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| author | Ralf Gommers <ralf.gommers@gmail.com> | 2022-05-25 20:55:53 +0200 |
|---|---|---|
| committer | GitHub <noreply@github.com> | 2022-05-25 20:55:53 +0200 |
| commit | d4732a26d2d044eee59bf6f889666a26ead5db92 (patch) | |
| tree | 7b92f32a192f5bea36aa16cdbc99f5d8654521dc /numpy/linalg | |
| parent | d985fd4af5d267be54ff6d544084d5e93c825b9f (diff) | |
| parent | 7332a698c8194c6e680510da086678fe07d9cf9d (diff) | |
| download | numpy-d4732a26d2d044eee59bf6f889666a26ead5db92.tar.gz | |
Merge pull request #21504 from Yulv-git/typos1
MAINT: Fix some typos.
Diffstat (limited to 'numpy/linalg')
| -rw-r--r-- | numpy/linalg/lapack_lite/f2c_c_lapack.c | 8 | ||||
| -rw-r--r-- | numpy/linalg/lapack_lite/f2c_d_lapack.c | 10 | ||||
| -rw-r--r-- | numpy/linalg/lapack_lite/f2c_s_lapack.c | 10 | ||||
| -rw-r--r-- | numpy/linalg/lapack_lite/f2c_z_lapack.c | 8 |
4 files changed, 18 insertions, 18 deletions
diff --git a/numpy/linalg/lapack_lite/f2c_c_lapack.c b/numpy/linalg/lapack_lite/f2c_c_lapack.c index c36c0e368..a7d1f836b 100644 --- a/numpy/linalg/lapack_lite/f2c_c_lapack.c +++ b/numpy/linalg/lapack_lite/f2c_c_lapack.c @@ -14509,7 +14509,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -16624,7 +16624,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -17341,7 +17341,7 @@ L80: /* ==== Accumulate U. (If necessary, update Z later - . with with an efficient matrix-matrix + . with an efficient matrix-matrix . multiply.) ==== */ @@ -25242,7 +25242,7 @@ L160: =============== The algorithm used in this program is basically backward (forward) - substitution, with scaling to make the the code robust against + substitution, with scaling to make the code robust against possible overflow. Each eigenvector is normalized so that the element of largest diff --git a/numpy/linalg/lapack_lite/f2c_d_lapack.c b/numpy/linalg/lapack_lite/f2c_d_lapack.c index 233db74b9..10e22ff1b 100644 --- a/numpy/linalg/lapack_lite/f2c_d_lapack.c +++ b/numpy/linalg/lapack_lite/f2c_d_lapack.c @@ -16423,7 +16423,7 @@ L90: N1 (input) INTEGER N2 (input) INTEGER - These arguements contain the respective lengths of the two + These arguments contain the respective lengths of the two sorted lists to be merged. A (input) DOUBLE PRECISION array, dimension (N1+N2) @@ -18032,7 +18032,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -20271,7 +20271,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -20870,7 +20870,7 @@ L90: /* ==== Accumulate U. (If necessary, update Z later - . with with an efficient matrix-matrix + . with an efficient matrix-matrix . multiply.) ==== */ @@ -40074,7 +40074,7 @@ L180: =============== The algorithm used in this program is basically backward (forward) - substitution, with scaling to make the the code robust against + substitution, with scaling to make the code robust against possible overflow. Each eigenvector is normalized so that the element of largest diff --git a/numpy/linalg/lapack_lite/f2c_s_lapack.c b/numpy/linalg/lapack_lite/f2c_s_lapack.c index 2a32315c7..26e7c18ac 100644 --- a/numpy/linalg/lapack_lite/f2c_s_lapack.c +++ b/numpy/linalg/lapack_lite/f2c_s_lapack.c @@ -16365,7 +16365,7 @@ L90: N1 (input) INTEGER N2 (input) INTEGER - These arguements contain the respective lengths of the two + These arguments contain the respective lengths of the two sorted lists to be merged. A (input) REAL array, dimension (N1+N2) @@ -17968,7 +17968,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -20194,7 +20194,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -20794,7 +20794,7 @@ L90: /* ==== Accumulate U. (If necessary, update Z later - . with with an efficient matrix-matrix + . with an efficient matrix-matrix . multiply.) ==== */ @@ -39901,7 +39901,7 @@ L180: =============== The algorithm used in this program is basically backward (forward) - substitution, with scaling to make the the code robust against + substitution, with scaling to make the code robust against possible overflow. Each eigenvector is normalized so that the element of largest diff --git a/numpy/linalg/lapack_lite/f2c_z_lapack.c b/numpy/linalg/lapack_lite/f2c_z_lapack.c index 8234eca41..64e41d082 100644 --- a/numpy/linalg/lapack_lite/f2c_z_lapack.c +++ b/numpy/linalg/lapack_lite/f2c_z_lapack.c @@ -14582,7 +14582,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -16718,7 +16718,7 @@ L60: } /* - ==== Use up to NS of the the smallest magnatiude + ==== Use up to NS of the smallest magnatiude . shifts. If there aren't NS shifts available, . then use them all, possibly dropping one to . make the number of shifts even. ==== @@ -17439,7 +17439,7 @@ L80: /* ==== Accumulate U. (If necessary, update Z later - . with with an efficient matrix-matrix + . with an efficient matrix-matrix . multiply.) ==== */ @@ -25358,7 +25358,7 @@ L160: =============== The algorithm used in this program is basically backward (forward) - substitution, with scaling to make the the code robust against + substitution, with scaling to make the code robust against possible overflow. Each eigenvector is normalized so that the element of largest |
