Saravanan666/pypi-org huggingface dataset:
Package: dm-robotics-geometry
Overviewgeometry.pyprovides primitives for dealing with scene and robot geometry.Main ConceptsGeometrical typesPose: The 6D position and orientation of a body. Construction methods:Pose(position=[x,y,z],quaternion=[w,i,j,k])Pose.from_hmat(homogeneous_matrix)Pose.from_poseuler(poseuler=[x,y,z,p,r,w],ordering="XYZ")WrenchandWrenchStamped6D force-torque.TwistandTwistStamped6D velocity.AccelandAccelStamped6D acceleration.For debugging and visualization,PoseandPoseStampedobjects can be
constructed with anameparameter.Frames and Stamped typesAll quantities here come in plain and 'Stamped' varieties. A stamped quantity
(E.g.TwistStamped) is always defined as a plain type (E.g.Twist) with
respect to aframe.  Aframeis something that can be evaluated
to a world-pose -- either aPoseStampedor aGrounding.  A grounding is
optional (i.e. can use None to indicate world-frame).  This library supports
different grounding back-ends, e.g. mujoco-elements or observation-dicts.For example, the pose of a plug in a robot gripper could be expressed as aPoseStampedwith a combination of thePoseof the gripper in world frame
and the pose of the plug with respect to the gripper.A frame for a stamped quantity can be:Another stamped quantity,A "grounding" (a user chosen type).A user suppliedPhysicsinstance must be able to provide the worldPoseof a grounding.  The library definedMujocoPhysicsdoes this
formjcf.Elementinstances.None, in which case, world frame is assumed.Therefore in the above example, the first quantity might come from a mujoco
model (possibly synchronized with the real world), and the second quantity
might be known a priori or estimated by vision.gripper_in_world=PoseStamped(pose=None,frame=synced_gripper_mjcf_body)plug_in_gripper=Pose(...)# From vision pose model.plug_pose=PoseStamped(plug_in_gripper,frame=gripper_in_world)(A more realistic example would have the pose of the plug in thecameraframe
then either having the camera in the kinematic tree of the robot (attached to
the robot) or having it and the robot in world frame)Then the pose of theplugin theworldframe can be calculated as:plug_in_world:Pose=plug_pose.get_world_pose()ImmutabilityAll types ingeometry.pyare immutable. You can create modified copies of
existing values with thereplaceandwith_*methods.replaceis similar in
spirit tocollections.namedtuple._replace, these methods return new objects.PoseStampedThis is the stamped version of a Pose.Its frame hierarchy can be flattened withto_world, which returns aPoseStampedin world frame.ThePoserelative to another frame is returned fromget_relative_pose.ThePoserelative to the world frame is returned fromget_world_pose.So, in the case of a gripper in camera frame which is not attached to the robot,
we couldto_world()either the gripper or plugPoseStamped, giving a new
frame and then calculate thier relative pose (plug relative to robot) withget_relative_pose.HybridPoseStampedAPoseStampedwhere the position or orientation can be overriden. This is
useful to express the idea of (for example) the position of the gripper with
world orientation to allow for more intuitive operator control of the gripper.
Package: dm-robotics-manipulation
Objects for robotic manipulationThis folder provides various physical objects and software utilities used to
build simulated environments for robotic manipulation.Cell for robotic manipulationContains assets and code to create a robotic cell in simulated environments.Parametric objects documentationInfrastructure to design families of parametric objects.RGB-objects 🛑🟩🔷 documentationContains assets and supported code that allows using the RGB-objects in
simulated environments. The RGB-objects is a set of parametric objects crafted
forRGB-stackingmanipulation tasks.
