Saravanan666/pypi-org huggingface dataset:
Package: toposis-bhanu-101803651
Source code for TOPSIS optimization algorithm in python.TOPSIS is an algorithm for the determination of the best choice out of many using Positive Ideal Solution and Negative Ideal
solution.For sample solutions visit:http://www.jiem.org/index.php/jiem/article/view/573/498WikiPedia:https://en.wikipedia.org/wiki/TOPSISTOPSIS is an acronym that stands for â€˜Technique of Order Preference Similarity to the Ideal Solutionâ€™ and is a pretty
straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solutionIn Command Prompttopsis data.csv "1,1,1,1" "+,+,-,+" final.csv
Sample dataset
The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.Output
Model   Score    Rank1  | 0.77221   |  2
2  |  0.225599 |   5
3  |  0.438897 |   4
4  |  0.523878 |   3
5  |  0.811389 |   1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best
decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: toposis-kushgupta-101803454
Source code for TOPSIS optimization algorithm in python.TOPSIS is an algorithm to determine the best choice out of many using Positive Ideal Solution and Negative Ideal
Solution.For sample solutions visit:http://www.jiem.org/index.php/jiem/article/view/573/498WikiPedia:https://en.wikipedia.org/wiki/TOPSISTOPSIS is an acronym that stands for â€˜Technique of Order Preference Similarity to the Ideal Solutionâ€™ and is a pretty
straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solutionIn Command Prompttopsis data.csv "1,1,1,1" "+,+,-,+" final.csv
Sample dataset
The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.Output
Model   Score    Rank1  | 0.77221   |  2
2  |  0.225599 |   5
3  |  0.438897 |   4
4  |  0.523878 |   3
5  |  0.811389 |   1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best
decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: toposis-parth-101853019
Source code for TOPSIS optimization algorithm in python.TOPSIS is an algorithm for the determination of the best choice out of many using Positive Ideal Solution and Negative Ideal
solution.For sample solutions visit:http://www.jiem.org/index.php/jiem/article/view/573/498WikiPedia:https://en.wikipedia.org/wiki/TOPSISTOPSIS is an acronym that stands for â€˜Technique of Order Preference Similarity to the Ideal Solutionâ€™ and is a pretty
straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solutionIn Command Prompttopsis data.csv "1,1,1,1" "+,+,-,+" final.csv
Sample dataset
The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.Output
Model   Score    Rank1  | 0.77221   |  2
2  |  0.225599 |   5
3  |  0.438897 |   4
4  |  0.523878 |   3
5  |  0.811389 |   1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best
decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: toposis-prakhar-101803365
Source code for TOPSIS optimization algorithm in python.TOPSIS is an algorithm for the determination of the best choice out of many using Positive Ideal Solution and Negative Ideal
solution.For sample solutions visit:http://www.jiem.org/index.php/jiem/article/view/573/498WikiPedia:https://en.wikipedia.org/wiki/TOPSISTOPSIS is an acronym that stands for â€˜Technique of Order Preference Similarity to the Ideal Solutionâ€™ and is a pretty
straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solutionIn Command Prompttopsis data.csv "1,1,1,1" "+,+,-,+" final.csv
Sample dataset
The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.Output
Model   Score    Rank1  | 0.77221   |  2
2  |  0.225599 |   5
3  |  0.438897 |   4
4  |  0.523878 |   3
5  |  0.811389 |   1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best
decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: toposis-vinay-101803473
Source code for TOPSIS optimization algorithm in python.TOPSIS is an algorithm to determine the best choice out of many using Positive Ideal Solution and Negative Ideal
Solution.For sample solutions visit:http://www.jiem.org/index.php/jiem/article/view/573/498WikiPedia:https://en.wikipedia.org/wiki/TOPSISTOPSIS is an acronym that stands for â€˜Technique of Order Preference Similarity to the Ideal Solutionâ€™ and is a pretty
straightforward MCDA method. As the name implies, the method is based on finding an ideal and an anti-ideal solutionIn Command Prompttopsis data.csv "1,1,1,1" "+,+,-,+" final.csv
Sample dataset
The decision matrix (a) should be constructed with each row representing a Model alternative, and each column representing a criterion like Accuracy, R2, Root Mean Squared Error, Correlation, and many more.ModelCorrelationR2RMSEAccuracyM10.790.621.2560.89M20.660.442.8963.07M30.560.311.5762.87M40.820.672.6870.19M50.750.561.380.39Weights (w) is not already normalised will be normalised later in the code.Information of benefit positive(+) or negative(-) impact criteria should be provided inI.Output
Model   Score    Rank1  | 0.77221   |  2
2  |  0.225599 |   5
3  |  0.438897 |   4
4  |  0.523878 |   3
5  |  0.811389 |   1The rankings are displayed in the form of a table using a package 'tabulate', with the 1st rank offering us the best
decision, and last rank offering the worst decision making, according to TOPSIS method.
