vwma function definition and test case fixes

src/Indicators.jl

@@ -4,7 +4,7 @@ module Indicators
     export
         runmean, runsum, runvar, runsd, runcov, runcor, runmax, runmin, runmad, runquantile, runacf,
         wilder_sum, mode, diffn,
-        sma, trima, wma, ema, mma, kama, mama, hma, swma, dema, tema, alma, zlema,
+        sma, trima, wma, ema, mma, kama, mama, hma, swma, dema, tema, alma, zlema, vwma,
         mlr_beta, mlr_slope, mlr_intercept, mlr, mlr_se, mlr_ub, mlr_lb, mlr_bands, mlr_rsq,
         aroon, donch, momentum, roc, macd, rsi, adx, psar, kst, wpr, cci, stoch, smi,
         bbands, tr, atr, keltner,

src/ma.jl

@@ -382,13 +382,14 @@ vwma(cv::Matrix{T})::Array{T}
 
 Volume weighted moving average (VWMA)
 """
-function vwma(cv::Matrix{T}, n::Int64=10)::Array{Float64} where {T<:Real}
-    @assert n<size(x,1) && n>0 "Argument n out of bounds."
-    out = zeros(size(cv))[1]
+function vwma(cv::Matrix{T}; n::Int64=10)::Array{Float64} where {T<:Real}
+    @assert n<size(cv,1) && n>0 "Argument n out of bounds."
+    N = size(cv, 1)
+    out = zeros(N)
     close_price = cv[:,1]
     volume = cv[:,2]
     out[1:n-1] .= NaN
-    @inbounds for i = n:size(close_price,1)
+    @inbounds for i = n:N
         weight = volume[i-n+1:i]   # get volumes as numerator
         d = sum(weight)  # denominator = sum(numerator weights)
         out[i] = sum(weight .* close_price[i-n+1:i]) / d

src/temporal.jl

@@ -1,31 +1,40 @@
 # Methods for porting Indicators.jl functions to TS objects from Temporal.jl package
 function close_fun(X::TS, f::Function, flds::Vector{Symbol}; args...)
     if size(X,2) == 1
-        return ts(f(X.values; args...), X.index, flds)
+        return TS(f(X.values; args...), X.index, flds)
     elseif size(X,2) > 1 && has_close(X)
-        return ts(f(cl(X).values; args...), X.index, flds)
+        return TS(f(cl(X).values; args...), X.index, flds)
     else
         error("Must be univariate or contain Close/Settle/Last.")
     end
 end
 function hlc_fun(X::TS, f::Function, flds::Vector{Symbol}; args...)
     if size(X,2) == 3
-        return ts(f(X.values; args...), X.index, flds)
+        return TS(f(X.values; args...), X.index, flds)
     elseif size(X,2) > 3 && has_high(X) && has_low(X) && has_close(X)
-        return ts(f(hlc(X).values; args...), X.index, flds)
+        return TS(f(hlc(X).values; args...), X.index, flds)
     else
         error("Argument must have 3 columns or have High, Low, and Close/Settle/Last fields.")
     end
 end
 function hl_fun(X::TS, f::Function, flds::Vector{Symbol}; args...)
     if size(X,2) == 2
-        return ts(f(X.values; args...), X.index, flds)
+        return TS(f(X.values; args...), X.index, flds)
     elseif size(X,2) > 2 && has_high(X) && has_low(X)
-        return ts(f(hl(X).values; args...), X.index, flds)
+        return TS(f(hl(X).values; args...), X.index, flds)
     else
         error("Argument must have 2 columns or have High and Low fields.")
     end
 end
+function cv_fun(X::TS, f::Function, flds::Vector{Symbol}; args...)
+    if size(X,2) == 2
+        return TS(f(X.values; args...), X.index, flds)
+    elseif size(X,2) > 2 && has_close(X) && has_volume(X)
+        return TS(f([cl(X) vo(X)].values; args...), X.index, flds)
+    else
+        error("Argument must have 2 columns or have Close and Volume fields.")
+    end
+end
 
 ###### run.jl ######
 function runcov(x::TS{V,T}, y::TS{V,T}; args...) where {V,T}
@@ -65,6 +74,7 @@ dema(X::TS{V,T}; args...) where {V,T} = close_fun(X, dema, [:DEMA]; args...)
 tema(X::TS{V,T}; args...) where {V,T} = close_fun(X, tema, [:TEMA]; args...)
 zlema(X::TS{V,T}; args...) where {V,T} = close_fun(X, zlema, [:ZLEMA]; args...)
 mama(X::TS{V,T}; args...) where {V,T} = close_fun(X, mama, [:MAMA,:FAMA]; args...)
+vwma(X::TS{V,T}; args...) where {V,T} = cv_fun(X, vwma, [:VWMA]; args...)
 
 ##### reg.jl ######
 mlr_beta(X::TS{V,T}; args...) where {V,T} = close_fun(X, mlr_beta, [:Intercept,:Slope]; args...)

test/ma.jl

@@ -3,6 +3,7 @@
     Random.seed!(SEED)
     @testset "Array" begin
         x = cumsum(randn(N))
+        X = cumsum(randn(N, 2), dims=1)
         tmp = sma(x)
         @test size(tmp, 1) == N
         @test size(tmp, 2) == 1
@@ -55,6 +56,9 @@
         @test size(tmp, 1) == N
         @test size(tmp, 2) == 1
         @test sum(isnan.(tmp)) != N
+        tmp = vwma(X)
+        @test size(tmp, 1) == N
+        @test size(tmp, 2) == 1        
     end
     @testset "Temporal" begin
         x = TS(cumsum(randn(N)))