{
"cells": [
{
"cell_type": "markdown",
"id": "3bbe8002-bdf3-490c-bde0-80dd3713a3d0",
"metadata": {},
"source": [
"## A complex (multistep) reaction `A <-> C` derived from 2 coupled elementary reactions: \n",
"## `A <-> B` and `B <-> C` \n",
"We are given the time evolution of the complex reaction, \n",
"and want to determine whether it can be modeled as an elementary reaction. \n",
"\n",
"In PART 1, a time evolution of [A], [B] and [C] is obtained by simulation \n",
"In PART 2, the time functions generated in Part 1 are taken as a _starting point,_ to explore how to model the composite reaction `A <-> C` \n",
"\n",
"**Background**: please see experiments `cascade_1` and `mystery_reaction_1`\n",
"\n",
"LAST REVISED: Dec. 6, 2023"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "4d9b4808-b2ec-4b90-a604-f7fa69af39b8",
"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": "3924c013",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from src.modules.reactions.reaction_dynamics import ReactionDynamics\n",
"from src.modules.visualization.plotly_helper import PlotlyHelper"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "75411c8b-f0c5-411d-9e12-1eaa423449f9",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "9329208b-070f-4902-8f37-0f11ddf75ed6",
"metadata": {},
"source": [
"# PART 1 - We'll generate the time evolution of [A] and [C] by simulating coupled elementary reactions of KNOWN rate constants...\n",
"## but pretend you don't see this section! (because we later assume that those time evolutions are just GIVEN to us)"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "72b4245c-de4e-480d-a501-3495b7ed8bc4",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 2 (at temp. 25 C)\n",
"0: A <-> B (kF = 8 / kR = 2 / delta_G = -3,436.6 / K = 4) | 1st order in all reactants & products\n",
"1: B <-> C (kF = 12 / kR = 1 / delta_G = -6,160 / K = 12) | 1st order in all reactants & products\n",
"Set of chemicals involved in the above reactions: {'A', 'C', 'B'}\n"
]
}
],
"source": [
"# Instantiate the simulator and specify the chemicals\n",
"dynamics = ReactionDynamics(names=[\"A\", \"B\", \"C\"])\n",
"\n",
"# Reaction A <-> B (slower, and with a smaller K)\n",
"dynamics.add_reaction(reactants=\"A\", products=\"B\",\n",
" forward_rate=8., reverse_rate=2.) \n",
"\n",
"# Reaction B <-> C (faster, and with a larger K)\n",
"dynamics.add_reaction(reactants=\"B\", products=\"C\",\n",
" forward_rate=12., reverse_rate=1.) \n",
" \n",
"dynamics.describe_reactions()"
]
},
{
"cell_type": "markdown",
"id": "98a9fbe5-2090-4d38-9c5f-94fbf7c3eae2",
"metadata": {},
"source": [
"### Run the simulation"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "ae304704-c8d9-4cef-9e0b-2587bb3909ef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"3 species:\n",
" Species 0 (A). Conc: 50.0\n",
" Species 1 (B). Conc: 0.0\n",
" Species 2 (C). Conc: 0.0\n",
"Set of chemicals involved in reactions: {'A', 'C', 'B'}\n"
]
}
],
"source": [
"dynamics.set_conc([50., 0., 0.], snapshot=True) # Set the initial concentrations of all the chemicals, in their index order\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "2502cd11-0df9-4303-8895-98401a1df7b8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* INFO: the tentative time step (0.01) leads to a least one norm value > its ABORT threshold:\n",
" -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.4 (set to 0.004) [Step started at t=0, and will rewind there]\n",
"Some steps were backtracked and re-done, to prevent negative concentrations or excessively large concentration changes\n",
"85 total step(s) taken\n"
]
}
],
"source": [
"# These settings can be tweaked to make the time resolution finer or coarser. \n",
"# Here we use a \"mid\" heuristic: neither too fast nor too prudent\n",
"dynamics.use_adaptive_preset(preset=\"mid\")\n",
"\n",
"dynamics.single_compartment_react(initial_step=0.01, reaction_duration=0.8,\n",
" snapshots={\"initial_caption\": \"1st reaction step\",\n",
" \"final_caption\": \"last reaction step\"},\n",
" variable_steps=True, explain_variable_steps=False)"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "a2c0e793-5457-46a5-9150-388c9f562cf0",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
" \n",
" "
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "blue",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "B",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "B",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
1.6,
3.0592,
3.72352,
4.0405520896,
4.3502977480192,
4.652890957773261,
4.948463392141688,
5.237144454078118,
5.519061314470442,
5.794338949761611,
6.06310017894175,
6.32546569992207,
6.581554125300875,
6.831482017531776,
7.075363923504084,
7.313312408545171,
7.5454380898544215,
7.771849669378253,
7.992653966135512,
8.251016344375778,
8.50160392227522,
8.744591847889835,
8.980151621934787,
9.254111081672768,
9.517852592409483,
9.771654355888268,
10.06461425570106,
10.34403228247831,
10.610353918423153,
10.864011226690561,
11.153705647116896,
11.426352050741748,
11.68263146812472,
11.971313970046767,
12.238283882218882,
12.48459437640964,
12.756584245234146,
13.001661660982421,
13.22141784776997,
13.456548650461645,
13.659443519072163,
13.832439116637216,
14.006780263898069,
14.144166733312131,
14.247911517843868,
14.335704567054655,
14.383519462948529,
14.39831953025766,
14.367895421717208,
14.284773753767965,
14.153860578422783,
13.949799277149335,
13.700113776207086,
13.359033005681415,
12.981434422909333,
12.500245076469138,
12.000257870459277,
11.394466723614562,
10.796345999818495,
10.21842044623623,
9.668583519552405,
9.151423390694013,
8.669195596553909,
8.222534188628476,
7.810969571439292,
7.433303638592873,
7.087879744907972,
6.772775341526878,
6.4859378862626595,
6.173147562576985,
5.895089242926046,
5.648327074911617,
5.429627797802673,
5.235999085365918,
5.064704243500656,
4.882973465060556,
4.72661132208144,
4.592154622601183,
4.4534695731066085,
4.338204866850339,
4.223286057749926,
4.1317229582794965,
4.044199736392051,
3.9648260660630523,
3.8975080860315083
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=C
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "C",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
0,
0.07680000000000001,
0.1500672,
0.1945993728,
0.2428913985024,
0.294852080080128,
0.350391919493327,
0.40942308827953394,
0.47185939864019183,
0.5376162750151969,
0.606610726137321,
0.6787613175584847,
0.753988144639991,
0.8322128059989615,
0.9133583774033439,
0.9973493861079896,
1.0841117856244238,
1.1735729309170524,
1.2656615540186744,
1.3792369772662034,
1.4963965282524951,
1.6170239488993554,
1.7410056427702898,
1.8936756146717337,
2.050859761277912,
2.2123750160185076,
2.4111770567145268,
2.615710383966741,
2.825684289832717,
3.040817806232308,
3.3048437305852914,
3.5755306949838888,
3.852440677883787,
4.191696079113364,
4.538727317661146,
4.892866710299698,
5.325602277242,
5.766791591462846,
6.215445088356687,
6.761670791823513,
7.316049463969531,
7.87716580507307,
8.557018909690294,
9.242944390659794,
9.933009357668057,
10.763950338029792,
11.596039759651704,
12.592947674008723,
13.584782654712381,
14.764902570548777,
15.928842885217733,
17.301186633802583,
18.639461254958444,
20.199014588706994,
21.69808977152376,
23.4195563927212,
25.04478383968739,
26.877577097667665,
28.57013122315092,
30.1260250239579,
31.551097797737526,
32.85255825184311,
34.03835230949977,
35.11672048418892,
36.09589355376397,
36.98388866349439,
37.788377927306854,
38.51660896708666,
39.175362291431625,
39.89004889222113,
40.52212605413672,
41.080826776657865,
41.57445107360825,
42.010428169804214,
42.395386054568036,
42.80319040125422,
43.153564364593,
43.454536077815554,
43.764733037188044,
44.02236442000321,
44.279101550040785,
44.483579328993194,
44.678989762749055,
44.85617420700618,
45.006430899005466
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"shapes": [
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0,
"x1": 0,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.004,
"x1": 0.004,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.008,
"x1": 0.008,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.01,
"x1": 0.01,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.011,
"x1": 0.011,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.012,
"x1": 0.012,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.013000000000000001,
"x1": 0.013000000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.014000000000000002,
"x1": 0.014000000000000002,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.015000000000000003,
"x1": 0.015000000000000003,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.016000000000000004,
"x1": 0.016000000000000004,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.017000000000000005,
"x1": 0.017000000000000005,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.018000000000000006,
"x1": 0.018000000000000006,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.019000000000000006,
"x1": 0.019000000000000006,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.020000000000000007,
"x1": 0.020000000000000007,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.021000000000000008,
"x1": 0.021000000000000008,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.02200000000000001,
"x1": 0.02200000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.02300000000000001,
"x1": 0.02300000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.02400000000000001,
"x1": 0.02400000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.025000000000000012,
"x1": 0.025000000000000012,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.026000000000000013,
"x1": 0.026000000000000013,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.027200000000000012,
"x1": 0.027200000000000012,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.028400000000000012,
"x1": 0.028400000000000012,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.02960000000000001,
"x1": 0.02960000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.03080000000000001,
"x1": 0.03080000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.03224000000000001,
"x1": 0.03224000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.03368000000000001,
"x1": 0.03368000000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.035120000000000005,
"x1": 0.035120000000000005,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.036848000000000006,
"x1": 0.036848000000000006,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.038576000000000006,
"x1": 0.038576000000000006,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.040304000000000006,
"x1": 0.040304000000000006,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.04203200000000001,
"x1": 0.04203200000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.04410560000000001,
"x1": 0.04410560000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.04617920000000001,
"x1": 0.04617920000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.04825280000000001,
"x1": 0.04825280000000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.050741120000000015,
"x1": 0.050741120000000015,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.05322944000000002,
"x1": 0.05322944000000002,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.05571776000000002,
"x1": 0.05571776000000002,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.058703744000000016,
"x1": 0.058703744000000016,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.06168972800000001,
"x1": 0.06168972800000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.06467571200000001,
"x1": 0.06467571200000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.06825889280000001,
"x1": 0.06825889280000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.07184207360000001,
"x1": 0.07184207360000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.07542525440000002,
"x1": 0.07542525440000002,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.07972507136000001,
"x1": 0.07972507136000001,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.08402488832,
"x1": 0.08402488832,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.08832470528,
"x1": 0.08832470528,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.093484485632,
"x1": 0.093484485632,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.098644265984,
"x1": 0.098644265984,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1048360024064,
