diff --git a/.github/workflows/url_check.yml b/.github/workflows/url_check.yml new file mode 100644 index 000000000..41ee62012 --- /dev/null +++ b/.github/workflows/url_check.yml @@ -0,0 +1,23 @@ +name: URL Check + +on: + push: + branches: [main] + pull_request: + +jobs: + url_check: + runs-on: ubuntu-latest + steps: + - name: Checkout repo + uses: actions/checkout@v4 + with: + path: repo + - name: Checkout PyAutoBuild + uses: actions/checkout@v4 + with: + repository: PyAutoLabs/PyAutoBuild + ref: main + path: PyAutoBuild + - name: Run url_check.sh + run: bash PyAutoBuild/autobuild/url_check.sh repo diff --git a/README.rst b/README.rst index 349a72395..2b1b8a40d 100644 --- a/README.rst +++ b/README.rst @@ -1,8 +1,8 @@ PyAutoGalaxy: Open-Source Multi Wavelength Galaxy Structure & Morphology ======================================================================== -.. image:: https://mybinder.org/badge_logo.svg - :target: https://mybinder.org/v2/gh/Jammy2211/autogalaxy_workspace/HEAD +.. image:: https://colab.research.google.com/assets/colab-badge.svg + :target: https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.4.13.6/start_here.ipynb .. image:: https://readthedocs.org/projects/pyautogalaxy/badge/?version=latest :target: https://pyautogalaxy.readthedocs.io/en/latest/?badge=latest @@ -34,7 +34,7 @@ PyAutoGalaxy: Open-Source Multi Wavelength Galaxy Structure & Morphology `Installation Guide `_ | `readthedocs `_ | -`Introduction on Colab `_ +`Introduction on Colab `_ `HowToGalaxy `_ **PyAutoGalaxy** is software for analysing the morphologies and structures of galaxies: @@ -54,7 +54,7 @@ The following links are useful for new starters: - `The PyAutoGalaxy readthedocs `_, which includes `an overview of PyAutoGalaxy's core features `_, `a new user starting guide `_ and `an installation guide `_. -- `The introduction Jupyter Notebook on Google Colab `_, where you can try **PyAutoGalaxy** in a web browser (without installation). +- `The introduction Jupyter Notebook on Google Colab `_, where you can try **PyAutoGalaxy** in a web browser (without installation). - `The autogalaxy_workspace GitHub repository `_, which includes example scripts and the `HowToGalaxy Jupyter notebook lectures `_ which give new users a step-by-step introduction to **PyAutoGalaxy**. diff --git a/docs/howtogalaxy/chapter_1_introduction.rst b/docs/howtogalaxy/chapter_1_introduction.rst index 538cd4da1..1d14fc6f7 100644 --- a/docs/howtogalaxy/chapter_1_introduction.rst +++ b/docs/howtogalaxy/chapter_1_introduction.rst @@ -3,24 +3,24 @@ Chapter 1: Galaxies In chapter 1, we introduce you to galaxy morphology, structure and the core **PyAutoGalaxy** API. -**Binder** links to every tutorial are included. +**Colab** links to every tutorial are included. The chapter contains the following tutorials: -`Tutorial 0: Visualization `_ +`Tutorial 0: Visualization `_ - Setting up **PyAutoGalaxy**'s visualization library. -`Tutorial 1: Grids And Galaxies `_ +`Tutorial 1: Grids And Galaxies `_ - Using grids of (y,x) coordinates with galaxies made up of light profiles. -`Tutorial 2: Data `_ +`Tutorial 2: Data `_ - Simulating and inspecting telescope imaging data of a galaxy. -`Tutorial 3: Fitting `_ +`Tutorial 3: Fitting `_ - Fitting data with a galaxy model. -`Tutorial 4: Methods `_ +`Tutorial 4: Methods `_ - An overview of the different methods used to fit galaxies with. -`Tutorial 5: Summary `_ +`Tutorial 5: Summary `_ - A summary of the chapter. \ No newline at end of file diff --git a/docs/howtogalaxy/chapter_2_modeling.rst b/docs/howtogalaxy/chapter_2_modeling.rst index 67ee3985b..9cd970aa5 100644 --- a/docs/howtogalaxy/chapter_2_modeling.rst +++ b/docs/howtogalaxy/chapter_2_modeling.rst @@ -5,27 +5,27 @@ In chapter 2, we'll take you through how to model galaxies using a non-linear se The chapter contains the following tutorials: -`Tutorial 1: Non-linear Search `_ +`Tutorial 1: Non-linear Search `_ - How a non-linear search is used to fit a model and the concepts of a parameter space and priors. -`Tutorial 2: Practicalities `_ +`Tutorial 2: Practicalities `_ - Practicalities of performing model-fitting, like how to inspect the results on your hard-disk. -`Tutorial 3: Realism and Complexity `_ +`Tutorial 3: Realism and Complexity `_ - Finding a balance between realism and complexity when composing and fitting a model. -`Tutorial 4: Dealing with Failure `_ +`Tutorial 4: Dealing with Failure `_ - What to do when PyAutoGalaxy finds an inaccurate model. -`Tutorial 5: Linear Profiles `_ +`Tutorial 5: Linear Profiles `_ - Light profiles which capture complex morphologies in a reduced number of non-linear parameters. -`Tutorial 6: Masking `_ +`Tutorial 6: Masking `_ - How to mask your data to improve the model. -`Tutorial 7: Results `_ +`Tutorial 7: Results `_ - Overview of the results available after successfully fitting a model. -`Tutorial 8: Need for Speed `_ +`Tutorial 8: Need for Speed `_ - How to fit complex models whilst balancing efficiency and run-time. diff --git a/docs/howtogalaxy/chapter_3_search_chaining.rst b/docs/howtogalaxy/chapter_3_search_chaining.rst index 7ace92401..03e38a775 100644 --- a/docs/howtogalaxy/chapter_3_search_chaining.rst +++ b/docs/howtogalaxy/chapter_3_search_chaining.rst @@ -6,11 +6,11 @@ robust modeling of large galaxy samples. The chapter contains the following tutorials: -`Tutorial 1: Search Chaining `_ +`Tutorial 1: Search Chaining `_ - Breaking the modeling procedure into a chained sequence of model-fits. -`Tutorial 2: Prior Passing `_ +`Tutorial 2: Prior Passing `_ - How the results of earlier searches are passed to later searches. -`Tutorial 3: x2 Galaxies `_ +`Tutorial 3: x2 Galaxies `_ - Modeling a dataset with two galaxies using chained searches. \ No newline at end of file diff --git a/docs/howtogalaxy/chapter_4_pixelizations.rst b/docs/howtogalaxy/chapter_4_pixelizations.rst index 6eecbcf56..506576cdb 100644 --- a/docs/howtogalaxy/chapter_4_pixelizations.rst +++ b/docs/howtogalaxy/chapter_4_pixelizations.rst @@ -5,17 +5,17 @@ In chapter 4, we use **Pixelizations** to reconstruct complex galaxies on pixeli The chapter contains the following tutorials: -`Tutorial 1: Pixelizations `_ +`Tutorial 1: Pixelizations `_ - Creating a pixel-grid which will reconstruct a galaxy's light. -`Tutorial 2: Mappers `_ +`Tutorial 2: Mappers `_ - How a pixelization maps between the data and pixelization. -`Tutorial 3: Inversions `_ +`Tutorial 3: Inversions `_ - Inverting the mappings to reconstruct the galaxy's light. -`Tutorial 4: Bayesian Regularization `_ +`Tutorial 4: Bayesian Regularization `_ - Smoothing the source within a Bayesian framework. -`Tutorial 6: Model Fit `_ +`Tutorial 6: Model Fit `_ - An example modeling pipeline which uses an inversion. \ No newline at end of file diff --git a/docs/howtogalaxy/chapter_optional.rst b/docs/howtogalaxy/chapter_optional.rst index 25d2bf600..ef337dfb2 100644 --- a/docs/howtogalaxy/chapter_optional.rst +++ b/docs/howtogalaxy/chapter_optional.rst @@ -5,12 +5,12 @@ This chapter contains optional tutorials expanding on different aspects of how * The chapter contains the following tutorials: -`Tutorial: Mass Profiles `_ +`Tutorial: Mass Profiles `_ - A description of mass profiles implemented in PyAutoGalaxy, which are currently only used by its child project PyAutoLens. -`Tutorial: Sub-grids `_ +`Tutorial: Sub-grids `_ - Use sub-grids to perform more