Package: gaussian-proc
A python package for machine learning with Gaussian process regression.This package is under development and has not been released.FeaturesTODOInteractive TutorialLaunch an online interactive tutorial inJupyter notebook.LinksDocumentationPackage on Anaconda CloudPackage on PyPiInstallSupported PlatformsSuccessful installation and tests have been performed on the following platforms and Python/PyPy versions shown in the table below.PlatformPython versionPyPy versionStatus2.73.63.73.83.92.73.63.7Linux✔✔✔✔✔✔✔✔macOS✔✔✔✔✔✖✖✖Windows✖✔✔✔✔✖✖✖For the Python/PyPy versions indicated by ✔ in the above, this package can be installed using eitherpiporconda(seeInstall Packagebelow.)This package cannot be installed viapiporcondaon the Python/PyPy versions indicated by ✖ in the above table.To install on the older Python 3 versions that are not listed in the above (for example Python 3.5), you shouldbuildthis package from the source code (seeBuild and Install from Source Code).DependenciesAt runtime:TODOFor tests:To runTest,scipypackage is required and can be installed bypython -m pip install -r tests/requirements.txtInstall PackageEitherInstall from PyPi,Install from Anaconda Cloud, orBuild and Install from Source Code.Install from PyPiThe recommended installation method is through the package available atPyPiusingpip.Ensurepipis installed within Python and upgrade the existingpipbypython -m ensurepip
python -m pip install --upgrade pipIf you are using PyPy instead of Python, ensurepipis installed and upgrade the existingpipbypypy -m ensurepip
pypy -m pip install --upgrade pipInstall this package in Python bypython -m pip install gaussian_processor, in PyPy bypypy -m pip install gaussian_processInstall from Anaconda CloudAlternatively, the package can be installed throughAnaconda could.InLinuxandWindows:conda install -c s-ameli gaussian_processInmacOS:conda install -c s-ameli -c conda-forge gaussian_processBuild and Install from Source CodeBuild dependencies:To build the package from the source code,numpyandcythonare required. These dependencies are installed automatically during the build process and no action is needed.Install both C and Fortran compilers as follows.Linux:Installgcc, for instance, byapt(or any other package manager on your Linux distro)sudo apt install gccmacOS:Installgccvia Homebrew:sudo brew install gccNote:Ifgccis already installed, but Fortran compiler is yet not available on macOS, you may resolve this issue by reinstalling:sudo brew reinstall gccWindows:Install bothMicrosoft Visual C++ compilerand Intel Fortran compiler (Intel oneAPI). Open the command prompt (where you will enter the installation commands in the next step) and load the Intel compiler variables byC:\Program Files (x86)\Intel\oneAPI\setvars.batHere, we assumed the Intel Fortran compiler is installed inC:\ProgramFiles(x86)\Intel\oneAPI. You may set this directory accordingly to the directory of your Intel compiler.Clone the source code and install this package bygit clone https://github.com/ameli/gaussian_process.git
cd gaussian_process
python -m pip install .Warning:After the package is built and installed from the source code, the package cannot be imported properly if the current working directory is the same as the source code directory. To properly import the package, change the current working directory to a directory anywhere elseoutsideof the source code directory. For instance:cd..python>>>importgaussian_processTestTo test package, installtox:python -m pip install toxand test the package withtoxModulesSyntaxUser guidetodo(nu, z, n)Module name todo  <https://ameli.github.io/gaussian_process/module_name.html>`_Typed Arguments:ArgumentTypeDescriptionnudoubleParameterExamplesRelated PackagesTODOAcknowledgementsNational Science Foundation #1520825American Heart Association #18EIA33900046CreditTODO.