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I spoke with a colleague today who uses matplotlib and he didn't have anything specific to give me beyond 'look at the documentation' for embedding matplotlib in another window, but he did suggest it might be easier to just draw the pictures then import those directly. Would that work for your use case? I don't know what your plots look like or if they need to be interactive in some clever ways.

It shouldn't be too hard to programmatically generate file names to save to from matplotlib and load using Read from JPEG/Bitmap/PNG (and optionally delete old plots when you no longer need them) but I don't know if this is sufficient for your use case.

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To get anywhere with an ActiveX/.NET container, I think you'll have to go quite a lot deeper. Information about matplotlib's backends can be found here, but it really doesn't give information that directly helps you get an image into another GUI (i.e. LabVIEW) - it just highlights that is the direction you'd need to go in to get somewhere. If you want to go down that rabbit-hole, this StackOverflow post might be helpful - Embedding matplotlib inside qt activex component.

Matplotlib was originally written by John D. Hunter. Since then it has had an active development community[4] and is distributed under a BSD-style license. Michael Droettboom was nominated as matplotlib's lead developer shortly before John Hunter's death in August 2012[5] and was further joined by Thomas Caswell.[6][7] Matplotlib is a NumFOCUS fiscally sponsored project.[8]

I tried installing the most recent version of QGIS, and the install fails because it can't find matplotlib. I'm thinking this is because I didn't use easy_install, which appears to put packages instead under /Library/...

I ran into the same problem. My matplotlib is installed under /System/Library/Frameworks/Python.framework/Versions/2.7/Extras/lib/python. In case anyone is interested, I was able to solve this problem by running this command:

It is due to the fact that the installer that is hardcoded to look for matplotlib under /Library/Python/2.7/site-packages/matplotlib-override. Further the installer does not provide user to specify path of matplotlib at time of installation.

In my case, I installed the matplotlib with conda install matplotlilb in conda instead of julia conda. So I think you should try this first. It is worth a shot, though I am not certain that it will fix the problem.

Conceivably, you could use JavaGnuplotHybrid or DataMelt. This would require some effort, and your code would not be compatible with matplotlib. You could also execute external Python code to generate images which you could then serve up to Ignition for display. This would also be quite a bit of work. There is no equivalent of numpy.

I am using Affinity Designer (last version) on Windows 10 for my work. I have generated a pdf with matplotlib on python. The pdf looks ok (see attached) but the labels do not display properly when opening the file with Affinity Designer (see the screenshot). However, the pdf displays correctly in Illustrator.

Hello everyone, I face the same issue using different pdf's, but also with svg files saved with seaborn / matplotlib. In all pdf readers they're read correctly, but especiialy the text is formatted wrong:

Affinity apps have an issue with how matplotlib writes (codes) the text in both the PDF and the SVG formats. Some other applications, including PDF editors, are able to interpret this as text. But some other applications also have an issue with it (open the SVG in Inkscape and look at the "text").

Open the SVG in a text editor and try to find the "text" (the actual text, not the comments).

There is another discussion around here somewhere about the text coding in these files.

I hope the developers understand that this is not just an annoying bug. These bugs make it literally impossible to use Designer efficiently for graphics in the scientific community in general. If I create several graphics and at least one of them includes a file from matplotlib I won't use a different tool just for this one graphic. I switch the tool for all graphics of this project. And since this is the case for almost 99% of my projects Designer is not useful for me at all at this point.

Just want to know this. I am trying to use dynamo plot two series of data , and conduct several statical functions and show the results using a diagram. Is it possible I can write a python script (or something like that) to import matplotlib in this case?

Thanks

The python visualization world can be a frustrating place for a new user. Thereare many different options and choosing the right one is a challenge.For example, even after 2 years, this article is one of the top posts thatlead people to this site. In that article, I threw some shade at matplotliband dismissed it during the analysis. However, after using tools such as pandas,scikit-learn, seaborn and the rest of the data science stack in python - Ithink I was a little premature in dismissing matplotlib. To be honest, Idid not quite understand it and how to use it effectively in my workflow.

