System setup
modopt version: v1.5.1
Describe the bug
Using Ridge in a reconstruction (with Condat in my case) raises a ValueError: dimension mismatch. Other similar proximity operators (SparseThreshold or ElasticNet) don't have this issue.
Ridge applies the _linear operator to the input_data before applying the thresholding operations, but when running a reconstruction, this input_data is already in the image space of this linear operator, so only the thresholding step should be done. This is what happens in SparseThreshold and ElasticNet.
Screenshots
Error when using Condat with Ridge:
Module and lines involved
Replacing line 729 of modopt.opt.proximity:
return self._linear.op(input_data) / (1 + threshold)
by:
return input_data / (1 + threshold).
worked and gave results that looked like what we would expect.
Changing the name of the parameter to 'linear_coeffs' or something similar would maybe make it less confusing.
Are you planning to submit a Pull Request?
System setup
modopt version: v1.5.1
Describe the bug
Using Ridge in a reconstruction (with Condat in my case) raises a ValueError: dimension mismatch. Other similar proximity operators (SparseThreshold or ElasticNet) don't have this issue.
Ridge applies the _linear operator to the input_data before applying the thresholding operations, but when running a reconstruction, this input_data is already in the image space of this linear operator, so only the thresholding step should be done. This is what happens in SparseThreshold and ElasticNet.
Screenshots
Error when using Condat with Ridge:
Module and lines involved
Replacing line 729 of modopt.opt.proximity:
return self._linear.op(input_data) / (1 + threshold)by:
return input_data / (1 + threshold).worked and gave results that looked like what we would expect.
Changing the name of the parameter to 'linear_coeffs' or something similar would maybe make it less confusing.
Are you planning to submit a Pull Request?