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"# Exploring the change of delta_x (spatial resolution) in diffusion accuracy.\n",
"#### From the same initial setup, diffusion is carried out over a fixed time span,\n",
"#### at different spatial resolutions - and then the respective results are compared\n",
"\n",
"LAST REVISED: June 4, 2023"
]
},
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"execution_count": 1,
"id": "24779840-3fd8-4bae-97f5-98c3891449b3",
"metadata": {},
"outputs": [
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"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"
]
},
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"id": "f56dee37-4187-410b-8daf-1f45f4587f14",
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"outputs": [],
"source": [
"from experiments.get_notebook_info import get_notebook_basename\n",
"\n",
"from src.life_1D.bio_sim_1d import BioSim1D\n",
"from src.modules.reactions.reaction_data import ChemData as chem\n",
"from src.modules.numerical.numerical import Numerical as num\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"
]
},
{
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"execution_count": 3,
"id": "7a4dd331-d083-4929-b7f1-089f44776f85",
"metadata": {},
"outputs": [
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"name": "stdout",
"output_type": "stream",
"text": [
"-> Output will be LOGGED into the file 'spatial_resolution_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\"])"
]
},
{
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"execution_count": 4,
"id": "14b4a1c2-9854-41c6-b407-6008bb4738be",
"metadata": {},
"outputs": [],
"source": [
"# Set the heatmap parameters (for the log file)\n",
"heatmap_pars = {\"range\": [0, 150],\n",
" \"outer_width\": 850, \"outer_height\": 150,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }\n",
"\n",
"# Set the parameters of the line plots\n",
"lineplot_pars = {\"range\": [0, 150],\n",
" \"outer_width\": 850, \"outer_height\": 250,\n",
" \"margins\": {\"top\": 30, \"right\": 30, \"bottom\": 30, \"left\": 55}\n",
" }"
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{
"cell_type": "markdown",
"id": "28c89c3d-a7f7-41d9-a99b-b0185620b5c1",
"metadata": {},
"source": [
"## Prepare the initial system"
]
},
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"execution_count": 5,
"id": "01b3a969-5122-4c25-900b-ad6fba315553",
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"text": [
"SYSTEM STATE at Time t = 0:\n",
"60 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 13. 17. 21. 25. 28. 30. 38. 42. 55. 65. 47. 35. 32.\n",
" 27. 23. 20. 17. 14. 8. 3. 10. 16. 18. 20. 25. 30. 35.\n",
" 40. 65. 85. 115. 150. 92. 73. 69. 65. 50. 42. 36. 20. 45.\n",
" 50. 55. 69. 82. 95. 77. 60. 43. 37. 31. 25. 22. 20. 18.\n",
" 15. 11. 9. 8.]\n"
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],
"source": [
"chem_data = chem(names=[\"A\"], diffusion_rates=[0.1])\n",
"\n",
"conc_list=[10,13,17,21,25,28,30,38,42,55,65,47,35,32,27,23,20,17,14,8,3,10,16,18,\n",
" 20,25,30,35,40,65,85,115,150,92,73,69,65,50,42,36,20,45,50,55,69,82,95,\n",
" 77,60,43,37,31,25,22,20,18,15,11,9, 8]\n",
"\n",
"bio = BioSim1D(n_bins=len(conc_list), chem_data=chem_data)\n",
"\n",
"bio.set_species_conc(species_name=\"A\", conc_list=conc_list)\n",
"\n",
"bio.describe_state()"
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""
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},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Line plot\n",
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\"], \n",
" title= f\"Diffusion. System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
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{
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"execution_count": 7,
"id": "94126c1b-fe6c-4709-98de-8f37a4b36402",
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Show as a heatmap\n",
"fig = px.imshow(bio.system_snapshot().T, \n",
" title= f\"Diffusion. System snapshot as a heatmap at time t={bio.system_time}\", \n",
" labels=dict(x=\"Bin number\", y=\"Chem. species\", color=\"Concentration\"),\n",
" text_auto=False, color_continuous_scale=\"gray_r\")\n",
"fig.data[0].xgap=2\n",
"fig.data[0].ygap=4\n",
