@staticmethod<EOL><INDENT>def _reshape_input_data(shape, desired_dim=<NUM_LIT:3>):<DEDENT>
if (len(shape) > <NUM_LIT:3>):<EOL><INDENT>raise ValueError("""<STR_LIT>""")<EOL><DEDENT>if (len(shape) > desired_dim):<EOL><INDENT>raise ValueError("<STR_LIT>")<EOL><DEDENT>elif len(shape) == <NUM_LIT:1>:<EOL><INDENT>if (desired_dim == <NUM_LIT:3>):<EOL><INDENT>return ((shape[<NUM_LIT:0>], <NUM_LIT:1>, <NUM_LIT:1>), shape)  <EOL><DEDENT>elif (desired_dim == <NUM_LIT:2>):<EOL><INDENT>return ((shape[<NUM_LIT:0>], <NUM_LIT:1>), shape)<EOL><DEDENT><DEDENT>elif len(shape) == <NUM_LIT:2>:<EOL><INDENT>if (desired_dim == <NUM_LIT:3>):<EOL><INDENT>return ((shape[<NUM_LIT:1>], <NUM_LIT:1>, <NUM_LIT:1>), shape) if (shape[<NUM_LIT:0>] == <NUM_LIT:1>) else((shape[<NUM_LIT:0>], shape[<NUM_LIT:1>], <NUM_LIT:1>), shape)  <EOL><DEDENT>elif (desired_dim == <NUM_LIT:2>):<EOL><INDENT>return ((shape[<NUM_LIT:1>], <NUM_LIT:1>), shape) if (shape[<NUM_LIT:0>] == <NUM_LIT:1>) else((shape[<NUM_LIT:0>], shape[<NUM_LIT:1>]), None)  <EOL><DEDENT><DEDENT>else:  <EOL><INDENT>return (shape, None)<EOL><DEDENT>
Static function returns the column-wise shape for for an input shape.

Input:
--------------
    shape: tuple
        Shape of an input array, so that it is always a column.

    desired_dim: int
        desired shape of output. For Y data it should be 3
        (sample_no, dimension, ts_no). For X data - 2 (sample_no, 1)
Output:
--------------
    new_shape: tuple
        New shape of the measurements array. Idea is that samples are
        along dimension 0, sample dimension - dimension 1, different
        time series - dimension 2.
    old_shape: tuple or None
        If the shape has been modified, return old shape, otherwise
        None.