0.7 Deprecations fix

.travis.yml

@@ -5,7 +5,6 @@ os:
   - osx
 julia:
   # - release
-  - 0.7.0-beta2
   - nightly
 notifications:
   email: false

src/Agents/AgentBase.jl

@@ -30,7 +30,6 @@ Prints information about agent into the specified I/O.
 ```julia-repl
 ```
 """
-# import Base.show
 function Base.show( io::IO, ::MIME"text/plain", agent::AgentBase )
     print( io, @sprintf("Agent: %s",info_str(agent)) )
     for param in fieldnames(agent)
@@ -77,7 +76,7 @@ function ==( agent1::AgentBase, agent2::AgentBase )
     if typeof(agent1) != typeof(agent2)
         return false
     else
-        for param in fieldnames(agent1)
+        for param in fieldnames(typeof(agent1))
             if getfield(agent1,param) != getfield(agent2,param)
                 # info( "Failed at ", param )
                 return false

src/Agents/EpsilonGreedy.jl

@@ -3,8 +3,7 @@
 Implements constant exploration ϵ-greedy agent. `noOfArms` is the number
 of arms to pick from and `ϵ` is the exploration factor.
 """
-
-type epsGreedy <: StationaryAgentBase
+mutable struct epsGreedy <: StationaryAgentBase
     noOfArms::Int64
     noOfSteps::Int64
     lastPlayedArm::Int64
@@ -73,8 +72,7 @@ of options, `c` and `d` are algorithm dependent parameters.
 
 Reference: Auer, P., Bianchi, N. C., & Fischer, P. (2002). Finite time analysis of the multiarmed bandit problem. Machine Learning, 47, 235–256.
 """
-
-type epsNGreedy <: StationaryAgentBase
+mutable struct epsNGreedy <: StationaryAgentBase
     noOfArms::Int64
     noOfSteps::Int64
     lastPlayedArm::Int64

src/Agents/StationaryAgentBase.jl

@@ -6,7 +6,6 @@
 arms. Even though it is not enforced, the assumption is the reward updated to
 stationary agents are from a stationary arm model.
 """
-
 abstract type StationaryAgentBase <: AgentBase end
 
 """

src/Arms/NonStationaryArms.jl

@@ -16,7 +16,7 @@ should switch from 0 to 1 from the start of period. `holdDuration` (Int) is the
 for which the pulse should stay 1. `isRestless` (bool) sets whether the arm is
 restless or not.
 """
-type Pulse <: NonstationaryArmBase
+mutable struct Pulse <: NonstationaryArmBase
     step::Int             # For tracking internally
     period::Int           # Period of the pulse
     changePoint::Int      # The point at which the signal goes high
@@ -40,7 +40,7 @@ function pull!( arm::Pulse )
         arm.step = 1
     end
 
-    return ((arm.step>=arm.changePoint)&&(arm.step<=arm.changePoint+arm.highDuration))?1:0;
+    return ((arm.step>=arm.changePoint)&&(arm.step<=arm.changePoint+arm.highDuration))  ? 1 : 0;
 end
 
 function tick!( arm::Pulse )
@@ -65,7 +65,7 @@ end
 `period`. `isRestless` (bool) sets whether the arm is restless or not. `offset`
 sets the offset for the arm (set to a random offset by default).
 """
-type Sinusoidal <: NonstationaryArmBase
+mutable struct Sinusoidal <: NonstationaryArmBase
     step::Int         # Time step
     period::Int       # Period of the sinusoidal wave
     isRestless::Bool    # Is this arm restless - True by default
@@ -108,7 +108,7 @@ a default value of `0` and changes to values as per the dictionary of changePoin
 arm1 = Arms.Square( 50, Dict(10=>0.5,25=>0.20,40=>1.0) )
 ```
 """
-type Square <: NonstationaryArmBase
+mutable struct Square <: NonstationaryArmBase
     step::Int                         # For internal tracking
     period::Int                       # Period at which wave repeats
     changePoints::Dict{Int,Float64}   # Dictionary of change points
@@ -163,7 +163,7 @@ end
 `Variational` creates a nonstationary arm as mentioned in
     Besbes, O., Gur, Y., & Zeevi, A. (2014). Optimal Exploration-Exploitation in a Multi-Armed-Bandit Problem with Non-stationary Rewards, 1–20.
 """
-type Variational <: NonstationaryArmBase
+mutable struct Variational <: NonstationaryArmBase
     step::Int64         # Time step
     variation::Float64  # Variation of the arms
     period::Float64     # Period of the sinusoidal wave

src/Arms/StationaryArms.jl

@@ -18,7 +18,7 @@ mean( arm::StationaryArmBase )      = Distributions.mean( arm.armDist )
     Bernoulli( p )
 `Bernoulli` creates a Bernoulli arm with success probability `p`.
 """
-type Bernoulli <: StationaryArmBase
+mutable struct Bernoulli <: StationaryArmBase
     armDist::Distributions.Bernoulli
 
     function Bernoulli( p::Real )
@@ -36,8 +36,7 @@ end
 
 `Beta` creates a Beta arm with parameters `α` and `β`.
 """
-
-type Beta <: StationaryArmBase
+mutable struct Beta <: StationaryArmBase
     armDist::Distributions.Beta
 
     function Beta( α::Real, β::Real )
@@ -55,8 +54,7 @@ end
 
 `Expoenential` creates a Expoenentially distributed arm with mean reward `θ`
 """
-
-type Exponential <: StationaryArmBase
+mutable struct Exponential <: StationaryArmBase
     armDist::Distributions.Exponential
 
     function Exponential( λ::Real ) # λ is the mean parameter
@@ -75,7 +73,7 @@ end
 Creates an arm with reward distributed as Normal random varaible with mean `μ`
 and standard deviation `σ`.
 """
-type Normal <: StationaryArmBase
+mutable struct Normal <: StationaryArmBase
     armDist::Distributions.Normal
 
     function Normal( μ::Real, σ::Real )

src/BanditOpt.jl

@@ -14,6 +14,7 @@ of agents and the common interface.
 module Agents
     using Distributions
     using LaTeXStrings
+    using Printf
     include( "Agents/AgentBase.jl" )
     include( "Agents/StationaryAgentBase.jl" )
 

test/Arms/StationaryArms.jl

@@ -1,4 +1,5 @@
 # Tests for Stationary Arm Model
+using InteractiveUtils
 
 @testset "Stationary Arm Models" begin
 

test/runtests.jl

@@ -1,5 +1,5 @@
 using BanditOpt
-using Base.Test
+using Test
 
 macro test_nothrow(ex)
     quote
@@ -38,7 +38,7 @@ if length(ARGS) > 0
     tests = ARGS
 end
 
-@testset "Bandit Tests" begin
+@testset "BanditOpt Tests" begin
 for test_script in tests
     fp = joinpath( dirname(@__FILE__), "$(test_script).jl" )
     # println( "Testing : ", test_script )