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Merge pull request #963 from SciML/fix-spelling-errors
Fix spelling errors and add typos configuration
2 parents 4e60958 + bf40951 commit da16fa0

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.typos.toml

Lines changed: 72 additions & 4 deletions
Original file line numberDiff line numberDiff line change
@@ -1,11 +1,79 @@
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[default.extend-words]
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AGS = "AGS"
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# Additional SciML terms
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# Julia-specific functions
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indexin = "indexin"
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findfirst = "findfirst"
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findlast = "findlast"
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eachindex = "eachindex"
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setp = "setp"
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getp = "getp"
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indexin = "indexin"
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setu = "setu"
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getu = "getu"
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# Mathematical/scientific terms
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jacobian = "jacobian"
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hessian = "hessian"
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eigenvalue = "eigenvalue"
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eigenvector = "eigenvector"
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discretization = "discretization"
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linearization = "linearization"
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parameterized = "parameterized"
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discretized = "discretized"
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vectorized = "vectorized"
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# Common variable patterns in Julia/SciML
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ists = "ists"
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ispcs = "ispcs"
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osys = "osys"
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rsys = "rsys"
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usys = "usys"
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fsys = "fsys"
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eqs = "eqs"
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rhs = "rhs"
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MTK = "MTK"
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lhs = "lhs"
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ode = "ode"
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pde = "pde"
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sde = "sde"
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dde = "dde"
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bvp = "bvp"
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ivp = "ivp"
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# Common abbreviations
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tol = "tol"
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rtol = "rtol"
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atol = "atol"
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idx = "idx"
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jdx = "jdx"
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prev = "prev"
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curr = "curr"
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init = "init"
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tmp = "tmp"
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vec = "vec"
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arr = "arr"
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dt = "dt"
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du = "du"
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dx = "dx"
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dy = "dy"
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dz = "dz"
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# Algorithm/type suffixes
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alg = "alg"
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prob = "prob"
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sol = "sol"
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cb = "cb"
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opts = "opts"
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args = "args"
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kwargs = "kwargs"
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# Scientific abbreviations
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ND = "ND"
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nd = "nd"
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MTK = "MTK"
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ODE = "ODE"
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PDE = "PDE"
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SDE = "SDE"
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# Optimization specific terms
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TikTak = "TikTak" # Legitimate algorithm name in MultistartOptimization
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Tak = "Tak" # Part of TikTak algorithm name
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opf = "opf" # Optimal Power Flow abbreviation
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AGS = "AGS" # Legitimate NLopt algorithm name

lib/OptimizationNLPModels/src/OptimizationNLPModels.jl

Lines changed: 1 addition & 1 deletion
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@@ -7,7 +7,7 @@ using Reexport
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OptimizationFunction(nlpmodel::AbstractNLPModel, adtype::AbstractADType = NoAD())
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Returns an `OptimizationFunction` from the `NLPModel` defined in `nlpmodel` where the
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available derivates are re-used from the model, and the rest are populated with the
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available derivatives are re-used from the model, and the rest are populated with the
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Automatic Differentiation backend specified by `adtype`.
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"""
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function SciMLBase.OptimizationFunction(nlpmodel::AbstractNLPModel,

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