Enhance 'lwf', 'mcd', 'oas' and 'sch' covariance estimator to process complex inputs #274
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agramfort
reviewed
Dec 14, 2023
qbarthelemy
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Dec 14, 2023
pyriemann/utils/covariance.py
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| if not is_real_type(X): | ||
| raise ValueError("Input must be real-valued.") | ||
| iscomplex = np.iscomplexobj(X) | ||
| if iscomplex: | ||
| X = np.concatenate((X.real, X.imag), axis=0) | ||
|
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@sylvchev , do you think that sch estimator could be easily generalized to complex-valued input?
Co-authored-by: Quentin Barthélemy <q.barthelemy@gmail.com>
add decorator, revert changes to m estimators revert list comprehensions
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Thank you for the suggestions, @qbarthelemy and @agramfort. |
qbarthelemy
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Dec 15, 2023
agramfort
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qbarthelemy
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qbarthelemy
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As noted in #204, this implements general complex covariance estimation described here.
I put the transformation in the individual estimators like _oas, _lwf etc., that made most sense to me.
What do you thin, @qbarthelemy?