# hvega [![vega-lite version](https://img.shields.io/badge/Vega--Lite-v4.7-purple.svg)](https://vega.github.io/vega-lite/) Create [Vega-Lite](https://vega.github.io/vega-lite/) visualizations in Haskell. It targets version 4.7 of the Vega-Lite specification. Note that the module does not include a viewer for these visualizations (which are JSON files), but does provide several helper functions, such as [toHtmlFile](https://hackage.haskell.org/package/hvega/docs/Graphics-Vega-VegaLite.html#v:toHtmlFile), which create HTML that can be viewed with a browser to display the visualization. Other approaches include automatic display in IHaskell notebooks - with the [ihaskell-vega](https://hackage.haskell.org/package/ihaskell-hvega) package - or use of external viewers such as [Vega View](https://hackage.haskell.org/package/vega-view) and [Vega-Desktop](https://github.com/vega/vega-desktop). It started off being a copy on an early version (2.2.1) of the [Elm Vega library](http://package.elm-lang.org/packages/gicentre/elm-vega/2.2.1/VegaLite), which is released under a BSD3 license by Jo Wood of the giCentre at the City University of London. This code is released under the BSD3 license. ## Examples ### Cars The [Vega-Lite example gallery](https://vega.github.io/vega-lite/examples/) contain a number of visualizations of the `cars.json` dataset, which has a number of columns to display, such as "Horsepower", "Miles_per_Gallon", and "Origin". The following code will create a visualization that plots the efficiency of the cars (the "mpg") as a function of its Horsepower, and color-code by the origin of the car: ```Haskell let cars = dataFromUrl "https://vega.github.io/vega-datasets/data/cars.json" [] enc = encoding . position X [ PName "Horsepower", PmType Quantitative ] . position Y [ PName "Miles_per_Gallon", PmType Quantitative ] . color [ MName "Origin", MmType Nominal ] bkg = background "rgba(0, 0, 0, 0.05)" in toVegaLite [ bkg, cars, mark Circle [], enc [] ] ``` When the JSON is viewed with a Vega-Lite aware viewer, the resultant plot is ![Simple scatterplot](https://raw.githubusercontent.com/DougBurke/hvega/master/hvega/images/intro.png "Simple scatterplot") ### Betelgeuse In late 2019 and early 2020 the [star Betelgeuse](https://en.wikipedia.org/wiki/Betelgeuse) - a member of the [constellation Orion](https://en.wikipedia.org/wiki/Orion_(constellation)) - dimmed enough that you could see it. Betelgeuse is a member of the class of Red Supergiant stars, which are massive enough that they will go supernova at some point, and so there was [some speculation](https://en.wikipedia.org/wiki/Betelgeuse#2019%E2%80%932020_fading) that we could see a "naked-eye" supernova (even though the current models suggest that Betelgeuse has about 100,000 more years to go before this happens). This interest lead to a lot of observations added to the [American Association of Variable Star Observers](https://www.aavso.org/) database, which we are going to look at below. This example is rather-more involved than the case one, since it involves data filtering and creation, multiple plots, faceting, and interactive selection. ```Haskell let titleStr = "Betelegeuse's magnitude measurements, collated by AAVSO" w = width 600 h = height 150 pos1Opts fld ttl = [PName fld, PmType Quantitative, PAxis [AxTitle ttl]] x1Opts = pos1Opts "days" "Days since January 1, 2020" y1Opts = pos1Opts "magnitude" "Magnitude" ++ [PSort [Descending], yRange] yRange = PScale [SDomain (DNumbers [-1, 3])] filtOpts = [MName "filterName", MmType Nominal] filtEnc = color (MLegend [ LTitle "Filter", LTitleFontSize 16, LLabelFontSize 14 ] : filtOpts) . shape filtOpts circle = mark Point [ MOpacity 0.5, MFilled False ] encOverview = encoding . position X x1Opts . position Y y1Opts . filtEnc selName = "brush" pos2Opts fld = [PName fld, PmType Quantitative, PAxis [AxNoTitle], PScale [SDomain (DSelectionField selName fld)]] x2Opts = pos2Opts "days" y2Opts = pos2Opts "magnitude" ++ [PSort [Descending]] encDetail = encoding . position X x2Opts . position Y y2Opts . filtEnc xlim = (Number (-220), Number 100) ylim = (Number (-0.5), Number 2.5) overview = asSpec [ w , h , encOverview [] , selection . select selName Interval [ Encodings [ChX, ChY] , SInitInterval (Just xlim) (Just ylim) ] $ [] , circle ] detailPlot = asSpec [ w , h , encDetail [] , circle ] headerOpts = [ HLabelFontSize 16 , HLabelAlign AlignRight , HLabelAnchor AEnd , HLabelPadding (-24) , HNoTitle , HLabelExpr "'Filter: ' + datum.label" ] details = asSpec [ columns 1 , facetFlow [ FName "filterName" , FmType Nominal , FHeader headerOpts ] , spacing 10 , specification detailPlot ] in toVegaLite [ title titleStr [ TFontSize 18 ] , dataFromUrl "https://raw.githubusercontent.com/DougBurke/hvega/master/hvega/data/betelgeuse-2020-03-19.json" [] , transform . filter (FExpr "datum.filterName[0] === 'V'") . filter (FExpr "datum.magnitude < 4") . calculateAs "datum.jd - 2458849.0" "days" $ [] , vConcat [overview, details] , configure . configuration (Axis [ TitleFontWeight Normal, TitleFontSize 16, LabelFontSize 14 ]) $ [] ] ``` This can be viewed as - an [interactive version](https://vega.github.io/editor/#/url/vega-lite/N4KABGBEAuBOCGA7AzgMwPawLaQFxgG1wIxhJUBLAG2gFNY8oATeaAVywDpKb6A5eFloEADAF0wAXmlgA5ADVZkAL4AaYhDI86DfJBbsuWeAHNEFdk1pgAPGAAsK9SVKR4yRvvgBPD6qgAxvBUAWxUrLSeBhycAFZMYAC0YABM9gCsAByZ9gCcnCIqxGLOgeiIlCaMoC5uAB4UHvg1LlDQFlS0AGLl0ADqtBQmABbQnoiYxlSQpbXhAEa0VD2I0ADKFABekfgAjPazJDAd3b0b24y7AGwaYMrEasRe0PDVt5BssNN6o9AADshcAB6IEIADunBMFmGbHmbGQ9ACvVoq04SKwQIAIug2CYAEKfADWtCBwwAbrQTPAgcZkDpSRSqUCDNTFnQqCZaPDaIkUiI+YkRABmRK7fKxZDlSAPUqQMlIxBBMb4IguFq1YaDEbKsC7dIiQ4QSDGWCE6qQdB-eABCzeRgiTjpfwwbx-HZQP7oCirGZQHidJiMVDBBGPVpQMEUJjQYaMK4iA23I0IzoBdpS5pJo7zWDw2OZ8O1b0Wc11RgEXl8-y7BMlKB2lWCx3+FKOsRhwtGlFIpjekxNQiQMvOu0lLO1aCu92Qb06MnBaWd+7hju1bvoXuIKoFwuQJFUTBvTtGyhLQN6bT8QSRQ2tF1u8boLDehe3uaUlHn0jju8LJYrdYtndfY3zvdpoE6TwumoHQZh-CcTgA85gJuY87h-Vc72QYZ4AfZpyAoM9PEvWABCEX172nCZn0QBdMNqMsd07AiiL0FhfDgtDKM8ABHNgkHA1gKApTjj3qRpzXAyC9ExHxkDAZBvQCawACkkH42BvF1Ft+UKZdC3oo4G2-LjTyoL9jVMcxLBveCoGQIJpNcJgn3gb1y1FfwhXbUDk0wHV9FoBzPz7UTmMnPCoD4gSLCEkTfKgeAGgHMgpOnABZKyLDYKwiiXLN9IgTD1SOZA3QCI9d01IZRkufVQMs01zUta1bXtZs2inTxPVnCj-VoL9gyoUMGsjaN8zAeNE2Y9dN23EyxP3Q8mLEsyLJIsjbLQo0Iqop8X2mBKjU6TlEC-EquL-ZYziAy4DjshCIOnaDeAYI6jjSpDbr2VDtsKgyEsgbDcPdLRCPM4iYKvcjnV2x8aLowHGIW0zwYs9i-Ae+zHNB-RXPc-C1qiOSKJTWg0woDMoBzPMVEM8NuL0aLVli9p4qx8SUuOJ7GEQMIqH+ldAeMi7dyJvRjDMbLcveoGcfNFzjAJ1xxagSXrJym97KWcn00QTwaewunZclWAAqsYKztC2W4aZ-iWZeNmtu2znJJOXn+cF1ovaKgrbz3dAqA4FBLn94NlJ1UWTzRyHXs2