# Render Hilbert spectrogram This function prepares results from the Hilbert transform of EMD or EEMD results for display using `HHGramImage`. ```r HHRender(hres, dt, dfreq, time.span = NULL, freq.span = NULL, scaling = "none", combine.imfs = TRUE, verbose = TRUE) ``` ## Arguments - `hres`: This is the output generated by `Sig2IMF`, `EEMDCompile`, `EEMDResift` , or `CEEMD` . - `dt`: Time resolution of spectrogram. Must be greater than the sample rate of the time series to avoid gaps. - `dfreq`: Frequency resolution of spectrogram. - `time.span`: Time span to render spectrogram over; `NULL` means over the whole time series. - `freq.span`: Frequency span to include in spectrogram; `NULL` means render all the frequencies in the time series - `scaling`: If `"log"`, render a log frequency spectrogram. Defaults to `"none"` (linear). - `combine.imfs`: If `TRUE`, add the spectra for all IMFS together in one ensemble Hilbert spectrogram, if `FALSE`, keep separate so you can investigate individual IMFs in `HHGramImage`. - `verbose`: If `TRUE`, print progress messages. ## Details `HHRender` processes Hilbert spectral data prior to displaying with `HHGramImage`. `HHRender` returns the ensemble Hilbert spectrogram if `combine.imfs = TRUE`, otherwise it returns an IMF-by-IMF Hilbert spectrogram of dimensions `[time, freq, imf]`. The user can then choose which IMFs to plot when he or she calls `HHGramImage`, but this makes `HHGramImage` run about 40x slower on my machine. The trade off is in speed versus flexibility for `HHGramImage`; the `combine.imfs` option does not affect `HHRender` very much. ## Note The `HHRender` function also keeps track of which trial contributes what data to the spectrogram. For the EMD, this does not make much sense, because there is only one trial. However, when `HHRender` is run on EEMD results, it remembers which time/frequency bin gets data from each trial. This is a way to distinguish between noise and signal in data: signal is where multiple trials contribute data to the same time/frequency bin, noise is where only one (or a couple) of trials contribute data. See options for `HHGramImage` for ways to plot data based on signal stability. ## Returns - **hgram**: A data structure containing the spectrogram image and other information required by `HHGramImage`. ## Author(s) Daniel Bowman danny.c.bowman@gmail.com ## See Also `EEMDCompile`, `HHGramImage` ## Examples ```r 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, noise.amp, 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(5, 10) freq.span <- c(0, 25) amp.span <- c(1e-6, 2.5e-5) ## Not run: HHGramImage(hgram, time.span = time.span, freq.span = freq.span, amp.span = amp.span) ## End(Not run) ```

HHRender function