Machine Learning Time-Series Platform

Related tags

Deep Learningcesium
Overview

cesium: Open-Source Platform for Time Series Inference

Join the chat at https://gitter.im/cesium-ml/cesium Build Status codecov.io

Summary

cesium is an open source library that allows users to:

  • extract features from raw time series data (see list),
  • build machine learning models from these features, and
  • generate predictions for new data.

More information and examples can be found on our home page.

Installation from binaries:

  • Wheels for Mac and Linux can be installed via pip install cesium.
  • We do not build binary wheels for Windows. To install on Windows, follow the instructions below for installation from source.

Installation from source:

  1. Install Cython
  2. Clone the repository: git clone https://github.com/cesium-ml/cesium.git
  3. cd cesium && pip install -e .

Note that cesium requires a C99 compiler, which in particular excludes MSVC. On Windows, a different compiler like MinGW has to be used. Please refer to the instructions for installing Cython & MinGW on Windows.

License:

cesium uses the 3-clause BSD licence.

Comments
  • Problem Installing on Windows

    Problem Installing on Windows

    I ran this

    pip install cesium-0.9.6.tar.gz

    and my output was. Any help would be greatly appreciated.

    Processing c:\users\skane\downloads\cesium-0.9.6.tar.gz Requirement already satisfied: scipy>=0.16.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (1.1.0) Requirement already satisfied: scikit_learn>=0.18.1 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.19.1) Requirement already satisfied: pandas>=0.17.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.23.0) Requirement already satisfied: dask>=0.15.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.17.5) Requirement already satisfied: toolz in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.9.0) Requirement already satisfied: gatspy>=0.3.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.3) Requirement already satisfied: cloudpickle in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from cesium==0.9.6) (0.5.3) Requirement already satisfied: numpy>=1.9.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from pandas>=0.17.0->cesium==0.9.6) (1.14.3) Requirement already satisfied: python-dateutil>=2.5.0 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from pandas>=0.17.0->cesium==0.9.6) (2.7.3) Requirement already satisfied: pytz>=2011k in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from pandas>=0.17.0->cesium==0.9.6) (2018.4) Requirement already satisfied: six>=1.5 in c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages (from python-dateutil>=2.5.0->pandas>=0.17.0->cesium==0.9.6) (1.11.0) Building wheels for collected packages: cesium Running setup.py bdist_wheel for cesium ... error Complete output from command "c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\python.exe" -u -c "import setuptools, tokenize;file='C:\Users\skane\AppData\Local\Temp\pip-req-build-yqy_oi\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" bdist_wheel -d C:\Users\skane\AppData\Local\Temp\pip-wheel-va7vz8i --python-tag cp36: running bdist_wheel running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building extension "cesium.features.lomb_scargle" sources building data_files sources build_src: building npy-pkg config files running build_py creating build creating build\lib.win-amd64-3.6 creating build\lib.win-amd64-3.6\cesium copying cesium\data_management.py -> build\lib.win-amd64-3.6\cesium copying cesium\featurize.py -> build\lib.win-amd64-3.6\cesium copying cesium\setup.py -> build\lib.win-amd64-3.6\cesium copying cesium\time_series.py -> build\lib.win-amd64-3.6\cesium copying cesium\util.py -> build\lib.win-amd64-3.6\cesium copying cesium\version.py -> build\lib.win-amd64-3.6\cesium copying cesium_init.py -> build\lib.win-amd64-3.6\cesium creating build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\andrzejak.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\asas_training.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\util.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets_init.py -> build\lib.win-amd64-3.6\cesium\datasets creating build\lib.win-amd64-3.6\cesium\features copying cesium\features\amplitude.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\cadence_features.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\common_functions.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\graphs.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\lomb_scargle.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\lomb_scargle_fast.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\num_alias.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\periodic_model.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\period_folding.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\qso_model.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\scatter_res_raw.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\setup.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\stetson.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features_init_.py -> build\lib.win-amd64-3.6\cesium\features creating build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\fixtures.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_data_management.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_featurize.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_time_series.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_util.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests_init_.py -> build\lib.win-amd64-3.6\cesium\tests creating build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_cadence_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_general_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_graphs.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_lomb_scargle_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\util.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests_init_.py -> build\lib.win-amd64-3.6\cesium\features\tests running build_ext No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler customize MSVCCompiler using build_ext building 'cesium.features._lomb_scargle' extension compiling C sources creating build\temp.win-amd64-3.6\Release\cesium creating build\temp.win-amd64-3.6\Release\cesium\features C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\include" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\ucrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\shared" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\um" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\winrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\cppwinrt" /Tccesium\features_lomb_scargle.c /Fobuild\temp.win-amd64-3.6\Release\cesium\features_lomb_scargle.obj _lomb_scargle.c c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2133: 'e': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2133: 'sx0': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2133: 'cx0': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2087: 'm': missing subscript c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2133: 'm': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2133: 'v': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2087: 'tmp': missing subscript c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2133: 'tmp': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'p': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'vec': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'eigs': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'sinx1': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'cosx1': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'sinx2': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'cosx2': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(200): warning C4018: '<': signed/unsigned mismatch c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION cesium\features_lomb_scargle.c(23369): warning C4244: 'initializing': conversion from 'double' to 'float', possible loss of data cesium\features_lomb_scargle.c(23375): warning C4244: 'initializing': conversion from 'double' to 'float', possible loss of data error: Command "C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\include" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\ucrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\shared" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\um" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\winrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\cppwinrt" /Tccesium\features_lomb_scargle.c /Fobuild\temp.win-amd64-3.6\Release\cesium\features_lomb_scargle.obj" failed with exit status 2


