{
"cells": [
{
"cell_type": "markdown",
"id": "3bbe8002-bdf3-490c-bde0-80dd3713a3d0",
"metadata": {},
"source": [
"## A complex (composite/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`"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "313e55f6-1051-45a4-ac4a-64891c199673",
"metadata": {},
"outputs": [],
"source": [
"LAST_REVISED = \"July 26, 2024\"\n",
"LIFE123_VERSION = \"1.0.0.beta.38\" # Version this experiment is based on"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "fb596420-0b1d-4667-8d37-187290ab622d",
"metadata": {},
"outputs": [],
"source": [
"#import set_path # Using MyBinder? Uncomment this before running the next cell!\n",
" # Importing this module will add the project's home directory to sys.path"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "3924c013",
"metadata": {
"tags": []
},
"outputs": [],
"source": [
"#import sys\n",
"#sys.path.append(\"C:/some_path/my_env_or_install\") # CHANGE to the folder containing your venv or libraries installation!\n",
"# NOTE: If any of the imports below can't find a module, uncomment the lines above, or try: import set_path\n",
"\n",
"from life123 import check_version, UniformCompartment, PlotlyHelper"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "323423d1-ad47-4fc4-ac23-36ab55488ba6",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"OK\n"
]
}
],
"source": [
"check_version(LIFE123_VERSION)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "fe5d6bfa-7e62-491a-a57f-be5105081a9d",
"metadata": {},
"outputs": [],
"source": []
},
{
"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": 5,
"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', 'B', 'C'}\n"
]
}
],
"source": [
"# Instantiate the simulator and specify the chemicals\n",
"# Here we use the \"mid\" preset for the variable steps, a compromise between speed and accuracy\n",
"dynamics = UniformCompartment(preset=\"mid\")\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": 6,
"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', 'B', 'C'}\n"
]
}
],
"source": [
"dynamics.set_conc({\"A\": 50.}, snapshot=True) # Set the initial concentrations of all the chemicals\n",
"dynamics.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "2502cd11-0df9-4303-8895-98401a1df7b8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Some steps were backtracked and re-done, to prevent negative concentrations or excessively large concentration changes\n",
"85 total step(s) taken\n",
"Number of step re-do's because of elective soft aborts: 1\n",
"Norm usage: {'norm_A': 24, 'norm_B': 25, 'norm_C': 23, 'norm_D': 23}\n"
]
}
],
"source": [
"dynamics.single_compartment_react(initial_step=0.01, duration=0.8,\n",
" snapshots={\"initial_caption\": \"1st reaction step\",\n",
" \"final_caption\": \"last reaction step\"},\n",
" variable_steps=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"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": "darkturquoise",
"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": [
-0.0007878033026275461,
0.8106495984037448
],
"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=['darkturquoise', 'orange', 'green'], show_intervals=True)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"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\n",
"Discrepancy between the two values: 11.1 %\n",
"Reaction IS in equilibrium (within 12% 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\n",
"Discrepancy between the two values: 3.771 %\n",
"Reaction IS in equilibrium (within 12% tolerance)\n",
"\n"
]
},
{
"data": {
"text/plain": [
"True"
]
},
"execution_count": 25,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"dynamics.is_in_equilibrium(tolerance=12)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "3d157b9c-f26a-4564-a250-ecc7514ff064",
"metadata": {},
"outputs": [],
"source": []
},
{
"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": 10,
"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",
" Initialized 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_simple(t=t_arr, A_conc=A_conc, B_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 the intermediate product builds up at one point"
]
},
{
"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": 15,
"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": "darkturquoise",
"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=['darkturquoise', '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": 16,
"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_simple(t=t_arr_early, A_conc=A_conc_early, B_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 no 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": 22,
"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": "darkturquoise",
"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": "iVBORw0KGgoAAAANSUhEUgAABGgAAAFoCAYAAAALss2XAAAgAElEQVR4Xuy9C5BdV3moufrdrX5I6tbTkixZkmXJsuVgBxPADnbCgHNnMB6qAty6Ra5vYCi4Gc9UyEwB4Ra5lxpedQdSNZ4EDwGuE+69MaSGMqZyA0wSnNiBwmATZGRJtiQky7beLXW3+v3Q/P8+Zx+dPjqnz36svffau79Nndrnsffa//7+0y33x7/+1XJFNsMGAQhAAAIQgAAEIAABCEAAAhCAAAQgkBmBFgRNZuy5MAQgAAEIQAACEIAABCAAAQhAAAIQ8AggaPgiQAACEIAABCAAAQhAAAIQgAAEIACBjAkgaDJOAJeHAAQgAAEIQAACEIAABCAAAQhAAAIIGr4DEIAABCAAAQhAAAIQgAAEIAABCEAgYwIImowTwOUhAAEIQAACEIAABCAAAQhAAAIQgACChu8ABCAAAQhAAAIQgAAEIAABCEAAAhDImACCJuMEcHkIQAACEIAABCAAAQhAAAIQgAAEIICg4TsAAQhAAAIQgAAEIAABCEAAAhCAAAQyJoCgyTgBXB4CEIAABCAAAQhAAAIQgAAEIAABCCBo+A5AAAIQgAAEIAABCEAAAhCAAAQgAIGMCSBoMk4Al4cABCAAAQhAAAIQgAAEIAABCEAAAggavgMQgAAEIAABCEAAAhCAAAQgAAEIQCBjAgiajBPA5SEAAQhAAAIQgAAEIAABCEAAAhCAAIKG7wAEIAABCEAAAhCAAAQgAAEIQAACEMiYAIIm4wRweQhAAAIQgAAEIAABCEAAAhCAAAQggKDhOwABCEAAAhCAAAQgAAEIQAACEIAABDImgKDJOAFcHgIQgAAEIAABCEAAAhCAAAQgAAEIIGj4DkAAAhCAAAQgAAEIQAACEIAABCAAgYwJIGgyTgCXhwAEIAABCEAAAhCAAAQgAAEIQAACCBq+AxCAAAQgAAEIQAACEIAABCAAAQhAIGMCCJqME8DlIQABCEAAAhCAAAQgAAEIQAACEIAAgobvAAQgAAEIQAACEIAABCAAAQhAAAIQyJgAgibjBHB5CEAAAhCAAAQgAAEIQAACEIAABCCAoOE7AAEIQAACEIAABCAAAQhAAAIQgAAEMiaAoMk4AVweAhCAAAQgAAEIQAACEIAABCAAAQggaPgOQAACEIAABCAAAQhAAAIQgAAEIACBjAkgaDJOAJeHAAQgAAEIQAACEIAABCAAAQhAAAIIGr4DEIAABCAAAQhAAAIQgAAEIAABCEAgYwIImowTwOUhAAEIQAACEIAABCAAAQhAAAIQgACChu8ABCAAAQhAAAIQgAAEIAABCEAAAhDImACCJuMEcHkIQAACEIAABCAAAQhAAAIQgAAEIICg4TsAAQhAAAIQgAAEIAABCEAAAhCAAAQyJoCgyTgBXB4CEIAABCAAAQhAAAIQgAAEIAABCCBo+A5AAAIQgAAEIAABCEAAAhCAAAQgAIGMCSBoMk4Al4cABCAAAQhAAAIQgAAEIAABCEAAAggavgMQgEAhCfyr//n/MP/8iyPmwffcZ/73D7+3kPeYxk395rs/Yk6fHTYf/b1/aX7nt9+exiW5BgQgAAEIQAACEIAABJYlAQRNnbR//x9+Yn7/j/6EP0iW5Y8EN22bwIEXj5t3f/DfV4ZNU5j8b5/6kvmbv/+xOfDko7Zva1mNp7JLJc3fffOLy+q+uVkIQAACEIAABCAAAQikSWDZCZq/+Kvvmc//yV9ew/iP/8Pvmbe95fXe+wiaq3j8P65/5Zad5r/83/8uze9moa6lVQgb1g0mxnDvPQ+a3/qNN5j/85MfXsTtP37pMfPoN76bqWzU2NKUMrVfHGX/ultuvIZN7XH+z72+X/RqkSC/B2v5ZJ3HQv1C4GYgAAEIQAACEIAABCBQh8CyEjT6B4Zu1TJGX/t/xPp/4CJoEDS2f1ssV0Hji4Bvfvnfm727ttnGanU8v9pGB7UtJH0O9STaUjfh/y4Ke95SYwb9PWgVLoNBAAIQgAAEIAABCEAAAk0JLBtB4/ejaDTVQStF/tNjf+P9v+wImqbfGw4ISSArQRMyTOuH+/IzD1OM/CokhaDTomxIpeqqnKhVRNVjxBU1YX4PWv8yMCAEIAABCEAAAhCAAAQgsCSBZSFo/D9wgv6BVC1o9h885v2x5m+1Ux8aTRWoPS7MmP61/P+n23+t/6++Nj2t/cOx+g84/9h6f1z6zT79Y3TKTZCeErXTZ6LcS6NvYW1Melx17EHuzc+BVkb9uUxhU0b+Vlst1Yitvl8tEWr7pujntWNV9zepzVX1WPXu0b9eNcsz5y9605F00z/E/817f2tR7xY/9to/0muvrcf5ua1m40/h865d0xem3v1F4Vqd5+qKlHrfubAxfP8fflr5WQz6sxz093/1veo52oMqzjVsiJna2OOKmrC/B4Oy4zgIQAACEIAABCAAAQhAwA6BZSFo/P8Xv9Ef60v9IVQtWvxxqgWC/mH3PWkqXN2fxf9jr/rcRv0t6o3p/+Fa+4e4//9+V1+/Xo+Reverf8RXT9todI16X6tGgkaPbcan0de00fX1j/p9e7Z7q8XUu49671VLsuoc12sQ2+iPVGX7r+WaKjH88ar/QK+X02oBUStkavvNNKqgWeoPeZ9RPXFUT9LUq66oJ2jq3ctS79XKmzCNd+t9v3W8KDEk2Remtgmu5ku3IAKz+juehJhZ6vdTGIkU9vegnX9iGAUCEIAABCAAAQhAAAIQCEpgWQga/w/KoFMWGk1x8v9gDvJHUW1j0jBjNloxpfaP3aXi0TF0U3G01JQtHbPZEsRLVdBUL7sbhk+QVWEaNb6tPbdRlUi9+w4y1ajRdfV79LNfvFT5o72RqKgnJZoJmjDyoTYOzXOjmOuxaRRL7f2E4droF04jQRM3hqC/4IIcV+97G0Vm+JVMQX4/BImr2TFhmxqH/T3Y7Pp8DgEIQAACEIAABCAAAQjYJYCgqcMzjEzxT683zaS6YiXMmM1W5PFFU6M/oDWm6j/iq6eSBK0iqsaShKBpdI/+dZtJJZ0K1IxD7RhBBFKQ6/oVLWkJGr9yqvarWl1ZE1TQLMWg9vuUlKCxEYPNX4NhqtiWum4UQVPv90bQn1EEjc1vAWNBAAIQgAAEIAABCEAgewLLStCE/cOntqqh3h+W/h/ptdNLaisEggqapf54rf1D0n+91NfI/yO+Xr8PPS9I81bbgiaIKFlKPtVWNwQVCUGaPzfqKVTN2BdDSQsaP5baXkH1rhtU0CzFoHbaUVCuS33/6skPGzHY/NXZqEeQf40gPyO1YlFfJ1VJE3Ualf+9Cfp70CZjxoIABCAAAQhAAAIQgAAEmhNYFoImbHPMoDJF8Tb6wzgNQRNnCWP/3CDLCdsWNEtxq/1Dt97Un9o/+oOKhCBiyM99kD9ikxY0jaaBxRE0NqpXgoguP49LVafUExhBq3ia/2oLdkQYWRRsxNJRUSXKUtegSXCYDHAsBCAAAQhAAAIQgAAE8kdgWQgaTYv//5Iv1YdG//Bdapnt2j9ul/pjN6qg8WOtbTKr74fpQVP9VdQ/enW86lV89PMgfWDqyZQwAqvRj0SjayvTZ39+2GsSnGYPGr0n3ZRRs+lX/j2FETTVPYGqmSwlCIL2afG/M6+75Ubv+1ub+8//yV8uWoEq6LhBxddSv/Zc70HTrC9LbXPtsL/ibYiauGKmOuYwvwfD3ivHQwACEIAABCAAAQhAAALxCCwbQeOLBt3XVkf4f0T605TCCIh6q734fwRF7UHTbBWoZqs46T3qPeiS09okuN6qRDZWcQoyBazR19NnXD01zI/JHzfoClVhREI9FrVVM/WO0fvQ+P6Xf/d/RWoS3EhULCVo6smDRitHNZJFS63i1GyVqjBcG+W52SpOUWOI92vv6tnNBEwzgRM0Dp9lvZW2lhqj3s9J0Gs2Os7ve9Ps92Dc63A+BCAAAQhAAAIQgAAEIBCOwLISNIqmUd+WaukRRtDomLU9LHQs/UO+ugom7Ji1vVBU9vzK3p1Gm+PW9sSo/n/Yq9Nfbwns6s+D9shIYoqTH0dtk9TamOrdW20VVFiRUK8fTyPZVPvjVB1fmAoaHae22a/msdl0oWoho2NonPsPHjN/8/c/vuZ7UP099PvWNGJTj0HtH+xhudb71dNI0OixcWII92uu/tH1RGjtkWGnR9qIK40xgvweTCMOrgEBCEAAAhCAAAQgAAEIXCWw7ARNnpNfb3nlPN8PsUMAAhCAAAQgAAEIQAACEIAABCBQIoCgcfCbUDuVRkNsVmnh4G0QEgQgAAEIQAACEIAABCAAAQhAAAIBCSBoAoJK87BGS2IHWVkozTi5FgQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyOk6EAAQgAAEIQAACEIAABCAAAQhAAAJ2CCBo7HBkFAhAAAIQgAAEIAABCEAAAhCAAAQgEJkAgiYyuqsnvnZh0sIoDOEKgdaWFrNudZc5PTzlSkjEYYnA0ECXuTw5a6ZnFyyNyDAuEOjubDMrutrM8NiMC+EQg0UC1w31GP6NtQjUkaFW9naYufkrZnxqzpGICMMGga6OVtPX02EujE7bGI4xHCKwdmWXuTQ+a2bn+O8nh9JiJRT9d5bNLQIIGgv54D8eLUB0aAgEjUPJsBwKgsYyUEeGQ9A4kogEwkDQJADVgSERNA4kIYEQEDQJQHVkSASNI4lIIAwETQJQYw6JoIkJUE9H0FiA6NAQCBqHkmE5FASNZaCODIegcSQRCYSBoEkAqgNDImgcSEICISBoEoDqyJAIGkcSkUAYCJoEoMYcEkETEyCCxgJAx4ZA0DiWEIvhfO873zB33Plms2b9ZoujMlTWBBA0WWcguesjaJJjm+XICJos6Sd3bQRNcmyzHhlBk3UGkrs+giY5tlFHRtBEJVd1HhU0FiA6NASCxqFkWA4FQWMZqCPDIWgcSUQCYSBoEoDqwJAIGgeSkEAICJoEoDoyJILGkUQkEAaCJgGoMYdE0MQEqKcjaCxAdGgIBI1DybAcCoLGMlBHhkPQOJKIBMJA0CQA1YEhETQOJCGBEBA0CUB1ZEgEjSOJSCAMBE0CUGMOiaCJCRBBYwGgY0MgaBxLiMVw6EFjEaZDQyFoHEqG5VAQNJaBOjIcgsaRRFgOA0FjGahDwyFoHEqG5VAQNJaBWhgOQWMBIhU0FiA6NASCxqFkWA4FQWMZqCPDIWgcSUQCYSBoEoDqwJAIGgeSkEAICJoEoDoyJILGkUQkEEbWguadD37CDA0OmK998aMJ3F2yQz5/8Jh574c/ZR770ifNrXu2W7sYgiYmyt9/9ZTZOtdi3t23MuZInO4KAQSNK5mwHweCxj5TF0ZE0LiQhWRiQNAkwzXrURE0WWcgmesjaJLh6sKoCBoXspBMDEkLmt/9yOfNj587uCj4wVX95qnHH/bey0LQPP7dp80nPvcV8+mPfcA8cN9dkcEiaCKjS/bElp/t9y6wt6PLfGTloLlvRV+yF2T0xAkgaBJHnNkF6EGTGfpEL4ygSRRvpoMjaDLFn9jFETSJoc10YARNpvgTvTiCJlG8mQ6epKDZe8+DplrG+Deq0mb9mtXms3/4wUwEjS3gCBpbJC2P84Wz58x/PnfR/PPMlDeyCpr75fHOFf2Wr8RwaRFA0KRFOv3rIGjSZ57GFRE0aVDO5hoImmy4J31VBE3ShLMZH0GTDfc0roqgSYNyNtdIStCohHnp2CuVSplGd+dX0OjnfqVNI6lTXYlTPa3o7gceMnfdeat5+pnnzfClMe9SH3rf/WbLpnVepYy/+efUEyu1lT56/kPvf5epVwF04MlHvSERNNl8ZwNd9UdnR80T42PyuGxemJ32zrm/t9+TNPf19AYag4PcIYCgcScXtiNB0Ngm6sZ4CBo38pBEFAiaJKhmPyaCJvscJBEBgiYJqm6MiaBxIw9JRJGUoNHqmfvf9iavSmapTQXNkeOvekJFhYhuKlxu3L650pdGJcmF4VHz7Uc/7X3+8Fe/ZR75+hPGFyV6vIoZX8D4n9dOpdJzdYxasVIrk/TzP/6zv/Kur5/9/v/025UeMxpvo3Fs5YceNBZI+k2CXxI588TEuDzGzJHZGdNpWsw7RdTcL6LmN3pWWLgSQ6RBAEGTBuVsrkEPmmy4J31VBE3ShLMbH0GTHfskr4ygSZJudmMjaLJjn/SVETRJE85u/CQEjS9AgvR4qdeD5uOf+bJ54cUTdWWKT0qlzLvfca8ndfwKGl8G1ats0TG1wkZ731R/ruNpo98gsfpy6Jvf+cE149AkOLvvcN0r167i9ILIGa+iRkTNiblZ09/aat7ZI9Oe+gbMm7p6HIuecGoJIGiK+51A0BQztwiaYuZV7wpBU8zcImiKmVcETTHzqneFoClubl0XNH5D33oZ8KtuGgmaaumiVTX1xMrRE69506D8apx61/ErdKo/0+OZ4uTwz0WjZbb/eXrKfHuyNPXp9PycWdPaVqmo+dWubofvaHmHhqApbv4RNMXMLYKmmHlF0BQ3rwiaYuYWQVPMvCJoiptX/9/ZJO4wzBSn2mW2qytofEHTTKBoD5raChobgkbv4w2376lMt6qeXoWgSeKbY2nMRoLGH/6ZqUnzxORlr6rmwsK82dTeYe73Kmr6za2y+hObWwQQNG7lw2Y09KCxSdOdsRA07uTCdiRU0Ngm6sZ4CBo38mA7CgSNbaLujEcFjTu5sB1JEhU0GmOzJsEqYRqt4lRvitNSU5DiVNBorI2mONWTQwga29/AhMZrJmj8y/7T9IT59mWd+nTZjF1ZMDe0d5YravrMTR2dCUXHsGEJIGjCEsvP8Qia/OQqTKQImjC08nUsgiZf+QoaLYImKKl8HYegyVe+wkSLoAlDK1/HJiVolEK9ZbZ96eE3EG7Wg8aXPbqCU3UVjUqcN9x+s3ngvrsa9qAJUkGjvWM0huFLo5UVp/wmwdocuFbe6D3pxhQnx7/nQQWNfxt/Pznh9adRUTMtomZ3p4iaHln1SSpqtrZ1OH63xQ8PQVPcHCNoiplbBE0x86p3haApZm4RNMXMK4KmmHnVu0LQFDe3SQqaarlSTbBanAQRNI3GqV7FKeoUJ7+5r7+alB+nH6OKoCe+/8NK+Nr3xl9BiilODv9chBU0/q18b3LcfLvcTPiKvHlbZ5dU1AzIqk99ZmNbu8N3XOzQEDTFzS89aIqZWwRNMfOKoCluXhE0xcwtgqaYeUXQFDev/r+zxb7D/N0dy2xbyFlUQeNf+jsqaaRHzX+Tihrd7uzukR41UlEjS3QPygpQbOkSQNCkyzvNqyFo0qSd3rUQNOmxTvtKVNCkTTyd6yFo0uGc9lUQNGkTT+96VNCkxzrtKyVdQZP2/RTheggaC1mMK2g0hLkrV2TFp1Ij4b+Vyhrd7upeYd65ot/c39tn+loQNRZSFWgIBE0gTLk8CEGTy7Q1DRpB0xRRbg9A0OQ2dUsGjqApZl4RNMXMq94Vgqa4uUXQuJdbBI2FnNgQNH4Y4wsLlf40/zg14b39GypqpJrmAZE17S0tFiJmiKUIIGiK+/2gB00xc4ugKWZe9a4QNMXMLYKmmHlF0BQzrwia4ubV/3e22HeYv7tD0FjImU1B44dzyRc145fNj2T1J93+hfSm0eW53yGyhi05Agia5NhmPTKCJusMJHN