Merge pull request #226 from Ciela-Institute/dev

Dev

.codespell-whitelist

@@ -2,3 +2,4 @@ sie
 childs
 dout
 din
+tht

.github/workflows/cd.yml

@@ -57,7 +57,7 @@ jobs:
           ls -ltrh
           ls -ltrh dist
       - name: Publish to Test PyPI
-        uses: pypa/gh-action-pypi-publish@v1.8.14
+        uses: pypa/gh-action-pypi-publish@v1.9.0
         with:
           repository-url: https://test.pypi.org/legacy/
           verbose: true
@@ -95,5 +95,5 @@ jobs:
           name: artifact
           path: dist
 
-      - uses: pypa/gh-action-pypi-publish@v1.8.14
+      - uses: pypa/gh-action-pypi-publish@v1.9.0
         if: startsWith(github.ref, 'refs/tags')

.github/workflows/image_ci.yml

@@ -98,7 +98,7 @@ jobs:
         uses: docker/setup-buildx-action@v3
 
       - name: Build and export to Docker
-        uses: docker/build-push-action@v5
+        uses: docker/build-push-action@v6
         with:
           context: .
           file: ./resources/docker/Dockerfile

.pre-commit-config.yaml

@@ -9,7 +9,7 @@ ci:
 
 repos:
   - repo: https://github.com/psf/black
-    rev: "24.4.0"
+    rev: "24.4.2"
     hooks:
       - id: black-jupyter
 
@@ -23,6 +23,7 @@ repos:
     rev: "v4.6.0"
     hooks:
       - id: check-added-large-files
+        args: ["--maxkb=1000"]
       - id: check-case-conflict
       - id: check-merge-conflict
       - id: check-symlinks
@@ -50,13 +51,13 @@ repos:
         args: [--prose-wrap=always]
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: "v0.4.1"
+    rev: "v0.4.10"
     hooks:
       - id: ruff
         args: ["--fix", "--show-fixes"]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: "v1.9.0"
+    rev: "v1.10.0"
     hooks:
       - id: mypy
         files: src
@@ -65,16 +66,25 @@ repos:
           - pytest
 
   - repo: https://github.com/codespell-project/codespell
-    rev: "v2.2.6"
+    rev: "v2.3.0"
     hooks:
       - id: codespell
         args: ["--write-changes", "--ignore-words", ".codespell-whitelist"]
 
-  - repo: https://github.com/kynan/nbstripout
-    rev: 0.7.1
+  #- repo: https://github.com/kynan/nbstripout
+  #rev: 0.7.1
+  #hooks:
+  #- id: nbstripout
+  #args: [--extra-keys=metadata.kernelspec metadata.language_info.version]
+
+  - repo: local
     hooks:
-      - id: nbstripout
-        args: [--extra-keys=metadata.kernelspec metadata.language_info.version]
+      - id: strip-output-keep-html
+        name: Strip Jupyter Notebook output but keep HTML
+        entry: python strip_output_keep_html.py
+        language: python
+        additional_dependencies: [nbformat]
+        files: \.ipynb$
 
   - repo: local
     hooks:

CODE_OF_CONDUCT.md

@@ -5,7 +5,7 @@
 We as members, contributors, and leaders pledge to make participation in our
 community a harassment-free experience for everyone, regardless of age, body
 size, visible or invisible disability, ethnicity, sex characteristics, gender
-identity and expression, level of experience, education, socio-economic status,
+identity and expression, level of experience, education, socioeconomic status,
 nationality, personal appearance, race, caste, color, religion, or sexual
 identity and orientation.
 

README.md

@@ -10,7 +10,9 @@
 [![Documentation Status](https://readthedocs.org/projects/caustics/badge/?version=latest)](https://caustics.readthedocs.io/en/latest/?badge=latest)
 [![PyPI version](https://badge.fury.io/py/caustics.svg)](https://pypi.org/project/caustics/)
 [![coverage](https://img.shields.io/codecov/c/github/Ciela-Institute/caustics)](https://app.codecov.io/gh/Ciela-Institute/caustics)
-[![DOI](https://zenodo.org/badge/521722463.svg)](https://zenodo.org/doi/10.5281/zenodo.10806382)
+[![status](https://joss.theoj.org/papers/995fa98462eb534a32952549ef2244f8/status.svg)](https://joss.theoj.org/papers/995fa98462eb534a32952549ef2244f8)
+[![Zenodo](https://zenodo.org/badge/521722463.svg)](https://zenodo.org/doi/10.5281/zenodo.10806382)
+[![arXiv](https://img.shields.io/badge/arXiv-2406.15542-b31b1b.svg)](https://arxiv.org/abs/2406.15542)
 
 # caustics
 
@@ -45,7 +47,7 @@ x = torch.tensor([
     5.0, -0.2, 0.0, 0.8, 0.0, 1., 1.0, 10.0
 ])  # fmt: skip
 
