numpy中的log和ln函数解读_python

import numpy as np


class NumpyStudy:
    def lnFunction(self):
        const = np.e
        result = np.log(const)
        print("函数ln(e)的值为：")
        print(result)


if __name__ == "__main__":
    main = NumpyStudy()
    main.lnFunction()
"""
函数ln(e)的值为：
1.0
"""

import numpy as np


class NumpyStudy:
    def logFunction(self):
        const = 100
        result = np.log10(const)
        print("函数ln(e)的值为：")
        print(result)


if __name__ == "__main__":
    main = NumpyStudy()
    main.logFunction()
"""
函数ln(e)的值为：
2.0
"""

import numpy as np


class NumpyStudy:
    def lnFunction(self):
        result = np.log(16) / np.log(2)
        result1 = np.log10(16) / np.log10(2)
        print("函数ln(e)的值为：")
        print(result)
        print(result1)


if __name__ == "__main__":
    main = NumpyStudy()
    main.lnFunction()
"""
函数ln(e)的值为：
4.0
4.0
"""

x=np.arrange(4)
#array([0, 1, 2, 3])
x + 2
#array([2, 3, 4, 5])
np.add(x,2)
#array([2, 3, 4, 5])

x=np.array([-2, -1, 0, 1, 2])
abs(x)
#array([2, 1, 0, 1, 2])
np.absolute(x)
#array([2, 1, 0, 1, 2])