Metadata-Version: 1.1
Name: histogramy
Version: 0.1.4
Summary: A small program to analysis 1 dimensional data
Home-page: https://github.com/lambdalisue/histogramy
Author: Alisue
Author-email: lambdalisue@hashnote.net
License: MIT
Download-URL: https://github.com/lambdalisue/histogramy/tarball/master
Description: Histogramy
        =============================================================================
        
        Histogramy is a CUI program to analyze 1-dimensional data.
        
        It draw a histogram with specified data and it also can draw the fitting curve
        estimated by a Gaussian Mixture Model probability distribution.
        
        ![Screenshot](https://raw.github.com/lambdalisue/Histogramy/master/static/screenshot.png)
        
        Requirements
        -----------------------------------------------------------------------------
        
        -   [Python][]
        -   [numpy][]
        -   [matplotlib][]
        -   [scikit-learn][]
        
        [Python]: http://www.python.org/
        [numpy]: http://www.numpy.org/
        [matplotlib]: http://matplotlib.org/
        [scikit-learn]: http://scikit-learn.org/dev/index.html
        
        
        Install
        -----------------------------------------------------------------------------
        
        1.  You have to install [Python][]. Follow the instruction at
            http://www.python.org/getit/
        
        2.  You also have to instal [numpy][], and [matplotlib][].
            Follow the instructions below
        
            1.  numpy: http://docs.scipy.org/doc/numpy/user/install.html
            2.  matplotlib: http://matplotlib.org/users/installing.html
        
        3.  Now, you can install Histogramy with [pip][] or [easy_install][].
            [scikit-learn][] will be installed automatically when you install
            Histogramy
        
            1.  Install [pip][] or [easy_install][], follow the instrcutions below
        
                -   pip: http://www.pip-installer.org/en/latest/installing.html
                -   easy_install: http://pypi.python.org/pypi/setuptools
        
            2.  Install Histogramy with the following command in Terminal (Command
                Prompt)
        
                ~~~
                pip install histogramy
                ~~~
        
                or
        
                ~~~
                easy_install histogramy
                ~~~
        
        [pip]: http://www.pip-installer.org/
        [easy_install]: http://pypi.python.org/pypi/setuptools
        
        
        Usage
        -----------------------------------------------------------------------------
        
            usage: histogramy [-h] [-b BINS] [-c N] [-C N] [--base BASE] [--auto-base]
                            [--min-threshold MIN] [--max-threshold MAX]
                            [--covariance-type TYPE] [--min-covar MIN_COVAR]
                            [--delimiter DELIMITER] [--encoding ENCODING] [--demo]
                            [filenames [filenames ...]] {histogram,fit,plot} ...
        
            positional arguments:
            filenames
            {histogram,fit,plot}
                histogram           Show histogram data
                fit                 Show fitting data
                plot                Create graph by matplotlib
        
            optional arguments:
            -h, --help            show this help message and exit
            -b BINS, --bins BINS  It defines the number of equal-width bins.
            -c N, --column N      A number of column in data file used for analysis
            -C N, --classifiers N
                                    The maximum number classifiers to simulate the fitting
            --base BASE           Base value to modulate the data
            --auto-base           Automatically find the base value to modulate the data
            --min-threshold MIN   Minimum threshold. Value smaller than this will be
                                    ignored
            --max-threshold MAX   Maximum threshold. Value grater than this will be
                                    ignored
            --covariance-type TYPE
                                    Type of covariance. Default is "diag"
            --min-covar MIN_COVAR
                                    Minimum value of covariance
            --delimiter DELIMITER
                                    Delimiter used to parse the data file
            --encoding ENCODING   Encoding used to open the data file
            --demo                Use demo data to analysis
        
Keywords: 1-dimensional,analysis,histogram
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Topic :: Internet :: WWW/HTTP