Now that I have taken the time to learn some of these tools and how to use them withmatplotlib, I have started to see matplotlib as an indispensable tool.This post will show how I use matplotlib and provide some recommendations for users gettingstarted or users who have not taken the time to learn matplotlib. I do firmly believematplotlib is an essential part of the python data science stack and hope thisarticle will help people understand how to use it for their own visualizations.

The reason two interfaces cause confusion is that in the world of stack overflowand tons of information available via google searches, new users will stumbleacross multiple solutions to problems that look somewhat similar but are not the same.I can speak from experience. Looking back on some of my old code, I can tell that thereis a mishmash of matplotlib code - which is confusing to me (even if I wrote it).

Another historic challenge with matplotlib is that some of the default stylechoices were rather unattractive. In a world where R could generate some reallycool plots with ggplot, the matplotlib options tended to look a bit ugly incomparison. The good news is that matplotlib 2.0 has much nicer styling capabilitiesand ability to theme your visualizations with minimal effort.

Despite some of these issues, I have come to appreciate matplotlib because itis extremely powerful. The library allows you to create almost any visualizationyou could imagine. Additionally, there is a rich ecosystem of python toolsbuilt around it and many of the more advanced visualization tools use matplotlib asthe base library. If you do any work in the python data science stack, you willneed to develop some basic familiarity with how to use matplotlib. That isthe focus of the rest of this post - developing a basic approach for effectivelyusing matplotlib.

The other benefit of this knowledge is that you have a starting point when yousee things on the web. If you take the time to understand this point, the restof the matplotlib API will start to make sense. Also, many of the advanced pythonpackages like seaborn and ggplot rely on matplotlib so understanding the basicswill make those more powerful frameworks much easier to learn.

The rest of this post will be a primer on how to do the basic visualizationcreation in pandas and customize the most common items using matplotlib. Onceyou understand the basic process, further customizations are relatively straightforward.

Up until now, I have been relying on the jupyter notebook to display the figuresby virtue of the %matplotlib inline directive. However, there are goingto be plenty of times where you have the need to save a figure in a specific formatand integrate it with some other presentation.

Hopefully this process has helped you understand how to more effectively usematplotlib in your daily data analysis. If you get in the habit of using this approachwhen doing your analysis, you should be able to quickly find out how to do whatever youneed to do to customize your plot.

I finally stumbled across an example matplotlibrc, and after some searching found two key settings: pdf.fonttype and ps.fonttype. You have to change these settings from the default of 3 to the alternative 42. You can do this in your matplotlibrc file with:

This causes matplotlib to use Type 42 (a.k.a. TrueType) fonts for PostScript and PDF files. This allows you to avoid Type 3 fonts without limiting yourself to the stone-age technology of Type 1 fonts.

to force matplotlib to produce Type 1 fonts. However, this caused some of the fonts to look quite different in the plots, and also garbled some of the text where my strings conflicted with TeX syntax.

I'm not able to use matplotlib with python3. I've installed matplotlib via pacman by running sudo pacman -Syu python-matplotlib. However when I try to import matplotlib in python, I get the following error:

The issue was that python was trying to use the locally installed version of PIL. Some time back I had removed all the locally installed packages of python and started installed pacakges via pacman. Somehow, I missed uninstalling PIL. As a result, I had a directory at ~/.local/lib/python3.11/site-packages/PIL. Since I had already installed PIL via pacman, this directory was of no use. Hence I deleted this directory and matplotlib started working again. Thanks to u/gcgc101 for the help.

The pyplot API has a convenient MATLAB-style stateful interface. In fact, the matplotlib Python library was originally written as an open source alternative for MATLAB. The OO API and its interface is more customizable and powerful than pyplot, but considered more difficult to use. As a result, the pyplot interface is more commonly used, and is referred to by default in this article.

Matplotlib is also available as uncompiled source files from GitHub. Compiling from source will require your local system to have the appropriate compiler for your OS, all dependencies, setup scripts, configuration files, and patches available. This can result in a fairly complex installation. Alternatively, consider using the ActiveState Platform to automatically build matplotlib from source and package it for your OS. e24fc04721