{ "cells": [ { "cell_type": "markdown", "id": "49bcb5b0-f19d-4b96-a5f1-e0ae30f66d8f", "metadata": {}, "source": [ "### A simple `A <-> B` reaction between 2 species with initial uniform concentrations across 3 bins,\n", "with 1st-order kinetics in both directions, taken to equilibrium\n", "\n", "Diffusion NOT taken into account\n", "\n", "See also the experiment _\"reactions_single_compartment/react_1\"_ \n", "\n", "LAST REVISED: May 6, 2024" ] }, { "cell_type": "code", "execution_count": 1, "id": "7245be7a-c9db-45f5-b033-d6c521237a9c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Added 'D:\\Docs\\- MY CODE\\BioSimulations\\life123-Win7' to sys.path\n" ] } ], "source": [ "import set_path # Importing this module will add the project's home directory to sys.path" ] }, { "cell_type": "code", "execution_count": 2, "id": "3cddd49a", "metadata": { "tags": [] }, "outputs": [], "source": [ "from experiments.get_notebook_info import get_notebook_basename\n", "\n", "from src.modules.chemicals.chem_data import ChemData as chem\n", "from src.life_1D.bio_sim_1d import BioSim1D\n", "\n", "import plotly.express as px\n", "from src.modules.visualization.graphic_log import GraphicLog" ] }, { "cell_type": "code", "execution_count": 3, "id": "cc53849f-351d-49e0-bfa8-22f8d8e22f8e", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> Output will be LOGGED into the file 'reaction_1.log.htm'\n" ] } ], "source": [ "# Initialize the HTML logging (for the graphics)\n", "log_file = get_notebook_basename() + \".log.htm\" # Use the notebook base filename for the log file\n", "\n", "# Set up the use of some specified graphic (Vue) components\n", "GraphicLog.config(filename=log_file,\n", " components=[\"vue_cytoscape_2\"],\n", " extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")" ] }, { "cell_type": "markdown", "id": "8af818bc-9bac-4ec7-9672-b76223876595", "metadata": {}, "source": [ "# Initialize the System" ] }, { "cell_type": "code", "execution_count": 4, "id": "de47e1df-67cf-4200-a580-fbcf50ebd1c0", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0:\n", "3 bins and 2 species:\n", " Species 0 (A). Diff rate: None. Conc: [10. 10. 10.]\n", " Species 1 (B). Diff rate: None. Conc: [50. 50. 50.]\n" ] } ], "source": [ "# Initialize the system\n", "chem_data = chem(names=[\"A\", \"B\"]) # Diffusion NOT taken into account\n", "bio = BioSim1D(n_bins=3, chem_data=chem_data) # We'll specify the reactions later\n", "\n", "bio.set_uniform_concentration(species_name=\"A\", conc=10.)\n", "bio.set_uniform_concentration(species_name=\"B\", conc=50.)\n", "\n", "bio.describe_state()" ] }, { "cell_type": "code", "execution_count": 5, "id": "5562fea2-834e-40a9-9b1d-5ea28a0100bf", "metadata": {}, "outputs": [], "source": [ "# Save the state of the concentrations of all species at bin 0\n", "bio.add_snapshot(bio.bin_snapshot(bin_address = 0), caption=\"Initial state\")" ] }, { "cell_type": "code", "execution_count": 6, "id": "3d22b349-c063-4c2d-9cde-ebd87bda6901", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
SYSTEM TIMEABcaption
0010.050.0Initial state
\n", "
