A set of python modules for cyclist using powermeters.
Project description
Installation
Dependencies
Scikit-cycling requires:
scipy
numpy
pandas
six
fit-parse
joblib
scikit-learn
Installation
scikit-cycling is currently available on the PyPi’s reporitories and you can install it via pip:
pip install -U scikit-cycling
The package is release also in conda-forge:
conda install -c conda-forge scikit-cycling
If you prefer, you can clone it and run the setup.py file. Use the following commands to get a copy from Github and install all dependencies:
git clone https://github.com/scikit-cycling/scikit-cycling.git cd scikit-cycling pip install .
Or install using pip and GitHub:
pip install -U git+https://github.com/scikit-cycling/scikit-cycling.git
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
File details
Details for the file scikit-cycling-0.1.3.tar.gz
.
File metadata
- Download URL: scikit-cycling-0.1.3.tar.gz
- Upload date:
- Size: 937.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | b392019256c1cbe8ab4f5387cc4c91ee05f27e15663be9eef37d47ca03c1ea2f |
|
MD5 | 210aba526aa061c41d7f2e163cd815c7 |
|
BLAKE2b-256 | e3b577b8118297221e5fd2a4fb9301228d88da1802d1bb29b2d8c3bdade49ce9 |
File details
Details for the file scikit_cycling-0.1.3-cp36-cp36m-win_amd64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp36-cp36m-win_amd64.whl
- Upload date:
- Size: 899.8 kB
- Tags: CPython 3.6m, Windows x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8fe30077ab36b880eecd7d7ffc98031761e5b4c027ee25e5d9d72cce9036746f |
|
MD5 | bd4abfe904b39c4517317a1c3f686e69 |
|
BLAKE2b-256 | 558912fae66709e2fbcb5945053ec45a8677193b00a1af87983ceaedabf75c21 |
File details
Details for the file scikit_cycling-0.1.3-cp36-cp36m-win32.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp36-cp36m-win32.whl
- Upload date:
- Size: 882.7 kB
- Tags: CPython 3.6m, Windows x86
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | bafc31d16f45eb868e4156efc8ad8780a0302223ea0b504e15cf4795125d47f8 |
|
MD5 | f1262e473032963dce5340a41ef7822b |
|
BLAKE2b-256 | 2510bd31c2c524ecac1b85c34e60904ec13e00e05c8a42b298e75521e1fe88bd |
File details
Details for the file scikit_cycling-0.1.3-cp36-cp36m-manylinux1_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp36-cp36m-manylinux1_x86_64.whl
- Upload date:
- Size: 940.9 kB
- Tags: CPython 3.6m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4a56a693af794ea6ee3618a5dd28621fb721308632bf9ca6bc45f9509ac4d2dc |
|
MD5 | 8095951a1243e8d9e8a66c510335fbd0 |
|
BLAKE2b-256 | 739f4ddb5d74057ce113fda99ef41124024764a54731dbfcb99e5035406fd999 |
File details
Details for the file scikit_cycling-0.1.3-cp36-cp36m-manylinux1_i686.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp36-cp36m-manylinux1_i686.whl
- Upload date:
- Size: 928.0 kB
- Tags: CPython 3.6m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 95745834742fd2241ab345d953a4031f2aa770f13c6c7467dab2b0a399d0fdb4 |
|
MD5 | 25506f7ba7915462ab80f8eaf005ea9e |
|
BLAKE2b-256 | 049883e4e0744855b480ca212cdc937e8f56f226ca6d9261b85855b792e938d5 |
File details
Details for the file scikit_cycling-0.1.3-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
- Upload date:
- Size: 2.0 MB
- Tags: CPython 3.6m, macOS 10.10+ intel, macOS 10.10+ x86-64, macOS 10.6+ intel, macOS 10.9+ intel, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 367a4d7a2fd0e0b71bf2fd08124c524ed507d6c07b0321866c67f8a7c2102941 |
|
MD5 | db1670d92d444c052251182500a2dd23 |
|
BLAKE2b-256 | d8d4a0ad53b1c25bba4a178c4483effc239bb935ad2201925fc64db9f0221ad6 |
File details
Details for the file scikit_cycling-0.1.3-cp35-cp35m-win_amd64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp35-cp35m-win_amd64.whl
- Upload date:
- Size: 899.0 kB
- Tags: CPython 3.5m, Windows x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8ec1a299b1eec8ff88770044b7361259cef51eb3a44966c497ca1c4234ba7a13 |
|
MD5 | 67ed222b1e33a188281ca0aa3994d666 |
|
BLAKE2b-256 | c2357bc026569e8390e987f119ce6289e597ec8102957d1c0b811e1964f09562 |
File details
Details for the file scikit_cycling-0.1.3-cp35-cp35m-win32.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp35-cp35m-win32.whl
- Upload date:
- Size: 881.4 kB
- Tags: CPython 3.5m, Windows x86
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 7cee2a9bdb6a9ad0bb7c72280a8fbd8e45c13f8909bcb91bfbfeb9016fa24af3 |
|
MD5 | ab2dbaabfc4ea65d30cab500a0121560 |
|
BLAKE2b-256 | 3c179e90f873bc530dec74a713f1cc28854a9defaad72b792853c152f34ff6f8 |
File details
Details for the file scikit_cycling-0.1.3-cp35-cp35m-manylinux1_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp35-cp35m-manylinux1_x86_64.whl
