Saravanan666/pypi-org huggingface dataset:
Package: psireact
PsiReactHierarchical Bayesian modeling of response time data.This package currently implements the linear ballistic accumulator (LBA) model (Brown & Heathcote 2008), with potential for other decision models to be added later.
LBA has a closed-form solution, making it mathmatically tractable, while capturing many important properties of response time distributions.
Importantly, while many response time models only support simulation of tasks with only two response options, LBA can simulate tasks with many response options.In this example, there are 24 possible responses with different levels of support.
Each curve shows the probability density function for one response according to the LBA model.
The overall height of each curve reflects the probability of that response, and the shape reflects the probability of different response times.PsiReact can be used to:Fit data to estimate model parametersUse hierarchical models to estimate both group-level tendencies and individual differencesGenerate simulated response time data for analysisCompare different models of response behaviorInstallationFirst, it is strongly recommended that you set up either aConda environmentor aPython virtual environment.
This helps keep packages installed for different projects separate.
For example, using Conda:condacreate-npsireactpython=3.8
condaactivatepsireactYou can install the latest stable version of PsiReact using pip:pipinstallpsireactYou can also install the development version directly from the code
repository on GitHub:pipinstallgit+git://github.com/mortonne/psireactGetting startedTo get an intuition for what sort of behavior the LBA model can produce, look at theLBA demo notebook.
The LBA model can be used to both generate simulated data and to estimate parameters based on observed data.
See theLBA parameter recoverynotebook for examples.
Also see examples of more complex hierachical models in theNireactandPsiReact-Garnetprojects.Road mapDirections for future development:notebook illustrating definition and use of a hierarchical modelsupport for additional response time modelstesting and demo of maximum likelihood estimationCitationIf you use PsiReact, please cite the following:Morton NW, Schlichting ML, Preston AR. 2020.
Representations of common event structure in medial temporal lobe and frontoparietal cortex support efficient inference.
Proceedings of the National Academy of Sciences.
117(47): 29338-29345.doi:10.1073/pnas.1912338117.Morton NW. 2020.
PsiReact: Modeling of response time data.
Zenodo.doi:10.5281/zenodo.4282757.
Package: psi-score
Psi-score$\psi$-score: Metric of user influence in Online Social NetworksRequirementsPython >=3.9,<3.11Installation$pipinstallpsi-scoreUsage>>>frompsi_scoreimportPsiScore>>>adjacency={0:[1,3],1:[0,2],2:[0,1,3],3:[0]}>>>lambdas=[0.23,0.50,0.86,0.19]>>>mus=[0.42,0.17,0.10,0.37]>>>psiscore=PsiScore()>>>scores=psiscore.fit_transform(adjacency,lambdas,mus)>>>scoresarray([0.21158803,0.35253745,0.28798439,0.14789014])>>>np.round(scores,2)array([0.21,0.35,0.29,0.15])You can use another algorithm and change some parameters:>>>psiscore=PsiScore(solver='power_nf',n_iter=500,tol=1e-3)>>>scores=psiscore.fit_transform(adjacency,lambdas,mus,ps=[1],qs=[0,3])Thepsandqsparameters allows to have some chosenp_iandq_ivectors (only with thepushandpower_nfmethods):>>>psiscore.P{1:array([0.5333334,0.1681094,0.46801851,0.34442264])}>>>psiscore.Q{0:array([0.46164044,0.0514935,0.02798624,0.30484491]),3:array([0.13087053,0.01616898,0.01850541,0.42554885])}Licensepsi-scorewas created by Nouamane Arhachoui. It is licensed under the terms of the MIT license.ReferencesGiovanidis, A., Baynat, B., Magnien, C., & Vendeville, A. (2021).
Ranking Online Social Users by Their Influence.
IEEE/ACM Transactions on Networking, 29(5), 2198-2214.https://doi.org/10.1109/tnet.2021.3085201Arhachoui, N., Bautista, E., Danisch, M., & Giovanidis, A. (2022).
