{ "cells": [ { "cell_type": "markdown", "id": "4e50d971", "metadata": {}, "source": [ "### `A <-> 3B` reaction, with 1st-order kinetics in both directions, taken to equilibrium\n", "### Examine State Space trajectory, using [A] and [B] as state variables\n", "\n", "Based on experiment \"1D/reaction/reaction_2\"\n", "\n", "LAST REVISED: June 4, 2023" ] }, { "cell_type": "code", "execution_count": 1, "id": "865c1166", "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": "d57ab02a", "metadata": {}, "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 plotly.express as px\n", "import plotly.graph_objects as go\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": "180bfbdd", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-> Output will be LOGGED into the file 'state_space_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_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": "610ce687-64a0-4ad8-a7df-a7d204b94684", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Number of reactions: 1 (at temp. 25 C)\n", "0: A <-> 3 B (kF = 5 / kR = 2 / Delta_G = -2,271.45 / K = 2.5) | 1st order in all reactants & products\n" ] } ], "source": [ "# Initialize the system\n", "chem_data = ChemData(names=[\"A\", \"B\"])\n", "\n", "\n", "# Reaction A <-> 3B , with 1st-order kinetics in both directions\n", "chem_data.add_reaction(reactants=\"A\", products=[(3,\"B\")], forward_rate=5., reverse_rate=2.)\n", "\n", "chem_data.describe_reactions()" ] }, { "cell_type": "code", "execution_count": 5, "id": "0423bb64-0481-4ea8-a566-f2d10d82574a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SYSTEM STATE at Time t = 0:\n", "2 species:\n", " Species 0 (A). Conc: 10.0\n", " Species 1 (B). Conc: 50.0\n" ] } ], "source": [ "dynamics = ReactionDynamics(reaction_data=chem_data)\n", "dynamics.set_conc(conc={\"A\": 10., \"B\": 50.},\n", " snapshot=True)\n", "dynamics.describe_state()" ] }, { "cell_type": "code", "execution_count": 6, "id": "4b5e75e5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[GRAPHIC ELEMENT SENT TO LOG FILE `state_space_1.log.htm`]\n" ] } ], "source": [ "# Send the plot 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": "dfb4e9e3", "metadata": { "tags": [] }, "source": [ "### To equilibrium" ] }, { "cell_type": "code", "execution_count": 7, "id": "c3ed24bd-c237-491f-a2b9-676fc666b087", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "10 total step(s) taken\n" ] } ], "source": [ "dynamics.single_compartment_react(initial_step=0.05, n_steps=10, variable_steps=False)" ] }, { "cell_type": "code", "execution_count": 8, "id": "56e68446-bc47-4b0d-b772-bc206bacaec4", "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", "
SYSTEM TIMEABcaption
00.0010.00000050.000000Initial state
10.0512.50000042.500000
20.1013.62500039.125000
30.1514.13125037.606250
40.2014.35906336.922812
50.2514.46157836.615266
60.3014.50771036.476870
70.3514.52847036.414591
80.4014.53781136.386566
90.4514.54201536.373955
100.5014.54390736.368280
\n", "
" ], "text/plain": [ " SYSTEM TIME A B caption\n", "0 0.00 10.000000 50.000000 Initial state\n", "1 0.05 12.500000 42.500000 \n", "2 0.10 13.625000 39.125000 \n", "3 0.15 14.131250 37.606250 \n", "4 0.20 14.359063 36.922812 \n", "5 0.25 14.461578 36.615266 \n", "6 0.30 14.507710 36.476870 \n", "7 0.35 14.528470 36.414591 \n", "8 0.40 14.537811 36.386566 \n", "9 0.45 14.542015 36.373955 \n", "10 0.50 14.543907 36.368280 " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df = dynamics.get_history()\n", "df" ] }, { "cell_type": "code", "execution_count": 9, "id": "968e0c7f-4fef-4dbf-b055-96168432aecb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "0: A <-> 3 B\n", "Final concentrations: [B] = 36.37 ; [A] = 14.54\n", "1. Ratio of reactant/product concentrations, adjusted for reaction orders: 2.50059\n", " Formula used: [B] / [A]\n", "2. Ratio of forward/reverse reaction rates: 2.5\n", "Discrepancy between the two values: 0.02341 %\n", "Reaction IS in equilibrium (within 1% tolerance)\n", "\n" ] }, { "data": { "text/plain": [ "True" ] }, "execution_count": 9, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Verify that the reaction has reached equilibrium\n", "dynamics.is_in_equilibrium()" ] }, { "cell_type": "code", "execution_count": 10, "id": "af88741e-72cc-41be-98d4-3e95f8a90a10", "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": "navy", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "A", "orientation": "v", "showlegend": true, "type": "scatter", "x": [ 0, 0.05, 0.1, 0.15000000000000002, 0.2, 0.25, 0.3, 0.35, 0.39999999999999997, 0.44999999999999996, 0.49999999999999994 ], "xaxis": "x", "y": [ 10, 12.5, 13.625, 14.13125, 14.3590625, 14.461578125, 14.50771015625, 14.5284695703125, 14.537811306640625, 14.54201508798828, 14.543906789594727 ], "yaxis": "y" }, { "hovertemplate": "Chemical=B
SYSTEM TIME=%{x}
