import dascore as dc
patch = dc.get_example_patch()
decimated_irr = patch.decimate(time=10, filter_type='iir')
# Example using fir along distance dimension
decimated_fir = patch.decimate(distance=10, filter_type='fir')decimate
decimate(
     patch: Patch ,
     filter_type: Literal[‘iir’, ‘fir’, None] = iir,
     copy = True,
     **kwargs ,
 )-> ‘PatchType’
Decimate a patch along a dimension.
Parameters
| Parameter | Description | 
|---|---|
| filter_type | filter type to use to avoid aliasing. Options are: iir - infinite impulse response fir - finite impulse response None - No pre-filtering, not recommended, may cause aliasing | 
| copy | If True, copy the decimated data array. This is needed if you want the old array to get gc’ed to free memory otherwise a view is returned. Only applies when filter_type == None. | 
| **kwargs | Used to pass dimension and factor. For example time=10is 10xdecimation along the time axis. | 
Note
- Simply uses scipy.signal.decimate if filter_type is specified. Otherwise,just slice data long specified dimension only including every n samples. 
- If the decimation dimension is small, this can fail due to lack of padding values. 
