# cwtp: Continuous Wavelet Transform with Phase Derivative In Rwave: Time-Frequency Analysis of 1-D Signals

## Description

Computes the continuous wavelet transform with (complex-valued) Morlet wavelet and its phase derivative.

## Usage

 `1` ```cwtp(input, noctave, nvoice=1, w0=2 * pi, twoD=TRUE, plot=TRUE) ```

## Arguments

 `input` input signal (possibly complex-valued) `noctave` number of powers of 2 for the scale variable `nvoice` number of scales in each octave (i.e., between two consecutive powers of 2). `w0` central frequency of the wavelet. `twoD` logical variable set to `T` to organize the output as a 2D array (signal size x nb scales), otherwise, the output is a 3D array (signal size x noctave x nvoice). `plot` if set to `TRUE`, display the modulus of the continuous wavelet transform on the graphic device.

## Value

list containing the continuous (complex) wavelet transform and the phase derivative

 `wt` array of complex numbers for the values of the continuous wavelet transform. `f` array of the same dimensions containing the values of the derivative of the phase of the continuous wavelet transform.

## References

See discussions in the text of “Practical Time-Frequency Analysis”.

## See Also

`cgt`, `cwt`, `cwtTh`, `DOG` for wavelet transform, and `gabor` for continuous Gabor transform.

## Examples

 ```1 2 3 4 5 6``` ``` ## discards imaginary part with error, ## c code does not account for Im(input) x <- 1:512 chirp <- sin(2*pi * (x + 0.002 * (x-256)^2 ) / 16) chirp <- chirp + 1i * sin(2*pi * (x + 0.004 * (x-256)^2 ) / 16) retChirp <- cwtp(chirp, noctave=5, nvoice=12) ```

### Example output ```Warning message:
In cwtp(chirp, noctave = 5, nvoice = 12) :
imaginary parts discarded in coercion
```

Rwave documentation built on May 2, 2019, 9:15 a.m.