View source: R/rendering_and_plotting.R
HHGramImage | R Documentation |
This function displays the Hilbert spectrogram of EMD and EEMD results.
HHGramImage(hgram, time.span = NULL, freq.span = NULL, amp.span = NULL,
clustergram = FALSE, cluster.span = NULL, imf.list = NULL,
fit.line = FALSE, scaling = "none", grid = TRUE, colorbar = TRUE,
backcol = c(0, 0, 0), colormap = NULL, pretty = FALSE, ...)
hgram |
Data structure generated by |
time.span |
Time span to render spectrogram over. |
freq.span |
Frequency span to render spectrogram over. |
amp.span |
This is the amplitude span to plot, everything below is set to |
clustergram |
If |
cluster.span |
Plots only parts of the signal that have a certain number of data points per pixel (see notes below).
This only applies when using EEMD.
The pixel range is defined as |
imf.list |
A vector of IMFs to plot on the spectrogram, the others will not be shown.
You must set |
fit.line |
If |
.
scaling |
determines whether to apply a logarithmic ( |
grid |
Boolean - whether to display grid lines or not |
colorbar |
Boolean - whether to display amplitude colorbar or not |
backcol |
What background color to use behind the spectrogram, in a 3 element vector: |
colormap |
What palette object to use for the spectrogram, defaults to |
pretty |
Boolean - to choose nice axes values or to use exactly the ranges given |
... |
This function supports some optional parameters as well:
|
This function plots the image generated by HHRender
along with the original signal trace.
The plotter can use data from both EMD and EEMD runs.
When it plots EEMD data, it shows the time frequency plot of every single trial at once.
The cluster.span
option is useful in this case because it can distinguish “signal” (pixels where multiple trials intersect) from “noise” (whether from EEMD or from nature) where only one trial contributes data.
img |
The spectrogram image, suitable for plotting with the generic |
Using the option combine.imfs = FALSE
in HHRender
will cause HHGramImage
to run much, much slower.
Unless you have a compelling reason to plot certain IMFs (as opposed to all of them combined), I recommend against using this.
It may take some trial and error to get a nice image.
For example, if the data points are too small (and thus the spectrogram looks like a mist of fine points rather than continuous frequency bands), try rerunning HHRender
, but with lower frequency resolution.
If the spectrogram is extremely noisy, try defining cluster.span
- this usually gets rid of most of the random noise.
For example, a cluster.span
of c(3, 10)
only keeps pixels that have data from at least 3 trials, up to 10.
Most noise pixels will only have one trial contributing data.
The upper limit (10) is a formality - it does not make much sense at this point to put an upper limit on trial intersections unless you are interested in the noise component isolated from the signal.
Daniel Bowman danny.c.bowman@gmail.com
FTGramImage
, HHRender
, HHSpecPlot
data(PortFosterEvent)
trials <- 10
nimf <- 10
noise.amp <- 6.4e-07
trials.dir <- "test"
set.seed(628)
#Run EEMD (this may take some time)
## Not run: EEMD(sig, tt, noise.amp, trials, nimf, trials.dir = trials.dir)
#Compile the results
## Not run: EEMD.result <- EEMDCompile(trials.dir, trials, nimf)
#Calculate spectrogram
dt <- 0.1
dfreq <- 0.1
## Not run: hgram <- HHRender(EEMD.result, dt, dfreq)
#Plot spectrogram
time.span <- c(4, 10)
freq.span <- c(0, 25)
## Not run: HHGramImage(hgram, time.span, freq.span,
pretty = TRUE, img.x.format = "%.1f", img.y.format = "%.0f",
main = "Port Foster event - ensemble Hilbert spectrogram")
## End(Not run)
#Plot intersections
## Not run: HHGramImage(hgram, time.span, freq.span, amp.span = c(1, 5),
clustergram = TRUE, pretty = TRUE, img.x.format = "%.1f", colorbar.format = "%.0f",
img.y.format = "%.0f", main = "Port Foster event - signal stability")
## End(Not run)
#Decluster
#show only areas with stable signal
#i.e. each pixel has data from at least 3 EEMD trials
## Not run: HHGramImage(hgram, time.span = time.span, freq.span = freq.span,
cluster.span = c(, 10), pretty = TRUE, img.x.format = "%.1f",
img.y.format = "%.0f",
main = "Port Foster event - ensemble Hilbert spectrogram")
## End(Not run)
#Log amplitude plot
## Not run: HHGramImage(hgram, time.span = time.span, freq.span = freq.span,
scaling = "log", pretty = TRUE, img.x.format = "%.1f", img.y.format = "%.0f",
main = "Port Foster event - ensemble Hilbert spectrogram with log amplitude")
## End(Not run)
#Log frequency plot
dfreq <- 0.001
## Not run: hgram=HHRender(EEMD.result, dt, dfreq, scaling = "log")
## Not run: HHGramImage(hgram, time.span, freq.span = c(0, 2),
pretty = TRUE, img.x.format = "%.1f", img.y.format = "%.2f",
img.y.lab = "log frequency",
main = "Port Foster event - ensemble Hilbert spectrogram with log frequency")
## End(Not run)
#Only show IMF 1
dfreq <- 0.1
## Not run: hgram=HHRender(EEMD.result, dt, dfreq, combine.imfs = FALSE)
## Not run: HHGramImage(hgram, time.span, freq.span, imf.list = 1,
pretty = TRUE, img.x.format = "%.1f", img.y.format = "%.0f",
main = "Port Foster event - ensemble Hilbert spectrogram of IMF 1")
## End(Not run)
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