"\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "d3097f06-8871-4379-8434-84b207d24b1a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1-D diffusion of a single species, with Diffusion rate 0.1\n",
"\n",
"\n",
"Initial system state at time t=0:\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `spatial_resolution_1.log.htm`]\n",
"[GRAPHIC ELEMENT SENT TO LOG FILE `spatial_resolution_1.log.htm`]\n"
]
}
],
"source": [
"log.write(\"1-D diffusion of a single species, with Diffusion rate 0.1\",\n",
" style=log.h2)\n",
"log.write(\"Initial system state at time t=0:\", blanks_before=2, style=log.bold)\n",
"\n",
"# Output a heatmap to the log file\n",
"bio.single_species_heatmap(species_index=0, heatmap_pars=heatmap_pars, graphic_component=\"vue_heatmap_11\")\n",
"\n",
"# Output a line plot the log file\n",
"bio.single_species_line_plot(species_index=0, plot_pars=lineplot_pars, graphic_component=\"vue_curves_3\")"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "1e42793c-0991-4324-8cae-4fe7b608f3eb",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"[[ 10. 13. 17. 21. 25. 28. 30. 38. 42. 55. 65. 47. 35. 32.\n",
" 27. 23. 20. 17. 14. 8. 3. 10. 16. 18. 20. 25. 30. 35.\n",
" 40. 65. 85. 115. 150. 92. 73. 69. 65. 50. 42. 36. 20. 45.\n",
" 50. 55. 69. 82. 95. 77. 60. 43. 37. 31. 25. 22. 20. 18.\n",
" 15. 11. 9. 8.]]\n"
]
}
],
"source": [
"bio.describe_state(concise=True)"
]
},
{
"cell_type": "markdown",
"id": "5b7faf57-7059-4bfc-adf8-82fa83fc822a",
"metadata": {},
"source": [
"### Populate the data set with more bins, using interpolated concentration values\n",
"### IMPORTANT: we're **NOT** changing spacial resolution here; we're just creating a less ragged dataset, as *our initial system state*"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "cd81720a-dfe7-4051-a839-1d77f4493873",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"119 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 11.5 13. 15. 17. 19. 21. 23. 25. 26.5 28. 29.\n",
" 30. 34. 38. 40. 42. 48.5 55. 60. 65. 56. 47. 41.\n",
" 35. 33.5 32. 29.5 27. 25. 23. 21.5 20. 18.5 17. 15.5\n",
" 14. 11. 8. 5.5 3. 6.5 10. 13. 16. 17. 18. 19.\n",
" 20. 22.5 25. 27.5 30. 32.5 35. 37.5 40. 52.5 65. 75.\n",
" 85. 100. 115. 132.5 150. 121. 92. 82.5 73. 71. 69. 67.\n",
" 65. 57.5 50. 46. 42. 39. 36. 28. 20. 32.5 45. 47.5\n",
" 50. 52.5 55. 62. 69. 75.5 82. 88.5 95. 86. 77. 68.5\n",
" 60. 51.5 43. 40. 37. 34. 31. 28. 25. 23.5 22. 21.\n",
" 20. 19. 18. 16.5 15. 13. 11. 10. 9. 8.5 8. ]\n"
]
}
],
"source": [
"bio.smooth_spatial_resolution()\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "2a9d184f-152c-4a07-8f90-43261dc3a39b",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"119"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.n_bins"
]
},
{
"cell_type": "markdown",
"id": "7efb504b-d93d-412d-b211-424d77c2fd53",
"metadata": {},
"source": [
"# The STARTING POINT\n",
"### This system setup will be our starting point in exploring diffusion using different spacial resolutions"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "19a33c8b-abef-41eb-9671-ceea867f2cb8",
"metadata": {},
"outputs": [],
"source": [
"original_state = bio.save_system() # SAVE a copy of the system state, to do multiple runs starting from it"
]
},
{
"cell_type": "code",
"execution_count": 13,
"id": "98c65a70-2509-4e3c-be0c-e9da89e7e847",
"metadata": {},
"outputs": [
{
"data": {
"application/vnd.plotly.v1+json": {
"config": {
"plotlyServerURL": "https://plot.ly"
},
"data": [
{
"hovertemplate": "Chemical=A
Bin number=%{x}
concentration=%{y}",
"legendgroup": "A",
"line": {
"color": "red",
"dash": "solid"
},
"marker": {
"symbol": "circle"
},
"mode": "lines",
"name": "A",
"orientation": "v",
"showlegend": true,
"type": "scatter",
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"y": [
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"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Line plot\n",
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\"], \n",
" title= f\"Diffusion. System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "code",
"execution_count": 14,
"id": "1583e159-8fca-4f6f-99e0-23b5ccb44f4b",
"metadata": {},
"outputs": [
{
"data": {
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"config": {
