From 9d03383a707a7be94b42ac339d52b991cf5d5bc1 Mon Sep 17 00:00:00 2001
From: Edoardo Pasca <edo.paskino@gmail.com>
Date: Tue, 16 Apr 2019 14:50:51 +0100
Subject: updated tests
---
Wrappers/Python/test/test_DataContainer.py | 64 +++++++++++++++++++++++-------
Wrappers/Python/test/test_Operator.py | 10 ++++-
2 files changed, 59 insertions(+), 15 deletions(-)
diff --git a/Wrappers/Python/test/test_DataContainer.py b/Wrappers/Python/test/test_DataContainer.py
index 40cd244..8e8ab87 100755
--- a/Wrappers/Python/test/test_DataContainer.py
+++ b/Wrappers/Python/test/test_DataContainer.py
@@ -174,7 +174,7 @@ class TestDataContainer(unittest.TestCase):
def binary_add(self):
print("Test binary add")
X, Y, Z = 512, 512, 512
- X, Y, Z = 1024, 512, 512
+ #X, Y, Z = 1024, 512, 512
steps = [timer()]
a = numpy.ones((X, Y, Z), dtype='float32')
steps.append(timer())
@@ -183,9 +183,10 @@ class TestDataContainer(unittest.TestCase):
#print("a refcount " , sys.getrefcount(a))
ds = DataContainer(a, False, ['X', 'Y', 'Z'])
ds1 = ds.copy()
+ out = ds.copy()
steps.append(timer())
- ds.add(ds1, out=ds)
+ ds.add(ds1, out=out)
steps.append(timer())
t1 = dt(steps)
print("ds.add(ds1, out=ds)", dt(steps))
@@ -196,20 +197,25 @@ class TestDataContainer(unittest.TestCase):
print("ds2 = ds.add(ds1)", dt(steps))
self.assertLess(t1, t2)
- self.assertEqual(ds.as_array()[0][0][0], 2.)
-
+ self.assertEqual(out.as_array()[0][0][0], 2.)
+ self.assertNumpyArrayEqual(out.as_array(), ds2.as_array())
+
ds0 = ds
- ds0.add(2, out=ds0)
steps.append(timer())
- print("ds0.add(2,out=ds0)", dt(steps), 3, ds0.as_array()[0][0][0])
- self.assertEqual(4., ds0.as_array()[0][0][0])
+ ds0.add(2, out=out)
+ steps.append(timer())
+ print("ds0.add(2,out=out)", dt(steps), 3, ds0.as_array()[0][0][0])
+ self.assertEqual(3., out.as_array()[0][0][0])
dt1 = dt(steps)
+ steps.append(timer())
ds3 = ds0.add(2)
steps.append(timer())
print("ds3 = ds0.add(2)", dt(steps), 5, ds3.as_array()[0][0][0])
dt2 = dt(steps)
self.assertLess(dt1, dt2)
+
+ self.assertNumpyArrayEqual(out.as_array(), ds3.as_array())
def binary_subtract(self):
print("Test binary subtract")
@@ -222,16 +228,17 @@ class TestDataContainer(unittest.TestCase):
#print("a refcount " , sys.getrefcount(a))
ds = DataContainer(a, False, ['X', 'Y', 'Z'])
ds1 = ds.copy()
+ out = ds.copy()
steps.append(timer())
- ds.subtract(ds1, out=ds)
+ ds.subtract(ds1, out=out)
steps.append(timer())
t1 = dt(steps)
print("ds.subtract(ds1, out=ds)", dt(steps))
- self.assertEqual(0., ds.as_array()[0][0][0])
+ self.assertEqual(0., out.as_array()[0][0][0])
steps.append(timer())
- ds2 = ds.subtract(ds1)
+ ds2 = out.subtract(ds1)
self.assertEqual(-1., ds2.as_array()[0][0][0])
steps.append(timer())
@@ -247,8 +254,8 @@ class TestDataContainer(unittest.TestCase):
#ds0.__isub__( 2 )
