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TJ Mahr tjmahr Madison, WI tjmahr.com Language and data scientist

stan-dev/bayesplot 232

bayesplot R package for plotting Bayesian models

stan-dev/posterior 56

The posterior R package

dmirman-zz/gazer 12

Functions for reading and pre-processing eye tracking data.

tjmahr/2015_Coartic 8

Mahr, et al. (2015). Anticipatory coarticulation facilitates word recognition in toddlers.

tjmahr/adventofcode17 4

My solutions (R) for Advent of Code 2017

tjmahr/bayesplot-satrdays-2019 1

My lightning talking on bayesplot for SatRdays Chicago, April, 27, 2019

tjmahr/bayes_R2 1

Materials for the paper 'R-squared for Bayesian model fits' by Andrew Gelman, Ben Goodrich, Jonah Gabry, and Imad Ali

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Bootstrap group matching

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get stan version of model to work

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Jonah Gabry

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Remove extra space in mcmc_areas (#230) * remove extra space from mcmc_areas fixes #218 * add example of adjusting spacing see #218 * `mcmc_areas()` try to prevent top plotting from clipping * fix copy-paste error in NEWS Co-authored-by: TJ Mahr <mahr@wisc.edu>

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PR merged stan-dev/bayesplot

Remove extra space in mcmc_areas plot aesthetics

Fixes #218

Copying from my comment in #218:

after playing around with a bunch of options and trying with different numbers of parameters, what ended up working best (I think) was to use an additive expansion that decreases with the number of parameters. I put this on a branch remove-extra-space-mcmc_areas. Here's a comparison with the current master branch:

For 2, 4, 10, and 20 parameters (simulated from standard normals) here is what the current master branch produces: areas_old

and here is what the version in this PR looks like for the same parameters:

areas_new

+430 -340

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jgabry

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issue closedstan-dev/bayesplot

remove extra space from mcmc_areas

I needed a mcmc_areas plot for a book, and noticed that all mcmc_areas plots have unnecessary extra space on top and bottom. This is not clear with just a few variables, but with 4 than more it's visible e.g. in bodyfat, candy, diabetes, mesquite, roaches, and winequality case studies at https://avehtari.github.io/modelselection/ It gets worse and worse with more variables. For example this kind of call has empty space

mcmc_areas(as.matrix(fit), pars=vars(-'(Intercept)',-sigma))

and it can be fixed with

p0 <- mcmc_areas(as.matrix(fit0), pars=vars(-'(Intercept)',-sigma)
p0 <- p0 + scale_y_discrete(limits = rev(levels(p0$data$parameter)))
p0

This approach is a bit annoying, so I propose to make the plots tight by default.

This had slipped past previously as in notebooks there is plenty of space, but for a book I need tight layout and then I noticed that the extra space is actually appearing in many plots.

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avehtari

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Jonah Gabry

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add extractor methods for CmdStanMCMC objects (from CmdStanR) (#227) * add extractor methods for CmdStanMCMC objects * fix test * Update bayesplot-extractors.R * Update NEWS.md

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PR merged stan-dev/bayesplot

add extractor methods for CmdStanMCMC objects (from CmdStanR) feature

Adds extractor functions (nuts_params, neff_ratio, etc.) for models fit using CmdStanR. Also added tests, but they are skipped on CRAN and if CmdStanR is not installed.

+123 -18

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`mcmc_areas()` try to prevent top plotting from clipping

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pull request commentstan-dev/bayesplot

Remove extra space in mcmc_areas

While we are under the hood for this one, I'd like to fix the clipping where the line in the top panel gets cut off.

image

The demos you supply here appear to fix this problem, but I can still get it if I use area_method = "equal areas" in this version.

I'm trying the geom_blank() strategies of adjusting plotting area by plotting invisible data.

jgabry

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issue commentstan-dev/cmdstanr

Update doc for install_cmdstan()?

