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

# ### A simple `A <-> B` reaction between 2 species with initial uniform concentrations across 3 bins,
# with 1st-order kinetics in both directions, taken to equilibrium
# 
# Diffusion NOT taken into account
# 
# See also the experiment _"reactions_single_compartment/react_1"_ 
# 
# LAST REVISED: June 4, 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.reactions.reaction_data import ChemData as chem
from src.modules.reactions.reaction_dynamics import ReactionDynamics
from src.life_1D.bio_sim_1d import BioSim1D

import plotly.express as px
from src.modules.html_log.html_log import HtmlLog as log
from src.modules.visualization.graphic_log import GraphicLog


# In[3]:


# Initialize the HTML logging (for the graphics)
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")


# # Initialize the System

# In[4]:


# Initialize the system
chem_data = chem(names=["A", "B"])              # Diffusion NOT taken into account
bio = BioSim1D(n_bins=3, chem_data=chem_data)   # We'll specify the reactions later

bio.set_uniform_concentration(species_name="A", conc=10.)
bio.set_uniform_concentration(species_name="B", conc=50.)

bio.describe_state()


# In[5]:


# Save the state of the concentrations of all species at bin 0
bio.add_snapshot(bio.bin_snapshot(bin_address = 0), caption="Initial state")


# In[6]:


bio.get_history()


# In[7]:


# Specify the reaction

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

print("Number of reactions: ", chem_data.number_of_reactions())


# In[8]:


chem_data.describe_reactions()


# In[9]:


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


# ### <a name="sec_1"></a>First step

# In[10]:


# First step of reaction
bio.react(time_step=0.1, n_steps=1)
bio.describe_state()


# NOTE: the concentration of species A is increasing, while that of species B is decreasing.
# All bins have identical concentrations; so, there's no diffusion (and we're not attempting to compute it):  
# [[17. 17. 17.]  
#  [43. 43. 43.]]

# In[11]:


# Save the state of the concentrations of all species at bin 0
bio.add_snapshot(bio.bin_snapshot(bin_address = 0))
bio.get_history()


# ### <a name="sec_more_steps"></a>Numerous more steps

# In[12]:


# Numerous more steps
bio.react(time_step=0.1, n_steps=10, snapshots={"sample_bin": 0})

bio.describe_state()


# ### <a name="sec_equilibrium"></a>Equilibrium

# NOTE: Consistent with the 3/2 ratio of forward/reverse rates (and the 1st order reactions),
#  the systems settles in the following equilibrium:
# 
# [A] = 23.99316406
#  
# [B] = 36.00683594
# 

# In[13]:


bio.bin_snapshot(bin_address = 0)


# In[14]:


# Verify that the reaction has reached equilibrium
bio.reaction_dynamics.is_in_equilibrium(conc=bio.bin_snapshot(bin_address = 0))


# In[15]:


# Save the state of the concentrations of all species at bin 0
#bio.save_snapshot(bio.bin_snapshot(bin_address = 0))
bio.get_history()


# ## Plots of changes of concentration with time

# In[16]:


fig = px.line(data_frame=bio.get_history(), x="SYSTEM TIME", y=["A", "B"], 
              title="Changes in concentrations with time",
              color_discrete_sequence = ['navy', 'darkorange'],
              labels={"value":"concentration", "variable":"Chemical"})
fig.show()


# In[17]:


# Same plot, but with a smoothed line
fig = px.line(data_frame=bio.get_history(), x="SYSTEM TIME", y=["A", "B"], 
              title="Changes in concentrations with time (smoothed)",
              color_discrete_sequence = ['navy', 'darkorange'],
              labels={"value":"concentration", "variable":"Chemical"},
              line_shape="spline")
fig.show()


# ## For more in-depth analysis of this reaction, see the experiment _"reactions_single_compartment/react_1"_ 

# In[ ]: