Metadata-Version: 2.1
Name: pyLDT-cosmo
Version: 0.3.12
Summary: Package for PDF calculations in Large Deviation Theory
Home-page: https://github.com/mcataneo/pyLDT-cosmo
Author: Matteo Cataneo
Author-email: mcataneo85@gmail.com
License: UNKNOWN
Description: # pyLDT
        Python code to generate matter PDF predictions in Large Deviation Theory for LCDM and alternative cosmologies
        
        ## Installation and testing
        
        (1) If not yet available on your machine, install julia (all platforms: download it from julialang.org; for macOS only you can alternatively 
        
            brew install --cask julia 
            
           with Homebrew)
        
        (2) make sure your system has a recent pip installation by running 
            
            python -m pip install --upgrade pip
        
        (3) for a clean install of pyLDT create a virtual environment first. I will use virtualenvwrapper, but conda or any other environment manager will do. For more details on how to install and configure virtualenvwrapper visit https://virtualenvwrapper.readthedocs.io/en/latest/index.html
        
        (4) Once virtualenvwrapper is setup, create simultaneously a project and an environment (e.g., pyLDTenv) typing in terminal
        
            mkproject pyLDTenv 
           
           If the envornment is not yet activated, type 
           
            workon pyLDTenv 
           
           This should take you directly into the pyLDTenv directory associated with the pyLDTenv project. 
        
        (5) Install PyJulia by running 
        
            python3 -m pip install julia
        
        (6) To install the Julia packages required by PyJulia launch a Python REPL and run the following code 
        
            >>> import julia 
            >>> julia.install() 
        
        (7) Install diffeqpy by running 
        
            pip install diffeqpy
        
        (8) To install Julia packages required for diffeqpy, open up the Python interpreter and run
        
            >>> import diffeqpy
            >>> diffeqpy.install()
        
        (9) Now run 
        
            pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple pyLDT-cosmo 
            
           hopefully at this stage all remaining Python dependencies will be automatically installed too
        
        (10) To check everything is working as expected install pytest by issuing the command
        
            pip install pytest 
           
           and run 
           
            pytest --pyargs pyLDT_cosmo 
           
           A test routine starts cruching the numbers (it should take about 90 sec.) and if pyLDT is correctly installed it should give 1 passed tests
        
        ## Jupyter notebook
        
        Go to https://github.com/mcataneo/pyLDT-cosmo/tree/main and download the example jupyter notebook showing how to use pyLDT. Move the notebook into the pyLDTenv directory. To fully exploit the notebook functionalities you'll need to 'pip install matplotlib' first.
        
        That's all! Have fun!
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.7
Description-Content-Type: text/markdown
