improved PyPlot backend: (#17)

* better fontsize recognition

* correct fig sizes

* tight_layout() also for SubVisualizer reveal

* fixed rare clipping of last colorlevel in scalarplot

* coordinate limits (xlimits etc.) are used in vectorsample (such that scaling only is applied to vectors in the clipped area)

* new vector scaling method vconstant that scales all arrows equally

* repaired streamplot (U and V arguments needed transposition)

* added density argument to streamplot

* version bump

---------

Co-authored-by: Christian Merdon <[email protected]>

Project.toml

@@ -1,7 +1,7 @@
 name = "GridVisualize"
 uuid = "5eed8a63-0fb0-45eb-886d-8d5a387d12b8"
 authors = ["Juergen Fuhrmann <[email protected]>"]
-version = "1.1.4"
+version = "1.1.5"
 
 [deps]
 ColorSchemes = "35d6a980-a343-548e-a6ea-1d62b119f2f4"

src/common.jl

@@ -153,7 +153,7 @@ streamlines.
 The code is 3D ready.
 """
 function vectorsample(grid::ExtendableGrid{Tv, Ti}, v; offset = :default,
-                      spacing = :default, reltol = 1.0e-10) where {Tv, Ti}
+                      spacing = :default, reltol = 1.0e-10, xlimits = (1,-1), ylimits = (1,-1), zlimits = (1,-1)) where {Tv, Ti}
     coord = grid[Coordinates]
     cn = grid[CellNodes]
     ncells::Int = num_cells(grid)
@@ -172,6 +172,15 @@ function vectorsample(grid::ExtendableGrid{Tv, Ti}, v; offset = :default,
 
     # coordinate window
     cminmax = extrema(coord; dims = (2,))
+    if xlimits[1] < xlimits[2]
+        cminmax[1] = xlimits[:]
+    end
+    if ylimits[1] < ylimits[2]
+        cminmax[2] = ylimits[:]
+    end
+    if zlimits[1] < zlimits[2]
+        cminmax[3] = zlimits[:]
+    end
 
     if offset == :default
         offset = [cminmax[i][1] for i = 1:dim]
@@ -255,8 +264,17 @@ function vectorsample(grid::ExtendableGrid{Tv, Ti}, v; offset = :default,
         # If so, obtain P1 interpolated raster data and
         # assign them to rasterflux
         for I[1] ∈ Imin[1]:Imax[1] # 0 alloc
+            if I[1] <= 0 || I[1] > length(rastercoord[1])
+                continue
+            end
             for I[2] ∈ Imin[2]:Imax[2]
+                if I[2] <= 0 || I[2] > length(rastercoord[2])
+                    continue
+                end
                 for I[3] ∈ Imin[3]:Imax[3]
+                    if dim == 3 && (I[3] <= 0 || I[3] > length(rastercoord[3]))
+                        continue
+                    end
 
                     # Fill raster point to be tested
                     for idim = 1:dim
@@ -315,7 +333,7 @@ is scaled by vscale
 Result data are meant to  be ready for being passed to calls to `quiver`.
 
 """
-function quiverdata(rastercoord, rasterflux; vscale = 1.0, vnormalize = true)
+function quiverdata(rastercoord, rasterflux; vscale = 1.0, vnormalize = true, vconstant = false)
     dim = length(rastercoord)
 
     imax = length(rastercoord[1])
@@ -355,7 +373,11 @@ function quiverdata(rastercoord, rasterflux; vscale = 1.0, vnormalize = true)
     qv = reshape(reinterpret(Float32, qvvalues), (2, length(qvvalues)))
 
     # Normalize vectors to raster point spacing
-    if vnormalize
+    if vconstant
+        for j = 1 : size(qv,2)
+            view(qv,:,j) ./= norm(view(qv,:,j))
+        end
+    elseif vnormalize
         @views vmax = maximum(norm, (qv[:, i] for i = 1:length(qvvalues)))
         vscale = vscale * min(spacing...) / vmax
     end

src/pyplot.jl

@@ -1,14 +1,15 @@
 function initialize!(p, ::Type{PyPlotType})
     PyPlot = p.context[:Plotter]
     PyPlot.PyObject(PyPlot.axes3D)# see https://github.com/JuliaPy/PyPlot.jl/issues/351
+    PyPlot.rc("font", size = p.context[:fontsize])
     if !haskey(p.context, :figure)
         res = p.context[:size]
         if !isdefined(Main, :PlutoRunner)
-            p.context[:figure] = PyPlot.figure(p.context[:fignumber]; dpi = 50)
+            p.context[:figure] = PyPlot.figure(p.context[:fignumber]; dpi = 50, figsize=res./50)
         else
-            p.context[:figure] = PyPlot.figure(p.context[:fignumber]; dpi = 100)
+            p.context[:figure] = PyPlot.figure(p.context[:fignumber]; dpi = 100, figsize=res./100)
         end
-        p.context[:figure].set_size_inches(res[1] / 100, res[2] / 100; forward = true)
+        #p.context[:figure].set_size_inches(res[1] / 100, res[2] / 100, forward = true)
         for ctx in p.subplots
             ctx[:figure] = p.context[:figure]
         end
@@ -43,6 +44,7 @@ function reveal(ctx::SubVisualizer, TP::Type{PyPlotType})
     if ctx[:show] || ctx[:reveal]
         reveal(ctx[:GridVisualizer], TP)
     end
+    ctx[:GridVisualizer].Plotter.tight_layout()
 end
 
 #translate Julia attribute symbols to pyplot-speak
@@ -552,6 +554,7 @@ function scalarplot!(ctx, TP::Type{PyPlotType}, ::Type{Val{2}}, grids, parentgri
         crange = (crange[1] - eps, crange[1] + eps)
         colorlevels = collect(crange[1]:((crange[2]-crange[1])/(1)):crange[2])
     else
+        crange = (crange[1] - 1e-16, crange[2] + 1e-16) # avoids rare clipping of last color level
         colorlevels =
             collect(crange[1]:((crange[2]-crange[1])/(ctx[:colorlevels]-1)):crange[2])
     end
@@ -716,10 +719,10 @@ function vectorplot!(ctx, TP::Type{PyPlotType}, ::Type{Val{2}}, grid, func)
     ax.set_aspect(ctx[:aspect])
     ax.set_title(ctx[:title])
 
-    rc, rv = vectorsample(grid, func; spacing = ctx[:spacing], offset = ctx[:offset])
-    qc, qv = quiverdata(rc, rv; vscale = ctx[:vscale], vnormalize = ctx[:vnormalize])
+    rc, rv = vectorsample(grid, func; spacing = ctx[:spacing], offset = ctx[:offset], xlimits = ctx[:xlimits], ylimits = ctx[:ylimits])
+    qc, qv = quiverdata(rc, rv; vscale = ctx[:vscale], vnormalize = ctx[:vnormalize], vconstant = ctx[:vconstant])
 
-    ax.quiver(qc[1, :], qc[2, :], qv[1, :], qv[2, :])
+    ax.quiver(qc[1, :], qc[2, :], qv[1, :], qv[2, :]; color = ctx[:color])
     ax.set_xlabel(ctx[:xlabel])
     ax.set_ylabel(ctx[:ylabel])
 
@@ -769,11 +772,11 @@ function streamplot!(ctx, TP::Type{PyPlotType}, ::Type{Val{2}}, grid, func)
         xout, yout
     end
 
-    rc, rv = vectorsample(grid, func; spacing = ctx[:spacing], offset = ctx[:offset])
+    rc, rv = vectorsample(grid, func; spacing = ctx[:spacing], offset = ctx[:offset], xlimits = ctx[:xlimits], ylimits = ctx[:ylimits])
 
     X, Y = meshgrid(rc)
 
-    ax.streamplot(X, Y, rv[1, :, :, 1], rv[2, :, :, 1]; color = ctx[:color])
+    ax.streamplot(X, Y, rv[1, :, :, 1]', rv[2, :, :, 1]'; color = ctx[:color], density = ctx[:density])
     ax.set_xlabel(ctx[:xlabel])
     ax.set_ylabel(ctx[:ylabel])