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

# # Transient separation of 2 chemicals in 1D, due to their different diffusion rates
# 
# ### Starting with identical concentrations in one of the bins, they initially separate... 
# ### until they eventually attain identical concentrations at equilibrium   
# 
# For a complete separation by means of membranes, see experiment `membranes_3`

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

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LAST_REVISED = "Aug. 15, 2025"
LIFE123_VERSION = "1.0.0rc6"        # 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, PlotlyHelper, check_version


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check_version(LIFE123_VERSION)


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# ## Prepare the initial system
# with identical bin concentrations of the chemicals `A` and `B`, in the center bin.  
# `B` diffuses much faster than `A`

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chem_data = ChemData(names=["A", "B"], diffusion_rates=[0.1, 2.], plot_colors=["turquoise", "green"])

bio = BioSim1D(n_bins=9, chem_data=chem_data)


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bio.set_bin_conc(bin_address=4, chem_label="A", conc=10.)
bio.set_bin_conc(bin_address=4, chem_label="B", conc=10.)

bio.describe_state()


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bio.system_snapshot()


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bio.visualize_system(title_prefix="Diffusion.  The 2 concentrations initially perfectly overlap")   # Line curve view


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bio.system_heatmaps(title_prefix="Diffusion")


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# ## Request history-keeping for some bins

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# Request to save the concentration history at the bin with the initial concentration injection, 
# and at a couple of other bins
bio.enable_history(bins=[0, 2, 4], frequency=3, take_snapshot=True)    


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# ## Initial Diffusion Step

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# Advancing to time t=1, with moderate time steps
bio.diffuse(total_duration=1.0, fraction_max_step=0.4)


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bio.describe_state()


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# ## The 2 chemicals `A` and `B`, previously identical in concentrations, have separated due to their different diffusion rates  
# Notice how `B` has spread out far more than `A`

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bio.visualize_system(title_prefix="Diffusion")   # Line curve view


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bio.system_heatmaps(title_prefix="Diffusion")


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# ## Let's advance the diffusion

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bio.diffuse(total_duration=2.0, fraction_max_step=0.4)


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bio.describe_state()


# ## `B` is close to equilibrium, while `A` is nowhere near it!

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bio.visualize_system(title_prefix="Diffusion")   # Line curve view


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bio.system_heatmaps(title_prefix="Diffusion")


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# ## Let's advance the diffusion some more

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bio.diffuse(total_duration=2.0, fraction_max_step=0.4)


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bio.describe_state()


# ## Notice that the concentrations of `A` and `B` in the central bin 4 are again getting closer in value

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bio.visualize_system(title_prefix="Diffusion")   # Line curve view


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bio.system_heatmaps(title_prefix="Diffusion")


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# ## Finally, let's advance the diffusion to equilibrium

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bio.diffuse(total_duration=95.0, fraction_max_step=0.4)


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bio.describe_state()


# ## All bins now have essentially uniform concentration  
# ## Notice that the concentrations of `A` and `B` in the central bin 4 are again essentially identical; the separation of `A` and `B` is coming to an end

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bio.visualize_system(title_prefix="Diffusion")   # Line curve view


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bio.system_heatmaps(title_prefix="Diffusion")


# #### Verify that the total amount of each chemicals hasn't changed

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# Let's verify mass conservation
bio.check_mass_conservation(chem_label="A", expected=10.)


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bio.check_mass_conservation(chem_label="B", expected=10.)


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# ## Visualization of time changes at particular bins

# #### Instead of visualizing the entire system at a moment in time, like in the previous diagrams, let's now look at the time evolution of the concentrations of `A` and `B` at selected bins (bins whose history-keeping we requested prior to running the simulation)

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bin4_hist = bio.conc_history.bin_history(bin_address=4)   # The bin where the initial concentration of `A` and `B` was applied
bin4_hist


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bio.plot_history_single_bin(bin_address=4, title_prefix="`A` and `B` separate, until they finally rejoin")


# ## The transient separation of `A` and `B` is best seen by plotting the difference of their concentrations, as a function of time

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bin4_hist["A"] - bin4_hist["B"]


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PlotlyHelper.plot_curves(x=bin4_hist['SYSTEM TIME'], y = bin4_hist['A'] - bin4_hist['B'], 
                         x_label="SYSTEM TIME", y_label="[A] - [B]", 
                         colors="purple", title="Transient separation of `A` and `B`, as seen in central bin 4")


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# ## The transient separation of `A` and `B` is also seen in other bins...

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bio.plot_history_single_bin(bin_address=0, title_prefix="The transient separation of `A` and `B` happens at other bins, too...")


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bio.plot_history_single_bin(bin_address=2, title_prefix="The transient separation of `A` and `B` happens at other bins, too...")


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