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output types to float. input types within the reals.
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@dysonance
dysonance committed Jul 8, 2020
1 parent f1c1242 commit f943b94
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Showing 6 changed files with 121 additions and 121 deletions.
32 changes: 16 additions & 16 deletions src/ma.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -5,25 +5,25 @@ sma(x::Array{T}; n::Int64=10)::Array{T}
Simple moving average (SMA)
"""
function sma(x::Array{T}; n::Int64=10)::Array{T} where {T<:Real}
function sma(x::Array{T}; n::Int64=10)::Array{Float64} where {T<:Real}
return runmean(x, n=n, cumulative=false)
end

"""
```
trima(x::Array{T}; n::Int64=10, ma::Function=sma, args...)::Array{T}
trima(x::Array{T}; n::Int64=10, ma::Function=sma, args...)::Array{Float64}
```
Triangular moving average (TRIMA)
"""
function trima(x::Array{T}; n::Int64=10, ma::Function=sma)::Array{T} where {T<:Real}
function trima(x::Array{T}; n::Int64=10, ma::Function=sma)::Array{Float64} where {T<:Real}
return ma(ma(x, n=n), n=n)
end

"""
```
wma(x::Array{T}; n::Int64=10, wts::Array{T}=collect(1:n)/sum(1:n))::Array{T}
wma(x::Array{T}; n::Int64=10, wts::Array{T}=collect(1:n)/sum(1:n))::Array{Float64}
```
Weighted moving average (WMA)
Expand Down Expand Up @@ -52,7 +52,7 @@ end

"""
```
ema(x::Array{T}; n::Int64=10, alpha::T=2.0/(n+1.0), wilder::Bool=false)::Array{T}
ema(x::Array{T}; n::Int64=10, alpha::T=2.0/(n+1.0), wilder::Bool=false)::Array{Float64}
```
Exponential moving average (EMA)
Expand All @@ -74,7 +74,7 @@ end

"""
```
mma(x::Array{T}; n::Int64=10)::Array{T}
mma(x::Array{T}; n::Int64=10)::Array{Float64}
```
Modified moving average (MMA)
Expand All @@ -85,7 +85,7 @@ end

"""
```
dema(x::Array{T}; n::Int64=10, alpha=2.0/(n+1), wilder::Bool=false)::Array{T}
dema(x::Array{T}; n::Int64=10, alpha=2.0/(n+1), wilder::Bool=false)::Array{Float64}
```
Double exponential moving average (DEMA)
Expand All @@ -98,7 +98,7 @@ end

"""
```
tema(x::Array{T}; n::Int64=10, alpha=2.0/(n+1), wilder::Bool=false)::Array{T}
tema(x::Array{T}; n::Int64=10, alpha=2.0/(n+1), wilder::Bool=false)::Array{Float64}
```
Triple exponential moving average (TEMA)
Expand All @@ -114,12 +114,12 @@ end

"""
```
mama(x::Array{T}; fastlimit::T=0.5, slowlimit::T=0.05)::Matrix{T}
mama(x::Array{T}; fastlimit::T=0.5, slowlimit::T=0.05)::Matrix{Float64}
```
MESA adaptive moving average (MAMA)
"""
function mama(x::Array{T}; fastlimit::T=0.5, slowlimit::T=0.05)::Matrix{T} where {T<:Real}
function mama(x::Array{T}; fastlimit::T=0.5, slowlimit::T=0.05)::Matrix{Float64} where {T<:Real}
n = size(x,1)
out = zeros(T, n, 2)
#smooth = [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
Expand Down Expand Up @@ -281,7 +281,7 @@ end

"""
```
hma(x::Array{T}; n::Int64=20)::Array{T}
hma(x::Array{T}; n::Int64=20)::Array{Float64}
```
Hull moving average (HMA)
Expand Down Expand Up @@ -330,12 +330,12 @@ end

