map2map

Create a x/y-map with fixed grid (dx and dy is constant) from a x/y-map with varying grid. This function was implemented to display spectrograms with varying hopsize dt and frequency resolution df.

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Usage 1

map2map(type, x, nc)

type

this argument must be set to 0; it will be used in future to select the format of the input data and/or the remapping algorithm

x

a NxM matrix containing the input map

nc

a vector with length N; the value nc[i] specifies the number of used columns in the row x[i,*] of the input map

2 <= nc[i] <= M; with: i=0..N-1

Description

Each row i of the input map contains a data vector {x[i,0], .., x[i,nc[i]-1]}. A linear interpolation is used to expand all vectors to the length M.

Example

x contains a spectrogram. The spectra are computed with constant hopsize, but different transformation length. The length of each spectrum x[i,*] is stored in nc[i].

Result 1

A NxM matrix containing the interpolated map y.

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Usage 2

map2map(type, x, nc, pr)

type, x, nc

see Usage 1

pr

a vector with length N; the value pr[i] specifies the relative position of the function stored in the row x[i,*] of the input map.

pr[0] < pr[1] < .. < pr[N-1]

Description

First the vectors x[i,*] are expanded as described above. In the second step interpolated rows are inserted to create a map with equidistant rows. The number of rows L of the interpolated map y depends on the range of the pr values and the minimum distance of two neighboring values of pr.

L = (pr[N-1] - pr[0]) / min(pr[i] - pr[i-1])

Example

x contains a spectrogram. The spectra stored in the columns of x are computed with varying hopsize and transformation length. The length of each spectrum x[i,*] is stored in nc[i] and the value pr[i] is set to the center position of the i-th analysis window.

Result 2

A LxM matrix containing the interpolated map y.

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See also

rpolyreg, qinterp, interp

<function list>

//----- // Map2Map(Type_s=0, X_m, NCol_v {, PRow_v}) // // Type_s=0 expand all rows to equal length (use linear interpolation) // if PRow_v is specified: map varying row distances to fixed grid (use linear interpolation) // // X_m input map (N rows, M columns) N > 2, M > 2 // NCol_v NCol_v[n] = the number of used columns in row X_m[n,*]; 0 <= n < N, 2 < NCol[n] < M // PRow_v XRow_v[n] = the relative position of row X_m[n,*]; 0 <= n < N, PRow_[0] < PRow[1] < .. < PRow[N-2] < PRow[NX-1] // // result: without PRow_v: Y_m (N rows, M columns) // with PRow_v: Y_m (NY rows, M columns); NY := int ( (PRow_v[N-1] - PRow_v[0]) / min(PRow_v) ) + 1 //-----