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641be67
commit before merge with changes to dictionary_vector_space
Aug 5, 2024
51e1bf8
Prettified all vector space notebook tutorials.
Aug 6, 2024
b672d88
finished edits to the vector_space, parameter_space, models, single m…
Aug 7, 2024
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13 changes: 9 additions & 4 deletions docs/source/conf.py
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Expand Up @@ -29,13 +29,18 @@
"sphinx.ext.intersphinx",
"sphinx_copybutton",
"sphinx_design",
"myst_nb",
"nbsphinx",
"jupyter_sphinx",
'sphinx.ext.todo',
'sphinx.ext.mathjax',
'sphinx.ext.ifconfig',
'sphinx.ext.napoleon',
# 'myst_nb',
]

nbsphinx_custom_formats = {
".md": ["jupytext.reads", {"fmt": "mystnb"}],
}
# nbsphinx_custom_formats = {
# ".md": ["jupytext.reads", {"fmt": "mystnb"}],
# }

# Adjusting size of embedded HTMLs
html_static_path = ['_static']
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133 changes: 85 additions & 48 deletions docs/source/notebooks/basic_model.ipynb
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202 changes: 134 additions & 68 deletions docs/source/notebooks/basic_sampling.ipynb
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189 changes: 143 additions & 46 deletions docs/source/notebooks/composite_vector_space.ipynb
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163 changes: 122 additions & 41 deletions docs/source/notebooks/dictionary_vector_space.ipynb
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293 changes: 210 additions & 83 deletions docs/source/notebooks/external_model.ipynb
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184 changes: 137 additions & 47 deletions docs/source/notebooks/external_qoi_model.ipynb
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Expand Up @@ -7,46 +7,69 @@
"source": [
"# External QoiModel tutorial\n",
"\n",
"In this tutorial you will learn the basics of the QoiModel interface. The QoIModel interface is almost identical to the model interface,\n",
"but has an additional method called compute_qoi() where it returns a (usually scalar) quantity of interest. This type of model is useful for various workflows, such as training a ROM to a desired tolerance on a specified QoI. The API for the model interface is provided here:\n",
"\n",
"https://pressio.github.io/rom-tools-and-workflows/romtools/workflows/models.html\n"
"In this tutorial you will learn the basics of the `QoiModel` interface. The `QoIModel` interface is almost identical to the `Model` interface,\n",
"but has an additional method called `compute_qoi()` where it returns a (usually scalar) quantity of interest. This type of model is useful for various workflows, such as training a ROM to a desired tolerance on a specified QoI. The API for the model interface is provided [here](https://pressio.github.io/rom-tools-and-workflows/romtools/workflows/models.html).\n"
]
},
{
"cell_type": "markdown",
"id": "81661d69",
"metadata": {},
"source": [
"## Modules\n",
"Here are the relevant modules for this example."
]
},
{
"cell_type": "code",
"execution_count": 11,
"execution_count": null,
"id": "358fb709-9c81-45a3-a871-2549de121580",
"metadata": {},
"outputs": [],
"source": [
"#First, let's import the relavant modules:\n",
"%%capture\n",
"import romtools\n",
"import os\n",
"import numpy as np\n",
"from matplotlib import pyplot as plt\n",
"from romtools.workflows import models"
]
},
{
"cell_type": "markdown",
"id": "a1c0d073",
"metadata": {},
"source": [
"## Model Definition\n",
"As a starting point, we will use the model created in the `external_model` tutorial."
]
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "b1ffa4be-246c-44a9-b486-f517b9f7acb9",
"metadata": {},
"outputs": [],
"source": [
"# As a starting point, we will use the model created in the external_model tutorial\n",
"from ipynb.fs.full.external_model import adrExternalRomToolsModel"
]
},
{
"cell_type": "markdown",
"id": "f8d5c05e",
"metadata": {},
"source": [
"## Model Class Definition\n",
"Now, we will create a QoI model. As a QoI, we will take the gradient of the state at the right of the domain."