steps.append(timer())
print("ds0.subtract(2,out=ds0)", dt(
- steps), -2., ds0.as_array()[0][0][0])
- self.assertEqual(-2., ds0.as_array()[0][0][0])
+ steps), -1., ds0.as_array()[0][0][0])
+ self.assertEqual(-1., ds0.as_array()[0][0][0])
dt1 = dt(steps)
ds3 = ds0.subtract(2)
@@ -256,8 +263,8 @@ class TestDataContainer(unittest.TestCase):
print("ds3 = ds0.subtract(2)", dt(steps), 0., ds3.as_array()[0][0][0])
dt2 = dt(steps)
self.assertLess(dt1, dt2)
- self.assertEqual(-2., ds0.as_array()[0][0][0])
- self.assertEqual(-4., ds3.as_array()[0][0][0])
+ self.assertEqual(-1., ds0.as_array()[0][0][0])
+ self.assertEqual(-3., ds3.as_array()[0][0][0])
def binary_multiply(self):
print("Test binary multiply")
@@ -300,6 +307,9 @@ class TestDataContainer(unittest.TestCase):
self.assertLess(dt1, dt2)
self.assertEqual(4., ds3.as_array()[0][0][0])
self.assertEqual(2., ds.as_array()[0][0][0])
+
+ ds.multiply(2.5, out=ds0)
+ self.assertEqual(2.5*2., ds0.as_array()[0][0][0])
def binary_divide(self):
print("Test binary divide")
@@ -575,6 +585,32 @@ class TestDataContainer(unittest.TestCase):
norm = dc.norm()
self.assertEqual(sqnorm, 8.0)
numpy.testing.assert_almost_equal(norm, numpy.sqrt(8.0), decimal=7)
+
+ def test_multiply_out(self):
+ print ("test multiply_out")
+ import functools
+ ig = ImageGeometry(10,11,12)
+ u = ig.allocate()
+ a = numpy.ones(u.shape)
+
+ u.fill(a)
+
+ numpy.testing.assert_array_equal(a, u.as_array())
+
+ #u = ig.allocate(ImageGeometry.RANDOM_INT, seed=1)
+ l = functools.reduce(lambda x,y: x*y, (10,11,12), 1)
+
+ a = numpy.zeros((l, ), dtype=numpy.float32)
+ for i in range(l):
+ a[i] = numpy.sin(2 * i* 3.1415/l)
+ b = numpy.reshape(a, u.shape)
+ u.fill(b)
+ numpy.testing.assert_array_equal(b, u.as_array())
+
+ u.multiply(2, out=u)
+ c = b * 2
+ numpy.testing.assert_array_equal(u.as_array(), c)
+
diff --git a/Wrappers/Python/test/test_Operator.py b/Wrappers/Python/test/test_Operator.py
index 0d6cb8b..5c97545 100644
--- a/Wrappers/Python/test/test_Operator.py
+++ b/Wrappers/Python/test/test_Operator.py
@@ -68,6 +68,7 @@ class TestOperator(CCPiTestClass):
numpy.testing.assert_array_equal(y.as_array(), img.as_array())
def test_FiniteDifference(self):
+ print ("test FiniteDifference")
##
N, M = 2, 3
@@ -94,10 +95,17 @@ class TestOperator(CCPiTestClass):
G = Gradient(ig)
u = G.range_geometry().allocate(ImageGeometry.RANDOM_INT)
- res = G.domain_geometry().allocate(ImageGeometry.RANDOM_INT)
+ res = G.domain_geometry().allocate()
G.adjoint(u, out=res)
w = G.adjoint(u)
self.assertNumpyArrayEqual(res.as_array(), w.as_array())
+
+ u = G.domain_geometry().allocate(ImageGeometry.RANDOM_INT)
+ res = G.range_geometry().allocate()
+ G.direct(u, out=res)
+ w = G.direct(u)
+ self.assertBlockDataContainerEqual(res, w)
+
def test_PowerMethod(self):
