Matplotlib axes'aspect refers to thedata, i.e. it defines the ratio of vertical vs. horizontal data units. However, it seems people often (mis)use it in order to set the aspect of the axes box, which is of course possible by knowing the limits of the data and usingadjustable="box". But it inevitably leads to problems, e.g.

It doesn't work when there is a twinned axes in the game (as inImprove handling of shared axes with specified aspect ratio #10033 (comment), orDefine aspect ratio when using twinx in new version of matplotlib)
It breaks down when limits change, i.e. in most interactive cases (zoom/pan...)
It may lead to overly complicated solutions (Create equal aspect (square) plot with multiple axes when data limits are different?), not even theaxes_grid1 toolkit is able to solve natively.

In short, sometimes people just want to make a square plot.

So it seems useful to introduce abox_aspect parameter, which sets the aspect (i.e. the ratio between height and width) of theaxes box, independent of the data.

Some usecases:

A. A square axes, independent of data

fig1, ax = plt.subplots()ax.set_xlim(300,400)ax.set_box_aspect(1)

B. Shared square axes

fig2, (ax, ax2) = plt.subplots(ncols=2, sharey=True)ax.plot([0,10])ax2.plot([10,20])ax.set_box_aspect(1)ax2.set_box_aspect(1)

C. Square twin axes

fig3, ax = plt.subplots()ax2 = ax.twinx()ax.plot([0,10])ax2.plot([12,10])ax.set_box_aspect(1)

D. Normal plot next to image (works with constrained_layout)

fig4, (ax, ax2) = plt.subplots(ncols=2, constrained_layout=True)im = np.random.rand(16,27)ax.imshow(im)ax2.plot([23,45])ax2.set_box_aspect(im.shape[0]/im.shape[1])

E. Square joint/marginal plot

fig5, axs = plt.subplots(2,2, sharex="col", sharey="row",                         gridspec_kw = dict(height_ratios=[1,3],                                            width_ratios=[3,1]))axs[0,1].set_visible(False)axs[0,0].set_box_aspect(1/3)axs[1,0].set_box_aspect(1)axs[1,1].set_box_aspect(3/1)x,y = np.random.randn(2,400) * np.array([[.5],[180]])axs[1,0].scatter(x,y)axs[0,0].hist(x)axs[1,1].hist(y, orientation="horizontal")

F. Equal data aspect, unequal box aspect

fig6, ax = plt.subplots()ax.add_patch(plt.Circle((5,3), 1))ax.set_aspect("equal", adjustable="datalim")ax.set_box_aspect(0.5)ax.autoscale()

Issues:

~~As@jklymak alreadypointed out, there might be a problem with layout managers, and indeed at least caseE. from above fails with contrained_layout.~~ (fixed byFIX constrained_layout w/ hidden axes #14919)
Obviously a fixed box_aspect only makes sense withadjustable="datalim". Since the order in whichbox_aspect andadjustable are set is arbitrary, this still needs to define in which cases to error out, or silently fall back.

PR Checklist

Has Pytest style unit tests
Code is finallyFlake 8 compliant
New features are documented, with examples if plot related
Documentation is sphinx and numpydoc compliant
Added an entry to doc/users/next_whats_new/ if major new feature (follow instructions in README.rst there)

ImportanceOfBeingErnest added topic: geometry manager

LayoutEngine, Constrained layout, Tight layout

status: work in progress topic: ticks axis labels status: needs comment/discussionneeds consensus on next step labels

Jul 30, 2019

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jklymak commentedJul 30, 2019

Seems cool. But I think we need to sit down and think about all the axes sizing and sharing options a bit more holistically.

I think if you change the non-original position then you can keep constrained layout working.

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ImportanceOfBeingErnest commentedJul 30, 2019

I think if you change the non-original position then you can keep constrained layout working.

I would have thought that is what I'm doing in line 1527. Will need to check this at some later point.

[..] we need to sit down and think about all the axes sizing and sharing options a bit more holistically.

Sure, that's why I put it out in its current state, to see what is possible and to define some working use cases. In general what's still missing is a sharing of geometries (as opposed to sharing of data); or maybe call it a twinning across subplots.

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jklymak commentedJul 30, 2019

Great, then I'm surprised there are issues withconstrained_layout since its no different than a data-aspect constrained axes.constrained_layout only cares about the "original" size.

