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

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

This version

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-3.1.40.tar.gz (91.8 kB view details)

Uploaded Source

File details

Details for the file efel-3.1.40.tar.gz.

File metadata

  • Download URL: efel-3.1.40.tar.gz
  • Upload date:
  • Size: 91.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.15.0 pkginfo/1.5.0.1 requests/2.24.0 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.50.2 CPython/2.7.15

File hashes

Hashes for efel-3.1.40.tar.gz
Algorithm Hash digest
SHA256 d1f89a264c87f849843d605d852ec8e252bedb985bc7844d98730f07f9f0f07d
MD5 3d89d01eb3be772b8de07bae0fe90d94
BLAKE2b-256 9d91cad554ce542b05891ce5e4c4ddd25e0133670818ddc50d6f58e3796e143c

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