72 lines
1.8 KiB
72 lines
1.8 KiB
1 year ago
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import numpy as np
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def uniform_spaced(n):
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'''
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Calculate parameters using the uniform spaced method.
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:param n: the number of the data points
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:return: parameters
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'''
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parameters = np.linspace(0, 1, n)
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return parameters
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def chord_length(n, P):
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'''
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Calculate parameters using the chord length method.
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:param n: the number of the data points
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:param P: data points
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:return: parameters
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'''
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parameters = np.zeros((1, n))
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for i in range(1, n):
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dis = 0
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for j in range(len(P)):
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dis = dis + (P[j][i] - P[j][i-1])**2
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dis = np.sqrt(dis)
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parameters[0][i] = parameters[0][i-1] + dis
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for i in range(1, n):
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parameters[0][i] = parameters[0][i]/parameters[0][n-1]
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return parameters[0]
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def centripetal(n, P):
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'''
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Calculate parameters using the centripetal method.
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:param n: the number of data points
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:param P: data points
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:return: parameters
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'''
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a = 0.5
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parameters = np.zeros((1, n))
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for i in range(1, n):
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dis = 0
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for j in range(len(P)):
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dis = dis + (P[j][i]-P[j][i-1])**2
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dis = np.sqrt(dis)
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parameters[0][i] = parameters[0][i-1] + np.power(dis, a)
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for i in range(1, n):
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parameters[0][i] = parameters[0][i] / parameters[0][n-1]
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return parameters[0]
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def knot_vector(param, k, N):
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'''
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Generate knot vector.
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:param param: parameters
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:param k: degree
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:param N: the number of data points
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:return: knot vector
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'''
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m = N + k
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knot = np.zeros((1, m+1))
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for i in range(k + 1):
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knot[0][i] = 0
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for i in range(m - k, m + 1):
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knot[0][i] = 1
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for i in range(k + 1, m - k):
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for j in range(i - k, i):
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knot[0][i] = knot[0][i] + param[j]
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knot[0][i] = knot[0][i] / k
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return knot[0]
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