Ecosyste.ms: Repos

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Package Usage: pypi: PyMeasure

Scientific measurement library for instruments, experiments, and live-plotting
19 versions
Latest release: 10 months ago
1 dependent package
4,687 downloads last month

View more package details: https://packages.ecosyste.ms/registries/pypi.org/packages/PyMeasure

View more repository details: https://repos.ecosyste.ms/hosts/GitHub/repositories/pymeasure%2Fpymeasure

Dependent Repos 6

alexliebmanp/strain_control

Orenstein Lab control of Razorbill strain cell

* requirements.txt

Size: 330 KB - Last synced: about 1 month ago - Pushed: 7 months ago

sumatrae/psu-viewer

power supply control gui

==0.6.1 requiremets.txt

Size: 45.5 MB - Last synced: about 1 year ago - Pushed: almost 2 years ago

amwaeber/ItMakesCoffee

IV measurement and analysis software

==0.9.0 requirements.txt

Size: 2.25 MB - Last synced: about 1 year ago - Pushed: over 1 year ago

xcapaldi/nanoprep

Nanopore formation, growth, conditioning and characterization using a PyMeasure interface with a Keithley 2400 Sourcemeter.

==0.10.0 requirements.txt

Size: 595 KB - Last synced: about 1 year ago - Pushed: over 1 year ago

nxwi/illacceptanything Fork of illacceptanything/illacceptanything

The project where literally anything* goes.

* data/requirements.txt

Size: 1.33 GB - Last synced: 7 months ago - Pushed: over 1 year ago

illacceptanything/illacceptanything

The project where literally anything* goes.

* data/requirements.txt

Size: 1.47 GB - Last synced: 10 days ago - Pushed: 10 days ago

This repository contains the code used for the publication of "On-demand training of deep learning equalizers for rolling shutter optical camera communications." It includes the U-net model and the training, validation, and testing procedures.

==0.9.0 requirements.txt

Last synced: over 1 year ago

ntchambers/illacceptanything

The project where literally anything* goes

* requirements.txt

Last synced: over 1 year ago

cristojv/opticalcamera

This repository contains the code used for the publication of "Convolutional autoencoder for exposure effects equalization and noise mitigation in optical camera communication" It includes the CAE model and the training, validation, and testing procedures. The latest version of this code can be found in the repository "On-demand training of deep learning equalizers for rolling shutter optical camera communications".