Sunday, May 6, 2018

Affine Transformation

I've been working on a personal project for data presentation and exploration. It is very much a work in progress but as part of the development I've come across some interesting little technical problems to solve. I hope to eventually have a longer series of posts along the lines of 'building your own data tools;' however, until I find the time to give that the attention it needs, I plan on posting some smaller entries centered around these technical problems.

One of the early challenges I came across when plotting data was mapping the input values to the fixed amount of space I had on screen. For example, if I generate a window that is 600px wide I can only support a range of input values less than or equal to 600 (using a naive approach of each value in the range maps to a pixel on screen). Supporting an input range greater than 600 values requires some level of mapping between the input values and the available pixels on the screen. There are simple conversions for specific input ranges (e.g. when the range is close to a multiple of the number of pixels) but a more general solution is necessary to handle arbitrary input data sets.

The way I ended up solving this was to use an affine transformation to map the input domain to a fixed pixel range. This is how scales work in D3.js if you are familiar with that JavaScript library. For example, if my input values come from [-100, 100] but I need my output values to fall within [28,63] then applying this transformation would look something like the image below:



Notice that the minimum value in the input interval (-100) maps directly to the minimum value in the output interval (28). Values along the input interval are mapped to the output interval preserving the relative position within each. The equation to do this is:

\[ range_{x} = (domain_{x} - domain_{a}) * ((range_{b} - domain_{a}) / (domain_{b} - domain_{a})) + range_{a} \]

Where domain and range are defined by the intervals \([domain_{a}, domain_{b}]\) and \([range_{a},range_{b}]\), respectively. Neither the domain nor the range is required to have a 0 as one of the endpoints and the intervals can be either increasing or decreasing. This generality is helpful in a variety of contexts. For example:

Setting Borders
The viewport used to plot data may not always use all available pixels of the window; multi-plot windows or viewports that have a border are two examples. In the case where there is a border around the plot (allowing for labels and tick marks) that area should not be considered as part of the range of the viewport. Instead, a window with 600px width that uses 30px on either side for border should use a range of [30,570] - the equation above makes this easy.

Inverted Axis
In most window coordinate systems the origin is at the top left of the screen. That means increasing y-axis values (from the window perspective) are typically decreasing data set y-axis values. Using a negative range makes this translation simple. Consider a 600px window height: mapping a domain to the range [600,0] automatically handles the inverted axis problem.

Another way that this simplifies things is when there is a need to 'flip' the layout of a graph. For example, in the two images below the data is the same; the only difference is the range. Having the ability to easily manipulate target ranges for the input data allows me to cycle through multiple views of the same data without much work on the backend.