def dorun(method, platonics=None, nsnrs=20, noise_samples=30, sweeps=30, burn=15):
    """
    platonics = create_many_platonics(N=50)
    dorun(platonics)
    """
    sigmas = np.logspace(np.log10(1.0/2048), 0, nsnrs)
    crbs, vals, errs, poss = [], [], [], []

    for sigma in sigmas:
        print "#### sigma:", sigma

        for i, (image, pos) in enumerate(platonics):
            print 'image', i, '|', 
            s,im = create_comparison_state(image, pos, method=method)

            # typical image
            set_image(s, im, sigma)
            crbs.append(crb(s))

            val, err = sample(s, im, sigma, N=noise_samples, sweeps=sweeps, burn=burn)
            poss.append(pos)
            vals.append(val)
            errs.append(err)


    shape0 = (nsnrs, len(platonics), -1)
    shape1 = (nsnrs, len(platonics), noise_samples, -1)

    crbs = np.array(crbs).reshape(shape0)
    vals = np.array(vals).reshape(shape1)
    errs = np.array(errs).reshape(shape1)
    poss = np.array(poss).reshape(shape0)

    return  [crbs, vals, errs, poss, sigmas]
def dorun(method, platonics=None, nsnrs=20, noise_samples=30, sweeps=30, burn=15):
    """
    platonics = create_many_platonics(N=50)
    dorun(platonics)
    """
    sigmas = np.logspace(np.log10(1.0/2048), 0, nsnrs)
    crbs, vals, errs, poss = [], [], [], []

    for sigma in sigmas:
        print "#### sigma:", sigma

        for i, (image, pos) in enumerate(platonics):
            print 'image', i, '|', 
            s,im = create_comparison_state(image, pos, method=method)

            # typical image
            set_image(s, im, sigma)
            crbs.append(crb(s))

            val, err = sample(s, im, sigma, N=noise_samples, sweeps=sweeps, burn=burn)
            poss.append(pos)
            vals.append(val)
            errs.append(err)


    shape0 = (nsnrs, len(platonics), -1)
    shape1 = (nsnrs, len(platonics), noise_samples, -1)

    crbs = np.array(crbs).reshape(shape0)
    vals = np.array(vals).reshape(shape1)
    errs = np.array(errs).reshape(shape1)
    poss = np.array(poss).reshape(shape0)

    return  [crbs, vals, errs, poss, sigmas]
def dorun ( method , platonics = None , nsnrs = 20 , noise_samples = 30 , sweeps = 30 , burn = 15 ) : sigmas = np . logspace ( np . log10 ( 1.0 / 2048 ) , 0 , nsnrs ) crbs , vals , errs , poss = [ ] , [ ] , [ ] , [ ] for sigma in sigmas : print "#### sigma:" , sigma for i , ( image , pos ) in enumerate ( platonics ) : print 'image' , i , '|' , s , im = create_comparison_state ( image , pos , method = method ) # typical image set_image ( s , im , sigma ) crbs . append ( crb ( s ) ) val , err = sample ( s , im , sigma , N = noise_samples , sweeps = sweeps , burn = burn ) poss . append ( pos ) vals . append ( val ) errs . append ( err ) shape0 = ( nsnrs , len ( platonics ) , - 1 ) shape1 = ( nsnrs , len ( platonics ) , noise_samples , - 1 ) crbs = np . array ( crbs ) . reshape ( shape0 ) vals = np . array ( vals ) . reshape ( shape1 ) errs = np . array ( errs ) . reshape ( shape1 ) poss = np . array ( poss ) . reshape ( shape0 ) return [ crbs , vals , errs , poss , sigmas ]
platonics = create_many_platonics(N=50)
    dorun(platonics)
platonics = create_many_platonics ( N = 50 ) dorun ( platonics )