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#162 - Add macros to automatically create boilerplate code #228

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merged 10 commits into from
Feb 11, 2018
Merged

#162 - Add macros to automatically create boilerplate code #228

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f75f6d3
add @commutative_neutral macro
schillic Feb 8, 2018
00df076
use macro
schillic Feb 8, 2018
5ddb0ca
add & use @commutative_absorbing macro
schillic Feb 8, 2018
8e9f0b8
add & use @commutative_neutral_absorbing macro
schillic Feb 8, 2018
9348d4a
docs, constructors, restructuring
schillic Feb 9, 2018
714a8eb
MinkowskiSum unit tests for neutral/absorbing element
schillic Feb 9, 2018
76da433
review: do not export, docs
schillic Feb 10, 2018
345fc24
add neutral/absorbing function and unify macros
schillic Feb 10, 2018
b85d1e4
fix docs
schillic Feb 10, 2018
c69313d
new @neutral and @absorbing macros
schillic Feb 11, 2018
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3 changes: 3 additions & 0 deletions docs/src/lib/utils.md
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Original file line number Diff line number Diff line change
Expand Up @@ -9,4 +9,7 @@ end

```@docs
sign_cadlag
@commutative_neutral
@commutative_absorbing
@commutative_neutral_absorbing
```
130 changes: 35 additions & 95 deletions src/CartesianProduct.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -20,6 +20,10 @@ The Cartesian product of three elements is obtained recursively.
See also `CartesianProductArray` for an implementation of a Cartesian product of
many sets without recursion, instead using an array.

The `EmptySet` is the absorbing element for `CartesianProduct`.

Constructors:

- `CartesianProduct{N<:Real, S1<:LazySet{N}, S2<:LazySet{N}}(X1::S1, X2::S2)`
-- default constructor

Expand All @@ -45,9 +49,12 @@ CartesianProduct(Xarr::Vector{S}) where {S<:LazySet{N}} where {N<:Real} =
: CartesianProduct(Xarr[1],
CartesianProduct(Xarr[2:length(Xarr)])))

# EmptySet is the absorbing element for CartesianProduct
@commutative_absorbing(CartesianProduct, EmptySet)

"""
```
*(X::LazySet, Y::LazySet)::CartesianProduct
*(X::LazySet, Y::LazySet)
```

Return the Cartesian product of two convex sets.
Expand All @@ -61,7 +68,7 @@ Return the Cartesian product of two convex sets.

The Cartesian product of the two convex sets.
"""
*(X::LazySet, Y::LazySet)::CartesianProduct = CartesianProduct(X, Y)
*(X::LazySet, Y::LazySet) = CartesianProduct(X, Y)

"""
×
Expand All @@ -70,43 +77,6 @@ Alias for the binary Cartesian product.
"""
×(X::LazySet, Y::LazySet) = *(X, Y)

"""
X × ∅

Right multiplication of a set by an empty set.

### Input

- `X` -- a convex set
- `∅` -- an empty set

### Output

An empty set, because the empty set is the absorbing element for the
Cartesian product.
"""
*(::LazySet, ∅::EmptySet) = ∅

"""
∅ × X

Left multiplication of a set by an empty set.

### Input

- `X` -- a convex set
- `∅` -- an empty set

### Output

An empty set, because the empty set is the absorbing element for the
Cartesian product.
"""
*(∅::EmptySet, ::LazySet) = ∅

# special case: pure empty set multiplication (we require the same numeric type)
(*(∅::E, ::E)) where {E<:EmptySet} = ∅

"""
dim(cp::CartesianProduct)::Int

Expand Down Expand Up @@ -180,32 +150,34 @@ Type that represents the Cartesian product of a finite number of convex sets.

### Notes

- `CartesianProductArray(array::Vector{<:LazySet})` -- default constructor
The `EmptySet` is the absorbing element for `CartesianProductArray`.

- `CartesianProductArray()` -- constructor for an empty Cartesian product
Constructors:
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while we are at this line, a general thought is that i find the illustration of the different constructors to be more friendly if it is given as a proper example, rather than a copy paste of the source code -- if one wants that level of detail, then it's better to just look the code, by clicking on "view source", no? (or use Julia's @edit macro). that is to say that for me we can delete this part and instead put some examples of the different uses (in another PR).

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I added #232.


- `CartesianProductArray(n::Int, [N]::Type=Float64)`
-- constructor for an empty Cartesian product with size hint and numeric type
- `CartesianProductArray(array::Vector{<:LazySet})` -- default constructor

- `CartesianProductArray([n]::Int=0, [N]::Type=Float64)`
-- constructor for an empty product with optional size hint and numeric type
"""
struct CartesianProductArray{N<:Real, S<:LazySet{N}} <: LazySet{N}
array::Vector{S}
end

# type-less convenience constructor
CartesianProductArray(arr::Vector{S}) where {S<:LazySet{N}} where {N<:Real} =
CartesianProductArray{N, S}(arr)
# constructor for an empty Cartesian product of floats
CartesianProductArray() =
CartesianProductArray{Float64, LazySet{Float64}}(Vector{LazySet{Float64}}(0))
# constructor for an empty Cartesian product with size hint and numeric type
function CartesianProductArray(n::Int, N::Type=Float64)::CartesianProductArray

# constructor for an empty product with optional size hint and numeric type
function CartesianProductArray(n::Int=0, N::Type=Float64)::CartesianProductArray
arr = Vector{LazySet{N}}(0)
sizehint!(arr, n)
return CartesianProductArray(arr)
end

"""
```
*(cpa::CartesianProductArray, S::LazySet)::CartesianProductArray
CartesianProductArray(cpa::CartesianProductArray,
S::LazySet)::CartesianProductArray
```

Multiply a convex set to a Cartesian product of a finite number of convex sets
Expand All @@ -220,14 +192,16 @@ from the right.

The modified Cartesian product of a finite number of convex sets.
"""
function *(cpa::CartesianProductArray, S::LazySet)::CartesianProductArray
function CartesianProductArray(cpa::CartesianProductArray,
S::LazySet)::CartesianProductArray
push!(cpa.array, S)
return cpa
end

"""
```
*(S::LazySet, cpa::CartesianProductArray)::CartesianProductArray
CartesianProductArray(S::LazySet,
cpa::CartesianProductArray)::CartesianProductArray
```

Multiply a convex set to a Cartesian product of a finite number of convex sets
Expand All @@ -242,52 +216,15 @@ from the left.

The modified Cartesian product of a finite number of convex sets.
"""
function *(S::LazySet, cpa::CartesianProductArray)::CartesianProductArray
push!(cpa.array, S)
return cpa
function CartesianProductArray(S::LazySet,
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ok, this change is to save the symbol * for the binary operator only, in other words these two that used to be the same are now different:

julia>  b = Ball2(zeros(2), 1.);

julia> c = CartesianProductArray([b, b])

julia> CartesianProductArray(b, c)
LazySets.CartesianProductArray{Float64,LazySets.Ball2{Float64}}(LazySets.Ball2{Float64}[LazySets.Ball2{Float64}([0.0, 0.0], 1.0), LazySets.Ball2{Float64}([0.0, 0.0], 1.0), LazySets.Ball2{Float64}([0.0, 0.0],
 1.0)])

julia> b * c
LazySets.CartesianProduct{Float64,LazySets.Ball2{Float64},LazySets.CartesianProductArray{Float64,LazySets.Ball2{Float64}}}(LazySets.Ball2{Float64}([0.0, 0.0], 1.0), LazySets.CartesianProductArray{Float64,Laz
ySets.Ball2{Float64}}(LazySets.Ball2{Float64}[LazySets.Ball2{Float64}([0.0, 0.0], 1.0), LazySets.Ball2{Float64}([0.0, 0.0], 1.0), LazySets.Ball2{Float64}([0.0, 0.0], 1.0)]))

i doubt a bit, but maybe it is more sensible the new behavior.

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Actually I wanted to discuss this.
Previously * and CartesianProduct were not identical. I found this inconsistent, because *(S, T) was said to be an alias for CartesianProduct(S, T).
Now it is identical, but we get what you observed.

I propose to additionally add a similar macro relating CartesianProduct and CartesianProductArray (and similarly for the other two) such that we also get the old behavior.
If you agree, should I do it here or in a follow-up PR?

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follow-up PR

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Okay, I took a note in the related issue #162.

cpa::CartesianProductArray)::CartesianProductArray
return CartesianProductArray(cpa, S)
end

"""
```
*(cpa::CartesianProductArray, ∅::EmptySet)
```

Right multiplication of a `CartesianProductArray` by an empty set.

### Input

- `cpa` -- Cartesian product array
- `∅` -- an empty set

### Output

An empty set, because the empty set is the absorbing element for the
Cartesian product.
"""
*(::CartesianProductArray, ∅::EmptySet) = ∅

"""
```
*(S::EmptySet, cpa::CartesianProductArray)
```

Left multiplication of a set by an empty set.

### Input

- `X` -- a convex set
- `∅` -- an empty set

### Output

An empty set, because the empty set is the absorbing element for the
Cartesian product.
"""
*(∅::EmptySet, ::CartesianProductArray) = ∅

"""
```
*(cpa1::CartesianProductArray, cpa2::CartesianProductArray)::CartesianProductArray
CartesianProductArray(cpa1::CartesianProductArray,
cpa2::CartesianProductArray)::CartesianProductArray
```

Multiply a finite Cartesian product of convex sets to another finite Cartesian
Expand All @@ -302,12 +239,15 @@ product.

