Add smoothing example to docs

examples/calculations/Smoothing.py

@@ -0,0 +1,75 @@
+# Copyright (c) 2015-2018 MetPy Developers.
+# Distributed under the terms of the BSD 3-Clause License.
+# SPDX-License-Identifier: BSD-3-Clause
+"""
+Smoothing
+=========
+
+Using MetPy's smoothing functions.
+
+This example demonstrates the various ways that MetPy's smoothing function
+can be utilized. While this example utilizes basic NumPy arrays, these
+functions all work equally well with Pint Quantities or xarray DataArrays.
+"""
+
+from itertools import product
+
+import matplotlib.pyplot as plt
+import numpy as np
+
+import metpy.calc as mpcalc
+
+###########################################
+# Start with a base pattern with random noise
+np.random.seed(61461542)
+size = 128
+x, y = np.mgrid[:size, :size]
+distance = np.sqrt((x - size / 2) ** 2 + (y - size / 2) ** 2)
+raw_data = np.random.random((size, size)) * 0.3 + distance / distance.max() * 0.7
+
+fig, ax = plt.subplots(1, 1, figsize=(4, 4))
+ax.set_title('Raw Data')
+ax.imshow(raw_data, vmin=0, vmax=1)
+ax.axis('off')
+plt.show()
+
+###########################################
+# Now, create a grid showing different smoothing options
+fig, ax = plt.subplots(3, 3, figsize=(12, 12))
+for i, j in product(range(3), range(3)):
+    ax[i, j].axis('off')
+
+# Gaussian Smoother
+ax[0, 0].imshow(mpcalc.smooth_gaussian(raw_data, 3), vmin=0, vmax=1)
+ax[0, 0].set_title('Gaussian - Low Degree')
+
+ax[0, 1].imshow(mpcalc.smooth_gaussian(raw_data, 8), vmin=0, vmax=1)
+ax[0, 1].set_title('Gaussian - High Degree')
+
+# Rectangular Smoother
+ax[0, 2].imshow(mpcalc.smooth_rectangular(raw_data, (3, 7), 2), vmin=0, vmax=1)
+ax[0, 2].set_title('Rectangular - 3x7 Window\n2 Passes')
+
+# 5-point smoother
+ax[1, 0].imshow(mpcalc.smooth_n_point(raw_data, 5, 1), vmin=0, vmax=1)
+ax[1, 0].set_title('5-Point - 1 Pass')
+
+ax[1, 1].imshow(mpcalc.smooth_n_point(raw_data, 5, 4), vmin=0, vmax=1)
+ax[1, 1].set_title('5-Point - 4 Passes')
+
+# Circular Smoother
+ax[1, 2].imshow(mpcalc.smooth_circular(raw_data, 2, 2), vmin=0, vmax=1)
+ax[1, 2].set_title('Circular - Radius 2\n2 Passes')
+
+# 9-point smoother
+ax[2, 0].imshow(mpcalc.smooth_n_point(raw_data, 9, 1), vmin=0, vmax=1)
+ax[2, 0].set_title('9-Point - 1 Pass')
+
+ax[2, 1].imshow(mpcalc.smooth_n_point(raw_data, 9, 4), vmin=0, vmax=1)
+ax[2, 1].set_title('9-Point - 4 Passes')
+
+# Arbitrary Window Smoother
+ax[2, 2].imshow(mpcalc.smooth_window(raw_data, np.diag(np.ones(5)), 2), vmin=0, vmax=1)
+ax[2, 2].set_title('Custom Window (Diagonal) \n2 Passes')
+
+plt.show()

src/metpy/calc/tools.py

@@ -1503,15 +1503,20 @@ def wrap_output_like(**wrap_kwargs):
         attrs) of other object
         - If shapes do not match, this will error
         - If input is a Quantity, use magnitude and add unit as attribute (rather than xarray
-            wrapping Quantity, at least for now)
+        wrapping Quantity, at least for now)
 
-    The behavior of this decorator is flexible. Use the following keyword arguments to control
-    the mapping behavior:
+    The behavior of this decorator is flexible. Use the optional keyword arguments to control
+    the mapping behavior.
 
-    - `argument`: specify the name of a single argument from the function signature from which
+    Parameters
+    ----------
+    argument : str
+        specify the name of a single argument from the function signature from which
         to take the other data object
-    - `other`: specify the other data object directly
-    - `match_unit`: if True and other data object has units, convert output to those units
+    other : `numpy.ndarray` or `pint.Quantity` or `xarray.DataArray`
+        specify the other data object directly
+    match_unit : bool
+        if True and other data object has units, convert output to those units
         (defaults to False)
 
     Notes