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update Documenter version #539

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2 changes: 1 addition & 1 deletion docs/Project.toml
Original file line number Diff line number Diff line change
Expand Up @@ -6,5 +6,5 @@ Plots = "91a5bcdd-55d7-5caf-9e0b-520d859cae80"
SpecialFunctions = "276daf66-3868-5448-9aa4-cd146d93841b"

[compat]
Documenter = "0.27"
Documenter = "1"
GR_jll = "< 0.58"
1 change: 1 addition & 0 deletions docs/make.jl
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Expand Up @@ -22,6 +22,7 @@ makedocs(
],
"Extending" => "extending.md",
],
warnonly = [:cross_references, :missing_docs],
)

deploydocs(repo = "github.com/JuliaMath/Polynomials.jl.git")
2 changes: 1 addition & 1 deletion docs/src/extending.md
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@@ -1,6 +1,6 @@
# Extending Polynomials

The [`AbstractUnivaeriatePolynomial`](@ref) type was made to be extended.
The [`AbstractUnivariatePolynomial`](@ref) type was made to be extended.

A polynomial's coefficients are relative to some *basis*. The `Polynomial` type relates coefficients `[a0, a1, ..., an]`, say, to the polynomial ``a_0 + a_1\cdot x + a_2\cdot x^2 + \cdots + a_n\cdot x^n``, through the standard basis ``1, x, x^2, ..., x^n``. New polynomial types typically represent the polynomial through a different basis. For example, `CheyshevT` uses a basis ``T_0=1, T_1=x, T_2=2x^2-1, \cdots, T_n = 2xT_{n-1} - T_{n-2}``. For this type the coefficients `[a0,a1,...,an]` are associated with the polynomial ``a0\cdot T_0 + a_1 \cdot T_1 + \cdots + a_n\cdot T_n`.

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2 changes: 1 addition & 1 deletion src/common.jl
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Expand Up @@ -105,7 +105,7 @@ the variance-covariance matrix.)

## large degree

For fitting with a large degree, the Vandermonde matrix is exponentially ill-conditioned. The [`ArnoldiFit`](@ref) type introduces an Arnoldi orthogonalization that fixes this problem.
For fitting with a large degree, the Vandermonde matrix is exponentially ill-conditioned. The `ArnoldiFit` type introduces an Arnoldi orthogonalization that fixes this problem.


"""
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2 changes: 1 addition & 1 deletion src/polynomials/ngcd.jl
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@@ -1,7 +1,7 @@
"""
ngcd(p, q, [k]; kwargs...)

Find numerical GCD of polynomials `p` and `q`. Refer to [`NGCD.ngcd(p,q)`](@ref) for details.
Find numerical GCD of polynomials `p` and `q`. Refer to `NGCD.ngcd` for details.

The main entry point for this function is `gcd(p, q, method=:numerical)`, but `ngcd` outputs the gcd factorization -- `u, v, w` with `u*v ≈ p` and `u*w ≈ q` -- along with `Θ`, an estimate on how close `p`,`q` is to a gcd factorization of degree `k` and `κ` the GCD condition number.

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2 changes: 1 addition & 1 deletion src/polynomials/standard-basis/laurent-polynomial.jl
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Expand Up @@ -219,7 +219,7 @@ The `cconj` of a polynomial, `p̃`, conjugates the coefficients and applies `s -

This satisfies for *imaginary* `s`: `conj(p(s)) = p̃(s) = (conj ∘ p)(s) = cconj(p)(s) `

[ref](https://github.com/hurak/PolynomialEquations.jl#symmetrix-conjugate-equation-continuous-time-case)
[reference](https://github.com/hurak/PolynomialEquations.jl#symmetrix-conjugate-equation-continuous-time-case)

Examples:
```jldoctest laurent
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2 changes: 1 addition & 1 deletion src/polynomials/standard-basis/standard-basis.jl
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Expand Up @@ -232,7 +232,7 @@ By default, uses the Euclidean division algorithm (`method=:euclidean`), which i

Passing `method=:noda_sasaki` uses scaling to circumvent some of these.

Passing `method=:numerical` will call the internal method `NGCD.ngcd` for the numerical gcd. See the help page of [`Polynomials.NGCD.ngcd(p,q)`](@ref) for details.
Passing `method=:numerical` will call the internal method `NGCD.ngcd` for the numerical gcd. See the docstring of `NGCD.ngcd` for details.
"""
function Base.gcd(p1::P, p2::Q, args...;
method=:euclidean,
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2 changes: 1 addition & 1 deletion src/rational-functions/fit.jl
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Expand Up @@ -83,7 +83,7 @@ end
"""
fit(::Type{RationalFunction}, r::Polynomial, m, n; var=:x)

Fit a Pade approximant ([`pade_fit`](@ref)) to `r`.
Fit a Pade approximant (cf docstring for `Polynomials.pade_fit`) to `r`.

Examples:

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2 changes: 1 addition & 1 deletion src/rational-functions/rational-function.jl
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Expand Up @@ -5,7 +5,7 @@
Create a rational expression (`p//q`) from the two polynomials.

Common factors are not cancelled by the constructor, as they are for
the base `Rational` type. The [`lowest_terms(pq)`](@ref) function attempts
the base `Rational` type. The [`lowest_terms`](@ref) function attempts
that operation.

For purposes of iteration, a rational function is treated like a two-element container.
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