renamed crossinterpolate->crossinterpolate1

also introduced deprecated crossinterpolate() for eventual removal.

Author: rittermarc

src/TensorCrossInterpolation.jl

@@ -12,7 +12,7 @@ import Base: ==, +
 import Base: isempty, iterate, getindex, lastindex, broadcastable
 import Base: length, size, sum
 
-export crossinterpolate, crossinterpolate2, optfirstpivot
+export crossinterpolate1, crossinterpolate2, optfirstpivot
 export tensortrain
 
 include("util.jl")

src/tensorci1.jl

@@ -1,7 +1,7 @@
 """
     mutable struct TensorCI1{ValueType} <: AbstractTensorTrain{ValueType}
 
-Type that represents tensor cross interpolations created using the TCI1 algorithm. Users may want to create these using [`crossinterpolate`](@ref) rather than calling a constructor directly.
+Type that represents tensor cross interpolations created using the TCI1 algorithm. Users may want to create these using [`crossinterpolate1`](@ref) rather than calling a constructor directly.
 """
 mutable struct TensorCI1{ValueType} <: AbstractTensorTrain{ValueType}
     Iset::Vector{IndexSet{MultiIndex}}
@@ -469,7 +469,7 @@ end
 
 
 @doc raw"""
-    function crossinterpolate(
+    function crossinterpolate1(
         ::Type{ValueType},
         f,
         localdims::Union{Vector{Int},NTuple{N,Int}},
@@ -504,7 +504,7 @@ Notes:
 
 See also: [`optfirstpivot`](@ref), [`CachedFunction`](@ref), [`crossinterpolate2`](@ref)
 """
-function crossinterpolate(
+function crossinterpolate1(
     ::Type{ValueType},
     f,
     localdims::Union{Vector{Int},NTuple{N,Int}},
@@ -551,3 +551,30 @@ function crossinterpolate(
     errornormalization = normalizeerror ? tci.maxsamplevalue : 1.0
     return tci, ranks, errors ./ errornormalization
 end
+
+@doc raw"""
+    function crossinterpolate(
+        ::Type{ValueType},
+        f,
+        localdims::Union{Vector{Int},NTuple{N,Int}},
+        firstpivot::MultiIndex=ones(Int, length(localdims));
+        tolerance::Float64=1e-8,
+        maxiter::Int=200,
+        sweepstrategy::Symbol=:backandforth,
+        pivottolerance::Float64=1e-12,
+        verbosity::Int=0,
+        additionalpivots::Vector{MultiIndex}=MultiIndex[],
+        normalizeerror::Bool=true
+    ) where {ValueType, N}
+
+Deprecated, and only included for backward compatibility. Please use [`crossinterpolate1`](@ref) instead.
+"""
+function crossinterpolate(
+    ::Type{ValueType},
+    f,
+    localdims::Union{Vector{Int},NTuple{N,Int}},
+    firstpivot::MultiIndex=ones(Int, length(localdims));
+    kwargs...
+) where {ValueType, N}
+    return crossinterpolate1(ValueType, f, localdims, firstpivot; kwargs...)
+end

test/test_conversion.jl

@@ -1,6 +1,6 @@
 using Test
 import TensorCrossInterpolation: TensorCI1, TensorCI2, sitedims, linkdims, rank,
-    addglobalpivot!, crossinterpolate, optimize!, MatrixACA, rrlu,
+    addglobalpivot!, crossinterpolate1, optimize!, MatrixACA, rrlu,
     nrows, ncols, evaluate, left, right
 
 @testset "Conversion between rrLU and ACA" begin
@@ -40,7 +40,7 @@ end
     @test linkdims(tci2) == linkdims(tci1)
 
     f(v) = (1.0 + 2.0im) ./ (sum(v .^ 2) + 1)
-    tci1, ranks, errors = crossinterpolate(
+    tci1, ranks, errors = crossinterpolate1(
         ComplexF64,
         f,
         fill(d, n),

test/test_tensorci1.jl

@@ -98,7 +98,7 @@ import TensorCrossInterpolation: IndexSet, MultiIndex, CachedFunction, TensorCI1
             @test rank(tci) == iter
         end
 
-        tci2, ranks, errors = crossinterpolate(
+        tci2, ranks, errors = crossinterpolate1(
             ValueType,
             f,
             fill(10, n),
@@ -111,7 +111,7 @@ import TensorCrossInterpolation: IndexSet, MultiIndex, CachedFunction, TensorCI1
         @test linkdims(tci) == linkdims(tci2)
         @test rank(tci) == rank(tci2)
 
-        tci3, ranks, errors = crossinterpolate(
+        tci3, ranks, errors = crossinterpolate1(
             ValueType,
             f,
             fill(10, n),
@@ -124,7 +124,7 @@ import TensorCrossInterpolation: IndexSet, MultiIndex, CachedFunction, TensorCI1
         @test all(linkdims(tci3) .<= 200)
         @test rank(tci3) <= 200
 
-        tci4, ranks, errors = crossinterpolate(
+        tci4, ranks, errors = crossinterpolate1(
             ValueType,
             f,
             fill(10, n),

test/test_tensortrain.jl

@@ -7,7 +7,7 @@ using Optim
     g(v) = 1 / (sum(v .^ 2) + 1)
     localdims = (6, 6, 6, 6)
     tolerance = 1e-8
-    tci, ranks, errors = TCI.crossinterpolate(Float64, g, localdims; tolerance=tolerance)
+    tci, ranks, errors = TCI.crossinterpolate1(Float64, g, localdims; tolerance=tolerance)
     tt = TCI.TensorTrain(tci)
     @test rank(tci) == rank(tt)
     @test TCI.linkdims(tci) == TCI.linkdims(tt)