"x1": 0.1048360024064,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.11102773882879999,
"x1": 0.11102773882879999,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.11845782253567999,
"x1": 0.11845782253567999,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.12588790624256,
"x1": 0.12588790624256,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.134804006690816,
"x1": 0.134804006690816,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.143720107139072,
"x1": 0.143720107139072,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1544194276769792,
"x1": 0.1544194276769792,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1651187482148864,
"x1": 0.1651187482148864,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.17795793286037503,
"x1": 0.17795793286037503,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.19079711750586367,
"x1": 0.19079711750586367,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.20620413908045004,
"x1": 0.20620413908045004,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.22161116065503642,
"x1": 0.22161116065503642,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.2370181822296228,
"x1": 0.2370181822296228,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.25242520380420913,
"x1": 0.25242520380420913,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.2678322253787955,
"x1": 0.2678322253787955,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.2832392469533818,
"x1": 0.2832392469533818,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.29864626852796816,
"x1": 0.29864626852796816,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.3140532901025545,
"x1": 0.3140532901025545,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.32946031167714085,
"x1": 0.32946031167714085,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.3448673332517272,
"x1": 0.3448673332517272,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.36027435482631354,
"x1": 0.36027435482631354,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.3756813764008999,
"x1": 0.3756813764008999,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.3941698022904035,
"x1": 0.3941698022904035,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.4126582281799071,
"x1": 0.4126582281799071,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.4311466540694107,
"x1": 0.4311466540694107,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.44963507995891433,
"x1": 0.44963507995891433,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.46812350584841794,
"x1": 0.46812350584841794,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.48661193173792155,
"x1": 0.48661193173792155,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.5087980428053259,
"x1": 0.5087980428053259,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.5309841538727302,
"x1": 0.5309841538727302,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.5531702649401345,
"x1": 0.5531702649401345,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.5797935982210197,
"x1": 0.5797935982210197,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.6064169315019049,
"x1": 0.6064169315019049,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.6383649314389672,
"x1": 0.6383649314389672,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.6703129313760294,
"x1": 0.6703129313760294,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.7086505313005041,
"x1": 0.7086505313005041,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.7546556512098738,
"x1": 0.7546556512098738,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
},
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.8098617951011173,
"x1": 0.8098617951011173,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
}
],
"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 `A <-> B` and `B <-> C` (time steps shown in dashed lines)"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
-0.000610755501584553,
0.8104725506027018
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-2.7777777777777777,
52.77777777777778
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['blue', 'orange', 'green'], show_intervals=True)"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "042a23ff-84de-4273-ae7b-09b73b740b4c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"0: A <-> B\n",
"Final concentrations: [A] = 1.096 ; [B] = 3.898\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 3.55592\n",
" Formula used: [B] / [A]\n",
"2. Ratio of forward/reverse reaction rates: 4.0\n",
"Discrepancy between the two values: 11.1 %\n",
"Reaction IS in equilibrium (within 15% tolerance)\n",
"\n",
"1: B <-> C\n",
"Final concentrations: [B] = 3.898 ; [C] = 45.01\n",
"1. Ratio of reactant/product concentrations, adjusted for reaction orders: 11.5475\n",
" Formula used: [C] / [B]\n",
"2. Ratio of forward/reverse reaction rates: 12.0\n",
"Discrepancy between the two values: 3.771 %\n",
"Reaction IS in equilibrium (within 15% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 7,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dynamics.is_in_equilibrium(tolerance=15)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "bed9100c-f575-4591-bf8e-a32de741fa7a",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "markdown",
"id": "1f447754-5017-4b48-a4f5-fc9049b7de64",
"metadata": {},
"source": [
"# PART 2 - This is the starting point of fitting the data from part 1. \n",
"### We're given the data of the time evolution of `A` and `C`, and we want to try to model the complex reaction `A <-> C`"
]
},
{
"cell_type": "markdown",
"id": "b5f75cfb-45b4-4fd2-ad4c-c2a2084ca62d",
"metadata": {},
"source": [
"Let's start by taking stock of the actual data (saved during the simulation of part 1):"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "f26c98c3-802c-4c38-a726-06ac4a77211a",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" C | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0.000000 | \n",
" 50.000000 | \n",
" 0.000000 | \n",
" Initial state | \n",
"
\n",
" \n",
" | 1 | \n",
" 0.004000 | \n",
" 48.400000 | \n",
" 0.000000 | \n",
" 1st reaction step | \n",
"
\n",
" \n",
" | 2 | \n",
" 0.008000 | \n",
" 46.864000 | \n",
" 0.076800 | \n",
" | \n",
"
\n",
" \n",
" | 3 | \n",
" 0.010000 | \n",
