plot(x_values, y_values, label="Lagrange Interpolation", color="blue") plt.scatter(x, y, label="Given Data Points", color="red", zorder=5) plt.xlabel("X-axis") plt.ylabel("Y-axis") plt.title("Lagrange Interpolation") plt.legend() plt.grid(True) plt.show() 我们有lx,ls函数,...
类图 我们还可以使用mermaid语法来展示类图: LagrangeInterpolation- x_points: List[float]- y_points: List[float]+__init__(x_points: List[float], y_points: List[float])+interpolate(x: float) : -> float 结论 通过本文的介绍,我们了解了如何使用Python实现拉格朗日插值法,并通过示例代码展示了其应用。
代码更新如下: deflagrange_interpolation(x,y,x_new):ifnot(isinstance(x,list)andisinstance(y,list)):raiseTypeError("输入必须为列表")iflen(x)!=len(y):raiseValueError("x 和 y 长度必须一致")total=0foriinrange(len(y)):L_i=1forjinrange(len(x)):ifi!=j:L_i*=(x_new-x[j])/(x[i]...
def lagrange_interpolation(x, y, interpolate_point): n = len(x) # 定义变量 t = sp.symbols('t') # 构建拉格朗日插值多项式 poly = 0 for i in range(n): term = y[i] for j in range(n): if j != i: term *= (t - x[j]) / (x[i] - x[j]) ...
```python def lagrange_interpolation(x, y, point): """ 拉格朗日插值函数 :param x: 用于拟合的数据点的x坐标列表 :param y: 用于拟合的数据点的y坐标列表 :param point: 需要插值的点的x坐标 :return: 插值点的y坐标 """ n = len(x) result = 0 for i in range(n): term = y[i] for j...
n = input("Interpolation times:") n = int(n) point_set = preprocess() point_set = sorted(point_set, key=lambda a: a[0]) span = binary_search(point_set, n+1, pred_x) print("Chosen points: {}".format(point_set[span[0]:span[1]+1])) ...
1importmatplotlib.pyplot as plt2frompylabimportmpl34#计算插值多项式的系数。5x = [0, 0.5, 1, 1.5, 2]6y = [0, 0.0625, 1, 5.0625, 16]78defParametersOfLagrangeInterpolation(data_x,data_y,size):9parameters=[]1011i=0;#i用来控制参数的个数12whilei <size:13j = 0;#j用来控制循环的变量做...
deflagrange_interpolation_1d(x,abscissa,values):""" evaluate lagrange interpolant at a set of points x """hier_indices=numpy.arange(abscissa.shape[0])basis=lagrange_polynomial_1d(x,abscissa,hier_indices)returnnumpy.dot(values,basis) 浏览完整代码来源:项目:jjakeman/pyheat ...
(CalculateTheValueOfLarangeInterpolation(x,parameters,1.75)) 58 Draw(x,y,datax,datay) 59 print("得到的四次Lagrange插值多项式为:L(x) = %f(x-0)(x-1)(x-1.5)(x-2) + %f(x-0)(x-0.5)(x-1.5)(x-2) + %f(x-0)(x-0.5)(x-1)(x-2) + %f(x-0)(x-0.5)(x-1)(x-1.5)"%(...