The modified first Cartesian product.
"""
function *(cpa1::CartesianProductArray,
cpa2::CartesianProductArray)::CartesianProductArray
function CartesianProductArray(cpa1::CartesianProductArray,
cpa2::CartesianProductArray)::CartesianProductArray
append!(cpa1.array, cpa2.array)
return cpa1
end

# EmptySet is the absorbing element for CartesianProduct
@commutative_absorbing(CartesianProductArray, EmptySet)

"""
array(cpa::CartesianProductArray{N, S})::Vector{S} where {N<:Real, S<:LazySet{N}}

Expand Down
70 changes: 26 additions & 44 deletions src/ConvexHull.jl
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Expand Up @@ -16,6 +16,10 @@ Type that represents the convex hull of the union of two convex sets.
- `X` -- convex set
- `Y` -- convex set

### Notes

The `EmptySet` is the neutral element for `ConvexHull`.

### Examples

Convex hull of two 100-dimensional Euclidean balls:
Expand All @@ -42,48 +46,16 @@ end
ConvexHull(X::S1, Y::S2) where {S1<:LazySet{N}, S2<:LazySet{N}} where {N<:Real} =
ConvexHull{N, S1, S2}(X, Y)

# EmptySet is the neutral element for ConvexHull
@commutative_neutral(ConvexHull, EmptySet)

"""
CH

Alias for `ConvexHull`.
"""
const CH = ConvexHull

"""
ConvexHull(X, ∅)

Convex hull of a set with the empty set from the right.

### Input

- `X` -- a convex set
- `∅` -- an empty set

### Output

The given set because the empty set is neutral for the convex hull.
"""
ConvexHull(X::LazySet{N}, ::EmptySet{N}) where {N<:Real} = X

"""
ConvexHull(∅, X)

Convex hull of a set with the empty set from the left.

### Input

- `∅` -- an empty set
- `X` -- a convex set

### Output

The given set because the empty set is neutral for the convex hull.
"""
ConvexHull(::EmptySet{N}, X::LazySet{N}) where {N<:Real} = X

# special case: pure empty set convex hull (we require the same numeric type)
(ConvexHull(∅::E, ::E)) where {E<:EmptySet} = ∅

"""
dim(ch::ConvexHull)::Int

Expand Down Expand Up @@ -132,6 +104,17 @@ Type that represents the symbolic convex hull of a finite number of convex sets.

- `array` -- array of sets

### Notes

The `EmptySet` is the neutral element for `ConvexHullArray`.

Constructors:

- `ConvexHullArray(array::Vector{<:LazySet})` -- default constructor

- `ConvexHullArray([n]::Int=0, [N]::Type=Float64)`
-- constructor for an empty hull with optional size hint and numeric type

### Examples

Convex hull of 100 two-dimensional balls whose centers follows a sinusoidal:
Expand All @@ -145,29 +128,28 @@ julia> c = ConvexHullArray(b);
struct ConvexHullArray{N<:Real, S<:LazySet{N}} <: LazySet{N}
array::Vector{S}
end
# type-less convenience constructor
ConvexHullArray(a::Vector{S}) where {S<:LazySet{N}} where {N<:Real} = ConvexHullArray{N, S}(a)

# constructor for an empty convex hull array
ConvexHullArray() = ConvexHullArray{Float64, LazySet{Float64}}(Vector{LazySet{Float64}}(0))
# type-less convenience constructor
ConvexHullArray(a::Vector{S}) where {S<:LazySet{N}} where {N<:Real} =
ConvexHullArray{N, S}(a)

# constructor for an empty convex hull array with size hint and numeric type
function ConvexHullArray(n::Int, N::Type=Float64)::ConvexHullArray
# constructor for an empty hull with optional size hint and numeric type
function ConvexHullArray(n::Int=0, N::Type=Float64)::ConvexHullArray
a = Vector{LazySet{N}}(0)
sizehint!(a, n)
return ConvexHullArray(a)
end

# EmptySet is the neutral element for ConvexHullArray
@commutative_neutral(ConvexHullArray, EmptySet)

"""
CHArray

Alias for `ConvexHullArray`.
"""
const CHArray = ConvexHullArray

CH(cha::ConvexHullArray, ∅::EmptySet) = cha
CH(∅::EmptySet, cha::ConvexHullArray) = cha

CH(cha1::ConvexHullArray, cha2::ConvexHullArray) = ConvexHullArray(vcat(cha1.array, cha2.array))

"""
Expand Down
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