calc-stats
Memory-Aware Statistical Calculations
motivation
I was looking for a way to calculate statistics for large grid files, including ASCII Grid, GeoTIFF, JPG, JPG2000, and PNG.
There were other solutions that worked on numerical arrays.
However, those didn't work for my use case because trying to put everything into one array would quickly drain my system's memory.
Additionally, some satellite imagery data is so large, it exceeds the maximum length allowed by most JavaScript engines.
I needed a solution that could stream the data.
However, the other streaming solutions I found, calculate the statistics after each number.
For my use case, I don't really care what the sum of half the points are.
I only really care about the stats at the end, for all the points.
Updating the statistics after each new number was wasted computations and slowed things down. Ultimately, I found it easier to create a new library tailored towards large datasets.
Enjoy!
install
npm install calc-stats
basic usage
import calcStats from "calc-stats";
const results = calcStats(data);
advanced usage
no data value
If you want to ignore a certain number as a "No Data Value", pass in noData:
const results = calcStats(data, { noData: -99 });
asynchronous iterations
If you pass in an asynchronous iterable, such as one fetching remote image tiles,
you can transform calcStats to handle this by setting async to true.
const results = await calcStats(datafetcher, { async: true });
specify calculations
If you only care about specific statistics, you can configure calcStats through an options object:
import calcStats from "calc-stats";
const options = {
calcHistogram: false,
calcMax: true,
calcMean: false,
calcMedian: false,
calcMin: true,
calcMode: false,
calcModes: false,
calcSum: false
};
const results = calcStats(data, options);