Saravanan666/pypi-org huggingface dataset:
Package: matrix-http-rendezvous-synapse
This is an implementation ofMSC3886forSynapse.UsageInstall the module to make it available to your Synapse environment:pip install matrix-http-rendezvous-synapseEnable the module in your homeserver.yaml:modules:
  - module: matrix_http_rendezvous_synapse.SynapseRendezvousModule
    config:
      prefix: /_synapse/client/org.matrix.msc3886/rendezvousMake the module available at the actual API endpoint in the Client-Server API by adding this to your homeserver.yaml:experimental_features:
  msc3886_endpoint: /_synapse/client/org.matrix.msc3886/rendezvousRun Synapse with the asyncio reactor enabled:SYNAPSE_ASYNC_IO_REACTOR=1 python -m synapse.app.homeserverConfiguration optionsApart from theprefixthe following config options are available:ttl: The time-to-live of the rendezvous session. Defaults to 60s.max_bytes: The maximum number of bytes that can be sent in a single request. Defaults to 4096 bytes.max_entries: The maximum number of entries to keep. Defaults to 10 000.An example configuration setting these and a custom prefix would like:modules:
  - module: matrix_http_rendezvous_synapse.SynapseRendezvousModule
    config:
      prefix: /rendezvous
      ttl: 15s
      max_bytes: 10KiB
      max_entries: 50000

experimental_features:
  msc3886_endpoint: /rendezvous # this should match aboveMemory usagemax_entriesandmax_bytesallow to tune how much memory the module may take.
There is a constant overhead of approximately 1KiB per entry, so with the default config (max_bytes = 4KiB,max_entries = 10000), the maximum theorical memory footprint of the module is(4KiB + ~1KiB) * 10000 ~= 50MiB.
Package: matrixlib
MatrixLibGeneral-purpose matrices for the layman.Implements a family of general-purpose matrix types, with comprehensive type-checking capabilities, and seamless integration with core Python services.>>>fromcollections.abcimportIterable>>>frommathimportfsum,sqrt,isclose>>>fromtypingimportLiteralasL>>>>>>frommatrixlibimportROW,RealMatrix,IntegerMatrix>>>>>>defnorm(a:Iterable[float])->float:...returnsqrt(fsum(map(lambdax:x*x,a)))...>>>a=IntegerMatrix[L[3],L[3],int](...(...1,2,3,...4,5,6,...7,8,9,...),...shape=(3,3),...)>>>>>>b=RealMatrix[L[3],L[3],float](...(...val...forrowina.slices(by=ROW)...forvalinrow/norm(row)...),...shape=a.shape,...)>>>>>>print(b)|0.26726…0.53452…0.80178…||0.45584…0.56980…0.68376…||0.50257…0.57436…0.64616…|(3×3)>>>>>>assertall(isclose(norm(row),1)forrowinb.slices(by=ROW))Getting StartedThis project is available throughpip(requires Python 3.9 or later, 3.11 recommended):pip install matrixlibWarning:  MatrixLib is currently in its infancy, and may see future changes that are not always backwards compatible.The current iteration of this library is inbeta. Further testing is being conducted at the moment.ContributingThis project is currently maintained byBraedyn L. Feel free to report bugs or make a pull request through this repository.LicenseDistributed under the MIT license. See theLICENSEfile for more details.
