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-rwxr-xr-xWrappers/Python/ccpi/optimisation/ops.py10
1 files changed, 4 insertions, 6 deletions
diff --git a/Wrappers/Python/ccpi/optimisation/ops.py b/Wrappers/Python/ccpi/optimisation/ops.py
index 993f2de..26787f5 100755
--- a/Wrappers/Python/ccpi/optimisation/ops.py
+++ b/Wrappers/Python/ccpi/optimisation/ops.py
@@ -63,25 +63,23 @@ class FiniteDiff2D(Operator):
d1[:,:-1] = x.as_array()[:,1:] - x.as_array()[:,:-1]
d2 = numpy.zeros_like(x.as_array())
d2[:-1,:] = x.as_array()[1:,:] - x.as_array()[:-1,:]
- d = numpy.stack((d1,d2),2)
+ d = numpy.stack((d1,d2),0)
return type(x)(d,geometry=x.geometry)
def adjoint(self,x):
- '''Backward differences, Newumann BC.'''
- #Nrows, Ncols, Nchannels = x.as_array().shape
- print (x)
+ '''Backward differences, Neumann BC.'''
Nrows = x.get_dimension_size('horizontal_x')
Ncols = x.get_dimension_size('horizontal_x')
Nchannels = 1
if len(x.shape) == 4:
Nchannels = x.get_dimension_size('channel')
zer = numpy.zeros((Nrows,1))
- xxx = x.as_array()[:,:-1,0]
+ xxx = x.as_array()[0,:,:-1]
h = numpy.concatenate((zer,xxx), 1) - numpy.concatenate((xxx,zer), 1)
zer = numpy.zeros((1,Ncols))
- xxx = x.as_array()[:-1,:,1]
+ xxx = x.as_array()[1,:-1,:]
v = numpy.concatenate((zer,xxx), 0) - numpy.concatenate((xxx,zer), 0)
return type(x)(h + v,geometry=x.geometry)