The Windows instruction are missing the info above:

On Windows we require mingw32-make for building models. mingw32-make does not come with RTools 4.0 but can be installed easily via RTools Bash. To open RTools Bash, which comes with RTools 4.0, just hit Windows Key, type rtools bash and hit Enter. A new console window will pop up. Now, just type

pacman -Sy mingw-w64-x86_64-make

Then restart the terminal and check that mingw32-make --version works.

Can make_cmd() check for this program and offer this advice in a message? (If not call pacman and do the installation?) I followed the CmdStan installation instructions exactly and ran into this problem.

Should this issue be open until stan-dev/cmdstan#909 is closed?

jgabry

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Jonah Gabry

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control sizes of intervals and points in mcmc_intervals (#229) * Add arguments to change interval and point size Fixes #228 Fixes #215 * add visual test * Update NEWS.md Co-authored-by: TJ Mahr <tjmahr@users.noreply.github.com>

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issue closedstan-dev/bayesplot

Feature request: allow changing size of credible interval lines and dot

When customizing the interval plot, I would like to be able to change the size of the interval lines and dot representing the median/mean because when you put the plot in Word lines/ dots are barely visible. Thanks

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quantumlinguist

PR merged stan-dev/bayesplot

control sizes of intervals and points in mcmc_intervals feature

Closes #215 and #228

This PR adds the arguments inner_size, outer_size, and point_size to mcmc_intervals() to control the size (thickness) of the interval segments and the size of the point estimate.

Also adds one new vdiffr visual test.

+87 -3

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jgabry

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issue closedstan-dev/bayesplot

Possible to modify point size for mcmc_intervals?

Hello, I would like to adjust the point size of the point estimates from mcmc_intervals; is it possible to make them smaller? I apologize for the mundane question! Also, if there's a better place to ask questions like this, please let me know.

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adkinsty

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issue commentopenjournals/joss-reviews

[REVIEW]: pypillometry: A Python package for pupillometric analyses

Thanks for the response. (I forgot that some eye trackers have chin rests. I was using data from a 4 year old with a free field eye tracker.) I don’t think it’s critical to address for publication.

I’m satisfied. Ship it. 👁

whedon

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issue commentopenjournals/joss-reviews

[REVIEW]: pypillometry: A Python package for pupillometric analyses

Thank you for this opportunity to review this package. I have written a few lab-specific in-house R packages for managing eyetracking data, so I applaud the effort to provide a general-purpose tool for working with eyetracking data.

I have two disclaimers: I have not formally analyzed pupil data beyond the data-cleaning stage and I seldom use Python.

The documentation is comprehensive and generously provides several notebooks with binder links. The installation instructions helped me use virtual environments for the first time ever. Functions that provide fake data also help learners play with the package.

I have Python 3.6.4 via Anaconda on Windows 10. Installation via cloning from Github and installing dependencies with pip 18.1 went smoothly. I tested the package on some 60 Hz Tobii data I had from an eyetracking task with preschoolers. I created csvs of gaze measurements and event onsets in R. Then in Python I was able to create a plot of pupil diameter over time with trial events annotated. It was cool to move from my own csvs to a nice default plot in a few steps.

I was unable to use velocity based blink detection (it raised an error), so I looked up the API reference for blink_detect() and tried d.blinks_detect(strategies = ["zero"]). This worked, but it treated all of the intertrial intervals (during which the eyetracker is not running) in the dataset as blinks (below). Fair enough.

image

After downsampling to 5 Hz, I noticed that these same blinks were changed to one spurious blink.

image

At this point, I gave up on trying to use blink detection or interpolation on my data because it was far too noisy and from a task that was never meant to analyze pupil size. That said, the availability of diagnostic plotting, as in d.blinks_interp_mahot(plot=True, plot_dim=(7,4)), is a user-friendly addition.

I have to ask: Is there a minimum sampling frequency required for blink analysis? Does the package make any assumptions about the capability of the eyetracker? How should missing eyetracking data be coded in csv file?

