{
"cells": [
{
"cell_type": "markdown",
"id": "49bcb5b0-f19d-4b96-a5f1-e0ae30f66d8f",
"metadata": {},
"source": [
"## `U` (\"Up-regulator\") up-regulates `X` , by sharing an upstream reagent `S` (\"Source\") across 2 separate reactions: \n",
"### `2 S <-> U` and `S <-> X` (both mostly forward)\n",
"\n",
"1st-order kinetics throughout. \n",
"\n",
"Invoking [Le Chatelier's principle](https://www.chemguide.co.uk/physical/equilibria/lechatelier.html), it can be seen that, starting from equilibrium, when [U] goes up, so does [S]; and when [S] goes up, so does [X]. \n",
"Conversely, when [U] goes down, so does [S]; and when [S] goes down, so does [X]. \n",
"\n",
"This experiment is a counterpart of experiment `up_regulate_2`, with \"upstream\" rather than \"downstream\" reactions.\n",
"\n",
"Note: numerical errors in the same reactions (with the same initial conditions) is explored in the experiment \"large_time_steps_2\"\n",
"\n",
"LAST REVISED: June 23, 2024 (using v. 1.0 beta36)"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "437be530-28df-4819-a681-0d63a66e9f83",
"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": "da078672",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from life123 import ChemData as chem\n",
"from life123 import UniformCompartment\n",
"\n",
"from life123 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 'up_regulate_3.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": "markdown",
"id": "d6d3ca49-589d-49b7-8424-37c7b01bcacf",
"metadata": {},
"source": [
"### Initialize the system"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "23c15e66-52e4-495b-aa3d-ecddd8d16942",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 2 (at temp. 25 C)\n",
"0: 2 S <-> U (kF = 8 / kR = 2 / delta_G = -3,436.6 / K = 4) | 1st order in all reactants & products\n",
"1: S <-> X (kF = 6 / kR = 3 / delta_G = -1,718.3 / K = 2) | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions: {'X', 'U', 'S'}\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `up_regulate_3.log.htm`]\n"
]
}
],
"source": [
"# Initialize the system\n",
"chem_data = chem(names=[\"U\", \"X\", \"S\"])\n",
"\n",
"# Reaction 2 S <-> U , with 1st-order kinetics for all species (mostly forward)\n",
"chem_data.add_reaction(reactants=[(2, \"S\", 1)], products=\"U\",\n",
" forward_rate=8., reverse_rate=2.)\n",
"\n",
"# Reaction S <-> X , with 1st-order kinetics for all species (mostly forward)\n",
"chem_data.add_reaction(reactants=\"S\", products=\"X\",\n",
" forward_rate=6., reverse_rate=3.)\n",
"\n",
"chem_data.describe_reactions()\n",
"\n",
"# Send the plot of the reaction network to the HTML log file\n",
"chem_data.plot_reaction_network(\"vue_cytoscape_2\")"
]
},
{
"cell_type": "markdown",
"id": "d1d0eabb-b5b1-4e15-846d-5e483a5a24a7",
"metadata": {},
"source": [
"### Set the initial concentrations of all the chemicals"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "e80645d6-eb5b-4c78-8b46-ae126d2cb2cf",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"3 species:\n",
" Species 0 (U). Conc: 50.0\n",
" Species 1 (X). Conc: 100.0\n",
" Species 2 (S). Conc: 0.0\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics = UniformCompartment(chem_data=chem_data)\n",
"dynamics.set_conc(conc={\"U\": 50., \"X\": 100.})\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "31da0ac3-db5a-4827-b955-21f849f33f49",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "f5030a8a-2609-4887-91c6-1531d66321fb",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "0b46b395-3f68-4dbd-b0c5-d67a0e623726",
"metadata": {
"tags": []
},
"source": [
"# 1. Take the initial system to equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "853a1827-5628-435b-91dc-cc51316ebcc2",
"metadata": {},
"outputs": [],
"source": [
"dynamics = UniformCompartment(chem_data=chem_data, preset=\"fast\")\n",
"dynamics.set_conc(conc={\"U\": 50., \"X\": 100.})\n",
"#dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "909a9301-8eda-44af-ba36-9d7167aedd33",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"30 total step(s) taken\n",
"Number of step re-do's because of negative concentrations: 0\n",
"Number of step re-do's because of elective soft aborts: 1\n",
"Norm usage: {'norm_A': 23, 'norm_B': 15, 'norm_C': 15, 'norm_D': 15}\n"
]
}
],
"source": [
"dynamics.set_diagnostics() # To save diagnostic information about the call to single_compartment_react()\n",
"\n",
"dynamics.single_compartment_react(initial_step=0.01, target_end_time=1.5,\n",
" variable_steps=True)\n",
"\n",
"#df = dynamics.get_history()\n",
"#dynamics.explain_time_advance()"
]
},
{
"cell_type": "markdown",
"id": "cbf6c9c7-8cec-400f-9e70-49ff1a9f485c",
"metadata": {
"tags": []
},
"source": [
"## Plots of changes of concentration with time"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "db4e74d0-3f9d-49dc-9553-bf3cdfe785f2",