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Chem. species: %{y}
Concentration: %{z}",
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},
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},
"type": "barpolar"
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],
"carpet": [
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"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
},
"baxis": {
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"gridcolor": "white",
"linecolor": "white",
"minorgridcolor": "white",
"startlinecolor": "#2a3f5f"
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"type": "carpet"
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"ticks": ""
},
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Show as a heatmap\n",
"fig = px.imshow(bio.system_snapshot().T, \n",
" title= f\"Diffusion. System snapshot as a heatmap at time t={bio.system_time}\", \n",
" labels=dict(x=\"Bin number\", y=\"Chem. species\", color=\"Concentration\"),\n",
" text_auto=False, color_continuous_scale=\"gray_r\")\n",
"fig.data[0].xgap=2\n",
"fig.data[0].ygap=4\n",
"\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "42c21d56-3f59-4b7e-a118-f9d2b206d909",
"metadata": {},
"source": [
"# Initial Diffusions with delta_x = 1"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "be02747a-1a34-40ff-864e-9d4cc524ef24",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"[[ 10. 11.5 13. 15. 17. 19. 21. 23. 25. 26.5 28. 29.\n",
" 30. 34. 38. 40. 42. 48.5 55. 60. 65. 56. 47. 41.\n",
" 35. 33.5 32. 29.5 27. 25. 23. 21.5 20. 18.5 17. 15.5\n",
" 14. 11. 8. 5.5 3. 6.5 10. 13. 16. 17. 18. 19.\n",
" 20. 22.5 25. 27.5 30. 32.5 35. 37.5 40. 52.5 65. 75.\n",
" 85. 100. 115. 132.5 150. 121. 92. 82.5 73. 71. 69. 67.\n",
" 65. 57.5 50. 46. 42. 39. 36. 28. 20. 32.5 45. 47.5\n",
" 50. 52.5 55. 62. 69. 75.5 82. 88.5 95. 86. 77. 68.5\n",
" 60. 51.5 43. 40. 37. 34. 31. 28. 25. 23.5 22. 21.\n",
" 20. 19. 18. 16.5 15. 13. 11. 10. 9. 8.5 8. ]]\n"
]
}
],
"source": [
"bio.describe_state(concise=True) # Our initial state"
]
},
{
"cell_type": "code",
"execution_count": 16,
"id": "40c45d26-e2b7-4a8c-8977-da4420bf3f10",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 7:\n",
"[[ 10.81374413 11.75949885 13.25000185 15.062428 17.01188631\n",
" 19.00006197 20.98868984 22.94206218 24.77953224 26.39811453\n",
" 27.84518887 29.27277252 31.20853868 34.12698244 37.32677234\n",
" 40.2862322 43.81041987 48.78035189 54.15351454 58.2814886\n",
" 59.14279616 54.77210271 48.04680994 41.79043277 36.93388531\n",
" 33.9061457 31.69382485 29.46191837 27.20137234 25.10925294\n",
" 23.22142636 21.55799283 20.01085627 18.49643905 16.96650717\n",
" 15.33320734 13.3825283 10.9090395 8.31230858 6.22475706\n",
" 5.52496549 7.11396222 9.88035549 12.74022689 15.15002384\n",
" 16.77867411 17.98845929 19.16168898 20.63070462 22.66884325\n",
" 25.03404219 27.50595199 30.00545331 32.53611034 35.22552071\n",
" 38.6175266 44.15676727 53.36291807 64.2882023 75.32432162\n",
" 87.08827561 100.66910178 115.12022797 127.63314241 130.92324021\n",
" 117.99541158 99.32869508 85.37270647 76.57561881 71.8930744\n",
" 69.0560342 66.42137568 62.7673733 57.27850579 51.36962997\n",
" 46.46995094 42.39418213 38.63544547 34.37871095 29.71340552\n",
" 28.29315172 33.66482748 41.2534017 46.46381152 49.88480842\n",
" 52.96994306 56.87891037 62.44917838 68.88403646 75.40392992\n",
" 81.63969537 86.7544752 88.48402236 84.3108163 76.86181696\n",
" 68.52015368 60.12863819 52.12045277 45.31624262 40.61956462\n",
" 37.12538915 34.02533947 31.03685317 28.17104426 25.64301661\n",
" 23.72523577 22.24431377 21.05990509 20.00048044 18.94381764\n",
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"source": [
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",
"text/html": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# Line plot\n",
"fig = px.line(data_frame=bio.system_snapshot(), y=[\"A\"], \n",
" title= f\"Diffusion. System snapshot at time t={bio.system_time}\",\n",
" color_discrete_sequence = ['red'],\n",
" labels={\"value\":\"concentration\", \"variable\":\"Chemical\", \"index\":\"Bin number\"})\n",
"fig.show()"
]
},
{
"cell_type": "markdown",
"id": "444efd67-8989-4265-83d0-2d431e5416b3",
"metadata": {},
"source": [
