Cardinal (version 1.4.0)

smoothSignal-methods: Smooth the Feature-Vectors of an Imaging Dataset

Description

Apply smoothing to a mass spectrometry imaging dataset.

Usage

## S3 method for class 'MSImageSet':
smoothSignal(object, method = c("gaussian", "sgolay", "ma"),
    ...,
    pixel = pixels(object),
    plot = FALSE)
## Gaussian smoothing
smoothSignal.gaussian(x, sd=window/4, window=5, ...)
## Savitsky-Golay smoothing
smoothSignal.sgolay(x, order=3, window=order + 3 - order %% 2, ...)
## Moving average smoothing
smoothSignal.ma(x, coef=rep(1, window + 1 - window %% 2), window=5, ...)

Arguments

object

An object of class MSImageSet.

method

The smoothing method to use.

pixel

The pixels to smooth. If less than the extent of the dataset, this will result in a subset of the data being processed.

plot

Plot the mass spectrum for each pixel while it is being processed?

...

Additional arguments passed to the smoothing method.

x

The mass spectrum to be smoothed.

sd

The standard deviation for the Gaussian kernel.

window

The smoothing window.

order

The order of the smoothing filter.

coef

The coefficients for the moving average filter.

Value

• An object of class MSImageSet with the smoothed spectra.

code

pixelApply

Details

Smoothing is usually performed using the provided functions, but a user-created function can also be passed to method. In this case it should take the following arguments:

• x: Anumericvector of intensities.

...: Additional arguments.

See Also

MSImageSet, pixelApply

Examples

data <- generateImage(as="MSImageSet")
smoothSignal(data, method="gaussian", plot=interactive())