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"cell_type": "markdown",
"id": "ef6b822a-73a9-4057-97ea-b55c1661c2bc",
"metadata": {},
"source": [
"**Reaction A + B <-> C, mostly forward and with 1st-order kinetics for each species,\n",
"taken to equilibrium**\n",
"\n",
"Initial concentrations of A and B are spacially separated to the opposite ends of the system;\n",
"as a result, no C is being generated.\n",
"\n",
"But, as soon as A and B, from their respective distant originating points at the edges, \n",
"diffuse into the middle - and into each other - the reaction starts,\n",
"consuming both A and B (the forward reaction is much more substantial than the reverse one),\n",
"until an equilibrium is reached in both diffusion and reactions.\n",
"\n",
"A LOT of plots are sent to the log file from this experiment; the reason is to compare two\n",
"graphic elements, \"vue_curves_3\" and \"vue_curves_4\"\n",
"\n",
"LAST REVISED: July 14, 2023"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "434f6178-c89b-49ac-879d-ec05f0590fa0",
"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": "8a51735f",
"metadata": {},
"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from src.life_1D.bio_sim_1d import BioSim1D\n",
"\n",
"import plotly.express as px\n",
"from src.modules.chemicals.chem_data import ChemData as chem\n",
"from src.modules.html_log.html_log import HtmlLog as log\n",
"from src.modules.visualization.graphic_log import GraphicLog"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "6eae381c-b048-4345-904b-939c551ce1ef",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-> Output will be LOGGED into the file 'rd_1.log.htm'\n"
]
}
],
"source": [
"# Initialize the HTML logging\n",
"log_file = get_notebook_basename() + \".log.htm\" # Use the notebook base filename for the log file\n",
"\n",
"# Set up the use of some specified graphic (Vue) components\n",
"GraphicLog.config(filename=log_file,\n",
" components=[\"vue_heatmap_11\", \"vue_curves_3\", \"vue_curves_4\", \"vue_cytoscape_1\"],\n",
" extra_js=\"https://cdnjs.cloudflare.com/ajax/libs/cytoscape/3.21.2/cytoscape.umd.js\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "8e1ce9d4-e35c-4840-ae65-9c4f9a8f4542",
"metadata": {},
"outputs": [],
"source": [
"# Initialize the system\n",
"chem_data = chem(names=[\"A\", \"B\", \"C\"], diffusion_rates=[50., 50., 1.])\n",
"\n",
"\n",
"\n",
"# Reaction A + B <-> C , with 1st-order kinetics for each species; note that it's mostly in the forward direction\n",
"chem_data.add_reaction(reactants=[\"A\", \"B\"], products=[\"C\"], forward_rate=20., reverse_rate=2.)\n",
"bio = BioSim1D(n_bins=7, chem_data=chem_data)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d3dfb8b7-f54a-4e56-915b-e1d9b89d2365",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0:\n",
" A B C\n",
"0 0.0 0.0 0.0\n",
"1 0.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 0.0 0.0\n",
"6 0.0 0.0 0.0\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "dc49e75c-6aa5-414d-831f-805461f04f3a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Number of reactions: 1 (at temp. 25 C)\n",
"0: A + B <-> C (kF = 20 / kR = 2 / Delta_G = -5,708.01 / K = 10) | 1st order in all reactants & products\n"
]
}
],
"source": [
"chem_data.describe_reactions()"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "37eb3a95-3d46-479e-9c93-2e81a2d3202d",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Reaction: A + B C\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"# Send a header and a plot to the HTML log file\n",
"log.write(\"Reaction: A + B <-> C\",\n",
" style=log.h2)\n",
"graph_data = chem_data.prepare_graph_network()\n",
"GraphicLog.export_plot(graph_data, \"vue_cytoscape_1\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "433d4426-ca90-4d48-a7e6-b83a98904f5c",
"metadata": {},
"outputs": [],
"source": [
"# Set the heatmap parameters\n",
"heatmap_pars = {\"range\": [0, 20],\n",
" \"outer_width\": 850, \"outer_height\": 100,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }\n",
"\n",
"# Set the parameters of the line plots (for now, same for single-curve and multiple-curves)\n",
"lineplot_pars = {\"range\": [0, 20],\n",
" \"outer_width\": 850, \"outer_height\": 200,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }"
]
},
{
"cell_type": "markdown",
"id": "3fbf21cc-79ab-4915-ac51-8a963f16dc88",
"metadata": {},
"source": [
"# Inject initial concentrations of A and B at opposite ends of the system"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "f9e1cf26-1df8-4f38-af51-10f162043c7c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"7 bins and 3 species:\n",
" Species 0 (A). Diff rate: 50.0. Conc: [20. 0. 0. 0. 0. 0. 0.]\n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 0. 20.]\n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
]
}
],
"source": [
"bio.set_bin_conc(bin_address=0, species_index=0, conc=20.)\n",
"bio.set_bin_conc(bin_address=6, species_index=1, conc=20.)\n",
"\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "4a7f7fe9-a0f2-4233-a815-09668d44dac2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0:\n",
" A B C\n",
"0 20.0 0.0 0.0\n",
"1 0.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 0.0 0.0\n",
"6 0.0 20.0 0.0\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "33f4d6c1-5d4b-4128-90dc-cb8789717eed",
"metadata": {},
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\n",
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\n",
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" C | \n",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "1fd5d82c-8523-418c-8132-cfc284605b1c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"Initial system state at time t=0:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
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"source": [
"log.write(f\"Initial system state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
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"### First step"
]
},
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"cell_type": "code",
"execution_count": 14,
"id": "a69f25a4-34c2-48d5-bd0a-17cd4f0d3656",
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"delta_t = 0.002 # This will be our time \"quantum\" for this experiment"
]
},
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"execution_count": 15,
"id": "f3c1fe2b-61d3-429e-92d2-b922e8a2fad5",
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"SYSTEM STATE at Time t = 0.002:\n",
"7 bins and 3 species:\n",
" Species 0 (A). Diff rate: 50.0. Conc: [18. 2. 0. 0. 0. 0. 0.]\n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 2. 18.]\n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
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}
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"# First step\n",
"bio.react_diffuse(time_step=delta_t, n_steps=1)\n",
"bio.describe_state()"
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"_After the first delta_t time step_:\n",
"\n",
" Species 0 (A). Diff rate: 50.0. Conc: [18. 2. 0. 0. 0. 0. 0.]\n",
" \n",
" Species 1 (B). Diff rate: 50.0. Conc: [ 0. 0. 0. 0. 0. 2. 18.]\n",
" \n",
" Species 2 (C). Diff rate: 1.0. Conc: [0. 0. 0. 0. 0. 0. 0.]\n"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "0efdf530-d562-4ff5-8629-e1096c42e681",
