MV2

allclose(a, b[, masked_equal, rtol, atol])	Returns True if two arrays are element-wise equal within a tolerance.
allequal(a, b[, fill_value])	Return True if all entries of a and b are equal, using fill_value as a truth value where either or both are masked.
arange(start[, stop, step, typecode, axis, …])	Just like range() except it returns a variable whose type can be specfied by the keyword argument typecode.
argsort(x[, axis, fill_value])	Treating masked values as if they have the value fill_value, return sort indices for sorting along given axis.
arrayrange(start[, stop, step, typecode, …])	Just like range() except it returns a variable whose type can be specfied by the keyword argument typecode.
asarray(data[, typecode, dtype, dtype, copy])	Assarray
as_masked(data[, dtype, copy, order, mask, …])	An array class with possibly masked values.
asVariable(s[, writeable])	As Variable
average(a[, axis, weights, returned])	Return the weighted average of array over the given axis.
axisAllclose(ax1, ax2[, rtol, atol])	All close
axisConcatenate(axes[, id, attributes])	Concatenate multiple axes including boundaries.
axisTake(ax, indices)	Take elements form an array along an axis
choose(myindices, t)	Choose
commonAxes(a, bdom[, omit])	Helper function for commonDomain.
commonDomain(a, b[, omit])	Common Domain
common_fill_value(a, b)	Return the common filling value of two masked arrays, if any.
commonGrid1(a, gb, axes)	Helper function for commonGrid.
commonGrid(a, b, axes)	Common Grid
compress(a, b)
concatenate(arrays[, axis, axisid, …])	Concatenate the arrays along the given axis.
count(a[, axis])	Count of the non-masked elements in a, or along a certain axis.
create_mask(newshape[, dtype])	Return a boolean mask of the given shape, filled with False.
diagonal(a[, offset, axis1, axis2])	Diagonal
dot(a, b[, strict, out])	Return the dot product of two arrays.
filled(a[, fill_value])	Return input as an array with masked data replaced by a fill value.
fill_value(ar)
fromfunction(f, dimensions)	Apply f to s to create an array as in numpy.
getmaskarray(arr)	Return the mask of a masked array, or full boolean array of False.
getmask(a)	Return the mask of a masked array, or nomask.
getNumericCompatibility()
get_print_limit()
get_printoptions()	Return the current print options.
indices(dimensions[, dtype, sparse])	Return an array representing the indices of a grid.
innerproduct(a, b)	Inner product of two arrays.
isarray(x)	Test whether input is an instance of MaskedArray.
is_floating(x)	Is x a scalar float, either python or numpy?
is_integer(x)	Is x a scalar integer, either python or numpy?
isMA(x)	Test whether input is an instance of MaskedArray.
isMaskedArray(x)	Test whether input is an instance of MaskedArray.
is_masked(x)	Is x a 0-D masked value?
isMaskedVariable(x)	Is x a masked variable, that is, an instance of AbstractVariable?
is_mask(m)	Return True if m is a valid, standard mask.
left_shift(a, n)	Left shift n bits
make_mask_none(newshape[, dtype])	Return a boolean mask of the given shape, filled with False.
make_mask(m[, copy, shrink, dtype])	Create a boolean mask from an array.
masked_array(a[, mask, fill_value, axes, …])	Masked Array
masked_equal(x, value)	masked_equal(x, value) = x masked where x == value For floating point consider masked_values(x, value) instead.
masked_greater_equal(x, value)	masked_greater_equal(x, value) = x masked where x >= value
masked_greater(x, value)	masked_greater(x, value) = x masked where x > value
masked_inside(x, v1, v2)	x with mask of all values of x that are inside [v1,v2]
masked_less_equal(x, value)	masked_less_equal(x, value) = x masked where x <= value
masked_less(x, value)	masked_less(x, value) = x masked where x < value
masked_not_equal(x, value)	masked_not_equal(x, value) = x masked where x != value
masked_object(data, value[, copy, …])	Create array masked where exactly data equal to value
masked_outside(x, v1, v2)	x with mask of all values of x that are outside [v1,v2]
masked_values(data, value[, rtol, atol, …])	Masked Values
masked_where(condition, x[, copy])	Marked Where
mask_or(m1, m2[, copy, shrink])	Combine two masks with the logical_or operator.
max(a[, axis])	Return the maximum along a given axis.
min(a[, axis])	Return the minimum along a given axis.
ones(myshape[, typecode, savespace, axes, …])	ones(n, typecode=float, savespace=0, axes=None, attributes=None, id=None) = an array of all ones of the given length or shape.
outerproduct(a,b) =, has shape ,len)
power(a, b[, third])	a**b
product(a[, axis, dtype])	Product of elements along axis.
putmask(a, mask, values)	Changes elements of an array based on conditional and input values.
put(a, indices, values[, mode])	Set storage-indexed locations to corresponding values.
repeat(a, repeats[, axis])	repeat elements of a repeats times along axis repeats is a sequence of length a.shape[axis] telling how many times to repeat each element.
reshape(a, newshape[, axes, attributes, id, …])	numpy doc:
resize(a, new_shape)	Resize
right_shift(a, n)	Right shift n bits
sctype2char(sctype)	Return the string representation of a scalar dtype.
set_default_fill_value(value_type, value)	Set the default fill value for value_type to value.
set_fill_value(a, fill_value)	Set the filling value of a, if a is a masked array.
set_print_limit([limit])
set_printoptions([precision, threshold, …])	Set printing options.
shape(obj)	Return the shape of an array.
size(obj[, axis])	Return the number of elements along a given axis.
sort(a[, axis])	The sort axis is replaced with a dummy axis.
squeeze(x)	call numpy.squeeze on ndarray and rebuild tvariable.
sum(a[, axis, fill_value, dtype])	Sum of elements along a certain axis.
take(a, myindices[, axis])	take(a, indices, axis=None) returns selection of items from a.
transpose(a[, axes])	transpose(a, axes=None) reorder dimensions per tuple axes
where(condition, x, y)	where(condition, x, y) is x where condition is true, y otherwise
zeros(myshape[, typecode, savespace, axes, …])	zeros(n, typecode=float, savespace=0, axes=None, attributes=None, id=None) = an array of all zeros of the given length or shape.