Saravanan666/pypi-org huggingface dataset:
Package: vpselector
vpselectorThe Visual Pandas Selector is a tool to visually select portions of numeric time-series data from a pandas dataframe. The tool is intended to provide an fast interactive way for manual data selection, as can be very useful in for example machine learning, regression or system identification.Easily configure the tool to plot dataframe columns in vertically stacked subplots and view data distributions with the included histogram feature. With a simple click and drag, you can then select horizontal data windows, and let the tool automatically combine them into a new dataframe.The user can subsequentially select different horizontal data windows via click and drag and he tool then automatically combines the visually selected sections into a new dataframe.InstallInstall the package using:pipinstallvpselectorUse in your projectThen simply import it usingimport vpselector. Then simply use:If your project does not contain a pyqt application:vpselector.select_visual_data(data : pd.DataFrame, plot_config : dict)To add the vpselector to an existing pyqt application:vpselector.select_visual_data_in_pyqt_app(data : pd.DataFrame, plot_config : dict, pyqt_app)Run the Examplepython3vpselector_example.pyUse the ToolLeft click with your mouse and drag to define the desired horizontal window of the data to be selected.The current selection distribution is now visualized in the histogram plot on the right.Confirm or cancel data selection.The already selected data is now marked by a grey span in the plot on the left.The plot on the right contains now the histogram of all selected data.repeat as many times as needed.Once you could select all desired horizontal data windows click "Done selecting"
Package: vpso
Vectorized Particle Swarm Optimizationvpsois a Python package for adaptive Particle Swarm Optimization (PSO)[1]that allows to run multiple similar optimization problems in a vectorized fashion.InstallationTo install the package, runpipinstallvpsovpsohas the following dependenciesNumbaSciPytyping_extensions.For playing around with the source code instead, rungitclonehttps://github.com/FilippoAiraldi/vectorized-particle-swarm.gitUsageExamplesOurexamplessubdirectory contains a simple use-case to get started with.LicenseThe repository is provided under the MIT License. See the LICENSE file included with this repository.AuthorFilippo Airaldi, PhD Candidate [f.airaldi@tudelft.nl|filippoairaldi@gmail.com]Delft Center for Systems and ControlinDelft University of TechnologyCopyright (c) 2023 Filippo Airaldi.Copyright notice: Technische Universiteit Delft hereby disclaims all copyright interest in the program “csnn” (Nueral Networks with CasADi) written by the Author(s). Prof. Dr. Ir. Fred van Keulen, Dean of 3mE.References[1]Z. H. Zhan, J. Zhang, Y. Li and H. S. H. Chung, "Adaptive Particle Swarm Optimization," in IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 39, no. 6, pp. 1362-1381, Dec. 2009, doi: 10.1109/TSMCB.2009.2015956.
Package: vpss
Video Patch Similarity Search (VPSS)A Python Implementation for a GPU accelerated implementation of Video Patch Similarity Searching.InstallThe package is available through Python pip,$ python -m pip install vpss --userOr the package can be downloaded through github,$ git clone https://github.com/gauenk/vpss/
$ cd vpss
$ python -m pip install -r requirements.txt --user
$ python -m pip install -e ./lib --userLICENSELicensed under the GNU Affero General Public License v3.0, seeLICENSE.
Package: vpt-core
Vizgen Post-processing Tool CoreThe Vizgen Post-processing Tool (VPT) enables users to reprocess and refine the single-cell results of MERSCOPE experiments.
VPT is a command line tool that emphasizes scalable, reproducible analysis, and can be run on a workstation, a cluster, or
be deployed in a cloud computing environment.VPT has a plugin architecture that allows users to install segmentation implementations a la carte. The vpt_core package implements the core classes and methods needed to build a VPT plugin.DocumentationUser GuideFeedbackIf you encounter issues or bugs, let us know bysubmitting an issue!Please include:A quick issue summarySteps that caused it to occurThe exception generated by the code, if applicableSpecific lines of code, if indicated in the error messageIf you have any other feedback or issues, please reach out to your regional Vizgen field application scientist and CC: Vizgen
Tech Support attechsupport@vizgen.com.Please include VPT in your subject line along with the above information in the body.Contributing & Code of ConductWe welcome code contributions! Please refer to thecontribution guidebefore getting started.AuthorsVizgenLicenseCopyright 2022 Vizgen, Inc. All Rights ReservedLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: vpt-plugin-cellpose
Vizgen Post-processing Tool Cellpose PluginThe Vizgen Post-processing Tool (VPT) enables users to reprocess and refine the single-cell results of MERSCOPE experiments.
