Saravanan666/pypi-org huggingface dataset:
Package: eeghdf
eeghdfProject to develop a easily accessible format for storing EEG in a way that is easy to access for machine learning.FeaturesFeatures derived from hdf5 format:hdf5 offers reliable, checksummed and compressed storage of digital EEG which was designed for long-term storage of datahdf5 is supported widely C, C++, javascript, python, julia, matlab,eeghdf offers a numpy-like interface to data without requiring the whole file to be loaded in memoryefficient reading (the whole file is not read into memory to access data)cloud enabled direct streaming from S3 buckets via the rcos3 driver"self documenting" and extensibleadvanced features: parallel readers/single writer, MPI, streaming supportedAdditional goals/features:build set of tools to visualize and analyze EEG based upon this format, visualizationeasy convertion to other formats: first target is mne-python "raw" format, BIDS-EEG next?Alternatives, background research and future goalslooked at edf and neo formats, seeNeurodata Without Borders. Compare withXDF.simplier than neo, but may need more of neo's structures as use growsONE formatcompare withMNEfif format of mne project to evolvefuture goalslook to support multiple records and different sampling rateslook to add fields for clinical report textlook to add field for montages and electrode geometry"extension" groupinstallationpip install eeghdfSimple install for developersThis assumes you want to make changes to the eeghdf code.change to the desired python virtual environmentmake sure you have git and git-lfs installedgit clone https://github.com/eegml/eeghdf.git 
cd eeghdf

python setup-dev.py developRe-samplingThere are many ways to resample signals. In my examples I used an approach based upon libsamplerate because it seemed to give accurate results. Depending on your
platform there are many options. Recently I have been suing pytorch based tools a lot, torchaudio has resamplinge tools and librosa is looks very impressive.Installation will vary but on ubuntu 18.04 I did:sudo apt install libsamplerate-dev
pip install git+https://github.com/cournape/samplerate/#egg=samplerateUltimately I will move the resampling code out of this repo. Maybe put it in eegml-signalTo Docode to write file, target initial release version is 1000initial scripts to convert edf to eeghdf and floating point hdf5code to subsample and convert edf -> eeghdfcode to write back to edfmore visualization code -> push to eegvisadd convenience interface to phys_signal with automagic conversion from digital->phys units
- should this use a subclass of numpy?add study admin code to record info (do not seem to include this now, e.g. EEG No like V17-105)code to clip and create subfilesallow patient info to propagatehash list/tree of history of file so that can track provenance of waveforms if desiredclip and maintain correct (relative) timesconsider how to handle derived records: for example the downsampled float32 records "frecord200Hz"
Package: eegio
EEG IOFor an easy-to-use API interfacing with EEG data in EDF, or FIF format in the BIDS-EEG layout.
This module stores the code for IO of EEG data for human patients, and pipelining code to convert clinical center data (i.e. time series eeg, clinical metadata) into a developer-friendly dataset that is also invertible and debug-friendly.TODOAdd support for adding structural context via neuroimaging processed data (e.g. FreeSurfer)Installation GuideEEGio is intended to be a lightweight wrapper for easily analyzing large batches of patients with EEG data. eegio relies on the following libraries to work:numpy
scipy
scikit-learn
pandas
mne
mne-bids
pybids
seaborn
matplotlib
pyedflib (deprecated)
xlrd (deprecated)SeeINSTALLATION GUIDEIntended Users / UsageEpilepsy researchers dealing with EEG data compliant with BIDS and MNE formats. Anyone with human patient EEG data.See example and docs for info on how to format this.https://github.com/bids-standard/bids-specification/blob/master/src/04-modality-specific-files/04-intracranial-electroencephalography.mdhttps://github.com/bids-standard/bids-starter-kit/wiki/The-BIDS-folder-hierarchySetting Up the BIDS Directory and Reading EEG Data From EDF/FiFThese are just lightweight wrappers of MNE/pyedflib reading to load in EDF/FiF data
easily, so that raw EEG ts are readily accessible in Python friendly format. We provide
an example that was built off of the examples in MNE-BIDS.
Seeexample.For more info, see tutorials and documentation.ContributingWe welcome contributions from anyone. Please view ourcontribution guidelines. Ourissuespage is a great place for suggestions!
If you have an idea for an improvement not listed there, pleasemake an issuefirst so you can discuss with the developers.
For information on setting up testing, seetesting guide.LicenseThis project is covered under theGNU GPL License.
