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authorSeth Troisi <sethtroisi@google.com>2019-10-02 22:07:49 -0700
committerSeth Troisi <sethtroisi@google.com>2019-10-02 22:07:49 -0700
commit5b4eee07263ea909d52488509bbaa95f3ee19972 (patch)
treeae04a6574c98716903c3f8c73bd0f4ace917f5de /numpy/lib/polynomial.py
parentc0992ed4856df9fe02c2b31744a8a7e9088aedbc (diff)
downloadnumpy-5b4eee07263ea909d52488509bbaa95f3ee19972.tar.gz
DOC: clarify residual in np.polyfit
Diffstat (limited to 'numpy/lib/polynomial.py')
-rw-r--r--numpy/lib/polynomial.py8
1 files changed, 4 insertions, 4 deletions
diff --git a/numpy/lib/polynomial.py b/numpy/lib/polynomial.py
index 2c72f623c..3d07a0de4 100644
--- a/numpy/lib/polynomial.py
+++ b/numpy/lib/polynomial.py
@@ -479,10 +479,10 @@ def polyfit(x, y, deg, rcond=None, full=False, w=None, cov=False):
coefficients for `k`-th data set are in ``p[:,k]``.
residuals, rank, singular_values, rcond
- Present only if `full` = True. Residuals of the least-squares fit,
- the effective rank of the scaled Vandermonde coefficient matrix,
- its singular values, and the specified value of `rcond`. For more
- details, see `linalg.lstsq`.
+ Present only if `full` = True. Residuals is sum of squared residuals
+ of the least-squares fit, the effective rank of the scaled Vandermonde
+ coefficient matrix, its singular values, and the specified value of
+ `rcond`. For more details, see `linalg.lstsq`.
V : ndarray, shape (M,M) or (M,M,K)
Present only if `full` = False and `cov`=True. The covariance