fix tests for Julia 1.12

Author: cortner

.github/workflows/CI.yml

@@ -20,6 +20,7 @@ jobs:
         version:
           - '1.10'
           - '1.11' 
+          - '1.12'
           # - 'nightly'
         os:
           - ubuntu-latest

README.md

@@ -9,6 +9,7 @@ This package implements a few polynomial basis types, and convenience methods fo
 * Trigonometric polynomials 
 * Complex and real spherical and solid harmonics 
 * A few quantum chemistry (atomic orbitals) basis sets 
+* Interpolate a basis onto splines
 * Utilities to recombine them into (tensor) product or compressed basis sets 
 
 We also aim to provide full `Lux.jl` integration. A possible application of this might be to implement various flavours of equivariant neural networks and related models. 

benchmark/benchmarks.jl

@@ -2,7 +2,7 @@ using Polynomials4ML
 using BenchmarkTools
 using LuxCore, Random, Zygote
 
-const P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 
 SUITE = BenchmarkGroup()

profile/ace/profile_sparseprodpool.jl

@@ -2,7 +2,7 @@ using BenchmarkTools, Test, Polynomials4ML, ChainRulesCore
 using Polynomials4ML: PooledSparseProduct, evaluate, evaluate!
 using LuxCore, Random, Zygote
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 ##
 

profile/ace/profile_sparsesymmprod.jl

@@ -6,7 +6,7 @@ using Random
 using ChainRulesCore: rrule 
 # using Zygote
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 ## 
 

profile/atomicorbitalradials/profile_gaussian.jl

@@ -8,7 +8,7 @@ using ObjectPools
 using Random
 using LuxCore
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 @info("Batched Implementation")
 @info("evaluate, evaluated, evaluated2, evaluated_dp")

profile/atomicorbitalradials/profile_slater.jl

@@ -8,7 +8,7 @@ using ObjectPools
 using Random
 using LuxCore
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 @info("Batched Implementation")
 @info("evaluate, evaluated, evaluated2, evaluated_dp")

profile/atomicorbitalradials/profile_stong.jl

@@ -8,7 +8,7 @@ using ObjectPools
 using Random
 using LuxCore
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
 
 @info("Batched Implementation")
 @info("evaluate, evaluated, evaluated2")

test/test_linear.jl

@@ -2,7 +2,8 @@ using Test, Polynomials4ML, Random, LuxCore
 using LinearAlgebra, Optimisers, ChainRulesCore, Zygote
 using ACEbase.Testing: println_slim, print_tf, fdtest
 
-P4ML = Polynomials4ML
+import Polynomials4ML as P4ML 
+
 @info("Testing LinearLayer")
 
 

test/test_mono.jl

@@ -11,7 +11,7 @@ basis = MonoBasis(N)
 @info("      correctness")
 mm = natural_indices(basis)
 for ntest = 1:30
-   local x, P 
+   local x, P, P2  
    x = 2*π * rand()
    P = basis(x)
    P2 = [ x^(m.n) for m in mm ]