Highlights:

• #184 Python 3 source compatibility
• #193 test with numpy 1.9
• #176 Failing type return on masked array on LHS
• #195 #197 Replace vectorize with list comprehension in ArrayStack.deepcopy

Highlights:

• #151 NumPy 1.10+1.11 fixes
• #173 Np slice stack deepcopy
• #177 Namespace tidy
• #183 Re-add ArrayContainer to public API
• #181 Add functionality to create a lazy masked array where equal to a given value

Highlights:

• Add support for all NumPy ufuncs and a few more besides (#153).
• Add r* operators (#155).
• Fix indexing of broadcast dimension (#156).
• Fix ArrayStack for Fortran-order arrays (#159).
• Fix indexing of unary operations (#162).
• Fix the handling of masked arrays for unary operations (#167).
• Fix the ability to use binary operators on two different bit-length data types (#165).
• Mimic NumPy's special type-promotion behaviour when dealing with Python floats & ints (#169).

Highlights:

• A fix for the __getitem__ for LinearMosaic that corrects array slicing output (#147).
• Biggus' __div__ method properly accounts for the dtype of arguments passed to it (#149).
• Added support for Python 3.5 (#150).

Highlights:

• Fix to ndarray indexing on LinearMosaic (#144)
• Support for dtype promotion on elementwise operations (#145)
• Addition of __orthogonal_indexing__ protocol (#142)
• Addition of the astype array method and associated AsDataTypeArray object (#141)
• Improved str and repr representations of arrays (#139)

Highlights:

• biggus.multiply(), biggus.floor_divide(), biggus.true_divide(), and biggus.power()
• Operator support for +, -, *, /, //, and **.
• Improved broadcasting.

Fixes error when indexing with N+1 keys where one of the keys is an Ellipsis.

Highlights:

• Adds Array.transpose() (using TransposedArray).
• Support for indexing with np.newaxis to add new axes.
• Support automatic numpy array conversion via __array__().
• Initial broadcasting support via BroadcastArray.
• A more human-readable format for str().

Other improvements:

• Tests work on 32-bit platforms.

Highlights:

• Support for NumPy 1.9
• Create LinearMosaic and ArrayStack from arrays with inhomogeneous fill_values.
• Extend biggus.save() to allow masked array output.

Bug fixes:

• Masked array evaluation of variance. (#107)
• LinearMosaic indexing with non-zero axis. (#113)

Highlights include:

• min, max and sum operators
• boolean indexing
• fixed indexing of aggregations with a non-zero axis