diff --git a/.gitignore b/.gitignore index dfa38d910f..15afd2682e 100644 --- a/.gitignore +++ b/.gitignore @@ -17,6 +17,8 @@ tags # Sphinx _build +docs/jupyter_execute +docs/source/api # Merge tool *.orig diff --git a/.gitmodules b/.gitmodules deleted file mode 100644 index b19939f4dc..0000000000 --- a/.gitmodules +++ /dev/null @@ -1,4 +0,0 @@ -[submodule "docs/source/pymc-examples"] - path = docs/source/pymc-examples - url = https://github.com/pymc-devs/pymc-examples.git - branch = main diff --git a/conda-envs/environment-dev-py37.yml b/conda-envs/environment-dev-py37.yml index fbbc2868ad..5516ef6e71 100644 --- a/conda-envs/environment-dev-py37.yml +++ b/conda-envs/environment-dev-py37.yml @@ -22,9 +22,8 @@ dependencies: - pytest>=3.0 - python-graphviz - python=3.7 -- recommonmark>=0.4 - scipy>1.4.1 -- sphinx-autobuild>=0.7 +- sphinx-copybutton - sphinx-notfound-page - sphinx-panels - sphinx>=1.5 diff --git a/conda-envs/environment-dev-py38.yml b/conda-envs/environment-dev-py38.yml index f83321d2f4..9a7a573f61 100644 --- a/conda-envs/environment-dev-py38.yml +++ b/conda-envs/environment-dev-py38.yml @@ -22,9 +22,8 @@ dependencies: - pytest>=3.0 - python-graphviz - python=3.8 -- recommonmark>=0.4 - scipy>1.4.1 -- sphinx-autobuild>=0.7 +- sphinx-copybutton - sphinx-notfound-page - sphinx-panels - sphinx>=1.5 diff --git a/conda-envs/environment-dev-py39.yml b/conda-envs/environment-dev-py39.yml index 5aeff923ee..e2bd1ee5d5 100644 --- a/conda-envs/environment-dev-py39.yml +++ b/conda-envs/environment-dev-py39.yml @@ -22,9 +22,8 @@ dependencies: - pytest>=3.0 - python-graphviz - python=3.9 -- recommonmark>=0.4 - scipy>1.4.1 -- sphinx-autobuild>=0.7 +- sphinx-copybutton - sphinx-notfound-page - sphinx-panels - sphinx>=1.5 diff --git a/conda-envs/windows-environment-dev-py38.yml b/conda-envs/windows-environment-dev-py38.yml index e8ac54d3b0..5250789968 100644 --- a/conda-envs/windows-environment-dev-py38.yml +++ b/conda-envs/windows-environment-dev-py38.yml @@ -29,8 +29,8 @@ dependencies: - pydata-sphinx-theme - pytest-cov>=2.5 - pytest>=3.0 -- recommonmark>=0.4 - sphinx-autobuild>=0.7 +- sphinx-copybutton - sphinx-notfound-page - sphinx-panels - sphinx>=1.5 diff --git a/docs/logos/sponsors/numfocus.png b/docs/logos/sponsors/numfocus.png new file mode 100644 index 0000000000..adf2de2257 Binary files /dev/null and b/docs/logos/sponsors/numfocus.png differ diff --git a/docs/pymc-labs-logo.png b/docs/logos/sponsors/pymc-labs.png similarity index 100% rename from docs/pymc-labs-logo.png rename to docs/logos/sponsors/pymc-labs.png diff --git a/docs/pymc_logo.jpg b/docs/pymc_logo.jpg deleted file mode 100644 index 28dcdfc437..0000000000 Binary files a/docs/pymc_logo.jpg and /dev/null differ diff --git a/docs/source/_templates/custom-class-template.rst b/docs/source/_templates/custom-class-template.rst new file mode 100644 index 0000000000..d4fd5208b6 --- /dev/null +++ b/docs/source/_templates/custom-class-template.rst @@ -0,0 +1,5 @@ +{{ fullname | escape | underline}} + +.. currentmodule:: {{ module }} + +.. autoclass:: {{ objname }} diff --git a/docs/source/_templates/custom-function-template.rst b/docs/source/_templates/custom-function-template.rst new file mode 100644 index 0000000000..29a8f06c55 --- /dev/null +++ b/docs/source/_templates/custom-function-template.rst @@ -0,0 +1,5 @@ +{{ fullname | escape | underline}} + +.. currentmodule:: {{ module }} + +.. autofunction:: {{ objname }} diff --git a/docs/source/_templates/custom-module-template.rst b/docs/source/_templates/custom-module-template.rst new file mode 100644 index 0000000000..a3260449a3 --- /dev/null +++ b/docs/source/_templates/custom-module-template.rst @@ -0,0 +1,69 @@ +{{ fullname | escape | underline}} + +.. automodule:: {{ fullname }} + + {% block attributes %} + {% if attributes %} + .. rubric:: {{ _('Module Attributes') }} + + .. autosummary:: + :toctree: + {% for item in attributes %} + {{ item }} + {%- endfor %} + {% endif %} + {% endblock %} + + {% block functions %} + {% if functions %} + .. rubric:: {{ _('Functions') }} + + .. autosummary:: + :toctree: + :template: custom-function-template.rst + {% for item in functions %} + {{ item }} + {%- endfor %} + {% endif %} + {% endblock %} + + {% block classes %} + {% if classes %} + .. rubric:: {{ _('Classes') }} + + .. autosummary:: + :toctree: + :template: custom-class-template.rst + {% for item in classes %} + {{ item }} + {%- endfor %} + {% endif %} + {% endblock %} + + {% block exceptions %} + {% if exceptions %} + .. rubric:: {{ _('Exceptions') }} + + .. autosummary:: + :toctree: + {% for item in exceptions %} + {{ item }} + {%- endfor %} + {% endif %} + {% endblock %} + +{% block modules %} +{% if modules %} +.. rubric:: Modules + +.. autosummary:: + :toctree: + :template: custom-module-template.rst + :recursive: +{% for item in modules %} + {% if "tests" not in item %} + {{ item }} + {% endif %} +{%- endfor %} +{% endif %} +{% endblock %} diff --git a/docs/source/_templates/footer.html b/docs/source/_templates/footer.html new file mode 100644 index 0000000000..93083ce2cc --- /dev/null +++ b/docs/source/_templates/footer.html @@ -0,0 +1,9 @@ + diff --git a/docs/source/_templates/layout.html b/docs/source/_templates/layout.html index fbcc5b278e..0f4ea8c215 100644 --- a/docs/source/_templates/layout.html +++ b/docs/source/_templates/layout.html @@ -2,25 +2,25 @@ {% block docs_sidebar %} - {% if pagename != 'index' %} - {{ super() }} - {% endif %} +{% if pagename != 'index' %} +{{ super() }} +{% endif %} {% endblock %} {% block docs_toc %} - {% if pagename != 'index' %} - {{ super() }} - {% endif %} +{% if pagename != 'index' %} +{{ super() }} +{% endif %} {% endblock %} {% block docs_main %} - {% if pagename == 'index' %} -
- {% block body %} {% endblock %} -
- {% else %} - {{ super() }} - {% endif %} +{% if pagename == 'index' %} +
+ {% block body %} {% endblock %} +
+{% else %} +{{ super() }} +{% endif %} {% endblock %} diff --git a/docs/source/about.rst b/docs/source/about.rst index 03aa510b0a..6a9669c59f 100644 --- a/docs/source/about.rst +++ b/docs/source/about.rst @@ -1,8 +1,3 @@ -:orphan: - -.. - _href from docs/source/index.rst - .. _about: ********** diff --git a/docs/source/api.rst b/docs/source/api.rst index d53175bdfc..c48abb6c1b 100644 --- a/docs/source/api.rst +++ b/docs/source/api.rst @@ -1,36 +1,10 @@ -:orphan: - -.. - _"api" is referenced in html_theme_options docs/source/conf.py - -.. _api: - ************* API Reference ************* -.. toctree:: - :maxdepth: 2 - - api/distributions - api/bounds - api/inference - api/glm - api/gp - api/plots - api/stats - api/backends - api/math - api/data - api/model - api/model_graph - api/variables - api/shape_utils - api/ode - -Indices and tables -=================== +.. autosummary:: + :toctree: api + :template: custom-module-template.rst + :recursive: -* :ref:`genindex` -* :ref:`modindex` -* :ref:`search` + pymc diff --git a/docs/source/api/backends.rst b/docs/source/api/backends.rst deleted file mode 100644 index 89a9918efb..0000000000 --- a/docs/source/api/backends.rst +++ /dev/null @@ -1,24 +0,0 @@ -******** -Backends -******** - -.. currentmodule:: pymc.backends - -.. automodule:: pymc.backends - :members: - -ndarray -^^^^^^^ - -.. currentmodule:: pymc.backends.ndarray - -.. automodule:: pymc.backends.ndarray - :members: - -tracetab -^^^^^^^^ - -.. currentmodule:: pymc.backends.tracetab - -.. automodule:: pymc.backends.tracetab - :members: diff --git a/docs/source/api/bounds.rst b/docs/source/api/bounds.rst deleted file mode 100644 index 7db2ade609..0000000000 --- a/docs/source/api/bounds.rst +++ /dev/null @@ -1,57 +0,0 @@ -================= -Bounded Variables -================= - -PyMC includes the construct :class:`~pymc.distributions.bound.Bound` for -placing constraints on existing probability distributions. It modifies a given -distribution to take values only within a specified interval. - -Some types of variables require constraints. For instance, it doesn't make -sense for a standard deviation to have a negative value, so something like a -Normal prior on a parameter that represents a standard deviation would be -inappropriate. PyMC includes distributions that have positive support, such -as :class:`~pymc.distributions.continuous.Gamma` or -:class:`~pymc.distributions.continuous.Exponential`. PyMC also includes -several bounded distributions, such as -:class:`~pymc.distributions.continuous.Uniform`, -:class:`~pymc.distributions.continuous.HalfNormal`, and -:class:`~pymc.distributions.continuous.HalfCauchy`, that are restricted to a -specific domain. - -All univariate distributions in PyMC can be given bounds. The distribution of -a continuous variable that has been bounded is automatically transformed into -an unnormalized distribution whose domain is unconstrained. The transformation -improves the efficiency of sampling and variational inference algorithms. - -Usage -##### - -For example, one may have prior information that suggests that the value of a -parameter representing a standard deviation is near one. One could use a -Normal distribution while constraining the support to be positive. The -specification of a bounded distribution should go within the model block:: - - import pymc as pm - - with pm.Model() as model: - norm = Normal.dist(mu=1.0, sigma=3.0) - x = Bound('x', norm, lower=0.0) - -Caveats -####### - -* Bounds cannot be given to variables that are ``observed``. To model - truncated data, use a :func:`~pymc.model.Potential` in combination with a cumulative - probability function. See `this example notebook `_. - -* The automatic transformation applied to continuous distributions results in - an unnormalized probability distribution. This doesn't effect inference - algorithms but may complicate some model comparison procedures. - -Bounded Variable API -#################### - - -.. currentmodule:: pymc.distributions.bound -.. automodule:: pymc.distributions.bound - :members: diff --git a/docs/source/api/data.rst b/docs/source/api/data.rst deleted file mode 100644 index 6b1971e9cb..0000000000 --- a/docs/source/api/data.rst +++ /dev/null @@ -1,8 +0,0 @@ -**** -Data -**** - -.. currentmodule:: pymc.data - -.. automodule:: pymc.data - :members: diff --git a/docs/source/api/distributions.rst b/docs/source/api/distributions.rst deleted file mode 100644 index 60bb36aa36..0000000000 --- a/docs/source/api/distributions.rst +++ /dev/null @@ -1,14 +0,0 @@ -************* -Distributions -************* - -.. toctree:: - - distributions/continuous - distributions/discrete - distributions/multivariate - distributions/mixture - distributions/simulator - distributions/timeseries - distributions/transforms - distributions/utilities diff --git a/docs/source/api/distributions/continuous.rst b/docs/source/api/distributions/continuous.rst deleted file mode 100644 index a6d4d99507..0000000000 --- a/docs/source/api/distributions/continuous.rst +++ /dev/null @@ -1,42 +0,0 @@ -********** -Continuous -********** - -.. currentmodule:: pymc.distributions.continuous -.. autosummary:: - - Uniform - Flat - HalfFlat - Normal - TruncatedNormal - HalfNormal - SkewNormal - Beta - Kumaraswamy - Exponential - Laplace - AsymmetricLaplace - StudentT - HalfStudentT - Cauchy - HalfCauchy - Gamma - InverseGamma - Weibull - LogNormal - ChiSquared - Wald - Pareto - ExGaussian - VonMises - Triangular - Gumbel - Rice - Logistic - LogitNormal - Interpolated - PolyaGamma - -.. automodule:: pymc.distributions.continuous - :members: diff --git a/docs/source/api/distributions/discrete.rst b/docs/source/api/distributions/discrete.rst deleted file mode 100644 index 1d10c592b7..0000000000 --- a/docs/source/api/distributions/discrete.rst +++ /dev/null @@ -1,26 +0,0 @@ -******** -Discrete -******** - -.. currentmodule:: pymc.distributions.discrete -.. autosummary:: - - Binomial - ZeroInflatedBinomial - BetaBinomial - Bernoulli - Poisson - ZeroInflatedPoisson - NegativeBinomial - ZeroInflatedNegativeBinomial - DiscreteUniform - Geometric - HyperGeometric - Categorical - DiscreteWeibull - Constant - OrderedLogistic - OrderedProbit - -.. automodule:: pymc.distributions.discrete - :members: diff --git a/docs/source/api/distributions/mixture.rst b/docs/source/api/distributions/mixture.rst deleted file mode 100644 index 9260123dad..0000000000 --- a/docs/source/api/distributions/mixture.rst +++ /dev/null @@ -1,12 +0,0 @@ -******* -Mixture -******* - -.. currentmodule:: pymc.distributions.mixture -.. autosummary:: - Mixture - NormalMixture - MixtureSameFamily - -.. automodule:: pymc.distributions.mixture - :members: diff --git a/docs/source/api/distributions/multivariate.rst b/docs/source/api/distributions/multivariate.rst deleted file mode 100644 index 7c3f5c9861..0000000000 --- a/docs/source/api/distributions/multivariate.rst +++ /dev/null @@ -1,22 +0,0 @@ -************ -Multivariate -************ - -.. currentmodule:: pymc.distributions.multivariate -.. autosummary:: - - MvNormal - MatrixNormal - KroneckerNormal - MvStudentT - Wishart - LKJCholeskyCov - LKJCorr - Multinomial - OrderedMultinomial - Dirichlet - DirichletMultinomial - CAR - -.. automodule:: pymc.distributions.multivariate - :members: diff --git a/docs/source/api/distributions/simulator.rst b/docs/source/api/distributions/simulator.rst deleted file mode 100644 index ed03609e01..0000000000 --- a/docs/source/api/distributions/simulator.rst +++ /dev/null @@ -1,11 +0,0 @@ -********** -Simulator -********** - -.. currentmodule:: pymc.distributions.simulator -.. autosummary:: - - Simulator - -.. automodule:: pymc.distributions.simulator - :members: diff --git a/docs/source/api/distributions/timeseries.rst b/docs/source/api/distributions/timeseries.rst deleted file mode 100644 index 44c0bb8454..0000000000 --- a/docs/source/api/distributions/timeseries.rst +++ /dev/null @@ -1,16 +0,0 @@ -********** -Timeseries -********** - -.. currentmodule:: pymc.distributions.timeseries -.. autosummary:: - AR1 - AR - GaussianRandomWalk - GARCH11 - EulerMaruyama - MvGaussianRandomWalk - MvStudentTRandomWalk - -.. automodule:: pymc.distributions.timeseries - :members: diff --git a/docs/source/api/distributions/transforms.rst b/docs/source/api/distributions/transforms.rst deleted file mode 100644 index 1a8d71341e..0000000000 --- a/docs/source/api/distributions/transforms.rst +++ /dev/null @@ -1,131 +0,0 @@ -**************************************************************** -Transformations of a random variable from one space to another. -**************************************************************** - -Note that for convenience these entities can be addressed as -``pm.transforms.``\ *X* for any name *X*, although they are actually -implemented as ``pm.distributions.transforms.