{ "cells": [ { "cell_type": "markdown", "id": "3bbe8002-bdf3-490c-bde0-80dd3713a3d0", "metadata": {}, "source": [ "## 2 COUPLED reactions of different speeds, forming a \"cascade\": \n", "### `A <-> B` (fast) and `B <-> C` (slow)\n", "All 1st order. Taken to equilibrium. Both reactions are mostly forward.\n", "The concentration of the intermediate product B manifests 1 oscillation (transient \"overshoot\")\n", "\n", "(Adaptive variable time resolution is used, with extensive diagnostics.)\n", "\n", "LAST REVISED: June 4, 2023" ] }, { "cell_type": "markdown", "id": "c8763f25-9fab-4b36-89cc-388321a16be0", "metadata": {}, "source": [ "## Bathtub analogy:\n", "A is initially full, while B and C are empty. \n", "Tubs are progressively lower (reactions are mostly forward.) \n", "A BIG pipe connects A and B: fast kinetics. A small pipe connects B and C: slow kinetics. \n", "\n", "INTUITION: B, unable to quickly drain into C while at the same time being blasted by a hefty inflow from A, \n", "will experience a transient surge, in excess of its final equilibrium level.\n", "\n", "* [Compare with the final reaction plot (the red line is B)](#cascade_1_plot)" ] }, { "cell_type": "markdown", "id": "b11f68d6-d3bc-4908-93c0-eaee580acbc1", "metadata": {}, "source": [ "![2 Coupled Reactions](../../docs/2_coupled_reactions.png)" ] }, { "cell_type": "code", "execution_count": 1, "id": "13e55c1d-609f-4bf0-a004-6c45bcfcbc99", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Added 'D:\\Docs\\- MY CODE\\BioSimulations\\life123-Win7' to sys.path\n" ] } ], "source": [ "import set_path # Importing this module will add the project's home directory to sys.path" ] }, { "cell_type": "code", "execution_count": 2, "id": "bdad128a-9214-46f5-aeb9-a7b77c81aa3e", "metadata": { "tags": [] }, "outputs": [], "source": [ "from experiments.get_notebook_info import get_notebook_basename\n", "\n", "from src.modules.reactions.reaction_data import ChemData\n", "from src.modules.reactions.reaction_dynamics import ReactionDynamics\n", "\n", "import numpy as np\n", "import plotly.express as px\n", "from src.modules.visualization.graphic_log import GraphicLog" ] }, { "cell_type": "code", "execution_count": 3, "id": "83c3cc5f-de21-4f66-9988-2806fbf0666d", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> Output will be LOGGED into the file 'cascade_1.log.htm'\n" ] } ], "source": [ "# Initialize the HTML logging (for the graphics)\n", "log_file = get_notebook_basename() + \".log.htm\" # Use the notebook base filename for the log file\n", "\n", "# Set up the use of some specified graphic (Vue) components\n", "GraphicLog.config(filename=log_file,\n", " components=[\"vue_cytoscape_1\"],\n", " extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")" ] }, { "cell_type": "markdown", "id": "9329208b-070f-4902-8f37-0f11ddf75ed6", "metadata": {}, "source": [ "# Initialize the System\n", "Specify the chemicals and the reactions" ] }, { "cell_type": "code", "execution_count": 4, "id": "72b4245c-de4e-480d-a501-3495b7ed8bc4", "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 2\n" ] } ], "source": [ "# Specify the chemicals\n", "chem_data = ChemData(names=[\"A\", \"B\", \"C\"])\n", "\n", "# Reaction A <-> B (fast)\n", "chem_data.add_reaction(reactants=[\"A\"], products=[\"B\"],\n", " forward_rate=64., reverse_rate=8.) \n", "\n", "# Reaction B <-> C (slow)\n", "chem_data.add_reaction(reactants=[\"B\"], products=[\"C\"],\n", " forward_rate=12., reverse_rate=2.) \n", "\n", "print(\"Number of reactions: \", chem_data.number_of_reactions())" ] }, { "cell_type": "code", "execution_count": 5, "id": "00ea560d-9a49-4041-b119-6de11bfcc7af", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 2 (at temp. 25 C)\n", "0: A <-> B (kF = 64 / kR = 8 / Delta_G = -5,154.85 / K = 8) | 1st order in all reactants & products\n", "1: B <-> C (kF = 12 / kR = 2 / Delta_G = -4,441.69 / K = 6) | 1st order in all reactants & products\n" ] } ], "source": [ "chem_data.describe_reactions()" ] }, { "cell_type": "code", "execution_count": 6, "id": "cb582868-431c-4022-aa0e-a2f554f80d6c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[GRAPHIC ELEMENT SENT TO LOG FILE `cascade_1.log.htm`]\n" ] } ], "source": [ "# Send a plot of the network of reactions to the HTML log file\n", "graph_data = chem_data.prepare_graph_network()\n", "GraphicLog.export_plot(graph_data, \"vue_cytoscape_1\")" ] }, { "cell_type": "markdown", "id": "98a9fbe5-2090-4d38-9c5f-94fbf7c3eae2", "metadata": {}, "source": [ "# Start the simulation" ] }, { "cell_type": "code", "execution_count": 7, "id": "c2f4a554-807b-49f9-8ca2-8d929fe6eeef", "metadata": {}, "outputs": [], "source": [ "dynamics = ReactionDynamics(reaction_data=chem_data)" ] }, { "cell_type": "markdown", "id": "b0345d36-5702-4b40-9221-a765dfcb0bac", "metadata": {}, "source": [ "### Set the initial concentrations of all the chemicals, in their index order" ] }, { "cell_type": "code", "execution_count": 8, "id": "ae304704-c8d9-4cef-9e0b-2587bb3909ef", "metadata": {}, "outputs": [], "source": [ "dynamics.set_conc([50., 0, 0.], snapshot=True)" ] }, { "cell_type": "code", "execution_count": 9, "id": "a605dacf-2c67-403e-9aa9-5be25fc9f481", "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" ] } ], "source": [ "dynamics.describe_state()" ] }, { "cell_type": "code", "execution_count": 10, "id": "0ff2c242-a15b-456d-ad56-0ba1041c0b4c", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SYSTEM TIMEABCcaption
00.050.00.00.0Initial state
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" ], "text/plain": [ " SYSTEM TIME A B C caption\n", "0 0.0 50.0 0.0 0.0 Initial state" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.get_history()" ] }, { "cell_type": "markdown", "id": "fc516ca2-e62d-4784-b826-5372ff7f4c75", "metadata": { "tags": [] }, "source": [ "## Run the reaction" ] }, { "cell_type": "code", "execution_count": 11, "id": "2502cd11-0df9-4303-8895-98401a1df7b8", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "*** CAUTION: negative concentration in chemical `A` in step starting at t=0. It will be AUTOMATICALLY CORRECTED with a reduction in time step size, as follows:\n", " INFO: the tentative time step (0.02) leads to a NEGATIVE concentration of `A` from reaction A <-> B (rxn # 0): \n", " Baseline value: 50 ; delta conc: -64\n", " -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.333 (set to 0.00666) [Step started at t=0, and will rewind there]\n", "* INFO: the tentative time step (0.00666) leads to a least one norm value > its ABORT threshold:\n", " -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.5 (set to 0.00333) [Step started at t=0, and will rewind there]\n", "* INFO: the tentative time step (0.00333) leads to a least one norm value > its ABORT threshold:\n", " -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.5 (set to 0.001665) [Step started at t=0, and will rewind there]\n", "* INFO: the tentative time step (0.001665) leads to a least one norm value > its ABORT threshold:\n", " -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.5 (set to 0.0008325) [Step started at t=0, and will rewind there]\n", "* INFO: the tentative time step (0.0008325) leads to a least one norm value > its ABORT threshold:\n", " -> will backtrack, and re-do step with a SMALLER delta time, multiplied by 0.5 (set to 0.00041625) [Step started at t=0, and will rewind there]\n", "Some steps were backtracked and re-done, to prevent negative concentrations or excessively large concentration changes\n", "56 total step(s) taken\n" ] } ], "source": [ "dynamics.set_diagnostics() # To save diagnostic information about the call to single_compartment_react()\n", "\n", "# These settings can be tweaked to make the time resolution finer or