Increase code coverage

.github/codecov.yml

@@ -0,0 +1,4 @@
+coverage:
+  precision: 2
+  round: down
+  range: 85...95 # FIXME: We should set this one to about 90...95

src/KnownProperties.jl

@@ -42,11 +42,3 @@ ERROR: MethodError: no method matching is_known(::typeof(dim), ::AbstractAlgebra
 ```
 """
 function is_known end
-
-# A generic implementation to look up attributes. This can be used to implement 
-# `is_known` for a specific type of arguments of unary functions.
-function _is_known_via_attributes(f::Function, x::Any)
-  @req _is_attribute_storing_type(typeof(x)) "objects of type $(typeof(x)) do not support attribute storage"
-  return has_attribute(x, nameof(f))
-end
-

src/NCPoly.jl

@@ -145,11 +145,16 @@ number_of_generators(R::NCPolyRing) = 1
 #
 ###############################################################################
 
-function show(io::IO, p::NCPolyRing)
+function show(io::IO, p::Union{NCPolyRing, PolyRing})
    @show_name(io, p)
    @show_special(io, p)
-   print(io, "Univariate polynomial ring in ", var(p), " over ")
-   print(terse(pretty(io)), Lowercase(), base_ring(p))
+   if is_terse(io)
+      print(io, "Univariate polynomial ring")
+   else
+      io = pretty(io)
+      print(io, "Univariate polynomial ring in ", var(p), " over ")
+      print(terse(io), Lowercase(), base_ring(p))
+   end
 end
 
 ###############################################################################

src/Poly.jl

@@ -471,18 +471,6 @@ end
 
 @enable_all_show_via_expressify Union{PolynomialElem, NCPolyRingElem}
 
-function show(io::IO, p::PolyRing)
-   @show_name(io, p)
-   @show_special(io, p)
-   if is_terse(io)
-      print(io, "Univariate polynomial ring")
-   else
-      io = pretty(io)
-      print(io, "Univariate polynomial ring in ", var(p), " over ")
-      print(terse(io), Lowercase(), base_ring(p))
-   end
-end
-
 ###############################################################################
 #
 #   Unary operations

src/generic/Misc/Poly.jl

@@ -13,7 +13,7 @@ function is_power(a::PolyRingElem, n::Int)
     fl || return false, a
     f = factor(a)
     all(i -> i % n == 0, values(f.fac)) || return false, a
-    return true, x*prod(p^div(k, n) for (p, k) = f.fac)
+    return true, f.unit * prod(p^div(k, n) for (p, k) = f.fac)
 end
 
 ################################################################################

src/julia/Matrix.jl

@@ -112,7 +112,7 @@ end
 function swap_cols!(a::Matrix{T}, i::Int, j::Int) where T <: NCRingElement
    if i != j
       for k = 1:nrows(a)
-         a[k, i], a[k, j] = a[k, i], a[k, j]
+         a[k, i], a[k, j] = a[k, j], a[k, i]
       end
    end
    return a

test/Rings-test.jl

@@ -1,4 +1,5 @@
 include("julia/Integers-test.jl")
+include("julia/Matrix-test.jl")
 include("broadcasting-test.jl")
 
 # artificially low cutoffs for testing purposes
@@ -62,6 +63,16 @@ end
    end
 end
 
+@testset "sqrt" begin
+  Base.sqrt(a::EuclideanRingResidueRingElem{BigInt}) = parent(a)(BigInt(sqrt(a.data)))
