diff --git a/CITATIONS.md b/CITATIONS.md index 5124098cf..0e2d5a32d 100644 --- a/CITATIONS.md +++ b/CITATIONS.md @@ -1,9 +1,9 @@ # Citations & References The bibtex entries for **PyAutoLens** and its affiliated software packages can be found -[here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.bib), with example text for citing **PyAutoLens** -in [.tex format here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.tex) format here and -[.md format here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.md). As shown in the examples, we +[here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.bib), with example text for citing **PyAutoLens** +in [.tex format here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.tex) format here and +[.md format here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.md). As shown in the examples, we would greatly appreciate it if you mention **PyAutoLens** by name and include a link to our GitHub page! **PyAutoLens** is published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.02825#) and its diff --git a/CODE_OF_CONDUCT.md b/CODE_OF_CONDUCT.md index 6a6b80836..077ffad8d 100644 --- a/CODE_OF_CONDUCT.md +++ b/CODE_OF_CONDUCT.md @@ -301,7 +301,7 @@ the situation is not yet resolved. ## License -This code of conduct has been adapted from [*NUMFOCUS code of conduct*](https://github.com/numfocus/numfocus/blob/main/manual/numfocus-coc.md#the-short-version), -which is adapted from numerous sources, including the [*Geek Feminism wiki, created by the Ada Initiative and other volunteers, which is under a Creative Commons Zero license*](http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Policy), the [*Contributor Covenant version 1.2.0*](http://contributor-covenant.org/version/1/2/0/), the [*Bokeh Code of Conduct*](https://github.com/bokeh/bokeh/blob/main/CODE_OF_CONDUCT.md), the [*SciPy Code of Conduct*](https://github.com/jupyter/governance/blob/main/conduct/enforcement.md), the [*Carpentries Code of Conduct*](https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html#enforcement-manual), and the [*NeurIPS Code of Conduct*](https://neurips.cc/public/CodeOfConduct). +This code of conduct has been adapted from [*NUMFOCUS code of conduct*](https://numfocus.org/code-of-conduct), +which is adapted from numerous sources, including the [*Geek Feminism wiki, created by the Ada Initiative and other volunteers, which is under a Creative Commons Zero license*](http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Policy), the [*Contributor Covenant version 1.2.0*](http://contributor-covenant.org/version/1/2/0/), the [*Bokeh Code of Conduct*](https://github.com/bokeh/bokeh/blob/main/docs/CODE_OF_CONDUCT.md), the [*SciPy Code of Conduct*](https://github.com/jupyter/governance/blob/main/conduct/enforcement.md), the [*Carpentries Code of Conduct*](https://docs.carpentries.org/topic_folders/policies/code-of-conduct.html#enforcement-manual), and the [*NeurIPS Code of Conduct*](https://neurips.cc/public/CodeOfConduct). **PyAutoLens Code of Conduct is licensed under the [Creative Commons Attribution 3.0 Unported License](https://creativecommons.org/licenses/by/3.0/).** \ No newline at end of file diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md index a331c2a3b..1540e2bb9 100644 --- a/CONTRIBUTING.md +++ b/CONTRIBUTING.md @@ -74,7 +74,7 @@ Contributions are welcome and greatly appreciated! ### Report Bugs -Report bugs at https://github.com/Jammy2211/PyAutoLens/issues +Report bugs at https://github.com/PyAutoLabs/PyAutoLens/issues If you are playing with the PyAutoLens library and find a bug, please reporting it including: @@ -86,7 +86,7 @@ reporting it including: ### Propose New Features The best way to send feedback is to open an issue at -https://github.com/Jammy2211/PyAutoLens +https://github.com/PyAutoLabs/PyAutoLens with tag *enhancement*. If you are proposing a nnew feature: diff --git a/README.md b/README.md index 5718624f0..87ac7789f 100644 --- a/README.md +++ b/README.md @@ -1,8 +1,8 @@ # PyAutoLens-JAX: Open-Source Strong Lensing -[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/start_here.ipynb) +[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/notebooks/imaging/start_here.ipynb) [![Documentation Status](https://readthedocs.org/projects/pyautolens/badge/?version=latest)](https://pyautolens.readthedocs.io/en/latest/?badge=latest) -[![Tests](https://github.com/Jammy2211/PyAutoLens/actions/workflows/main.yml/badge.svg)](https://github.com/Jammy2211/PyAutoLens/actions) +[![Tests](https://github.com/PyAutoLabs/PyAutoLens/actions/workflows/main.yml/badge.svg)](https://github.com/PyAutoLabs/PyAutoLens/actions) [![Build](https://github.com/Jammy2211/PyAutoBuild/actions/workflows/release.yml/badge.svg)](https://github.com/Jammy2211/PyAutoBuild/actions) [![Code