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authorChristian Brueffer <christian@brueffer.de>2012-11-09 15:00:06 +0800
committerChristian Brueffer <christian@brueffer.de>2012-11-09 15:00:06 +0800
commit6c948c5bca99c4a030e67fcc5bb2c0b9d8c72658 (patch)
tree213c9863a19957b1df8c309b592f55dac3b6e467
parent82c0bb8a964c10b4c37665c5f2f6885fa46cd6a1 (diff)
downloadnumpy-6c948c5bca99c4a030e67fcc5bb2c0b9d8c72658.tar.gz
Fix typos.
-rw-r--r--INSTALL.txt14
1 files changed, 7 insertions, 7 deletions
diff --git a/INSTALL.txt b/INSTALL.txt
index d75d4d9d0..d593dc8ee 100644
--- a/INSTALL.txt
+++ b/INSTALL.txt
@@ -60,7 +60,7 @@ How to check the ABI of blas/lapack/atlas
One relatively simple and reliable way to check for the compiler used to build
a library is to use ldd on the library. If libg2c.so is a dependency, this
-means that g77 has been used. If libgfortran.so is a a dependency, gfortran has
+means that g77 has been used. If libgfortran.so is a dependency, gfortran has
been used. If both are dependencies, this means both have been used, which is
almost always a very bad idea.
@@ -74,8 +74,8 @@ You can install the necessary packages for optimized ATLAS with this command:
sudo apt-get install libatlas-base-dev
-If you have a recent CPU with SIMD suppport (SSE, SSE2, etc...), you should
-also install the corresponding package for optimal performances. For example,
+If you have a recent CPU with SIMD support (SSE, SSE2, etc...), you should
+also install the corresponding package for optimal performance. For example,
for SSE2:
sudo apt-get install libatlas3gf-sse2
@@ -91,8 +91,8 @@ You can install the necessary packages for optimized ATLAS with this command:
sudo apt-get install atlas3-base-dev
-If you have a recent CPU with SIMD suppport (SSE, SSE2, etc...), you should
-also install the corresponding package for optimal performances. For example,
+If you have a recent CPU with SIMD support (SSE, SSE2, etc...), you should
+also install the corresponding package for optimal performance. For example,
for SSE2:
sudo apt-get install atlas3-sse2
@@ -111,7 +111,7 @@ http://mingw-w64.sourceforge.net/
To use the free compilers (mingw-w64), you need to build your own toolchain, as
the mingw project only distribute cross-compilers (cross-compilation is not
supported by numpy). Since this toolchain is still being worked on, serious
-compilers bugs can be expected. binutil 2.19 + gcc 4.3.3 + mingw-w64 runtime
+compiler bugs can be expected. binutil 2.19 + gcc 4.3.3 + mingw-w64 runtime
gives you a working C compiler (but the C++ is broken). gcc 4.4 will hopefully
be able to run natively.
@@ -127,7 +127,7 @@ fragile, and often segfault on invalid C code). The main drawback is that no
fortran compiler + MS compiler combination has been tested - mingw-w64 gfortran
+ MS compiler does not work at all (it is unclear whether it ever will).
-For python 2.5, you need VS 2005 (MS compiler version 14) targetting
+For python 2.5, you need VS 2005 (MS compiler version 14) targeting
AMD64 bits, or the Platform SDK v6.0 or below (which gives command
line versions of 64 bits target compilers). The PSDK is free.