CHANGELOG.md

v3.6.20181017

• Feature parity with ArrayFire v3.6. Refer to the release notes for more information regarding upstream library improvements in v3.6.
  • anisotropic_diffusion(): Anisotropic diffusion filter.
  • topk(): Returns top-K elements given an array.
• Bug fixes:
  • Fixed sift() and gloh(), which were improperly calling the library.
• Enhancements:
  • Added len() method, which returns array.elements().
• Documentation:
  • Documented statistics API.
  • Corrected sign() documentation.
  • Modified helloworld example to match C++ lib.

v3.5.20170721

• Bug fixes when using v3.5 of arrayfire libs + graphics

v3.5.20170721

• Bug fixes for canny edge detection

v3.5.20170718

• Feature parity with ArrayFire 3.5.

  • canny: Canny Edge detector
  • Array.scalar: Return the first element of the array
  • dot: Now support option to return scalar
  • print_mem_info: Prints memory being used / locked by arrayfire memory manager.
  • Array.allocated: Returs the amount of memory allocated for the given buffer.
  • set_fft_plan_cache_size: Sets the size of the fft plan cache.

• Bug Fixes:

  • sort_by_key had key and value flipped in documentation.

• Improvements and bugfixes from upstream include:

  • CUDA backend uses nvrtc instead of nvvm
  • Performance improvements to arrayfire.reorder
  • Faster unified backend
  • You can find more information at arrayfire's release notes

v3.4.20170222

• Bugfix: Fixes typo in approx1.
• Bugfix: Fixes typo in hamming_matcher and nearest_neighbour.
• Bugfix: Added necessary copy and lock mechanisms in interop.py.
• Example / Benchmark: New conjugate gradient benchmark.
• Feature: Added support to create arrayfire arrays from numba.
• Behavior change: af.print() only prints full arrays for smaller sizes.

v3.4.20161126

• Fixing memory leak in array creation.
• Supporting 16 bit integer types in interop.

v3.4.20160925

• Feature parity with ArrayFire 3.4 libs

  • Sparse matrix support

    • create_sparse
    • create_sparse_from_dense
    • create_sparse_from_host
    • convert_sparse_to_dense
    • convert_sparse
    • sparse_get_info
    • sparse_get_nnz
    • sparse_get_values
    • sparse_get_row_idx
    • sparse_get_col_idx
    • sparse_get_storage

  • Random Engine support

    • Three new random engines, RANDOM_ENGINE.PHILOX, RANDOM_ENGINE.THREEFRY, and RANDOM_ENGINE.MERSENNE.
    • randu and randn now accept an additional engine parameter.
    • set_default_random_engine_type
    • get_default_random_engine

  • New functions

    • scan
    • scan_by_key
    • clamp
    • medfilt1
    • medfilt2
    • moments
    • get_size_of
    • get_manual_eval_flag
    • set_manual_eval_flag

  • Behavior changes

    • eval now supports fusing kernels.

  • Graphics updates

    • plot updated to take new parameters.
    • plot2 added.
    • scatter updated to take new parameters.
    • scatter2 added.
    • vector_field added.
    • set_axes_limits added.

• Bug fixes

  • ArrayFire now has higher priority when numpy for mixed operations. ^{1 2}
  • Numpy interoperability issues on Widnows. ¹
  • Switch to a working backend by default. ¹
  • Fixed incorrect behavior for Hermitian transpose and QR. ¹
  • array[0:0] now returns empty arrays. ¹

• Further Improvements from upstream can be read in the arrayfire release notes.

v3.3.20160624

• Adding 16 bit integer support
• Adding support for sphinx documentation

v3.3.20160516

• Bugfix: Increase arrayfire's priority over numpy for mixed operations

• Added new library functions

  • get_backend returns backend name

v3.3.20160510

• Bugfix to af.histogram

• Added missing functions / methods

  • gaussian_kernel

• Added new array properties

  • Array.T now returns transpose
  • Array.H now returns hermitian transpose
  • Array.shape now allows easier access individual dimensions

v3.3.20160427

• Fixes to numpy interop on Windows
• Fixes issues with occasional double free
• Fixes to graphics examples

v3.3.20160328

• Fixes to make arrayfire-python to work on 32 bit systems

v3.3.20160320

• Feature parity with Arrayfire 3.3 libs

  • Functions to interact with arryafire's internal data structures.
    • Array.offset
    • Array.strides
    • Array.is_owner
    • Array.is_linear
    • Array.raw_ptr
  • Array constructor now takes offset and strides as optional parameters.
  • New visualization functions: scatter and scatter3
  • OpenCL backend specific functions:
    • get_device_type
    • get_platform
    • add_device_context
    • delete_device_context
    • set_device_context
  • Functions to allocate and free memory on host and device
    • alloc_host and free_host
    • alloc_pinned and free_pinned
    • alloc_device and free_device
  • Function to query which device and backend an array was created on
    • get_device_id
    • get_backend_id
  • Miscellaneous functions
    • is_lapack_available
    • is_image_io_available

• Interopability

  • Transfer PyCUDA GPUArrays using af.pycuda_to_af_array
  • Transfer PyOpenCL Arrays using af.pyopencl_to_af_array
  • New helper function af.to_array added to convert a different array to arrayfire Array.
    • This function can be used in place of af.xyz_to_af_array functions mentioned above.

• Deprecated functions list

  • lock_device_ptr is deprecated. Use lock_array instead.
  • unlock_device_ptr is deprecated. Use unlock_array instead.

• Bug Fixes:

  • Boolean indexing giving faulty results for multi dimensional arrays.
  • Enum types comparision failures in Python 2.x
  • Support loading SO versioned libraries in Linux and OSX.
  • Fixed typo that prevented changing backend
  • Fixed image processing functions that accepted floating point scalar paramters.
    • Affected functions include: translate, scale, skew, histogram, bilateral, mean_shift.

v3.2.20151224

• Bug fixes:

  • A default AF_PATH is set if none is found as an environment variable.

• Examples:

  • Heston model example uses a smaller data set to help run on low end GPUs.

v3.2.20151214

• Bug fixes:

  • get_version() now returns ints instead of c_int
  • Fixed bug in tests/simple/device.py

• The module now looks at additional paths when loading ArrayFire libraries.

  • Link to the wiki is provided when ctypes.cdll.LoadLibrary fails.

• New function:

  • info_str() returns information similar to info() as a string.

• Updated README.md with latest instructions

v3.2.20151211

• Feature parity with ArrayFire 3.2 libs

  • New computer vision functions: sift, gloh, homography
  • New graphics functions: plot3, surface
  • Functions to load and save native images: load_image_native, save_image_native
  • Use unified backend when possible

• Added missing functions

  • eval, init, convolve2_separable, as_type method
  • cuda backend specific functions
  • opencl backend specific functions
  • timeit function to benchmark arrayfire functions

• Added new examples

  • getting_started: intro, convolve
  • benchmarks: bench_blas, bench_fft
  • financial: monte_carlo_options, black_scholes, heston_model
  • graphics: fractal, histogram, plot3d, conway, surface

• Bug fixes

  • Fixed bug when array types were being reported incorrectly
  • Fixed various bugs in graphics functions

v3.1.20151111

• Feature parity with ArrayFire 3.1 libs
• Ability to interop with other python libs
• Ability to extract raw device pointers
• Load and Save arrays from disk
• Improved __repr__ support

v3.0.20150914

• Feature parity with ArrayFire 3.0 libs
• Ability to switch all backends
• Supports both python2 and python3