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Diffstat (limited to 'AutopyExtended/Curve/test.py')
-rw-r--r-- | AutopyExtended/Curve/test.py | 55 |
1 files changed, 55 insertions, 0 deletions
diff --git a/AutopyExtended/Curve/test.py b/AutopyExtended/Curve/test.py new file mode 100644 index 0000000..ab9ee6c --- /dev/null +++ b/AutopyExtended/Curve/test.py @@ -0,0 +1,55 @@ +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() |