``\*X*. - -.. currentmodule:: pymc.distributions.transforms - - -.. contents :: - -.. - .. autosummary:: - - transform - stick_breaking - logodds - interval - log_exp_m1 - lowerbound - upperbound - ordered - log - sum_to_1 - circular - CholeskyCovPacked - Chain - - - -Transform Instances -~~~~~~~~~~~~~~~~~~~ - -Transform instances are the entities that should be used in the -``transform`` parameter to a random variable constructor. These are -initialized instances of the Transform Classes, which are described -below. - -.. glossary:: - -``stick_breaking`` - Instantiation of :class:`~pymc.distributions.transforms.StickBreaking` - :class:`~pymc.distributions.transforms.Transform` class for use in the ``transform`` - argument of a random variable. - -``logodds`` - Instantiation of - :class:`~pymc.distributions.transforms.LogOdds` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``interval`` - Alias of - :class:`~pymc.distributions.transforms.Interval` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``log_exp_m1`` - Instantiation of - :class:`~pymc.distributions.transforms.LogExpM1` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``lowerbound`` - Alias of - :class:`~pymc.distributions.transforms.LowerBound` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``upperbound`` - Alias of - :class:`~pymc.distributions.transforms.UpperBound` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``ordered`` - Instantiation of - :class:`~pymc.distributions.transforms.Ordered` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -``log`` - Instantiation of - :class:`~pymc.distributions.transforms.Log` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - - -``sum_to_1`` - Instantiation of - :class:`~pymc.distributions.transforms.SumTo1` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - - -``circular`` - Instantiation of - :class:`~pymc.distributions.transforms.Circular` :class:`~pymc.distributions.transforms.Transform` class - for use in the ``transform`` argument of a random variable. - -Transform Base Classes -~~~~~~~~~~~~~~~~~~~~~~ - -Typically the programmer will not use these directly. - -.. autoclass:: Transform - :members: - - -Transform Composition Classes -~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. autoclass:: Chain - :members: -.. autoclass:: CholeskyCovPacked - :members: - - -Specific Transform Classes -~~~~~~~~~~~~~~~~~~~~~~~~~~ - -.. autoclass:: Log - :members: -.. autoclass:: LogExpM1 - :members: -.. autoclass:: LogOdds - :members: -.. autoclass:: Interval - :members: -.. autoclass:: Ordered - :members: -.. autoclass:: SumTo1 - :members: -.. autoclass:: StickBreaking - :members: -.. autoclass:: Circular - :members: diff --git a/docs/source/api/distributions/utilities.rst b/docs/source/api/distributions/utilities.rst deleted file mode 100644 index 9e1be98faf..0000000000 --- a/docs/source/api/distributions/utilities.rst +++ /dev/null @@ -1,20 +0,0 @@ -******************************************* -Distribution utility classes and functions -******************************************* - -.. currentmodule:: pymc.distributions -.. autosummary:: - - Distribution - Discrete - Continuous - NoDistribution - DensityDist - - -.. autoclass:: Distribution -.. autoclass:: Discrete -.. autoclass:: Continuous -.. autoclass:: NoDistribution -.. autoclass:: DensityDist - :members: diff --git a/docs/source/api/glm.rst b/docs/source/api/glm.rst deleted file mode 100644 index f3dcb307d3..0000000000 --- a/docs/source/api/glm.rst +++ /dev/null @@ -1,10 +0,0 @@ -************************* -Generalized Linear Models -************************* - -.. currentmodule:: pymc.glm.linear - -Generalized Linear Models are delegated to the -`Bambi `_. -library, a high-level Bayesian model-building -interface built on top of the PyMC. diff --git a/docs/source/api/gp.rst b/docs/source/api/gp.rst deleted file mode 100644 index 284e83144f..0000000000 --- a/docs/source/api/gp.rst +++ /dev/null @@ -1,10 +0,0 @@ -Gaussian Processes API ----------------------- - -.. currentmodule:: pymc.gp.gp - -.. toctree:: - - gp/implementations - gp/mean - gp/cov diff --git a/docs/source/api/gp/cov.rst b/docs/source/api/gp/cov.rst deleted file mode 100644 index 215f8a32e8..0000000000 --- a/docs/source/api/gp/cov.rst +++ /dev/null @@ -1,24 +0,0 @@ -******************** -Covariance Functions -******************** - -.. currentmodule:: pymc.gp.cov -.. autosummary:: - Constant - WhiteNoise - ExpQuad - RatQuad - Matern32 - Matern52 - Exponential - Cosine - Periodic - Linear - Polynomial - WarpedInput - Gibbs - Kron - Coregion - -.. automodule:: pymc.gp.cov - :members: diff --git a/docs/source/api/gp/implementations.rst b/docs/source/api/gp/implementations.rst deleted file mode 100644 index 8166f19cca..0000000000 --- a/docs/source/api/gp/implementations.rst +++ /dev/null @@ -1,15 +0,0 @@ -*************** -Implementations -*************** - -.. currentmodule:: pymc.gp.gp -.. autosummary:: - Latent - Marginal - LatentKron - MarginalKron - MarginalSparse - TP - -.. automodule:: pymc.gp.gp - :members: diff --git a/docs/source/api/gp/mean.rst b/docs/source/api/gp/mean.rst deleted file mode 100644 index 9ff7d921fe..0000000000 --- a/docs/source/api/gp/mean.rst +++ /dev/null @@ -1,13 +0,0 @@ -************** -Mean Functions -************** - -.. currentmodule:: pymc.gp.mean -.. autosummary:: - - Zero - Constant - Linear - -.. automodule:: pymc.gp.mean - :members: diff --git a/docs/source/api/inference.rst b/docs/source/api/inference.rst deleted file mode 100644 index c5348bb5b2..0000000000 --- a/docs/source/api/inference.rst +++ /dev/null @@ -1,113 +0,0 @@ -********* -Inference -********* - -Sampling --------- - -.. currentmodule:: pymc.sampling - -.. automodule:: pymc.sampling - :members: - - -Step-methods -^^^^^^^^^^^^ - -.. currentmodule:: pymc.sampling - -.. autofunction:: pymc.sampling.assign_step_methods - - -NUTS -~~~~ - -.. currentmodule:: pymc.step_methods.hmc.nuts - -.. automodule:: pymc.step_methods.hmc.nuts - :members: - -Metropolis -~~~~~~~~~~ - -.. currentmodule:: pymc.step_methods.metropolis - -.. automodule:: pymc.step_methods.metropolis - :members: - -Slice -~~~~~ - -.. currentmodule:: pymc.step_methods.slicer - -.. automodule:: pymc.step_methods.slicer - :members: - -Hamiltonian Monte Carlo -~~~~~~~~~~~~~~~~~~~~~~~ - -.. currentmodule:: pymc.step_methods.hmc.hmc - -.. autoclass:: pymc.step_methods.hmc.hmc.HamiltonianMC - :members: - -MultiTrace -^^^^^^^^^^ - -.. currentmodule:: pymc.backends.base -.. autoclass:: pymc.backends.base.MultiTrace - :members: - -.. autoclass:: pymc.backends.base.BaseTrace - -Variational Inference ---------------------- - -OPVI -^^^^ - -.. currentmodule:: pymc.variational.opvi - -.. automodule:: pymc.variational.opvi - :members: - -VI Inference API -^^^^^^^^^^^^^^^^ - -.. currentmodule:: pymc.variational.inference - -.. automodule:: pymc.variational.inference - :members: - -Approximations -^^^^^^^^^^^^^^ - -.. currentmodule:: pymc.variational.approximations - -.. automodule:: pymc.variational.approximations - :members: - -Operators -^^^^^^^^^ - -.. currentmodule:: pymc.variational.operators - -.. automodule:: pymc.variational.operators - :members: - - -Sequential Monte Carlo ----------------------- - -.. currentmodule:: pymc.smc.sample_smc - -.. automodule:: pymc.smc.sample_smc - :members: - -Kernels -^^^^^^^ - -.. currentmodule:: pymc.smc.smc - -.. automodule:: pymc.smc.smc - :members: diff --git a/docs/source/api/math.rst b/docs/source/api/math.rst deleted file mode 100644 index 3f7ceeb99c..0000000000 --- a/docs/source/api/math.rst +++ /dev/null @@ -1,63 +0,0 @@ -==== -Math -==== - -This submodule contains various mathematical functions. Most of them are imported directly -from aesara.tensor (see there for more details). Doing any kind of math with PyMC random -variables, or defining custom likelihoods or priors requires you to use these Aesara -expressions rather than NumPy or Python code. - -.. currentmodule:: pymc.math - -.. autosummary:: - dot - constant - flatten - zeros_like - ones_like - stack - concatenate - sum - prod - lt - gt - le - ge - eq - neq - switch - clip - where - and_ - or_ - abs_ - exp - log - cos - sin - tan - cosh - sinh - tanh - sqr - sqrt - erf - erfinv - dot - maximum - minimum - sgn - ceil - floor - det - matrix_inverse - extract_diag - matrix_dot - trace - sigmoid - logsumexp - invlogit - logit - -.. automodule:: pymc.math - :members: diff --git a/docs/source/api/model.rst b/docs/source/api/model.rst deleted file mode 100644 index 13da8f6f55..0000000000 --- a/docs/source/api/model.rst +++ /dev/null @@ -1,6 +0,0 @@ -Model ------ - -.. currentmodule:: pymc.model -.. automodule:: pymc.model - :members: diff --git a/docs/source/api/model_graph.rst b/docs/source/api/model_graph.rst deleted file mode 100644 index de9b9f223b..0000000000 --- a/docs/source/api/model_graph.rst +++ /dev/null @@ -1,6 +0,0 @@ -Graphing Models ---------------- - -.. currentmodule:: pymc.model_graph -.. automodule:: pymc.model_graph - :members: diff --git a/docs/source/api/ode.rst b/docs/source/api/ode.rst deleted file mode 100644 index bf61bc2ada..0000000000 --- a/docs/source/api/ode.rst +++ /dev/null @@ -1,12 +0,0 @@ -==== -ODE -==== - -This submodule contains tools used to perform inference on ordinary differential equations. - -.. currentmodule:: pymc.ode - -.. autosummary:: - -.. automodule:: pymc.ode - :members: DifferentialEquation diff --git a/docs/source/api/plots.rst b/docs/source/api/plots.rst deleted file mode 100644 index fd7fb8220b..0000000000 --- a/docs/source/api/plots.rst +++ /dev/null @@ -1,13 +0,0 @@ -***** -Plots -***** - -.. currentmodule:: pymc.plots - -Plots are delegated to the -`ArviZ `_. -library, a general purpose library for -"exploratory analysis of Bayesian models". - -Functions from the `arviz.plots` module are available through ``pymc.`` or ``pymc.plots.``, -but for their API documentation please refer to the :ref:`ArviZ documentation `. diff --git a/docs/source/api/shape_utils.rst b/docs/source/api/shape_utils.rst deleted file mode 100644 index f85f402405..0000000000 --- a/docs/source/api/shape_utils.rst +++ /dev/null @@ -1,23 +0,0 @@ -*********** -shape_utils -*********** - -This submodule contains various functions that apply numpy's broadcasting rules to shape tuples, and also to samples drawn from probability distributions. - -The main challenge when broadcasting samples drawn from a generative model, is that each random variate has a core shape. When we draw many i.i.d samples from a given RV, for example if we ask for `size_tuple` i.i.d draws, the result usually is a `size_tuple + RV_core_shape`. In the generative model's hierarchy, the downstream RVs that are conditionally dependent on our above sampled values, will get an array with a shape that is incosistent with the core shape they expect to see for their parameters. This is a problem sometimes because it prevents regular broadcasting in complex hierachical models, and thus make prior and posterior predictive sampling difficult. - -This module introduces functions that are made aware of the requested `size_tuple` of i.i.d samples, and does the broadcasting on the core shapes, transparently ignoring or moving the i.i.d `size_tuple` prepended axes around. - -.. currentmodule:: pymc.distributions.shape_utils - -.. autosummary:: - - to_tuple - shapes_broadcasting - broadcast_dist_samples_shape - get_broadcastable_dist_samples - broadcast_distribution_samples - broadcast_dist_samples_to - -.. automodule:: pymc.distributions.shape_utils - :members: diff --git a/docs/source/api/stats.rst b/docs/source/api/stats.rst deleted file mode 100644 index bafa5cca56..0000000000 --- a/docs/source/api/stats.rst +++ /dev/null @@ -1,13 +0,0 @@ -***** -Stats -***** - -.. currentmodule:: pymc.stats - -Statistics and diagnostics are delegated to the -`ArviZ `_. -library, a general purpose library for -"exploratory analysis of Bayesian models". - -Functions from the `arviz.stats` module are available through ``pymc.`` or ``pymc.stats.``, -but for their API documentation please refer to the :ref:`ArviZ documentation `. diff --git a/docs/source/api/variables.rst b/docs/source/api/variables.rst deleted file mode 100644 index 78d9ca7cd0..0000000000 --- a/docs/source/api/variables.rst +++ /dev/null @@ -1,10 +0,0 @@ -Random Variables ----------------- - -.. currentmodule:: pymc.model - -The normal PyMC programmer will typically not need to interact with these classes, except possibly when debugging. Otherwise they are primarily of interest to developers. - - -.. autoclass:: ValueGradFunction - :members: diff --git a/docs/source/community.md b/docs/source/community.md new file mode 100644 index 0000000000..612b90accb --- /dev/null +++ b/docs/source/community.md @@ -0,0 +1,36 @@ +# Community + +:::{list-table} +:header-rows: 0 +:widths: 10 150 + +* - {fa}`discourse,fa-2x,style=fab` + - [Discourse Forum](https://discourse.pymc.io/) + + The PyMC discourse forum is a great place to ask general questions about Bayesian statistics, or more specific ones about PyMC usage. +* - {fa}`meetup,fa-2x,style=fab` + - Conferences + + PyMC talks have been given at a number of conferences, including [PyCon](https://us.pycon.org/), + [PyData](https://pydata.org/events/), and [ODSC](https://odsc.com/) events. +* - {fa}`python,fa-2x,style=fab` + - [Meetup Groups](https://www.meetup.com/) + + Many areas have an local Bayesian, PyData, or Stan meetup. +::: + +## Videos + +:::{list-table} +:header-rows: 0 +:widths: 10 150 + +* - {fa}`youtube,fa-2x,style=fab` + - [YouTube Playlist](https://www.youtube.com/playlist?list=PL1Ma_1DBbE82OVW8Fz_6Ts1oOeyOAiovy) + + There is an actively curated playlist of PyMC talks on YouTube. +* - {fa}`youtube,fa-2x,style=fab` + - [Advance Bayesian Modelling with PyMC](https://github.com/junpenglao/advance-bayesian-modelling-with-PyMC) + + A two days advance workshop in May 2018 @CEAi in the Czech Republic. +::: diff --git a/docs/source/conf.py b/docs/source/conf.py index c899b9a441..a314261342 100755 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -19,14 +19,17 @@ import os import sys +from sphinx.ext.autosummary import generate # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. sys.path.insert(0, os.path.abspath(os.path.join("..", ".."))) -sys.path.insert(0, os.path.abspath("sphinxext")) import pymc # isort:skip +sys.path.insert(0, os.path.abspath("sphinx_autosummary")) +import custom_generate # isort:skip + # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. @@ -47,11 +50,12 @@ "IPython.sphinxext.ipython_directive", "sphinx.ext.autosectionlabel", "sphinx.ext.napoleon", - "gallery_generator", "myst_nb", "sphinx_design", "sphinx_panels", "notfound.extension", + "sphinx_design", + "sphinx_copybutton", ] # Don't auto-generate summary for class members. @@ -116,7 +120,7 @@ # myst and panels config jupyter_execute_notebooks = "off" -myst_heading_anchors = 3 +myst_heading_anchors = 2 myst_enable_extensions = [ "colon_fence", ] @@ -154,6 +158,7 @@ "arviz": ("https://arviz-devs.github.io/arviz/", None), "aesara": ("https://aesara.readthedocs.io/en/latest/", None), "numpy": ("https://numpy.org/doc/stable/", None), + "nb": ("https://pymc-examples.readthedocs.io/en/latest/", None), } @@ -180,12 +185,19 @@ "url": "https://twitter.com/pymc_devs", "icon": "fab fa-twitter-square", }, + { + "name": "Discourse", + "url": "https://discourse.pymc.io", + "icon": "fab fa-discourse", + }, ], "show_prev_next": False, + "navbar_align": "left", "navbar_start": ["navbar-logo", "navbar-version"], "navbar_end": ["search-field.html", "navbar-icon-links.html"], "search_bar_text": "Search...", "use_edit_page_button": False, # TODO: see how to skip of fix for generated pages + "externalrefs": True, "google_analytics_id": "UA-176578023-1", } html_context = { @@ -194,7 +206,12 @@ "github_version": "main", "doc_path": "docs/source/", } -html_sidebars = {"learn": [], "**": ["sidebar-nav-bs.html", "sidebar-ethical-ads.html"]} +# this controls which sidebar sections are available in which