Saravanan666/pypi-org huggingface dataset:
Package: rmsd
The root-mean-square deviation (RMSD) is calculated, using Kabsch algorithm
(1976) or Quaternion algorithm (1991) for rotation, between two Cartesian
coordinates in either.xyzor.pdbformat, resulting in the minimal
RMSD.For more information please readRMSDandKabsch algorithm.MotivationYou have molecule A and B and want to calculate the structural difference
between those two. If you just calculate theRMSDstraight-forward you might
get a too big of a value as seen below. You would need to first recenter the
two molecules and then rotate them unto each other to get the true minimal
RMSD. This is what this script does.No ChangesRe-centeredRotatedRMSD 2.50RMSD 1.07RMSD 0.25CitationImplementation:Calculate Root-mean-square deviation (RMSD) of Two Molecules Using Rotation, GitHub,http://github.com/charnley/rmsd, <git commit hash or version number>Kabsch algorithm:Kabsch W., 1976,
A solution for the best rotation to relate two sets of vectors,
Acta Crystallographica, A32:922-923,
doi: http://dx.doi.org/10.1107/S0567739476001873Quaternion algorithm:Michael W. Walker and Lejun Shao and Richard A. Volz, 1991,
Estimating 3-D location parameters using dual number quaternions, CVGIP: Image Understanding, 54:358-367,
doi:http://dx.doi.org/10.1016/1049-9660(91)90036-oPlease cite this project when using it for scientific publications.InstallationEasiest is to get the program vis PyPi under the package namermsd,pipinstallrmsdor download the project from GitHub viagitclonehttps://github.com/charnley/rmsdThere is only one Python file, so you can also downloadcalculate_rmsd.pyand
put it in your bin folder.wget-Ocalculate_rmsdhttps://raw.githubusercontent.com/charnley/rmsd/master/rmsd/calculate_rmsd.pychmod+xcalculate_rmsdUsage examplesUsecalculate_rmsd--helpto see all the features. Usage is pretty straight
forward, callcalculate_rmsdwith two structures in either.xyzor.pdb. In this example Ethane has the exact same structure, but is
translated in space, so the RMSD should be zero.calculate_rmsdtests/ethane.xyztests/ethane_translate.xyzIt is also possible to ignore all hydrogens (useful for larger molecules where
hydrogens move around indistinguishable) and print the rotated structure for
visual comparison. The output will be in XYZ format.calculate_rmsd--no-hydrogen--printtests/ethane.xyztests/ethane_mini.xyzIf the atoms are scrambled and not aligned you can use the--reorderargument which will align the atoms from structure B unto A. Use--reorder-methodto select what method for reordering. Choose betweenHungarian(default), distance (very approximate) and brute force (slow).calculate_rmsd--reordertests/water_16.xyztests/water_16_idx.xyzIt is also possible to use RMSD as a library in other scripts, seeexample.pyfor example usage.Problems?Submit issues or pull requests on GitHub.ContributionsPlease note that we are usingblackwith line length of 99. Easiest way to
abide to the code standard is to install the following package.pipinstallpre-commitand run the following command in your repositorypre-commitinstallThis will install a hook in your git and re-format your code to adhere to the standard.
As well as check for code quality.
