This project, along with all my others, has moved to GitLab: https://gitlab.com/madphysicist/madphysicist. Please download the latest version and submit updates there rather than GitHub, which will no longer be monitored.

Hi, I am algorithm engineer with a background in physics and signal processing. Coding is a hobby of mine. I like to contribute fixes and improvements to projects that I use frequently, such as the numpy / scipy / matplotlib stack. My ongoing pet project is scikit-guess. It's a collection of linearized optimization routines that started as a translation and python implementation of Jean Jacquelin's paper, which you can find in the repo.

• https://nvie.com/posts/a-successful-git-branching-model/

Here is a selection of repos with a note about each one:

• scikit-guess [PyPi] [RTD] See above.

• haggis [PyPi] [RTD] Originally made to support imprint, this library has a whole bunch of routines I find useful on a regular basis for all kinds of projects.

• imprint [PyPi] [RTD] A publication system for generating MS Word documents I made while at the Detector Characterization Lab at NASA GSFC. Only really useful in the case where you want to generate the same document over and over, but with different data.

• is_integer_ufunc is a foray into the C code of numpy. It contains bit twiddling operations for determining whether an IEEE754 float (any format) is an integer or not. It's becoming pretty clear that a ufunc is inadequate for the purpose, so I am concocting two alternatives to the pure ufunc:

  • A numpy function that labels each element with whether it can be stored in an integer of specified bit-width.
  • The number of bits required to store the integer stored in a float, with negative numbers indicating a fractional portion.

  See the Stack Exchange section below for the inspiration.

• puzzle-solvers [PyPi] [RTD] Another Stack Overflow-inspired package. This one is currently just a system for solving a zebra puzzle, which I really enjoyed writing. See the Stack Exchange section for the inspiration.

• libpluck never got past the README phase, as it's more of an April fool's library than anything. Developed in conjunction with Ventsy Velev while working on GOES-R together. An idea that never made it even this far was a library for generating unit tests with gramatically meaningful, fancy sounding names, all of which pass after much output and fanfare.

• BOFH is a small Java program that depends on JTools, and displays a GUI for the excuse generator from Simon Travaglia's BOFH series of articles.

• JTools is a small library of Java utilities from many years ago when I coded in Java. It's so old that it was written before Java 7 even existed. There were no streams back in those days. The library has all sorts of tools for I/O, process management, GUI elements, XML parsing and the like.

• JTools-extras is an extension of JTools that contains utilities with external dependencies (like TestNG).

I've been on Stack Exchange for a while now, and some of the open source work I've done is a direct consequence of my contributions there. The list below maps some of my PRs to the questions that they originated with. In most cases, I added an answer to the question referencing the contribution.

Part of the reason for putting this section here is that my SE profile is limited to 3000 characters, so I gave up on trying to squeeze it in there.

• scikit-guess entirely came about from my work with a paper by Jean Jacquelin. It was later supplemented by some Stack Overflow and Math Stack Exchange questions:

  • N-dimensional spheres:
    • https://stackoverflow.com/q/68302951/2988730 (JJ)
    • https://stackoverflow.com/q/26574945/2988730
    • https://stackoverflow.com/q/10344119/2988730
    • https://stackoverflow.com/q/18934805/2988730
    • https://math.stackexchange.com/q/820815/295281 (JJ)
    • https://math.stackexchange.com/q/214661/295281
    • https://math.stackexchange.com/q/2898295/295281 (JJ)
  • N-dimensional ellipses:
    • https://stackoverflow.com/q/7272252/2988730
    • https://stackoverflow.com/q/58501545/2988730
    • https://stackoverflow.com/q/29230039/2988730
    • https://stackoverflow.com/q/37229712/2988730
  • N-dimensional Gaussians:
    • https://stackoverflow.com/q/25720600/2988730
    • https://stackoverflow.com/q/27539933/2988730
    • https://stackoverflow.com/q/27230824/2988730
    • https://stackoverflow.com/q/67538941/2988730
    • https://stackoverflow.com/q/8780912/2988730
    • https://math.stackexchange.com/q/441422/295281 (JJ)
    • https://math.stackexchange.com/q/1292889/295281 (JJ)
  • Gaussian Mixtures:
    • https://math.stackexchange.com/q/2656406/295281 (JJ)
    • https://stackoverflow.com/q/38261081/2988730
  • Exponentials:
    • https://stackoverflow.com/q/53273033/2988730
    • https://stackoverflow.com/q/3433486/2988730
    • https://stackoverflow.com/q/3938042/2988730 (JJ)
    • https://math.stackexchange.com/q/1337601/295281 (JJ)
    • https://math.stackexchange.com/q/1163618/295281 (JJ)
  • Sinusoids:
    • https://stackoverflow.com/q/16716302/2988730
    • https://stackoverflow.com/q/8126001/2988730
    • https://stackoverflow.com/q/13405053/2988730
    • https://math.stackexchange.com/q/36725/295281
    • https://stackoverflow.com/q/42169643/2988730
    • https://dsp.stackexchange.com/q/4886/26517
    • https://stackoverflow.com/q/46296263/2988730
    • https://stackoverflow.com/q/41191748/2988730
    • https://stackoverflow.com/q/40221984/2988730
    • https://stackoverflow.com/q/24086998/2988730
    • https://stats.stackexchange.com/q/126273/102011

• matplotlib.ticker.PrecentFormatter added to matplotlib in PR #6251 in response to these posts:

  • Y-axis: https://stackoverflow.com/a/36319915/2988730
  • X-axis: https://stackoverflow.com/a/36320013/2988730
  • Not my answer, but still a good example after the fact: https://stackoverflow.com/q/51473993/2988730

• scipy.stats.iqr added to scipy in PR #5805 partly just to write https://stackoverflow.com/a/38620147/2988730

• count parameter added to numpy.unpackbits to make it invertible with respect to numpy.packbits in PR #10855 to improve this answer: https://stackoverflow.com/q/5602155/2988730

• Relaxed contiguity requirements for numpy.ndarray.view (see note about version 1.23.0) in PR #20722, which allows for np.char.slice_ to exist in PR #20694:

  • https://stackoverflow.com/q/70547027/2988730
  • https://stackoverflow.com/q/53296394/2988730
  • https://stackoverflow.com/q/39042214/2988730
  • https://stackoverflow.com/q/40976714/2988730
  • https://stackoverflow.com/q/64981711/2988730
  • https://stackoverflow.com/q/31387047/2988730
  • https://stackoverflow.com/q/69856133/2988730

• haggis.numbers.english implements the usage rules from this answer on English Language and Usage SE: https://english.stackexchange.com/a/111837/207127.

• haggis.math.full_width_half_max implements a solution to https://stackoverflow.com/q/10582795/2988730

• My first attempt at a ufunc: is_integer_ufunc. This still needs work before it's ready for review by the numpy community, but the question crops up fairly frequently:

  • https://stackoverflow.com/q/35042128/2988730
  • https://stackoverflow.com/q/64044147/2988730
  • https://stackoverflow.com/q/52094533/2988730
  • https://stackoverflow.com/q/6209008/2988730
  • https://stackoverflow.com/q/21583758/2988730
  • Showing that a limit on dtype size is necessary:
    • https://stackoverflow.com/q/36505879/2988730

• One of my first introductions to numpy was in the area of automatic histogram bin estimation in PR #, in which I added Doane's estimator: https://stats.stackexchange.com/q/55134/102011. Most of my research can be referenced to questions on Cross Validated:

  • https://stats.stackexchange.com/q/206907/102011
  • https://stats.stackexchange.com/q/55777/102011
  • https://stats.stackexchange.com/a/143295/102011

• This question led me to write puzzle-solvers: https://stackoverflow.com/q/56284249/2988730. Others that are near-duplicates:

  • https://stackoverflow.com/q/318888/2988730
  • https://stackoverflow.com/a/320981/2988730
  • https://stackoverflow.com/q/44080418/2988730

• Added haggis.math.segment_distance as a result of the first of these questions:

  • https://stackoverflow.com/a/70645020/2988730
  • https://stackoverflow.com/q/39840030/2988730
  • https://stackoverflow.com/q/23103345/2988730

  With an interesting application here:

  • https://stackoverflow.com/q/70762830/2988730

• Angular distances are implemented in haggis.math.ang_diff_pos, haggis.math.ang_diff_min and haggis.math.ang_diff_abs. They have appeared in

  • https://stackoverflow.com/q/15927755/2988730
  • https://stackoverflow.com/q/1878907/2988730

• haggis.npy_util.unmasked_index, while not written specifically for https://stackoverflow.com/q/71389165/2988730, does provide an answer.