"metadata": {},
"outputs": [
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"name": "stdout",
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"text": [
"SYSTEM SNAPSHOT at time 0.002:\n",
" A B C\n",
"0 18.0 0.0 0.0\n",
"1 2.0 0.0 0.0\n",
"2 0.0 0.0 0.0\n",
"3 0.0 0.0 0.0\n",
"4 0.0 0.0 0.0\n",
"5 0.0 2.0 0.0\n",
"6 0.0 18.0 0.0\n"
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},
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"cell_type": "code",
"execution_count": 17,
"id": "13d683c6-4264-4acc-88e7-d9043e0bc125",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "47bca5d0-c1f8-478d-ac9a-acb3a4ffbb3c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.002:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "c2f8bbb7-ccfc-4490-8245-580f2d753e10",
"metadata": {},
"source": [
"### Several more steps"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "a2746d1b-48f9-4d57-980c-9ea807a4e989",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0.004:\n",
"[[16.4 3.4 0.2 0. 0. 0. 0. ]\n",
" [ 0. 0. 0. 0. 0.2 3.4 16.4]\n",
" [ 0. 0. 0. 0. 0. 0. 0. ]]\n",
"SYSTEM STATE at Time t = 0.006:\n",
"[[15.1 4.38 0.5 0.02 0. 0. 0. ]\n",
" [ 0. 0. 0. 0.02 0.5 4.38 15.1 ]\n",
" [ 0. 0. 0. 0. 0. 0. 0. ]]\n",
"SYSTEM STATE at Time t = 0.008:\n",
"[[1.4028e+01 5.0640e+00 8.4000e-01 6.5984e-02 2.0000e-03 0.0000e+00\n",
" 0.0000e+00]\n",
" [0.0000e+00 0.0000e+00 2.0000e-03 6.5984e-02 8.4000e-01 5.0640e+00\n",
" 1.4028e+01]\n",
" [0.0000e+00 0.0000e+00 0.0000e+00 1.6000e-05 0.0000e+00 0.0000e+00\n",
" 0.0000e+00]]\n",
"SYSTEM STATE at Time t = 0.01:\n",
"[[1.31316000e+01 5.53800000e+00 1.18493120e+00 1.36813108e-01\n",
" 8.13120000e-03 2.00000000e-04 0.00000000e+00]\n",
" [0.00000000e+00 2.00000000e-04 8.13120000e-03 1.36813108e-01\n",
" 1.18493120e+00 5.53800000e+00 1.31316000e+01]\n",
" [0.00000000e+00 0.00000000e+00 6.72320000e-05 1.90027530e-04\n",
" 6.72320000e-05 0.00000000e+00 0.00000000e+00]]\n",
"SYSTEM STATE at Time t = 0.012:\n",
"[[1.23722400e+01 5.86200882e+00 1.51504114e+00 2.28008774e-01\n",
" 1.98211433e-02 9.28816000e-04 2.00000000e-05]\n",
" [2.00000000e-05 9.28816000e-04 1.98211433e-02 2.28008774e-01\n",
" 1.51504114e+00 5.86200882e+00 1.23722400e+01]\n",
" [0.00000000e+00 4.44384640e-05 4.52470702e-04 9.37489304e-04\n",
" 4.52470702e-04 4.44384640e-05 0.00000000e+00]]\n",
"SYSTEM STATE at Time t = 0.014:\n",
"[[1.17212070e+01 6.07811756e+00 1.81983529e+00 3.33817478e-01\n",
" 3.75512896e-02 2.50955578e-03 1.00983808e-04]\n",
" [1.00983808e-04 2.50955578e-03 3.75512896e-02 3.33817478e-01\n",
" 1.81983529e+00 6.07811756e+00 1.17212070e+01]\n",
" [9.98666893e-06 2.62777001e-04 1.65200869e-03 3.01131931e-03\n",
" 1.65200869e-03 2.62777001e-04 9.98666893e-06]]\n",
"SYSTEM STATE at Time t = 0.016:\n",
"[[1.11568507e+01 6.21598919e+00 2.09433486e+00 4.48347321e-01\n",
" 6.09468566e-02 5.16378807e-03 2.94534867e-04]\n",
" [2.94534867e-04 5.16378807e-03 6.09468566e-02 4.48347321e-01\n",
" 2.09433486e+00 6.21598919e+00 1.11568507e+01]\n",
" [5.77983875e-05 8.74133777e-04 4.37882730e-03 7.45120113e-03\n",
" 4.37882730e-03 8.74133777e-04 5.77983875e-05]]\n"
]
}
],
"source": [
"# Continue with several delta_t steps\n",
"for _ in range(7):\n",
" bio.react_diffuse(time_step=delta_t, n_steps=1)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "fa7d3b56-4ff5-4ccb-90ee-493a9e93b32f",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.016:\n",
" A B C\n",
"0 11.156851 0.000295 0.000058\n",
"1 6.215989 0.005164 0.000874\n",
"2 2.094335 0.060947 0.004379\n",
"3 0.448347 0.448347 0.007451\n",
"4 0.060947 2.094335 0.004379\n",
"5 0.005164 6.215989 0.000874\n",
"6 0.000295 11.156851 0.000058\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "7280ab4a-b2b2-401f-a832-353ff62b9826",
"metadata": {},
"outputs": [
{
"data": {
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"text/plain": [
" SYSTEM TIME A B C caption\n",
"0 0.000 0.000000 0.000000 0.000000 \n",
"1 0.002 0.000000 0.000000 0.000000 \n",
"2 0.016 0.448347 0.448347 0.007451 "
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},
"execution_count": 22,
"metadata": {},
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"source": [
"# Save the state of the concentrations of all species at the middle bin\n",
"bio.add_snapshot(bio.bin_snapshot(bin_address = 3))\n",
"bio.get_history()"
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},
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"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot (interpolated) at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "b8f59740-166c-4909-bd92-321f6e865479",
"metadata": {},
"source": [
"A is continuing to diffuse from the left. \n",
"B is continuing to diffuse from the right. \n",
"They're finally beginning to overlap in the middle bin"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "9974a579-14c5-447b-9616-b136e356ee90",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.016:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "4dc3b1cd-3ef9-4882-abfe-479cfc0a25cf",
"metadata": {},
"source": [
"### Several group of longer runs"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "bb248152-bda9-4f70-b81d-52d982a2233e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.036:\n",
"[[7.92576526 5.95824446 3.31917619 1.31581241 0.35918764 0.07038175\n",
" 0.01251229]\n",
" [0.01251229 0.07038175 0.35918764 1.31581241 3.31917619 5.95824446\n",
" 7.92576526]\n",
" [0.01555131 0.07914514 0.24409632 0.36133444 0.24409632 0.07914514\n",
" 0.01555131]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.056:\n",
"[[6.29600683 5.06118233 3.15970431 1.44600532 0.47532616 0.12019317\n",
" 0.03045075]\n",
" [0.03045075 0.12019317 0.47532616 1.44600532 3.15970431 5.06118233\n",
" 6.29600683]\n",
" [0.07498099 0.28735559 0.78250579 1.12144639 0.78250579 0.28735559\n",
" 0.07498099]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.076:\n",
"[[5.13609493 4.21433746 2.7454954 1.35328847 0.4992179 0.14748071\n",
" 0.04559633]\n",
" [0.04559633 0.14748071 0.4992179 1.35328847 2.7454954 4.21433746\n",
" 5.13609493]\n",
" [0.1615343 0.52706799 1.31954666 1.8421909 1.31954666 0.52706799\n",
" 0.1615343 ]]\n",
"\n",
"\n",
"+ 10 steps later:\n",
"SYSTEM STATE at Time t = 0.096:\n",
"[[4.2209458 3.50170661 2.34873485 1.23042685 0.50075376 0.16821567\n",
" 0.0606064 ]\n",
" [0.0606064 0.16821567 0.50075376 1.23042685 2.34873485 3.50170661\n",
" 4.2209458 ]\n",
" [0.25982593 0.75464804 1.76534285 2.40897641 1.76534285 0.75464804\n",
" 0.25982593]]\n"
]
}
],
"source": [
"# Now, do several group of longer runs\n",
"for _ in range(4):\n",
" print(\"\\n\\n+ 10 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=10)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "dfa3d4e1-a187-4231-b9f1-658fbfc7dedc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.09600000000000007:\n",
" A B C\n",
"0 4.220946 0.060606 0.259826\n",
"1 3.501707 0.168216 0.754648\n",
"2 2.348735 0.500754 1.765343\n",
"3 1.230427 1.230427 2.408976\n",
"4 0.500754 2.348735 1.765343\n",
"5 0.168216 3.501707 0.754648\n",
"6 0.060606 4.220946 0.259826\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "c962bc0d-b2b9-411c-8c61-f2a0a1fdeb27",