    Failed building wheel for cesium Running setup.py clean for cesium Failed to build cesium Installing collected packages: cesium Running setup.py install for cesium ... error Complete output from command "c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\python.exe" -u -c "import setuptools, tokenize;file='C:\Users\skane\AppData\Local\Temp\pip-req-build-yqy_oi\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record C:\Users\skane\AppData\Local\Temp\pip-record-7mvb49xz\install-record.txt --single-version-externally-managed --compile: running install running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building extension "cesium.features.lomb_scargle" sources building data_files sources build_src: building npy-pkg config files running build_py creating build creating build\lib.win-amd64-3.6 creating build\lib.win-amd64-3.6\cesium copying cesium\data_management.py -> build\lib.win-amd64-3.6\cesium copying cesium\featurize.py -> build\lib.win-amd64-3.6\cesium copying cesium\setup.py -> build\lib.win-amd64-3.6\cesium copying cesium\time_series.py -> build\lib.win-amd64-3.6\cesium copying cesium\util.py -> build\lib.win-amd64-3.6\cesium copying cesium\version.py -> build\lib.win-amd64-3.6\cesium copying cesium_init.py -> build\lib.win-amd64-3.6\cesium creating build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\andrzejak.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\asas_training.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets\util.py -> build\lib.win-amd64-3.6\cesium\datasets copying cesium\datasets_init_.py -> build\lib.win-amd64-3.6\cesium\datasets creating build\lib.win-amd64-3.6\cesium\features copying cesium\features\amplitude.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\cadence_features.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\common_functions.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\graphs.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\lomb_scargle.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\lomb_scargle_fast.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\num_alias.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\periodic_model.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\period_folding.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\qso_model.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\scatter_res_raw.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\setup.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features\stetson.py -> build\lib.win-amd64-3.6\cesium\features copying cesium\features_init_.py -> build\lib.win-amd64-3.6\cesium\features creating build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\fixtures.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_data_management.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_featurize.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_time_series.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests\test_util.py -> build\lib.win-amd64-3.6\cesium\tests copying cesium\tests_init_.py -> build\lib.win-amd64-3.6\cesium\tests creating build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_cadence_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_general_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_graphs.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\test_lomb_scargle_features.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests\util.py -> build\lib.win-amd64-3.6\cesium\features\tests copying cesium\features\tests_init_.py -> build\lib.win-amd64-3.6\cesium\features\tests running build_ext No module named 'numpy.distutils._msvccompiler' in numpy.distutils; trying from distutils customize MSVCCompiler customize MSVCCompiler using build_ext building 'cesium.features._lomb_scargle' extension compiling C sources creating build\temp.win-amd64-3.6\Release\cesium creating build\temp.win-amd64-3.6\Release\cesium\features C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\include" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\ucrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\shared" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\um" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\winrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\cppwinrt" /Tccesium\features_lomb_scargle.c /Fobuild\temp.win-amd64-3.6\Release\cesium\features_lomb_scargle.obj _lomb_scargle.c c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_eigs.h(135): error C2133: 'e': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2133: 'sx0': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(81): error C2133: 'cx0': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2087: 'm': missing subscript c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2133: 'm': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(113): error C2133: 'v': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2087: 'tmp': missing subscript c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(156): error C2133: 'tmp': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'p': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'vec': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(172): error C2133: 'eigs': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2057: expected constant expression c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2466: cannot allocate an array of constant size 0 c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'sinx1': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'cosx1': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'sinx2': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(199): error C2133: 'cosx2': unknown size c:\users\skane\appdata\local\temp\pip-req-build-yqy_oi\cesium\features_lomb_scargle.h(200): warning C4018: '<': signed/unsigned mismatch c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include\numpy\npy_1_7_deprecated_api.h(12) : Warning Msg: Using deprecated NumPy API, disable it by #defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION cesium\features_lomb_scargle.c(23369): warning C4244: 'initializing': conversion from 'double' to 'float', possible loss of data cesium\features_lomb_scargle.c(23375): warning C4244: 'initializing': conversion from 'double' to 'float', possible loss of data error: Command "C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\bin\HostX86\x64\cl.exe /c /nologo /Ox /W3 /GL /DNDEBUG /MD -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\lib\site-packages\numpy\core\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\include" -I"C:\Program Files (x86)\Microsoft Visual Studio\2017\BuildTools\VC\Tools\MSVC\14.15.26726\include" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\ucrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\shared" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\um" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\winrt" -I"C:\Program Files (x86)\Windows Kits\10\include\10.0.17134.0\cppwinrt" /Tccesium\features_lomb_scargle.c /Fobuild\temp.win-amd64-3.6\Release\cesium\features_lomb_scargle.obj" failed with exit status 2

