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

# # Simulating Deletions

# In[1]:


import pandas
from time import time

import cobra.test
from cobra.flux_analysis import \
    single_gene_deletion, single_reaction_deletion, \
    double_gene_deletion, double_reaction_deletion

cobra_model = cobra.test.create_test_model("textbook")
ecoli_model = cobra.test.create_test_model("ecoli")


# ## Single Deletions

# Perform all single gene deletions on a model

# In[2]:


growth_rates, statuses = single_gene_deletion(cobra_model)


# These can also be done for only a subset of genes

# In[3]:


gr, st = single_gene_deletion(cobra_model,
                              cobra_model.genes[:20])
pandas.DataFrame.from_dict({"growth_rates": gr,
                            "status": st})


# This can also be done for reactions

# In[4]:


gr, st = single_reaction_deletion(cobra_model,
                                  cobra_model.reactions[:20])
pandas.DataFrame.from_dict({"growth_rates": gr,
                            "status": st}).round(4)


# ## Double Deletions
# 
# Double deletions run in a similar way. Passing in return_frame=True will cause them to format the results as a pandas Dataframe

# In[5]:


double_gene_deletion(cobra_model, cobra_model.genes[-5:],
                     return_frame=True).round(4)


# By default, the double deletion function will automatically use multiprocessing, splitting the task over up to 4 cores if they are available. The number of cores can be manually sepcified as well. Setting use of a single core will disable use of the multiprocessing library, which often aids debuggging.

# In[6]:


start = time()  # start timer()
double_gene_deletion(ecoli_model, ecoli_model.genes[:300],
                     number_of_processes=2)
t1 = time() - start
print("Double gene deletions for 200 genes completed in "
      "%.2f sec with 2 cores" % t1)

start = time()  # start timer()
double_gene_deletion(ecoli_model, ecoli_model.genes[:300],
                     number_of_processes=1)
t2 = time() - start
print("Double gene deletions for 200 genes completed in "
      "%.2f sec with 1 core" % t2)

print("Speedup of %.2fx" % (t2 / t1))


# Double deletions can also be run for reactions

# In[7]:


double_reaction_deletion(cobra_model,
                         cobra_model.reactions[2:7],
                         return_frame=True).round(4)