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bundles / numpy latest / numpy / geomspace

_ArrayFunctionDispatcher

numpy:geomspace

source: /dev/numpy/build-install/usr/lib/python3.14/site-packages/numpy/_core/function_base.py :311

Signature

def   geomspace ( start stop num = 50 endpoint = True dtype = None axis = 0 )

Summary

Return numbers spaced evenly on a log scale (a geometric progression).

Extended Summary

This is similar to logspace, but with endpoints specified directly. Each output sample is a constant multiple of the previous.

Parameters

start : array_like

The starting value of the sequence.

stop : array_like

The final value of the sequence, unless endpoint is False. In that case, num + 1 values are spaced over the interval in log-space, of which all but the last (a sequence of length num) are returned.

num : integer, optional

Number of samples to generate. Default is 50.

endpoint : boolean, optional

If true, stop is the last sample. Otherwise, it is not included. Default is True.

dtype : dtype

The type of the output array. If dtype is not given, the data type is inferred from start and stop. The inferred dtype will never be an integer; float is chosen even if the arguments would produce an array of integers.

axis : int, optional

The axis in the result to store the samples. Relevant only if start or stop are array-like. By default (0), the samples will be along a new axis inserted at the beginning. Use -1 to get an axis at the end.

Returns

samples : ndarray

num samples, equally spaced on a log scale.

Notes

If the inputs or dtype are complex, the output will follow a logarithmic spiral in the complex plane. (There are an infinite number of spirals passing through two points; the output will follow the shortest such path.)

Examples

import numpy as np
np.geomspace(1, 1000, num=4)
np.geomspace(1, 1000, num=3, endpoint=False)
np.geomspace(1, 1000, num=4, endpoint=False)
np.geomspace(1, 256, num=9)
Note that the above may not produce exact integers:
np.geomspace(1, 256, num=9, dtype=int)
np.around(np.geomspace(1, 256, num=9)).astype(int)
Negative, decreasing, and complex inputs are allowed:
np.geomspace(1000, 1, num=4)
np.geomspace(-1000, -1, num=4)
np.geomspace(1j, 1000j, num=4)  # Straight line
np.geomspace(-1+0j, 1+0j, num=5)  # Circle
Graphical illustration of `endpoint` parameter:
import matplotlib.pyplot as plt
N = 10
y = np.zeros(N)
plt.semilogx(np.geomspace(1, 1000, N, endpoint=True), y + 1, 'o')
plt.semilogx(np.geomspace(1, 1000, N, endpoint=False), y + 2, 'o')
plt.axis([0.5, 2000, 0, 3])
plt.grid(True, color='0.7', linestyle='-', which='both', axis='both')
plt.show()
fig-2cdcf19fcc070fa7.png

See also

arange

Similar to linspace, with the step size specified instead of the number of samples.

how-to-partition

ref

linspace

Similar to geomspace, but with arithmetic instead of geometric progression.

logspace

Similar to geomspace, but with endpoints specified using log and base.

Aliases

  • numpy.geomspace

Referenced by