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"source": [
"# Generate a Simulated Data Tensor\n",
"\n",
"This notebook demonstrates how to generate a simulated data tensor using the `simulated_sparse_tensor()` function of the `Barnacle` library. In this example we generate a mode-3 data tensor from 5 sparse simulated components. We use the `barnacle.visualize_3d_tensor()` function to visualize the simulated data tensor, as well as the components used to generate the simulation, and we use the `barnacle.plot_factors_heatmap()` to visualize the factors matrices used to generate the simulation components."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"# imports\n",
"\n",
"import numpy as np\n",
"import scipy\n",
"import tensorly as tl\n",
"from barnacle import (\n",
" visualize_3d_tensor, \n",
" simulated_sparse_tensor, \n",
" plot_factors_heatmap\n",
")\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"5\n",
"5\n",
"5\n"
]
}
],
"source": [
"# generate simulated data tensor\n",
"\n",
"true_rank = 5\n",
"true_shape = [15, 20, 10]\n",
"true_densities = [.4, .2, .6]\n",
"\n",
"# re-seed simulated data until all factor matrices are full rank\n",
"full_rank = False\n",
"while not full_rank:\n",
" # generate simulated tensor\n",
" sim_tensor = simulated_sparse_tensor(\n",
" shape=true_shape, \n",
" rank=true_rank, \n",
" densities=true_densities, \n",
" factor_dist_list=[\n",
" scipy.stats.uniform(), \n",
" scipy.stats.uniform(loc=-1, scale=2), \n",
" scipy.stats.uniform()\n",
" ], \n",
" random_state=9481\n",
" )\n",
" # check that all factors are full rank\n",
" full_rank = np.all([np.linalg.matrix_rank(factor) == true_rank for factor in sim_tensor.factors])\n",
"\n",
"# ensure that factor matrices are full rank\n",
"for factor in sim_tensor.factors:\n",
" print(np.linalg.matrix_rank(factor))\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
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"# visualize simulated tensor data\n",
"\n",
"fig = visualize_3d_tensor(\n",
" sim_tensor.to_tensor(),\n",
" shell=False, \n",
" midpoint=0, \n",
" show_colorbar=True,\n",
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")\n",
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""
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},
"metadata": {},
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],
"source": [
"# visualize each individual component used to generate the simulated data tensor\n",
"\n",
"for i in range(true_rank):\n",
" component = sim_tensor.get_components()[i]\n",
" fig = visualize_3d_tensor(\n",
" component.to_tensor(), \n",
" shell=False, \n",
" midpoint=0, \n",
" show_colorbar=False,\n",
" label_axes=True, \n",
" range_color=[-1, 1], \n",
" opacity=1\n",
" )\n",
" print(f'Component {i}')\n",
" fig.show()\n"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
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",
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# visualize the factor matrices used to generate the simulated data tensor\n",
"\n",
"heatmap_params = {'vmin':-1, 'vmax':1, 'cmap':'seismic', 'center':0}\n",
"fig, ax = plot_factors_heatmap(\n",
" tl.cp_normalize(sim_tensor).factors, \n",
" mask_thold=[0, 0], \n",
" ratios=True, \n",
" heatmap_kwargs=heatmap_params\n",
")\n"
]
}
],
"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": "3.10.8"
}
},
"nbformat": 4,
"nbformat_minor": 4
}