"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=U
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "U",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "U",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464
],
"xaxis": "x",
"y": [
50,
49.4,
49.04096,
48.763923968,
48.5588101603328,
48.41671872879657,
48.32979387770522,
48.27175619336873,
48.32683522066911,
48.55411763921066,
49.077388573199165,
49.790484986867625,
51.006727934504546,
52.05646092651994,
53.6172250736525,
54.81081929992456,
56.50308266262827,
57.73614118822553,
59.44644135898895,
60.65907560891633,
62.311932198375104,
63.453115116860744,
64.97733532821864,
65.99630540998021,
67.32379760385716,
68.38947965598064,
69.67273943946861,
70.57636939039658,
71.53082976621369,
72.32720965641225,
72.72664619276735
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=X
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "X",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "X",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464
],
"xaxis": "x",
"y": [
100,
98.2,
96.87232,
95.62267648,
94.4429748355072,
93.32605085737812,
92.2655624615607,
90.75105982301784,
88.63403720555992,
86.71565094458077,
84.07358856779834,
81.71501501598343,
78.48503580981725,
76.1824444519704,
72.96552692258743,
70.63047709591837,
67.36207993773947,
65.00233951133892,
61.7331874227858,
59.41679597214133,
56.25945023492399,
54.07951404385893,
51.167885799472565,
49.22140722163711,
46.68557698061788,
44.649867258798544,
42.19853158961267,
40.47238046584005,
38.64913094722562,
37.12785337561009,
36.364832680090714
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=S
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "S",
"line": {
"color": "darkturquoise",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "S",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464
],
"xaxis": "x",
"y": [
0,
3,
5.0457600000000005,
6.849475584,
8.4394048438272,
9.84051168502874,
11.074849783028846,
12.705427790244698,
14.712292353101866,
16.17611377699791,
17.77163428580333,
18.704015010281328,
19.501508321173656,
19.704633694989724,
19.800022930107573,
19.747884304232507,
19.631754737003988,
19.525378112210017,
19.3739298592363,
19.265052810026,
19.11668536832579,
19.014255722419566,
18.877443544090124,
18.785981958402438,
18.66682781166776,
18.57117342924013,
18.455989531450037,
18.37488075336674,
18.289209520346965,
18.217727311565383,
18.18187493437456
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"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 concentration for `2 S <-> U` and `S <-> X`"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
1.663810464
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-5.555555555555555,
105.55555555555556
],
"title": {
"text": "Concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['green', 'orange', 'darkturquoise'])"
]
},
{
"cell_type": "markdown",
"id": "53406956-8084-43fe-9540-1212e9cc2258",
"metadata": {},
"source": [
"### Note that [S] is initially 0, and that it builds up thru _reverse_ reactions"
]
},
{
"cell_type": "markdown",
"id": "962acf15-3b50-40e4-9daa-3dcca7d3291a",
"metadata": {},
"source": [
"### Equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "2783a665-fca0-44e5-8d42-af2a96eae392",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0: 2 S <-> U\n",
"Final concentrations: [S] = 18.18 ; [U] = 72.73\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 3.99995\n",
" Formula used: [U] / [S]\n",
"2. Ratio of forward/reverse reaction rates: 4\n",
"Discrepancy between the two values: 0.001174 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n",
"1: S <-> X\n",
"Final concentrations: [S] = 18.18 ; [X] = 36.36\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 2.00006\n",
" Formula used: [X] / [S]\n",
"2. Ratio of forward/reverse reaction rates: 2\n",
"Discrepancy between the two values: 0.002978 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"dynamics.is_in_equilibrium()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "27a1b761-19bb-4ec4-83e7-6b7c85e0f165",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "4d321a08-0524-4b32-86ae-34ed7f182fd1",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "448ec7fa-6529-438b-84ba-47888c2cd080",
"metadata": {
"tags": []
},
"source": [
"# 2. Now, let's suddenly increase [U]"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "e82c46d1-482a-41fb-873e-11a42561603d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 1.6638105:\n",
"3 species:\n",
" Species 0 (U). Conc: 72.72664619276735\n",
" Species 1 (X). Conc: 36.364832680090714\n",
" Species 2 (S). Conc: 18.18187493437456\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "7245be7a-c9db-45f5-b033-d6c521237a9c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 1.6638105:\n",