Package: toposort
toposortOverviewImplements a topological sort algorithm.FromWikipedia <http://en.wikipedia.org/wiki/Topological_sorting>_:
In computer science, a topological sort (sometimes abbreviated topsort
or toposort) or topological ordering of a directed graph is a linear
ordering of its vertices such that for every directed edge uv from
vertex u to vertex v, u comes before v in the ordering.Input data descriptionThe input to the toposort function is a dict describing the
dependencies among the input nodes. Each key is a dependent node, the
corresponding value is a set containing the dependent nodes.Note that toposort does not care what the input node values mean: it
just compares them for equality. The examples here usually use
integers, but they could be any hashable type.Typical usageThe interpretation of the input data here is: If 2 depends on 11; 9
depends on 11, 8 and 10; 10 depends on 11 and 3 (and so on), then in what
order should we process the items such that all nodes are processed
before any of their dependencies?::>>> from toposort import toposort, toposort_flatten
>>> list(toposort({2: {11},
...                9: {11, 8, 10},
...                10: {11, 3},
...                11: {7, 5},
...                8: {7, 3},
...               }))
[{3, 5, 7}, {8, 11}, {2, 10}, {9}]And the answer is: process 3, 5, and 7 (in any order); then process 8
and 11; then process 2 and 10; then process 9. Note that 3, 5, and 7
are returned first because they do not depend on anything. They are
then removed from consideration, and then 8 and 11 don't depend on
anything remaining. This process continues until all nodes are
returned, or a circular dependency is detected.Circular dependenciesA circular dependency will raise a CyclicDependencyError, which is
derived from ValueError.  Here 1 depends on 2, and 2 depends on 1::>>> list(toposort({1: {2},
...                2: {1},
...               }))
Traceback (most recent call last):
    ...
toposort.CircularDependencyError: Circular dependencies exist among these items: {1:{2}, 2:{1}}In addition, the 'data' attribute of the raised CyclicDependencyError
will contain a dict containing the subset of the input data involved
in the circular dependency.Module contentstoposort(data)Returns an iterator describing the dependencies among nodes in the
input data. Each returned item will be a set. Each member of this set
has no dependencies in this set, or in any set previously returned.toposort_flatten(data, sort=True)Like toposort(data), except that it returns a list of all of the
depend values, in order. If sort is true, the returned nodes are sorted within
each group before they are appended to the result::>>> toposort_flatten({2: {11},
...                   9: {11, 8, 10},
...                   10: {11, 3},
...                   11: {7, 5},
...                   8: {7, 3},
...                  })
[3, 5, 7, 8, 11, 2, 10, 9]Note that this result is the same as the first example:[{3, 5, 7}, {8, 11}, {2, 10}, {9}],
except that the result is flattened, and within each set the nodes
are sorted.TestingTo test, run 'python setup.py test'. On python >= 3.0, this also runs the doctests.