coarser\n", "dynamics.set_thresholds(norm=\"norm_A\", low=0.5, high=1.0, abort=1.44)\n", "dynamics.set_thresholds(norm=\"norm_B\", low=0.2, high=0.5, abort=1.5)\n", "dynamics.set_step_factors(upshift=1.4, downshift=0.5, abort=0.5)\n", "dynamics.set_error_step_factor(0.333)\n", "\n", "dynamics.single_compartment_react(initial_step=0.02, reaction_duration=0.4,\n", " snapshots={\"initial_caption\": \"1st reaction step\",\n", " \"final_caption\": \"last reaction step\"},\n", " variable_steps=True, explain_variable_steps=False)" ] }, { "cell_type": "markdown", "id": "199b6238-f6ed-44a8-8130-a003444d7658", "metadata": {}, "source": [ "### Plots of changes of concentration with time" ] }, { "cell_type": "code", "execution_count": 12, "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
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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dynamics.plot_curves(title=\"Coupled reactions A <-> B and B <-> C\",\n", " colors=['blue', 'red', 'green'])" ] }, { "cell_type": "code", "execution_count": 13, "id": "844183a6-e61f-4b7a-8aa6-013f4530a74b", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Min abs distance found at data row: 26\n" ] }, { "data": { "text/plain": [ "(0.011856795047959055, 24.04728216157861)" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.curve_intersection(\"A\", \"B\", t_start=0, t_end=0.05)" ] }, { "cell_type": "code", "execution_count": 14, "id": "025c387b-5bd2-4666-a140-9c66630da072", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Min abs distance found at data row: 35\n" ] }, { "data": { "text/plain": [ "(0.03191446684059964, 8.846824660878902)" ] }, "execution_count": 14, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.curve_intersection(\"A\", \"C\", t_start=0, t_end=0.05)" ] }, { "cell_type": "code", "execution_count": 15, "id": "86f3a798-4a5b-4016-b4d1-121f9fb48506", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Min abs distance found at data row: 43\n" ] }, { "data": { "text/plain": [ "(0.07775497645748508, 23.275670893111585)" ] }, "execution_count": 15, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.curve_intersection(\"B\", \"C\", t_start=0.05, t_end=0.1)" ] }, { "cell_type": "code", "execution_count": 16, "id": "80fbaee3-bd6f-4197-9270-23374d46a4a7", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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SYSTEM TIMEABCcaption
00.00000050.0000000.0000000.000000Initial state
10.00041648.6680001.3320000.0000001st reaction step
20.00099946.8590883.1315970.009315
30.00129045.9925603.9871820.020259
40.00143645.5683724.4044040.027224
50.00158245.1486264.8164590.034916
60.00172744.7332745.2234010.043326
70.00187344.3222685.6252870.052445
80.00201943.9155646.0221720.062264
90.00222343.3521346.5708880.076978
100.00242742.7969547.1100160.093029
110.00263142.2499017.6397050.110394
120.00291641.4952358.3682570.136509
130.00320240.7560249.0788710.165105
140.00348740.0319469.7719340.196120
150.00388739.03897810.7181810.242841
160.00428738.07444211.6314940.294064
170.00468737.13750412.5128680.349628
180.00524635.86329813.7034280.433274
190.00580634.64006314.8351150.524822
200.00636633.46571015.9104210.623868
210.00714931.88724717.3402640.772489
220.00793330.39690118.6687790.934320
230.00871628.98961919.9019921.108389
240.00981327.12904521.5030181.367938
250.01091025.41314322.9388651.647992
260.01200723.83030724.2233611.946332
270.01354321.78569125.8275442.386764
280.01507919.96174527.1828482.855407
290.01661418.33372128.3186923.347587
300.01876416.29804429.6381284.063828
310.02091414.56517730.6237924.811031
320.02306513.08771031.3318385.580452
330.02607511.32093132.0004846.678584
340.0290859.91061232.2951307.794258
350.0332998.32646432.3118399.361697
360.0375137.17012531.91310410.916771
370.0434125.96904330.98366113.047296
380.0493125.17760029.73551915.086881
390.0552124.62608228.35988217.014036
400.0611124.21788026.96105918.821061
410.0670113.89778625.59448120.507733
420.0729113.63405524.28819222.077754
430.0811713.31792722.56169824.120374
440.0894303.05482820.98704125.958131