Package: rm-sdk-python
Official Resellme Python SDKUsageMake sure you already got you developer token. If you dont have the token refer to this guide: - and that its set properly using this guide: -Installation GuideUse the pyhton package managerpipto install the official Python SDKpip3installrm_sdk_pythonImport the Resellme module to your projectImport the resellme package and initiate with theAPI_KEYfrom Resellmefromrm_sdk_pythonimportResellmeresellme=Resellme(api_key='YOUR_RESELLME_API_KEY_TOKEN')Checking / Searching for Domain AvailabilityTheresellme.search_domainmethod can return a json object with the values such asavailableornot_availablesearch_response=resellme.search_domain('xyz.co.zw')# search_response is a json objectifsearch_response['status']=='available':# do registration etcRegistering a New DomainThe client's contact details are entered upon registering the domainThe SDK uses default nameservers upon creation and registration of the domain, however there is room to update to your preferred nameservers, check theUpdating Nameserver section# A contact is created with the details provided upon registering a domainresponse=resellme.register_domain(domain_name='xbc.co.zw',first_name='Beven',last_name='Nyamande',email='beven@crontab.co.zw',company='test1',mobile='123123123',street_address='123 Xyz Street',core_business='Area of business undertaken by the company',city='Harare',country='Zimbabwe',)Updating nameserversTo update nameservers to custom nameservers, firstly provide the domain name of the site you want to update as shown belowNB: The method returns a json objectresponse=resellme.update_nameserver('test8.co.zw',ns1='ns1.xyz.com',ns2='ns2.xyz.com')Updating Contact detailsTo update theemail, mobile, citydetails for a specified domain use the following methodThe following method illustrates a case were you want to update all the fields, however you can choose any specific fieldNB: the method requires the domain and email as positional argumentsupdated_contact_details=resellme.update_contact('test.co.zw',email='beven@crontab.co.zw',first_name='your name',last_name='your surname',company='Xyz Inc',mobile='0777123123',street_address='Xyz Street',core_business='Vending',city='Harare',country='Zimbabwe')Get DomainsYou can use this method to fetch all your domainsdomains=resellme.get_all_domains()
Package: rmsfact
rmsfactA port of the R packagermsfactby Dirk Edelbuettel.Display a randomly selected quote about Richard M. Stallman based on the collection in the 'GNU
Octave' function 'fact()' which was aggregated by Jordi Gutiérrez Hermoso based on the (now defunct)
site stallmanfacts.com (which is accessible only viahttp://archive.org).InstallationpipinstallrmsfactUsageThe package exports a single functionrmsfact()which returns a single randomly-chosen "fact" as
astr.importrmsfactrmsfact.rmsfact()You can also runpython -m rmsfactfrom a shell.Building from sourceIn the event you want to build the package from source, clone the repository...git clone https://github.com/lewinfox/rmsfact.git...cdinto the project directory...cd rmsfact...and install withmakemake installThis builds the package and then runspython -m pip install .Making changesTo add a new fact you can editrmsfact/data/rmsfact.txt.echo "A new fact" >> rmsfact/data/rmsfact.txtTheMakefileprovides a couple of useful targets, one of which ismake build_binary_datawhich
executes the scriptrmsfact/data/build_rms_fact.pyto convertrmsfact/data/rmsfact.txtinto a.datfile usingpickle. This.datfile is then read when the package is loaded.Executingmake buildwill rebuild the data file and produce the source and binary packages under
adist/directory. You may need topython -m pip install buildfirst.make buildOther makefile targetsmake install_dev: Install withpip -e
Package: rms-fpzip
PyPI ReleaseTest StatusIntroductionThis is a fork ofhttps://github.com/seung-lab/fpzipwith changes to allow it to work
with Python 3.11 and 3.12; it also has a different test and PyPI deployment system.
We are grateful to William Silversmith for all of the hard work necessary to make this
project in the first place.This fork is maintained by the Ring-Moon Systems Node of NASA's Planetary Data System.fpzipfpzip is a compression algorithm supporting lossless and lossy encoding for up to 4 dimensional floating point data. This package contains Python C++ bindings for the fpzip algorithm (version 1.3.0). The version number for this package is independent. Python 3.7+ is supported.importfpzipimportnumpyasnpdata=np.array(...,dtype=np.float32)# up to 4d float or double array# Compress data losslessly, interpreting the underlying buffer in C (default) or F order.compressed_bytes=fpzip.compress(data,precision=0,order='C')# returns byte string# Back to 3d or 4d float or double array, decode as C (default) or F order.data_again=fpzip.decompress(compressed_bytes,order='C')InstallationpipBinary Installationpipinstallrms-fpzipIf we have a precompiled binary available the above command should just work. However, if you have to compile from source, it's unfortunately necessary to install numpy first because of a quirk in the Python installation procedure that won't easily recognize when a numpy installation completes in the same process. There are some hacks, but I haven't gotten them to work.pipSource InstallationRequires C++ compiler.pipinstallnumpy
pipinstallrms-fpzipDirect InstallationRequires C++ compiler.$pipinstallnumpy
$pythonsetup.pydevelopReferencesAlgorithm and C++ code by Peter Lindstrom and Martin Isenburg. Cython interface code by William Silversmith. Check outDr. Lindstrom's siteor thefpzip Github page.Peter Lindstrom and Martin Isenburg, "Fast and Efficient Compression of Floating-Point Data," IEEE Transactions on Visualization and Computer Graphics, 12(5):1245-1250, September-October 2006, doi:10.1109/TVCG.2006.143.
Package: rmsgd
RMSGD: Augmented SGD OptimizerOfficial PyTorch implementation of theRMSGDoptimizer from:Exploiting Explainable Metrics for Augmented SGDMahdi S. Hosseini, Mathieu Tuli, Konstantinos N. PlataniotisAccepted in IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR2022)We propose new explainability metrics that measure the redundant information in a network's layers and exploit this information to augment the Stochastic Gradient Descent (SGD) optimizer by adaptively adjusting the learning rate in each layer. We call this new optimizerRMSGD. RMSGD is fast, performs better than existing sota, and generalizes well across experimental configurations.ContentsThis repository + branch contains the standalone optimizer, which is pip installable. Equally, you could copy the contents ofsrc/rmsgdinto your local repository and use the optimizer as is.For all code relating to our paper and to replicate those experiments, see thepaperbranchInstallationYou can install rmsgd usingpip install rmsgd, or equally:git clone https://github.com/mahdihosseini/RMSGD.gitcd RMSGDpip install .UsageRMSGD can be used like any other optimizer, with one additional step:fromrmsgdimportRMSGD...optimizer=RMSGD(...)...forinputindata_loader:optimizer.zero_grad()output=network(input)optimizer.step()optimizer.epoch_step()Simply, you must call.epoch_step()at the end of each epoch to update the analysis of the network layers.Citation@Article{hosseini2022rmsgd,
  author  = {Hosseini, Mahdi S. and Tuli, Mathieu and Plataniotis, Konstantinos N.},
  title   = {Exploiting Explainable Metrics for Augmented SGD},
  journal = {Accepted in IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year    = {2022},
}LicenseThis project is released under the MIT license. Please see theLICENSEfile for more information.
Package: rms-interval
PyPI ReleaseTest StatusCode Coveragerms-intervalPDS Ring-Moon Systems Node, SETI InstituteSupported versions: Python >= 3.7The interval class behaves like a dictionary keyed by ranges of
floating-point numbers. Each value of the dictionary applies for any key
value within the numeric range. Later entries into the dictionary can
partially or completely replace earlier values.Note that this package is deprecated in favor of theportionmodule.
Eventually this package may be removed entirely.
Package: rmskin-builder
rmskin-actionA Python-based Github action tool to package a Repository’s Rainmeter Content into a validating
.rmskin file for Rainmeter’s Skin Installer.ImportantIf the repository contains a RMSKIN.bmp image to used as a header image in the rmskin package,
then it must be using 24-bit colors. Additionally, if the image is not exactly 400x60, then
this action’s python script will resize it accordingly.rmskin-builder Python packageThis action’srmskin-builder.pyis now also available as a Python executable script via PyPI.
However, it is important that your Python installation’sScriptsfolder is found in your
Operating System’s environment variablePATH. If you’re using a Python virtual environment,
then theScriptsfolder does not need to be in your Operating System’s environment variablePATH.pipinstallrmskin-builderrmskin-builder.exe--helpInput ArgumentsArgumentDescriptionRequiredversionVersion of the Rainmeter rmskin package. Defaults to last 8 digits of SHA from commit or ref/tags or otherwise ‘x0x.x0xy’.notitleName of the Rainmeter rmskin package. Defaults to name of repository or otherwise the last directory in thepathargument.noauthorAccount Username maintaining the rmskin package. Defaults to Username that triggered the action or otherwise ‘Unknown’.nopathBase directory of repo being packaged. Defaults to current working pathnodir_outPath to save generated rmskin package. Defaults to current working pathnoNoteYou can use your repository’sRMSKIN.inifile to override any above inputs exceptdir_out&pathinputs.The above arguments are used as CLI arguments to thermskin_builder.pyscript, but remember to
append the CLI arguments’ name with a--. For example, setting thepathargument to use a
relative directory calledtests:rmskin-builder.exe--pathtestsOutput Argumentsarc_name: The name of the generated rmskin file saved in the
path specified bydir_outinput argument.If executing thermskin_builder.pyscript when not in a Github Action Runner, then this output
argument will show in the script’s log output (& not saved anywhere).Ideal Repo Structureroot directorySkinsa folder to contain all necessary Rainmeter skinsRMSKIN.inilist of options specific to installing the skin(s)Layoutsa folder that contains Rainmeter layout filesPluginsa folder that contains Rainmeter plugins@Vaultresources folder accessible by all installed skinsTipA cookiecutter repositoryhas also been created to facilitate development of Rainmeter skins on Github
quickly.Example Usagename:RMSKIN Packageron:push:pull_request:release:types:[published]jobs:Build_n_Release:runs-on:ubuntu-lateststeps:# Checkout code-name:Checkout this Repouses:actions/checkout@v3# Runs a rmskin packager action-name:Run Build actionid:builderuses:2bndy5/rmskin-action@v1.1.8# Upload the asset (using the output from the `builder` step)-name:Upload Release Assetif:github.event_name == 'release'uses:shogo82148/actions-upload-release-asset@v1with:upload_url:${{ github.event.release.upload_url }}asset_path:${{ steps.builder.outputs.arc_name }}asset_content_type:application/zip
Package: rmslib
vegLib is a powerful Python library designed for calculating and analyzing
vegetation indices from remote sensing and spectral data. With easy-to-use
functions, it empowers researchers and developers to quantify and monitor vegetation
health, enabling precise insights into ecosystems, agriculture, and environmental studies.
vegLib is the go-to tool for extracting valuable information from spectral imagery,
contributing to more informed decisions in the realm of vegetation analysis.
MIT LicenseCopyright (c) 2023 Derraz RadhwanePermission 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: rmsorn
Reward Modulated Self-Organizing Recurrent Neural NetworksRMSORN is a subclass of neuro-inspired artificial network, Self Organizing Recurrent Neural Networks. With reward driven self-organization, this network achieves performance with networks trained with supervised learning algorithms.To install the latest release:pipinstallrmsornThe library is still in alpha stage, so you may also want to install the latest version from the development branch:pipinstallgit+https://github.com/Saran-nns/rmsornUsage:Update Network configurationsNavigate to home/conda/envs/ENVNAME/Lib/site-packages/rmsornor if you are unsure about the directory of rmsornRunimportrmsornrmsorn.__file__to find the location of the rmsorn packageThen, update/edit the configuration.inifromrmsorn.tasksimportPatternRecognitioninputs,targets=PatternRecognitionTask.generate_sequence()train_plast_inp_mat,X_all_inp,Y_all_inp,R_all,frac_pos_active_conn=SimulateRMSorn(phase='Plasticity',matrices=None,inputs=np.asarray(inputs),sequence_length=4,targets=targets,reward_window_sizes=[1,5,10,20],epochs=1).train_rmsorn()
