Wrap plot() and plotlinefit() under kw -> d protecting functions. (#1823)

* Wrap plot() and plotlinefit() under kw -> d protecting functions.

(Completely useless apparently. So fck disparing)

* Fix recent bug in peaks()

Author: joa-quim

src/GMT.jl

@@ -433,6 +433,14 @@ using GMT.Laszip
 	theme()
 	#rescale(mat2img(rand(UInt16, 16,16,3)))
 	plot(rand(5,2))
+	
+	# This one is really unbelievable. It executes only ONE F NEW LINE:
+	# "bar(arg1, arg2; first=true, kw...) = common_plot_xyz("", cat_2_arg2(arg1, arg2, true), "bar", first, false; kw...)"
+	# but it causes recompilation of a big chunk of common_plot_xyz() that should have been **ALL** precompiled
+	# by the "plot(rand(5,2))" above. But no, another 3 MB of ... landed in the precompiled cache.
+	# I'm commenting this because we can't afford adding (3)MEGABYTES for just one TINNY function.
+	#bar(1:5, (20, 35, 30, 35, 27), width=0.5, color=:lightblue, limits=(0.5,5.5,0,40))
+	
 	resetGMT()
 end
 

src/linefit.jl

@@ -176,6 +176,9 @@ plotlinefit(D, band_ab=true, band_ci=true, legend=true, show=1)
 """
 function plotlinefit(D::Vector{<:GMTdataset}; first::Bool=true, kw...)
 	d = KW(kw)
+	_plotlinefit(D, first, d)
+end
+function _plotlinefit(D::Vector{<:GMTdataset}, first::Bool, d::Dict{Symbol,Any})
 	N_clusters = numel(D) 
 	cycle_colors = (N_clusters <= 7) ? matlab_cycle_colors : simple_distinct	# Will blow if > 20
 
@@ -213,11 +216,14 @@ end
 # --------------------------------------------------------------------------------------------------
 plotlinefit(m::Matrix{<:Real}; first::Bool=true, grp::Bool=false, kw...) = plotlinefit(linearfitxy(m); first=first, grp=grp, kw...)
 function plotlinefit(D::GMTdataset; first::Bool=true, grp::Bool=false, kw...)
+	d = KW(kw)
+	_plotlinefit(D, first, grp, d)
+end
+function _plotlinefit(D::GMTdataset, first::Bool, grp::Bool, d::Dict{Symbol,Any})
 	# Plot fit line, data points and confidence intervals (some optional) from GMTds created by linearfitxy.
 	# `grp=true` only when originally called from plotlinefit(D::Vector{<:GMTdataset})
 
 	(get(D.attrib, "a", "") == "" || get(D.attrib, "b", "") == "") && (@warn("Input must be the result of linearfitxy"); return nothing)
-	d = KW(kw)
 
 	function do_ribs(d, symbs, def_color::String)
 		do_rib, rib_cor = false, ""

src/plot.jl

@@ -99,12 +99,15 @@ Parameters
 - $(opt_savefig)
 """
 function plot(arg1; first=true, kw...)
+	d = KW(kw)
+	_plot(arg1, first, d)
+end
+function _plot(arg1, first, d)
 	# First check if arg1 is a GMTds of a linear fit and if yes, call the plotlinefit() fun
-	if (isa(arg1, GDtype) && find_in_kwargs(kw, [:linefit :regress])[1] !== nothing)
+	if (isa(arg1, GDtype) && is_in_dict(d, [:linefit :regress]; del=false) !== nothing)
 		att = isa(arg1, GMTdataset) ? arg1.attrib : arg1[1].attrib
-		(get(att, "linearfit", "") != "") && return plotlinefit(arg1; first=first, kw...)
-		# If it didn't return above, see if we have a 'groupvar' request and if yest perform regression on grouos
-		d = KW(kw)
+		(get(att, "linearfit", "") != "") && return plotlinefit(arg1; first=first, d...)
+		# If it didn't return above, see if we have a 'groupvar' request and if yes perform regression on grouops
 		arg1 = with_xyvar(d, arg1)		# But first check if we have a column selection
 		gidx, gnames = get_group_indices(d, arg1)
 		cycle_colors = (numel(gidx) <= 7) ? matlab_cycle_colors : simple_distinct	# Will blow if > 20
@@ -119,7 +122,7 @@ function plot(arg1; first=true, kw...)
 			return plotlinefit(Dv; first=first, d...)
 		end
 	end
-	common_plot_xyz("", Tables.istable(arg1) ? arg1 : cat_1_arg(arg1, true), "plot", first, false; kw...)
+	common_plot_xyz("", Tables.istable(arg1) ? arg1 : cat_1_arg(arg1, true), "plot", first, false, d)
 end
 plot!(arg1; kw...) = plot(arg1; first=false, kw...)
 