"### Enough time has proceeded to result in some smoothing, and non-puny changes in most values - but still nowhere near equilibrium"
]
},
{
"cell_type": "markdown",
"id": "9f2c62f4-a88e-4ed4-902b-86f27d23c9ca",
"metadata": {},
"source": [
"# Now restore the system to its initial (pre-diffusion) state\n",
"### and then perform a diffusion over the same time span, but with DOUBLE the spacial resolution\n",
"#### delta_x will be be 1/2 instead of the original default 1"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "a3cc74ba-fa61-47ff-bc0a-f3360446aa2e",
"metadata": {},
"outputs": [],
"source": [
"bio.restore_system(original_state)"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "58217aca-d556-45cd-899f-bed201d4c52b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"119 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 11.5 13. 15. 17. 19. 21. 23. 25. 26.5 28. 29.\n",
" 30. 34. 38. 40. 42. 48.5 55. 60. 65. 56. 47. 41.\n",
" 35. 33.5 32. 29.5 27. 25. 23. 21.5 20. 18.5 17. 15.5\n",
" 14. 11. 8. 5.5 3. 6.5 10. 13. 16. 17. 18. 19.\n",
" 20. 22.5 25. 27.5 30. 32.5 35. 37.5 40. 52.5 65. 75.\n",
" 85. 100. 115. 132.5 150. 121. 92. 82.5 73. 71. 69. 67.\n",
" 65. 57.5 50. 46. 42. 39. 36. 28. 20. 32.5 45. 47.5\n",
" 50. 52.5 55. 62. 69. 75.5 82. 88.5 95. 86. 77. 68.5\n",
" 60. 51.5 43. 40. 37. 34. 31. 28. 25. 23.5 22. 21.\n",
" 20. 19. 18. 16.5 15. 13. 11. 10. 9. 8.5 8. ]\n"
]
}
],
"source": [
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 21,
"id": "1c16e9ce-4a92-40a6-952a-1586b957ee7c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"238 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 10. 11.5 11.5 13. 13. 15. 15. 17. 17. 19. 19.\n",
" 21. 21. 23. 23. 25. 25. 26.5 26.5 28. 28. 29. 29.\n",
" 30. 30. 34. 34. 38. 38. 40. 40. 42. 42. 48.5 48.5\n",
" 55. 55. 60. 60. 65. 65. 56. 56. 47. 47. 41. 41.\n",
" 35. 35. 33.5 33.5 32. 32. 29.5 29.5 27. 27. 25. 25.\n",
" 23. 23. 21.5 21.5 20. 20. 18.5 18.5 17. 17. 15.5 15.5\n",
" 14. 14. 11. 11. 8. 8. 5.5 5.5 3. 3. 6.5 6.5\n",
" 10. 10. 13. 13. 16. 16. 17. 17. 18. 18. 19. 19.\n",
" 20. 20. 22.5 22.5 25. 25. 27.5 27.5 30. 30. 32.5 32.5\n",
" 35. 35. 37.5 37.5 40. 40. 52.5 52.5 65. 65. 75. 75.\n",
" 85. 85. 100. 100. 115. 115. 132.5 132.5 150. 150. 121. 121.\n",
" 92. 92. 82.5 82.5 73. 73. 71. 71. 69. 69. 67. 67.\n",
" 65. 65. 57.5 57.5 50. 50. 46. 46. 42. 42. 39. 39.\n",
" 36. 36. 28. 28. 20. 20. 32.5 32.5 45. 45. 47.5 47.5\n",
" 50. 50. 52.5 52.5 55. 55. 62. 62. 69. 69. 75.5 75.5\n",
" 82. 82. 88.5 88.5 95. 95. 86. 86. 77. 77. 68.5 68.5\n",
" 60. 60. 51.5 51.5 43. 43. 40. 40. 37. 37. 34. 34.\n",
" 31. 31. 28. 28. 25. 25. 23.5 23.5 22. 22. 21. 21.\n",
" 20. 20. 19. 19. 18. 18. 16.5 16.5 15. 15. 13. 13.\n",
" 11. 11. 10. 10. 9. 9. 8.5 8.5 8. 8. ]\n"
]
}
],
"source": [
"# Double the spacial resolution\n",
"bio.increase_spatial_resolution(2)\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 22,
"id": "9fe5455a-d6d4-4b70-8066-4ae93dd8afda",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'steps': 14000}"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Now repeat the idential diffusion process as before, but with half the delta_x\n",
"bio.diffuse(total_duration=7, time_step=0.0005, delta_x=0.5)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"id": "04f50181-dcad-493a-bd5d-2a945ac4321d",
"metadata": {},
"outputs": [],
"source": [
"# Finally, halve the resolution, to return to the original number of bins\n",
"bio.decrease_spatial_resolution(2)"
]
},
{
"cell_type": "code",
"execution_count": 24,
"id": "535fe84a-d96e-463a-9e3f-325f9dee3684",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 7:\n",
"[[ 10.89266176 11.7848539 13.26762024 15.06704663 17.01129224\n",
" 19.00001264 20.98893325 22.93586947 24.75899763 26.38192007\n",
" 27.82438658 29.30805339 31.32877441 34.1360355 37.24341866\n",
" 40.31811624 43.99520185 48.83623707 54.09824855 58.06985342\n",
" 58.57966756 54.62426556 48.17247393 41.90469993 37.11644548\n",
" 33.94904366 31.65030415 29.45000857 27.22040768 25.12325332\n",
" 23.24141451 21.56414243 20.01086312 18.49744005 16.96700181\n",
" 15.31270487 13.32065434 10.88965328 8.33006728 6.31235026\n",
" 5.7658755 7.18787019 9.85810569 12.70102493 15.06827539\n",
" 16.75109893 17.98883114 19.18350838 20.69123723 22.68863443\n",
