wifi-densepose/rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui/node_modules/source-map-js
rUv 341d9e05a8
ruv-neural: publish 11 crates to crates.io — full implementation, no stubs
* Add temporal graph evolution & RuVector integration research

GOAP Agent 8 output: 1,528-line SOTA research document covering temporal
graph models (TGN, JODIE, DyRep), RuVector graph memory design, mincut
trajectory tracking with Kalman filtering, event detection pipelines,
compressed temporal storage, cross-room transition graphs, and a 5-phase
integration roadmap.

Part of RF Topological Sensing research swarm (10 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add transformer architectures for graph sensing research

GOAP Agent 4 output: 896-line SOTA document covering Graph Transformers
(Graphormer, SAN, GPS, TokenGT), Temporal Graph Transformers (TGN, TGAT,
DyRep), ViT for RF spectrograms, transformer-based mincut prediction,
positional encoding for RF graphs, foundation models for RF sensing, and
efficient edge deployment with INT8 quantization.

Part of RF Topological Sensing research swarm (10 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add attention mechanisms for RF sensing research

GOAP Agent 3 output: 1,110-line document covering GAT for RF graphs,
self-attention for CSI sequences, cross-attention multi-link fusion,
attention-weighted differentiable mincut, spatial node attention,
antenna-level subcarrier attention, and efficient attention variants
(linear, sparse, LSH, S4/Mamba). 8 ASCII architecture diagrams.

Part of RF Topological Sensing research swarm (10 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add sublinear mincut algorithms research

GOAP Agent 5 output: 698-line document covering classical mincut complexity,
sublinear approximation (sampling, sparsifiers), dynamic mincut with lazy
recomputation hybrid, streaming sketch algorithms, Benczur-Karger
sparsification, local partitioning (PageRank-guided cuts), randomized
methods reliability analysis, and Rust implementation with const-generic
RfGraph, zero-alloc Stoer-Wagner, SIMD batch updates.

Part of RF Topological Sensing research swarm (10 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add CSI edge weight computation research

GOAP Agent 2 output: ~700-line document covering CSI feature extraction,
coherence metrics (cross-correlation, mutual information, phasor coherence),
multipath stability scoring (MUSIC, ESPRIT, ISTA), temporal windowing
(EMA, Welford, Kalman), noise robustness (phase noise, AGC, clock drift),
edge weight normalization, and implementation architecture showing 32KB
memory for 120 edges within ESP32-S3 capability.

Part of RF Topological Sensing research swarm (10 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add contrastive learning for RF coherence research

GOAP Agent 7 output: 1,226-line document covering SimCLR/MoCo/BYOL for CSI,
AETHER-Topo dual-head extension, coherence boundary detection with multi-scale
analysis, delta-driven updates (2-12x efficiency), self-supervised pre-training
protocol, triplet networks for 5-state edge classification, and MERIDIAN
cross-environment transfer with EWC continual learning.

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add resolution and spatial granularity analysis research

GOAP Agent 9 output: 1,383-line document covering Fresnel zone analysis,
node density vs resolution (16-node/5m room → 30-60cm), Cramer-Rao lower
bounds with Fisher Information Matrix, graph cut resolution theory,
multi-frequency enhancement (6cm coherent dual-band limit), RF tomography
comparison, experimental validation protocols, and resolution scaling laws
(8.8cm theoretical limit).

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add RF graph theory and minimum cut foundations research

GOAP Agent 1 output: Graph-theoretic foundations covering max-flow/min-cut
for RF (Ford-Fulkerson, Stoer-Wagner, Karger), RF as dynamic graph with
CSI coherence weights, topological change detection via Fiedler vector and
Cheeger inequality, dynamic graph algorithms, comparison to classical RF
sensing, formal mathematical framework, and 9 open research questions.

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add ESP32 mesh hardware constraints research

GOAP Agent 6 output: ESP32 CSI capabilities (52/114 subcarriers), 16-node
mesh topology with 120 edges, TDM synchronized sensing (3ms slots),
computational budget (Stoer-Wagner uses 0.07% of one core), channel hopping,
power analysis (0.44W/node), dual-core firmware architecture, and edge vs
server computing with 100x data reduction on-device.

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add system architecture and prototype design research

GOAP Agent 10 output: End-to-end architecture with pipeline diagrams,
existing crate integration mapping, new rf_topology module design (DDD
aggregate roots), 100ms latency budget breakdown, 3-phase prototype plan
(4-node POC → 16-node room → 72-node multi-room), benchmark design with
8 metrics, ADR-044 draft, and Rust trait definitions (EdgeWeightComputer,
TopologyGraph, MinCutSolver, BoundaryInterpolator).

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add quantum sensing and quantum biomedical research documents

Agent 11: Quantum-level sensors (729 lines) — NV centers, SQUIDs, Rydberg
atoms, quantum illumination, quantum graph theory (walks, spectral, QAOA),
hybrid classical-quantum architecture, quantum ML (VQC, kernels, reservoir
computing), NISQ applications (D-Wave, VQE), hardware roadmap.

Agent 12: Quantum biomedical sensing (827 lines) — whole body biomagnetic
mapping, neural field imaging without electrodes, circulation sensing,
cellular EM signaling, non-contact diagnostics, coherence-based diagnostics
(disease as coherence breakdown), neural interfaces, multimodal observatory,
room-scale ambient health monitoring, graph-based biomedical analysis.

Part of RF Topological Sensing research swarm (12 agents).

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add research index synthesizing all 12 documents (14,322 lines)

Master index for RF Topological Sensing research compendium covering:
graph theory foundations, CSI edge weights, attention mechanisms,
transformers, sublinear algorithms, ESP32 hardware, contrastive learning,
temporal graphs, resolution analysis, system architecture, quantum sensors,
and quantum biomedical sensing. Includes key findings, proposed ADRs
(044, 045), and 5-phase implementation roadmap.

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add SOTA neural decoding landscape and 10 application domains research

- Doc 21: Comprehensive SOTA map (2023-2026) of brain sensors, decoders,
  and visualization systems with RuVector/mincut positioning analysis
- Doc 22: Ten application domains for brain state observatory including
  disease detection, BCI, cognitive monitoring, mental health diagnostics,
  neurofeedback, dream reconstruction, cognitive research, HCI, wearables,
  and brain network digital twins with strategic roadmap

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add NV diamond neural magnetometry research document (13/22)

Comprehensive 600+ line document covering NV center physics, neural
magnetic field sources, sensor architecture, SQUID comparison, signal
processing pipeline, RuVector integration, and development roadmap.

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add ruv-neural workspace Cargo.toml with 12 crate definitions

Workspace structure for the rUv Neural brain topology analysis system.
12 mix-and-match crates with shared dependencies including RuVector
integration, petgraph, rustfft, and WASM/ESP32 support.

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add ruv-neural crate ecosystem — 12 mix-and-match crates (WIP)

Initial implementation of the rUv Neural brain topology analysis system:
- ruv-neural-core: Core types, traits, errors, RVF format (compiles)
- ruv-neural-sensor: NV diamond, OPM, EEG sensor interfaces (in progress)
- ruv-neural-signal: DSP, filtering, spectral, connectivity (in progress)
- ruv-neural-graph: Brain connectivity graph construction (in progress)
- ruv-neural-mincut: Dynamic minimum cut topology analysis (in progress)
- ruv-neural-embed: RuVector graph embeddings (in progress)
- ruv-neural-memory: Persistent neural state memory + HNSW (compiles)
- ruv-neural-decoder: Cognitive state classification + BCI (in progress)
- ruv-neural-esp32: ESP32 edge sensor integration (compiles)
- ruv-neural-wasm: WebAssembly browser bindings (in progress)
- ruv-neural-viz: Visualization + ASCII rendering (in progress)
- ruv-neural-cli: CLI tool (in progress)

Agents still writing remaining modules. Next: fix compilation, tests, push.

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Fix ruv-neural crate compilation: all 12 crates build and 1200+ tests pass

- Fix node2vec.rs type inference error (Vec<_> → Vec<Vec<f64>>)
- Fix artifact.rs with full filter-based detection implementations
- Fix signal crate ConnectivityMetric re-export and trait method names
- Fix embed crate EmbeddingGenerator trait implementations
- Complete spectral, topology, and node2vec embedders with tests
- Complete preprocessing pipeline with sequential stage processing
- All workspace crates compile cleanly, 0 test failures

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* Add ruv-neural-cli README

https://claude.ai/code/session_01DGUAowNScGVp88bK2eiuRv

* fix: convert desktop icons from RGB to RGBA for Tauri build

Tauri's generate_context!() macro requires RGBA PNG icons. All 5 icon
files (32x32.png, 128x128.png, 128x128@2x.png, icon.icns, icon.ico)
were RGB-only, causing a proc macro panic on Linux builds.

