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Merge pull request #226 from ArnoStrouwen/typos
typos CI
2 parents ffbed52 + ed52fe4 commit 48aaa11

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8 files changed

+32
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.github/dependabot.yml

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@@ -5,3 +5,6 @@ updates:
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directory: "/" # Location of package manifests
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schedule:
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interval: "weekly"
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ignore:
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- dependency-name: "crate-ci/typos"
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update-types: ["version-update:semver-patch"]

.github/workflows/SpellCheck.yml

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name: Spell Check
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on: [pull_request]
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jobs:
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typos-check:
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name: Spell Check with Typos
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runs-on: ubuntu-latest
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steps:
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- name: Checkout Actions Repository
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uses: actions/checkout@v3
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- name: Check spelling
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uses: crate-ci/[email protected]

.typos.toml

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[default.extend-words]
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ND = "ND"

README.md

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@@ -18,7 +18,7 @@ operators, fast tensor-product evaluations, pre-cached mutating
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evaluations, as well as `Zygote`-compatible non-mutating evaluations.
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The lazily implemented operator algebra allows the user to update the
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operator state by passing in an update function that accepts arbirary
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operator state by passing in an update function that accepts arbitrary
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parameter objects. Further, our operators behave like `AbstractMatrix` types
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thanks to overloads defined for methods in `Base`, and `LinearAlgebra`.
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## Installation
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`SciMLOperators.jl` is a registerd package and can be installed via
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`SciMLOperators.jl` is a registered package and can be installed via
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```
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julia> import Pkg

docs/src/interface.md

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@@ -35,7 +35,7 @@ interface includes, but is not limited to, the following:
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- `LinearAlgebra: mul!, ldiv!, lmul!, rmul!, factorize, issymmetric, ishermitian, isposdef`
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- `SparseArrays: sparse, issparse`
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## Multidimension arrays and batching
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## Multidimensional arrays and batching
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SciMLOperator can also be applied to `AbstractMatrix` subtypes where
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operator-evaluation is done column-wise.
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```
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The update behavior makes this package flexible enough to be used
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in `OrdianryDiffEq`. As the parameter object `p` is often reserved
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in `OrdinaryDiffEq`. As the parameter object `p` is often reserved
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for sensitivity computation via automatic-differentiation, a user may
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prefer to pass in state information via other arguments. For that
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reason, we allow update functions with arbitrary keyword arguments.

src/basic.jl

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@@ -36,7 +36,7 @@ has_mul!(::IdentityOperator) = true
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has_ldiv(::IdentityOperator) = true
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has_ldiv!(::IdentityOperator) = true
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# opeator application
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# operator application
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for op in (:*, :\)
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@eval function Base.$op(ii::IdentityOperator, u::AbstractVecOrMat)
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@assert size(u, 1) == ii.len
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has_adjoint(::NullOperator) = true
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has_mul!(::NullOperator) = true
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# opeator application
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# operator application
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Base.:*(nn::NullOperator, u::AbstractVecOrMat) = (@assert size(u, 1) == nn.len; zero(u))
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function LinearAlgebra.mul!(v::AbstractVecOrMat, nn::NullOperator, u::AbstractVecOrMat)

src/func.jl

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@@ -265,7 +265,7 @@ function FunctionOperator(op,
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end
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if !_unwrap_val(_isinplace) & !_unwrap_val(_outofplace)
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@error """Please provide a funciton with signatures `op(u, p, t)` for
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@error """Please provide a function with signatures `op(u, p, t)` for
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applying the operator out-of-place, and/or the signature is
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`op(v, u, p, t)` for in-place application."""
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end
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if !isa(u, AbstractVecOrMat)
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msg = """$L constructed with `batch = true` only
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accept input arrays that are `AbstractVecOrMat`s with
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`size(L, 2) == size(u, 1)`. Recieved $(typeof(u))."""
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`size(L, 2) == size(u, 1)`. Received $(typeof(u))."""
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throw(ArgumentError(msg))
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end
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if size(L, 2) != size(u, 1)
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msg = """$L accepts input `AbstractVecOrMat`s of size
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($(size(L, 2)), K). Recievd array of size $(size(u))."""
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($(size(L, 2)), K). Received array of size $(size(u))."""
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throw(DimensionMismatch(msg))
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end
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end # u
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if !isa(v, AbstractVecOrMat)
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msg = """$L constructed with `batch = true` only
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returns output arrays that are `AbstractVecOrMat`s with
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`size(L, 1) == size(v, 1)`. Recieved $(typeof(v))."""
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`size(L, 1) == size(v, 1)`. Received $(typeof(v))."""
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throw(ArgumentError(msg))
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end
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if size(L, 1) != size(v, 1)
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msg = """$L accepts output `AbstractVecOrMat`s of size
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($(size(L, 1)), K). Recievd array of size $(size(v))."""
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($(size(L, 1)), K). Received array of size $(size(v))."""
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throw(DimensionMismatch(msg))
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end
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end # v
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else # !batch
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if !isnothing(u)
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if size(u) (sizes[1], tuple(size(L, 2)))
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msg = """$L recievd input array of size $(size(u)), but only
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msg = """$L received input array of size $(size(u)), but only
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accepts input arrays of size $(sizes[1]), or vectors like
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`vec(u)` of size $(tuple(prod(sizes[1])))."""
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throw(DimensionMismatch(msg))
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if !isnothing(v)
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if size(v) (sizes[2], tuple(size(L, 1)))
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msg = """$L recievd output array of size $(size(v)), but only
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msg = """$L received output array of size $(size(v)), but only
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accepts output arrays of size $(sizes[2]), or vectors like
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`vec(u)` of size $(tuple(prod(sizes[2])))"""
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throw(DimensionMismatch(msg))

src/matrix.jl

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Represents an elementwise scaling (diagonal-scaling) operation that may
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be applied to an `AbstractVecOrMat`. When `diag` is an `AbstractVector`
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of length N, `L = DiagonalOpeator(diag, ...)` can be applied to
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of length N, `L = DiagonalOperator(diag, ...)` can be applied to
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`AbstractArray`s with `size(u, 1) == N`. Each column of the `u` will be
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scaled by `diag`, as in `LinearAlgebra.Diagonal(diag) * u`.
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