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

# In[1]:


import networkx
import math
import scipy.optimize
import numpy
from lib.time_graph import *
from lib.vis import *
from lib.syn import *
from lib.experiments import *
from IPython.display import Image


# # Size Graph

# In[4]:


algos = [TemporalCuts("FSTC-16", "fast-sparse", eps=1e-5, k=16), 
             TemporalCuts("FSTC-64", "fast-sparse", eps=1e-5, k=64), 
             TemporalCuts("STC", "diff-sparse", eps=1e-5), 
             TemporalCuts("LAP", "laplacian-sparse"),
             TemporalCuts("UNION", "union-sparse"), 
             TemporalCuts("SINGLE", "indep-sparse")]

size = [1000, 1500, 2000, 2500]

res = size_experiments(algos, size, True, n=10)


# In[4]:


res


# In[5]:


output_file_name = "figs/syn_size_slide.png"
plot_size_experiments(res, algos, size, output_file_name, 0, 500, 2000)
Image(filename=output_file_name)


# In[2]:


algos = [TemporalCuts("FSTC-16", "fast-norm", eps=1e-5, k=16), 
             TemporalCuts("FSTC-64", "fast-norm", eps=1e-5, k=64), 
             TemporalCuts("STC", "diff-norm", eps=1e-5), 
             TemporalCuts("LAP", "laplacian-norm"),
             TemporalCuts("UNION", "union-norm"), 
             TemporalCuts("SINGLE", "indep-norm")]

size = [1000, 1500, 2000, 2500]

res = size_experiments(algos, size, True, n=10)


# In[3]:


output_file_name = "figs/syn_norm_size_slide.png"
plot_size_experiments(res, algos, size, output_file_name, 0, 500, 2000)
Image(filename=output_file_name)


# # Density

# In[ ]:


algos = [TemporalCuts("FSTC-16", "fast-sparse", eps=1e-5, k=16), 
             TemporalCuts("FSTC-64", "fast-sparse", eps=1e-5, k=64), 
             TemporalCuts("STC", "diff-sparse", eps=1e-5), 
             TemporalCuts("LAP", "laplacian-sparse"),
             TemporalCuts("UNION", "union-sparse"), 
             TemporalCuts("SINGLE", "indep-sparse")]

hop = [1, 2, 3, 4]

res = hop_experiments(algos, hop, True, 10)


# In[ ]:


output_file_name = "figs/syn_hop_slide.png"
plot_hop_experiments(res, algos, hop, output_file_name, 0, 500, 1000)
Image(filename=output_file_name)


# In[ ]:


algos = [TemporalCuts("FSTC-16", "fast-norm", eps=1e-5, k=16), 
             TemporalCuts("FSTC-64", "fast-norm", eps=1e-5, k=64), 
             TemporalCuts("STC", "diff-norm", eps=1e-5), 
             TemporalCuts("LAP", "laplacian-norm"),
             TemporalCuts("UNION", "union-norm"), 
             TemporalCuts("SINGLE", "indep-norm")]

hop = [1, 2, 3, 4]

res = hop_experiments(algos, hop, True, 10)


# In[ ]:


output_file_name = "figs/syn_norm_hop_slide.png"
plot_hop_experiments(res, algos, hop, output_file_name, 0, 500, 2000)
Image(filename=output_file_name)


# # Snapshots

# In[2]:


algos = [TemporalCuts("FSTC-10", "fast-sparse", eps=1e-5, k=10), 
             TemporalCuts("FSTC-50", "fast-sparse", eps=1e-5, k=50), 
             TemporalCuts("STC", "diff-sparse", eps=1e-5), 
             TemporalCuts("LAP", "laplacian-sparse"),
             TemporalCuts("UNION", "union-sparse"), 
             TemporalCuts("SINGLE", "indep-sparse")]

n_snaps = [5, 10, 15, 20]

res = num_snaps_experiments(algos, n_snaps, True, 10)


# In[4]:


output_file_name = "figs/syn_num_snaps_slide.png"
plot_num_snaps_experiments(res, algos, n_snaps, output_file_name, 0, 500, 2000)
Image(filename=output_file_name)


# # Rank

# In[ ]:


output_file_name = "figs/syn_norm_rank_time_slide.png"
plot_rank_time_experiments(res, rank, output_file_name)
Image(filename=output_file_name)


# In[ ]:


output_file_name = "figs/syn_norm_rank_time_slide.png"
plot_rank_time_experiments(res, rank, output_file_name)
Image(filename=output_file_name)