"3 species:\n",
" Species 0 (U). Conc: 100.0\n",
" Species 1 (X). Conc: 36.364832680090714\n",
" Species 2 (S). Conc: 18.18187493437456\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.set_single_conc(species_name=\"U\", conc=100.)\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "61eead55-fcef-41cd-b29e-f2d5ad5c6078",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" U | \n",
" X | \n",
" S | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 29 | \n",
" 1.296478 | \n",
" 72.327210 | \n",
" 37.127853 | \n",
" 18.217727 | \n",
" | \n",
"
\n",
" \n",
" | 30 | \n",
" 1.663810 | \n",
" 72.726646 | \n",
" 36.364833 | \n",
" 18.181875 | \n",
" | \n",
"
\n",
" \n",
" | 31 | \n",
" 1.663810 | \n",
" 100.000000 | \n",
" 36.364833 | \n",
" 18.181875 | \n",
" Set concentration of `U` | \n",
"
\n",
" \n",
"
\n",
"
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "U",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "U",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147
],
"xaxis": "x",
"y": [
50,
49.4,
49.04096,
48.763923968,
48.5588101603328,
48.41671872879657,
48.32979387770522,
48.27175619336873,
48.32683522066911,
48.55411763921066,
49.077388573199165,
49.790484986867625,
51.006727934504546,
52.05646092651994,
53.6172250736525,
54.81081929992456,
56.50308266262827,
57.73614118822553,
59.44644135898895,
60.65907560891633,
62.311932198375104,
63.453115116860744,
64.97733532821864,
65.99630540998021,
67.32379760385716,
68.38947965598064,
69.67273943946861,
70.57636939039658,
71.53082976621369,
72.32720965641225,
72.72664619276735,
100,
99.45454999474997,
98.9178303080806,
98.40384015229299,
97.92248518243052,
97.47621313482031,
97.0579789883547,
96.65232057517363,
96.24053342287766,
95.80856828836745,
95.35342111896276,
94.88367696355547,
94.41491190157609,
93.96595305913047,
93.55781748260308,
93.21039957175695,
92.93918455598191,
92.749419143692,
92.63850662716726,
92.57375924458273
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=X
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "X",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "X",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147
],
"xaxis": "x",
"y": [
100,
98.2,
96.87232,
95.62267648,
94.4429748355072,
93.32605085737812,
92.2655624615607,
90.75105982301784,
88.63403720555992,
86.71565094458077,
84.07358856779834,
81.71501501598343,
78.48503580981725,
76.1824444519704,
72.96552692258743,
70.63047709591837,
67.36207993773947,
65.00233951133892,
61.7331874227858,
59.41679597214133,
56.25945023492399,
54.07951404385893,
51.167885799472565,
49.22140722163711,
46.68557698061788,
44.649867258798544,
42.19853158961267,
40.47238046584005,
38.64913094722562,
37.12785337561009,
36.364832680090714,
36.364832680090714,
36.36480019575047,
36.44330952360692,
36.62009107000094,
36.91131685828268,
37.326214602569294,
37.864432163138666,
38.51551427997978,
39.261273468059436,
40.08006109906903,
40.94983889215096,
41.847061264938105,
42.74257735972748,
43.60013740810818,
44.37985812837188,
45.04335030903558,
45.56184250478355,
45.92300437781088,
46.14046743855492,
46.234703179720654
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=S
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "S",
"line": {
"color": "darkturquoise",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "S",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147
],
"xaxis": "x",
"y": [
0,
3,
5.0457600000000005,
6.849475584,
8.4394048438272,
9.84051168502874,
11.074849783028846,
12.705427790244698,
14.712292353101866,
16.17611377699791,
17.77163428580333,
18.704015010281328,
19.501508321173656,
19.704633694989724,
19.800022930107573,
19.747884304232507,
19.631754737003988,
19.525378112210017,
19.3739298592363,
19.265052810026,
19.11668536832579,
19.014255722419566,
18.877443544090124,
18.785981958402438,
18.66682781166776,
18.57117342924013,
18.455989531450037,
18.37488075336674,
18.289209520346965,
18.217727311565383,
18.18187493437456,
18.18187493437456,
19.27280742921488,
20.267737474697167,
21.118936239878366,
21.790420391321547,
22.268066742255353,
22.566317474617207,
22.72655218413824,
22.804367300650522,
22.84950993866133,
22.89002648438879,
22.932292422416214,
22.97430645158561,
23.014664088096133,
23.051214520887218,
23.082558161915767,
23.106495997717868,
23.124864949270368,
23.1292269215758,
23.16448594557913
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"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 concentration for `2 S <-> U` and `S <-> X`"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
3.2112104608531147
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-5.555555555555555,
105.55555555555556
],
"title": {
"text": "Concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['green', 'orange', 'darkturquoise'])"
