Electrophys Feature Extract Library (eFEL)

Navigation

Verified details

These details have been verified by PyPI
Maintainers
Avatar for aurelienjaquier from gravatar.com aurelienjaquier Avatar for bbp.opensource from gravatar.com bbp.opensource Avatar for wvangeit from gravatar.com wvangeit

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU Lesser General Public License v3 (LGPLv3) (LGPLv3)
  • Author: BlueBrain Project, EPFL
  • Maintainer: Werner Van Geit
  • Tags feature, extraction, electrophysiology, BlueBrainProject
Classifiers

Project description

The Electrophys Feature Extract Library (eFEL) allows neuroscientists to automatically extract features from time series data recorded from neurons (both in vitro and in silico). Examples are the action potential width and amplitude in voltage traces recorded during whole-cell patch clamp experiments. The user of the library provides a set of traces and selects the features to be calculated. The library will then extract the requested features and return the values to the user.

Project details

Verified details

These details have been verified by PyPI
Maintainers
Avatar for aurelienjaquier from gravatar.com aurelienjaquier Avatar for bbp.opensource from gravatar.com bbp.opensource Avatar for wvangeit from gravatar.com wvangeit

Unverified details

These details have not been verified by PyPI
Project links
Meta
  • License: GNU Lesser General Public License v3 (LGPLv3) (LGPLv3)
  • Author: BlueBrain Project, EPFL
  • Maintainer: Werner Van Geit
  • Tags feature, extraction, electrophysiology, BlueBrainProject
Classifiers

