DOC: change Numpy to NumPy in remaining files

the files in doc/ and numpy/ were covered in previous commits
numpy · jaimefrio · Sep 7, 2016 · Sep 5, 2016 · Sep 6, 2016 · Sep 6, 2016
commit 3f6672a30cd06d273e0b2160084a9abadcf9c315
diff --git a/INSTALL.rst.txt b/INSTALL.rst.txt
@@ -1,8 +1,8 @@
 Building and installing NumPy
 +++++++++++++++++++++++++++++
 
-**IMPORTANT**: the below notes are about building Numpy, which for most users
-is *not* the recommended way to install Numpy.  Instead, use either a complete
+**IMPORTANT**: the below notes are about building NumPy, which for most users
+is *not* the recommended way to install NumPy.  Instead, use either a complete
 scientific Python distribution (recommended) or a binary installer - see
 http://scipy.org/install.html.
 
@@ -39,13 +39,13 @@ nose__ http://somethingaboutorange.com/mrl/projects/nose/
 
 .. note:: 
 
-   If you want to build Numpy in order to work on Numpy itself, use
+   If you want to build NumPy in order to work on NumPy itself, use
    ``runtests.py``.  For more details, see
    http://docs.scipy.org/doc/numpy-dev/dev/development_environment.html
 
 .. note::
 
-   More extensive information on building Numpy (and Scipy) is maintained at
+   More extensive information on building NumPy (and Scipy) is maintained at
    http://scipy.org/scipylib/building/index.html
 
 
@@ -68,8 +68,8 @@ NPY_NUM_BUILD_JOBS.
 Choosing compilers
 ==================
 
-Numpy needs a C compiler, and for development versions also Cython.  A Fortran
-compiler isn't needed to build Numpy itself; the ``numpy.f2py`` tests will be
+NumPy needs a C compiler, and for development versions also Cython.  A Fortran
+compiler isn't needed to build NumPy itself; the ``numpy.f2py`` tests will be
 skipped when running the test suite if no Fortran compiler is available.  For
 building Scipy a Fortran compiler is needed though, so we include some details
 on Fortran compilers in the rest of this section.
@@ -91,7 +91,7 @@ good `application note <https://software.intel.com/en-us/articles/numpyscipy-wit
 on this.
 
 If you want to use a free compiler toolchain, the recommended compiler is MingwPy__.
-The older MinGW32 compiler set used to produce older .exe installers for Numpy
+The older MinGW32 compiler set used to produce older .exe installers for NumPy
 itself is still available at https://github.com/numpy/numpy-vendor, but not
 recommended for use anymore.
 
@@ -103,7 +103,7 @@ Building with optimized BLAS support
 
 Configuring which BLAS/LAPACK is used if you have multiple libraries installed,
 or you have only one installed but in a non-standard location, is done via a
-``site.cfg`` file.  See the ``site.cfg.example`` shipped with Numpy for more
+``site.cfg`` file.  See the ``site.cfg.example`` shipped with NumPy for more
 details.
 
 Windows
@@ -117,7 +117,7 @@ For an overview of the state of BLAS/LAPACK libraries on Windows, see
 OS X
 ----
 
-OS X ships the Accelerate framework, which Numpy can build against without any
+OS X ships the Accelerate framework, which NumPy can build against without any
 manual configuration.  Other BLAS/LAPACK implementations (OpenBLAS, Intel MKL,
 ATLAS) will also work.
 
@@ -149,7 +149,7 @@ Or by preloading a specific BLAS library with::
 Build issues
 ============
 
-If you run into build issues and need help, the Numpy
+If you run into build issues and need help, the NumPy
 `mailing list <http://scipy.org/scipylib/mailing-lists.html>`_ is the best
-place to ask.  If the issue is clearly a bug in Numpy, please file an issue (or
+place to ask.  If the issue is clearly a bug in NumPy, please file an issue (or
 even better, a pull request) at https://github.com/numpy/numpy.
diff --git a/benchmarks/README.rst b/benchmarks/README.rst
@@ -4,19 +4,19 @@
 NumPy benchmarks
 ================
 
-Benchmarking Numpy with Airspeed Velocity.
+Benchmarking NumPy with Airspeed Velocity.
 
 
 Usage
 -----
 
 Airspeed Velocity manages building and Python virtualenvs by itself,
 unless told otherwise. Some of the benchmarking features in
-``runtests.py`` also tell ASV to use the Numpy compiled by
+``runtests.py`` also tell ASV to use the NumPy compiled by
 ``runtests.py``. To run the benchmarks, you do not need to install a
-development version of Numpy to your current Python environment.
+development version of NumPy to your current Python environment.
 
-Run a benchmark against currently checked out Numpy version (don't
+Run a benchmark against currently checked out NumPy version (don't
 record the result)::
 
     python runtests.py --bench bench_core
@@ -46,9 +46,9 @@ See `ASV documentation`_ for basics on how to write benchmarks.
 
 Some things to consider:
 
-- The benchmark suite should be importable with any Numpy version.
+- The benchmark suite should be importable with any NumPy version.
 
-- The benchmark parameters etc. should not depend on which Numpy version
+- The benchmark parameters etc. should not depend on which NumPy version
   is installed.
 
