FindPeaks
FindPeaks[list]
gives positions and values of the detected peaks in list.
FindPeaks[list,σ]
finds peaks that survive Gaussian blurring up to scale σ.
FindPeaks[list,σ,s]
finds peaks with minimum sharpness s.
FindPeaks[list,σ,s,t]
finds only peaks with values greater than t.
FindPeaks[list,σ,{s,σs},{t,σt}]
uses different scales for thresholding sharpness and value.
Details and Options
- FindPeaks finds local maxima using the given constraints, returning the result as {{x1,y1},{x2,y2},…}.
- Input list can be of one of the following forms:
-
{y1,y2,…} a list of values TimeSeries[…] regularly sampled time series object EventSeries[…] regularly sampled event series object - FindPeaks[list] automatically chooses scale, sharpness and threshold parameters.
- To avoid the detection of noise-related peaks, the input is regularized by performing a Gaussian filtering using the standard deviation σ.
- The value of σ defaults to
, with n being the number of data points in list. Larger values for σ reduce the number of peaks. - Peaks detected in the regularized data are traced back to the corresponding peaks in the original data.
- By default, peaks are not filtered based on their sharpness (
). The sharpness s is computed as the second derivative of the data with a Gaussian filter at scale σ. Specify a smaller scale using {s,σs}. - By default, peaks of any height are returned. Use a threshold t to dismiss peaks with smaller values. To apply the threshold at a scale other than 0, use {t,σt}.
- FindPeaks[list,σ,s,t] is equivalent to FindPeaks[list,σ,{s,σ},{t,0}].
- The following options can be given:
-
InterpolationOrder Automatic spline interpolation order of up to order 3 Padding "Reflected" padding scheme to use - By default, InterpolationOrder1 is assumed for lists of data. For TimeSeries objects, the interpolation order is inherited.
- The interpolation order is used when computing peak positions. Peaks may be located in between and possibly above {x,y} samples interpolation orders.
- For interpolation orders 0 or 1, a plateau of two or more data samples is assigned a single peak at its center location.
- For possible settings for Padding, see the reference page for ArrayPad.
Examples
open allclose allBasic Examples (1)
Scope (12)
Data (4)
Parameters (8)
By default, an automatic scale is used:
Compute peaks at different scales:
When finding peaks at scale 
, only peaks that sustain a blur up to scale 
are returned:
Signal and its blurred version at scale 
:
By default, peaks are not filtered based on their sharpness, equivalent to 
:
Specify minimum sharpness value 
:
Sharpness, defined by the negative second derivative, should be greater than the specified s:
Specify a minimum height value 
:
Apply the value threshold after smoothing the data using a scale 
:
Options (3)
InterpolationOrder (1)
By default, InterpolationOrder1 is used:
Find peaks of the cubic interpolation:
Note that the number and position of peaks may vary depending on the interpolation order:
Padding (2)
By default, Padding"Reflected" is used:
Padding influences the occurrence and position of peaks at the boundary:
By default, "Reflected" padding causes a peak at position 1:
Text
Wolfram Research (2014), FindPeaks, Wolfram Language function, https://reference.wolfram.com/language/ref/FindPeaks.html (updated 2021).
BibTeX
BibLaTeX
CMS
Wolfram Language. 2014. "FindPeaks." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2021. https://reference.wolfram.com/language/ref/FindPeaks.html.
APA
Wolfram Language. (2014). FindPeaks. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/FindPeaks.html