"""
```
alma{T}(x::Array{T}; n::Int64=9, offset::T=0.85, sigma::T=6.0)::Array{T}
alma{T}(x::Array{T}; n::Int64=9, offset::T=0.85, sigma::T=6.0)::Array{Float64}
```
Arnaud-Legoux moving average (ALMA)
"""
function alma(x::Array{T}; n::Int64=9, offset::T=0.85, sigma::T=6.0)::Array{T} where {T<:Real}
function alma(x::Array{T}; n::Int64=9, offset::T=0.85, sigma::T=6.0)::Array{Float64} where {T<:Real}
@assert n<size(x,1) && n>0 "Argument n out of bounds."
@assert sigma>0.0 "Argument sigma must be greater than 0."
@assert offset>=0.0 && offset<=1 "Argument offset must be in (0,1)."
Expand All @@ -354,7 +354,7 @@ function alma(x::Array{T}; n::Int64=9, offset::T=0.85, sigma::T=6.0)::Array{T} w
return out
end

function lagged(x::Array{T}, n::Int=1)::Array{T} where {T<:Real}
function lagged(x::Array{T}, n::Int=1)::Array{Float64} where {T<:Real}
if n > 0
return [fill(NaN,n); x[1:end-n]]
elseif n < 0
Expand All @@ -366,11 +366,11 @@ end

"""
```
zlema(x::Array{T}; n::Int=10, ema_args...)::Array{T}
zlema(x::Array{T}; n::Int=10, ema_args...)::Array{Float64}
```
Zero-lag exponential moving average (ZLEMA)
"""
function zlema(x::Array{T}; n::Int=10, ema_args...)::Array{T} where {T<:Real}
function zlema(x::Array{T}; n::Int=10, ema_args...)::Array{Float64} where {T<:Real}
return ema(x+(x-lagged(x,round(Int, (n-1)/2.0))), n=n; ema_args...)
end
52 changes: 26 additions & 26 deletions src/mom.jl
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@

"""
```
aroon(hl::Matrix{T}; n::Int64=25)::Array{T}
aroon(hl::Matrix{T}; n::Int64=25)::Array{Float64}
```
Aroon up/down/oscillator
Expand All @@ -13,7 +13,7 @@ Aroon up/down/oscillator
- Column 2: Aroon Down
- Column 3: Aroon Oscillator
"""
function aroon(hl::Matrix{T}; n::Int64=25)::Matrix{T} where {T<:Real}
function aroon(hl::Matrix{T}; n::Int64=25)::Matrix{Float64} where {T<:Real}
@assert size(hl,2) == 2 "Argument `hl` must have exactly 2 columns."
@assert n < size(hl,1) "Argument `n` must be less than the number of rows in argument `hl`."
out = zeros(T, (size(hl,1),3))
Expand All @@ -30,7 +30,7 @@ end

"""
```
donch(hl::Matrix{T}; n::Int64=10, inclusive::Bool=true)::Array{T}
donch(hl::Matrix{T}; n::Int64=10, inclusive::Bool=true)::Array{Float64}
```
Donchian channel (if inclusive is set to true, will include current bar in calculations.)
Expand All @@ -41,7 +41,7 @@ Donchian channel (if inclusive is set to true, will include current bar in calcu
- Column 2: Average of highest high and lowest low of last `n` periods
- Column 3: Highest high of last `n` periods
"""
function donch(hl::Matrix{T}; n::Int64=10, inclusive::Bool=true)::Matrix{T} where {T<:Real}
function donch(hl::Matrix{T}; n::Int64=10, inclusive::Bool=true)::Matrix{Float64} where {T<:Real}
@assert size(hl,2) == 2 "Argument `hl` must have exactly 2 columns."
local lower::Array{T} = runmin(hl[:,2], n=n, cumulative=false, inclusive=inclusive)
local upper::Array{T} = runmax(hl[:,1], n=n, cumulative=false, inclusive=inclusive)
Expand All @@ -51,24 +51,24 @@ end

"""
```
momentum(x::Array{T}; n::Int64=1)::Array{T}
momentum(x::Array{T}; n::Int64=1)::Array{Float64}
```
Momentum indicator (price now vs price `n` periods back)
"""
function momentum(x::Array{T}; n::Int64=1)::Array{T} where {T<:Real}
function momentum(x::Array{T}; n::Int64=1)::Array{Float64} where {T<:Real}
@assert n>0 "Argument n must be positive."
return diffn(x, n=n)
end

"""
```
roc(x::Array{T}; n::Int64=1)::Array{T}
roc(x::Array{T}; n::Int64=1)::Array{Float64}
```
Rate of change indicator (percent change between i'th observation and (i-n)'th observation)
"""
function roc(x::Array{T}; n::Int64=1)::Array{T} where {T<:Real}
function roc(x::Array{T}; n::Int64=1)::Array{Float64} where {T<:Real}
@assert n<size(x,1) && n>0 "Argument n out of bounds."
out = zeros(size(x)) .* NaN
@inbounds for i = (n+1):size(x,1)
Expand All @@ -79,7 +79,7 @@ end

"""
```
macd(x::Array{T}; nfast::Int64=12, nslow::Int64=26, nsig::Int64=9)::Array{T}
macd(x::Array{T}; nfast::Int64=12, nslow::Int64=26, nsig::Int64=9)::Array{Float64}
```
Moving average convergence-divergence
Expand All @@ -91,7 +91,7 @@ Moving average convergence-divergence
- Column 3: MACD Histogram
"""
function macd(x::Array{T}; nfast::Int64=12, nslow::Int64=26, nsig::Int64=9,
fastMA::Function=ema, slowMA::Function=ema, signalMA::Function=sma)::Matrix{T} where {T<:Real}
fastMA::Function=ema, slowMA::Function=ema, signalMA::Function=sma)::Matrix{Float64} where {T<:Real}
out = zeros(T, (length(x),3))
out[:,1] = fastMA(x, n=nfast) - slowMA(x, n=nslow)
out[:,2] = signalMA(out[:,1], n=nsig)
Expand All @@ -101,12 +101,12 @@ end

"""
```
rsi(x::Array{T}; n::Int64=14, ma::Function=ema, args...)::Array{T}
rsi(x::Array{T}; n::Int64=14, ma::Function=ema, args...)::Array{Float64}
```
Relative strength index
"""
function rsi(x::Array{T}; n::Int64=14, ma::Function=ema, args...)::Array{T} where {T<:Real}
function rsi(x::Array{T}; n::Int64=14, ma::Function=ema, args...)::Array{Float64} where {T<:Real}
@assert n<size(x,1) && n>0 "Argument n is out of bounds."
N = size(x,1)
ups = zeros(N)
Expand All @@ -126,7 +126,7 @@ end

"""
```
adx(hlc::Array{T}; n::Int64=14, wilder=true)::Array{T}
adx(hlc::Array{T}; n::Int64=14, wilder=true)::Array{Float64}
```
Average directional index
Expand All @@ -137,7 +137,7 @@ Average directional index
- Column 2: DI-
- Column 3: ADX
"""
function adx(hlc::Array{T}; n::Int64=14, ma::Function=ema, args...)::Matrix{T} where {T<:Real}
function adx(hlc::Array{T}; n::Int64=14, ma::Function=ema, args...)::Matrix{Float64} where {T<:Real}
@assert n<size(hlc,1) && n>0 "Argument n is out of bounds."
if size(hlc,2) != 3
error("HLC array must have three columns")
Expand All @@ -164,7 +164,7 @@ end

"""
```
psar(hl::Array{T}; af_min::T=0.02, af_max::T=0.2, af_inc::T=af_min)::Array{T}
psar(hl::Array{T}; af_min::T=0.02, af_max::T=0.2, af_inc::T=af_min)::Array{Float64}
```
Parabolic stop and reverse (SAR)
Expand All @@ -175,7 +175,7 @@ Parabolic stop and reverse (SAR)
- `af_max`: maximum acceleration factor (accel factor capped at this value)
- `af_inc`: increment to the acceleration factor (speed of increase in accel factor)
"""
function psar(hl::Array{T}; af_min::T=0.02, af_max::T=0.2, af_inc::T=af_min)::Array{T} where {T<:Real}
function psar(hl::Array{T}; af_min::T=0.02, af_max::T=0.2, af_inc::T=af_min)::Array{Float64} where {T<:Real}
@assert af_min<1.0 && af_min>0.0 "Argument af_min must be in [0,1]."
@assert af_max<1.0 && af_max>0.0 "Argument af_max must be in [0,1]."
@assert af_inc<1.0 && af_inc>0.0 "Argument af_inc must be in [0,1]."
Expand Down Expand Up @@ -227,14 +227,14 @@ end
```
kst(x::Array{T};
nroc::Array{Int64}=[10,15,20,30], navg::Array{Int64}=[10,10,10,15],
wgts::Array{Int64}=collect(1:length(nroc)), ma::Function=sma)::Array{T}
wgts::Array{Int64}=collect(1:length(nroc)), ma::Function=sma)::Array{Float64}
```
KST (Know Sure Thing) -- smoothed and summed rates of change
"""
function kst(x::Array{T}; nroc::Array{Int64}=[10,15,20,30], navg::Array{Int64}=[10,10,10,15],
wgts::Array{Int64}=collect(1:length(nroc)), ma::Function=sma)::Array{T} where {T<:Real}
wgts::Array{Int64}=collect(1:length(nroc)), ma::Function=sma)::Array{Float64} where {T<:Real}
@assert length(nroc) == length(navg)
@assert all(nroc.>0) && all(nroc.<size(x,1))
@assert all(navg.>0) && all(navg.<size(x,1))
Expand All @@ -249,25 +249,25 @@ end