- Upload date:
- Size: 940.0 kB
- Tags: CPython 3.5m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 438b1a32f6854874ec1aa4a3526ac57fa344c4dae9680a4e0a9313455fa70d63 |
|
MD5 | 20af275f4df3e91ab7e0b63a969312f6 |
|
BLAKE2b-256 | bc29f0672790f75bb09fecea6c4c35d7ab995b82e59842851c5c105ff56664c0 |
File details
Details for the file scikit_cycling-0.1.3-cp35-cp35m-manylinux1_i686.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp35-cp35m-manylinux1_i686.whl
- Upload date:
- Size: 927.0 kB
- Tags: CPython 3.5m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 9746e597784a98f9fe541209a5729adae97f780b12f2258c988ea05c8a865e09 |
|
MD5 | 2b2ab31f65758defb877b9e4b7d484e9 |
|
BLAKE2b-256 | add2d0ed02afeb11a2860a6d499c4f78996304ad1646cd547dc74ea35a07f255 |
File details
Details for the file scikit_cycling-0.1.3-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
- Upload date:
- Size: 2.0 MB
- Tags: CPython 3.5m, macOS 10.10+ intel, macOS 10.10+ x86-64, macOS 10.6+ intel, macOS 10.9+ intel, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 37e65e6089257fe61962dc0027251fc161d8343fbc70b4238b6ef7b791761dfe |
|
MD5 | 326a93ff9ef3086b19364a976dbcb489 |
|
BLAKE2b-256 | a1aec47662f94d852d1411e01ece340e394b027076361f2c99fcca0e1835c3e4 |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27mu-manylinux1_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27mu-manylinux1_x86_64.whl
- Upload date:
- Size: 937.7 kB
- Tags: CPython 2.7mu
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 76054fb36907b499b8d5c03bda503186bd4a9274918d481bdd366cec31c07c35 |
|
MD5 | 91ff678fcf3f5470801ac7856e1979ee |
|
BLAKE2b-256 | 948ada53ff441904003bad372b5f4877db184d962e28dfcce90ec36236d9b820 |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27mu-manylinux1_i686.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27mu-manylinux1_i686.whl
- Upload date:
- Size: 926.8 kB
- Tags: CPython 2.7mu
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6b376d6f3db02d4c179a7088691c2a0ea2893537eb100f64af102d9692c5dcce |
|
MD5 | 4c493f37bd31813c455457d43f0f29d2 |
|
BLAKE2b-256 | 630fc1021c33fd5e932232887e1bd5ffc3576a21983d72a6833314f6075a9b44 |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27m-win_amd64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27m-win_amd64.whl
- Upload date:
- Size: 899.6 kB
- Tags: CPython 2.7m, Windows x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 8cde092227059d12f614319a6143e6fc22083405204697311abaae4e20827bc8 |
|
MD5 | 72c198fb22a8f2586d409763387ad3b5 |
|
BLAKE2b-256 | aa5265a6ef00be1e973dbaa9d618cd1acdd1a4b94cfec4b1fabecd7ce0828e37 |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27m-win32.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27m-win32.whl
- Upload date:
- Size: 882.9 kB
- Tags: CPython 2.7m, Windows x86
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2a7dc45c795c10584f893596e78ab2928a43e4084e7dca073df441405a8699ad |
|
MD5 | 396e1ab857a68b73e0737da4233eef04 |
|
BLAKE2b-256 | be9e4a1c6735927a9452676272abf02a24f5fac6f5371e8c3c6cd5aa867e4955 |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27m-manylinux1_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27m-manylinux1_x86_64.whl
- Upload date:
- Size: 939.7 kB
- Tags: CPython 2.7m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3a4b2fe4493e78454deb80021fae832c1b8efef77a2e95959ee8aac32a48cc0f |
|
MD5 | 5384dc0ef248af6e79ef6a09bacdeba0 |
|
BLAKE2b-256 | 214f38b80071e02e6523e07442a9f90cc1955576b4614e3efda3c31af72384ef |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27m-manylinux1_i686.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27m-manylinux1_i686.whl
- Upload date:
- Size: 927.0 kB
- Tags: CPython 2.7m
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | ac53fcaf8faf9857bcdeb4c0ba5d8cf966f20599beee2c57751f6a418b89aaab |
|
MD5 | 658886fb3e9a7b2f08c41bf6dc69ae30 |
|
BLAKE2b-256 | 9224f5d9b12f322c886118308613042c8ac3324a3a3bbdc1452533da250123bb |
File details
Details for the file scikit_cycling-0.1.3-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
.
File metadata
- Download URL: scikit_cycling-0.1.3-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
- Upload date:
- Size: 1.9 MB
- Tags: CPython 2.7m, macOS 10.10+ intel, macOS 10.10+ x86-64, macOS 10.6+ intel, macOS 10.9+ intel, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3424591e5b80c2c391417efa17c62f05fd90919a3e932a8a3c6fb2719a34cae5 |
|
MD5 | 8db0e1b555757fe8d161bfc7aca0dfc0 |
|
BLAKE2b-256 | 92a0282459a0e7e1fb1ecc054a6b2627e74081e958b1d7db59763406bc5f615e |