-minisim = caustics.Lens_Source(
+minisim = caustics.LensSource(
     lens=sie, source=src, lens_light=lnslt, pixelscale=0.05, pixels_x=100
 )
 plt.imshow(minisim(x, quad_level=3), origin="lower")

docs/source/_toc.yml

@@ -9,7 +9,12 @@ chapters:
   - file: websim
   - file: tutorials/index
     sections:
-      - file: tutorials/BasicIntroduction
+      - file: tutorials/Introduction
+      - file: interfaceindex
+        sections:
+          - file: tutorials/InterfaceIntroduction_yaml
+          - file: tutorials/InterfaceIntroduction_oop
+          - file: tutorials/InterfaceIntroduction_func
       - file: tutorials/LensZoo
       - file: tutorials/VisualizeCaustics
       - file: tutorials/MultiplaneDemo
@@ -23,6 +28,7 @@ chapters:
       - file: examples/Example_ImageFit_NUTS
       - file: examples/Example_QSOLensFit
   - file: contributing
+  - file: frequently_asked_questions
   - file: citation
   - file: license
   - file: modules

docs/source/examples/Example_ImageFit_LM.ipynb

@@ -56,10 +56,9 @@
     "cosmology.to(dtype=torch.float32)\n",
     "\n",
     "upsample_factor = 1\n",
-    "thx, thy = caustics.utils.get_meshgrid(\n",
+    "thx, thy = caustics.utils.meshgrid(\n",
     "    pixelscale / upsample_factor,\n",
     "    upsample_factor * numPix,\n",
-    "    upsample_factor * numPix,\n",
     "    dtype=torch.float32,\n",
     ")\n",
     "z_l = torch.tensor(0.5, dtype=torch.float32)\n",
@@ -110,7 +109,7 @@
     ")\n",
     "\n",
     "# Image plane simulator\n",
-    "sim = caustics.Lens_Source(\n",
+    "sim = caustics.LensSource(\n",
     "    lens=lens_mass_model,\n",
     "    lens_light=lens_light_model,\n",
     "    source=source_light_model,\n",

docs/source/examples/Example_ImageFit_NUTS.ipynb

@@ -61,10 +61,9 @@
     "cosmology.to(dtype=torch.float32)\n",
     "\n",
     "upsample_factor = 1\n",
-    "thx, thy = caustics.utils.get_meshgrid(\n",
+    "thx, thy = caustics.utils.meshgrid(\n",
     "    pixelscale / upsample_factor,\n",
     "    upsample_factor * numPix,\n",
-    "    upsample_factor * numPix,\n",
     "    dtype=torch.float32,\n",
     ")\n",
     "z_l = torch.tensor(0.5, dtype=torch.float32)\n",
@@ -115,7 +114,7 @@
     ")\n",
     "\n",
     "# Image plane simulator\n",
-    "sim = caustics.Lens_Source(\n",
+    "sim = caustics.LensSource(\n",
     "    lens=lens_mass_model,\n",
     "    lens_light=lens_light_model,\n",
     "    source=source_light_model,\n",

docs/source/examples/Example_QSOLensFit.ipynb

@@ -103,10 +103,9 @@
     "res = 0.05\n",
     "upsample_factor = 1\n",
     "fov = res * n_pix\n",
-    "thx, thy = caustics.utils.get_meshgrid(\n",
+    "thx, thy = caustics.utils.meshgrid(\n",
     "    res / upsample_factor,\n",
     "    upsample_factor * n_pix,\n",
-    "    upsample_factor * n_pix,\n",
     "    dtype=torch.float32,\n",
     ")\n",
     "\n",

docs/source/frequently_asked_questions.rst

@@ -0,0 +1,10 @@
+FAQs - Frequently asked questions
+=================================
+| **Q:** How do I know what order to put the parameter values in the pytorch tensor which gets passed to the simulator?
+| **A:** If you are using a simulator, then you can get the parameters using ``your_simulator.state_dict()``. The parameters whose values are set dynamically will say "None", while the static parameters will have their values shown. The order of the dynamical parameters corresponds to the order you should use in your parameter value tensor.
+|
+| **Q:** Why can I put the lens redshift at higher values than the source redshift or to negative values for some parametric models?
+| **A:** We can calculate everything for those profiles with reduced deflection angles where the redshifts do not actually play into the calculation. If you use a profile defined by the lens mass, like a NFW lens, or a Multiplane lens then it does matter that the redshifts make sense and you will very likely get errors for those. Similarly, if you call the ``lens.physical_deflection_angle`` you will encounter errors.
+|
+| **Q:** I do (multiplane-)lensing with pixelated convergence using the pixelated kappa map of a parametric profile. The lensing effect differs from directly using the parametric lens. Why is the lensing effect different?
+| **A:** Since you do pixelated convergence your mass is binned in pixels in a finite field of view (FOV) so you are missing some mass. At the limit of infinite resolution and infinite FOV the pixelated profile gives you the parametric profile. If the difference is above your error tolerance then you have to increase the resolution and/or FOV of your pixelated convergence map. Especially for SIE or EPL profiles (which go to infinity density in the center, and have infinite mass outside any FOV) you will miss infinite mass when pixelating.

docs/source/interfaceindex.rst

@@ -0,0 +1,10 @@
+The three interfaces to Caustics
+================================
+
+There are three user interfaces to Caustics: configuration file, object-oriented, and functional.
+Here we have built the same tutorial three times over so you can see how the three interfaces compare.
+They provide progressively more freedom and power, but also require more knowledge of the underlying system.
+
+1. Configuration File: :doc:`tutorials/BasicIntroduction_yaml`
+2. Object-Oriented: :doc:`tutorials/BasicIntroduction_oop`
+3. Functional: :doc:`tutorials/BasicIntroduction_func`

docs/source/intro.md

@@ -39,7 +39,7 @@ x = torch.tensor([
     5.0, -0.2, 0.0, 0.8, 0.0, 1., 1.0, 10.0
 ])  # fmt: skip
 
-minisim = caustics.Lens_Source(
+minisim = caustics.LensSource(
     lens=sie, source=src, lens_light=lnslt, pixelscale=0.05, pixels_x=100
 )
 plt.imshow(minisim(x, quad_level=3), origin="lower")