Saravanan666/pypi-org huggingface dataset:
Package: ep-bandpass-filter-selector
ep-bandpass-filter-selectorThe EP Bandpass Filter Selector package cycles through various combinations of high- and low-pass cutoffs of the bandpass frequency filter within user-specified limits and selects the optimal filtering option. Optimization is carried out basing on the ratio of the EP interpeak amplitude to the EP curves variability coefficient.RequirementsPackage require python >= 3.8.
For development require python3-venv.
Tested on Ubuntu 20.04.InstallationFor usual using:$ pip install ep_bandpass_filter_selectorFor development:$ git clone https://github.com/yaricp/ep-bandpass-filter-selector.git
$ cd ep-bandpass-filter-selector/
$ cd scripts/
$ ./install.shinstall.shwill download and set up the necessary packages in the .venv folder.UsageThis package can be imported as a separated module:$ python3
>>> from eeg_filters.upload import prepare_data
>>> from ep_bandpass_filter_selector import PassbandSelector
>>> (
    sample_rate, list_times, list_ticks, list_out
) = prepare_data("file_data_path.dat")
>>> pbs = PassbandSelector(
    curves=list_out,
    tick_times=list_ticks,
    fsr=sample_rate,
    max_search_range: (0.016, 0.023),
    min_search_range: (0.022, 0.028)
)
>>> result = pbs.start()
>>> print(result[0])
20,200In this example, all curves from the file_data_path.dat were used for selecting the passband filter.
Also, additional parameters were used with the default values.
Their values are listed here:filter_low_limit_range = 1, 30
step_low_filter = 1
filter_high_limit_range = 100, 500
step_high_filter = 10You can declare them when creating an item of PassbandSelector.
For example:>>> pbs = PassbandSelector(
    curves=list_out,
    tick_times=list_ticks,
    fsr=sample_rate,
    max_search_range=(0.016, 0.023),
    min_search_range=(0.022, 0.028),
    filter_low_limit_range=[5, 20],
    step_low_filter=5,
    filter_high_limit_range=[100, 300],
    step_high_filter=50,
    type_mean="average",
    cheb_filter_order=3,
    cheb_ripple=3
)Another notation is also possible for declaring parameters.
For example:>>> pbs = PassbandSelector(
    curves=list_out,
    tick_times=list_ticks,
    fsr=sample_rate,
    max_search_range=(0.016, 0.023),
    min_search_range=(0.022, 0.028),
    fllr=[5, 20],
    slf=5,
    fhlr=[100, 300],
    shf=50,
    tm="average",
    chfo=3,
    chr=3
)Export dataOn this moment there is only export to CSV format.>>> from ep_bandpass_filter_selector import export_data
>>> export_data(
    "filepath_for_export.csv",
    list(result[0]),
    result[1]
)
Package: epc
Links:Documentation(at Read the Docs)Repository(at GitHub)Issue tracker(at GitHub)PyPITravis CIOther resources:kiwanami/emacs-epc(Client and server implementation in Emacs Lisp and Perl.)tkf/emacs-jedi(Python completion for Emacs using EPC server.)What is this?EPC is an RPC stack for Emacs Lisp and Python-EPC is its server side
and client side implementation in Python.  Using Python-EPC, you can
easily call Emacs Lisp functions from Python and Python functions from
Emacs.  For example, you can use Python GUI module to build widgets
for Emacs (seeexamples/gtk/server.pyfor example).Python-EPC is tested against Python 2.6, 2.7 and 3.2.InstallTo install Python-EPC and its dependencysexpdata, run the following
command.:pip install epcUsageSave the following code asmy-server.py.
(You can find functionally the same code inexamples/echo/server.py):from epc.server import EPCServer

server = EPCServer(('localhost', 0))

@server.register_function
def echo(*a):
    return a

server.print_port()
server.serve_forever()And then run the following code from Emacs.
This is a stripped version ofexamples/echo/client.elincluded in
Python-EPCrepository.:(require 'epc)

(defvar my-epc (epc:start-epc "python" '("my-server.py")))

(deferred:$
  (epc:call-deferred my-epc 'echo '(10))
  (deferred:nextc it
    (lambda (x) (message "Return : %S" x))))

