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convert some sample plots to use plt.subplots() instead of other methods #17340

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Merged
merged 9 commits into from
May 25, 2020
Merged

convert some sample plots to use plt.subplots() instead of other methods #17340

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a2765d5
convert some sample plots to use plt.subplots() instead of other methods
asafmaman101 May 6, 2020
3c4faca
fixing line length
asafmaman101 May 6, 2020
cd25cea
changing the use of gridspec() to avoid repeatation, removing unpacki…
asafmaman101 May 7, 2020
2ae3dd9
fix exeeded line while linting test
asafmaman101 May 7, 2020
1e58203
revert plot_streamplot.py to original version
asafmaman101 May 11, 2020
a664c8a
adding both methods how to generate multiple plots
asafmaman101 May 17, 2020
a9d580e
fix linting
asafmaman101 May 17, 2020
bc444fa
revert xkcd.py
asafmaman101 May 19, 2020
820bbdf
modify heading in subplot.py
asafmaman101 May 25, 2020
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15 changes: 9 additions & 6 deletions 15 examples/images_contours_and_fields/plot_streamplot.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,30 +22,30 @@
V = 1 + X - Y**2
speed = np.sqrt(U**2 + V**2)

fig = plt.figure(figsize=(7, 9))
gs = gridspec.GridSpec(nrows=3, ncols=2, height_ratios=[1, 1, 2])

gs = {'height_ratios': [1, 1, 2]}
fig, axes = plt.subplots(nrows=3, ncols=2, gridspec_kw=gs, figsize=(7, 9))
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We usually use axs for a list of axes.

((ax0, ax1), (ax2, ax3), (ax4, ax5)) = axes
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There is really no need to unpack these, so don't do so. Just refer to axs[0, 1] etc.


# Varying density along a streamline
ax0 = fig.add_subplot(gs[0, 0])
ax0.streamplot(X, Y, U, V, density=[0.5, 1])
ax0.set_title('Varying Density')

# Varying color along a streamline
ax1 = fig.add_subplot(gs[0, 1])
plt.sca(ax1)
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I don't see why this is needed.

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Hi, thanks for the review. I deleted line 34 to fix the issue (of consistant use of .subplots() instead of different method in each sample) and in line 35 I added sca() in order to display the colorbar next to the right axes.

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I think it would be better to pass the axes to fig.colorbar (as fig.calorbar(strm.lines, ax=axN)) instead. That will explicitly tell colorbar which axes to steal the space from rather than relying on the global state.

strm = ax1.streamplot(X, Y, U, V, color=U, linewidth=2, cmap='autumn')
fig.colorbar(strm.lines)
ax1.set_title('Varying Color')

# Varying line width along a streamline
ax2 = fig.add_subplot(gs[1, 0])
lw = 5*speed / speed.max()
ax2.streamplot(X, Y, U, V, density=0.6, color='k', linewidth=lw)
ax2.set_title('Varying Line Width')

# Controlling the starting points of the streamlines
seed_points = np.array([[-2, -1, 0, 1, 2, -1], [-2, -1, 0, 1, 2, 2]])

ax3 = fig.add_subplot(gs[1, 1])
plt.sca(ax3)
strm = ax3.streamplot(X, Y, U, V, color=U, linewidth=2,
cmap='autumn', start_points=seed_points.T)
fig.colorbar(strm.lines)
Expand All @@ -61,6 +61,9 @@
U[:20, :20] = np.nan
U = np.ma.array(U, mask=mask)

gs = gridspec.GridSpec(nrows=3, ncols=2, height_ratios=[1, 1, 2])
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Not sure this is the best way to do this. @jklymak?

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Yeah, don't create a new gridspec. You can get the old one with gs = axs.get_subpltospec().get_gridspec().

ax4.remove()
ax5.remove()
ax4 = fig.add_subplot(gs[2:, :])
ax4.streamplot(X, Y, U, V, color='r')
ax4.set_title('Streamplot with Masking')
Expand Down
2 changes: 1 addition & 1 deletion 2 examples/pie_and_polar_charts/polar_demo.py
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Expand Up @@ -12,7 +12,7 @@
r = np.arange(0, 2, 0.01)
theta = 2 * np.pi * r

ax = plt.subplot(111, projection='polar')
fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
ax.plot(theta, r)
ax.set_rmax(2)
ax.set_rticks([0.5, 1, 1.5, 2]) # Less radial ticks
Expand Down
8 changes: 4 additions & 4 deletions 8 examples/showcase/xkcd.py
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Expand Up @@ -14,8 +14,8 @@
# Based on "Stove Ownership" from XKCD by Randall Munroe
# https://xkcd.com/418/

fig = plt.figure()
ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))
fig, ax = plt.subplots()
ax.set_position((0.1, 0.2, 0.8, 0.7))
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add_axes() is specifically designed for adding axes at arbitrary locations. IMHO it's the right method to use here. Creating a figure and then creating an axes at a specific position is conceptually simpler than creating a figure and an axes in the default layout and then moving the existing axes raound.

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subplots sets up a gridspec for the underlying axes, whereas if you are just going to move it that gridspec is not needed. So there is some advantage to add_axes here.

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Hi, no problem I can revert it to the original version, but I want to make sure I understand - you suggest to keep it the same way it was in the beginning? or some other method using both subplots and add_axes (if it's feasible, didn't already thought about it to details).

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Hi, no problem I can revert it to the original version, but I want to make sure I understand - you suggest to keep it the same way it was in the beginning? or some other method using both subplots and add_axes (if it's feasible, didn't already thought about it to details).

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That example was already correct as it was originally. Please revert your change.

ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.set_xticks([])
Expand Down Expand Up @@ -44,8 +44,8 @@
# Based on "The Data So Far" from XKCD by Randall Munroe
# https://xkcd.com/373/

fig = plt.figure()
ax = fig.add_axes((0.1, 0.2, 0.8, 0.7))
fig, ax = plt.subplots()
ax.set_position((0.1, 0.2, 0.8, 0.7))
ax.bar([0, 1], [0, 100], 0.25)
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
Expand Down
18 changes: 9 additions & 9 deletions 18 examples/subplots_axes_and_figures/subplot.py
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Expand Up @@ -15,14 +15,14 @@
y1 = np.cos(2 * np.pi * x1) * np.exp(-x1)
y2 = np.cos(2 * np.pi * x2)

plt.subplot(2, 1, 1)
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From the filename, I'm not sure if this file is actually about subplot...

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Did you mean it should be an example of the subplot() function? The page is referenced from the section “ Multiple Subplots”, so I guess it does not specifically refer to subplot().

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I think its reasonable to have what we feel is the canonical way here.

Can I suggest you add a second figure that shows subplot though with a bit of preceding text that says it is an alternate way using pyplot?

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BTW, the rest seems fine. Ping for a review, and thanks for working on this!

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Not sure I fully understand what you mean, you recommand adding a second example in the same page with the original method of subplot?

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Yes. Each example can have multiple figures on it.

plt.plot(x1, y1, 'o-')
plt.title('A tale of 2 subplots')
plt.ylabel('Damped oscillation')

plt.subplot(2, 1, 2)
plt.plot(x2, y2, '.-')
plt.xlabel('time (s)')
plt.ylabel('Undamped')
fig, (ax1, ax2) = plt.subplots(2, 1)
fig.suptitle('A tale of 2 subplots')

ax1.plot(x1, y1, 'o-')
ax1.set_ylabel('Damped oscillation')

ax2.plot(x2, y2, '.-')
ax2.set_xlabel('time (s)')
ax2.set_ylabel('Undamped')

plt.show()
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