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jklymak commentedJul 30, 2019

Thanks - that was a bug:#14918, and solution:#14919

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Jul 30, 2019

FIX constrained_layout w/ hidden axes#14919

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anntzer commentedJul 30, 2019

I think it's a great idea :)
I believe this is mutually exclusive with setting the old data aspect? If so, perhaps this should be exposed in the same API, e.g.set_aspect(aspect, "data"/"axes") (the second argument defaulting to "data" which maintains backcompat) and internally stored in the same attribute? The point being that after

ax.set_aspect(a, "data")ax.set_aspect(b, "axes")

it's not too surprising if the second call overwrites the first one, whereas in

ax.set_aspect(a)ax.set_box_aspect(b)

... do we want the second to overwrite the first one? do we want to add a check and error out? or whatnot.

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ImportanceOfBeingErnest commentedJul 30, 2019

No, the usual (data-)aspect and the box aspect are not mutually exclusive. In fact using both may make perfect sense, as shown in caseF.. (It's just thatadjustable cannot be "box" in case of using a box aspect.)

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anntzer commentedJul 30, 2019•
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Ah, thanks for the clarification, I missed that; ignore the nonsense I wrote above.

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jklymak commentedJul 30, 2019

Some things to consider: What happens if the user manually sets the position and thebox_aspect?

ax.set_position([0.1,0.1,0.9,0.2])ax.set_box_aspect(1.)

For constrained_layout, theset_position method takes the axes out of the automatic layout because we assume the user wants that position set. But I indicate that just by setting the layout boxes associated with the axes toNone inax.set_position, which you probably don't want to depend on here.

I'm not sure which behaviour you want here, but you'll need to decide which call trumps which here. Even more tricky is

ax.set_box_aspect(1.)ax.set_position([0.1,0.1,0.9,0.2])

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July 31, 2019 15:43

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ImportanceOfBeingErnest commentedJul 31, 2019

The order of setting position and box_aspect isn't relevant. But I added a test to make sure that's the case.

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August 1, 2019 01:46

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ImportanceOfBeingErnest added this to thev3.2.0 milestone

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Aug 7, 2019

Addaxes.aspect as an option to rcParams#15001

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Aug 8, 2019

Adding colorbar without affecting the plotting area size.#15010

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andrzejnovak commentedAug 8, 2019

Just so it doesn't get lost from#15010 , I would really like if it was possible to choose this behaviour as a default setting in rcParams.

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ImportanceOfBeingErnest commentedAug 9, 2019•
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I mentionned my problem with an rc parameter for this in#15001 (comment):

if it's to be set at init time of any axes, it would sure cause problems e.g. with colorbar axes [also: Widget axes, insets etc.] and also the interplay between the adjustable parameter would need to be sorted before the axes is drawn.

I could imagine though to let this be taken as argument by the axes' init, to allow for something like

fig, axs = plt.subplots(2,2, subplot_kw=dict(box_aspect=1))

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andrzejnovak commentedAug 9, 2019

I think that's a good compromise. It could be made to work by only applying it to the first axes.append_axes,add_subplot andadd_axes would check if there already is one in the figure and go back to auto, but I could see why that would not be very transparent.

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August 10, 2019 23:35

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Aug 12, 2019

How to handle sphinx nitpicky mode#15042

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tacaswell commentedAug 12, 2019

Power cycled to try to re-run against master and then belated realized this won't help with circle...

Half of the warnings were from the required target not being hit, pushed a commit making sure they are generated (we do not auto-docAxes).

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tacaswell commentedAug 12, 2019

ok, I understand the other half of the errors.

