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

# ## Exploring reaching equilibrium, first on a shorter timescale and then a longer one 
# ### (but both with identical time steps.)
# 
# The system starts out with a "concentration pulse" in bin 2 (the 3rd bin from the left) - i.e. that bin is initially the only one with a non-zero concentration of the only chemical species.
# 
# Notice the diffusing pulse "bouncing" off the left wall after total time 30.
# 
# Then the system is left undisturbed, and followed to equilibrium.

# ### TAGS :  "diffusion 1D", "basic"

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LAST_REVISED = "May 2, 2025"
LIFE123_VERSION = "1.0.0rc3"       # Library version this experiment is based on


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#import set_path                    # Using MyBinder?  Uncomment this before running the next cell!


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#import sys
#sys.path.append("C:/some_path/my_env_or_install")   # CHANGE to the folder containing your venv or libraries installation!
# NOTE: If any of the imports below can't find a module, uncomment the lines above, or try:  import set_path   

from life123 import BioSim1D, ChemData, check_version


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check_version(LIFE123_VERSION)


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chem_data = ChemData(diffusion_rates=0.1)
bio = BioSim1D(n_bins=10, chem_data=chem_data)

bio.set_uniform_concentration(chem_index=0, conc=0.)
bio.inject_conc_to_bin(chem_index=0, bin_address=2, delta_conc=10.)

bio.describe_state()


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print("\n\nSTARTING on SHORTER time scales.  Dtime=10, with time steps of 0.1 ...")


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for i in range(10):
    delta_time = 10.
    status = bio.diffuse(total_duration=delta_time, time_step=0.1)
    print(f"\nAfter Delta time {delta_time}.  ({status['steps']} steps taken):")
    bio.describe_state(concise=True)


# *Notice the diffusing pulse "bounces" off the left wall after total time 30:*  
# the concentration at cell 0 increases from t=0 to 30, and then it's coming down by t=40

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print("\n\nREPEATING to LONGER time scales.  Dtime=100, again with time steps of 0.1 ...")

# Reset the concentrations
bio.set_uniform_concentration(chem_index=0, conc=0.)
bio.inject_conc_to_bin(chem_index=0, bin_address=2, delta_conc=10.)

#total_time = 0.
for i in range(20):
    delta_time = 100.
    status = bio.diffuse(total_duration=delta_time, time_step=0.1)
    print(f"\nAfter Delta time {delta_time}.  ({status['steps']} steps taken):")
    bio.describe_state(concise=True)


# ## The system has now reached equilibrium

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