Style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black) [![JOSS](https://joss.theoj.org/papers/10.21105/joss.02825/status.svg)](https://doi.org/10.21105/joss.02825) @@ -14,7 +14,7 @@ [Installation Guide](https://pyautolens.readthedocs.io/en/latest/installation/overview.html) | [readthedocs](https://pyautolens.readthedocs.io/en/latest/index.html) | -[Introduction on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/start_here.ipynb) | +[Introduction on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/notebooks/imaging/start_here.ipynb) | [HowToLens](https://pyautolens.readthedocs.io/en/latest/howtolens/howtolens.html) @@ -28,7 +28,7 @@ This is called strong gravitational lensing and **PyAutoLens** makes it **simple The following links are useful for new starters: - [The PyAutoLens readthedocs](https://pyautolens.readthedocs.io/en/latest): which includes [an overview of PyAutoLens's core features](https://pyautolens.readthedocs.io/en/latest/overview/overview_1_start_here.html), [a new user starting guide](https://pyautolens.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html) and [an installation guide](https://pyautolens.readthedocs.io/en/latest/installation/overview.html). -- [The introduction Jupyter Notebook on Google Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/start_here.ipynb): try **PyAutoLens** in a web browser (without installation). +- [The introduction Jupyter Notebook on Google Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/notebooks/imaging/start_here.ipynb): try **PyAutoLens** in a web browser (without installation). - [The autolens_workspace GitHub repository](https://github.com/PyAutoLabs/autolens_workspace): example scripts covering every **PyAutoLens** use case. - [The HowToLens GitHub repository](https://github.com/PyAutoLabs/HowToLens): a Jupyter notebook lecture series teaching strong lensing and lens modeling from the ground up. @@ -39,7 +39,7 @@ gravitational lensing analysis, and helps troubleshoot problems. Slack is invitation-only. If you'd like to join, please send an email requesting an invite. -For installation issues, bug reports, or feature requests, please raise an issue on the [GitHub issues page](https://github.com/Jammy2211/PyAutoLens/issues). +For installation issues, bug reports, or feature requests, please raise an issue on the [GitHub issues page](https://github.com/PyAutoLabs/PyAutoLens/issues). ## HowToLens @@ -51,10 +51,10 @@ A complete overview of the lectures [is provided on the HowToLens readthedocs pa ## Citations -Information on how to cite **PyAutoLens** in publications can be found [on the citations page](https://github.com/Jammy2211/PyAutoLens/blob/main/CITATIONS.md). +Information on how to cite **PyAutoLens** in publications can be found [on the citations page](https://github.com/PyAutoLabs/PyAutoLens/blob/main/CITATIONS.md). ## Contributing -Information on how to contribute to **PyAutoLens** can be found [on the contributing page](https://github.com/Jammy2211/PyAutoLens/blob/main/CONTRIBUTING.md). +Information on how to contribute to **PyAutoLens** can be found [on the contributing page](https://github.com/PyAutoLabs/PyAutoLens/blob/main/CONTRIBUTING.md). Hands on support for contributions is available via our Slack workspace, again please email to request an invite. diff --git a/docs/api/plot.rst b/docs/api/plot.rst index 4f4b2c759..5de714fd3 100644 --- a/docs/api/plot.rst +++ b/docs/api/plot.rst @@ -5,12 +5,12 @@ Plotting **PyAutoLens** custom visualization library. Step-by-step Juypter notebook guides illustrating all objects listed on this page are -provided on the `autolens_workspace: plot tutorials `_ and +provided on the `autolens_workspace: plot tutorials `_ and it is strongly recommended you use those to learn plot customization. **Examples / Tutorials:** -- `autolens_workspace: plot tutorials `_ +- `autolens_workspace: plot tutorials `_ Plotters [aplt] --------------- diff --git a/docs/conf.py b/docs/conf.py index bf2a48f6c..d6b4dd528 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -4,7 +4,7 @@ # # This file only contains a selection of the most common options. For a full # list see the documentation: -# https://www.sphinx-doc.org/en/main/usage/configuration.html +# https://www.sphinx-doc.org/en/master/usage/configuration.html # -- Path setup -------------------------------------------------------------- @@ -65,7 +65,7 @@ intersphinx_mapping = { "python": ("https://docs.python.org/3", None), - "sphinx": ("https://www.sphinx-doc.org/en/main", None), + "sphinx": ("https://www.sphinx-doc.org/en/master", None), } # -- Options for TODOs ------------------------------------------------------- diff --git a/docs/general/citations.md b/docs/general/citations.md index 615756e06..7390b3074 100644 --- a/docs/general/citations.md +++ b/docs/general/citations.md @@ -3,9 +3,9 @@ # Citations & References The bibtex entries for **PyAutoLens** and