" 46.126413 | \n",
" 0.150067 | \n",
" | \n",
"
\n",
" \n",
" | 4 | \n",
" 0.011000 | \n",
" 45.764849 | \n",
" 0.194599 | \n",
" | \n",
"
\n",
" \n",
" | ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
" ... | \n",
"
\n",
" \n",
" | 81 | \n",
" 0.638365 | \n",
" 1.497612 | \n",
" 44.279102 | \n",
" | \n",
"
\n",
" \n",
" | 82 | \n",
" 0.670313 | \n",
" 1.384698 | \n",
" 44.483579 | \n",
" | \n",
"
\n",
" \n",
" | 83 | \n",
" 0.708651 | \n",
" 1.276811 | \n",
" 44.678990 | \n",
" | \n",
"
\n",
" \n",
" | 84 | \n",
" 0.754656 | \n",
" 1.179000 | \n",
" 44.856174 | \n",
" | \n",
"
\n",
" \n",
" | 85 | \n",
" 0.809862 | \n",
" 1.096061 | \n",
" 45.006431 | \n",
" last reaction step | \n",
"
\n",
" \n",
"
\n",
"
86 rows × 4 columns
\n",
"
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_0",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C'(t)",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"xaxis": "x",
"y": [
-9.600000000000001,
9.600000000000001,
30.822399999999995,
41.899315200000004,
46.41209925119996,
50.12635364006394,
53.750260495463436,
57.28550409970293,
60.73373957343236,
64.09659336783142,
67.37566374856453,
70.57252127164378,
73.6887092513349,
76.72574422023837,
79.68511638167638,
82.56829005451397,
85.37670411053989,
88.11177240453134,
90.77488419712517,
93.25115170979711,
96.13957259742529,
99.07790484714667,
101.92046438241448,
104.54659440517338,
107.5882355929242,
110.65951435651903,
113.47432857809292,
116.70583563316939,
119.93843550873544,
123.00561986850903,
125.7843600870674,
128.9334704744358,
132.04015897436716,
134.81271347105132,
137.9016042505301,
140.8923754152064,
143.50321860426106,
146.3378372360919,
149.00327850294707,
151.24788504239746,
153.5792410492994,
155.6570928893061,
157.28583223293128,
158.81822392583024,
160.00570033308645,
160.73927115789127,
161.15321666154205,
161.1470905253102,
160.59654024240706,
159.57010292399718,
157.74117244028037,
155.40924682975253,
152.00694437392258,
148.12617713177906,
142.93564276949814,
137.3683550357964,
130.3312539141483,
123.11744183441544,
114.40716709576532,
105.42102218018886,
96.740520552774,
88.4834623838841,
80.71821343668819,
73.4782586428164,
66.77284231425006,
60.594715541430105,
54.925748151563766,
49.74096700560449,
45.0114370714125,
40.89269386418346,
36.4218071012117,
32.203333359839235,
28.45902149162862,
25.14009031115279,
22.201321677305486,
19.712244496792778,
17.086778023456304,
14.679131339928404,
12.695565997208973,
10.664110616744892,
8.931080086504835,
7.218212562579652,
5.807951609959446,
4.5308738538129205,
3.3379213974987465,
2.1055557740023687
],
"yaxis": "y"
},
{
"hovertemplate": "Linear Fit :
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_1",
"line": {
"color": "red",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "Linear Fit",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"xaxis": "x",
"y": [
113.42798208145142,
111.81493139540385,
110.26640273679817,
109.52279927493572,
109.1582858489891,
108.79732776648709,
108.4398818929536,
108.08590570913911,
107.73535730144269,
107.38819535248909,
107.04437913185845,
106.70386848696594,
106.36662383408895,
106.03260614953949,
105.70177696097923,
105.374098338875,
105.04953288809227,
104.72804373962461,
104.40959454245655,
104.09414945555791,
103.71917787689733,
103.34843115280913,
102.98184991296881,
102.61937578079113,
102.18926646991984,
101.76490745719985,
101.3462028314711,
100.85042974677746,
100.36253095700818,
99.88235042545858,
99.40973582461987,
98.8514989608544,
98.30373379707765,
97.76619534212793,
97.13313555120666,
96.51412619032996,
95.90877862665047,
95.19830497187621,
94.50644058463351,
93.83257889786907,
93.04484911767737,
92.2813987399005,
91.5412988859598,
90.68013724595367,
89.85010980445531,
89.04982520175977,
88.12359735382402,
87.23651593943336,
86.21655578074187,
85.24730298891909,
84.14135687870198,
83.099903668832,
81.92209191687388,
80.82462352488358,
79.59621227236056,
78.46558814793033,
77.21519432984509,
76.08077586569325,
74.8437654924751,
73.74040514908454,
72.75445992901044,
71.87208506425337,
71.0813874531863,
70.37208242565798,
69.73522302971479,
69.16298477751013,
68.64849300945836,
68.18568319056777,
67.76918681290061,
67.39423734554269,
66.98906292960375,
66.63215646936078,
66.31767353226593,
66.04050603734913,
65.79618089567082,
65.58077507196423,
65.35285749424138,
65.15726318178356,
64.98938995856217,
64.81647908112848,
64.67295116531996,
64.52997607789382,
64.4161403896418,
64.30737317644173,
64.20876459144948,
64.1251493750498
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Curve vs Fit:"
},
"tracegroupgap": 0
},
"margin": {
"t": 60
},
"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": "d/dt C(t) as a function of A(t), alongside its least-square fit"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
1.096061014963001,
50
],
"title": {
"text": "A(t)"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-19.086289814530115,
170.63950647607217
],
"title": {
"text": "C'(t)"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.estimate_rate_constants(t=t_arr, reactant_conc=A_conc, product_conc=C_conc, reactant_name=\"A\", product_name=\"C\")"
]
},
{
"cell_type": "markdown",
"id": "94af05ee-037a-4223-a1a7-fa681baf5ae1",
"metadata": {},
"source": [
"### The least-square fit is awful : the complex reaction `A <-> C` doesn't seem to be amenable to being modeled as a simple reaction with some suitable rate constants\n",
"Probably not too surprising given our \"secret\" knowledge from Part 1 that the complex reaction originates from 2 elementary reactions where one doesn't dominate the other one in terms of reaction kinetics"
]
},
{
"cell_type": "markdown",
"id": "8951650d-cb8c-4def-99c3-4e465a12b9d4",
"metadata": {},
"source": [
"### A glance at the above diagram reveals much-better linear fits, if split into 2 portions, one where A(t) ranges from 0 to about 24, and one from about 24 to 50 \n",
"Indeed, revisiting the early portion of the time plot from Part 1, one can see an inflection in the [C] green curve roughly around time t=0.1, which is when [A] is around 24 (blue). That's shortly after the peak of the mystery intermediate B (orange). \n",
"\n",