we auto-generate and insert

    ..table:::class: property-table       =======================================================================================   =====================================================================================================       Property                                                                                  Description       =======================================================================================   =====================================================================================================:meth:`adjustable <matplotlib.axes._base._AxesBase.set_adjustable>`                       {'box', 'datalim'}:meth:`agg_filter <matplotlib.artist.Artist.set_agg_filter>`                              a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array:meth:`alpha <matplotlib.artist.Artist.set_alpha>`                                        float or None:meth:`anchor <matplotlib.axes._base._AxesBase.set_anchor>`                               2-tuple of floats or {'C', 'SW', 'S', 'SE', ...}:meth:`animated <matplotlib.artist.Artist.set_animated>`                                  bool:meth:`aspect <matplotlib.axes._base._AxesBase.set_aspect>`                               {'auto', 'equal'} or num:meth:`autoscale_on <matplotlib.axes._base._AxesBase.set_autoscale_on>`                   bool:meth:`autoscalex_on <matplotlib.axes._base._AxesBase.set_autoscalex_on>`                 bool:meth:`autoscaley_on <matplotlib.axes._base._AxesBase.set_autoscaley_on>`                 bool:meth:`axes_locator <matplotlib.axes._base._AxesBase.set_axes_locator>`                   Callable[[Axes, Renderer], Bbox]:meth:`axisbelow <matplotlib.axes._base._AxesBase.set_axisbelow>`                         bool or 'line':meth:`box_aspect <matplotlib.axes._base._AxesBase.set_box_aspect>`                       None, or a number:meth:`clip_box <matplotlib.artist.Artist.set_clip_box>`                                  `.Bbox`:meth:`clip_on <matplotlib.artist.Artist.set_clip_on>`                                    bool:meth:`clip_path <matplotlib.artist.Artist.set_clip_path>`                                [(`~matplotlib.path.Path`, `.Transform`) | `.Patch` | None]:meth:`contains <matplotlib.artist.Artist.set_contains>`                                  callable:meth:`facecolor <matplotlib.axes._base._AxesBase.set_facecolor>`                         color:meth:`fc <matplotlib.axes._base._AxesBase.set_facecolor>`                                color:meth:`figure <matplotlib.axes._base._AxesBase.set_figure>`                               `.Figure`:meth:`frame_on <matplotlib.axes._base._AxesBase.set_frame_on>`                           bool:meth:`gid <matplotlib.artist.Artist.set_gid>`                                            str:meth:`in_layout <matplotlib.artist.Artist.set_in_layout>`                                bool:meth:`label <matplotlib.artist.Artist.set_label>`                                        object:meth:`navigate <matplotlib.axes._base._AxesBase.set_navigate>`                           bool:meth:`navigate_mode <matplotlib.axes._base._AxesBase.set_navigate_mode>`                 unknown:meth:`path_effects <matplotlib.artist.Artist.set_path_effects>`                          `.AbstractPathEffect`:meth:`picker <matplotlib.artist.Artist.set_picker>`                                      None or bool or float or callable:meth:`position <matplotlib.axes._base._AxesBase.set_position>`                           [left, bottom, width, height] or `~matplotlib.transforms.Bbox`:meth:`prop_cycle <matplotlib.axes._base._AxesBase.set_prop_cycle>`                       unknown:meth:`rasterization_zorder <matplotlib.axes._base._AxesBase.set_rasterization_zorder>`   float or None:meth:`rasterized <matplotlib.artist.Artist.set_rasterized>`                              bool or None:meth:`sketch_params <matplotlib.artist.Artist.set_sketch_params>`                        (scale: float, length: float, randomness: float):meth:`snap <matplotlib.artist.Artist.set_snap>`                                          bool or None:meth:`title <matplotlib.axes._axes.Axes.set_title>`                                      str:meth:`transform <matplotlib.artist.Artist.set_transform>`                                `.Transform`:meth:`url <matplotlib.artist.Artist.set_url>`                                            str:meth:`visible <matplotlib.artist.Artist.set_visible>`                                    bool:meth:`xbound <matplotlib.axes._base._AxesBase.set_xbound>`                               unknown:meth:`xlabel <matplotlib.axes._axes.Axes.set_xlabel>`                                    str:meth:`xlim <matplotlib.axes._base._AxesBase.set_xlim>`                                   (left: float, right: float):meth:`xmargin <matplotlib.axes._base._AxesBase.set_xmargin>`                             float greater than -0.5:meth:`xscale <matplotlib.axes._base._AxesBase.set_xscale>`                               {"linear", "log", "symlog", "logit", ...}:meth:`xticklabels <matplotlib.axes._base._AxesBase.set_xticklabels>`                     List[str]:meth:`xticks <matplotlib.axes._base._AxesBase.set_xticks>`                               unknown:meth:`ybound <matplotlib.axes._base._AxesBase.set_ybound>`                               unknown:meth:`ylabel <matplotlib.axes._axes.Axes.set_ylabel>`                                    str:meth:`ylim <matplotlib.axes._base._AxesBase.set_ylim>`                                   (bottom: float, top: float):meth:`ymargin <matplotlib.axes._base._AxesBase.set_ymargin>`                             float greater than -0.5:meth:`yscale <matplotlib.axes._base._AxesBase.set_yscale>`                               {"linear", "log", "symlog", "logit", ...}:meth:`yticklabels <matplotlib.axes._base._AxesBase.set_yticklabels>`                     List[str]:meth:`yticks <matplotlib.axes._base._AxesBase.set_yticks>`                               unknown:meth:`zorder <matplotlib.artist.Artist.set_zorder>`                                      float       =======================================================================================   =====================================================================================================

into a bunch of docstrings which points to the base class (because it asks the methods what class they belong to). Will push a commit 'fixing' this soon...