(message "Return : %S" (epc:call-sync my-epc 'echo '(10 40)))If you havecartoninstalled, you can run the above sample by
simply typing the following commands:make elpa        # install EPC in a separated environment
make run-sample  # run examples/echo/client.elFor example of bidirectional communication and integration with GTK,
seeexamples/gtk/server.py.  You can run this example by:make elpa
make run-gtk-sample  # run examples/gtk/client.elLicensePython-EPC is licensed under GPL v3.
See COPYING for details.
Package: epc-api-python
epc-api-pythonSimple python client to interface with the EPC data API.API docs for the domestic api can be foundhereAPI docs for the non-domestic api can be foundhereYou need to sign up with the EPC api which will provide you with an api key. You need to use
the api key in conjunction with your sign up email address, or with the authorisation
token that you are provided with to access the apiInstallationThis package can be installed by runningpip install epc-api-pythonUsageSome usage examples can be found in the/examplesfolderTo set up the api import theEpcClientclass an initialise the client by tunningimport dotenv
from epc_api.client import EpcClient

your_email = "email you signed up with"
api_key = "api you were emailed after sign up"


# I have auth_token in my environment
client = EpcClient(
    user_email=your_email, api_key=your_email_key, version="v1"
)

client.domestic  # interfaces with the domestic url https://epc.opendatacommunities.org/api/<version>/domestic/
client.non_domestic  # interfaces with the non-domestic url https://epc.opendatacommunities.org/api/<version>/non-domestic/There are three main functions that you should use. They are used identically
for both the domestic and non-domestic urls. These aresearch,certificateandrecommendations, which
access the/search,/certificateand/recommendationsurls respectively. Detailed description of these urls
can be found in the api documentation however each of these functions can be used immediately,
for examplesearch_resp = client.domestic.search()
print(search_resp)

# Test the certificate endpoint
# Use the first lmk_key which is provided as a response from /search
lmk_key = search_resp["rows"][0]["lmk-key"]

certificate_resp = client.domestic.certificate(lmk_key=lmk_key)
print(certificate_resp)