VPT is a command line tool that emphasizes scalable, reproducible analysis, and can be run on a workstation, a cluster, or
be deployed in a cloud computing environment.CellposeThe Cellpose plugin for VPT is an interface to Cellpose 1.0.2:Stringer, C., Wang, T., Michaelos, M., & Pachitariu, M. (2021). Cellpose: a generalist algorithm for cellular segmentation.Nature methods, 18(1), 100-106.Addtional information about Cellpose can be found athttps://www.cellpose.org/DocumentationUser GuideFeedbackIf you encounter issues or bugs, let us know bysubmitting an issue!Please include:A quick issue summarySteps that caused it to occurThe exception generated by the code, if applicableSpecific lines of code, if indicated in the error messageIf you have any other feedback or issues, please reach out to your regional Vizgen field application scientist and CC: Vizgen
Tech Support attechsupport@vizgen.com.Please include VPT in your subject line along with the above information in the body.Contributing & Code of ConductWe welcome code contributions! Please refer to thecontribution guidebefore getting started.AuthorsVizgenLicenseCopyright 2022 Vizgen, Inc. All Rights ReservedLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: vpt-plugin-cellpose2
Cellpose 2.0 PluginThis Vizgen Post-processing Tool (VPT) Cellpose plugin enables users to useCellposeto segment MERSCOPE experiments.
VPT is a command line tool that emphasizes scalable, reproducible analysis, and can be run on a workstation, a cluster, or
be deployed in a cloud computing environment.FeaturesPerform cell segmentation, reproduce standard Vizgen segmentation options, & perform reproducible custom segmentationRun cellpose using models from the model zoo or custom modelsFull customization of model parametersInstallationInstall the tool through your choice ofpippoetryUsageVPT accepts two types of inputs to specify how to run segmentation:Command line parametersrelate to where to find the input data and are expected to vary with each experimentSegmentation algorithm .json file parametersdescribes a series of steps to perform on the input dataUsing the same segmentation algorithm on a series of experiments ensures that they are processed identically and reproducibly.In addition to the user guide, several working segmentation algorithm .json files are provided that can serve either as a
robust segmentation definition or as a template for a custom workflow.DocumentationUser GuideFeedbackIf you encounter issues or bugs, let us know by submitting an issue!
Please include:A quick issue summarySteps that caused it to occurThe exception generated by the code, if applicableSpecific lines of code, if indicated in the error messageIf you have any other feedback or issues, please reach out to your regional Vizgen field application scientist and CC: Vizgen
Tech Support attechsupport@vizgen.com.Please include VPT in your subject line along with the above information in the body.Contributing & Code of ConductWe welcome code contributions! Please refer to thecontribution guidebefore getting started.AuthorsVizgenLicenseCopyright 2022 Vizgen, Inc. All Rights ReservedLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: vpt-plugin-watershed
Vizgen Post-processing Tool Watershed PluginThe Vizgen Post-processing Tool (VPT) enables users to reprocess and refine the single-cell results of MERSCOPE experiments.
