def _lag_view()

in afa/core.py [0:0]

• 6 lines of code
• 4 McCabe index (conditional complexity)

    def _lag_view(self, x, order):
        """
        For every value X_i create a row that lags k values: [X_i-1, X_i-2, ... X_i-k]
        """
        y = x.copy()
        # Create features by shifting the window of `order` size by one step.
        # This results in a 2D array [[t1, t2, t3], [t2, t3, t4], ... [t_k-2, t_k-1, t_k]]
        x = np.array([y[-(i + order):][:order] for i in range(y.shape[0])])
        
        # Reverse the array as we started at the end and remove duplicates.
        # Note that we truncate the features [order -1:] and the labels [order]
        # This is the shifting of the features with one time step compared to the labels
        x = np.stack(x)[::-1][order - 1: -1]
        y = y[order:]

        return x, y