# Test the recommendations endpoint with the same lmk_key
recommendation_resp = client.domestic.recommendations(lmk_key=lmk_key)
print(recommendation_resp)The client can be set up with multiple mime types, with the default value beingapplication/json. If this value is supplied, the json data is parsed and returned in a
list/dictionary format, however for other mime types, the user is presented the
content back and it's up to the user to parse the response in a suitable
fashion. Some examples of handling different mime types of have provided in/examples.
Package: epcdltranslator
GS1 EPC URI - Digital Link URI TranslatorTranslates EPC URIs and EPC Class URIs into their corresponding canonical GS1 Digital Link URI equivalents.IntroductionTheEPC Pure Identity URI(or simply EPC URI) is a universal identifier for any physical or digital object such as products, assets, logistics units, documents, or locations. It is the preferred way within information systems to denote arbitrary business objects. Applications based onEPCIS, GS1’s core standard for supply chain visibility, SHOULD use this syntax. It takes the form of a Uniform Resource Name (URN), which, taking the example of an SGTIN (= Serialised Global Trade Item Number) looks sth. like this:urn:epc:id:sgtin:4012345.011111.987.AGS1 Digital Link URIis another GS1 URI, introduced especially to enable web applications through embedding GS1 keys and descriptive attributes into a web-friendly syntax. It SHOULD NOT be used in EPCIS for the purpose of identifying objects or locations. It takes the form of a Web URI, which, taking the above example, looks like this:https://id.gs1.org/01/04012345111118/21/987orhttps://example.com/01/04012345111118/21/987?15=211231.In case organisation wish to combine the powerful features of both supply chain visibility and accessibility to object-related information in the web (e.g. product description page or patient information leaflet), they need to translate EPC URIs into GS1 Digital Link URIs. As GS1 Digital Link URIs can also be constructed with company-specific domain names, this script can easily be adapted to also support custom domain names (e.g "example.com").Supported EPC/EPC Class URIsSGTIN:  Serialised Global Trade Item NumberSSCC:   Serial Shipping Container CodeSGLN:   Global Location Number with or without extensionGRAI:   Global Returnable Asset IdentifierGIAI:   Global Individual Asset IdentifierGSRN:   Global Service Relation Number - RecipientGSRNP:  Global Service Relation Number – ProviderGDTI:   Global Document Type IdentifierCPI:    Component / Part IdentifierSGCN:   Serialised Global Coupon NumberGINC:   Global Identification Number for ConsignmentGSIN:   Global Shipment Identification NumberITIP:   Individual Trade Item PieceUPUI:   Unit Pack IdentifierPGLN:   Global Location Number of PartyLGTIN:  GTIN + Batch/LotNote that the remaining EPC schemes as defined in the EPC Tag Data Standard, namely GID, USDOD, ADI, and BIC, are not supported as they lack a GS1 Company Prefix, thus cannot be translated into GS1 Element Strings/GS1 Digital Link URIs.ReferencesEPC Tag Data Standard, v. 1.12:https://www.gs1.org/standards/epcrfid-epcis-id-keys/epc-rfid-tds/EPCIS Standard, v. 1.2:https://www.gs1.org/standards/epcisCore Business Vocabulary (CBV) Standard, v. 1.2.2:https://www.gs1.org/standards/epcisGS1 Digital Link Standard, v. 1.1:https://www.gs1.org/standards/gs1-digital-link
Package: epc-encoding-utils
EPC Encoding Utilspip install epc-encoding-utilsLibrary for encoding/decoding and representing GS1 Electronic Product Codes (EPCs). It supports the following encoding schemes:GIAIGIDGRAISGLNSGTINThe library's goal is to abstract away much of the complexity of converting between tag representations, and make generating tags and barcodes simple.Docshttps://epcpy-tools.readthedocs.io/en/latest/index.htmlExamplesCreate a new GID encoded tag>>>fromepc.schemesimportGID>>>tag=GID()>>>tag.manager_number(31231).object_class(11).serial_number(12)<epc.schemes.GIDurn:epc:id:gid:31231.11.12>>>>hex(tag)'0x3500079ff00000b00000000c'>>>tag.tag_uri'urn:epc:tag:gid-96:31231.11.12'Generate GIAI barcode from/to a hexadecimal tag data representation>>>fromepc.schemesimportGIAI>>>tag=GIAI(epc='0x341401388000000000000001')>>>tag.barcode'800400200001'>>>tag.barcode_humanized'(8004) 0020000 1'>>>tag=GIAI(barcode='800400200001',company_prefix_length=7)>>>hex(tag)'0x341401388000000000000001'Decode an EPC data tag with unknown encoding>>>fromepc.utilsimportdecode_epc>>>tag=decode_epc('341401388000000000000001')# '0x' prefix is optional>>>print(tag)<epc.schemes.GIAIurn:epc:id:giai:0020000.1>This library was built based on the Tag Data Standard v1.11.Running Testspython-munittestdiscover-sepc/schemes/tests
Package: epconversions
epconversionsUnit conversions for E+Free software: Mozilla Public License 2.0 (MPL 2.0)Documentation:https://epconversions.readthedocs.io.Energyplus has a bunch of conversion factors at the top of theEnergy+.iddfile. It looks like this:! Default IP conversions (no \ip-units necessary)
!      $/(m3/s)               =>   $/(ft3/min)         0.000472000059660808
!      $/(W/K)                =>   $/(Btu/h-F)         0.52667614683731
!      $/kW                   =>   $/(kBtuh/h)         0.293083235638921
!      $/m2                   =>   $/ft2               0.0928939733269818
!      $/m3                   =>   $/ft3               0.0283127014102352
!      (kg/s)/W               =>   (lbm/sec)/(Btu/hr)  0.646078115385742
!      1/K                    =>   1/F                 0.555555555555556
!      1/m                    =>   1/ft                0.3048
!      A/K                    =>   A/F                 0.555555555555556
!      C                      =>   F                   1.8 (plus 32)
!      cm                     =>   in                  0.3937
!      cm2                    =>   inch2               0.15500031000062
!      deltaC                 =>   deltaF              1.8
!      deltaC/hr              =>   deltaF/hr           1.8
!      deltaJ/kg              =>   deltaBtu/lb         0.0004299
!      g/GJ                   =>   lb/MWh              0.00793664091373665
!      g/kg                   =>   grains/lb           7Note thecmin the middle of that text snippet. It shows the conversion formcmtoinand the multipier to use to convertFeaturesThe libraryepconversionshas functions that will do these conversions:from epconversions import epconversions