"metadata": {},
"outputs": [
{
"data": {
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" B | \n",
" C | \n",
" caption | \n",
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\n",
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" \n",
" \n",
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]
},
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"source": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "461feca1-4016-44d8-ab71-bf36e437e121",
"metadata": {},
"source": [
"A is continuing to diffuse from the left. \n",
"B is continuing to diffuse from the right. \n",
"By now, they're overlapping in the middle bin sufficiently to react and generate C"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "cff27b4b-5cf3-4d70-80a7-8a13e1e3cd99",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.09600000000000007:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(bio.n_species):\n",
" log.write(f\"{bio.chem_data.get_name(i)}:\", also_print=False)\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "c15dfca3-00fc-4b9a-80c4-01f565f30cf8",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.156:\n",
"[[2.39736516 2.05453684 1.50075745 0.92781069 0.48529917 0.22472198\n",
" 0.11560109]\n",
" [0.11560109 0.22472198 0.48529917 0.92781069 1.50075745 2.05453684\n",
" 2.39736516]\n",
" [0.57202182 1.29674075 2.59761288 3.36115673 2.59761288 1.29674075\n",
" 0.57202182]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.216:\n",
"[[1.43652347 1.28435794 1.02979899 0.73906751 0.47257834 0.28028088\n",
" 0.18445971]\n",
" [0.18445971 0.28028088 0.47257834 0.73906751 1.02979899 1.28435794\n",
" 1.43652347]\n",
" [0.8597085 1.64384498 2.94653088 3.67276444 2.94653088 1.64384498\n",
" 0.8597085 ]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.276:\n",
"[[0.94369275 0.88396666 0.77535511 0.63019458 0.46959173 0.33300009\n",
" 0.25664867]\n",
" [0.25664867 0.33300009 0.46959173 0.63019458 0.77535511 0.88396666\n",
" 0.94369275]\n",
" [1.09382006 1.85282552 3.05530325 3.70365274 3.05530325 1.85282552\n",
" 1.09382006]]\n",
"\n",
"\n",
"+++ 30 steps later:\n",
"SYSTEM STATE at Time t = 0.336:\n",
"[[0.69798039 0.68111864 0.64213556 0.57196145 0.47435422 0.37878712\n",
" 0.32097915]\n",
" [0.32097915 0.37878712 0.47435422 0.57196145 0.64213556 0.68111864\n",
" 0.69798039]\n",
" [1.27482053 1.97696102 3.05404907 3.62102222 3.05404907 1.97696102\n",
" 1.27482053]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n\\n+++ 30 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=30)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "c4ae0ca5-2b98-4db4-b5e0-874ec2117ef0",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.33600000000000024:\n",
" A B C\n",
"0 0.697980 0.320979 1.274821\n",
"1 0.681119 0.378787 1.976961\n",
"2 0.642136 0.474354 3.054049\n",
"3 0.571961 0.571961 3.621022\n",
"4 0.474354 0.642136 3.054049\n",
"5 0.378787 0.681119 1.976961\n",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "ba4c44a3-3384-4f1a-b656-783c06eeb4af",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.33600000000000024:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "d7bd2795-9a78-4a2e-834c-477951677878",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.436:\n",
"[[0.53513401 0.5437576 0.54867719 0.53174198 0.48696931 0.43256384\n",
" 0.39647767]\n",
" [0.39647767 0.43256384 0.48696931 0.53174198 0.54867719 0.5437576\n",
" 0.53513401]\n",
" [1.49508439 2.09028492 2.96849022 3.41695934 2.96849022 2.09028492\n",
" 1.49508439]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.536:\n",
"[[0.48751897 0.50165856 0.51768297 0.51798994 0.49498758 0.46076288\n",
" 0.4365229 ]\n",
" [0.4365229 0.46076288 0.49498758 0.51798994 0.51768297 0.50165856\n",
" 0.48751897]\n",
" [1.65797359 2.15520413 2.86719131 3.22213812 2.86719131 2.15520413\n",
" 1.65797359]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.636:\n",
"[[0.47470241 0.48869324 0.50591479 0.51120986 0.49756771 0.47365233\n",
" 0.45594669]\n",
" [0.45594669 0.47365233 0.49756771 0.51120986 0.50591479 0.48869324\n",
" 0.47470241]\n",
" [1.78774781 2.20070508 2.77778668 3.05983384 2.77778668 2.20070508\n",
" 1.78774781]]\n",
"\n",
"+++++ 50 steps later:\n",
"SYSTEM STATE at Time t = 0.736:\n",
"[[0.47257504 0.48488523 0.50040062 0.50652836 0.49733067 0.47935337\n",
" 0.46567693]\n",
" [0.46567693 0.47935337 0.49733067 0.50652836 0.50040062 0.48488523\n",
" 0.47257504]\n",
" [1.89367665 2.23536347 2.70338342 2.9284027 2.70338342 2.23536347\n",
" 1.89367665]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n+++++ 50 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=50)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "9bea764f-c52e-4346-a1e5-8a3e78bfca47",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 0.7360000000000005:\n",
" A B C\n",
"0 0.472575 0.465677 1.893677\n",
"1 0.484885 0.479353 2.235363\n",
"2 0.500401 0.497331 2.703383\n",
"3 0.506528 0.506528 2.928403\n",
"4 0.497331 0.500401 2.703383\n",
"5 0.479353 0.484885 2.235363\n",
"6 0.465677 0.472575 1.893677\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "420d2e10-a6e7-4c90-80ea-5995db2b5ed6",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"
\n",
" \n",
" \n",
" | \n",
" SYSTEM TIME | \n",
" A | \n",
" B | \n",
" C | \n",
" caption | \n",
"
\n",
" \n",
" \n",
" \n",
" | 0 | \n",
" 0.000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" | \n",
"
\n",
" \n",
" | 1 | \n",
" 0.002 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" 0.000000 | \n",
" | \n",
"
\n",
" \n",
" | 2 | \n",
" 0.016 | \n",
" 0.448347 | \n",
" 0.448347 | \n",
" 0.007451 | \n",
" | \n",
"
\n",
" \n",
" | 3 | \n",
" 0.096 | \n",
" 1.230427 | \n",
" 1.230427 | \n",
" 2.408976 | \n",
" | \n",
"
\n",
" \n",
" | 4 | \n",
" 0.336 | \n",
" 0.571961 | \n",
" 0.571961 | \n",
" 3.621022 | \n",
" | \n",
"
\n",
" \n",
" | 5 | \n",
" 0.736 | \n",
" 0.506528 | \n",
" 0.506528 | \n",
" 2.928403 | \n",
" | \n",
"
\n",
" \n",
"
\n",
"
"
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"text/plain": [
" SYSTEM TIME A B C caption\n",
"0 0.000 0.000000 0.000000 0.000000 \n",
"1 0.002 0.000000 0.000000 0.000000 \n",
"2 0.016 0.448347 0.448347 0.007451 \n",
"3 0.096 1.230427 1.230427 2.408976 \n",
"4 0.336 0.571961 0.571961 3.621022 \n",
"5 0.736 0.506528 0.506528 2.928403 "
]
},
"execution_count": 37,
"metadata": {},
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],
"source": [
"# Save the state of the concentrations of all species at the middle bin\n",
"bio.add_snapshot(bio.bin_snapshot(bin_address = 3))\n",
"bio.get_history()"
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 39,
"id": "8ac79f33-0548-49ce-a165-24b9773a7c4c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=0.7360000000000005:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "b041f211-cc16-42a4-b0ca-2beb4e2c34aa",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.036:\n",
"[[0.47744061 0.4845086 0.49346999 0.49747162 0.49331726 0.48423339\n",
" 0.47709743]\n",
" [0.47709743 0.48423339 0.49331726 0.49747162 0.49346999 0.4845086\n",
" 0.47744061]\n",
" [2.11014111 2.3007984 2.55138084 2.66782039 2.55138084 2.3007984\n",