]
},
{
"cell_type": "markdown",
"id": "158e3787-f2d5-4a01-aaa9-6066e93e584c",
"metadata": {},
"source": [
"### The (transiently) high value of [U] led to an increase in [X]"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "c3afbcc8-bdae-4938-a3f1-ce00d62816f2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0: 2 S <-> U\n",
"Final concentrations: [S] = 23.16 ; [U] = 92.57\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 3.99637\n",
" Formula used: [U] / [S]\n",
"2. Ratio of forward/reverse reaction rates: 4\n",
"Discrepancy between the two values: 0.09086 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n",
"1: S <-> X\n",
"Final concentrations: [S] = 23.16 ; [X] = 46.23\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 1.99593\n",
" Formula used: [X] / [S]\n",
"2. Ratio of forward/reverse reaction rates: 2\n",
"Discrepancy between the two values: 0.2035 %\n",
"Reaction IS in equilibrium (within 1% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"dynamics.is_in_equilibrium()"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "019f3e6c-081d-45e1-86e7-1ca485d59998",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "98ac2b25-56e2-44c3-b39b-28b7a303322d",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "f6619731-c5ea-484c-af3e-cea50d685361",
"metadata": {
"tags": []
},
"source": [
"# 3. Let's again suddenly increase [U]"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "32de9623-5221-420b-a6f2-5414df281d44",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 3.2112105:\n",
"3 species:\n",
" Species 0 (U). Conc: 92.57375924458273\n",
" Species 1 (X). Conc: 46.234703179720654\n",
" Species 2 (S). Conc: 23.16448594557913\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "d3618eba-a673-4ff5-85d0-08f5ea592361",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 3.2112105:\n",
"3 species:\n",
" Species 0 (U). Conc: 150.0\n",
" Species 1 (X). Conc: 46.234703179720654\n",
" Species 2 (S). Conc: 23.16448594557913\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.set_single_conc(species_name=\"U\", conc=150.)\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "e8fe3554-d5ab-4306-b890-4e36289b5b4b",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" U | \n",
" X | \n",
" S | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 49 | \n",
" 2.944977 | \n",
" 92.638507 | \n",
" 46.140467 | \n",
" 23.129227 | \n",
" | \n",
"
\n",
" \n",
" | 50 | \n",
" 3.211210 | \n",
" 92.573759 | \n",
" 46.234703 | \n",
" 23.164486 | \n",
" | \n",
"
\n",
" \n",
" | 51 | \n",
" 3.211210 | \n",
" 150.000000 | \n",
" 46.234703 | \n",
" 23.164486 | \n",
" Set concentration of `U` | \n",
"
\n",
" \n",
"
\n",
"
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "U",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "U",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377
],
"xaxis": "x",
"y": [
50,
49.4,
49.04096,
48.763923968,
48.5588101603328,
48.41671872879657,
48.32979387770522,
48.27175619336873,
48.32683522066911,
48.55411763921066,
49.077388573199165,
49.790484986867625,
51.006727934504546,
52.05646092651994,
53.6172250736525,
54.81081929992456,
56.50308266262827,
57.73614118822553,
59.44644135898895,
60.65907560891633,
62.311932198375104,
63.453115116860744,
64.97733532821864,
65.99630540998021,
67.32379760385716,
68.38947965598064,
69.67273943946861,
70.57636939039658,
71.53082976621369,
72.32720965641225,
72.72664619276735,
100,
99.45454999474997,
98.9178303080806,
98.40384015229299,
97.92248518243052,
97.47621313482031,
97.0579789883547,
96.65232057517363,
96.24053342287766,
95.80856828836745,
95.35342111896276,
94.88367696355547,
94.41491190157609,
93.96595305913047,
93.55781748260308,
93.21039957175695,
92.93918455598191,
92.749419143692,
92.63850662716726,
92.57375924458273,
150,
148.85315887564633,
147.91252290876886,
146.97347844816994,
146.05678515760263,
145.176753264363,
144.33602207473916,
143.5225026479313,
142.71132241396958,
141.8733428785369,
140.98804693236715,
140.05403195706245,
139.0901394073237,
138.1282278285491,
137.2069792139752,
136.36947500648193,
135.65660449508508,
135.10000451084136,
134.71083687228074,
134.48228669496106
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=X
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "X",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "X",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377
],
"xaxis": "x",
"y": [
100,
98.2,
96.87232,
95.62267648,
94.4429748355072,
93.32605085737812,
92.2655624615607,
90.75105982301784,
88.63403720555992,
86.71565094458077,
84.07358856779834,
81.71501501598343,
78.48503580981725,
76.1824444519704,
72.96552692258743,
70.63047709591837,
67.36207993773947,
65.00233951133892,
61.7331874227858,
59.41679597214133,
56.25945023492399,
54.07951404385893,
