Python – numpy.geomspace

numpy.geomspace() returns a set of numbers spaced evenly on a log scale (a geometric progression). This function is useful for creating exponentially spaced arrays where each element is a constant multiple of the previous one.

Key differences from similar functions ?

• Linspace − Creates linearly spaced numbers between two endpoints

• Logspace − Creates logarithmically spaced numbers using base and power endpoints

• Geomspace − Creates geometrically spaced numbers using actual start and stop values

Syntax

numpy.geomspace(start, stop, num=50, endpoint=True, dtype=None)

Parameters

The above function accepts the following parameters ?

• start − Starting value of the geometric sequence (must be non-zero)

• stop − End value of the geometric sequence

• num − Number of elements to generate between start and stop (default: 50)

• endpoint − If True, stop is the last sample. If False, stop is not included (default: True)

• dtype − Data type of the output array

Example 1: Basic Usage

Creating a geometric sequence from 1 to 2000 with 8 elements ?

import numpy as np

# Create geometric sequence
x = np.geomspace(1, 2000, num=8)
print("geomspace of X:")
print(x)

geomspace of X:
[1.00000000e+00 2.96193630e+00 8.77306662e+00 2.59852645e+01
 7.69666979e+01 2.27970456e+02 6.75233969e+02 2.00000000e+03]

Example 2: Using endpoint=False

Creating a sequence where the stop value is not included ?

import numpy as np

# geomspace with endpoint=False
x = np.geomspace(2, 800, num=9, endpoint=False)
print("geomspace of X:")
print(x)

geomspace of X:
[ 2.         3.89177544  7.57295802 14.73612599 28.67484658
 55.79803176 108.57670466 211.27807602 411.12341312]

Notice that 800 is not included in the output since endpoint=False.

Example 3: Negative Values

Working with negative geometric progressions ?

import numpy as np

# Geometric sequence with negative values
x = np.geomspace(-1, -1000, num=5)
print("Negative geomspace:")
print(x)

Negative geomspace:
[  -1.          -5.62341325  -31.6227766  -177.827941  -1000.        ]

Comparison with Other Functions

Conclusion

NumPy's geomspace() is ideal for creating exponentially spaced arrays where you need a constant multiplicative ratio between consecutive elements. Use it when modeling exponential growth, decay, or when you need logarithmic scaling with specific start and end values.