{ "cells": [ { "cell_type": "markdown", "id": "5cbc8640", "metadata": {}, "source": [ "### A MINIMALIST, \"get-started\", demonstration for the reaction `A <-> B`,\n", "with 1st-order kinetics in both directions, taken to equilibrium.\n", "\n", "**\"No frills!\"** For advanced graphics, analysis, diagnostics, fine-tuning, etc, please see other experiments." ] }, { "cell_type": "code", "execution_count": 1, "id": "97a57e9a-039b-479a-81dc-81399e22743a", "metadata": {}, "outputs": [], "source": [ "LAST_REVISED = \"Aug. 19, 2024\"\n", "LIFE123_VERSION = \"1.0.0.beta.38\" # Version this experiment is based on" ] }, { "cell_type": "code", "execution_count": 2, "id": "b5b8a8b0-d417-4432-b6a8-c196af57b105", "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": "a29db1c7", "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", "import life123" ] }, { "cell_type": "code", "execution_count": 4, "id": "ccd6701b-ae96-4d20-b537-40c2c40df9aa", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "OK\n" ] } ], "source": [ "life123.check_version(LIFE123_VERSION)" ] }, { "cell_type": "code", "execution_count": null, "id": "ac9eea69-174c-43e5-9eed-443cbc5e2ba7", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "e0529a0c", "metadata": {}, "source": [ "## Initialize the System" ] }, { "cell_type": "code", "execution_count": 5, "id": "78077d8c", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 1 (at temp. 25 C)\n", "0: A <-> B (kF = 3 / kR = 2 / delta_G = -1,005.1 / K = 1.5) | 1st order in all reactants & products\n", "Set of chemicals involved in the above reactions: {'A', 'B'}\n" ] } ], "source": [ "# Instantiate the simulator and specify the chemicals\n", "dynamics = life123.UniformCompartment() \n", "\n", "# Reaction A <-> B , with 1st-order kinetics in both directions\n", "dynamics.add_reaction(reactants=\"A\", products=\"B\", \n", " forward_rate=3., reverse_rate=2.)\n", "\n", "dynamics.describe_reactions()" ] }, { "cell_type": "code", "execution_count": 6, "id": "9fc3948d", "metadata": {}, "outputs": [], "source": [ "# Set the initial concentrations of all the chemicals\n", "dynamics.set_conc({\"A\": 80., \"B\": 10.})" ] }, { "cell_type": "markdown", "id": "987af2c5", "metadata": { "tags": [] }, "source": [ "## Run the reaction" ] }, { "cell_type": "code", "execution_count": 7, "id": "43735178-313b-48cf-a583-5181238feac3", "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", "47 total step(s) taken\n", "Number of step re-do's because of elective soft aborts: 3\n", "Norm usage: {'norm_A': 26, 'norm_B': 22, 'norm_C': 22, 'norm_D': 22}\n" ] } ], "source": [ "dynamics.single_compartment_react(initial_step=0.1, target_end_time=1.) # Using defaults for all other parameters" ] }, { "cell_type": "code", "execution_count": 8, "id": "2d5df59c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
\n", "\n", "\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
SYSTEM TIMEABcaption
00.00000080.00000010.000000Initialized state
10.00640078.59200011.408000
20.00960077.91052812.089472
30.01344077.10584612.894154
40.01804876.15876713.841233
50.02357875.04845814.951542
60.02910773.96884616.031154
70.03463772.91908317.080917
80.04016671.89834418.101656
90.04569670.90582719.094173
100.05233269.74773520.252265
110.05896768.62806721.371933
120.06560367.54554622.454454
130.07223866.49894023.501060
140.07887465.48705824.512942
150.08550964.50874925.491251
160.09347263.37372626.626274
170.10143462.28389327.716107
180.10939761.23744928.762551
190.11736060.23266829.767332
200.12532259.26788930.732111
210.13487758.15624931.843751
220.14443357.09771732.902283
230.15398856.08975833.910242
240.16354355.12995534.870045
250.17500954.03321835.966782
260.18647552.99935737.000643
270.19794152.02476937.975231
280.21170150.92231239.077688
290.22546049.89570040.104300
300.23922048.93971741.060283
310.25573147.87145942.128541
320.27224246.89139343.108607
330.29205645.81240744.187593
340.31186944.84031445.159686
350.33564643.78936546.210635
360.35942242.86335547.136645
370.38795341.88424548.115755
380.42219140.87692749.123073
390.45642940.04205049.957950
400.49751439.21170450.788296
410.54681738.41997951.580021
420.60598037.70411352.295887
430.67697537.09919152.900809
440.76217036.63096553.369035
450.86440436.30843653.691564