9BE0yXF0YFUHjQhbsx4Cgsc/UhRERNC5kIZkYqKBJhqsLo1JB40IWFseAoLGQkyQEjR/W2fk5aSQsU58mx8xz01NGJzrdL5U0WlHztp5eC9EzRC0BBE1xvxMImmLmFkFTzLzqXSFoiplbBE0x84qgKWZe9a4QNMXNLYLGvdwiaCzkJElB44eny3H/xdiI+dOxi+bs/Lz39n1SUfN7/avN7V3dFu6CIXwCCJrifhfoQVPM3CJoiplXBE1x84qgKWZuETTFzCuCprh59f+dLfYd5u/uEDQWcpaGoPHDHBdR8/+MXjR/NnbJjMo0KN3e2LXC/K8rV5m7u6mosZBOg6CxQdHNMRA0buYlblQImrgE3T2fChp3cxMnMgRNHHrunougcTc3cSOjgiYuQXfPp4LGvdwgaCzkJE1B44ercuYrUk1TLWr2dnSZD/Sv9KY/dbHqU+TMImgio3P+RASN8ymKFCCCJhK2XJyEoMlFmkIHiaAJjSwXJyBocpGmSEEiaCJhy8VJCBr30oSgsZCTLARNtaj5r5dHRNZcMqekX41u69razPv7V5nf6VtlBlpZnjtsihE0YYnl53h60OQnV2EiRdCEoZWvYxE0+cpX0GgRNEFJ5es4BE2+8hUmWgRNGFr5OhZB416+EDQWcpKloPHDP7cwb743OW6+Jw2F/35q3Ht7a3unNBJeYd6+otebBsUWjACCJhinPB6FoMlj1prHjKBpziivRyBo8pq5peNG0BQzrwiaYuZV7wpBU9zcLldBs/eeB83ObZvMtx/9tHPJRdBYSIkLgsa/jbkrV0qiRh8Tl81l6VmjVTRvl+W53y6rPr1dGgtTU7N00hE0Fn4oHB0CQeNoYmKGhaCJCdDh0xE0DicnRmgImhjwHD4VQeNwcmKGhqCJCdDh05ejoHn4q98yf/vUs2b40qj508/+vrl1z3anMoSgsZAOlwRN9e3809REWdZcNq/MlaY//XcqabxHvxlsQ9XUSz+CxsIPhaND0IPG0cTEDAtBExOgw6cjaBxOTozQEDQx4Dl8KoLG4eTEDA1BExOgw6cvR0Hzzgc/Yd569x3mZwdeMuvXrDaf/cMPOpUhBI2FdLgqaPxbe2F2RqppxjxZ8/zMtPf267t7PFHzNln5aUdHpwUKxRkCQVOcXNbeCYKmmLlF0BQzr3pXCJpi5hZBU8y8ImiKmVe9KwRNcXObtKB5cuxyJvDu6e+re93nDx4z7/3wp8xjX/qkOXriNfOFR75hnnr84UxibHRRBI2FdLguaPxbfE2qaL43edkTNU9JdY1uO6VPjfao0SlQd3R1W6CR/yEQNPnPYaM7QNAUM7cImmLmFUFT3LwiaIqZWwRNMfOKoCluXv1/Z5O8w5af7U9y+IZjX3ndvrqf+dOb/N4z2otGZY1L05wQNBa+MnkRNP6tTkhfGu1Po6Lm+5MTZlper2ltK019kiW6f7N7eTcURtBY+KFwdAh60DiamJhhIWhiAnT4dCpoHE5OjNAQNDHgOXwqgsbh5MQMjQqamAAdPj3pCpp7XzqWyd3/4Mb6fWX86U0Pvf9dXly/+5HPOzfNCUFj4TtG9RcAACAASURBVCuTN0FTfctPap+asqw5I8t0t7e0lKY+eX1q+kz/MlymG0Fj4YfC0SEQNI4mJmZYCJqYAB0+HUHjcHJihIagiQHP4VMRNA4nJ2ZoCJqYAB0+PWlB49Kt+9ObamMaXNXv1DQnBI2Fb02eBY1/+/88M1WqqBFZc0h61uj2xi7tUyOrP8kUqOvbOyyQyscQCJp85ClKlAiaKNTcPwdB436OokaIoIlKzu3zEDRu5ydqdAiaqOTcPw9B436Ooka4nARN7fQmn5lOc/r0xz5gHrjvrqgYrZ6HoLGAswiCxsdwYk4bCouokcqaH5X71OzplD41suqTVtbs6+yyQMztIRA0bucnTnT0oIlDz91zETTu5iZuZAiauATdPB9B42Ze4kaFoIlL0N3zETTu5iZuZMtJ0Nz9wEPm3e+41/jTm3x2Os1Jt6998aNxcVo5H0FThfHjn/myeeL7P7ymUZDOVTty/FXvyJ3bNhm/qZB/apEEjX9PowvSp6bcUFinQC3IBxvb272KmrdJj5q3iKwp6oagKWpmjUHQFDO3CJpi5lXvCkFTzNwiaIqZVwRNMfOqd4WgKW5ul5OgyUsWETTlTD3+3afNf3rsbzwRU93JWY3aheHRipRRWTM0OLDIsBVR0FR/gf8/mfqk05++NzlmhucXTLeRPjUrSlOftKqmu6U1L9/3QHEiaAJhyuVBCJpcpq1p0AiapohyewCCJrepWzJwBE0x84qgKWZeETTFzav/f4QU+w7zd3cImnLO/CW2/HXR/aW2tBTqDz70nsqcNBU5teulF13Q+F/rk3Oz5quXR8w35KEVNrrt7egy7+tfad4lqz/1FkTUIGjy94ssaMT0oAlKKl/HIWjyla8w0SJowtDKz7EImvzkKkykCJowtPJ1LBU0+cpXmGipoAlDK51jETTCWati/s17f8vs2HqdqRY0fqfn6oqaeu+duTiVTrYcucqIyJn/MjZi/mz0ojklKz/ptlJWe3qPiJrf6VtpdnZ0OhJptDBU0Ayt7DTnLk1HG4CznCXw3779mPnVN9xl1m3Y7GyMBBaeQFdnm+npbDWXLs+GP5kznCawfnW3WW7/xjqdEEvB9a/oMPPzV8zEdOm/IdiKQaCzo9X0drebi2OlxSbYikNgaKDTjE7Mmdm50v9By+YGgbmFOXPqcqkNx2uyn5fXuo1My/+ZPn3Jez53RY95rRLwuYkzZmq+9Lfr+Mxl851/9S03boYoKgSWvaDRvjNnzl/0pizVypeggmZ+4cqy/ErNXbli/np01Hz5wkXzvbGxCoM39K4wHxxcbd6zapXpzuky3W2tLfJLbnnmtchf5v/89b8wv/7rv26u37qtyLe57O6tRe64RcTqgvxOYisWAX4XFyuf/t3IP7FGf1r5kS1WfvldXKx8Vt+N/p+X/BtrJ78qVV4ZfcUb7Mzl054suSyi5PzEee+9EyMnvP2FiQve+1NzU+a0HKfbq2OvGD3/0tQl72Fju/JH/LeTDY42x8hE0Oi0oeFLV/+gr76hA08+avP+lhyrdrpSVEGzXKY4LQXziCzN/Sdjl8xfj4+Z8Sslu65TnnTq07/sGzC3dXanlte4F2KKU1yC7p5PDxp3cxMnMqY4xaHn9rlMcXI7P1GjY4pTVHJun8cUJ7fzEyc6pjgZc3K0JE6Gpy6YiVkVJ9Pm3ERJnGgVy/yVeTM6M+JVr0yLVDkrlSpXP5uT9y9JVctInDTUPXfLwFbv/bUr1puuttLfW70dvWawZ03l+C3911eer+4e8j7Xrau923z4137HekwMGI9A6oKmXpPdeLcQ/WwVNJ/43FfqDvCh993vLcFVrweNnlMtkhA0VxEeE1Hz5NSk+YGsAPWkLNPtF0K+pbvX3Nsjqz9195hd0rfG5Q1B43J24sWGoInHz9WzETSuZiZ+XAia+AxdHAFB42JW4seEoInP0NUR8i5opqVK5ez4GaN7neIzPjtuhifPe/uLIlx8saLTglSwXJwqfTYuImZ48oL1tPhSZVBkyYqOPtPd3iWCZYN3nY19m0x7S5vp71xpVnatNG2t7eY6eU83X8L0yjmDPUNW4qIHjRWMVgdJXdBoM95Pf+wDlaa7Vu8m5mD1pjSxilN0qP8oguYHU+PmH2R/eKY0H3mTLNV9r8iat8hS3SpsehxsLIygiZ5z189E0LieoWjxIWiiccvDWQiaPGQpfIwImvDM8nAGgiYPWYoWowuCRitStDJFBYuKFr/nil+9cnLsZe/mtNJl3uu78qo3Hcjv0RLtzq+e5ZJUiXsv1ecjaGzStDMWgqaKYz1Box9r1Y8uv63bzm2bKktu+6dSQbP0l/G1uTkRNRMiasalsmbCTJSnQP1aV6mi5l5ZrvtWh6pqEDR2frm4OAqrOLmYlfgxIWjiM3R1BASNq5mJFxeCJh4/V89G0Liamfhx2RA0UatYtIJFK1nibO1ShaKVKW0tpb1fsdLV1mXWydSgFTolyJv6U6pMGehaZQakgsVmpUqc+JM8F0GTJN1oY6cuaFR2vPXuO7zpQ0XZEDTBM/nj6Ulv6tOTk+Nm/0xplaQhaSR8b0+fuUcqau4RabO6rS34gAkciaBJAKojQyJoHEmE5TAQNJaBOjQcgsahZFgMBUFjEaZDQyFoHEqG5VBU0JwaGTEXxi9604FGp+QxMyqPS2ZM9iPSsFb33me6glB5P1buyaKfXZ6p3380SKjaW0Wn++i0nwHZVx4dAyWZ0lXa93fKXo/plkdH+Th53S+fs9UngKBx75uRuqCpbczrHpLwESFowjO7sDAvkqYkanQa1EVZulu3X5Fmwvf09Jp7pLLm9V094Qe2cAaCxgJER4dA0DiamJhhIWhiAnT4dASNw8mJERqCJgY8h09F0DicHAltXv7buyJRRJyMiUjRfisViaKv9X0VLV5D2/JeXo/PjZpLk5fM7MJs5Jv0pIrKk2rJUn7eL595AkakircvC5cBES5eLxYRLp2tbvewjAwm4xOXq6DRtiu1W5qLFS2V9tQFTT0Y1QG6AibMzwqCJgyta4/9uVTSPKlNhaW65hlpMKxbn/SmuUemPt0jkuZeETYb2trjXSTE2QiaELBydig9aHKWsIDhImgCgsrhYQiaHCYtQMgImgCQcngIgib5pE3OTVytUClXsahgqVSuVFWv+JUs1qpYZMWfgXLFigqUleWKlZVehUpZrFxT4aJVL3Jsd6m6hc09AstN0PiLBPkLAvkZ+fhnvuw9/ewffjDzJKUuaDK/4wQCQNDYgarLc3tVNdNSVTMxYU7Nz3kD7+7s8qY+aVPhu6S5cNIbgiZpwtmNj6DJjn2SV0bQJEk327ERNNnyT+rqCJqkyGY7LoKmOf8F+W/d+lOAytUsVVUsnlgRCXNVsJSOmbNQxeIJls6SNPFES1XFyoC8X5oydLXaZduatcbMrTCtprP5TXJErggsN0GjKzS/+x33Ot1uBUFj4UcIQWMBYs0Qh2TVp3+YllWgZArUU9KzRjetodHpT1pRo1OgtrUn848EgsZ+Pl0ZEUHjSibsxoGgscvTpdEQNC5lw14sCBp7LF0aaTkKGr+B7StjJypLN+uqQRNS6aKrDulSzlrdYnNFIRUnKlX8JZq1qa02s9Vmt9r0trQUc1dpueaq5rj+KkRRvjM2mgRHuS7nJE8gaUHz5PEnk7+JOle4Z9s917zbaEGgTAJc4qKZCBq/tKg6LleX3g6SMARNEErRjpm7ckVEzaSImsteVc3x+dLc123tHWVRI42FpaqmvaUl2gXqnIWgsYbSuYHoQeNcSqwEhKCxgtHJQRA0TqYldlAImtgInRwg74LGX2VoeOqC14NFpYrfo+XUeOm5Chld5llXFYqzfLPKEn9FIV+i+CsKdZZXFvJXEFqhKwvJCkMqZVTOZLEhaLKgns41kxY0Lf/B3t9oYYhc+aMr1xzuOwjXW6qkLmge/uq3zCNff8I89qVPmlv3bPfA+Tardi5YmCRkeSyCJh36J+ZmvWW6n9TluqWqRuWNbnd3S0VNT4+Iml6zuyN+VQ2CJp18ZnEVBE0W1JO/JoImecZZXQFBkxX5ZK+LoEmWb1ajuyZofMFyceq8V80yPjNuTotoUQEzPjtuTo6eMBMiWvS1X+ESlp0vUbRqRZvbrl2xobxcc6/Z3H+9t7KQvu8v8RyniiVsbDaPR9DYpOnWWEkLmnv//N5MbvgH//oH11yXCpoGqWg070vFzTe/8wPz1OMPZ5LEOBdF0MShF+1cnQL1VxOj5pvjo2Z4ft4bpEuqaP6HFf3mf5TH3TIFKmpVDYImWk7ycBaCJg9ZCh8jgiY8s7ycgaDJS6bCxYmgCccrL0cnLWh0KecLU+fM+Ylzsj9vLsj0oQsTZ73n3nvy+vzkWW9akb6nqxaF2bSR7arOQbO6Rx7dq83qriHv+aoueS4VLKv0Pdmv7pb35LlWtSyXxrcImjDfpHwdm7SgcY2Guoi77rzViWbAjdikXkGjqzjVm86Ul5KjeiARNNn96E1Ls7XvSp+avxJRo9U1/rZRVn16Z2+/+e0VA9JkOFxVDYImu3wmfWV60CRNOJvxETTZcE/jqgiaNCinfw0ETfrM07hiVEGjlSxaxVKaPnTaq2a5OD1szo6f8Spf9PWwCBdtrhtm054sWsGi1S1