npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

gdal-exprtk

v2.0.0

Published

ExprTk.js plugin for gdal-async

Downloads

5

Readme

gdal-exprtk

License: Apache 2.0 npm version Node.js CIcodecov

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 [email protected] and [email protected].

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. [email protected] supports converting integer types to NaN, [email protected] 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

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

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

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 [email protected] which is implemented in JS. [email protected] 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