460.98708436.11924153.880759
471.13430036.03147053.968530
\n", "
" ], "text/plain": [ " SYSTEM TIME A B caption\n", "0 0.000000 80.000000 10.000000 Initialized state\n", "1 0.006400 78.592000 11.408000 \n", "2 0.009600 77.910528 12.089472 \n", "3 0.013440 77.105846 12.894154 \n", "4 0.018048 76.158767 13.841233 \n", "5 0.023578 75.048458 14.951542 \n", "6 0.029107 73.968846 16.031154 \n", "7 0.034637 72.919083 17.080917 \n", "8 0.040166 71.898344 18.101656 \n", "9 0.045696 70.905827 19.094173 \n", "10 0.052332 69.747735 20.252265 \n", "11 0.058967 68.628067 21.371933 \n", "12 0.065603 67.545546 22.454454 \n", "13 0.072238 66.498940 23.501060 \n", "14 0.078874 65.487058 24.512942 \n", "15 0.085509 64.508749 25.491251 \n", "16 0.093472 63.373726 26.626274 \n", "17 0.101434 62.283893 27.716107 \n", "18 0.109397 61.237449 28.762551 \n", "19 0.117360 60.232668 29.767332 \n", "20 0.125322 59.267889 30.732111 \n", "21 0.134877 58.156249 31.843751 \n", "22 0.144433 57.097717 32.902283 \n", "23 0.153988 56.089758 33.910242 \n", "24 0.163543 55.129955 34.870045 \n", "25 0.175009 54.033218 35.966782 \n", "26 0.186475 52.999357 37.000643 \n", "27 0.197941 52.024769 37.975231 \n", "28 0.211701 50.922312 39.077688 \n", "29 0.225460 49.895700 40.104300 \n", "30 0.239220 48.939717 41.060283 \n", "31 0.255731 47.871459 42.128541 \n", "32 0.272242 46.891393 43.108607 \n", "33 0.292056 45.812407 44.187593 \n", "34 0.311869 44.840314 45.159686 \n", "35 0.335646 43.789365 46.210635 \n", "36 0.359422 42.863355 47.136645 \n", "37 0.387953 41.884245 48.115755 \n", "38 0.422191 40.876927 49.123073 \n", "39 0.456429 40.042050 49.957950 \n", "40 0.497514 39.211704 50.788296 \n", "41 0.546817 38.419979 51.580021 \n", "42 0.605980 37.704113 52.295887 \n", "43 0.676975 37.099191 52.900809 \n", "44 0.762170 36.630965 53.369035 \n", "45 0.864404 36.308436 53.691564 \n", "46 0.987084 36.119241 53.880759 \n", "47 1.134300 36.031470 53.968530 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.get_history() # The system's history, saved during the run of single_compartment_react()" ] }, { "cell_type": "markdown", "id": "03866901", "metadata": { "tags": [] }, "source": [ "## Plots changes of concentration with time \n", "Notice that adaptive variable time steps were automatically taken" ] }, { "cell_type": "code", "execution_count": 9, "id": "6b033cc7-078f-4b94-a466-1aa91e2fca4d", "metadata": {}, "outputs": [ { "data": { "text/html": [ " \n", " " ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Chemical=A
SYSTEM TIME=%{x}
Concentration=%{y}", "legendgroup": "A", "line": { "color": "blue", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "A", "orientation": "v", "showlegend": true, "type": "scatter", "x": [ 0, 0.006400000000000002, 0.009600000000000003, 0.013440000000000004, 0.018048000000000005, 0.023577600000000004, 0.029107200000000007, 0.03463680000000001, 0.04016640000000001, 0.045696000000000014, 0.05233152000000001, 0.05896704000000001, 0.06560256000000002, 0.07223808000000002, 0.07887360000000003, 0.08550912000000004, 0.09347174400000004, 0.10143436800000004, 0.10939699200000004, 0.11735961600000004, 0.12532224000000003, 0.13487738880000003, 0.14443253760000002, 0.15398768640000002, 0.16354283520000001, 0.17500901376000003, 0.18647519232000004, 0.19794137088000005, 0.21170078515200005, 0.22546019942400006, 0.23921961369600006, 0.25573091082240007, 0.27224220794880005, 0.29205576450048004, 0.31186932105216003, 0.335645588914176, 0.359421856776192, 0.38795337821061116, 0.42219120393191417, 0.4564290296532172, 0.4975144205187808, 0.5468168895574572, 0.6059798524038689, 0.6769754078195629, 0.7621700743183957, 0.8644036741169949, 0.9870839938753141, 1.1343003775852971 ], "xaxis": "x", "y": [ 80, 78.592, 77.910528, 77.1058458624, 76.15876717373031, 75.04845757891101, 73.96884582376929, 72.91908317443371, 71.89834436282696, 70.90582693788352, 69.7477353740692, 68.62806650892247, 67.54554556951605, 66.49894007682887, 65.48705844253587, 64.50874861235279, 63.373726382799354, 62.2838929294738, 61.237449146205506, 60.23266755485373, 59.26788945357223, 58.15624872361806, 57.09771745659816, 56.0897583084074, 55.12995515844305, 54.033217749985546, 52.999357276322066, 52.02476894664434, 50.92231177389454, 49.89570042592975, 48.93971693212988, 47.871459377140354, 46.89139341164059, 45.81240721519991, 44.84031378886753, 43.78936544572559, 42.863355249162076, 41.88424541214457, 40.87692656753266, 40.042049758158775, 39.21170378709872, 38.41997915447455, 37.704113470448206, 37.099191058819024, 36.630964980446095, 36.30843587395681, 36.11924081574702, 36.031469807322495 ], "yaxis": "y" }, { "hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
