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

# ## `A <-> B` reaction, with 1st-order kinetics in both directions,
# ### taken to equilibrium
# 
# Diffusion not done
# 
# LAST REVISED: July 14, 2023

# In[1]:


import set_path      # Importing this module will add the project's home directory to sys.path


# In[2]:


from experiments.get_notebook_info import get_notebook_basename

from src.modules.chemicals.chem_data import ChemData as chem
from src.life_2D.bio_sim_2d import BioSim2D

from src.modules.visualization.graphic_log import GraphicLog


# In[3]:


# Initialize the HTML logging
log_file = get_notebook_basename() + ".log.htm"    # Use the notebook base filename for the log file
# Set up the use of some specified graphic (Vue) components
GraphicLog.config(filename=log_file,
                  components=["vue_cytoscape_1"],
                  extra_js="https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js")


# In[4]:


# Initialize the system
chem_data = chem(names=["A", "B"])     # NOTE: Diffusion not done



# Reaction A <-> B , with 1st-order kinetics in both directions
chem_data.add_reaction(reactants=["A"], products=["B"], forward_rate=3., reverse_rate=2.)

bio = BioSim2D(n_bins=(3,4), chem_data=chem_data)

bio.set_bin_conc_all_species(bin_x=0, bin_y=0, conc_list=[10.,50.])
bio.set_bin_conc_all_species(bin_x=0, bin_y=1, conc_list=[20.,35.])
bio.set_bin_conc_all_species(bin_x=2, bin_y=3, conc_list=[5.,100.])

bio.describe_state()


# In[5]:


chem_data.describe_reactions()


# In[6]:


# Send the plot to the HTML log file
graph_data = chem_data.prepare_graph_network()
GraphicLog.export_plot(graph_data, "vue_cytoscape_1")


# ## First step

# In[7]:


# First step (NOTE: here we're using a lower-level function that doesn't update the system state;
#                   it only computes the delta_reactions array)
bio.reaction_step(delta_time=0.1)
print("bio.delta_reactions:\n", bio.delta_reactions)


# In[8]:


bio.system += bio.delta_reactions       # Matrix operation to update all the concentrations
bio.system_time += 0.1

bio.describe_state()


# ## Second step

# In[9]:


# NOTE: now, we're using a highel-level function that also updates the system state
bio.react(time_step=0.1, n_steps=1)
bio.describe_state()


# ## Many more steps, to equilibrium

# In[10]:


bio.react(time_step=0.1, n_steps=8)
bio.describe_state()


# In[11]:


bio.react(time_step=0.1, n_steps=10)
bio.describe_state()


# ### The system has now reached equilibrium
# ### in individual bins, which remain separate because we're NOT doing diffusion in this experiment

# Verify the equilibrium in each of the active bins

# In[12]:


bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc={"A": 23.99998665, "B": 36.00001335})


# In[13]:


bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc={"A": 21.99999809, "B": 33.00000191})


# In[14]:


bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc={"A": 41.99996471, "B": 63.00003529}, explain=False)


# In[ ]: