.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "auto_examples/oversample/plot_ncpt1.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_oversample_plot_ncpt1.py: Oversample NC at 0.1 degree =========================== Create a 0.1 degree gridded product over NC. Using gridfit=True to resize the grid on the fly to match the lon/lat bounding box. The crs_proj4 for global is pure lon/lat, which doesn't play well with IOAPI ROW/COL coordinates. To solve this, we convert the ROW/COL to lon/lat before plotting. .. GENERATED FROM PYTHON SOURCE LINES 14-73 .. image-sg:: /auto_examples/oversample/images/sphx_glr_plot_ncpt1_001.png :alt: TSTEP = 2020-01-01, LAY = 0.9975 :srcset: /auto_examples/oversample/images/sphx_glr_plot_ncpt1_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none 2020-01-01 00:00:00 2020-01-02 00:00:00 2020-01-03 00:00:00 2020-01-04 00:00:00 2020-01-05 00:00:00 2020-01-06 00:00:00 2020-01-07 00:00:00 2020-01-08 00:00:00 2020-01-09 00:00:00 2020-01-10 00:00:00 did not find a match in any of xarray's currently installed IO backends ['netcdf4', 'scipy']. Consider explicitly selecting one of the installed engines via the ``engine`` parameter, or installing additional IO dependencies, see: https://docs.xarray.dev/en/stable/getting-started-guide/installing.html https://docs.xarray.dev/en/stable/user-guide/io.html 2020-01-11 00:00:00 2020-01-12 00:00:00 2020-01-13 00:00:00 2020-01-14 00:00:00 2020-01-15 00:00:00 | .. code-block:: default import matplotlib.pyplot as plt import pyrsig import pandas as pd import xarray as xr import pycno import os # Create a working directory gdnam = 'global_0pt1' # or finer! 'global_0pt01' bdate = '2020-01-01' edate = '2020-01-15' wdir = f'{gdnam}/{bdate[:4]}' os.makedirs(gdnam, exist_ok=True) rsigapi = pyrsig.RsigApi( bdate=bdate, bbox=(-85, 33, -75, 37), encoding={"zlib": True, "complevel": 1, "_FillValue": -9.999e36}, workdir=wdir, grid_kw=gdnam, gridfit=True ) # Update to download daily averages instead of hourly rsigapi.grid_kw['REGRID_AGGREGATE'] = 'daily' # Loop over days dss = [] for bdate in pd.date_range(bdate, edate): print(bdate) try: ds = rsigapi.to_ioapi(key='tropomi.offl.no2.nitrogendioxide_tropospheric_column', bdate=bdate) dss.append(ds) except Exception as e: print(e) # Create a simple long-term average outds = dss[0][['DAILY_NO2', 'COUNT']].isel(TSTEP=0, LAY=0) outds['DAILY_NO2'] = outds['DAILY_NO2'].fillna(0) * outds['COUNT'] for ds in dss[1:]: ds = ds.isel(TSTEP=0, LAY=0) outds['DAILY_NO2'] += ds['DAILY_NO2'].fillna(0) * ds['COUNT'] outds['COUNT'] += ds['COUNT'] Z = outds['DAILY_NO2'] = (outds['DAILY_NO2'] / outds['COUNT']) # Convert COL/ROW to lon/lat for plotting Z.coords['COL'] = Z.COL.data * outds.XCELL + outds.XORIG Z.coords['ROW'] = Z.ROW.data * outds.YCELL + outds.YORIG # Make a plot with a medium grey background and state boundaries qm = Z.plot() qm.axes.set(facecolor='gainsboro') pycno.cno(dss[0].attrs['crs_proj4']).drawstates(ax=qm.axes) # Show the figure plt.show() # Or save the figure # qm.figure.savefig('nc_0pt1.png') .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 20.651 seconds) .. _sphx_glr_download_auto_examples_oversample_plot_ncpt1.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_ncpt1.py ` .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_ncpt1.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_