its affiliated software packages can be found -[here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.bib), with example text for citing **PyAutoLens** -in [.tex format here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.tex) format here and -[.md format here](https://github.com/Jammy2211/PyAutoLens/blob/main/files/citations.md). As shown in the examples, we +[here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.bib), with example text for citing **PyAutoLens** +in [.tex format here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.tex) format here and +[.md format here](https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/citations.md). As shown in the examples, we would greatly appreciate it if you mention **PyAutoLens** by name and include a link to our GitHub page! **PyAutoLens** is published in the [Journal of Open Source Software](https://joss.theoj.org/papers/10.21105/joss.02825#) and its diff --git a/docs/general/configs.md b/docs/general/configs.md index 1bdbecf9c..2bb658ed3 100644 --- a/docs/general/configs.md +++ b/docs/general/configs.md @@ -4,7 +4,7 @@ visualization and other aspects of **PyAutoLens**. Descriptions of every configuration file and their input parameters are provided in the `README.md` in -the [config directory of the workspace](https://github.com/Jammy2211/autolens_workspace/tree/release/config) +the [config directory of the workspace](https://github.com/PyAutoLabs/autolens_workspace/tree/main/config) ## Setup diff --git a/docs/general/credits.md b/docs/general/credits.md index 474cbab1f..b86664ad0 100644 --- a/docs/general/credits.md +++ b/docs/general/credits.md @@ -6,7 +6,7 @@ [James Nightingale](https://github.com/Jammy2211): Lead developer & PyAutoLens guru. -[Richard Hayes](https://github.com/rhayes777): Lead developer & [PyAutoFit](https://github.com/rhayes777/PyAutoFit) guru. +[Richard Hayes](https://github.com/rhayes777): Lead developer & [PyAutoFit](https://github.com/PyAutoLabs/PyAutoFit) guru. [Aristeidis Amvrosiadis](https://github.com/Sketos): Interferometer Analysis. diff --git a/docs/general/demagnified_solutions.md b/docs/general/demagnified_solutions.md index edb83984e..7dae1802a 100644 --- a/docs/general/demagnified_solutions.md +++ b/docs/general/demagnified_solutions.md @@ -10,12 +10,12 @@ models to be estimated. This is due to demagnified source reconstructions, where the source is reconstructed as the lensed source galaxy (without any lensing): -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/general/images/data.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/general/images/data.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/general/images/model_image.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/general/images/model_image.png :alt: Alternative text :width: 400 ``` @@ -30,14 +30,14 @@ models with **too much mass**, such that the ray-tracing inverts in on itself. The following schematic is from the paper Maresca et al 2021 () and illustrates this beautifully: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/general/images/maresca_fig1.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/general/images/maresca_fig1.png :alt: Alternative text :width: 400 ``` The source reconstructions and model-fits of these solutions are also illustrated by Maresca et al 2021: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/general/images/maresca_fig2.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/general/images/maresca_fig2.png :alt: Alternative text :width: 400 ``` @@ -64,13 +64,13 @@ positions = al.Grid2DIrregular( Here is where the multiple images appear for an example strong lens, where multiple images are drawn on with black stars: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/general/images/lensed_source.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/general/images/lensed_source.png :alt: Alternative text :width: 400 ``` The `autolens_workspace` also includes a Graphical User Interface for drawing lensed source positions via -mouse click (). +mouse click (). Next, we create `PositionsLH` object, which has an input `threshold`. diff --git a/docs/general/model_cookbook.md b/docs/general/model_cookbook.md index 31f05aace..bc5184376 100644 --- a/docs/general/model_cookbook.md +++ b/docs/general/model_cookbook.md @@ -372,8 +372,8 @@ profiles. The following example notebooks show how to compose and fit these models: - - + + ## Model Linking (Advanced) @@ -381,7 +381,7 @@ When performing non-linear search chaining, the inferred model of one phase can The following example notebooks show how to compose and fit these models: - + ## Across Datasets (Advanced) @@ -390,7 +390,7 @@ but certain parameters are free to vary across the datasets. The following example notebooks show how to compose and fit these models: - + ## Relations (Advanced) @@ -399,7 +399,7 @@ We can compose models where the free parameter(s) vary according to a user-speci The following example notebooks show how to compose and fit these models: - + ## PyAutoFit API diff --git a/docs/general/workspace.md b/docs/general/workspace.md index 282558f6e..9b1bbb880 100644 --- a/docs/general/workspace.md +++ b/docs/general/workspace.md @@ -2,7 +2,7 @@ # Workspace Tour -You should have downloaded and configured the [autolens workspace](https://github.com/Jammy2211/autolens_workspace) +You should have downloaded and configured the [autolens workspace](https://github.com/PyAutoLabs/autolens_workspace) when you installed **PyAutoLens**. If you didn't, checkout the [installation instructions](https://pyautolens.readthedocs.io/en/latest/general/installation.html#installation-with-pip) for how to downloaded and configure the workspace. @@ -18,7 +18,7 @@ There are numerous example describing how to perform lensing calculations, lens **PyAutoLens** features. All examples are provided as Python scripts and Jupyter notebooks. Descriptions of every configuration file and their input parameters are provided in the `README.md` in -the [config directory of the workspace](https://github.com/Jammy2211/autolens_workspace/tree/release/config) +the [config directory of the workspace](https://github.com/PyAutoLabs/autolens_workspace/tree/main/config) ## Config diff --git a/docs/index.md b/docs/index.md index 94ab74021..833c7ba63 100644 --- a/docs/index.md +++ b/docs/index.md @@ -13,7 +13,7 @@ This is called strong gravitational lensing and **PyAutoLens** makes it simple t The following links are useful for new starters: - [The PyAutoLens readthedocs](https://pyautolens.readthedocs.io/en/latest): which includes [an overview of PyAutoLens's core features](https://pyautolens.readthedocs.io/en/latest/overview/overview_1_start_here.html), [a new user starting guide](https://pyautolens.readthedocs.io/en/latest/overview/overview_2_new_user_guide.html) and [an installation guide](https://pyautolens.readthedocs.io/en/latest/installation/overview.html). -- [The introduction Jupyter Notebook on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/start_here.ipynb), where you can try **PyAutoLens** in a web browser (without installation). +- [The introduction Jupyter Notebook on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/notebooks/imaging/start_here.ipynb), where you can try **PyAutoLens** in a web browser (without installation). - [The autolens_workspace GitHub repository](https://github.com/PyAutoLabs/autolens_workspace), which includes example scripts covering every **PyAutoLens** use case. - [The HowToLens GitHub repository](https://github.com/PyAutoLabs/HowToLens): a Jupyter notebook lecture series teaching strong lensing and lens modeling from the ground up. @@ -28,7 +28,7 @@ imaged source galaxy whose light has been distorted into an 'Einstein ring'. The reconstructions of the source's lensed and unlensed light distributions, which are created using a model of the lens galaxy's mass to trace backwards how the source's light is gravitationally lensed. -```{image} https://github.com/Jammy2211/PyAutoLens/blob/main/files/imageaxis.png?raw=true +```{image} https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/imageaxis.png?raw=true ``` Strong lensing provides astronomers with an invaluable tool to study a diverse range of topics, including the @@ -109,7 +109,7 @@ tracer_plotter.figures_2d(image=True) ``` To perform lens modeling, **PyAutoLens** adopts the probabilistic programming -language [PyAutoFit](https://github.com/rhayes777/PyAutoFit). **PyAutoFit** allows users to compose a +language [PyAutoFit](https://github.com/PyAutoLabs/PyAutoFit). **PyAutoFit** allows users to compose a lens model from `LightProfile`, `MassProfile` and `Galaxy` objects, customize the model parameterization and fit it to data via a non-linear search (e.g. [dynesty](https://github.com/joshspeagle/dynesty), [emcee](https://github.com/dfm/emcee) or [PySwarms](https://pyswarms.readthedocs.io/en/latest/)). The example @@ -194,7 +194,7 @@ datasets. For new **PyAutoLens** users, we recommend they start by [installing PyAutoLens](https://pyautolens.readthedocs.io/en/latest/installation/overview.html) (if you haven't already!), read through the `start_here.ipynb` notebook on -the [autolens_workspace](https://github.com/Jammy2211/autolens_workspace) and take the +the [autolens_workspace](https://github.com/PyAutoLabs/autolens_workspace) and take the [HowToLens Jupyter notebook lecture series](https://pyautolens.readthedocs.io/en/latest/howtolens/howtolens.html) on strong gravitational lensing. diff --git a/docs/installation/conda.md b/docs/installation/conda.md index 340f6d0bc..463792824 100644 --- a/docs/installation/conda.md +++ b/docs/installation/conda.md @@ -66,7 +66,7 @@ the `autolens_workspace`, reducing