concentration=%{y}", "legendgroup": "B", "line": { "color": "orange", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "B", "orientation": "v", "showlegend": true, "type": "scatter", "x": [ 0, 0.05, 0.1, 0.15000000000000002, 0.2, 0.25, 0.3, 0.35, 0.39999999999999997, 0.44999999999999996, 0.49999999999999994 ], "xaxis": "x", "y": [ 50, 42.5, 39.125, 37.60625, 36.9228125, 36.615265625, 36.47686953125, 36.4145912890625, 36.386566080078126, 36.37395473603516, 36.36827963121582 ], "yaxis": "y" } ], "layout": { "autosize": true, "legend": { "title": { "text": "Chemical" }, "tracegroupgap": 0 }, "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 <-> 3 B` . Changes in concentrations with time" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ 0, 0.49999999999999994 ], "title": { "text": "SYSTEM TIME" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 7.777777777777778, 52.22222222222222 ], "title": { "text": "concentration" }, "type": "linear" } } }, "image/png": "iVBORw0KGgoAAAANSUhEUgAAAx4AAAFoCAYAAADZ3i3LAAAAAXNSR0IArs4c6QAAIABJREFUeF7tvQ24HNV55/n2/dK9ki76BAnZMrLEh2CCzZgAcnZMmBDvJGIYe8miwDrzQPDICmQmC2jESLB+MOPB0kojYCcbGEVjGc/GY0beYSfLIifPE/wQnN2VIXhxsDE2SICxQcLoC33cq/vV+5zqW626dau7q7pPnY+qX/PwqG/3qfd9z+9f3af+fU5VVarValV4QAACEIAABCAAAQhAAAIQyJFABeORI11CQwACEIAABCAAAQhAAAIBAYwHOwIEIAABCEAAAhCAAAQgkDsBjEfuiEkAAQhAAAIQgAAEIAABCGA82AcgAAEIQAACEIAABCAAgdwJYDxyR0wCCEAAAhCAAAQgAAEIQADjwT4AAQhAAAIQgAAEIAABCOROAOORO2ISQAACEIAABCAAAQhAAAIYD/YBCEAAAhCAAAQgAAEIQCB3AhiP3BGTAAIQgAAEIAABCEAAAhDAeLAPQAACEIAABCAAAQhAAAK5E8B45I6YBBCAAAQgAAEIQAACEIAAxoN9AAIQgAAEIAABCEAAAhDInQDGI3fEJIAABCAAAQhAAAIQgAAEMB7sAxCAAAQgAAEIQAACEIBA7gQwHrkjJgEEIAABCEAAAhCAAAQggPFgH4AABCAAAQhAAAIQgAAEcieA8cgdMQkgAAEIQAACEIAABCAAAYwH+wAEIAABCEAAAhCAAAQgkDsBjEfuiEkAAQhAAAIQgAAEIAABCGA82AcgAAEIQAACEIAABCAAgdwJYDxyR0wCCEAAAhCAAAQgAAEIQADjwT4AAQhAAAIQgAAEIAABCOROAOORO2ISQAACEIAABCAAAQhAAAIYD/YBCEAAAhCAAAQgAAEIQCB3AhiP3BGTAAIQgAAEIAABCEAAAhDAeLAPQAACEIAABCAAAQhAAAK5E8B45I6YBBCAAAQgAAEIQAACEIAAxoN9AAIQgAAEIAABCEAAAhDInQDGI3fEJIAABCAAAQhAAAIQgAAEMB7sAxCAAAQgAAEIQAACEIBA7gQwHrkjJgEEIAABCEAAAhCAAAQggPFgH4AABCAAAQhAAAIQgAAEcieA8cgdMQkgAAEIQAACEIAABCAAAYwH+wAEIAABCEAAAhCAAAQgkDsBjEfuiEkAAQhAAAIQgAAEIAABCGA8SrAPHDl2XG7f+HDQ08e23CXz5gyWoNdudvGhHbvlq9/cI48/slGuuGylm0VSFQQgAAEIQAACEMiBAMYjB6guhgzNx5rrr5EbVl/tYomlqUmZjwPvHZYHNtwmA/19zvf7yT3PyaNf/3PZsXW9rDhvifP1UiAEINCcgPoOev6lV/khih0FAhAwTsAL4/HCS6/KrXdumQbn3EULnDgYCg/qr7xspdy9bs2UOve99Y6su2e7rP6Nq6a9Z1ptxXHT5p2pmIW/zF968fLCDk7qgPqLW3dNkeHzN69OpdPQ8Ijcv22XPP3M3sz7pUsmMIlB/HOF8TgjsUufZ9PfH7ryNfu+1JEj1OiOWz4z7UeWcH8v2oxjyPQjS86p/6DRjEOnxsOXMU/H/kQMCEBALwGvjEd8sHBl2UrRvoTD/swZnCV/8/zLWpcFhQfsP3vnvUyGJtzu+z98LZVxavUxSToACQfqT/zKBS1nI8J6VJ74zIXaL/d853ta6mzVj3bfDzV+//CxaXWGbL58z23BgRvGA+PR7n6WtB3GQyfNWiyMh36mRIQABPIh4LXxSPqyzQdT86h5D6Sm+xTOjGzetFa279gtSTM5WWuKzhB0MosSms1OZ7v+8tnn5fyPfnja0qG0vwQ2Mx7hDF144J6VVd7t05g/ZcJef+Pn8o+uuRLjkbcgJYuf9/dls1/6y4Ta1oxHmRjTVwhAIDuBwhqP+BKS665dNeWX6UZLZeLtQqThYPnyj/fXKau2d37hRrn7S38i0ddVgzDOOwffD5Zaxaf9w0Hh3YOHgnhJB9LRgUO1iS4LymupQPyA+rGv/9eO1gLrMhzxXTuvpWA6jUdeGmX/mE/dIqsxCmc8HvnX/1z+4+6/rC8vSzKQaZZuqWqyxFTtkz4vC+edJR/50KJpM07xpZlJdcbjqRxpjGLSwVzWvjTSr9F3THRGrdX3Wjts0+RNwzT87Hxl01q5d/PO+ndi9Ds1KVf0+/Lb39lbP5/oz//ib4ILMaiH+iypR9KS2+jnLElXtV24hLLR7F2a7+MsOieNL43Gluj+kPT9E7KP9jNu3uJ/t+KQRqss+2mrMU+x2/3UsxLfN8LP5uGjx4NxMhwPG/04lWY/7PT7ke0hAIF8CXhtPJIOAhr9mhv/Qlfttj32hHzuht+s/+rd6FfsRgdqf/pnT8m1n7pc5s8dDK4a1ewcj6jxSBpImi39UV/G0YOiPJe+xJkm1Zpml8zLcORpQLKs/260rzSbCUnDzUSbrEvBQi5Rc9yon6qtekQvYJC0v2aJmfT5a5Q/qW/x/EnfG2n380bGQ/0okIZPI31bfceok/qTvsPUeUbxZYudslU1ht9tYd740sEkTZN+DEia3Wg24xE1VnHjrhh993t/N+UcrCTdWp3jEb9QQtrv47Rck/bNtLM8SefhhVyj55+FfVSz0urqeEnxW814KFMXPcBPW6PaP9IsL46OeSG7pHzqR7s0daT5bJv4/iQHBCDQGQFvjUcjg9HoBOq00+/x7dN8GWf5Em7WNn5g0ajmPE9Ojh9QtHMgnTTIdLabtt46HJzT/KoYjRb9BTbLts1OLo/+wtq6cvMt0s7qhJU1MrppL1aQtL+mjRlyXnzO/Gkn/cevDhY/GAvrj3/mmv3qPTR8Wn7loo82FKXZjEf8ql9Z+TRb0tjIGCV9n6Rlm+a7LS1TBazRfhX+2h1eyruV8chyBbWk/SOL8cjyfZyWa6P8qtbn9r4ULF9sNZsQXn0wWl/0KlRpmLYyHklXtYrHbVVn2h/bGsVN+3qW/dD8NyoZIQCBLAS8Mh7xjiUtZWl0qdJGBzCtloY0+sJLOnhN8yXcLF6aX2Zb/dqURfx422a/Ymc5GGjHeCTpkMUItGs8ogxCbdJcgayZIQsPFlRsF++botN4qKUv8c9ho2UeaWbt4gfYrQ6eopclbnbQFP1e+OGr+4MlO+2ca5TVeCTxiX/u0nzHNOpb0n7Y7AA5Wk8neUOjEeXfzHhEvz86MR6NlmolzQY0uqpVtJYs38dpuUZrzLrcMj5Oqc+DOs8uXKK0ft2aYIYjPs61M+PRyHik+a7P8mOb2lfSGozojx1qaVb4/Zn2s+3D5ck7GaPZFgJFIOCV8Qi/xBsd2LX6FTr6S3QYI35Vn/ivlGmWYGT5Em4WL+1BV5pfKtvZORsdMIax0qyBD9v6uNQqHCDTDLytZoLS7DftaKRjm3aWWiUxSepjaACj+0rWGY/owXEzjvGDrzB3I0ZRIxtfKx79bmjGOA/jkWZfaWYW4++lPUBOmzc8zyKJS5Rp3sYj/HEiajI6nfHI8n2clmv0x6HouX9pjW70IPtrT3w7wK4u0674qsftt3w2uJT3qssvqS9pLLrxyPLZ1vEdSQwIQCA/Al4aD4UjPABYOH/OlF+VG814xBFmnTYP19ImSZHFeGT5ha3VUisdV5uK9qfRgUOrg+xmu2deBiRpPbmOj0magzGVpxWTRmv2ddTYaYystaU94Gq1v0ZvXpk1ZtLnL/5ZT7tMJIlfkmFKapeH8ehk5sHmjEecT57Go9F3bKfGI8v3cdp9Nmm/CT9zaWZxwx+/wqsKhrMc4eyH+lvdjyn6mSi68ejks93p9yXbQwACegl4azwUhqQv80aDQ9pBMss5Hj/8yRsy0D9DlixaGPwClbQOPX6gkmVNcasDOZ3Go9UsSvhrY9alAyF3XQYkPEDs5HK6qpb/8vRfy+9c9+vT7hyedv9Jazza5aX3Yz41WqPzo6Kt1P6gfq29etXHG15ON27SWp2H0I7xaPV5iS71SWsan9v7g2CZ1bw5g/Uut9r/w4Z5GI9mucPvmMNHPgiWh8X3p6zneERjdJK3kXlLs3yn2Xk7zc6/Sbo6YFKsZufAxeO32r/i51WkmflT+0jSuUJplziGNan7KB07frL+w1qj8z2UFkn9aMYhrUls9D3UTMNGn5Ho0qkwbtolWGk/23l+bxIbAhDQQ8Br46EQxKffwy/EpBvNqbbqoa64k/RFFr4WP6hN+oU4blAafZEnfQknxUs6sDdpPFp9sac9MGu1W6Y56E2K0UzXVjnj7zeKFTJIc/fyZsYj1C3NjQiz1K6TQaOlhtHPVKsbCMb3mWYHP8rEtHOOR1hP/IAv/LzEf0EOjWmzKyIlHdy22v/zNB7RH1GijJK+Y6JXl2r0Wcryy3za7za13KrVVaayHMxmaav4JH3eoj9mJC2/UtvFb+7ZTPv4/qmuVBbtc1quSd/bWb8/w/04/l3U6PWk+M2+o7Lyz2I08zAeKn+az3aW71PaQgACdgh4bzyiX0jRg5Ckk5Xja2zj67zVl/ynrvpYMI0dv0JN0vkP0UEpfn6J7vt4RC9PmnUQa7VrpTUDaX+xa5XPhfcbnQ+Udoai1flEWc6HSctDp/GI/uIYvT+Mej1uvNMecKltoyfWqr/VZy48MbadGY9GdSq+b759QKIzHmHbpPM34n2KrxlPO4OWx4xH3NSE9zJQr8f3x/j3WtLSnSx6qRytvtuixii6ryYxTTPjETUSTz+zNwgZ9iN6Hw91Kd/oI/6ZU/nDe8vEZ5vj+6HO+3gkXb0sPhuVtA9m+U5oNMPcaJlkozGhEQcdxiPLmJd2ZiP6eU+aIUnz2U77fUo7CEDADgEvjIcdNGSFAARcJdBsqYerNVMXBCAAAQhAoOwEMB5l3wPoPwQcJ6B+5Uy6cVzSzKTjXaE8CEAAAhCAQKkJYDxKLT+dh4D7BJKWV6S9NKn7vaNCCEAAAhCAQHkIYDzKozU9hQAEIAABCEAAAhCAgDUCGA9r6EkMAQhAAAIQgAAEIACB8hDAeJRHa3oKAQhAAAIQgAAEIAABawQwHtbQkxgCEIAABCAAAQhAAALlIYDxKI/W9BQCEIAABCAAAQhAAALWCGA8rKEnMQQgAAEIQAACEIAABMpDAONRHq3pKQQgAAEIQAACEIAABKwRwHhYQ09iCEAAAhCAAAQgAAEIlIcAxqM8WtNTCEAAAhCAAAQgAAEIWCOA8bCGnsQQgAAEIAABCEAAAhAoDwGMR3m0pqcQgAAEIAABCEAAAhCwRgDjYQ09iSEAAQhAAAIQgAAEIFAeAhiP8mhNTyEAAQhAAAIQgAAEIGCNAMbDGnoSQwACEIAABCAAAQhAoDwEMB7l0ZqeQgACEIAABCAAAQhAwBoBjIc19CSGAAQgAAEIQAACEIBAeQhgPMqjNT2FAAQgAAEIQAACEICANQIYD2voSQwBCEAAAhCAAAQgAIHyEMB4lEdregoBCEAAAhCAAAQgAAFrBDAe1tCTGAIQgAAEIAABCEAAAuUhgPEoj9b0FAIQgAAEIAABCEAAAtYIYDysoScxBCAAAQhAAAIQgAAEykMA41EerekpBCAAAQhAAAIQgAAErBHAeFhDT2IIQAACEIAABCAAAQiUhwDGozxa01MIQAACEIAABCAAAQhYI4DxsIaexBCAAAQgAAEIQAACECgPAYxHebSmpxCAAAQgAAEIQAACELBGAONhDT2JIQABCEAAAhCAAAQgUB4CGI/yaE1PIQABCEAAAhCAAAQgYI0AxsMaehJDAAIQgAAEIAABCECgPAQwHuXRmp5CAAIQgAAEIAABCEDAGgGMhzX0JIYABCAAAQhAAAIQgEB5CGA8yqM1PYUABCAAAQhAAAIQgIA1AhgPa+hJDAEIQAACEIAABCAAgfIQwHiUR2t6CgEIQAACEIAABCAAAWsEMB7W0JMYAhCAAAQgAAEIQAAC5SGA8SiP1vQUAhCAAAQgAAEIQAAC1ghgPKyhJzEEIAABCEAAAhCAAATKQwDjUR6t6SkEIAABCEAAAhCAAASsEcB4WENPYghAAAIQgAAEIAABCJSHAMajPFrTUwhAAAIQgAAEIAABCFgjgPGwhp7EEIAABCAAAQhAAAIQKA8BjEd5tKanEIAABCAAAQhAAAIQsEYA42ENPYkhAAEIQAACEIAABCBQHgIYj/JoTU8hAAEIQAACEIAABCBgjQDGwxp6EkMAAhCAAAQgAAEIQKA8BDAe5dGankIAAhCAAAQgAAEIQMAaAYyHBvTvHBrSEIUQPhAYHOgRqVTk+KlRH8qlRg0E0FwDRM9CoLlngmkoF801QPQwxJIFAx5W7XfJGA8N+mE8NED0JASDkydCaSwTzTXC9CQUmnsilMYy0VwjTI9CYTzMi4Xx0MAc46EBoichGJw8EUpjmWiuEaYnodDcE6E0lonmGmF6FArjYV4sjIcG5hgPDRA9CcHg5IlQGstEc40wPQmF5p4IpbFMNNcI06NQGA/zYmE8ROShHbvlq9/cM4X+l++5TW5YfXXw2pN7npMvbt0VPL/u2lXywIbbZKC/r94e42F+x7WVkcHJFnl7edHcHntbmdHcFnl7edHcHnubmTEe5uljPCaNh0J/97o10xR44aVXZfuO3fLYlrtk3pzBwKTE22I8zO+4tjIyONkiby8vmttjbyszmtsiby8vmttjbzMzxsM8fYxHC+OhjMaypYvrsx9xI6Ikw3iY33FtZWRwskXeXl40t8feVmY0t0XeXl40t8feZmaMh3n6GI+EpVbhMquh4RG5f9suWXX5JXXjse+td+S+zTvlwU1rZcV5SwLFMB7md1xbGRmcbJG3lxfN7bG3lRnNbZG3lxfN7bG3mdmE8VDL9fe++Mq0Zfo2+91O7iPHjsvtGx+W9evWyBWXrWwnRLANxiOGThmLdfdsl82b1sqvrFweGI8br7+mDnma8Xj2OhmZ90kZWfGHUu0ebFsINvSDwIyeLpGKyOnRCT8KpsqOCZRZ82q1KpVKpWOGvgUos+a+aaWrXjTXRdKvOIHh7PARHje+e/BQPdK5ixbIjq3rgx+obRmP8MfzxefMTzyVIGu3MR5ZiWVoHy6v+u3fWNV6xuM/1Qblas9cGTn/n8voij+Sau/cDNlo6hOBvt4u5ddlZHTcp7KptQMCZda8KhWpSLUDen5uWmbN/VSs86rRvHOGPkYYnNnbUdnhxYcef2TjlFkAtSz/W089G8xyfPs7e5nxiFBmxiNhl4ue19HyHI9f/o2c/v79MuPQd2oGpHu2nPjIOjn50btlondeRzs0G7tHgOl49zTJuyI0z5uwe/HR3D1N8q4IzfMm7Gb8TpZaRVfINFt6FM54/ONPfzJYqqQe0RmRkEx85uTzN6+uz1SE5xf//u/+ltz9pUenxPjBj16vX3n10ouX1y+GlHS6gNoweqVW9XeYJ2nmJnqFV2Y8NO3DCuSeZ/bK5274dBAxvpQq7VWtej/4vgy+9m+k//2/qBmQrplycuk/kxPL75aJvnM0VUsY2wQYnGwrYD4/mptnbjsjmttWwHx+NDfP3IWMnRgPdQC/+6ln6wf6jfoTHuhHjYT6UfvAe4fr533Ejz3jy6TUseitd26pmwSVK7wVRDyuek9dpTXJeMRrVm3+y9N/Lb9z3a/LOwffl2e++6J84feurx8Ph6ceKGOF8dC0x4bCPP3M3nrE+JRZlvt49J74kcx+/d/IwMH/U9kPqVb65dTSW+XE8ntkfMZiTVUTxhYBBidb5O3lRXN77G1lRnNb5O3lRXN77G1m7sR4xM1DM+MRP7k86Uft6BVUVaxom9ff+MWUWzvE31e3e4i/1j9jxpTTBdoxDtFVP+1sn8SEpVYa9vikq1r1nHxNBl9/UAYO/O8iMiHVrj45teT35MTyfyXjA0s1ZCWEDQIMTjao282J5nb528iO5jao282J5nb528rugvEIDUL0B/CQR7h0SofxULMq2x59Qjbfuza4L13SI5xZib4XzqhgPGztpQl5m11Ot3voTRnc9xWZ+c4TItUxkUqPnFpykxxfca+MDyxzqBeUkoYAg1MaSsVqg+bF0jNNb9A8DaVitUHzYumZtjedGI8sS62azXjEZyYaGYLozazjsxtpZjxaGQ81u7HnO9+rX41L5YjeNBvjkXavMtAuzX08uofeltn7t8rMd/43qUyMiFS6ZWjR78jx8++TsVkXGKiSFDoIMDjpoOhXDDT3Sy8d1aK5Dop+xUBzv/TSVW0nxqPZyeXRcyeSrmqV5vzhaB+Tbl7d6rUsS63C0w6it4/AeOjay3KIk8Z4hGm7Tx+QWfv/rcz6+dekMjEUXJp16JzPyokL7pXR2X8vh+oIqZMAg5NOmn7EQnM/dNJZJZrrpOlHLDT3QyfdVXZiPFQtSZfTDWcGPrLknIaX042bhnCJU/wqUl974tty+y2flR++ur/jczxCI/H8S69OufKVOrl89bWflC1//GcSvedH/IR2Zjx0730dxMtiPMI0XaPvy+z922XWz/6DVCZOBi8Pn71ajl/wRRkd/HgH1bBpngQYnPKk62ZsNHdTlzyrQvM86boZG83d1CXvqjo1Hqq+pMvQRq80lXQDwaTZimaXs201u5FmqVXIMrwaVvh3/ByOl3+8P3hLvR4+1FWyMB55740Z4rdjPM4YkGMy642HZdbb/166xj4IXj694Dfl+Pn/k4zMvTJDFTQ1QYDByQRlt3KguVt6mKgGzU1QdisHmrulh6lqdBgPU7UWJQ9XtdKgZCfGo25Axj6QWT97VGa9+cfSNXqkZkDmXy0nVtwb/MvDDQIMTm7oYLIKNDdJ241caO6GDiarQHOTtN3JhfEwrwXGQwNzHcYjLKMyflJm/exPZfYbj0jX6C+Dl0fmfFKOX7ApmAnhYZcAg5Nd/jayo7kN6nZzorld/jayo7kN6vZzYjzMa4Dx0MBcp/GoG5CJYZn186/KrP0PSffpd2sG5KzL5cT5m4JzQXjYIcDgZIe7zaxobpO+ndxoboe7zaxobpO+vdwYD/PsMR4amOdhPM4YkFGZ+YvHZfYb26V76GfBy6ODH5MTKzbK0KLPBFfF4mGOAIOTOdauZEJzV5QwVweam2PtSiY0d0UJs3VgPMzyVtkwHhqY52k86uVVx2TmO/9JZu/bJj1D+4KXx2atlOPKgCz+70UqXRp6QohWBBicWhEq3vtoXjxNW/UIzVsRKt77aF48TdP0COORhpLeNhgPDTyNGI+wzuqEzDzwLZm973+WnpOv1gzIzPPlxIp75NS5Nwc3JuSRHwEGp/zYuhoZzV1VJr+60Dw/tq5GRnNXlcm3LoxHvnyTomM8NDA3ajzq9VZl4OB/ldmvb5HeEy8Hr473L5MTK/6lnFryT6Xa1auhZ4SIE2BwKt8+geZoXj4C5esxn/Pyaa56jPEwrzvGQwNzO8bjTOH9v9wjs1/fLH0fvFgzIDM+JCeWr5dTS39fqpUZGnpIiJAAg1P59gU0R/PyEShfj/mcl09zjIcdzTEeGrjbNh5hF2a8/4wM7tssfUf/n5oB6VskJ5ffJSeXrpVq14CGnhKCwal8+wCao3n5CJSvx3zOy6c5xsOO5hgPDdxdMR51A3L4uzJ732aZcfjZ4KWJ3oVyctn/KCfO+wOpds/S0OPyhmBwKp/2aI7m5SNQvh7zOS+f5kU3Hi+89KrceucW+fI9t8kNq925ETXGQ8NnzTXjEXap94Pvy+BrX5b+9/9y0oDMlZPn/Qs5ed4fykTPWRp6Xr4QDE5oXj4C5esxn3M0Lx+Bcva4yOd4PLRjdyDqgfcOywMbbpOB/j4nRMZ4aJDBVeNRNyAnfiSDr/1r6X/v/xKRqlS7B+XER/5ATn70TpnonaeBQHlCcEBSHq3DnqI5mpePQPl6zOe8fJoXecbjyLHjsvnffUP+4JbPyNY/+aZsuOMmWXHeEidExnhokMF14xF2sefEqzL4+ldk4OCTagGWVLtmycmP/LPgRHS1HItHawIMTq0ZFa0FmhdN0db9QfPWjIrWAs2Lpmi6/uiY8XjzzaOi/jf9WLZsrqj/kx5qmdV3v/d3cve6NaJmPpYtXezMciuMh4Y9xRfjUTcgp/YF54DMfHe3SHUsOPH85Id/X04u/5cyPmOxBiLFDcHgVFxtG/UMzdG8fATK12M+5+XTXNeMx5e+9Kw88MBfGwd4//2/Ll/60jWJeZXZ+NRVH5MrLlspyoRs37FbHttyl8ybM2i8znhCjIcGCXwzHmGXu4feltn7tsjMd78hlYmR4NK7pz70T+XEin8l4/0f0kCmeCEYnIqnaaseoXkrQsV7H82Lp2mrHqF5K0LFfF/HjMfjj78kX//6D4wDuuWWj8utt142Le++t96RbY8+IZvvXRsYDbXs6vaND8v6dWsCI2L7gfHQoICvxqNuQE4fkNn7t8rMtx+XSnVYqpVeGTr3Zjl+/kYZH1imgVBxQjA4FUfLtD1B87SkitMOzYujZdqeoHlaUsVqp8N4uEbkyT3PyRe37ppW1udvXh0svbL9wHhoUMB34xEi6Bp5T2bvf1hmvf0fpDJxUqTSLacW3ygnzr9Pxmau0EDK/xAMTv5rmLUHaJ6VmP/t0dx/DbP2AM2zEitG+6IZj6HhEbl/2y5ZdfklU87piM+C2FQP46GBflGMR92AjB6RWW8+LLPf2iGV8eMi0iVDi/47Oa4MyGz703QaJGs7BINT2+i83RDNvZWu7cLRvG103m6I5t5K11HhRTMeymDct3mnPLhp7ZSrWIWG5Mbrr7G+3Arj0dEuW9u4aMajbkDGPpBZb/2vwf9do+qKDRUZPue6wICMDn5cAzn/QjA4+adZpxWjeacE/dsezf3TrNOK0bxTgn5uXzTj4YMKGA8NKhXVeIRoKuMnZfZbfyKz3lQG5P3g5aFFvyOnPvIFGRtYJuMDSzVQ9CMEg5MfOumsEs110vQjFpr7oZPOKtFcJ01/YmE8zGuF8dDAvOjGo25AJoaC8z9m7/u30jWIoi19AAAgAElEQVT6yzo5dQ+QkblXyci8X5PROb8qI3N/NbhEbxEfDE5FVLV5