How to use the metpy.calc.smooth_n_point function in MetPy

def test_smooth_n_pt_5():
    """Test the smooth_n_pt function using 5 points."""
    hght = np.array([[5640., 5640., 5640., 5640., 5640.],
                    [5684., 5676., 5666., 5659., 5651.],
                    [5728., 5712., 5692., 5678., 5662.],
                    [5772., 5748., 5718., 5697., 5673.],
                    [5816., 5784., 5744., 5716., 5684.]])
    shght = smooth_n_point(hght, 5, 1)
    s_true = np.array([[5640., 5640., 5640., 5640., 5640.],
                      [5684., 5675.75, 5666.375, 5658.875, 5651.],
                      [5728., 5711.5, 5692.75, 5677.75, 5662.],
                      [5772., 5747.25, 5719.125, 5696.625, 5673.],
                      [5816., 5784., 5744., 5716., 5684.]])
    assert_array_almost_equal(shght, s_true)

def test_smooth_n_pt_9_units():
    """Test the smooth_n_pt function using 9 points with units."""
    hght = np.array([[5640., 5640., 5640., 5640., 5640.],
                    [5684., 5676., 5666., 5659., 5651.],
                    [5728., 5712., 5692., 5678., 5662.],
                    [5772., 5748., 5718., 5697., 5673.],
                    [5816., 5784., 5744., 5716., 5684.]]) * units.meter
    shght = smooth_n_point(hght, 9, 1)
    s_true = np.array([[5640., 5640., 5640., 5640., 5640.],
                      [5684., 5675.5, 5666.75, 5658.75, 5651.],
                      [5728., 5711., 5693.5, 5677.5, 5662.],
                      [5772., 5746.5, 5720.25, 5696.25, 5673.],
                      [5816., 5784., 5744., 5716., 5684.]]) * units.meter
    assert_array_almost_equal(shght, s_true)

ds = xr.open_dataset('https://thredds.ucar.edu/thredds/dodsC/'
                     'casestudies/python-gallery/NARR_19930313_1800.nc').metpy.parse_cf()

# Get lat/lon data from file
lats = ds.lat.data
lons = ds.lon.data

# Calculate variable dx, dy values for use in calculations
dx, dy = mpcalc.lat_lon_grid_deltas(lons, lats)

# Get 700-hPa data and smooth
level = 700 * units.hPa
hght_700 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_700 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_700 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_700 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Get 300-hPa data and
level = 300 * units.hPa
hght_300 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_300 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_300 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_300 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

lon_slice = slice(200, 350)
lat_slice = slice(85, 10)

# Grab lat/lon values (GFS will be 1D)
lats = ds.lat.sel(lat=lat_slice).values
lons = ds.lon.sel(lon=lon_slice).values

# Grab data and smooth using a nine-point filter applied 50 times to grab the synoptic signal
level = 850 * units.hPa
hght_850 = mpcalc.smooth_n_point(ds.Geopotential_height_isobaric.metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)
tmpk_850 = mpcalc.smooth_n_point(ds.Temperature_isobaric.metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 25)
uwnd_850 = mpcalc.smooth_n_point(ds['u-component_of_wind_isobaric'].metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)
vwnd_850 = mpcalc.smooth_n_point(ds['v-component_of_wind_isobaric'].metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)

# Convert temperatures to degree Celsius for plotting purposes
tmpc_850 = tmpk_850.to('degC')

# Get a sensible datetime format
vtime = ds.time.data[0].astype('datetime64[ms]').astype('O')


######################################################################
# Compute Q-vectors
# -----------------
#
# Use the MetPy module to compute Q-vectors from requisite data and
# additionally compute the Q-vector divergence (and multiply by -2) to
# calculate the right hand side forcing of the Q-G Omega equation.

# Get lat/lon data from file
lats = ds.lat.data
lons = ds.lon.data

# Calculate variable dx, dy values for use in calculations
dx, dy = mpcalc.lat_lon_grid_deltas(lons, lats)

# Get 700-hPa data and smooth
level = 700 * units.hPa
hght_700 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_700 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_700 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_700 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Get 300-hPa data and
level = 300 * units.hPa
hght_300 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_300 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_300 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_300 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Convert Temperatures to degC
tmpc_700 = tmpk_700.to('degC')
tmpc_300 = tmpk_300.to('degC')

# from 850 hPa
#

# Set subset slice for the geographic extent of data to limit download
lon_slice = slice(200, 350)
lat_slice = slice(85, 10)

# Grab lat/lon values (GFS will be 1D)
lats = ds.lat.sel(lat=lat_slice).values
lons = ds.lon.sel(lon=lon_slice).values

# Grab data and smooth using a nine-point filter applied 50 times to grab the synoptic signal
level = 850 * units.hPa
hght_850 = mpcalc.smooth_n_point(ds.Geopotential_height_isobaric.metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)
tmpk_850 = mpcalc.smooth_n_point(ds.Temperature_isobaric.metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 25)
uwnd_850 = mpcalc.smooth_n_point(ds['u-component_of_wind_isobaric'].metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)
vwnd_850 = mpcalc.smooth_n_point(ds['v-component_of_wind_isobaric'].metpy.sel(
    vertical=level, lat=lat_slice, lon=lon_slice).squeeze(), 9, 50)

# Convert temperatures to degree Celsius for plotting purposes
tmpc_850 = tmpk_850.to('degC')

# Get a sensible datetime format
vtime = ds.time.data[0].astype('datetime64[ms]').astype('O')


######################################################################
# Compute Q-vectors
# -----------------

lats = ds.lat.data
lons = ds.lon.data

# Grab x, y data and make 2D for wind component plotting because
# u- and v-components are grid relative
x = ds['u-component_of_wind_isobaric'].x
y = ds['u-component_of_wind_isobaric'].y

xx, yy = np.meshgrid(x, y)

# Grab Cartopy CRS from metadata for plotting wind barbs
datacrs = ds['u-component_of_wind_isobaric'].metpy.cartopy_crs

# Select and grab 500-hPa geopotential heights and smooth with n-point smoother
level = 500 * units.hPa
hght_500 = mpcalc.smooth_n_point(ds.Geopotential_height_isobaric.metpy.sel(
    vertical=level).squeeze(), 9, 50)

# Select and grab 500-hPa wind components
uwnd_500 = ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze()
vwnd_500 = ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze()

# Compute north-relative wind components for plotting purposes
uwnd_er, vwnd_er = earth_relative_wind_components(uwnd_500, vwnd_500)

# Smooth wind components as desired
uwnd_er = mpcalc.smooth_n_point(uwnd_er, 9, 50)
vwnd_er = mpcalc.smooth_n_point(vwnd_er, 9, 50)

# Create a clean datetime object for plotting based on time of Geopotential heights
vtime = ds.time.data[0].astype('datetime64[ms]').astype('O')

dx, dy = mpcalc.lat_lon_grid_deltas(lons, lats)

# Get 700-hPa data and smooth
level = 700 * units.hPa
hght_700 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_700 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_700 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_700 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Get 300-hPa data and
level = 300 * units.hPa
hght_300 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_300 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_300 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_300 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Convert Temperatures to degC
tmpc_700 = tmpk_700.to('degC')
tmpc_300 = tmpk_300.to('degC')

# Get time in a nice datetime object format
vtime = ds.time.values.astype('datetime64[ms]').astype('O')[0]

# Get 700-hPa data and smooth
level = 700 * units.hPa
hght_700 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_700 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_700 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_700 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Get 300-hPa data and
level = 300 * units.hPa
hght_300 = mpcalc.smooth_n_point(ds['Geopotential_height_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
tmpk_300 = mpcalc.smooth_n_point(ds['Temperature_isobaric'].metpy.sel(
    vertical=level).squeeze(), 9)
uwnd_300 = mpcalc.smooth_n_point(
    ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)
vwnd_300 = mpcalc.smooth_n_point(
    ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze(), 9)

# Convert Temperatures to degC
tmpc_700 = tmpk_700.to('degC')
tmpc_300 = tmpk_300.to('degC')

# Get time in a nice datetime object format
vtime = ds.time.values.astype('datetime64[ms]').astype('O')[0]


######################################################################
# Differential Temperature Advection Calculation

datacrs = ds['u-component_of_wind_isobaric'].metpy.cartopy_crs

# Select and grab 500-hPa geopotential heights and smooth with n-point smoother
level = 500 * units.hPa
hght_500 = mpcalc.smooth_n_point(ds.Geopotential_height_isobaric.metpy.sel(
    vertical=level).squeeze(), 9, 50)

# Select and grab 500-hPa wind components
uwnd_500 = ds['u-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze()
vwnd_500 = ds['v-component_of_wind_isobaric'].metpy.sel(vertical=level).squeeze()

# Compute north-relative wind components for plotting purposes
uwnd_er, vwnd_er = earth_relative_wind_components(uwnd_500, vwnd_500)

# Smooth wind components as desired
uwnd_er = mpcalc.smooth_n_point(uwnd_er, 9, 50)
vwnd_er = mpcalc.smooth_n_point(vwnd_er, 9, 50)

# Create a clean datetime object for plotting based on time of Geopotential heights
vtime = ds.time.data[0].astype('datetime64[ms]').astype('O')


######################################################################
# MetPy Absolute Vorticity Calculation
# ------------------------------------
#
# This code first uses MetPy to calcualte the grid deltas (sign aware) to
# use for derivative calculations with the funtcion
# ``lat_lon_grid_deltas()`` and then calculates ``absolute_vorticity()``
# using the wind components, grid deltas, and latitude values.
#