the download size): ```bash cd /path/on/your/computer/you/want/to/put/the/autolens_workspace -git clone https://github.com/Jammy2211/autolens_workspace --depth 1 +git clone https://github.com/PyAutoLabs/autolens_workspace --depth 1 cd autolens_workspace ``` diff --git a/docs/installation/overview.md b/docs/installation/overview.md index a97155486..0d4f2cf5b 100644 --- a/docs/installation/overview.md +++ b/docs/installation/overview.md @@ -34,10 +34,10 @@ If you install **PyAutoLens** without a proper GPU setup, a warning will be disp **PyAutoLens** uses the following parent packages: -**PyAutoConf** +**PyAutoConf** -**PyAutoFit** +**PyAutoFit** -**PyAutoArray** +**PyAutoArray** -**PyAutoGalaxy** +**PyAutoGalaxy** diff --git a/docs/installation/pip.md b/docs/installation/pip.md index cc706e202..c18d41353 100644 --- a/docs/installation/pip.md +++ b/docs/installation/pip.md @@ -53,7 +53,7 @@ the `autolens_workspace`, reducing the download size): ```bash cd /path/on/your/computer/you/want/to/put/the/autolens_workspace -git clone https://github.com/Jammy2211/autolens_workspace --depth 1 +git clone https://github.com/PyAutoLabs/autolens_workspace --depth 1 cd autolens_workspace ``` diff --git a/docs/installation/source.md b/docs/installation/source.md index 014a8de0f..3aabbce1a 100644 --- a/docs/installation/source.md +++ b/docs/installation/source.md @@ -22,11 +22,11 @@ contribute the development **PyAutoLens** or experiment with yourself! A large amount of **PyAutoLens** functionality is contained in its parent projects: -**PyAutoFit** +**PyAutoFit** -**PyAutoArray** +**PyAutoArray** -**PyAutoGalaxy** +**PyAutoGalaxy** If you wish to build from source all code you may need to build from source these 3 additional projects. We include below instructions for building just **PyAutoLens** from source or building all projects. @@ -42,7 +42,7 @@ pip install --upgrade pip First, clone (or fork) the **PyAutoLens** GitHub repository: ```bash -git clone https://github.com/Jammy2211/PyAutoLens +git clone https://github.com/PyAutoLabs/PyAutoLens ``` Next, install the **PyAuto** parent projects via pip: @@ -105,10 +105,10 @@ pip install --upgrade pip First, clone (or fork) all 4 GitHub repositories: ```bash -git clone https://github.com/rhayes777/PyAutoFit -git clone https://github.com/Jammy2211/PyAutoArray -git clone https://github.com/Jammy2211/PyAutoGalaxy -git clone https://github.com/Jammy2211/PyAutoLens +git clone https://github.com/PyAutoLabs/PyAutoFit +git clone https://github.com/PyAutoLabs/PyAutoArray +git clone https://github.com/PyAutoLabs/PyAutoGalaxy +git clone https://github.com/PyAutoLabs/PyAutoLens ``` Next, install **PyAutoConf** via pip: diff --git a/docs/installation/troubleshooting.md b/docs/installation/troubleshooting.md index 496565c48..9d366db13 100644 --- a/docs/installation/troubleshooting.md +++ b/docs/installation/troubleshooting.md @@ -21,7 +21,7 @@ instead, or visa versa. ## Support If you are still having issues with installation, please raise an issue on the -[autolens_workspace issues page](https://github.com/Jammy2211/autolens_workspace/issues) with a description of the +[autolens_workspace issues page](https://github.com/PyAutoLabs/autolens_workspace/issues) with a description of the problem and your system setup (operating system, Python version, etc.). ## Current Working Directory diff --git a/docs/overview/overview_1_start_here.md b/docs/overview/overview_1_start_here.md index baaaf97c0..9ac7cd100 100644 --- a/docs/overview/overview_1_start_here.md +++ b/docs/overview/overview_1_start_here.md @@ -9,7 +9,7 @@ It uses **JAX** to **accelerate lensing calculations**, with the example code be Here is a schematic of a strong gravitational lens: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/schematic.jpg +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/schematic.jpg :alt: Alternative text :width: 600 ``` @@ -52,7 +52,7 @@ aplt.plot_grid(grid=grid, title="") The `Grid2D` looks like this: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/0_grid.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/0_grid.png :alt: Alternative text :width: 600 ``` @@ -103,7 +103,7 @@ for fits to large datasets. aplt.plot_array(array=sersic_light_profile.image_2d_from(grid=grid), title="Image") ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/1_image_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/1_image_2d.png :alt: Alternative text :width: 600 ``` @@ -144,12 +144,12 @@ aplt.plot_array(array=isothermal_mass_profile.convergence_2d_from(grid=grid), ti aplt.plot_array(array=isothermal_mass_profile.potential_2d_from(grid=grid), title="Potential") ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/2_deflections_y_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/2_deflections_y_2d.png :alt: Alternative text :width: 600 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/3_deflections_x_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/3_deflections_x_2d.png :alt: Alternative text :width: 600 ``` @@ -192,22 +192,22 @@ aplt.plot_array(array=lens_galaxy.image_2d_from(grid=grid), title="Lens Galaxy I aplt.plot_array(array=source_galaxy.image_2d_from(grid=grid), title="Source Galaxy Image") ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/4_image_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/4_image_2d.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/7_image_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/7_image_2d.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/5_deflections_y_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/5_deflections_y_2d.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/6_deflections_x_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/6_deflections_x_2d.png :alt: Alternative text :width: 400 ``` @@ -218,7 +218,7 @@ The individual light profiles of the galaxy can be plotted on a subplot: aplt.subplot_galaxy_light_profiles(galaxy=lens_galaxy, grid=grid) ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/8_subplot_image.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/8_subplot_image.png :alt: Alternative text :width: 600 ``` @@ -240,7 +240,7 @@ tracer = al.Tracer(galaxies=[lens_galaxy, source_galaxy], cosmology=al.cosmo.Pla aplt.plot_array(array=tracer.image_2d_from(grid=grid), title="Image") ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/9_image_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/9_image_2d.png :alt: Alternative text :width: 600 ``` @@ -324,7 +324,7 @@ tracer = al.Tracer(galaxies=[lens_galaxy_0, lens_galaxy_1, source_galaxy]) aplt.plot_array(array=tracer.image_2d_from(grid=grid), title="Image") ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_1/10_image_2d.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_1/10_image_2d.png :alt: Alternative text :width: 600 ``` diff --git a/docs/overview/overview_2_new_user_guide.md b/docs/overview/overview_2_new_user_guide.md index 14a6a513c..439b644cd 100644 --- a/docs/overview/overview_2_new_user_guide.md +++ b/docs/overview/overview_2_new_user_guide.md @@ -17,18 +17,18 @@ There are three scales to choose from: - **Galaxy Scale**: Made up of a single lens galaxy lensing a single source galaxy, the simplest strong lens you can get! If you're interested in galaxy scale lenses, go to the question below called "What Data Type?". - **Group Scale**: Strong Lens Groups contains 2-10 lens galaxies, normally with one main large galaxy responsible for the majority of lensing. - They also typically lens just one source galaxy. If you are interested in groups, go to the [group/start_here.ipynb](https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/group/start_here.ipynb) notebook. + They also typically lens just one source galaxy. If you are interested in groups, go to the [group/start_here.ipynb](https://github.com/PyAutoLabs/autolens_workspace/blob/main/notebooks/group/start_here.ipynb) notebook. - **Cluster Scale**: Strong Lens Galaxy clusters often contained 20-50, or more, lens galaxies, lensing 10, or more, sources galaxies. - If you are interested in clusters, go to the [cluster/start_here.ipynb](https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/cluster/start_here.ipynb) notebook. + If you are interested in clusters, go to the [cluster/start_here.ipynb](https://github.com/PyAutoLabs/autolens_workspace/blob/main/notebooks/cluster/start_here.ipynb) notebook. ## What Dataset Type? If you are interested in galaxy-scale strong lenses, you now need to decide what type of strong lens data you are interested in: -- **CDD Imaging**: For image data from telescopes like Hubble and James Webb, go to [imaging/start_here.ipynb](https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/imaging/start_here.ipynb). -- **Interferometer**: For radio / sub-mm interferometer from instruments like ALMA, go to [interferometer/start_here.ipynb](https://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/interferometer/start_here.ipynb). -- **Point Sources**: For strongly lensed point sources (e.g. lensed quasars, supernovae), go to [point_source/start_here.ipynb](hhttps://github.com/Jammy2211/autolens_workspace/blob/release/notebooks/point_source/start_here.ipynb). +- **CDD Imaging**: For image data from telescopes like Hubble and James Webb, go to [imaging/start_here.ipynb](https://github.com/PyAutoLabs/autolens_workspace/blob/main/notebooks/imaging/start_here.ipynb). +- **Interferometer**: For radio / sub-mm interferometer from instruments like ALMA, go to [interferometer/start_here.ipynb](https://github.com/PyAutoLabs/autolens_workspace/blob/main/notebooks/interferometer/start_here.ipynb). +- **Point Sources**: For strongly lensed point sources (e.g. lensed quasars, supernovae), go to [point_source/start_here.ipynb](https://github.com/PyAutoLabs/autolens_workspace/blob/main/notebooks/point_source/start_here.ipynb). ## Google Colab diff --git a/docs/overview/overview_3_features.md b/docs/overview/overview_3_features.md index fbee87ce3..ed901dbca 100644 --- a/docs/overview/overview_3_features.md +++ b/docs/overview/overview_3_features.md @@ -36,7 +36,7 @@ The image below shows a pixelized source reconstruction of the strong lens SLACS reconstructed on a Voronoi mesh adapted to the source morphology, revealing it to be a grand-design face on spiral galaxy: -```{image} https://github.com/Jammy2211/PyAutoLens/blob/main/files/imageaxis.png?raw=true +```{image} https://github.com/PyAutoLabs/PyAutoLens/blob/main/files/imageaxis.png?raw=true :alt: Alternative text :width: 600 ``` @@ -58,27 +58,27 @@ surface brightness distribution. Instead, we assume that our source is a point source with a centre (y,x), and ray-trace triangles at iteratively higher resolutions to determine the source's exact locations in the image-plane: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/point_0.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/point_0.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/point_1.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/point_1.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/point_2.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/point_2.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/point_3.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/point_3.png :alt: Alternative text :width: 400 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/point_4.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/point_4.png :alt: Alternative text :width: 400 ``` @@ -92,7 +92,7 @@ Checkout the `autolens_workspace/*/point_source` package to get started. Modeling of interferometer data from submillimeter (e.g. ALMA) and radio (e.g. LOFAR) observatories: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoGalaxy/main/paper/almacombined.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoGalaxy/main/paper/almacombined.png :alt: Alternative text :width: 600 ``` @@ -107,7 +107,7 @@ Checkout the `autolens_workspace/*/interferometer` package to get started. An MGE decomposes the light of a galaxy into tens or hundreds of two dimensional Gaussians: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/mge.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/mge.png :alt: Alternative text :width: 600 ``` @@ -131,7 +131,7 @@ Checkout `autolens_workspace/notebooks/features/multi_gaussian_expansion.ipynb` The strong lenses we've discussed so far have just a single lens galaxy responsible for the lensing. Group-scale strong lenses are systems where there two or more lens galaxies deflecting one or more background sources: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/group.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/group.png :alt: Alternative text :width: 600 ``` @@ -147,12 +147,12 @@ The `autolens_workspace/*/group` package has example scripts for simulating data Modeling imaging datasets observed at different wavelengths (e.g. HST F814W and F150W) simultaneously or simultaneously analysing imaging and interferometer data: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/g_image.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/g_image.png :alt: Alternative text :width: 600 ``` -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/r_image.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/r_image.png :alt: Alternative text :width: 600 ``` @@ -169,7 +169,7 @@ feature and it is recommended you first get to grips with the core API. Ellipse fitting is a technique which fits many ellipses to a galaxy's emission to determine its ellipticity, position angle and centre, without assuming a parametric form for its light (e.g. like a Seisc profile): -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/ellipse.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/ellipse.png :alt: Alternative text :width: 600 ``` @@ -188,7 +188,7 @@ Checkout `autolens_workspace/notebooks/features/ellipse_fitting.ipynb` to learn Shapelets are a set of orthogonal basis functions that can be combined the represent galaxy structures: -```{image} https://raw.githubusercontent.com/Jammy2211/PyAutoLens/main/docs/overview/images/overview_3/shapelets.png +```{image} https://raw.githubusercontent.com/PyAutoLabs/PyAutoLens/main/docs/overview/images/overview_3/shapelets.png :alt: Alternative text :width: 600 ``` diff --git a/files/citations.md b/files/citations.md index cf914917c..2eee2262f 100644 --- a/files/citations.md +++ b/files/citations.md @@ -1,6 +1,6 @@ **Insert in the main body of the paper:** -We use the lens modeling software `PyAutoLens` https://github.com/Jammy2211/PyAutoLens) [@pyautolens] [@Nightingale2015] [@Nightingale2018] to... +We use the lens modeling software `PyAutoLens` https://github.com/PyAutoLabs/PyAutoLens) [@pyautolens] [@Nightingale2015] [@Nightingale2018] to... **At the end of the paper (delete as appropriate, see https://pyautofit.readthedocs.io/en/latest/general/citations.html):** @@ -16,9 +16,9 @@ This work uses the following software packages: - `matplotlib` https://github.com/matplotlib/matplotlib [@matplotlib] - `numba` https://github.com/numba/numba [@numba] - `NumPy` https://github.com/numpy/numpy [@numpy] -- `PyAutoFit` https://github.com/rhayes777/PyAutoFit [@pyautofit] -- `PyAutoGalaxy` https://github.com/Jammy2211/PyAutoGalaxy [@Nightingale2018] [@pyautogalaxy] -- `PyAutoLens` https://github.com/Jammy2211/PyAutoLens [@Nightingale2015] [@Nightingale2018] [@pyautolens] +- `PyAutoFit` https://github.com/PyAutoLabs/PyAutoFit [@pyautofit] +- `PyAutoGalaxy` https://github.com/PyAutoLabs/PyAutoGalaxy [@Nightingale2018] [@pyautogalaxy] +- `PyAutoLens` https://github.com/PyAutoLabs/PyAutoLens [@Nightingale2015] [@Nightingale2018] [@pyautolens] - `PyNUFFT` https://github.com/jyhmiinlin/pynufft [@pynufft] - `PySwarms` https://github.com/ljvmiranda921/pyswarms [@pyswarms] - `Python` https://www.python.org/ [@python] diff --git a/paper/README.md b/paper/README.md index 36d738ebf..277eb40e5 100644 --- a/paper/README.md +++ b/paper/README.md @@ -1,5 +1,5 @@ PyAutoLens JOSS Paper ===================== -Paper accompanying [PyAutoGalaxy](https://github.com/rhayes777/PyAutoGalaxy) for submission to the Journal of Open Source +Paper accompanying [PyAutoGalaxy](https://github.com/PyAutoLabs/PyAutoGalaxy) for submission to the Journal of Open Source Software (JOSS). \ No newline at end of file diff --git a/paper/paper.md b/paper/paper.md index a567b39a1..a70a948ec 100644 --- a/paper/paper.md +++ b/paper/paper.md @@ -72,7 +72,7 @@ affiliations: index: 7 date: 25 January 2022 -codeRepository: https://github.com/Jammy2211/PyAutoLens +codeRepository: https://github.com/PyAutoLabs/PyAutoLens license: MIT bibliography: paper.bib --- @@ -88,7 +88,7 @@ strong lenses. The API allows users to perform ray-tracing by using analytic lig lens systems. Accompanying `PyAutoLens` is the [autolens workspace](https://github.com/PyAutoLabs/autolens_workspace), which includes example scripts and lens datasets covering every use case. The [`HowToLens`](https://github.com/PyAutoLabs/HowToLens) repository provides a separate Jupyter notebook lecture series which introduces non-experts to strong lensing using `PyAutoLens`. Readers can -try `PyAutoLens` right now by going to [the introduction Jupyter notebook on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/start_here.ipynb) +try `PyAutoLens` right now by going to [the introduction Jupyter notebook on Colab](https://colab.research.google.com/github/PyAutoLabs/autolens_workspace/blob/2026.5.14.2/notebooks/imaging/start_here.ipynb) or checkout the [readthedocs](https://pyautolens.readthedocs.io/en/latest/) for a complete overview of `PyAutoLens`'s features. # Background @@ -137,7 +137,7 @@ extensible, making it straightforward to compose highly customized lensing syste optimized using the packages `NumPy` [@numpy], `numba` [@numba] and `pyquad` [@pyquad]. To perform lens modeling, `PyAutoLens` adopts the probabilistic programming -language `PyAutoFit` (https://github.com/rhayes777/PyAutoFit). `PyAutoFit` allows users to compose a +language `PyAutoFit` (https://github.com/PyAutoLabs/PyAutoFit). `PyAutoFit` allows users to compose a lens model from `LightProfile`, `MassProfile` and `Galaxy` objects, customize the model parameterization and fit it to data via a non-linear search (e.g., `dynesty` [@dynesty], `emcee` [@emcee], `PySwarms` [@pyswarms]). By composing a lens model with a `Pixelization` object, the background source's light is reconstructed using a @@ -149,7 +149,7 @@ Automated lens modeling uses `PyAutoFit`'s non-linear search chaining feature, w a chained sequence of non-linear searches. These fits pass information gained about simpler lens models fitted by earlier searches to subsequent searches, which fit progressively more complex models. By granularizing the model-fitting procedure, automated pipelines that fit complex lens models without human intervention can be carefully crafted, with -example pipelines found on the [autolens workspace](https://github.com/Jammy2211/autolens_workspace). To ensure the +example pipelines found on the [autolens workspace](https://github.com/PyAutoLabs/autolens_workspace). To ensure the analysis and interpretation of fits to large lens datasets is feasible, `PyAutoFit`'s database tools write lens modeling results to a relational database which can be queried from hard-disk to a Python script or Jupyter notebook. This uses memory-light `Python` generators, ensuring it is practical for thousands of lenses.