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

# ### `A` down-regulates `B` , by being the *limiting reagent* in reaction `A + 2 B <-> Y` (mostly forward)
# 1st-order kinetics.   
# If [A] is low and [B] is high, then [B] remains high.  If [A] goes high, [B] goes low.  However, at that point, A can no longer bring B up to any substantial extent.
# 
# Single-bin reaction
# 
# Based on experiment "reactions_single_compartment/down_regulate_2"
# 
# 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
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", "Y"])     # NOTE: Diffusion not applicable (just 1 bin)

# Reaction A + 2 B <-> Y , with 1st-order kinetics for all species
chem_data.add_reaction(reactants=[("A") , (2, "B")], products=[("Y")],
                       forward_rate=8., reverse_rate=2.)

chem_data.describe_reactions()

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


# In[5]:


bio = BioSim1D(n_bins=1, chem_data=chem_data)

bio.set_uniform_concentration(species_name="A", conc=5.)     # Scarce
bio.set_uniform_concentration(species_name="B", conc=100.)   # Plentiful
# Initially, no "Y" is present

bio.describe_state()


# In[6]:


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


# ### Take the initial system to equilibrium

# In[7]:


bio.react(time_step=0.0005, n_steps=30, snapshots={"frequency": 2, "sample_bin": 0})  # At every other step, take a snapshot 
                                                                                      # of all species at bin 0
bio.describe_state()
bio.get_history()


# A, as the scarse limiting reagent, stops the reaction.  
# When A is low, B is also low.

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

# In[8]:


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


# ## Plots of changes of concentration with time

# In[9]:


fig = px.line(data_frame=bio.get_history(), x="SYSTEM TIME", y=["A", "B", "Y"], 
              title="Changes in concentrations (reaction A + 2 B <-> Y)",
              color_discrete_sequence = ['red', 'blue', 'green'],
              labels={"value":"concentration", "variable":"Chemical"})
fig.show()


# # Now, let's suddenly increase [A]

# In[10]:


bio.set_bin_conc(bin_address=0, species_index=0, conc=40.)
bio.describe_state()


# In[11]:


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


# ### Again, take the system to equilibrium

# In[12]:


bio.react(time_step=0.0005, n_steps=80, snapshots={"frequency": 2, "sample_bin": 0})  # At every other step, take a snapshot 
                                                                                      # of all species at bin 0
bio.describe_state()
bio.get_history()


# In[13]:


# Verify that the reaction has reached equilibrium
bio.reaction_dynamics.is_in_equilibrium(conc=bio.bin_snapshot(bin_address = 0), tolerance=7)


# In[14]:


fig = px.line(data_frame=bio.get_history(), x="SYSTEM TIME", y=["A", "B", "Y"], 
              title="Changes in concentrations (reaction A + 2 B <-> Y)",
              color_discrete_sequence = ['red', 'blue', 'green'],
              labels={"value":"concentration", "variable":"Chemical"})
fig.show()


# **A**, still the limiting reagent, is again stopping the reaction.  
# The (transiently) high value of [A] led to a high value of [B]

# # Let's again suddenly increase [A]

# In[15]:


bio.set_bin_conc(bin_address=0, species_index=0, conc=30.)
bio.describe_state()


# In[16]:


# Save the state of the concentrations of all species at bin 0 (the only bin in this system)
bio.add_snapshot(bio.bin_snapshot(bin_address = 0))


# ### Yet again, take the system to equilibrium

# In[17]:


bio.react(time_step=0.0005, n_steps=70, snapshots={"frequency": 2, "sample_bin": 0})  # At every other step, take a snapshot 
                                                                                      # of all species at bin 0
bio.describe_state()
bio.get_history()


# In[18]:


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


# In[19]:


fig = px.line(data_frame=bio.get_history(), x="SYSTEM TIME", y=["A", "B", "Y"], 
              title="Changes in concentrations (reaction A + 2 B <-> Y)",
              color_discrete_sequence = ['red', 'blue', 'green'],
              labels={"value":"concentration", "variable":"Chemical"})
fig.show()


# **A**, again the scarse limiting reagent, stops the reaction yet again   
# 
# Note: A can down-regulate B, but it cannot bring it up.

# # For additional exploration, see the experiment "reactions_single_compartment/down_regulate_2"

# In[ ]: