Metadata-Version: 2.1
Name: nice-figures
Version: 0.0.2
Summary: Methods and style files for making publication quality figures
Home-page: https://github.com/Rob217/nice-figures
Author: Rob Bettles
Author-email: rjbcoding@gmail.com
License: UNKNOWN
Description: # Nice Figures
        
        A collection of scripts, modules, and style files for making publication quality figures in Matplotlib.
        
        Styles are in accordance with American Physical Society (APS) and Nature publications. 
        
        ![alt text](https://github.com/Rob217/nice-figures/blob/master/examples/figs/advanced_fig.png "Example figure")
        
        To load module:
        ```python
        from nice_figures load *
        ```
        
        ## Installation instructions
        
        This package requires prior intallation of the following packages:
        * [numpy](https://numpy.org/install/)
        
        * [matplotlib](https://matplotlib.org/)
        
        I recommend installing for the PyPI server using pip:
        ```python
        pip install nice-figures
        ```
        
        Alternatively, the files can be downloaded directly from GitHub.
        
        To import, use:
        ```python
        from nice_figures import *
        ```
        
        ## Functions
        
        The following functions are included:
        * [load_style()](./nice_figures/load_style.py)
        
           Load a set of predefined rcParams.
           
        * [add_numbering()](./nice_figures/add_numbering.py)
        
           Add numbering (e.g., a, b, c, 1, 2, 3, ...) to axes.
        
        * [load_cols()](./nice_figures/load_cols.py)
        
           Load a dictionary of colors.
        
        * [add_border()](./nice_figures/add_border.py)
        
           Add a border around the figure. This is useful in, e.g., Jupyter notebooks, where it is unclear how large the figure.
        
        For more details about each function, please see the function docstrings.
        
        ## Examples
        
        Example scripts and figures are given in [examples](./examples/).
        
        ## Useful resources
        
        * https://matplotlib.org/3.2.1/tutorials/introductory/customizing.html
        * https://journals.aps.org/prl/authors
        * https://www.nature.com/nature/for-authors/final-submission
        
        ## Where was this package used?
        
        * https://arxiv.org/abs/1907.07030
        
        
        
        ---
        Any suggestions for improvements are very welcome!
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