N, M = 200, 300
--
cgit v1.2.3
From 9a8c03aff07d63f2c635c75fade0da835eb1fb98 Mon Sep 17 00:00:00 2001
From: Edoardo Pasca <edo.paskino@gmail.com>
Date: Tue, 16 Apr 2019 15:28:55 +0100
Subject: fix new implementation of PowerMethod
fixes different values found in #224
---
.../ccpi/optimisation/operators/LinearOperator.py | 39 ++++++----------------
1 file changed, 11 insertions(+), 28 deletions(-)
diff --git a/Wrappers/Python/ccpi/optimisation/operators/LinearOperator.py b/Wrappers/Python/ccpi/optimisation/operators/LinearOperator.py
index bc18f9b..f304cc6 100755
--- a/Wrappers/Python/ccpi/optimisation/operators/LinearOperator.py
+++ b/Wrappers/Python/ccpi/optimisation/operators/LinearOperator.py
@@ -24,59 +24,42 @@ class LinearOperator(Operator):
raise NotImplementedError
@staticmethod
- def PowerMethod(operator, iterations, x0=None):
+ def PowerMethod(operator, iterations, x_init=None):
'''Power method to calculate iteratively the Lipschitz constant'''
- # Initialise random
- if x0 is None:
- #x0 = op.create_image_data()
+ # Initialise random
+ if x_init is None:
x0 = operator.domain_geometry().allocate(ImageGeometry.RANDOM_INT)
-
+ else:
+ x0 = x_init.copy()
+
x1 = operator.domain_geometry().allocate()
y_tmp = operator.range_geometry().allocate()
s = numpy.zeros(iterations)
# Loop
for it in numpy.arange(iterations):
- #x1 = operator.adjoint(operator.direct(x0))
operator.direct(x0,out=y_tmp)
operator.adjoint(y_tmp,out=x1)
x1norm = x1.norm()
- #s[it] = (x1*x0).sum() / (x0.squared_norm())
s[it] = x1.dot(x0) / x0.squared_norm()
- #x0 = (1.0/x1norm)*x1
- #x1 *= (1.0 / x1norm)
- #x0.fill(x1)
x1.multiply((1.0/x1norm), out=x0)
return numpy.sqrt(s[-1]), numpy.sqrt(s), x0
@staticmethod
- def PowerMethodNonsquare(op,numiters , x0=None):
- # Initialise random
- # Jakob's
- # inputsize , outputsize = op.size()
- #x0 = ImageContainer(numpy.random.randn(*inputsize)
- # Edo's
- #vg = ImageGeometry(voxel_num_x=inputsize[0],
- # voxel_num_y=inputsize[1],
- # voxel_num_z=inputsize[2])
- #
- #x0 = ImageData(geometry = vg, dimension_labels=['vertical','horizontal_y','horizontal_x'])
- #print (x0)
- #x0.fill(numpy.random.randn(*x0.shape))
+ def PowerMethodNonsquare(op,numiters , x_init=None):
+ '''Power method to calculate iteratively the Lipschitz constant'''
- if x0 is None:
- #x0 = op.create_image_data()
+ if x_init is None:
x0 = op.allocate_direct()
x0.fill(numpy.random.randn(*x0.shape))
+ else:
+ x0 = x_init.copy()
s = numpy.zeros(numiters)
# Loop
for it in numpy.arange(numiters):
x1 = op.adjoint(op.direct(x0))
- #x1norm = numpy.sqrt((x1*x1).sum())
x1norm = x1.norm()
- #print ("x0 **********" ,x0)
- #print ("x1 **********" ,x1)
s[it] = (x1*x0).sum() / (x0.squared_norm())
x0 = (1.0/x1norm)*x1
return numpy.sqrt(s[-1]), numpy.sqrt(s), x0
--
cgit v1.2.3