pages. [] removes the left sidebar +html_sidebars = { + "learn": [], + "installation": [], + "**": ["sidebar-nav-bs.html", "sidebar-ethical-ads.html"], +} # Add any paths that contain custom themes here, relative to this directory. # html_theme_path = [] @@ -208,7 +225,7 @@ # The name of an image file (relative to this directory) to place at the top # of the sidebar. -html_logo = "../pymc_logo.jpg" +html_logo = "../logos/PyMC.jpg" # The name of an image file (within the static path) to use as favicon of the # docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32 @@ -365,3 +382,13 @@ # def setup(app): # app.add_css_file("https://cdn.jsdelivr.net/npm/semantic-ui@2.4.2/dist/semantic.min.css") # app.add_css_file("default.css") + +# Autosummary +autosummary_generate = True + +## Overwrite the autosummary generator function with custom one +generate.generate_autosummary_content = custom_generate.generate_autosummary_content + +# Autodoc +## Do not show docstring of parent class. +autodoc_inherit_docstrings = False diff --git a/docs/source/developer_guide.rst b/docs/source/contributing/developer_guide.rst similarity index 100% rename from docs/source/developer_guide.rst rename to docs/source/contributing/developer_guide.rst diff --git a/docs/source/developer_guide_implementing_distribution.md b/docs/source/contributing/developer_guide_implementing_distribution.md similarity index 100% rename from docs/source/developer_guide_implementing_distribution.md rename to docs/source/contributing/developer_guide_implementing_distribution.md diff --git a/docs/source/contributing/index.md b/docs/source/contributing/index.md new file mode 100644 index 0000000000..002764710e --- /dev/null +++ b/docs/source/contributing/index.md @@ -0,0 +1,34 @@ +# Contributing + +PyMC is an open source, collective effort. Find all the ways in which you can help make it better. + +## Help develop PyMC + +Learn about developing PyMC in our Developer's section. + +See open issues + +## Help improve the documentation + +:::{list-table} +:header-rows: 0 +:widths: 10 150 + +* - {fa}`discourse,fa-2x,style=fab` + - Beginners + +New to the open source space? Find a good beginner friendly documentation issue you can help with [here](https://github.com/pymc-devs/pymc/issues?q=is%3Aissue+is%3Aopen+label%3A%22beginner+friendly%22+label%3A%22docs%22) or [here](https://github.com/pymc-devs/pymc-examples/issues?q=is%3Aopen+label%3Adocs+label%3A%22good+first+issue%22). + +You will need to express your interest in the issue by commenting on it using your Github account, and you will need to use some beginner level Git to complete the Pull Request process, but don't worry! There are plenty of good [tutorials](https://guides.github.com/activities/hello-world/) out there, and PyMC reviewers are happy to help. +:::: + + +## Others +Issue triaging + +:::{toctree} +:hidden: + +developer_guide +developer_guide_implementing_distribution +::: diff --git a/docs/source/glossary.md b/docs/source/glossary.md index fe73454b84..460820e993 100644 --- a/docs/source/glossary.md +++ b/docs/source/glossary.md @@ -3,16 +3,7 @@ A glossary of common terms used throughout the PyMC documentation and examples. :::::{glossary} -:sorted: -[Term with external reference](https://www.youtube.com/watch?v=6dc7JgR8eI0) - Terms are defined within this glossary directive. The term id is defined as the non - indented line, and can be text alone (like {term}`second term`) or also include a link - to an external reference. - -Second term - Definitions can have as many lines as desired, and should be written in markdown. Definitions - can contain any markdown formatting for MyST to parse, this includes basic markdown like **bold** - as well as MyST directives and roles like {fa}`fort awesome,style=fab` + Functional Programming Functional programming is a programming style that prefers the use of basic functions with explicit and distinct inputs and outputs. This contrasts with functions or methods that depend on variables that are not explicitly passed as an input (such as accessing `self.variable` inside a method) or that alter the inputs or other state variables in-place, instead of returning new distinct variables as outputs. diff --git a/docs/source/Gaussian_Processes.rst b/docs/source/guides/Gaussian_Processes.rst similarity index 100% rename from docs/source/Gaussian_Processes.rst rename to docs/source/guides/Gaussian_Processes.rst diff --git a/docs/source/Probability_Distributions.rst b/docs/source/guides/Probability_Distributions.rst similarity index 100% rename from docs/source/Probability_Distributions.rst rename to docs/source/guides/Probability_Distributions.rst diff --git a/docs/source/index.md b/docs/source/index.md new file mode 100644 index 0000000000..f9cecbd087 --- /dev/null +++ b/docs/source/index.md @@ -0,0 +1,99 @@ +--- +sd_hide_title: true +--- + +# PyMC Documentation + +:::{card} +:img-top: https://raw.githubusercontent.com/pymc-devs/pymc/main/docs/logos/PyMC.jpg +:margin: 0 2 auto auto +:width: 50% +:text-align: center + ++++ +Probabilistic Programming in Python +::: + +:::{button-ref} learning +:color: primary +:shadow: + +Get started! +::: + + +:::{card} Announcements: library name change and launching PyMC 4.0! +:width: 75% +:margin: auto + +We have two major announcements that we're excited to share. First of all, a new name for our library: the PyMC3 library you know and love is now called PyMC. PyMC3 still exists, as a specific major release between PyMC2 and PyMC 4.0. Read more about the renaming and how to solve related issues you might experience from this update [here](). + +This ties into our second announcement, which is that we are hereby launching the newest version of PyMC: PyMC 4.0! Read more about this new release [here](). +::: + +--- + +# Main Features & Benefits + +::::{grid} 1 2 2 2 +:::{grid-item-card} Friendly modelling API +PyMC allows you to write down models using an intuitive syntax to describe a data generating process. +::: +:::{grid-item-card} Cutting edge algorithms and model building blocks +Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate inference — including minibatch-ADVI for scaling to large datasets — or using Gaussian processes to build Bayesian nonparametric models. +::: +:::: + +# Support + +PyMC is a non-profit project under NumFOCUS umbrella. If you value PyMC and want to support its development, consider donating to the project. + +:::{button-link} https://numfocus.org/donate-to-pymc3 +:color: secondary +:shadow: + +Donate +::: + +## Our sponsors + +::::{grid} 2 4 4 4 + +:::{grid-item} +::: + +:::{grid-item-card} +:img-background: https://www.numfocus.org/wp-content/uploads/2017/07/NumFocus_LRG.png +:link: https://numfocus.org/ +::: + +:::{grid-item-card} +:img-background: https://github.com/pymc-devs/pymc/raw/main/docs/pymc-labs-logo.png +:link: https://www.pymc-labs.io/ +::: + +:::{grid-item} +::: + +:::: + +# Citing PyMC + +Use this to cite the library: + +Salvatier J., Wiecki T.V., Fonnesbeck C. (2016) Probabilistic programming in Python using PyMC3. PeerJ Computer Science 2:e55 [DOI: 10.7717/peerj-cs.55.](https://doi.org/10.7717/peerj-cs.55) + +See [Google Scholar](https://scholar.google.de/scholar?oi=bibs&hl=en&authuser=1&cites=6936955228135731011) for a continuously updated list of papers citing PyMC3. + +:::{toctree} +:maxdepth: 1 +:hidden: + +installation +learning +api +developers +community +contributing/index +about +::: diff --git a/docs/source/index.rst b/docs/source/index.rst deleted file mode 100644 index 1ef2b4c258..0000000000 --- a/docs/source/index.rst +++ /dev/null @@ -1,159 +0,0 @@ -.. title:: PyMC Documentation - -.. raw:: html - -
-
-
- -
-