" 25.03321123 27.50397596 30.00236415 32.52570687 35.22087023\n",
" 38.75134897 44.55667676 53.45617766 64.17981427 75.34602862\n",
" 87.29799843 100.81761735 115.23752191 127.02910436 129.04849394\n",
" 117.62993512 100.12856257 85.77621563 76.87924473 71.97878724\n",
" 69.04898398 66.33678631 62.54319331 57.25105821 51.51321158\n",
" 46.53921156 42.43097232 38.55845361 34.16913353 29.92635975\n",
" 29.12067234 33.80781119 40.84273642 46.30651206 49.8823516\n",
" 53.03921126 57.06182315 62.50278661 68.86587891 75.40882931\n",
" 81.6468186 86.55058818 87.86393314 84.11348004 76.88853987\n",
" 68.53716736 60.12964051 52.19284837 45.53614153 40.69176909\n",
" 37.12206867 34.01800894 31.03444131 28.19000887 25.70272045\n",
" 23.75153806 22.26365369 21.06545194 20.0002062 18.9371436\n",
" 17.75869087 16.37681178 14.7806228 13.06289215 11.46110516\n",
" 10.1887551 9.26494555 8.63951029 8.30600783]]\n"
]
}
],
"source": [
"bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 25,
"id": "426a1290-ebe1-41b0-b593-ee4d904ac8a7",
"metadata": {},
"outputs": [],
"source": [
"# SAVE the above system data: this is the result of diffusion with delta_x of 1/2\n",
"diffuse_dx_1_2 = bio.system"
]
},
{
"cell_type": "markdown",
"id": "30c10874-86f5-44fe-a7f7-95a85b483a0a",
"metadata": {},
"source": [
"### Compare the last 2 runs (with dx=1 and dx=1/2)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"id": "279f7108-0945-41e7-9d96-a7459f684dfc",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Max of unsigned absolute differences: 1.8747462722119792\n",
"L2 norm of differences (vectors) / Frobenius norm (matrices): 2.7316311840631684\n",
"Relative differences: [[-7.29790045e-03 -2.15613319e-03 -1.32968992e-03 -3.06632150e-04\n",
" 3.49208820e-05 2.59663515e-06 -1.15973861e-05 2.69928224e-04\n",
" 8.28692275e-04 6.13470206e-04 7.47069769e-04 -1.20524538e-03\n",
" -3.85265494e-03 -2.65275678e-04 2.23308031e-03 -7.91437615e-04\n",
" -4.21776329e-03 -1.14564947e-03 1.02054299e-03 3.63125894e-03\n",
" 9.52150784e-03 2.69913226e-03 -2.61544918e-03 -2.73428998e-03\n",
" -4.94289119e-03 -1.26519730e-03 1.37316033e-03 4.04243991e-04\n",
" -6.99793078e-04 -5.57578381e-04 -8.60763159e-04 -2.85258123e-04\n",
" -3.42447190e-07 -5.41183447e-05 -2.91538906e-05 1.33712864e-03\n",
" 4.62348860e-03 1.77707875e-03 -2.13643382e-03 -1.40717463e-02\n",
" -4.36038933e-02 -1.03891427e-02 2.25192283e-03 3.07702233e-03\n",
" 5.39592866e-03 1.64346643e-03 -2.06718026e-05 -1.13869947e-03\n",
" -2.93410303e-03 -8.73056317e-04 3.31929918e-05 7.18400209e-05\n",
" 1.02952955e-04 3.19751640e-04 1.32020109e-04 -3.46532734e-03\n",
" -9.05658439e-03 -1.74764791e-03 1.68597072e-03 -2.88180506e-04\n",
" -2.40816367e-03 -1.47528453e-03 -1.01888209e-03 4.73261129e-03\n",
" 1.43194308e-02 3.09737859e-03 -8.05273331e-03 -4.72644216e-03\n",
" -3.96504687e-03 -1.19222672e-03 1.02094122e-04 1.27352632e-03\n",
" 3.57160065e-03 4.79195110e-04 -2.79506797e-03 -1.49043883e-03\n",
" -8.67812292e-04 1.99277808e-03 6.09613948e-03 -7.16694099e-03\n",
" -2.92480890e-02 -4.24727283e-03 9.95470117e-03 3.38541861e-03\n",
" 4.92498985e-05 -1.30768881e-03 -3.21582770e-03 -8.58429642e-04\n",
" 2.63595933e-04 -6.49752035e-05 -8.72520217e-05 2.35016149e-03\n",
" 7.00792303e-03 2.34058050e-03 -3.47674716e-04 -2.48301846e-04\n",
" -1.66695826e-05 -1.38900549e-03 -4.85254083e-03 -1.77757860e-03\n",
" 8.94397998e-05 2.15443001e-04 7.77095929e-05 -6.73194980e-04\n",
" -2.32826908e-03 -1.10862093e-03 -8.69432472e-04 -2.63384091e-04\n",
" 1.37117998e-05 3.52307297e-04 1.13315268e-03 8.68045408e-04\n",
" 1.37839117e-03 -5.01506606e-04 -3.49996806e-03 -1.92703159e-03\n",
" -2.03295683e-03 -1.35774126e-03 -3.07625876e-03]]\n",
"Max of unsigned relative differences: 0.04360389332348327\n",
"Mean of relative differences: -0.0009733870307526427\n",
"Median of relative differences: -0.00026338409050621263\n",
"Standard deviation of relative differences: 0.005897685168763968\n",
"np.allclose with lax tolerance? (rtol=1e-01, atol=1e-01) : True\n",
"np.allclose with mid tolerance? (rtol=1e-02, atol=1e-03) : False\n",
"np.allclose with tight tolerance? (rtol=1e-03, atol=1e-05) : False\n",
"np.allclose with extra-tight tolerance? (rtol=1e-05, atol=1e-08) : False\n"