"""
```
wpr(hlc::Matrix{T}, n::Int64=14)::Array{T}
wpr(hlc::Matrix{T}, n::Int64=14)::Array{Float64}
```
Williams %R
"""
function wpr(hlc::Matrix{T}; n::Int64=14)::Array{T} where {T<:Real}
function wpr(hlc::Matrix{T}; n::Int64=14)::Array{Float64} where {T<:Real}
hihi = runmax(hlc[:,1], n=n, cumulative=false)
lolo = runmin(hlc[:,2], n=n, cumulative=false)
return -100 * (hihi - hlc[:,3]) ./ (hihi - lolo)
end

"""
```
cci(hlc::Matrix{T}; n::Int64=20, c::T=0.015, ma::Function=sma)::Array{T}
cci(hlc::Matrix{T}; n::Int64=20, c::T=0.015, ma::Function=sma)::Array{Float64}
```
Commodity channel index
"""
function cci(hlc::Matrix{T}; n::Int64=20, c::T=0.015, ma::Function=sma, args...)::Array{T} where {T<:Real}
function cci(hlc::Matrix{T}; n::Int64=20, c::T=0.015, ma::Function=sma, args...)::Array{Float64} where {T<:Real}
tp = (hlc[:,1] + hlc[:,2] + hlc[:,3]) ./ 3.0
dev = runmad(tp, n=n, cumulative=false, fun=mean)
avg = ma(tp, n=n; args...)
Expand All @@ -276,13 +276,13 @@ end

"""
```
stoch(hlc::Matrix{T}; nK::Int64=14, nD::Int64=3, kind::Symbol=:fast, ma::Function=sma, args...)::Matrix{T}
stoch(hlc::Matrix{T}; nK::Int64=14, nD::Int64=3, kind::Symbol=:fast, ma::Function=sma, args...)::Matrix{Float64}
```
Stochastic oscillator (fast or slow)
"""
function stoch(hlc::Matrix{T}; nK::Int64=14, nD::Int64=3,
kind::Symbol=:fast, ma::Function=sma, args...)::Matrix{T} where {T<:Real}
kind::Symbol=:fast, ma::Function=sma, args...)::Matrix{Float64} where {T<:Real}
@assert kind == :fast || kind == :slow "Argument `kind` must be either :fast or :slow"
@assert nK<size(hlc,1) && nK>0 "Argument `nK` out of bounds."
@assert nD<size(hlc,1) && nD>0 "Argument `nD` out of bounds."
Expand All @@ -301,13 +301,13 @@ end
"""
```
smi(hlc::Matrix{T}; n::Int64=13, nFast::Int64=2, nSlow::Int64=25, nSig::Int64=9,
maFast::Function=ema, maSlow::Function=ema, maSig::Function=sma)::Matrix{T}
maFast::Function=ema, maSlow::Function=ema, maSig::Function=sma)::Matrix{Float64}
```
SMI (stochastic momentum oscillator)
"""
function smi(hlc::Matrix{T}; n::Int64=13, nFast::Int64=2, nSlow::Int64=25, nSig::Int64=9,
maFast::Function=ema, maSlow::Function=ema, maSig::Function=sma)::Matrix{T} where {T<:Real}
maFast::Function=ema, maSlow::Function=ema, maSig::Function=sma)::Matrix{Float64} where {T<:Real}
hihi = runmax(hlc[:,1], n=n, cumulative=false)
lolo = runmin(hlc[:,2], n=n, cumulative=false)
hldif = hihi-lolo
Expand Down
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