n9AczctHoHw95nNePs1VjzEe5nXHeGhgXhbjEUU1cPDPpffoXuk7+oL0Hvt+cDWs6EMtxRqZe6WMzvmEjM65QkZnX6KBtP0QDE72NTBdAZqbJm4/H5rb18B0BWhumrgb+TAe5nXAeGhgXkbjMQVbdUx6j78sfUefl96j3wvMSM/QvqlNugdlZM7lMqJMyNwrZWTuJ2Wib74G+mZDMDiZ5e1CNjR3QQWzNaC5Wd4uZENzF1QwXwPGwzxzjIcG5qU3HgkMu0YOS9+x70nvke9J37Hnpe/Y30pl/MSUluMD58nIWVfI6Lwra4bkrL8v1a4+DYrkF4LBKT+2rkZGc1eVya8uNM+PrauR0dxVZfKtC+ORL9+k6FaNR3g3xZd/vH9abZdevNyZ27u3kgXj0YqQiFQnpPfkq9J39IwZ6Tn5E/VGfWN148KxwUsnl2ipWZFflbGZ56cIbq4Jg5M51q5kQnNXlDBXB5qbY+1KJjR3RQmzdWA8zPJW2awaj4d27A567MKdFDtBj/Foj15l7Lj0HXshmBHpPbxX+j54QbpGj0wJNtE778ysiFqiNecqqfYMtpdQw1YMThogehYCzT0TTEO5aK4Bomch0NwzwTSVi/HQBDJDGGvGQ812bPrKTtlwx01TbnKSoXbtTcMbrKjAD2y4TQb6a8t+orefv+7aVVPeU+9jPPRJ0XPqtdoJ68G5Is9L74kfilTHIwkqwSyImg0ZnXOVjMy9QkYHPxbcZd3Eg8HJBGW3cqC5W3qYqAbNTVB2Kweau6WHqWowHqZIn8mD8ZhkEZqOp5/ZK1Fz8cJLr8r2Hbvry76SZmkwHvntuJWJU9J37MW6Gek9+rx0jxycklBdund08LKaCZl3hYycdWVu9xZhcMpPa1cjo7mryuRXF5rnx9bVyGjuqjL51oXxyJdvUnRrxkMVow7ily1dLDesvtp8z2MZw1rUy3tffKU+qxGvMW5EmPEwL1330M8mT1xXJ60/L73HfyCViZEphYz3LZJRZUTmqHNF1BKty6XaPavjYhmcOkboXQA0906yjgtG844RehcAzb2TTEvBRTQe6jj11ju3TOHz+ZtXO3Nag1Xjse+td+QbT/6VbLj9pvqyJi17UsYg0VkMtawqNB4qzP3bdsmqyy+pmyNV832bd8qDm9bWl4gx45ERuObmlepp6T32g5oJmbyKVvfw27EsXTI6e6WMzLlSxsKraM26WKTSlakaBqdMuArRGM0LIWOmTqB5JlyFaIzmhZAxcyeKajyiK3XCCzmtX7dGrrhsZWZGujewZjyaXdFKddLUVa2U0Xjz7QN1J5hkPG68/pq6WEnGQ7coxNNAYPiAyC//X5H394ocUv//rcj4qamBe2aLLLhCZMFVIgtXiZz9ayIzztaQnBAQKAaBkbEJ6evJZs6L0XN6AQEIQMBPAvGVOeGpBNEf0W32zJrxsNnpaG412/HVb+6ZVo46z2Pjv/g92fLHf8aMhytidVJHdfzMTQ6PTd7k8NTr0yKO9y+t3VMknBWZ8wmpVmbU2/GrWCci+LktmvupWydVo3kn9PzcFs391K3TqrXMeJx8U+TEm52Wkn372ctEZi2btl3ceLh2MafSG4+4YtEZD3VVK87xyP5Z8GULdene4L4i6gpa6iaHR9VNDo9PLb/SI6Pq3iKTd1zvXfxJmZh9oRw/NepLN6mzQwIckHQI0MPN0dxD0TosGc07BOjp5lqMx8tfEnn5AfMELr1f5NIvJRqP+Dke5y5aIDu2rnfiKrLWjUfSSTCPP7LR2jq0uPHgqlbmP0s2M/ae+NHkTQ6fl94P/lZ6T7wyfVZk7uUyVpkpUqnIRO/ZMj5jsUz0L5GJGYtlvH9J7e++xTLRO8dmV8itiQAHJJpAehQGzT0SS1OpaK4JpGdhtBiP/Y+L7P+6+Z4vv0Vk+a0tZzxUg6QLI5kvuJbRqvFIAqHOoVh3z3a545bPWLnaVdx4KEjcx8PW7mk/b+0mh39bP3F9xrEXpDJ6KFVh1a6ZNRMy41wZD/5fLBMDSwJTMt5fe02ZlYmes1LFo5EdAhyQ2OFuMyua26RvJzea2+FuO6sW42G7E7H8ScfWLi23smY8wpNdoiduh+wUtG899ey0G/U5pm29HK5q5aoy+utSg1Nl7JicOvK2dJ8+IN2n3w3+rwzX/lWvdU3+W5kYSlUABiUVJmuNOCCxht5aYjS3ht5aYjS3ht5q4rIYD2Y8RKSZ+1KzHtsefUI237tW5s0ZtLpTpkmO8UhDqRhtsgxOXaPH6iZEmZIuZUqG36kbFgyKH/tEFs396BFVtiKA5q0IFe99NC+epml6VFTjET/Hw9SVYtMwZ8YjDaUWbTAeGiB6EiKPwSkwKCMHpDuYNanNmEw1KLWZFWZQ7OwkeWhupydkTUsAzdOSKk47NC+Olll6UkTjkaX/NtpaMx6qs+rcid1PPSuPbbmrPrNh+xyPdkTAeLRDzc9tbA5OXWMf1GZQphiUpCVesfuVNEDNEq90+6BNzdNVSCvdBNBcN1H346G5+xrlUSHGIw+qzWNaNR6qNNeuatWOBBiPdqj5uY0Pg1PjJV7KpByUrtO15V7pZ1AGghPhR8/6hIzNvnC6cF09Uu2eKdXuWVLtmiUTPbOk2j0o1Z7+4O9q8PcsmVDvd8/2TngfNPcOquMFo7njAuVQHprnANWDkBgP8yJZNx7mu6w/I8ZDP1NXIxZpcKov8VInyQ+rc1A6W+KVVrNq10DNqPSEZqRmTGrmZXbwb2BSegZFetRrNVMzUX//TNuJ4P3Jv7tmpi0hU7siaZ6p4yVujOblEx/Ny6e56jHGw7zuGA8NzDEeGiB6EqKMg1N9idfIe6IuL1wZPymV8VPSFfx7UmTslFTGTgTPw9fCNpXxE9I1rt6vbVOZSLcMrN3dYYpxCczLWVLtnhGZcQlNzmyRwPjUDFDNvNQMTDgzExqeWWedHdyzhZtGtquKf9uV8XPun0p6K0ZzvTx9iYbxMK8UxkMDc4yHBoiehGBw6lwoZUZqxqX2b2BKJoalos5hUX9PGhr1nowdjxiXmtGpjA9Nbju5vTI8o0c6L6xJhPEF/0DGJiqd56hURCrdUpUeka6e2vNKj4h01553dYtIT+21SnfQphq8p/7uqr3e1Vt/T21XndZOxVExVRwVQ8WczFNvq+Kp97sm34/kDF6frCf4N2wbPq/lVEatqA8+50VVtnG/0Lx8mjPjYUdz48ZDXUb39o0Py+//7m/J1/7zX8jLP96f2HOXLv3VShqMRytCxXmfwcltLdXszBnjEhqVU9IVzLic+Ts6cxO+XmszJDVjdKa9iskjHQG1jK5moGpmaqqBmjRTgfGqmaq68YqYnemvhe1qZqhmmKLbhqZt0sCFxkwZL2W6ouZOGTkVY9L4BcZr0vgFNU+awpkDMwKjd+r0uLrPrlRFGUZlPCf/rUaeq9dUm/D9aNv486BdVy1O8J7iOjVWPVc8Ryx+0C4aX7VPahO8Npkn8n61qz+dqCVpxXd7SYSOdZMZD/O6GzceYReb3ceDGwia3xHImI4Ag1M6TkVqFdU8WCpWnZDKxJiIjEulOiainlfHpSK1f2VCPR8XqY7V2qnXZEwqk++deT752uR2lYlauyBWEDeMqV47k1MmRmsxVXzVLvpemDPMX52o1RepNaztzHaTdUzJORGJP1lPPafKPZ764gRF2hfoi14C1UrE/NQNUmjGwlyRmcYpbaK1nGlTM4CxbVPErgSGUKRarU6aweb5a8avVY0Z2zSqMzChMmluE3JGa2nY12i5DeqKxEnkWCsi0u2M/UusM6Jdqn40yB+tK0Wc8IeCGb/9nN6dmmgtCThpPLiBYEvdaGCJAMbDEniLadE8HXy1XK5mhqabnbrxUSYpMEsR46RMUWDQqiLV0dj7tXaBSQr+jZik0KAF/4btlPGrGbMzeSYNnDJ2avuo0ZtiCieNnIxLj0yIVCZkfGxCHWnValP/ViLPJ19X8yFT2kTbq+0q1RqTKe2CI7gzcdWcymTbKa+HeSNtg3zR18O40Tb194Mj6Sm5K9XhdILSCgJlIPA/qM8HD5MEnDQe6v4ee198RR7YcJsM9PeZ5NFWLpZatYXNy404CPVSto6KRvOO8Hm5MZrrky0wpPVH9CAv8jwwR+GjwYFgpE3N7E0+Gm7boI0yj/Fc1arM7ldL7URODI3W3+0oT5oao7U06l+aOGGbKehas57Sv2ieRs+zsm4QJzDZzfaJRu834FUz9dP3h4b9izRfcMF/q29nJ1IqAsaNR3iDwHcPHmpY4LmLFsiOretlxXlLUnXCdiOMh20FzOXngMQca1cyobkrSpirA83NsXYlE5q7ooTZOjjHwyxvlc248Qi72OwcD/MYOsuI8eiMn09bMzj5pJaeWtFcD0efoqC5T2rpqRXN9XD0LQrGw7xi1oyH+a7mlxHjkR9b1yIzOLmmSP71oHn+jF3LgOauKZJ/PWieP2MXM2A8zKuC8dDAHOOhAaInIRicPBFKY5lorhGmJ6HQ3BOhNJaJ5hphehQK42FeLKvGo9n5HtzHw/zOQMbWBBicWjMqWgs0L5qirfuD5q0ZFa0FmhdN0XT9wXik46SzlTXjMTQ8Ivdv2yWrLr9EPv73zpdvPPlXsuH2m4KrWD20Y7d86qqPyRWXrdTZ19xiMeORG1rnAjM4OSdJ7gWhee6InUuA5s5JkntBaJ47YicTYDzMy2LNeERPLlfd3vboE7L53rUyb86gcANB8zsCGdMRYHBKx6lIrdC8SGqm6wuap+NUpFZoXiQ10/cF45Gela6WThiP+XMHZfO/+4Zs+qPPBcaDGwjqkpc4ugkwOOkm6n48NHdfI90Vorluou7HQ3P3NcqjQoxHHlSbx7RmPKJLrW5YfXWwvGrZ0sWinnMDQfM7AhnTEWBwSsepSK3QvEhqpusLmqfjVKRWaF4kNdP3BeORnpWultaMR7wDaunV7Rsflpd/vF+4gaAueYmjmwCDk26i7sdDc/c10l0hmusm6n48NHdfozwqxHjkQdXRGQ/zXc0vIyeX58fWtcgMTq4pkn89aJ4/Y9cyoLlriuRfD5rnz9jFDBgP86pYm/HgzuXmxSZj5wQYnDpn6FsENPdNsc7rRfPOGfoWAc19U0xPvRgPPRyzRMF4ZKHVoC0zHhogehKCwckToTSWieYaYXoSCs09EUpjmWiuEaZHoTAe5sWyZjxUV327X0cjeTAe5ndcWxkZnGyRt5cXze2xt5UZzW2Rt5cXze2xt5kZ42GevlXjoS6bG71xoPnu68mI8dDD0YcoDE4+qKS3RjTXy9OHaGjug0p6a0RzvTx9iYbxMK+UNeMRvYpVUrcvvXi5PLblruC+Hq4/MB6uK6SvPgYnfSx9iYTmviilr04018fSl0ho7otSeuvEeOjlmSaaNeORpjhf2mA8fFGq8zoZnDpn6FsENPdNsc7rRfPOGfoWAc19U0xPvRgPPRyzRLFmPJpd1eqFl16Vbz31rDyw4TYZ6O/L0h8rbTEeVrBbScrgZAW71aRobhW/leRobgW71aRobhW/teQYD/PonTQe6tyPbY8+IZvvXctSK/P7BBmbEGBwKt/ugeZoXj4C5esxn/Pyaa56jPEwr7uTxuPJPc/J3hdfMTbjoa6u9dVv7qnTf/yRjXLFZSvrf6t6vrh1V/D3ddeumlYXMx7md1xbGRmcbJG3lxfN7bG3lRnNbZG3lxfN7bG3mRnjYZ6+ceOhZjPW3bNd3j14qGFvz120QHZsXS8rzluSOxG15OtrT3xbbr/ls8GyLlXffZt3yoOb1gb51bKv7Tt21090VyZFPe5et6ZeG8Yjd5mcScDg5IwUxgpBc2OonUmE5s5IYawQNDeG2qlEGA/zchg3HmEXXb1zeXi1rfXr1gSzHspoLFu6WG5YfXVQetyIqNcwHuZ3XFsZGZxskbeXF83tsbeVGc1tkbeXF83tsbeZGeNhnr4142G+q+kyKmOxafPOYMZlyaKFcv+2XbLq8kvqxiM+I4LxSMe1KK0YnIqiZPp+oHl6VkVpieZFUTJ9P9A8PasitcR4mFcT4zHJPLoELDzHY2h4JDAeN15/Tf2cjyTjcXxozLxyZLRCYEZPl0hF5PTohJX8JDVPoMyaV6tVqVQq5qFbzlhmzS2jt5Yeza2ht5o4MJw8jBKwajya3UTQ1g0Eo0utfmXl8lQzHsdPjRoVjWT2CPT1dolyHiOj4/aKILNRAmXWvCoVqUjVKG8XkpVZcxf426gBzW1Qt59zcGav/SJKVoFV45F0orYL/KPndXCOhwuKuFMD0/HuaGGqEjQ3RdqdPGjujhamKkFzU6TdysNSK/N6WDMerpxcrpZOPfPdF+ULv3d9QD9ccrV509pgeRVXtTK/U7qckcHJZXXyqQ3N8+HqclQ0d1mdfGpD83y4uh4V42FeodIbj/A8jqef2Vunz308zO+IvmRkcPJFKX11ork+lr5EQnNflNJXJ5rrY+lTJIyHebWsGQ/V1fgyJvPd15ORy+nq4ehDFAYnH1TSWyOa6+XpQzQ090ElvTWiuV6evkTDeJhXyqrxUMuavvHkX8mG228Kbt7n6wPj4aty2etmcMrOzPct0Nx3BbPXj+bZmfm+BZr7rmB79WM82uPWyVbWjEezK1qpDtm6qlU7MDEe7VDzcxsGJz9166RqNO+Enp/bormfunVSNZp3Qs/fbTEe5rWzZjzMdzW/jBiP/Ni6FpnByTVF8q8HzfNn7FoGNHdNkfzrQfP8GbuYAeNhXhWMhwbmGA8NED0JweDkiVAay0RzjTA9CYXmngilsUw01wjTo1AYD/NiWTUe0StKnbtogezYul6WLFo47aZ95rFky4jxyMbL59YMTj6r117taN4eN5+3QnOf1WuvdjRvj5vvW2E8zCto1XiEV7X67d9YJdsee0I+d8NvyorzlgT3zvjWU8/KAxtu8+Kkc4yH+R3XVkYGJ1vk7eVFc3vsbWVGc1vk7eVFc3vsbWbGeJinb814RG8gqGY5osZDXe1q26NPyOZ718q8OYPmqWTMiPHICMzj5gxOHovXZulo3iY4jzdDc4/Fa7N0NG8TnOebYTzMC+ik8WDGw/yOQMZ0BBic0nEqUis0L5Ka6fqC5uk4FakVmhdJzfR9wXikZ6WrpTXjoTrw5J7nZO+Lr8imP/qc/PGu/yNYajV/7qDcvvFhWXP9NXLD6qt19TPXOMx45IrXqeAMTk7JYaQYNDeC2akkaO6UHEaKQXMjmJ1LgvEwL4lV46G6q2Y3br1zy5SeP/7IRrnispXmabSZEePRJjgPN2Nw8lC0DktG8w4Berg5mnsoWoclo3mHAD3dHONhXjjrxsN8l/VnxHjoZ+pqRAYnV5XJry40z4+tq5HR3FVl8qsLzfNj63JkjId5dawaD3VVqwPvHZ5y9arwErurLr+EpVbm9wcytiDA4FS+XQTN0bx8BMrXYz7n5dNc9RjjYV53a8YjNBg3Xn/NtGVVnFxufkcgYzoCDE7pOBWpFZoXSc10fUHzdJyK1ArNi6Rm+r5gPNKz0tXSmvGIXk5X3bsj+uByurrkJY5uAgxOuom6Hw/N3ddId4Vorpuo+/HQ3H2N8qgQ45EH1eYxrRkPZjzMi03GzgkwOHXO0LcIaO6bYp3Xi+adM/QtApr7ppieejEeejhmiWLNeKgi1ZKqTZt3yo6t64M7lquHmu1Yd892ueOWz3CORxYlaWuEAIOTEcxOJUFzp+QwUgyaG8HsVBI0d0oOY8VgPIyhrieyajyiRuPdg4fqRXE5XfM7AhnTEWBwSsepSK3QvEhqpusLmqfjVKRWaF4kNdP3BeORnpWultaNh66O2IzD5XRt0jebm8HJLG8XsqG5CyqYrQHNzfJ2IRuau6CC+RowHuaZYzw0MMd4aIDoSQgGJ0+E0lgmmmuE6UkoNPdEKI1lorlGmB6FwniYF8uq8VBXtrp948Py8o/3T+v5pRcvl8e23CXz5gyap5IxI8YjIzCPmzM4eSxem6WjeZvgPN4MzT0Wr83S0bxNcJ5vhvEwL6BV46FuIKged69bY77nGjNiPDTCdDwUg5PjAuVQHprnANXxkGjuuEA5lIfmOUD1ICTGw7xI1oxHs/t4mMfQWUaMR2f8fNqawckntfTUiuZ6OPoUBc19UktPrWiuh6NvUTAe5hXDeGhgjvHQANGTEAxOngilsUw01wjTk1Bo7olQGstEc40wPQqF8TAvljXjobqqllotW7rYm/t1NJIH42F+x7WVkcHJFnl7edHcHntbmdHcFnl7edHcHnubmTEe5ulbNR7qZoHfePKvZMPtN8lAf5/53mvKiPHQBNKDMAxOHoikuUQ01wzUg3Bo7oFImktEc81APQmH8TAvlDXj0eyKVgoDV7UyvzOQsTUBBqfWjIrWAs2Lpmjr/qB5a0ZFa4HmRVM0XX8wHuk46WxlzXjo7ITtWMx42FbAXH4GJ3OsXcmE5q4oYa4ONDfH2pVMaO6KEmbrwHiY5a2yYTw0MMd4aIDoSQgGJ0+E0lgmmmuE6UkoNPdEKI1lorlGmB6FwniYF8u68XjhpVfl1ju3TOn5449slCsuW2meRpsZMR5tgvNwMwYnD0XrsGQ07xCgh5ujuYeidVgymncI0NPNMR7mhbNqPJTp2L5j95Q7lKsTztfds13uuOUz3lztCuNhfse1lZHByRZ5e3nR3B57W5nR3BZ5e3nR3B57m5kxHubpWzMeQ8Mjcv+2XXLj9ddMm91QhuRbTz0rD2y4zYurXWE8zO+4tjIyONkiby8vmttjbyszmtsiby8vmttjbzMzxsM8fWvGo9mdy9Wsx7ZHn5DN966VeXMGc6USGqCnn9lbzxNf6vXknufki1t3Be9fd+2qaYYI45GrRE4FZ3BySg4jxaC5EcxOJUFzp+QwUgyaG8HsXBKMh3lJrBkPV2Y8lAH62hPflttv+Wwwu6JmWzZt3ik7tq6XFectCf6OLgdTNz1Uj7vXramrhfEwv+PaysjgZIu8vbxobo+9rcxobou8vbxobo+9zcwYD/P0rRkP1VU1k7D7qWedOscjvL/I+nVrgiVg8burJ52XgvEwv+PaysjgZIu8vbxobo+9rcxobou8vbxobo+9zcwYD/P0rRoP1V3Xrmqllnndt3mnPLhprSxZtDA4D2XV5ZfUT3SPvq9mRNQD42F+x7WVkcHJFnl7edHcHntbmdHcFnl7edHcHnubmTEe5ulbNx7mu9w4Y7j8KzQaScvBkoyHS32gFghAAAK6CIyMTUhfT5eucMSBAAQgAIGSE7BqPNQypgPvHZ5ysnb84N+UPmHexefMr5+/kVQLMx6mFHEzD7+KualLnlWheZ503YyN5m7qkmdVaJ4nXXdjM+NhXhtrxsOVk8sV8iTTEUrBOR7md0qXMzI4uaxOPrWheT5cXY6K5i6rk09taJ4PV9ejYjzMK2TNeLh2Od3oeRxRGbiqlfmd0uWMDE4uq5NPbWieD1eXo6K5y+rkUxua58PV9agYD/MKWTMersx4hHdKf/fgoSn0P3/z6vqSK+7jYX7HdDUjg5OryuRXF5rnx9bVyGjuqjL51YXm+bF1OTLGw7w61oyH6mr8nhnqtdAI3HHLZ+pXkjKPJVtGrmqVjZfPrRmcfFavvdrRvD1uPm+F5j6r117taN4eN9+3wniYV9Cq8YgajeiMQ/zO4eaxZMuI8cjGy+fWDE4+q9de7WjeHjeft0Jzn9Vrr3Y0b4+b71thPMwraN14mO+y/owYD/1MXY3I4OSqMvnVheb5sXU1Mpq7qkx+daF5fmxdjozxMK8OxkMDc4yHBoiehGBw8kQojWWiuUaYnoRCc0+E0lgmmmuE6VEojId5sTAeGphjPDRA9CQEg5MnQmksE801wvQkFJp7IpTGMtFcI0yPQmE8zIuF8dDAHOOhAaInIRicPBFKY5lorhGmJ6HQ3BOhNJaJ5hphehQK42FeLIyHBuYYDw0QPQnB4OSJUBrLRHONMD0JheaeCKWxTDTXCNOjUBgP82JhPDQwx3hogOhJCAYnT4TSWCaaa4TpSSg090QojWWiuUaYHoXCeJgXC+OhgTnGQwNET0IwOHkilMYy0VwjTE9CobknQmksE801wvQoFMbDvFgYDw3MMR4aIHoSgsHJE6E0lonmGmF6EgrNPRFKY5lorhGmR6EwHubFwnhoYI7x0ADRkxAMTp4IpbFMNNcI05NQaO6JUBrLRHONMD0KhfEwLxbGQwNzjIcGiJ6EYHDyRCiNZaK5RpiehEJzT4TSWCaaa4TpUSiMh3mxMB4amGM8NED0JASDkydCaSwTzTXC9CQUmnsilMYy0VwjTI9CYTzMi4Xx0MAc46EBoichGJw8EUpjmWiuEaYnodDcE6E0lonmGmF6FArjYV4sjIcG5hgPDRA9CcHg5IlQGstEc40wPQmF5p4IpbFMNNcI06NQGA/zYmE8NDDHeGiA6EkIBidPhNJYJpprhOlJKDT3RCiNZaK5RpgehcJ4mBcL46GBOcZDA0RPQjA4eSKUxjLRXCPMnEKdPj0m1WoteLVajT2vBK/V3qy9X2sXe67enHx91oxukYrI8VNjtYZJ7WOvn0lxJr/atlldSfVOllHrxySvsE8Na8/Yv2icqf2rJZyYqNUdzRvUMtmfKa/H2oWMg+3Vf/E4wd9ntJjyfqx9o3y1+ib5NKwponG0hgY19XarDlZkZHQ8p72UsK4R6Orukm2br3WtrMLXg/HQIDHGQwNET0JwENq5UENDozI2VpWx0QkZG5+Q8bEJGRubkPFx9W+19nfwvPbe6Ni4jKv29TbR9qpNtR5ndErMM7HGx8ZFvRfmULHGxsbrOWp11HLEa6qOi0xUa+9FD0CTDjTjB71TDiIbHhhHDl9FPwMAABY8SURBVJgjB5qND5LPHEjHD57rB5GTB+BZDpgbHiRPHqi1PEiuVib5TD/YVsaABwQgAAHXCFSr97tWUuHrwXhokBjjoQGiJyF8MB4nToyKOtA7PTxW+/f0uAwP1V4bHh6ffG1MhofOPD89PC7DwfujMjwUbqdi1NoMB7HGG5qF0BSMjiqTED14rwbb8oCAKQIzZvRIpeaBpFKpxJ7X3J96Xc1oJLdRb6ntVIMz7cOYKmCw+eQLqZ7XEk3ma7RtdXrMaI2TAKf3KbkfzfoXlBP0cWot0b5VKrV6wjb1fyf7Mu31yVj1mNG/I7mmbhcU0jBPva9JdVREurpqOgWYGrSp5Tujeb1PsZr61SwXMx6mPqbO5Nm+9dPO1FKWQjAeGpTGeGiA6EmItMbj+AcjwYF87eB/PDigD5+HB/LhwXzdIKiDf3XgH7StGYGagVCv156PBLHGaiYhZhBOnRr1gqI6MOzp6ZLunor0dHdJT29X8Ld63q3+7alIt3o9aBN9ryK9vd1T3wvaVWrt6tt3BW16eyM51Pu93dNyBPEmt43WFOZV/541szeodeh0bQlGcPzY6CBy8miv0cFoeJAVxokfvE45YI4caDY+iJx+YBw9MA0PxhodaDY6eNbTvzMHrvEDfLUPuPxI+zl3uQ/Ulo0AmmfjVZTWnONhXkmMhwbmGA8NEB0J8e47x+Xw4SE5cnhYDh8+JUcOD8nRo8Py/i9PyZEjp+SDo8OiZhTUQX4jg2C7KwMDvTKjv1vUwV1/f0/wvH9GT/B38Ly/t/48bNMftlfbzqhtO6O/tn2wrYozoyc4AO+dZgimHvyHhqG3Rx3UV2TmzF7bSDrKzwFJR/i83BjNvZSto6LRvCN83m6M8TAvHcZDA3OMhwaImkOcPDlSNxDHlHF4XxmHITly6FTw+uFDQ8Hf4b/KaKhzD3Q9Zs3qqx3ATx68n3muDuy7ph38BwZgoFsGBvpkRp/aLjQOZ0yEijXQ3y19faqtMgJnDILafnCwT1f5xIkQ4ICkfLsDmqN5+QiUs8cYD/O6Yzw0MMd4aIDYJMQHx07XTIMyDLHZiEOH1KzEcDAbUTMRw3LwwIm2Czr7nFkyb36/zJ8/U+bNH5D58wdkwYIBmTtPPZ8pSxbPkrPm9MtERSZnAqIH/92iDAePYhHgILRYeqbpDZqnoVSsNmheLD3T9gbjkZaUvnYYDw0sMR7pIKor8KjZh+hMQ81IDEnNQNSMQ81AnJIj6t+jw8EJzVkfagZg/oIBmTevf/LfmfW/FyycKfPmKWPRH5iLmsGYKbNnt14SxOCUVQn/26O5/xpm7QGaZyXmf3s091/DdnqA8WiHWmfbYDw64xdsXUbjoa6jHjUJ4WxDMCtx6OTkORLhLEVtVkKdK6G2y/pQ5wjUTMTAmX+VYVgwM5iRiM5QhEZDneeQx4PBKQ+qbsdEc7f1yaM6NM+Dqtsx0dxtffKqDuORF9nGcTEeGpgX2XgcPz4ir//0kLz22iF57Sfvy2vq+U8Py9s/Oyrj49lNxOBZffXZhpppqM02KGMR/TuYjZhXW+bU2xfc2cmJB4OTEzIYLQLNjeJ2IhmaOyGD0SLQ3ChuZ5JhPMxLgfHQwLwIxuO9gyfl9dcOy09/8r7se+2Q/GTSZKjXGz3mzJ0RmIiFC2dK8HzSRCxYMLmMSRmHhQMyd25tpkKdP+H7g8HJdwWz14/m2Zn5vgWa+65g9vrRPDuzImyB8TCvIsZDA3NfjIc6x0LNVKgZi2DmQpkLNZPx00OiTuCOP9Ssw4UXLpQLLlogF61cKBdcuFAuvGiBLFo8WwM1P0MwOPmpWydVo3kn9PzcFs391K2TqtG8E3r+bovxMK8dxkMDc9eMx+jIuLyx/6j89KeTS6N+oszF+7J/35HEu0ifffbMwFxceJEyFrX/1d9qJoPHVAIMTuXbI9AczctHoHw95nNePs1VjzEe5nXHeGhgbst4qHtVvD45e6FMRnAuxk8Py1tvHkk8/2LxubODGQs1cxHMYKiZjIvODpZJ8UhHgMEpHacitULzIqmZri9ono5TkVqheZHUTN8XjEd6VrpaYjw0kMzbeKib39VMxSH56U8OyeuvqZmMw6Lush1/VCoiH/rwWXLBhZMzGCsXyoXq+cqzU10uVgOOQodgcCq0vImdQ3M0Lx+B8vWYz3n5NGfGw47mGI8I94d27JZlSxfLDauvnqLGk3ueky9u3RW8dt21q+SBDbfJQP+ZG8XpMB7q/Iuf//zY5AzG+zWDMXk1qaNHhqftHV1dFVn6kTm1GYzJmYvacqkFktelZO3som5lZXBySw8T1aC5Ccpu5UBzt/QwUQ2am6DsXg5mPMxrgvEQkaix+PI9t00xHi+89Kps37FbHttyl8ybMyjKnKjH3evW1NXKYjzUzfD27z8y7RK1+14/IkNDo9P2gJ6eLjlv2Ry5QJ17MTlzUVsutUD6HLrMrPld105GBic73G1mRXOb9O3kRnM73G1mRXOb9O3lxniYZ4/xaDHjEZ8FiRsRtXmS8Th1ajS4PK2atVCXqA3vg/HWm8dkbGz6nbjVvSo+unxucBUpZSwuDJZILZQV58+Xnt4u83sGGRMJMDiVb8dAczQvH4Hy9ZjPefk0Vz3GeJjXHePRxHgMDY/I/dt2yarLL6nPgux76x25b/NOeXDTWllx3hJR519893u/mDQYanmUMhmH5Rc//yBRzRkzemTF+fNqV4+aPP9CzWacf8F88+qTMTMBBqfMyLzfAM29lzBzB9A8MzLvN0Bz7yVsqwMYj7awdbQRxiOF8bjx+mvkistWBi3jxqNSeSBRgJmzeuWiixbKypULZeXF6ipSZwfPl310rqjzM3j4SWBGT5dIReT06PRZKz97RNWtCJRZ82q1KhV1xYqSPcqsecmkrncXzcupfGA4eRglgPFIYTyazXgsX/6/yMKzZ00ajJq5UP9/eOlZUsLx2ujOayNZX7DsrSIjo+M20pPTAoEya16VilSkaoG63ZRl1twueXvZ0dwee5uZB2f22kxfytwYjybGQ73V7jkepdybStBppuNLIHKsi2iO5uUjUL4e8zkvn+aqxyy1Mq87xqOF8dB9VSvzEpNRJwEGJ500/YiF5n7opLNKNNdJ049YaO6HTrqrxHjoJto6HsYjdjldhezcRQtkx9b1wcnj6mHiPh6tpaKFCwQYnFxQwWwNaG6WtwvZ0NwFFczWgOZmebuSDeNhXgmMhwbmWe7joSEdISwSYHCyCN9SajS3BN5iWjS3CN9SajS3BN5yWoyHeQEwHhqYYzw0QPQkBIOTJ0JpLBPNNcL0JBSaeyKUxjLRXCNMj0JhPMyLhfHQwBzjoQGiJyEYnDwRSmOZaK4Rpieh0NwToTSWieYaYXoUCuNhXiyMhwbmGA8NED0JweDkiVAay0RzjTA9CYXmngilsUw01wjTo1AYD/NiYTw0MMd4aIDoSQgGJ0+E0lgmmmuE6UkoNPdEKI1lorlGmB6FwniYFwvjYZ45GSEAAQhAAAIQgAAEIFA6AhiP0klOhyEAAQhAAAIQgAAEIGCeAMbDPHMyQgACEIAABCAAAQhAoHQEMB6lk5wOQwACEIAABCAAAQhAwDwBjEebzFvdzbzNsGzmAIF2tN331juy7dEnZPO9a2XenEEHekEJWQhk0fyFl16VW+/cUg9/3bWr5IENt8lAf1+WlLS1TCCL5urzve6e7fLuwUNB1WhuWbw202fRPJoi/Mw//shGueKylW1mZzMbBLJoHv+cq3ovvXi5PLblLsZ1jeJhPNqAqb6Etu/YXd8ZH9qxO4hy97o1bURjE5cIZNX2yLHjcvvGh+XlH+/nC8olITPUklVzNZAtXXJOcAAyNDwi92/bJYvPmc/nPwNz20070VzVzne+bQWz58+qeZgh+kMDxiM7d5tbZNVcGY/7Nu+UBzetlRXnLbFZeqFzYzzakFcNOsuWLpYbVl8dbB3fudsIySaOEGhXW2Y8HBGwjTLa1TxMpYzI3hdfYdajDfa2NkFzW+Tt5W1H8/B7/Z4/vFnu3bxT1q9bw4yHPQkzZ86qOcYjM+K2NsB4ZMQW/sK56vJL6saDnTUjREebd6ItxsNRUVuU1YnmYWh+/fZL+041Z5bLL71Vte1oHh3X588dDGa2MR7+aN+u5tEllSyzykdvjEdGruHOfOP119R/+cB4ZIToaPNOtMV4OCpqSuPR7ueZ2U7/dO/kc65M5le/uYdzPDyTPavmagntpq/slA133BQsuQmX1GI8/BE+q+ZJPVOf9wPvHWY2W7PsGI+MQNtx0RlT0NwSgU60xXhYEq3DtJ1orkzHps07ZcfW9awH7lAHk5t3onlYJ8vrTCrWea6smiedZBxWwXkenethIkJWzZNqYlzPRymMRxtcs64bbCMFm1gi0K62fEFZEkxD2nY0x3RoAG8xRDuaR8vl825RvDZTd6I5Mx5tQre8WSeaq9L5nOcjIMajDa5Zr5TQRgo2sUSglbaNpl75grIkmIa0WTVneZUG6JZDZNX8T//sKbn2U5fXZ7ZYgmFZwDbSZ9U8mgLj0QZwBzbJqvlfPvu8nP/RD0/5nKtucMVSvWJiPNrkmeXa0G2mYDNLBJppGz/giF5ONyz38zev5ovKknbtps2iebjOP5rr3EULWHLVLnxL22XRnHu3WBJJc9osmmM8NMO3FC6L5nzOzYiE8TDDmSwQgAAEIAABCEAAAhAoNQGMR6nlp/MQgAAEIAABCEAAAhAwQwDjYYYzWSAAAQhAAAIQgAAEIFBqAhiPUstP5yEAAQhAAAIQgAAEIGCGAMbDDGeyQAACEIAABCAAAQhAoNQEMB6llp/OQwACEIAABCAAAQhAwAwBjIcZzmSBAAQgAAEIQAACEIBAqQlgPEotP52HAAQgAAEIQAACEICAGQIYDzOcyQIBCEAAAhCAAAQgAIFSE8B4lFp+Og8BCEAAAhCAAAQgAAEzBDAeZjiTBQIQgAAEIAABCEAAAqUmgPEotfx0HgIQgAAEIAABCEAAAmYIYDzMcCYLBCAAAQhAAAIQgAAESk0A41Fq+ek8BCAAAQhAAAIQgAAEzBDAeJjhTBYIQAACEIAABCAAAQiUmgDGo9Ty03kIQAACEIAABCAAAQiYIYDxMMOZLBCAAAQgAAEIQAACECg1AYxHqeWn8xCAAAQgAAEIQAACEDBDAONhhjNZIACBEhN4cs9z8sWtu6YQuPTi5fLYlrvk9Td+IbfeuUUef2SjXHHZyiltHtqxW55/6dWg3bw5g9IszuGjx2XdPdvl3YOHGpL+8j23ydIl5wT5kh5hDS+89GrQ5rprV8kDG26Tgf6+evNm76lGR44dl9s3Piwv/3h/wzo+f/NqWbZ08RQmqrYbVl8t+956J+jHwvlz6v0OAyW9F9bTrD8l3vXoOgQgAAGnCGA8nJKDYiAAgaIRiJuHsH/q9U9d9bHAbChDsfupZ6ccaKuD7Ps275QHN62VFectkTRxouxUzL0vvpJoHDZt3ik7tq4P4iY9woP5cxctmNJuaHhE7t+2S55+Zm+iKWkUa/uO3dNMhGqr8sRrCc2FMlBxM6YYfPWbeyQ0bcqMJcUo2j5EfyAAAQgUhQDGoyhK0g8IQMA5AuGv/2uuvyb4Nb/RIzygX3zOfLl73RoJ/151+SXBdmnj6DQeyiz8xn/z9+XEyaGgptAofOupZ2X27Jly4sSpaaZGl/FQhusff/rX5O9e2VfPoQzJtkefkE9ceoF85//+/+pGBuPh3G5PQRCAAAQaEsB4sHNAAAIQyIlA3FA0SxP+0r9501p5+533psyAZIkT5uh0xkMZj/Xr1sj2f/+fp8y6qCVSb759QA68dzhX47H+D35XwhrCWSGVV+WPzg5hPHLaeQkLAQhAIAcCGI8coBISAhCAQEggfg5CdJlQnFK4lEi9Hl9mlCWO2r6Z8Uhzjke4POprT3w7KPMzv/UPghmHzfeuFfVa3sZDLTH7wY9eD5aL3fWFG+WBh74