Refactoring, Bezier

Refactored module layout.
Added missing dependencies to setup.
Added time scaling to curves.

1 files changed, 0 insertions, 55 deletions

diff --git a/AutopyExtended/Curve/test.py b/AutopyExtended/Curve/test.py
deleted file mode 100644
index ab9ee6c..0000000
--- a/AutopyExtended/Curve/test.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import numpy as np
-from scipy.special import comb
-
-def bernstein_poly(i, n, t):
-    """
-     The Bernstein polynomial of n, i as a function of t
-    """
-
-    return comb(n, i) * ( t**(n-i) ) * (1 - t)**i
-
-
-
-def bezier_curve(points, nTimes=1000):
-    """
-       Given a set of control points, return the
-       bezier curve defined by the control points.
-       points should be a list of lists, or list of tuples
-       such as [ [1,1], 
-                 [2,3], 
-                 [4,5], ..[Xn, Yn] ]
-        nTimes is the number of time steps, defaults to 1000
-        See http://processingjs.nihongoresources.com/bezierinfo/
-    """
-
-    nPoints = len(points)
-    xPoints = np.array([p[0] for p in points])
-    yPoints = np.array([p[1] for p in points])
-
-    t = np.linspace(0.0, 1.0, nTimes)
-
-    polynomial_array = np.array([ bernstein_poly(i, nPoints-1, t) for i in range(0, nPoints)   ])
-
-    xvals = np.dot(xPoints, polynomial_array)
-    yvals = np.dot(yPoints, polynomial_array)
-
-    return xvals, yvals
-
-
-
-if __name__ == "__main__":
-    from matplotlib import pyplot as plt
-
-    nPoints = 4
-    points = np.random.rand(nPoints,2)*200
-    xpoints = [p[0] for p in points]
-    ypoints = [p[1] for p in points]
-
-    xvals, yvals = bezier_curve(points, nTimes=1000)
-    plt.plot(xvals, yvals)
-    plt.plot(xpoints, ypoints, "ro")
-    for nr in range(len(points)):
-        plt.text(points[nr][0], points[nr][1], nr)
-
-
-    plt.show()