# *****************************************************************************
# Written by Ritchie Lee, ritchie.lee@sv.cmu.edu
# *****************************************************************************
# Copyright ã ``2015, United States Government, as represented by the
# Administrator of the National Aeronautics and Space Administration. All
# rights reserved.  The Reinforcement Learning Encounter Simulator (RLES)
# platform is licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License. You
# may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable
# law or agreed to in writing, software distributed under the License is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the specific language
# governing permissions and limitations under the License.
# _____________________________________________________________________________
# Reinforcement Learning Encounter Simulator (RLES) includes the following
# third party software. The SISLES.jl package is licensed under the MIT Expat
# License: Copyright (c) 2014: Youngjun Kim.
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to
# deal in the Software without restriction, including without limitation the
# rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
# sell copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
# The above copyright notice and this permission notice shall be included in
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# "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT
# NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR
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# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN
# ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
# CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
# *****************************************************************************

#Implementation of the functions in grammar

using DataFrames

typealias RealVec Vector{Float64}
typealias BoolVec Vector{Bool}

function eq(v1::BoolVec, v2::BoolVec)
    r = similar(v1) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] == v2[i]
    end
    r
end
function eq(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] == v2[i]
    end
    r
end
function eq(v1::RealVec, b::Real)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] == b
    end
    r
end
function lt(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] < v2[i]
    end
    r
end
function lt(v1::RealVec, b::Real)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] < b
    end
    r
end
function lte(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] <= v2[i]
    end
    r
end

function lte(v1::RealVec, b::Real)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] <= b
    end
    r
end

function gt(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] > v2[i]
    end
    r
end

function gt(v1::RealVec, b::Real)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] > b
    end
    r
end

function gte(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] >= v2[i]
    end
    r
end

function gte(v1::RealVec, b::Real)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] >= b
    end
    r
end

function feq{T}(D::DataFrame, col_id::Int64, V::Vector{T}, val_id::Int64)
    v1 = get_ref(D, col_id)
    b = get_val(V, col_id, val_id)
    eq(v1, b)
end
function flt{T}(D::DataFrame, col_id::Int64, V::Vector{T}, val_id::Int64)
    v1 = get_ref(D, col_id)
    b = get_val(V, col_id, val_id)
    lt(v1, b)
end
function flte{T}(D::DataFrame, col_id::Int64, V::Vector{T}, val_id::Int64)
    v1 = get_ref(D, col_id)
    b = get_val(V, col_id, val_id)
    lte(v1, b)
end
function fgt{T}(D::DataFrame, col_id::Int64, V::Vector{T}, val_id::Int64)
    v1 = get_ref(D, col_id)
    b = get_val(V, col_id, val_id)
    gt(v1, b)
end
function fgte{T}(D::DataFrame, col_id::Int64, V::Vector{T}, val_id::Int64)
    v1 = get_ref(D, col_id)
    b = get_val(V, col_id, val_id)
    gte(v1, b)
end

eventually(v::BoolVec) = any(v)
globally(v::BoolVec) = all(v)

function implies(v1::BoolVec, v2::BoolVec)
    r = similar(v1) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v2[i] || !v1[i]
    end
    all(r)
end

function sign_(v1::RealVec, v2::RealVec)
    r = fill(false, length(v1)) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] * v2[i] >= 0.0
    end
    r
end

or(x1::Bool, x2::Bool) = x1 || x2
function or(v1::BoolVec, v2::BoolVec)
    r = similar(v1) 
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] || v2[i] 
    end
    r 
end

and(x1::Bool, x2::Bool) = x1 && x2
function and(v1::BoolVec, v2::BoolVec)
    r = similar(v1)
    @simd for i = 1:length(v1)
        @inbounds r[i] = v1[i] && v2[i] 
    end
    r 
end

not(x) = !x
function not(v::BoolVec)
    r = similar(v)
    @simd for i = 1:length(v)
        @inbounds r[i] = !v[i]
    end
    r 
end

#get
get_ref(D::DataFrame, id::Int64) = D[id]
get_val{T}(V::Vector{T}, col_id::Int64, val_id::Int64) = V[col_id][val_id]