uG+64KXgtbjxa9Ye9EQIQgAAE3CCA8XBDB6qAAAQKTiB6foTqavz8CfVauKTqystW1pc3xbGkidPKeKQ5xyM0HuqkdbX0ST3W/JN/GCz9UgbJhPGYP3cwOFF9zuAsuWjF0oBJ/HwYZjwK/sGhexCAQKEIYDwKJSedgQAEfCDQaOlU/NyOVn1ptgRLx1Kr8Gpa8RPbTRkPdfK76sejX//z+knuGI9WewXvQwACEHCXAMbDXW2oDAIQ8JyAmsFQl5W9etXHp/VEHbyrR3jitnreyHhkjaNzxkNdOUqdf/L6Gz+Xf3TNlUHNJo2H6vueZ/bK5274dJAb4+H5h4LyIQCBUhPAeJRafjoPAQjkSSBcOvWRJedMORE7PF8jfh5HM+OhlhyljaPbeMQZmTQe8dwYjzz3WGJDAAIQyJcAxiNfvkSHAARKTiDphnpJ53c0m/FQ72WJ08p4tDoZWxmjRvfe0DXjEb8ZYvQGgtH7l6QxHq36U/JdkO5DAAIQcIYAxsMZKSgEAhCAAAQgAAEIQAACxSWA8SiutvQMAhCAAAQgAAEIQAACzhDAeDgjBYVAAAIQgAAEIAABCECguAQwHsXVlp5BAAIQgAAEIAABCEDAGQIYD2ekoBAIQAACEIAABCAAAQgUlwDGo7ja0jMIQAACEIAABCAAAQg4QwDj4YwUFAIBCEAAAhCAAAQgAIHiEsB4FFdbegYBCEAAAhCAAAQgAAFnCGA8nJGCQiAAAQhAAAIQgAAEIFBcAhiP4mpLzyAAAQhAAAIQgAAEIOAMAYyHM1JQCAQgAAEIQAACEIAABIpLAONRXG3pGQQgAAEIQAACEIAABJwhgPFwRgoKgQAEIAABCEAAAhCAQHEJYDyKqy09gwAEIAABCEAAAhCAgDMEMB7OSEEhEIAABCAAAQhAAAIQKC4BjEdxtaVnEIAABCAAAQhAAAIQcIYAxsMZKSgEAhCAAAQgAAEIQAACxSWA8SiutvQMAhCAAAQgAAEIQAACzhDAeDgjBYVAAAIQgAAEIAABCECguAQwHsXVlp5BAAIQgAAEIAABCEDAGQIYD2ekoBAIQAACEIAABCAAAQgUlwDGo7ja0jMIQAACEIAABCAAAQg4QwDj4YwUFAIBCEAAAhCAAAQgAIHiEsB4FFdbegYBCEAAAhCAAAQgAAFnCGA8nJGCQiAAAQhAAAIQgAAEIFBcAhiP4mpLzyAAAQhAAAIQgAAEIOAMAYyHM1JQCAQgAAEIQAACEIAABIpLAONRXG3pGQQgAAEIQAACEIAABJwhgPFwRgoKgQAEIAABCEAAAhCAQHEJYDyKqy09gwAEIAABCEAAAhCAgDMEMB7OSEEhEIAABCAAAQhAAAIQKC4BjEdxtaVnEIAABCAAAQhAAAIQcIYAxsMZKSgEAhCAAAQgAAEIQAACxSWA8SiutvQMAhCAAAQgAAEIQAACzhDAeDgjBYVAAAIQgAAEIAABCECguAQwHsXVlp5BAAIQgAAEIAABCEDAGQIYD2ekoBAIQAACEIAABCAAAQgUlwDGo7ja0jMIQAACEIAABCAAAQg4QwDj4YwUFAIBCEAAAhCAAAQgAIHiEvj/AdsB1yCBCy8DAAAAAElFTkSuQmCC", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dynamics.plot_curves(colors=['navy', 'orange'])" ] }, { "cell_type": "code", "execution_count": null, "id": "84bf7d8f-3ad4-4b5a-8b26-321122660f41", "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "markdown", "id": "70994860-4cde-45ba-b3a2-2ada1c541bf5", "metadata": {}, "source": [ "## Same data, but shown differently" ] }, { "cell_type": "code", "execution_count": 11, "id": "85b3c06f", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "A=%{x}
B=%{y}", "legendgroup": "", "line": { "color": "#C83778", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "", "orientation": "v", "showlegend": false, "type": "scatter", "x": [ 10, 12.5, 13.625, 14.13125, 14.3590625, 14.461578125, 14.50771015625, 14.5284695703125, 14.537811306640625, 14.54201508798828, 14.543906789594727 ], "xaxis": "x", "y": [ 50, 42.5, 39.125, 37.60625, 36.9228125, 36.615265625, 36.47686953125, 36.4145912890625, 36.386566080078126, 36.37395473603516, 36.36827963121582 ], "yaxis": "y" } ], "layout": { "autosize": true, "legend": { "tracegroupgap": 0 }, "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": "State space of reaction A <-> 3B : [A] vs. [B]" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ 10, 14.543906789594727 ], "title": { "text": "A" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 35.61096183295003, 50.75731779826579 ], "title": { "text": "B" }, "type": "linear" } } }, "image/png": "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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "fig0 = px.line(data_frame=dynamics.get_history(), x=\"A\", y=\"B\", \n", " title=\"State space of reaction A <-> 3B : [A] vs. [B]\",\n", " color_discrete_sequence = ['#C83778'],\n", " labels={\"value\":\"concentration\", \"variable\":\"Chemical\"})\n", "fig0.show()" ] }, { "cell_type": "code", "execution_count": 12, "id": "50b08a83-7a05-4fa7-bbde-93d3d6402df9", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "customdata": [ [ 0 ], [ 0.05 ], [ 0.1 ], [ 0.15 ], [ 0.2 ], [ 0.25 ], [ 0.3 ], [ 0.35 ], [ 0.4 ], [ 0.45 ], [ 0.5 ] ], "hovertemplate": "A=%{x}
B=%{y}
SYSTEM TIME=%{customdata[0]}", "legendgroup": "", "marker": { "color": "#2FAC74", "size": 6, "symbol": "circle" }, "mode": "markers", "name": "", "orientation": "v", "showlegend": false, "type": "scatter", "x": [ 10, 12.5, 13.625, 14.13125, 14.3590625, 14.461578125, 14.50771015625, 14.5284695703125, 14.537811306640625, 14.54201508798828, 14.543906789594727 ], "xaxis": "x", "y": [ 50, 42.5, 39.125, 37.60625, 36.9228125, 36.615265625, 36.47686953125, 36.4145912890625, 36.386566080078126, 36.37395473603516, 36.36827963121582 ], "yaxis": "y" } ], "layout": { "annotations": [ { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 0, "ay": 20, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "t=0.0", "x": 10, "y": 50 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 16, "ay": 28, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.05", "x": 12.5, "y": 42.5 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 32, "ay": 36, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.1", "x": 13.625, "y": 39.125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 48, "ay": 44, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.15", "x": 14.13125, "y": 37.60625 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 64, "ay": 52, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.2", "x": 14.3590625, "y": 36.9228125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 96, "ay": 68, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.3", "x": 14.50771015625, "y": 36.47686953125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 128, "ay": 84, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.4", "x": 14.537811306640625, "y": 36.386566080078126 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 160, "ay": 100, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.5", "x": 14.543906789594727, "y": 36.36827963121582 } ], "autosize": true, "legend": { "tracegroupgap": 