Package: matrixlib-jfj
MatrixlibNOTICE"rank" and "inverse" functions are a work in progress, they DO NOT WORK.A basic library for matrix and vector operations. Any feedback is highly encouraged. I enjoy trying to create modules and programs that work with mathematical functions and data. I also like looking into higher end modules and researching the processes and programs they use to perform tasks. Any feedback will be taken and acted upon.InstallationUse the package manager pip to install matrixlib_jfj.Release Versions:pipinstallmatrixlib_jfjTest Versions:pipinstall-ihttps://test.pypi.org/simplematrixlib-jfjGeneral Usageimportmatrixlib_jfjasml# matrix = ml.matrix.Matrix(rowcols=(x, y) or values=[[nested list(s) with values assigned]]) Initialises the matrix.Example:matrix=ml.matrix.Matrix(rowcols=(3,3))>>>[[0,0,0],[0,0,0],[0,0,0]]print(matrix)+--+|000|>>>|000||000|+--+# matrix.random(a, b) Adds random values to the entire matrixExample:matrix.random(1,10)+--+|7107|>>>|117||1058|+--+# matrix.identity() Creates an identity matrix from an existing square matrix+--+|100|>>>|010||001|+--+### Adding ###matrix1=ml.matrix.Matrix(values=[[1,2,3],[4,5,6],[7,8,9]])matrix2=ml.matrix.Matrix(values=[[9,8,7],[6,5,4],[3,2,1]])+--+|101010|>>>|101010||101010|+--+UpdatesUpdate 0.0.7Added "get_submatrix" function that gets the submatrix of any square matrix, added the "det" function which gets the determinant of a square matrix.Update 0.0.8Fixed bug where an external program would run when the user of the package would run their own program.Update 0.0.81Updated README file to reflect certain information.Update 0.0.82Fixed Type Annotations.Update 0.1.82Removed Deprecations, Removed functionality in utils.py (Temporary) added better typing, improved cumsum function.Update 0.1.90Added temporary base case to Matrix.rank() function.ContributingAny and All feedback and help is highly encouraged. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseGNU General Public License v3.0
Package: matrix-lite
MATRIX-Lite-PyMATRIX Lite Python is a library that allows users of varying skill levels to easily program their MATRIX Device.RoadmapLedsSensorsIMUHumidityPressureUVGPIOMicrophonesHal MicsALSA Mics (available through anyALSA wrapper)NFC(separate library)InstallationEnsure you have a Raspberry Pi, attached with a MATRIX device, that's flashed withRaspbian.1. Install MATRIX HALhttps://matrix-io.github.io/matrix-documentation/matrix-hal/getting-started/installation-package/2. Install Python 3To call your scripts with python 3, usepython3 YOUR_SCRIPT.pysudo apt-get install python3-pip3. Upgrade PIPpython3 -m pip install --upgrade pip4. Install matrix-lite-pypython3 -m pip install --user matrix-liteUsageThe matrix-lite package contains amatrix_lite&_matrix_halPython module._matrix_halis the direct HAL implementation.matrix_litecontains small abstractions for_matrix_hal.Everloopfrommatrix_liteimportledimporttime# Get LED countprint('This device has '+str(led.length)+' Leds')# A single string, object, or tuple will set all LEDs# Below are different ways of expressing a color (number values are from 0-255)led.set('blue')led.set('#0000ff')# Objects and tuples can utilize the white LEDled.set({'r':0,'g':0,'b':255,'w':0})led.set((0,0,255,0))# LEDs offled.set('black')led.set([])led.set()led.set({})# Arrays set individual LEDsled.set(['red','gold','purple',{},'black','#6F41C1','blue',{'g':255}])# Arrays can simulate motioneverloop=['black']*led.lengtheverloop[0]={'b':100}whileTrue:everloop.append(everloop.pop(0))led.set(everloop)time.sleep(0.050)Sensorsfrommatrix_liteimportsensorsimporttime#  Sensors will update with each .read() callwhileTrue:# Each .read() returns a dictionaryprint(sensors.imu.read())print(sensors.uv.read())print(sensors.humidity.read())print(sensors.pressure.read())time.sleep(5/1000)GPIOfrommatrix_liteimportgpio# Read GPIO pin 0 (digital)gpio.setFunction(0,'DIGITAL')gpio.setMode(0,'input')print('Pin 