"We'll pick time **t=0.1** as the divider between the 2 domains of the `A <-> C` time evolution that we want to model. "
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "ef2fb66f-1a60-4bd4-9d68-8ac5fa742c7f",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "blue",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "B",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "B",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
1.6,
3.0592,
3.72352,
4.0405520896,
4.3502977480192,
4.652890957773261,
4.948463392141688,
5.237144454078118,
5.519061314470442,
5.794338949761611,
6.06310017894175,
6.32546569992207,
6.581554125300875,
6.831482017531776,
7.075363923504084,
7.313312408545171,
7.5454380898544215,
7.771849669378253,
7.992653966135512,
8.251016344375778,
8.50160392227522,
8.744591847889835,
8.980151621934787,
9.254111081672768,
9.517852592409483,
9.771654355888268,
10.06461425570106,
10.34403228247831,
10.610353918423153,
10.864011226690561,
11.153705647116896,
11.426352050741748,
11.68263146812472,
11.971313970046767,
12.238283882218882,
12.48459437640964,
12.756584245234146,
13.001661660982421,
13.22141784776997,
13.456548650461645,
13.659443519072163,
13.832439116637216,
14.006780263898069,
14.144166733312131,
14.247911517843868,
14.335704567054655,
14.383519462948529,
14.39831953025766,
14.367895421717208,
14.284773753767965,
14.153860578422783,
13.949799277149335,
13.700113776207086,
13.359033005681415,
12.981434422909333,
12.500245076469138,
12.000257870459277,
11.394466723614562,
10.796345999818495,
10.21842044623623,
9.668583519552405,
9.151423390694013,
8.669195596553909,
8.222534188628476,
7.810969571439292,
7.433303638592873,
7.087879744907972,
6.772775341526878,
6.4859378862626595,
6.173147562576985,
5.895089242926046,
5.648327074911617,
5.429627797802673,
5.235999085365918,
5.064704243500656,
4.882973465060556,
4.72661132208144,
4.592154622601183,
4.4534695731066085,
4.338204866850339,
4.223286057749926,
4.1317229582794965,
4.044199736392051,
3.9648260660630523,
3.8975080860315083
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=C
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "C",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
0,
0.07680000000000001,
0.1500672,
0.1945993728,
0.2428913985024,
0.294852080080128,
0.350391919493327,
0.40942308827953394,
0.47185939864019183,
0.5376162750151969,
0.606610726137321,
0.6787613175584847,
0.753988144639991,
0.8322128059989615,
0.9133583774033439,
0.9973493861079896,
1.0841117856244238,
1.1735729309170524,
1.2656615540186744,
1.3792369772662034,
1.4963965282524951,
1.6170239488993554,
1.7410056427702898,
1.8936756146717337,
2.050859761277912,
2.2123750160185076,
2.4111770567145268,
2.615710383966741,
2.825684289832717,
3.040817806232308,
3.3048437305852914,
3.5755306949838888,
3.852440677883787,
4.191696079113364,
4.538727317661146,
4.892866710299698,
5.325602277242,
5.766791591462846,
6.215445088356687,
6.761670791823513,
7.316049463969531,
7.87716580507307,
8.557018909690294,
9.242944390659794,
9.933009357668057,
10.763950338029792,
11.596039759651704,
12.592947674008723,
13.584782654712381,
14.764902570548777,
15.928842885217733,
17.301186633802583,
18.639461254958444,
20.199014588706994,
21.69808977152376,
23.4195563927212,
25.04478383968739,
26.877577097667665,
28.57013122315092,
30.1260250239579,
31.551097797737526,
32.85255825184311,
34.03835230949977,
35.11672048418892,
36.09589355376397,
36.98388866349439,
37.788377927306854,
38.51660896708666,
39.175362291431625,
39.89004889222113,
40.52212605413672,
41.080826776657865,
41.57445107360825,
42.010428169804214,
42.395386054568036,
42.80319040125422,
43.153564364593,
43.454536077815554,
43.764733037188044,
44.02236442000321,
44.279101550040785,
44.483579328993194,
44.678989762749055,
44.85617420700618,
45.006430899005466
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"shapes": [
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1,
"x1": 0.1,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
}
],
"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 `A <-> B` and `B <-> C`"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0,
0.4
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-2.7777777777777777,
52.77777777777778
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['blue', 'orange', 'green'], xrange=[0, 0.4], \n",
" vertical_lines=[0.1])"
]
},
{
"cell_type": "markdown",
"id": "6d4a4dbd-de22-471c-a1a4-5507941d92e1",
"metadata": {},
"source": [
"#### Let's locate where the t = 0.1 point occurs in the data"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "3795ba32-68ec-4d20-9b6b-c2a117810741",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" search_value | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" C | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 47 | \n",
" 0.1 | \n",
" 0.098644 | \n",
" 24.020441 | \n",
" 14.383519 | \n",
" 11.59604 | \n",
" | \n",
"
\n",
" \n",
"
\n",
"
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_0",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C'(t)",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745
],
"xaxis": "x",
"y": [
-9.600000000000001,
9.600000000000001,
30.822399999999995,
41.899315200000004,
46.41209925119996,
50.12635364006394,
53.750260495463436,
57.28550409970293,
60.73373957343236,
64.09659336783142,
67.37566374856453,
70.57252127164378,
73.6887092513349,
76.72574422023837,
79.68511638167638,
82.56829005451397,
85.37670411053989,
88.11177240453134,
90.77488419712517,
93.25115170979711,
96.13957259742529,
99.07790484714667,
101.92046438241448,
104.54659440517338,
107.5882355929242,
110.65951435651903,
113.47432857809292,
116.70583563316939,
119.93843550873544,
123.00561986850903,
125.7843600870674,
128.9334704744358,
132.04015897436716,
134.81271347105132,
137.9016042505301,
140.8923754152064,
143.50321860426106,
146.3378372360919,
149.00327850294707,
151.24788504239746,
153.5792410492994,
155.6570928893061,
157.28583223293128,
158.81822392583024,
160.00570033308645,
160.73927115789127,
161.15321666154205,
161.37579227171
],
"yaxis": "y"
},
{
"hovertemplate": "Linear Fit :
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_1",
"line": {
