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MLinExpr.__getitem__()

__getitem__ ( )

Index or slice this MLinExpr.

Return value:

An MLinExpr object.

Example usage:

  mle = 2 * m.addMVar((2,2))
col0 = mle[:, 0]  # The first column of mle, 1-D result
elmt = mle[1, 0]  # The element at position (1, 0), 0-D result


You can index and slice MLinExpr objects like you would index NumPy's ndarray, and indexing behaviour is straighforward to understand if you only read from the returned object. When you write to the returned object, be aware that some kinds of indexing return NumPy views on the indexed expression (e.g., slices), while others result in copies being returned (e.g., fancy indexing). Here is an example:

Example usage:

  mle = 2 * m.addMVar(4)

If you are unsure about any of these concepts and want to avoid any risk of accidentally writing back to the indexed object, you should always combine indexing with the copy method.
  expr = 2 * model.addMVar((2,2)) + 1