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docs: add basic Variable documentation
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@hollandjg
hollandjg committed Dec 20, 2023
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{
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"# `autora.variable`: `Variable` and `VariableCollection`\n",
"\n",
"`autora.variable.Variable` represents an experimental variable: \n",
"- an independent variable, or\n",
"- dependent variable.\n",
"\n",
"They can be initialized as follows:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "c2bfbd97b0a14547",
"metadata": {},
"outputs": [],
"source": [
"from autora.variable import Variable\n",
"\n",
"x1 = Variable(\n",
" name=\"x1\",\n",
")\n",
"x2 = Variable(\n",
" name=\"x2\",\n",
")\n",
"y = Variable(\n",
" name=\"y\",\n",
")"
]
},
{
"cell_type": "markdown",
"id": "3d195cbb145dcd58",
"metadata": {},
"source": [
"A group of `Variables` representing the domain of an experiment is a `autora.variable.VariableCollection`. \n",
"\n",
"They can be initialized as follows:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "8f1dce3b50b7984c",
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"outputs": [
{
"data": {
"text/plain": [
"VariableCollection(independent_variables=[Variable(name='x1', value_range=None, allowed_values=None, units='', type=<ValueType.REAL: 'real'>, variable_label='', rescale=1, is_covariate=False), Variable(name='x2', value_range=None, allowed_values=None, units='', type=<ValueType.REAL: 'real'>, variable_label='', rescale=1, is_covariate=False)], dependent_variables=[Variable(name='y', value_range=None, allowed_values=None, units='', type=<ValueType.REAL: 'real'>, variable_label='', rescale=1, is_covariate=False)], covariates=[])"
]
},
"execution_count": null,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from autora.variable import VariableCollection\n",
"\n",
"VariableCollection(\n",
" independent_variables=[x1, x2],\n",
" dependent_variables=[y]\n",
")"
]
},
{
"cell_type": "markdown",
"id": "80e85b4c6997a5fe",
"metadata": {},
"source": [
"For the full list of arguments, see the documentation in the `autora.variable` submodule.\n",
"\n",
"Some functions included in AutoRA use specific values stored on the Variable objects. For instance, the \n",
"`autora.experimentalist.grid.pool` uses the `allowed_values` field to create a grid of conditions:"
]
},
{
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"<div>\n",
"<style scoped>\n",
" .dataframe tbody tr th:only-of-type {\n",
" vertical-align: middle;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
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"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>x1</th>\n",
" <th>x2</th>\n",
" </tr>\n",
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" <td>-2</td>\n",
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" <tr>\n",
" <th>5</th>\n",
" <td>-2</td>\n",
" <td>13</td>\n",
" </tr>\n",
" <tr>\n",
" <th>6</th>\n",
" <td>-3</td>\n",
" <td>11</td>\n",
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" <tr>\n",
" <th>7</th>\n",
" <td>-3</td>\n",
" <td>12</td>\n",
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" <tr>\n",
" <th>8</th>\n",
" <td>-3</td>\n",
" <td>13</td>\n",
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"text/plain": [
" x1 x2\n",
"0 -1 11\n",
"1 -1 12\n",
"2 -1 13\n",
"3 -2 11\n",
"4 -2 12\n",
"5 -2 13\n",
"6 -3 11\n",
"7 -3 12\n",
"8 -3 13"
]
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"metadata": {},
"output_type": "execute_result"
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"source": [
"from autora.experimentalist.grid import grid_pool\n",
"\n",
"grid_pool(\n",
" VariableCollection(independent_variables=[\n",
" Variable(name=\"x1\", allowed_values=[-1, -2, -3]),\n",
" Variable(name=\"x2\", allowed_values=[11, 12, 13])\n",
" ])\n",
")"
]
},
{
"cell_type": "markdown",
"id": "6f3f12554ba12ad",
"metadata": {},
"source": [
"The `autora.experimentalist.random.pool` uses the `value_range` field to sample conditions:"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f890f05dd5c601ab",
"metadata": {},
"outputs": [
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" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>x1</th>\n",
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" </thead>\n",
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" <td>0.456338</td>\n",
" <td>101.527294</td>\n",
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" <td>1.008636</td>\n",
" <td>101.297280</td>\n",
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" <th>2</th>\n",
" <td>0.319617</td>\n",
" <td>101.962166</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>-1.753273</td>\n",
" <td>101.859696</td>\n",
" </tr>\n",
" <tr>\n",
" <th>4</th>\n",
" <td>-1.933420</td>\n",
" <td>101.201565</td>\n",
" </tr>\n",
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"text/plain": [
" x1 x2\n",
"0 0.456338 101.527294\n",
"1 1.008636 101.297280\n",
"2 0.319617 101.962166\n",
"3 -1.753273 101.859696\n",
"4 -1.933420 101.201565"
]
},
"execution_count": null,
"metadata": {},
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}
],
"source": [
"from autora.experimentalist.random import random_pool\n",
"\n",
"random_pool(\n",
" VariableCollection(independent_variables=[\n",
" Variable(name=\"x1\", value_range=(-3, 3)),\n",
" Variable(name=\"x2\", value_range=(101, 102))\n",
" ]), \n",
" random_state=180\n",
")"
]
},
{
"cell_type": "markdown",
"id": "f4ab2b25903f40a7",
"metadata": {},
"source": [
"The `autora.state.estimator_from_state` function uses the `names` of the variables to pass the correct columns to a \n",
"scikit-learn compatible estimator for curve fitting."
]
},
{
"cell_type": "markdown",
"id": "3f4d28f5979fe9cb",
"metadata": {},
"source": [
"Check the documentation for any functions you are using to determine whether you need to include specific metadata."
]
}
],
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