histogramy 0.1.5
A small program to analysis 1 dimensional data
License: MIT
Keywords: 1-dimensional,analysis,histogram

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