cdec cleanup, remove bayesian stuff, parsing stuff

1 files changed, 0 insertions, 55 deletions

diff --git a/gi/posterior-regularisation/simplex_pg.py b/gi/posterior-regularisation/simplex_pg.py
deleted file mode 100644
index 5da796d3..00000000
--- a/gi/posterior-regularisation/simplex_pg.py
+++ /dev/null
@@ -1,55 +0,0 @@
-#
-# Following Leunberger and Ye, Linear and Nonlinear Progamming, 3rd ed. p367
-# "The gradient projection method"
-# applied to an equality constraint for a simplex.
-#
-#   min f(x)
-#   s.t. x >= 0, sum_i x = d
-#
-# FIXME: enforce the positivity constraint - a limit on the line search?
-#
-
-from numpy import *
-from scipy import *
-from linesearch import line_search
-# local copy of scipy's Amijo line_search - wasn't enforcing alpha max correctly
-import sys
-
-dims = 4
-
-def f(x):
-    fv = x[0]*x[0] + x[1]*x[1] + x[2]*x[2] + x[3]*x[3] - 2*x[0] - 3*x[3]
-    # print 'evaluating f at', x, 'value', fv
-    return fv
-
-def g(x):
-    return array([2*x[0] - 2, 2*x[1], 2*x[2], 2*x[3]-3])
-
-def pg(x):
-    gv = g(x)
-    return gv - sum(gv) / dims
-
-x = ones(dims) / dims
-old_fval = None
-
-while True:
-    fv = f(x)
-    gv = g(x)
-    dv = pg(x)
-
-    print 'x', x, 'f', fv, 'g', gv, 'd', dv
-
-    if old_fval == None:
-        old_fval = fv + 0.1
-
-    # solve for maximum step size i.e. when positivity constraints kick in
-    # x - alpha d = 0   => alpha = x/d
-    amax = max(x/dv)
-    if amax < 1e-8: break
-
-    stuff = line_search(f, pg, x, -dv, dv, fv, old_fval, amax=amax)
-    alpha = stuff[0] # Nb. can avoid next evaluation of f,g,d using 'stuff'
-    if alpha < 1e-8: break
-    x -= alpha * dv
-
-    old_fval = fv