{
"cells": [
{
"cell_type": "markdown",
"id": "4e50d971",
"metadata": {},
"source": [
"### One-bin A <-> 3B reaction, taken to equilibrium. \n",
"#### A hypothetical scenario with 1st-order kinetics in both directions. \n",
"### Examine State Space trajectory, using [A] and [B] as state variables\n",
"\n",
"Based on experiment `1D/reaction/reaction_2`\n",
"\n",
"Diffusion not applicable (just 1 bin).\n",
"\n",
"This is the 1D version of the single-compartment reaction by the same name."
]
},
{
"cell_type": "markdown",
"id": "98206a01-1439-4e2f-9e05-5c814463d42c",
"metadata": {},
"source": [
"### TAGS : \"reactions 1D\""
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "afa628e5-55b1-4c9d-9846-86fd15735cf8",
"metadata": {},
"outputs": [],
"source": [
"LAST_REVISED = \"Dec. 16, 2024\"\n",
"LIFE123_VERSION = \"1.0-rc.1\" # Library version this experiment is based on"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "5af4024c-86c0-4006-9a41-259ff3906c35",
"metadata": {},
"outputs": [],
"source": [
"#import set_path # Using MyBinder? Uncomment this before running the next cell!"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e49a243f",
"metadata": {},
"outputs": [],
"source": [
"#import sys\n",
"#sys.path.append(\"C:/some_path/my_env_or_install\") # CHANGE to the folder containing your venv or libraries installation!\n",
"# NOTE: If any of the imports below can't find a module, uncomment the lines above, or try: import set_path \n",
"\n",
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from life123 import UniformCompartment, BioSim1D\n",
"\n",
"import plotly.express as px\n",
"import plotly.graph_objects as go\n",
"from life123 import GraphicLog"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "180bfbdd",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-> Output will be LOGGED into the file 'state_space_1.log.htm'\n"
]
}
],
"source": [
"# Initialize the HTML logging\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": "code",
"execution_count": 5,
"id": "863bfb96-f23d-4161-89e7-6c90e645e861",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 1 (at temp. 25 C)\n",
"0: A <-> 3 B (kF = 5 / kR = 2 / delta_G = -2,271.4 / K = 2.5) | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions: {'A', 'B'}\n"
]
}
],
"source": [
"# Initialize the system. NOTE: Diffusion not applicable (just 1 bin)\n",
"uc = UniformCompartment(names=[\"A\", \"B\"])\n",
"\n",
"\n",
"# Reaction A <-> 3B , with 1st-order kinetics in both directions\n",
"uc.add_reaction(reactants=\"A\", products=[(3,\"B\",1)], forward_rate=5., reverse_rate=2.)\n",
"\n",
"uc.describe_reactions()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "85cd752b-363f-4c59-b175-7118a2d81591",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"1 bins and 2 species:\n",
" Species 0 (A). Diff rate: None. Conc: [10.]\n",
" Species 1 (B). Diff rate: None. Conc: [50.]\n"
]
}
],
"source": [
"bio = BioSim1D(n_bins=1, reaction_handler=uc)\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": 7,
"id": "3f53fbc7",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0 | \n",
" 10.0 | \n",
" 50.0 | \n",
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\n",
" \n",
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\n",
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"
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"text/plain": [
" SYSTEM TIME A B caption\n",
"0 0 10.0 50.0 "
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},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
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],
"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": "code",
"execution_count": 8,
"id": "4b5e75e5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[GRAPHIC ELEMENT SENT TO LOG FILE `state_space_1.log.htm`]\n"
]
}
],
"source": [
"# Send the plot to the HTML log file\n",
"uc.plot_reaction_network(\"vue_cytoscape_2\")"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f393bdf3-1b5b-4d41-a541-54e71b8fa971",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "dfb4e9e3",
"metadata": {
"tags": []
},
"source": [
"### To equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "b2500732",
"metadata": {},
"outputs": [],
"source": [
"# Using smaller steps that in experiment reaction_2, to avoid the initial overshooting\n",
"bio.react(time_step=0.05, n_steps=10, snapshots={\"frequency\": 1, \"sample_bin\": 0})"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "c995c50f-4b3e-41b8-bf06-e6d64f028dfe",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.5:\n",
"1 bins and 2 species:\n",
" Species 0 (A). Diff rate: None. Conc: [14.54390679]\n",
" Species 1 (B). Diff rate: None. Conc: [36.36827963]\n"
]
}
],
"source": [
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "494466ba-f534-44c0-a65b-b4976340017a",
"metadata": {},
"outputs": [
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\n",
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" 12.500000 | \n",
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\n",
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" 13.625000 | \n",
" 39.125000 | \n",
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\n",
" \n",
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" 0.15 | \n",
" 14.131250 | \n",
" 37.606250 | \n",
" | \n",
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\n",
" \n",
" | 4 | \n",
" 0.20 | \n",
" 14.359063 | \n",
" 36.922812 | \n",
" | \n",
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\n",
" \n",
" | 5 | \n",
" 0.25 | \n",
" 14.461578 | \n",
" 36.615266 | \n",
" | \n",
