Skip to main content

3D in matplotlib

One of the frustrating things about matplotlib is its lack of 3D plotting. If matplotlib were a mediocre library it wouldn' hurt. But it is a GREAT library and produces really good looking plots. So the lack of 3D plotting sometimes makes me want to go out and strangle somebody. There has however always been a furtive 3D plotting feature in matplotlib, and apparently, its being worked on some more. Yeehah! No more futzing with pyVtk.

Important links:
  1. Docs for 3D features
  2. Installing the svn code (that has all this goodness)

Comments

  1. badly written post..
    there is 3d support in matplotlib from 1.0, and there has been on svn for quite a while.

    mplot3d is now better integrated.

    ReplyDelete
  2. Indeed, welcome progress in 3D plotting support in matplotlib has been made in the past year and a half since this post was written.

    ReplyDelete

Post a Comment

Popular posts from this blog

Remove field code from Word document

e.g. before submitting a MS, or hand manipulating some formatting because Word does things (like cross-references) so half-assed [from here ] Select all the text (CTRL-A) Press Ctrl+Shift+F9 Editing to remove anonymous comments that only contain thanks. I really appreciate the thanks, but it makes it harder to find comments that carry pertinent information. I'm also going to try and paste informative comments in the body of the post to make them easier to find.

h5py and multiprocessing

The HDF5 format has been working awesome for me, but I ran into danger when I started to mix it with multiprocessing. It was the worst kind of danger: the intermittent error. Here are the dangers/issues in order of escalation (TL;DR is use a generator to feed data from your file into the child processes as they spawn. It's the easiest way. Read on for harder ways.) An h5py file handle can't be pickled and therefore can't be passed as an argument using pool.map() If you set the handle as a global and access it from the child processes you run the risk of racing which leads to corrupted reads. My personal runin was that my code sometimes ran fine but sometimes would complain that there are NaNs or Infinity in the data. This wasted some time tracking down. Other people have had this kind of problem [ 1 ]. Same problem if you pass the filename and have the different processes open individual instances of the file separately. The hard way to solve this problem is to sw...

Reading spreadsheet data in Python: The lack of a good ODS reader

I try and keep long term data in as simple a format as possible, which means text where ever possible. In earlier times I would enter data in excel spreadsheets and then read them from my Python programs using the xlrd package which is excellent. This works well, but in the back of my mind is the thought that someday Microsoft might do something funny with their business model making office software more janky to use and all my fears about keeping data in proprietary formats would come true. Oh, look, that day is today . So, I'm completely abandoning the MS Office suite and going back to basic text files. However, there is a tension between keeping tabulated data in a simple form, such as csv, and entering it in a convenient manner. Excel, of course, nags you everytime you edit a csv file and save it. Libreoffice is excellent: it handles loading and saving in a very streamlined fashion. However, every time you open up the csv file you need to tell Calc what widths you want...