uk->us (JuliaMolSim#212)

codegen/xc_fallback/lda_c_vwn.jl

@@ -2,7 +2,7 @@
 #
 # LDA correlation according to Vosko Wilk,and Nusair, (DOI 10.1139/p80-159)
 #
-# This version generates the "standard" parametrisation, where a Pade approximation of a
+# This version generates the "standard" parametrization, where a Pade approximation of a
 # numerical diffusion Monte-Carlo simulation is used.
 
 as_rational(x) = nsimplify(Sym(x))

examples/Silicon_Graphite.ipynb

@@ -133,7 +133,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# Discretise the model\n",
+    "# Discretize the model\n",
     "basis = PlaneWaveBasis(model, Ecut, kgrid=kgrid);"
    ]
   },

examples/cohen_bergstresser.jl

@@ -13,14 +13,14 @@ Si = ElementCohenBergstresser(:Si)
 lattice = Si.lattice_constant / 2 .* [[0 1 1.]; [1 0 1.]; [1 1 0.]]
 atoms = [Si => [ones(3)/8, -ones(3)/8]]
 
-# Model, discretisation and Hamiltonian
+# Model, discretization and Hamiltonian
 model = Model(Matrix{T}(lattice); atoms=atoms, terms=[Kinetic(), AtomicLocal()])
 basis = PlaneWaveBasis(model, Ecut)
 
-# Diagonalise (at the Gamma point) to find Fermi level used in Cohen-Bergstresser,
+# Diagonalize (at the Gamma point) to find Fermi level used in Cohen-Bergstresser,
 # then compute the bands
 ham = Hamiltonian(basis)
-eigres = diagonalise_all_kblocks(DFTK.lobpcg_hyper, ham, 6)
+eigres = diagonalize_all_kblocks(DFTK.lobpcg_hyper, ham, 6)
 εF = find_fermi_level(basis, eigres.λ)
 
 ρ0 = guess_density(basis)  # Just dummy, has no meaning in this model

examples/gross_pitaevskii.jl

@@ -22,7 +22,7 @@ terms = [Kinetic(),
          PowerNonlinearity(C, α),
 ]
 model = Model(lattice; n_electrons=n_electrons, terms=terms,
-              spin_polarisation=:spinless)  # "spinless fermions"
+              spin_polarization=:spinless)  # "spinless fermions"
 basis = PlaneWaveBasis(model, Ecut)
 
 scfres = direct_minimization(basis, x_tol=1e-8, f_tol=-1, g_tol=-1)

examples/gross_pitaevskii_2D.jl

@@ -31,7 +31,7 @@ terms = [Kinetic(),
          Magnetic(Apot),
 ]
 model = Model(lattice; n_electrons=n_electrons,
-              terms=terms, spin_polarisation=:spinless)  # "spinless fermions"
+              terms=terms, spin_polarization=:spinless)  # "spinless fermions"
 basis = PlaneWaveBasis(model, Ecut)
 
 n_bands_scf = model.n_electrons

examples/magnesium_pbe.jl

@@ -22,7 +22,7 @@ pystruct.make_supercell(supercell)
 lattice = load_lattice(pystruct)
 atoms = [Mg => [s.frac_coords for s in pystruct.sites]]
 
-# Setup PBE model with Methfessel-Paxton smearing and its discretisation
+# Setup PBE model with Methfessel-Paxton smearing and its discretization
 model = model_DFT(lattice, atoms, [:gga_x_pbe, :gga_c_pbe];
                   temperature=Tsmear,
                   smearing=DFTK.Smearing.MethfesselPaxton1())

examples/silicon_lda_arbitrary_floattype.jl

@@ -12,7 +12,7 @@ lattice = a / 2 .* [[0 1 1.]; [1 0 1.]; [1 1 0.]]
 Si = ElementPsp(:Si, psp=load_psp(:Si, functional="lda"))
 atoms = [Si => [ones(3)/8, -ones(3)/8]]
 