VPT is a command line tool that emphasizes scalable, reproducible analysis, and can be run on a workstation, a cluster, or
be deployed in a cloud computing environment.DocumentationUser GuideFeedbackIf you encounter issues or bugs, let us know bysubmitting an issue!Please include:A quick issue summarySteps that caused it to occurThe exception generated by the code, if applicableSpecific lines of code, if indicated in the error messageIf you have any other feedback or issues, please reach out to your regional Vizgen field application scientist and CC: Vizgen
Tech Support attechsupport@vizgen.com.Please include VPT in your subject line along with the above information in the body.Contributing & Code of ConductWe welcome code contributions! Please refer to thecontribution guidebefore getting started.AuthorsVizgenLicenseCopyright 2022 Vizgen, Inc. All Rights ReservedLicensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: vptrade
vptradevptrade is a technical indicators trading tools can be used to all instruments.RequirementsPython 3.9 or higherFeaturesTrends IndicatorOscillators IndicatorInstallationInstal this package with pippipinstallvptradeUsage/ExamplesMoving Averagefromvptrade.indicators.trendsimportTrendimportpandasaspddata=pd.read_csv(r'YOUR PATH\TSLA.csv',index_col='Date',parse_dates=True)trend=Trend(data)#simple moving averagesma=trend.sma(period=30,volume="Close",show=True,save="sma_img.png")#exponential moving averageema=trend.ema(period=30,volume="Close",show=True,save="ema_img.png")#cummulative moving average show only without savecma=trend.cma(period=30,volume="Close",show=True)#smoothed moving average without save and showsmma=trend.smma(period=30,volume="Close",show=False)#lienar-weighted moving average without show and savelwma=trend.lwma(period=30,volume="Close")Bollinger bandfromvptrade.indicators.trendsimportTrendimportpandasaspddata=pd.read_csv(r'YOUR PATH\TSLA.csv',index_col='Date',parse_dates=True)trend=Trend(data)bollinger=trend.bollinger_bands(period=30,volume="Close",show=True,save="bolinger_band.png")SupportFor support, Join my discordhttps://discord.gg/HZJZAVAZdrContributingContributions are always welcome!Seecontributing.mdfor ways to get started.Please adhere to this project'scode of conduct.
Package: vptree
This package contains an implementation of avantage-point treedata structure.InstallationSimply install through pip:pip install vptreeExampleExample usage:importnumpyasnpimportvptree# Define distance function.defeuclidean(p1,p2):returnnp.sqrt(np.sum(np.power(p2-p1,2)))# Generate some random points.points=np.random.randn(20000,10)query=[.5]*10# Build tree in O(n log n) time complexity.tree=vptree.VPTree(points,euclidean)# Query single point.tree.get_nearest_neighbor(query)# Query n-points.tree.get_n_nearest_neighbors(query,10)# Get all points within certain distance.tree.get_all_in_range(query,3.14)
Package: vpype-dxf
vpype-dxfvpype dxf loading pluginAdds command dread (dxf-read) that reads dxf files and into the vpype pipeline.ezdxfEzdxf is used as the backend of this project. The-Q/--queryfeed directly into thequery fieldof the ezdxf query(), and the-g/--groupbyoption is directly in the groupby value. This will allow you to useanyvalid ezdxf properties togroupby. The defaults are*for query andcolorfor groupby.Examplesvpype <file> dread --groupby lineweight write lines.svg-- This would load the file and group the layers such that each lineweight in the dxf document is a different grouped according to their lineweight.vpype dread -Q 'LINE CIRCLE[color==1]' 3colors.dxf write lines-circ.svg-- This finds and processes only theLINEandCIRCLEobjects wherecolor==1and writes those to the given file.vpype dread -g lineweight file.dxf show --colorful-- Will group by the lineweight and show colorful layer groupings of those groups. This can work wonders for visualizing a messy file.vpype dread --groupby center circles.dxf stat-- Will group objects by the center of their circles.See the ezdxf documentation on query for advanced help.https://ezdxf.readthedocs.io/en/stable/query.htmlAcknowledgementezdxf author mozman did all the heavy lifting of parsing the dxf files.abruto's research and suggestions in issue#5lead to rather large increase in functionality.