Package: rmsp-gui
Resource Management System (RMS) GUI ManualThe package provides GUI support to thermsppackage.Installationpip install rmsp-guiQuick startTo start the RMS set up:DBPATH="/path/to/db/"DBNAME="test.db"DBRESDIR="Resources/"LIBPATH=f"{DBPATH}RMSLibrary/"importsysimportlogginglogger=logging.getLogger("rmspool")logger.setLevel("INFO")logger.addHandler(logging.StreamHandler(sys.stdout))# RMS Corefromrmspimportrmscorefromrmspimportrmsbuilderfromrmsp.rmstemplateimportRMSTemplateLibraryrms=rmscore.ResourceManagementSystem(f"{DBPATH}{DBNAME}",f"{DBPATH}{DBRESDIR}")rmspool=rmsbuilder.RMSProcessWrapPool(rms,1)rmsb=rmsbuilder.RMSUnrunTasksBuilder(rmspool)rmstlib=RMSTemplateLibrary(rmsb,LIBPATH)# Interactorfromrmsp.rmsinteractorimportRMSPoolInteractionCore,RMSInteractionCore,RMSTemplateLibraryInteractionCorefromrmsp.interactorhelperimportLocalInteractorrms_interactor=LocalInteractor(RMSInteractionCore(rms))rmspool_interactor=LocalInteractor(RMSPoolInteractionCore(rmspool))rmstemplatelib_interactor=LocalInteractor(RMSTemplateLibraryInteractionCore(rmstlib))Starting GUI in jupyter%guiqt5fromrmsp.rmsgui.qt.mainappimportRMSWindowwin=RMSWindow(rms_interactor,rmspool_interactor,rmstemplatelib_interactor)win.showMaximized()Starting GUI in python scriptfromPyQt5.QtWidgetsimportQApplicationapp=QApplication([])fromrmsp.rmsgui.qt.mainappimportRMSWindowwin=RMSWindow(rms_interactor,rmspool_interactor,rmstemplatelib_interactor)win.showMaximized()app.exec()
Package: rms-textkernel
PyPI ReleaseTest StatusCode Coveragerms-textkernelSupported versions: Python >= 3.8PDS Ring-Moon Systems Node, SETI InstituteTextKernel LibraryThis is a set of routines for parsing SPICE text kernels. The simplest use case is as
follows:import textkernel
        tkdict = textkernel.from_file('path/to/kernel/file')The returned dictionary is keyed by all the parameter names (on the left side of an equal
sign) in the text kernel, and each associated dictionary value is that found on the right
side. Values are Python ints, floats, strings, datetime objects, or lists of one or more
of these.This module implements the complete syntax specification as discussed in the SPICE Kernel
Required Reading document, "kernel.req":https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/req/kernel.htmlFor convenience, the returned dictionary adds additional, "hierarchical" keys that provide
alternative access to the same values. Hierarchical keys are substrings from the original
parameter name, which return a sub-dictionary keyed by part or all of the remainder of
that parameter name.Parameter names with a slash are split apart as if they represented components of a file
directory tree, so these are equivalent:tkdict["DELTET/EB"] == tkdict["DELTET"]["EB"]When a body or frame ID is embedded inside a parameter name, it is extracted, converted
to integer, and used as a piece of the hierarchy, making these equivalent:tkdict["BODY399_POLE_RA"] == tkdict["BODY"][399]["POLE_RA"]
        tkdict["SCLK01_MODULI_32"] == tkdict["SCLK"][-32]["01_MODULI"]Leading and trailing underscores before and after the embedded numeric ID are stripped
from the hierarchical keys, as you can see in the examples above. Note also that the
components of the parameter name are re-ordered in the second example, so that the
second key is always the numeric ID.When the name associated with a body or frame ID is known, that name can be used in the
place of the integer ID:tkdict["BODY"][399] == tkdict["BODY"]["EARTH"]
        tkdict["FRAME"][10013] == tkdict["FRAME"]["IAU_EARTH"]
        tkdict["SCLK"][-32] == tkdict["SCLK"]["VOYAGER 2"]If a frame is uniquely or primarily associated with a particular central body, that
body's ID can also be used in place of the frame's ID:tkdict["FRAME"][399] == tkdict["FRAME"]["IAU_EARTH"]Note that the "BODY" and "FRAME" dictionaries also have an additional entry keyed by "ID",
which returns the associated integer ID:tkdict["FRAME"][623]["ID"] = 623
        tkdict["FRAME"]["IAU_SUTTUNGR"]["ID"] = 623This ensures that you can look up a body or frame by name and readily obtain its ID.
