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bundles / scipy 1.17.1 / scipy / signal / _savitzky_golay / savgol_filter

function

scipy.signal._savitzky_golay:savgol_filter

source: /scipy/signal/_savitzky_golay.py :253

Signature

def   savgol_filter ( x ,  window_length ,  polyorder ,  deriv = 0 ,  delta = 1.0 ,  axis = -1 ,  mode = interp ,  cval = 0.0 )

Summary

Apply a Savitzky-Golay filter to an array.

Extended Summary

This is a 1-D filter. If x has dimension greater than 1, axis determines the axis along which the filter is applied.

Parameters

x : array_like

The data to be filtered. If x is not a single or double precision floating point array, it will be converted to type numpy.float64 before filtering.

window_length : int

The length of the filter window (i.e., the number of coefficients). If mode is 'interp', window_length must be less than or equal to the size of x.

polyorder : int

The order of the polynomial used to fit the samples. polyorder must be less than window_length.

deriv : int, optional

The order of the derivative to compute. This must be a nonnegative integer. The default is 0, which means to filter the data without differentiating.

delta : float, optional

The spacing of the samples to which the filter will be applied. This is only used if deriv > 0. Default is 1.0.

axis : int, optional

The axis of the array x along which the filter is to be applied. Default is -1.

mode : str, optional

Must be 'mirror', 'constant', 'nearest', 'wrap' or 'interp'. This determines the type of extension to use for the padded signal to which the filter is applied. When mode is 'constant', the padding value is given by cval. See the Notes for more details on 'mirror', 'constant', 'wrap', and 'nearest'. When the 'interp' mode is selected (the default), no extension is used. Instead, a degree polyorder polynomial is fit to the last window_length values of the edges, and this polynomial is used to evaluate the last window_length // 2 output values.

cval : scalar, optional

Value to fill past the edges of the input if mode is 'constant'. Default is 0.0.

Returns

y : ndarray, same shape as `x`

The filtered data.

Notes

Details on the mode options:

'mirror':

Repeats the values at the edges in reverse order. The value closest to the edge is not included.

'nearest':

The extension contains the nearest input value.

'constant':

The extension contains the value given by the cval argument.

'wrap':

The extension contains the values from the other end of the array.

For example, if the input is [1, 2, 3, 4, 5, 6, 7, 8], and window_length is 7, the following shows the extended data for the various mode options (assuming cval is 0) 

mode       |   Ext   |         Input          |   Ext
-----------+---------+------------------------+---------
'mirror'   | 4  3  2 | 1  2  3  4  5  6  7  8 | 7  6  5
'nearest'  | 1  1  1 | 1  2  3  4  5  6  7  8 | 8  8  8
'constant' | 0  0  0 | 1  2  3  4  5  6  7  8 | 0  0  0
'wrap'     | 6  7  8 | 1  2  3  4  5  6  7  8 | 1  2  3

Array API Standard Support

savgol_filter has experimental support for Python Array API Standard compatible backends in addition to NumPy. Please consider testing these features by setting an environment variable SCIPY_ARRAY_API=1 and providing CuPy, PyTorch, JAX, or Dask arrays as array arguments. The following combinations of backend and device (or other capability) are supported.

====================  ====================  ====================
Library               CPU                   GPU
====================  ====================  ====================
NumPy                 ✅                     n/a                 
CuPy                  n/a                   ✅                   
PyTorch               ✅                     ⛔                   
JAX                   ⚠️ no JIT             ⛔                   
Dask                  ✅                     n/a                 
====================  ====================  ====================

See dev-arrayapi for more information.

Examples

import numpy as np
from scipy.signal import savgol_filter
np.set_printoptions(precision=2)  # For compact display.
x = np.array([2, 2, 5, 2, 1, 0, 1, 4, 9])
✓
Filter with a window length of 5 and a degree 2 polynomial. Use the defaults for all other parameters. 
savgol_filter(x, 5, 2)
✓
Note that the last five values in x are samples of a parabola, so when mode='interp' (the default) is used with polyorder=2, the last three values are unchanged. Compare that to, for example, `mode='nearest'`: 
savgol_filter(x, 5, 2, mode='nearest')
✓

See also

savgol_coeffs

Aliases

  • scipy.signal.savgol_filter

Referenced by

This package