-# Setup LDA model and discretisation
+# Setup LDA model and discretization
 model = model_DFT(Array{T}(lattice), atoms, [:lda_x, :lda_c_vwn])
 basis = PlaneWaveBasis(model, Ecut, kgrid=kgrid)
 

src/DFTK.jl

@@ -99,7 +99,7 @@ export lobpcg_hyper
 export lobpcg_scipy
 export lobpcg_itsolve
 export diag_full
-export diagonalise_all_kblocks
+export diagonalize_all_kblocks
 include("eigen/diag.jl")
 
 export KerkerMixing

src/Model.jl

@@ -16,16 +16,16 @@ struct Model{T <: Real}
     # Electrons, occupation and smearing function
     n_electrons::Int # not necessarily consistent with `atoms` field
 
-    # spin_polarisation values:
-    #     :none       No spin polarisation, αα and ββ density identical,
+    # spin_polarization values:
+    #     :none       No spin polarization, αα and ββ density identical,
     #                 αβ and βα blocks zero
-    #     :collinear  Spin is polarised, but everywhere in the same direction.
+    #     :collinear  Spin is polarized, but everywhere in the same direction.
     #                 αα ̸= ββ, αβ = βα = 0
-    #     :full       Generic magnetisation, non-uniform direction.
+    #     :full       Generic magnetization, non-uniform direction.
     #                 αβ, βα, αα, ββ all nonzero, different
     #     :spinless   No spin at all ("spinless fermions", "mathematicians' electrons").
     #                 Difference with :none is that the occupations are 1 instead of 2
-    spin_polarisation::Symbol  # :none, :collinear, :full, :spinless
+    spin_polarization::Symbol  # :none, :collinear, :full, :spinless
 
     # If temperature=0, no fractional occupations are used.
     # If temperature is nonzero, the occupations are
@@ -43,7 +43,7 @@ struct Model{T <: Real}
 end
 
 function Model(lattice::AbstractMatrix{T}; n_electrons=nothing, atoms=[], terms=[], temperature=0.0,
-               smearing=nothing, spin_polarisation=:none) where {T <: Real}
+               smearing=nothing, spin_polarization=:none) where {T <: Real}
     lattice = Mat3{T}(lattice)
 
     if n_electrons === nothing
@@ -73,7 +73,7 @@ function Model(lattice::AbstractMatrix{T}; n_electrons=nothing, atoms=[], terms=
     unit_cell_volume = abs(det(lattice[1:d, 1:d]))
     recip_cell_volume = abs(det(recip_lattice[1:d, 1:d]))
 
-    @assert spin_polarisation in (:none, :collinear, :full, :spinless)
+    @assert spin_polarization in (:none, :collinear, :full, :spinless)
 
     if smearing === nothing
         @assert temperature >= 0
@@ -86,7 +86,7 @@ function Model(lattice::AbstractMatrix{T}; n_electrons=nothing, atoms=[], terms=
     end
 
     Model{T}(lattice, recip_lattice, unit_cell_volume, recip_cell_volume, d, n_electrons,
-             spin_polarisation, T(temperature), smearing, atoms, terms)
+             spin_polarization, T(temperature), smearing, atoms, terms)
 end
 
 
@@ -130,8 +130,8 @@ end
 Maximal occupation of a state (2 for non-spin-polarized electrons, 1 otherwise).
 """
 function filled_occupation(model)
-    @assert model.spin_polarisation in (:none, :spinless)
-    if model.spin_polarisation == :none
+    @assert model.spin_polarization in (:none, :spinless)
+    if model.spin_polarization == :none
         @assert model.n_electrons % 2 == 0
         filled_occ = 2
     else

src/PlaneWaveBasis.jl

@@ -73,14 +73,14 @@ Base.show(io::IO, basis::PlaneWaveBasis) =
 Base.eltype(basis::PlaneWaveBasis{T}) where {T} = T
 
 function build_kpoints(model::Model{T}, fft_size, kcoords, Ecut) where T
-    model.spin_polarisation in (:none, :collinear, :spinless) || (
-        error("$(model.spin_polarisation) not implemented"))
+    model.spin_polarization in (:none, :collinear, :spinless) || (
+        error("$(model.spin_polarization) not implemented"))
     spin = (:undefined,)
-    if model.spin_polarisation == :collinear
+    if model.spin_polarization == :collinear
         spin = (:up, :down)
-    elseif model.spin_polarisation == :none
+    elseif model.spin_polarization == :none
         spin = (:both, )
-    elseif model.spin_polarisation == :spinless
+    elseif model.spin_polarization == :spinless
         spin = (:spinless, )
     end
 

src/densities.jl

@@ -33,7 +33,7 @@ end
 """
     compute_density(basis::PlaneWaveBasis, ψ::AbstractVector, occupation::AbstractVector)
 