+n5YtUtXiLdtcrmrRCpjqz8OMv5yORdAUN9vLTdA0WsVJi0VeO3PeCXGTuqChgqa4P+BZ39mpuTmpqBmRx2VzfG6mEs7eji7z38uS3SpsgjQWRtBkncnkro+gSY5tliMjaLKkn+y1ETTJ8s1qdARNVuSTva4vaE6cL1WwXPArXWR/frJc9eJVuiyugpmZnw4UWF9nvxnqXmOGVqz19mt615Ve++/1rDVryp8N9awx2suFzQ4BBI0dji6OstwEjebAn+pUnY/BVf3OzORJXdDQg8bFH83ixfTc9JT51sSY+bY8/ClQepd3ytSnfyG9anQq1MZ2XRfq2g1BU7zvg39HCJpi5hZBU8y86l0haIqZWwRN/vI6IT1bvClFVaLFky7etKJzUv1Seq6VLudEwkzNTQa6yRUdvUZlypDIlUXSRd5bI+8N1kiX7vaeQONykF0CCBq7PF0abTkKGpf414sldUGjQbCKk+tfi+LEd0HmH/9Qpj79UFaC0seR2VJlTW9Lq3mTyJo3dcmjZ4W5Raps/A1BU5z8194JPWiKmVsETTHziqApbl4RNG7kViWKL1iq+7lU3itXu/j9XlTSBNlUoqh0UcHiyZcV5UoX/z2tcikLGf1cJQ2b2wQQNG7nJ050CJo49JI5NxNBk8ytZDcqPWiyYx/mymfn50qiRoTNP8n+uKwKpdtAq8gaFTWyXPeb5XFzZ5dZt7rLnB6eCjM8x+aAAIImB0mKECKCJgK0nJxCBU1OEhUyTARNSGAhDtfpQtXS5bw00fWb5noVL+XpRv57l2fGAo2u04WqpcsakS6DKl90qpHKFpEuG/vXm+tXbzCtcwNGpyOxFYcAgqY4uay9EwSNe7lF0FjICYLGAsSUhzglsuafZKnuH05pZc2EOSn9a3RbLbJGJc19gwNm73y72VVVWZNyiFwuAQIImgSgOjAkgsaBJCQUAoImIbAZD4ugCZ+A6fkpr1muPl7TprnSUFcb6eprbayrr7XRrjbcDbMNSLPcQZEsugz0dfLQZrqruwa9196S0fJaVysKsjx01CbBYeLl2GwIIGiy4Z7GVRE0aVAOd43UBI2u3vSh991vHvn6E0tGeODJR8PdgQNHI2gcSEKMEE5KJc0PVdaUp0G9VpY1a1vbvKoanQL1pq5us7093GpQMULi1IQI0IMmIbAZD4ugyTgBCV4eQZMg3AyHRtAshq9y5dR4Sb7oykWn5fnJsZcrKxqpkAmzglG1dNGVjHzJsllWMNKqFxUuunKRSpj21vr9+KJ8PRA0Uajl4xwETT7yFCVKBE0Uasmek5qgSfY2sh0dQZMtf5tX12lPP5KqmmfNjPm7kTGj06J02yDLdmtlzRtF1Ki02dreYfOyjJUSAQRNSqBTvgyCJmXgKV4OQZMi7BQvtVwEzdzCXKXqxRcw52TKkSdiZPnoV8ZOeM/1uGabihQVKqXKFpEuIllUvmzoLVW96Gv/c5vSpVlc1Z8jaMLQytexCJp85StMtAiaMLTSOTZ1QaOVNJ/+2AfMA/fdtegOdXWnb37nB84sbxUGP4ImDC33j/WbBD99ZtT8SFaD+ieZAqV9a7ThsG6bRc68UXrWvNlrMrzCbGqwGpT7d7r8IkTQFDPnCJpi5lXvCkFTzNzmXdDMy38PnJs8Y86Mn5YqF39/+uprmXKk72s1jE5NWmrraOv0RMu63g1mXc96T754z2Wvz9fL89J7601nq9vLRiNoivnzqneFoClubhE07uXWGUHjr+zEFCf3viTLLaJ6qzgdmpkRWVPqV6O9a0YWFjwsW2Xak7calDzeLLJmfVvbcsOVq/ulB02u0hU4WARNYFS5OxBBk7uUBQrYdUHjTznSfi5a4XJ6/DWv4sV/re81Ey8Koqut2xMrm/u3ev1dVLRs6L3Oe08FjL5ve5pRoAQkdBCCJiGwDgyLoHEgCQmFgKBJCGyMYZ0RNB//zJfN0888TwVNjGRyqh0CzZbZfkGW6i41GJ7wKmzGypU12qPGFzVv7O42a2VaFJtbBBA0buXDVjQIGlsk3RsHQeNeTmxElLWgUcHiyRbt9SL7V6Tfiz/d6OToy2Z89nLT21TB4k830n1JuFzvNdb1X+vUo+W0IWiKm20ETXFzi6BxL7epCBq/OqbZ7deb+tTsHBc+Z4qTC1mwF0MzQVN9pf0z06WqGpkCpbJm8kqpsmZXR7myRqpqdAnv1VTW2EtQjJEQNDHgOXwqgsbh5MQMDUETE6CjpycpaLSfi8oWv9pF5Ys23L36+kTTni9+L5ctUuGiqxet6VlXqYDRz4KsaOQo+kTDQtAkijfTwRE0meJP9OIImkTxRho8FUFTHVmjHjSRonfkJASNI4mwFEYYQVN9yVOy+tP/OzFqnhi/bA7MTlc+GhQ5c9+KXvOunn7zepE17S0tliJlmLAE6EETllg+jkfQ5CNPUaJE0ESh5v45cQTNmfFTUvnymjk1Vpp65E9B0pWOTl8uvZ6an2wIQVc42ijTjDwJ07/Zm3LkPZdmu/77q7pXuw/RwQgRNA4mxVJICBpLIB0cBkHjXlJSFzTuIYgfEYImPkOXRogqaKrv4fjcjPn2+Jj564nxa2TNvd295u09veYeWb67t6XVpVsvfCwImmKmGEFTzLzqXSFoipnbRoJmdn6mJF/KfV/qyReVMgvlatV6dNb0rL0qXbxVj8oCRp77Mqa3o6+YYDO+KwRNxglI8PIImgThZjw0gibjBNS5PILGQk4QNBYgOjSEDUFTK2u+JbLmuzWypksqae6WJbvf3t1n3ioVNuuYBpX4twBBkzjiTC6AoMkEeyoXRdCkgjm1i1yeHfMqX8bmz5qTI6+YE5dOmurKF5Uv5yfPLRmPVruoaNGmu97zGgFznVTC6MpIbOkTQNCkzzytKyJo0iKd/nUQNOkzb3bF1AXN8wePmfd++FMN42IVp2Yp4/OkCdgWNLWyRkXN96bGzTNTi0uwb+/qNveKsPlNqa65rbM76dtcluPTg6aYaUfQFDOvelcImnzl9sLU+co0I5UtnnypmY40NjPa8KZUrKhgqUw7qhIwKmT89/NFZflEi6Apbq4RNMXNLYLGvdymLmjufuAhc9edt5o33H6z+cIj36is2vTOBz9h3nr3Heah97/LPUpNIqKCJncpWzLgJAVN9YXPzs+bvxVZ88TkmHlGlvCevnKl8rFW02hVzT1dTIWy+e1C0Nik6c5YCBp3cmE7EgSNbaLRx7si/0ZVTz2qTEWSvi9+Lxh9b2b+ag+22qvp1CKtetk8UKp+Wdsj04+0B0x/uRpGnusUJbZ8EkDQ5DNvQaJG0AShlM9jEDTu5S11QeM3Cd6x9Trzbz/+xxVBoys9VQsb91A1jghBk6dsNY81LUFTHckr0mD4pzOT5qciap6dnjb7Z6YqH69tbTO/KtU1vyoNhv1987vgiHoEEDTF/F4gaIqZV70rBE16uZ2am1wkWjwZU26668sYbdC71KbNdUsNd1W8XJUu2ozXf1+b9MZpEpweEa4UlgCCJiyx/ByPoMlPrsJGiqAJSyz54zMTNA/cd5dRWeNPafKX4maKU/JJ5wpLE8hC0FRHNGOumJ/K9CeVNT+VZbx1P7JQWr5bN0/SdF6VNWvpXRP4K00PmsCocnUggiZX6QoVLIImFK6mB49Oj5hfjhw1x/VxSR6jv/SqYnQJal2aWpeoXmrTCpgtA9eXqmBkCerN/dd7S07rctT+0tRNg5ADEDRBKOXvGARN/nIWNGIETVBS+TsOQeNezlIXNDqV6eZdW81n//CDpvr5xz/zZfP0M89XKmrcQ9U4Iipo8pSt5rFmLWhqI3xJlux+dnqqImtemp2pHLK1vcNbutuXNns6aYy4VIYRNM2//3k8AkGTx6wFixlBE4xT9VFnJ86U5ItKGBEw/nMVMypoltoGe4a8yhdPushjU19JwKh8UQmjn9vYEDQ2KLo3BoLGvZzYighBY4uke+MgaNzLSeqCphaBVtH422Nf+qS5dc929yg1iQhBk7uULRmwa4KmOthRqaT5qUx/+olU2Dwre62u8XvX6JLdpWlQXZXpUCtYxntRrhE0xfpZ9e8GQVPMvOpdIWjq51YrXjwBM3Ks/DjqVcHo6/HZyw2/EH4FzLaVO0zpsb1SDaOVMWktP42gKebPLIKmmHnVu0LQFDe3CBr3cpu5oHEPSfiIEDThmbl8hsuCppbb8zIFyhM1OiVK9ifnZiuH3Nyhoqbcu6a722xt63AZeyqx0YMmFcypXwRBkzry1C64XAXNxalhmXL0cukxqnudglR+fvllc2nqYt0ctEnPss1S9XJd/xZv+tFmkS6b+7aYTfrae369E0tQI2hS+xFK9UIImlRxp3oxBE2quFO9GIImVdyBLpa6oPGbBGsPmqJsCJqiZLJ0H3kSNNXkdVWon3h9a0qNhp+V5/62rq39qqyRJbzvEHGzHDcETTGzjqApZl71roosaLThbkXCVETMy+ZVETCvjJ5sWAmjVS6bRbhsEgHjiZeyiNnUW5IwOh3J9Q1B43qGosWHoInGLQ9nIWjykKVoMSJoonFL8iwEjQW6CBoLEB0aIq+CphqhLtitVTXPzuo0qFKFzbmFee+QlhZtNCxToUTU6P6Ozi6zVgTOctgQNMXMMoKmmHktgqCZnp8yRy6+6PWBOXLxsDl66SVzUqph9LX2imm0dbV1mxtWbfca8d6waofZOrDd6wWjU5J0alJ7a75/ZyNoivkzi6ApZl71rhA0xc0tgsa93KYuaLQx8FvvvsM89P53uUcjYkQImojgHD2tCIKmFu34lQXz5OSEeXJ63PztxLjRaht/09419/SsMPd09Zq7e3rMFmk8XNSNHjTFzCyCpph5zZOgGZ684AmYw8MviIR50fzSEzIiZqRPTKNNl5u+odwLRuWLSpidq3dVmvIWN6us4lTU3CJoippZBE1xM1uqVGVzi0Dqgub5g8fMv/34H+dytaZGqUPQuPWljhtNEQVNLZOfS7+aJydF1kxNmOekwqZ629beae7u7jH3dK8QYbPCqMApyoagKUomF98HgqaYeXVN0OgS1CpcfPFyePigJ2X00Wh1JJ2OpFUvO1ff5MmXHfLQChgVMypolutGBU0xM4+gKWZe9a6ooClubhE07uU2dUFTvWpTPRwHnnzUPUpNIkLQ5C5lSwa8HARNNYBhqab528nL5mkRNU9NLa6uaZf5UPtkCtS9Imvu6lphbpfeNfpeXjcETV4zt3TcCJpi5jUrQaNNeV8e0+Wpf2lelmWqT+hDVkfSfb3mvG0tbWarSJitK7d5VTAqZK5feYP3XN/raV9R3ARFvDMETURwjp+GoHE8QTHCQ9DEgOf4qQga9xKUuqBxD0H8iBA08Rm6NMJyEzS17LW65imprHlyctI8Jw2H/WW89TitptGqml+T/jVvkv1eWSkqTxs9aPKUreCxImiCs8rbkUk1CZ6YHRf5ctxblvrlkbKEGRUJM3LckzJaLVO7rexeZbb2i3iR3jBbB64KGJUz2qiXLTgBBE1wVnk6EkGTp2yFixVBE45Xno5G0LiXrdQFTaNVnB7+6rfMN7/zg1xOfULQuPfFjhPRchc01ey0d82PpMHwkyJsVNocmZ1ZhHagtdW8SaprXidVNm+SChuttnG5wgZBE+cnw91zETTu5iZuZHEFzdmJ01IJIxLGq4Q5XqmEUSnTqEmvrox0vQgYrxJmYJu39ypk5L1V3avj3hLnCwEETTG/BgiaYuZV7wpBU9zcImjcy60zgubx7z5tPvG5rximOLn3JVluESFoGmf81NyceUaqalTa/EiW8a4VNlphc2d3t/k1WR3KRWGDoCnmTzOCpph51bsKImjmFmZLlTCegFERo5UwpelJOk1pan7yGkDd7T0iXGRKkidf/GoY2etzqZJpbytus3QXvi0IGheyYD8GBI19pq6MiKBxJRP240DQ2Gcad0RnBM3HP/Nl8/Qzz1NBEzejnB+bAIImOMJDUlGzX3rXPD87bfbL1KjnZ2ZkStRCZYDNsiLUrTINal9Xl7mlo9vbr2ltC34By0fSg8YyUEeGQ9A4kogEwqgWNLpS0uKeMGUhI3Lmtcuv1L36mp61Xj+YbdIPxtvLw6+OWd+7MYGIGTIIAQRNEEr5OwZBk7+cBY0YQROUVP6OQ9C4l7NUBI1fHdPs9j/9sQ+YB+67q9lhzn3OFCfnUhIrIARNdHyHRdg874maq8JmskrYbGxrF0nTLdKmU/Y93