Fixes #200

Co-Authored-By: claude-flow <ruv@ruv.net>

* Add Subcarrier Manifold and Vitals Oracle modules for 3D visualizations

- Implemented Subcarrier Manifold to visualize amplitude data as a 3D surface with height and age attributes.
- Created Vitals Oracle to represent vital signs using toroidal rings and particle trails, incorporating breathing and heart rate dynamics.
- Both modules utilize Three.js for rendering and include custom shaders for visual effects.

* feat: complete ruv-neural implementation — physics models, security, witness verification

Replace all stubs/mocks with production physics-based signal models:
- NV Diamond: ODMR Lorentzian dip, 1/f pink noise (Voss-McCartney), brain oscillations
- OPM: SERF-mode, 50/60Hz powerline harmonics, full cross-talk compensation
  via Gaussian elimination with partial pivoting
- EEG: 5 frequency bands, eye blink artifacts (Fp1/Fp2), muscle artifacts,
  impedance-based thermal noise floor
- ESP32 ADC: ring-buffer reader with calibration signal generator, i16 clamp

Security hardening (SEC-001 through SEC-005):
- RVF bounded allocation (16MB metadata, 256MB payload)
- sample_rate validation (>0, finite)
- Signal NaN/Inf rejection
- ADC resolution_bits overflow clamp
- HNSW HashSet visited tracking + bounds checks

Performance optimizations (PERF-001 through PERF-005):
- 67x fewer FFTs via pre-computed analytic signals
- VecDeque O(1) eviction in memory store
- Thread-local FFT planner caching
- BrainGraph::validate() for edge/weight integrity
- Eigenvalue convergence early termination

Ed25519 witness verification system:
- 41 capability attestations across all 12 crates
- SHA-256 digest + Ed25519 signature
- CLI commands: `witness --output` and `witness --verify`

README: ethics warning, hardware parts list (AliExpress), assembly instructions

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs: add crates.io badges and install instructions to ruv-neural README

Add version badges linking to each published crate on crates.io,
cargo add instructions, and crate search link in the Crate Map table.

Co-Authored-By: claude-flow <ruv@ruv.net>

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-03-09 10:52:24 -04:00
..
LICENSE ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00
README.md ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00
package.json ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00
source-map.d.ts ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00
source-map.js ruv-neural: publish 11 crates to crates.io — full implementation, no stubs 2026-03-09 10:52:24 -04:00

README.md

Source Map JS

NPM

Difference between original source-map:

TL,DR: it's fork of original source-map@0.6, but with perfomance optimizations.

This journey starts from source-map@0.7.0. Some part of it was rewritten to Rust and WASM and API became async.

It's still a major block for many libraries like PostCSS or Sass for example because they need to migrate the whole API to the async way. This is the reason why 0.6.1 has 2x more downloads than 0.7.3 while it's faster several times.

Downloads count

More important that WASM version has some optimizations in JS code too. This is why community asked to create branch for 0.6 version and port these optimizations but, sadly, the answer was «no». A bit later I discovered the issue created by Ben Rothman (@benthemonkey) with no response at all.

Roman Dvornov (@lahmatiy) wrote a serveral posts (russian, only, sorry) about source-map library in his own Telegram channel. He mentioned the article «Maybe you don't need Rust and WASM to speed up your JS» written by Vyacheslav Egorov (@mraleph). This article contains optimizations and hacks that lead to almost the same performance compare to WASM implementation.

I decided to fork the original source-map and port these optimizations from the article and several others PR from the original source-map.


This is a library to generate and consume the source map format described here.

Use with Node

$ npm install source-map-js

Table of Contents

Examples

Consuming a source map

var rawSourceMap = {
  version: 3,
  file: 'min.js',
  names: ['bar', 'baz', 'n'],
  sources: ['one.js', 'two.js'],
  sourceRoot: 'http://example.com/www/js/',
  mappings: 'CAAC,IAAI,IAAM,SAAUA,GAClB,OAAOC,IAAID;CCDb,IAAI,IAAM,SAAUE,GAClB,OAAOA'
};

var smc = new SourceMapConsumer(rawSourceMap);

console.log(smc.sources);
// [ 'http://example.com/www/js/one.js',
//   'http://example.com/www/js/two.js' ]

console.log(smc.originalPositionFor({
  line: 2,
  column: 28
}));
// { source: 'http://example.com/www/js/two.js',
//   line: 2,
//   column: 10,
//   name: 'n' }

console.log(smc.generatedPositionFor({
  source: 'http://example.com/www/js/two.js',
  line: 2,
  column: 10
}));
// { line: 2, column: 28 }

smc.eachMapping(function (m) {
  // ...
});