A Fast Algorithm for Ranking Users by their Influence in Online Social Platforms.
2022 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 526-533.https://doi.org/10.1109/ASONAM55673.2022.10068673
Package: psite-recommender
Recommender_System_ProteomicsScripts to run Recommender Systems on Proteomics data.Downloading:click on the green "Code" button on the top right and Download ZIP, then unzip itor usegit clonehttps://github.com/ManuelGander/Recommender_System_Proteomics.gitRunning the scripts:The notebook "Full_script.ipynb" contains all the information needed to run the scripts
Package: psiturk-dallinger
<img src=”https://psiturk.org/static/images/psiturk_logo_README.png”>[![Build Status](https://travis-ci.org/NYUCCL/psiTurk.png?branch=master)](https://travis-ci.org/NYUCCL/psiTurk)
[![Coverage Status](http://coveralls.io/repos/NYUCCL/psiTurk/badge.png?branch=master)](http://coveralls.io/r/NYUCCL/psiTurk?branch=master)
[![Code Health](https://landscape.io/github/NYUCCL/psiTurk/master/landscape.png)](https://landscape.io/github/NYUCCL/psiTurk/master)
[![Downloads](https://pypip.in/d/PsiTurk/badge.png)](https://pypi.python.org/pypi/PsiTurk/)
[![License](http://img.shields.io/badge/license-MIT-red.svg)](http://en.wikipedia.org/wiki/MIT_License)The current stable version is 2.1.1.Please visit [psiturk.org](https://psiturk.org) for more information.You are welcome to use this code for personal or academic uses. If you fork,
or use this in an academic paper please cite as follows:McDonnell, J.V., Martin, J.B., Markant, D.B., Coenen, A., Rich, A.S., and Gureckis, T.M.
(2012). psiTurk (Version 1.02) [Software]. New York, NY: New York University.
Available fromhttps://github.com/NYUCCL/psiTurk
Package: psiturk-wallace
<img src=”https://psiturk.org/static/images/psiturk_logo_README.png”>[![Build Status](https://travis-ci.org/NYUCCL/psiTurk.png?branch=master)](https://travis-ci.org/NYUCCL/psiTurk)
[![Coverage Status](http://coveralls.io/repos/NYUCCL/psiTurk/badge.png?branch=master)](http://coveralls.io/r/NYUCCL/psiTurk?branch=master)
[![Code Health](https://landscape.io/github/NYUCCL/psiTurk/master/landscape.png)](https://landscape.io/github/NYUCCL/psiTurk/master)
[![Downloads](https://pypip.in/d/PsiTurk/badge.png)](https://pypi.python.org/pypi/PsiTurk/)
[![License](http://img.shields.io/badge/license-MIT-red.svg)](http://en.wikipedia.org/wiki/MIT_License)The current stable version is 2.1.1.Please visit [psiturk.org](https://psiturk.org) for more information.You are welcome to use this code for personal or academic uses. If you fork,
or use this in an academic paper please cite as follows:McDonnell, J.V., Martin, J.B., Markant, D.B., Coenen, A., Rich, A.S., and Gureckis, T.M.
(2012). psiTurk (Version 1.02) [Software]. New York, NY: New York University.
Available fromhttps://github.com/NYUCCL/psiTurk
Package: psiz
WARNING:This package is pre-release and the API is not stable. All APIs are subject to change and all releases are alpha.PurposePsiZ provides computational tools for modeling how people perceive the world. The primary use case of PsiZ is to infer psychological representations from human behavior (e.g., similarity judgments). The package integrates cognitive theory with modern computational methods.ResourcesOfficial Psiz Documentation:psiz.readthedocs.io/en/latestPsiZ ExamplesWhat's in a name?The name PsiZ (pronounced like the wordsize, /sʌɪz/) is meant to serve as shorthand for the termpsychological embedding. The greek letter Psi is often used to denote the field of psychology and the matrix variableZis often used in machine learning to denote a latent feature space.InstallationThere are two different ways to install: PyPI or git. Installing via git has the advantage of including examples and tests in the cloned repository.Using PyPI$ pip install psizYou can optionally install the python packages necessary for running package tests (e.g.,pytest):$ pip install "psiz[test]"Using git# Clone the PsiZ repository from GitHub to your local machine.