n6dvJfWhqBJi3S610HQpMs76atpM16/L8yFJlJAvgAAIABJREFUmZPmwJmXzAmZpnRCGveOTY/WvXypIW+pAqY0NUn20ivm+v5tpq+zP+mQGT8kAQRNSGA5ORxBk5NERQgTQRMBWk5OQdC4l6hUBE31bTfqQeMemuARIWiCs8rDkQgae1l6SSprntcqG5E2v5gu7bWvjb+tFzlzq/StKUmbLu+xsT05YYOgsZdbl0ZC0LiUjWCxjM2Mlpr0an8YES/e1CS/Wa9UxNTb+jsHKj1hqgWM37Q32JU5ygUCCBoXsmA/BgSNfaaujIigcSUT9uNA0NhnGnfE1AVN3IBdPB9B42JWoseEoInOrtmZx+ZmPUlTmhYl1TayH6sSNmtl+tOtMg3qVlklypsaJftNFoUNPWiaZSifnyNo3M3bqcuvlvvDlJv0aiWM17D3mNEpS/W2Db3XlVZJkgqYWzbcaAY7tlSqYoZ61rh7s0QWmACCJjCqXB2IoMlVukIFi6AJhStXByNo3EsXgsZCThA0FiA6NASCJr1kHFdhU+lho9U2U2Zk/mqFzWBbqydpbpX+NVppo9Lm+o7ozTsRNOnlNs0rIWjSpF3/Wroi0oFz+0XGHDVHL71ojlx80Ry+cKDhSkk6yroV681NQ3vNztW7zI5Vu0TC7DC7h242G/s2VS4SpElw9ndPBGEJIGjCEsvH8QiafOQpSpQImijU8nEOgsa9PGUiaO5+4CEzfGmsLg1WcXLvS7LcIkLQZJfxEyJsfuH1ryn3sBFhc7FK2KwSYaOypiRttI9Nt9kqjYiDbgiaoKTydRyCJr18jU6PmEMiXg6c3++JmJ+ffU5kzGGj79fb2lvbPQGj8mXn6pvMrsE93v4GeT3QtbJp4AiapohyeQCCJpdpaxo0gqYpotwegKDJbeqaBo6gaYoo9QNSFzTvfPATZmhwwHztix9N/WaTuiAVNEmRzWZcBE023Otd9aQIG2047D1E1uyfnjYXFuYrh/a3tois0WbDpZWitMpme3tnwxugB407ubUZCYLGJs3SWNPzU14VjMqYF84/70mY/SJjtFKm3tbb0SfVMDd78uUmkTAlIbPLex1nQ9DEoefuuQgad3MTJzIETRx6bp+LoHE7P3GiQ9DEoZfMuakLGpoEJ5NIRrVHAEFjj6XtkV6bn6v0r9k/PemJm3NVwqZPe9hIZc2tlZWius3OKmGDoLGdETfGQ9BEz8P47GVz7NIR80t5HLv0kvf8qLd/qW5VjC5bfcOqnWb7qhtlv8Pbb18pr1fvNF1t3dEDaXAmgsY6UicGRNA4kQbrQSBorCN1ZkAEjTOpsB4IgsY60tgDImhiIzSGChoLEB0aAkHjUDKahDItDYafkx42PxJZ88OpKfPczKSZvnJl0Vl7pbrmdhE2t0t1zW8MrTSbFlrN9OzVPjf5uVsibUQAQdP8u3FFfi48ATNSFjEXXxIRU3p+ZvzUNQPoiknbRcTc4MkXkTFSEaN7lTFBpiY1jyjYEQiaYJzydhSCJm8ZCxYvgiYYpzwehaDJY9aCxYygCcYpzaNSFzQ6xemtd99hHnr/u9K8z0SvhaBJFG/qgyNoUkdu7YLNhM2DP3zK/GT3XrNx0xZP2HjipqvH9La0WouBgdIngKBZzFxXTlpUDSMyxquSETlTu3W2ybTAciWMJ2NUymiFjMiYtT3r0k9mzRURNJmnIJEAEDSJYM18UARN5ilILAAETWJoMx8YQZN5Cq4JIHVB8/h3nzZfeOQb5qnHH3aPRsSIEDQRwTl6GoLG0cRECEuFzYGZGfOsVNj8RJb33vx33zPfu/Emc3zN4qV6q6tsVNjslGlSbPkhsJwFzcnRE17D3hfkoXt96Hv1tsGeIekPs9fcsnaft2rS3jX7vB4xaVbEhP1WIWjCEsvH8QiafOQpbJQImrDE8nM8giY/uQobKYImLLHkj09d0GgPmqU2VnFKPulcYWkCCJrifkN0Faetd/yaObpqyBM2Km4OSB+b2mlRA62t5k4RNVpls1dWjLpdHoNtbcUFk/M7Ww6CZm5hzhwefkGWsv65eeHC8+YXsqT1gfM/r9snxm/YqwJGRYwuXb13zW1GBU3eNgRN3jIWLF4ETTBOeTsKQZO3jAWPF0ETnFXejkTQuJex1AWNewjiR0QFTXyGLo2AoHEpG3ZjqdckuLbKRnvanJJmxLXbxrZ2c5tMidon1TVIG7t5iTta0QSNLlmt8kUljMoYlTIqZ1TSXPO97Ntkblt3u6ygtNfsW/s6T8boCkpF2RA0Rcnk4vtA0BQzrwiaYuZV7wpBU9zcImjcyy2CxkJOEDQWIDo0BILGoWRYDiXoKk6n5uak4bA2HZ7yKmx+LvvRhWsbCyNtLCco4nB5FTQzC9PeUtYvDR/y9rqU9ZFheVx60czMTy+isap7tTcd6cbVuyvLV+sy1kWSMfXSj6CJ+EPh+GkIGscTFDE8BE1EcDk4DUGTgyRFDBFBExFcgqdlImi0UfCR4696t/Xpj33APHDfXUanPr3h9j3ma1/8aIK3m8zQCJpkuGY1KoImK/LJXzeooKmNZEZ62bwo0ubw7LR5UXra+PsT87OLDm1vaTG72jvMTbJy1K7OTnneaW6S/Q1VS30nf5fL7wp5EDQXJs+LeBH5UhYyR1XGyPOXR49fk7AtA1urJMxVIaNLXC+3DUFTzIwjaIqZVwRNMfOqd4WgKW5uETTu5TZ1QaNyZmhwwBMxdz/wkPmDD73HEzQPf/Vb5pvf+UEumwcjaNz7YseJCEETh57b52oPmjvufLNZs35z7ECnRNocnp0xL8lD94dF3Lw4N2NOzi2WNh2tIm3aVNR0mRtV3sj+JpkmtU2es9kh4JqgOTFyzKuC8SpiyiJGq2QuTg0vFnqtHebGwZu8ypjSY1elQqarrdsOnJyPgqDJeQIbhI+gKWZeETTFzCuCprh51TtD0LiX39QFjVbKPPalT5pb92xfJGh0dadPfO4rhibB7n1JlltECJriZtymoKlHaUIrbcqiRqXNi1Jxo/tXpfqmeuuQSpubvOoakTYdpYobrbTZ2oa0ifLty0rQTM9PXZ2iVCNkZudnFt3K6u7B0hSlaiEjDXy3rtwe5ZaXzTkImmKmGkFTzLwiaIqZVwRNcfOKoHEzt6kLGq2a+dPP/v41giarCprf/cjnzY+fO7goO7WSqHpK1s5tm8y3H/30ouOpoHHzyx01KgRNVHLun5e0oKlH4LL0rnnRq7KR6VFSXeNJG5E4tY2IO41Im/K0KJ0e5U2TEnmzlelRTb9YaQia85PnKtUwpaqYUt+YektaX79ym9kp8mWHJ2SuTlEa6l68vHvTG+MA7//Z49/Y4n0REDTFy6neEYKmmHlF0BQ3rwgaN3ObuqD5+Ge+bJ5+5nlvKpM/xWnH1uvMez/8KXP/295kPvuHH0yVlMagsfhbdXz6ngqcC8OjFSlTPUXLP4f/eEw1ZYlfDEGTOOLMLhC1B43tgMdE2njTospVNipuDksz4jM1q0d1aaWNJ2qkn03VYyvToxalxLagOT5y9GrTXm3eK71jdIrSpamLi67bIVPXbqxMTypNUfKrZDpbu2x/bZbleAiaYqYdQVPMvCJoiplXBE1x84qgcTO3qQsaxeBPZ6pG8qH33W8eev+7Mqf0/MFjniyqNw3Lj/0Lj3xjkdRB0GSeNqsBIGis4nRqMFcETT0oIyptRNJoHxuttjk8M2tekudna6RNd0ur14h4l/ay8StuRN5cv4ylTVRBMzU/WRExL+nqSX7PGJmuNFfTAHqwZ6i8ipKImFXykKlKO0TIbB24wanveNGCQdAULaOl+0HQFDOvCJpi5hVBU9y8ImjczG0mgsZNFKWoqqda1coa/bzeewgalzMaPjYETXhmeTnDZUFTj+FFr9JGpI3XhLjUz0anSF2oWfK7R6WNTIfaVZ4Wpb1tdrV3mS3t7XlJTaw4gwiauQVZhWv4BfPzM8+ZFy/K/uxz5tCFA2Z0euSaaw90rTR719xmblm7z9w8dKvZu/Y2c9Pgzaa9dXnwjJUMyycjaCwDdWQ4BI0jibAcBoLGMlCHhmMVJ4eSYTkUmgRbBmphuNQFjd/zpbbPiwvLbPvyxV/6O6iguTA6bSEVDOEKgRaZVrK6r8MMjy1u8ulKfMQRncB3vvWYufONbzbrN26JPkjGZ06LnDkokuanU1PmgOx/NjltDsl+7sqVayK7QSprbhVZc0dXt9nd1WV+RfZDbW0Z34H9y3e2t5muzlYzNlFaQUtljMqXn51+zhw4v9/89NQz5qC8np6buubi18uS1resK8mYW9bIQ57re2xuEFCpyr+xbuTCZhS93e1mfuGKmZqZtzksY2VMoKO91fR0tpvRCf77KeNUWL/8yt5Oc3lqzszPL1gfmwGzJaD/zrK5RSB1QaM9X979jnuvmc6UVZNgPx2+jKmeahVU0EzP8svKra91vGha5PSOjlYzQ17jgXTw7L/8r183d93162bL9cX6A3xKpM2B6SnzzMSk2S/75yZE3si+nrQZkqqaO3q6zU0ia/aJtNmnz0XidLe2Opix5iGpjDl44RfmZ6eeFSHzc/PMqz82B879wkzVyBitftm79hZz+8Y7zM1r9prb1v+K2bf+NrOqe1Xzi3BEZgT0/5Hn39jM8Cd24fa2FqNOWSUNW3EItMp/QLVJbmfnyGtxslq6k872Fpn6e8XwI1u0zJaae7O5RSB1QaOVMn6FSjWKLJfZ9q/t952pjstvZPzAfXd5b9eLkylObn2p40bDFKe4BN09P4tVnLKiMS1Lfh+SKVHPiah5YW5ahM2MOSKvx+X92q1dqsZ26nLfMi1qn8ianVJ5s1emS210bIrUxclh8+Klg+bFC/IYPihTlg5K896D5uzEmUW3pFOUdg3uMTet3iOrKMl+aI/ZJc839F2XVTq4bkQCTHGKCM7x05ji5HiCIobHFKeI4HJwGlOccpCkiCEyxSkiuARPS13QuFZBo8KltulvNW9WcUrw2+fo0AgaRxNjIay89aCxcMuLhlA5c0xWjDoqouaYPI7Ozsrr0r6euNHVonboQ5oR75TlvneIxNkhEmddCtOkwsiY3UM3y9Skveb6vl3IGNtfmozHQ9BknICELo+gSQhsxsMiaDJOQIKXR9AkCDfjoRE0GSegzuVTFzQ6lemRrz9RWSVJY6o3vSgNVP51612ruspHl9Y+cvxV77Cd2zZVltz2z6OCJo1spXcNBE16rNO+0nIXNI14q5zR6hqtsnlxfsYckobE2t9meL5+f4jdImx2iLDZLZU2ugy4Pr+ho910SbPiKJvfwPe50894jXx1f+jCC2Z6fnHPGJ2mpM16b1t/uzTv3Wdu33CnUTmzsqfXrOhqo29UFPiOn4OgcTxBEcND0EQE5/hpCBrHExQjPARNDHiOn4qgcS9BqQsaRVBvme16057cw1U/IgRNXjIVLE4ETTBOeTwKQRMua2dF0BzwVo+Sh1TeaF+bI1JxM12nIbEnsEXY6GObVN3cpA+ZLnWDyJuBmv42J0dPmP2yitJPTv/IW01JV1YKKmO62rqvuYkgqziFu3OOdoUAgsaVTNiNA0Fjl6croyFoXMmE/TgQNPaZujIigsaVTFyNIxNB4x6GeBEhaOLxc+1sBI1rGbEXz3LqQWOP2rUjHZqRaVEialTcHJHpUVp901DczI6ZVaMHzeqRF8y8PM6f/YmZmB6+ZlCthNm37g6zb+3rKpUx9WRMvftC0CSZ7WzHRtBkyz+pqyNokiKb7bgImmz5J3l1BE2SdLMdG0GTLf96V0fQWMgJgsYCRIeGQNA4lAzLoSBoLAOtGu7ywrx5fuKs+dGZ/eZ5WVXpmExROiMNfS9fOmyuzE8uvnD/dmP6bzQrV+82m6R57y6ZtnTL6h1ma1uH2SYVOFulOXFviOlSCJrk8pr1yAiarDOQzPURNMlwzXpUBE3WGUju+gia5NhmPTKCJusMXHv9TASNNgoevjRWl8aBJx91j1KTiBA0uUvZkgEjaIqVz+q7QdDYy+3c/Kw5OHzAHDr/C1nm+oA5fPGAOXj+gDkzfmrRRTb2bTJbRMIMrdptulftMvN9O81o33ZzfH7BnJBpU/UWY13b2ma2SZ8bT9iIrNFmxdtkqpQ+Btuu7XODoLGXV9dGQtC4lhE78SBo7HB0bRQEjWsZsRcPgsYeS9dGQtC4lhFjUhc02nB3aHDAfO2LH3WPRsSIEDQRwTl6GoLG0