print(epconversions.convert2ip(100, 'cm'))
>> (39.37, 'in')Can I convert to SI units ? Yes.:epconversions.convert2si(100, 'in')
>> (254.00050800101602, 'cm')What if I want only converted value. I don’t want the unit string:epconversions.convert2si(100, 'in', unitstr=False)
>> 254.00050800101602Nice !!Why does it convertcmtoin. Would it convert tom:epconversions.convert2si(100, 'in', 'm')
>> (2.5399999999999987, 'm')

# for clarity
epconversions.convert2si(100, 'in', siunit='m')
(2.5399999999999987, 'm')What are all the units it can convertinto ?:epconversions.getsiunits('in')
>> {'cm', 'm'}How do I know what it converts it to by default?:epconversions.defaultsiunit('in')
>> 'cm'
epconversions.defaultsiunit('ft')
>> 'm'What are all the units it can convert?:epconversions.allsiunits()
>> ['$/(m3/s)',
'$/(W/K)',

<snip>

'A/K',
'C',
'cm',
'cm2',
'deltaC',
'deltaC/hr',
'deltaJ/kg',
'g/GJ',
'g/kg',
'g/MJ',


<snip>

'W',
'W/((m3/s)-Pa)',
'W/(m3/s)',
'W/K',
'W/m',
'W/m2',

<snip>

'years']

# around 128 now

# also try out ``allipunits()``Thats all for nowCreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History0.1.0 (2023-10-28)First release on PyPI.
Package: epcrawler
Anime Episode Name Scraperepcrawler- get episode names from anidb🎨 Table of ContentsAnime Episode Name Scraperepcrawler- get episode names from anidb🎨 Table of Contents💾 Installation📙 Usage🖥️ Command line interface💾 InstallationThe recommended installation method is usingpip:pipinstallepcrawlerCheck thecommand linesection for supported commands.📙 UsageCopy the name of the anime and pass it toepcrawler.You can use--nameand--outputcommand line argument to specify the anime name and output file respectively.🖥️ Command line interfaceCurrentlyepcrawlersupports these commandsusage:EpisodeFinder[-h]-nNAME[-oOUTPUT]Findtheepisodesnamesfromyourfavoriteanime!