$ git clone https://github.com/psiz-org/psiz.git
# Use `pip` to install the cloned repository.
$ pip install /local/path/to/psizNotes:PsiZ depends on TensorFlow. Please see theTF compatibility matrixfor supported Python and CUDA versions for each version of TensorFlow.PsiZ versions <=0.5.0 must be installed using git clone and editable mode (e.g.,pip install -e /local/path/to/psiz).You can install specific releases:using PyPI:pip install 'psiz==0.5.1'using git:git clone https://github.com/psiz-org/psiz.git --branch v0.5.1AttributionIf you use PsiZ in your work please cite at least one of the following:@InProceedings{Roads_Love_2021:CVPR,
    title     = {Enriching ImageNet with Human Similarity Judgments and Psychological Embeddings},
    author    = {Brett D. Roads and Bradley C. Love},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year      = {2021},
    month     = {6},
    pages     = {3547--3557}
    doi       = {10.1109/CVPR46437.2021.00355},
}@Article{Roads_Mozer_2019:BRM,
    title   = {Obtaining psychological embeddings through joint kernel and metric learning},
    author  = {Brett D. Roads and Michael C. Mozer},
    journal = {Behavior Research Methods},
    year    = {2019},
    volume  = {51},
    pages   = {2180–-2193},
    doi     = {10.3758/s13428-019-01285-3}
}Contribution GuidelinesIf you would like to contribute please see thecontributing guidelines.This project uses aCode of Conductadapted from theContributor Covenantversion 2.0, available athttps://www.contributor-covenant.org/version/2/0/code_of_conduct.html.LicenceThis project is licensed under the Apache Licence 2.0 - see LICENSE file for details.
Package: psiz-datasets
PsiZ DatasetsWARNING:This package is pre-release and the API is not stable. All APIs are subject to change and all releases are alpha.PurposeProvide pre-formatted TensorFlow Datasets for hassle-free model ingestion.ResourcesOfficial Psiz Documentation:psiz.readthedocs.io/en/latestRaw JSON-formatted data files used to create TensorFlow Datasets:osf.io psiz-datasetsInstallationThere are two different ways to install: PyPI or git.Using PyPI$ pip install psiz-datasetsUsing git# Clone the repository from GitHub to your local machine.
$ git clone https://github.com/psiz-org/psiz-datasets.git
# Use `pip` to install the cloned repository.
$ pip install /local/path/to/psiz-datasetsContribution GuidelinesIf you would like to contribute please see thecontributing guidelines.This project uses aCode of Conductadapted from theContributor Covenantversion 2.0, available athttps://www.contributor-covenant.org/version/2/0/code_of_conduct.html.LicenceThis project is licensed under the Apache Licence 2.0 - see LICENSE file for details.
