an array of axis objects. My recommendation would be to use plt.subplots(3, 1) (notice the extra "s") rather than repeated calls to plt.subplot. The axis will resize the plot limits for you, unless you have a specific reason for overriding them. Since you have 3 subplots, I think you wanted to 3 rows stacked vertically. One options is to reduce the number of ticks, the other is to stretch the x-axis out.
When you add the data to the plot, ax.set_xticks(time) adds 45 ticks to the xaxis (which is quite a few), and ax.set_xticklabels(time, fontsize = 8) adds a label at each tick. subplot(3, 4, 3) you are only selecting the first 3 of the 12 sections. We can number them with the following code: plt.figure( figsize=(12, 5), dpi=80, facecolor='w', edgecolor='k' )Īx.annotate(s=str(N), xy=(.4.4), fontsize=16) subplot(3,4,_) breaks the plot into 3 rows and 4 columns and the underscore selects which piece of this grid to select starting with 1 (instead of 0). After you instantiate the plot, you call ax = plt.subplot(3, 4, _) 3 times. Ok, so several things are happening here. Thanks in advance for any assistance (and if anyone can offer more general advice about what I'm doing in addition to specific advice about solving this problem, I would appreciate the edification). The pyplot documentation is essentially gibberish to me.
#Pyplot subplot spacing vspace how to
I've searched and found no explanation as to how to do this that's written at a level I can understand. I have some ideas about how to solve this, but I feel like I need to resolve 1) first.ģ) The axes are so small that the xticks appear all bunched up Reducing the size of the figure doesn't make the subplots any more easily readable.Ģ) They are too close together. There are currently 9 missing plots, as I'm sure you could guess,ġ) Each subplot is tiny compared to the size of the figure (and, you know. Plt.title('Annual Mean Global Mean Temperature', fontsize=14) Yearlymean_gm = np.load('ts_globalmean_annualmean.npz')
I have this: import matplotlib.pyplot as plt I have searched for similar problems and not found any, so I apologize.
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