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

# # Diffusion of 2 chemicals
# 
# ### Identical to experiment `diffusion_2_a` EXCEPT for some extra rows of bins at the top of the system (high y-bin values), which breaks the previously-perfect symmetry of the 2 chemicals: now, one of them (`A`) is more "hemmed in by the walls", compared to the other one

# ### TAGS :  "diffusion 2D", "basic"

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LAST_REVISED = "Jan. 20, 2025"
LIFE123_VERSION = "1.0.0rc2"        # 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 BioSim2D, ChemData, check_version


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check_version(LIFE123_VERSION)


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# Prepare the initial system, with two concentration pulses, at almost-opposite ends of the system, with the same diffusion rate coefficient
chem_data = ChemData(names=["A", "B"], diffusion_rates=[0.05, 0.05])

bio = BioSim2D(x_bins=7, y_bins=10, chem_data=chem_data)  # 3 more rows, compared to experiment `diffusion_2_a` 

bio.set_bin_conc(bin_address = (1,1), chem_label="A", conc=10.)
bio.set_bin_conc(bin_address = (5,5), chem_label="B", conc=10.)


# ### Different ways to visualize the system   
# Notice the bin with the initial concentration of `A` and the other bin with the initial concentration of `B`

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bio.describe_state()


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bio.system_snapshot(chem_label="A")


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bio.system_snapshot(chem_label="B")


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bio.system_heatmaps()


# Notice that the bins with the initial concentration pulses lie on a diagonal from each other, but one is closer to the system "walls"

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# ## Request history-keeping for some bins

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# Request to save the concentration history of all chemicals at selected bins 
bio.enable_history(bins=[(1,1), (3,3), (1,6)], frequency=5, take_snapshot=True)    # Taking a snapshot to include the current initial state in the history


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# # Initial Diffusion Step

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delta_time = 2.5


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status = bio.diffuse(total_duration=delta_time, time_step=0.1)
print("\n", status)

bio.system_heatmaps(title_prefix="Diffusion")


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# MASS-CONSERVATION CHECK. Verify that that sum of all the entries in each of the above matrices is still the initial 10.
bio.check_mass_conservation(chem_label="A", expected=10.) \
and \
bio.check_mass_conservation(chem_label="B", expected=10.)


# # A second step

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status = bio.diffuse(total_duration=delta_time, time_step=0.1)
print("\n", status)

bio.system_heatmaps(title_prefix="Diffusion")


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# ## This is still an early stage in the diffusion process; let's advance it more... (Visualization from results shown at selected times)

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for i in range(300):
    status = bio.diffuse(total_duration=delta_time, time_step=0.2)

    if i==3 or i==20 or i==50 or i==100 or i==299:
        fig = bio.system_heatmaps(title_prefix="Diffusion")
        fig.show()


# # All bins now have essentially uniform concentration. The diffusion has reached equilibrium
# 
# Notice how `B`, further away from walls compared to `A`, has an opportunity to spread out more quickly, in spite of the same diffusion rate coefficient

# **Mass conservations**: the initial "10. units of concentration" are now uniformly spread across the 70 (7x10) bins, leading to a near-constant concentration of 10./60

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10./70


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# Mass conservation for both `A` and `B` can also be verified as follows:
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 concentration changes with time at particular bins

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bio.plot_history_single_bin(bin_address=(1,1))    # The bin with the initial pulse of `A`


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bio.plot_history_single_bin(bin_address=(3,3))    # The bin halfway between the initial pulses of `A` and `B`


# Even thought bin (3,3) is exactly halfway between the bins with the initial pulses of `A` and `B`, **an asymmetry develops** because `A` is more "hemmed in by walls", and has fewer directions to spread out, including towards (3,3), while `B` also dilutes away towards the top (high y-bin values) of the system.  Thus `A` arrives more quickly.  
# (Compare to the perfect overlap in experiment `diffusion_2_a`) 

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bio.plot_history_single_bin(bin_address=((1, 6))) # Distance from (1,1), with the initial pulse of `A`, is 5;  
                                                  # distance from (5,5), with the initial pulse of `B`, is 4.12


# `B` arrives more quickly at this bin, until `A` eventually catches up

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