0 }, "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": "Trajectory in State space: [A] vs. [B]" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ 9.574008738475495, 17.00712156711738 ], "title": { "text": "A" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 11.520586807102884, 52.93340818062445 ], "title": { "text": "B" }, "type": "linear" } } }, "image/png": "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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Now show the individual data points\n", "\n", "df['SYSTEM TIME'] = round(df['SYSTEM TIME'], 2) # To avoid clutter from too many digits, in the column\n", "\n", "fig1 = px.scatter(data_frame=df, x=\"A\", y=\"B\",\n", " title=\"Trajectory in State space: [A] vs. [B]\",\n", " hover_data=['SYSTEM TIME'])\n", "\n", "fig1.update_traces(marker={\"size\": 6, \"color\": \"#2FAC74\"}) # Modify the style of the dots\n", "\n", "# Add annotations (showing the System Time value) to SOME of the points, to avoid clutter\n", "for ind in df.index:\n", " label = df[\"SYSTEM TIME\"][ind]\n", " if ind == 0:\n", " label = f\"t={label}\"\n", " \n", " label_x = ind*16\n", " label_y = 20 + ind*8 # A greater y value here means further DOWN!!\n", " \n", " if (ind <= 3) or (ind%2 == 0):\n", " fig1.add_annotation(x=df[\"A\"][ind], y=df[\"B\"][ind],\n", " text=label,\n", " font=dict(\n", " size=10,\n", " color=\"grey\"\n", " ),\n", " showarrow=True, arrowhead=0, ax=label_x, ay=label_y, arrowcolor=\"#b0b0b0\",\n", " bordercolor=\"#c7c7c7\")\n", "\n", "fig1.show()" ] }, { "cell_type": "code", "execution_count": 13, "id": "f3c287ce-9a33-43bd-8473-f81f22ff9e81", "metadata": {}, "outputs": [ { "data": { "application/vnd.plotly.v1+json": { "config": { "plotlyServerURL": "https://plot.ly" }, "data": [ { "hovertemplate": "A=%{x}
B=%{y}", "legendgroup": "", "line": { "color": "#C83778", "dash": "solid" }, "marker": { "symbol": "circle" }, "mode": "lines", "name": "", "orientation": "v", "showlegend": false, "type": "scatter", "x": [ 10, 12.5, 13.625, 14.13125, 14.3590625, 14.461578125, 14.50771015625, 14.5284695703125, 14.537811306640625, 14.54201508798828, 14.543906789594727 ], "xaxis": "x", "y": [ 50, 42.5, 39.125, 37.60625, 36.9228125, 36.615265625, 36.47686953125, 36.4145912890625, 36.386566080078126, 36.37395473603516, 36.36827963121582 ], "yaxis": "y" }, { "customdata": [ [ 0 ], [ 0.05 ], [ 0.1 ], [ 0.15 ], [ 0.2 ], [ 0.25 ], [ 0.3 ], [ 0.35 ], [ 0.4 ], [ 0.45 ], [ 0.5 ] ], "hovertemplate": "A=%{x}
B=%{y}
SYSTEM TIME=%{customdata[0]}", "legendgroup": "", "marker": { "color": "#2FAC74", "size": 6, "symbol": "circle" }, "mode": "markers", "name": "", "orientation": "v", "showlegend": false, "type": "scatter", "x": [ 10, 12.5, 13.625, 14.13125, 14.3590625, 14.461578125, 14.50771015625, 14.5284695703125, 14.537811306640625, 14.54201508798828, 14.543906789594727 ], "xaxis": "x", "y": [ 50, 42.5, 39.125, 37.60625, 36.9228125, 36.615265625, 36.47686953125, 36.4145912890625, 36.386566080078126, 36.37395473603516, 36.36827963121582 ], "yaxis": "y" } ], "layout": { "annotations": [ { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 0, "ay": 20, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "t=0.0", "x": 10, "y": 50 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 16, "ay": 28, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.05", "x": 12.5, "y": 42.5 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 32, "ay": 36, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.1", "x": 13.625, "y": 39.125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 48, "ay": 44, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.15", "x": 14.13125, "y": 37.60625 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 64, "ay": 52, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.2", "x": 14.3590625, "y": 36.9228125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 96, "ay": 68, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.3", "x": 14.50771015625, "y": 36.47686953125 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 128, "ay": 84, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.4", "x": 14.537811306640625, "y": 36.386566080078126 }, { "arrowcolor": "#b0b0b0", "arrowhead": 0, "ax": 160, "ay": 100, "bordercolor": "#c7c7c7", "font": { "color": "grey", "size": 10 }, "showarrow": true, "text": "0.5", "x": 14.543906789594727, "y": 36.36827963121582 } ], "autosize": true, "legend": { "tracegroupgap": 0 }, "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": "Trajectory in State space: [A] vs. [B]" }, "xaxis": { "anchor": "y", "autorange": true, "domain": [ 0, 1 ], "range": [ 9.574008738475495, 17.00712156711738 ], "title": { "text": "A" }, "type": "linear" }, "yaxis": { "anchor": "x", "autorange": true, "domain": [ 0, 1 ], "range": [ 11.520586807102884, 52.93340818062445 ], "title": { "text": "B" }, "type": "linear" } } }, "image/png": "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", "text/html": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Combine the two above plots, while using the layout of fig1 (which includes the title and annotations)\n", "all_fig = go.Figure(data=fig0.data + fig1.data, layout = fig1.layout)\n", "all_fig.show()" ] }, { "cell_type": "markdown", "id": "4fe369cf-d2c0-454c-a3f9-9794008be8d8", "metadata": {}, "source": [ "#### Note how the trajectory is progressively slowing down towards the dynamical system's \"attractor\" (equilibrium state of the reaction)" ] }, { "cell_type": "code", "execution_count": null, "id": "c4e0120d-1541-4552-a2d0-8100a3fea8d9", "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 }