    ----------------------------------------
    

    Command ""c:\program files (x86)\microsoft visual studio\shared\anaconda3_64\python.exe" -u -c "import setuptools, tokenize;file='C:\Users\skane\AppData\Local\Temp\pip-req-build-yqy_oi\setup.py';f=getattr(tokenize, 'open', open)(file);code=f.read().replace('\r\n', '\n');f.close();exec(compile(code, file, 'exec'))" install --record C:\Users\skane\AppData\Local\Temp\pip-record-7mvb49xz\install-record.txt --single-version-externally-managed --compile" failed with error code 1 in C:\Users\skane\AppData\Local\Temp\pip-req-build-yqy_oi\

    opened by stephen-kane 17
  • API refactor

    API refactor

    • Store feature info in a pd.DataFrame instead of xr.Dataset; for multi-channel features, columns labels are a (feature, channel) tuple.
    • Since feature data is simply rectangular now, there's no need for the build_model/predict wrapper functionality.
    • Otherwise haven't changed the featurize API yet.

    Some open questions:

    • What functionality would be useful to add on top of sklearn for model building/prediction?
    • What part of the Featureset class do we still want to include?
      • Is .impute redundant w/ sklearn's imputation functionality?
      • Definitely want some form of serialization besides CSV; what about joblib instead of netCDF4? We already use it for models on the front end.
    opened by bnaul 14
  • Failing to pip install cesium

    Failing to pip install cesium

    Hello,

    I am not able to install the cesium package through pip install even though all the dependencies are satisfied. I am getting something like following. Does anyone know what is going on here:

    image

    Thanks!

    opened by pkgandhi 14
  • Remove API docs from repo and autogenerate; remove hard-coded mocks

    Remove API docs from repo and autogenerate; remove hard-coded mocks

    • The API doc code is now in doc/conf.py so that the Sphinx build generates them automatically. A little hacky, but removes the need to keep them in the repo and remember to rebuild them every time.
    • Mocking is now handled by monkey patching __import__ in the Sphinx build to use mocks where needed. No longer necessary to add new requirements to the mock list.
    • The list of modules to include in the API docs is still hard-coded; I played around with auto-generating it but it was not nearly as easy to adapt the scikit-image code as I'd hoped, so I think this is fine for now.

    Drone is happy but I can't 100% know that this works until it's merged and built on readthedocs, so if you guys aren't around I may just self-merge :smiling_imp:

    opened by bnaul 14
  • Integrating Coverage.py with cesium

    Integrating Coverage.py with cesium

    1. updated travis.yml to run codecov after build passes.
    2. added in a .coveragerc file to stop coverage.py from testing scikit-learn imports
    3. updated requirements.txt to include coverage.
    opened by arkwave 12
  • Change

    Change "collections" into "collections.abc" for Python 3.10 compatibility

    For Python 3.10 compatibility, "from collections import Iterable" should be changed into "from collections.abc import Iterable". See for example: https://stackoverflow.com/questions/72032032/importerror-cannot-import-name-iterable-from-collections-in-python

