# Create an arrayarr=np.array([3, 1, 5, 2, 4])# Get the indices that would sort the arraysorted_indices=np.argsort(arr)[13 0 4 2] 8、其他一些高级的函数 numpy.unique:在数组中查找唯一的元素。 arr= np.array([2,1,3,2,1,4,5,...
[11,19,20]])# create an empty arrayarray2= np.array([0,0,0]) # pass the 'out' argument to store the result in array2np.prod(array1, axis =0, out = array2) print(array2) Run Code Output [ 1650 3553 11000] Here, after specifyingout=array2, the result of the product ofarr...
a = np.array([1, 2, 3]) b = np.array([4, 5, 6]) # Compute the dot product of the arrays dot_product = np.dot(a, b) 32 numpy.linalg.inv:计算一个方阵的逆, numpy.linalg.eig:一个方阵的特征值和特征向量。numpy.linalg.solve:求解一个线性方程组。 7、排序函数 numpy.sort:沿指定...
numpy.cumsum(a, axis=None, dtype=None, out=None) * Return the cumulative sum of the elements along a given axis. numpy.prod numpy.prod(a[, axis=None, dtype=None, out=None, …]) * Return the product of array elements over a given axis. numpy.cumprod numpy.cumprod(a, axis=None, d...
Write a function to calculate the matrix product of two large 2D NumPy arrays using nested for loops. Optimize it using NumPy's matmul() function. Sample Solution: Python Code: importnumpyasnp# Generate two large 2D NumPy arrays with random integersarray1=np.random.randint(1,100,size=(500,...
ediff1d(ary[, to_end, to_begin])The differences between consecutive elements of an array. gradient(f, *varargs, **kwargs)Return the gradient of an N-dimensional array. cross(a, b[, axisa, axisb, axisc, axis])Return the cross product of two (arrays of) vectors. trapz(y[, x, dx...
Dot product of the said two arrays: [23 53 83] Explanation: In the above exercise - nums1 = np.array([[1, 2], [3, 4], [5, 6]]): This code creates a 2D NumPy array with shape (3, 2) containing the values [[1, 2], [3, 4], [5, 6]] and assigns it to the variabl...
>>> from numpy import pi >>> np.linspace(0, 2, 9) # 9 numbers from 0 to 2 array([0\. , 0.25, 0.5 , 0.75, 1\. , 1.25, 1.5 , 1.75, 2\. ]) >>> x = np.linspace(0, 2 * pi, 100) # useful to evaluate function at lots of points >>> f = np.sin(x) 另请参阅...
dot(A, B) # another matrix product array([[5, 4], [3, 4]]) 有一些操作,如 += 和 *=,其输出结果会改变一个已存在的数组,而不是如上述运算创建一个新数组。 代码语言:javascript 代码运行次数:0 运行 AI代码解释 >>> a = np.ones((2,3), dtype=int) >>> b = np.random.random((2,...
To find the product of the elements in an array, use the prod() function.ExampleGet your own Python Server Find the product of the elements of this array: import numpy as nparr = np.array([1, 2, 3, 4])x = np.prod(arr)print(x) Try it Yourself » ...