Concentration=%{y}", "legendgroup": "B", "line": { "color": "green", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "B", "orientation": "v", "showlegend": true, "type": "scatter", "x": [ 0, 0.006400000000000002, 0.009600000000000003, 0.013440000000000004, 0.018048000000000005, 0.023577600000000004, 0.029107200000000007, 0.03463680000000001, 0.04016640000000001, 0.045696000000000014, 0.05233152000000001, 0.05896704000000001, 0.06560256000000002, 0.07223808000000002, 0.07887360000000003, 0.08550912000000004, 0.09347174400000004, 0.10143436800000004, 0.10939699200000004, 0.11735961600000004, 0.12532224000000003, 0.13487738880000003, 0.14443253760000002, 0.15398768640000002, 0.16354283520000001, 0.17500901376000003, 0.18647519232000004, 0.19794137088000005, 0.21170078515200005, 0.22546019942400006, 0.23921961369600006, 0.25573091082240007, 0.27224220794880005, 0.29205576450048004, 0.31186932105216003, 0.335645588914176, 0.359421856776192, 0.38795337821061116, 0.42219120393191417, 0.4564290296532172, 0.4975144205187808, 0.5468168895574572, 0.6059798524038689, 0.6769754078195629, 0.7621700743183957, 0.8644036741169949, 0.9870839938753141, 1.1343003775852971 ], "xaxis": "x", "y": [ 10, 11.408000000000001, 12.089472, 12.894154137600001, 13.841232826269698, 14.951542421088993, 16.031154176230725, 17.080916825566298, 18.101655637173042, 19.094173062116482, 20.252264625930806, 21.371933491077524, 22.45445443048395, 23.501059923171127, 24.512941557464124, 25.491251387647203, 26.62627361720064, 27.716107070526196, 28.762550853794487, 29.767332445146263, 30.732110546427762, 31.84375127638193, 32.90228254340183, 33.910241691592596, 34.87004484155694, 35.96678225001445, 37.00064272367793, 37.97523105335565, 39.07768822610545, 40.10429957407024, 41.06028306787011, 42.12854062285964, 43.1086065883594, 44.18759278480008, 45.15968621113246, 46.2106345542744, 47.13664475083792, 48.11575458785542, 49.123073432467336, 49.95795024184122, 50.78829621290127, 51.580020845525446, 52.29588652955179, 52.90080894118097, 53.3690350195539, 53.69156412604318, 53.88075918425297, 53.9685301926775 ], "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": 0.006400000000000002, "x1": 0.006400000000000002, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.009600000000000003, "x1": 0.009600000000000003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.013440000000000004, "x1": 0.013440000000000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.018048000000000005, "x1": 0.018048000000000005, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.023577600000000004, "x1": 0.023577600000000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.029107200000000007, "x1": 0.029107200000000007, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.03463680000000001, "x1": 0.03463680000000001, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.04016640000000001, "x1": 0.04016640000000001, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.045696000000000014, "x1": 0.045696000000000014, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.05233152000000001, "x1": 0.05233152000000001, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.05896704000000001, "x1": 0.05896704000000001, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.06560256000000002, "x1": 0.06560256000000002, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.07223808000000002, "x1": 0.07223808000000002, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.07887360000000003, "x1": 0.07887360000000003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.08550912000000004, "x1": 0.08550912000000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.09347174400000004, "x1": 0.09347174400000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.10143436800000004, "x1": 0.10143436800000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.10939699200000004, "x1": 