"""Return a curried version of the given two-argument function.""" def g(x): def h(y): return f(x, y) return h return g >>> def uncurry2(g): """Return a two-argument version of the given curried function.""" def f(x, y): return g(x)(y) return f >>> pow_curried ...
for (int i = 0; i < 10000; i++) { Assert.assertEquals(2.166795861438391, squareRoots.TSqrt(), 0.000001); } } @Test public void testFastInverseSquareRoot() { for (int i = 0; i < 10000; i++) { Assert.assertEquals(2.1667948388864198, squareRoots.FastInverseSquareRoot(), 0.000001); }...
square_root_result = math.sqrt(9) print(f"平方根的计算结果:{square_root_result}") 9. 代码解析 在这个高级应用示例中,我们展示了数学模块在科学计算中的角色,通过numpy库解决了一个线性方程组的问题。同时,我们使用了math模块的函数进行辅助计算。 科学计算中,数学模块的功能不仅仅限于提供数学函数,还包括...
from numpy.linalg import inv, qr 线性代数 diag Return the diagonal (or off-diagonal非对角) elements of a square matrix as a 1D array, or convert a 1D array into a square matrix with zeros on the off-diagonal dot Matrix multiplication trace 这是迹Compute the sum of the diagonal elements ...
这个过程(Square-Root Diffusion)由Cox-Ingersoll和Ross(1985)提出,用于对随机短期利率进行建模。其随机微分方程可以表示为: CIR模型认为,利率围绕一个长期均值波动率波动,如果利率偏离了平均值,它总是要回到平均值的。利率回到平均值的时间由模型中的调整速度描述。参数相关解释: ...
Function Classes Numpy Array importnumpyasnp a = np.array([1,2,3,4])# Create a rank 1 arrayprint(type(a))# Prints "<class 'numpy.ndarray'>"print(a.shape)# Prints "(3,)"print(a[0], a[1], a[2])# Prints "1 2 3"a[0] =5# Change an element of the arrayprint(a)# Pri...
import numpyasnp # 生成正弦函数的数据 x= np.linspace(0,2* math.pi,100) # 在0到2π之间生成100个点 y=np.sin(x) # 绘制正弦函数图形 plt.plot(x, y, label='sin(x)') plt.title('Sin Function') plt.xlabel('x') plt.ylabel('sin(x)') ...
importmatplotlib.pyplotaspltimportnumpyasnp # 创建数据 x=np.linspace(0,2*np.pi,100)y1=np.sin(x)y2=np.cos(x) # 创建子图 plt.subplot(2,1,1)# 两行一列,当前选中第一个子图 plt.plot(x,y1,label='Sin')plt.title('Sin Function')plt.legend() ...
import numpy as npimport mahotasimport mahotas.demos from mahotas.thresholding import soft_thresholdfrom matplotlib import pyplot as pltfrom os import pathf = mahotas.demos.load('lena', as_grey=True)f = f[128:,128:]plt.gray# Show the data:print("Fraction of zeros in original image: {0}...
Let me first explain the function np.meshgrid, which is used to quickly generate a grid point coordinate matrix. First look at a piece of code for coordinate points: import numpy as np import matplotlib.pyplot as plt x = np.array([[0, 1, 2], [0, 1, 2]]) ...