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Aug 12, 2019

DOC: more nitpick follow up#15048

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August 15, 2019 01:45

box aspect for axes

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Aug 24, 2019

ImportanceOfBeingErnest added status: needs review and removed status: needs comment/discussionneeds consensus on next step labels

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anntzer commentedSep 11, 2019

I think this is basically good to go.
Minor nit: perhaps name this "axes_aspect"? consistently with transAxes, with the places that accept "axes"/"data" as transform specifiers, etc. Obviously it's a bit(...) late to rename the classic "aspect" to "data_aspect", though...

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ImportanceOfBeingErnest commentedSep 11, 2019

I would agree that if we had.set_data_aspect, naming this.set_axes_aspect would be ideal. But given that the data aspect is by now commonly known as"the aspect", it is important to distinguish clearly.

In general we have the semantics ofobject.set_property(...) throughout the code, which reads as"set the object's property to ...". In the case of the aspect,axes.set_aspect, needs to read"set the axes' aspect to ...". Following this,axes.set_axes_aspect would read"set the axes' axes aspect to" in which case there is little indication for that to be different from"set the axes' aspect to"; and that would be the data aspect.

I therefore find.set_box_aspect much clearer: The axes has an aspect (which is related to data), and it has a box-aspect (which is related to its box).

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jklymak commentedSep 11, 2019

OK, I'll check later, but what if you set two axes to have different aspect ratio, and use a layout manager? I'm just a little concerned there are all sorts of edge cases here that will cause problems, but I may be completely incorrect.

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Actually because this works on theactive position of the axes, it works fine w/ the layout managers. Or at least I couldn't easily break it.

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jklymak commentedSep 11, 2019

I'll merge tomorrow, if no one else does, or@ImportanceOfBeingErnest you can self-merge if we give this a day or so to make sure there are no further objections.

jklymak merged commit805cb72 intomatplotlib:master

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jklymak commentedOct 1, 2019

Thanks@ImportanceOfBeingErnest I think this will be a pretty valuable tool in the axes shaping toolbox!

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May 28, 2020

FIX: add set_box_aspect, improve tight bounding box for Axes3D + fix bbox_inches support with fixed box_aspect#17515

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May 30, 2020

FIX: support bbox_inches='tight' for box_aspect Axes

390a57a

The way that bbox_inches='tight' is implemented we need to ensure thatwe do not try to adjust the aspect during the draw (because we havetemporarily de-coupled the reported figure size from the transformswhich results in the being distorted).  Previously we did not have away to fix the aspect ratio in screen space of the Axes (only theaspect ratio in dataspace) however in 3.3 we gained this ability forboth Axes (matplotlib#14917) and Axes3D (matplotlib#8896 /matplotlib#16472).Rather than add an aspect value to `set_aspect` to handle this case,in the tight_bbox code we monkey-patch the `apply_aspect` method witha no-op function and then restore it when we are done.  Previously wewould set the aspect to "auto" and restore it in the same places.closesmatplotlib#16463.

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Jun 4, 2020

FIX: support bbox_inches='tight' for box_aspect Axes

c0ab395

The way that bbox_inches='tight' is implemented we need to ensure thatwe do not try to adjust the aspect during the draw (because we havetemporarily de-coupled the reported figure size from the transformswhich results in the being distorted).  Previously we did not have away to fix the aspect ratio in screen space of the Axes (only theaspect ratio in dataspace) however in 3.3 we gained this ability forboth Axes (matplotlib#14917) and Axes3D (matplotlib#8896 /matplotlib#16472).Rather than add an aspect value to `set_aspect` to handle this case,in the tight_bbox code we monkey-patch the `apply_aspect` method witha no-op function and then restore it when we are done.  Previously wewould set the aspect to "auto" and restore it in the same places.closesmatplotlib#16463.

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topic: geometry manager

LayoutEngine, Constrained layout, Tight layout

topic: ticks axis labels

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