diff --git a/docs/src/tut1.md b/docs/src/tut1.md
index 83824c3..ee0ae38 100644
--- a/docs/src/tut1.md
+++ b/docs/src/tut1.md
@@ -29,16 +29,15 @@ depending on `bfrac`. Their amplitudes are determined by `afrac`.
 gobs=zeros(ntg,nr) # allocate
 FBD.toy_direct_green!(gobs, c=4.0, bfrac=0.20, afrac=1.0); # add arrival 1
 FBD.toy_reflec_green!(gobs, c=1.5, bfrac=0.35, afrac=-0.6); # add arrival 2
-#plotg=(x;args...)->heatmap(x, size=(250,500), yflip=true, ylabel="time", xlabel="channel";args...) # define a plot recipe
-#p1=plotg(gobs, title="True g")
+plotg=(x,args...)->spy(x, Guide.xlabel("channel"), Guide.ylabel("time"),args...) # define a plot recipe
+p1=plotg(gobs, Guide.title("True g"))
 ```
 
 The source signature `s` for the experiment is arbitrary: we simply use a Gaussian random signal.
 
 ```@example tut1
 sobs=randn(nts)
-#plot(sobs, label="arbitrary source", size=(1000,200))
-plot(x=1:10, y=randn(10))
+plot(y=sobs,x=1:nts,Geom.line, Guide.title("arbitrary source"), Guide.xlabel("time"))
 ```
 
 The next task is to generate synthetic observed records `dobs`:
@@ -66,7 +65,7 @@ FBD.lsbd!(pa)
 We extract `g` from `pa` and plot to notice that it doesn't match `gobs`.
 
 ```@example tut1
-#p2=plotg(pa[:g], title="LSBD g")
+p2=plotg(pa[:g], Guide.title("LSBD g"))
 ```
 
 Instead, we perform FBD that uses the focusing functionals to regularize `lsbd!`.
@@ -78,7 +77,6 @@ FBD.fbd!(pa)
 Notice that the extract impulse responses are closer to `gobs`, except for a scaling factor and an overall translation in time.
 
 ```@example tut1
-#p3=plotg(pa[:g], title="FBD g")
-#plot(p1,p2,p3, size=(750,500), layout=(1,3))
+p3=plotg(pa[:g], Guide.title("FBD g"))
 ```
 
diff --git a/test/tut1.jl b/test/tut1.jl
index a5109ce..bb150a8 100644
--- a/test/tut1.jl
+++ b/test/tut1.jl
@@ -18,13 +18,12 @@ nts=nt # samples in `s`
 gobs=zeros(ntg,nr) # allocate
 FBD.toy_direct_green!(gobs, c=4.0, bfrac=0.20, afrac=1.0); # add arrival 1
 FBD.toy_reflec_green!(gobs, c=1.5, bfrac=0.35, afrac=-0.6); # add arrival 2
-#plotg=(x;args...)->heatmap(x, size=(250,500), yflip=true, ylabel="time", xlabel="channel";args...) # define a plot recipe 
-#p1=plotg(gobs, title="True g")
+plotg=(x,args...)->spy(x, Guide.xlabel("channel"), Guide.ylabel("time"),args...) # define a plot recipe 
+p1=plotg(gobs, Guide.title("True g"))
 
 # The source signature `s` for the experiment is arbitrary: we simply use a Gaussian random signal.
 sobs=randn(nts)
-#plot(sobs, label="arbitrary source", size=(1000,200))
-plot(x=1:10, y=randn(10))
+plot(y=sobs,x=1:nts,Geom.line, Guide.title("arbitrary source"), Guide.xlabel("time"))
 
 # The next task is to generate synthetic observed records `dobs`: 
 # first lets construct a linear operator `S`; then applying `S` on `g` will result in measurements `d`.
@@ -43,14 +42,13 @@ FBD.lsbd!(pa)
 #+
 
 # We extract `g` from `pa` and plot to notice that it doesn't match `gobs`.
-#p2=plotg(pa[:g], title="LSBD g")
+p2=plotg(pa[:g], Guide.title("LSBD g"))
 
 # Instead, we perform FBD that uses the focusing functionals to regularize `lsbd!`. 
 FBD.fbd!(pa)
 #+
 
 # Notice that the extract impulse responses are closer to `gobs`, except for a scaling factor and an overall translation in time.
-#p3=plotg(pa[:g], title="FBD g")
-#plot(p1,p2,p3, size=(750,500), layout=(1,3))
+p3=plotg(pa[:g], Guide.title("FBD g"))