0 is: '+str(gpio.getDigital(0)))# Set GPIO pin 1 (digital)gpio.setFunction(1,'DIGITAL')gpio.setMode(1,'output')gpio.setDigital(1,'ON')# Set GPIO pin 2 (PWM)gpio.setFunction(2,'PWM')gpio.setMode(2,'output')gpio.setPWM({"pin":2,"percentage":25,"frequency":50,# min 36})# Set Servo Angle pin 3gpio.setFunction(3,'PWM')gpio.setMode(3,'output')gpio.setServoAngle({"pin":3,"angle":90,# min_pulse_ms (minimum pulse width for a PWM wave in milliseconds)"min_pulse_ms":0.8,})Building Locally For DevelopmentMake sure you haveMATRIX HAL& Python 3 installed.If you want to contribute to matrix-lite-py, below are the steps to build locally. Each step should take place on your Raspberry Pi.Download the repository.git clone https://github.com/matrix-io/matrix-lite-pyInstall pybind11.sudo python3 -m pip install pybind11Compile and install thematrix_litepython package with your changes.cd matrix-lite-py
sudo python3 -m pip install ./
Package: matrix-log-handler
matrix_log_handler==================.. image:: https://img.shields.io/pypi/v/matrix_log_handler.svg?style=flat-square:target: https://pypi.python.org/pypi/matrix_log_handler.. image:: https://img.shields.io/pypi/wheel/matrix_log_handler.svg?style=flat-square:target: https://pypi.python.org/pypi/matrix_log_handler.. image:: https://img.shields.io/pypi/format/matrix_log_handler.svg?style=flat-square:target: https://pypi.python.org/pypi/matrix_log_handler.. image:: https://img.shields.io/pypi/pyversions/matrix_log_handler.svg?style=flat-square:target: https://pypi.python.org/pypi/matrix_log_handler.. image:: https://img.shields.io/pypi/status/matrix_log_handler.svg?style=flat-square:target: https://pypi.python.org/pypi/matrix_log_handlerPython log handler that posts to a Matrix room. Posts to the Matrix API usinghttps://github.com/matrix-org/matrix-python-sdk.Installation------------.. code-block:: bashpip install matrix-log-handlerOptions-------base_url (required)~~~~~~~~~~~~~~~~~~~The base URL of the Matrix Homeserver to use.  Up to, but *not* including `/_matrix/client`.room_id (required)~~~~~~~~~~~~~~~~~~The room ID to use, like !ppfKZfDaaAaWzLkYrw:example.org.token~~~~~An access token that can be used to send messages.username and password~~~~~~~~~~~~~~~~~~~~~An optional username/password to login with.  Note that it advised *not* to use these parameters, but use ``token`` instead.fail_silent~~~~~~~~~~~Defaults to ``False``.If your access token, username/password, or base URL is invalid, or for some other reason the APIcall returns an error, this option will silently ignore the API error.If you enable this setting, **make sure you have another log handler** that will also handle thesame log events, or they may be lost entirely.Logging configuration--------------------This example will send log messages with the level of ERROR or above to Matrix... code-block:: pythonimport logginglogging.dictConfig({'version': 1,'disable_existing_loggers': False,'handlers': {'matrix-error': {'class': 'matrix_log_handler.MatrixLogHandler','level': 'ERROR','base_url': 'https://matrix.example.com','room_id': '!ppfKZfDaaAaWzLkYrw:example.org'},'loggers': {'': {'handlers': ['matrix-error'],'level': 'ERROR','propagate': True,},}}})logging.error('Hello, Matrix!')License-------Apache 2.0Matrix-Python-SDK is also under Apache 2.0.
Package: matrix_manipulation_aharas
Matrix manipulation helpersChangelogremoved an if condition from transpose2d, it was unnecessaryadded wraps to decorators to preserve the attributes, annotations and docstringsTable of ContentsProject OverviewPrerequisitesProject StructureTestProject OverviewA POC Python library that should help the data scientists to do data transformations, mainly focused on matrix transformations. The functions in the library are developed with vanilla python, but can work with Numpy arrays as well.PrerequisitesProject makes use of numpy and Python 3.10.
To start the process one needs to install dependencies listed in requirements.txt
Package can be install viapip3 install matrix_manipulation_aharas==0.4.2Project StructureProject consists of:
1.helpers- file containing required functions
2.decorators- decorators used fo validation of incoming data (matrix)
3.classes- an additional file with custom Matrix class. Main purpose was to practice inheritance, variance, static typing and goose typing.
4.tests- various test of functionsTestTo run the test executepython3 -m tests.testinmatrix-manipulation-aharasfolder.
Package: matrix-mdp-gym
Matrix MDPEasily generate an MDP from transition and reward matricies.Want to learn more on the story behind this repo? Check the blog posthere!InstallationAssuming you are in the root directory of the project, run the following command:pipinstallmatrix-mdp-gymUsageimportgymnasiumasgymimportmatrix_mdpenv=gym.make('matrix_mdp/MatrixMDP-v0')Environment documentationDescriptionA flexible environment to have a gym API for discrete MDPs withN_sstates andN_aactions given:A vector of initial state distribution vector P_0(S)A transition probability matrix P(S' | S, A)A reward matrix R(S', S, A) of the reward for reaching S' after having taken action A in state SAction SpaceThe action is andarraywith shape(1,)representing the index of the action to execute.Observation SpaceThe observation is andarraywith shape(1,)representing index of the state the agent is in.RewardsThe reward function is defined according to the reward matrix given at the creation of the environment.Starting StateThe starting state is a random state sampled from $P_0$.Episode TruncationThe episode truncates when a terminal state is reached.
Terminal states are inferred from the transition probability matrix as
$\sum_{s' \in S} \sum_{s \in S} \sum_{a \in A} P(s' | s, a) = 0$Argumentsp_à:ndarrayof shape(n_states, )representing the initial state probability distribution.p:ndarrayof shape(n_states, n_states, n_actions)representing the transition dynamics $P(S' | S, A)$.r:ndarrayof shape(n_states, n_states, n_actions)representing the reward matrix.importgymnasiumasgymimportmatrix_mdpgym.make('MatrixMDP-v0',p_0=p_0,p=p,r=r)Version Historyv0: Initial versions releaseAcknowledgementsThanks toWill Dudleyfor his help on learning how to put a Python package together/
Package: matrix-nio
nionio is a multilayeredMatrixclient library. The
underlying base layer doesn't do any network IO on its own, but on top of that
is a full-fledged batteries-included asyncio layer usingaiohttp. File IO is only done if you
enable end-to-end encryption (E2EE).DocumentationThe full API documentation for nio can be found athttps://matrix-nio.readthedocs.ioFeaturesnio has most of the features you'd expect in a Matrix library, but it's still a work in progress.✅ transparent end-to-end encryption (EE2E)✅ encrypted file uploads & downloads✅ space parents/children✅ manual and emoji verification✅ customauthentication types✅ well-integrated type system✅ knocking, kick, ban and unban✅ typing notifications✅ message redaction✅ token based login✅ user registration✅ read receipts✅ live syncing✅m.reactions✅m.tags❌ cross-signing support❌ server-side key backups (room key backup, "Secure Backup")❌ user deactivation (#112)❌ threading support❌ in-room emoji verificationInstallationTo install nio, simply use pip:$pipinstallmatrix-nioNote that this installs nio without end-to-end encryption support. For e2ee
support, python-olm is needed which requires thelibolmC library (version 3.x).
On Debian and Ubuntu one can useapt-getto install packagelibolm-dev.
On Fedora one can usednfto install packagelibolm-devel.
On MacOS one can usebrewto install packagelibolm.
Make sure version 3 is installed.After libolm has been installed, the e2ee enabled version of nio can be
installed using pip:$pipinstallmatrix-nio[e2e]Additionally, a docker image with the e2ee enabled version of nio is provided in
thedocker/directory.ExamplesFor examples of how to use nio, and how others are using it,read the docs
Package: matrix-odin-morphology
READMEWhat is this repository for?This repo hosts a version of MOM sofware, originally developed by David Wax in 2014.It was later significantly changed by Olga Zamaraeva.It is part of the AGGREGATION projectThe software helps infer morphological position classes (slots) from interlinearized data.What to cite if I use MOM for my research?Wax, David Allen. Automated grammar engineering for verbal morphology. Diss. 2014.Zamaraeva, Olga. Inferring Morphotactics from Interlinear Glossed Text: Combining Clustering and Precision Grammars. SIGMORPHON 2016 (2016): 141.How do I get set up?Please see theWiki. Most of the info is there, some may be outdated.There are dependencies; you should be able to easily install them by pip, but you may need to manually install Graphviz.You will need a config file. Please see a sample eng_config under config_files, ass well as documented_config for comments.You will need some files, particularly files containing what the program will treat as gloss grams and POS tags. See mom/util/collect_tags_xigt.pyFor morphosyntactic features, the program relies on FeatDict.py. mom/util/collect_tags_xigt.py will report if it finds grams that are not yet mapped to anything in FeatDict.py. Please enter them there manually, all lowercased, to whichever dictionary you think they should belong.Who do I talk to?Please contact Emily M. Bender about the AGGREGATION project and ask who is currently working on MOM.You can also contact olga.zamaraeva@ (geeeeemail), who may or may not be able to help you at this point (she will try).
Package: matrixor
matrixorMatrix transformations in Python. Implements algorithm 2.4 (AO+Scaling) of the paper:@article{devetal2018,
    title={{Absolute Orientation for Word Embedding Alignment}},
    author={Sunipa Dev and Safia Hassan and Jeff M. Phillips},
    journal={CoRR},
    year={2018},
    volume={abs/1806.01330}}Installpipinstallmatrixoror, after a git clone:python3setup.pyinstallRunAlign two models with Absolute Orientation + Scaling and return RMSETo align two embeddings, run:matrixoralign\--matrix-1/abs/path/to/xxx.vec.npy\--matrix-2/abs/path/to/yyy.vec.npy\pass in the--averageto return the averaged RMSE by aligning A and B then B and A (alignment may not be symmetric due to floating point average)
Package: matrixorbital-vfd
MatrixOrbital-VFDI2C display driver for Matrix Orbital VFDs.unofficial, not affiliated withMatrix Orbital CorpInstallpipinstallmatrixorbital-vfdUsagefrommatrixorbital_vfdimportVFD,BrightnesswithVFD(1,0x2e)asvfd:vfd.clear()vfd.brightness(Brightness.HIGH)vfd.write('Hello, world!')FunctionsVFD.display(True/False)turn on/off displayVFD.home()move cursor to home position 0x0VFD.position(column, row)move cursor to specified column/row positionVFD.move('left'/'right')move cursor left/right 1 columnVFD.clear()clear screenVFD.brightness(Brightness.MEDIUM or 'MEDIUM')set brightness to specified levelVFD.cursor(True/False)enable/disable block (blinking) cursorVFD.wrap(True/False)enable/disable line wrappingVFD.scroll(True/False)enable/disable auto line scrollingVFD.write('text')write text to display
Package: matrix-orderbot
OrderBotMatrix bot for take-out/delivery balance trackingInstallation (using Docker)Clone this repositoryFill inmatrix.envDBPATH=
MUSERNAME=
MSERVER=
MPASSWORD=Start container withdocker-compose up -dUsageInvite the bot into a room (it will auto-join). Start commands with!ob.