"color": "red",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "Linear Fit",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745
],
"xaxis": "x",
"y": [
27.884687837813658,
37.86653236097197,
47.44910310320398,
52.05065357362378,
54.30632748137833,
56.54000029158675,
58.75193892805845,
60.94240650747139,
63.11166239864258,
65.25996228083812,
67.38755820114,
69.49469863088422,
71.58162852118608,
73.64858935756718,
75.6958192136994,
77.72355280427968,
79.73202153705108,
81.72145356398255,
83.69207383162268,
85.64410413064044,
87.96449494735077,
90.25874161258528,
92.52721152047056,
94.77026591569839,
97.43185882546598,
100.0578678675941,
102.64888655739884,
105.71681857775232,
108.73602306068611,
111.70746558907928,
114.63208879264752,
118.086557786958,
121.4762260393668,
124.80260959875409,
128.72009617341507,
132.550636188119,
136.29663457204285,
140.6931719041299,
144.97455177910996,
149.14452774178562,
154.01913971780584,
158.7435064336392,
163.32337595512934,
168.65239733939342,
173.78875476613527,
178.74105821665978,
184.47272086748956,
189.96213842542602
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Curve vs Fit:"
},
"tracegroupgap": 0
},
"margin": {
"t": 60
},
"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": "d/dt C(t) as a function of A(t), alongside its least-square fit"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
24.020440777399745,
50
],
"title": {
"text": "A(t)"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-20.686785468079222,
201.04892389350525
],
"title": {
"text": "C'(t)"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.estimate_rate_constants(t=t_arr_early, reactant_conc=A_conc_early, product_conc=C_conc_early, \n",
" reactant_name=\"A\", product_name=\"C\")"
]
},
{
"cell_type": "markdown",
"id": "49e2b683-f622-4d9a-a6e8-e687a7b44f34",
"metadata": {},
"source": [
"Trying to fit an elementary reaction to that region leads to a **negative** reverse rate constant! \n",
"It's not surprise that an elementary reaction is a good fit, if one observes what happens to the time evolution of the concentrations. Repeating the earlier plot, but only showing `A` and `C` (i.e. hiding the intermediary `B`):"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "41162cab-0e40-4a68-98ab-9909a462ebd8",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "blue",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=C
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "C",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
0,
0.07680000000000001,
0.1500672,
0.1945993728,
0.2428913985024,
0.294852080080128,
0.350391919493327,
0.40942308827953394,
0.47185939864019183,
0.5376162750151969,
0.606610726137321,
0.6787613175584847,
0.753988144639991,
0.8322128059989615,
0.9133583774033439,
0.9973493861079896,
1.0841117856244238,
1.1735729309170524,
1.2656615540186744,
1.3792369772662034,
1.4963965282524951,
1.6170239488993554,
1.7410056427702898,
1.8936756146717337,
2.050859761277912,
2.2123750160185076,
2.4111770567145268,
2.615710383966741,
2.825684289832717,
3.040817806232308,
3.3048437305852914,
3.5755306949838888,
3.852440677883787,
4.191696079113364,
4.538727317661146,
4.892866710299698,
5.325602277242,
5.766791591462846,
6.215445088356687,
6.761670791823513,
7.316049463969531,
7.87716580507307,
8.557018909690294,
9.242944390659794,
9.933009357668057,
10.763950338029792,
11.596039759651704,
12.592947674008723,
13.584782654712381,
14.764902570548777,
15.928842885217733,
17.301186633802583,
18.639461254958444,
20.199014588706994,
21.69808977152376,
23.4195563927212,
25.04478383968739,
26.877577097667665,
28.57013122315092,
30.1260250239579,
31.551097797737526,
32.85255825184311,
34.03835230949977,
35.11672048418892,
36.09589355376397,
36.98388866349439,
37.788377927306854,
38.51660896708666,
39.175362291431625,
39.89004889222113,
40.52212605413672,
41.080826776657865,
41.57445107360825,
42.010428169804214,
42.395386054568036,
42.80319040125422,
43.153564364593,
43.454536077815554,
43.764733037188044,
44.02236442000321,
44.279101550040785,
44.483579328993194,
44.678989762749055,
44.85617420700618,
45.006430899005466
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"shapes": [
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1,
"x1": 0.1,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
}
],
"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 `A <-> C`"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0,
0.4
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-2.7777777777777777,
52.77777777777778
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['blue', 'green'], xrange=[0, 0.4], vertical_lines=[0.1], \n",
" chemicals=['A', 'C'], title=\"Changes in concentration for `A <-> C`\")"
]
},
{
"cell_type": "markdown",
"id": "5f418b9d-8bd4-4ee7-aa95-1d233be40c0e",
"metadata": {},
"source": [
"In the zone to the left of the vertical dashed line: \n",
"when the reactant `A` is plentiful, the rate of change (gradient) of the product `C` is low - and vice versa. \n",
"Does that look like an elementary reaction in its kinetics? Nope!"
]
},
{
"cell_type": "markdown",
"id": "652e8cc0-b053-40d1-9d1c-2f2a30f59469",
"metadata": {},
"source": [
"### II. And now let's consider the LATE region, when t > 0.1"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "2d61a783-e1e5-473a-9fd8-cba5cb842a85",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Total REACTANT + PRODUCT has a median of 42.74, \n",
" with standard deviation 3.695 (ideally should be zero)\n",
"The sum of the time derivatives of reactant and product \n",
" has a median of 16.91 (ideally should be zero)\n",
"Least square fit: Y = 4.132 + 7.995 X\n",
" where X is the array [A] and Y is the time gradient of C\n",
"\n",
"-> ESTIMATED RATE CONSTANTS: kF = 8.091 , kR = -0.09668\n"
]
},
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "C'(t) :
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_0",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C'(t)",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"xaxis": "x",
"y": [
160.80367045416915,
159.57010292399718,
157.74117244028037,
155.40924682975253,
152.00694437392258,
148.12617713177906,
142.93564276949814,
137.3683550357964,
130.3312539141483,
123.11744183441544,
114.40716709576532,
105.42102218018886,