options:-h,--helpshowthishelpmessageandexit-nNAME,--nameNAMEspecifytheanimename-oOUTPUT,--outputOUTPUTspecifytheoutputfile
Package: epcy
Citing:Manuscript in preparationEPCY: Evaluation of Predictive CapabilitY for ranking biomarker gene candidates. Poster at ISMB ECCB 2019:https://f1000research.com/posters/8-1349Introduction:This tool was developed to Evaluate Predictive CapabilitY of each gene (feature) to become a predictive (bio)marker candidates.
Documentation is availablevia Read the Docs.Requirements:python3(Optional) virtualenvInstall:Using pypi:pipinstallepcyFrom source:python3-mvenv$HOME/.virtualenvs/epcysource$HOME/.virtualenvs/epcy/bin/activatepipinstallpipsetuptools--upgradepipinstallwheelcd[your_epcy_folder]# If need it
# CFLAGS=-std=c99 pip3 install numpy==1.17.0python3setup.pyinstallepcy-hUsage:General:After install:epcy-hFrom source:cd[your_epcy_folder]python3-mepcy-hGeneric case:EPCY is design to work on any quantitative data, provided that values of each feature are comparable between each samples (normalized).To run a comparative analysis,epcy predneed two tabulated files:Amatrixof quantitative normalized data for each samples (column) with an “ID” column to identify each feature.Adesigntable which describe the comparison.# Run epcy on any normalized quantification dataepcypred-d./data/small_for_test/design.tsv-m./data/small_for_test/log_normalized_matrix.tsv-o./data/small_for_test/EPCY_output# If your data are normalized, but require a log2 transforamtion, add --logepcypred--log-d./data/small_for_test/design.tsv-m./data/small_for_test/normalized_matrix.tsv-o./data/small_for_test/EPCY_output# If your data are not normalized and require a log2 transforamtion, add --norm --logepcypred--norm--log-d./data/small_for_test/design.tsv-m./data/small_for_test/matrix.tsv-o./data/small_for_test/EPCY_output# Different runs might show small variations.
# To ensure reproducibility set a random seed, using --randomseedepcypred-d./data/small_for_test/design.tsv-m./data/small_for_test/normalized_matrix.tsv-o./data/small_for_test/EPCY_output--randomseed42epcypred-d./data/small_for_test/design.tsv-m./data/small_for_test/normalized_matrix.tsv-o./data/small_for_test/EPCY_output2--randomseed42diff./data/small_for_test/EPCY_output/predictive_capability.tsv./data/small_for_test/EPCY_output2/predictive_capability.tsvMore documentation is availablevia Read the Docs.
Package: epd
EPD (ePaper Driving) library for MpicoSys TCM (Timing Controller Module).This library consist of the following parts:image preparation for use with 1 and 2 bit color ePaper display,image conversion and compression to TCM format,commands formatting for use with TCM,Image preparationfrom PIL import Image
import epd.imageimg = Image.open("test_image.png")
img1bit = epd.image.pilimage_to_1bit(img)
img2bit = epd.image.pilimage_to_2bit(img)Image conversion to EPD dataimport epd.convert
not_compressed_epd_data = epd.convert.toType0_1bit(img1bit.tobytes())
compressed_data =  epd.convert.compress_lz(no_compressed_data)TCM Commands formattingimport epd.tcmimg = Image.open("test_133_image.png")
tcm = epd.tcm.TCM(system_version_code)
epd_data = tcm.get_epd_header(img)+tcm.convert(img)
Package: epdb
Adds functionality to the python debugger, including support for remote
debuggingInstallationpip install epdbUsageFor debugging code locally, epdb generally works the same aspdb. You can debug a program from
the python interpreter:>>> import epdb
>>> import mymodule
>>> epdb.Epdb().run('mymodule.test()')
*** NameError: name 'execfile' is not defined
> /home/wasche/git/epdb/<string>(1)<module>()
-> """
(Epdb) continue
Traceback (most recent call last):
  File "<console>", line 1, in <module>
  File "/usr/lib64/python3.5/bdb.py", line 431, in run
    exec(cmd, globals, locals)
  File "<string>", line 1, in <module>
  File "/home/wasche/git/epdb/mymodule.py", line 2, in test
    import spam
ImportError: No module named 'spam'You can also drop breakpoints at specific places in a program’s code by
inserting:import epdb; epdb.set_trace()or by using the aliasst:import epdb; epbd.st()To debug code that is either running on a remote system, or in a process that
isn’t attached to your tty you can use epdb in server mode:import epdb; epdb.serve()By defaultepdb.serve()will start a simple telnet server on port 8080, but
you can use theportkeyword argument to use a different port:import epdb; epdb.serve(port=8888)You can connect to the epdb server by usingepdb.connect():>>> import epdb
>>> epdb.connect()By defaultepdb.connect()will attempt to connect to port 8080 on
localhost. If you are debugging a process on another host or port, you can call
connect with thehostorportkeyword arguments:>>> import epdb