  • Another possible application: https://stackoverflow.com/q/64082288/2988730

• haggis.objects.getsizeof was added to help with this question: https://stackoverflow.com/q/70792724/2988730, with the help of this one: https://stackoverflow.com/q/449560/2988730

• A question about formatting determinacy https://stackoverflow.com/q/41050445/2988730 led to a new test case for pyformat.info in PR #38.

• haggis.objects.copy_class is based on https://stackoverflow.com/q/49157255/2988730

• haggis.objects.copy_func is based on https://stackoverflow.com/q/13503079/2988730 (duplicate of https://stackoverflow.com/q/6527633/2988730), implemented in https://stackoverflow.com/q/49076566/2988730

• haggis.load.load_module is based on four answers:

  • https://stackoverflow.com/a/43602645/2988730 (general loading technique)
  • https://stackoverflow.com/a/67692/2988730 (general loading technique)
  • https://stackoverflow.com/a/50395128/2988730 (regisering in sys.modules)
  • https://stackoverflow.com/q/38647348/2988730 (variable injection)

• haggis.logs.add_logging_level is a productionized version of https://stackoverflow.com/a/35804945/2988730.

• haggis.files.docx.list_number is based on the answers to https://stackoverflow.com/q/51829366/2988730.

Stuff that might get turned into PRs one day:

• Estimating the size of an index in numpy: https://stackoverflow.com/a/65857268/2988730
• np.atleast_nd function (numpy PR #18386):
  • https://stackoverflow.com/q/19636487/2988730
  • https://stackoverflow.com/q/15940831/2988730
  • https://stackoverflow.com/q/70758062/2988730
• Reverse winding of paths in matplotlib: https://stackoverflow.com/q/68275413/2988730
• Weighted partitioning in numpy: https://stackoverflow.com/q/20601872/2988730. This in turn will enable weighted histogram bin estimation.
• Weights to np.std: https://stackoverflow.com/q/2413522/2988730
• Add a count method to Ufuncs returning booleans, like greater_than:
  • https://stackoverflow.com/q/12995937/2988730
  • https://stackoverflow.com/q/21367595/2988730
• Justification for adding np.same (or special case of count method on np.equal):
  • https://stackoverflow.com/q/14859458/2988730
  • https://stackoverflow.com/q/26163727/2988730
• Wand's estimator for np.histogram: https://stats.stackexchange.com/a/114517/102011
• Bin estimators for 2D histograms: https://stats.stackexchange.com/q/114490/102011
• Shimazaki-Shinomoto method of histogram bin estimation, possibly others: https://stats.stackexchange.com/q/798/102011
• Multiple lines to plt.axvline: https://stackoverflow.com/q/21300953/2988730
• PGM reader/writer (for scipy.io?)
  • https://stackoverflow.com/q/17765599/2988730
  • https://stackoverflow.com/q/4270700/2988730
  • https://stackoverflow.com/q/46944048/2988730
  • https://stackoverflow.com/q/7368739/2988730
  • https://stackoverflow.com/q/35723865/2988730
• Histogram of times (numpy filters down to pandas) might have been resolved by now:
  • https://stackoverflow.com/q/27365467/2988730
  • https://stackoverflow.com/q/34814606/2988730
  • https://stackoverflow.com/q/30330389/2988730
  • https://stackoverflow.com/q/29672375/2988730
  • https://stackoverflow.com/q/8369584/2988730
• Speedup to np.vander: https://stackoverflow.com/q/48245987/2988730
• Quaternion integrator:
  • https://math.stackexchange.com/q/1693067/295281
  • https://stackoverflow.com/q/66454668/2988730