pysparse.cs package

Subpackages

• pysparse.cs.recovery package
  • Submodules
  • pysparse.cs.recovery.lasso module
  • pysparse.cs.recovery.omp module
  • Module contents
• pysparse.cs.sensing package
  • Submodules
  • pysparse.cs.sensing.obsmat module
  • Module contents

Submodules

pysparse.cs.cs module

pysparse.cs.cs.cs1d(y, Phi, Psi=None, optim='OMP', k=1000, tol=1e-08, osshape=None, verbose=True)

Solves the 1-d Compressive Sensing problem

for sparse signal \(\bm x\)

\[{\bm y} = {\bm \Phi}{\bm x} + {\bf n}, \]

for non-sparse signal \({\bm x} = {\bm \Psi}{\bm z}\)

\[{\bm y} = {\bm \Phi \Psi}{\bm z} + {\bm n}, \]

see https://iridescent.ink/aitrace/SignalProcessing/Sparse/LinearCompressiveSensing/index.html for details.

Parameters:

• y (ndarray) – the mesurements \({\bm y}\), if ndarray, each colum is a mesurement
• Phi (2darray) – the mesurement matrix \({\bm \Phi}\)

Keyword Arguments:  

• Psi (2darray) – the dictionary \({\bm \Psi}\) (default: {None})
• optim (str) – optimization method, OMP, LASSO (default: {‘OMP’})
• k (integer) – sparse degree for OMP, max iter for LASSO (default: size of \({\bm x}\) )
• tol (float) – tolerance of error (LASSO) (default: {1e-8})
• osshape (tuple) – orignal signal shape, such as an H-W image (default: {None})
• verbose (bool) – show log info (default: {True})

Returns:

x – reconstructed signal with sieof osshape

Return type:

ndarray

Module contents