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. The method returns the natural logarithm of x, elementwise. This is a scalar if x is a scalar. The 1st parameter is the input value, array-like. The 2nd parameter is out, a location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
Logarithm is a multivalued function − for each x there is an infinite number of z such that exp(z) = x. The convention is to return the z whose imaginary part lies in [-pi, pi]. For real-valued input data types, log always returns real output. For each value that cannot be expressed as a real number or infinity, it yields nan and sets the invalid floating point error flag. For complex-valued input, log is a complex analytical function that has a branch cut [-inf, 0] and is continuous from above on it. log handles the floating-point negative zero as an infinitesimal negative number, conforming to the C99 standard.
Steps
At first, import the required library −
import numpy as np
Creating a numpy array using the array() method −
arr = np.array([1, 2, np.e, np.e**2])
Display the array −
print("Our Array...\n",arr)Check the Dimensions −
print("\nDimensions of our Array...\n",arr.ndim)Get the Datatype −
print("\nDatatype of our Array object...\n",arr.dtype)Get the Shape −
print("\nShape of our Array...\n",arr.shape)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 −
print("\nResult (log)...\n",np.log(arr))Example
import numpy as np
# Creating a numpy array using the array() method
arr = np.array([1, 2, np.e, np.e**2])
# Display the array
print("Our Array...\n",arr)
# Check the Dimensions
print("\nDimensions of our Array...\n",arr.ndim)
# Get the Datatype
print("\nDatatype of our Array object...\n",arr.dtype)
# Get the Shape
print("\nShape of our Array...\n",arr.shape)
# 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.
print("\nResult (log)...\n",np.log(arr))Output
Our Array... [1. 2. 2.71828183 7.3890561 ] Dimensions of our Array... 1 Datatype of our Array object... float64 Shape of our Array... (4,) Result (log)... [0. 0.69314718 1. 2. ]