@@ -464,9 +467,12 @@ function bar(cmd0::String="", arg=nothing; first=true, kw...)
 	(cmd0 != "" && arg === nothing) && (arg = gmtread(cmd0))
 	isa(arg, GMTdataset) && (arg::Matrix{<:Float64} = arg.data)
 	isa(arg, Vector{<:GMTdataset}) && (arg = arg[1].data; @warn("Multi-segments not allowed in 'bar'. Keeping only first segment."))
+	invokelatest(_bar, arg, first, d)
+end
+function _bar(arg, first::Bool, d::Dict{Symbol,Any})
 
 	do_cat = ((haskey(d, :stack) || haskey(d, :stacked)) && isvector(arg) && length(arg) > 2) ? false : true
-	is_waterfall = ((val = find_in_kwargs(kw, [:stack :stacked])[1]) !== nothing && startswith(string(val), "water"))
+	is_waterfall = ((val = hlp_desnany_str(d, [:stack :stacked])) !== "" && startswith(val, "water"))
 	if (is_waterfall)
 		isa(arg, Vector) && (arg = reshape(arg, 1, length(arg)))		# Waterfall stacks must be matrices
 		(arg[1] != 0) && (arg = hcat(repeat([1.0],size(arg,1)), arg))	# If first el != 0 assume coord is missing
@@ -2264,13 +2270,13 @@ function stereonet(mat::AbstractArray{T,2}; first=true, schmidt=true, wulff=fals
 	(is_in_dict(d, [:lt :linethickness]) === nothing) && (d[:lt] = 0.5)
 	d[:par] = (MAP_GRID_PEN_PRIMARY="0.25,gray", MAP_GRID_PEN_SECONDARY="0.25,black")
 	d[:B], d[:R], d[:J] = "pg5 sg20", :d, prj
-	_common_plot_xyz("", Dv, "plot", false, true, false, d)		# Plot the fault planes
+	common_plot_xyz("",  Dv, "plot", first, false, d)		# Plot the fault planes
 
 	(is_in_dict(d, [:marker :Marker :shape]) === nothing) && (d[:marker] = "circ")
 	(is_in_dict(d, [:mec :markeredgecolor :MarkerEdgeColor]) === nothing) && (d[:mec] = "0.0p,black")
 	(is_in_dict(d, [:mc :markercolor]) === nothing) && (d[:mc] = "blue")
 	(is_in_dict(d, [:ms :markersize :MarkerSize :size]) === nothing) && (d[:ms] = "3p")
-	_common_plot_xyz("", Dp, "plot", true, true, false, d)		# Plot the poles
+	common_plot_xyz("",  Dp, "stereonet", false, false, d)		# Plot the poles
 	basemap!(J="P" * CTRL.pocket_J[2] * "+a", B="a15", show=show)
 end
 stereonet!(mat::AbstractArray{T,2}; schmidt=true, wulff=false, kw...) where T<:Real =

src/psxy.jl

@@ -13,11 +13,11 @@ function common_plot_xyz(cmd0::String, arg1, caller::String, first::Bool, is3D::
 	(cmd0 != "" && arg1 === nothing && is_in_dict(d, [:groupvar :hue]) !== nothing) && (arg1 = gmtread(cmd0); cmd0 = "")
 	invokelatest(_common_plot_xyz, cmd0, arg1, caller, O, K, is3D, d)
 end
-function common_plot_xyz(cmd0::String, arg1, caller::String, first::Bool, is3D::Bool, d)
+function common_plot_xyz(cmd0::String, arg1, caller::String, first::Bool, is3D::Bool, d::Dict{Symbol, Any})
 	(cmd0 != "" && arg1 === nothing && is_in_dict(d, [:groupvar :hue]) !== nothing) && (arg1 = gmtread(cmd0); cmd0 = "")
 	invokelatest(_common_plot_xyz, cmd0, arg1, caller, !first, true, is3D, d)
 end
-function _common_plot_xyz(cmd0::String, arg1, caller::String, O::Bool, K::Bool, is3D::Bool, d::Dict)
+function _common_plot_xyz(cmd0::String, arg1, caller::String, O::Bool, K::Bool, is3D::Bool, d::Dict{Symbol, Any})
 	first = !O
 	(caller != "bar") && (arg1 = if_multicols(d, arg1, is3D))	# Check if it was asked to split a GMTdataset in its columns 
 