Generating a source map

In depth guide: Compiling to JavaScript, and Debugging with Source Maps

With SourceNode (high level API)

function compile(ast) {
  switch (ast.type) {
  case 'BinaryExpression':
    return new SourceNode(
      ast.location.line,
      ast.location.column,
      ast.location.source,
      [compile(ast.left), " + ", compile(ast.right)]
    );
  case 'Literal':
    return new SourceNode(
      ast.location.line,
      ast.location.column,
      ast.location.source,
      String(ast.value)
    );
  // ...
  default:
    throw new Error("Bad AST");
  }
}

var ast = parse("40 + 2", "add.js");
console.log(compile(ast).toStringWithSourceMap({
  file: 'add.js'
}));
// { code: '40 + 2',
//   map: [object SourceMapGenerator] }

With SourceMapGenerator (low level API)

var map = new SourceMapGenerator({
  file: "source-mapped.js"
});

map.addMapping({
  generated: {
    line: 10,
    column: 35
  },
  source: "foo.js",
  original: {
    line: 33,
    column: 2
  },
  name: "christopher"
});

console.log(map.toString());
// '{"version":3,"file":"source-mapped.js","sources":["foo.js"],"names":["christopher"],"mappings":";;;;;;;;;mCAgCEA"}'

API

Get a reference to the module:

// Node.js
var sourceMap = require('source-map');

// Browser builds
var sourceMap = window.sourceMap;

// Inside Firefox
const sourceMap = require("devtools/toolkit/sourcemap/source-map.js");

SourceMapConsumer

A SourceMapConsumer instance represents a parsed source map which we can query for information about the original file positions by giving it a file position in the generated source.

new SourceMapConsumer(rawSourceMap)

The only parameter is the raw source map (either as a string which can be JSON.parse'd, or an object). According to the spec, source maps have the following attributes:

  • version: Which version of the source map spec this map is following.

  • sources: An array of URLs to the original source files.

  • names: An array of identifiers which can be referenced by individual mappings.

  • sourceRoot: Optional. The URL root from which all sources are relative.

  • sourcesContent: Optional. An array of contents of the original source files.

  • mappings: A string of base64 VLQs which contain the actual mappings.

  • file: Optional. The generated filename this source map is associated with.

var consumer = new sourceMap.SourceMapConsumer(rawSourceMapJsonData);

SourceMapConsumer.prototype.computeColumnSpans()

Compute the last column for each generated mapping. The last column is inclusive.

// Before:
consumer.allGeneratedPositionsFor({ line: 2, source: "foo.coffee" })
// [ { line: 2,
//     column: 1 },
//   { line: 2,
//     column: 10 },
//   { line: 2,
//     column: 20 } ]

consumer.computeColumnSpans();

// After:
consumer.allGeneratedPositionsFor({ line: 2, source: "foo.coffee" })
// [ { line: 2,
//     column: 1,
//     lastColumn: 9 },
//   { line: 2,
//     column: 10,
//     lastColumn: 19 },
//   { line: 2,
//     column: 20,
//     lastColumn: Infinity } ]

SourceMapConsumer.prototype.originalPositionFor(generatedPosition)

Returns the original source, line, and column information for the generated source's line and column positions provided. The only argument is an object with the following properties:

  • line: The line number in the generated source. Line numbers in this library are 1-based (note that the underlying source map specification uses 0-based line numbers -- this library handles the translation).

  • column: The column number in the generated source. Column numbers in this library are 0-based.

  • bias: Either SourceMapConsumer.GREATEST_LOWER_BOUND or SourceMapConsumer.LEAST_UPPER_BOUND. Specifies whether to return the closest element that is smaller than or greater than the one we are searching for, respectively, if the exact element cannot be found. Defaults to SourceMapConsumer.GREATEST_LOWER_BOUND.

and an object is returned with the following properties:

  • source: The original source file, or null if this information is not available.

  • line: The line number in the original source, or null if this information is not available. The line number is 1-based.

  • column: The column number in the original source, or null if this information is not available. The column number is 0-based.