Package: vpype-embroidery
vpype-embroideryVpype plugin for embroidery
See:https://github.com/abey79/vpypeEmbroidery vpype plugin. Reads and Writes embroidery files for the vpype pipeline.ereadload an embroidery into the pipelineewritewrite embroidery geometries to diskefillfill closed shapes in the document with a Eulerian fill.Installingpipx-basedvpypeinstall:$ pipx inject vpype vpype-embroideryGlobal or venv-basedvpypeinstall:$ pip install vpype-embroideryExamplesComplex fillsvpype begin grid -o 25 25 10 10 circle 0 0 100 end efill showZoomedConvert SVG -> DSTvpype read butterfly.svg ewrite butterfly.dstConvert PES -> SVGvpype eread duck.pes write duck.svgSupported Formats.This usespyembroideryfor the backend so the formats supported are as follows:https://github.com/EmbroidePy/pyembroideryEmbroidery FormatsWrite.pes.dst.exp.jef.vp3.u01.pec.xxx.tbf.gcodeRead.pes.dst.exp.jef.vp3.10o.100.bro.dat (barudan & sunstar).dsb.dsz.emd.exy.fxy.gt.hus.inb.jpx.ksm.max.mit.new.pcd.pcm.pcq.pcs.pec.phb.phc.sew.shv.stc.stx.tap.tbf.u01.xxx.zxy.gcodeRelated FormatsWe also write some miscellaneous formatsWrite.col : Color format..edr : Color format..inf : Color format..pmv : Brother Stitch Format.Read.col : Color format..edr : Color format..inf : Color format..pmv : Brother Stitch Format.Utility Formats:Write.csv : comma-separated values.json : JavaScript Object Notation.png : Portable Network Graphic.txt : text file..svg : Scalable Vector GraphicsRead.csv : comma-separated values.json : JavaScript Object Notation
Package: vpype-pixelart
vpype-pixelartvpypeplug-in to plot pixel art.UsageConvert pixelart image to vectorsThepixelartcommand takes an image file as input and converts it to lines according to one of three modes (big,line, andsmall– see examples below). Each unique color in the the input file results in a new layer created. Pixels which are 100% transparent (alpha = 0) yield no output.Example invocation:$vpypepixelart--modesnake--pen-width.35mminput.pnglinesortwriteoutput.svgInline help:$vpypepixelart--helpConvert geometries to bitmaps and back to vectorThepixelizecommand rasterizes the current geometries into a bitmap, and converts them back to vectors similarly to thepixelartcommand.Example invocation:$vpypereadinput.svgpixelize--modesnake--pen-width.35mmlinesortwriteoutput.svgInline help:$vpypepixelize--helpExamplesModebigIn this mode, each pixel is drawn using a 5x5 square spiral. The pixel pitch is thus five times the specified pen width.Cactus sprites fromSuper Mario World:Result plotted with Pentel Sign Pen (using--pen-width 0.6mm):ModelineIn this mode, horizontal lines are generated for horizontal sequences of same-color pixels. The pixel pitch is equal to the specified pen width.Original art byReddituseru/_NoMansDream:Result plotted with Pentel Sign Pen (using--pen-width 0.6mm):ModesnakeIn this mode, [snake](https://en.wikipedia.org/wiki/Snake_(video_game_genre)-likelines attempt to traverse zones of contiguous, same-color pixels. Again, the pixel pitch is equal to the specified pen width.Detail of the snake algoritm:Result plotted with Pentel Sign Pen (using--pen-width 0.5mm):pixelizecommandSeries of cubes created withvpype-perspectiveand pixelated usingpixelize:InstallationSeevpype'sinstallation instructionsfor information on how to installvpype.ExistingvpypeinstallationIfvpypewas installed using pipx, use the following command:$pipxinjectvpypevpype-pixelartIfvpypewas installed using pip in a virtual environment, activate the virtual environment and use the following command:$pipinstallvpype-pixelartCheck that your install is successful:$ vpype --help
Usage: vpype [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...

Options:
  -v, --verbose
  -I, --include PATH  Load commands from a command file.
  --help              Show this message and exit.

Commands:
[...]
  Plugins:
    pixelart   Plot pixel art.
[...]Stand-alone installationUse this method if you need to edit this project. First, clone the project:$gitclonehttps://github.com/abey79/vpype-pixelart.git
$cdvpype-pixelartCreate a virtual environment:$python3-mvenvvenv
$sourcevenv/bin/activate
$pipinstall--upgradepipInstallvpype-pixelartand its dependencies (includingvpype):$pipinstall-e.Check that your install is successful:$ vpype --help
Usage: vpype [OPTIONS] COMMAND1 [ARGS]... [COMMAND2 [ARGS]...]...