-Compute the density for a wave function `ψ` discretised on the plane-wave grid `basis`,
+Compute the density for a wave function `ψ` discretized on the plane-wave grid `basis`,
 where the individual k-Points are occupied according to `occupation`. `ψ` should
 be one coefficient matrix per k-Point.
 """

src/eigen/diag.jl

@@ -8,7 +8,7 @@ that really does the work, operating on a single ``k``-Block.
 `eigensolver` should support the API `eigensolver(A, X0; prec, tol, maxiter)`
 `prec_type` should be a function that returns a preconditioner when called as `prec(ham, kpt)`
 """
-function diagonalise_all_kblocks(eigensolver, ham::Hamiltonian, nev_per_kpoint::Int;
+function diagonalize_all_kblocks(eigensolver, ham::Hamiltonian, nev_per_kpoint::Int;
                                  guess=nothing,
                                  prec_type=PreconditionerTPA, interpolate_kpoints=true,
                                  tol=1e-6, miniter=1, maxiter=200, n_conv_check=nothing,
@@ -33,7 +33,7 @@ function diagonalise_all_kblocks(eigensolver, ham::Hamiltonian, nev_per_kpoint::
         elseif interpolate_kpoints && ik > 1
             # use information from previous kpoint
             X0 = interpolate_kpoint(results[ik - 1].X, kpoints[ik - 1], kpoints[ik])
-            guessk = Matrix{T}(qr(X0).Q)  # Re-orthogonalise and renormalise
+            guessk = Matrix{T}(qr(X0).Q)  # Re-orthogonalize and renormalize
         else
             # random initial guess
             qrres = qr(randn(T, length(G_vectors(kpoints[ik])), nev_per_kpoint))
@@ -62,7 +62,7 @@ end
 
 @doc raw"""
 Function to select a subset of eigenpairs on each ``k``-Point. Works on the
-Tuple returned by `diagonalise_all_kblocks`.
+Tuple returned by `diagonalize_all_kblocks`.
 """
 function select_eigenpairs_all_kblocks(eigres, range)
     merge(eigres, (λ=[λk[range] for λk in eigres.λ],

src/eigen/lobpcg_hyper_impl.jl

@@ -62,7 +62,7 @@ end
 
 import LinearAlgebra: cholesky
 function cholesky(X::Union{Matrix{ComplexF16}, Hermitian{ComplexF16,Matrix{ComplexF16}}})
-    # Cholesky factorisation above may promote the type
+    # Cholesky factorization above may promote the type
     # (e.g. Float16 is promoted to Float32. This undoes it)
     # See https://github.com/JuliaLang/julia/issues/16446
     U = cholesky(ComplexF32.(X)).U

src/eigen/preconditioners.jl

@@ -39,7 +39,7 @@ end
 function PreconditionerTPA(basis::PlaneWaveBasis, kpt::Kpoint{T}; default_shift=1) where T
     kin = Vector{T}([sum(abs2, basis.model.recip_lattice * (G + kpt.coordinate))
                      for G in G_vectors(kpt)] ./ 2)
-    @assert basis.model.spin_polarisation in (:none, :collinear, :spinless)
+    @assert basis.model.spin_polarization in (:none, :collinear, :spinless)
     PreconditionerTPA{T}(basis, kpt, kin, nothing, default_shift)
 end
 

src/elements.jl

@@ -129,8 +129,8 @@ function ElementCohenBergstresser(key; lattice_constant=nothing)
     unit_cell_volume = det(lattice_constant / 2 .* [[0 1 1]; [1 0 1]; [1 1 0]])
 
