Add dev instructions
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61
networks/curve.py
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61
networks/curve.py
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class Curve:
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def __init__(self, points):
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self.points = points # list of tuples (x1, y1, z1) in order
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def curve(points, resolution=40, debug=False):
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"""
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Returns a 3d curve.
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https://stackoverflow.com/questions/18962175/spline-interpolation-coefficients-of-a-line-curve-in-3d-space
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Args:
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points (np.array): Points where the curve should pass in order.
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resolution (int, optional): Number of points to compute. Defaults to 40.
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debug (bool, optional): Visual. Defaults to False.
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Returns:
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tuple: Tuple of list of each coordinate.
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"""
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# Remove duplicates.
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points = tuple(map(tuple, points))
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points = sorted(set(points), key=points.index)
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x_sample = []
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y_sample = []
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z_sample = []
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for i in range(len(points)):
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x_sample.append(points[i][0])
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z_sample.append(points[i][1])
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y_sample.append(points[i][2])
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x_sample = np.array(x_sample)
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y_sample = np.array(y_sample)
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z_sample = np.array(z_sample)
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tck, u = interpolate.splprep([x_sample, y_sample, z_sample], s=2, k=2)
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x_knots, y_knots, z_knots = interpolate.splev(tck[0], tck)
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u_fine = np.linspace(0, 1, number_true_pts)
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x_fine, y_fine, z_fine = interpolate.splev(u_fine, tck)
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if debug:
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fig2 = plt.figure(2)
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ax3d = fig2.add_subplot(111, projection="3d")
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ax3d.plot(x_sample, y_sample, z_sample, "r*")
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ax3d.plot(x_knots, y_knots, z_knots, "go")
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ax3d.plot(x_fine, y_fine, z_fine, "r")
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fig2.show()
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plt.show()
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x = x_fine.tolist()
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z = y_fine.tolist()
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y = z_fine.tolist()
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for i in x:
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i = round(i)
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for i in y:
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i = round(i)
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for i in z:
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i = round(i)
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return x, y, z
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