    opened by YannCabanes 11
  • Python3 fixes: str encodings, iterator usage

    Python3 fixes: str encodings, iterator usage

    This should fix all the remaining Python3 incompatibilities (which were almost all problems with the test code and how data read from files/web requests were being compared to known string values).

    Fixes #75.

    opened by bnaul 11
  • Compatibility with dask 0.20 : 'get' keyword replaced with 'scheduler'

    Compatibility with dask 0.20 : 'get' keyword replaced with 'scheduler'

    Related to https://github.com/cesium-ml/cesium/pull/276 https://github.com/cesium-ml/cesium/issues/277.

    I think this is the only places where get was used. I updated the requirements.txt.

    opened by milesial 10
  • Sample datasets module

    Sample datasets module

    It would be nice to have a module (mltsp.datasets?) that allows for easy fetching of a few sample datasets; any tutorials we write up could then use these built-in functions rather than requiring the user to manually download the data.

    1. Is it ok to download data from public URLs out of our control or should we host them ourselves?
    2. asas_training_set.tar.gz in mltsp/data/sample_data isn't being used by any tests; we could migrate it out of the repo and instead make it downloadable through mltsp.datasets? EDIT: we could also just keep the relevant data in the repo, asas_training_set.tar.gz is ~3MB and my EEG dataset is ~6MB, dunno if that's too large or not.
    opened by bnaul 10
  • Mock out additional readthedocs libraries

    Mock out additional readthedocs libraries

    Some libraries were already present on Drone (e.g. requests) and not readthedocs; from now on Drone should fail whenever readthedocs is missing a dependency or mock library.

    Also fixes a docstring indentation warning.

    opened by bnaul 9
  • Feature generation refactor (closes gh-32)

    Feature generation refactor (closes gh-32)

    • Move relevant code from TCP module into science_features; TCP is no longer in use anywhere, will be removed later
    • Rename lc_tools to obs_feature_tools, remove unused legacy code
    • Improve consistency of style/parameters between various feature generation functions, including:
      • short_fname should now always be a basename without an extension (this is used as a key in various dictionaries)
      • Some featurization functions were returning a dict, and some a list of a single dict; should always be a dict now, and a lot of tests were changed to reflect this flattening (e.g. result[0]['somekey'] -> result['somekey'])

    As far as I know this is functionally finished (all tests passing for me), just needs to be thoroughly reviewed. The new functionality should all have docstrings, but some of the old code that I changed was lacking docstrings to begin with; will try to go back and add them as I review my changes.

    opened by bnaul 9
  • test_roundtrip_featureset fails on fresh install

    test_roundtrip_featureset fails on fresh install

    When I run make test after a fresh install on an M1 Mac, all tests pass except test_roundtrip_featureset. For that test, I get the below error. I followed the 'Installation from source' instructions.

