Aqua + typos CI

.github/workflows/Downgrade.yml

@@ -7,7 +7,7 @@ on:
       - 'docs/**'
   push:
     branches:
-      - master
+      - main
     paths-ignore:
       - 'docs/**'
 jobs:

.github/workflows/SpellCheck.yml

@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v3
+      - name: Check spelling
+        uses: crate-ci/typos@v1.16.23 

.typos.toml

@@ -0,0 +1,2 @@
+[default.extend-words]
+numer = "numer"

Project.toml

@@ -14,18 +14,21 @@ SymbolicUtils = "d1185830-fcd6-423d-90d6-eec64667417b"
 Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 
 [compat]
+Aqua = "0.8"
 DataDrivenDiffEq = "1.3"
 DataDrivenSparse = "0.1.2"
 DataStructures = "0.18.13"
+LinearAlgebra = "1.10"
 SpecialFunctions = "2"
-Statistics = "1.9"
+Statistics = "1.10"
 SymbolicUtils = "1.4"
 Symbolics = "5.12"
-julia = "1.9"
-LinearAlgebra = "<0.0.1, 1"
+Test = "1"
+julia = "1.10"
 
 [extras]
+Aqua = "4c88cf16-eb10-579e-8560-4a9242c79595"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["Test"]
+test = ["Aqua", "Test"]

src/integral.jl

@@ -1,8 +1,6 @@
 using LinearAlgebra
 using Statistics: mean, std
 
-Base.signbit(z::Complex{T}) where {T <: Number} = signbit(real(z))
-Base.signbit(x::SymbolicUtils.Sym{Number}) = false
 
 """
     integrate(eq, x; kwargs...)

src/sparse.jl

@@ -52,9 +52,9 @@ function prune_basis(eq, x, basis; plan = default_plan())
     return basis[l]
 end
 
-# init_basis_matrix tranforms the integration problem into a linear system
-# 
-# It returns A, X, V, where 
+# init_basis_matrix transforms the integration problem into a linear system
+#
+# It returns A, X, V, where
 #
 #   A: the normalized training matrix, we seek a vector q such that A * q = 1
 #   X: a vector of complex test points
@@ -217,14 +217,14 @@ function hints(eq, x, basis; plan = default_plan())
 
         return h, ε
     catch e
-        # println("Error from hints: ", e)        
+        # println("Error from hints: ", e)
     end
 
     return 0, Inf
 end
 
 # best_hints works is the link between numerical and symbolic integration.
-# It convers a symbolic integrad eq into a univariate expression, performs
+# It converts a symbolic integrad eq into a univariate expression, performs
 # symbolic-numeric integration, and the returns a list of symbolic ansatzes
 # corresponding to the solution
 function best_hints(eq, x, basis; plan = default_plan(), num_trials = 10)

src/symbolic.jl

@@ -1,6 +1,6 @@
 ########################### Utility functions #########################
 
-# beautify convers floats to integers/rational numbers with small 
+# beautify converts floats to integers/rational numbers with small
 # denominators if possible
 function beautify(eq)
     if is_add(eq)
@@ -47,22 +47,22 @@ function split_terms(eq, x)
     end
 end
 
-# is_holonomic checks whether y is a holonomic function, i.e., 
+# is_holonomic checks whether y is a holonomic function, i.e.,
 # is closed under differentiation w.r.t. x
-#    
+#
 # For our purpose, we define a holonomic function as one composed
 # of the positive powers of x, sin, cos, exp, sinh, and cosh
-#    
+#
 #   Args:
 #       y: the expression to check for holonomy
 #       x: independent variable
-#        
+#
 #   Returns:
 #       true if y is holonomic
 function is_holonomic(y, x)
     y = value(y)
 
-    # technically, polynomials are not holonomic, but 
+    # technically, polynomials are not holonomic, but
     # practically we can include them
     if is_polynomial(y, x)
         return true
@@ -90,8 +90,8 @@ function is_holonomic(y, x)
     return false
 end
 
-# blender generates a list of ansatzes based on repetative 
-# differentiation. It works for holonomic functions, which 
+# blender generates a list of ansatzes based on repetitive
+# differentiation. It works for holonomic functions, which
 # are closed under differentiation.
 function blender(y, x; n = 3)
     basis = value(y)
@@ -111,7 +111,7 @@ function blender(y, x; n = 3)
     return split_terms(basis, x)
 end
 
-# subs_symbols returns a dictionary of the symbolic constants 
+# subs_symbols returns a dictionary of the symbolic constants
 # in the expression and random real value assignments.
 #
 #   Args:
@@ -138,8 +138,8 @@ function subs_symbols(eq, x; include_x = false, radius = 5.0, as_complex = true)
     return S
 end
 