450.0976902.82675919.56378427.609457
460.1059492.62520618.28235629.092438
470.1175132.37365116.66984630.956503
480.1290762.15909315.28720432.553704
490.1406401.97541614.10247533.922109
500.1568291.75513812.68144335.563419
510.1730171.57904811.54542336.875529
520.1956821.38196610.27399238.344042
530.2274121.1835308.99381439.822657
540.2718341.0149317.90613641.078933
550.3340250.9088037.22145941.869738
560.4210920.8746977.00150042.123803last reaction step
\n", "
" ], "text/plain": [ " SYSTEM TIME A B C caption\n", "0 0.000000 50.000000 0.000000 0.000000 Initial state\n", "1 0.000416 48.668000 1.332000 0.000000 1st reaction step\n", "2 0.000999 46.859088 3.131597 0.009315 \n", "3 0.001290 45.992560 3.987182 0.020259 \n", "4 0.001436 45.568372 4.404404 0.027224 \n", "5 0.001582 45.148626 4.816459 0.034916 \n", "6 0.001727 44.733274 5.223401 0.043326 \n", "7 0.001873 44.322268 5.625287 0.052445 \n", "8 0.002019 43.915564 6.022172 0.062264 \n", "9 0.002223 43.352134 6.570888 0.076978 \n", "10 0.002427 42.796954 7.110016 0.093029 \n", "11 0.002631 42.249901 7.639705 0.110394 \n", "12 0.002916 41.495235 8.368257 0.136509 \n", "13 0.003202 40.756024 9.078871 0.165105 \n", "14 0.003487 40.031946 9.771934 0.196120 \n", "15 0.003887 39.038978 10.718181 0.242841 \n", "16 0.004287 38.074442 11.631494 0.294064 \n", "17 0.004687 37.137504 12.512868 0.349628 \n", "18 0.005246 35.863298 13.703428 0.433274 \n", "19 0.005806 34.640063 14.835115 0.524822 \n", "20 0.006366 33.465710 15.910421 0.623868 \n", "21 0.007149 31.887247 17.340264 0.772489 \n", "22 0.007933 30.396901 18.668779 0.934320 \n", "23 0.008716 28.989619 19.901992 1.108389 \n", "24 0.009813 27.129045 21.503018 1.367938 \n", "25 0.010910 25.413143 22.938865 1.647992 \n", "26 0.012007 23.830307 24.223361 1.946332 \n", "27 0.013543 21.785691 25.827544 2.386764 \n", "28 0.015079 19.961745 27.182848 2.855407 \n", "29 0.016614 18.333721 28.318692 3.347587 \n", "30 0.018764 16.298044 29.638128 4.063828 \n", "31 0.020914 14.565177 30.623792 4.811031 \n", "32 0.023065 13.087710 31.331838 5.580452 \n", "33 0.026075 11.320931 32.000484 6.678584 \n", "34 0.029085 9.910612 32.295130 7.794258 \n", "35 0.033299 8.326464 32.311839 9.361697 \n", "36 0.037513 7.170125 31.913104 10.916771 \n", "37 0.043412 5.969043 30.983661 13.047296 \n", "38 0.049312 5.177600 29.735519 15.086881 \n", "39 0.055212 4.626082 28.359882 17.014036 \n", "40 0.061112 4.217880 26.961059 18.821061 \n", "41 0.067011 3.897786 25.594481 20.507733 \n", "42 0.072911 3.634055 24.288192 22.077754 \n", "43 0.081171 3.317927 22.561698 24.120374 \n", "44 0.089430 3.054828 20.987041 25.958131 \n", "45 0.097690 2.826759 19.563784 27.609457 \n", "46 0.105949 2.625206 18.282356 29.092438 \n", "47 0.117513 2.373651 16.669846 30.956503 \n", "48 0.129076 2.159093 15.287204 32.553704 \n", "49 0.140640 1.975416 14.102475 33.922109 \n", "50 0.156829 1.755138 12.681443 35.563419 \n", "51 0.173017 1.579048 11.545423 36.875529 \n", "52 0.195682 1.381966 10.273992 38.344042 \n", "53 0.227412 1.183530 8.993814 39.822657 \n", "54 0.271834 1.014931 7.906136 41.078933 \n", "55 0.334025 0.908803 7.221459 41.869738 \n", "56 0.421092 0.874697 7.001500 42.123803 last reaction step" ] }, "execution_count": 16, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dynamics.get_history()" ] }, { "cell_type": "code", "execution_count": 17, "id": "144d0388-a632-4165-a9c5-50bc7943fc88", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "From time 0 to 0.0004163, in 1 step of 0.000416\n", "From time 0.0004163 to 0.000999, in 1 step of 0.000583\n", "From time 0.000999 to 0.00129, in 1 step of 0.000291\n", "From time 0.00129 to 0.002019, in 5 steps of 0.000146\n", "From time 0.002019 to 0.002631, in 3 steps of 0.000204\n", "From time 0.002631 to 0.003487, in 3 steps of 0.000286\n", "From time 0.003487 to 0.004687, in 3 steps of 0.0004\n", "From time 0.004687 to 0.006366, in 3 steps of 