Metadata-Version: 1.1
Name: pydendroheatmap
Version: 1.5
Summary: Tool for creating heatmaps, where rows and columns are organized by hierarchical clusters as seen in http://code.activestate.com/recipes/578175-hierarchical-clustering-heatmap-python/
Home-page: https://github.com/themantalope/pydendroheatmap
Author: Matt Antalek Jr
Author-email: matthew.antalek@northwestern.edu
License: MIT
Description: # pydendroheatmap - a plotting tool for making heatmaps with hierarchically clustered data in python.
        
        pydendroheatmap is registered as a package on PyPI, so to install, simply type
        
        ```bash
        pip install pydendroheatmap
        ```
        
        To install the package from source, download the repository, unpack and open a command line prompt in the unpackaged directory. Then simply type:
        
        ```bash
        python setup.py install
        ```
        
        
        To make a plot, simply import the package, and create a DendroHeatMap object. Data for the heatmap and
        dendrogram do not need to be specified at the time of creation, however, if no data is supplied then
        the plot for these objects will not be rendered. See example uses below.
        
        The data for the heat map should be either a numpy.ndarray or numpy.matrix object, and the top and left dendrogram
        data should be in the form of a (n-1) x 4 linkage matrix used in the scipy hierarchical clustering package.
        
        ```python
        import pydendroheatmap as pdh
        try: import cPickle as pickle
        except: import pickle
        
        heatmap_array = pickle.load(open('some_data_file.pickle'))#a numpy.ndarray or numpy.matrix, for this example, let's say mxn array
        top_dendrogram = pickle.load(open('another_data_file.pickle'))#a (n-1) x 4 array
        side_dendrogram = pickle.load(open('a_third_data_file.pickle'))#a (m-1) x 4 array
        
        heatmap = pdh.DendroHeatMap(heat_map_data=heatmap_array, left_dendrogram=side_dendrogram, top_dendrogram=top_dendrogram)
        heatmap.title = 'This is an example'
        heatmap.show()
        
        heatmap.colormap = heatmap.yellowBlackBlue
        
        heatmap.show()
        
        heatmap.row_labels = ['some', 'row','labels'] #must have the same number of rows in heat_map_data
        
        heatmap.reset_plot()
        heatmap.show()
        
        #excellent, let's export it
        
        heatmap.export('awesome_heatmap_plot.png')
        ```
        
        
        To see a built-in example, run these commands in the python interpreter:
        
        ```python
        from pydendroheatmap import example
        example.run()
        ```
        
        The example should make a plot that will look similar to this:
        
        ![Example Image](https://github.com/themantalope/pydendroheatmap/blob/master/pydendroheatmap/exampledata/example.png)
        
        
        The DendroHeatMap object's `render_plot()` function will generate a heat plot, similar in fashion to the one found here:
        
        http://code.activestate.com/recipes/578175-hierarchical-clustering-heatmap-python/
        
        Each time the DendroHeatMap object's `show()`, `export()`, and `render_plot()` functions are called,
        the plot will be reset and any changes that have been made to the plot's instance variables should be taken into account
        in the new plot.
        
        A special thanks to [Nathan Salomonis](http://www.cincinnatichildrens.org/bio/s/nathan-salomonis/) for posting the
        original example and figuring out much of the parameters for getting the plots in the correct position!
        
Platform: UNKNOWN
Classifier: Topic :: Scientific/Engineering :: Visualization
