Python binding for Khiva library.

Related tags

Deep Learningpythongpuopenclmulticoredata-serieskhiva
Overview

Khiva-Python

License: MPL 2.0 Gitter chat

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README

This is the Khiva Python binding, it allows the usage of Khiva library from Python.

License

This project is licensed under MPL-v2.

Quick Summary

This Python binding called 'khiva' provides all the functionalities of the KHIVA library for time series analytics.

Set up

In order to use this binding, you need to install Khiva library.

Prerequisites

Note: By now, only 64-bit Python versions are supported.

Note Windows' users: Search your 64-bits version here

Install latest version

Install latest stable version of Khiva library. Follow the steps in the "Installation" section of the Khiva repository

To install the Khiva Python binding, we just need to execute the following command:

python setup.py install

Install any release

Install the prerequisites listed in the "Installation" section of the Khiva library repository. Download and install your selected Khiva release from Khiva repository.

Install the Khiva python binding compatible with the Khiva library installed previously. Follow the steps to install the Khiva python binding explained in pypi.

Executing the tests:

All tests can be executed separately, please find them in /tests/unit_tests.

Documentation

This Khiva Python binding follows the standard way of writing documentation of Python by using Sphinx.

In order to generate the documentation (in html format), run the following command under the /docs folder:

make html

Contributing

The rules to contribute to this project are described here

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Comments
  • Access violation

    Access violation

    Describe the bug I get a access violation whenever I use khiva python lib

    To Reproduce Run a simple program like:

    from khiva.library import *
set_backend(KHIVABackend.KHIVA_BACKEND_OPENCL)
set_device(0)

from khiva.array import *
a = Array([1, 2, 3, 4, 5, 6, 7, 8])
a.display()

    Expected behavior Application should run without exceptions

    Screenshots

    (base) C:\Progetti\Lab\Khiva\MyPythonSamples\HelloKhiva>python main.py
array
[8 1 1 1]
    1.0000
    2.0000
    3.0000
    4.0000
    5.0000
    6.0000
    7.0000
    8.0000

Traceback (most recent call last):
  File "main.py", line 7, in <module>
    a.display()
  File "C:\Anaconda3\lib\site-packages\khiva\array.py", line 323, in display
    KhivaLibrary().c_khiva_library.display(ctypes.pointer(self.arr_reference))
OSError: exception: access violation writing 0x00007FFE94CB180A

    Environment information:

    • OS: Windows 10
    • Version 0.3.0
    opened by maiorfi 6
  • V0.5.0

    V0.5.0

    Make sure you have checked all steps below.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

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    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

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    opened by raulbocanegra 1
  • V0.5.0

    V0.5.0

    Make sure you have checked all steps below.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

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    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

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    License

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    opened by raulbocanegra 1
  • Khiva Python Bindings not passing all unit tests

    Khiva Python Bindings not passing all unit tests

    Describe the bug Khiva Python Bindings not passing all unit tests. Problems include seg fault or is not able to find required library in khiva function call.

    To Reproduce Build khiva from source, install. Run install script to generate python bindings. Run unit tests from this repo.

    Expected behavior All tests should pass.

    Environment information: Ubuntu 18.04.4 LTS Python 3.6.9 Conan version 1.23.0 ArrayFire-v3.6.2

    Additional context I joined the Gitter, it may be easier to continue the conversation there. Saw no errors during installation of both khiva and the python bindings. Prerequisites were installed prior to installing khiva.

    opened by yuhongsun96 1
  • update setup.py

    update setup.py

    Make sure you have checked all steps below.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

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    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

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    • [ ] My commits have been squashed if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":
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      3. Subject does not end with a period
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      6. Body explains "what" and "why", not "how"

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    Documentation

    • [ ] In case of new functionality, my PR adds documentation that describes how to use it.
    opened by raulbocanegra 1
  • Feature/error handling

    Feature/error handling

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    opened by avilchess 1
  • Feature/scamp_getChains

    Feature/scamp_getChains

    • Add scamp algorithm
    • Add get_chains function

    Description

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    opened by jrecuerda 1
  • Increase package version

    Increase package version

    Make sure you have checked all steps below.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

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    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

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      5. Body wraps at 72 characters
      6. Body explains "what" and "why", not "how"

    License

    Documentation

    • [ ] In case of new functionality, my PR adds documentation that describes how to use it.
    opened by jrecuerda 1
  • Add mass and findBestNOccurrences functions

    Add mass and findBestNOccurrences functions

    Make sure you have checked all steps below.

    Description

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    opened by jrecuerda 1
  • Fix issue with numpy interop

    Fix issue with numpy interop

    Reading from an Array:

    • When an Array of real or complex numbers with more than two dimensions was benig converted to numpy this conversion didn't return an np.array with a proper shape.

    Creating an Array:

    • When an Array of real numbers with more than two dimensions was built. The shape in the device (arrayfire) was not correct.
    • For complex numbers it occurrs with more than one dimension.

    Make sure you have checked all steps below.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

    Tests

    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

    Commits

    • [ ] My commits have been squashed if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":
      1. Subject is separated from body by a blank line
      2. Subject is limited to 50 characters
      3. Subject does not end with a period
      4. Subject uses the imperative mood ("add", not "adding")
      5. Body wraps at 72 characters
      6. Body explains "what" and "why", not "how"

    License

    Documentation

    • [ ] In case of new functionality, my PR adds documentation that describes how to use it.
    opened by jrecuerda 1
  • Fix bug when doing get_data from an Array with one element.

    Fix bug when doing get_data from an Array with one element.

    This PR solves one issue when doing get_data().tolist() on a Khiva.Array with one element.

    Description

    • [ ] Here are some details about my PR, including screenshots of any UI changes:

    Tests

    • [ ] My PR adds the following unit tests OR does not need testing for this extremely good reason:

    Commits

    • [ ] My commits have been squashed if they address the same issue. In addition, my commits follow the guidelines from "How to write a good git commit message":
      1. Subject is separated from body by a blank line
      2. Subject is limited to 50 characters
      3. Subject does not end with a period
      4. Subject uses the imperative mood ("add", not "adding")
      5. Body wraps at 72 characters
      6. Body explains "what" and "why", not "how"

    License

    Documentation

    • [ ] In case of new functionality, my PR adds documentation that describes how to use it.
    opened by avilchess 1
  • Bump numpy from 1.18.1 to 1.22.0

    Bump numpy from 1.18.1 to 1.22.0

    Bumps numpy from 1.18.1 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

    Commits

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    dependencies 
    opened by dependabot[bot] 1
  • Improve packaging

    Improve packaging

    Use of Khiva Python requires a lot of previous installation of Arrayfire and other dependencies. We could try to bundle most of the dependencies (Arrayfire at least) in order to make life easier to our users.

    opened by raulbocanegra 0
Releases(v0.3.0)

  • v0.3.0(Jun 11, 2019)

    Added

    • mass (Mueen's Algorithm for Similarity Search) function with a proper public interface.
    • findBestNOccurrences function.

    Improved

    • STOMP (self-join) performance has been improved by a ~54%.

    Fixed

    • STOMP (self-join) doesn't crash in batched mode for long time series.
    Source code(tar.gz)
    Source code(zip)

  • v0.2.2(May 7, 2019)

  • v0.2.1(Mar 5, 2019)

  • v0.2.0(Feb 27, 2019)

    Added

    • KMeans algorithm.
    • KShape Algorithm.
    • Added Ljung-Box test.
    • SBD distance function.

    Changed

    • Implementation improvement of stomp function and find motifs and discords functions.
    Source code(tar.gz)
    Source code(zip)
Owner
Shapelets
Accelerated Time Series Analytics
Shapelets
GitHub Repository https://khiva-python.readthedocs.io/
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