#46 Issue/46/sparse Using sparse properties of parameter matrices in FusedLassoADMM #47
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zalgo3
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kitoranaoki
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Feb 25, 2019
spmimage/linear_model/admm.py
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| def _dia_to_tridiagonal(X): | ||
| n_samples = X.shape[0] | ||
| index = 0 | ||
| for offset in X.offsets: |
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I think we can use enumerate so that we do not need to initialize and increment index.
| @@ -77,7 +99,8 @@ def admm_path(X, y, Xy=None, alphas=None, eps=1e-3, n_alphas=100, rho=1.0, max_i | |||
| return alphas, coefs, n_iters | |||
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| def _admm(X: np.ndarray, y: np.ndarray, D: np.ndarray, alpha: float, rho: float, tol: float, max_iter: int): | |||
| def _admm(X: np.ndarray, y: np.ndarray, D: np.ndarray, alpha: float, | |||
| rho: float, tol: float, max_iter: int, tridiagonal: bool): | |||
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We prefer indentation like this.
https://www.python.org/dev/peps/pep-0008/#indentation
spmimage/linear_model/admm.py
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| index = index + 1 | ||
| band = X.data[[one, zero, minusone], :] | ||
| return band | ||
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Can you remove trailing spaces?
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