]
}
],
"source": [
"num.compare_states(diffuse_dx_1 , diffuse_dx_1_2, verbose=True)"
]
},
{
"cell_type": "markdown",
"id": "029954ed-7283-4deb-b1b8-e8abcaaa7b11",
"metadata": {},
"source": [
"# Again, restore the system to its initial (pre-diffusion) state\n",
"### and then perform a diffusion over the same time span, but with QUADRUPLE the spacial resolution\n",
"### delta_x will be be 1/4 instead of the original default 1"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "5165aa24-ef43-42ef-87a9-546822f5a1b5",
"metadata": {},
"outputs": [],
"source": [
"bio.restore_system(original_state)"
]
},
{
"cell_type": "code",
"execution_count": 28,
"id": "99eeec00-5118-4360-b228-3e0a1042d13e",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"119 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 11.5 13. 15. 17. 19. 21. 23. 25. 26.5 28. 29.\n",
" 30. 34. 38. 40. 42. 48.5 55. 60. 65. 56. 47. 41.\n",
" 35. 33.5 32. 29.5 27. 25. 23. 21.5 20. 18.5 17. 15.5\n",
" 14. 11. 8. 5.5 3. 6.5 10. 13. 16. 17. 18. 19.\n",
" 20. 22.5 25. 27.5 30. 32.5 35. 37.5 40. 52.5 65. 75.\n",
" 85. 100. 115. 132.5 150. 121. 92. 82.5 73. 71. 69. 67.\n",
" 65. 57.5 50. 46. 42. 39. 36. 28. 20. 32.5 45. 47.5\n",
" 50. 52.5 55. 62. 69. 75.5 82. 88.5 95. 86. 77. 68.5\n",
" 60. 51.5 43. 40. 37. 34. 31. 28. 25. 23.5 22. 21.\n",
" 20. 19. 18. 16.5 15. 13. 11. 10. 9. 8.5 8. ]\n"
]
}
],
"source": [
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 29,
"id": "53417fe4-e623-45c9-af24-250eb4300796",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 0:\n",
"476 bins and 1 species:\n",
" Species 0 (A). Diff rate: 0.1. Conc: [ 10. 10. 10. 10. 11.5 11.5 11.5 11.5 13. 13. 13. 13.\n",
" 15. 15. 15. 15. 17. 17. 17. 17. 19. 19. 19. 19.\n",
" 21. 21. 21. 21. 23. 23. 23. 23. 25. 25. 25. 25.\n",
" 26.5 26.5 26.5 26.5 28. 28. 28. 28. 29. 29. 29. 29.\n",
" 30. 30. 30. 30. 34. 34. 34. 34. 38. 38. 38. 38.\n",
" 40. 40. 40. 40. 42. 42. 42. 42. 48.5 48.5 48.5 48.5\n",
" 55. 55. 55. 55. 60. 60. 60. 60. 65. 65. 65. 65.\n",
" 56. 56. 56. 56. 47. 47. 47. 47. 41. 41. 41. 41.\n",
" 35. 35. 35. 35. 33.5 33.5 33.5 33.5 32. 32. 32. 32.\n",
" 29.5 29.5 29.5 29.5 27. 27. 27. 27. 25. 25. 25. 25.\n",
" 23. 23. 23. 23. 21.5 21.5 21.5 21.5 20. 20. 20. 20.\n",
" 18.5 18.5 18.5 18.5 17. 17. 17. 17. 15.5 15.5 15.5 15.5\n",
" 14. 14. 14. 14. 11. 11. 11. 11. 8. 8. 8. 8.\n",
" 5.5 5.5 5.5 5.5 3. 3. 3. 3. 6.5 6.5 6.5 6.5\n",
" 10. 10. 10. 10. 13. 13. 13. 13. 16. 16. 16. 16.\n",
" 17. 17. 17. 17. 18. 18. 18. 18. 19. 19. 19. 19.\n",
" 20. 20. 20. 20. 22.5 22.5 22.5 22.5 25. 25. 25. 25.\n",
" 27.5 27.5 27.5 27.5 30. 30. 30. 30. 32.5 32.5 32.5 32.5\n",
" 35. 35. 35. 35. 37.5 37.5 37.5 37.5 40. 40. 40. 40.\n",
" 52.5 52.5 52.5 52.5 65. 65. 65. 65. 75. 75. 75. 75.\n",
" 85. 85. 85. 85. 100. 100. 100. 100. 115. 115. 115. 115.\n",
" 132.5 132.5 132.5 132.5 150. 150. 150. 150. 121. 121. 121. 121.\n",
" 92. 92. 92. 92. 82.5 82.5 82.5 82.5 73. 73. 73. 73.\n",
" 71. 71. 71. 71. 69. 69. 69. 69. 67. 67. 67. 67.\n",
" 65. 65. 65. 65. 57.5 57.5 57.5 57.5 50. 50. 50. 50.\n",
" 46. 46. 46. 46. 42. 42. 42. 42. 39. 39. 39. 39.\n",
" 36. 36. 36. 36. 28. 28. 28. 28. 20. 20. 20. 20.\n",
" 32.5 32.5 32.5 32.5 45. 45. 45. 45. 47.5 47.5 47.5 47.5\n",
" 50. 50. 50. 50. 52.5 52.5 52.5 52.5 55. 55. 55. 55.\n",
" 62. 62. 62. 62. 69. 69. 69. 69. 75.5 75.5 75.5 75.5\n",
" 82. 82. 82. 82. 88.5 88.5 88.5 88.5 95. 95. 95. 95.\n",
" 86. 86. 86. 86. 77. 77. 77. 77. 68.5 68.5 68.5 68.5\n",
" 60. 60. 60. 60. 51.5 51.5 51.5 51.5 43. 43. 43. 43.\n",
" 40. 40. 40. 40. 37. 37. 37. 37. 34. 34. 34. 34.\n",
" 31. 31. 31. 31. 28. 28. 28. 28. 25. 25. 25. 25.\n",
" 23.5 23.5 23.5 23.5 22. 22. 22. 22. 21. 21. 21. 21.\n",
" 20. 20. 20. 20. 19. 19. 19. 19. 18. 18. 18. 18.\n",
" 16.5 16.5 16.5 16.5 15. 15. 15. 15. 13. 13. 13. 13.\n",
" 11. 11. 11. 11. 10. 10. 10. 10. 9. 9. 9. 9.\n",
" 8.5 8.5 8.5 8.5 8. 8. 8. 8. ]\n"
]
}
],
"source": [
"# Quadruple the spacial resolution\n",
"bio.increase_spatial_resolution(4)\n",
"bio.describe_state()"
]
},
{
"cell_type": "code",
"execution_count": 30,
"id": "391a6de8-4e23-46cf-b9a4-fe0b5ca47d81",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'steps': 14000}"
]
},
