NumPy linspace()

import numpy as np

# create an array with 3 elements between 5 and 10
array1 = np.linspace(5, 10, 3)

print(array1)

# Output: [ 5.   7.5 10. ]

linspace() Syntax

The syntax of linspace() is:

numpy.linspace(start, stop, num = 50, endpoint = True, retstep = False, dtype = None, axis = 0)

linspace() Argument

The linspace() method takes the following arguments:

• start- the start value of the sequence, 0 by default (can be array_like)
• stop- the end value of the sequence (can be array_like)
• num(optional)- number of samples to generate (int)
• endpoint(optional)- specifies whether to include end value (bool)
• retstep(optional)- if True, returns steps between the samples (bool)
• dtype(optional)- type of output array
• axis(optional)- axis in the result to store the samples(int)

linspace() Return Value

The linspace() method returns an array of evenly spaced values.

Example 1: Create a 1-D Array Using linspace

import numpy as np
 
# create an array of 5 elements between 2.0 and 3.0
array1 = np.linspace(2.0, 3.0, num=5)
print("Array1:", array1)

# create an array of 5 elements between 2.0 and 3.0 excluding the endpoint
array2 = np.linspace(2.0, 3.0, num=5, endpoint=False)
print("Array2:", array2)

# create an array of 5 elements between 2.0 and 3.0 with the step size included
array3, step_size = np.linspace(2.0, 3.0, num=5, retstep=True)
print("Array3:", array3)

print("Step Size:", step_size)

Output

Array1: [2.   2.25 2.5  2.75 3.  ]
Array2: [2.  2.2 2.4 2.6 2.8]
Array3: [2.   2.25 2.5  2.75 3.  ]
Step Size: 0.25

Example 2: Create an n-D Array Using linspace

import numpy as np
 
# create an array of 5 elements between [1, 2] and [3, 4]
array1 = np.linspace([1, 2], [3, 4], num=5)
print("Array1:")
print(array1)

# create an array of 5 elements between [1, 2] and [3, 4] along axis 1
array2 = np.linspace([1, 2], [3, 4], num=5, axis=1)
print("\nArray2:")
print(array2)

Output

Array1:
[[1.  2. ]
 [1.5 2.5]
 [2.  3. ]
 [2.5 3.5]
 [3.  4. ]]

Array2:
[[1.  1.5 2.  2.5 3. ]
 [2.  2.5 3.  3.5 4. ]]

Key Differences Between arange and linspace

Both np.arange() and np.linspace() are NumPy functions used to generate numerical sequences, but they have some differences in their behavior.

• arange() generates a sequence of values from start to stop with a given step size whereas linspace generates a sequence of num evenly spaced values from start to stop.
• arange() excludes stop value whereas linspace includes stop value unless specified otherwise by endpoint = False

Let us see an example.

import numpy as np

# elements between 10 and 40 with stepsize 4
array1 = np.arange(10, 50 , 4)

# generate 4 elements between 10 and 40 
array2 = np.linspace(10, 50 , 4)

print('Using arange:', array1) # doesn't include 50
print('Using linspace:', array2) #includes 50

Output

Using arange: [10 14 18 22 26 30 34 38 42 46]
Using linspace: [10.         23.33333333 36.66666667 50.        ]