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README.rst

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@@ -94,14 +94,14 @@ Example
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:width: 800
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:alt: An example figure showing the component vectors of a three component PARAFAC model fitted to a fluoresence spectroscopy dataset.
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This example uses TensorLy to fit five three-component PARAFAC models to the data. Then it uses TLViz to:
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#. Select the model that gave the lowest reconstruction error,
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#. normalise the component vectors, storing their magnitude in a separate weight-vector,
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#. permute the components in descending weight (i.e. signal strength) order,
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#. flip the components so they point in a logical direction compared to the data,
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#. convert the factor matrices into Pandas DataFrames with logical indices,
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#. and plot the components using matplotlib.
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This example uses TensorLy to fit five three-component PARAFAC models to the data. Then it uses TLViz to do the following steps:
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#. Select the model that gave the lowest reconstruction error.
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#. Normalise the component vectors, storing their magnitude in a separate weight-vector.
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#. Permute the components in descending weight (i.e. signal strength) order.
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#. Flip the components so they point in a logical direction compared to the data.
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#. Convert the factor matrices into Pandas DataFrames with logical indices.
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#. Plot the components using matplotlib.
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All these steps are described in the `API documentation <https://tensorly.org/viz/stable/api.html>`_ with references to the literature.
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