In some situations, we have several subplots and we want to use only one colorbar for all the subplots.
How to do this in Matplotlib? The first method is like normal plotting: first draw the main plot, then add a colorbar to the main plot. Matplotlib provide different ways to add a colorbar: explicit or implicit way. The idea is to adjust the existing axes manually to make room for an additional colorbar. Then explicitly add an axes where the colorbar resides. See the code below for details:. Matplotlib also offers method which can adjust the existing axes and make room for a colorbar implicitly.
See the code below for an example:. In this way, you have to manually tweak the shrink param of fig. See the output image below. Both the two methods have an disadvantage that it is difficult to control the padding space between subplots.
You have to adjust the figure aspect ratio and also the padding params to make the padding between the subplots appear the same. In fact, the padding in horizontal and vertical direction is not the same for the above two plots even after tweaking. Matplotlib also provides a AxesGrid toolkit to deal with padding and colorbar issues arising from plotting multiple subplots.
By using axesgrid, the padding between subplots are guaranted to be the same.
Also the colorbar have exactly the same height as the main plot. Following is a working example showing how to use axesgrid:. You can see that the padding between subplots are all the same, also the colorbar have the same height as the main plot. Conveniently, isn't it? Using the normal way is more flexible but also annoying because you have to adjust the paramters by trial and error. By employing the axesgrid, you can simplify the plotting of multiple plot with just one colorbar, significantly.
In my opinion, the latter way is prefered. Author jdhao. LastMod Two ways can be employed. The conventional method The first method is like normal plotting: first draw the main plot, then add a colorbar to the main plot. The explicit way The idea is to adjust the existing axes manually to make room for an additional colorbar.
See the code below for details: import matplotlib.Click here to download the full example code. It is often desirable to show data which depends on two independent variables as a color coded image plot. This is often referred to as a heatmap.
If the data is categorical, this would be called a categorical heatmap. Matplotlib's imshow function makes production of such plots particularly easy. The following examples show how to create a heatmap with annotations. We will start with an easy example and expand it to be usable as a universal function. We may start by defining some data. What we need is a 2D list or array which defines the data to color code.
We then also need two lists or arrays of categories; of course the number of elements in those lists need to match the data along the respective axes. The heatmap itself is an imshow plot with the labels set to the categories we have. The locations are just the ascending integer numbers, while the ticklabels are the labels to show. Finally we can label the data itself by creating a Text within each cell showing the value of that cell.
We create a function that takes the data and the row and column labels as input, and allows arguments that are used to customize the plot. Here, in addition to the above we also want to create a colorbar and position the labels above of the heatmap instead of below it. The annotations shall get different colors depending on a threshold for better contrast against the pixel color.
Finally, we turn the surrounding axes spines off and create a grid of white lines to separate the cells. In the following we show the versatility of the previously created functions by applying it in different cases and using different arguments.
Total running time of the script: 0 minutes 1. Keywords: matplotlib code example, codex, python plot, pyplot Gallery generated by Sphinx-Gallery. Version 3.John Hunter Excellence in Plotting Contest submissions are open! Entries are due June 1, Function signatures for the pyplot interface; all but the first are also method signatures for the colorbar method:. The matplotlib. ScalarMappable i.
This argument is mandatory for the Figure. Note that one can create a ScalarMappable "on-the-fly" to generate colorbars not attached to a previously drawn artist, e. Parent axes from which space for a new colorbar axes will be stolen. If a list of axes is given they will all be resized to make room for the colorbar axes. If cax is Nonea new cax is created as an instance of Axes. See also its base class, ColorbarBase.
If mappable is a ContourSetits extend kwarg is included automatically. The shrink kwarg provides a simple way to scale the colorbar with respect to the axes. Note that if cax is specified, it determines the size of the colorbar and shrink and aspect kwargs are ignored.
For more precise control, you can manually specify the positions of the axes objects in which the mappable and the colorbar are drawn. In this case, do not use any of the axes properties kwargs. It is known that some vector graphics viewers svg and pdf renders white gaps between segments of the colorbar. This is due to bugs in the viewers, not Matplotlib. As a workaround, the colorbar can be rendered with overlapping segments:. However this has negative consequences in other circumstances, e.
Version 3. Table of Contents matplotlib. Show Page Source. If False, the parent axes' anchor will be unchanged. If set to 'auto', makes the triangular colorbar extensions the same lengths as the interior boxes when spacing is set to 'uniform' or the same lengths as the respective adjacent interior boxes when spacing is set to 'proportional'. If a scalar, indicates the length of both the minimum and maximum triangular colorbar extensions as a fraction of the interior colorbar length.
A two-element sequence of fractions may also be given, indicating the lengths of the minimum and maximum colorbar extensions respectively as a fraction of the interior colorbar length. If True the extensions will be rectangular.
If a format string is given, e. An alternative Formatter object may be given instead. Property Description boundaries None or a sequence values None or a sequence which must be of length 1 less than the sequence of boundaries. For each region delimited by adjacent entries in boundariesthe color mapped to the corresponding value in values will be used. Examples using matplotlib. None or list of ticks or Locator If None, ticks are determined automatically from the input.
I'm writing a simple Python application that uses matplotlib to display a few figures on screen. The number of figures generated is based on user input and changes throughout the application's life. The user has the ability to issue a "plot" command to generate a new figure window with the selected data series. In order to improve the user experience, I would like to provide another command that would programmatically arrange all open figure windows in some convenient arrangement e.