    =============================================== FAILURES ================================================
    _______________________________________ test_roundtrip_featureset _______________________________________
    
    tmpdir = local('/private/var/folders/8_/ky643qs168ngjmhrpwcq1fdm0000gn/T/pytest-of-bhealy/pytest-35/test_roundtrip_featureset0')
    
        def test_roundtrip_featureset(tmpdir):
            fset_path = os.path.join(str(tmpdir), "test.npz")
            for n_channels in [1, 3]:
                for labels in [["class1", "class2"], []]:
                    fset, labels = sample_featureset(
                        3,
                        n_channels,
                        ["amplitude"],
                        labels,
                        names=["a", "b", "c"],
                        meta_features=["meta1"],
                    )
        
                    pred_probs = pd.DataFrame(
                        np.random.random((len(fset), 2)),
                        index=fset.index.values,
                        columns=["class1", "class2"],
                    )
        
    >               featurize.save_featureset(
                        fset, fset_path, labels=labels, pred_probs=pred_probs
                    )
    
    cesium/tests/test_featurize.py:284: 
    _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
    cesium/featurize.py:446: in save_featureset
        size = max(len(x) for x in arr["index"])
    _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
    
    self = rec.array([('amplitude', 0, 0.11471806, 0.60767208, 0.14693643),
               ('meta1', '', 0.41085066, 0.62965584, 0.85743668)],
              dtype=[('feature', 'O'), ('channel', 'O'), ('a', '<f8'), ('b', '<f8'), ('c', '<f8')])
    indx = 'index'
    
        def __getitem__(self, indx):
    >       obj = super().__getitem__(indx)
    E       ValueError: no field of name index
    
    ../miniforge3/envs/cesium-env/lib/python3.11/site-packages/numpy/core/records.py:509: ValueError
    
    ======================================== short test summary info ========================================
    FAILED cesium/tests/test_featurize.py::test_roundtrip_featureset - ValueError: no field of name index
    =============================== 1 failed, 55 passed, 12 warnings in 6.03s ===============================
    make: *** [test] Error 1
    
    opened by bfhealy 0
  • Migrate away from numpy.distutils

    Migrate away from numpy.distutils

    Per wheel build CI:

    numpy.distutils is deprecated since NumPy 1.23.0, as a result of the deprecation of distutils itself. It will be removed for Python >= 3.12. For older Python versions it will remain present. It is recommended to use setuptools < 60.0 for those Python versions. For more details, see: https://numpy.org/devdocs/reference/distutils_status_migration.

    opened by stefanv 0
  • Is cesium compatible with the current sklearn version (scikit-learn 1.1) ?

    Is cesium compatible with the current sklearn version (scikit-learn 1.1) ?

    Hello,

    It appears cesium doesn't work with current versions of the dependencies (e.g. sklearn, dask).

    For sklearn as an example:

    https://github.com/cesium-ml/cesium/blob/master/cesium/featurize.py#L11 contains

    from sklearn.impute import SimpleImputer as Imputer
    

    as per https://stackoverflow.com/questions/59439096/importerror-cannnot-import-name-imputer-from-sklearn-preprocessing,

    from sklearn.preprocessing import Imputer was deprecated with scikit-learn v0.20.4 and removed as of v0.22.2.

    from sklearn.impute import SimpleImputer
    imputer = SimpleImputer(missing_values=np.nan, strategy='mean')
    

    is cesium compatible with the current versions of the dependencies (e.g. sklearn and dask)?