Package: psj.content
IntroductionThePlone Scholarly Journal(PSJ) is a collection of packages to
create and maintain scholarly journals using Plone.The special abilities of PSJ are:High quality on-the-fly transformations of office documents using
OpenOffice.org.Flexible metadata handlingThis package contains the content types and metadata handling.Currently, the whole thing consists of three packages:psj.content(this package)psj.policy(provides mainly office-document transformations using
OpenOffice.org)psj.site(kind of umbrella package for the other packages).RequirementsPSJ runs on Plone 3.x with Python 2.4.InstallationIf you want to run a complete PSJ site, then you should usepsj.site, which will fetch all other needed packages
automatically.psj.sitecomes also with extended installation
notes.The whole installation process is driven byzc.buildout.If you want to run this package alone, follow the follwing steps:Runbootstrap.py:$ python2.4 bootstrap/bootstrap.pyThis will create basic build scripts and directories.Runbuildout:$ ./bin/buildoutThis will fetch all packages needed from the internet and install
it locally. Also all scripts are created by this step.Start the server:$ ./bin/instance fgNow you can login onhttp://localhost:8080/manage. Default
credentials are: usernameadmin, passwordadmin.You can change the credentials inbuildout.cfg.If you want to start the server in background, do:$ ./bin/instance startStop the server by pressing CTRL-C on the commandline. If you
started the server in background, do:$ ./bin/instance stopIf you want to run the tests:Do the tests:$ ./bin/instance test -s psj.contentSponsors/CreditsInitial programming was undertaken on behalf of the “Stiftung Deutsche
Geisteswissenschaftliche Institute im Ausland” (Foundation German
Humanities Institutes Abroad) for the publication platformhttp://www.perspectivia.net.Funding was provided by the German “Bundesministerium fuer Bildung und
Forschung” (Federal Ministry of Education and Research).The programming was coordinated by theFafalter GmbH, Duesseldorf,
Germany, namely Ruth and Bories von dem Bussche.Many thanks to all these institutions and persons!Changelog0.2 (2008-12-09)Feature ChangesAdded metadatabox for all content types.Added exporter for metadata schemata.Display a link to metadatafield ‘bdb_id’ if it is present in PSJ
document views (PSJDocument, PSJRetroArticle, PSJReview)Bug FixesLink to source document in PSJ document views is now only visible
when principal has ‘PSJ: Add PSJ Document’ permission.Remove inline metadata from folderish PSJ document views.0.1 (2008-10-26)Initial releaseDownload
Package: ps-k8s-ctrl-common
ps-k8s-ctrl-commonWhat does this package doThis package is a of functions that are common to all Commercial Mobility
Kubernetes Configuration controllersSetupClone Repo# Make a copy of the repo
git clone git@git.viasat.com:Mobility-Engineering/ps-k8s-ctrl-common.git
# Load any submodules
cd ps-k8s-ctrl-common
git submodule update --initSetup version.txt file (one time only)This repo uses automatic versioning; so you will need a version.txt file.
To create one (one time only), use the following command:make version.txtCreate a virtual environment (one time, unless new packages added)make virt-envGenerate package documentationmake documentationThe documentation is created as a web page in the pdoc folder.  Open your browser
at this URL:
file:///(home directory for your repo)/pdoc/index.html
(eg. My repo is located at /Users/snakada/git/nebula/ps/ps-k8s-ctrl-common; so
I would open the browser at: file:///Users/snakada/git/nebual/ps/ps-k8s-ctrl-common/pdoc/index.html)
In the left column, navigate to the ps_k8s tab to find the documentation for the
PsK8s classHow to run Unit Testssource venv/bin/activate
make unit-testRun static analysismake static-anaylsisCleanupRemove built wheel packagemake cleanRemove test docker containermake remove-container
Package: pskca
Pre-shared key-based certificate authority and requestorThis package implements a protocol for certificate issuance that two parties
(a server, the CA -- and a client, the requestor) can use to negotiate the
issuance of certificates valid from the perspective of the CA.  The only
prerequisites for a successful certificate issuance are:There is a cleartext communication channel between the two parties.Both parties already have a PSK they both trust (generated, perhaps
with the blindecdh Python module, and then subsequently verified
by both parties).The purpose of this is to establish enduring trust between server and client.After successful untampered and verified key exchange between two parties
(the server and the client), both have a shared secret they can use to encrypt
and decrypt traffic.  This is useful, but the key is not enough — the modern
goal of communications cryptography is to arrive at mutually authenticated TLS
between the peers, so that the peers can then continue in a fully symmetrically
authenticated manner (e.g. via mTLS or gRPC).The package contains two main parts:a certificate authority (CA) capable of issuing certificates to authorized
entities,a certificate requestor to negotiate certificate issuance requests with the
certificate authority.Authentication for certificate issuance is predicated on both sides (the CA
and the requestor) holding a pre-shared key (which can be negotiated via ECDH
using theblindecdh packageand then
authorized using theshortauthstrings package).A set of utility functions and objects are also provided to simplify use of
this package.Here is some sample code:import os, pskca

client_id = "xxx"
ca_cert, ca_key = pskca.create_certificate_and_key(ca=True)
client_csr, client_key = pskca.create_certificate_signing_request()
psk = os.urandom(32)

C = pskca.CA(ca_cert, ca_key)
C.add_psk(client_id, psk)
R = pskca.Requestor(psk)
payload = R.encrypt_csr(client_csr)
