#!/usr/bin/env python
# coding: utf-8

# # Clustergrammer Widget
# 
# ## Gene Expression Example
# This example shows how to visualize a matrix of gene expression data saved as a tab-separated-file (e.g. [rc_two_cats.txt](https://github.com/MaayanLab/clustergrammer-widget/blob/master/rc_two_cats.txt)) using the Clustergrammer interactive widget (see the Clustergrammer Jupyter Widget [Documentation](http://clustergrammer.readthedocs.io/clustergrammer_widget.html) for more information).

# In[1]:


# import widget classes and instantiate Network instance
from clustergrammer_widget import *
net = Network(clustergrammer_widget)


# In[2]:


# load matrix file
net.load_file('rc_two_cats.txt')

# cluster using default parameters
net.cluster(enrichrgram=True)

# make interactive widget
net.widget()


# ## Interactive Features
# * zoom/pan
# * reorder rows and columns using buttons or by double-clicking row/column/category names
# * interactively perform dimensionality reduction (and re-clustering) using row-filter sliders (e.g. filter rows based on variance)
# * identify clusters of varying sizes using the interactive row and column dendrograms 
# * export cluster names or crop matrix to clusters using the dendrogram and dendrogram crop buttons
# * search for rows using the search box
# * crop the matrix using the brush cropping tool in the sidebar
# * take a PNG/SVG snapshot or download a TSV file snapshot of the matrix using the sidebar icons
# 
# ## Biollogy-specific Features
# Clustergrammer widget has biology-specific features that are activated when rows are given as official gene symbols:
# * mouseover gene (row) name to show full name and description (information provided by [Harmonizome](http://amp.pharm.mssm.edu/Harmonizome/))
# * find biological information specific to your gene list with enrichment analysis from [Enrichr](http://amp.pharm.mssm.edu/Enrichr/)
# 
# # General Purpose Pandas DataFrame Viewer
# Clustergrammer can also be used as a general purpose Pandas dataframe viewer. This example generates a dataframe with random data and visualizes it with Clustergrammer widget:

# In[3]:


import numpy as np
import pandas as pd

# generate random matrix
num_rows = 500
num_cols = 10
np.random.seed(seed=100)
mat = np.random.rand(num_rows, num_cols)

# make row and col labels
rows = range(num_rows)
cols = range(num_cols)
rows = [str(i) for i in rows]
cols = [str(i) for i in cols]

# make dataframe 
df = pd.DataFrame(data=mat, columns=cols, index=rows)


# Initialize the network object, load the dataframe, hierarchically cluster the rows and columns using default parameters, and finally visualize using clustergrammer_widget.

# In[4]:


net.load_df(df)
net.cluster(enrichrgram=False)
net.widget()


# # Installation
# Clustergrammer widget is built using the [ipywidgets](https://github.com/ipython/ipywidgets) framework (using the [cookie cutter](https://github.com/jupyter/widget-cookiecutter) template) and can be installed (with pip) and enabled using the following commands:
# 
#     pip install clustergrammer_widget
#     jupyter nbextension enable --py --sys-prefix widgetsnbextension
#     jupyter nbextension enable --py --sys-prefix clustergrammer_widget
#     
# See the [documentation](http://clustergrammer.readthedocs.io/clustergrammer_widget.html) and clustergrammer_widget [GitHub](https://github.com/MaayanLab/clustergrammer-widget) for more information. 
# 
# # nbviewer
# Interactive widgets can also be rendered using Jupyter's [nbviewer](http://nbviewer.jupyter.org/) by using the 'Save Notebook with Widgets' action from the Widgets menu in the notebook (see ipywidgets [documents](http://ipywidgets.readthedocs.io/en/latest/embedding.html#rendering-interactive-widgets-on-nbviewer)). This notebook is being rendered by nbviewer using the Github [repo](https://github.com/MaayanLab/clustergrammer-widget).
# 
# # Clustergrammer Web-app and Libraries
# The Clustergrammer project can also be used through:
# * a web application: http://amp.pharm.mssm.edu/clustergrammer/ 
# * and as JavaScript (front-end) and Python (back-end) libraries by developers: [clustergrammer.js](https://github.com/MaayanLab/clustergrammer) and [clustergrammer.py](https://github.com/MaayanLab/clustergrammer-py)