Sorry this is in HTML, but the documentation below requires it. The latest source release is 17.2.0. Revised documentation in HTML and PDF is available at http://numpy.sourceforge.net. Package MA contains a number of new constructors. The complete list is: Constructing masked arrays 1.. array (data, typecode = None, copy = 1, savespace = 0, mask = None, fill_value = None) creates a masked array with the given data and mask. The name array is simply an alias for the class name, MA. This constructor sets the data area of the resulting masked array to filled (data, value = fill_value, copy = copy, savespace = savespace), the mask to make_mask (mask, savespace), and the fill value is set to fill_value. The class name MA may also be used instead of the name array. 2.. masked_array (data, mask = None, fill_value = None) is an easier to use version of array, for the common case of typecode = None, copy = 0. When data is newly-created this function can be used to make it a masked array without copying the data if data is already a Numeric array. 3.. masked_values (data, value, rtol=1.e-5, atol=1.e-8, typecode = None, copy = 1, savespace = 0) constructs a masked array whose mask is set at those places where abs (data - value) < atol + rtol * abs (data). That is a careful way of saying that those elements of the data that have value = value (to within a tolerance) are to be treated as invalid. 4.. masked_object (data, value, copy=1, savespace=0) creates a masked array with those entries marked invalid that are equal to value. Again, copy and savespace are passed on to the Numeric array constructor. 5.. masked_where (condition, data) creates a masked array whose shape is that of condition, whose values are those of data, and which is masked where elements of condition are true. 6.. masked_greater (data, value) is equivalent to masked_where (greater(data, value), data)). Similarly, masked_greater_equal, masked_equal, masked_not_equal, masked_less, masked_less_equal are called in the same way with the obvious meanings. Note that for floating point data, masked_values is preferable to masked_equal in most cases. On entry to any of these constructors, data must be any object which the Numeric package can accept to create an array (with the desired typecode, if specified). The mask if given must be None or any object that can be turned into a Numeric array of integer type (it will be converted to typecode MaskType, if necessary), have the same shape as data, and contain only values of 0 or 1. If the mask is not None but its shape does not match that of data, an exception will be thrown, unless one of the two is of length 1, in which case the scalar will be resized (using Numeric.resize) to match the other.