Friendly modelling API

-

PyMC allows you to write down models using an intuitive syntax to describe a data generating - process.

-

Cutting edge algorithms and model building blocks

-

Fit your model using gradient-based MCMC algorithms like NUTS, using ADVI for fast approximate - inference — including minibatch-ADVI for scaling to large datasets — or using - Gaussian processes to build Bayesian nonparametric models.

-
-
- -.. toctree:: - :maxdepth: 1 - :hidden: - - Tutorials - Examples - Books + Videos - API - Developer Guide - About PyMC - -.. code-block:: python - - import pymc as pm - - X = np.random.normal(size=100) - y = np.random.normal(X) * 1.2 - - with pm.Model() as linear_model: - weights = pm.Normal("weights", mu=0, sigma=1) - noise = pm.Gamma("noise", alpha=2, beta=1) - y_observed = pm.Normal( - "y_observed", - mu=X @ weights, - sigma=noise, - observed=y, - ) - - prior = pm.sample_prior_predictive() - posterior = pm.sample() - posterior_pred = pm.sample_posterior_predictive(posterior) - -.. raw:: html - -
-
-
- -
- -

Installation

- -
-
-

Via conda-forge:

- -.. code-block:: bash - - conda install -c conda-forge pymc - - -.. raw:: html - -

Latest (unstable):

- -.. code-block:: bash - - pip install git+https://github.com/pymc-devs/pymc - -.. raw:: html - -
-
-
- -
-

In-Depth Guides

-
- - -
-
Probability Distributions
-
PyMC includes a comprehensive set of pre-defined statistical distributions that can be used as model building blocks. -
-
- - - -
-
Gaussian Processes
-
Sometimes an unknown parameter or variable in a model is not a scalar value or a fixed-length vector, but a function. A Gaussian process (GP) can be used as a prior probability distribution whose support is over the space of continuous functions. PyMC provides rich support for defining and using GPs. -
-
- - - -
-
Variational Inference
-
Variational inference saves computational cost by turning a problem of integration into one of optimization. PyMC's variational API supports a number of cutting edge algorithms, as well as minibatch for scaling to large datasets. -
-
- - - -
-
PyMC and Aesara
-
Aesara is the library PyMC uses to construct probability distributions and then access the gradient in order to implement cutting edge inference algorithms. More advanced models may be built by understanding this layer. -
-
- - -
-
- -
-

License

-

PyMC is licensed under the Apache License, V2.

