histogramy 0.1.5

A small program to analysis 1 dimensional data

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.


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