  • name: The original identifier, or null if this information is not available.

consumer.originalPositionFor({ line: 2, column: 10 })
// { source: 'foo.coffee',
//   line: 2,
//   column: 2,
//   name: null }

consumer.originalPositionFor({ line: 99999999999999999, column: 999999999999999 })
// { source: null,
//   line: null,
//   column: null,
//   name: null }

SourceMapConsumer.prototype.generatedPositionFor(originalPosition)

Returns the generated line and column information for the original source, line, and column positions provided. The only argument is an object with the following properties:

  • source: The filename of the original source.

  • line: The line number in the original source. The line number is 1-based.

  • column: The column number in the original source. The column number is 0-based.

and an object is returned with the following properties:

  • line: The line number in the generated source, or null. The line number is 1-based.

  • column: The column number in the generated source, or null. The column number is 0-based.

consumer.generatedPositionFor({ source: "example.js", line: 2, column: 10 })
// { line: 1,
//   column: 56 }

SourceMapConsumer.prototype.allGeneratedPositionsFor(originalPosition)

Returns all generated line and column information for the original source, line, and column provided. If no column is provided, returns all mappings corresponding to a either the line we are searching for or the next closest line that has any mappings. Otherwise, returns all mappings corresponding to the given line and either the column we are searching for or the next closest column that has any offsets.

The only argument is an object with the following properties:

  • source: The filename of the original source.

  • line: The line number in the original source. The line number is 1-based.

  • column: Optional. The column number in the original source. The column number is 0-based.

and an array of objects is returned, each with the following properties:

  • line: The line number in the generated source, or null. The line number is 1-based.

  • column: The column number in the generated source, or null. The column number is 0-based.

consumer.allGeneratedpositionsfor({ line: 2, source: "foo.coffee" })
// [ { line: 2,
//     column: 1 },
//   { line: 2,
//     column: 10 },
//   { line: 2,
//     column: 20 } ]

SourceMapConsumer.prototype.hasContentsOfAllSources()

Return true if we have the embedded source content for every source listed in the source map, false otherwise.

In other words, if this method returns true, then consumer.sourceContentFor(s) will succeed for every source s in consumer.sources.

// ...
if (consumer.hasContentsOfAllSources()) {
  consumerReadyCallback(consumer);
} else {
  fetchSources(consumer, consumerReadyCallback);
}
// ...

SourceMapConsumer.prototype.sourceContentFor(source[, returnNullOnMissing])

Returns the original source content for the source provided. The only argument is the URL of the original source file.

If the source content for the given source is not found, then an error is thrown. Optionally, pass true as the second param to have null returned instead.

consumer.sources
// [ "my-cool-lib.clj" ]

consumer.sourceContentFor("my-cool-lib.clj")
// "..."

consumer.sourceContentFor("this is not in the source map");
// Error: "this is not in the source map" is not in the source map

consumer.sourceContentFor("this is not in the source map", true);
// null

SourceMapConsumer.prototype.eachMapping(callback, context, order)

Iterate over each mapping between an original source/line/column and a generated line/column in this source map.

  • callback: The function that is called with each mapping. Mappings have the form { source, generatedLine, generatedColumn, originalLine, originalColumn, name }

  • context: Optional. If specified, this object will be the value of this every time that callback is called.

  • order: Either SourceMapConsumer.GENERATED_ORDER or SourceMapConsumer.ORIGINAL_ORDER. Specifies whether you want to iterate over the mappings sorted by the generated file's line/column order or the original's source/line/column order, respectively. Defaults to SourceMapConsumer.GENERATED_ORDER.

consumer.eachMapping(function (m) { console.log(m); })
// ...
// { source: 'illmatic.js',
//   generatedLine: 1,
//   generatedColumn: 0,
//   originalLine: 1,
//   originalColumn: 0,
//   name: null }
// { source: 'illmatic.js',
//   generatedLine: 2,
//   generatedColumn: 0,
//   originalLine: 2,
//   originalColumn: 0,
//   name: null }
// ...

SourceMapGenerator

An instance of the SourceMapGenerator represents a source map which is being built incrementally.

new SourceMapGenerator([startOfSourceMap])

You may pass an object with the following properties:

  • file: The filename of the generated source that this source map is associated with.

  • sourceRoot: A root for all relative URLs in this source map.

  • skipValidation: Optional. When true, disables validation of mappings as they are added. This can improve performance but should be used with discretion, as a last resort. Even then, one should avoid using this flag when running tests, if possible.