cRYCIseNNEhnhg95gmYQ1Ido0LmkDyOXDy8aMC+jn6ze81es3twr9mz5hZp4Cv7oVvMyq5VdS98QiTPcZkudWJ+zvxSpkydkOlSx0XaHJ+bkz431y4H3i+9bLS/TUnYlB9ScbOru9vc2NdFk+Do6XX2TASNs6mJFRiCJhY+Z09G0DibmtiBIWhiI3R2AASNe6lJXdDsvedBk+eGwPVSiKBx74sdJyIETRx6bp+LoAmWnwuT5z0RoyspHRouCxmRM5NzE4sG0L4xu0XA6MpKKmJUyGwZ2BrsIkscdUoEzXGVN9Lb5kTVc5U3YwvXipvOlhazXSputsgqT9tkKXCtvNnqVdzo604TbW2p2LfBABYIIGgsQHRwCASNg0mxEBKCxgJER4dA0DiaGAthIWgsQLQ8BILGAlAEjQWIDg2BoHEoGZZDQdBcC3RWltWuTFXypiyVqmTOTpxZdPB1fZsrFTFaJbNnUISM7Fvkf2ltWlXzy9m5SoPiQyJwjmuTYrmH6YV6k6WMt4KUriy1V5YD16qb0kpTpSlTbO4TQNC4n6MoESJoolBz/xwEjfs5ihohgiYqOffPQ9C4l6PUBY1OcXrr3XeYh97/LvdoRIwIQRMRnKOnIWgcTYyFsOhBY8zxkaOlKUraO0aFjDw/evHFRXT7uwZKFTHlqUp+hcxA10oLWbA/hPagOWnmzLOXxr3VpI5K1c1hWR5cV5carzNVSiNol6obf5rUDdqYuE2qbUTa3NBR2rO5QQBB40YebEeBoLFN1I3xEDRu5CGJKBA0SVB1Y0wEjRt5qI4idUHz+HefNl945Bvmqccfdo9GxIgQNBHBOXoagsbRxFgIa7kJmvOT50o9Y7Qqpqqh7/T81CKafq8Yb6+9Y0TMbOrfYoF4OkMs1SRYp0tppc0RWRL8qEyROiwCR6dOnZ2fbxgc8iadvAW5CoImCKX8HYOgyV/OgkSMoAlCKZ/HIGjymbcgUSNoglBK95jUBY32oFlqYxWndL8AXO1aAgia4n4riixoZhamr2niq1Uy5ybPLkro5v7rF01V2q1TlaSXTJ63KKs4qaB5RYTNSel1c1L3InK817LX1zN115cyZqVMmdoiPW62yDSpzdLjxnsuU6d0r6+1kTGbPQIIGnssXRoJQeNSNuzFgqCxx9K1kRA0rmXEXjwIGnssbY2UuqCxFbhL41BB41I24seCoInP0NURitSD5tillyqrKflVMr8cObII/cruVV6vmJtEwPhNfLVKpr9zwNUURYoriqBZ6kI6LcpbTUr623irS4nEOaIrTIWsvNkky4V78kZkjgoc7YfDFo4AgiYcr7wcjaDJS6bCxYmgCccrT0cjaPKUrXCxImjC8UrjaASNBcoIGgsQHRoCQeNQMiyHkldBo1UwWg2j/WJKS1yXpi1p1Yy/tba0LlreWldX2iMyZmPfJssU3RvOtqBJQt7omCpo/OobFTe+wNGeN1uk902v5JBtMQEETTG/EQiaYuYVQVPMvOpdIWiKm1sEjXu5zUTQaB+aT3zuK4to5HnpbQSNe1/sOBEhaOLQc/vcPAiaqbnJkohRISN9Y1TIHJaH9pOp3q5fuc0TMipivOWuvUqZPW4nIKHo0hQ0YeTNKzptyptCVZo2NX2l/kpT/piDbVJxU54qpQJnszQuLu21Cmd5ChwETUI/NBkPi6DJOAEJXR5BkxBYB4ZF0DiQhIRCQNAkBDbGsKkLmoe/+i3zyNefMI996ZPm1j3bvdCfP3jMvPfDnzIfet/9uVzdCUET4xvo4KkIGgeTYikkF3vQHL30ore0dWWpa5ExutJS9baqe3VlWWu/MkanKvV29Fkik+9hXBE0S1HUnjaviaQ5Jb1vXvX2c/JaH6X3XluYNRfnFxoOoY2LN4mw2SiP60TabBSZc52Im+uk703pvXYzJFOqirYhaIqW0dL9IGiKmVcETTHzqneFoClubhE07uU2dUFz9wMPmXe/495rRIyKm29+5we5XN0JQePeFztORAiaOPTcPjdrQXN2/LRUxJSmKh0afqE0VUmez87PVMC1t7aXKmNkNSWdouRVyAzebDb0Xec23Ayjy4OgaYZnqixwVNpUy5vXVOTI49TCnBlZQuB0yfQoT9qIvLmuIm/KIkeFjsib1fJ+3jYETd4yFixeBE0wTnk7CkGTt4wFjxdBE5xV3o5E0LiXsdQFja7iVG86kz/tiVWc3PuSLLeIEDTFzXiagmZybqI8VUlljL/U9S/M8OSFRYC3DtzgrarkCRlPzOw1N67eXdwkJHBnRRA0zbBo4+JKtY1U3XgiR6TN1f28GVtovHR4jwicSrVNbRVOuQLHxSbGCJpm34x8fo6gyWfemkWNoGlGKL+fI2jym7tmkSNomhFK//PUBQ0VNOknmSuGI4CgCccrT0cn2YPmpeFD5rBUxVSa+EplzImRY4vwDPYMeb1i9oiEqexFzvS0r8gTRudiXQ6Cphn0sQUROOVpU14Fjvdcpk+JtNG9ipwJkTyNtj6psPErcLTaxq/E2ehNoyq97sugiTGCplnm8/k5giafeWsWNYKmGaH8fo6gyW/umkWOoGlGKP3PUxc09KBJP8lcMRwBBE04Xnk62pagOTN+apGI8VZYkoa+c1LR4G8dbZ1Xpyh5TXz3ektdr+vdkCdkuYgVQdM8TSMqcCpVN7PSB6c8lcoXOdIHZ2oJgdPfKj1wvKlS0u+mugLH74cj+xUJCBwETfPc5vEIBE0es9Y8ZgRNc0Z5PQJBk9fMNY8bQdOcUdpHpC5o9AZZxSntNHO9MAQQNGFo5evYKIJmfPayrKIklTEiYFTEeBUyMmXp4uTwopvftnJHSchUTVXasWpXvgDlNFoETfzETYucKa02VVp5Sleg0pWnTnrPZ81ZEThLbdrEWJsV64pT/lSqDdLzZl25sbF+tlEaGYfdEDRhieXjeARNPvIUNkoETVhi+TkeQZOfXIWNFEETlljyx2ciaJK/rXSvQJPgdHknfTUETdKEsxs/SA+aF4cPlnrHqIgpN/R9efT4oqDX9Ky92sTXW+q69Ohu78nu5pbxlRE0ySf/vDdVqmrVKRE33upTOn2q/HyuyTLi/a2tZr2ImnVShbNe5M16ETbr5fk6mUK1XqZVrZcqnHXyfvVUKgRN8rnN4goImiyoJ39NBE3yjLO6AoImK/LJXxdBkzzjsFdA0IQlVud4BI0FiA4NgaBxKBmWQ6kVNKfHXzMHZYlrrYjxlrpWISOVMvNVzVY7W7tKPWNkelJpVaVSlczannWWo2O4qAQQNFHJ2TvvrEyVOifTqM6IxDkrwkYrbs7Ie2flZ0n353Q/N2+0UmeprVemSamk2aCyRqTN9r4u0yuLnJXe8+VOu3GxobE9msUfCUFTzBwjaIqZV70rBE1xc4ugcS+3qQkav/fMh953f90lth/5+hOm3mfuIbs2IgRNHrIUPEYETXBWeTry8syY+ZsnHjMzmxbMCzOHylUyvzAj05cW3cb2VTdeFTEqZUTO3LByZ55uddnFiqDJR8q1D86ZsrxRcaNS54yInLMidTyZo8+lj5M2PF5q65bpVFp5s75DhY1U3mhVjgocb3+1QiePy4rnI5Pxo0TQxGfo4ggIGhezYicmBI0dji6OgqBxLyupCZp3PvgJMzQ4YL72xY/WpfC7H/m8uTA8ar796Kfdo9QkIgRN7lK2ZMAImmLkU5ezfubUD83PzvzE/Pzsc+a5088Y7SdTvXW1dUtFzM3mzuveZG5d+zpzx4Y7jfaSYcsXAQRNvvLVLNpTWoUjokb3E90t5vDolFeJc3JWp1Vpc+NZqcS50mwYT9oMymN1S7vZ0tFhBmWK1Wp5qNTRfjiDInMGW0rP2dIlgKBJl3daV0PQpEU6/esgaNJnntYVETRpkQ5+ndQEzd57HjSf/tgHzAP33VU3Or9x8IEnHw0evSNHImgcSYSlMBA0lkCmOIyunnTg/H7zzGslIfPcmWfMydET10Rw09Bus2/d68xta19vbhcZs3fNPtMu/088W74JIGjynb+loq/Xg0Z73XhTprTixqu88StxZGqVV5lTnl4l7y/d2rh05R6ZVjXU1mrWyO8ClThrZHrVkPdem1kjD90PyWdD3mftptu0FBd4SneGoEkJdMqXQdCkDDzFyyFoUoSd8qUQNCkDD3A5BE0ASM0OQdA0I5SvzxE07ufr1OVXvYqYn5z+kXlW9gfO7TfT81OLAh/oWulVxNy+/k7zOnno8xvWrjOXJ+X/fZ9degqF+wSIsJoAgqa434c4TYIviqi5cGXenNe9PkTenJeqnAvSB+e8yJvSe/J8YdYMzwf7naA9cjxhow+pvlFho+KmJHFKImeNND0ufdZmOpE5db+cCJpi/swiaIqZV70rBE1xc4ugcS+3qQmaux94yPzBh96zZAXNFx75hnnq8Yfdo9QkIgRN7lK2ZMAIGrfyqdOS9ssUJZ2m9JNTP/L2KmhqN62G0aqYfWtv9/Y6dal2C7KKk1t3TzRBCCBoglDK5zFxBE3QO9bJUrpK1QVpYnzhylxZ6Ki4EYlTLXRU5ojYGW3SI8e/br8Im0EROp6wkeclcVMWOip2vM+kWkcrc+RzXap8uWwImmJmGkFTzLwiaIqbV70zBI17+U1N0Hz8M182L7x4omGPmWY9atxDdzUiBI3L2QkfG4ImPDObZxy68IJXHbP/XKlvjE5dqt0Ge4bMnRvfJDLmdZ6M0UdvR1/TMBA0TRHUMgVIAAAgAElEQVTl8gAETS7TFijoNARNoEDKB83K9CqvEsevyFlUiaOVOiJ4VPaUPx8PKHN0VaqSxCmLG+2PU6nSUcGjEkdkjkzFGpLP2sIE7eCxCBoHk2IhJASNBYiODkEFjaOJsRAWgsYCRMtDpCZoNG6totGttkpG3x++NGby2H9G7wdBY/lbmfFwCJr0EnB24ownYdJq5IugSS+3aV4JQZMm7XSv5ZqgCXP3kzKV6oJMnfIqcSpCpzzVyntder8kexaaLkHuX3uVJ3NkKlWlP45OuSr3yNFpVt77+rrUQ8fFuhwETZhvUn6ORdDkJ1dhI0XQhCWWn+MRNO7lKlVBo7evlTRPfP+Hi0i84fY9DVd3cg/ZtREhaPKQpeAxImiCswpz5Onx18zB8wfMoeFfmEOyP3jhF95jQf6I8bfO1i5vWevdurz14F6zZ+0t3vM1PWvDXKrhsUMDXfSgsULSrUEQNG7lw2Y0eRY0YTmcnJNeOFJ9o/1wzslKVbpi1TkRN8NeM+R57/WwSJ2gU6z0+l0ybUqXHvdWrdIpV1KBs1Hkzlqt0NHXIns2yzQr7a2jFTtpbQiatEinex0ETbq807wagiZN2uleC0GTLu8gV0td0AQJKm/HIGjylrGl40XQxM/nxNx4ScIMi5BREXNOHiJmLk1dXDS4Lmm9Z0hEzJpbRcTIXh7bV90YP4AGIyBoEkOb6cAImkzxJ3rx5SRogoLUVay85calP44vdE5Lo2OVOPpaV7jyliqXY4IsR159XV2afIUuPS4CZ6XInAFdklyer5AyHF2eXJcm7xXpE1fqIGiCZjtfxyFo8pWvMNEiaMLQytexCBr38oWgsZATBI0FiA4NgaAJn4wjFw+LiDlgXhAZc+i8POT5idFfLhpI+8bsGbrVkzAlGaPVMXtNd3tP+AtGPANBExGc46chaBxPUIzwEDQx4Mmp41KhqBU4r3jVOQuetLkoAuekyhxteCyfq8wZkffCVObElToImnh5dfVsBI2rmYkfF4ImPkNXR0DQuJcZBI2FnCBoLEB0aAgEzdLJ0L4xB88/L1OVpEJGpyxphYw8n5OSfH9rb+vwpih5U5V0ypJOV5Ln63o3ZJppetBkij+xiyNoEkOb+cAImnRToLJGpc45bzrVghkXcfOKPB+Xqh19rVOv9HlcqbNeplzptKr1Mt2qXqVOb3n61QqZgqVTsdKegpUu9eJcDUFTnFzW3gmCpri5RdC4l1sEjYWcIGgsQHRoCATN1WRMzU161TDaK6a0LwmZC5PnF2Vs68ANXjXM7jWl3jH6/MbB3Q5ltRQKgsa5lFgJCEFjBaOTgyBonEzLoqDSkjp6UV/U9La2mNWyZLnu/WlX2k9nhfbSkT2CJ5vvDYImG+5pXBVBkwblbK6BoMmG+1JXRdBYyAmCxgJEh4ZYzoLm2KWXyhKmXBkjQuaXl44sys6q7tUiYWR6UrmZ7806VUmer2jvdSiL9UNB0DifokgBImgiYcvFSQiaXKQpdJCXO40ZmVswL09MLarUGZXqnBGp1BmVyp0RaZase52GFWcKVnVwvuAZEJGj/XX86p2VInUGpLdOv7zvPdfPdC89efTYlfJal0JnW5oAgqa43xAETXFzi6BxL7cIGgs5QdBYgOjQEMtF0JyfPFeanuStrKTTlZ73ns8sTFey0Sr/YepNT9LKGHnsFjGjU5Y29F7nUMaCh0IPmuCs8nQkgiZP2QoXK4ImHK+8HB2lB82MueL1yRnzBI7uVd7IezIFy3tPnnvv6WcidSrHLJTfl/dm5JioW5cndVTilGRNvydySnsVOypy9PlKkTr9ntCpOVY+7xAJVOQNQVPc7CJoiptbBI17uUXQWMgJgsYCRIeGKKKgmZ2fKa2oJA18vUa+OlVJnp+bPLuI/Ob+60syptzAV3vI3DS4x6HsxAsFQROPn6tnI2hczUz8uBA08Rm6OEIUQRP3PqarBY80SdbqnDEVPLoPIHhGRPDoClpRt+4qwVMtdzzJU67Sufp+jeDxzm017Y4LHgRN1G+H++chaNzPUdQIETRRySV3HoLGAlsEjQWIDg1RBEFzYvSYeUGWtvYb+OqS10cvvbiI8kDXyoqIuSpk9pr+zgGHsmE3FASNXZ6ujIagcSUT9uNA0Nhn6sKIWQiauPc9KYLmavVOafpVSfBoxY4Kn2sreErVPXKMfK7HxhE8PV6FTotU6miFjlbq6OvSFCyvgmdRVc9VweNJn3J1T9KCB0ET91vm7vkIGndzEzcyBE1cgvbPR9BYYIqgsQDRoSHyJmiGJy+URIxWxQyXpyzJ88m5iUVUtU+M1ztGl7j2pivtNZv6tzhEPvlQ6EGTPOMsroCgyYJ6OtdE0KTDOe2r5FHQxGU0cY3gKU/F8t6vEjxa3VM5tqrKRwTPfIwKHm2gPCBSxxc83hQsT/D4+/J0rXIPHl8GaT8eX/4068KDoIn7LXH3fASNu7mJGxmCJi5B++cjaCwwRdBYgOjQEC4LmrmFOa9fjE5PqhYyZ8ZPLSJ4Xd/mkogpN/BVMaNSZrlvCJpifgMQNMXMq94VgqaYuV2OgsZGJs+KvJkWeaMrZ83LlK3XpEJHpc0p3csFTsl/I8xdaZHPZ2Uvr733S5/Hqd7xY9/Y1u5Ns9ooy6S3yXWu072+1vflOqvb28z67k5zeXLWbGnv8E5bLUup62pb7aZ0Hls+CSBo8pm3IFEjaIJQSvcYBI0F3ggaCxAdGsIlQfPy6PFSvxitkNFGvjJt6aWLhxbR6uvoL62opM18RcjsWatLXd9idAoT22ICCJpifiMQNMXMK4KmuHlF0GSTWxU7cypsmgiek7OzXoCvzJf2J0X42NzWSSNlbbrcJXJnrQgc72e9LHt65T1dKl23zSJ+dPNX1WqrkjyDMoauysWWDgEETTqcs7gKgiYL6ktfE0FjIScIGgsQHRoiK0EzMn1JqmJKDXy9FZU8MXPAjM9eXkRnlzTt9atj/KlKWwa2OkTQ3VDoQeNubuJEhqCJQ8/tc6mgcTs/UaND0EQll+15vqh5pSxsKq+lQke3EZE/0+JMJmbmzWsigXQ7J1U901Llo5U/WgFke1PJs64sctaq+DGtXsXOYPm9auHTqcfKlC3dukQC+c+rxY9+5lf/2I41z+MhaPKcvaVjR9C4l1sEjYWcIGgsQHRoiLQEzfGRo+bAuf3muTM/kccz3vNaGdPV1m1uW3+7uW3d7eb1G95o9skeGRP9y4Kgic7O5TMRNC5nJ15sCJp4/Fw9G0HjambixRW0B41fyTMuDZQvisDRzZc9I+Vl0uekWkanZuk2LHs9dtosmHNlyXNW3lPxk/RWLWv8qV16Ta8KqFzpo6Knq7yC+mp5rlJIN7/yx3sux2uzZt208kcrgPK0IWjylK1wsSJowvFK42gEjQXKCBoLEB0aIglBUy1jDpzfb35+9lkzOj1yzV3vHrpZJMwdZt/a15k7r3uTLHF9s2kvl/86hCi3oSBocpu6JQNH0BQzr3pXCJpi5hZBU8y8BhU0Nu9+XCpzhsvSxp+6pZJHV9nSbVwkzsWq58PymW7TsvcreuZbStO+dNNePb4Yshlno7GqK4Cqp3y1i+PZWO7jo+duqRI6/tQvfV+lkfb30W2tVA3pGLr508hs3QOCxhZJ98ZB0LiXEwSNhZwgaCxAdGiIOIJmen5KpiW94FXDvHBhv1EZo9OU6smYbSt3mL1r95nb17/e7F2zT6pk7qBvTMLfA3rQJAw4o+ERNBmBT+GyCJoUIGdwCQRNBtBTuGQWgiap21JRMykFOrq8uveQCp7Kc5nKdfV1+X0RPpNyzlTls6rjK+fqe3pu6VgdL8kaIP3vWV2evVuu0iPVPvq8p/yet9f3RO5Unld/7h1vSufLsRv6uszC9ILpEL/VI1PIqsdJevn2pHLMuCUCCBr3vgkIGgs5QdBYgOjQEEEFjS5vrVOTjlw8bPaf/Zk5rKsriZypt+m0JJUwWhmzd+1tImXuNIM9Qw7d9fIIBUFTzDwjaIqZV/8/HPk3tnj5RdAUL6d6R0USNGllqLoCSKdsnStP6/KbOWscujLX6YWrjZpPVvXy8Vfs0uP8Vbv0eVpTwHxOtqaC1fYDWlle5j2tfCzH6yBo3Ms6gsZCTviPRwsQHRqiVtBo9YtKmNLjRW9/9NJL3r52G+pZY3auusnsXL1LHrIfvMnskOdbB25w6A6XbygImmLmHkFTzLwiaIqbVwRNMXOLoHEzrzoFTEWQbsMy3WuiPM0rzFSwTplzNTW/UGn+nPZUMJ+sv9S7JwSrVgHT14Nt2iD6am8ff/l3/ay6QXTpWFn+vTwdTF9vrppOlsceQXG+eQiaOPSSORdBY4ErgsYCREeGODl6why79KI5PXXUPPfqAXO0LGTOTZ69JsKtA9uvihiRMTeKjFEps7p70JG7IYxrBNpAl7k8OWumZ0v/ocJWDAIImmLksd5dMMWpmLlF0BQzrwiaYuZV76pZD5rqpdj9XkB63mtSETRfbuZ8VuTQTPm59gLS/kC6+U2g9Xl1I+jSZ1flUpZ0Gy3rvrmt45qwqlcRq/6wupm0/77qJBVJtZuKJn+5+erPqvsM+e9rDyLtRRR1Q9BEJZfceQgaC2wRNBYgpjzE1NxkpQrGr4o5MlyqkJlZmF4UTU/7iioRU66M0eqYVbtMe51fzCnfCpcLQYAmwSFg5ehQBE2OkhUyVARNSGA5ORxBk5NEhQwTQRMSWI4ObyZokr6VWe3vU+7xMyVyR6eD6evSXl5LAN7nIoEqn0nvHe9Y+Uz7/njLvetx3nvlz7w+Q3KO91o/l4fsvbHluVYK5WmT9kCmXabEdcoTVTZaOaQCp0P2HbqXhcQ65PMO+bxT+gvpMf+4Z2eebnFZxIqgsZBmBI0FiAkOcXb8tMgYnZpUmp7kT1V6Zezla666bsV6rwrm1o03m+t6dlSmK20euD7BCBk6LQIImrRIp3sdBE26vNO8GoImTdrpXQtBkx7rNK+EoEmTdrrXylrQpHu3pavNi5uZlaXdZ3UvokbX+ZoRGXR131J6XXOcdguaFQk0K7KktG+RvZ5/xasgmpVzZkWWlPblY3Rfew05d07OnfH21ceVjp2V8RbtvTgXTGn9suDbldftC34wR6ZCAEFjATOCxgJEC0NckV9WvnypFTJjM6PXXEF7w3i9Yqp7xoicWdW9yqxb3WVOD09ZiIohXCJADxqXsmEvFgSNPZaujYSgcS0jduJB0Njh6NooCBrXMmIvnuUoaOzRS28kncB/VfyoxCm9rkglqZ6ZEemkUsnfv2cTi5akl6FgV0LQBOO05FEIGgsQQw4xtzDnVcToykn+Cko/P/uc0ZWV6m27h26WZr03easo7R7aa/atu91otUy9LegqTiFD5nAHCCBoHEhCAiEgaBKA6siQCBpHEmE5DASNZaCODIegcSQRCYSBoEkAqiND0oPGkURUhYGgsZATBI0FiA2GGJ+9bI6PHDPHLx0VGfOCOSSPo+XVlFTS1G69HX1eVcztG+40O6RHjO71tb4fdEPQBCWVv+MQNPnLWZCIETRBKOXzGARNPvPWLGoETTNC+fwcQZPPvAWJGkEThFI+j0HQuJc3BI2FnCBo4kGcnp8yv7wkEmbkaPlxzJMxKmXOTpxpOLhWwGgljFcRI5UxN0mVjPaPibshaOISdPd8etC4m5s4kSFo4tBz+1wEjdv5iRodgiYqObfPQ9C4nZ840SFo4tBz+1wEjXv5QdBYyAmCpjlErXYpCZhjImOOmhOjJSFz6MIL5tTlVxsO0N7abrat3CGP7eaGVTu8qpi9a/Z5Imaga2XzC0c4AkETAVpOTkHQ5CRRIcNE0IQElqPDETQ5SlaIUBE0IWDl6FAETY6SFTJUBE1IYDk6HEHjXrIQNBZygqApQdTpSCdHXzYnx47L/oR5efS4eWVM9iPyWvaj0yN1aev0oy2yStLm/q3m+oFtZovst6ws7fV1UiKmUeoRNBZ+KBwdAkHjaGJihoWgiQnQ4dMRNA4nJ0ZoCJoY8Bw+FUHjcHJihoagiQnQ4dMRNO4lB0FjISfLSdDMLEyXhIuKGBEwKl48EaNCRsRMoya9nW1dJeGycuu1ImZgqxnqXmMhE3aGQNDY4ejiKPSgcTEr8WNC0MRn6OoICBpXMxMvLgRNPH6uno2gcTUz8eNC0MRn6OoICBr3MoOgCZCTdz74CXPkeGkazs5tm8y3H/30orOKJGi058s5eQxPnvemHunj3ORZb69VMTpFSStlGm2DPUPelKQb5LFrcI+33yZTk3SKUphGvQHSktghCJrE0GY+MIIm8xQkEgCCJhGsTgyKoHEiDdaDQNBYR+rEgAgaJ9KQSBAImkSwOjEogsaJNCwKAkHTJCe/+5HPmwvDoxUpo7JmaHDAfO2LH62c6bqg0f4vnmgR8eILGH1+avxVc3a8LGSmLngCJsimU4488VKWLzeJiPGlTNrTkYLEG/YYBE1YYvk5HkGTn1yFiRRBE4ZWvo5F0OQrX0GjRdAEJZWv4xA0+cpXmGgRNGFo5etYBI17+ULQNMnJ3Q88ZP7gQ+8xD9x3l3fk49992nzhkW+Ypx5/OHNBo5UsnmgR+fKaPHR60XmpdlEJo7Ll4tR573mjaUf1bl0rYAZlutFaWSFpi0w90pWSVncPmo19m7wpSipi9Jgibwia4maXHjTFzC2Cpph51btC0BQztwiaYuYVQVPMvOpdIWiKm1sEjXu5RdAskZPnDx4z7/3wp8xjX/qkuXXPdu/Ieu9VV9DoktFalVK9jc6MSIPcS4veU3EyPTe16L1Xxl5e9Hp6fnrRMtMqYrQaRhvv6jX0WkE3FSwqW1S8DPasEdlyvffce9095AkYfeiqSct9Q9AU9xuAoClmbhE0xcwrgqa4eUXQFDO3CJpi5hVBU9y8+v/OFvsO83d3CJqYgqblP7RklvXu9m6zoW+D2Tyw2dvrY82KNWarNOKtfq2fs0EAAhCAAAQgAAEIQAACEIAABCDgLgEEjSVB09fZ58mR6k2rUerJEX2vtlJFhYoKl+ptpfR6WdW9qvKWf4wvX6o/c/crRmQQcIfAn//5n5u3vOUtZtu2be4ERSQQgAAEIAABCEAAAhCAAASEAIKmydegXg+aT3zuK+bAk49WznS9STDf9HAEmOIUjleejqZJcJ6yFTxWpjgFZ5W3I+lBk7eMBYuXKU7BOOXtKKY45S1jweOlB01wVnk7kh407mUMQdMkJ0VYxcm9r53bESFo3M5PnOgQNHHouXsugsbd3MSNDEETl6Cb5yNo3MxL3KgQNHEJuns+gsbd3MSNDEETl6D98xE0AZjq0tpHjr/qHblz26bKktv+qVTQBICYo0MQNDlKVshQaRIcElhODkfQ5CRREcJE0ESAloNTEDQ5SFKEEBE0EaDl5BQETU4SFSFMBE0EaAmfgqCxABhBYwGiQ0MgaBxKhuVQEDSWgToyHILGkUQkEAaCJgGoDgyJoHEgCQmEgKBJAKojQyJoHElEAmEgaBKAGnNIBE1MgHo6gsYCRIeGQNA4lAzLoSBoLAN1ZDgEjSOJSCAMBE0CUB0YEkHjQBISCAFBkwBUR4ZE0DiSiATCQNAkADXmkAiamAARNBYAOjYEgsaxhFgMhx40FmE6NBSCxqFkWA7l/2/vfl7tqA44gM8/YEhjoVALSqqFKNlk0UCJ4KrYTQxumo2QGilxkY1dRBtwIY3VhXaRhcFfDQglbcHGdFERoUKCoFA3QbJQggtdCBqL/QfquXAek5t739wzc2bm+M7nrTRv5pwzn+/My833zZ2roMkMWshwCppCgsi8DAVNZtCChlPQFBRG5qUoaDKDZhhOQZMB0R00GRALGkJBU1AYmZeioMkMWshwCppCghhhGQqaEVALGFJBU0AIIyxBQTMCaiFDKmgKCWKEZShoRkAdOKSCZiBg2F1BkwGxoCEUNAWFkXkpCprMoIUMp6ApJIgRlqGgGQG1gCEVNAWEMMISFDQjoBYypIKmkCBGWIaCZgTUgUMqaAYC2p0AAQIECBAgQIAAAQIECBAgMFRAQTNU0P4ECBAgQIAAAQIECBAgQIAAgYECCpqBgHYnQIAAAQIECBAgQIAAAQIECAwVUNAMFbQ/AQIECBAgQIAAAQIECBAgQGCggIKmJ+BDx043n372xWLvu++6o3nr/JmeI9ltCoHUvLbb/uLbV5rTz716y7I/fu/8FIdijg6B1KzDcFevXW+OPv5Mc+Glp5v9+/YyLkAgZ46u2QIC3WYJKVk/+sTzzQcfXbtpND97y8g3Z46u2TIyXbWKlJyfevbl5tI777teC40zZ5au2UJD/m5ZKTm3jyJev14bT5+tgqaHeXiB+PWNb7dKmXDi375nV/P6i6d6jGaXsQVS8+raPvwl9MK5vzaXL54de+nGTxToym7VcPcfOdnc+O//Ft/yl1Ai+Eib587RNTtSUBmGTc06XK/tn73hBeSVD6/6eZwhiyFD5M7RNTskjfH2Tc05vD7+w6njW7/4OPvam83f/vlv1+t4EW08cu4sXbMb00+6YWrOcXEhzz9f+NfiZgSvjSeNbDGZgqaHeXiB+LsTv26OPHhosbcfSj0QJ9wlNa+u7eU9YXiJU3Vlt244d9AkQo+8ee4cXbMjBzZg+L5ZxylduwPwM+6aO0fXbMZwMg6VO+eMSzNUokDuLF2ziQFMtHnfnO974NiimHF3+URBLU2joEl0X/Vi0AvERMQJN0/Na5PtV93G6Rb7CUNdM9Um2Slo5s+pawVj5Oia7VKf5/tDso4r9hv5ebJrzzpGjq7Z+XNdXkGOnMNv8z+5/rk7aGaOd4wsXbMzh7pi+r45hzvffnP0V81P7/yxgmamWBU0ifB9T/bEaWyeSSA1r9TtwzKXbx/MtHTDJAr0yS5OoWRNxB5x8ylydM2OGGDC0EOyDtPE/c88+djWHa0J09s0k8AUObpmM4U1YJghObffSuwXWgNCyLTrFFm6ZjOFNWCYPjmHtw1/+dU3i8d2eG08AH/grgqaRMA+J3viFDbPKJCaV+r27X8keNGRMbgeQ/XJTkHTA3rkXabIMc7hmh05zI7hc2R94pHDzcnjD897IJXPPkWOrtn5T7IhOcfVhzvezr1xqfGzd948p8jSNTtvxu1/n7SfIbNd6bL8NjUFzXwZKmh62K96P1/4VB9/4fTAnGCX1LxSt4+3dcp/gjA7pkjNTkEzf2arVjB2jq7ZcnLvk3XMz4ML68nRNVtG1n2u1+WVx2db+MTEeTMdO0vX7Lz5xtlTcl73SVxhLL8MmTZPBU0P775PxO4xlV0yCHTlFd5rGb7iR6V3bb/8KSI+xStDSJmG6MpuOWsFTSb4zMPkztE1mzmgjMOlZu1BlBnxMw6VO0fXbMZwMg6VmrNPXcuIn3mo3Fm6ZjMHlGm41Jzb07qDJlMIPYZR0PRAC7v0/Uz5ntPZbaDAdnmt+kd71/bhY+fi18ED+3zE+sB8cu7elV27jAv/3X5vfPj/Pbtv8wDDnIH0HCtnju2xwnJcsz1DGWm3TbOOLxZXLcNzaEYKJ2HYnDm6ZhPgJ95005yXXyvHZbrbeOLAtpkuZ5au2XJyXV5JSs7tfRU082WqoJnP3swECBAgQIAAAQIECBAgQIAAgYWAgsaJQIAAAQIECBAgQIAAAQIECBCYWUBBM3MApidAgAABAgQIECBAgAABAgQIKGicAwQIECBAgAABAgQIECBAgACBmQUUNDMHYHoCBAgQIECAAAECBAgQIECAgILGOUCAAAECBAgQIECAAAECBAgQmFlAQTNzAKYnQIAAAQIECBAgQIAAAQIECChonAMECBAgQIAAAQIECBAgQIAAgZkFFDQzB2B6AgQIECBAgAABAgQIECBAgICCxjlAgAABAgQIECBAgAABAgQIEJhZQEEzcwCmJ0CAAAECBAgQIECAAAECBAgoaJwDBAgQIECAAAECBAgQIECAAIGZBRQ0MwdgegIECBAgQIAAAQIECBAgQICAgsY5QIAAAQIECBAgQIAAAQIECBCYWUBBM3MApidAgAABAgQIECBAgAABAgQIKGicAwQIECBAgAABAgQIECBAgACBmQUUNDMHYHoCBAgQIECAAAECBAgQIECAgILGOUCAAAECBAgQIECAAAECBAgQmFlAQTNzAKYnQIAAAQIECBAgQIAAAQIECChonAMECBAgQGCHC5x97c3m3BuXbjnKE48cbk4ef7i5/8jJxfcuXzx7yzbhe3t272reOn9m8b2use574Ni2mnt237aY59Ennm8++Ojaym3PPPlYc+TBQ81Dx043n372RRP/P2588e0rzennXm3uvuuOrXUtD7TJOg79fH9z6Z33t3Y9/MtfNH/8/W+T5t3kOHb46eXwCBAgQIAAgUwCCppMkIYhQIAAAQIlCsQC4cJLTzf79+3dWmIoWt69/J+tgiMUGgcP7Gtef/HU1jZPPftyc+XDq1vFzaZjLRcpywVL+H4Y6+sb364tWMI2saBZXlf88+0KmnYWsdBZtY5V30uZd5PjKPG8sCYCBAgQIECgPAEFTXmZWBEBAgQIEMgmEIqXeGfIdoMuFxVXr11vjj7+zE13r2w6Vs6C5vY9uxZ32sSCKa4rlDZdBc8m61hX0Gw6r4Im26lqIAIECBAgUL2Agqb6UwAAAQIECOxkgfAWpXv2/uSmO2PWHW8oGz65/vnijplwF0koKdp31KSMFebY7s6VTYqNsIZ7f3Zn8+VX3zQ/+uEPFm8/Cnf1hK/wZ2MWNJvOu8lx7OTzy7ERIECAAAEC+QQUNPksjUSAAAECBIoTiCVJXFh8Bsy6hbaf3fLxe+dv2ix1rK6CZpNn0ISi5OCBexfPnAnrCesLd9P86ZW/j17QbDKvZ9AUd8pbEAECBAgQ+N4KKGi+t9FZOAECBAgQSBOIbw+Ke6166wGjRIIAAATfSURBVFMsVeIDhNfNkDLWkGfQhIImPrg3rCXe1ZNy50qfZ9BsOm/KOtLSsjUBAgQIECBQm4CCprbEHS8BAgQIEPhOILxVKHyC0fJdMquePdMFtm6srjtout6iFN/iFAqa+OlRsexJKUaGFDRd86aso8vR9wkQIECAAIG6BRQ0defv6AkQIEBgBwuEsuUv/3h3cQfK8lcsHpY/3WldQdNnrJwFTVh/eAZO/CjwlGJkSEHTNW/KOnbwqebQCBAgQIAAgQwCCpoMiIYgQIAAAQIlCrTfhtS+U6b9SUjthwCHY9iuoAmf6hS+Nh0rd0HTNk4pRoYWNNvNm7KOEs8RayJAgAABAgTKEVDQlJOFlRAgQIAAgVEE2g/+jROse8ZM11ucUsbqKmg2fUjwqjuAUoqRdeuIb82KJvGZPO23Vi0HsjyvhwSPcsoalAABAgQIVCmgoKkydgdNgAABAgQIECBAgAABAgQIlCSgoCkpDWshQIAAAQIECBAgQIAAAQIEqhRQ0FQZu4MmQIAAAQIECBAgQIAAAQIEShJQ0JSUhrUQIECAAAECBAgQIECAAAECVQooaKqM3UETIECAAAECBAgQIECAAAECJQkoaEpKw1oIECBAgAABAgQIECBAgACBKgUUNFXG7qAJECBAgAABAgQIECBAgACBkgQUNCWlYS0ECBAgQIAAAQIECBAgQIBAlQIKmipjd9AECBAgQIAAAQIECBAgQIBASQIKmpLSsBYCBAgQIECAAAECBAgQIECgSgEFTZWxO2gCBAgQIECAAAECBAgQIECgJAEFTUlpWAsBAgQIECBAgAABAgQIECBQpYCCpsrYHTQBAgQIECBAgAABAgQIECBQkoCCpqQ0rIUAAQIECBAgQIAAAQIECBCoUkBBU2XsDpoAAQIECBAgQIAAAQIECBAoSUBBU1Ia1kKAAAECBAgQIECAAAECBAhUKaCgqTJ2B02AAAECBAgQIECAAAECBAiUJKCgKSkNayFAgAABAgQIECBAgAABAgSqFFDQVBm7gyZAgAABAgQIECBAgAABAgRKElDQlJSGtRAgQIAAAQIECBAgQIAAAQJVCihoqozdQRMgQIAAAQIECBAgQIAAAQIlCShoSkrDWggQIECAAAECBAgQIECAAIEqBRQ0VcbuoAkQIECAAAECBAgQIECAAIGSBBQ0JaVhLQQIECBAgAABAgQIECBAgECVAgqaKmN30AQIECBAgAABAgQIECBAgEBJAgqaktKwFgIECBAgQIAAAQIECBAgQKBKAQVNlbE7aAIECBAgQIAAAQIECBAgQKAkAQVNSWlYCwECBAgQIECAAAECBAgQIFClgIKmytgdNAECBAgQIECAAAECBAgQIFCSgIKmpDSshQABAgQIECBAgAABAgQIEKhSQEFTZewOmgABAgQIECBAgAABAgQIEChJQEFTUhrWQoAAAQIECBAgQIAAAQIECFQpoKCpMnYHTYAAAQIECBAgQIAAAQIECJQkoKApKQ1rIUCAAAECBAgQIECAAAECBKoUUNBUGbuDJkCAAAECBAgQIECAAAECBEoSUNCUlIa1ECBAgAABAgQIECBAgAABAlUKKGiqjN1BEyBAgAABAgQIECBAgAABAiUJKGhKSsNaCBAgQIAAAQIECBAgQIAAgSoF/g/gzx9MnP3LPgAAAABJRU5ErkJggg==",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"dynamics.plot_history(colors=['darkturquoise', '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": "code",
"execution_count": null,
"id": "8b4558a2-9e0b-4fe9-82d6-1d6661805a4f",
"metadata": {},
"outputs": [],
"source": []
},
{
"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": 23,
"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_simple(t=t_arr_late, A_conc=A_conc_late, B_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 on \n",
"\n",
"Let's see the graph again:"
]
},
{
"cell_type": "code",
"execution_count": 24,
"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": "darkturquoise",
"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=['darkturquoise', '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": "2c1ea8cf-b3f6-4569-a700-c0fe86e47fbb",
"metadata": {},
"source": [
"#### Is that surprising? At early times, compare the inflection of the final product, C, of the composite reaction vs. the inflection of the product of a simple reaction (such as B in experiment `react1`, both appearing in green.)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "1014bb04-6d8a-4ab5-b59c-2c23ef6896b4",
"metadata": {},
"outputs": [],
"source": []
},
{
"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": "3.9.13"
}
},
"nbformat": 4,
"nbformat_minor": 5
}