tut/Set1/example1.4/SConstruct

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"""/*!
@page es1step4 Step 4
The next step is to create a compound operator @b PC where @b P is the diagonal 
weighting on the range of @b C.
\f[
  \tilde{\textbf{x}} = \arg\min \|\textbf{x}\|_1\quad\mbox{s.t.}\quad
      \textbf{PC}
    \textbf{x}+\epsilon=\textbf{y}
\f]
 
\par Objectives: 
 - Create a compound operator  
 - Learn more of the builtin SLIMpy Options
 
@section Walkthrough

The code in extremely similar to the previous example, except this time we pass the
operator @a A into the solver.
@code
>>> C = Cosine( y.space )
>>> P = DiagonalWeight( C.range(), weight )
    
>>> A = CompoundOperator( [P,C] ).H

@endcode
*/"""


from slimproj import *

from SLIMpy.linear_operators import *
from slimpy_contrib.ana.GenLandweber import GenThreshLandweber
from slimpy_contrib.ana.utils.thresholds import LinearCooling
from SLIMpy import DotTest

from rsfproj import *
#===============================================================================
# import local plotting function
#===============================================================================
from os.path import abspath
sys.path.append( abspath('..') )
from swellplot import plot_swell



data = '../data.rsf'
sig = '../sig.rsf'
noise = '../swellnoise.rsf'

weight = 'lowfweight.rsf'

@slim_builder_simple
def SwellSeparation( vectors, nouter=2, ninner=2, lmax=0.01, lmin=0.02 ):
    """
    @param vectors  a list of vectors created from SCons sources
    @param thr      the value to threshold with 
    """
    
    y = vectors[0]
    weight = vectors[1]
    
    C = Cosine( y.space )
    P = DiagonalWeight( C.range(), weight )
    
    A = CompoundOperator( [P,C] ).H
    
    thresh = LinearCooling( .01, .02, nouter )
    solver = GenThreshLandweber( nouter, 5, thresh )
    
    #solve for x s.t. y = C*x
    x = solver.solve( A, y )

    res = C * x

    return res


Flow ( weight, None, 
       'math n1=512 output="1-(1*x1*0.1/512.0)" '
       )

SwellSeparation( ['enoise'], [data,weight] , nouter=5, ninner=5, lmax=0.001, lmin=0.1 )

Flow( 'esig', ['enoise', data] , 'math x=${SOURCES[1]} output="x-input"' )

#===============================================================================
# RSF plotting functions
#===============================================================================
plot_swell( data, noise, sig , 'enoise', 'esig' )

#===============================================================================
# Dot Test 
#===============================================================================

@slim_builder_simple
def WeightedCosineDotTest( vectors):
    
    y = vectors[0]
    weight = vectors[1]
    
    C = Cosine( y.space )
    P = DiagonalWeight( y.space, weight )
    
    A = CompoundOperator( [P,C] )
    DotTest(A,3,5)


test = WeightedCosineDotTest( 'test', [data,weight],
                               debug=[] )
Alias( 'dottest', test)

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