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Collect the first ``n`` local maxima and minima of the training signal which are separated by a minimum gap ``d``. This is an analysis node, i.e. the data is analyzed during training and the results are stored internally. Use the ``get_maxima`` and ``get_minima`` methods to access them.
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_train_seq List of tuples:: |
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dtype dtype |
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input_dim Input dimensions |
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output_dim Output dimensions |
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supported_dtypes Supported dtypes |
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Input arguments: n -- Number of maxima and minima to store d -- Minimum gap between two maxima or two minima
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Return the list of dtypes supported by this node.
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Return the tuple (maxima, indices). Maxima are sorted in descending order. If the training phase has not been completed yet, call stop_training. |
Return the tuple (minima, indices). Minima are sorted in ascending order. If the training phase has not been completed yet, call stop_training. |
Update the internal structures according to the input data `x`. `x` is a matrix having different variables on different columns and observations on the rows. By default, subclasses should overwrite `_train` to implement their training phase. The docstring of the `_train` method overwrites this docstring. Note: a subclass supporting multiple training phases should implement the *same* signature for all the training phases and document the meaning of the arguments in the `_train` method doc-string. Having consistent signatures is a requirement to use the node in a flow.
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