0.00056\n", "From time 0.006366 to 0.008716, in 3 steps of 0.000784\n", "From time 0.008716 to 0.01201, in 3 steps of 0.0011\n", "From time 0.01201 to 0.01661, in 3 steps of 0.00154\n", "From time 0.01661 to 0.02306, in 3 steps of 0.00215\n", "From time 0.02306 to 0.02908, in 2 steps of 0.00301\n", "From time 0.02908 to 0.03751, in 2 steps of 0.00421\n", "From time 0.03751 to 0.07291, in 6 steps of 0.0059\n", "From time 0.07291 to 0.1059, in 4 steps of 0.00826\n", "From time 0.1059 to 0.1406, in 3 steps of 0.0116\n", "From time 0.1406 to 0.173, in 2 steps of 0.0162\n", "From time 0.173 to 0.1957, in 1 step of 0.0227\n", "From time 0.1957 to 0.2274, in 1 step of 0.0317\n", "From time 0.2274 to 0.2718, in 1 step of 0.0444\n", "From time 0.2718 to 0.334, in 1 step of 0.0622\n", "From time 0.334 to 0.4211, in 1 step of 0.0871\n", "(56 steps total)\n" ] } ], "source": [ "dynamics.explain_time_advance()" ] }, { "cell_type": "markdown", "id": "c02a8f55-a671-4771-86c9-fc4d1b126bf8", "metadata": {}, "source": [ "### Check the final equilibrium" ] }, { "cell_type": "code", "execution_count": 18, "id": "b139f5e4-625f-4a5e-8f57-8f00244dced4", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0: A <-> B\n", "Final concentrations: [B] = 7.001 ; [A] = 0.8747\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 8.00449\n", " Formula used: [B] / [A]\n", "2. Ratio of forward/reverse reaction rates: 8.0\n", "Discrepancy between the two values: 0.05606 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n", "1: B <-> C\n", "Final concentrations: [C] = 42.12 ; [B] = 7.001\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 6.0164\n", " Formula used: [C] / [B]\n", "2. Ratio of forward/reverse reaction rates: 6.0\n", "Discrepancy between the two values: 0.2733 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 18, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Verify that all the reactions have reached equilibrium\n", "dynamics.is_in_equilibrium()" ] }, { "cell_type": "code", "execution_count": null, "id": "4d9b4808-b2ec-4b90-a604-f7fa69af39b8", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "5c3f8b4f-3a75-4a21-8579-13550bcebb3c", "metadata": {}, "source": [ "# EVERYTHING BELOW IS FOR DIAGNOSTIC INSIGHT\n", "\n", "### Perform some verification" ] }, { "cell_type": "markdown", "id": "07dd5aa4-9e71-40c1-9f15-a16a9333ed10", "metadata": {}, "source": [ "### Take a peek at the diagnostic data saved during the earlier reaction simulation" ] }, { "cell_type": "code", "execution_count": 19, "id": "5ad64dc5-ba89-4f09-b7db-da40de1df4ed", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reaction: A <-> B\n" ] }, { "data": { "text/html": [ "
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START_TIMEDelta ADelta BDelta Ctime_stepcaption
00.000000NaNNaNNaN0.020000aborted: neg. conc. in `A`
10.000000-21.31200021.3120000.00.006660aborted: excessive norm value(s)
20.000000-10.65600010.6560000.00.003330aborted: excessive norm value(s)
30.000000-5.3280005.3280000.00.001665aborted: excessive norm value(s)
40.000000-2.6640002.6640000.00.000833aborted: excessive norm value(s)
.....................
560.173017-0.1970820.1970820.00.022664
570.195682-0.1984370.1984370.00.031730
580.227412-0.1685990.1685990.00.044422
590.271834-0.1061280.1061280.00.062191
600.334025-0.0341060.0341060.00.087067
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61 rows × 6 columns

