DougManuel

@DougManuel·5 public vizzes

LAP-JV

The LAP-JV example visualizes the Linear Assignment Problem, showing how seven randomly placed points are optimally matched to a 7x7 grid of target cells. The code uses the `lap()` function from the lap-jv library to compute the minimum-cost assignment, with costs derived from squared Euclidean distances. Animated SVG lines initially converge from points to their assigned grid positions, followed by circles transitioning to their final cells, while a d3-annotation callout highlights the most expensive attribution. The visualization relies on d3.v4 with SVG transitions and the d3-annotation library to label the result.

Mar 12, 2017

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Make the figures click-able in your RMarkdown=>HTML reports.

This example demonstrates how to make figures clickable in an RMarkdown-generated HTML report, allowing readers to open images in full resolution in a new browser tab. It shows the integration of JavaScript with RMarkdown's HTML output to enhance interactivity. The code uses jQuery to select all images wrapped in figure elements, then wraps each image in an anchor tag that references the image source as the link URL. The script sets the link's title attribute to the image's alt text and adds `target="_blank"` to open the link in a new tab. The implementation relies on jQuery's `wrap` function and attribute manipulation methods.

Sep 28, 2016

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Reusable Chart component for D3 - using prototypes and factories

This example demonstrates a reusable bar-chart component built with D3.js, using a factory method and prototype-based class to create configurable chart instances. The code defines a `BarChart.instanceOf` factory that returns chart objects with chainable accessor methods for width, height, bar padding, and fill color. When the `render` method is called on a selection, it binds to each data array, computes bar dimensions from the data extent, and appends SVG rectangles via `d3.select` and `selection.append`. The chart reads data directly from bound arrays, scaling bar widths proportionally to the maximum value, and applies the configured fill color. The implementation emphasizes encapsulation and reuse through JavaScript prototypes and closures, without relying on external data sources.

Sep 17, 2015

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Define in global scope vars for each used CSS classname

This example shows a JavaScript utility that automatically creates global jQuery variables named after CSS classnames found in the DOM. The function `defineVarsFromClassName()` scans all elements with a `class` attribute, splits each class name, and assigns a jQuery object reference to a variable like `$className` (with hyphens converted to underscores) if it doesn’t already exist. It relies on jQuery selectors and the global `window` object to store these variables, making class-based DOM access more convenient. The code demonstrates a pattern for reducing repetitive variable declarations in jQuery-heavy projects, using the document’s existing class attributes as the source of variable names.

Jul 11, 2015

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Rprofile.R

This R configuration script customizes a user’s R environment for data analysis, primarily by setting package options, a CRAN mirror, and database connections via RODBC. It defines utility functions like `tdf` for transposing data frames, `propmiss` for summarizing missing values, and `qq` for generating QQ plots of p-values. The code uses base R functions such as `lapply`, `sapply`, `hist`, and `plot`, along with `utils::head` and `base::summary` shortcuts. The script demonstrates practical workflows for data wrangling, statistical visualization, and system-specific setup, emphasizing reproducible coding habits.

Jan 9, 2012