Package: dm-robotics-panda
Model and Tools for the Panda Robot in dm_roboticsThis package includes a model of the Panda robot fordm_robotics, tools to build simulation environments suited for reinforcement learning, and allows you to run these simulations with real hardware in the loop.Run yourdm_roboticssimulation environment on the real hardware without modification.Haptic interaction mode allows you to physically interact with the simulation environment.To get started, checkout thetutorial.InstallThe recommended way of installing is using PyPI:pip install dm-robotics-pandaAlternatively, you can install this package from source by executingpip install .in the repository's root directory.RequirementsHardware-in-the-loop operation requirespanda-pyto control the robot. However, the version automatically installed from PyPI may not be compatible with your robot if you use an older firmware or use the new Franka Research 3 robot. In that case refer to the panda-pyinstructionson what version to install and where to find it.If you're having trouble running the included viewer or rendering scenes, please refer to the requirements ofdm_control.CitationIf you use dm_robotics_panda in published research, please consider citing theoriginal software paper.@article{elsner2023taming,
title = {Taming the Panda with Python: A powerful duo for seamless robotics programming and integration},
journal = {SoftwareX},
volume = {24},
pages = {101532},
year = {2023},
issn = {2352-7110},
doi = {https://doi.org/10.1016/j.softx.2023.101532},
url = {https://www.sciencedirect.com/science/article/pii/S2352711023002285},
author = {Jean Elsner}
}
Package: dm-robotics-transformations
DeepMind Robotics TransformationsTransformations is a pure python library for rigid-body transformations
including velocities and forces.The objectives for this library aresimplicityandcomprehensivenessacross all canonical representations (euler, axis-angle, quaternion,
homogeneous matrices).Supported conversions:Quaternion to Rotation matrix, Axis-angle and Euler-angleAxis-angle to Quaternion, Rotation matrix and Euler-angleRotation matrix to Quaternion, Axis-angle and Euler-angleEuler-angle to Quaternion, Rotation matrix and Axis-angleQuaternions:Quaternions are represented with the scalar part (w) first, e.g.identity_quaternion=np.asarray([1,0,0,0])# w, i, j, kSupported quaternion operations:DifferenceDistanceMultiplicationInverseConjugateLogarithm and ExponentSlerp (spherical linear interpolation)Rotation of a vector by a quaternion.Euler-anglesAll 24 from-euler orderings are supported.
7 of 24 to-euler orderings are supported.TransformsThis library supports force and velocity transforms.Usage Examplefromdm_robotics.transformationsimporttransformationsastr# Convert a pose, euler angle into a homogeneous matrix (a 4x4 matrix):hmat=tr.poseuler_to_hmat(np.array([x,y,z,rot_x,rot_y,rot_z]),'XYZ')# Convert the homogeneous matrix to a twist (a 6 vector):twist=tr.hmat_to_twist(hmat)
Package: dms
dmsDatabase Management Service dashboardFeaturesstandalone and independent as a serviceonly a simple json configuration for dashboardno database model definitions written in pythonvery generic from database perspectivelimited touuidandintegerfor primary keys valueslimited todatetimeordatefor auto created or updated field valuessupport for sqlite and postgresuse as a docker containerConfigurationDashboardFor an example dashboard configuration look atdocs/dms.json.ServiceService configuration can be done using environmental variables or by.envfile mounted into container.UsageSimple docker compose configurationservices:
  dms:
    image: ambrozic/dms:latest
    ports:
      - "8000:8000"
    volumes:
      - /path/to/your/dms.json:/srv/app/dms.json
    environment:
      - DMS_HOST=0.0.0.0
      - DMS_SECRET_KEY=<secret-key>
      - DMS_DATABASE=postgresql://postgres@db:5432/dband openhttp://0.0.0.0:8000Screenshotshere
Package: dm.sharedresource
A shared resource is some resource identified by an id
and used concurrently by several threads.
To make the concurrent use safe, calls to resource methods
are synchronized.A resource is obtained by a call toget_resource.
The required resource is identified by an id (an arbitrary
object adequate as a dictionary key).
If a resouce of this id already exists, it is returned.
Otherwise, one is created calling the creator and
the creator parameters provided toget_resource.
The returned value is a wrapper around the resource.
The wrapping ensures that calls to the resource’s methods
are synchronized.>>> from dm.sharedresource import get_resource
>>> r = get_resource(1, dict) # a new resource is created with the `dict` creator
>>> r is get_resource(1, dict)
TrueThe resource behaves quite like the created object. However,
calls to its methods are synchronized (i.e. thread safe).
However, special methods (those the names of which start and and in__) may not be found (Python 2.4 introduced that some methods
must be defined at class creation time and are not longer looked
up in the instance). As a special case,__getitem__,__setitem__,__delitem__,__len__,__nonzero__are explicitely delegated.>>> r[1] = 1
>>> r[1]
1Parameters and keyword parameters for the creator can be provided
as arguments toget_resource.>>> r = get_resource('with args', dict, {1:1}, a='a', b='b')
>>> sorted(r.items())
[(1, 1), ('a', 'a'), ('b', 'b')]Now look that normal classes work as creators, too.>>> class Resource:
...   def __init__(self, v): self.v = v
...   def f(self): return self.v
...
>>> r = get_resource('class', Resource, 1)
>>> r.f()
1
Package: dmsp
Digital Meridian SpectrometerFor Geophysical Institute's Poker Flat Digital Meridian Spectrometer, which uses NetCDFThis library is also usable from Matlab, as seen indmsp.m.Data sources2011-present:ftp://optics.gi.alaska.edu/PKR/DMSP/NCDF/1983-2010 (NetCDF 3 .PF files)other datesInstallpython-mpipinstall-e.MatlabMatlab users need:Matlab ≥ R2018bdmsppackage installed into thePython environment associated with MatlabUsageLoadMSPdata.pycreates many plots.Use as a Python module is like:importdmspdat=dmsp.load('~/data/myfile.PF')which returnsxarray.DatasetNotesYou can also graphically browse the files with thencviewprogram:aptinstallncviewError: libnetcdf.so.7if you getImportError: libnetcdf.so.7: cannot open shared object file: No such file or directorytry:aptinstalllibnetcdf-dev
python-mpipinstallnetcdf4orcondainstallnetcdf4
Package: dms-struct
Visualize deep mutational scanning on protein structure.dms_structis a Python package written bythe Bloom lab.dms_structis essentially a collection of code that simplifies the use ofnglviewto visualize selection on protein structures in aJupyter notebook.The source code ison GitHub.See thedms_struct documentationfor details on how to install and usedms_struct.To contribute to this package, read the instructions inCONTRIBUTING.rst.
Package: dms-to-decimal
dms-to-decimal
A Python library for converting degrees, minutes, and seconds to decimalInstallationpip install dms-to-decimalExampleimport dms_to_decimal as dmsdegree = 46
minutes = 59
seconds = 5
direction = ‘N’converDms2Decimal = dms.DMS2Decimal(degree, minutes, seconds, direction)print(converDms2Decimal); # Output: 46.984722222222224
Package: dms_tools
dms_toolsis aPythonpackage that provides tools for analyzing and visualizingdeepmutationalscanning data.See thedms_tools documentationfor information on how to install and usedms_tools.dms_toolssource code is on GitHubunder an open-sourceGPLv3license.Pleasecite dms_tools appropriatelyif you use it.dms_toolsis written by theBloom Lab(seehttps://github.com/jbloom/dms_tools/graphs/contributorsfor a full list of contributors).
Package: dmsuite
A collection of spectral collocation differentiation matricesThis collection is based on their original matlab/octave version developed by
Weidemann and Reddy and available fromDMSUITE. The theory and examples are
explained in their paper: J. A. C. Weidemann and S. C. Reddy, A MATLAB
Differentiation Matrix Suite, ACM Transactions on Mathematical Software, 26,
(2000): 465-519.The port to python was initiated as part of a larger project by
ronojoy ashttps://github.com/ronojoy/pyddx.gitIt isavailable on PyPI. You can install
and update dmsuite with the following command:python3 -m pip install --user -U dmsuite
Package: dmsuploader
DMS Uploader!This python package contains required methods to download files from a direct link and upload them in to DMS (Document Management System) or any WebDav server with authentication:Required InformationWell, first you need few configurations before start:Required ParametersUsername of the DMSPassword of the DMSWebDav URL (SLT or DMS) (EX:https://dms.***.**/remote.php/dav/files/bf4f27ce-7d83-11ee-b962-0242ac120002/)Optional Parameterszip - Wether you want to zip the file or notpath - Download pathlogLevel - Log level you want (default: logging.DEBUG)filename - Custom file name to download the file (default: Actual File Name)Options Dict is as followsoptions={"username":None,"password":None,"mode":"slt","webdavurl":"","chunkSize":400,# 400MB"zip":True,"path":None,"logLevel":logging.DEBUG,"filename":None}How to use DMS UploaderFirst install the dmsdownloader using pip.pipinstalldmsuploaderThen initialize dmsuploader as belowfromdmsuploaderimportDMSUploadoptions={"username":"testuser","password":"testpassword","webdavurl: "https://dms.***.**/remote.php/dav/files/bf4f27ce-7d83-11ee-b962-0242ac120002/",.......}uploader=DMSUpload(options)download_link="https://rs20.seedr.cc/ff_get/1657431157/************.mkv?st=s5UIkvBEH1T3WKaMTKpxRg&e=1699458900"uploader.upload(download_link)Available Methods in DMSDownloader classupload (url)download_file (url)zip_file (file_path, extension)upload_file(file_path)LicenseMIT LicenseCopyright (c) 2023 MTLMPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
Package: dmt
Domain Management ToolDMT (for short) is a collection of tools to manage yourRASA domainslike if they were packages not unlike pip with python but with YAML for RASA.Installationpipinstalldmt# Or using#pip install git+https://gitlab.com/waser-technologies/technologies/dmt.gitUsageUse thedmtshortcut command.❯dmt--help
usage:dmt[-h][-v][-l][-c][-aADD][-s][-V][-T][-S]DomainManagementTool

optionalarguments:-h,--helpshowthishelpmessageandexit-v,--versionoutputversioninformationandexit-l,--listlistinstalleddomains-c,--createCreateanewdomainfromtemplate-aADD,--addADDgitrepositoryhostingadomaintoadd-s,--syncSynchronizeallinstalleddomains-V,--validateValidateallinstalleddomains-T,--trainTrainnewmodelfromallinstalleddomains-S,--serveServethelastestmodel-LLANG,--langLANGlanguagetoworkwith(defaultstoyoursystempreference:$LANG)Find a domain using the tag#NLP Domains.And add it.dmt--add$domain_git_urlNow validate the domain's data with the installed ones.dmt--validateThis will generate some warnings but that is ok most of the time. Unless you made the domain, in which case you should act upon them.As long as there is not any error you can train a new model using your data. This will take time and computing resourses.dmt--trainOr you could add, validate and train with a new domain in one line.dmt-V-T-a$domain_git_urlOnce trained, you should be able to serve the latest model using thedmt.dmt--serveOr by enabling its service.cp./dmt.service.example/usr/lib/systemd/user/dmt.service
systemctl--userenable--nowdmt.serviceYou can also import those tools frompython.#!/usr/bin/env python3fromdomain.managementimporttoolsasdmt# Where are your domains installed?INSTALL_PATH="/usr/share/assistant"# install a new domain from a local repopath_to_new_domain="smalltalk"# git clone https://gitlab.com/waser-technologies/data/nlu/en/smalltalk.git ./smalltalkdomains_path=f"{INSTALL_PATH}/domains/en"dmt.install_domain(tmp_domain,domains_path)# Get list of installed domainslist_installed_domains=dmt.get_list_installed_domains(domains_path)# Validate all domains combineddmt.validate_data(INSTALL_PATH,domains="domains/en",data="data/en",config="configs/en/config.yml")# Train new model on all domainsdmt.train_lm(INSTALL_PATH,domains="domains/en",data="data/en",config="configs/en/config.yml",models="models/en/NLU")# Serve the new modeldmt.models_as_service()Creating your own domainsDMT allows you to quickly start a new domain from a template.dmt--createOnce hosted, you can use the--addflag to install your domain.With python.fromdomain.managementimporttoolsasdmtdmt.bake_cookie_domain(recipe_url="https://gitlab.com/waser-technologies/cookiecutters/nlu-domain-template")
Package: dmtaclasses
DmtaClassespython's dataclasses module with some salt on it.Installationpython -m pip install dmtaclassesSetup:-Visit this Url for learning how to usedataclasses.Now replace import statement with the following:-fromdataclassesimport*# tofromdmtaclasses.dmtaclassesimport*andimportdataclasses# toimportdmtaclasses.dmtaclassesasdataclassesYou don't have to make any further changes to your codebase other than thisHow It works:-Let us assume this code:-@dataclass()classMyclass:x:inty:floatd:Literal["2022-01-01"]|datetempd:Literal["6"]|Nonewhat happnesHere this codes acts same as any-other dataclass object,with a additional
feature of6dayssleep when tried to run after the date2022-01-01.how?The dataclass decorator is hijacked do that,
when their is any variable name that hasdin it, this code will try
to find aLiteraltype annotation for it, and When it finds aLiteralannotation, it tries to parse date from it with these formats:-formats       || unhinged notes  
%Y{0}%m{0}%d  || {0} means any symbol that you wish
%d{0}%Y{0}%m  || and %Y means year like 1990,..,2021,2020....
%m{0}%d{0}%Y  || and %m means month like 01,02,03,...11,12 
%d            || and %d means day like 01,02,..12,..28.. 32 
%Y{0}%mif it can find a date in any of the above format ;
it will check for today date and the parsed date and if today's date is greater
then it will toggle a flagparsed_date=date_parse(foramts)ifparsed_date<today_date:toggle_the_flag()Now next variable is searched for ammount of sleep.
NOw thetintempdwill denote thetimeyou want to sleep
anddat theenddenotes ammount in seconds/days/minutes/hoursformat 
*t*d   || sleep for X days 
*t*h   || sleep for X hours 
*t*m   || sleep for X minutes
*t*s   || sleep for X secondsTheXammount is again parsed from theLiteralExamples1) Program that sleeps for 1 seconds@dataclass()classMyclass:variabl1:intvariabl2:intvariadl3:int|Literal["2023u01u03"]variabl4:floatvariabts:float|Literal["1"]# it ends with d2) Program that sleeps for 1 minutes@dataclass()classMyclass:variabl1:intvariabl2:intvariadl3:int|Literal["2023p01p03"]variabl4:floatvariabtm:float|Literal["1"]# it ends with d3) Program that sleeps for 1 day@dataclass()classMyclass:variabl1:intvariabl2:intvariadl3:int|Literal["2023L01L03"]variabl4:floatvariabtd:float|Literal["1"]# it ends with d4) Program that sleeps for 1 year@dataclass()classMyclass:variadl3:int|Literal["2023u01u03"]variabtd:float|Literal["365"]5) Program that sleeps for 0.1 seconds@dataclass()classMyclass:variabl1:intvariabl2:intvariadl3:int|Literal["2023u01u03"]variabl4:floatvariabts:float|Literal["0.1"]
Package: dmt-htwk
DMT-HTWKEine IPython-Erweiterung zur Verbindung mit dem E-Assessment-Tool DMT (Data Management Tester)Diese Erweiterung ermöglicht es Aufgaben aus dem E-Assessment-Tool DMT abzufragen und dynamisch im Notebook darzustellen.
Ebenso können die Eingaben und Lösungen an DMT gesendet werden, um ein automtatisches Feedback zu erhalten.%dmtConDieser Befehl ermöglicht es die URL von DMT zu hinterlegen (z.B.: "%dmtConhttp://localhost:8081")%dmtDieser Befehl fragt die Aufgaben-Attribute per REST-Request über eine gültige TaskID von DMT ab und erstellt abhängig vom TaskType ein dynamisches UI.
(z.B.: "%dmt modell:1")
Druch einen Klick auf den generierten Button "Abgabe Überprüfen", werden alle UI-Felder ausgelesen und als Antwort an DMT geschickt.
