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Remove arg normalize from Lasso() (no longer exists) #183

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Mar 3, 2024
Merged

Remove arg normalize from Lasso() (no longer exists) #183

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4 changes: 2 additions & 2 deletions ldsc_polyfun/jackknife.py
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Original file line number Diff line number Diff line change
Expand Up @@ -264,7 +264,7 @@ def __init__(self, x, y, is_large_chi2=False, n_blocks=None, nn=False, separator
self.est = np.atleast_2d(nnls(x, np.array(y).T[0])[0])
else:
xtx = x.T.dot(x)
lasso = Lasso(alpha=1e-100, fit_intercept=False, normalize=False, precompute=xtx, positive=True, max_iter=10000, random_state=0)
lasso = Lasso(alpha=1e-100, fit_intercept=False, precompute=xtx, positive=True, max_iter=10000, random_state=0)
self.est = lasso.fit(x,y[:,0]).coef_.reshape((1, x.shape[1]))
else:
self.est = np.atleast_2d(np.linalg.lstsq(x, np.array(y).T[0])[0])
Expand Down Expand Up @@ -292,7 +292,7 @@ def __init__(self, x, y, is_large_chi2=False, n_blocks=None, nn=False, separator
else:
x_block = x[s[i] : s[i+1]]
xtx_noblock = xtx - x_block.T.dot(x_block)
lasso_noblock = Lasso(alpha=1e-100, fit_intercept=False, normalize=False, precompute=xtx_noblock, positive=True, max_iter=10000, random_state=0)
lasso_noblock = Lasso(alpha=1e-100, fit_intercept=False, precompute=xtx_noblock, positive=True, max_iter=10000, random_state=0)
jk_est = lasso_noblock.fit(x_noblock, y_noblock[:,0]).coef_.reshape((1, x.shape[1]))
###z = nnls(x_noblock, y_noblock[:,0])[0]
###assert np.allclose(z, jk_est[0])
Expand Down
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