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call into generix axpy! intead of the BLAS specific one #133

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23 changes: 11 additions & 12 deletions src/0.deprecated/BayesCDom.jl
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Expand Up @@ -26,13 +26,13 @@ function sampleEffectsBayesCDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, markerM
probDelta1::Float64 = 1.0/(1.0 + exp(logDelta0[1] - logDelta1))
if (rand() < probDelta1)
a[j] = gHat + randn()*sqrt(invLhs)
BLAS.axpy!(olda-a[j],x,yCorr)
BLAS.axpy!(a[j],x,gj)
axpy!(olda-a[j],x,yCorr)
axpy!(a[j],x,gj)
nAddEff = nAddEff + 1
δ[j,1] = 1
else
if (δ[j,1]!=0)
BLAS.axpy!(olda,x,yCorr)
axpy!(olda,x,yCorr)
end
a[j] = 0
δ[j,1] = 0
Expand All @@ -52,13 +52,13 @@ function sampleEffectsBayesCDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, markerM
probDelta1 = 1.0/(1.0 + exp(logDelta0[2] - logDelta1))
if (rand() < probDelta1)
d[j] = gHat + randn()*sqrt(invLhs)
BLAS.axpy!(oldd-d[j],w,yCorr)
BLAS.axpy!(d[j],w,gj)
axpy!(oldd-d[j],w,yCorr)
axpy!(d[j],w,gj)
nDomEff = nDomEff + 1
δ[j,2] = 1
else
if (δ[j,2]!=0)
BLAS.axpy!(oldd,w,yCorr)
axpy!(oldd,w,yCorr)
end
d[j] = 0
δ[j,2] = 0
Expand All @@ -67,15 +67,15 @@ function sampleEffectsBayesCDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, markerM
# estimate substitution effect by OLS
if (a[j]!=0 && d[j]==0)
α[j] = a[j]
BLAS.axpy!(1,gj,g)
BLAS.axpy!(1,gj,u)
axpy!(1,gj,g)
axpy!(1,gj,u)
elseif (a[j]==0 && d[j]!=0)
α[j] = 0
BLAS.axpy!(1,gj,g)
axpy!(1,gj,g)
elseif (a[j]!=0 && d[j]!=0)
α[j] = dot(x,gj-mean(gj))/dot(x,x)
BLAS.axpy!(1,gj,g)
BLAS.axpy!(α[j],x,u)
axpy!(1,gj,g)
axpy!(α[j],x,u)
else
α[j] = 0
end
Expand Down Expand Up @@ -235,4 +235,3 @@ function BayesCDom!(options,X,y,C,Rinv)

return output
end

23 changes: 11 additions & 12 deletions src/0.deprecated/BayesCPiDom.jl
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Expand Up @@ -28,13 +28,13 @@ function sampleEffectsBayesCPiDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, marke
probDelta1::Float64 = 1.0/(1.0 + exp(logDelta0[1] - logDelta1))
if (rand() < probDelta1)
a[j] = gHat + randn()*sqrt(invLhs)
BLAS.axpy!(olda-a[j],x,yCorr)
BLAS.axpy!(a[j],x,gj)
axpy!(olda-a[j],x,yCorr)
axpy!(a[j],x,gj)
nAddEff = nAddEff + 1
δ[j,1] = 1
else
if (δ[j,1]!=0)
BLAS.axpy!(olda,x,yCorr)
axpy!(olda,x,yCorr)
end
a[j] = 0
δ[j,1] = 0
Expand All @@ -54,13 +54,13 @@ function sampleEffectsBayesCPiDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, marke
probDelta1 = 1.0/(1.0 + exp(logDelta0[2] - logDelta1))
if (rand() < probDelta1)
d[j] = gHat + randn()*sqrt(invLhs)
BLAS.axpy!(oldd-d[j],w,yCorr)
BLAS.axpy!(d[j],w,gj)
axpy!(oldd-d[j],w,yCorr)
axpy!(d[j],w,gj)
nDomEff = nDomEff + 1
δ[j,2] = 1
else
if (δ[j,2]!=0)
BLAS.axpy!(oldd,w,yCorr)
axpy!(oldd,w,yCorr)
end
d[j] = 0
δ[j,2] = 0
Expand All @@ -69,15 +69,15 @@ function sampleEffectsBayesCPiDom!(yCorr, nObs, nMarkers, xArray, XpRinvX, marke
# estimate substitution effect by OLS
if (a[j]!=0 && d[j]==0)
α[j] = a[j]
BLAS.axpy!(1,gj,g)
BLAS.axpy!(1,gj,u)
axpy!(1,gj,g)
axpy!(1,gj,u)
elseif (a[j]==0 && d[j]!=0)
α[j] = 0
BLAS.axpy!(1,gj,g)
axpy!(1,gj,g)
elseif (a[j]!=0 && d[j]!=0)
α[j] = dot(x,gj-mean(gj))/dot(x,x)
BLAS.axpy!(1,gj,g)
BLAS.axpy!(α[j],x,u)
axpy!(1,gj,g)
axpy!(α[j],x,u)
else
α[j] = 0
end
Expand Down Expand Up @@ -224,4 +224,3 @@ function BayesCPiDom!(options,X,y,C,Rinv)

return output
end

3 changes: 1 addition & 2 deletions src/0.deprecated/BayesN.jl
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Expand Up @@ -38,7 +38,7 @@ function sampleEffectsBayesN!(yCorr, nObs, nWindows, windows, windowSizes, xArra
probDelta1 = 1.0/(1.0 + exp(logDelta0ToDelta1))
if (rand() < probDelta1)
if (Δ[i]==0)
BLAS.axpy!(-1,windowEffect,yCorr)
axpy!(-1,windowEffect,yCorr)
end
Δ[i] = 1
π = (windowSizes[i] - k)/windowSizes[i]
Expand Down Expand Up @@ -168,4 +168,3 @@ function BayesN!(options,X,y,C,Rinv)

return output
end

2 changes: 1 addition & 1 deletion src/0.deprecated/MCMC_BayesCC.jl
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Expand Up @@ -333,7 +333,7 @@ function sampleMarkerEffectsBayesCC!(xArray,xpx,wArray,alphaArray,meanAlphaArray