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" ], "text/plain": [ " START_TIME Delta A Delta B Delta C time_step \\\n", "0 0.000000 NaN NaN NaN 0.020000 \n", "1 0.000000 -21.312000 21.312000 0.0 0.006660 \n", "2 0.000000 -10.656000 10.656000 0.0 0.003330 \n", "3 0.000000 -5.328000 5.328000 0.0 0.001665 \n", "4 0.000000 -2.664000 2.664000 0.0 0.000833 \n", ".. ... ... ... ... ... \n", "56 0.173017 -0.197082 0.197082 0.0 0.022664 \n", "57 0.195682 -0.198437 0.198437 0.0 0.031730 \n", "58 0.227412 -0.168599 0.168599 0.0 0.044422 \n", "59 0.271834 -0.106128 0.106128 0.0 0.062191 \n", "60 0.334025 -0.034106 0.034106 0.0 0.087067 \n", "\n", " caption \n", "0 aborted: neg. conc. in `A` \n", "1 aborted: excessive norm value(s) \n", "2 aborted: excessive norm value(s) \n", "3 aborted: excessive norm value(s) \n", "4 aborted: excessive norm value(s) \n", ".. ... \n", "56 \n", "57 \n", "58 \n", "59 \n", "60 \n", "\n", "[61 rows x 6 columns]" ] }, "execution_count": 19, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Concentration increments due to reaction 0 (A <-> B)\n", "# Note that [C] is not affected\n", "dynamics.get_diagnostic_rxn_data(rxn_index=0)" ] }, { "cell_type": "code", "execution_count": 20, "id": "71f62382-f07a-416d-876f-97832c1f79e5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Reaction: B <-> C\n" ] }, { "data": { "text/html": [ "
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START_TIMEDelta ADelta BDelta Ctime_stepcaption
00.0000000.00.0000000.0000000.006660aborted: excessive norm value(s)
10.0000000.00.0000000.0000000.003330aborted: excessive norm value(s)
20.0000000.00.0000000.0000000.001665aborted: excessive norm value(s)
30.0000000.00.0000000.0000000.000833aborted: excessive norm value(s)
40.0000000.00.0000000.0000000.000416
50.0004160.0-0.0093150.0093150.000583
60.0009990.0-0.0109440.0109440.000291
70.0012900.0-0.0069650.0069650.000146
80.0014360.0-0.0076920.0076920.000146
90.0015820.0-0.0084100.0084100.000146
100.0017270.0-0.0091190.0091190.000146
110.0018730.0-0.0098190.0098190.000146
120.0020190.0-0.0147140.0147140.000204
130.0022230.0-0.0160510.0160510.000204
140.0024270.0-0.0173640.0173640.000204
150.0026310.0-0.0261150.0261150.000286
160.0029160.0-0.0285960.0285960.000286
170.0032020.0-0.0310150.0310150.000286
180.0034870.0-0.0467210.0467210.000400
190.0038870.0-0.0512230.0512230.000400
200.0042870.0-0.0555630.0555630.000400
210.0046870.0-0.0836460.0836460.000560
220.0052460.0-0.0915480.0915480.000560
230.0058060.0-0.0990460.0990460.000560
240.0063660.0-0.1486200.1486200.000784
250.0071490.0-0.1618310.1618310.000784
260.0079330.0-0.1740690.1740690.000784
270.0087160.0-0.2595480.2595480.001097
280.0098130.0-0.2800540.2800540.001097
290.0109100.0-0.2983400.2983400.001097
300.0120070.0-0.4404320.4404320.001536
310.0135430.0-0.4686430.4686430.001536
320.0150790.0-0.4921800.4921800.001536
330.0166140.0-0.7162410.7162410.002150
340.0187640.0-0.7472030.7472030.002150
350.0209140.0-0.7694210.7694210.002150
360.0230650.0-1.0981321.0981320.003010
370.0260750.0-1.1156731.1156730.003010
380.0290850.0-1.5674391.5674390.004214
390.0332990.0-1.5550741.5550740.004214
400.0375130.0-2.1305252.1305250.005900
410.0434120.0-2.0395852.0395850.005900
420.0493120.0-1.9271551.9271550.005900
430.0552120.0-1.8070251.8070250.005900
440.0611120.0-1.6866721.6866720.005900
450.0670110.0-1.5700211.5700210.005900
460.0729110.0-2.0426212.0426210.008260
470.0811710.0-1.8377571.8377570.008260
480.0894300.0-1.6513261.6513260.008260
490.0976900.0-1.4829811.4829810.008260
500.1059490.0-1.8640641.8640640.011563
510.1175130.0-1.5972011.5972010.011563
520.1290760.0-1.3684051.3684050.011563
530.1406400.0-1.6413101.6413100.016189
540.1568290.0-1.3121101.3121100.016189
550.1730170.0-1.4685131.4685130.022664
560.1956820.0-1.4786151.4786150.031730
570.2274120.0-1.2562761.2562760.044422
580.2718340.0-0.7908050.7908050.062191
590.3340250.0-0.2540650.2540650.087067