96.740520552774,
88.4834623838841,
80.71821343668819,
73.4782586428164,
66.77284231425006,
60.594715541430105,
54.925748151563766,
49.74096700560449,
45.0114370714125,
40.89269386418346,
36.4218071012117,
32.203333359839235,
28.45902149162862,
25.14009031115279,
22.201321677305486,
19.712244496792778,
17.086778023456304,
14.679131339928404,
12.695565997208973,
10.664110616744892,
8.931080086504835,
7.218212562579652,
5.807951609959446,
4.5308738538129205,
3.3379213974987465,
2.1055557740023687
],
"yaxis": "y"
},
{
"hovertemplate": "Linear Fit :
A(t)=%{x}
value=%{y}",
"legendgroup": "wide_variable_1",
"line": {
"color": "red",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "Linear Fit",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"xaxis": "x",
"y": [
188.08057584811036,
180.39435031741746,
171.62413959464521,
163.3653609578865,
154.02525192273418,
145.322269950631,
135.58090421922432,
126.61499554799929,
116.69930691746858,
107.70330893302585,
97.89375172300169,
89.14404626693198,
81.3254489037543,
74.32816989630064,
68.05789632420986,
62.433070213176315,
57.3827417644395,
52.84486237854385,
48.76491564401451,
45.09480947994312,
41.79197133650465,
38.818602373278516,
35.60554798081531,
32.775261011375925,
30.281394807988576,
28.083442020355825,
26.145930818323198,
24.437751326242704,
22.630352967871623,
21.0792798002161,
19.748036325727437,
18.37684398882845,
17.238660080397377,
16.10486013006543,
15.202137145175907,
14.339607433573544,
13.557636177047613,
12.89456312070189
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Curve vs Fit:"
},
"tracegroupgap": 0
},
"margin": {
"t": 60
},
"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": "d/dt C(t) as a function of A(t), alongside its least-square fit"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
1.096061014963001,
23.008732795733597
],
"title": {
"text": "A(t)"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-8.226389785670298,
198.41252140778303
],
"title": {
"text": "C'(t)"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.estimate_rate_constants(t=t_arr_late, reactant_conc=A_conc_late, product_conc=C_conc_late, \n",
" reactant_name=\"A\", product_name=\"C\")"
]
},
{
"cell_type": "markdown",
"id": "222e6b40-5f4f-45eb-bab8-7fa208675f7d",
"metadata": {},
"source": [
"This time we have an adequate linear fit AND meaningful rate constants : kF of about 8 and kR of about 0. Do those numbers sound familiar? A definite resemblance to the kF=8, kR=2 of the SLOWER elementary reaction `A <-> B`! \n",
"\n",
"#### The slower `A <-> B` reaction dominates the kinetics from about t=0.1 \n",
"\n",
"Let's see the graph again:"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "0c1a9e04-5622-480c-beca-525857353618",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "blue",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
50,
48.4,
46.864,
46.1264128,
45.764848537599995,
45.4068108534784,
45.05225696214661,
44.701144688364984,
44.35343245764235,
44.00907928688937,
43.668044775223194,
43.33028909492093,
42.99577298251945,
42.664457730059134,
42.33630517646926,
42.01127769909257,
41.689338205346836,
41.37045012452115,
41.05457739970469,
40.74168447984581,
40.36974667835801,
40.00199954947228,
39.638384203210805,
39.278842735294916,
38.85221330365549,
38.4312876463126,
38.015970628093214,
37.524208687584405,
37.04025733355494,
36.56396179174412,
36.09517096707712,
35.5414506222978,
34.99811725427435,
34.464927853991476,
33.83698995083985,
33.22298880011996,
32.62253891329065,
31.91781347752384,
31.231546747554717,
30.563137063873327,
29.781780557714825,
29.02450701695829,
28.290395078289695,
27.436200826411618,
26.612888876028055,
25.819079124488056,
24.900345094915533,
24.020440777399745,
23.008732795733597,
22.04732192357039,
20.950323675683237,
19.917296536359462,
18.74901408904806,
17.660424968834448,
16.44195240561157,
15.320475805566884,
14.08019853080964,
12.954958289853312,
11.727956178717752,
10.633522777030562,
9.655554529805844,
8.780318682710046,
7.996018357462855,
7.292452093946299,
6.6607453271825845,
6.093136874796711,
5.5828076979127115,
5.123742327785151,
4.710615691386435,
4.33869982230569,
3.9368035452018617,
3.5827847029372126,
3.270846148430494,
2.9959211285890497,
2.753572744829843,
2.539909701931287,
2.313836133685203,
2.1198243133255397,
1.9533092995832424,
1.7817973897053232,
1.6394307131464319,
1.4976123922092663,
1.384697712727285,
1.276810500858867,
1.178999726930746,
1.096061014963001
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "B",
"line": {
"color": "orange",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "B",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
1.6,
3.0592,
3.72352,
4.0405520896,
4.3502977480192,
4.652890957773261,
4.948463392141688,
5.237144454078118,
5.519061314470442,
5.794338949761611,
6.06310017894175,
6.32546569992207,
6.581554125300875,
6.831482017531776,
7.075363923504084,
7.313312408545171,
7.5454380898544215,
7.771849669378253,
7.992653966135512,
8.251016344375778,
8.50160392227522,
8.744591847889835,
8.980151621934787,
9.254111081672768,
9.517852592409483,
9.771654355888268,
10.06461425570106,
10.34403228247831,
10.610353918423153,
10.864011226690561,
11.153705647116896,
11.426352050741748,
11.68263146812472,
11.971313970046767,
12.238283882218882,
12.48459437640964,
12.756584245234146,
13.001661660982421,
13.22141784776997,
13.456548650461645,
13.659443519072163,
13.832439116637216,
14.006780263898069,
14.144166733312131,
14.247911517843868,
14.335704567054655,
14.383519462948529,
14.39831953025766,
14.367895421717208,
14.284773753767965,
14.153860578422783,
13.949799277149335,
13.700113776207086,
13.359033005681415,
12.981434422909333,
12.500245076469138,
12.000257870459277,
11.394466723614562,
10.796345999818495,
10.21842044623623,
9.668583519552405,
9.151423390694013,
8.669195596553909,
8.222534188628476,
7.810969571439292,
7.433303638592873,
7.087879744907972,
6.772775341526878,
6.4859378862626595,
6.173147562576985,
5.895089242926046,
5.648327074911617,
5.429627797802673,
5.235999085365918,
5.064704243500656,
4.882973465060556,
4.72661132208144,
4.592154622601183,
4.4534695731066085,
4.338204866850339,
4.223286057749926,
4.1317229582794965,
4.044199736392051,
