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mwplotlib

An extension to Matplotlib that plots the shape of the Milky Way.

Installation

pip install mwplotlib

Usage

Here is a simple example of how to use mwplotlib:

from mwplotlib import MilkyWay
import matplotlib.pyplot as plt

# Add the mwplotlib to the matplotlib.pyplot
plt = MilkyWay.mw_plt(plt) # Add the mwplotlib to the matplotlib.pyplot

# Plot the Milky Way in polar coordinates (region-style)
plt.figure(figsize=(9, 9))
plt.MilkyWay.shape(plot_type="polar", style="region")

# Plot the Milky Way in polar coordinates (line-style)
plt.figure(figsize=(9, 9))
plt.MilkyWay.shape(plot_type="polar", style="line")

# Plot the Milky Way in Cartesian coordinates (region-style)
plt.figure(figsize=(9, 9))
plt.MilkyWay.shape(plot_type="cartesian", style="region")

# Plot the Milky Way in Cartesian coordinates (line-style)
plt.figure(figsize=(9, 9))
plt.MilkyWay.shape(plot_type="cartesian", style="line")

For more examples of usage, please refer to examples notebook. Those examples are also available on Google Colab:

Reference

The galaxy model and data used in this package is based on the following paper:

@ARTICLE{2023ApJ...947...54X,
       author = {{Xu}, Y. and {Hao}, C.~J. and {Liu}, D.~J. and {Lin}, Z.~H. and {Bian}, S.~B. and {Hou}, L.~G. and {Li}, J.~J. and {Li}, Y.~J.},
        title = "{What Does the Milky Way Look Like?}",
      journal = {\apj},
     keywords = {Galaxy structure, Milky Way Galaxy, Trigonometric parallax, 622, 1054, 1713},
         year = 2023,
        month = apr,
       volume = {947},
       number = {2},
          eid = {54},
        pages = {54},
          doi = {10.3847/1538-4357/acc45c},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2023ApJ...947...54X},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Please BOTH cite the above paper AND acknowledge this package if you are using it in your research.

License

This package is licensed under the MIT license. See LICENSE for details.

Acknowledgement

We would like to thank the authors of the above paper for making their data publicly available, which made this package possible. We would also like to credit Prof. Ryan Trainor at Franklin and Marshall College for his guidance and support.