`numpy:unwrap`

source: /numpy/lib/_function_base_impl.py :1740

Signature

   def     unwrap (    p    ,    discont    =  None   ,    axis    =  -1   ,  * ,     period    =  6.283185307179586     )

Summary

Unwrap by taking the complement of large deltas with respect to the period.

Extended Summary

This unwraps a signal p by changing elements which have an absolute difference from their predecessor of more than max(discont, period/2) to their period-complementary values.

For the default case where period is $2 π$ and discont is $π$ , this unwraps a radian phase p such that adjacent differences are never greater than $π$ by adding $2 k π$ for some integer $k$ .

Parameters

p : array_like: Input array.
discont : float, optional: Maximum discontinuity between values, default is period/2. Values below period/2 are treated as if they were period/2. To have an effect different from the default, discont should be larger than period/2.
axis : int, optional: Axis along which unwrap will operate, default is the last axis.
period : float, optional: Size of the range over which the input wraps. By default, it is 2 pi.
versionadded 1.21.0

Returns

out : ndarray: Output array.

Notes

If the discontinuity in p is smaller than period/2, but larger than discont, no unwrapping is done because taking the complement would only make the discontinuity larger.

Examples

import numpy as np

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phase = np.linspace(0, np.pi, num=5)
phase[3:] += np.pi

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phase
np.unwrap(phase)

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np.unwrap([0, 1, 2, -1, 0], period=4)
np.unwrap([ 1, 2, 3, 4, 5, 6, 1, 2, 3], period=6)
np.unwrap([2, 3, 4, 5, 2, 3, 4, 5], period=4)
phase_deg = np.mod(np.linspace(0 ,720, 19), 360) - 180
np.unwrap(phase_deg, period=360)

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This example plots the unwrapping of the wrapped input signal `w`. First generate `w`, then apply `unwrap` to get `u`.

t = np.linspace(0, 25, 801)
w = np.mod(1.5 * np.sin(1.1 * t + 0.26) * (1 - t / 6 + (t / 23) ** 3), 2.0) - 1
u = np.unwrap(w, period=2.0)

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Plot `w` and `u`.

import matplotlib.pyplot as plt

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plt.plot(t, w, label='w (a signal wrapped to [-1, 1])')
plt.plot(t, u, linewidth=2.5, alpha=0.5, label='unwrap(w, period=2)')
plt.xlabel('t')

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plt.grid(alpha=0.6)

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plt.legend(framealpha=1, shadow=True)

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plt.show()

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Aliases

numpy.unwrap