`numpy:geomspace`

source: /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)

✗

array([  1.,   2.,   4.,   8.,  16.,  32.,  64., 128., 256.])

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)

✓

array([  1,   2,   4,   8,  16,  32,  64, 128, 256])

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

✓

array([0.   +1.j, 0.  +10.j, 0. +100.j, 0.+1000.j])

np.geomspace(-1+0j, 1+0j, num=5)  # Circle

✗

array([-1.00000000e+00+0.j        , -7.07106781e-01+0.70710678j,
       -6.12323400e-17+1.j        ,  7.07106781e-01+0.70710678j,
        1.00000000e+00+0.j        ])

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')

✓

[<matplotlib.lines.Line2D object at 0x7fe9860a4d70>]

plt.axis([0.5, 2000, 0, 3])

✗

(np.float64(0.5), np.float64(2000.0), np.float64(0.0), np.float64(3.0))

plt.grid(True, color='0.7', linestyle='-', which='both', axis='both')
plt.show()

✓

Aliases

numpy.geomspace