" 2.11014111]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.336:\n",
"[[0.48168804 0.48554921 0.49041386 0.49259511 0.49040626 0.48553552\n",
" 0.48167096]\n",
" [0.48167096 0.48553552 0.49040626 0.49259511 0.49041386 0.48554921\n",
" 0.48168804]\n",
" [2.2288825 2.33377315 2.46847456 2.52988061 2.46847456 2.33377315\n",
" 2.2288825 ]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.636:\n",
"[[0.48405962 0.48615505 0.48878337 0.48995858 0.48878299 0.48615437\n",
" 0.48405877]\n",
" [0.48405877 0.48615437 0.48878299 0.48995858 0.48878337 0.48615505\n",
" 0.48405962]\n",
" [2.29360822 2.350868 2.42345244 2.45618991 2.42345244 2.350868\n",
" 2.29360822]]\n",
"\n",
"+++++++++++++++ 150 steps later:\n",
"SYSTEM STATE at Time t = 1.936:\n",
"[[0.48534444 0.4864795 0.48789956 0.48853323 0.48789955 0.48647947\n",
" 0.4853444 ]\n",
" [0.4853444 0.48647947 0.48789955 0.48853323 0.48789956 0.4864795\n",
" 0.48534444]\n",
" [2.32876222 2.35988613 2.39905402 2.4166151 2.39905402 2.35988613\n",
" 2.32876222]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(4):\n",
" print(\"\\n+++++++++++++++ 150 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=150)\n",
" bio.describe_state(concise=True)"
]
},
{
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 44,
"id": "149c2dd1-ae24-42af-9cb7-ea3e3b7bc7ae",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=1.9360000000000015:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "c9a71254-b873-4f84-92e8-55110fd3e9e1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"++++++++++ ... ++++++++++ 1,000 steps later:\n",
"SYSTEM STATE at Time t = 3.936:\n",
"[[0.48683089 0.48684974 0.48687325 0.48688372 0.48687325 0.48684974\n",
" 0.48683089]\n",
" [0.48683089 0.48684974 0.48687325 0.48688372 0.48687325 0.48684974\n",
" 0.48683089]\n",
" [2.36959744 2.37011659 2.37076408 2.37105229 2.37076408 2.37011659\n",
" 2.36959744]]\n",
"\n",
"++++++++++ ... ++++++++++ 1,000 steps later:\n",
"SYSTEM STATE at Time t = 5.936:\n",
"[[0.48685551 0.48685582 0.48685621 0.48685639 0.48685621 0.48685582\n",
" 0.48685551]\n",
" [0.48685551 0.48685582 0.48685621 0.48685639 0.48685621 0.48685582\n",
" 0.48685551]\n",
" [2.37027551 2.37028411 2.37029484 2.37029961 2.37029484 2.37028411\n",
" 2.37027551]]\n"
]
}
],
"source": [
"# Continue the simulation\n",
"for _ in range(2):\n",
" print(\"\\n++++++++++ ... ++++++++++ 1,000 steps later:\")\n",
" bio.react_diffuse(time_step=delta_t, n_steps=1000)\n",
" bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "665df78f-4f5d-4f49-bd1e-7fe92f6f9be1",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM SNAPSHOT at time 5.935999999999568:\n",
" A B C\n",
"0 0.486856 0.486856 2.370276\n",
"1 0.486856 0.486856 2.370284\n",
"2 0.486856 0.486856 2.370295\n",
"3 0.486856 0.486856 2.370300\n",
"4 0.486856 0.486856 2.370295\n",
"5 0.486856 0.486856 2.370284\n",
"6 0.486856 0.486856 2.370276\n"
]
}
],
"source": [
"bio.show_system_snapshot()"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "123afda8-993f-4d81-823b-dd4bca921727",
"metadata": {},
"outputs": [
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"# Save the state of the concentrations of all species at the middle bin\n",
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},
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"cell_type": "code",
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"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": "A + B <-> C . System snapshot at time t=5.935999999999568"
},
"xaxis": {
"anchor": "y",
"autorange": true,
"domain": [
0,
1
],
"range": [
0,
6
],
"title": {
"text": "Bin number"
},