"execution_count": 30,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Now repeat the idential diffusion process as before, but with 1/4 the delta_x\n",
"bio.diffuse(total_duration=7, time_step=0.0005, delta_x=0.25)"
]
},
{
"cell_type": "code",
"execution_count": 31,
"id": "e2af3fdf-98cb-4d7b-bdec-cb33297d560c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 7:\n",
"[[ 10.9110498 11.79298317 13.27125046 15.06849169 17.01120689\n",
" 19.00000505 20.9889355 22.93396624 24.75464755 26.37685365\n",
" 27.82036504 29.31906987 31.35336039 34.13881577 37.22693938\n",
" 40.32794219 44.03328497 48.85375011 54.08582706 58.00398505\n",
" 58.46305352 54.57827613 48.19757613 41.94032917 37.15466295\n",
" 33.96229007 31.64173724 29.44629083 27.22423232 25.12764114\n",
" 23.24562187 21.56603866 20.01093031 18.49776361 16.96694036\n",
" 15.30636174 13.30779924 10.88358481 8.33420858 6.33960051\n",
" 5.81582285 7.21086316 9.85389609 12.68880637 15.05118007\n",
" 16.74254972 17.98886835 19.19030566 20.7038042 22.6947809\n",
" 25.03319586 27.50341077 30.00154792 32.52240795 35.22096403\n",
" 38.7930256 44.63917184 53.48517183 64.1588254 75.35244\n",
" 87.34200001 100.86427456 115.25735194 126.84107661 128.66226344\n",
" 117.51620543 100.29022264 85.90199754 76.94490243 72.00512119\n",
" 69.04735136 66.31052176 62.496998 57.24253268 51.5425832\n",
" 46.56093864 42.43820564 38.53427331 34.12800735 29.99268233\n",
" 29.29052368 33.85235505 40.75977408 46.25740082 49.88097703\n",
" 53.06093861 57.09980983 62.51931722 68.86280603 75.4104181\n",
" 81.64659333 86.48718521 87.7355725 84.05211787 76.89241675\n",
" 68.54251739 60.13069322 52.21527733 45.58166864 40.71424215\n",
" 37.12191698 34.01569142 31.03400274 28.19593816 25.71513906\n",
" 23.75971844 22.26781878 21.06716906 20.00013474 18.93508199\n",
" 17.754446 16.37238573 14.77644125 13.06493272 11.46938478\n",
" 10.19485558 9.26894187 8.64323169 8.31194648]]\n"
]
}
],
"source": [
"# Finally, reduce the resolution by a factor 4, to return to the original number of bins\n",
"bio.decrease_spatial_resolution(4)\n",
"bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 32,
"id": "4add12b8-1fb5-4315-a292-2f7094ec7990",
"metadata": {},
"outputs": [],
"source": [
"# SAVE the above system data: this is the result of diffusion with delta_x of 1/4\n",
"diffuse_dx_1_4 = bio.system"
]
},
{
"cell_type": "markdown",
"id": "15d35fe4-d252-4b3a-8792-7bb0f859e05c",
"metadata": {},
"source": [
"### Compare the latest 2 runs (with dx=1/2 and dx=1/4)"
]
},
{
"cell_type": "code",
"execution_count": 33,
"id": "9466d672-5fbd-4d09-bd55-84d2a44d7f10",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Max of unsigned absolute differences: 0.3862305022112764\n",
"L2 norm of differences (vectors) / Frobenius norm (matrices): 0.6099407690744825\n",
"Max of unsigned relative differences: 0.008662578999936136\n",
"Mean of relative differences: -0.00023057453135932627\n",
"Median of relative differences: -7.806036263243106e-05\n",
"Standard deviation of relative differences: 0.001284581809105773\n",
"np.allclose with lax tolerance? (rtol=1e-01, atol=1e-01) : True\n",
"np.allclose with mid tolerance? (rtol=1e-02, atol=1e-03) : True\n",
"np.allclose with tight tolerance? (rtol=1e-03, atol=1e-05) : False\n",
"np.allclose with extra-tight tolerance? (rtol=1e-05, atol=1e-08) : False\n"
]
}
],
"source": [
"num.compare_states(diffuse_dx_1_2 , diffuse_dx_1_4)"
]
},
{
"cell_type": "markdown",
"id": "dcbe0848-a86c-41b0-8a78-ed02541b2b0f",
"metadata": {},
"source": [
"### Notice how the discrepancies have gone down"
]
},
{
"cell_type": "markdown",
"id": "4ec7d406-d535-4217-b458-3c0a4f17cbd1",
"metadata": {},
"source": [
"# One last time, restore the system to its initial (pre-diffusion) state\n",
"### and then perform a diffusion over the same time span, but with 10x the spacial resolution\n",
"### delta_x will be be 1/10 instead of the original default 1"
]
},
{
"cell_type": "code",
"execution_count": 34,
"id": "c30da69c-664b-4e5e-9200-b3e8f0d1638a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"1190"
]
},
"execution_count": 34,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bio.restore_system(original_state)\n",
"\n",
"# Increase by a factor 10 the spacial resolution\n",
"bio.increase_spatial_resolution(10)\n",
