gdal-exprtk

gdal-exprtk

This is a plugin that adds support for ExprTk.js expressions to gdal-async.

It allows for truly asynchronous background processing performing only O(1) operations on the V8 main thread. Multiple operations run in parallel and never block the event loop.

Requires gdal-async@3.4 and ExprTk.js@2.0.

Installation

To use as a library in a project:

npm install --save gdal-exprtk

Install globally to use the command-line version:

sudo npm install -g gdal-exprtk

Usage

Command-line utility

The command-line utility supports both JS functions and ExprTk expressions. It uses parallel processing whenever possible.

With ExprTk expression:

gdal_calc.js -i AROME_D2m_10.tiff=d -i AROME_T2m_10.tiff=t
    -o CLOUDBASE.tiff \
    -e -c '125*(t-d)' -f GTiff -t Float64

With JS function:

gdal_calc.js -i AROME_D2m_10.tiff=d -i AROME_T2m_10.tiff=t
    -o CLOUDBASE.tiff \
    -j -c 'return 125*(t-d);' -f GTiff -t Float64

With multiband input files and automatic variable naming:

gdal_calc.js -i multiband.tif@1 -i multiband.tif@2
    -o output.tiff \
    -e -c '(a+b)/2' -f GTiff -t Float64

Producing a multiband output file:

gdal_calc.js -i multiband.tif@1=x -i multiband.tif@2=y
    -o output.tiff \
    -e -c '(x+y)/2' -c '(x-y)/2' -f GTiff -t Float64

With NoData<->Nan conversion

If a NoData value is specified for the output file, then all input NoData values will be converted to NaN before invoking the user function and all NaN values returned from the user function will be written as the NoData value. This works only if the output data type is a floating point type. gdal-async@3.5 supports converting integer types to NaN, gdal-async@3.4 requires that all input files have a floating point type for this to work.

gdal_calc.js -i AROME_D2m_10.tiff=d -i AROME_T2m_10.tiff=t
    -o CLOUDBASE.tiff \
    -e -c '125*(t-d)' -f GTiff -t Float64 -n -1e-38

Reading a JS function from a file

gdal_calc.js can use both a default and a named export. The arguments order must be given explicitly.

espy.js:

module.exports = {};
module.exports.espy = (t, td) => (125 * (t - td));
module.exports.espy.args = ['t', 'td'];

Then:

gdal_calc.js -i AROME_D2m_10.tiff=td -i AROME_T2m_10.tiff=t
    -o CLOUDBASE.tiff \
    -j -c =./espy.js@espy -f GTiff -t Float64 -n -1e-38

Reading an ExprTk expression from a file

espy.exprtk:

125 * (t - td)

Then:

gdal_calc.js -i AROME_D2m_10.tiff=td -i AROME_T2m_10.tiff=t
    -o CLOUDBASE.tiff \
    -e -c =./espy.exprtk -f GTiff -t Float64 -n -1e-38

With calcAsync

import * as gdal from 'gdal-async';
import { Float64 as Float64Expression } from 'exprtk.js';
import { calcAsync } from 'gdal-exprtk';

const T2m = await gdal.openAsync('AROME_T2m_10.tiff'));
const D2m = await gdal.openAsync('AROME_D2m_10.tiff'));
const size = await T2m.rasterSizeAsync;

const filename = `/vsimem/AROME_CLOUDBASE.tiff`;
const dsCloudBase = gdal.open(filename, 'w', 'GTiff',
    size.x, size.y, 1, gdal.GDT_Float64);

// Espy's estimation for cloud base height
const espyExpr = new Float64Expression('125 * (T2m - D2m)');

// This is required for the automatic NoData handling
// (it will get converted from/to NaN)
(await cloudBase.bands.getAsync(1)).noDataValue = -1e38;

// Mapping to ExprTk.js variables is by (case-insensitive) name
// and does not depend on the order
await calcAsync({
    T2m: await T2m.bands.getAsync(1),
    D2m: await D2m.bands.getAsync(1)
}, await cloudBase.bands.getAsync(1), espyExpr, { convertNoData: true });

As a Node.js Streams-compatible Transform

import * as gdal from 'gdal-async';
import { Float64 as Float64Expression } from 'exprtk.js';
import { RasterTransform } from 'gdal-exprtk';

import { finished as _finished } from 'stream';
import { promisify } from 'util';
const finished = promisify(_finished);

// Espy's estimation for cloud base height (lifted condensation level)
// LCL = 125 * (T2m - Td2m)
// where T2m is the temperature at 2m and Td2m is the dew point at 2m
const expr = new Float64Expression('125 * (T2m - D2m)');

const dsT2m = gdal.open('AROME_T2m_10.tiff'));
const dsD2m = gdal.open('AROME_D2m_10.tiff'));

const filename = `/vsimem/AROME_CLOUDBASE.tiff`;
const dsCloudBase = gdal.open(filename, 'w', 'GTiff',
    dsT2m.rasterSize.x, dsT2m.rasterSize.y, 1, gdal.GDT_Float64);

// Mapping to ExprTk.js variables is by (case-insensitive) name
// and does not depend on the order
const mux = new gdal.RasterMuxStream({
    T2m: dsT2m.bands.get(1).pixels.createReadStream(),
    D2m: dsD2m.bands.get(1).pixels.createReadStream()
});

const ws = dsCloudBase.bands.get(1).pixels.createWriteStream();

const espyEstimation = new RasterTransform({ type: Float64Array, expr });

mux.pipe(espyEstimation).pipe(ws);
await finished(ws);
dsCloudBase.close();

API

Table of Contents

• RasterTransform
  • Parameters
  • Examples
• RasterTransformOptions
  • Properties
• CalcOptions
  • Properties
• ProgressCb
  • Parameters
• calcAsync
  • Parameters
  • Examples
• toPixelFunc
  • Parameters
  • Examples

RasterTransform

Extends stream.Transform

A raster Transform stream

Applies an ExprTk.js Expression on all data elements.

