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author | Edoardo Pasca <edo.paskino@gmail.com> | 2017-10-27 12:40:53 +0100 |
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committer | Edoardo Pasca <edo.paskino@gmail.com> | 2018-01-19 14:26:06 +0000 |
commit | 42ebac43aca279c5e6e9ba7fe8946e69ccc53c09 (patch) | |
tree | 07d8fc796cb6b6160feaa9684631c8f5e2121162 | |
parent | 34e00beb5c35068083fc4ecd5da5b93a504d62bf (diff) | |
download | regularization-42ebac43aca279c5e6e9ba7fe8946e69ccc53c09.tar.gz regularization-42ebac43aca279c5e6e9ba7fe8946e69ccc53c09.tar.bz2 regularization-42ebac43aca279c5e6e9ba7fe8946e69ccc53c09.tar.xz regularization-42ebac43aca279c5e6e9ba7fe8946e69ccc53c09.zip |
handles correctly the slicing
-rw-r--r-- | src/Python/ccpi/imaging/Regularizer.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/src/Python/ccpi/imaging/Regularizer.py b/src/Python/ccpi/imaging/Regularizer.py index fb9ae08..8ab6c6a 100644 --- a/src/Python/ccpi/imaging/Regularizer.py +++ b/src/Python/ccpi/imaging/Regularizer.py @@ -216,13 +216,13 @@ class Regularizer(): #assuming it's 3D # run independent calls on each slice out3d = input.copy() - for i in range(np.shape(input)[2]): - out = self.algorithm(input, regularization_parameter, + for i in range(np.shape(input)[0]): + out = self.algorithm(input[i], regularization_parameter, self.pars['first_order_term'] , self.pars['second_order_term'] , self.pars['number_of_iterations']) # copy the result in the 3D image - out3d.T[i] = out[0].copy() + out3d[i] = out[0].copy() # append the rest of the info that the algorithm returns output = [out3d] for i in range(1,len(out)): |