I believe to have found APIs that allow me to adjust the size of the figure window in pixelsbut haven't had any success in finding a way to set their absolute position on screen. Is there a way to do this without delving into the details of whatever backend is in use?
How to Plot Only One Colorbar for Multiple Plot Using Matplotlib
I would like to do this in a backend-agnostic way so I can avoid relying upon implementation details that might change in the future. So I think you can exhaust through all the backends that are capable of doing this, if imposing a certain one is not an option. I was searching quite often for this and finally invested the 30 minutes to find this out.
Hope that helps someone. With help from the answers thus far and some tinkering on my own, here's a solution that checks for the current backend and uses the correct syntax.
Inspired by theo answer, I wrote a script to move and resize a window to a specific standard position on the screen. This was tested with the Qt4Agg backend:. If you want to send a plot to an image and have it open with the default image manager which likely remembers position use this from here :. For the windows platform you could install and use pyfig module from Pyfig.
How about defining a function to raise the window to the top level and move it toward the top-left corner for example like this:.
Then whenever you open a new figure you just type "topfig ". Is there a way to pre-define topfig so it will always be available? Learn more.
How do you set the absolute position of figure windows with matplotlib? Ask Question. Asked 8 years, 7 months ago. Active 1 month ago. Viewed 53k times. Jason R Jason R 9, 3 3 gold badges 40 40 silver badges 67 67 bronze badges. Active Oldest Votes. SetPosition0 show per tim at the comment section below, you might wanna switch to thismanager. For TkAggjust change it to thismanager. I might be able to enforce that the user must use some subset of them, though.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together.
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Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Already on GitHub? Sign in to your account. Definitely a low-priority bug, but at some figure sizes, there seems to be an issue with the colorbar not being drawn at the correct position in some backends seems like PDF and SVG are affected, but not Agg. The colorbar "fill" the actual colored bit will not line up with the box that contains it the black marker edge that makes the rectangle that is filled by the color bar, see below.
Seems like some sort of rounding issue. I have a more "dramatic" example, but still need to distill it to a minimum working example, as it is a plot of proprietary data. Interesting, I can reproduce it in Chrome but by default "qpdfview" doesn't show the problem until I zoom in.
Whereas "qpdfview" looks like this:. Also Foxit on my system, still shows the alignment off.
How to Plot Only One Colorbar for Multiple Plot Using Matplotlib
But you can only see it if you zoom in a bit. The gap renders only after a certain zoom level. Maybe a similar rendering artifact like I suspect not actually, because I can make a better example that also "overflows" the top of the bar instead of just "underflowing" the top.
Sorry that it took awhile to get this:. Screenshot from Foxit Reader on Debian Jessie. Circles obviously made in post in Gimp for emphasis. This suggests the issue is actually the PNG position is being rounded to the nearest pixel, whereas the SVG path data is being kept as floats. By zooming in, it is clear that the bar is slightly to the left instead of Here are the two files I obtain zipped, for github to me upload them : test. Okay, thanks everyone for your patience here, after games of reinstalling-everything-in-a-fresh-venvI think I've determined that this is a Jupyter-specific bug.
The following produces a "correct" plot, as reported by ImportanceOfBeingErnest :. Ok, this does not mean that it's a bug with jupyter necessarily.
After all, it's still matplotlib producing the output. But most probably there are some settings being made e. It might then be possible to construct an example which shows the same problem outside of jupyter as well. Looks like ? Jupyter does set the DPI itself actuallyEver been frustrated with colorbars on your matplotlib plots that just totally mess with the layout of your figure?
I plot a lot of image data, much of it in side-by-side comparisons, and the combination of matplotlib's default colorbar behavior and subplots was really getting up my nose. Here's how I finally got things looking right. When preparing plots for a paper, I collected some customizations to the matplotlib defaults to improve their appearance. Some text. The use of savefig. Since wonky colorbar sizes are most apparent with image plots which force equal aspect ratio by defaultlet's make an image of a square.
If you have a single Axes in your figure i. Anyone who's used image plots with colorbars in matplotlib has probably seen something like the above figure. We'd like for the colorbar to be the same height as the image, but the image is constrained to have equal width and height. One solution is Axes. There's a lot you can do with it, but we're interested in the example of a "colorbar whose height or width [is] in sync with the master axes". It's a bit tedious to do all that every time you want to add a colorbar to an image subplot, so you can wrap it up in a function:.
Updated December 12, Thanks to Mike Lampton for pointing out that later plt. The above function has been updated with plt.
Matplotlib Subplots – A Helpful Illustrated Guide
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I want to create a figure consisting of nine subplots. I really hated the fact that I needed to create ax1 to ax9 separately so I created a for loop to do so. However, when I want to include a colorbar, the colorbar is positioned right of the last subplot. This is also illustrated in the following figure:.
I found the answer to my question, resulting in the correct colorbar vs subplot spacing. Notice that if the spacing between subplot and colorbar does not matter, the answer of Molly is correct.
Learn more. Wrong colorbar positioning when using subplots matplotlib Ask Question. Asked 5 years, 11 months ago. Active 4 years, 2 months ago. Viewed 7k times. This is also illustrated in the following figure: What is going wrong and how can I fix this? The image has been generated with the following code: import numpy import layout import matplotlib. The Dude The Dude 2, 2 2 gold badges 22 22 silver badges 41 41 bronze badges. Active Oldest Votes.
Molly Molly 11k 2 2 gold badges 32 32 silver badges 35 35 bronze badges.