python--ufunc function--numpy calculation

NumPy "Universal Function" (ufunc)
·Element-level functions: perform operations on each element in the
array·Array-level functions: statistical functions, functions like aggregates, summation, average, etc.

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Calculate the absolute value abs

import numpy as np
arr = np.array([5,2,0,-1,-3,-1,-4])
np.abs(arr)
#array([5, 2, 0, 1, 3, 1, 4])

Calculate the square of each element

np.square(arr)
#array([25,  4,  0,  1,  9,  1, 16], dtype=int32)

Square root of each element

np.sqrt(arr)

Exponent based on e (E to the power of X)

np.exp(arr)

Logarithm to base e

np.log(arr)
np.log10(arr)
np.log2(arr)

Returns the sign of each element

np.sign(arr)

Sort (default ascending) sort

np.sort(arr)

#多维数组排序
arr.sort(axis=1)

Remove duplicate elements

arr=np.array([5.2,-0.1,3,14])
np.unique(arr)

Improvement / trade-in

np.ceil(arr)
np.floor(arr)

rounding

np.rint(arr)

Decimal integer separation

np.modf(arr)

Trigonometric function

np.tan(arr)
np.cos(arr)
np.sin(arr)

Sum

np.sum(arr)

Average

np.mean(arr)

Standard deviation

np.std(arr)

variance

np.var(arr)

Min/max value and index

np.min(arr)
np.max(arr)
np.argmaxin(arr)
np.argmax(arr)

Cumulative sum/product of array elements

np.cumsum(arr)
np.cumprod(arr)

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Matrix operations numpy.linalg

Returns the diagonal elements of the matrix

np.diag(a)

Diagonal elements and

np.trace(a)

Calculate the matrix determinant

np.linalg.det(a)

Matrix inverse

np.linalg.inv(a)

Matrix dot

product np.dot (a, aT)