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Merge pull request #1132 from abhro/md-links
Use markdown link syntax and update hyperlinks
2 parents 2a04d3b + 76505f6 commit 580f514

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ext/SciMLBaseForwardDiffExt.jl

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@@ -98,7 +98,7 @@ to be specified at compiled time and thus cannot have a Bool-based opt out, so i
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may be extended to use a preference system to opt-out with a `UPCONVERT_DUALS`. In the case where
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upconversion is not done automatically, the user is required to upconvert all initial conditions
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themselves, for an example of how this can be confusing to a user see
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https://discourse.julialang.org/t/typeerror-in-julia-turing-when-sampling-for-a-forced-differential-equation/82937
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<https://discourse.julialang.org/t/typeerror-in-julia-turing-when-sampling-for-a-forced-differential-equation/82937>
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"""
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@generated function anyeltypedual(x, ::Type{Val{counter}}) where {counter}
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x = x.name === Core.Compiler.typename(Type) ? x.parameters[1] : x

ext/SciMLBaseMakieExt.jl

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@@ -16,7 +16,7 @@ function ensure_plottrait(PT::Type, arg, desired_plottrait_type::Type)
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::$(string(typeof(arg)))
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Makie needs to convert all plot input arguments to types that can be consumed by the backends (typically Arrays with Float32 elements).
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You can define a method for `Makie.convert_arguments` (a type recipe) for these types or their supertypes to make this set of arguments convertible (See http://docs.makie.org/stable/documentation/recipes/index.html).
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You can define a method for `Makie.convert_arguments` (a type recipe) for these types or their supertypes to make this set of arguments convertible (See <http://docs.makie.org/stable/documentation/recipes/index.html>).
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Alternatively, you can define `Makie.convert_single_argument` for single arguments which have types that are unknown to Makie but which can be converted to known types and fed back to the conversion pipeline.
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""")

src/alg_traits.jl

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@@ -275,7 +275,7 @@ not converge to the same answer. In the context of a stochastic differential equ
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on the integral rule that is chosen. This trait describes which interpretation the solver algorithm subscribes to, and thus whether the solution should
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be interpreted as the solution to the SDE under the Ito or Stratonovich interpretation.
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For more information, see https://oatml.cs.ox.ac.uk/blog/2022/03/22/ito-strat.html as a good high-level explanation.
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For more information, see <https://oatml.cs.ox.ac.uk/blog/2022/03/22/ito-strat.html> as a good high-level explanation.
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!!! note
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src/debug.jl

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definition of `f`.
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For more information, check out the following FAQ page:
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https://docs.sciml.ai/Optimization/stable/API/FAQ/#The-Solver-Seems-to-Violate-Constraints-During-the-Optimization,-Causing-DomainErrors,-What-Can-I-Do-About-That?"""
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<https://docs.sciml.ai/Optimization/stable/API/FAQ/#The-Solver-Seems-to-Violate-Constraints-During-the-Optimization,-Causing-DomainErrors,-What-Can-I-Do-About-That?>"""
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FUNCTIONWRAPPERSWRAPPERS_MSG = """
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No appropriate function wrapper found. This means that the auto-despecialization code used for the reduction
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For more information on the control of specialization options, please see the documentation at:
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https://docs.sciml.ai/SciMLBase/stable/interfaces/Problems/#Specialization-Choices
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<https://docs.sciml.ai/SciMLBase/stable/interfaces/Problems/#Specialization-Choices>
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If one wants way more detail than necessary on why the function wrappers exist and what they are doing, see:
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https://sciml.ai/news/2022/09/21/compile_time/"""
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<https://sciml.ai/news/2022/09/21/compile_time>"""
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const NO_PARAMETERS_ARITHMETIC_ERROR_MESSAGE = """
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src/errors.jl

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The only allowed keyword arguments to `solve` are:
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$allowedkeywords
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See https://diffeq.sciml.ai/stable/basics/common_solver_opts/ for more details.
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See <https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts> for more details.
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Set kwargshandle=KeywordArgError for an error message.
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Set kwargshandle=KeywordArgSilent to ignore this message.
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The only allowed keyword arguments to `solve` are:
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$allowedkeywords
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See https://diffeq.sciml.ai/stable/basics/common_solver_opts/ for more details.
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See <https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts> for more details.
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"""
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struct CommonKwargError <: Exception
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choice in the problem constructor, i.e. `ODEProblem{false}(f,u0,tspan,p,kwargs...)`.
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For a longer discussion on mutability vs immutability and in-place vs out-of-place, see:
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https://diffeq.sciml.ai/stable/tutorials/faster_ode_example/#Example-Accelerating-a-Non-Stiff-Equation:-The-Lorenz-Equation
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<https://docs.sciml.ai/DiffEqDocs/stable/tutorials/faster_ode_example#Example-Accelerating-a-Non-Stiff-Equation:-The-Lorenz-Equation>
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"""
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struct IncompatibleInitialConditionError <: Exception end
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`init(prob, Tsit5())` for an ODE) or import DifferentialEquations
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directly.
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You can find the list of available solvers at https://diffeq.sciml.ai/stable/solvers/ode_solve/
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You can find the list of available solvers at <https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve>
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and its associated pages.
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"""
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Please double check the arguments being sent to the solver.
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You can find the list of available solvers at https://diffeq.sciml.ai/stable/solvers/ode_solve/
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You can find the list of available solvers at <https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve>
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and its associated pages.
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"""
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For more details on automatic differentiation, adjoint, and sensitivity analysis
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of differential equations, see the documentation page:
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https://diffeq.sciml.ai/stable/analysis/sensitivity/
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<https://docs.sciml.ai/SciMLSensitivity/>
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"""
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struct DirectAutodiffError <: Exception end
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```
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This will be safer and fast for small ODEs. For more information, see:
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https://diffeq.sciml.ai/stable/tutorials/faster_ode_example/#Further-Optimizations-of-Small-Non-Stiff-ODEs-with-StaticArrays
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<https://docs.sciml.ai/DiffEqDocs/stable/tutorials/faster_ode_example/#Further-Optimizations-of-Small-Non-Stiff-ODEs-with-StaticArrays>
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"""
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struct TupleStateError <: Exception end

src/problems/bvp_problems.jl

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@doc doc"""
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Defines an BVP problem.
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/>
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## Mathematical Specification of a BVP Problem
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/bvp_types/>
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## Mathematical Specification of a second order BVP Problem
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src/problems/dae_problems.jl

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Defines an implicit ordinary differential equation (ODE) or
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differential-algebraic equation (DAE) problem.
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/dae_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/dae_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/dae_types/>
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## Mathematical Specification of an DAE Problem
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src/problems/dde_problems.jl

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@doc doc"""
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Defines a delay differential equation (DDE) problem.
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/dde_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/dde_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/dde_types/>
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## Mathematical Specification of a DDE Problem
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src/problems/discrete_problems.jl

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Defines a discrete dynamical system problem.
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/>
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## Mathematical Specification of a Discrete Problem
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src/problems/implicit_discrete_problems.jl

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@doc doc"""
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Defines a discrete dynamical system problem.
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Documentation Page: [https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/](https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/)
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Documentation Page: <https://docs.sciml.ai/DiffEqDocs/stable/types/discrete_types/>
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## Mathematical Specification of a ImplicitDiscrete Problem
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