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" ], "text/plain": [ " START_TIME Delta A Delta B Delta C time_step \\\n", "0 0.000000 0.0 0.000000 0.000000 0.006660 \n", "1 0.000000 0.0 0.000000 0.000000 0.003330 \n", "2 0.000000 0.0 0.000000 0.000000 0.001665 \n", "3 0.000000 0.0 0.000000 0.000000 0.000833 \n", "4 0.000000 0.0 0.000000 0.000000 0.000416 \n", "5 0.000416 0.0 -0.009315 0.009315 0.000583 \n", "6 0.000999 0.0 -0.010944 0.010944 0.000291 \n", "7 0.001290 0.0 -0.006965 0.006965 0.000146 \n", "8 0.001436 0.0 -0.007692 0.007692 0.000146 \n", "9 0.001582 0.0 -0.008410 0.008410 0.000146 \n", "10 0.001727 0.0 -0.009119 0.009119 0.000146 \n", "11 0.001873 0.0 -0.009819 0.009819 0.000146 \n", "12 0.002019 0.0 -0.014714 0.014714 0.000204 \n", "13 0.002223 0.0 -0.016051 0.016051 0.000204 \n", "14 0.002427 0.0 -0.017364 0.017364 0.000204 \n", "15 0.002631 0.0 -0.026115 0.026115 0.000286 \n", "16 0.002916 0.0 -0.028596 0.028596 0.000286 \n", "17 0.003202 0.0 -0.031015 0.031015 0.000286 \n", "18 0.003487 0.0 -0.046721 0.046721 0.000400 \n", "19 0.003887 0.0 -0.051223 0.051223 0.000400 \n", "20 0.004287 0.0 -0.055563 0.055563 0.000400 \n", "21 0.004687 0.0 -0.083646 0.083646 0.000560 \n", "22 0.005246 0.0 -0.091548 0.091548 0.000560 \n", "23 0.005806 0.0 -0.099046 0.099046 0.000560 \n", "24 0.006366 0.0 -0.148620 0.148620 0.000784 \n", "25 0.007149 0.0 -0.161831 0.161831 0.000784 \n", "26 0.007933 0.0 -0.174069 0.174069 0.000784 \n", "27 0.008716 0.0 -0.259548 0.259548 0.001097 \n", "28 0.009813 0.0 -0.280054 0.280054 0.001097 \n", "29 0.010910 0.0 -0.298340 0.298340 0.001097 \n", "30 0.012007 0.0 -0.440432 0.440432 0.001536 \n", "31 0.013543 0.0 -0.468643 0.468643 0.001536 \n", "32 0.015079 0.0 -0.492180 0.492180 0.001536 \n", "33 0.016614 0.0 -0.716241 0.716241 0.002150 \n", "34 0.018764 0.0 -0.747203 0.747203 0.002150 \n", "35 0.020914 0.0 -0.769421 0.769421 0.002150 \n", "36 0.023065 0.0 -1.098132 1.098132 0.003010 \n", "37 0.026075 0.0 -1.115673 1.115673 0.003010 \n", "38 0.029085 0.0 -1.567439 1.567439 0.004214 \n", "39 0.033299 0.0 -1.555074 1.555074 0.004214 \n", "40 0.037513 0.0 -2.130525 2.130525 0.005900 \n", "41 0.043412 0.0 -2.039585 2.039585 0.005900 \n", "42 0.049312 0.0 -1.927155 1.927155 0.005900 \n", "43 0.055212 0.0 -1.807025 1.807025 0.005900 \n", "44 0.061112 0.0 -1.686672 1.686672 0.005900 \n", "45 0.067011 0.0 -1.570021 1.570021 0.005900 \n", "46 0.072911 0.0 -2.042621 2.042621 0.008260 \n", "47 0.081171 0.0 -1.837757 1.837757 0.008260 \n", "48 0.089430 0.0 -1.651326 1.651326 0.008260 \n", "49 0.097690 0.0 -1.482981 1.482981 0.008260 \n", "50 0.105949 0.0 -1.864064 1.864064 0.011563 \n", "51 0.117513 0.0 -1.597201 1.597201 0.011563 \n", "52 0.129076 0.0 -1.368405 1.368405 0.011563 \n", "53 0.140640 0.0 -1.641310 1.641310 0.016189 \n", "54 0.156829 0.0 -1.312110 1.312110 0.016189 \n", "55 0.173017 0.0 -1.468513 1.468513 0.022664 \n", "56 0.195682 0.0 -1.478615 1.478615 0.031730 \n", "57 0.227412 0.0 -1.256276 1.256276 0.044422 \n", "58 0.271834 0.0 -0.790805 0.790805 0.062191 \n", "59 0.334025 0.0 -0.254065 0.254065 0.087067 \n", "\n", " caption \n", "0 aborted: excessive norm value(s) \n", "1 aborted: excessive norm value(s) \n", "2 aborted: excessive norm value(s) \n", "3 aborted: excessive norm value(s) \n", "4 \n", "5 \n", "6 \n", "7 \n", "8 \n", "9 \n", "10 \n", "11 \n", "12 \n", "13 \n", "14 \n", "15 \n", "16 \n", "17 \n", "18 \n", "19 \n", "20 \n", "21 \n", "22 \n", "23 \n", "24 \n", "25 \n", "26 \n", "27 \n", "28 \n", "29 \n", "30 \n", "31 \n", "32 \n", "33 \n", "34 \n", "35 \n", "36 \n", "37 \n", "38 \n", "39 \n", "40 \n", "41 \n", "42 \n", "43 \n", "44 \n", "45 \n", "46 \n", "47 \n", "48 \n", "49 \n", "50 \n", "51 \n", "52 \n", "53 \n", "54 \n", "55 \n", "56 \n", "57 \n", "58 \n", "59 " ] }, "execution_count": 20, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Concentration increments due to reaction 1 (B <-> C)\n", "# Note that [A] is not affected. \n", "# Also notice that the 0-th row from the A <-> B reaction isn't seen here, because that step was aborted\n", "# early on, before even getting to THIS reaction\n", "dynamics.get_diagnostic_rxn_data(rxn_index=1)" ] }, { "cell_type": "code", "execution_count": null, "id": "520b3b44-7da9-49d3-9cfd-685607169f01", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "b4d987b6-fe56-408a-98f4-8dad3c14af1f", "metadata": {}, "source": [ "### Provide a detailed explanation of all the steps/substeps of the