0.10939699200000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.11735961600000004, "x1": 0.11735961600000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.12532224000000003, "x1": 0.12532224000000003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.13487738880000003, "x1": 0.13487738880000003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.14443253760000002, "x1": 0.14443253760000002, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.15398768640000002, "x1": 0.15398768640000002, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.16354283520000001, "x1": 0.16354283520000001, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.17500901376000003, "x1": 0.17500901376000003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.18647519232000004, "x1": 0.18647519232000004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.19794137088000005, "x1": 0.19794137088000005, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.21170078515200005, "x1": 0.21170078515200005, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.22546019942400006, "x1": 0.22546019942400006, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.23921961369600006, "x1": 0.23921961369600006, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.25573091082240007, "x1": 0.25573091082240007, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.27224220794880005, "x1": 0.27224220794880005, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.29205576450048004, "x1": 0.29205576450048004, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.31186932105216003, "x1": 0.31186932105216003, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.335645588914176, "x1": 0.335645588914176, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.359421856776192, "x1": 0.359421856776192, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.38795337821061116, "x1": 0.38795337821061116, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.42219120393191417, "x1": 0.42219120393191417, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.4564290296532172, "x1": 0.4564290296532172, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.4975144205187808, "x1": 0.4975144205187808, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.5468168895574572, "x1": 0.5468168895574572, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.6059798524038689, "x1": 0.6059798524038689, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.6769754078195629, "x1": 0.6769754078195629, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.7621700743183957, "x1": 0.7621700743183957, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.8644036741169949, "x1": 0.8644036741169949, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 0.9870839938753141, "x1": 0.9870839938753141, "xref": "x", "y0": 0, "y1": 1, "yref": "y domain" }, { "line": { "color": "gray", "dash": "dot", "width": 1 }, "type": "line", "x0": 1.1343003775852971, "x1": 1.1343003775852971, "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": "Reaction `A <-> B` . Changes in concentrations with time (time steps shown in dashed lines)" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ -0.001166975697104215, 1.1354673532824013 ], "title": { "text": "SYSTEM TIME" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 6.111111111111111, 83.88888888888889 ], "title": { "text": "Concentration" }, "type": "linear" } } }, "image/png": "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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dynamics.plot_history(show_intervals=True)" ] }, { "cell_type": "code", "execution_count": 10, "id": "23c4b3ba", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0: A <-> B\n", "Final concentrations: [A] = 36.03 ; [B] = 53.97\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 1.49782\n", " Formula used: [B] / [A]\n", "2. Ratio of forward/reverse reaction rates: 1.5\n", "Discrepancy between the two values: 0.1456 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Verify that the reaction has reached equilibrium\n", "dynamics.is_in_equilibrium()" ] }, { "cell_type": "code", "execution_count": null, "id": "7f59733f", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.10" } }, "nbformat": 4, "nbformat_minor": 5 }