Cache computed lipschitz constant, seed random number generator to ensure that different runs give exactly the same resultfast_tnv

1 files changed, 27 insertions, 4 deletions

diff --git a/Wrappers/Python/ccpi/optimisation/operators/Operator.py b/Wrappers/Python/ccpi/optimisation/operators/Operator.py
index d49bc1a..4e2d04d 100644
--- a/Wrappers/Python/ccpi/optimisation/operators/Operator.py
+++ b/Wrappers/Python/ccpi/optimisation/operators/Operator.py
@@ -21,6 +21,7 @@ from __future__ import print_function
 from numbers import Number

 import numpy

 import functools

+from hashlib import md5
 

 class Operator(object):

     '''Operator that maps from a space X -> Y'''

@@ -126,11 +127,13 @@ class LinearOperator(Operator):
         :returns: tuple with: L, list of L at each iteration, the data the iteration worked on.

         '''

         

+
         # Initialise random

-        if x_init is None:

-            x0 = operator.domain_geometry().allocate('random')

-        else:

-            x0 = x_init.copy()

+        x0 = operator.domain_geometry().allocate('random', seed=1)

+        #if x_init is None:

+        #    x0 = operator.domain_geometry().allocate('random', seed=1)

+        #else:

+        #    x0 = x_init.copy()

             

         x1 = operator.domain_geometry().allocate()

         y_tmp = operator.range_geometry().allocate()

@@ -158,9 +161,29 @@ class LinearOperator(Operator):
         :parameter force: forces the recalculation of the norm

         :type force: boolean, default :code:`False`

         '''

+
+        fname = md5("{} {}".format(self.domain_geometry(), self.range_geometry()).encode('utf-8')).hexdigest()
+        fname = "/tmp/ccpi_cache_opnorm_{}".format(fname)
+        try:
+            f = open(fname)
+            s1 = float(f.read())
+            print ("Returning norm {} from cache".format(s1))
+            return s1
+        except:
+            pass
+
         x0 = kwargs.get('x_init', None)

         iterations = kwargs.get('iterations', 25)

         s1, sall, svec = LinearOperator.PowerMethod(self, iterations, x_init=x0)

+
+        try:
+            print(fname)
+            f = open(fname, "w")
+            f.write("{}".format(s1))
+        except:
+            pass
+
+
         return s1

 

     @staticmethod