Test divonne with xgiven

.cirrus.yml

@@ -2,7 +2,7 @@ task:
   matrix:
     - name: FreeBSD
       freebsd_instance:
-        image_family: freebsd-13-1
+        image_family: freebsd-13-3
       env:
         matrix:
           - JULIA_VERSION: 1
@@ -41,5 +41,5 @@ task:
     - cirrusjl build
   test_script:
     - cirrusjl test
-  coverage_script:
-    - cirrusjl coverage codecov
+  # coverage_script:
+  #   - cirrusjl coverage codecov

docs/src/index.md

@@ -539,9 +539,9 @@ These optional keywords can be passed only to [`divonne`](@ref):
     treated.
 -   `ngiven` (type: `Integer`, default: `0`): the number of points in
     the `xgiven` array
--   `ldxgiven` (type: `Integer`, default: `0`): the leading dimension of
+-   `ldxgiven` (type: `Integer`, default: `ndim`): the leading dimension of
     `xgiven`, i.e. the offset between one point and the next in memory
--   `xgiven` (type: `AbstractArray{Real}`, default:
+-   `xgiven` (type: `AbstractMatrix{Real}`, default:
     `zeros(Cdouble, ldxgiven, ngiven)`): a list of points where the
     integrand might have peaks. Divonne will consider these points when
     partitioning the integration region. The idea here is to help the

src/divonne.jl

@@ -115,7 +115,7 @@ function divonne(integrand::T, ndim::Integer=2, ncomp::Integer=1;
                  maxpass::Integer=MAXPASS, border::Real=BORDER,
                  maxchisq::Real=MAXCHISQ,
                  mindeviation::Real=MINDEVIATION,
-                 ngiven::Integer=NGIVEN, ldxgiven::Integer=LDXGIVEN,
+                 ngiven::Integer=NGIVEN, ldxgiven::Integer=ndim,
                  xgiven::Array{Cdouble,2}=zeros(Cdouble, ldxgiven,
                                                 ngiven),
                  nextra::Integer=NEXTRA,

test/runtests.jl

@@ -143,6 +143,14 @@ end
     @test_throws ArgumentError suave((x,f) -> f[1] = 1; maxevals=typemax(Int64)÷2 + 1)
 end
 
+@testset "divonne with xgiven" begin
+    # Inspired by https://discourse.julialang.org/t/slow-cubature/116120/20
+    gauss(x, x₀=0.5, μ=0.0001) = exp(-((x - x₀) / μ) ^ 2)
+    # Note: the syntax [0.5;;] to define a 1x1 matrix was introduced only in
+    # Julia v1.7, so we can't use it here.
+    @test divonne((x, y) ->  y[1] = gauss(x[1]); ngiven=1, xgiven=reshape([0.5], 1, 1)).integral[1] ≈ 0.0001772453850905516 rtol=6e-6
+end
+
 # Make sure these functions don't crash.
 Cuba.init(C_NULL, C_NULL)
 Cuba.exit(C_NULL, C_NULL)