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mkdocs.yml
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# Adapted from : https://github.com/patrick-kidger/equinox/blob/main/mkdocs.yml
site_name: jinns
site_description: The documentation for the jinns software library.
site_author: Hugo Gangloff & Nicolas Jouvin
site_url: https://mia_jinns.gitlab.io/jinns/
theme:
name: "material"
features:
- navigation.sections # Sections are included in the navigation on the left.
- toc.integrate # Table of contents is integrated on the left; does not appear separately on the right.
- header.autohide # header disappears as you scroll
icon:
repo: fontawesome/brands/gitlab # GitHub logo in top right
logo: "material/oil-lamp" # jinns logo in top left
favicon: "_static/favicon.png"
palette:
# Light mode / dark mode
# We deliberately don't automatically use `media` to check a user's preferences. We default to light mode as
# (a) it looks more professional, and (b) is more obvious about the fact that it offers a (dark mode) toggle.
- scheme: default
primary: white
accent: amber
toggle:
icon: material/weather-night
name: Switch to dark mode
- scheme: slate
primary: black
accent: amber
toggle:
icon: material/weather-sunny
name: Switch to light mode
markdown_extensions:
- toc:
permalink: "#" # Adds a clickable permalink to each section heading
toc_depth: 3
- pymdownx.arithmatex:
generic: true
- admonition
- pymdownx.details
- pymdownx.superfences
- pymdownx.emoji:
emoji_index: !!python/name:material.extensions.emoji.twemoji
emoji_generator: !!python/name:material.extensions.emoji.to_svg
extra_javascript:
- javascripts/katex.js
- https://unpkg.com/katex@0/dist/katex.min.js
- https://unpkg.com/katex@0/dist/contrib/auto-render.min.js
extra_css:
- https://unpkg.com/katex@0/dist/katex.min.css
- _static/custom_css.css
plugins:
- search # default search plugin; needs manually re-enabling when using any other plugins
- autorefs # Cross-links to headings
- mknotebooks # Jupyter notebooks
- mkdocstrings:
handlers:
python:
options:
docstring_style: numpy
show_root_heading: true
show_source: false # don't include source code
setup_commands:
- import pytkdocs_tweaks
- pytkdocs_tweaks.main()
- import jaxtyping
- jaxtyping.set_array_name_format("array")
- import jax
- jax.ShapeDtypeStruct.__module__ = "jax"
- jax.core.ClosedJaxpr.__module__ = "jax.core"
selection:
inherited_members: true # Allow looking up inherited methods
rendering:
show_root_heading: true # actually display anything at all...
show_root_full_path: true # display "jinns.abcd" not just "abcd"
show_if_no_docstring: true
show_signature_annotations: true
members_order: source # order methods according to their order of definition in the source code, not alphabetical order
heading_level: 3
repo_url: https://gitlab.com/mia_jinns/jinns
repo_name: mia_jinns/jinns
nav:
- 'index.md'
- 'changelog.md'
- Citation: 'https://mia_jinns.gitlab.io/jinns/#citing-us'
- Tutorials:
- Implementing your own problem: 'Notebooks/Tutorials/implementing_your_own_PDE_problem.ipynb'
- Saving / loading your model: 'Notebooks/Tutorials/load_save_model.ipynb'
- Using validation module: 'Notebooks/Tutorials/introducing_validation_loss.ipynb'
- A simple inverse problem: 'Notebooks/Tutorials/1D_non_stationary_Burgers_JointEstimation_Vanilla.ipynb'
- Examples:
- Forward problems:
- ODE:
- Linear first-order equation: 'Notebooks/ODE/linear_fo_equation.ipynb'
- Generalized Lotka-Volterra: 'Notebooks/ODE/1D_Generalized_Lotka_Volterra.ipynb'
- PDE:
- Navier-Stokes in pipe flow:
- Hard-constraints: 'Notebooks/PDE/2D_Navier_Stokes_PipeFlow.ipynb'
- Soft-constraints: 'Notebooks/PDE/2D_Navier_Stokes_PipeFlow_SoftConstraints.ipynb'
- 1D Burgers equation: 'Notebooks/PDE/1D_non_stationary_Burgers.ipynb'
- 1D Fisher-KPP: 'Notebooks/PDE/1D_non_stationary_Fisher_KPP_Bounded_Domain.ipynb'
- 2D Fisher-KPP with covariates: 'Notebooks/PDE/Reaction_Diffusion_2D_heterogenous_model.ipynb'
- 2D learning Ornstein Uhlenbeck pdf (RAR sampling): 'Notebooks/PDE/2D_non_stationary_OU.ipynb'
- Inverse problems:
- ODE:
- SBINNs: 'Notebooks/ODE/systems_biology_informed_neural_network.ipynb'
- PDE:
- Heat equation 2D and estimation of the diffusion coefficient: 'Notebooks/PDE/2D_Heat_inverse_problem.ipynb'
- Poisson in 2D: 'Notebooks/PDE/2D_Poisson_inverse_problem.ipynb'
- Meta-modeling:
# - ODE:
- PDE:
- Navier-Stokes in pipe flow: 'Notebooks/PDE/2D_Navier_Stokes_PipeFlow_Metamodel_hyperpinn.ipynb'
- Fisher-KPP: 'Notebooks/PDE/Reaction_Diffusion_2D_homogeneous_metamodel_hyperpinn_diffrax.ipynb'
- Basic API:
- DataGenerators:
- Main DataGenerators: 'api/datagenerators/datagenerators_core.md'
- Other DataGenerators: 'api/datagenerators/datagenerators_other.md'
- Loss:
- Dynamic loss: 'api/loss/dynamic_loss.md'
- Total loss: 'api/loss/loss_xde.md'
- Systems: 'api/loss/systems_of_xde.md'
- Neural Networks:
- 'api/pinn/pinn.md'
- 'api/pinn/spinn.md'
- 'api/pinn/hyperpinn.md'
- 'api/pinn/save_load.md'
- Plot: 'api/plot.md'
- Solve: 'api/solver.md'
- Advanced:
- Differential operators: 'api/advanced/differential_operators.md'
- Derivative keys: 'api/advanced/derivative_keys.md'
- Misc:
- Framework & notations: 'maths/introduction_to_pinns.md'
- 'maths/fokker_planck.md'