Options:
  -v, --verbose
  -I, --include PATH  Load commands from a command file.
  --help              Show this message and exit.

Commands:
[...]
  Plugins:
    pixelart   Plot pixel art.
[...]LicenseSee theLICENSEfile for details.
Package: vpype-rerun
vpype-rerunThis plug-in integrates theRerun viewerinvpype.Examplevpype random -n 500 -a 20cm 20cm rerunWhy?This plug-in makes it easy to log large quantities of2D line stripsto the Rerun viewer, which is useful for stress-testing, etc.InstallationSee theinstallation instructionsfor information on how
to installvpype(TL;DR:pipx install "vpype[all]").Ifvpypewas installed using pipx, use the following command:$pipxinjectvpypevpype-rerunIfvpypewas installed using pip in a virtual environment, activate the virtual environment and use the following command:$pipinstallvpype-rerunDocumentationThe complete plug-in documentation is available directly in the CLI help:$vpypererun--helpLicenseSee theLICENSEfile for details.
Package: vpype-ttf
vpype-ttfVpype plugin for ttf
See:https://github.com/abey79/vpypeInstallationInstall repository:pip install vpype-ttfUsageHave font file specified, eg:vpype render ./Vera.ttf "Vpype!" write a.svgOptionsvpype-ttf currently supports font scaling with the -s or --size option.vpype render -s 10cm ./Vera.ttf "Vpype!" write a.svgContributingThanks toTatarizefor creating this plugin in the first place.
If you would like to contribute and expand vpype-ttf, bug reports, feature requests, and issues are welcome.
Package: vpype-vectrace
vpype-vectraceVpype plugin for vector tracing.
See:https://github.com/abey79/vpypevpype plugin. Reads image files and traces them for the vpype pipeline.ireadload an image for vector tracingVectracePronounced "Vect-Race", Vectrace is a Pure Python Polygon Production Program. Basically the hooks for polygon tracing programs in python are really kinda annoying. And I didn't want to port code that isn't licensed in a maximally useful way, so I wrote my own.This is especially useful because vpype does not need a bunch of preprocessing. The main goal of Vectrace is to create perfect vectors from images. The optimizations and modifications can be done elsewhere in the pipeline. Or not at all, I don't really mind/care.Installing$ pip install vpype-vectraceSupported Formats.Vectrace supports all image formats that are supported by Pillow.Examplevpype iread github.png write github.svgOriginal.Vector.Filled With Black.vpype iread github.png linemerge efill -d 0.3 ewrite github.pes(Using vpype-embroideryhttps://github.com/EmbroidePy/vpype-embroidery)
Package: vpypi
vpypivpypiis a CLI tool to verifyGPGsignature for Python packages onPyPI.Installationpython3-mpipinstall--uservpypiUsage$python3.9-mvpypiflask==1.1.1{"created":"2019-07-08","fingerprint":"AD253D8661D175D001F462D77A1C87E3F5BC42A8","key_id":"7A1C87E3F5BC42A8","name":"Flask-1.1.1-py2.py3-none-any.whl","status":"signature valid","username":"David Lord <davidism@gmail.com>"}{"created":"2019-07-08","fingerprint":"AD253D8661D175D001F462D77A1C87E3F5BC42A8","key_id":"7A1C87E3F5BC42A8","name":"Flask-1.1.1.tar.gz","status":"signature valid","username":"David Lord <davidism@gmail.com>"}
Package: vqapi
ViQi APILow level interface to ViQi servicesInstallpip install viqi-apiConfigurationFor command line tools create~/.config/viqi/profileswith the following[default]
host=https://science.viqiai.cloud
user=myuser
password=mysecret

[science-user2]
host=https://science.viqiai.cloud
user=myuser2
password=mysecret2UsageExample ipython session:ipython
from vqapi import bisque_session
session = bisque_session(args=["--profile=science-user2"])

meta = session.service("meta")
user = meta.fetch("user")
print(user)