"type": "linear"
},
"yaxis": {
"anchor": "x",
"autorange": true,
"domain": [
0,
1
],
"range": [
0.3822197281848969,
2.4749353952225412
],
"title": {
"text": "concentration"
},
"type": "linear"
}
}
},
"image/png": 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""
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"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\", \"B\", \"C\"], \n",
" title= f\"A + B <-> C . System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red', 'orange', 'green'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"},\n",
" line_shape=\"spline\")\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "ebc287ae-60de-4d52-9b34-6714b3813198",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"System state at time t=5.935999999999568:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `rd_1.log.htm`]\n"
]
}
],
"source": [
"log.write(f\"System state at time t={bio.system_time}:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output to the log file a heatmap for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_heatmap(species_index=i, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output to the log file a one-curve line plot for each chemical species\n",
"for i in range(3):\n",
" bio.single_species_line_plot(species_index=i, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")\n",
"\n",
"# Output to the log file a line plot for ALL the chemicals together (same color as used for plotly elsewhere)\n",
"bio.line_plot(plot_pars=lineplot_pars, graphic_component=\"vue_curves_4\", color_mapping={0: 'red', 1: 'orange', 2: 'green'})"
]
},
{
"cell_type": "markdown",
"id": "1ede543d-6d62-4ede-bb7b-7b6022c69b09",
"metadata": {
"tags": []
},
"source": [
"### Equilibrium"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "1678d6bf-434f-476c-a966-998fbfa0e74a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Ratio of equilibrium concentrations ((C_eq) / (A_eq * B_eq)) : 9.999968840509963\n",
"Ratio of forward/reverse rates: 10.0\n"
]
}
],
"source": [
"# Verify equilibrium concentrations (sampled in the 1st bin; at this point, all bins have equilibrated)\n",
"A_eq = bio.bin_concentration(0, 0)\n",
"B_eq = bio.bin_concentration(0, 1)\n",
"C_eq = bio.bin_concentration(0, 2)\n",
"print(f\"\\nRatio of equilibrium concentrations ((C_eq) / (A_eq * B_eq)) : {(C_eq) / (A_eq * B_eq)}\")\n",
"print(f\"Ratio of forward/reverse rates: {chem_data.get_forward_rate(0) / chem_data.get_reverse_rate(0)}\")\n",
"# Both are essentially equal, as expected"
]
},
{
"cell_type": "markdown",
"id": "ee7d1b45-0e56-45fd-bd63-7a97b39eb8f0",
"metadata": {
"tags": []
},
"source": [
"# Plots of changes of concentration with time"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "790211a2-8f53-498a-8363-1c6e5f6f5d7e",
"metadata": {
"tags": []
},
"outputs": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"fig = px.line(data_frame=bio.get_history(), x=\"SYSTEM TIME\", y=[\"A\", \"B\", \"C\"], \n",
" title=\"Reactions: A + B <-> C . Changes in concentrations in the MIDDLE bin\",\n",
" color_discrete_sequence = ['navy', 'cyan', 'red'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "4dbf45ff-5161-4265-a278-aca3121b8e37",
"metadata": {},
"source": [
"A and B overlap on the plot, due to the symmetry of the system. \n",
"Initially, in the middle bin, neither A nor B are present; over time they diffuse there... but then they react and get consumed (producing C), to an equilibrium value.\n",
"C gradually diffuses away."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "146f8c63",
"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
}