# If you were sending the encrypted payload over the wire, you'd then
# call .to_bytes() on the object resulting from encrypt_csr() call.
_, __, enc_client_cert, enc_cert_chain = C.issue_certificate(client_id, payload)

# If you received enc_client_cert and enc_cert_chain over the wire,
# they'd be bytes, so you'd create the respective objects thus:
# enc_client_cert = pskca.EncryptedClientCertificate(enc_client_cert)
# enc_cert_chain = pskca.EncryptedCertificateChain(enc_cert_chain)
client_cert, enc_cert_chain = R.decrypt_reply(enc_client_cert, enc_cert_chain)

print("Client certificate obtained: %s" % client_cert)
print("Root of trust certificate obtained: %s" % cert_chain)
print("CA certificate should be valid according to root of trust: %s" % ca_cert)

# Client certificate obtained: <Certificate(subject=<Name(CN=projects)>, ...)>
# Root of trust certificate obtained: [<Certificate(subject=<Name(C=XX,...)>...]
# CA certificate should be valid according to root of trust: <Certificate(subject=<Name(C=XX...)>You'll find more developer and implementation documentation in themodule.This package is distributed under the GNU Lesser General Public License v2.1.
For relicensing, contact the package author.
Package: psk-escpos
DescriptionPython ESC/POS is a library which lets the user have access to all those printers handled
by ESC/POS commands, as defined by Epson, from a Python application.The library tries to implement the functions provided by the ESC/POS-commandset and supports sending text, images,
barcodes and qr-codes to the printer.Text can be aligned/justified and fonts can be changed by size, type and weight.Also, this module handles some hardware functionalities like cutting paper, control characters, printer reset
and similar functions.Since supported commands differ from printer to printer the software tries to automatically apply the right
settings for the printer that you set. These settings are handled byescpos-printer-dbwhich is also used inescpos-php.DependenciesThis library makes use of:pyusbfor USB-printersPillowfor image printingqrcodefor the generation of QR-codespyserialfor serial printerspython-barcodefor the generation of barcodesDocumentation and UsageThe basic usage is:fromescpos.printerimportUsb""" Seiko Epson Corp. Receipt Printer (EPSON TM-T88III) """p=Usb(0x04b8,0x0202,0,profile="TM-T88III")p.text("Hello World\n")p.image("logo.gif")p.barcode('1324354657687','EAN13',64,2,'','')p.cut()Another example based on the Network printer class:fromescpos.printerimportNetworkkitchen=Network("192.168.1.100")#Printer IP Addresskitchen.text("Hello World\n")kitchen.barcode('1324354657687','EAN13',64,2,'','')kitchen.cut()Another example based on the Serial printer class:fromescpos.printerimportSerial""" 9600 Baud, 8N1, Flow Control Enabled """p=Serial(devfile='/dev/tty.usbserial',baudrate=9600,bytesize=8,parity='N',stopbits=1,timeout=1.00,dsrdtr=True)p.text("Hello World\n")p.qr("You can readme from your smartphone")p.cut()The full project-documentation is available onRead the Docs.ContributingThis project is open for any contribution! Please seeCONTRIBUTING.rstfor more information.DisclaimerNone of the vendors cited in this project agree or endorse any of the patterns or implementations.