    If not, is there a requirements.txt file or a dictionary of dependencies and versions known to work correctly?

    opened by aaelony 6
  • Harmonic oscillation reduction

    Harmonic oscillation reduction

    To solve the overflow problem in issue #284 :

    new py file cesium/features/lomb_scargle_norm.py incorporating in lomb_scargle_model()

    • normalization of the input data if opt_normalize
    • computation of the Lomb-Scargle model via fit_lomb_scargle()
    • rescaling of the output dictionary via rescale_lomb_model()

    Notes

    1. modifications are solely made in cesium/features/lomb_scargle_norm.py not in the original source file cesium/features/lomb_scargle.py
    2. successful local py tests for checking the rescaled output variables in the lomb_scargle_model.

    Additional output The full power spectrum and associated frequencies are added in the output dictionary in fit_lomb_scargle() [Lines 299-302]

    opened by sarajamal57 4
  • possible overflow? (cesium lomb_scargle model)

    possible overflow? (cesium lomb_scargle model)

    (cesium.features.lomb_scargle.lomb_scargle_model.py)

    When varying the number of harmonics (nharm) in function lomb_scargle_model(), the computed model can showcase some instabilities for high nharmonics, not in a regular pattern though (see attached file). Must specify that these instabilities (when changing nharm) do not appear for all light-curves tested, but still noticed for some data. In the following, one identified case is reported.

    Possible source of error In real astronomical TS, the flux/mags values would refer to negative values or a different numerical precision that could possibly be the source of underflow/overflow within the optimization part (refine_psd, get_eigs) in _lomb_scargle.h and _eigs.h

    Possible solution normalize the signal before fitting the lomb_scargle (temporary solution?) As a result, the computed model would be a normalized version of the usual model (=computed on initial mag/flux measurements).

    Proposition within cesium.features.lomb_scargle.lomb_scargle_model.py :

    • compute internally the normalization of the lc = signal entry in functions fit_lomb_scargle() and lomb_scargle_model()
    • compute the lomb_scargle model using fit_lomb_scargle() and _lomb_scargle.h. Output: normalized fitted model
    • compute adjustments (*scale and +mean) to provide the model on initial flux/mags

    Attached files displays of initial light_curve superimposed with the estimated trend from cesium_fit for a varying nharm. The cesium_period is specified for each run. When computing the cesium model on normalized data, no instabilities are detected.

    snippet:

    from cesium.features.lomb_scargle import lomb_scargle_model
    lc ## cesium TS object from MACHO, object_name='6.6692.9', red band
    times = lc.time.copy(); mags = lc.measurement.copy(); errors = lc.error.copy(); 
    sys_err=0.00; nfreq=1; tone_control=5.0
    for nharm in range(1,21):
        model_cesium = lomb_scargle_model(times-min(times), mags, errors,
                                             sys_err=sys_err, nharm=nharm, nfreq=nfreq, tone_control=tone_control)
        period_cesium  = 1/model_cesium['freq_fits'][0]['freq']
        trend_cesium   = model_cesium['freq_fits'][0]['trend']
    

    MAG_fit_nharm_1-20 NORMAG_fit_nharm_1-20

    opened by sarajamal57 0
Releases(v0.10.1)
Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad to your characters in Modo.

Applicator Kit for Modo Applicator Kit for Modo allow you to apply Apple ARKit Face Tracking data from your iPhone or iPad with a TrueDepth camera to

Andrew Buttigieg 3 Aug 24, 2021
Code release for the paper “Worldsheet Wrapping the World in a 3D Sheet for View Synthesis from a Single Image”, ICCV 2021.

Worldsheet: Wrapping the World in a 3D Sheet for View Synthesis from a Single Image This repository contains the code for the following paper: R. Hu,

Meta Research 37 Jan 04, 2023
In Search of Probeable Generalization Measures

In Search of Probeable Generalization Measures Exciting News! In Search of Probeable Generalization Measures has been accepted to the International Co

Mahdi S. Hosseini 6 Sep 11, 2022
[CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment

RADN [CVPRW 2021] Code for Region-Adaptive Deformable Network for Image Quality Assessment [Paper on arXiv] Overview Update [2021/5/7] add codes for W

IIGROUP 53 Dec 28, 2022
Simple object detection app with streamlit

object-detection-app Simple object detection app with streamlit. Upload an image and perform object detection. Adjust the confidence threshold to see

Robin Cole 68 Jan 02, 2023
CVPR2021 Workshop - HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization.