Package: eeglabio
eeglabioI/O support for EEGLAB files in Python.InstallationInstall fromPyPI:pipinstalleeglabioInstall fromTest PyPI(built fromstablebranch):pipinstall-ihttps://test.pypi.org/simple/eeglabioInstall fromconda-forge:condainstall-cconda-forgeeeglabioInstall the latest version of the code from GitHub directly (unstable):pipinstallhttps://github.com/jackz314/eeglabio/archive/main.zipDependencieseeglabio requires Python >= 3.6 and the following packages:numpyscipyFor testing, we also require the following additional packages:mneExample Usage (withMNE)Export from MNEEpochsto EEGLAB (.set):importmnefromeeglabio.utilsimportexport_mne_epochsepochs=mne.Epochs(...)export_mne_epochs(epochs,"file_name.set")Export from MNERawto EEGLAB (.set):importmnefromeeglabio.utilsimportexport_mne_rawraw=mne.io.read_raw(...)export_mne_raw(raw,"file_name.set")
Package: eeg-positions
eeg_positionsCompute and plot standard EEG electrode positions.Please see theDocumentation.QuickstartThere are two common ways to make use of this repository:Go to thedata/directory and download the EEG electrode position files you need
(see theREADMEthere).Useeeg_positionsas a Python package (install throughpip install eeg_positions),
and then obtain the EEG electrode positions through theget_elec_coordsfunction.
See theExamplesandAPI documentation.CiteIf you find this repository useful and want to cite it in your work, please go
to theZenodo recordand obtain the
appropriate citation from the"Cite as"section there.
Package: eeg-sleep-analysis
Python scripts to analyze sleep-scored EEG filesOverviewEEG-based murine sleep studies use waveform signature to define three behavioral states--wake, rapid eye movement (REM) sleep, and non-REM (NREM) sleep. These recordings are long (typically 6-48 hours) and broken down into short epochs (usually 4-10 seconds). Either automatic or manual scoring is required to label each epoch as wake, NREM, or REM (and this package does not assist with this scoring).These scripts will read in scored EEG files and output key metrics into Excel. These metrics inlcude:Total time in wake, NREM, or REM sleep of user-specified bin size (default = 2 hours)Total number of wake, NREM, and REM sleep bouts of user-specified bin size (default = 12 hours)Average length of wake, NREM, and REM sleep bouts of user-specified bin size (default = 12 hours)Wake bout distribution, or a frequency of wake bouts by their duration. This binning can be specified by user; default is power of 2 (16 seconds - 2048 seconds).Spectral analysis (to be completed)This code was originally built in MATLAB, which was first used to analyze results inPerron IJ et al..If you use this analysis package, please cite this repo.Detailed installation istructions for first time usersFor users comfortable with python/anaconda, skip to last stepDownload andinstall anaconda, if you have not done so already.On your local machine, open anaconda shell. If you see (base), that means python is active in root environment.Non-first time users skip to step 4.. First time users should create new virtual environment:conda create --name env3In this example, env3 is the virutal environment name; it can be named whatever you prefer.Activate virutal environment:conda activate env3The terminal should now show (env3) instead of (base) if this worked correctly.Install eeg-sleep-analysis package:pip install eeg-sleep-analysisDetailed user instructionsIn terminal, navigate to your preferred directory.
To list directory routes:ls -la (for mac/linux)dir (for windows)To change directory:cd  (for mac/linux/windows)Type the command to launch the GUIpython -m EEGAnalysisFor a new experiment, create a config.txt file. This will be created in your current directory. You must open and edit this config file with correct file directories and experiment details.In the GUI, navigate to the correct config.txt file.Create a new conditions.csv. If the config.txt file is setup properly, this should be generated automatically and correctly. However, it is highly recommended to double check conditions.csv before running analysis.In the GUI, navigate to the correct conditions.csv file.Run the analysis. Results will be output into the specified directory in the config.txt file.Contact informationPlease direct any questions or suggestions toijperron@gmail.comAcknowledgementsThank you to the members of theUniversity of Pennsylvania Center for Sleep and Circadian Neurobiology, especially Drs. Allan Pack and Sigrid Veasey.
Thank you to Cameron Jones for his help to debug this program.