accurate and precise calculations. -`Tutorial: Searches `_ +`Tutorial: Searches `_ - Alternative non-linear searches to sample parameter space. diff --git a/docs/index.rst b/docs/index.rst index 8d1f00357..6266e0d38 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -21,7 +21,7 @@ The following links are useful for new starters: - `The PyAutoGalaxy readthedocs `_, which includes `an overview of PyAutoGalaxy's core features `_, `a new user starting guide `_ and `an installation guide `_. -- `The introduction Jupyter Notebook on Binder `_, where you can try **PyAutoGalaxy** in a web browser (without installation). +- `The introduction Jupyter Notebook on Colab `_, where you can try **PyAutoGalaxy** in a web browser (without installation). - `The autogalaxy_workspace GitHub repository `_, which includes example scripts and the `HowToGalaxy Jupyter notebook lectures `_ which give new users a step-by-step introduction to **PyAutoGalaxy**. diff --git a/docs/overview/overview_2_new_user_guide.rst b/docs/overview/overview_2_new_user_guide.rst index 076ab189b..eb7f88c26 100644 --- a/docs/overview/overview_2_new_user_guide.rst +++ b/docs/overview/overview_2_new_user_guide.rst @@ -29,13 +29,13 @@ environment with all the required dependencies already installed. This is a great way to get started quickly without needing to install **PyAutoGalaxy** on your own machine, so you can check it is the right software for you before going through the installation process: -- `imaging/start_here.ipynb `_: +- `imaging/start_here.ipynb `_: Galaxy modeling with CCD imaging (e.g. Hubble, James Webb, ground-based telescopes). -- `interferometer/start_here.ipynb `_: +- `interferometer/start_here.ipynb `_: Galaxy modeling with interferometer data (e.g. ALMA), fitting directly in the uv-plane. -- `multi_band/start_here.ipynb `_: +- `multi_band/start_here.ipynb `_: Multi-band galaxy modeling to study colour gradients and wavelength-dependent structure. Still Unsure? diff --git a/paper/paper.md b/paper/paper.md index 011da2511..95d45eaba 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -75,7 +75,7 @@ massively parallel model-fitting and an SQLite3 database that allows large suite queried and analysed. Accompanying `PyAutoGalaxy` is the [autogalaxy workspace](https://github.com/Jammy2211/autogalaxy_workspace), which includes example scripts, datasets and the `HowToGalaxy` lectures in Jupyter notebook format which introduce non-experts to studies of galaxy morphology using `PyAutoGalaxy`. Readers can try `PyAutoGalaxy` right now by going -to [the introduction Jupyter notebook on Binder](https://mybinder.org/v2/gh/Jammy2211/autogalaxy_workspace/release) or +to [the introduction Jupyter notebook on Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.4.13.6/start_here.ipynb) or checkout the [readthedocs](https://pyautogalaxy.readthedocs.io/en/latest/) for a complete overview of `PyAutoGalaxy`'s features. @@ -156,7 +156,7 @@ contains example scripts for modeling and simulating galaxies and tutorials on h interferometer datasets before a `PyAutoGalaxy` analysis. Also included are the `HowToGalaxy` tutorials, a four-chapter lecture series composed of over 20 Jupyter notebooks aimed at non-experts, introducing them to galaxy morphology analysis, Bayesian inference and teaching them how to use `PyAutoGalaxy` for scientific study. The lectures -are available on [Binder](https://mybinder.org/v2/gh/Jammy2211/autogalaxy_workspace/HEAD) and may therefore be +are available on [Colab](https://colab.research.google.com/github/PyAutoLabs/autogalaxy_workspace/blob/2026.4.13.6/start_here.ipynb) and may therefore be taken without a local `PyAutoGalaxy` installation. # Software Citations