Renamed CHull to QHull, fixes #8.

We also used @stevengj's [advice](https://groups.google.com/d/msg/julia-users/oiz8bbykvag/uR4roTsFAwAJ)
to not use @pyimport in a Module.

LICENSE

@@ -1,6 +1,6 @@
 Copyright (c) 2013--2016 David A. van Leeuwen, Michael Krabbe Borregaard, Chris Binz, and others.
 
-The Julia package "CHull" is licensed under a Better License.
+The Julia package "QHull" is licensed under a Better License.
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,26 +1,25 @@
-CHull
+QHull
 =====
-[![Build Status](https://travis-ci.org/davidavdav/CHull.jl.svg)](https://travis-ci.org/davidavdav/CHull.jl)
+[![Build Status](https://travis-ci.org/davidavdav/QHull.jl.svg)](https://travis-ci.org/davidavdav/QHull.jl)
 
 
 A Julia wrapper around a PyCall wrapper around `scipy.spatial.ConvexHull`, which uses the qhull Convex Hull library.
 
 The qhull library for computing the convex hull of data points seems to be the standard and very widely used.
 
-This module is a quick wrapper around a Python wrapper around the library, as suggested by [Miles Lubin](https://groups.google.com/d/topic/julia-users/e9m8t5W3TVs/discussion). 
+This module is a quick wrapper around a Python wrapper around the library, as suggested by [Miles Lubin](https://groups.google.com/d/topic/julia-users/e9m8t5W3TVs/discussion).
 
 Synopsis
 --------
 
 ```julia
 
-using CHull
+using QHull
 
 p = rand(10,2)
 ch = chull(p)
 ch.points         # original points
 ch.vertices       # indices to line segments forming the convex hull
+ch.simplices      # the simplexes forming the convex hull
 show(ch)
 ```
-
-

runtest.jl

@@ -1,6 +1,6 @@
 #!/usr/bin/env julia
-include("src/CHull.jl")
-using CHull
+include("src/QHull.jl")
+using QHull
 
 cd("test")
 include("test/runtests.jl")

src/CHull.jl → src/QHull.jl

@@ -5,12 +5,17 @@
 ## This code is licensed under the GNU General Public License, version 2
 ## See the file LICENSE in this distribution
 
-module CHull
+__precompile__(true)
+module QHull
 
 export Chull, chull, display, show
 
 using PyCall
-@pyimport scipy.spatial as spatial
+const spatial = PyNULL()
+
+function __init__()
+    copy!(spatial, pyimport_conda("scipy.spatial", "scipy"))
+end
 
 type Chull{T<:Real}
     points::Array{T}
@@ -25,7 +30,7 @@ end
 
 function chull{T<:Real}(x::Array{T})
     r, c = size(x)
-    py = spatial.ConvexHull(x)
+    py = spatial[:ConvexHull](x)
     points = convert(Array{T}, py["points"])
     vertices = convert(Array{Int}, py["vertices"])
     incone(vertices)
@@ -36,21 +41,12 @@ function chull{T<:Real}(x::Array{T})
     Chull(points, vertices, simplices)
 end
 
-import Base.show
-## I don't seem to be able to print newlines in the display()
-#function display(t::TextDisplay, ch::Chull)
-#    display(t, string("Convex Hull of ", size(ch.points,1), " points in ", size(ch.points,2), "dimensions"))
-#    display(t, ch.vertices)
-#    display(t, ch.points[sort(ch.vertices[:,1]),:])
-#end
-
-## should I use print statements in show()
-function show(io::IO, ch::Chull)
-    println(io, string("Convex Hull of ", size(ch.points,1), " points in ", size(ch.points,2), " dimensions"))
+function Base.show(io::IO, ::MIME"text/plain", ch::Chull)
+    println(io, string("Convex Hull of ", size(ch.points, 1), " points in ", size(ch.points, 2), " dimensions"))
     println(io, "Hull segment vertex indices:")
     println(io, ch.vertices)
     println(io, "Points on convex hull in original order:\n")
-    println(io, ch.points[sort(ch.vertices[:,1]),:])
+    println(io, ch.points[sort(ch.vertices[:, 1]), :])
 end
 
 using RecipesBase

src/test.jl

@@ -1,4 +1,4 @@
-using CHull
+using QHull
 
 p = rand(10,2)
 ch = chull(p)

test/runtests.jl

@@ -1,5 +1,5 @@
 using Base.Test
-import CHull
+import QHull
 
 pts = [-1.0 0;
        1 1;
@@ -9,11 +9,11 @@ pts = [-1.0 0;
        0 3;
        -1 2]
 
-hull = CHull.chull(pts)
+hull = QHull.chull(pts)
 @test hull.vertices == [1, 3, 4, 6, 7]
 @test size(hull.points) == size(pts)
 @test hull.simplices == Array{Int,1}[[3,1], [4,3], [6,4], [7,1], [7,6]]
 
 ## multi-dim
 x = randn(1000, 5)
-hull = CHull.chull(x)
+hull = QHull.chull(x)