.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "auto_examples/gridemiss/run_gridemiss_01_perturb.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_auto_examples_gridemiss_run_gridemiss_01_perturb.py>`
        to download the full example code.

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_auto_examples_gridemiss_run_gridemiss_01_perturb.py:


Domain-wide Gridded Emission Scaling
====================================

Apply a constant factor to a subset of emission variables in a file.

The basic steps are:

1. Copy a file.
2. Select species to scale NOx species.
3. Scale by a multiplicative factor.
4. Plot the old and new result.

*Reminder*: You must have already activated your python environment.

.. GENERATED FROM PYTHON SOURCE LINES 18-20

Configuration
'''''''''''''

.. GENERATED FROM PYTHON SOURCE LINES 20-34

.. code-block:: Python


    # date to process
    date = '20160610'
    # file to copy
    oldpath = f'../../camx/emiss/camx_area.mobile.{date}.36km.nc'
    # new file to create
    newpath = f'outputs/camx_area_2x.mobile.{date}.36km.nc'
    # species to scale
    scalekeys = ['NO', 'NO2', 'HONO']  # list of strings or set to 'all'
    # factor to scale by
    factor = 2.
    # path for figure comparing
    figpath = 'outputs/scaled_gridemiss_scalewholedomain.png'








.. GENERATED FROM PYTHON SOURCE LINES 35-37

Imports and File Prep
'''''''''''''''''''''

.. GENERATED FROM PYTHON SOURCE LINES 37-45

.. code-block:: Python


    import netCDF4
    import shutil
    import os

    os.makedirs('outputs', exist_ok=True)
    shutil.copyfile(oldpath, newpath)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none


    'outputs/camx_area_2x.mobile.20160610.36km.nc'



.. GENERATED FROM PYTHON SOURCE LINES 46-50

Open Files
''''''''''
- Open the existing file in read-only mode
- Open the new file in editable append mode

.. GENERATED FROM PYTHON SOURCE LINES 50-54

.. code-block:: Python


    infile = netCDF4.Dataset(oldpath, mode='r')
    outfile = netCDF4.Dataset(newpath, mode='a')








.. GENERATED FROM PYTHON SOURCE LINES 55-58

Select Emission Variables to Scale
''''''''''''''''''''''''''''''''''
- if scalekeys is all, identify all emission variables by unit

.. GENERATED FROM PYTHON SOURCE LINES 58-69

.. code-block:: Python


    if scalekeys == 'all':
        scalekeys = [
            k for k, v in outfile.variables.items()
            if v.units.strip() in ('mol hr-1', 'g hr-1')
        ]

    noscalekeys = sorted(set(outfile.variables).difference(scalekeys))
    print('INFO:: no scale', noscalekeys)
    print('INFO:: to scale', scalekeys)





.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    INFO:: no scale ['ACET', 'ALD2', 'ALDX', 'BENZ', 'BNZA', 'CH4', 'CO', 'CPRM', 'ECH4', 'ETFLAG', 'ETH', 'ETHA', 'ETHY', 'ETOH', 'FORM', 'FPRM', 'IOLE', 'ISOP', 'ISP', 'IVOA', 'KET', 'MEOH', 'NA', 'NH3', 'NVOL', 'OLE', 'PAL', 'PAR', 'PCA', 'PCL', 'PEC', 'PFE', 'PH2O', 'PK', 'PMG', 'PMN', 'PNH4', 'PNO3', 'POA', 'PRPA', 'PSI', 'PSO4', 'PTI', 'SO2', 'SULF', 'TERP', 'TFLAG', 'TOL', 'TOLA', 'TRP', 'UNK', 'UNR', 'X', 'XYL', 'Y', 'latitude', 'longitude']
    INFO:: to scale ['NO', 'NO2', 'HONO']




.. GENERATED FROM PYTHON SOURCE LINES 70-72

Apply Scaling
-------------

.. GENERATED FROM PYTHON SOURCE LINES 72-83

.. code-block:: Python


    for skey in scalekeys:
        print('INFO:: scaling', skey, 'by', factor)
        outvar = outfile.variables[skey]
        invar = infile[skey]
        outvar[:] = factor * invar[:]

    outfile.sync()
    del outfile






.. rst-class:: sphx-glr-script-out

 .. code-block:: none

    INFO:: scaling NO by 2.0
    INFO:: scaling NO2 by 2.0
    INFO:: scaling HONO by 2.0




.. GENERATED FROM PYTHON SOURCE LINES 84-86

Plot Comparison
'''''''''''''''

.. GENERATED FROM PYTHON SOURCE LINES 86-102

.. code-block:: Python


    import pyrsig
    import pycno
    import matplotlib.colors as mc

    oldfile = pyrsig.open_ioapi(oldpath)
    newfile = pyrsig.open_ioapi(newpath)
    key = scalekeys[0]
    compfile = newfile[[]]
    compfile['New'] = newfile[key].sum('LAY').mean('TSTEP')
    compfile['Old'] = oldfile[key].sum('LAY').mean('TSTEP')
    Z = compfile.to_dataarray(dim='version')
    Z.attrs.update(oldfile[key].attrs)
    fca = Z.plot(col='version', norm=mc.LogNorm(10, compfile['Old'].max()))
    pycno.cno(oldfile.crs_proj4).drawstates(ax=fca.axs)
    fca.fig.savefig(figpath)



.. image-sg:: /auto_examples/gridemiss/images/sphx_glr_run_gridemiss_01_perturb_001.png
   :alt: version = New, version = Old
   :srcset: /auto_examples/gridemiss/images/sphx_glr_run_gridemiss_01_perturb_001.png
   :class: sphx-glr-single-img






.. rst-class:: sphx-glr-timing

   **Total running time of the script:** (0 minutes 8.584 seconds)


.. _sphx_glr_download_auto_examples_gridemiss_run_gridemiss_01_perturb.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: run_gridemiss_01_perturb.ipynb <run_gridemiss_01_perturb.ipynb>`

    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: run_gridemiss_01_perturb.py <run_gridemiss_01_perturb.py>`

    .. container:: sphx-glr-download sphx-glr-download-zip

      :download:`Download zipped: run_gridemiss_01_perturb.zip <run_gridemiss_01_perturb.zip>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_