-
- -
-

Citing PyMC

-

Please choose from the following:

-
    -
  • DOIpaper Probabilistic programming in Python using PyMC3, Salvatier J., Wiecki T.V., Fonnesbeck C. (2016)
    • -
  • DOIzenodo A DOI for all versions.
    • -
  • DOIs for specific versions are shown on Zenodo and under Releases
    • -
-

See Google Scholar for a continuously updated list of papers citing PyMC.

-
- -
-

Support and sponsors

-

PyMC is a non-profit project under NumFOCUS umbrella. - If you value PyMC and want to support its development, consider - donating to the project or - read our support PyMC page. -

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-
diff --git a/docs/source/installation.md b/docs/source/installation.md new file mode 100644 index 0000000000..60ec17cc82 --- /dev/null +++ b/docs/source/installation.md @@ -0,0 +1,13 @@ +# Installation + +To install PyMC, select the operating system where you want to perform the installation. + + +## Linux +[Linux installation guide](https://github.com/pymc-devs/pymc/wiki/Installation-Guide-(Linux)) + +## MacOS +[MacOS installation guide](https://github.com/pymc-devs/pymc/wiki/Installation-Guide-(MacOS)) + +## Windows +[Windows installation guide](https://github.com/pymc-devs/pymc/wiki/Installation-Guide-(Windows)) diff --git a/docs/source/learn.md b/docs/source/learn.md deleted file mode 100644 index 8766060759..0000000000 --- a/docs/source/learn.md +++ /dev/null @@ -1,182 +0,0 @@ -# Learn Bayesian statistics - -## ...with others! - -:::{list-table} -:header-rows: 0 -:widths: 10 150 - -* - {fa}`discourse,fa-2x,style=fab` - - [Discourse Forum](https://discourse.pymc.io/) - - The PyMC discourse forum is a great place to ask general questions about Bayesian statistics, or more specific ones about PyMC usage. -* - {fa}`meetup,fa-2x,style=fab` - - Conferences - - PyMC talks have been given at a number of conferences, including [PyCon](https://us.pycon.org/), - [PyData](https://pydata.org/events/), and [ODSC](https://odsc.com/) events. -* - {fa}`python,fa-2x,style=fab` - - [Meetup Groups](https://www.meetup.com/) - - Many areas have an local Bayesian, PyData, or Stan meetup. -::: - -## ...with a video! - -:::{list-table} -:header-rows: 0 -:widths: 10 150 - -* - {fa}`youtube,fa-2x,style=fab` - - [YouTube Playlist](https://www.youtube.com/playlist?list=PL1Ma_1DBbE82OVW8Fz_6Ts1oOeyOAiovy) - - There is an actively curated playlist of PyMC talks on YouTube. -* - {fa}`youtube,fa-2x,style=fab` - - [Advance Bayesian Modelling with PyMC](https://github.com/junpenglao/advance-bayesian-modelling-with-PyMC) - - A two days advance workshop in May 2018 @CEAi in the Czech Republic. -::: - -## ...with a book! - -::::{panels} -:column: col-lg-4 col-md-4 - ---- -:img-top: https://camo.githubusercontent.com/4a0aca82ca82efab71747d00db30f3a68de98e82/687474703a2f2f692e696d6775722e636f6d2f36444b596250622e706e673f31 - -Bayesian Methods for Hackers - -*Cameron Davidson-Pilon* -^^^^^^^^ - -Fantastic book with many applied code examples. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][hackers source] - - [Github Repo][hackers source] -* - [{fa}`link`][hackers homepage] - - [Project Homepage][hackers homepage] -::: - ---- -:img-top: https://lh3.googleusercontent.com/qU5yWpiVSkujyCnRZhQo8cBUrW_3e_7Cx4jEs5yfpmMbEEuDnxTGOELhy2x7F7qkwFwQJ4pFYNszZhNpN1jCSdrdHsVUHtf1Mg6F8qwb3SQe1TDE=w1280 - -Doing Bayesian Data Analysis - -*John Kruschke* -^^^^^^^^ - -Principled introduction to Bayesian data analysis. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][dbda website] - - [Book Website][dbda website] -* - [{fa}`link`][dbda 1st ed nb] - - [PyMC notebooks for *first edition*][dbda 1st ed nb] -* - [{fa}`link`][dbda 2nd ed nb] - - [PyMC notebooks for *second edition*][dbda 2nd ed nb] -::: - ---- -:img-top: http://xcelab.net/rm/wp-content/uploads/2012/01/9781482253443-191x300.jpg - -Statistical Rethingking - -*Richard McElreath* -^^^^^^^^ - -A Bayesian Course with Examples in R and Stan. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][rethinking website] - - [Book Website][rethinking website] -* - [{fa}`link`][rethinking port] - - [PyMC port of the code][rethinking port] -::: - ---- -:img-top: https://raw.githubusercontent.com/aloctavodia/BAP/master/Cover.png - -Bayesian Analysis with Python - -*Osvaldo Martin* -^^^^^^^^ - -A great introductory book written by a maintainer of PyMC. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][bap website] - - [Book Website][bap website] -* - [{fa}`link`][bap code] - - [Code and errata in PyMC][bap code] -::: - ---- -:img-top: https://images-na.ssl-images-amazon.com/images/I/51K33XI2I8L._SX330_BO1,204,203,200_.jpg - -Bayesian Cognitive Modeling: A Practical Course - -*Michael Lee and Eric-Jan Wagenmakers* -^^^^^^^^ - -Focused on using Bayesian statistics in cognitive modeling. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][bcm website] - - [Book Website][bcm website] -* - [{fa}`link`][bcm code] - - [PyMC implementation][bcm code] -::: - ---- -:img-top: http://www.stat.columbia.edu/~gelman/book/bda_cover.png - -Bayesian Data Analysis - -*Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin* -^^^^^^^^ - -A comprehensive, standard, and wonderful textbook on Bayesian methods. - -:::{list-table} -:header-rows: 0 -:widths: 4 60 - -* - [{fa}`link`][bda3 website] - - [Book Website][bda3 website] -* - [{fa}`link`][bda3 port] - - [Examples and exercises implemented in PyMC][bda3 port] -::: - -:::: - - -[hackers source]: https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers -[hackers homepage]: http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/ -[dbda website]: https://sites.google.com/site/doingbayesiandataanalysis/home -[dbda 1st ed nb]: https://github.com/aloctavodia/Doing_bayesian_data_analysis -[dbda 2nd ed nb]: https://github.com/JWarmenhoven/DBDA-python -[rethinking website]: http://xcelab.net/rm/statistical-rethinking/ -[rethinking port]: https://github.com/pymc-devs/resources/tree/master/Rethinking -[bap website]: https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition -[bap code]: https://github.com/aloctavodia/BAP -[bcm website]: https://bayesmodels.com/ -[bcm code]: https://github.com/pymc-devs/resources/tree/master/BCM -[bda3 website]: https://www.stat.columbia.edu/~gelman/book/ -[bda3 port]: https://github.com/pymc-devs/resources/tree/master/BDA3 diff --git a/docs/source/learn/step1.md b/docs/source/learn/step1.md new file mode 100644 index 0000000000..236d3846df --- /dev/null +++ b/docs/source/learn/step1.md @@ -0,0 +1,6 @@ +# Step 1 + +Detailed explanation of step 1, which sections of the documentation are indicated +and which external references are recommended. i.e. to make the most of pymc3, you should +be familiar with Bayesian statistics. Here are some books whose code is available using pymc3 to +help you learn Bayesian statistics with pymc3. diff --git a/docs/source/learn/step2.md b/docs/source/learn/step2.md new file mode 100644 index 0000000000..b249cdf397 --- /dev/null +++ b/docs/source/learn/step2.md @@ -0,0 +1,28 @@ +# Step 2 + +Detailed explanation of step 2, which sections of the documentation are indicated +and which external references are recommended. + +::::{grid} 1 2 3 4 + +:::{grid-item} +{fas}`info-circle;fa-5x` + +{doc}`case_studies/multilevel_modeling` +::: +:::{grid-item} +{fas}`golf-ball;fa-5x` + +{doc}`case_studies/putting_workflow` +::: +:::{grid-item} +{fas}`book-open;fa-5x` + +{doc}`diagnostics_and_criticism/model_comparison` +::: +:::{grid-item} +{fas}`football-ball;fa-5x` + +{doc}`case_studies/rugby_analytics` +::: +:::: diff --git a/docs/source/learn/step3.md b/docs/source/learn/step3.md new file mode 100644 index 0000000000..78890e488a --- /dev/null +++ b/docs/source/learn/step3.md @@ -0,0 +1,3 @@ +# Step 3 + +More content diff --git a/docs/source/learning.md b/docs/source/learning.md new file mode 100644 index 0000000000..1c56c90f34 --- /dev/null +++ b/docs/source/learning.md @@ -0,0 +1,88 @@ +(learning)= +# Learning + +## Getting started + +Start here to get acquainted with the core concepts of Bayesian analysis and PyMC. The following resources only assume a very basic knowledge of code and statistics. + +::::{grid} 2 +:gutter: 4 + +:::{grid-item-card} Bayesian Methods for Hackers + +By Cameron Davidson-Pilon + +The "hacker" in the title means learn-as-you-code. This hands-on introduction teaches intuitive definitions of the Bayesian approach to statistics, worklflow and decision-making by applying them using PyMC. + +[Github repo](https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers) + +[Project homepage](http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/) +::: + +:::{grid-item-card} Bayesian Analysis with Python + +by Osvaldo Martin + +A great introductory book written by a maintainer of PyMC. It provides a hands-on introduction to the main concepts of Bayesian statistics using synthetic and real data sets. Mastering the concepts in this book is a great foundation to pursue more advanced knowledge. + +[Book website](https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition) + +[Code and errata in PyMC](https://github.com/aloctavodia/BAP) +::: + +:::{grid-item-card} Getting started with PyMC + +The {doc}`nb:getting_started` notebook in our documentation shows the PyMC 4.0 code in action +::: + +:::{grid-item-card} Glossary + +PyMC's own {doc}`glossary` defines many core terms and provides useful references. +::: +:::: + +--- + +## Using PyMC + +(the path in pymc-examples repo excluding the `examples` folder, or using manual anchors if we decide to create them). + +::::{grid} 2 +:gutter: 4 + +:::{grid-item-card} TODO + + +TODO +::: + +:::: + +--- +## Diving deeper + +Links to intermediate notebooks. {doc}`More about step 3... ` + +::::{grid} 2 +:gutter: 4 + +:::{grid-item-card} TODO + + +TODO +::: + +:::{grid-item-card} TODO + + +TODO +::: +:::: + +:::{toctree} +:hidden: + +learn/step1 +learn/step2 +learn/step3 +::: diff --git a/docs/source/pymc-examples b/docs/source/pymc-examples deleted file mode 160000 index 04d973bf0a..0000000000 --- a/docs/source/pymc-examples +++ /dev/null @@ -1 +0,0 @@ -Subproject commit 04d973bf0ab6fb632b03dcb2897be291f734cb1a diff --git a/docs/source/semantic_sphinx/layout.html b/docs/source/semantic_sphinx/layout.html deleted file mode 100644 index 778952c41d..0000000000 --- a/docs/source/semantic_sphinx/layout.html +++ /dev/null @@ -1,159 +0,0 @@ -{% extends "basic/layout.html" %} - - -{% set script_files = script_files + [ -'_static/highlight.min.js', -'_static/semantic.min.js', -] -%} -{% if pagename == 'nb_examples/index' or pagename == 'nb_tutorials/index' %} -{% set script_files = script_files + [ -'_static/gallery.js', -] -%} -{% endif %} - -{%- block extrahead %} - - - - - - -{% if pagename == 'nb_tutorials/index' %} - -{# this is used when loading the gallery index using $.ajax fails, -such as on Chrome for documents on localhost #} - -{% endif %} -{% if pagename == 'nb_examples/index' %} - -{# this is used when loading the gallery index using $.ajax fails, -such as on Chrome for documents on localhost #} - -{% endif %} -{% endblock %} - -{# Silence the sidebar's, relbar's #} -{% block header %}{% endblock %} -{% block relbar1 %}{% endblock %} -{% block relbar2 %}{% endblock %} -{% block sidebarsourcelink %}{% endblock %} - -{%- block content %} -
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- // The function takes a result array [filename, title, anchor, descr, score] - // and returns the new score. - /* - score: function(result) { - return result[4]; - }, - */ - - // query matches the full name of an object - objNameMatch: 11, - // or matches in the last dotted part of the object name - objPartialMatch: 6, - // Additive scores depending on the priority of the object - objPrio: { - 0: 15, // used to be importantResults - 1: 5, // used to be objectResults - 2: -5 - }, // used to be unimportantResults - // Used when the priority is not in the mapping. - objPrioDefault: 0, - - // query found in title - title: 15, - // query found in terms - term: 5 - }; -} - -if (!splitQuery) { - function splitQuery(query) { - return query.split(/\s+/); - } -} - -/** - * Search Module - */ -var Search = { - - _index: null, - _queued_query: null, - _pulse_status: -1, - - htmlToText: function (htmlString) { - var htmlElement = document.createElement('span'); - htmlElement.innerHTML = htmlString; - $(htmlElement).find('.headerlink').remove(); - docContent = $(htmlElement).find('[role=main]')[0]; - return docContent.textContent || docContent.innerText; - }, - - init: function () { - var params = $.getQueryParameters(); - if (params.q) { - var query = params.q[0]; - $('input[name="q"]')[0].value = query; - this.performSearch(query); - } - }, - - loadIndex: function (url) { - $.ajax({ - type: "GET", url: url, data: null, - dataType: "script", cache: true, - complete: function (jqxhr, textstatus) { - if (textstatus != "success") { - document.getElementById("searchindexloader").src = url; - } - } - }); - }, - - setIndex: function (index) { - var q; - this._index = index; - if ((q = this._queued_query) !== null) { - this._queued_query = null; - Search.query(q); - } - }, - - hasIndex: function () { - return this._index !== null; - }, - - deferQuery: function (query) { - this._queued_query = query; - }, - - stopPulse: function () { - this._pulse_status = 0; - }, - - startPulse: function () { - if (this._pulse_status >= 0) - return; - function pulse() { - var i; - Search._pulse_status = (Search._pulse_status + 1) % 4; - var dotString = ''; - for (i = 0; i < Search._pulse_status; i++) - dotString += '.'; - Search.dots.text(dotString); - if (Search._pulse_status > -1) - window.setTimeout(pulse, 500); - } - pulse(); - }, - - /** - * perform a search for something (or wait until index is loaded) - */ - performSearch: function (query) { - // create the required interface elements - this.out = $('#search-results'); - this.title = $('