3.9648260660630523,
3.8975080860315083
],
"yaxis": "y"
},
{
"hovertemplate": "Chemical=C
SYSTEM TIME=%{x}
concentration=%{y}",
"legendgroup": "C",
"line": {
"color": "green",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "C",
"orientation": "v",
"showlegend": true,
"type": "scatter",
"x": [
0,
0.004,
0.008,
0.01,
0.011,
0.012,
0.013000000000000001,
0.014000000000000002,
0.015000000000000003,
0.016000000000000004,
0.017000000000000005,
0.018000000000000006,
0.019000000000000006,
0.020000000000000007,
0.021000000000000008,
0.02200000000000001,
0.02300000000000001,
0.02400000000000001,
0.025000000000000012,
0.026000000000000013,
0.027200000000000012,
0.028400000000000012,
0.02960000000000001,
0.03080000000000001,
0.03224000000000001,
0.03368000000000001,
0.035120000000000005,
0.036848000000000006,
0.038576000000000006,
0.040304000000000006,
0.04203200000000001,
0.04410560000000001,
0.04617920000000001,
0.04825280000000001,
0.050741120000000015,
0.05322944000000002,
0.05571776000000002,
0.058703744000000016,
0.06168972800000001,
0.06467571200000001,
0.06825889280000001,
0.07184207360000001,
0.07542525440000002,
0.07972507136000001,
0.08402488832,
0.08832470528,
0.093484485632,
0.098644265984,
0.1048360024064,
0.11102773882879999,
0.11845782253567999,
0.12588790624256,
0.134804006690816,
0.143720107139072,
0.1544194276769792,
0.1651187482148864,
0.17795793286037503,
0.19079711750586367,
0.20620413908045004,
0.22161116065503642,
0.2370181822296228,
0.25242520380420913,
0.2678322253787955,
0.2832392469533818,
0.29864626852796816,
0.3140532901025545,
0.32946031167714085,
0.3448673332517272,
0.36027435482631354,
0.3756813764008999,
0.3941698022904035,
0.4126582281799071,
0.4311466540694107,
0.44963507995891433,
0.46812350584841794,
0.48661193173792155,
0.5087980428053259,
0.5309841538727302,
0.5531702649401345,
0.5797935982210197,
0.6064169315019049,
0.6383649314389672,
0.6703129313760294,
0.7086505313005041,
0.7546556512098738,
0.8098617951011173
],
"xaxis": "x",
"y": [
0,
0,
0.07680000000000001,
0.1500672,
0.1945993728,
0.2428913985024,
0.294852080080128,
0.350391919493327,
0.40942308827953394,
0.47185939864019183,
0.5376162750151969,
0.606610726137321,
0.6787613175584847,
0.753988144639991,
0.8322128059989615,
0.9133583774033439,
0.9973493861079896,
1.0841117856244238,
1.1735729309170524,
1.2656615540186744,
1.3792369772662034,
1.4963965282524951,
1.6170239488993554,
1.7410056427702898,
1.8936756146717337,
2.050859761277912,
2.2123750160185076,
2.4111770567145268,
2.615710383966741,
2.825684289832717,
3.040817806232308,
3.3048437305852914,
3.5755306949838888,
3.852440677883787,
4.191696079113364,
4.538727317661146,
4.892866710299698,
5.325602277242,
5.766791591462846,
6.215445088356687,
6.761670791823513,
7.316049463969531,
7.87716580507307,
8.557018909690294,
9.242944390659794,
9.933009357668057,
10.763950338029792,
11.596039759651704,
12.592947674008723,
13.584782654712381,
14.764902570548777,
15.928842885217733,
17.301186633802583,
18.639461254958444,
20.199014588706994,
21.69808977152376,
23.4195563927212,
25.04478383968739,
26.877577097667665,
28.57013122315092,
30.1260250239579,
31.551097797737526,
32.85255825184311,
34.03835230949977,
35.11672048418892,
36.09589355376397,
36.98388866349439,
37.788377927306854,
38.51660896708666,
39.175362291431625,
39.89004889222113,
40.52212605413672,
41.080826776657865,
41.57445107360825,
42.010428169804214,
42.395386054568036,
42.80319040125422,
43.153564364593,
43.454536077815554,
43.764733037188044,
44.02236442000321,
44.279101550040785,
44.483579328993194,
44.678989762749055,
44.85617420700618,
45.006430899005466
],
"yaxis": "y"
}
],
"layout": {
"autosize": true,
"legend": {
"title": {
"text": "Chemical"
},
"tracegroupgap": 0
},
"shapes": [
{
"line": {
"color": "gray",
"dash": "dot",
"width": 1
},
"type": "line",
"x0": 0.1,
"x1": 0.1,
"xref": "x",
"y0": 0,
"y1": 1,
"yref": "y domain"
}
],
"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 `A <-> B` and `B <-> C`"
},
"xaxis": {
"anchor": "y",
"domain": [
0,
1
],
"range": [
0,
0.4
],
"title": {
"text": "SYSTEM TIME"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
-2.7777777777777777,
52.77777777777778
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": "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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['blue', 'orange', 'green'], xrange=[0, 0.4], \n",
" vertical_lines=[0.1])"
]
},
{
"cell_type": "markdown",
"id": "57e7c2b9-c693-4e16-92f6-6e0a94b18a2b",
"metadata": {},
"source": [
"A possible conclusion to draw is that, in this case, the earlier part of the complex (compound) reaction `A <-> C` cannot be modeled by an elementary reaction, while the later part can indeed be modeled by a 1st order elementary reaction, with kinetics similar to the slower `A <-> B` reaction"
]
},
{
"cell_type": "markdown",
"id": "e9069c36-6852-4530-bd51-7a18aaeb4eb7",
"metadata": {},
"source": [
"**The intuition:** imagine `A <-> B <-> C` as a supply line. \n",
"`A <-> B` is slow, but the moment something arrives in B, it's very quickly moved to C. \n",
"The slow link (`A <-> B`) largely determines the kinetics of the supply line."
]
},
{
"cell_type": "markdown",
"id": "18171c4e-eb73-42c7-a5b7-c74c61357b20",
"metadata": {},
"source": [
"### While it's a well-known Chemistry notion that the slower reaction is the rate-determining step in a chain, we saw in this experiment that the complex reaction could be roughly modeled with the rate constants of the slower reaction only after some time. "
]
},
{
"cell_type": "markdown",
"id": "106971a6-169a-41e8-98a5-7d74fead715c",
"metadata": {},
"source": [
"If we were interested in early transients (for example, if diffusion quickly intervened), we couldn't use that model."
]
},
{
"cell_type": "markdown",
"id": "43c44071-8633-4a25-a236-3ce6f8295de5",
"metadata": {},
"source": [
"#### In the continuation experiment, `cascade_2_b`, we explore the scenario where the 2 elementary reactions are much more different from each other"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a485900d-f5ef-4bd3-9c4b-3896ad3de241",
"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": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}