use relative paths w.r.t. script file directory using @__DIR__

tutorials/julia/t20.jl

@@ -17,7 +17,7 @@ gmsh.model.add("t20")
 
 # Load a STEP file (using `importShapes' instead of `merge' allows to directly
 # retrieve the tags of the highest dimensional imported entities):
-path = abspath(joinpath("..","t20_data.step"))
+path = abspath(joinpath(@__DIR__, "..", "t20_data.step"))
 v = gmsh.model.occ.importShapes(path)
 
 # If we had specified
@@ -91,13 +91,12 @@ if surf
     # won't modify any OpenCASCADE entities later on):
     dels = gmsh.model.getEntities(2)
     for e in s
-        deleteat!(dels, findall(x->x==e,dels))
+        deleteat!(dels, findall(x -> x == e, dels))
     end
     gmsh.model.removeEntities(gmsh.model.getEntities(3))
     gmsh.model.removeEntities(dels)
     gmsh.model.removeEntities(gmsh.model.getEntities(1))
     gmsh.model.removeEntities(gmsh.model.getEntities(0))
-
 end
 
 # Finally, let's specify a global mesh size and mesh the partitioned model:

tutorials/julia/t4.jl

@@ -120,22 +120,22 @@ gmsh.view.addListDataString(v, [0, 0.11, 0], ["Hole"],
 # a `@' symbol in the form `widthxheight' (if one of `width' or `height' is
 # zero, natural scaling is used; if both are zero, original image dimensions in
 # pixels are used):
-gmsh.view.addListDataString(v, [0, 0.09, 0], ["file://../t4_image.png@0.01x0"],
+png = abspath(joinpath(@__DIR__, "..", "t4_image.png"))
+gmsh.view.addListDataString(v, [0, 0.09, 0], ["file://" * png * "@0.01x0"],
                             ["Align", "Center"])
 
 # The 3D orientation of the image can be specified by proving the direction
 # of the bottom and left edge of the image in model space:
 gmsh.view.addListDataString(v, [-0.01, 0.09, 0],
-                            ["file://../t4_image.png@0.01x0,0,0,1,0,1,0"])
+                            ["file://" * png * "@0.01x0,0,0,1,0,1,0"])
 
 # The image can also be drawn in "billboard" mode, i.e. always parallel to
 # the camera, by using the `#' symbol:
-gmsh.view.addListDataString(v, [0, 0.12, 0],
-                            ["file://../t4_image.png@0.01x0#"],
+gmsh.view.addListDataString(v, [0, 0.12, 0], ["file://" * png * "@0.01x0#"],
                             ["Align", "Center"])
 
 # The size of 2D annotations is given directly in pixels:
-gmsh.view.addListDataString(v, [150, -7], ["file://../t4_image.png@20x0"])
+gmsh.view.addListDataString(v, [150, -7], ["file://" * png * "@20x0"])
 
 # These annotations are handled by a list-based post-processing view. For
 # large post-processing datasets, that contain actual field values defined on

tutorials/julia/t7.jl

@@ -14,7 +14,7 @@ import gmsh
 gmsh.initialize()
 
 # Merge a list-based post-processing view containing the target mesh sizes:
-path = abspath(joinpath("..","t7_bgmesh.pos"))
+path = abspath(joinpath(@__DIR__, "..","t7_bgmesh.pos"))
 gmsh.merge(path)
 
 # If the post-processing view was model-based instead of list-based (i.e. if it

tutorials/julia/t9.jl

@@ -20,7 +20,7 @@ import gmsh
 gmsh.initialize()
 
 # Let us for example include a three-dimensional scalar view:
-path = abspath(joinpath("..","view3.pos"))
+path = abspath(joinpath(@__DIR__, "..","view3.pos"))
 gmsh.merge(path)
 
 v = gmsh.view.getTags()