Release history Release notifications | RSS feed

5.7.12

5.7.11

5.7.10

5.7.9

5.7.8

5.7.7

5.7.6

5.7.5

5.7.4

5.7.3

5.7.2

5.7.1

5.7.0

5.6.29

5.6.28

5.6.27

5.6.26

5.6.25

5.6.24

5.6.23

5.6.22

5.6.21

5.6.20

5.6.19

5.6.18

5.6.17

5.6.16

5.6.15

5.6.14

5.6.13

5.6.12

5.6.11

5.6.10

5.6.9

5.6.8

5.6.7

5.6.6

5.6.5

5.6.4

5.6.3

5.6.2

5.6.1

5.5.7

5.5.6

5.5.5

5.5.4

5.5.3

5.5.2

5.5.1

5.5.0

5.4.1

5.4.0

5.3.10

5.3.9

5.3.8

5.3.7

5.3.5

5.3.4

5.3.3

5.3.2

5.3.1

5.3.0

5.2.10

5.2.9

5.2.8

5.2.7

5.2.5

5.2.4

5.2.1

5.2.0

5.1.6

5.1.5

5.1.4

5.1.3

5.1.2

5.1.1

5.1.0

5.0.7

5.0.6

5.0.5

5.0.4

5.0.1

4.3.6

4.3.5

4.3.4

4.3.0

4.2.12

4.2.10

4.2.7

4.2.5

4.2

4.1.98

4.1.95

4.1.93

4.1.91

4.1.86

4.1.84

4.1.81

4.1.78

4.1.76

4.1.73

4.1.63

4.1.61

4.1.58

4.1.56

4.1.54

4.1.49

4.1.47

This version

4.1.40

4.1.31

4.1.23

4.1.19

4.1.14

4.1.1

4.0.50

4.0.47

4.0.44

4.0.42

4.0.40

4.0.34

4.0.32

4.0.30

4.0.26

4.0.4

3.2.4

3.2.1

3.1.100

3.1.98

3.1.96

3.1.92

3.1.90

3.1.88

3.1.82

3.1.77

3.1.75

3.1.72

3.1.70

3.1.63

3.1.60

3.1.58

3.1.56

3.1.54

3.1.52

3.1.50

3.1.46

3.1.44

3.1.42

3.1.40

3.1.39

3.1.37

3.1.10

3.0.113

3.0.103

3.0.99

3.0.93

3.0.87

3.0.84

3.0.82

3.0.80

3.0.73

3.0.72

3.0.70

3.0.68

3.0.66

3.0.62

3.0.60

3.0.58

3.0.56

3.0.43

3.0.39

3.0.36

3.0.34

3.0.31

3.0.30

3.0.22

3.0.19

3.0.16

3.0.12

3.0.7

3.0.5

3.0.3

2.13.13

2.13.6

2.13.3

2.13.1

2.12.11

2.12.9

2.12.6

2.12.4

2.11.52

2.11.50

2.11.47

2.11.45

2.11.41

2.11.35

2.11.33

2.11.31

2.11.28

2.11.26

2.11.14

2.11.12

2.11.10

2.11.9

2.11.7

2.11.5

2.11.3

2.11.1

2.10.150

2.10.147

2.10.146

2.10.144

2.10.135

2.10.134

2.10.132

2.10.130

2.10.129

2.10.127

2.10.124

2.10.121

2.10.120

2.10.118

2.10.116

2.10.115

2.10.114

2.10.112

2.10.111

2.10.109

2.10.107

2.10.105

2.10.102

2.10.99

2.10.97

2.10.95

2.10.93

2.10.86

2.10.85

2.10.83

2.10.80

2.10.78

2.10.76

2.10.74

2.10.72

2.10.66

2.10.65

2.10.63

2.10.61

2.10.60

2.10.59

2.10.57

2.10.53

2.10.51

2.10.49

2.10.47

2.10.45

2.10.43

2.10.41

2.10.39

2.10.38

2.10.36

2.10.34

2.10.33

2.10.32

2.10.31

2.10.30

2.10.29

2.10.28

2.10.25

2.10.21

2.10.20

2.10.18

2.10.15

2.10.13

2.10.11

2.10.9

2.10.7

2.10.6

2.10.5

2.10.4

2.10.3

2.10.1

2.9.22

2.9.19

2.9.17

2.9.15

2.9.14

2.9.13

2.9.12

2.9.11

2.9.10

2.9.4

2.9.3

2.9.2

2.9.1

2.8.8

2.8.2

2.8.1

2.8

2.7.10

2.7.9

2.7.8

2.7.7

2.7.5

2.7.4

2.7.post0.dev15 pre-release

2.7.post0.dev13 pre-release

2.7.post0.dev12 pre-release

2.6.40

2.6.38

2.6.37

2.6.36

2.6.35

2.6.34

2.6.32

2.6.31

2.6.30

2.6.29

2.6.26

2.6.25

2.6.24

2.6.23

2.6.22

2.6.21

2.6.20

2.6.19

2.6.18

2.6.17

2.6.14

2.6.13

2.6.12

2.6.11

2.6.10

2.6.9

2.6.7

2.6.3

2.6.1

2.4.28

2.4.27

2.4.24

2.4.22

2.4.21

2.4.18

2.4.13

2.4.12

2.4.11

2.4.9

2.4.8

2.4.2

2.4.1

2.3.90

2.3.73

2.3.71

2.3.70

2.3.68

2.3.67

2.3.66

2.3.64

2.3.63

2.3.62

2.3.60

2.3.59

2.3.57

2.3.49

2.3.48

2.3.47

2.3.46

2.3.44

2.3.37

2.3.36

2.3.35

2.3.34

2.3.33

2.3.32

2.3.31

2.3.29

2.3.28

2.3.27

2.3.26

2.3.25

2.3.24

2.3.23

2.3.22

2.3.21

2.3.20

2.3.19

2.3.18

2.3.17

2.3.16

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

efel-4.1.40.tar.gz (107.6 kB view details)

Uploaded Source

Built Distributions

efel-4.1.40-cp310-cp310-win_amd64.whl (199.3 kB view details)

Uploaded CPython 3.10 Windows x86-64

efel-4.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

efel-4.1.40-cp310-cp310-macosx_10_9_x86_64.whl (254.1 kB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

efel-4.1.40-cp39-cp39-win_amd64.whl (199.3 kB view details)

Uploaded CPython 3.9 Windows x86-64

efel-4.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

efel-4.1.40-cp39-cp39-macosx_10_9_x86_64.whl (254.0 kB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

efel-4.1.40-cp38-cp38-win_amd64.whl (199.3 kB view details)

Uploaded CPython 3.8 Windows x86-64

efel-4.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

efel-4.1.40-cp38-cp38-macosx_10_9_x86_64.whl (254.0 kB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

efel-4.1.40-cp37-cp37m-win_amd64.whl (199.3 kB view details)

Uploaded CPython 3.7m Windows x86-64

efel-4.1.40-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

efel-4.1.40-cp37-cp37m-macosx_10_9_x86_64.whl (254.0 kB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

efel-4.1.40-cp36-cp36m-win_amd64.whl (216.6 kB view details)

Uploaded CPython 3.6m Windows x86-64

efel-4.1.40-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.3 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

efel-4.1.40-cp36-cp36m-macosx_10_9_x86_64.whl (254.2 kB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file efel-4.1.40.tar.gz.

File metadata

  • Download URL: efel-4.1.40.tar.gz
  • Upload date:
  • Size: 107.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40.tar.gz
Algorithm Hash digest
SHA256 09273c59a6e2072a0fbf8082bd93de8b634fd45f3345a3ff63833148809cb244
MD5 3e1c3e460fe5c89ee468d368814d5a66
BLAKE2b-256 b959c711a291f7b49d50aa83d985b96254632c2a4dfbc03d34197e8f464b96ce

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: efel-4.1.40-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 199.3 kB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 161240bedd164b7eabf951180e5cce4922b99965731616a83847d80dcab2f4ab
MD5 d34935cd6db4b30c6ab0810355089d31
BLAKE2b-256 b9d867525908ab59dfcd426e7fd998a7d47c3d2dfbe6c9767839f44da309068a