"bio.n_bins"
]
},
{
"cell_type": "code",
"execution_count": 35,
"id": "4f5bb9ea-9488-4300-a894-f8ad341e1a4d",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'steps': 14000}"
]
},
"execution_count": 35,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Now repeat the idential diffusion process as before, but with 1/10 the delta_x\n",
"bio.diffuse(total_duration=7, time_step=0.0005, delta_x=0.1)"
]
},
{
"cell_type": "code",
"execution_count": 36,
"id": "417e3555-761e-4732-9713-6f5e69cfed65",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"SYSTEM STATE at Time t = 7:\n",
"[[ 10.9161213 11.79534703 13.27224519 15.06889944 17.01119333\n",
" 19.00000338 20.98892613 22.93342377 24.75346019 26.37538504\n",
" 27.8193336 29.32224482 31.35993783 34.13959443 37.22264801\n",
" 40.33074926 44.04350095 48.85885219 54.08228117 57.9850481\n",
" 58.43161184 54.5650653 48.20415782 41.95062292 37.16503013\n",
" 33.96606998 31.63952326 29.44520209 27.22524894 25.12890686\n",
" 23.24676849 21.56657954 20.01095977 18.49786149 16.96689233\n",
" 15.30454171 13.30433429 10.88181544 8.33541818 6.34742941\n",
" 5.82930238 7.21746817 9.85284142 12.68527302 15.04654903\n",
" 16.74009407 17.98886906 19.19226541 20.70719698 22.69654408\n",
" 25.03322271 27.50324578 30.00131432 32.52141484 35.22119659\n",
" 38.80499992 44.66137184 53.49347076 64.15346368 75.35420342\n",
" 87.35391443 100.87790208 115.26183635 126.78700415 128.55849521\n",
" 117.48352229 100.33303879 85.9383081 76.96307468 72.01259667\n",
" 69.04692294 66.30294186 62.4845971 57.24008251 51.55042279\n",
" 46.56723079 42.44010875 38.52721713 34.11735772 30.01175902\n",
" 29.33604167 33.86516393 40.73781027 46.24318925 49.88047063\n",
" 53.06723078 57.11005998 62.52405086 68.86208623 75.4109248\n",
" 81.64620029 86.46899111 87.70095286 84.03450966 76.89314005\n",
" 68.54409875 60.13111756 52.22170551 45.59395032 40.72069246\n",
" 37.1219866 34.01499435 31.0339081 28.19763978 25.71849996\n",
" 23.76206593 22.26897366 21.06765706 20.00011435 18.93449137\n",
" 17.75328892 16.37111133 14.77532277 13.06551858 11.47161872\n",
" 10.19660621 9.27004622 8.64430525 8.31358802]]\n"
]
}
],
"source": [
"# Finally, reduce the resolution by a factor 10, to return to the original number of bins\n",
"bio.decrease_spatial_resolution(10)\n",
"bio.describe_state(concise=True)"
]
},
{
"cell_type": "code",
"execution_count": 37,
"id": "8163bc82-24ab-435f-89a7-0eb7401c1046",
"metadata": {},
"outputs": [],
"source": [
"# SAVE the above system data: this is the result of diffusion with delta_x of 1/10\n",
"diffuse_dx_1_10 = bio.system"
]
},
{
"cell_type": "markdown",
"id": "e09667d0-7903-4967-bf8c-50c49c82ec02",
"metadata": {},
"source": [
"### Again, compare the latest 2 runs (with dx=1/4 and dx=1/10)"
]
},
{
"cell_type": "code",
"execution_count": 38,
"id": "0214630a-0762-49f8-a075-f81bbed36503",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Max of unsigned absolute differences: 0.1037682236950559\n",
"L2 norm of differences (vectors) / Frobenius norm (matrices): 0.16693544887735995\n",
"Max of unsigned relative differences: 0.002317733310755785\n",
"Mean of relative differences: -6.382496227915533e-05\n",
"Median of relative differences: -2.2808505444596986e-05\n",
"Standard deviation of relative differences: 0.0003503290914748486\n",
"np.allclose with lax tolerance? (rtol=1e-01, atol=1e-01) : True\n",
"np.allclose with mid tolerance? (rtol=1e-02, atol=1e-03) : True\n",
"np.allclose with tight tolerance? (rtol=1e-03, atol=1e-05) : False\n",
"np.allclose with extra-tight tolerance? (rtol=1e-05, atol=1e-08) : False\n"
]
}
],
"source": [
"num.compare_states(diffuse_dx_1_4 , diffuse_dx_1_10)"
]
},
{
"cell_type": "markdown",
"id": "850eea0e-ac7d-43c6-a5ba-7934fb008c1a",
"metadata": {},
"source": [
"### Notice how the discrepancies have gone down even more\n",
"### This matches expectations that we're getting closer and closer to a \"true\" (very high precision) value, as we keep increasing the spacial resolution"
]
},
{
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"id": "b3ae84bc-72b9-4043-b5b9-70532eafdb44",
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"outputs": [],
"source": []
}
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