tut/Set1/example1.2/SConstruct

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"""/*!
@page es1step2 Step 2
\par Objectives: 
 - Integrate the previous example with SCons and Madagascar reproducibility 
 - Perform a dot-test on a linear operator
\section walkthrough Walkthrough

@par Usage:
@code
    scons view
    scons dottest
@endcode
@par Preamble

@code
from slimproj import *
@endcode 

slimproj is the SLIMpy SCons integration package.
Hopefully you are familiar with the Madagascar pacage
 
@code
from rsfproj import *

Flow( 'sig', None , "sigmoid n1=256 n2=256" )
Flow( 'data', 'sig' , "noise var=0.0002" )
@endcode 

This code does the same as in the previous example and creates the sigmoid synthetic model and data.
 
@code
@slim_builder_simple
def SwellSeparation( vectors, thr=0.001 ):
@endcode 

Here I define the body of the code in the function SurfaceletDeNoise. 
SurfaceletDeNoise is a special function because it has the 
\ref slimproj_core.builders.funtion_decorators.slim_builder_simple "slim_builder_simple" 
decorator above it. 
This turns the function into a SCons Builder object.
The body of the code is defined the same as the previous example.
@code
res = SwellSeparation( 'enoise', data , thr=0.001 )
@endcode
Here we call the SCons Builder to build the target @a res.rsf from the soucre @a data.rsf. 
The reason that I do it this way - by putting the body of the code inside a builder - instead 
of just calling the code inline inside of the SConstruct, is becuase at the time scons is evaulating 
this code nothing has been built yet. This means that we have to give scons 
somthing to run after this script exits
so that scons can track the dependancies and build everything in order.

@par Dot-Testing functionality

Dot-testing in SLIMpy is very simple. SLIMpy can create random noise realizations from a linear operator's domain and range 
which are
@ref slimpy_base.Core.User.Structures.VectorSpace.VectorSpace "VectorSpace"
objects. From these the 
@ref slimpy_base.utils.DotTest.DotTest "DotTest"
can compute @f$ \langle Ay,x \rangle \approx \langle A^{H}x, y \rangle @f$. 

@code
DotTest(A,5,5)
@endcode

In this case the first parameter @b A is the cosine transform and the second two parameters are 
the precision of a pass or fail and the number of noise realizations to test.

*/"""

import sys

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

from SLIMpy.linear_operators import Cosine
from SLIMpy import DotTest

#===============================================================================
# Madagascar 
#===============================================================================

from rsfproj import *

data = '../data.rsf'
sig = '../sig.rsf'
noise = '../swellnoise.rsf'
#SConscript( '../SConstruct' )

#===============================================================================
# SLIMpy Bulider
#===============================================================================

@slim_builder_simple
def SwellSeparation( vectors, thr=0.001 ):
    """
    @param vectors  a list of vectors created from SCons sources
    @param thr      the value to threshold with 
    """
    
    data = vectors[0]
    A = Cosine( data.space )
    
    tmp1 = A * data
    tmp2 = tmp1.thr( thr )
    res  = A.H * tmp2 

    return res

e_noise = SwellSeparation( 'enoise', data , thr=5 )





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

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

@slim_builder_simple
def CosineDotTest( vectors):
    
    A = Cosine( vectors[0].space )
    DotTest(A,5,5)


test = CosineDotTest( 'test', data , 
                      debug=[], logfile='dottest' )
Alias( 'dottest', test)

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