Package: eegsynth
The EEGsynth is aPythoncodebase released under theGNU general public licensethat provides a real-time interface between (open-hardware) devices for electrophysiological recordings (e.g., EEG, EMG and ECG) and analogue and digital devices (e.g., MIDI, lights, games and analogue synthesizers). The EEGsynth allows one to use electrical activity recorded from the brain or body to flexibly control devices in real-time, i.e. (re)active and passive brain-computer-interfaces (BCIs), biofeedback and neurofeedback.Since December 2018, the EEGsynth is registered as a legalAssociationwith the French authorities.DocumentationThe EEGsynth code and documentation are hosted on Github and organized as follows:bincontains binaries for the buffer and for some EEG systemsdoccontains the documentation on the EEGsynth softwarehardwarecontains the hardware documentationlibcontains some librariesmodulecontains the EEGsynth modulespatchescontains patches for performancesDisclaimerThe EEGsynth does not allow diagnostic investigations or clinical applications. It also does not provide a graphical user interface for offline analysis. Rather, the EEGsynth is intended as a collaborative interdisciplinaryopen-sourceandopen-hardwareproject that brings together programmers, musicians, artists, neuroscientists and developers in scientific and artistic exploration.Although there are plans to make it more 'plug-and-play', the EEGsynth currently has to be run from the command line, usingPythonandBashscripts, and is therefore not friendly for those not familiar with such an approach.Collaborate and get more informationWhen you start an project with the EEGsynth, consider doing it together with in a group of people that have knowledge and experience complimentary to yours, such as in electrophysiology, neuroscience, psychology, programming, computer science or signal processing.More information can be found atour website.  Follow us onFacebookandTwitter, and check our past and upcoming events onour calendar. Please feel free to contact us via ourcontact form.
Package: eek
Eek is a web crawler that outputs metadata about a website in CSV
format.Installation$ pip install eekUsageusage: eek [-h] [–graph] [–delay SECONDS] [–grep PATTERN] [-i] URLeek recursively crawls a website, outputing metadata about each page in
CSV format.positional arguments:
  URL                The base URL to start the crawl

optional arguments:
  -h, --help         show this help message and exit
  --graph            output a graphviz digraph of links instead of CSV
                     metadata
  --delay SECONDS    Time, in seconds, to wait in between fetches. Defaults to
                     0.
  --grep PATTERN     Print urls containing PATTERN (a python regular
                     expression).
  -i, --ignore-case  Ignore case. Only valid with --grepExample:eek http://example.com/To save output to a file, use redirectioneek http://example.com/ > ~/some_file.csvTo slow down crawling, use--delay=[seconds]
Package: eelale
cross-compiles Python wheels inside containers.Usage#buildwheelfromasinglepackage:$eelalebuildgevent#orfromasetofrequirements:$eelalebuild-rrequirements.txt#buildportablewheels(PEP513)$eelalebuild--policymanylinux1_x86_64gevent#providebuilddependenciesviaimages:$eelalebuild--imagebuild-dependency-imagepsycopg2InstallationSimplypip install eelale. You also need Docker.
Package: eelgraph
eelgraphcreates live chart.js charts from pythonExample Usage:importeelgraphfromeelgraph.chartsimportDoughnutchart=Doughnut({"People who use 4 spaces":5000,"People who use 2 spaces":50})eelgraph.plot(chart,title="Secrets of the Universe")Installationpython3 setup.py install
Package: eelifx
|SourceAutomatically set yourLifx globesaccording
to player ship game state inEmptyEpsilon. It uses theLifx LAN Protocoland may control
any lights that are on the same network as EELifx.InstallationWith Python 3.6+, runpip install eelifx(Virtualenvrecommended).Quick StartStart EmptyEpsilon in another console with the httpserver switch:EmptyEpsilon httpserver=8080Turn on your Lifx lights, make sure they are connRun EELifx and point it at your server, e.g.eelifx run 192.168.1.10oreelifx run localhostAdvanced UsageThe full range of commands are avaliable by running help:$ eelifx
Usage: eelifx [OPTIONS] COMMAND [ARGS]...

  EELifx Copyright (C) 2017 Chris Speck

Options:
  --loglevel TEXT  E.g. "DEBUG" or "INFO"
  --help           Show this message and exit.

Commands:
  grouptest   Execute each rule in succession.
  queryship   Query EE and set parameters if given.
  reset       Reset lights to base state.
  run         Poll and set lights according to game state.