     # The form factors in the Cohen-Bergstresser paper Table 2 are
-    # with respect to normalised planewaves (i.e. not plain Fourier coefficients)
-    # and are already symmetrised into a sin-cos basis (see derivation p. 141)
+    # with respect to normalized planewaves (i.e. not plain Fourier coefficients)
+    # and are already symmetrized into a sin-cos basis (see derivation p. 141)
     # => Scale by Ω / 2 to get them into the DFTK convention
     V_sym = Dict(key => value * unit_cell_volume / 2
                  for (key, value) in pairs(data[symbol].form_factors))

src/external/abinit.jl

@@ -24,7 +24,7 @@ function run_abinit_scf(infile::PyObject, outdir)
 
     # Adjust common infile settings:
     infile.set_vars(
-        paral_kgb=0,    # Parallelisation over k-Points and Bands
+        paral_kgb=0,    # Parallelization over k-Points and Bands
         iomode=3,       # Use NetCDF output
         istwfk="*1",    # Needed for extracting the wave function later
     )
@@ -81,14 +81,14 @@ function run_abinit_scf(model::Model, outdir;
         tolvrs=tol,       # General tolerance settings
     )
 
-    # Spin-polarisation
-    if model.spin_polarisation == :spinless
-        error("spin_polarisation == spinless is not supported by abinit")
-    elseif model.spin_polarisation == :none
+    # Spin-polarization
+    if model.spin_polarization == :spinless
+        error("spin_polarization == spinless is not supported by abinit")
+    elseif model.spin_polarization == :none
         infile.set_vars(nsppol=1, nspinor=1, nspden=1)
-    elseif model.spin_polarisation == :collinear
+    elseif model.spin_polarization == :collinear
         infile.set_vars(nsppol=2, nspinor=1, nspden=2)
-    elseif model.spin_polarisation == :full
+    elseif model.spin_polarization == :full
         infile.set_vars(nsppol=1, nspinor=2, nspden=4)
     end
 
@@ -119,14 +119,14 @@ function run_abinit_scf(model::Model, outdir;
         end
     end
 
-    # Spin-polarisation
-    if model.spin_polarisation == :spinless
-        error("spin_polarisation == spinless is not supported by abinit")
-    elseif model.spin_polarisation == :none
+    # Spin-polarization
+    if model.spin_polarization == :spinless
+        error("spin_polarization == spinless is not supported by abinit")
+    elseif model.spin_polarization == :none
         infile.set_vars(nsppol=1, nspinor=1, nspden=1)
-    elseif model.spin_polarisation == :collinear
+    elseif model.spin_polarization == :collinear
         infile.set_vars(nsppol=2, nspinor=1, nspden=2)
-    elseif model.spin_polarisation == :full
+    elseif model.spin_polarization == :full
         infile.set_vars(nsppol=1, nspinor=2, nspden=4)
     end
 

src/external/etsf_nanoquanta.jl

@@ -13,7 +13,7 @@ struct EtsfFolder
 end
 
 """
-Initialise a EtsfFolder from the path to the folder which contains
+Initialize a EtsfFolder from the path to the folder which contains
 the data in the ETSF Nanoquanta format.
 """
 function EtsfFolder(folder::AbstractString)

src/external/pymatgen.jl

@@ -37,8 +37,8 @@ function pymatgen_bandstructure(basis, λ, εF, klabels)
     Spin = pyimport("pymatgen.electronic_structure.core").Spin
     bandstructure = pyimport("pymatgen.electronic_structure.bandstructure")
 
-    # This assumes no spin polarisation
-    @assert basis.model.spin_polarisation in (:none, :spinless)
+    # This assumes no spin polarization
+    @assert basis.model.spin_polarization in (:none, :spinless)
 
     eigenvals_spin_up = Matrix{eltype(λ[1])}(undef, length(λ[1]), length(basis.kpoints))
     for (ik, λs) in enumerate(λ)

src/fft.jl

@@ -4,8 +4,8 @@ import FFTW
 Determine the minimal grid size for the cubic basis set to be able to
 represent product of orbitals (with the default `supersampling=2`).
 
-Optionally optimise the grid afterwards for the FFT procedure by
-ensuring factorisation into small primes.
+Optionally optimize the grid afterwards for the FFT procedure by
+ensuring factorization into small primes.
 