sK701eArF0FHdyugBBRVhmWqBPwThmroAUTqP5U8gWQXp0fBZDAABqMBoi4K6C9-eBFioAAFZO5sYXl7su9v-xui4fsBtKPaoKhAczqghn1vRYBqsYMIa22oGog7F29-2ytardLhEW59LHI0ABIHM1YxPF+AFgSBRl4EhaFYU4SmgUv2hjAfyl4ESOe6AP3sHESU+tZQTxWjAWgdQAp4loOyD83JZDyXVtLawQh3CfC-iiaAyB-D7nCHQBI8wtIZwzvINYAB5BO5AR7AUyDKJ4FsAhLz+HrTwAAJdAYIwA4XknA9knIkHyRzMvRAQV5LziXgNfw8x3ADTAOURurB4BgAIREYhpDyFULAAAClvoCEEYJjGcHgPAMkkpOCYBMECAAlJwMAABNHECkc5hASCGdAYADzoEJGAVgvDoD-EMUCaAkYgn0DRE+IEbIljzHQNAfxZ1AnBPvlCGMr90SkgoH8P4xIYnwLiQkhxABJRJYJ3D+KnmAGM1gECckUYgBS6AbTBDAEIXsqiAm1IUi8M2ijUCpF0pwaUyggA) - as a PNG: ![PNG version of the lightcurve](https://raw.githubusercontent.com/DougBurke/hvega/master/hvega/images/example.png "PNG version of the lightcurve") ## Documentation A tutorial is provided as part of the module: it is based, as is so much of the module, on the [Elm Vega walk through](https://github.com/gicentre/elm-vegalite/tree/master/docs/walkthrough). The tutorial is [available on hackage](https://hackage.haskell.org/package/hvega/docs/Graphics-Vega-Tutorials-VegaLite.html) - and includes the plot outputs - and the plots it creates are also available by importing the `Graphics.Vega.Tutorials.VegaLite` module. The [Vega-Lite Example Gallery](https://vega.github.io/vega-lite/examples/) has been converted to IHaskell notebooks in the [notebooks directory](https://github.com/DougBurke/hvega/tree/master/notebooks). Start with the [overview notebook](https://github.com/DougBurke/hvega/blob/master/notebooks/VegaLiteGallery.ipynb), which describes the set up, and then the individual sections have their own notebooks (with names of `VegaLiteGallery-
.ipynb`. Unfortunately the plots created by VegaEmbed **do not always appear** in the notebook when viewed with either GitHub's viewer or [ipynb viewer](http://nbviewer.jupyter.org/github/DougBurke/hvega/blob/master/notebooks/VegaLiteGallery.ipynb), but things seem better when using Jupyter Lab (rather than notebook) to create the notebooks (since Vega is natively supported in this environment). However, the native support is for Vega-Lite version 1, and so many of the more-recent capabilities are either ignored or cause the visualization to fail. The notebooks have been re-created using Jupyter Lab (thanks to Tweag I/O's [JupyterWith environment](https://www.tweag.io/posts/2019-02-28-jupyter-with.html)), which should make the plots appear on GitHub (you may need to reload the notebooks as I find they don't display on the first try). ## Differences to Elm Vega Elm Vega has changed significantly since I started `hvega`, and no-longer exposes data types directly but uses functions instead: for example, rather than `PName`, it uses a function like `pName`. It is an open question whether `hvega` will make the same switch. Over time the naming of certain operations or data types has diverged between `hevga` and Elm Vega. One of the more-obvious changes is that the output of `toVegaLite` is a separate type from the input values - that is `VegaLite` and `VLSpec` - since it makes it easier to display the output of `hvega` in `IHaskell`. The JSON specification is retrieved from this type with `fromVL`. The `0.5.0.0` release adds some more type safety (restricting the functions that can be applied to `encoding` and `transform` for instance).