use complex directly instead of 1im

Author: ptiede

examples/advanced/Hibi/main.jl

@@ -94,7 +94,7 @@ end
 
 using VLBIImagePriors
 using Distributions
-fgain(x) = exp(x.lg + 1im * x.gp)
+fgain(x) = exp(complex(x.lg , x.gp))
 G = SingleStokesGain(fgain)
 
 intpr = (

examples/intermediate/PolarizedImaging/main.jl

@@ -231,8 +231,8 @@ skym = SkyModel(sky, skyprior, grid; metadata = skymeta)
 # The first element of the tuple is the gain for the first polarization feed (R) and the
 # second is the gain for the second polarization feed (L).
 function fgain(x)
-    gR = exp(x.lgR + 1im * x.gpR)
-    gL = gR * exp(x.lgrat + 1im * x.gprat)
+    gR = exp(complex(x.lgR, x.gpR))
+    gL = gR * exp(complex(x.lgrat, x.gprat))
     return gR, gL
 end
 G = JonesG(fgain)

examples/intermediate/StokesIImaging/main.jl

@@ -130,7 +130,7 @@ skym = SkyModel(sky, prior, grid; metadata = skymeta)
 G = SingleStokesGain() do x
     lg = x.lg
     gp = x.gp
-    return exp(lg + 1im * gp)
+    return exp(complex(lg, gp))
 end
 
 intpr = (

src/instrument/jonesmatrices.jl

@@ -47,8 +47,8 @@ is the complex gain `g1` and the second element is the complex gain `g2`.
 ## Example
 ```julia
 G = JonesG() do
-    g1 = exp(x.lg1 + 1im.*x.gp1)
-    g2 = g1*exp(x.lgratio + 1im.*x.gpratio)
+    g1 = exp(complex(x.lg1, x.gp1))
+    g2 = g1*exp(complex(x.lgratio, x.gpratio))
     return g1, g2
 end
 ```

src/instrument/model.jl

@@ -106,7 +106,7 @@ visibilities.
 
 A Stokes I example is
 ```julia-repl
-julia> G = SingleStokesGain(x->exp(x.lg + 1im*x.pg))
+julia> G = SingleStokesGain(x->exp(complex(x.lg, x.pg)))
 julia> intprior = (lg = ArrayPrior(IIDSitePrior(ScanSeg(), Normal(0.0, 0.1))),
             pg = ArrayPrior(IIDSitePrior(ScanSeg(), DiagVonMises(0.0, inv(π^2))))
             )
@@ -117,8 +117,8 @@ julia> intm = InstrumentModel(G, intprior)
 A standard polarized example is
 ```julia-repl
 julia> G = JonesG() do
-        gR = exp.(x.lgr + 1im*x.gpr)
-        gL = gr*exp.(x.lgrat + 1im*x.gprat)
+        gR = exp.(complex(x.lgr, x.gpr))
+        gL = gr*exp.(complex(x.lgrat, x.gprat))
         return gR, gL
     end
 julia> D = JonesD() do

src/posterior/vlbiposterior.jl

@@ -55,7 +55,7 @@ skyprior = (r = Uniform(μas2rad(10.0), μas2rad(30.0)), a = Uniform(1.0, 10.0))
 g  = imagepixels(μas2rad(100.0), μas2rad(100.0), 256, 256)
 skym = SkyModel(sky, skyprior, g)
 
-G = SingleStokesGain(x->exp(x.lg + 1im*x.pg))
+G = SingleStokesGain(x->exp(complex(x.lg, x.pg)))
 intprior = (lg = ArrayPrior(IIDSitePrior(ScanSeg(), Normal(0.0, 0.1))),
             pg = ArrayPrior(IIDSitePrior(ScanSeg(), DiagVonMises(0.0, inv(π^2))))
             )

test/Core/bayes.jl

@@ -144,7 +144,7 @@ using FiniteDifferences
     @test gz ≈ gfd
 
     R = JonesR()
-    Gp = JonesG(x -> (exp(x.lg + 1im * x.gp), exp(x.lg + 1im * x.gp)))
+    Gp = JonesG(x -> (exp(complex(x.lg, x.gp)), exp(complex(x.lg, x.gp))))
     J = JonesSandwich(Gp, R)
     pr = (
         lg = ArrayPrior(IIDSitePrior(ScanSeg(), Normal(0.0, 1.0))),
@@ -174,7 +174,7 @@ end
     post_lc = VLBIPosterior(skym, lcamp)
     post_vis = VLBIPosterior(skym, vis)
 
-    G = SingleStokesGain(x -> exp(x.lg + 1im .* x.gp))
+    G = SingleStokesGain(x -> exp(complex(x.lg, x.gp)))
     intm = InstrumentModel(
         G, (
             lg = ArrayPrior(IIDSitePrior(ScanSeg(), Normal(0.0, 1.0))),