 The function will determine the smallest cube containing the wave vectors
  ``|G|^2/2 \leq E_\text{cut} ⋅ \text{supersampling}^2``.
@@ -25,7 +25,7 @@ function determine_grid_size(lattice::AbstractMatrix{T}, Ecut; supersampling=2,
         end
     end
 
-    # Optimise FFT grid size: Make sure the number factorises in small primes only
+    # Optimize FFT grid size: Make sure the number factorises in small primes only
     if ensure_smallprimes
         Vec3([nextprod([2, 3, 5], 2gs + 1) for gs in Gmax])
     else

src/fft_generic.jl

@@ -11,7 +11,7 @@ const GENERIC_FFT_LOADED = true
 
 function next_working_fft_size(::Any, size)
     # TODO FourierTransforms has a bug, which is triggered
-    #      only in some factorisations, see
+    #      only in some factorizations, see
     #      https://github.com/JuliaComputing/FourierTransforms.jl/issues/10
     # To be safe we fall back to powers of two
 
@@ -22,7 +22,7 @@ function next_working_fft_size(::Any, size)
     adjusted
 end
 
-# Generic fallback function, Float32 and Float64 specialisation in fft.jl
+# Generic fallback function, Float32 and Float64 specialization in fft.jl
 function build_fft_plans(T, fft_size)
     tmp = Array{Complex{T}}(undef, fft_size...)
 

src/interpolation.jl

@@ -9,7 +9,7 @@ function interpolate_density(ρ_in::RealFourierArray, b_out::PlaneWaveBasis)
     from_real(b_out, ρ_out)
 end
 
-# TODO Specialisation for the common case lattice_out = lattice_in
+# TODO Specialization for the common case lattice_out = lattice_in
 function interpolate_density(ρ_in::AbstractArray, grid_in, grid_out, lattice_in, lattice_out=lattice_in)
     T = real(eltype(ρ_in))
     @assert size(ρ_in) == grid_in
@@ -64,7 +64,7 @@ end
 
 """
 Interpolate some data from one k-Point to another. The interpolation is fast, but not
-necessarily exact or even normalised. Intended only to construct guesses for iterative
+necessarily exact or even normalized. Intended only to construct guesses for iterative
 solvers
 """
 function interpolate_kpoint(data_in::AbstractVecOrMat, kpoint_in::Kpoint, kpoint_out::Kpoint)
@@ -102,7 +102,7 @@ function interpolate_blochwave(ψ_in, basis_in, basis_out)
         # Get indices of the G vectors of the old basis inside the new basis.
         idcs_out = index_G_vectors.(Ref(basis_out), G_vectors(basis_in.kpoints[ik]))
 
-        # Linearise the indices
+        # Linearize the indices
         idcs_out = getindex.(Ref(LinearIndices(basis_out.fft_size)), idcs_out)
 
         # Map to the indices of the corresponding G-vectors in G_vectors(kpt_out)

src/occupation.jl

@@ -13,7 +13,7 @@ end
 Find the occupation and Fermi level.
 """
 function find_occupation(basis::PlaneWaveBasis{T}, energies) where {T}
-    @assert basis.model.spin_polarisation in (:none, :spinless)
+    @assert basis.model.spin_polarization in (:none, :spinless)
     model = basis.model
     n_electrons = model.n_electrons
     temperature = model.temperature
@@ -80,7 +80,7 @@ and zero temperature. This function is for DEBUG purposes only, and the
 finite-temperature version with 0 temperature should be preferred.
 """
 function find_occupation_bandgap(basis, energies)
-    @assert basis.model.spin_polarisation in (:none, :spinless)
+    @assert basis.model.spin_polarization in (:none, :spinless)
     n_bands = length(energies[1])
     @assert all(e -> length(e) == n_bands, energies)
     n_electrons = basis.model.n_electrons

src/postprocess/DOS.jl

@@ -76,6 +76,6 @@ function LDOS(ε, basis, eigenvalues, ψ; smearing=basis.model.smearing, T=basis
 
     # Use compute_density routine to compute LDOS, using just the modified
     # weights (as "occupations") at each kpoint. Note, that this automatically puts in the
-    # required symmetrisation with respect to kpoints and BZ symmetry
+    # required symmetrization with respect to kpoints and BZ symmetry
     compute_density(basis, ψ, weights).real
 end