reactions, from the saved diagnostic data" ] }, { "cell_type": "code", "execution_count": null, "id": "46fdcb5b-ed5f-43a9-9829-533039666d0c", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "de51ec27-1d0f-4bfb-83f0-b1c79b436d75", "metadata": { "tags": [] }, "source": [ "# Re-run with very small constanst steps" ] }, { "cell_type": "markdown", "id": "ff9fffab-a1f5-4497-9d7b-c3db023d1bd2", "metadata": {}, "source": [ "We'll use constant steps of size 0.0005, which is 1/4 of the smallest steps (the \"substep\" size) previously used in the variable-step run" ] }, { "cell_type": "code", "execution_count": 21, "id": "93418d81-12fa-417d-9906-1dd24a40de48", "metadata": {}, "outputs": [], "source": [ "dynamics2 = ReactionDynamics(reaction_data=chem_data)" ] }, { "cell_type": "code", "execution_count": 22, "id": "ecf2029b-57a7-4db4-9b30-c854da91fb76", "metadata": { "tags": [] }, "outputs": [], "source": [ "dynamics2.set_conc([50., 0, 0.], snapshot=True)" ] }, { "cell_type": "code", "execution_count": 23, "id": "00777982-d633-4c12-8c92-2ece6bf00e5e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "800 total step(s) taken\n" ] } ], "source": [ "dynamics2.single_compartment_react(initial_step=0.0005, reaction_duration=0.4,\n", " snapshots={\"initial_caption\": \"1st reaction step\",\n", " \"final_caption\": \"last reaction step\"},\n", " ) " ] }, { "cell_type": "code", "execution_count": 24, "id": "78ed4dee-870a-4517-8bd0-58122c10e663", "metadata": {}, 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SYSTEM TIMEABCcaption
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10.000548.4000001.6000000.0000001st reaction step
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..................
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801 rows × 5 columns

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" ], "text/plain": [ " SYSTEM TIME A B C caption\n", "0 0.0000 50.000000 0.000000 0.000000 Initial state\n", "1 0.0005 48.400000 1.600000 0.000000 1st reaction step\n", "2 0.0010 46.857600 3.132800 0.009600 \n", "3 0.0015 45.370688 4.600925 0.028387 \n", "4 0.0020 43.937230 6.006806 0.055964 \n", ".. ... ... ... ... ...\n", "796 0.3980 0.925494 7.329151 41.745354 \n", "797 0.3985 0.925195 7.327221 41.747584 \n", "798 0.3990 0.924898 7.325303 41.749800 \n", "799 0.3995 0.924602 7.323396 41.752002 \n", "800 0.4000 0.924309 7.321501 41.754190 last reaction step\n", "\n", "[801 rows x 5 columns]" ] }, "execution_count": 28, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df2 = dynamics2.get_history()\n", "df2" ] }, { "cell_type": "markdown", "id": "45d5883d-c2c6-40a7-80b4-8a5976b8dfcd", "metadata": {}, "source": [ "## Notice that we now did 801 steps - vs. the 56 of the earlier variable-resolution run!" ] }, { "cell_type": "markdown", "id": "0f590255-1555-43d5-9adb-ace15ac80aa4", "metadata": {}, "source": [ "### Let's compare some entries with the coarser previous variable-time run" ] }, { "cell_type": "markdown", "id": "bfef068e-d576-4c3c-bda8-b0b51c5f88da", "metadata": {}, "source": [ "## Let's compare the plots of [B] from the earlier (variable-step) run, and the latest (high-precision, fixed-step) one:" ] }, { "cell_type": "code", "execution_count": 29, "id": "ce76fb06-b0fa-486b-b1ce-78f5786d8a85", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "Variable-step run=B
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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import plotly.graph_objects as go\n", "\n", "all_fig = go.Figure(data=fig1.data + fig2.data) # Note that the + is concatenating lists\n", "all_fig.update_layout(title=\"The 2 runs contrasted\")\n", "all_fig['data'][0]['name']=\"B (variable steps)\"\n", "all_fig['data'][1]['name']=\"B (fixed high precision)\"\n", "all_fig.show()" ] }, { "cell_type": "code", "execution_count": null, "id": "a796af3e-a7cc-4faa-b425-f07ddaf33aa1", "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 }