  • ignoreInvalidMapping: Optional. When true, instead of throwing error on invalid mapping, it will be ignored.

var generator = new sourceMap.SourceMapGenerator({
  file: "my-generated-javascript-file.js",
  sourceRoot: "http://example.com/app/js/"
});

SourceMapGenerator.fromSourceMap(sourceMapConsumer, sourceMapGeneratorOptions)

Creates a new SourceMapGenerator from an existing SourceMapConsumer instance.

  • sourceMapConsumer The SourceMap.

  • sourceMapGeneratorOptions options that will be passed to the SourceMapGenerator constructor which used under the hood.

var generator = sourceMap.SourceMapGenerator.fromSourceMap(consumer, {
  ignoreInvalidMapping: true,
});

SourceMapGenerator.prototype.addMapping(mapping)

Add a single mapping from original source line and column to the generated source's line and column for this source map being created. The mapping object should have the following properties:

  • generated: An object with the generated line and column positions.

  • original: An object with the original line and column positions.

  • source: The original source file (relative to the sourceRoot).

  • name: An optional original token name for this mapping.

generator.addMapping({
  source: "module-one.scm",
  original: { line: 128, column: 0 },
  generated: { line: 3, column: 456 }
})

SourceMapGenerator.prototype.setSourceContent(sourceFile, sourceContent)

Set the source content for an original source file.

  • sourceFile the URL of the original source file.

  • sourceContent the content of the source file.

generator.setSourceContent("module-one.scm",
                           fs.readFileSync("path/to/module-one.scm"))

SourceMapGenerator.prototype.applySourceMap(sourceMapConsumer[, sourceFile[, sourceMapPath]])

Applies a SourceMap for a source file to the SourceMap. Each mapping to the supplied source file is rewritten using the supplied SourceMap. Note: The resolution for the resulting mappings is the minimum of this map and the supplied map.

  • sourceMapConsumer: The SourceMap to be applied.

  • sourceFile: Optional. The filename of the source file. If omitted, sourceMapConsumer.file will be used, if it exists. Otherwise an error will be thrown.

  • sourceMapPath: Optional. The dirname of the path to the SourceMap to be applied. If relative, it is relative to the SourceMap.

    This parameter is needed when the two SourceMaps aren't in the same directory, and the SourceMap to be applied contains relative source paths. If so, those relative source paths need to be rewritten relative to the SourceMap.

    If omitted, it is assumed that both SourceMaps are in the same directory, thus not needing any rewriting. (Supplying '.' has the same effect.)

SourceMapGenerator.prototype.toString()

Renders the source map being generated to a string.

generator.toString()
// '{"version":3,"sources":["module-one.scm"],"names":[],"mappings":"...snip...","file":"my-generated-javascript-file.js","sourceRoot":"http://example.com/app/js/"}'

SourceNode

SourceNodes provide a way to abstract over interpolating and/or concatenating snippets of generated JavaScript source code, while maintaining the line and column information associated between those snippets and the original source code. This is useful as the final intermediate representation a compiler might use before outputting the generated JS and source map.

new SourceNode([line, column, source[, chunk[, name]]])

  • line: The original line number associated with this source node, or null if it isn't associated with an original line. The line number is 1-based.

  • column: The original column number associated with this source node, or null if it isn't associated with an original column. The column number is 0-based.

  • source: The original source's filename; null if no filename is provided.

  • chunk: Optional. Is immediately passed to SourceNode.prototype.add, see below.

  • name: Optional. The original identifier.

var node = new SourceNode(1, 2, "a.cpp", [
  new SourceNode(3, 4, "b.cpp", "extern int status;\n"),
  new SourceNode(5, 6, "c.cpp", "std::string* make_string(size_t n);\n"),
  new SourceNode(7, 8, "d.cpp", "int main(int argc, char** argv) {}\n"),
]);

SourceNode.fromStringWithSourceMap(code, sourceMapConsumer[, relativePath])

Creates a SourceNode from generated code and a SourceMapConsumer.

  • code: The generated code

  • sourceMapConsumer The SourceMap for the generated code

  • relativePath The optional path that relative sources in sourceMapConsumer should be relative to.

var consumer = new SourceMapConsumer(fs.readFileSync("path/to/my-file.js.map", "utf8"));
var node = SourceNode.fromStringWithSourceMap(fs.readFileSync("path/to/my-file.js"),
                                              consumer);

SourceNode.prototype.add(chunk)

Add a chunk of generated JS to this source node.

