naginterfaces.library.wav.dim1_mxolap_inv¶
- naginterfaces.library.wav.dim1_mxolap_inv(ca, cd, n, comm)[source]¶
dim1_mxolap_inv
computes the inverse one-dimensional maximal overlap discrete wavelet transform (MODWT) at a single level. The initialization functiondim1_init()
must be called first to set up the MODWT options.For full information please refer to the NAG Library document for c09db
https://support.nag.com/numeric/nl/nagdoc_30.2/flhtml/c09/c09dbf.html
- Parameters
- cafloat, array-like, shape
The approximation coefficients, . These will normally be the result of some transformation on the coefficients computed by
dim1_mxolap_fwd()
.- cdfloat, array-like, shape
The detail coefficients, . These will normally be the result of some transformation on the coefficients computed by
dim1_mxolap_fwd()
.- nint
, the length of the original data array from which the wavelet coefficients were computed by
dim1_mxolap_fwd()
and the length of the data array that is to be reconstructed by this function.- commdict, communication object
Communication structure.
This argument must have been initialized by a prior call to
dim1_init()
.
- Returns
- yfloat, ndarray, shape
The reconstructed data based on approximation and detail coefficients and and the transform options supplied to the initialization function
dim1_init()
.
- Raises
- NagValueError
- (errno )
On entry, array dimension not large enough: but must be at least .
- (errno )
On entry, is inconsistent with the value passed to the initialization function: , should be .
- (errno )
On entry, the initialization function
dim1_init()
has not been called first or it has not been called with , or the communication array [‘icomm’] has become corrupted.
- Notes
dim1_mxolap_inv
performs the inverse operation ofdim1_mxolap_fwd()
. That is, given sets of approximation coefficients and detail coefficients, computed bydim1_mxolap_fwd()
using a MODWT as set up by the initialization functiondim1_init()
, on a real data array of length ,dim1_mxolap_inv
will reconstruct the data array , for , from which the coefficients were derived.
- References
Percival, D B and Walden, A T, 2000, Wavelet Methods for Time Series Analysis, Cambridge University Press