The pipeline based processing is a terrific design. By storing the data in a PupilData object, the data can keep track of the changes made to it. And because the history is itself data, it can be applied to other objects with the apply_history(). This set of features is awesome for reproducibility and usability.

In eyetracking, we often want to see how gaze measures change in response to some event and adjust times around that event. This package's ERPD (event-related pupil dilation) nicely handles this process by allowing users to select an event and time window before and after this event. It also provides automatic plotting of aggregating gaze measurements. I was not able to get it to work on my noisy Tobii data, but I reproduced the plots in the notebook using the supplied data.

I ran through the phasic and tonic components to confirm that I was able to get pystan to do the modeling.


I would recommend this package to any person analyzing pupil data. The history feature is a really smart way to let users prototype a workflow on a single dataset and then quickly apply it to several datasets. My only concern is that it was not clear what requirements are placed on the data.

whedon

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pupillometry with python

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proposed solution to travis always timing out

What about GitHub actions?

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plots for model predictions without y variable

Sounds good.

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issue openedtjmahr/usedrake

Remove references to iris

It's time to move on from the iris dataset. Try some of the other datasets in data(), ggplot2::mpg, dplyr::starwars, or this dataset about penguins.

Reference(s) to iris occur in the following files.

References

https://github.com/tjmahr/usedrake/blob/3f628695fd07326958ff071847dc22048860fd5e/inst/templates/notebook/plan.R#L3

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issue openedtjmahr/tristan

Remove references to iris

It's time to move on from the iris dataset. Try some of the other datasets in data(), ggplot2::mpg, dplyr::starwars, or this dataset about penguins.

Reference(s) to iris occur in the following files.

References

https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L11 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L14 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L53 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L54 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L55 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-augment.R#L56 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L67 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L68 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L71 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L75 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L107 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L121 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L127 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L147 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L155 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L163 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L173 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.Rmd#L204 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L43 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L44 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L47 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L51 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L96 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L126 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L132 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L151 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L159 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L181 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/README.md#L189 https://github.com/tjmahr/tristan/blob/a30a40c0dad805df0f75c6cc8a1aed457d055bbd/tests/testthat/test-ranef.R#L22

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issue openedtjmahr/tjmisc

Remove references to iris

It's time to move on from the iris dataset. Try some of the other datasets in data(), ggplot2::mpg, dplyr::starwars, or this dataset about penguins.

Reference(s) to iris occur in the following files.

References

https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L4 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L5 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L11 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L12 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L28 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L32 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L52 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L54 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L56 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L65 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L67 https://github.com/tjmahr/tjmisc/blob/ea7b654ccc4cbe81a0ca7294d1aa938134558991/tests/testthat/test-tidy-stats.R#L72 https://github.com/tjmahr/tjmisc/blob/ea1a41882ae957e56d6b3bdcc960cd720f09a5fd/README.Rmd#L74 https://github.com/tjmahr/tjmisc/blob/ea1a41882ae957e56d6b3bdcc960cd720f09a5fd/README.Rmd#L77 https://github.com/tjmahr/tjmisc/blob/ea1a41882ae957e56d6b3bdcc960cd720f09a5fd/README.Rmd#L89 https://github.com/tjmahr/tjmisc/blob/ea1a41882ae957e56d6b3bdcc960cd720f09a5fd/README.Rmd#L91 https://github.com/tjmahr/tjmisc/blob/ea1a41882ae957e56d6b3bdcc960cd720f09a5fd/README.Rmd#L148 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PR opened rstudio-conf-2020/r-for-excel

clarify the function() convention

I have a few colleagues working through this workshop and the list of functions for exploring dataframes all threw them off. ("names() didn't do anything.") I updated the material to try to prevent this issue.

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issue commentstan-dev/bayesplot

`expand_scale()` is deprecated; use `expansion()` instead

That's exactly what I think should happen. A patch in preparation for dplyr 1.0.0 (out on May 29, 2020).

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issue commentstan-dev/bayesplot

`expand_scale()` is deprecated; use `expansion()` instead

That sounds good.

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