 - Try to keep the runtime of the benchmark reasonable.

diff --git a/runtests.py b/runtests.py
@@ -28,7 +28,7 @@
 from __future__ import division, print_function
 
 #
-# This is a generic test runner script for projects using Numpy's test
+# This is a generic test runner script for projects using NumPy's test
 # framework. Change the following values to adapt to your project:
 #
 

diff --git a/setup.py b/setup.py
@@ -255,18 +255,18 @@ def parse_setuppy_commands():
 
               - `pip install .`       (from a git repo or downloaded source
                                        release)
-              - `pip install numpy`   (last Numpy release on PyPi)
+              - `pip install numpy`   (last NumPy release on PyPi)
 
             """))
         return True
 
     if '--help' in sys.argv[1:] or '-h' in sys.argv[1]:
         print(textwrap.dedent("""
-            Numpy-specific help
+            NumPy-specific help
             -------------------
 
-            To install Numpy from here with reliable uninstall, we recommend
-            that you use `pip install .`. To install the latest Numpy release
+            To install NumPy from here with reliable uninstall, we recommend
+            that you use `pip install .`. To install the latest NumPy release
             from PyPi, use `pip install numpy`.
 
             For help with build/installation issues, please ask on the

diff --git a/site.cfg.example b/site.cfg.example
@@ -90,7 +90,7 @@
 # Atlas
 # -----
 # Atlas is an open source optimized implementation of the BLAS and Lapack
-# routines. Numpy will try to build against Atlas by default when available in
+# routines. NumPy will try to build against Atlas by default when available in
 # the system library dirs. To build numpy against a custom installation of
 # Atlas you can add an explicit section such as the following. Here we assume
 # that Atlas was configured with ``prefix=/opt/atlas``.
@@ -135,14 +135,14 @@
 # ----
 # BLIS (https://github.com/flame/blis) also provides a BLAS interface.  It's a
 # relatively new library, its performance in some cases seems to match that of
-# MKL and OpenBLAS, but it hasn't been benchmarked with Numpy or Scipy yet.
+# MKL and OpenBLAS, but it hasn't been benchmarked with NumPy or Scipy yet.
 #
 # Notes on compiling BLIS itself:
-#   - the CBLAS interface (needed by Numpy) isn't built by default; define
+#   - the CBLAS interface (needed by NumPy) isn't built by default; define
 #     BLIS_ENABLE_CBLAS to build it.
 #   - ``./configure auto`` doesn't support 32-bit builds, see gh-7294 for
 #     details.
-# Notes on compiling Numpy against BLIS:
+# Notes on compiling NumPy against BLIS:
 #   - ``include_dirs`` below should be the directory where the BLIS cblas.h
 #     header is installed.
 #

diff --git a/tools/c_coverage/HOWTO_C_COVERAGE.txt b/tools/c_coverage/HOWTO_C_COVERAGE.txt
@@ -27,7 +27,7 @@ For most cases, it is good enough to do::
   > c_coverage_collect.sh python -c "import numpy; numpy.test()"
   > c_coverage_report.py callgrind.out.pid
 
-which will run all of the Numpy unit tests, create a directory called
+which will run all of the NumPy unit tests, create a directory called
 `coverage` and place the coverage results there.
 
 In a more advanced scenario, you may wish to run individual unit tests
@@ -41,7 +41,7 @@ To collect coverage results, you merely run the python interpreter
 under valgrind's callgrind tool.  The `c_coverage_collect.sh` helper
 script will pass all of the required arguments to valgrind.
 
-For example, in typical usage, you may want to run all of the Numpy
+For example, in typical usage, you may want to run all of the NumPy
 unit tests::
 
   > c_coverage_collect.sh python -c "import numpy; numpy.test()"
@@ -99,7 +99,7 @@ HTML reports
 The HTML report highlights the code that was run in green.
 
 The HTML report has special support for the "generated" functions in
-Numpy.  Each run line of code also contains a number in square
+NumPy.  Each run line of code also contains a number in square
 brackets indicating the number of different generated functions the
 line was run in.  Hovering the mouse over the line will display a list
 of the versions of the function in which the line was run.  These
@@ -112,6 +112,6 @@ Caveats
 The coverage results occasionally misses lines that clearly must have
 been run.  This usually can be traced back to the compiler optimizer
 removing lines because they are tautologically impossible or to
-combine lines together.  Compiling Numpy without optimizations helps,
+combine lines together.  Compiling NumPy without optimizations helps,
 but not completely.  Even despite this flaw, this tool is still
 helpful in identifying large missed blocks or functions.
diff --git a/tools/numpy-macosx-installer/art/dmgbackground.svg b/tools/numpy-macosx-installer/art/dmgbackground.svg
diff --git a/tools/travis-test.sh b/tools/travis-test.sh
@@ -71,7 +71,7 @@ setup_chroot()
   #   linux32 python setup.py build
   # when travis updates to ubuntu 14.04
   #
-  # Numpy may not distinguish between 64 and 32 bit ATLAS in the
+  # NumPy may not distinguish between 64 and 32 bit ATLAS in the
   # configuration stage.
   DIR=$1
   set -u

diff --git a/tools/win32build/nsis_scripts/numpy-superinstaller.nsi.in b/tools/win32build/nsis_scripts/numpy-superinstaller.nsi.in
@@ -15,7 +15,7 @@ SetCompressor /Solid LZMA ; Useful to disable compression under development
 ;General
 
 ;Name and file
-Name "Numpy super installer"
+Name "NumPy super installer"
 OutFile "@NUMPY_INSTALLER_NAME@"
 
 ;Default installation folder