HDRUNet [Paper Link] HDRUNet: Single Image HDR Reconstruction with Denoising and Dequantization By Xiangyu Chen, Yihao Liu, Zhengwen Zhang, Yu Qiao an

XyChen 105 Dec 20, 2022
A font family with a great monospaced variant for programmers.

Fantasque Sans Mono A programming font, designed with functionality in mind, and with some wibbly-wobbly handwriting-like fuzziness that makes it unas

Jany Belluz 6.3k Jan 08, 2023
Auto-updating data to assist in investment to NEPSE

Symbol Ratios Summary Sector LTP Undervalued Bonus % MEGA Strong Commercial Banks 368 5 10 JBBL Strong Development Banks 568 5 10 SIFC Strong Finance

Amit Chaudhary 16 Nov 01, 2022
Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks

Stable Neural ODE with Lyapunov-Stable Equilibrium Points for Defending Against Adversarial Attacks Stable Neural ODE with Lyapunov-Stable Equilibrium

Kang Qiyu 8 Dec 12, 2022
The codes and related files to reproduce the results for Image Similarity Challenge Track 2.

ISC-Track2-Submission The codes and related files to reproduce the results for Image Similarity Challenge Track 2. Required dependencies To begin with

Wenhao Wang 89 Jan 02, 2023
An implementation of the WHATWG URL Standard in JavaScript

whatwg-url whatwg-url is a full implementation of the WHATWG URL Standard. It can be used standalone, but it also exposes a lot of the internal algori

314 Dec 28, 2022
This repo contains the official code of our work SAM-SLR which won the CVPR 2021 Challenge on Large Scale Signer Independent Isolated Sign Language Recognition.

Skeleton Aware Multi-modal Sign Language Recognition By Songyao Jiang, Bin Sun, Lichen Wang, Yue Bai, Kunpeng Li and Yun Fu. Smile Lab @ Northeastern

Isen (Songyao Jiang) 128 Dec 08, 2022
A Runtime method overload decorator which should behave like a compiled language

strongtyping-pyoverload A Runtime method overload decorator which should behave like a compiled language there is a override decorator from typing whi

20 Oct 31, 2022
Planar Prior Assisted PatchMatch Multi-View Stereo

ACMP [News] The code for ACMH is released!!! [News] The code for ACMM is released!!! About This repository contains the code for the paper Planar Prio

Qingshan Xu 127 Dec 31, 2022
graph-theoretic framework for robust pairwise data association

CLIPPER: A Graph-Theoretic Framework for Robust Data Association Data association is a fundamental problem in robotics and autonomy. CLIPPER provides

MIT Aerospace Controls Laboratory 118 Dec 28, 2022
Robot Servers and Server Manager software for robo-gym

robo-gym-server-modules Robot Servers and Server Manager software for robo-gym. For info on how to use this package please visit the robo-gym website

JR ROBOTICS 4 Aug 16, 2021
Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning

Circuit Training: An open-source framework for generating chip floor plans with distributed deep reinforcement learning. Circuit Training is an open-s

Google Research 479 Dec 25, 2022
Liecasadi - liecasadi implements Lie groups operation written in CasADi

liecasadi liecasadi implements Lie groups operation written in CasADi, mainly di

Artificial and Mechanical Intelligence 14 Nov 05, 2022
TuckER: Tensor Factorization for Knowledge Graph Completion

TuckER: Tensor Factorization for Knowledge Graph Completion This codebase contains PyTorch implementation of the paper: TuckER: Tensor Factorization f

Ivana Balazevic 296 Dec 06, 2022
AntroPy: entropy and complexity of (EEG) time-series in Python

AntroPy is a Python 3 package providing several time-efficient algorithms for computing the complexity of time-series. It can be used for example to e

Raphael Vallat 153 Dec 27, 2022