Package: topostats
TopoStats)|Installation|Tutorials and Examples|Contributing|Licence|Citation|An AFM image analysis program to batch process data and obtain statistics from images.There is more complete documentation on the projectsdocumentation website.InstallationTopoStats is available via PyPI and can be installed in your Virtual Environment with...pipinstalltopostatsFor more on installation and how to upgrade please see theinstallation
instructions.How to UseTutorials and ExamplesFor a full description of usage please refer to theusagedocumentation.A default configuration is loaded automatically and so the simplest method of processing images is to runtopostats processin the same directory as your scansafterhaving activated the virtual environment in which you have
installed TopoStatstopostatsprocessIf you have your own YAML configuration file (seeUsage : Configuring
TopoStats) then invoketopostats processand use the argument for--config <config_file>.yamlthat points to your file.# Edit and save my_config.yaml then run TopoStats with this configuration filetopostatsprocess--configmy_config.yamlThe configuration file is validated before analysis begins and if there are problems you will see errors messages that
are hopefully useful in resolving the error(s) in your modified configuration.You can generate a sample configuration file using thetopostats create-configargument which writes the default
configuration to the file./config.yaml(i.e. in the current directory). This willnotrun any analyses.NB- This feature is only available in versions > v2.0.0 as it was introduced after v2.0.0 was released. In older
version > 2.0.0 and <= 2.1.2 you can use the olderrun_topostats --create-configoption.run_topostats--create-config-fileconfig.yamlNotebooksExample Jupyter Notebooks have been developed that show how to use TopoStats package interactively which is useful when
you are unsure of what parameters are most suited to your scans. Other notebooks exist which show how to produce plots
of the summary grain and tracing statistics or how to generate plots of scans from processed images which saves having
to run the processing again. See the documentation onNotebooksfor further details.ContributingSeecontributing guidelines.LicenceThis software is licensed as specified by theGPL LicenseandLGPL License.CitationPlease use theCitation File Formatwhich is available in this repository.PublicationsTopoStats – A program for automated tracing of biomolecules from AFM images
Package: topos-theme
Topos Theme===========.. list-table:::stub-columns: 1* - docs- |docs|* - pypi- |version| |supported-versions|.. |travis| image:: https://travis-ci.org/alcarney/topos.svg?branch=dev:target: https://travis-ci.org/alcarney/topos.. |coveralls| image:: https://coveralls.io/repos/github/alcarney/topos/badge.svg?branch=dev:target: https://coveralls.io/github/alcarney/topos?branch=dev.. |docs| image:: https://readthedocs.org/projects/topos-theme/badge/?version=latest:target: https://topos-theme.readthedocs.io/en/latest/:alt: Documentation Status.. |version| image:: https://img.shields.io/pypi/v/topos-theme.svg:alt: PyPI Package latest release:target: https://pypi.org/project/topos-theme.. |supported-versions| image:: https://img.shields.io/pypi/pyversions/topos-theme.svg:alt: Supported versions:target: https://pypi.org/project/topos-theme:code:`topos-theme` is a HTML theme for `sphinx`_ that was originally developedfor the `topos <topos-gh>`_ python package but it has now been extracted outinto its own independent project.Getting Started---------------To use this theme for your own sphinx sites first you need to install the:code:`topos-theme` package.. code-block:: sh$ pip install topos-themethen in your :code:`conf.py`.. code-block:: pythonextensions = [...,"topos_theme"]html_theme = "topos-theme"Finally rebuild your project and you should see that :code:`topos-theme` has takeneffect.Projects Using this Theme-------------------------Here are some projects that are using this theme.- `stylo`_- `topos <https://topos.readthedocs.io/en/latest/>`_- `topos-theme`_Do you have a project that is making use of this theme? You are more thanwelcome to open a pull request to add your project to this list... _sphinx: http://www.sphinx-doc.org/en/master.. _topos-gh: https://github.com/alcarney/topos.. _topos-theme: https://topos-theme.readthedocs.io/en/latest/.. _stylo: https://alcarney.github.io/stylo/
Package: topper
TopperTopper is a library made to parse and process log files of music
listening. The purpose of this application
is to get the top 50 songs the most listened on the
last 7 days grouped by country or user id.You must provide:landing_folder: where daily files are sentcheckpoint_directory: used by the application to process, archive and
persist data across daysoutput_directory: where result files are written everydaymode (optional):country(default) oruseris the aggregation modeInput filesEach log file must match the pattern
listen-YYYYMMDD.log.
