Super Low-Level Raster Reprojection and Resampling Library
npm install -S geowarpconst geowarp = require("geowarp");
const proj4 = require("proj4-fully-loaded");
const result = geowarp({
// control the level of console log output
// set debug_level to zero to turn off console logging
debug_level: 2,
// reproject from an [x, y] point in the input spatial reference system
// to an [x, y] point in the output spatial reference system
forward: proj4("EPSG:" + in_srs, "EPSG:3857").forward,
// reproject from an [x, y] point in the output spatial reference system
// to an [x, y] point in the input spatial reference system
inverse: proj4("EPSG:" + in_srs, "EPSG:3857").inverse,
// two-dimensional array of pixel data organized by band
// usually [ r, g, b ] or [ r, g, b, a ]
// pixel data for each band is usually flattened,
// so the end of one row is immediately followed by the next row
in_data: [
[0, 123, 123, 162, ...],
[213, 41, 62, 124, ...],
[84, 52, 124, 235, ...]
],
// bounding box of input data (in_data)
// in [xmin, ymin, xmax, ymax] format
in_bbox: [ -122.51, 40.97, -122.34, 41.11 ],
// layout of the in_data using xdim layout syntax
// see: https://github.com/danieljdufour/xdim
in_layout: "[band][row,column]",
// a number or array of numbers
in_no_data: -99,
// a number or string representing the spatial reference system of the input data
// could be 4326 or "EPSG:4326"
in_srs: 4326,
// only necessary when in_data is skewed or rotated
// 6-parameter geotransform using the order from https://gdal.org/tutorials/geotransforms_tut.html
in_geotransform: [337934.48363, -0.142999, -0.576775, 7840518.4648, -0.57677, 0.14299],
// how many pixels wide the input data is
in_width: 1032,
// how many pixels tall the input data is
in_height: 1015,
// optional array of constructor names for each array level
// default is to use Array (untyped) for everything
out_array_types: ["Array", "Array", "Uint8Array"],
// optional array for sampling and/or changing band order
// array is the order of the bands in the output with numbers
// indicating the band index in the input (starting at zero)
// for example, [13, 12, 11] skips the first 11 bands,
// and takes the 12th, 13th, and 14th in reverse order
out_bands: [13, 12, 11],
// bounding box of output
// this is the space that you want to paint
// in same format as in_bbox
out_bbox: [-13638811.83098057, 5028944.964938315, -13619243.951739563, 5028944.964938315],
// optional
// single or multi-dimensional array that will hold the output
out_data: [[[[],[],[],...],[[],[],[],...],[[],[],[],...],[[],[],[],...],...]],
// optional, default is null
// the no data value for your output data
out_no_data: -99,
// layout of the result using xdim layout syntax
// see: https://github.com/danieljdufour/xdim
out_layout: "[row][column][band]",
// a number or string representing the spatial reference system of the input data
// could be 4326 or "EPSG:4326"
out_srs: 3857,
// optional
// number of bands in the output
out_pixel_depth: 3,
// height of the output image in pixels
out_height: 256,
// width of the output image in pixels
out_width: 256,
// horizontal and vertical resolution
// resolution of [0.25, 0.25] (i.e. 25%) means that you sample once for every 4 x 4 pixels
// this is useful if you need your output to be a certain height or width (like 256 x 256)
// but don't necessarily want to render data at that high resolution
out_resolution: [0.5, 0.5],
// method for sampling pixels
// current supported methods are:
// "near", "vectorize", "near-vectorize", "bilinear", "max", "mean", "median", "min", "mode", "mode-max", "mode-mean", "mode-median", and "mode-min"
// you can also pass in a custom function that takes in ({ values }) and returns a number
method: 'median',
// round output pixel values to closest integer
// do this if you will convert your output to a PNG or JPG
round: true,
// optional
// the lowest possible pixel value considering the bit-depth of the data
// this is used to speed up the min and mode-min resampling
// if in_data is an array of typed arrays, this will be automatically calculated
theoretical_min: 0,
// optional
// the highest possible pixel value considering the bit-depth of the data
// this is used to speed up the max and mode-max resampling
// if in_data is an array of typed arrays, this will be automatically calculated
theoretical_max: 255,
// optional
// band math expression that maps a pixel from the read bands to the output
// if expr is async (i.e. returns a promise), geowarp will return a promise
expr: ({ pixel }) => {
// clamp values above 100
return pixel.map(value => Math.min(value, 100));
},
// optional
// whether to insert or skip null values
// "skip" - default, don't insert null values
// "insert" - try to insert null values into output data
insert_null_strategy: "skip",
// optional
// array of band indexes to read from
// use this if your expr function only uses select bands
read_bands: [0, 1, 2],
// optional
// polygon or multi-polygons defining areas to cut out (everything outside becomes no data)
// terminology taken from https://gdal.org/programs/gdalwarp.html
cutline: geojson,
// if you specify a cutline, this is required
cutline_srs: 4326,
// function to reproject [x, y] point from cutline_srs to out_srs
// required if you specify a cutline and the cutline is a different srs than out_srs,
cutline_forward: proj4("EPSG:4326", "EPSG:3857").forward,
// optional, default is "outside"
// cut out the pixels "inside" or "outside" the cutline
// in other words, if your cutline_strategy is "inside",
// geowarp will set every pixel inside your cutline geometry to out_no_data
cutline_strategy: "inside",
// optional, default is false
// enable experimental turbocharging via proj-turbo
turbo: true,
// completely optional and not recommended
// you don't want this in most cases
// over-ride the default function for inserting data into the output multidimensional array
// useful if writing to an alternative object like a canvas
insert_pixel: ({ row, column, pixel }) => {
context.fillStyle = toColor(pixel);
context.fillRect(column, row, 1, 1);
},
// completely optional and not recommended in most cases
// take pixel values for a given sample located by sample row and column
// and insert into the output multidimensional array
// by default, this will call insert_pixel
insert_sample: ({ row, column, pixel }) => {
const [xmin, ymin, xmax, ymax] = scalePixel([column, row], [x_scale, y_scale]);
for (let y = ymin; y < ymax; y++) {
for (let x = xmin; x < xmax; x++) {
insert_pixel({ row: y, column: x, pixel });
}
}
},
// skip writing a pixel if "any" or "all" its values are no data
// default is undefined, meaning don't skip no data values
skip_no_data_strategy: "any"
});result is
{
// a multi-dimensional array of pixel values with the structure defined by out_layout
data: [
[ [...], [...], [...] ], // band 1
// ...
]
}