src/utils.jl

@@ -440,7 +440,7 @@ end
 
 # --------------------------------------------------------------------------------------------------
 function peaks(n::Int=49; N::Int=49, grid::Bool=true, pixreg::Bool=false)
-	(N != n) && (N = n)
+	(n != 49 && N == 49) && (N = n)
 	x,y = meshgrid(range(-3,stop=3,length=N))
 
 	z = 3 * (1 .- x).^2 .* exp.(-(x.^2) .- (y .+ 1).^2) .- 10*(x./5 .- x.^3 .- y.^5) .* exp.(-x.^2 .- y.^2)
@@ -540,7 +540,7 @@ function tic()
 end
 
 function _toq()
-	_ = time_ns()
+	t1 = time_ns()
 	timers = get(task_local_storage(), :TIMERS, ())
 	(timers === ()) && error("`toc()` without `tic()`")
 	t0 = timers[1]::UInt64

test/assets/iris.dat

@@ -0,0 +1,151 @@
+#Sepal Length,Sepal Width,Petal Length,Petal Width,Species
+5.1	3.5	1.4	0.2 setosa
+4.9	3.0	1.4	0.2 setosa
+4.7	3.2	1.3	0.2 setosa
+4.6	3.1	1.5	0.2 setosa
+5.0	3.6	1.4	0.2 setosa
+5.4	3.9	1.7	0.4 setosa
+4.6	3.4	1.4	0.3 setosa
+5.0	3.4	1.5	0.2 setosa
+4.4	2.9	1.4	0.2 setosa
+4.9	3.1	1.5	0.1 setosa
+5.4	3.7	1.5	0.2 setosa
+4.8	3.4	1.6	0.2 setosa
+4.8	3.0	1.4	0.1 setosa
+4.3	3.0	1.1	0.1 setosa
+5.8	4.0	1.2	0.2 setosa
+5.7	4.4	1.5	0.4 setosa
+5.4	3.9	1.3	0.4 setosa
+5.1	3.5	1.4	0.3 setosa
+5.7	3.8	1.7	0.3 setosa
+5.1	3.8	1.5	0.3 setosa
+5.4	3.4	1.7	0.2 setosa
+5.1	3.7	1.5	0.4 setosa
+4.6	3.6	1.0	0.2 setosa
+5.1	3.3	1.7	0.5 setosa
+4.8	3.4	1.9	0.2 setosa
+5.0	3.0	1.6	0.2 setosa
+5.0	3.4	1.6	0.4 setosa
+5.2	3.5	1.5	0.2 setosa
+5.2	3.4	1.4	0.2 setosa
+4.7	3.2	1.6	0.2 setosa
+4.8	3.1	1.6	0.2 setosa
+5.4	3.4	1.5	0.4 setosa
+5.2	4.1	1.5	0.1 setosa
+5.5	4.2	1.4	0.2 setosa
+4.9	3.1	1.5	0.2 setosa
+5.0	3.2	1.2	0.2 setosa
+5.5	3.5	1.3	0.2 setosa
+4.9	3.6	1.4	0.1 setosa
+4.4	3.0	1.3	0.2 setosa
+5.1	3.4	1.5	0.2 setosa
+5.0	3.5	1.3	0.3 setosa
+4.5	2.3	1.3	0.3 setosa
+4.4	3.2	1.3	0.2 setosa
+5.0	3.5	1.6	0.6 setosa
+5.1	3.8	1.9	0.4 setosa
+4.8	3.0	1.4	0.3 setosa
+5.1	3.8	1.6	0.2 setosa
+4.6	3.2	1.4	0.2 setosa
+5.3	3.7	1.5	0.2 setosa
+5.0	3.3	1.4	0.2 setosa
+7.0	3.2	4.7	1.4 versicolor
+6.4	3.2	4.5	1.5 versicolor
+6.9	3.1	4.9	1.5 versicolor
+5.5	2.3	4.0	1.3 versicolor
+6.5	2.8	4.6	1.5 versicolor
+5.7	2.8	4.5	1.3 versicolor
+6.3	3.3	4.7	1.6 versicolor
+4.9	2.4	3.3	1.0 versicolor
+6.6	2.9	4.6	1.3 versicolor
+5.2	2.7	3.9	1.4 versicolor
+5.0	2.0	3.5	1.0 versicolor
+5.9	3.0	4.2	1.5 versicolor
+6.0	2.2	4.0	1.0 versicolor
+6.1	2.9	4.7	1.4 versicolor