]
},
{
"cell_type": "code",
"execution_count": 9,
"execution_count": null,
"id": "217759fb-6ec9-4488-897b-e5b4db9f4b2c",
"metadata": {},
"outputs": [],
"source": [
"#Now, we will create a QoI model. As a QoI, we will take the gradient of the state at the right of the domain\n",
"class adrExternalRomToolsQoiModel(adrExternalRomToolsModel):\n",
" # Our class will inherit all the methods from adrExternalRomToolsModel\n",
" \n",
Expand All @@ -57,52 +80,119 @@
" x = solution['x']\n",
" dx = x[1] - x[0] #we use a uniform grid\n",
" ux_at_right_edge = (0. - u[-1])/dx\n",
" return ux_at_right_edge\n",
"\n",
"# We can now instatiate our QoI\n",
"myModel = adrExternalRomToolsQoiModel()\n",
" return ux_at_right_edge"
]
},
{
"cell_type": "markdown",
"id": "1f21b795",
"metadata": {},
"source": [
"We can now instatiate our QoI."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "411588c9",
"metadata": {},
"outputs": [],
"source": [
"myModel = adrExternalRomToolsQoiModel()"
]
},
{
"cell_type": "markdown",
"id": "665ddbfe",
"metadata": {},
"source": [
"That's it!"
]
},
{
"cell_type": "markdown",
"id": "dfbb0c29",
"metadata": {},
"source": [
"## Example\n",
"Let's do an example run of the model similar to how it will be used in a workflow.\n",
"\n",
"#That's it!"
"First, let's make a dictionary that is a stand in for the parameter space."
]
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": null,
"id": "dbf42fd4-340f-4074-9682-69a9df424b26",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The QoI is -6.429918802201725\n"
]
}
],
"source": [
"#Let's do an example run of the model similar to how it will be used in a workflow.\n",
"\n",
"if __name__==\"__main__\":\n",
" #First, let's make a dictionary that is a stand in for the parameter space\n",
" parameter_sample = {}\n",
" parameter_sample['c'] = 0.5\n",
" parameter_sample['nu'] = 1e-1\n",
"\n",
" #Now, let's populate our run directory. In this example, we will just use the current run directory.\n",
" #In a full workflow, romtools will manage creating directories\n",
" myModel.populate_run_directory(os.getcwd(),parameter_sample)\n",
"\n",
" #Now, let's run the model\n",
" run_dir = os.getcwd()\n",
"outputs": [],
"source": [
"parameter_sample = {}\n",
"parameter_sample['c'] = 0.5\n",
"parameter_sample['nu'] = 1e-1"
]
},
{
"cell_type": "markdown",
"id": "66d99534",
"metadata": {},
"source": [
"Now, let's populate our run directory. In this example, we will just use the current run directory.\n",
"In a full workflow, romtools will manage creating directories."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "32b442c6",
"metadata": {},
"outputs": [],
"source": [
"myModel.populate_run_directory(os.getcwd(),parameter_sample)"
]
},
{
"cell_type": "markdown",
"id": "7d29ca27",
"metadata": {},
"source": [
"Now, let's run the model and compute the QoI."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8b7ce69d",
"metadata": {},
"outputs": [],
"source": [
"run_dir = os.getcwd()\n",
"\n",
" myModel.run_model(run_dir,parameter_sample)\n",
"myModel.run_model(run_dir,parameter_sample)\n",
"\n",
" qoi = myModel.compute_qoi(run_dir,parameter_sample)\n",
"qoi = myModel.compute_qoi(run_dir,parameter_sample)\n",
"\n",
" print('The QoI is ' + str(qoi))\n",
" #We will finish by cleaning up the files we created\n",
" os.system('rm params.dat')\n",
" os.system('rm solution.npz')"
"print('The QoI is ' + str(qoi))"
]
},
{
"cell_type": "markdown",
"id": "746f061a",
"metadata": {},
"source": [
"We will finish by cleaning up the files we created."
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "99887167",
"metadata": {},
"outputs": [],
"source": [
"%%capture\n",
"os.system('rm params.dat')\n",
"os.system('rm solution.npz')"
]
}
],
Expand All @@ -122,7 +212,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.12.4"
"version": "3.11.9"
}
},
"nbformat": 4,
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