.. only:: html .. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_sars.py: Plotting data from the SARS database ==================================== .. image:: /auto_examples/images/sphx_glr_plot_sars_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none /Users/travis/build/sharppy/SHARPpy/examples/plot_sars.py:29: UserWarning: Matplotlib is currently using agg, which is a non-GUI backend, so cannot show the figure. plt.show() | .. code-block:: default import sharppy.sharptab as tab import sharppy.databases.sars as sars import numpy as np import os import matplotlib.pyplot as plt database_fn = os.path.join( os.path.dirname( sars.__file__ ), 'sars_supercell.txt') supercell_database = np.loadtxt(database_fn, skiprows=1, dtype=bytes, comments="%%%%") magnitude = [] mlcape = [] srh01 = [] for record in supercell_database: magnitude.append(int(record[1])) mlcape.append(float(record[3])) srh01.append(float(record[6])) plt.grid() plt.scatter(mlcape, srh01, c=magnitude, marker='.') plt.colorbar() plt.xlabel("MLCAPE [J/kg]") plt.ylabel(r'0-1 km Storm Relative Helicity [$m^{2}/s^{2}$]') plt.savefig('plot_sars.png', bbox_inches='tight') plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 0.885 seconds) .. _sphx_glr_download_auto_examples_plot_sars.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_sars.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_sars.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_