Search is not available for this dataset
repo_id stringlengths 12 110 | file_path stringlengths 24 164 | content stringlengths 3 89.3M | __index_level_0__ int64 0 0 |
|---|---|---|---|
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/c-api.config.rst | System configuration
====================
.. sectionauthor:: Travis E. Oliphant
When NumPy is built, information about system configuration is
recorded, and is made available for extension modules using Numpy's C
API. These are mostly defined in ``numpyconfig.h`` (included in
``ndarrayobject.h``). The public symbols... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/arrays.rst | .. _arrays:
*************
Array objects
*************
.. currentmodule:: numpy
NumPy provides an N-dimensional array type, the :ref:`ndarray
<arrays.ndarray>`, which describes a collection of "items" of the same
type. The items can be :ref:`indexed <arrays.indexing>` using for
example N integers.
All ndarrays are :... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/routines.sort.rst | Sorting and searching
=====================
.. currentmodule:: numpy
Sorting
-------
.. autosummary::
:toctree: generated/
sort
lexsort
argsort
ndarray.sort
msort
sort_complex
Searching
---------
.. autosummary::
:toctree: generated/
argmax
nanargmax
argmin
nanargmin
argwhere... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/arrays.classes.rst | #########################
Standard array subclasses
#########################
.. currentmodule:: numpy
The :class:`ndarray` in NumPy is a "new-style" Python
built-in-type. Therefore, it can be inherited from (in Python or in C)
if desired. Therefore, it can form a foundation for many useful
classes. Often whether to ... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/routines.ma.rst | .. _routines.ma:
Masked array operations
***********************
.. currentmodule:: numpy
Constants
=========
.. autosummary::
:toctree: generated/
ma.MaskType
Creation
========
From existing data
~~~~~~~~~~~~~~~~~~
.. autosummary::
:toctree: generated/
ma.masked_array
ma.array
ma.copy
m... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/routines.functional.rst | Functional programming
**********************
.. currentmodule:: numpy
.. autosummary::
:toctree: generated/
apply_along_axis
apply_over_axes
vectorize
frompyfunc
piecewise
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/maskedarray.baseclass.rst | .. currentmodule:: numpy.ma
.. _numpy.ma.constants:
Constants of the :mod:`numpy.ma` module
=======================================
In addition to the :class:`MaskedArray` class, the :mod:`numpy.ma` module
defines several constants.
.. data:: masked
The :attr:`masked` constant is a special case of :class:`Mask... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/arrays.interface.rst | .. index::
pair: array; interface
pair: array; protocol
.. _arrays.interface:
*******************
The Array Interface
*******************
.. warning::
This page describes the old, deprecated array interface. Everything still
works as described as of numpy 1.2 and on into the foreseeable future, but
n... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/internals.code-explanations.rst | .. currentmodule:: numpy
*************************
Numpy C Code Explanations
*************************
Fanaticism consists of redoubling your efforts when you have forgotten
your aim.
--- *George Santayana*
An authority is a person who can tell you more about something than
you really care to kno... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/routines.poly.rst | Polynomials
***********
.. currentmodule:: numpy
Basics
------
.. autosummary::
:toctree: generated/
poly1d
polyval
poly
roots
Fitting
-------
.. autosummary::
:toctree: generated/
polyfit
Calculus
--------
.. autosummary::
:toctree: generated/
polyder
polyint
Arithmetic
----------... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/reference/routines.array-manipulation.rst | Array manipulation routines
***************************
.. currentmodule:: numpy
Changing array shape
====================
.. autosummary::
:toctree: generated/
reshape
ravel
ndarray.flat
ndarray.flatten
Transpose-like operations
=========================
.. autosummary::
:toctree: generated/
... | 0 |
public_repos/datetime/doc/source/reference | public_repos/datetime/doc/source/reference/figures/threefundamental.fig | #FIG 3.2
Landscape
Center
Inches
Letter
100.00
Single
-2
1200 2
6 1950 2850 4350 3450
2 2 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 5
1950 2850 4350 2850 4350 3450 1950 3450 1950 2850
2 1 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 2
2550 2850 2550 3450
2 1 0 1 0 7 50 -1 -1 0.000 0 0 -1 0 0 2
3150 2850 3150 3450
2 1 0 1 0 7 50 -... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.indexing.rst | .. _basics.indexing:
********
Indexing
********
.. seealso:: :ref:`Indexing routines <routines.indexing>`
.. automodule:: numpy.doc.indexing
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.subclassing.rst | .. _basics.subclassing:
*******************
Subclassing ndarray
*******************
.. automodule:: numpy.doc.subclassing
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.types.rst | **********
Data types
**********
.. seealso:: :ref:`Data type objects <arrays.dtypes>`
.. automodule:: numpy.doc.basics
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.broadcasting.rst | ************
Broadcasting
************
.. seealso:: :class:`numpy.broadcast`
.. automodule:: numpy.doc.broadcasting
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/c-info.python-as-glue.rst | ********************
Using Python as glue
********************
| There is no conversation more boring than the one where everybody
| agrees.
| --- *Michel de Montaigne*
| Duct tape is like the force. It has a light side, and a dark side, and
| it holds the universe together.
| --- *Carl Zwanzig*
Ma... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/c-info.rst | #################
Using Numpy C-API
#################
.. toctree::
c-info.how-to-extend
c-info.python-as-glue
c-info.beyond-basics
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.byteswapping.rst | ************
Broadcasting
************
.. automodule:: numpy.doc.byteswapping
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.rst | ************
Numpy basics
************
.. toctree::
:maxdepth: 2
basics.types
basics.creation
basics.io
basics.indexing
basics.broadcasting
basics.byteswapping
basics.rec
basics.subclassing
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/install.rst | *****************************
Building and installing NumPy
*****************************
Binary installers
=================
In most use cases the best way to install NumPy on your system is by using an
installable binary package for your operating system.
Windows
-------
Good solutions for Windows are, The Enthou... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/index.rst | .. _user:
################
NumPy User Guide
################
This guide is intended as an introductory overview of NumPy and
explains how to install and make use of the most important features of
NumPy. For detailed reference documentation of the functions and
classes contained in the package, see the :ref:`reference... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/introduction.rst | ************
Introduction
************
.. toctree::
whatisnumpy
install
howtofind
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/performance.rst | ***********
Performance
***********
.. automodule:: numpy.doc.performance
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.io.genfromtxt.rst | .. sectionauthor:: Pierre Gerard-Marchant <pierregmcode@gmail.com>
*********************************************
Importing data with :func:`~numpy.genfromtxt`
*********************************************
Numpy provides several functions to create arrays from tabular data.
We focus here on the :func:`~numpy.genfromtx... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/misc.rst | *************
Miscellaneous
*************
.. automodule:: numpy.doc.misc
.. automodule:: numpy.doc.methods_vs_functions
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/c-info.how-to-extend.rst | *******************
How to extend NumPy
*******************
| That which is static and repetitive is boring. That which is dynamic
| and random is confusing. In between lies art.
| --- *John A. Locke*
| Science is a differential equation. Religion is a boundary condition.
| --- *Alan Turing*
.. _`sec... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/whatisnumpy.rst | **************
What is NumPy?
**************
NumPy is the fundamental package for scientific computing in Python.
It is a Python library that provides a multidimensional array object,
various derived objects (such as masked arrays and matrices), and an
assortment of routines for fast operations on arrays, including
ma... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.rec.rst | .. _structured_arrays:
***************************************
Structured arrays (aka "Record arrays")
***************************************
.. automodule:: numpy.doc.structured_arrays
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/howtofind.rst | *************************
How to find documentation
*************************
.. seealso:: :ref:`Numpy-specific help functions <routines.help>`
.. automodule:: numpy.doc.howtofind
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.creation.rst | .. _arrays.creation:
**************
Array creation
**************
.. seealso:: :ref:`Array creation routines <routines.array-creation>`
.. automodule:: numpy.doc.creation
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/c-info.beyond-basics.rst | *****************
Beyond the Basics
*****************
| The voyage of discovery is not in seeking new landscapes but in having
| new eyes.
| --- *Marcel Proust*
| Discovery is seeing what everyone else has seen and thinking what no
| one else has thought.
| --- *Albert Szent-Gyorgi*
Iterating over... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/user/basics.io.rst | **************
I/O with Numpy
**************
.. toctree::
:maxdepth: 2
basics.io.genfromtxt | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/_templates/indexsidebar.html | <h3>Resources</h3>
<ul>
<li><a href="http://scipy.org/">Scipy.org website</a></li>
<li> </li>
</ul>
| 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/_templates/indexcontent.html | {% extends "defindex.html" %}
{% block tables %}
<p><strong>Parts of the documentation:</strong></p>
<table class="contentstable" align="center"><tr>
<td width="50%">
<p class="biglink"><a class="biglink" href="{{ pathto("user/index") }}">Numpy User Guide</a><br/>
<span class="linkdescr">start he... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/_templates/layout.html | {% extends "!layout.html" %}
{% block rootrellink %}
<li><a href="{{ pathto('index') }}">{{ shorttitle }}</a>{{ reldelim1 }}</li>
{% endblock %}
{% block sidebarsearch %}
{%- if sourcename %}
<ul class="this-page-menu">
{%- if 'reference/generated' in sourcename %}
<li><a href="/numpy/docs/{{ sourcename.replace('ref... | 0 |
public_repos/datetime/doc/source/_templates | public_repos/datetime/doc/source/_templates/autosummary/class.rst | {% extends "!autosummary/class.rst" %}
{% block methods %}
{% if methods %}
.. HACK
.. autosummary::
:toctree:
{% for item in methods %}
{{ name }}.{{ item }}
{%- endfor %}
{% endif %}
{% endblock %}
{% block attributes %}
{% if attributes %}
.. HACK
.. autosummary::
... | 0 |
public_repos/datetime/doc/source | public_repos/datetime/doc/source/_static/scipy.css | @import "default.css";
/**
* Spacing fixes
*/
div.body p, div.body dd, div.body li {
line-height: 125%;
}
ul.simple {
margin-top: 0;
margin-bottom: 0;
padding-top: 0;
padding-bottom: 0;
}
/* spacing around blockquoted fields in parameters/attributes/returns */
td.field-body > blockquote {
m... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/newbugtracker.rst | Some release managers of both numpy and scipy are becoming more and more
disatisfied with the current development workflow, in particular for bug
tracking. This document is a tentative to explain some problematic scenario,
current trac limitations, and what can be done about it.
Scenario
========
new release
--------... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/npy-format.txt | Title: A Simple File Format for NumPy Arrays
Discussions-To: numpy-discussion@mail.scipy.org
Version: $Revision$
Last-Modified: $Date$
Author: Robert Kern <robert.kern@gmail.com>
Status: Draft
Type: Standards Track
Content-Type: text/plain
Created: 20-Dec-2007
Abstract
We propose a standard binary file format (N... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/pep_buffer.txt | :PEP: 3118
:Title: Revising the buffer protocol
:Version: $Revision$
:Last-Modified: $Date$
:Authors: Travis Oliphant <oliphant@ee.byu.edu>, Carl Banks <pythondev@aerojockey.com>
:Status: Draft
:Type: Standards Track
:Content-Type: text/x-rst
:Created: 28-Aug-2006
:Python-Version: 3000
Abstract
========
This PEP prop... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/math_config_clean.txt | ===========================================================
Cleaning the math configuration of numpy.core
===========================================================
:Author: David Cournapeau
:Contact: david@ar.media.kyoto-u.ac.jp
:Date: 2008-09-04
Executive summary
=================
Before building numpy.core, we u... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/datetime-proposal.rst | ====================================================================
A proposal for implementing some date/time types in NumPy
====================================================================
:Author: Travis Oliphant
:Contact: oliphant@enthought.com
:Date: 2009-06-09
Revised only slightly from the third proposal... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/structured_array_extensions.txt |
1. Create with-style context that makes "named-columns" available as names in the namespace.
with np.columns(array):
price = unit * quantityt
2. Allow structured arrays to be sliced by their column (i.e. one additional indexing option for structured arrays) so that a[:4, 'foo':'bar'] would be allowed.... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/datetime-proposal3.rst | ====================================================================
A (third) proposal for implementing some date/time types in NumPy
====================================================================
:Author: Francesc Alted i Abad
:Contact: faltet@pytables.com
:Author: Ivan Vilata i Balaguer
:Contact: ivan@selido... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/groupby_additions.rst | ====================================================================
A proposal for adding groupby functionality to NumPy
====================================================================
:Author: Travis Oliphant
:Contact: oliphant@enthought.com
:Date: 2010-04-27
Executive summary
=================
NumPy provid... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/generalized-ufuncs.rst | ===============================
Generalized Universal Functions
===============================
There is a general need for looping over not only functions on scalars
but also over functions on vectors (or arrays), as explained on
http://scipy.org/scipy/numpy/wiki/GeneralLoopingFunctions. We propose
to realize this c... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/neps/warnfix.txt | ===========================================================
A proposal to build numpy without warning with a big set of
warning flags
===========================================================
:Author: David Cournapeau
:Contact: david@ar.media.kyoto-u.ac.jp
:Date: 2008-09-04
Executive summary
=================
When... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/traitsdoc.py | """
=========
traitsdoc
=========
Sphinx extension that handles docstrings in the Numpy standard format, [1]
and support Traits [2].
This extension can be used as a replacement for ``numpydoc`` when support
for Traits is required.
.. [1] http://projects.scipy.org/numpy/wiki/CodingStyleGuidelines#docstring-standard
.... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/MANIFEST.in | recursive-include tests *.py
include *.txt
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/compiler_unparse.py | """ Turn compiler.ast structures back into executable python code.
The unparse method takes a compiler.ast tree and transforms it back into
valid python code. It is incomplete and currently only works for
import statements, function calls, function definitions, assignments, and
basic expressions.
... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/docscrape_sphinx.py | import re, inspect, textwrap, pydoc
import sphinx
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
class SphinxDocString(NumpyDocString):
def __init__(self, docstring, config={}):
self.use_plots = config.get('use_plots', False)
NumpyDocString.__init__(self, docstring, config=config)
... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/LICENSE.txt | -------------------------------------------------------------------------------
The files
- numpydoc.py
- autosummary.py
- autosummary_generate.py
- docscrape.py
- docscrape_sphinx.py
- phantom_import.py
have the following license:
Copyright (C) 2008 Stefan van der Walt <stefan@mentat.z... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/README.txt | =====================================
numpydoc -- Numpy's Sphinx extensions
=====================================
Numpy's documentation uses several custom extensions to Sphinx. These
are shipped in this ``numpydoc`` package, in case you want to make use
of them in third-party projects.
The following extensions are ... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/phantom_import.py | """
==============
phantom_import
==============
Sphinx extension to make directives from ``sphinx.ext.autodoc`` and similar
extensions to use docstrings loaded from an XML file.
This extension loads an XML file in the Pydocweb format [1] and
creates a dummy module that contains the specified docstrings. This
can be ... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/setup.py | from distutils.core import setup
import setuptools
import sys, os
version = "0.3.dev"
setup(
name="numpydoc",
packages=["numpydoc"],
package_dir={"numpydoc": ""},
version=version,
description="Sphinx extension to support docstrings in Numpy format",
# classifiers from http://pypi.python.org/py... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/plot_directive.py | """
A special directive for generating a matplotlib plot.
.. warning::
This is a hacked version of plot_directive.py from Matplotlib.
It's very much subject to change!
Usage
-----
Can be used like this::
.. plot:: examples/example.py
.. plot::
import matplotlib.pyplot as plt
plt.plot... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/autosummary_generate.py | #!/usr/bin/env python
r"""
autosummary_generate.py OPTIONS FILES
Generate automatic RST source files for items referred to in
autosummary:: directives.
Each generated RST file contains a single auto*:: directive which
extracts the docstring of the referred item.
Example Makefile rule::
generate:
./e... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/only_directives.py | #
# A pair of directives for inserting content that will only appear in
# either html or latex.
#
from docutils.nodes import Body, Element
from docutils.writers.html4css1 import HTMLTranslator
try:
from sphinx.latexwriter import LaTeXTranslator
except ImportError:
from sphinx.writers.latex import LaTeXTranslat... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/autosummary.py | """
===========
autosummary
===========
Sphinx extension that adds an autosummary:: directive, which can be
used to generate function/method/attribute/etc. summary lists, similar
to those output eg. by Epydoc and other API doc generation tools.
An :autolink: role is also provided.
autosummary directive
-------------... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/comment_eater.py | from cStringIO import StringIO
import compiler
import inspect
import textwrap
import tokenize
from compiler_unparse import unparse
class Comment(object):
""" A comment block.
"""
is_comment = True
def __init__(self, start_lineno, end_lineno, text):
# int : The first line number in the block. ... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/docscrape.py | """Extract reference documentation from the NumPy source tree.
"""
import inspect
import textwrap
import re
import pydoc
from StringIO import StringIO
from warnings import warn
class Reader(object):
"""A line-based string reader.
"""
def __init__(self, data):
"""
Parameters
-----... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/__init__.py | from numpydoc import setup
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/sphinxext/numpydoc.py | """
========
numpydoc
========
Sphinx extension that handles docstrings in the Numpy standard format. [1]
It will:
- Convert Parameters etc. sections to field lists.
- Convert See Also section to a See also entry.
- Renumber references.
- Extract the signature from the docstring, if it can't be determined otherwise.... | 0 |
public_repos/datetime/doc/sphinxext | public_repos/datetime/doc/sphinxext/tests/test_docscrape.py | # -*- encoding:utf-8 -*-
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
from docscrape import NumpyDocString, FunctionDoc, ClassDoc
from docscrape_sphinx import SphinxDocString, SphinxClassDoc
from nose.tools import *
doc_txt = '''\
numpy.multivariate_normal(mean, cov, shape=None)
... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/release/2.0.0-notes.rst | =========================
NumPy 2.0.0 Release Notes
=========================
Plans
=====
This release has the following aims:
* Python 3 compatibility
* :pep:`3118` compatibility
Highlights
==========
New features
============
Warning on casting complex to real
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Numpy now em... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/release/time_based_proposal.rst | .. vim:syntax=rst
Introduction
============
This document proposes some enhancements for numpy and scipy releases.
Successive numpy and scipy releases are too far apart from a time point of
view - some people who are in the numpy release team feel that it cannot
improve without a bit more formal release process. The ... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/release/1.4.0-notes.rst | =========================
NumPy 1.4.0 Release Notes
=========================
This minor includes numerous bug fixes, as well as a few new features. It
is backward compatible with 1.3.0 release.
Highlights
==========
* New datetime dtype support to deal with dates in arrays
* Faster import time
* Extended array wr... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/release/1.3.0-notes.rst | =========================
NumPy 1.3.0 Release Notes
=========================
This minor includes numerous bug fixes, official python 2.6 support, and
several new features such as generalized ufuncs.
Highlights
==========
Python 2.6 support
~~~~~~~~~~~~~~~~~~
Python 2.6 is now supported on all previously supported ... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/newdtype_example/setup.py |
from numpy.distutils.core import setup
def configuration(parent_package = '', top_path=None):
from numpy.distutils.misc_util import Configuration
config = Configuration('floatint',parent_package,top_path)
config.add_extension('floatint',
sources = ['floatint.c']);
return conf... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/newdtype_example/example.py | import floatint.floatint as ff
import numpy as np
# Setting using array is hard because
# The parser doesn't stop at tuples always
# So, the setitem code will be called with scalars on the
# wrong shaped array.
# But we can get a view as an ndarray of the given type:
g = np.array([1,2,3,4,5,6,7,8]).view(ff.floatint... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/newdtype_example/floatint.c |
#include "Python.h"
#include "structmember.h" /* for offsetof macro if needed */
#include "numpy/arrayobject.h"
/* Use a Python float as the cannonical type being added
*/
typedef struct _floatint {
PyObject_HEAD
npy_int32 first;
npy_int32 last;
} PyFloatIntObject;
static PyTypeObject PyFloatInt_Type =... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/numpyx.c | /* Generated by Pyrex 0.9.5.1 on Wed Jan 31 11:57:10 2007 */
#include "Python.h"
#include "structmember.h"
#ifndef PY_LONG_LONG
#define PY_LONG_LONG LONG_LONG
#endif
#ifdef __cplusplus
#define __PYX_EXTERN_C extern "C"
#else
#define __PYX_EXTERN_C extern
#endif
__PYX_EXTERN_C double pow(double, double);
#include "st... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/README.txt | WARNING: this code is deprecated and slated for removal soon. See the
doc/cython directory for the replacement, which uses Cython (the actively
maintained version of Pyrex).
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/setup.py | #!/usr/bin/env python
"""
WARNING: this code is deprecated and slated for removal soon. See the
doc/cython directory for the replacement, which uses Cython (the actively
maintained version of Pyrex).
Install file for example on how to use Pyrex with Numpy.