51.167885799472565,
49.22140722163711,
46.68557698061788,
44.649867258798544,
42.19853158961267,
40.47238046584005,
38.64913094722562,
37.12785337561009,
36.364832680090714,
36.364832680090714,
36.36480019575047,
36.44330952360692,
36.62009107000094,
36.91131685828268,
37.326214602569294,
37.864432163138666,
38.51551427997978,
39.261273468059436,
40.08006109906903,
40.94983889215096,
41.847061264938105,
42.74257735972748,
43.60013740810818,
44.37985812837188,
45.04335030903558,
45.56184250478355,
45.92300437781088,
46.14046743855492,
46.234703179720654,
46.234703179720654,
46.237531241063785,
46.37772571180847,
46.66626965309202,
47.13739397063343,
47.81955941855112,
48.72982960755876,
49.86934090591567,
51.22202255757629,
52.75781192928274,
54.43881302269023,
56.223542573018555,
58.06464723193076,
59.90222854650905,
61.66194079261074,
63.26190831082723,
64.62340881666765,
65.68729469549706,
66.42857488684056,
66.874053871657
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=S
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "S",
"line": {
"color": "darkturquoise",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "S",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377
],
"xaxis": "x",
"y": [
0,
3,
5.0457600000000005,
6.849475584,
8.4394048438272,
9.84051168502874,
11.074849783028846,
12.705427790244698,
14.712292353101866,
16.17611377699791,
17.77163428580333,
18.704015010281328,
19.501508321173656,
19.704633694989724,
19.800022930107573,
19.747884304232507,
19.631754737003988,
19.525378112210017,
19.3739298592363,
19.265052810026,
19.11668536832579,
19.014255722419566,
18.877443544090124,
18.785981958402438,
18.66682781166776,
18.57117342924013,
18.455989531450037,
18.37488075336674,
18.289209520346965,
18.217727311565383,
18.18187493437456,
18.18187493437456,
19.27280742921488,
20.267737474697167,
21.118936239878366,
21.790420391321547,
22.268066742255353,
22.566317474617207,
22.72655218413824,
22.804367300650522,
22.84950993866133,
22.89002648438879,
22.932292422416214,
22.97430645158561,
23.014664088096133,
23.051214520887218,
23.082558161915767,
23.106495997717868,
23.124864949270368,
23.1292269215758,
23.16448594557913,
23.16448594557913,
25.45534013294334,
27.196417595953573,
28.785962575867842,
30.148224839461072,
31.226123178022682,
31.99731536826271,
32.484842923521526,
32.754521739784366,
32.89469143894327,
32.984282237875284,
33.067582638156395,
33.1542630787217,
33.24050492169264,
33.323289904738765,
33.39833080150878,
33.46257131846207,
33.51188540812009,
33.54894049389783,
33.56056186372072
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"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 concentration for `2 S <-> U` and `S <-> X`"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
4.502377124897377
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-8.333333333333334,
158.33333333333334
],
"title": {
"text": "Concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['green', 'orange', 'darkturquoise'])"
]
},
{
"cell_type": "markdown",
"id": "ffbf3294-7a8d-4679-9c4b-5b9a975bf8fc",
"metadata": {},
"source": [
"### The (transiently) high value of [U] again led to an increase in [X]"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "31c9c18f-3a7f-4690-8e2f-70fdb02ef5c7",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"dynamics.is_in_equilibrium(explain=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "6fd8ca29-4a92-4381-8fcb-0acf5e4a1f16",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "d4091237-d833-41c1-bbc8-3fe036895c70",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "64ebc51b-0dc7-4cff-b231-4c35843a7113",
"metadata": {
"tags": []
},
"source": [
"# 4. Now, instead, let's DECREASE [U]"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "e7ced06d-f506-41ee-80d6-d4b2a8ed28bc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 4.5023771:\n",
"3 species:\n",
" Species 0 (U). Conc: 134.48228669496106\n",
" Species 1 (X). Conc: 66.874053871657\n",
" Species 2 (S). Conc: 33.56056186372072\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "52f4843c-0671-4cd9-9c51-74a44feb4fe4",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 4.5023771:\n",
"3 species:\n",
" Species 0 (U). Conc: 80.0\n",
" Species 1 (X). Conc: 66.874053871657\n",
" Species 2 (S). Conc: 33.56056186372072\n",
"Set of chemicals involved in reactions: {'X', 'U', 'S'}\n"
]
}
],
"source": [
"dynamics.set_single_conc(species_name=\"U\", conc=80.)\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "e5ce5d59",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" U | \n",
" X | \n",
" S | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 69 | \n",
" 4.280516 | \n",
" 134.710837 | \n",
" 66.428575 | \n",
" 33.548940 | \n",
" | \n",
"
\n",
" \n",
" | 70 | \n",
" 4.502377 | \n",
