The natural logarithm log is the inverse of the exponential function, so that log(exp(x)) = x. The natural logarithm is logarithm in base e. import numpy as np x = np.arange(1, 5) print(x) # [1 2 3 4] y = np.exp(x) print(y) # [ 2.71828183 7.3890561 20.08553692 54.59815003...
e, np.pi]]) # Natural logarithm print(repr(np.log(arr2))) # Base 10 logarithm print(repr(np.log10(arr2))) array([[ 2.71828183, 7.3890561 ], [20.08553692, 54.59815003]]) array([[ 2., 4.], [ 8., 16.]]) array([[2.30258509, 4.60517019], [1. , 1.14472989]]) array([[1. ...
Natural Log, or Log at Base eUse the log() function to perform log at the base e.Example Find log at base e of all elements of following array: import numpy as nparr = np.arange(1, 10)print(np.log(arr)) Try it Yourself » ...
numpy.log numpy.log(x, args, kwargs) Natural logarithm, element-wise. numpy.exp2 numpy.exp2(x, *args, kwargs) * Calculate 2p for all p in the input array. numpy.log2 numpy.log2(x, args, kwargs) Base-2 logarithm of x.
Natural logarithm (base e), log base 10, log base 2, and log(1 + x), respectively sign Compute the sign of each element: 1 (positive), 0 (zero), or –1 (negative) ceil 计算大于等于的最大整数值 Compute the ceiling of each element (i.e., the smallest integer greater than or equ...
from __future__ import print_function import numpy as np #A Pythagorean triplet is a set of three natural numbers, a < b < c, for which, #a ** 2 + b ** 2 = c ** 2 # #For example, 3 ** 2 + 4 ** 2 = 9 + 16 = 25 = 5 ** 2. # #There exists exactly one Pytha...
Now, we’ll use the Numpy log function onmy_arrayto calculate the natural log of each number. np.log(my_array) OUT: array([0., 0.69314718, 1.09861229, 1.38629436]) Explanation This should be very easy to understand. Here, we used np.log to calculate the natural logarithm, ...
z=np.array([1+1j,2-2j])# 复数指数函数exp_result=np.exp(z)print("numpyarray.com - Exponential:",exp_result)# 复数对数函数log_result=np.log(z)print("numpyarray.com - Natural logarithm:",log_result)# 复数平方根sqrt_result=np.sqrt(z)print("numpyarray.com - Square root:",sqrt_resul...
The numpy.log() method is used to calculate the natural logarithm of the elements in an array. The numpy.log() function is used to calculate the natural logarithm of the elements in an array.
Natural logarithm, element-wise. 3 )numpy.exp2 numpy.exp2(x, *args, kwargs) Calculate 2p for all p in the input array. 4 )numpy.log2 numpy.log2(x, *args, **kwargs) Base-2 logarithm of x . 5 )numpy.log10 numpy.log10(x, *args, **kwargs) ...