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‎.github/workflows/link-check.yml‎

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name: Markdown Link Validator
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on:
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pull_request:
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push:
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branches: [ main, master ]
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jobs:
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linkChecker:
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runs-on: ubuntu-latest
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permissions:
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contents: read
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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fetch-depth: 1
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- name: Check links with lychee
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# See https://github.com/lycheeverse/lychee-action
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uses: lycheeverse/lychee-action@v2
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with:
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# Check all markdown and reStructuredText files
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args: >-
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--verbose
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--no-progress
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--max-concurrency 12
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--max-retries 3
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--retry-wait-time 4
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--accept 200,206,403,429
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--exclude-path "docs/get_started/legacy_licenses/gpl-3.0.rst"
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"**/*.md" "**/*.rst"
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# Fail the build on any broken link
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fail: true
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env:
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# Exclude localhost and badges
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LY_CHEE_EXCLUDE: "http://localhost,https://localhost,https://127.0.0.1,https://img.shields.io"

‎docs/README.md‎

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# k-Wave-python
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# k-wave-python
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[![Support](https://dcbadge.vercel.app/api/server/Yq5Qj6D9vN?style=flat)](https://discord.gg/Yq5Qj6D9vN)
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[![Support](https://img.shields.io/discord/1234942672418897960?style=flat&logo=discord)](https://discord.gg/your-invite-code)
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[![Documentation Status](https://readthedocs.org/projects/k-wave-python/badge/?version=latest)](https://k-wave-python.readthedocs.io/en/latest/?badge=latest)
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[![codecov](https://codecov.io/gh/waltsims/k-wave-python/graph/badge.svg?token=6ofwtPiDNG)](https://codecov.io/gh/waltsims/k-wave-python)
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[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/waltsims/k-wave-python/master)
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![](_static/example_bmode.png)
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A large [collection of examples](../examples/) exists to get started with k-wave-python. All examples can be run in Google Colab notebooks with a few clicks. One can begin with e.g. the [B-mode reconstruction example notebook](https://colab.research.google.com/github/waltsims/k-wave-python/blob/master/examples/us_bmode_linear_transducer/us_bmode_linear_transducer.ipynb).
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A large [collection of examples](../examples/) exists to get started with k-wave-python. All examples can be run in Google Colab notebooks with a few clicks. One can begin with e.g. the [B-mode reconstruction example notebook](https://colab.research.google.com/github/waltsims/k-wave-python/blob/HEAD/examples/us_bmode_linear_transducer/us_bmode_linear_transducer.ipynb).
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This example file steps through the process of:
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1. Generating a simulation medium

‎docs/conf.py‎

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"sphinx.ext.napoleon",
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"sphinx.ext.viewcode",
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"sphinx_mdinclude",
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"sphinx.ext.extlinks", # Enables :ghfile: external links
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]
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# Provide a simple GitHub branch/sha fallback for linking to example files.
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# Priority: explicit override via _GITHUB_BRANCH →
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# READTHEDOCS_GIT_IDENTIFIER (commit) →
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# READTHEDOCS_GIT_BRANCH / GITHUB_REF_NAME →
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# "master".
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import os
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def _detect_current_branch() -> str:
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"""Return a branch/commit identifier for GitHub links with minimal logic.
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Order: _GITHUB_BRANCH override → READTHEDOCS_GIT_IDENTIFIER (commit) →
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READTHEDOCS_GIT_BRANCH / GITHUB_REF_NAME → "master".
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"""
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return (
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os.getenv("_GITHUB_BRANCH")
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or os.getenv("READTHEDOCS_GIT_IDENTIFIER")
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or os.getenv("READTHEDOCS_GIT_BRANCH")
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or os.getenv("GITHUB_REF_NAME")
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or "master"
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)
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_GITHUB_BRANCH = _detect_current_branch()
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# Define an extlink so we can write :ghfile:`examples/foo.py` in .rst/.md
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extlinks = {
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"ghfile": (
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f"https://github.com/waltsims/k-wave-python/blob/{_GITHUB_BRANCH}/%s",
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"%s", # pass-through caption
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),
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"ghdir": (
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f"https://github.com/waltsims/k-wave-python/tree/{_GITHUB_BRANCH}/%s",
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"%s",
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),
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}
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source_suffix = [".rst", ".md"]
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templates_path = ["_templates"]
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exclude_patterns = ["README.md", "_build", "Thumbs.db", ".DS_Store"]
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html_theme = "furo"
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html_theme_options = {
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"source_repository": "https://github.com/waltsims/k-wave-python",
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"source_branch": "master",
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"source_branch": _GITHUB_BRANCH,
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"source_directory": "docs/",
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}
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html_static_path = ["_static"]
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# -- Options for todo extension ----------------------------------------------