" 134.482287 | \n",
" 66.874054 | \n",
" 33.560562 | \n",
" | \n",
"
\n",
" \n",
" | 71 | \n",
" 4.502377 | \n",
" 80.000000 | \n",
" 66.874054 | \n",
" 33.560562 | \n",
" Set concentration of `U` | \n",
"
\n",
" \n",
"
\n",
"
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "U",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "U",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377,
4.502377124897377,
4.512377124897377,
4.5223771248973765,
4.534377124897376,
4.548777124897376,
4.566057124897377,
4.586793124897377,
4.611676324897377,
4.641536164897377,
4.677367972897377,
4.720366142497377,
4.771963946017377,
4.8338813102413765,
4.9081821473101765,
4.9973431517927365,
5.104336357171809,
5.232728203626695,
5.386798419372559,
5.571682678267595,
5.793543788941639,
6.059777121750491
],
"xaxis": "x",
"y": [
50,
49.4,
49.04096,
48.763923968,
48.5588101603328,
48.41671872879657,
48.32979387770522,
48.27175619336873,
48.32683522066911,
48.55411763921066,
49.077388573199165,
49.790484986867625,
51.006727934504546,
52.05646092651994,
53.6172250736525,
54.81081929992456,
56.50308266262827,
57.73614118822553,
59.44644135898895,
60.65907560891633,
62.311932198375104,
63.453115116860744,
64.97733532821864,
65.99630540998021,
67.32379760385716,
68.38947965598064,
69.67273943946861,
70.57636939039658,
71.53082976621369,
72.32720965641225,
72.72664619276735,
100,
99.45454999474997,
98.9178303080806,
98.40384015229299,
97.92248518243052,
97.47621313482031,
97.0579789883547,
96.65232057517363,
96.24053342287766,
95.80856828836745,
95.35342111896276,
94.88367696355547,
94.41491190157609,
93.96595305913047,
93.55781748260308,
93.21039957175695,
92.93918455598191,
92.749419143692,
92.63850662716726,
92.57375924458273,
150,
148.85315887564633,
147.91252290876886,
146.97347844816994,
146.05678515760263,
145.176753264363,
144.33602207473916,
143.5225026479313,
142.71132241396958,
141.8733428785369,
140.98804693236715,
140.05403195706245,
139.0901394073237,
138.1282278285491,
137.2069792139752,
136.36947500648193,
135.65660449508508,
135.10000451084136,
134.71083687228074,
134.48228669496106,
80,
81.08484494909766,
81.97382483970385,
82.86043094519592,
83.72482517881699,
84.55330411109296,
85.34327120045002,
86.1061554045364,
86.86557914794764,
87.64928212746909,
88.47689443572739,
89.3499856899865,
90.25100985813866,
91.15018073661754,
92.01134199880816,
92.7942197040456,
93.4605951365493,
93.98088743015613,
94.34468426587755,
94.55827533938317,
94.67802574153163
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=X
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "X",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "X",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377,
4.502377124897377,
4.512377124897377,
4.5223771248973765,
4.534377124897376,
4.548777124897376,
4.566057124897377,
4.586793124897377,
4.611676324897377,
4.641536164897377,
4.677367972897377,
4.720366142497377,
4.771963946017377,
4.8338813102413765,
4.9081821473101765,
4.9973431517927365,
5.104336357171809,
5.232728203626695,
5.386798419372559,
5.571682678267595,
5.793543788941639,
6.059777121750491
],
"xaxis": "x",
"y": [
100,
98.2,
96.87232,
95.62267648,
94.4429748355072,
93.32605085737812,
92.2655624615607,
90.75105982301784,
88.63403720555992,
86.71565094458077,
84.07358856779834,
81.71501501598343,
78.48503580981725,
76.1824444519704,
72.96552692258743,
70.63047709591837,
67.36207993773947,
65.00233951133892,
61.7331874227858,
59.41679597214133,
56.25945023492399,
54.07951404385893,
51.167885799472565,
49.22140722163711,
46.68557698061788,
44.649867258798544,
42.19853158961267,
40.47238046584005,
38.64913094722562,
37.12785337561009,
36.364832680090714,
36.364832680090714,
36.36480019575047,
36.44330952360692,
36.62009107000094,
36.91131685828268,
37.326214602569294,
37.864432163138666,
38.51551427997978,
39.261273468059436,
40.08006109906903,
40.94983889215096,
41.847061264938105,
42.74257735972748,
43.60013740810818,
44.37985812837188,
45.04335030903558,
45.56184250478355,
45.92300437781088,
46.14046743855492,
46.234703179720654,
46.234703179720654,
46.237531241063785,
46.37772571180847,
46.66626965309202,
47.13739397063343,
47.81955941855112,
48.72982960755876,
49.86934090591567,
51.22202255757629,
52.75781192928274,
54.43881302269023,
56.223542573018555,
58.06464723193076,
59.90222854650905,
61.66194079261074,
63.26190831082723,
64.62340881666765,
65.68729469549706,
66.42857488684056,
66.874053871657,
66.874053871657,
66.88146596733053,
66.75802958050173,
66.49522394183738,
66.06071125118204,
65.42763064776268,
64.57992988851589,
63.516647636277476,
62.25309867166093,
60.817778800035086,
59.24646657596397,
57.57814251446746,
55.85712358741672,
54.1393969980208,
52.494461399258455,
50.99885022644643,
49.726153970089456,
48.73165646378088,
