# NumPy logspace()

The `logspace()` method creates an array with evenly spaced numbers on a logarithm scale.

### Example

``````import numpy as np

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

print(array1)

# Output: [1.00000000e+05 3.16227766e+07 1.00000000e+10]``````

## logspace() Syntax

The syntax of `logspace()` is:

``numpy.logspace(start, stop, num = 50, endpoint = True, base = 10, dtype = None, axis = 0)``

## logspace() Argument

The `logspace()` method takes the following arguments:

• `start`- the start value of the sequence
• `stop`- the end value of the sequence
• `num`(optional)- number of samples to generate
• `endpoint`(optional)- specifies whether to include end value
• `dtype`(optional)- type of output array
• `base`(optional)- base of log scale
• `axis`(optional)- the axis in the result to store the samples

Notes:

• In linear space, the sequence generated by `logspace()` starts at base ** start (base to the power of start) and ends with base ** stop.
• If `dtype` is omitted, `logspace()` will determine the type of the array elements from the types of other parameters.

## logspace() Return Value

The `logspace()` method returns an array of evenly spaced values on a logarithmic scale.

## Example 1: Create a 1-D Array Using logspace

``````import numpy as np

# create an array of 5 elements between 10^2 and 10^3
array1 = np.logspace(2.0, 3.0, num = 5)
print("Array1:", array1)

# create an array of 5 elements between 10^2 and 10^3 without including the endpoint
array2 = np.logspace(2.0, 3.0, num = 5, endpoint = False)
print("Array2:", array2)

# create an array of 5 elements between 2^2 and 2^3
array3 = np.logspace(2.0, 3.0, num = 5, base = 2)
print("Array3:", array3)``````

Output

```Array1: [ 100.          177.827941    316.22776602  562.34132519 1000.        ]
Array2: [100.         158.48931925 251.18864315 398.10717055 630.95734448]
Array3: [4.         4.75682846 5.65685425 6.72717132 8.        ]```

## Example 2: Create an N-d Array Using logspace

Similar to 1D arrays, we can also create N-d arrays using logspace. For this, we can simply pass a sequence to start and stop values instead of integers.

Let us look at an example.

``````import numpy as np

# create an array of 5 elements between [10^1, 10^2] and [10^5, 10^6]
array1 = np.logspace([1, 2], [5, 6], num=5)
print("Array1:")
print(array1)

# create an array of 5 elements between [1, 2] and [3, 4] along axis 1
array2 = np.logspace([1, 2], [5, 6], num=5, axis=1)
print("Array2:")
print(array2)``````

Output

```Array1:
[[1.e+01 1.e+02]
[1.e+02 1.e+03]
[1.e+03 1.e+04]
[1.e+04 1.e+05]
[1.e+05 1.e+06]]
Array2:
[[1.e+01 1.e+02 1.e+03 1.e+04 1.e+05]
[1.e+02 1.e+03 1.e+04 1.e+05 1.e+06]]```