update version to 1.1.0 and store handle to basis in Sampling objects

Project.toml

@@ -1,7 +1,7 @@
 name = "SparseIR"
 uuid = "4fe2279e-80f0-4adb-8463-ee114ff56b7d"
 authors = ["Samuel Badr <[email protected]>", "Hiroshi Shinaoka <[email protected]>", "Markus Wallerberger <[email protected]>"]
-version = "1.0.19"
+version = "1.1.0"
 
 [deps]
 Bessels = "0e736298-9ec6-45e8-9647-e4fc86a2fe38"

src/abstract.jl

@@ -176,6 +176,13 @@ Return sampling points.
 """
 sampling_points(sampling::AbstractSampling) = sampling.sampling_points
 
+"""
+    basis(sampling::AbstractSampling)
+
+Return the IR basis associated with `sampling`.
+"""
+basis(sampling::AbstractSampling) = sampling.basis
+
 function Base.show(io::IO, ::MIME"text/plain", smpl::S) where {S<:AbstractSampling}
     println(io, "$S with sampling points:")
     for p in sampling_points(smpl)[begin:(end - 1)]

src/sampling.jl

@@ -6,10 +6,11 @@ Sparse sampling in imaginary time.
 Allows the transformation between the IR basis and a set of sampling points
 in (scaled/unscaled) imaginary time.
 """
-struct TauSampling{T,TMAT,F} <: AbstractSampling{T,TMAT,F}
+struct TauSampling{T,TMAT,F,B} <: AbstractSampling{T,TMAT,F}
     sampling_points :: Vector{T}
     matrix          :: Matrix{TMAT}
     matrix_svd      :: F
+    basis           :: B
 end
 
 """
@@ -24,7 +25,7 @@ function TauSampling(basis::AbstractBasis;
         sampling_points=default_tau_sampling_points(basis), factorize=true)
     matrix = eval_matrix(TauSampling, basis, sampling_points)
     matrix_svd = factorize ? svd(matrix) : nothing
-    sampling = TauSampling(sampling_points, matrix, matrix_svd)
+    sampling = TauSampling(sampling_points, matrix, matrix_svd, basis)
     if factorize && iswellconditioned(basis) && cond(sampling) > 1e8
         @warn "Sampling matrix is poorly conditioned (cond = $(cond(sampling)))."
     end
@@ -41,11 +42,13 @@ Sparse sampling in Matsubara frequencies.
 Allows the transformation between the IR basis and a set of sampling points
 in (scaled/unscaled) imaginary frequencies.
 """
-struct MatsubaraSampling{T<:MatsubaraFreq,TMAT,F} <: AbstractSampling{T,TMAT,F}
+struct MatsubaraSampling{T<:MatsubaraFreq,TMAT,F,B<:AbstractBasis} <:
+       AbstractSampling{T,TMAT,F}
     sampling_points :: Vector{T}
     matrix          :: Matrix{TMAT}
     matrix_svd      :: F
     positive_only   :: Bool
+    basis           :: B
 end
 
 """
@@ -82,7 +85,7 @@ function MatsubaraSampling(basis::AbstractBasis; positive_only=false,
     else
         svd_matrix = nothing
     end
-    sampling = MatsubaraSampling(sampling_points, matrix, svd_matrix, positive_only)
+    sampling = MatsubaraSampling(sampling_points, matrix, svd_matrix, positive_only, basis)
     if factorize && iswellconditioned(basis) && cond(sampling) > 1e8
         @warn "Sampling matrix is poorly conditioned (cond = $(cond(sampling)))."
     end

test/sampling.jl

@@ -76,6 +76,7 @@ isdefined(Main, :sve_logistic) || include("_conftest.jl")
 
         basis = FiniteTempBasis(stat, 1, Λ; sve_result=sve_logistic[Λ])
         smpl = TauSampling(basis)
+        @test basis === SparseIR.basis(smpl)
         @test issorted(smpl.sampling_points)
         Random.seed!(5318008)
 
@@ -109,6 +110,7 @@ isdefined(Main, :sve_logistic) || include("_conftest.jl")
 
         basis = FiniteTempBasis(stat, 1, Λ; sve_result=sve_logistic[Λ])
         smpl = MatsubaraSampling(basis; positive_only)
+        @test basis === SparseIR.basis(smpl)
         if !positive_only
             @test smpl isa
                   (stat == Fermionic() ? MatsubaraSampling64F : MatsubaraSampling64B)