48.038735604704414,
47.622271856053636,
47.43802338355751
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=S
SYSTEM TIME=%{x}
Concentration=%{y}",
"legendgroup": "S",
"line": {
"color": "darkturquoise",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "S",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.006,
0.0108,
0.015600000000000001,
0.0204,
0.0252,
0.03,
0.0372,
0.048,
0.058800000000000005,
0.07500000000000001,
0.0912,
0.1155,
0.13494,
0.1641,
0.18742799999999998,
0.22241999999999998,
0.25041359999999996,
0.29240399999999994,
0.32599631999999995,
0.37638479999999996,
0.41669558399999995,
0.47716175999999993,
0.5255347008,
0.598094112,
0.6706535231999999,
0.77949264,
0.8883317568,
1.051590432,
1.2964784448,
1.663810464,
1.663810464,
1.673810464,
1.685810464,
1.700210464,
1.717490464,
1.738226464,
1.7631096640000001,
1.7929695040000002,
1.8288013120000002,
1.8717994816,
1.92339728512,
1.9853146493440001,
2.0596154864128002,
2.14877649089536,
2.2557696962744322,
2.3841615427293186,
2.5382317584751823,
2.7231160173702187,
2.9449771280442625,
3.2112104608531147,
3.2112104608531147,
3.2212104608531145,
3.2312104608531143,
3.2432104608531143,
3.2576104608531145,
3.2748904608531144,
3.2956264608531143,
3.3205096608531144,
3.3503695008531142,
3.3862013088531144,
3.4291994784531146,
3.4807972819731146,
3.5427146461971146,
3.6170154832659147,
3.7061764877484746,
3.8131696931275467,
3.941561539582433,
4.095631755328297,
4.280516014223333,
4.502377124897377,
4.502377124897377,
4.512377124897377,
4.5223771248973765,
4.534377124897376,
4.548777124897376,
4.566057124897377,
4.586793124897377,
4.611676324897377,
4.641536164897377,
4.677367972897377,
4.720366142497377,
4.771963946017377,
4.8338813102413765,
4.9081821473101765,
4.9973431517927365,
5.104336357171809,
5.232728203626695,
5.386798419372559,
5.571682678267595,
5.793543788941639,
6.059777121750491
],
"xaxis": "x",
"y": [
0,
3,
5.0457600000000005,
6.849475584,
8.4394048438272,
9.84051168502874,
11.074849783028846,
12.705427790244698,
14.712292353101866,
16.17611377699791,
17.77163428580333,
18.704015010281328,
19.501508321173656,
19.704633694989724,
19.800022930107573,
19.747884304232507,
19.631754737003988,
19.525378112210017,
19.3739298592363,
19.265052810026,
19.11668536832579,
19.014255722419566,
18.877443544090124,
18.785981958402438,
18.66682781166776,
18.57117342924013,
18.455989531450037,
18.37488075336674,
18.289209520346965,
18.217727311565383,
18.18187493437456,
18.18187493437456,
19.27280742921488,
20.267737474697167,
21.118936239878366,
21.790420391321547,
22.268066742255353,
22.566317474617207,
22.72655218413824,
22.804367300650522,
22.84950993866133,
22.89002648438879,
22.932292422416214,
22.97430645158561,
23.014664088096133,
23.051214520887218,
23.082558161915767,
23.106495997717868,
23.124864949270368,
23.1292269215758,
23.16448594557913,
23.16448594557913,
25.45534013294334,
27.196417595953573,
28.785962575867842,
30.148224839461072,
31.226123178022682,
31.99731536826271,
32.484842923521526,
32.754521739784366,
32.89469143894327,
32.984282237875284,
33.067582638156395,
33.1542630787217,
33.24050492169264,
33.323289904738765,
33.39833080150878,
33.46257131846207,
33.51188540812009,
33.54894049389783,
33.56056186372072,
33.56056186372072,
31.383459869851873,
29.72893647546828,
28.2185299031485,
26.924254126561713,
25.90037686542912,
25.168143445961796,
24.70565729002746,
24.45035876782152,
24.318272680404462,
24.234360287958992,
24.156501840937302,
24.0754724316837,
23.99485726412185,
23.91747033850295,
23.847326100840096,
23.787271492189678,
23.741184411284586,
23.706511598918215,
23.695793200557745,
23.64054086875697
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"template": {
"data": {
"bar": [
{
"error_x": {
"color": "#2a3f5f"
},
"error_y": {
"color": "#2a3f5f"
},
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "bar"
}
],
"barpolar": [
{
"marker": {
"line": {
"color": "#E5ECF6",
"width": 0.5
},
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "barpolar"
}
],
"carpet": [
{
"aaxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
"endlinecolor": "#2a3f5f",
"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"type": "carpet"
}
],
"choropleth": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "choropleth"
}
],
"contour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "contour"
}
],
"contourcarpet": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "contourcarpet"
}
],
"heatmap": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmap"
}
],
"heatmapgl": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "heatmapgl"
}
],
"histogram": [
{
"marker": {
"pattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
}
},
"type": "histogram"
}
],
"histogram2d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2d"
}
],
