69 lines
1.9 KiB
ReStructuredText
69 lines
1.9 KiB
ReStructuredText
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scipy.signal
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============
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This module defines the single function:
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1. `scipy.signal.sosfilt <#sosfilt>`__
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sosfilt
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-------
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``scipy``:
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https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.sosfilt.html
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Filter data along one dimension using cascaded second-order sections.
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The function takes two positional arguments, ``sos``, the filter
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segments of length 6, and the one-dimensional, uniformly sampled data
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set to be filtered. Returns the filtered data, or the filtered data and
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the final filter delays, if the ``zi`` keyword arguments is supplied.
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The keyword argument must be a float ``ndarray`` of shape
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``(n_sections, 2)``. If ``zi`` is not passed to the function, the
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initial values are assumed to be 0.
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.. code::
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# code to be run in micropython
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from ulab import numpy as np
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from ulab import scipy as spy
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x = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
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sos = [[1, 2, 3, 1, 5, 6], [1, 2, 3, 1, 5, 6]]
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y = spy.signal.sosfilt(sos, x)
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print('y: ', y)
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.. parsed-literal::
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y: array([0.0, 1.0, -4.0, 24.0, -104.0, 440.0, -1728.0, 6532.000000000001, -23848.0, 84864.0], dtype=float)
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.. code::
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# code to be run in micropython
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from ulab import numpy as np
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from ulab import scipy as spy
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x = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])
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sos = [[1, 2, 3, 1, 5, 6], [1, 2, 3, 1, 5, 6]]
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# initial conditions of the filter
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zi = np.array([[1, 2], [3, 4]])
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y, zf = spy.signal.sosfilt(sos, x, zi=zi)
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print('y: ', y)
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print('\n' + '='*40 + '\nzf: ', zf)
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.. parsed-literal::
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y: array([4.0, -16.0, 63.00000000000001, -227.0, 802.9999999999999, -2751.0, 9271.000000000001, -30775.0, 101067.0, -328991.0000000001], dtype=float)
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========================================
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zf: array([[37242.0, 74835.0],
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[1026187.0, 1936542.0]], dtype=float)
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