Das Feedback, ob die Lösung richtig oder flasch ist, sowie die erhaltenen Punkte werden unter dem Button angezeigt.NutzungNach der Installation sind folgende Schritte für die Nutzung nötig:%load_ext dmt_htwk%dmtCon + Basispfad der DMT-URLDa nun das Package geladen, sowie eine URL hinterlegt ist, können sie mit der Nutzung von DMT beginnen.
Dazu schreiben sie folgenden Befehl in eine neue Cell:%dmt + gewünschte TaskIDWenn alles geklappt hat, sollten sie nun die ensprechende Aufgabe aus DMT in ihrem Notebook bearbeiten können.
Package: dmt-magic
DMT-MagicDMT-Magic ist eine IPython-Erweiterung, die das Jupyter Magic Commanddmtzur Verfügung stellt, mit dem das E-Assessment-Tool DMT (Data Management Tester) an Notebooks angebunden werden kann.Initialisiserung im Jupyter Notebook%load_ext dmtzum Laden der Erweiterung%dmt url=<url>zur Angabe der URL, unter der die Instanz von DMT erreichbar istAufruf einer Aufgabe%dmt <taskid>zur Darstellung einer Aufgabe (referenziert über TaskId)
Package: dmtoolkit
dmtoolkit!!!!!!!!!!!!!!!!!!!! NOT YET STABLE !!!!!!!!!!!!!!!!!!!!!!!!pypigithubOverviewCompletely rewritten from the ground up as a TTRPG worldbuilding tool using AI to generate entire worlds.Much more to come...SetupAdd the following to your .env file:### DB ConfigREDIS_PORT=REDIS_HOST=RQ_DEFAULT_CONNECTION=REDIS_DB=REDIS_DECODE=REDIS_USERNAME=REDIS_PASSWORD=#### OpenAI ConfigOPENAI_KEY=### Cloudinary ConfigCLOUD_NAME=CLOUDINARY_KEY=CLOUDINARY_SECRET=### WikiJS ConfigWIKIJS_TOKEN=""WIKIJS_URL=""# DEV OPTIONSDEBUG=TrueTESTING=TrueLOG_LEVEL=INFOFeaturesTBDDeveloper NotesTODOA TODO listIssue TrackingNoneMake CommandsTestsmaketestspackageUpdate version in/src/dmtoolkit/__init__.pymakepackage
Package: dmtools
dmtools (Digital Media Tools) is a Python package providing low-level tools for
working with digital media programmatically. It supports the PNG andNetpbmimage file formats as well as the MPEG-4 andWAVvideo and audio file
formats respectively.Thetransformmodule provides image transformation tools such as rescale
(based on theImageMagickimplementation) and composite (based on theCairoimplementation). Theadjustmentsmodule provides a curves tool and
thecolorspacemodule provides colorspace conversion tools. Thearrangemodule provides image layout tools. Lastly, theanimationandsoundmodules
provide tools for working with video and sound respectively. For more details,
see theDocumentation.InstallationsThe quickest way to get started is with a pip install.pip install dmtoolsTheanimationmodule requiresffmpegwhich you can install with a package
manager likeHomebrew. Note that this may take some time to install.brew install ffmpegFor in-depth installation instructions seeInstallation.UsageThe usage example below illustrates how an image can be read, manipulated,
and exported using dmtools. It features a change of color space, inversion of
the red channel, and blur. For more usage examples, see theIntroduction to dmtoolsinTutorials. Both the input imagechecks_5.pngand output imageresult.pngcan be found in thedmtoolsGitHub repository.importdmtoolsfromdmtoolsimportcolorspace,transform,adjustments,arrangeimage=dmtools.read("checks_5.png")image=colorspace.gray_to_RGB(image)image=adjustments.apply_curve(image,lambdax:1-x,0)image=transform.blur(image,5)image=arrange.image_grid([image]*2,2,1,15,color=1)dmtools.write_png(image,"result.png")checks_5.pngresult.pngLicenseLicensed under theMIT License