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Python script to calc 3D-Spline-Interpolation.
#! /usr/local/bin/python3.6
"""
3-D spline interpolation
(with graph drawing by matplotlib)
"""
import matplotlib.pyplot as plt
import sys
import traceback
class SplineInterpolation:
def __init__(self, xs, ys):
""" Initialization
:param list xs: x-coordinate list of given points
:param list ys: y-coordinate list of given points
"""
self.xs, self.ys = xs, ys
self.n = len(self.xs) - 1
h = self.__calc_h()
w = self.__calc_w(h)
matrix = self.__gen_matrix(h, w)
v = [0] + self.__gauss_jordan(matrix) + [0]
self.b = self.__calc_b(v)
self.a = self.__calc_a(v)
self.d = self.__calc_d()
self.c = self.__calc_c(v)
def interpolate(self, t):
""" Interpolation
:param float t: x-value for a interpolate target
:return float : computated y-value
"""
try:
i = self.__search_i(t)
return self.a[i] * (t - self.xs[i]) ** 3 \
+ self.b[i] * (t - self.xs[i]) ** 2 \
+ self.c[i] * (t - self.xs[i]) \
+ self.d[i]
except Exception as e:
raise
def __calc_h(self):
""" H calculation
:return list: h-values
"""
try:
return [self.xs[i + 1] - self.xs[i] for i in range(self.n)]
except Exception as e:
raise
def __calc_w(self, h):
""" W calculation
:param list h: h-values
:return list : w-values
"""
try:
return [
6 * ((self.ys[i + 1] - self.ys[i]) / h[i]
- (self.ys[i] - self.ys[i - 1]) / h[i - 1])
for i in range(1, self.n)
]
except Exception as e:
raise
def __gen_matrix(self, h, w):
""" Matrix generation
:param list h: h-values
:param list w: w-values
:return list mtx: generated 2-D matrix
"""
mtx = [[0 for _ in range(self.n)] for _ in range(self.n - 1)]
try:
for i in range(self.n - 1):
mtx[i][i] = 2 * (h[i] + h[i + 1])
mtx[i][-1] = w[i]
if i == 0:
continue
mtx[i - 1][i] = h[i]
mtx[i][i - 1] = h[i]
return mtx
except Exception as e:
raise
def __gauss_jordan(self, matrix):
""" Solving of simultaneous linear equations
with Gauss-Jordan's method
:param list mtx: list of 2-D matrix
:return list v: answers list of simultaneous linear equations
"""
v = []
n = self.n - 1
try:
for k in range(n):
p = matrix[k][k]
for j in range(k, n + 1):
matrix[k][j] /= p
for i in range(n):
if i == k:
continue
d = matrix[i][k]
for j in range(k, n + 1):
matrix[i][j] -= d * matrix[k][j]
for row in matrix:
v.append(row[-1])
return v
except Exception as e:
raise
def __calc_a(self, v):
""" A calculation
:param list v: v-values
:return list : a-values
"""
try:
return [
(v[i + 1] - v[i])
/ (6 * (self.xs[i + 1] - self.xs[i]))
for i in range(self.n)
]
except Exception as e:
raise
def __calc_b(self, v):
""" B calculation
:param list v: v-values
:return list : b-values
"""
try:
return [v[i] / 2.0 for i in range(self.n)]
except Exception as e:
raise
def __calc_c(self, v):
""" C calculation
:param list v: v-values
:return list : c-values
"""
try:
return [
(self.ys[i + 1] - self.ys[i]) / (self.xs[i + 1] - self.xs[i]) \
- (self.xs[i + 1] - self.xs[i]) * (2 * v[i] + v[i + 1]) / 6
for i in range(self.n)
]
except Exception as e:
raise
def __calc_d(self):
""" D calculation
:return list: c-values
"""
try:
return self.ys
except Exception as e:
raise
def __search_i(self, t):
""" Index searching
:param float t: t-value
:return int i: index
"""
i, j = 0, len(self.xs) - 1
try:
while i < j:
k = (i + j) // 2
if self.xs[k] < t:
i = k + 1
else:
j = k
if i > 0:
i -= 1
return i
except Exception as e:
raise
class Graph:
def __init__(self, xs_0, ys_0, xs_1, ys_1):
self.xs_0, self.ys_0, self.xs_1, self.ys_1 = xs_0, ys_0, xs_1, ys_1
def plot(self):
""" Graph plotting """
try:
plt.title("3-D Spline Interpolation")
plt.scatter(
self.xs_1, self.ys_1, c = "b",
label = "interpolated points", marker = "+"
)
plt.scatter(
self.xs_0, self.ys_0, c = "r",
label = "given points"
)
plt.xlabel("x")
plt.ylabel("y")
plt.legend(loc = 2)
plt.grid(color = "gray", linestyle = "--")
#plt.show()
plt.savefig("spline_interpolation.png")
except Exception as e:
raise
if __name__ == '__main__':
# (N + 1) points
X = [0.0, 2.0, 3.0, 5.0, 7.0, 8.0]
Y = [0.8, 2.8, 3.2, 1.9, 4.5, 2.5]
S = 0.1 # Step for interpolation
S_1 = 1 / S # Inverse of S
xs_g, ys_g = [], [] # List for graph
try:
# 3-D spline interpolation
si = SplineInterpolation(X, Y)
for x in [x / S_1 for x in range(int(X[0] / S), int(X[-1] / S) + 1)]:
y = si.interpolate(x)
print("{:8.4f}, {:8.4f}".format(x, y))
xs_g.append(x)
ys_g.append(y)
# Graph drawing
g = Graph(X, Y, xs_g, ys_g)
g.plot()
except Exception as e:
traceback.print_exc()
sys.exit(1)
@FredEckert

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FredEckert commented Aug 8, 2018

Hello, I am also working to plot splines in 3D.

To be 3D this needs the 3rd dimension, e.g: Z = [0.0, 0.2, 0.4, 1.0, 2.5, 5.0]

It could be plotted using mpl_toolkits.mplot3d import axes3d

fig = plt.figure(figsize=(10,6))
ax = axes3d.Axes3D(fig)
ax.scatter3D(
self.xs_1,self.ys_1,self.zs_1, c='b',
label = "interpolated points", marker = "+"
)
etc..

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