" ], "text/plain": [ " SYSTEM TIME A B caption\n", "0 0 10.0 50.0 Initial state" ] }, "execution_count": 6, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bio.get_history()" ] }, { "cell_type": "code", "execution_count": 7, "id": "25155c63-e53c-41e1-be1e-41577158a4ca", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 1\n" ] } ], "source": [ "# Specify the reaction\n", "\n", "# Reaction A <-> B , with 1st-order kinetics in both directions\n", "chem_data.add_reaction(reactants=[\"A\"], products=[\"B\"], forward_rate=3., reverse_rate=2.)\n", "\n", "print(\"Number of reactions: \", chem_data.number_of_reactions())" ] }, { "cell_type": "code", "execution_count": 8, "id": "16396b37-96ce-4b6d-a415-dc8f72b04559", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 1 (at temp. 25 C)\n", "0: A <-> B (kF = 3 / kR = 2 / delta_G = -1,005.1 / K = 1.5) | 1st order in all reactants & products\n", "Set of chemicals involved in the above reactions: {'B', 'A'}\n" ] } ], "source": [ "chem_data.describe_reactions()" ] }, { "cell_type": "code", "execution_count": 9, "id": "00a39103-a470-490a-8165-bd58c6f70fb6", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[GRAPHIC ELEMENT SENT TO LOG FILE `reaction_1.log.htm`]\n" ] } ], "source": [ "# Send a plot of the network of reactions to the HTML log file\n", "chem_data.plot_reaction_network(\"vue_cytoscape_2\")" ] }, { "cell_type": "markdown", "id": "0b46b395-3f68-4dbd-b0c5-d67a0e623726", "metadata": { "tags": [] }, "source": [ "### First step" ] }, { "cell_type": "code", "execution_count": 10, "id": "bcf652b8-e0dc-438e-bdbe-02216c1d52a0", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0.1:\n", "3 bins and 2 species:\n", " Species 0 (A). Diff rate: None. Conc: [17. 17. 17.]\n", " Species 1 (B). Diff rate: None. Conc: [43. 43. 43.]\n" ] } ], "source": [ "# First step of reaction\n", "bio.react(time_step=0.1, n_steps=1)\n", "bio.describe_state()" ] }, { "cell_type": "markdown", "id": "7dc56592-179d-4e4c-b75a-8eb81dcafe71", "metadata": {}, "source": [ "NOTE: the concentration of species A is increasing, while that of species B is decreasing.\n", "All bins have identical concentrations; so, there's no diffusion (and we're not attempting to compute it): \n", "[[17. 17. 17.] \n", " [43. 43. 43.]]" ] }, { "cell_type": "code", "execution_count": 11, "id": "54ee2411-de4e-4895-91a9-dfb4cab743ec", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
SYSTEM TIMEABcaption
00.010.050.0Initial state
10.117.043.0
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" ], "text/plain": [ " SYSTEM TIME A B caption\n", "0 0.0 10.0 50.0 Initial state\n", "1 0.1 17.0 43.0 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Save the state of the concentrations of all species at bin 0\n", "bio.add_snapshot(bio.bin_snapshot(bin_address = 0))\n", "bio.get_history()" ] }, { "cell_type": "markdown", "id": "82a62165-425d-4e8d-abac-01d579dfd1ae", "metadata": {}, "source": [ "### Numerous more steps" ] }, { "cell_type": "code", "execution_count": 12, "id": "cf6a7337-8e2e-4c02-9bb3-85052f37144f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 1.1:\n", "3 bins and 2 species:\n", " Species 0 (A). Diff rate: None. Conc: [23.99316406 23.99316406 23.99316406]\n", " Species 1 (B). Diff rate: None. Conc: [36.00683594 36.00683594 36.00683594]\n" ] } ], "source": [ "# Numerous more steps\n", "bio.react(time_step=0.1, n_steps=10, snapshots={\"sample_bin\": 0})\n", "\n", "bio.describe_state()" ] }, { "cell_type": "markdown", "id": "962acf15-3b50-40e4-9daa-3dcca7d3291a", "metadata": {}, "source": [ "### Equilibrium" ] }, { "cell_type": "markdown", "id": "809b4afa-fb2f-4ac3-92c9-083fc487c81b", "metadata": {}, "source": [ "NOTE: Consistent with the 3/2 ratio of forward/reverse rates (and the 1st order reactions),\n", " the systems settles in the following equilibrium:\n", "\n", "[A] = 23.99316406\n", " \n", "[B] = 36.00683594\n" ] }, { "cell_type": "code", "execution_count": 13, "id": "490fdc0f-fa2a-48d8-ae04-7c80d298842a", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "{'A': 