# adjust for locus j
for trait = 1:ntraits
BLAS.axpy!(oldu[trait]-newu[trait],x,wArray[trait])
axpy!(oldu[trait]-newu[trait],x,wArray[trait])
meanAlphaArray[trait][j] += (α[trait] - meanAlphaArray[trait][j])/iIter
meanDeltaArray[trait][j] += (δ[trait] - meanDeltaArray[trait][j])/iIter
meanuArray[trait][j] += (newu[trait] - meanuArray[trait][j])/iIter
Expand Down
4 changes: 1 addition & 3 deletions src/0.deprecated/Tools.jl
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Expand Up @@ -20,7 +20,7 @@ end
function center!(X)
nrow,ncol = size(X)
colMeans = mean(X,1)
BLAS.axpy!(-1,ones(nrow)*colMeans,X)
axpy!(-1,ones(nrow)*colMeans,X)
return colMeans
end

Expand All @@ -41,5 +41,3 @@ function get_dom_cov(x, n) # create dominance covariates from additive covariat
end
return w
end


4 changes: 2 additions & 2 deletions src/1.JWAS/src/markers/BayesianAlphabet/BayesABC.jl
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Expand Up @@ -40,10 +40,10 @@ function BayesABC!(xArray,xRinvArray,xpRinvx,
δ[j] = 1
β[j] = gHat + randn()*sqrt(invLhs)
α[j] = β[j]
BLAS.axpy!(oldAlpha-α[j],x,yCorr)
axpy!(oldAlpha-α[j],x,yCorr)
else
if (oldAlpha!=0)
BLAS.axpy!(oldAlpha,x,yCorr)
axpy!(oldAlpha,x,yCorr)
end
δ[j] = 0
β[j] = randn()*sqrt(varEffects[j])
Expand Down
2 changes: 1 addition & 1 deletion src/1.JWAS/src/markers/BayesianAlphabet/BayesC0L.jl
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Expand Up @@ -42,6 +42,6 @@ function BayesL!(xArray,xRinvArray,xpRinvx,
mean = invLhs*rhs
oldAlpha = α[j]
α[j] = mean + randn()*sqrt(invLhs*vRes)
BLAS.axpy!(oldAlpha-α[j],x,yCorr)
axpy!(oldAlpha-α[j],x,yCorr)
end
end
6 changes: 3 additions & 3 deletions src/1.JWAS/src/markers/BayesianAlphabet/MTBayesABC.jl
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Expand Up @@ -70,13 +70,13 @@ function MTBayesABC!(xArray,xRinvArray,xpRinvx,
if(rand()<probDelta1)
δ[k] = 1
β[k] = newα[k] = gHat1 + randn()*sqrt(invLhs1)
BLAS.axpy!(oldα[k]-newα[k],x,wArray[k])
axpy!(oldα[k]-newα[k],x,wArray[k])
else
β[k] = gHat0 + randn()*sqrt(invLhs0)
δ[k] = 0
newα[k] = 0
if oldα[k] != 0
BLAS.axpy!(oldα[k],x,wArray[k])
axpy!(oldα[k],x,wArray[k])
end
end
end
Expand Down Expand Up @@ -173,7 +173,7 @@ function MTBayesABC_samplerII!(xArray,

# adjust for locus j
for trait in 1:ntraits
BLAS.axpy!(oldα[trait]-newα[trait],x,wArray[trait]) #update wArray (ycorr)
axpy!(oldα[trait]-newα[trait],x,wArray[trait]) #update wArray (ycorr)
betaArray[trait][marker] = β[trait]
deltaArray[trait][marker] = δ[trait]
alphaArray[trait][marker] = newα[trait]
Expand Down
2 changes: 1 addition & 1 deletion src/1.JWAS/src/markers/BayesianAlphabet/MTBayesC0L.jl
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Expand Up @@ -45,7 +45,7 @@ function MTBayesL!(xArray,xRinvArray,xpRinvx,
newα[trait] = alphaArray[trait][marker]
end
for trait = 1:ntraits
BLAS.axpy!(oldα[trait]-newα[trait],x,wArray[trait])
axpy!(oldα[trait]-newα[trait],x,wArray[trait])
end
end
end
2 changes: 1 addition & 1 deletion src/1.JWAS/src/markers/BayesianAlphabet/MTBayesCC_deprecated.jl
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Expand Up @@ -80,7 +80,7 @@ function sampleMarkerEffectsBayesCC!(xArray,xpx,wArray,alphaArray,

# adjust for locus j
for trait = 1:ntraits
BLAS.axpy!(oldu[trait]-newu[trait],x,wArray[trait])
axpy!(oldu[trait]-newu[trait],x,wArray[trait])
alphaArray[trait][marker] = α[trait]
deltaArray[trait][marker] = δ[trait]
uArray[trait][marker] = newu[trait]
Expand Down
2 changes: 1 addition & 1 deletion src/1.JWAS/src/markers/tools4genotypes.jl
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Expand Up @@ -21,7 +21,7 @@ end
function center!(X)
nrow = size(X,1)
colMeans = mean(X,dims=1)
BLAS.axpy!(-1,ones(nrow)*colMeans,X)
axpy!(-1,ones(nrow)*colMeans,X)
return colMeans
end

Expand Down