Using--helpor-hdisplays the help message for any command.CommandsOverall, the commands are split into two categories:usercommands: These commands are used to manage the users' accounts.ordercommands: These commands are used to order.User commandsjoin                join system with matrix-address
    register            register a different user, e.g. via just the name, use join to register yourself
    transfer            transfer money from one user to another
    payout              get a suggestion for a potential payout
    balance             display the balance of all users
    init                initialize a user's balance
    exit                deactivates user, if balance is zeroOrder commandsstart               start a new collective order
    add                 add item of a user to order
    tip                 set tip of the order
    remove              remove a user's item from the current collective order, all items of a user or all users
    edit                edit the price of an item
    end                 finish collective order
    cancel              cancel current collective order
    print               display current collective order
    reopen              reopen last order, if no current order
    suggest             return the last 5 ordered item of the user, with
                        pricing
    reorder             reorder the last item of a user, from the last order
    history             display history of the last [k] ordersExamplesHere, you can find a short set of commands which demonstrates the usage of the bot.!ob user join --allregisters all users in the matrix room with their current display name and their matrix address!ob order start "The Foo Bar"starts a new collective order with the name "The Foo Bar"!ob order add "Pizza" 10.50adds an item with name "Pizza" and price of 10.50 to the collective order for the current user!ob order add "Burger" --name @user:foo.bar 20adds an item with name "Burger" and price 20.00 to the collective order for user @user:foo.bar, assuming that user is registered!ob order tip 5adds a tip of 5.00 to the collective order!ob order endends the current collective order, assuming that the current user paid
Package: matrix-package
matrix_package is a molecular dynamics analysis code allowing to calculate several structural, dynamic, thermodynamic properties of amorphous, crystalline or semi-amorphous and electronic systems of certain 2D layered materials of Van Der Waals.
It is based on powerful solving algorithms, using MACHINE LEARNING to solve certain more or less complex problems such as the computation of the properties of dipole moments from Wanier centers.
version 22.02.09-alpha offers the possibility of processing six different inputs.
LAMMPS outputs, DL_POLY outputs, CPMD outputs, GAMESS outputs, Abinit outputs and VASP outputs.
this version will evolve gradually and will take into account more versions of inputs.
However, it has a module that allows you to convert an input into an XYZ file that it can then use to do several calculations.
Package: matrix-path
matrix_pathDescriptionUse the matrix class to create matrix objects and navigate the 2D matrix. Move with theright,left,up, anddownfunctions.
The '1's represent the path.Installationpip install matrix_pathHow to use?from matrix import Matrix

start_point = [0, 0]
end_point = [0, 4]
walls = [[0, 1], [1, 2]]
maze = Matrix(5, start_point, end_point, walls)
maze.print_matrix()License© 2020 Arush SharmaThis repository is licensed under the MIT license. See LICENSE for details.
Package: matrix-photos
matrix-photosThis aims to be a simplematrixclient for the photOS DIY photoframe.Matrix is an open standard for secure, decentralised, real-time communication.For photOS please checkouthttps://github.com/avanc/photOSfor more information.This client can be used to transfer files (pictures/photos) to the photoframe with end to end encryption support.
The idea is, that trusted users just can create a matrix room and invite the photoframe matrix user.
The photoframe user will automatically join this room and download all media sent to this room (You can specify which mimetypes are allowed).ConfigurationThere is a config-example.yml in this project which should be mostly self-explaining.It is possible to add textmessages to the images. This is done with the tool 'convert'.
The client automatically adds the first message after you post media content to the latest image when write_text_messages is set to true.You can also optionally define an admin_user which can run some administration commands on the photoframe.
If you define an admin user then just send !help from the specified user to the chatroom and the client sends you a list of available commands.RunningJust create a virtual environement install the requirements and you can run the client.python -m matrix_photos -c /path/to/config.ymlDevelopmentIf you want to develop or test the client, there is a docker-compose file in the docker directory which starts a matrix synapse homeserver,
a postgres database, an element matrix client and pgadmin if you want to check the database.