Input must be a gdal.RasterMuxStream

calcAsync provides a higher-level interface for the same feature

Parameters

• options RasterTransformOptions?

  • options.exr (Function | Expression) Function to be applied on all data

Examples

const dsT2m = gdal.open('AROME_T2m_10.tiff'));
const dsD2m = gdal.open('AROME_D2m_10.tiff'));

const dsCloudBase = gdal.open('CLOUDBASE.tiff', 'w', 'GTiff',
  dsT2m.rasterSize.x, dsT2m.rasterSize.y, 1, gdal.GDT_Float64);

const mux = new gdal.RasterMuxStream({
  T2m: dsT2m.bands.get(1).pixels.createReadStream(),
  D2m: dsD2m.bands.get(1).pixels.createReadStream()
});
const ws = dsCloudBase.bands.get(1).pixels.createWriteStream();

// Espy's estimation for cloud base height (lifted condensation level)
// LCL = 125 * (T2m - Td2m)
// where T2m is the temperature at 2m and Td2m is the dew point at 2m
const expr = new Float64Expression('125 * (t - td)');
const espyEstimation = new RasterTransform({ type: Float64Array, expr });

mux.pipe(espyEstimation).pipe(ws);

RasterTransformOptions

Extends stream.TransformOptions

Properties

• expr Expression Function to be applied on all data

CalcOptions

Type: object

Properties

• convertNoData boolean?
• progress_cb ProgressCb?

ProgressCb

Type: Function

Parameters

• complete number

calcAsync

Compute a new output band as a pixel-wise function of given input bands

This is an alternative implementation of gdal_calc.py.

It is identical to the one in gdal-async except that it accepts an ExprTK.js expression as function instead of a JS function.

It's main advantage is that it does not solicit the V8's main thread for any operation that is not O(1) - all computation is performed in background async threads. The only exception is the convertNoData option with gdal-async@3.4 which is implemented in JS. gdal-async@3.5 supports C++ conversion of NoData to NaN.

It internally uses a RasterTransform which can also be used directly for a finer-grained control over the transformation.

There is no sync version.

Parameters

• inputs Record<string, gdal.RasterBand> An object containing all the input bands

• output gdal.RasterBand Output raster band

• expr Expression ExprTk.js expression

• options CalcOptions? Options

  • options.convertNoData boolean Input bands will have their NoData pixels converted toNaN and a NaN output value of the given function will be converted to a NoData pixel, provided that the output raster band has its RasterBand.noDataValue set (optional, default false)
  • options.progress_cb ProgressCb Progress callback (optional, default undefined)

Examples

const T2m = await gdal.openAsync('TEMP_2M.tiff'));
const D2m = await gdal.openAsync('DEWPOINT_2M.tiff'));
const size = await T2m.rasterSizeAsync
const cloudBase = await gdal.openAsync('CLOUDBASE.tiff', 'w', 'GTiff',
   size.x, size.y, 1, gdal.GDT_Float64);

(await cloudBase.bands.getAsync(1)).noDataValue = -1e38
// Espy's estimation for cloud base height
const espyFn = (t, td) => 125 * (t - td);

await calcAsync({
 t: await T2m.bands.getAsync(1),
 td: await D2m.bands.getAsync(1)
}, cloudBase.bands.getAsync(1), espyFn, { convertNoData: true });

Returns Promise<void>

toPixelFunc

Get a gdal-async pixel function descriptor for this ExprTk.js expression.

Every call of this function produces a permanent GDAL descriptor that cannot be garbage-collected, so it must be called only once per ExprTk.js expression.

As of GDAL 3.4, GDAL does not allow unregistering a previously registered function.

The returned object can be used across multiple V8 instances (ie worker threads).

gdal-async does not support multiple V8 instances.

If the V8 instance containing the ExprTk.js expression is destroyed, further attempts to read from Datasets referencing the function will produce an exception.

Parameters

• expression Expression

Examples

// This example will register a new GDAL pixel function called sum2
// that requires a VRT dataset with 2 values per pixel

const gdal = require('gdal-async);
const Float64Expression = require('exprtk.js').Float64;
const { toPixelFunc } = require('gdal-exprtk');
const sum2 = new Float64Expression('a + b');
gdal.addPixelFunc('sum2', toPixelFunc(sum2));

Returns gdal.PixelFunction

Changelog

[2.0.0] 2024-01-08

• Support Node.js 16.x to 21.x
• Support transforming an Expression to a GDAL pixel function
• Support reading functions and expressions from a file
• In the CLI-tool, replace all : with @ to achieve better compatibility with Windows where : is a common symbol in a filename (C:\...)