+5.6	2.9	3.6	1.3 versicolor
+6.7	3.1	4.4	1.4 versicolor
+5.6	3.0	4.5	1.5 versicolor
+5.8	2.7	4.1	1.0 versicolor
+6.2	2.2	4.5	1.5 versicolor
+5.6	2.5	3.9	1.1 versicolor
+5.9	3.2	4.8	1.8 versicolor
+6.1	2.8	4.0	1.3 versicolor
+6.3	2.5	4.9	1.5 versicolor
+6.1	2.8	4.7	1.2 versicolor
+6.4	2.9	4.3	1.3 versicolor
+6.6	3.0	4.4	1.4 versicolor
+6.8	2.8	4.8	1.4 versicolor
+6.7	3.0	5.0	1.7 versicolor
+6.0	2.9	4.5	1.5 versicolor
+5.7	2.6	3.5	1.0 versicolor
+5.5	2.4	3.8	1.1 versicolor
+5.5	2.4	3.7	1.0 versicolor
+5.8	2.7	3.9	1.2 versicolor
+6.0	2.7	5.1	1.6 versicolor
+5.4	3.0	4.5	1.5 versicolor
+6.0	3.4	4.5	1.6 versicolor
+6.7	3.1	4.7	1.5 versicolor
+6.3	2.3	4.4	1.3 versicolor
+5.6	3.0	4.1	1.3 versicolor
+5.5	2.5	4.0	1.3 versicolor
+5.5	2.6	4.4	1.2 versicolor
+6.1	3.0	4.6	1.4 versicolor
+5.8	2.6	4.0	1.2 versicolor
+5.0	2.3	3.3	1.0 versicolor
+5.6	2.7	4.2	1.3 versicolor
+5.7	3.0	4.2	1.2 versicolor
+5.7	2.9	4.2	1.3 versicolor
+6.2	2.9	4.3	1.3 versicolor
+5.1	2.5	3.0	1.1 versicolor
+5.7	2.8	4.1	1.3 versicolor
+6.3	3.3	6.0	2.5 virginica
+5.8	2.7	5.1	1.9 virginica
+7.1	3.0	5.9	2.1 virginica
+6.3	2.9	5.6	1.8 virginica
+6.5	3.0	5.8	2.2 virginica
+7.6	3.0	6.6	2.1 virginica
+4.9	2.5	4.5	1.7 virginica
+7.3	2.9	6.3	1.8 virginica
+6.7	2.5	5.8	1.8 virginica
+7.2	3.6	6.1	2.5 virginica
+6.5	3.2	5.1	2.0 virginica
+6.4	2.7	5.3	1.9 virginica
+6.8	3.0	5.5	2.1 virginica
+5.7	2.5	5.0	2.0 virginica
+5.8	2.8	5.1	2.4 virginica
+6.4	3.2	5.3	2.3 virginica
+6.5	3.0	5.5	1.8 virginica
+7.7	3.8	6.7	2.2 virginica
+7.7	2.6	6.9	2.3 virginica
+6.0	2.2	5.0	1.5 virginica
+6.9	3.2	5.7	2.3 virginica
+5.6	2.8	4.9	2.0 virginica
+7.7	2.8	6.7	2.0 virginica
+6.3	2.7	4.9	1.8 virginica
+6.7	3.3	5.7	2.1 virginica
+7.2	3.2	6.0	1.8 virginica
+6.2	2.8	4.8	1.8 virginica
+6.1	3.0	4.9	1.8 virginica
+6.4	2.8	5.6	2.1 virginica
+7.2	3.0	5.8	1.6 virginica
+7.4	2.8	6.1	1.9 virginica
+7.9	3.8	6.4	2.0 virginica
+6.4	2.8	5.6	2.2 virginica
+6.3	2.8	5.1	1.5 virginica
+6.1	2.6	5.6	1.4 virginica
+7.7	3.0	6.1	2.3 virginica
+6.3	3.4	5.6	2.4 virginica
+6.4	3.1	5.5	1.8 virginica
+6.0	3.0	4.8	1.8 virginica
+6.9	3.1	5.4	2.1 virginica
+6.7	3.1	5.6	2.4 virginica
+6.9	3.1	5.1	2.3 virginica
+5.8	2.7	5.1	1.9 virginica
+6.8	3.2	5.9	2.3 virginica
+6.7	3.3	5.7	2.5 virginica
+6.7	3.0	5.2	2.3 virginica
+6.3	2.5	5.0	1.9 virginica
+6.5	3.0	5.2	2.0 virginica
+6.2	3.4	5.4	2.3 virginica
+5.9	3.0	5.1	1.8 virginica