Metadata-Version: 2.1
Name: nondim-slurry
Version: 0.1
Summary: Python code that solves the 1D, steady, spherical slurry       equations outlined in Wong et al (in prep, EPSL) (see also Wong et al. 2018)
Home-page: https://github.com/jnywong/nondim-slurry
Author: Jenny Wong
Author-email: jenny.wong@univ-grenoble-alpes.fr
License: LICENSE.md
Description: [![Build Status](https://travis-ci.org/jnywong/nondim-slurry.svg?branch=master)](https://travis-ci.org/jnywong/nondim-slurry)
        
        # slurpy
        
        Python module to solve the 1D, steady, spherical slurry system outlined in Wong et al.
        (2021) (see also Wong et al. 2018).
        
        ## Getting Started
        
        ### Prerequisites
        - [Python](https://www.python.org/)
        
        ### Installing
        Conda:
        ```
        conda install -c jnywong nondim-slurry
        ```
        
        Pip:
        ```
        pip install nondim-slurry
        ```
        
        Git:
        
        Find the latest version of the repository [here](https://github.com/jnywong/nondim-slurry).
        
        ## Package structure
        ```
        slurpy/
          __init__.py
          coreproperties.py
          data_utils.py
          getparameters.py
          lookup.py
          lookupdata/
            denPREM.csv
            gravPREM.csv
            presPREM.csv
            radAK135.csv
            radPREM.csv
            vpAK135.csv
            vpPREM.csv
          plot_utils.py
          scripts/
            parameter_search.py
            seismic.py
            sensitivity.py
          slurry.py
        ```
        
        ## Example scripts
        
        ### Parameter search
        
        1. Open `scripts/parameter_search.py`
        
        2. Enter some input parameters. For example, try:
        
        ```
        # %% MODEL INPUTS
        # Show plots?
        plotOn=1 # show temp, xi, solid flux and density profiles
        
        # Input parameters
        layer_thicknesses=np.array([150e3]) # (m)
        thermal_conductivities=np.array([100.]) # (W m^-1 K^-1)
        icb_heatfluxes=np.array([3.4]) # (TW)
        csb_heatfluxes=np.array([7.4]) # (TW)
        
        h=0.05 # stepsize of heat flux through parameter space
        ```
        
        3. Run `parameter_search.py`
        
        4. Admire the output:
        
        ![](https://raw.githubusercontent.com/jnywong/nondim-slurry/master/slurpy/docs/simple_output.png)
        
        ### Sensitivity study
        
        1. Open `scripts/sensitivity.py`
        
        2. Enter some input parameters. For example, try:
        
        ```
        # %% MODEL INPUTS
        # Save plot?
        saveOn=0
        
        # Input parameters
        layer_thickness=150e3 # (m)
        thermal_conductivity=100. # (W m^-1 K^-1)
        icb_heatflux=2.5 # (TW)
        csb_heatflux=5.0 # (TW)
        h=0.05 # stepsize of heat flux through parameter space
        
        # Sensitivity study
        csb_temp = np.arange(4500.,6100.,100) # (K)
        csb_oxy = np.arange(2,12.5,0.5) # (mol.%)
        sed_con= np.array([1e-5,1e-4,1e-3,1e-2,1e-1]) # (kg s/m^3) pre-factor in sedimentation coefficient, b(phi)
        ```
        
        3. Run `sensitivity.py`
        
        4. Admire the output:
        
        ![hello!](https://raw.githubusercontent.com/jnywong/nondim-slurry/master/slurpy/docs/sensitivity_example.png)
        
        ## Links
        * [PyPI](https://pypi.org/project/nondim-slurry/)
        * [Anaconda Cloud](https://anaconda.org/jnywong/nondim-slurry)
        
        ## Authors
        
        * [**Jenny Wong**](https://jnywong.github.io/) - *University of Leeds - Institut de Physique du Globe de Paris - Institut des Sciences de la Terre*
        * [**Chris Davies**](https://environment.leeds.ac.uk/see/staff/1225/dr-chris-davies) - *University of Leeds*
        * [**Chris Jones**](https://eps.leeds.ac.uk/maths/staff/4042/professor-christopher-jones-) - *University of Leeds*
        
        ## License
        
        This project is licensed under the MIT License - see the [LICENSE.md](LICENSE.md) file for details
        
        ## Acknowledgments
        
        * ERC SEIC
        * Del Duca Foundation
        * EPSRC Centre for Doctoral Training in Fluid Dynamics
        
        :tada:
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