Package: rms-vicar
rms-vicarPDS Ring-Moon Systems Node, SETI InstituteSupported versions: Python >= 3.7Classes and methods to read and write JPL's VICAR-format data files:VicarLabel      class for reading, writing, and parsing of VICAR labels.
VicarImage      class for handling VICAR image (and other) data files.
VicarError      extension of class ValueError to contain exceptions.This module supports the definition of the VICAR file format as found here:https://www-mipl.jpl.nasa.gov/external/VICAR_file_fmt.pdfTo read a VICAR image file:vic = VicarImage("path/to/file")
vic.array     = the 3-D data array converted to native format.
vic.array2d   = same as above, but with leading dimension (typically, bands) stripped.
vic.prefix    = the array prefix bytes as a 3-D array of unsigned bytes.
vic.prefix2d  = same as above, but with the leading dimension stripped.
vic.binheader = the binary header as a bytes object; use vic.binheader_array() to
              = extract information.
vic.label     = the internal VicarLabel object that manages the VICAR label
                information, if direct access is needed.VICAR parameter values can be extracted from the label using dictionary-like syntax:len(vic)          = the number of parameters in the VICAR label.
vic['LBLSIZE']    = the value of the LBLSIZE parameter (an integer).
vic[0]            = the value of the first parameter.
vic[-1]           = the value of the last parameter.
vic['LBLSIZE',-1] = the value of the last occurrence of the LBLSIZE parameter.
vic.get(('LBLSIZE',2), 99) = the value of the third occurrence of the LBLSIZE
                    parameter, or 99 if there are fewer than 3 occurrences.
vic.arg('LBLSIZE') = the numeric index of "LBLSIZE" among the VICAR parameters.You can also use dictionary-like syntax to modify and insert header values:vic['SOLDIST'] = 1.e9   # set SOLDICT to this value.
del vic['SOLDIST',0]    # Remove the first occurrence of SOLDIST from the label.
vic['LBLSIZE+'] = 2000  # insert a new LBLSIZE parameter instead of modifying an
                        # existing one.Note that certain required VICAR parameters contain structural information about the file;
these cannot generally be modified directly.Numerous methods are available to iterate over the VICAR label parameters:for (name,value) in vic.items(): ...
for key in vic.keys(): ...
for name in vic.names(): ...
for value in vic.values(): ...Iterators can take a regular expression as input to restrict the items returned:for value in vic.values(r'LAB\d\d'): ...Usestr(vic)to get the VICAR label content represented as a string.Here are the steps to create and write a VICAR image file:vic = VicarImage()
vic.array = array
vic.prefix = prefix
vic.binheader = binheader
vic['NOTES'] = ['add as many more VICAR parameters', 'as you wish']
vic.write_file("path/to/file")
Package: rmsyutls
rmsy-utlsUtility functions for RamseyAboutContains some utility functions for using Ramsey and other JAX-based packages.InstallationTo install the latest GitHub , just call the following on the
command line:pipinstallgit+https://github.com/ramsey-devs/rmsy-utls@<RELEASE>AuthorSimon Dirmeiersfyrbnd @ pm me