The file must contains data structured with:One row per stream (1 listening).Each row is in the following format:song_id|user_id|countryFile managementInput files will be moved to the directorycheckpoint/current/Invalid files will be moved to the directorycheckpoint/errors/Data files older than 7 days will be moved to the directorycheckpoint/archive/Output filesMode 'country'Produced files have the following format:country1|sng_id1:n1,sng_id2:n2,sng_id3:n3,...,sng_id50:n50
country2|sng_id1:n1,sng_id2:n2,sng_id3:n3,...,sng_id50:n50Where country is the country ISO2 code, sng_id1:n1 the identifier of the song the most
listened with the related number of streams, sng_id2:n2 the identifier of the 2nd song
the most listened with the related number of streams and so on..Mode 'user'Produced files have the following format:user_id1|sng_id1:n1,sng_id2:n2,sng_id3:n3,...,sng_id50:n50
user_id2|sng_id1:n1,sng_id2:n2,sng_id3:n3,...,sng_id50:n50Where user_id is a user, sng_id1:n1 the identifier of the song the most
listened with the related number of streams, sng_id2:n2 the identifier of the 2nd song
the most listened with the related number of streams and so on..UsageSupported Python VersionsPython >= 3.6Installationvirtualenv -p python3 venv
source venv/bin/activate
make installDisplay usagetopper -hExampletopper --landing_folder sample/ --checkpoint_directory checkpoint --output_directory output --mode countryDevelopmentmake test # coverage tests
make linter # runs pylint
make build
Package: topp.featurelets
topp.featurelets provides an infrastructure for “featurelets”.
Featurelets are feature plug-ins, little bundles of functionality that
can be installed into a particular location within a Plone or CMF
site.  It’s a very simple concept, but is a bit hard to explain in the
abstract, so a concrete example would probably be helpful.In an OpenCore site, eg.http://www.coactivate.org, anyone can create a
project.  In these projects, we offer feature modules that can be
turned on and off.  The optional features that someone might want to
add to her project include, for instance, blogging capabilities, or
mailing lists.  Each of these is a featurelet.  The project, into
which the featurelets are installed, is a “featurelet supporter”.Featurelets are deliberately vague so that they can be flexible.  Each
featurelet contains a “package”, and when a featurelet is installed
into a featurelet supporter this package is delivered to the
supporter.  Common operations associated w/ the delivery of a package
include the creation of content objects and the registration of menu
items; support for both of these operations are built into the
featurelets core.  It’s possible to make a featurelet do anything,
however, provided the featurelet supporter can support the operations.
To ensure this, featurelets support the idea of required interfaces;
if a featurelet is installed into a supporter that does not implement
or adapt to all of the featurelet’s required interfaces, an adaptation
exception will be raised.Requires Zope 2, version 2.10 or later, and CMF.
Package: toppics
toppicsA Python CLI for adding pre-defined topics to a GitHub repository.Developmentpoetry installpoetry shellTech StackClick(for the interface)Packaging and DevelopmentPoetryMypyisortBlackFlake8flake8-bugbearflake8-comprehensionspep8-namingflake8-builtinsBanditThis CLI was created withCookiecutterand thejoaopalmeiro/cookiecutter-templates/python-cliproject template.NotesReplace all repository topics.ghapidocumentation:repos.replace_all_topics(owner, repo, names).regex101website.Click 7documentation:Utils.Click 8documentation.toppics https://github.com/joaopalmeiro/toppics "Python CLI".