' + _('Searching') + '

').appendTo(this.out); - this.dots = $('').appendTo(this.title); - this.status = $('

').appendTo(this.out); - this.output = $('
').appendTo(this.out); - - $('#search-progress').text(_('Preparing search...')); - this.startPulse(); - - // index already loaded, the browser was quick! - if (this.hasIndex()) - this.query(query); - else - this.deferQuery(query); - }, - - /** - * execute search (requires search index to be loaded) - */ - query: function (query) { - var i; - var stopwords = DOCUMENTATION_OPTIONS.SEARCH_LANGUAGE_STOP_WORDS; - - // stem the searchterms and add them to the correct list - var stemmer = new Stemmer(); - var searchterms = []; - var excluded = []; - var hlterms = []; - var tmp = splitQuery(query); - var objectterms = []; - for (i = 0; i < tmp.length; i++) { - if (tmp[i] !== "") { - objectterms.push(tmp[i].toLowerCase()); - } - - if ($u.indexOf(stopwords, tmp[i].toLowerCase()) != -1 || tmp[i].match(/^\d+$/) || - tmp[i] === "") { - // skip this "word" - continue; - } - // stem the word - var word = stemmer.stemWord(tmp[i].toLowerCase()); - // prevent stemmer from cutting word smaller than two chars - if (word.length < 3 && tmp[i].length >= 3) { - word = tmp[i]; - } - var toAppend; - // select the correct list - if (word[0] == '-') { - toAppend = excluded; - word = word.substr(1); - } - else { - toAppend = searchterms; - hlterms.push(tmp[i].toLowerCase()); - } - // only add if not already in the list - if (!$u.contains(toAppend, word)) - toAppend.push(word); - } - var highlightstring = '?highlight=' + $.urlencode(hlterms.join(" ")); - - // console.debug('SEARCH: searching for:'); - // console.info('required: ', searchterms); - // console.info('excluded: ', excluded); - - // prepare search - var terms = this._index.terms; - var titleterms = this._index.titleterms; - - // array of [filename, title, anchor, descr, score] - var results = []; - $('#search-progress').empty(); - - // lookup as object - for (i = 0; i < objectterms.length; i++) { - var others = [].concat(objectterms.slice(0, i), - objectterms.slice(i + 1, objectterms.length)); - results = results.concat(this.performObjectSearch(objectterms[i], others)); - } - - // lookup as search terms in fulltext - results = results.concat(this.performTermsSearch(searchterms, excluded, terms, titleterms)); - - // let the scorer override scores with a custom scoring function - if (Scorer.score) { - for (i = 0; i < results.length; i++) - results[i][4] = Scorer.score(results[i]); - } - - // now sort the results by score (in opposite order of appearance, since the - // display function below uses pop() to retrieve items) and then - // alphabetically - results.sort(function (a, b) { - var left = a[4]; - var right = b[4]; - if (left > right) { - return 1; - } else if (left < right) { - return -1; - } else { - // same score: sort alphabetically - left = a[1].toLowerCase(); - right = b[1].toLowerCase(); - return (left > right) ? -1 : ((left < right) ? 1 : 0); - } - }); - - // for debugging - //Search.lastresults = results.slice(); // a copy - //console.info('search results:', Search.lastresults); - - // print the results - var resultCount = results.length; - function displayNextItem() { - // results left, load the summary and display it - if (results.length) { - var item = results.pop(); - var listItem = $('
'); - var isMethod = item[1].startsWith('pymc.') - var header = isMethod ? item[1].slice(item[1].lastIndexOf('.') + 1, item[1].length) : item[1]; - if (DOCUMENTATION_OPTIONS.FILE_SUFFIX === '') { - // dirhtml builder - var dirname = item[0] + '/'; - if (dirname.match(/\/index\/$/)) { - dirname = dirname.substring(0, dirname.length - 6); - } else if (dirname == 'index/') { - dirname = ''; - } - listItem.append($('
').html( - $('').attr('href', - DOCUMENTATION_OPTIONS.URL_ROOT + dirname + - highlightstring + item[2]).html(header)) - ); - } else { - // normal html builders - listItem.append($('
').html( - $('').attr('href', - item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX + - highlightstring + item[2]).html(header)) - ); - } - - if (isMethod) { - listItem.append($('
').html( - $('
').html( - $('
In ' + - item[1].replace('pymc.', 'pm.') + '
') - ) - )); - Search.output.append(listItem); - listItem.slideDown(5, function () { - displayNextItem(); - }); - } else if (DOCUMENTATION_OPTIONS.HAS_SOURCE) { - $.ajax({ - url: DOCUMENTATION_OPTIONS.URL_ROOT + item[0] + DOCUMENTATION_OPTIONS.FILE_SUFFIX, - dataType: "text", - complete: function (jqxhr, textstatus) { - var data = jqxhr.responseText; - if (data !== '' && data !== undefined) { - listItem.append(Search.makeSearchSummary(data, searchterms, hlterms)); - } - Search.output.append(listItem); - listItem.slideDown(5, function () { - displayNextItem(); - }); - } - }); - } else { - // no source available, just display title - Search.output.append(listItem); - listItem.slideDown(5, function () { - displayNextItem(); - }); - } - } - // search finished, update title and status message - else { - Search.stopPulse(); - Search.title.text(_('Search Results')); - if (!resultCount) - Search.status.text(_('Your search did not match any documents. Please make sure that all words are spelled correctly and that you\'ve selected enough categories.')); - else - Search.status.text(_('Search finished, found %s page(s) matching the search query.').replace('%s', resultCount)); - Search.status.fadeIn(500); - } - } - displayNextItem(); - }, - - /** - * search for object names - */ - performObjectSearch: function (object, otherterms) { - var filenames = this._index.filenames; - var docnames = this._index.docnames; - var objects = this._index.objects; - var objnames = this._index.objnames; - var titles = this._index.titles; - - var i; - var results = []; - - for (var prefix in objects) { - for (var name in objects[prefix]) { - var fullname = (prefix ? prefix + '.' : '') + name; - if (fullname.toLowerCase().indexOf(object) > -1) { - var score = 0; - var parts = fullname.split('.'); - // check for different match types: exact matches of full name or - // "last name" (i.e. last dotted part) - if (fullname.toLowerCase() == object || parts[parts.length - 1].toLowerCase() == object) { - score += Scorer.objNameMatch; - // matches in last name - } else if (parts[parts.length - 1].indexOf(object) > -1) { - score += Scorer.objPartialMatch; - } - var match = objects[prefix][name]; - var objname = objnames[match[1]][2]; - var title = titles[match[0]]; - // If more than one term searched for, we require other words to be - // found in the name/title/description - if (otherterms.length > 0) { - var haystack = (prefix + ' ' + name + ' ' + - objname + ' ' + title).toLowerCase(); - var allfound = true; - for (i = 0; i < otherterms.length; i++) { - if (haystack.indexOf(otherterms[i]) == -1) { - allfound = false; - break; - } - } - if (!allfound) { - continue; - } - } - var descr = objname + _(', in ') + title; - - var anchor = match[3]; - if (anchor === '') - anchor = fullname; - else if (anchor == '-') - anchor = objnames[match[1]][1] + '-' + fullname; - // add custom score for some objects according to scorer - if (Scorer.objPrio.hasOwnProperty(match[2])) { - score += Scorer.objPrio[match[2]]; - } else { - score += Scorer.objPrioDefault; - } - results.push([docnames[match[0]], fullname, '#' + anchor, descr, score, filenames[match[0]]]); - } - } - } - - return results; - }, - - /** - * search for full-text terms in the index - */ - performTermsSearch: function (searchterms, excluded, terms, titleterms) { - var docnames = this._index.docnames; - var filenames = this._index.filenames; - var titles = this._index.titles; - - var i, j, file; - var fileMap = {}; - var scoreMap = {}; - var results = []; - - // perform the search on the required terms - for (i = 0; i < searchterms.length; i++) { - var word = searchterms[i]; - var files = []; - var _o = [ - { files: terms[word], score: Scorer.term }, - { files: titleterms[word], score: Scorer.title } - ]; - - // no match but word was a required one - if ($u.every(_o, function (o) { return o.files === undefined; })) { - break; - } - // found search word in contents - $u.each(_o, function (o) { - var _files = o.files; - if (_files === undefined) - return - - if (_files.length === undefined) - _files = [_files]; - files = files.concat(_files); - - // set score for the word in each file to Scorer.term - for (j = 0; j < _files.length; j++) { - file = _files[j]; - if (!(file in scoreMap)) - scoreMap[file] = {} - scoreMap[file][word] = o.score; - } - }); - - // create the mapping - for (j = 0; j < files.length; j++) { - file = files[j]; - if (file in fileMap) - fileMap[file].push(word); - else - fileMap[file] = [word]; - } - } - - // now check if the files don't contain excluded terms - for (file in fileMap) { - var valid = true; - - // check if all requirements are matched - if (fileMap[file].length != searchterms.length) - continue; - - // ensure that none of the excluded terms is in the search result - for (i = 0; i < excluded.length; i++) { - if (terms[excluded[i]] == file || - titleterms[excluded[i]] == file || - $u.contains(terms[excluded[i]] || [], file) || - $u.contains(titleterms[excluded[i]] || [], file)) { - valid = false; - break; - } - } - - // if we have still a valid result we can add it to the result list - if (valid) { - // select one (max) score for the file. - // for better ranking, we should calculate ranking by using words statistics like basic tf-idf... - var score = $u.max($u.map(fileMap[file], function (w) { return scoreMap[file][w] })); - results.push([docnames[file], titles[file], '', null, score, filenames[file]]); - } - } - return results; - }, - - /** - * helper function to return a node containing the - * search summary for a given text. keywords is a list - * of stemmed words, hlwords is the list of normal, unstemmed - * words. the first one is used to find the occurrence, the - * latter for highlighting it. - */ - makeSearchSummary: function (htmlText, keywords, hlwords) { - var text = Search.htmlToText(htmlText); - var textLower = text.toLowerCase(); - var start = 0; - $.each(keywords, function () { - var i = textLower.indexOf(this.toLowerCase()); - if (i > -1) - start = i; - }); - start = Math.max(start - 120, 0); - var excerpt = ((start > 0) ? 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