"histogram2dcontour": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "histogram2dcontour"
}
],
"mesh3d": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"type": "mesh3d"
}
],
"parcoords": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "parcoords"
}
],
"pie": [
{
"automargin": true,
"type": "pie"
}
],
"scatter": [
{
"fillpattern": {
"fillmode": "overlay",
"size": 10,
"solidity": 0.2
},
"type": "scatter"
}
],
"scatter3d": [
{
"line": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatter3d"
}
],
"scattercarpet": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattercarpet"
}
],
"scattergeo": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergeo"
}
],
"scattergl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattergl"
}
],
"scattermapbox": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scattermapbox"
}
],
"scatterpolar": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolar"
}
],
"scatterpolargl": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterpolargl"
}
],
"scatterternary": [
{
"marker": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"type": "scatterternary"
}
],
"surface": [
{
"colorbar": {
"outlinewidth": 0,
"ticks": ""
},
"colorscale": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"type": "surface"
}
],
"table": [
{
"cells": {
"fill": {
"color": "#EBF0F8"
},
"line": {
"color": "white"
}
},
"header": {
"fill": {
"color": "#C8D4E3"
},
"line": {
"color": "white"
}
},
"type": "table"
}
]
},
"layout": {
"annotationdefaults": {
"arrowcolor": "#2a3f5f",
"arrowhead": 0,
"arrowwidth": 1
},
"autotypenumbers": "strict",
"coloraxis": {
"colorbar": {
"outlinewidth": 0,
"ticks": ""
}
},
"colorscale": {
"diverging": [
[
0,
"#8e0152"
],
[
0.1,
"#c51b7d"
],
[
0.2,
"#de77ae"
],
[
0.3,
"#f1b6da"
],
[
0.4,
"#fde0ef"
],
[
0.5,
"#f7f7f7"
],
[
0.6,
"#e6f5d0"
],
[
0.7,
"#b8e186"
],
[
0.8,
"#7fbc41"
],
[
0.9,
"#4d9221"
],
[
1,
"#276419"
]
],
"sequential": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
],
"sequentialminus": [
[
0,
"#0d0887"
],
[
0.1111111111111111,
"#46039f"
],
[
0.2222222222222222,
"#7201a8"
],
[
0.3333333333333333,
"#9c179e"
],
[
0.4444444444444444,
"#bd3786"
],
[
0.5555555555555556,
"#d8576b"
],
[
0.6666666666666666,
"#ed7953"
],
[
0.7777777777777778,
"#fb9f3a"
],
[
0.8888888888888888,
"#fdca26"
],
[
1,
"#f0f921"
]
]
},
"colorway": [
"#636efa",
"#EF553B",
"#00cc96",
"#ab63fa",
"#FFA15A",
"#19d3f3",
"#FF6692",
"#B6E880",
"#FF97FF",
"#FECB52"
],
"font": {
"color": "#2a3f5f"
},
"geo": {
"bgcolor": "white",
"lakecolor": "white",
"landcolor": "#E5ECF6",
"showlakes": true,
"showland": true,
"subunitcolor": "white"
},
"hoverlabel": {
"align": "left"
},
"hovermode": "closest",
"mapbox": {
"style": "light"
},
"paper_bgcolor": "white",
"plot_bgcolor": "#E5ECF6",
"polar": {
"angularaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
},
"bgcolor": "#E5ECF6",
"radialaxis": {
"gridcolor": "white",
"linecolor": "white",
"ticks": ""
}
},
"scene": {
"xaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"yaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
},
"zaxis": {
"backgroundcolor": "#E5ECF6",
"gridcolor": "white",
"gridwidth": 2,
"linecolor": "white",
"showbackground": true,
"ticks": "",
"zerolinecolor": "white"
}
},
"shapedefaults": {
"line": {
"color": "#2a3f5f"
}
},
"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 concentration for `2 S <-> U` and `S <-> X`"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
6.059777121750491
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-8.333333333333334,
158.33333333333334
],
"title": {
"text": "Concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['green', 'orange', 'darkturquoise'])"
]
},
{
"cell_type": "markdown",
"id": "a1629b91-2753-4df7-b6a0-dedf86ac3dc1",
"metadata": {},
"source": [
"### The (transiently) LOW value of [U] led to an DECREASE in [X]"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "aff608b1-5c78-4070-845a-118afe7c2108",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 28,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Verify that the reaction has reached equilibrium\n",
"dynamics.is_in_equilibrium(explain=False)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "0640a359-be0e-4137-bf95-d230cc55e096",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "777ebec9-ed31-4cf3-adfc-b44db383bd39",
"metadata": {},
"source": [
"### **IDEAS TO EXPLORE**: \n",
"\n",
"* Effect of the stoichiometry and the Delta_G on the \"amplification\" of the signal (from [U] to [X]) \n",
"\n",
"* Effect of a continuously-varying (maybe oscillating [U]), and its being affected by the reactions' kinetics\n",
"\n",
"* Combining this experiment and `up_regulate_2` in a *\"bifan motif\"*"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "38b77468",
"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
}