+  R = residue_ring(ZZ, 101)[1]
+
+  @test sqrt(R(81), check=true) == R(9)
+  @test_throws ErrorException sqrt(R(82), check=true)
+  @test is_square_with_sqrt(R(16)) == (true, R(4))
+  @test is_square_with_sqrt(R(15))[1] == false
+end
+
 @testset "properties" begin
   @test is_perfect(QQ)
   @test is_perfect(GF(2))

test/generic/Poly-test.jl

@@ -3053,3 +3053,66 @@ end
   @test is_separable(x)
   @test !is_separable(x^2)
 end
+
+@testset "Generic.Poly.Misc" begin
+  # factor function is required for is_power.  Implement naive ones here.
+  function AbstractAlgebra.factor(a::Integer)
+    R = parent(a)
+    f = Fac{typeof(a)}()
+    f.unit = sign(a)
+    a = abs(a)
+    for ix in [R(2), R(3), R(5), R(7), R(11)]
+      if is_zero(a % ix)
+        a /= ix
+        f.fac[ix] = 1
+      end
+      while is_zero(a % ix)
+        a /= ix
+        f.fac[ix] += 1
+      end
+    end
+    if !is_one(a)
+      error()
+    end
+    return f
+  end
+  function AbstractAlgebra.factor(p::PolyRingElem)
+    P = parent(p)
+    x = gen(P)
+    f = Fac{typeof(p)}()
+    ct = content(p)
+    cf = factor(ct)
+    ut = sign(leading_coefficient(p))
+    for (t, k) in cf
+      f.fac[P(t)] = k
+    end
+    f.unit = P(ut)
+    p /= ut * ct
+    for y in [x + c for c in -2:2]
+      if is_zero(p % y)
+        p /= y
+        f.fac[y] = 1
+      end
+      while is_zero(p % y)
+        p /= y
+        f.fac[y] += 1
+      end
+    end
+    if !is_one(p)
+      error()
+    end
+    return f
+  end
+  ZZx, x = ZZ[:x]
+  @test is_power(x, 2) == (false, x)
+  @test is_power(x, 3) == (false, x)
+  @test is_power(x^2, 2) == (true, x)
+  @test is_power(3 * x^2, 2) == (false, 3 * x^2)
+  @test is_power(2^2 * x^2, 2) == (true, 2 * x)
+  @test is_power(2^3 * x^3, 3) == (true, 2 * x)
+  @test is_power(3^4 * x^4, 2) == (true, 9 * x^2)
+  @test is_power(-3^4 * x^4, 2) == (false, -81 * x^4)
+  @test is_power(-3^3 * x^3, 3) == (true, -3 * x)
+  @test is_power(3^2 * (x + 1)^2 * x^2, 2) == (true, 3 * (x + 1) * x)
+  @test is_power(-3^2 * (x + 1)^2 * x^2, 2) == (false, -3^2 * (x + 1)^2 * x^2)
+end

test/julia/Matrix-test.jl

@@ -0,0 +1,36 @@
+@testset "Julia.Matrix.manipulation" begin
+  r, c = 1, 2
+  A = zero_matrix(Int, r, c)
+  A[1, :] = [10, -2]
+  B = Int[10 -2]
+
+  @test A == B
+  @test number_of_rows(A) == r
+  @test number_of_columns(A) == c
+end
+
+@testset "Julia.Matrix.array_creation" begin
+  M = matrix_ring(ZZ, 2)
+  m1 = M(ZZ[1 2; 3 4])
+  m2 = M(ZZ[1 0; 0 1])
+  arr = Array(M, 2)
+  arr[1] = deepcopy(m1)
+  arr[2] = deepcopy(m2)
+  @test arr[1] == m1
+  @test arr[2] == m2
+end
+
+@testset "Julia.Matrix.permutations" begin
+  M = matrix_ring(ZZ, 2)
+  m0 = M([1 2; 3 4])
+  m1 = M([2 3; 4 5])
+  m2 = M([3 4; 5 6])
+  m3 = M([4 5; 6 7])
+  m = elem_type(M)[m0 m1; m2 m3]
+  Rm = elem_type(M)[m2 m3; m0 m1]
+  Cm = elem_type(M)[m1 m0; m3 m2]
+  rm = swap_rows(m, 2, 1)
+  cm = swap_cols(m, 1, 2)
+  @test rm == Rm
+  @test cm == Cm
+end