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 04120576bb476d3e8fab83bdbd64f4f67b6a225f459df4094ab1bf117974b525
MD5 78dfb58ecc3aa759b5ecda47634b2661
BLAKE2b-256 77dce96040f0dbbac4971a455882acb5f3691860e430b8e38456a42ec1ffde33

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 3bae6f8859d67cf4ab72091b6911efd25a3544d53a75f19b29dfacf4b4dbc73b
MD5 1123ae6684b05c7ae6bae95ab7265056
BLAKE2b-256 840b9a98838ba3981307119ade1bf0084ec7e90b429017f7b254c318fb3e6e9a

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: efel-4.1.40-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 199.3 kB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 97b1ebe846c8ac78e8cd14c5c30f159fb37459543f88e89267cbb7f4e5e974ad
MD5 7953f177a9dc5302e58d71982f3b03d1
BLAKE2b-256 9c8a850cf8307ca573f7ea68c6ff93c1e9d74db07a1e3395267565778fccea57

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1ca79eb7566e01856f315f10245b97f423ad676e29837ed3f59f4b432d29bb1e
MD5 6650912a85b187b416142178a9c26113
BLAKE2b-256 feae7f5349f2974f0757895d543a93020a662485224c4d11dae827d61adb1edb

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 cfa6d46f65c8033a2414b68000001c0453f7eb1b8b67d48a6213bda9f18c54af
MD5 8fed651043eea849b1fe06ca5f211045
BLAKE2b-256 eb602e4359ea8c51028a3cf5383bf2b40afbc57e940c80f17c1685ac221335c5

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: efel-4.1.40-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 199.3 kB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 6c2f1ff1616d98ffaf506957d23727fb8ec3f443bd9edb797486f7bbbbf0d690
MD5 76363c7cb079859b5e4df7149cbad162
BLAKE2b-256 6cc23341765187435101cbef19992bf4b0041805314ae55af37ebab8283ea84e

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 5ecd969a12c2d4ed1836e2ff4110bdb23e8853674cda0e03f78c0275192fe05f
MD5 0cec77070117346e20160e49615efc52
BLAKE2b-256 70479bbe46b5db09e1c1f493028774b414a34a62d723aba06d3bf33c818ca18a

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 628abb4152319616d1e5209cc06f6be77f2a52d7afeb72351a185f9b023fd097
MD5 f6b8799501256dccba40c5fb292155f3
BLAKE2b-256 1d5531acb0862f266168ca79cbc208a4cef4fbeb2459375c33a5e910ff570aad

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: efel-4.1.40-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 199.3 kB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 19830181abf24f75197618940873aa6e9d7fdd2f6bad0510ae1c694743ff9938
MD5 521e740d6e4aa3f29b5a86246ca2f52b
BLAKE2b-256 ec4669278c6cd645532bd054108bd7e8df8562dc34820a97918916e39998effb

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b206948c05e0e24a988e0e8008f0c3b025562361bcc37dffb800f0f3ac2781de
MD5 2a388e46dda7df1e96a98a3869467125
BLAKE2b-256 170de21ce26c5d4fa9bd9cbe33d5b3ada2648c02acf3d298f9c2d36873992c7d

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 58e9e094e4cc3c19ac164ba5a96e0eb0b43c22b230615baf380103301c4a71a0
MD5 91a8dbbf77e3efe175578759bb773569
BLAKE2b-256 5a32c62063bcf8e19cff1ed9b2da12eb1814a2ab11e9db44d43b8591f75d1090

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp36-cp36m-win_amd64.whl.

File metadata

  • Download URL: efel-4.1.40-cp36-cp36m-win_amd64.whl
  • Upload date:
  • Size: 216.6 kB
  • Tags: CPython 3.6m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.15

File hashes

Hashes for efel-4.1.40-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 f05861c957affb651bed142d92387dac2294c30ce7c8ab54439fa64fb8478d9a
MD5 705479bcba40311aedc1cae0fb9706a7
BLAKE2b-256 bb323eedcc43d57ea7884257b712e94991da4d1b33e714698f6757af83232069

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 f3454ee9dab22d49eac5a3f459691976adec4b8ec26019bdfbd594770b27abb1
MD5 12390d6f3a802c91d6d50f650ea2a9a2
BLAKE2b-256 5827656b40d3c2c92a5bb41a6ae92c87a0f4d4f95c6a594813498d8336fefc36

See more details on using hashes here.

Provenance

File details

Details for the file efel-4.1.40-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for efel-4.1.40-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 fe3dd61a0eacf14557e54f62015326bd73639a58d3fec4aedf737cc2a5588674
MD5 044780692aecb5ff5fc9e4e97c412525
BLAKE2b-256 263425749ec4d356a08d5aefe77b1d0c162a4ffbdee71689609a92fcd4ecbba3

See more details on using hashes here.

Provenance

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page