  • chunk: A string snippet of generated JS code, another instance of SourceNode, or an array where each member is one of those things.
node.add(" + ");
node.add(otherNode);
node.add([leftHandOperandNode, " + ", rightHandOperandNode]);

SourceNode.prototype.prepend(chunk)

Prepend a chunk of generated JS to this source node.

  • chunk: A string snippet of generated JS code, another instance of SourceNode, or an array where each member is one of those things.
node.prepend("/** Build Id: f783haef86324gf **/\n\n");

SourceNode.prototype.setSourceContent(sourceFile, sourceContent)

Set the source content for a source file. This will be added to the SourceMap in the sourcesContent field.

  • sourceFile: The filename of the source file

  • sourceContent: The content of the source file

node.setSourceContent("module-one.scm",
                      fs.readFileSync("path/to/module-one.scm"))

SourceNode.prototype.walk(fn)

Walk over the tree of JS snippets in this node and its children. The walking function is called once for each snippet of JS and is passed that snippet and the its original associated source's line/column location.

  • fn: The traversal function.
var node = new SourceNode(1, 2, "a.js", [
  new SourceNode(3, 4, "b.js", "uno"),
  "dos",
  [
    "tres",
    new SourceNode(5, 6, "c.js", "quatro")
  ]
]);

node.walk(function (code, loc) { console.log("WALK:", code, loc); })
// WALK: uno { source: 'b.js', line: 3, column: 4, name: null }
// WALK: dos { source: 'a.js', line: 1, column: 2, name: null }
// WALK: tres { source: 'a.js', line: 1, column: 2, name: null }
// WALK: quatro { source: 'c.js', line: 5, column: 6, name: null }

SourceNode.prototype.walkSourceContents(fn)

Walk over the tree of SourceNodes. The walking function is called for each source file content and is passed the filename and source content.

  • fn: The traversal function.
var a = new SourceNode(1, 2, "a.js", "generated from a");
a.setSourceContent("a.js", "original a");
var b = new SourceNode(1, 2, "b.js", "generated from b");
b.setSourceContent("b.js", "original b");
var c = new SourceNode(1, 2, "c.js", "generated from c");
c.setSourceContent("c.js", "original c");

var node = new SourceNode(null, null, null, [a, b, c]);
node.walkSourceContents(function (source, contents) { console.log("WALK:", source, ":", contents); })
// WALK: a.js : original a
// WALK: b.js : original b
// WALK: c.js : original c

SourceNode.prototype.join(sep)

Like Array.prototype.join except for SourceNodes. Inserts the separator between each of this source node's children.

  • sep: The separator.
var lhs = new SourceNode(1, 2, "a.rs", "my_copy");
var operand = new SourceNode(3, 4, "a.rs", "=");
var rhs = new SourceNode(5, 6, "a.rs", "orig.clone()");

var node = new SourceNode(null, null, null, [ lhs, operand, rhs ]);
var joinedNode = node.join(" ");

SourceNode.prototype.replaceRight(pattern, replacement)

Call String.prototype.replace on the very right-most source snippet. Useful for trimming white space from the end of a source node, etc.

  • pattern: The pattern to replace.

  • replacement: The thing to replace the pattern with.

// Trim trailing white space.
node.replaceRight(/\s*$/, "");

SourceNode.prototype.toString()

Return the string representation of this source node. Walks over the tree and concatenates all the various snippets together to one string.

var node = new SourceNode(1, 2, "a.js", [
  new SourceNode(3, 4, "b.js", "uno"),
  "dos",
  [
    "tres",
    new SourceNode(5, 6, "c.js", "quatro")
  ]
]);

node.toString()
// 'unodostresquatro'

SourceNode.prototype.toStringWithSourceMap([startOfSourceMap])

Returns the string representation of this tree of source nodes, plus a SourceMapGenerator which contains all the mappings between the generated and original sources.

The arguments are the same as those to new SourceMapGenerator.

var node = new SourceNode(1, 2, "a.js", [
  new SourceNode(3, 4, "b.js", "uno"),
  "dos",
  [
    "tres",
    new SourceNode(5, 6, "c.js", "quatro")
  ]
]);

node.toStringWithSourceMap({ file: "my-output-file.js" })
// { code: 'unodostresquatro',
//   map: [object SourceMapGenerator] }