-# atomize splits terms into a part dependent on x and a part 
-# constant w.r.t. variables in xs. 
+# atomize splits terms into a part dependent on x and a part
+# constant w.r.t. variables in xs.
 #
 # For example, `atomize(a*sin(b*x), x)` is `(a, sin(b*x))`)
 function atomize(eq, xs...)
@@ -165,7 +165,7 @@ function atomize(eq, xs...)
     end
 end
 
-# apply_coefs generates the final integral based on the list 
+# apply_coefs generates the final integral based on the list
 # of coefficients (q) and a list of ansatzes (ker).
 function apply_coefs(q, ker)
     s = 0
@@ -201,11 +201,11 @@ complex_from_num(x) = Complex(value(real(x)), value(imag(x)))
 ########################### Symbolic Integration #############################
 
 # integrate_symbolic is the main entry point for symbolic integration.
-#    
+#
 #   Argu:
 #       eq: the expression to integrate
 #       x: independent variable
-#        
+#
 #   Returns:
 #       the integral or nothing if no solution
 function integrate_symbolic(eq, x; plan = default_plan())
@@ -226,10 +226,10 @@ struct Problem
     x::Expression           # independent variable
     coef::Expression        # coefficient of the integrand
     ker::Array{Expression}  # the pruned list of the basis expressions (kernel)
-    plan::NumericalPlan     # the numerial plan, containing various parameters
+    plan::NumericalPlan     # the numerical plan, containing various parameters
 end
 
-# Constructor to create a Problem for integrand eq 
+# Constructor to create a Problem for integrand eq
 function Problem(eq, x; plan = default_plan())
     eq = expand(eq)
     coef, eq = atomize(eq, x)
@@ -314,14 +314,14 @@ subs_symbols(prob::Problem) = subs_symbols(prob.eq, prob.x)
 abstract type IntegrationAlgorithm end
 
 struct SymbolicIntegrator <: IntegrationAlgorithm
-    eqs::Vector{Equation}        # list of equations of the form Σ θ[i]*frag[i] ~ 0  
+    eqs::Vector{Equation}        # list of equations of the form Σ θ[i]*frag[i] ~ 0
     vars::Vector{Expression}     # list of dummy variables (θ[1], θ[2], ...)
     frags::Dict                  # Dict of fragments of form frag => expression in θs
 end
 
 @variables θ[1:30]
 
-# Constructor creating a SymbolicIntegrator algorithm 
+# Constructor creating a SymbolicIntegrator algorithm
 # from an integration Problem
 function SymbolicIntegrator(prob::Problem)
     frags = Dict()
@@ -355,16 +355,16 @@ function solver(prob::Problem, alg::SymbolicIntegrator)
         sol = apply_coefs(q, prob.ker)
         return sol
     catch e
-        # println(e) 
+        # println(e)
     end
 
     return nothing
 end
 
 # If the linear system generated by the SymbolicIntegrator solver is
-# under-determined, make_square uses semi-numerical methods to 
+# under-determined, make_square uses semi-numerical methods to
 # generate a full-rank linear system.
-# 
+#
 # The output is another SymbolicIntegrator or nothing if unsuccessful.
 function make_square(prob::Problem, alg::SymbolicIntegrator)
     n = length(alg.vars)
@@ -390,10 +390,10 @@ function make_square(prob::Problem, alg::SymbolicIntegrator)
 end
 
 struct NumericIntegrator
-    A::AbstractMatrix           # training dataset as a normalized linear system 
+    A::AbstractMatrix           # training dataset as a normalized linear system
     X::AbstractVector           # vector of test points
     V::AbstractMatrix           # verification dataset
-    basis::Vector{Expression}   # expand basis 
+    basis::Vector{Expression}   # expand basis
 end
 
 # Constructor to create a NumericIntegrator algorithm from prob

test/qa.jl

@@ -0,0 +1,11 @@
+using SymbolicNumericIntegration, Aqua
+@testset "Aqua" begin
+    Aqua.find_persistent_tasks_deps(SymbolicNumericIntegration)
+    Aqua.test_ambiguities(SymbolicNumericIntegration, recursive = false)
+    Aqua.test_deps_compat(SymbolicNumericIntegration)
+    Aqua.test_piracies(SymbolicNumericIntegration, broken = true)
+    Aqua.test_project_extras(SymbolicNumericIntegration)
+    Aqua.test_stale_deps(SymbolicNumericIntegration)
+    Aqua.test_unbound_args(SymbolicNumericIntegration)
+    Aqua.test_undefined_exports(SymbolicNumericIntegration)
+end

test/runtests.jl

@@ -7,6 +7,8 @@ using SymbolicUtils.Rewriters
 
 using Test
 
+@testset "Quality Assurance" begin include("qa.jl") end
+
 include("axiom.jl")
 
 ##############################################################################