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\n",
" \n",
" | 6 | \n",
" 0.30 | \n",
" 14.507710 | \n",
" 36.476870 | \n",
" | \n",
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\n",
" \n",
" | 7 | \n",
" 0.35 | \n",
" 14.528470 | \n",
" 36.414591 | \n",
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" \n",
" | 8 | \n",
" 0.40 | \n",
" 14.537811 | \n",
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" 0.45 | \n",
" 14.542015 | \n",
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\n",
" \n",
" | 10 | \n",
" 0.50 | \n",
" 14.543907 | \n",
" 36.368280 | \n",
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"text/plain": [
" SYSTEM TIME A B caption\n",
"0 0.00 10.000000 50.000000 \n",
"1 0.05 12.500000 42.500000 \n",
"2 0.10 13.625000 39.125000 \n",
"3 0.15 14.131250 37.606250 \n",
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"7 0.35 14.528470 36.414591 \n",
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"9 0.45 14.542015 36.373955 \n",
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},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.get_history()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "d168a44c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A <-> 3 B\n",
"Final concentrations: [A] = 14.54 ; [B] = 36.37\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 2.50059\n",
" Formula used: [B] / [A]\n",
"2. Ratio of forward/reverse reaction rates: 2.5\n",
"Discrepancy between the two values: 0.02341 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
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],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"bio.reaction_dynamics.is_in_equilibrium(rxn_index=0, conc=bio.bin_snapshot(bin_address = 0))"
]
},
{
"cell_type": "markdown",
"id": "3f5fd10b",
"metadata": {
"tags": []
},
"source": [
"# Plots of changes of concentration with time"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "0832782c",
"metadata": {},
"outputs": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"df = bio.get_history()\n",
"\n",
"px.line(data_frame=df, x=\"SYSTEM TIME\", y=[\"A\", \"B\"], \n",
" title=\"Reaction A <-> 3B . Changes in [A] and [B] over time\",\n",
" color_discrete_sequence = ['darkturquoise', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c4e0120d-1541-4552-a2d0-8100a3fea8d9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "e647f76c-4503-48be-b96a-22e81c9fadc5",
"metadata": {},
"source": [
"## Same data, but shown differently"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "85b3c06f",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "A=%{x}
B=%{y}",
"legendgroup": "",
"line": {
"color": "#C83778",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "",
"orientation": "v",
"showlegend": false,
"type": "scatter",
"x": [
10,
12.5,
13.625,
14.13125,
14.3590625,
14.461578125,
14.50771015625,
14.5284695703125,
14.537811306640625,
14.54201508798828,
14.543906789594727
],
"xaxis": "x",
"y": [
50,
42.5,
39.125,
37.60625,
36.9228125,
36.615265625,
36.47686953125,
36.4145912890625,
36.386566080078126,
36.37395473603516,
36.36827963121582
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"tracegroupgap": 0
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
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""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig0 = px.line(data_frame=bio.get_history(), x=\"A\", y=\"B\", \n",
" title=\"State space of reaction A <-> 3B : [A] vs. [B]\",\n",
" color_discrete_sequence = ['#C83778'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n",
"fig0.show()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "50b08a83-7a05-4fa7-bbde-93d3d6402df9",
"metadata": {},
"outputs": [
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""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Now show the individual data points\n",
"\n",
"df['SYSTEM TIME'] = round(df['SYSTEM TIME'], 2) # To avoid clutter from too many digits, in the column\n",
"\n",
"fig1 = px.scatter(data_frame=df, x=\"A\", y=\"B\",\n",
" title=\"Trajectory in State space: [A] vs. [B]\",\n",
" hover_data=['SYSTEM TIME'])\n",
"\n",
"fig1.update_traces(marker={\"size\": 6, \"color\": \"#2FAC74\"}) # Modify the style of the dots\n",
"\n",
"# Add annotations (showing the System Time value) to SOME of the points, to avoid clutter\n",
"for ind in df.index:\n",
" label = df[\"SYSTEM TIME\"][ind]\n",
" if ind == 0:\n",
" label = f\"t={label}\"\n",
" \n",
" label_x = ind*16\n",
" label_y = 20 + ind*8 # A greater y value here means further DOWN!!\n",
" \n",
" if (ind <= 3) or (ind%2 == 0):\n",
" fig1.add_annotation(x=df[\"A\"][ind], y=df[\"B\"][ind],\n",
" text=label,\n",
" font=dict(\n",
" size=10,\n",
" color=\"grey\"\n",
" ),\n",
" showarrow=True, arrowhead=0, ax=label_x, ay=label_y, arrowcolor=\"#b0b0b0\",\n",
" bordercolor=\"#c7c7c7\")\n",
"\n",
"fig1.show()"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "f3c287ce-9a33-43bd-8473-f81f22ff9e81",
"metadata": {},
"outputs": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Combine the two above plots, while using the layout of fig1 (which includes the title and annotations)\n",
"all_fig = go.Figure(data=fig0.data + fig1.data, layout = fig1.layout)\n",
"all_fig.show()"
]
},
{
"cell_type": "markdown",
"id": "4fe369cf-d2c0-454c-a3f9-9794008be8d8",
"metadata": {},
"source": [
"### Note how the trajectory is progressively slowing down towards the dynamical system's \"attractor\" (equilibrium state of the reaction)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "7f982020",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}