For more details, see:
http://www.scipy.org/Cookbook/Pyrex_... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/Makefile | all:
python setup.py build_ext --inplace
test: all
python run_test.py
.PHONY: clean
clean:
rm -rf *~ *.so *.c *.o build
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/c_numpy.pxd | # :Author: Travis Oliphant
cdef extern from "numpy/arrayobject.h":
cdef enum NPY_TYPES:
NPY_BOOL
NPY_BYTE
NPY_UBYTE
NPY_SHORT
NPY_USHORT
NPY_INT
NPY_UINT
NPY_LONG
NPY_ULONG
NPY_LONGLONG
NPY_ULONGLONG
NPY_FLOAT
... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/c_python.pxd | # -*- Mode: Python -*- Not really, but close enough
# Expose as much of the Python C API as we need here
cdef extern from "stdlib.h":
ctypedef int size_t
cdef extern from "Python.h":
ctypedef int Py_intptr_t
void* PyMem_Malloc(size_t)
void* PyMem_Realloc(void *p, size_t n)
void PyMem_Free(vo... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/notes | - cimport with a .pxd file vs 'include foo.pxi'?
- the need to repeat: pyrex does NOT parse C headers. | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/run_test.py | #!/usr/bin/env python
from numpyx import test
test()
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/numpyx.pyx | # -*- Mode: Python -*- Not really, but close enough
"""WARNING: this code is deprecated and slated for removal soon. See the
doc/cython directory for the replacement, which uses Cython (the actively
maintained version of Pyrex).
"""
cimport c_python
cimport c_numpy
import numpy
# Numpy must be initialized
c_numpy.i... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/pyrex/MANIFEST | numpyx.pyx
setup.py
| 0 |
public_repos/datetime/doc | public_repos/datetime/doc/swig/README | Notes for the numpy/doc/swig directory
======================================
This set of files is for developing and testing file numpy.i, which is
intended to be a set of typemaps for helping SWIG interface between C
and C++ code that uses C arrays and the python module NumPy. It is
ultimately hoped that numpy.i wi... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/swig/Makefile | # List all of the subdirectories here for recursive make
SUBDIRS = test doc
# Default target
.PHONY : default
default:
@echo "There is no default make target for this Makefile"
@echo "Valid make targets are:"
@echo " test - Compile and run tests of numpy.i"
@echo " doc - Generate numpy.i... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/swig/numpy.i | /* -*- C -*- (not really, but good for syntax highlighting) */
#ifdef SWIGPYTHON
%{
#ifndef SWIG_FILE_WITH_INIT
# define NO_IMPORT_ARRAY
#endif
#include "stdio.h"
#include <numpy/arrayobject.h>
%}
/**********************************************************************/
%fragment("NumPy_Backward_Compatibility", "he... | 0 |
public_repos/datetime/doc | public_repos/datetime/doc/swig/pyfragments.swg | /*-*- C -*-*/
/**********************************************************************/
/* For numpy versions prior to 1.0, the names of certain data types
* are different than in later versions. This fragment provides macro
* substitutions that allow us to support old and new versions of
* numpy.
*/
%fragment("... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Matrix.cxx | #include <stdlib.h>
#include <math.h>
#include <iostream>
#include "Matrix.h"
// The following macro defines a family of functions that work with 2D
// arrays with the forms
//
// TYPE SNAMEDet( TYPE matrix[2][2]);
// TYPE SNAMEMax( TYPE * matrix, int rows, int cols);
// TYPE SNAMEMin( int rows, i... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Fortran.i | // -*- c++ -*-
%module Fortran
%{
#define SWIG_FILE_WITH_INIT
#include "Fortran.h"
%}
// Get the NumPy typemaps
%include "../numpy.i"
%init %{
import_array();
%}
%define %apply_numpy_typemaps(TYPE)
%apply (TYPE* IN_FARRAY2, int DIM1, int DIM2) {(TYPE* matrix, int rows, int cols)};
%enddef /* %apply_numpy_typ... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Array1.cxx | #include "Array1.h"
#include <iostream>
#include <sstream>
// Default/length/array constructor
Array1::Array1(int length, long* data) :
_ownData(false), _length(0), _buffer(0)
{
resize(length, data);
}
// Copy constructor