Its names are used only to maintain context.
Package: psl
pslMozilla Public Suffix list as a Python package and updated daily.Install viapython -m pip install pslSeehttps://publicsuffix.orgfor more information regarding the list itself.APIThe package provides the following members as an API:domain_suffixes()defdomain_suffixes(dn:str,*,icann_only:bool=False)->Suffixes:...Queries the Public Suffix list for the given domain and returns a named tuple containing
the public and private suffixes for the domain.  Either value can beNoneif that
field isn't available. (egprivate=Nonefor the domaincom)domain_can_set_cookie()defdomain_can_set_cookie(*,http_domain:str,cookie_domain:str)->bool:...Determines if a user-agent that receives an HTTP response from domain<http_domain>withSet-Cookieheaders with parameterDomain=<cookie_domain>should allow
that cookie to be set.  This disallows cookies from being set on public suffixes
and on domains that the HTTP domain has no authority over.This is the same mechanism that modern browsers use to determine whether it's safe
to set a cookie to prevent 'super-cookies'.LicenseMPL-2.0
Package: pslab
PSLab Python LibraryThe Python library for thePocket Science Labfrom FOSSASIA.This repository hosts the Python library for communicating with the Pocket Science Lab open hardware platform (PSLab). Using this library you can communicate with the PSLab using simple Python code. The Python library is also used by the PSLab GUI as a backend component.The goal of PSLab is to create an Open Source hardware device (open on all layers) and software applications that can be used for experiments by teachers, students and scientists. Our tiny pocket lab provides an array of instruments for doing science and engineering experiments. It provides functions of numerous measurement tools including an oscilloscope, a waveform generator, a logic analyzer, a programmable voltage and current source, and even a component to control robots with up to four servos.For more information seehttps://pslab.io.BuyYou can get a Pocket Science Lab device from theFOSSASIA Shop.More resellers are listed on thePSLab website.Installationpslab-python can be installed from PyPI:$ pip install pslabNote: Linux users must either install a udev rule by running 'pslab install' as root, or be part of the 'dialout' group in order for pslab-python to be able to communicate with the PSLab device.Note: If you are only interested in using PSLab as an acquisition device without a display/GUI, only pslab-python needs to be installed. If you would like a GUI, install thepslab-desktop appand follow the instructions of the Readme in that repo.Validate installationPlug in the PSLab device and check that both the LEDs light up.The following piece of code should run without errors:from pslab import ScienceLab
psl = ScienceLab()
capacitance = psl.multimeter.measure_capacitance()
print(capacitance)CommunicationIf you encounter any bugs, please file them in ourissue tracker.You can chat with the PSLab developers onGitter.There is also amailing list.Wherever we interact, we strive to follow theFOSSASIA Code of Conduct.ContributingSeeCONTRIBUTING.mdto get started.LicenseCopyright (C) 2014-2021 FOSSASIAThis program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3.This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.You should have received a copy of the GNU General Public License along with this program.  If not, seehttp://www.gnu.org/licenses/.
Package: pslib
pslibA python library for interacting with Pokémon Showdown.🚧 Work in progress 🚧importasyncioimportpslibasyncdefjoin_battles(client):whileTrue:forbattleinawaitclient.query_battles():try:awaitbattle.join()exceptpslib.JoiningRoomFailed:passasyncdefdisplay_logs(client):asyncformessageinclient.listen(pslib.WinMessage,all_rooms=True):print(message.room.logs)awaitmessage.room.leave()asyncdefmain():asyncwithpslib.connect()asclient:awaitasyncio.gather(join_battles(client),display_logs(client))asyncio.run(main())InstallationThe package can be installed withpip.$pipinstallpslibLicense -MIT