Package: toppra
toppra: Time-Optimal Path ParameterizationOverviewSupportsCitingtoppraOverviewtopprais a library for computing the time-optimal path
parametrization for robots subject to kinematic and dynamic
constraints.  In general, given the inputs:a geometric pathp(s),sin[0, s_end];a list of constraints on joint velocity, joint accelerations, tool
Cartesian velocity, et cetera.topprareturns the time-optimal path parameterization:s_dot (s), from which the fastest trajectoryq(t)that satisfies the
given constraints can be found.Documentation and tutorialsare availablehere.You can install the package with pip:pipinstalltoppraTo install from source for development:pipinstall-rrequirement3.txt
pipinstall-e.SupportBug trackingPlease report any issues, questions or feature request viaGithub issues tracker.Have a quick question? Try asking in our slack channel.ContributionsPull Requests are welcome! Create a Pull Request and we will review
your proposal!Creditstopprawas originally developed byHung
Pham(Eureka Robotics, former CRI
Group) andPhạm Quang Cưong(Eureka Robotics, CRI Group) with major contributions from talented
contributors:Joseph Mirabel(C++ API)EdsterG (Python3 support).If you have taken part in developing and supporting the library, feel
free to add your name to the list.The development is also generously supported byEureka Robotics.Citing toppraIf you use this library for your research, we encourage you toreference the accompanying paperA new approach to Time-Optimal Path Parameterization based on Reachability Analysis,IEEE Transactions on Robotics, vol. 34(3), pp. 645-659, 2018.put a star on this repository.
Package: topp.recipes.cfgtemplate
========================topp.recipes.cfgtemplate========================This is a zc.buildout recipe that provides support for templatesubstitution within the buildout.cfg file.  When this recipe is loadedin a buildout.cfg file, it will search the buildout configuration forany instances of the the template syntax, i.e. any text enclosed by{{double-curly-braces}}.  If substitutions are found, theconfiguration will be altered directly in memory, and any subsequentrecipes will be run with the substituted values.The template substitution values come from a separate config file,specified in the topp.recipes.cfgtemplate configuration, defaulting to"cfgsubs.cfg".  If the substitution file does not exist, or if it ismissing any values required by the buildout.cfg file, then the userwill be interactively prompted to enter the requested information, andthe substitution file will be created or amended with the providedvalues.The idea is that you'll create a templatized buildout.cfg file andstore it in a revision control system (RCS).  The templatized valueswould represent information that is not suitable for storage in theRCS, such as port numbers, passwords, database connection strings, oranything else that is either sensitive or likely to vary fromdeployment to deployment.  The first time this buildout.cfg file isused in a new location, the user will interactively provide thesevalues, which would then be stored in the substitution file, which isleft out of the RCS, or (if desired) is stored in a more securerepository elsewhere.Change history**************${0.1.0 or "0.0.0"} (xxxx-xx-xx)==================- Created recipe with ZopeSkel [${Rob Miller or ""}].Detailed Documentation**********************Supported options=================The recipe supports the following options:.. Note to recipe author!----------------------For each option the recipe uses you shoud include a descriptionabout the purpose of the option, the format and semantics of thevalues it accepts, whether it is mandatory or optional and what thedefault value is if it is omitted.option1Description for ``option1``...option2Description for ``option2``...Example usage=============.. Note to recipe author!----------------------zc.buildout provides a nice testing environment which makes itrelatively easy to write doctests that both demonstrate the use ofthe recipe and test it.You can find examples of recipe doctests from the PyPI, e.g.http://pypi.python.org/pypi/zc.recipe.eggThe PyPI page for zc.buildout contains documentation about the testenvironment.http://pypi.python.org/pypi/zc.buildout#testing-supportBelow is a skeleton doctest that you can start with when buildingyour own tests.We'll start by creating a buildout that uses the recipe::>>> write('buildout.cfg',... """... [buildout]... parts = test1...... [test1]... recipe = topp.recipes.cfgtemplate... option1 = %(foo)s... option2 = %(bar)s... """ % { 'foo' : 'value1', 'bar' : 'value2'})Running the buildout gives us::>>> print system(buildout)Upgraded:...Installing test1.Unused options for test1: 'option2' 'option1'.Contributors************${Rob Miller or ""}, AuthorDownload********