Array1::Array1(const Array1 & source) :
_length(source._length)
{
allocateMemory();
*t... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Tensor.cxx | #include <stdlib.h>
#include <math.h>
#include <iostream>
#include "Tensor.h"
// The following macro defines a family of functions that work with 3D
// arrays with the forms
//
// TYPE SNAMENorm( TYPE tensor[2][2][2]);
// TYPE SNAMEMax( TYPE * tensor, int rows, int cols, int num);
// TYPE SNAMEMin( ... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Vector.i | // -*- c++ -*-
%module Vector
%{
#define SWIG_FILE_WITH_INIT
#include "Vector.h"
%}
// Get the NumPy typemaps
%include "../numpy.i"
%init %{
import_array();
%}
%define %apply_numpy_typemaps(TYPE)
%apply (TYPE IN_ARRAY1[ANY]) {(TYPE vector[3])};
%apply (TYPE* IN_ARRAY1, int DIM1) {(TYPE* series, int size)};
%appl... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Farray.h | #ifndef FARRAY_H
#define FARRAY_H
#include <stdexcept>
#include <string>
class Farray
{
public:
// Size constructor
Farray(int nrows, int ncols);
// Copy constructor
Farray(const Farray & source);
// Destructor
~Farray();
// Assignment operator
Farray & operator=(const Farray & source);
// Equa... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Farray.cxx | #include "Farray.h"
#include <sstream>
// Size constructor
Farray::Farray(int nrows, int ncols) :
_nrows(nrows), _ncols(ncols), _buffer(0)
{
allocateMemory();
}
// Copy constructor
Farray::Farray(const Farray & source) :
_nrows(source._nrows), _ncols(source._ncols)
{
allocateMemory();
*this = source;
}
// ... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/testArray.py | #! /usr/bin/env python
# System imports
from distutils.util import get_platform
import os
import sys
import unittest
# Import NumPy
import numpy as np
major, minor = [ int(d) for d in np.__version__.split(".")[:2] ]
if major == 0:
BadListError = TypeError
else:
BadListError = ValueError
import Array
#####... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Tensor.h | #ifndef TENSOR_H
#define TENSOR_H
// The following macro defines the prototypes for a family of
// functions that work with 3D arrays with the forms
//
// TYPE SNAMENorm( TYPE tensor[2][2][2]);
// TYPE SNAMEMax( TYPE * tensor, int rows, int cols, int num);
// TYPE SNAMEMin( int rows, int cols, int ... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/setup.py | #! /usr/bin/env python
# System imports
from distutils.core import *
from distutils import sysconfig
# Third-party modules - we depend on numpy for everything
import numpy
# Obtain the numpy include directory. This logic works across numpy versions.
try:
numpy_include = numpy.get_include()
except Attribute... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Array2.cxx | #include "Array2.h"
#include <sstream>
// Default constructor
Array2::Array2() :
_ownData(false), _nrows(0), _ncols(), _buffer(0), _rows(0)
{ }
// Size/array constructor
Array2::Array2(int nrows, int ncols, long* data) :
_ownData(false), _nrows(0), _ncols(), _buffer(0), _rows(0)
{
resize(nrows, ncols, data);
}
... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Farray.i | // -*- c++ -*-
%module Farray
%{
#define SWIG_FILE_WITH_INIT
#include "Farray.h"
%}
// Get the NumPy typemaps
%include "../numpy.i"
// Get the STL typemaps
%include "stl.i"
// Handle standard exceptions
%include "exception.i"
%exception
{
try
{
$action
}
catch (const std::invalid_argument& e)
{
... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Vector.cxx | #include <stdlib.h>
#include <math.h>
#include <iostream>
#include "Vector.h"
// The following macro defines a family of functions that work with 1D
// arrays with the forms
//
// TYPE SNAMELength( TYPE vector[3]);
// TYPE SNAMEProd( TYPE * series, int size);
// TYPE SNAMESum( int size, TYPE * series)... | 0 |
public_repos/datetime/doc/swig | public_repos/datetime/doc/swig/test/Makefile | # SWIG
INTERFACES = Array.i Farray.i Vector.i Matrix.i Tensor.i Fortran.i
WRAPPERS = $(INTERFACES:.i=_wrap.cxx)
PROXIES = $(INTERFACES:.i=.py )
# Default target: build the tests
.PHONY : all
all: $(WRAPPERS) Array1.cxx Array1.h Farray.cxx Farray.h Vector.cxx Vector.h \
Matrix.cxx Matrix.h Tensor.cxx Tensor.... | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.