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

# ## Regulatory graph visualization with GINsim
# 
# GINsim models in GINML format contains layout information for displaying the regulatory graph of a Boolean or multi-valued network. The regulatory graph shows the activation and inhibition relations between the nodes of the network.
# 
# In this notebook, we show how to use the `ginsim` Python module to visualize a network model, with optionnaly a state.

# In[1]:


import ginsim


# First, we load a model from the GINsim repository:

# In[2]:


lrg = ginsim.load("http://ginsim.org/sites/default/files/SuppMat_Model_Master_Model.zginml")


# The regulatory graph can be visualized using the `ginsim.show` function:

# In[3]:


ginsim.show(lrg)


# The `show` function also allows an additional parameters which specifies for each node a state value (0 or 1 in case of a Boolean node).
# This state can also come from the result of a model analysis, for instance, a fixpoint analysis.
# 
# Let us use biolqm to compute the fixpoints of the model with bioLQM:

# In[4]:


import biolqm


# First, we convert the model to bioLQM:

# In[5]:


lqm = ginsim.to_biolqm(lrg)


# Then, we use `biolqm.fixpoints` to compute the list of all the fixpoints of the network, and store it in the `fps` variable:

# In[6]:


fps = biolqm.fixpoints(lqm)
print(len(fps), "fixpoints")


# The third fixpoint (`fps[2]`) can then be displayed as follows:

# In[7]:


ginsim.show(lrg, fps[2])


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