msresample
Resample signal with peaks
Syntax
[
Xout
, Intensitiesout
]
= msresample(X
, Intensities
, N
)
msresample(..., 'Uniform', UniformValue
,
...)
msresample(..., 'Range', RangeValue
,
...)
msresample(..., 'RangeWarnOff', RangeWarnOffValue
,
...)
msresample(..., 'Missing', MissingValue
,
...)
msresample(..., 'Window', WindowValue
,
...)
msresample(..., 'Cutoff', CutoffValue
,
...)
msresample(..., 'ShowPlot', ShowPlotValue
,
...)
Arguments
X | Vector of separation-unit values for
a set of signals with peaks. The number of elements in the vector
equals the number of rows in the matrix Intensities .
The separation unit can quantify wavelength, frequency, distance,
time, or m/z depending on the instrument that generates the signal
data. |
Intensities | Matrix of intensity values for a set
of peaks that share the same separation-unit range. Each row corresponds
to a separation-unit value, and each column corresponds to either
a set of signals with peaks or a retention time. The number of rows
equals the number of elements in vector X . |
N | Positive integer specifying the total number of samples. |
Description
Tip
Use the following syntaxes with data from any separation technique that produces signal data, such as spectroscopy, NMR, electrophoresis, chromatography, or mass spectrometry.
[
resamples
raw noisy signal data, Xout
, Intensitiesout
]
= msresample(X
, Intensities
, N
)Intensities
. The
output signal has N
samples with a spacing
that increases linearly within the range [min(
. X
)
max(X
)]X
can
be a linear or a quadratic function of its index. When you set input
arguments such that down-sampling takes place, msresample
applies
a lowpass filter before resampling to minimize aliasing.
For the antialias filter, msresample
uses
a linear-phase FIR filter with a least-squares error minimization.
The cutoff frequency is set by the largest down-sampling ratio when
comparing the same regions in the X
and
Xout
vectors.
Tip
msresample
is particularly useful when you
have signals with different separation-unit vectors and you want to
match the scales.
msresample(..., '
calls PropertyName
', PropertyValue
,
...)msresample
with optional properties
that use property name/property value pairs. You can specify one or
more properties in any order. Each PropertyName
must
be enclosed in single quotes and is case insensitive. These property
name/property value pairs are as follows:
msresample(..., 'Uniform',
, when UniformValue
,
...)
is UniformValue
true
,
it forces the vector X
to be uniformly
spaced. The default value is false
.
msresample(..., 'Range',
specifies a RangeValue
,
...)1
-by-2
vector
with the separation-unit range for the output signal, Intensitiesout
. RangeValue
must
be within [min(
].
Default value is the full range X
) max(X
)[min(
. When X
)
max(X
)]RangeValue
values
exceed the values in X
, msresample
extrapolates
the signal with zeros and returns a warning message.
msresample(..., 'RangeWarnOff',
controls the return of a warning message when RangeWarnOffValue
,
...)RangeValue
values
exceed the values in X
. RangeWarnOffValue
can
be true
or false
(default).
msresample(..., 'Missing',
, when MissingValue
,
...)
is MissingValue
true
,
analyzes the input vector, X
, for dropped
samples. The default value is false
. If the down-sample
factor is large, checking for dropped samples might not be worth the
extra computing time. Dropped samples can only be recovered if the
original separation-unit values follow a linear or a quadratic function
of the X
vector index.
msresample(..., 'Window',
specifies the window used when calculating parameters
for the lowpass filter. Enter WindowValue
,
...)'Flattop'
, 'Blackman'
, 'Hamming
',
or 'Hanning'
. The default value is 'Flattop'
.
msresample(..., 'Cutoff',
specifies the cutoff frequency. Enter a scalar value
from CutoffValue
,
...)0
to 1
(Nyquist frequency
or half the sampling frequency). By default, msresample
estimates
the cutoff value by inspecting the separation-unit vectors, X
and XOut
.
However, the cutoff frequency might be underestimated if X
has
anomalies.
msresample(..., 'ShowPlot',
plots the original and the resampled signal. When ShowPlotValue
,
...)msresample
is
called without output arguments, the signals are plotted unless
is ShowPlotValue
false
.
When
is ShowPlotValue
true
,
only the first signal in Intensities
is
plotted.
can
also contain an index to one of the signals in ShowPlotValue
Intensities
.
Tip
LC/MS data analysis requires extended amounts of memory from the operating system.
If you receive errors related to memory, try the following:
Increase the virtual memory (swap space) for your operating system as described in Resolve “Out of Memory” Errors.
If you receive errors related to Java® heap space, increase your Java heap space:
If you have MATLAB® version 7.10 (R2010a) or later, see Java Heap Memory Preferences.
If you have MATLAB version 7.9 (R2009b) or earlier, see https://www.mathworks.com/matlabcentral/answers/92813-how-do-i-increase-the-heap-space-for-the-java-vm-in-matlab.
Examples
Version History
Introduced before R2006a
See Also
mspalign
| msbackadj
| msdotplot
| msalign
| msheatmap
| mslowess
| msnorm
| mspeaks
| msppresample
| mssgolay
| msviewer
Topics
- Mass Spectrometry and Bioanalytics
- Preprocessing Raw Mass Spectrometry Data
- Visualizing and Preprocessing Hyphenated Mass Spectrometry Data Sets for Metabolite and Protein/Peptide Profiling
- Differential Analysis of Complex Protein and Metabolite Mixtures Using Liquid Chromatography/Mass Spectrometry (LC/MS)