  showconfig  Print default config to standard out.Custom ConfigsYour can pass the path to a custom config to therunandgrouptestcommands with--config<FILE>.You can find example configs inthe
repoor by
runningeelifx showconfigRules and GroupsGroups represent Lifx Groups, and have a match regex defined within the
configuration which tell EELifx which bulbs to apply the groups’ rules
to. The default pattern is.*(i.e. all groups).This tool peroidically polls EmptyEpsilon, parses the game state into a
ship object, and evaluates rule statements in the order in which they
are defined within each group. If the rule statement returns true then
its effect is applied, with the following notes:lights are always initially set to their base_stateset_powerlatches to False, that is, any call to False will
override any other call to True within that iterationset_colouraccepts any colour which thecolourpackage supportsthe last call toset_colouroverrides any earlier callset_luminanceaccepts a float in range 0 - 1the last call toset_luminanceoverrides any earlier callthe last call toset_waveformoverrides any earlier callthe luminance of any colour set throughset_colourorset_waveformwill be clipped to that group’smax_luminancethe luminance of any colour will be multiplied by any value set byset_luminanceWaveform SupportThis doesn’t seem to be documented particulararly well, but the source
of thelifx-gemshows that the following waveforms are supported:SAW = 0
SINE = 1
HALF_SINE = 2
TRIANGLE = 3
PULSE = 4set_waveformtakes a dictionary with the following keys: *hzas an integer *waveformas a string, being one of those named
above * an optinalalt_colour, being the same format as that given
toset_colourLifxCommanderThe methodsset_colour,set_power,set_waveformandset_luminanceare the only methods on lifx_commander which you
should call in your config. See example configs for details.Ship objectThe ship object exposes the following properties:ship.hull - float in range 0 - 1ship.energy - float in range 0 - 1ship.alert_level - string, ‘Normal’, ‘YELLOW ALERT’ or ‘RED ALERT’Licensed under the GPLv3
Package: eencijfer
eencijferETL-tool for Dutch eencijferDocumentation:https://enningb.github.io/eencijferGitHub:https://github.com/enningb/eencijferPyPI:https://pypi.org/project/eencijfer/Free software: MITFeaturesTODOCreditsThis package was created withCookiecutterand theenningb/cookiecutter-pypackageproject template.
Package: e-encryption
Easy EncryptionSimple data encryptionInstallationUse pip to install the package:pip install e-encryptionUsageThis package provides an easy way to encrypt informationPlease change the environment variableEASY_ENCRYPTION_KEY_LOCATIONto assign a location to the file that stores the key.By default the file key is generated in the home folder.frome_encryptionimportEasyEncryptionenc_msg=EasyEncryption.encrypt('This is an encrypted message')print('Encrypt',enc_msg)print('Decrypt',EasyEncryption.decrypt(enc_msg))Setting key file pathfrome_encryptionimportEasyEncryptionkey_file='/home/custom_location.key'ecryp=EasyEncryption(key_file)enc_msg=ecryp.encrypt('This is an encrypted message')print('Encrypt',enc_msg)print('Decrypt',ecryp.decrypt(enc_msg))
Package: eensight
Theeensighttool for measurement and verification of energy efficiency improvementsTheeensightPython package implements the measurement and verification (M&V) methodology that has been developed by the H2020 projectSENSEI - Smart Energy Services to Improve the Energy Efficiency of the European Building Stock.The online bookRethinking Measurement and Verification of Energy Savings(accessiblehere) explains in detail both the methodology and its implementation.Installationeensightcan be installed by pip:pipinstalleensightUsage1. Through the command lineAll the functionality ineensightis organized around data pipelines. Each pipeline consumes data and other artifacts (such as models) produced by a previous pipeline, and produces new data and artifacts for its successor pipelines.There are four (4) pipelines ineensight. The names of the pipelines and the associations between pipelines and namespaces are summarized below:traintestapplypreprocess✔✔✔predict✔✔✔evaluate✔✔adjust✔The primary way of usingeensightis through the command line. The first argument is always the name of the pipeline to run, such as:eensightrunpredict--namespacetrainThe commandeensightrun--helpprints the documentation for all the options that can be passed to the command line.2. As a libraryThe pipelines ofeensightare separate from the methods that implement them, so that the latter can be used directly:importpandasaspdfromeensight.methods.prediction.baselineimportUsagePredictorfromeensight.methods.prediction.activityimportestimate_activitynon_occ_features=["temperature","dew point temperature"]activity=estimate_activity(X,y,non_occ_features=non_occ_features,exog="temperature",assume_hurdle=False,)X_act=pd.concat([X,activity.to_frame("activity")],axis=1)model=UsagePredictor(skip_calendar=True).fit(X_act,y)
Package: eenum
EEnum is an extension to the python enum library.  It adds some features to
enum and wraps Enum3.4 so it can be used invisibly across python versions.Installation$pipinstalleenumSupportsPython eenum has been tested with Python 2.7, 3.5, and 3.6Docs & SourceDocs:http://python-eenum.readthedocs.io/en/latest/Source:https://github.com/cltrudeau/eenum
Package: eep
Emacs style, point based search-replace for python.It works by moving apointand amarkaround in the text,
somewhat similar to how emacs handles itsbuffers. This becomes
intuitive and easier forsometext processing tasks which require
usage ofafterandbeforein text.An example problem ishere. Usingeep, the equivalent python code isimporteeptext="""<p class='q'>Q: Why</p>\n<p class='a'>Because</p>\n<p class='a'>You need to do</p>\n\n<p class='q'>Q: How</p>\n<p class='a'>Do this</p>\n<p class='a'>And that</p>"""es=eep.Searcher(text)print("Before :\n"+str(es)+"\n\n")whilees.search_forward("<p class='q'>"):es.search_forward("<p class='a'>")es.swap_markers()es.insert("<div class='a'>\n")ifes.search_forward("<p class='q'>"):es.search_backward("</p>")es.swap_markers()es.insert("\n</div>")es.goto("end")es.search_backward("<p class='a'>")es.search_forward("</p>")es.insert("\n</div>")es.goto("start")whilees.search_forward("<p class='a'>"):es.replace("<p>")es.goto("start")whilees.search_forward("<p class='q'>Q: "):es.replace("<p class='q'>")print("After :\n"+str(es))Before:<pclass='q'>Q:Why</p><pclass='a'>Because</p><pclass='a'>Youneedtodo</p><pclass='q'>Q:How</p><pclass='a'>Dothis</p><pclass='a'>Andthat</p>After:<pclass='q'>Why</p><divclass='a'><p>Because</p><p>Youneedtodo</p></div><pclass='q'>How</p><divclass='a'><p>Dothis</p><p>Andthat</p></div>UsageInstall usingpip install eepInstantiate a searcherimporteepes=eep.Searcher("this is a sample text. this is a sentence.")A searcher has two markers for defining regions. Apointmoves
around while searching, replacing, inserting etc. It is thecurrentposition where operations are done.markmoves after successful forward or backward searches to mark
matching region with thepoint.# Search forward for first match from current point# Return true if match found# Set mark in beginning and point at endes.search_forward("th")# Search backward for first match from current point# Return true if match found# Set point in beginning and mark at endes.search_backward("th")# Replace marked regiones.replace("dodo")# Insert at current pointes.insert("dodo")# Move the pointes.jump(-3)es.goto(34)# also accepts "start" and "end" strings# Exchange markerses.swap_markers()
Package: eepackages
# eepackages[![PyPi version](https://badgen.net/pypi/v/eepackages/)](https://pypi.com/project/eepackages)
[![CI](https://github.com/gee-community/ee-packages-py/actions/workflows/ci.yaml/badge.svg?branch=main&event=push)](https://github.com/gee-community/ee-packages-py/actions/workflows/ci.yaml)
[![CD](https://github.com/gee-community/ee-packages-py/actions/workflows/cd.yaml/badge.svg?branch=main&event=release)](https://github.com/gee-community/ee-packages-py/actions/workflows/cd.yaml)A set of utilities built on top of Google Earth Engine (migrated from JavaScript)This repository is basically a Python version of a set of utilities developed by me (@gena) while working with Google Earth Engine and migrated from JavaScript repository:https://code.earthengine.google.com/?accept_repo=users/gena/packagesFor a GitHub clone of this package see:https://github.com/gee-community/ee-packages-jsThere are not docs (yet), some of the utilities are demonstrated in the following presentation:https://docs.google.com/presentation/d/103gfl3gS8rokkrcMJV9qMBnkV7oLLbDf8ygDu6QaIZQ/edit?usp=sharing## Usage## Installation## Requirements## Compatibility## Licence## Authorseepackageswas written byGennadii Donchyts.## TODOunit testingcoverage
Package: eeprivacy
This repository contains the pilot implementation of the core privacy methods for Energy Differential Privacy (EDP). The key components are:Core Differential Privacy for energy efficiency analytics (eeprivacy)Python API documentation foreeprivacySample implementations of key use cases[Examples and library documentation](https://openeemeter.github.io/eeprivacy/)—Energy Differential Privacy (EDP) enables the use of the gold standard of privacy protection, differential privacy, for high value energy efficiency analytics.—Installationpip install eeprivacyLocal UsageNotebooksWith your preferred notebook environment (like [JupyterLab](https://jupyterlab.readthedocs.io/en/stable/) or [nteract](https://nteract.io/)), installeeprivacyand try out any of the [example notebooks](https://openeemeter.github.io/eeprivacy/private-load-shape-algorithm-design.html).REPL>>> from eeprivacy.mechanisms import LaplaceMechanism
>>> LaplaceMechanism.execute(value=0, epsilon=0.1, sensitivity=1)
1.198515653814998DevelopmentBuild docs:./bin/build_docsRun tests:./bin/test