def tmin(a, lowerlimit=None, axis=0, inclusive=True, nan_policy='propagate'):
 (a, axis) = _chk_asarray(a, axis)
 am = _mask_to_limits(a, (lowerlimit, None), (inclusive, False))
 (contains_nan, nan_policy) = _contains_nan(am, nan_policy)
 if (contains_nan and (nan_policy == 'omit')):
  am = ma.masked_invalid(am)
 res = ma.minimum.reduce(am, axis).data
 if (res.ndim == 0):
  return res[()]
 return res

def tmin ( a , lowerlimit = None , axis = 0 , inclusive = True , nan_policy = 'propagate' ) : ( a , axis ) = _chk_asarray ( a , axis ) am = _mask_to_limits ( a , ( lowerlimit , None ) , ( inclusive , False ) ) ( contains_nan , nan_policy ) = _contains_nan ( am , nan_policy ) if ( contains_nan and ( nan_policy == 'omit' ) ) : am = ma . masked_invalid ( am ) res = ma . minimum . reduce ( am , axis ) . data if ( res . ndim == 0 ) : return res [ ( ) ] return res
compute the trimmed minimum this function finds the miminum value of an array a along the specified axis .