Skip to content

threshold_operator.py#

Thresholding operators for POCS algorithm. These functions are only used when pywavelets package is not installed (fallback option).

_soft_threshold(data, value, substitute=0) #

Soft thresholding (from pywavelet).

Parameters:

  • data (ndarray) –

    Input coefficients.

  • value (float) –

    Threshold value.

  • substitute (float, default: 0 ) –

    Value to insert for values below threshold (default: 0).

Returns:

  • ndarray –

    Coefficients with applied threshold.

References#

  1. PyWavelets, https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py ↩

Source code in pseudo_3D_interpolation\functions\threshold_operator.py 
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
def _soft_threshold(data, value, substitute=0):
    """
    Soft thresholding (from `pywavelet`).

    Parameters
    ----------
    data : np.ndarray
        Input coefficients.
    value : float
        Threshold value.
    substitute : float, optional
        Value to insert for values below threshold (default: `0`).

    Returns
    -------
    np.ndarray
        Coefficients with applied threshold.

    References
    ----------
    [^1]: PyWavelets, [https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py](https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py)

    """
    data = np.asarray(data)
    magnitude = np.absolute(data)

    with np.errstate(divide='ignore'):
        # divide by zero okay as np.inf values get clipped, so ignore warning.
        thresholded = 1 - value / magnitude
        thresholded.clip(min=0, max=None, out=thresholded)
        thresholded = data * thresholded

    if substitute == 0:
        return thresholded
    else:
        cond = np.less(magnitude, value)
        return np.where(cond, substitute, thresholded)

_nn_garrote(data, value, substitute=0) #

Non-negative Garrote thresholding (from pywavelet).

Parameters:

  • data (ndarray) –

    Input coefficients.

  • value (float) –

    Threshold value.

  • substitute (float, default: 0 ) –

    Value to insert for values below threshold (default: 0).

Returns:

  • ndarray –

    Coefficients with applied threshold.

References#

  1. PyWavelets, https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py ↩

Source code in pseudo_3D_interpolation\functions\threshold_operator.py 
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
def _nn_garrote(data, value, substitute=0):
    """
    Non-negative Garrote thresholding (from `pywavelet`).

    Parameters
    ----------
    data : np.ndarray
        Input coefficients.
    value : float
        Threshold value.
    substitute : float, optional
        Value to insert for values below threshold (default: `0`).

    Returns
    -------
    np.ndarray
        Coefficients with applied threshold.

    References
    ----------
    [^1]: PyWavelets, [https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py](https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py)

    """
    data = np.asarray(data)
    magnitude = np.absolute(data)

    with np.errstate(divide='ignore'):
        # divide by zero okay as np.inf values get clipped, so ignore warning.
        thresholded = 1 - value**2 / magnitude**2
        thresholded.clip(min=0, max=None, out=thresholded)
        thresholded = data * thresholded

    if substitute == 0:
        return thresholded
    else:
        cond = np.less(magnitude, value)
        return np.where(cond, substitute, thresholded)

_hard_threshold(data, value, substitute=0) #

Hard thresholding (from pywavelet).

Parameters:

  • data (ndarray) –

    Input coefficients.

  • value (float) –

    Threshold value.

  • substitute (float, default: 0 ) –

    Value to insert for values below threshold (default: 0).

Returns:

  • ndarray –

    Coefficients with applied threshold.

References#

  1. PyWavelets, https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py ↩

Source code in pseudo_3D_interpolation\functions\threshold_operator.py 
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
def _hard_threshold(data, value, substitute=0):
    """
    Hard thresholding (from `pywavelet`).

    Parameters
    ----------
    data : np.ndarray
        Input coefficients.
    value : float
        Threshold value.
    substitute : float, optional
        Value to insert for values below threshold (default: `0`).

    Returns
    -------
    np.ndarray
        Coefficients with applied threshold.

    References
    ----------
    [^1]: PyWavelets, [https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py](https://github.com/PyWavelets/pywt/blob/master/pywt/_thresholding.py)

    """
    data = np.asarray(data)
    cond = np.less(np.absolute(data), value)
    return np.where(cond, substitute, data)
Last update: Monday, 03 July 2023 at 09:46:51