‎docs/examples_guide.rst‎

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Examples: k-Wave-Python Step-by-Step
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=======================
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The k-Wave Python examples are organized to help you progress from basic wave physics to advanced applications. Each example demonstrates the four-component framework (Grid, Medium, Source, Sensor) with increasing complexity.
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Start with the :doc:`get_started/first_simulation` tutorial, then follow this suggested learning path:
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Basic Wave Propagation (IVP - Initial Value Problems)
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-----------------------------------------------------
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**Start Here**: Learn fundamental wave physics using initial pressure distributions (the simplest source type).
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Core Concept
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- Topics
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* - :ghdir:`examples/ivp_photoacoustic_waveforms/`
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- 2D vs 3D wave propagation physics
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- **IVP** • Wave spreading • Compact support
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Simple Transducers & Sources
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-----------------------------
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**Next Step**: Introduction to time-varying sources and practical transducer modeling.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Core Concept
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- Topics
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* - :ghdir:`examples/us_defining_transducer/`
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- Basic ultrasound transducer setup
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- **US** • Transducer basics • Time-varying sources
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* - :ghdir:`examples/at_circular_piston_3D/`
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- Simple focused geometry
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- **AT** • 3D focusing • Geometric sources
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* - :ghdir:`examples/at_circular_piston_AS/`
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- Computational efficiency with symmetry
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- **AT** • Axisymmetric • Computational optimization
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Medical Imaging Applications
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----------------------------
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**Practical Applications**: See how basic concepts combine into real-world medical imaging systems.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Application
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- Topics
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* - :ghdir:`examples/us_beam_patterns/`
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- Understanding acoustic beam formation
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- **US** • Beam focusing • Field patterns
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* - :ghdir:`examples/us_bmode_linear_transducer/`
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- Complete ultrasound imaging pipeline
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- **US** • Medical imaging • Signal processing
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* - :ghdir:`examples/pr_2D_FFT_line_sensor/`
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- Photoacoustic image reconstruction
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- **PR** • Image reconstruction • FFT methods
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* - :ghdir:`examples/pr_2D_TR_line_sensor/`
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- Alternative reconstruction approach
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- **PR** • Time reversal • Reconstruction
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Advanced Transducer Modeling (AT - Array Transducers)
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-----------------------------------------------------
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**Complex Geometries**: Learn sophisticated techniques for modeling complex transducer arrays using Cartesian space methods.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Advanced Technique
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- Topics
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* - :ghdir:`examples/at_array_as_source/`
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- kWaveArray for complex geometries
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- **AT** • Array modeling • Anti-aliasing
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* - :ghdir:`examples/at_array_as_sensor/`
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- Complex sensor array geometries
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- **AT** • Sensor arrays • Flexible positioning
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* - :ghdir:`examples/at_linear_array_transducer/`
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- Multi-element linear arrays
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- **AT** • Linear arrays • Element spacing
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* - :ghdir:`examples/at_focused_bowl_3D/`
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- 3D focused ultrasound therapy
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- **AT** • Therapeutic US • 3D focusing
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* - :ghdir:`examples/at_focused_annular_array_3D/`
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- Multi-element focused systems
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- **AT** • Annular arrays • Complex focusing
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Advanced Imaging & Reconstruction (PR - Pressure/Photoacoustic Reconstruction)
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-------------------------------------------------------------------------------
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**3D Reconstruction**: Advanced reconstruction techniques for photoacoustic and pressure field imaging.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Reconstruction Method
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- Topics
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* - :ghdir:`examples/pr_3D_FFT_planar_sensor/`
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- 3D FFT-based reconstruction
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- **PR** • 3D imaging • Planar arrays
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* - :ghdir:`examples/pr_3D_TR_planar_sensor/`
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- 3D time reversal reconstruction
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- **PR** • 3D time reversal • Volumetric imaging
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* - :ghdir:`examples/us_bmode_phased_array/`
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- Advanced ultrasound beamforming
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- **US** • Phased arrays • Electronic steering
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Sensor Physics & Directivity (SD - Sensor Directivity)
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------------------------------------------------------
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**Sensor Modeling**: Understanding how sensor size, shape, and directivity affect measurements.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Physics Concept
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- Topics
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* - :ghdir:`examples/sd_directivity_modelling_2D/`
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- How sensor size affects measurements
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- **SD** • Directivity • Finite sensor size
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* - :ghdir:`examples/sd_focussed_detector_2D/`
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- Directional sensor sensitivity
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- **SD** • Focused detection • Sensor design
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* - :ghdir:`examples/sd_focussed_detector_3D/`
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- 3D focused sensor modeling
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- **SD** • 3D detection • Sensor focusing
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Computational Optimization (NA - Numerical Analysis)
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----------------------------------------------------
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**Advanced Numerics**: Optimize simulations and understand computational aspects.
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.. list-table::
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:header-rows: 1
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:widths: 40 40 20
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* - Example
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- Optimization Topic
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- Topics
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* - :ghdir:`examples/na_controlling_the_pml/`
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- Boundary conditions and efficiency
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- **NA** • PML boundaries • Computational domains
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Understanding the Prefixes
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--------------------------
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- **IVP** = Initial Value Problems (wave propagation from initial pressure)
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- **US** = Ultrasound (medical and therapeutic ultrasound applications)
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- **AT** = Array Transducers (complex geometries using Cartesian space methods)
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- **PR** = Pressure/Photoacoustic Reconstruction (image reconstruction techniques)
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- **SD** = Sensor Directivity (sensor physics and measurement effects)
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- **NA** = Numerical Analysis (computational optimization and methods)
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Learning Strategy
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-----------------
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1. **Start with IVP**: Understand basic wave physics
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2. **Move to simple US/AT**: Learn transducer basics
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3. **Apply to imaging**: See concepts in real applications (US, PR)
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4. **Master advanced AT**: Handle complex geometries
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5. **Understand sensors**: Learn about measurement physics (SD)
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6. **Optimize**: Improve computational efficiency (NA)
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Each example builds on the four-component framework, but with increasing sophistication in how the components are configured and used.

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