23.9931640625, 'B': 36.0068359375}" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "bio.bin_snapshot(bin_address = 0)" ] }, { "cell_type": "code", "execution_count": 14, "id": "f22258b2-5181-4ff9-b379-f6a12ad5c8fb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0: A <-> B\n", "Final concentrations: [A] = 23.99 ; [B] = 36.01\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 1.50071\n", " Formula used: [B] / [A]\n", "2. Ratio of forward/reverse reaction rates: 1.5\n", "Discrepancy between the two values: 0.04749 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Verify that the reaction has reached equilibrium\n", "bio.reaction_dynamics.is_in_equilibrium(conc=bio.bin_snapshot(bin_address = 0))" ] }, { "cell_type": "code", "execution_count": 15, "id": "382e3253-045e-40a5-beab-c1c6e8608334", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " SYSTEM TIME A B caption\n", "0 0.0 10.000000 50.000000 Initial state\n", "1 0.1 17.000000 43.000000 \n", "2 0.2 20.500000 39.500000 \n", "3 0.3 22.250000 37.750000 \n", "4 0.4 23.125000 36.875000 \n", "5 0.5 23.562500 36.437500 \n", "6 0.6 23.781250 36.218750 \n", "7 0.7 23.890625 36.109375 \n", "8 0.8 23.945312 36.054688 \n", "9 0.9 23.972656 36.027344 \n", "10 1.0 23.986328 36.013672 \n", "11 1.1 23.993164 36.006836 " ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Save the state of the concentrations of all species at bin 0\n", "#bio.save_snapshot(bio.bin_snapshot(bin_address = 0))\n", "bio.get_history()" ] }, { "cell_type": "markdown", "id": "cbf6c9c7-8cec-400f-9e70-49ff1a9f485c", "metadata": { "tags": [] }, "source": [ "## Plots of changes of concentration with time" ] }, { "cell_type": "code", "execution_count": 16, "id": "665dfff9-e943-44e1-b76d-af363d94c9f8", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Chemical=A
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}, "ternary": { "aaxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "baxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" }, "bgcolor": "#E5ECF6", "caxis": { "gridcolor": "white", "linecolor": "white", "ticks": "" } }, "title": { "x": 0.05 }, "xaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 }, "yaxis": { "automargin": true, "gridcolor": "white", "linecolor": "white", "ticks": "", "title": { "standoff": 15 }, "zerolinecolor": "white", "zerolinewidth": 2 } } }, "title": { "text": "Changes in concentrations with time" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ 0, 1.0999999999999999 ], "title": { "text": "SYSTEM TIME" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 7.777777777777778, 52.22222222222222 ], "title": { "text": "concentration" }, "type": "linear" } } 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Same plot, but with a smoothed line\n", "fig = px.line(data_frame=bio.get_history(), x=\"SYSTEM TIME\", y=[\"A\", \"B\"], \n", " title=\"Changes in concentrations with time (smoothed)\",\n", " color_discrete_sequence = ['navy', 'darkorange'],\n", " labels={\"value\":\"concentration\", \"variable\":\"Chemical\"},\n", " line_shape=\"spline\")\n", "fig.show()" ] }, { "cell_type": "markdown", "id": "37879680-50e8-4564-a872-a1f94cedfd22", "metadata": {}, "source": [ "## For more in-depth analysis of this reaction, see the experiment _\"reactions_single_compartment/react_1\"_ " ] }, { "cell_type": "code", "execution_count": null, "id": "da56d751", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "jupytext": { "formats": "ipynb,py:percent" }, "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }