diff --git a/.url_check_allowlist.txt b/.url_check_allowlist.txt index 97dae87..0eef273 100644 --- a/.url_check_allowlist.txt +++ b/.url_check_allowlist.txt @@ -14,11 +14,6 @@ https://academic.oup.com/mnras/article/488/1/1387/5526256 # CITATIONS.md:22 # Code of Conduct boilerplate http://geekfeminism.wikia.com/wiki/Conference_anti-harassment/Policy # CODE_OF_CONDUCT.md:305 -# Colab refs to notebooks no longer in HowTo/workspace -https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_4_complex_source.ipynb # scripts/chapter_3_search_chaining/README.md:16 -https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_11_adapt_regularization.py.ipynb # scripts/chapter_4_pixelizations/README.md:27 -https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_3_pixelizations.ipynb # scripts/chapter_4_pixelizations/README.md:11 - # External dead / paywalled / departmental pages http://www.ita.uni-heidelberg.de/~massimo/sub/Lectures/gl_all.pdf # README.md:66 diff --git a/notebooks/chapter_1_introduction/README.md b/notebooks/chapter_1_introduction/README.md index c992dec..7b5bdb5 100644 --- a/notebooks/chapter_1_introduction/README.md +++ b/notebooks/chapter_1_introduction/README.md @@ -4,20 +4,20 @@ In chapter 1, we introduce you to strong gravitational lensing and the core **Py # Files -- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library. +- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library. -- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles. +- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles. -- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing. +- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing. -- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing. +- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing. -- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations when the source galaxy is a point-source (e.g. a quasar). +- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations when the source galaxy is a point-source (e.g. a quasar). -- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing. +- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing. -- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens. +- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens. -- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model. +- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model. -- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter. +- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter. diff --git a/notebooks/chapter_2_lens_modeling/README.md b/notebooks/chapter_2_lens_modeling/README.md index 4d1bd61..35d0b98 100644 --- a/notebooks/chapter_2_lens_modeling/README.md +++ b/notebooks/chapter_2_lens_modeling/README.md @@ -4,18 +4,18 @@ In chapter 2, we'll take you through how to model strong lenses using a non-line # Files -- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors. +- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors. -- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk. +- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk. -- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model. +- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model. -- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model. +- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model. -- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters. +- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters. -- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model. +- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model. -- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model. +- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model. -- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time. +- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time. diff --git a/notebooks/chapter_3_search_chaining/README.md b/notebooks/chapter_3_search_chaining/README.md index 59fb251..efdc068 100644 --- a/notebooks/chapter_3_search_chaining/README.md +++ b/notebooks/chapter_3_search_chaining/README.md @@ -5,14 +5,14 @@ different lens model. # Files -- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits. +- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits. -- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches. +- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches. -- [Tutorial 3: Lens and Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb) — Fitting the lens's light followed by its mass using chained searches. +- [Tutorial 3: Lens and Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb) — Fitting the lens's light followed by its mass using chained searches. -- [Tutorial 4: Two Lens galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb) — Modeling a strong lens with two lens galaxies using chained searches. +- [Tutorial 4: Two Lens galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb) — Modeling a strong lens with two lens galaxies using chained searches. -- [Tutorial 5: Complex Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_4_complex_source.ipynb) — Using multiple light profiles to fit a complex and irregular source using chained searches. +- [Tutorial 5: Complex Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_5_complex_source.ipynb) — Using multiple light profiles to fit a complex and irregular source using chained searches. -- [Tutorial 6: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb) — Template pipelines for fitting lens model is standardized ways. +- [Tutorial 6: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb) — Template pipelines for fitting lens model is standardized ways. diff --git a/notebooks/chapter_4_pixelizations/README.md b/notebooks/chapter_4_pixelizations/README.md index bc077ce..358e8c9 100644 --- a/notebooks/chapter_4_pixelizations/README.md +++ b/notebooks/chapter_4_pixelizations/README.md @@ -4,24 +4,24 @@ In chapter 4, we use **Pixelizations** to reconstruct complex source galaxies on # Files -- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane. +- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane. -- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels. +- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels. -- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_3_pixelizations.ipynb) — Inverting the mappings to reconstruct the source's light. +- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light. -- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework. +- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework. -- [Tutorial 5: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion. +- [Tutorial 5: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion. -- [Tutorial 6: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb) — How to use inversions to fit a lens model. +- [Tutorial 6: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb) — How to use inversions to fit a lens model. -- [Tutorial 7: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb) — A Voronoi mesh which adapts to the mass model's magnification. +- [Tutorial 7: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb) — A Voronoi mesh which adapts to the mass model's magnification. -- [Tutorial 8: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion. +- [Tutorial 8: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion. -- [Tutorial 9: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb) — The shortcomings of our lens models and inversions. +- [Tutorial 9: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb) — The shortcomings of our lens models and inversions. -- [Tutorial 10: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology. +- [Tutorial 10: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology. -- [Tutorial 11: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_11_adapt_regularization.py.ipynb) — Adapting the regularization to the source's morphology. +- [Tutorial 11: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_11_adaptive_regularization.ipynb) — Adapting the regularization to the source's morphology. diff --git a/scripts/chapter_1_introduction/README.md b/scripts/chapter_1_introduction/README.md index c992dec..7b5bdb5 100644 --- a/scripts/chapter_1_introduction/README.md +++ b/scripts/chapter_1_introduction/README.md @@ -4,20 +4,20 @@ In chapter 1, we introduce you to strong gravitational lensing and the core **Py # Files -- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library. +- [Tutorial 0: Visualization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_0_visualization.ipynb) — Setting up **PyAutoLens**'s visualization library. -- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles. +- [Tutorial 1: Grids And Galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_1_grids_and_galaxies.ipynb) — Using grids of (y,x) coordinates with galaxies made up of light profiles. -- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing. +- [Tutorial 2: Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_2_ray_tracing.ipynb) — Using grids, galaxies and mass profiles to perform strong lens ray-tracing. -- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing. +- [Tutorial 3: More Ray Tracing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_3_more_ray_tracing.ipynb) — Advanced strong lens ray-tracing. -- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations when the source galaxy is a point-source (e.g. a quasar). +- [Tutorial 4: Point Sources](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_4_point_sources.ipynb) — How lensing calculations when the source galaxy is a point-source (e.g. a quasar). -- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing. +- [Tutorial 5: Lensing Formalism](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_5_lensing_formalism.ipynb) — The algebraic lensing formalism used to describe strong lensing. -- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens. +- [Tutorial 6: Data](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_6_data.ipynb) — Loading and inspecting telescope imaging data of a strong lens. -- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model. +- [Tutorial 7: Fitting](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_7_fitting.ipynb) — Fitting data with a strong lens model. -- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter. +- [Tutorial 8: Summary](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_1_introduction/tutorial_8_summary.ipynb) — A summary of the chapter. diff --git a/scripts/chapter_2_lens_modeling/README.md b/scripts/chapter_2_lens_modeling/README.md index 4d1bd61..35d0b98 100644 --- a/scripts/chapter_2_lens_modeling/README.md +++ b/scripts/chapter_2_lens_modeling/README.md @@ -4,18 +4,18 @@ In chapter 2, we'll take you through how to model strong lenses using a non-line # Files -- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors. +- [Tutorial 1: Non-linear Search](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_1_non_linear_search.ipynb) — How a non-linear search is used to fit a lens model and the concepts of a parameter space and priors. -- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk. +- [Tutorial 2: Practicalities](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_2_practicalities.ipynb) — Practicalities of performing model-fitting, like how to inspect the results on your hard-disk. -- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model. +- [Tutorial 3: Realism and Complexity](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_3_realism_and_complexity.ipynb) — Finding a balance between realism and complexity when composing and fitting a lens model. -- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model. +- [Tutorial 4: Dealing with Failure](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_4_dealing_with_failure.ipynb) — What to do when PyAutoLens finds an inaccurate lens model. -- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters. +- [Tutorial 5: Linear Profiles](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_5_linear_profiles.ipynb) — Light profiles which capture complex morphologies in a reduced number of non-linear parameters. -- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model. +- [Tutorial 6: Masking and Positions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_6_masking_and_positions.ipynb) — How to mask and mark positions on your data to improve the lens model. -- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model. +- [Tutorial 7: Results](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_7_results.ipynb) — Overview of the results available after successfully fitting a lens model. -- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time. +- [Tutorial 8: Need for Speed](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_2_lens_modeling/tutorial_8_need_for_speed.ipynb) — How to fit complex models whilst balancing efficiency and run-time. diff --git a/scripts/chapter_3_search_chaining/README.md b/scripts/chapter_3_search_chaining/README.md index 59fb251..efdc068 100644 --- a/scripts/chapter_3_search_chaining/README.md +++ b/scripts/chapter_3_search_chaining/README.md @@ -5,14 +5,14 @@ different lens model. # Files -- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits. +- [Tutorial 1: Search Chaining](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_1_search_chaining.ipynb) — Breaking the lens modeling procedure into a chained sequence of model-fits. -- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches. +- [Tutorial 2: Prior Passing](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_2_prior_passing.ipynb) — How the results of earlier searches are passed to later searches. -- [Tutorial 3: Lens and Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb) — Fitting the lens's light followed by its mass using chained searches. +- [Tutorial 3: Lens and Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_3_lens_and_source.ipynb) — Fitting the lens's light followed by its mass using chained searches. -- [Tutorial 4: Two Lens galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb) — Modeling a strong lens with two lens galaxies using chained searches. +- [Tutorial 4: Two Lens galaxies](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_4_x2_lens_galaxies.ipynb) — Modeling a strong lens with two lens galaxies using chained searches. -- [Tutorial 5: Complex Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_4_complex_source.ipynb) — Using multiple light profiles to fit a complex and irregular source using chained searches. +- [Tutorial 5: Complex Source](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_5_complex_source.ipynb) — Using multiple light profiles to fit a complex and irregular source using chained searches. -- [Tutorial 6: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb) — Template pipelines for fitting lens model is standardized ways. +- [Tutorial 6: SLaM](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_3_search_chaining/tutorial_6_slam.ipynb) — Template pipelines for fitting lens model is standardized ways. diff --git a/scripts/chapter_4_pixelizations/README.md b/scripts/chapter_4_pixelizations/README.md index bc077ce..358e8c9 100644 --- a/scripts/chapter_4_pixelizations/README.md +++ b/scripts/chapter_4_pixelizations/README.md @@ -4,24 +4,24 @@ In chapter 4, we use **Pixelizations** to reconstruct complex source galaxies on # Files -- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane. +- [Tutorial 1: Pixelizations](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_1_pixelizations.ipynb) — Creating a pixel-grid in the source-plane. -- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels. +- [Tutorial 2: Mappers](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_2_mappers.ipynb) — How a pixelization maps source-pixels to image-pixels. -- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_3_pixelizations.ipynb) — Inverting the mappings to reconstruct the source's light. +- [Tutorial 3: Inversions](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_3_inversions.ipynb) — Inverting the mappings to reconstruct the source's light. -- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework. +- [Tutorial 4: Bayesian Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_4_bayesian_regularization.ipynb) — Smoothing the source within a Bayesian framework. -- [Tutorial 5: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion. +- [Tutorial 5: Borders](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_5_borders.ipynb) — Preventing highly demagnified image-pixels ruining the inversion. -- [Tutorial 6: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb) — How to use inversions to fit a lens model. +- [Tutorial 6: Lens Modeling](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_6_lens_modeling.ipynb) — How to use inversions to fit a lens model. -- [Tutorial 7: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb) — A Voronoi mesh which adapts to the mass model's magnification. +- [Tutorial 7: Adaptive Pixelization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_7_adaptive_pixelization.ipynb) — A Voronoi mesh which adapts to the mass model's magnification. -- [Tutorial 8: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion. +- [Tutorial 8: Model Fit](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_8_model_fit.ipynb) — An example lens modeling pipeline which uses an inversion. -- [Tutorial 9: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb) — The shortcomings of our lens models and inversions. +- [Tutorial 9: Fit Problems](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_9_fit_problems.ipynb) — The shortcomings of our lens models and inversions. -- [Tutorial 10: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology. +- [Tutorial 10: Brightness Adaption](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_10_brightness_adaption.ipynb) — Adapting the pixelization to the source's morphology. -- [Tutorial 11: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/main/notebooks/chapter_4_pixelizations/tutorial_11_adapt_regularization.py.ipynb) — Adapting the regularization to the source's morphology. +- [Tutorial 11: Adaptive Regularization](https://colab.research.google.com/github/PyAutoLabs/HowToLens/blob/2026.7.6.649/notebooks/chapter_4_pixelizations/tutorial_11_adaptive_regularization.ipynb) — Adapting the regularization to the source's morphology.