summaryrefslogtreecommitdiff
path: root/numpy/linalg
diff options
context:
space:
mode:
authorRalf Gommers <ralf.gommers@gmail.com>2022-05-25 20:55:53 +0200
committerGitHub <noreply@github.com>2022-05-25 20:55:53 +0200
commitd4732a26d2d044eee59bf6f889666a26ead5db92 (patch)
tree7b92f32a192f5bea36aa16cdbc99f5d8654521dc /numpy/linalg
parentd985fd4af5d267be54ff6d544084d5e93c825b9f (diff)
parent7332a698c8194c6e680510da086678fe07d9cf9d (diff)
downloadnumpy-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.c8
-rw-r--r--numpy/linalg/lapack_lite/f2c_d_lapack.c10
-rw-r--r--numpy/linalg/lapack_lite/f2c_s_lapack.c10
-rw-r--r--numpy/linalg/lapack_lite/f2c_z_lapack.c8
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