Add a gallery example showing how to use advanced grdgradient via the "azimuth" & "normalize" parameters

examples/gallery/images/grdgradient_shading.py

@@ -0,0 +1,62 @@
+"""
+Calculating grid gradient with custom ``azimuth`` and ``normalize`` parameters
+------------------------------------------------------------------------------
+The :func:`pygmt.grdgradient` function calculates the gradient of a grid file.
+As input, :func:`pygmt.grdgradient` gets a :class:`xarray.DataArray` object or
+a path string to a grid file. It then calculates the respective gradient and
+returns an :class:`xarray.DataArray` object. The example below sets two main
+parameters:
+
+- ``azimuth``: to set the illumination light source direction (0° is North,
+  90° is East, 180° is South, 270° is West).
+- ``normalize`` to enhance the three-dimensional sense of the topography.
+
+The ``normalize`` parameter calculates the azimuthal gradient of each point
+along a certain azimuth angle, then adjusts the brightness value of the color
+according to the positive/negative of the azimuthal gradient and the amplitude
+of each point.
+"""
+
+import pygmt
+
+# Load the 3 arc-minutes global relief grid in the target area around Caucasus
+grid = pygmt.datasets.load_earth_relief(resolution="03m", region=[35, 50, 35, 45])
+
+fig = pygmt.Figure()
+
+# Define a colormap to be used for topography
+pygmt.makecpt(cmap="terra", series=[-7000, 7000])
+
+# Define figure configuration
+pygmt.config(FONT_TITLE="10p,5", MAP_TITLE_OFFSET="1p", MAP_FRAME_TYPE="plain")
+
+# Setup subplot panels with three rows and four columns
+with fig.subplot(
+    nrows=3,
+    ncols=4,
+    figsize=("28c", "21c"),
+    sharex="b",
+    sharey="l",
+):
+    # E.g. "0/90" illuminates light source from the North (top) and East
+    # (right), and so on
+    for azi in ["0/90", "0/300", "180/225"]:
+        # "e" and "t" are cumulative Laplace distribution and cumulative
+        # Cauchy distribution, respectively
+        # "amp" (e.g. 1 or 10) controls the brightness value of the color
+        for nor in ["t1", "e1", "t10", "e10"]:
+            # Making an intensity DataArray using azimuth and normalize
+            # parameters
+            shade = pygmt.grdgradient(grid=grid, azimuth=azi, normalize=nor)
+            fig.grdimage(
+                grid=grid,
+                shading=shade,
+                projection="M?",
+                frame=["a4f2", f"+tazimuth={azi}, normalize={nor}"],
+                cmap=True,
+                panel=True,
+            )
+
+fig.colorbar(position="x9.0c/-1.1c+w10c/0.25c+h", frame="a2000f500+lElevation (m)")
+
+fig.show()