Metadata-Version: 1.1 Name: np Version: 0.2.0 Summary: np = numpy++: numpy with added convenience functionality Home-page: https://github.com/k7hoven/np Author: Koos Zevenhoven Author-email: koos.zevenhoven@aalto.fi License: BSD Description-Content-Type: UNKNOWN Description: np -- create numpy arrays as ``np[1,3,5]``, and more ==================================================== ``np`` = ``numpy`` + handy tools For the numerical Python package ``numpy`` itself, see http://www.numpy.org/. The idea of ``np`` is to provide a way of creating numpy arrays with a compact syntax and without an explicit function call. Making the module name ``np`` subscriptable, while still keeping it essentially an alias for numpy, does this in a clean way. Any feedback is very welcome: ``koos.zevenhoven@aalto.fi``. Getting Started =============== Requirements ------------ * Works best with Python 3.5+ (Tested also with 3.4 and 2.7) * numpy (you should install this using your python package manager like `conda` or `pip`) Installation ------------ np can be installed with pip: .. code-block:: bash $ pip install np or directly from the source code: .. code-block:: bash $ git clone https://github.com/k7hoven/np.git $ cd np $ python setup.py install Basic Usage =========== Even before the ``np`` tool, a popular style of using ``numpy`` has been to import it as ``np``: .. code-block:: python >>> import numpy as np >>> my_array = np.array([3, 4, 5]) >>> my_2d_array = np.array([[1, 2], [3, 4]]) The most important feature of ``np`` is to make the creation of arrays less verbose, while everything else works as before. The above code becomes: .. code-block:: python >>> import np >>> my_array = np[3, 4, 5] >>> my_2d_array = np[[1, 2], [3, 4]] As you can see from the above example, you can create numpy arrays by subscripting the `np` module. Since most people would have numpy imported as ``np`` anyway, this requires no additional names to clutter the namespace. Also, the syntax ``np[1,2,3]`` resembles the syntax for ``bytes`` literals, ``b"asd"``. The `np` package also provides a convenient way of ensuring something is a numpy array, that is, a shortcut to ``numpy.asanyarray()``: .. code-block:: python >>> import np >>> mylist = [1, 3, 5] >>> mylist + [7, 9, 11] [1, 3, 5, 7, 9, 11] >>> np(mylist) + [7, 9, 11] array([8, 12, 16]) As an experimental feature, there are also shortcuts for giving the arrays a specific data type (numpy dtype): .. code-block:: python >>> np[1, 2, 3] array([1, 2, 3]) >>> np.f[1, 2, 3] array([ 1., 2., 3.]) >>> np.f2[1, 2, 3] array([ 1., 2., 3.], dtype=float16) >>> np.u4[1, 2, 3] array([1, 2, 3], dtype=uint32) >>> np.c[1, 2, 3] array([ 1.+0.j, 2.+0.j, 3.+0.j]) Changelog ========= 0.2.0 (2016-03-29) ------------------ - Quick types are now np.i, np.f, np.u, np.c, or with the number of /bytes/ per value appended: np.i4 -> int32, np.u2 -> uint16, np.c16 -> complex128, ... (still somewhat experimental) - Removed the old np.i8 and np.ui8 which represented 8-bit types, which was inconsistent with short numpy dtype names which correspond to numbers of bytes. The rest of the bit-based shortcuts are deprecated and will be removed later. - Handle Python versions >=3.5 better; now even previously imported plain numpy module objects become the exact same object as np. - Tests for all np functionality - Ridiculously slow tests that runs the numpy test suite several times to make sure that np does not affect numpy functionality. - Remove numpy from requirements and give a meaningful error instead if numpy is missing (i.e. install it using your package manager like conda or pip) - Better reprs for subscriptable array creator objects and the np/numpy module. 0.1.4 (2016-01-26) ------------------ - Bug fix 0.1.2 (2015-06-17) ------------------ - Improved experimental dtype shortcuts: np.f[1,2], np.i32[1,2], etc. 0.1.1 (2015-06-17) ------------------ - PyPI-friendly readme 0.1.0 (2015-06-17) ------------------ - First distributable version - Easy arrays such as np[[1,2],[3,4]] - Shortcut for np.asanyarray(obj): np(obj) - Experimental dtype shortcuts: np.f64[[1,2],[3,4]] Platform: UNKNOWN Classifier: Development Status :: 5 - Production/Stable Classifier: Natural Language :: English Classifier: Operating System :: OS Independent Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3