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# numpy.amin

`numpy.``amin`(a, axis=None, out=None)

  Return the minimum of an array or minimum along an axis.

  Parameters : | a : array_like Input data. axis : int, optional Axis along which to operate. By default a flattened input is used. out : ndarray, optional Alternative output array in which to place the result. Must be of the same shape and buffer length as the expected output. See doc.ufuncs (Section “Output arguments”) for more details.
  Returns : | amin : ndarray A new array or a scalar array with the result.

  See also

  `nanmin`
    nan values are ignored instead of being propagated
  `fmin`
    same behavior as the C99 fmin function
  `argmin`
    Return the indices of the minimum values.

  `amax`, `nanmax`, `fmax`

  Notes

  NaN values are propagated, that is if at least one item is nan, the corresponding min value will be nan as well. To ignore NaN values (matlab behavior), please use nanmin.

  Examples

      >>> a = np.arange(4).reshape((2,2))
      >>> a
      array([[0, 1],
             [2, 3]])
      >>> np.amin(a)           # Minimum of the flattened array
      0
      >>> np.amin(a, axis=0)         # Minima along the first axis
      array([0, 1])
      >>> np.amin(a, axis=1)         # Minima along the second axis
      array([0, 2])

      >>> b = np.arange(5, dtype=np.float)
      >>> b[2] = np.NaN
      >>> np.amin(b)
      nan
      >>> np.nanmin(b)
      0.0

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