>>> epdb.connect(host='some.host.com', port=8888)
Package: e.pdfminer.six
Fork of PDFMiner using six for Python 2+3 compatibilityPDFMiner is a tool for extracting information from PDF documents.
Unlike other PDF-related tools, it focuses entirely on getting and analyzing
text data. PDFMiner allows to obtain the exact location of texts in a page,
as well as other information such as fonts or lines.
It includes a PDF converter that can transform PDF files into other text
formats (such as HTML). It has an extensible PDF parser that can be used for
other purposes instead of text analysis.
Package: epdfpy
# ePDFpy
ePDFpy is a standalone tool for reduced electron pair distribution function (ePDF) analysis. Users can do ePDF analysis with the diffraction images obtained by transmission electron microscope (TEM), and use the outputs to deduce the atomic structures.This software is Python-based software with an interactive graphical user interface (GUI) environment built with PyQt5. Currently, built with the python3.8 version but confirmed that still compatible with python3.10.# Installation
For the convenience, it is recommended to use Anaconda (www.anaconda.com/download) or Miniconda (https://docs.conda.io/en/latest/miniconda.html) to set up a virtual environment. All dependencies can easily installed by using ‘environment.yaml’ file in the conda terminal:First, users must install pre-requiste libralies, which are listed in below:numpy >= 1.22.4scipy >= 1.9.1opencv (cv2) >= 4.6.0pandas >= 1.4.4pyqt5 >= 5.15.7pyqtgraph >= 0.12.4hyperspy >= 1.7.1mrcfile >= 1.4.2pyqtdarktheme == 2.1.0Users can install all dependencies manually using pip install or conda install.` pip install-rrequirements.txt `or` conda env create--fileenvironment.yaml `It is recommended to install ePDFpy via PyPI or Anaconda distribution. Users can establish the virtual environment (), then use following command line to install.` pip install epdfpy `or` conda install epdfpy `## Using source codeIf users want to install ePDFpy directly from the source code, download the source code, and moved into the directory path. Using terminal type:` python setup.py install `## ePDFpy GUI package
For those who are not familiar with Python, users can simply download executable files for each OS (Windows, Mac, Linux), which are compiled with PyInstaller.
Simply open the executable file:
- Windows: ePDFpy.exe
- Mac: ePDFpy.app# Running GUIAfter installation, users can open ePDFpy simply typing command line in the terminal:` epdfpy `which will automatically opens the GUI script (run_ui.py) in source folder.Those who are not accustomed to Python, just open executable files from distributed package.# Example
![example](https://github.com/GWlab-SKKU/ePDFpy/assets/59153513/aa1f59c5-0daa-4276-81f4-d48a829b3b56)# LicenseGNU GPLv3ePDFpyis open-source software distributed under a GPLv3 license.
It is free to use, alter, or build on, provided that any work derived fromePDFpyis also kept free and open under a GPLv3 license.
Package: epdnorway
epdnorwayPython module (pypi.org) to consume XML data fromhttps://digi.epd-norge.no/into any python project.Requirementspython v3.7
xmltodict (xmltodict-0.12.0)Usagepip install epdnorwayExample usage:from epdnorway import *
	import pprint as ppquery dataset and show a json list resultres = epdnorway.list_query("limtre")
	pp.pprint(res)get a specific dataset, e.g. first of resultsdataset = epdnorway.DataSet(res[0]["uuid"])To get a list of available Exchange Flows:dataset.availableFlows()Correspondingly, to get available Impact Assessments:dataset.availableImpactAssessments()Data Points are now accessible asdataset.impactAssessmentsanddataset.exchangeFlowsEntire dataset is accessible indataset.dataPossible DatapointsHandled Datapoints are to be found in the following constants:pp.pprint(epdnorway.EXCHANGE_FLOWS)
	pp.pprint(epdnorway.LIFE_CYCLE_METHODS)Data Points are stored as keys, and values in secondary keys inamountsList possible amounts for modules:pp.pprint(epdnorway.KNOWN_MODULES)Get specific datapointsExample: get the numbers for Global warming potential>>> gwp = dataset.getImpact("GWP")
	>>> gwp.data
	{'id': '77e416eb-a363-4258-a04e-171d843a6460', 'name': 'Global warming potential', 'meanAmount': '0.0', 'unit': 'kg CO2-Äqv.', 'amounts': {'A1-A3': -679.0}}get the reference flow of the dataset>>> dataset.referenceFlow.data
	{'id': '5ba9fce9-252d-457d-aea8-45d7d4c9a17d', 'name': 'Limtre', 'meanAmount': '1.0', 'resultingAmount': '1.0', 'version': '00.01.000'}and the units for reference flow (if any):>>> dataset.referenceFlow.units
	[{'name': 'bulk density', 'desc': 'kilograms per cubic metre', 'unit': 'kg/m^3', 'value': '430.0'}]