Changeset 1213

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Timestamp:
08/08/08 21:55:05 (4 months ago)
Author:
pierregm
Message:

doc update

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  • trunk/timeseries/scikits/timeseries/doc/source/conf.py

    r1211 r1213  
    3636 
    3737# General substitutions. 
    38 project = 'Climpy' 
    39 copyright = '2008, Pierre GERARD-MARCHANT' 
     38project = 'TimeSeries' 
     39copyright = '2008, Pierre GERARD-MARCHANT & Matt KNOX' 
    4040 
    4141# The default replacements for |version| and |release|, also used in various 
    …… 
    129129 
    130130# Output file base name for HTML help builder. 
    131 htmlhelp_basename = 'ClimPydoc' 
     131htmlhelp_basename = 'TimeSeriesDoc' 
    132132 
    133133 
    …… 
    144144# (source start file, target name, title, author, document class [howto/manual]). 
    145145latex_documents = [ 
    146   ('index', 'ClimPy.tex', 'ClimPy Reference Guide', 
    147    'Written by the ClimPy community', 'manual'), 
     146  ('index', 'TimeSeries.tex', 'TimeSeries Reference Guide', 
     147   'Written by Pierre Gerard-marchant and Matt Knox', 'manual'), 
    148148] 
    149149 

  • trunk/timeseries/scikits/timeseries/doc/source/index.rst

    r1211 r1213  
    1313   intro 
    1414   installing 
     15   examples/index 
    1516   implementation/index 
    1617 

  • trunk/timeseries/scikits/timeseries/doc/source/installing.rst

    r1211 r1213  
    1111------------ 
    1212 
    13 In order to use the TimeSeries package, you will first need install the following 
    14 external packages: 
     13In order to use the :mod:`scikits.timeseries` package, the following external  
     14packages must be installed before hand: 
    1515 
    16 * `Python 2.4 or later <http://www.python.org/download/>`__ (but not Python 3) 
     16* `Python <http://www.python.org/download/>`_ 2.4 or later (but not Python 3). 
    1717 
    18 * `setuptools <http://pypi.python.org/pypi/setuptools>`__: scikits is a 
    19   namespace package, and as a result every scikit requires setuptools to be 
     18* `setuptools <http://pypi.python.org/pypi/setuptools>`_: scikits is a 
     19  namespace package, and as a result every scikit requires ``setuptools`` to be 
    2020  installed to function properly. 
    2121 
    22 * `numpy 1.2.0 or later <http://sourceforge.net/project/showfiles.php?group_id=1369&package_id=175103>`__ 
     22* `Numpy <http://www.scipy.org/Download>`_ 1.2.0 or later 
    2323 
    2424Optional 
    2525-------- 
    2626 
    27 * `scipy <http://sourceforge.net/project/showfiles.php?group_id=27747>`__: 
    28   Some of the lib sub-modules (interpolate, moving_funcs) make use of scipy 
    29   functions. 
    30 * `matplotlib 0.98.0 or later <http://matplotlib.sourceforge.net>`__: 
     27* `Scipy 0.7.0 or later<http://www.scipy.org/Download>`_: 
     28  Some of the lib sub-modules (:mod:`~scikits.timeseries.lib.interpolate`,  
     29  :mod:`~scikits.timeserires.lib.moving_funcs`) make use of Scipy functions. 
     30* `matplotlib <http://matplotlib.sourceforge.net>`_ 0.98.0 or later: 
    3131  matplotlib is required for time series plotting. 
    3232 
    …… 
    3939manner to compile the C code. If you have difficulty installing, please ask 
    4040for assistance on the 
    41 `scipy-user mailing list <http://projects.scipy.org/mailman/listinfo/scipy-user>`__. 
     41`scipy-user mailing list <http://projects.scipy.org/mailman/listinfo/scipy-user>`_. 
    4242 
    43 The timeseries module itself is currently only through subversion 
    44 (http://svn.scipy.org/svn/scikits/trunk/timeseries). To install it, run:: 
     43The :mod:`scikits.timeseries` module itself is currently only through subversion. 
     44You can download the latest sources by checking out the repository with the 
     45command: 
     46:: 
     47 
     48   svn co http://svn.scipy.org/svn/scikits/trunk/timeseries timeseries 
     49 
     50This command will create a :file:`timeseries` folder in the current directory. 
     51On Windows, you can also use a SVN client such as `Tortoise SVN <http://tortoisesvn.net/>`_. 
     52 
     53To install the :mod:`scikits.timeseries` package, run the command 
     54:: 
    4555 
    4656    python setup.py install 
    4757 
    48 in the directory you checked out the source code to. If you are using Windows 
    49 and are having trouble compiling the module, please see the following page in 
    50 the cookbook: 
    51 `Compiling Extensions on Windows <http://www.scipy.org/Cookbook/CompilingExtensionsOnWindowsWithMinGW>`__ 
     58in the directory you checked out the source code to.  
     59If you are using Windows and are having trouble compiling the module,  
     60please see the following page in the cookbook: 
     61`Compiling Extensions on Windows <http://www.scipy.org/Cookbook/CompilingExtensionsOnWindowsWithMinGW>`_ 
    5262 
    5363The current plan is to begin doing official releases and distributing windows 

  • trunk/timeseries/scikits/timeseries/doc/source/intro.rst

    r1211 r1213  
    22============ 
    33 
    4 The scikits.timeseries module provides classes and functions for 
     4The :mod:`scikits.timeseries` module provides classes and functions for 
    55manipulating, reporting, and plotting time series of various frequencies. 
    66The focus is on convenient data access and manipulation while leveraging 
    77the existing mathematical functionality in numpy and scipy. 
    88 
    9 The scikits.timeseries module originally grew out of a need to manipulate 
     9The :mod:`scikits.timeseries` module originally grew out of a need to manipulate 
    1010financial and economic data of business day and monthly frequencies. The need 
    1111to compare monthly data with business frequency data led to the creation of 
    1212a series of frequency conversion algorithms (implemented in C for extra 
    13 speediness) for reshaping the series. The initial version was released as a 
    14 scipy "sandbox" module. Pierre Gerard-Marchant took the original prototype 
    15 and adapted it to be based on his MaskedArray class for handling missing data 
     13speed) for reshaping the series. The initial version was released as a scipy  
     14"sandbox" module. Pierre Gerard-Marchant took the original prototype and adapted 
     15it to be based on the :class:`numpy.ma.MaskedArray` class for handling missing data 
    1616in order to work with climate data. 
    1717 
    …… 
    1919the scikits.timeseries module useful: 
    2020 
    21 * Compare many time series with different ranges of data (eg. stock 
    22   prices) 
    23  
     21* Compare many time series with different ranges of data (eg. stock prices) 
    2422* Determine the last business day of the previous month/quarter/year for 
    2523  reporting purposes 
    26  
    2724* Create time series plots with intelligently spaced axis labels 
    28  
    2925* Convert a daily time series to monthly by taking the average value during 
    3026  each month 
    31  
    32 * compute a moving standard deviation EFFICIENTLY 
     27* Compute a moving standard deviation *efficiently*. 
    3328 
    3429These are just some of the scenarios that are made very simple with the 
    3530scikits.timeseries module. 
     31 
     32 
     33.. toctree:: 
     34 
     35   license