Add gallery example "Cross-section along a transect" (#2515)

Co-authored-by: Michael Grund <[email protected]>
Co-authored-by: Dongdong Tian <[email protected]>
Co-authored-by: Wei Ji <[email protected]>

Author: 4 people

examples/gallery/images/cross_section.py

@@ -0,0 +1,138 @@
+"""
+Cross-section along a transect
+==============================
+:func:`pygmt.project` and :func:`pygmt.grdtrack` can be used to focus on
+a quantity and its variation along a desired survey line.
+In this example, the elevation is extracted from a grid provided via
+:func:`pygmt.datasets.load_earth_relief`.
+The figure consists of two parts, a map of the elevation in the study
+area showing the survey line and a Cartesian plot showing the elevation
+along the survey line.
+
+*This example is orientated on an example in the GMT/China documentation*:
+https://docs.gmt-china.org/latest/examples/ex026/
+"""
+
+import pygmt
+
+# Define region of study area
+# lon_min, lon_max, lat_min, lat_max in degrees East and North
+region_map = [122, 149, 30, 49]
+
+# Create a new pygmt.Figure instance
+fig = pygmt.Figure()
+
+# ----------------------------------------------------------------------------
+# Bottom: Map of elevation in study area
+
+# Set up basic map
+fig.basemap(
+    region=region_map,
+    projection="M12c",  # Mercator projection with a width of 12 centimeters
+    frame="af",
+)
+
+# Download grid for Earth relief with a resolution of 10 arc-minutes and
+# gridline registration [Default]
+grid_map = pygmt.datasets.load_earth_relief(
+    resolution="10m",
+    region=region_map,
+)
+
+# Plot the downloaded grid with color-coding based on the elevation
+fig.grdimage(grid=grid_map, cmap="oleron")
+
+# Add a colorbar for the elevation
+fig.colorbar(
+    # Place the colorbar inside the plot (lower-case "j") with justification
+    # Bottom Right and an offset ("+o") of 0.7 centimeters and
+    # 0.3 centimeters in x or y directions, respectively
+    # Move the x label above the horizontal colorbar ("+ml")
+    position="jBR+o0.7c/0.8c+h+w5c/0.3c+ml",
+    # Add a box around the colobar with a fill ("+g") in "white" color and
+    # a transparency ("@") of 30 % and with a 0.8-points thick black
+    # outline ("+p")
+    box="+gwhite@30+p0.8p,black",
+    # Add x and y labels ("+l")
+    frame=["x+lElevation", "y+lm"],
+)
+
+# Choose a survey line
+fig.plot(
+    x=[126, 146],  # Longitude in degrees East
+    y=[42, 40],  # Latitude in degrees North
+    # Draw a 2-points thick red dashed line for the survey line
+    pen="2p,red,dashed",
+)
+
+# Add labels "A" and "B" for the start and end points of the survey line
+fig.text(
+    x=[126, 146],
+    y=[42, 40],
+    text=["A", "B"],
+    offset="0c/0.2c",  # Move text 0.2 centimeters up (y direction)
+    font="15p",  # Use a font size of 15 points
+)
+
+# ----------------------------------------------------------------------------
+# Top: Elevation along survey line
+
+# Shift plot origin 12.5 centimeters to the top
+fig.shift_origin(yshift="12.5c")
+
+fig.basemap(
+    region=[0, 15, -8000, 6000],  # x_min, x_max, y_min, y_max
+    # Cartesian projection with a width of 12 centimeters and
+    # a height of 3 centimeters
+    projection="X12c/3c",
+    # Add annotations ("a") and ticks ("f") as well as labels ("+l")
+    # at the west or left and south or bottom sides ("WSrt")
+    frame=["WSrt", "xa2f1+lDistance+u°", "ya4000+lElevation / m"],
+)
+
+# Add labels "A" and "B" for the start and end points of the survey line
+fig.text(
+    x=[0, 15],
+    y=[7000, 7000],
+    text=["A", "B"],
+    no_clip=True,  # Do not clip text that fall outside the plot bounds
+    font="10p",  # Use a font size of 10 points
+)
+
+# Generate points along a great circle corresponding to the survey line
+# and store them in a pandas.DataFrame
+track_df = pygmt.project(
+    center="126/42",  # Start point of survey line (longitude/latitude)
+    endpoint="146/40",  # End point of survey line (longitude/latitude)
+    generate="0.1",  # Output data in steps of 0.1 degrees
+)
+
+# Extract the elevation at the generated points from the downloaded grid
+# and add it as new column "elevation" to the pandas.DataFrame
+track_df = pygmt.grdtrack(
+    grid=grid_map,
+    points=track_df,
+    newcolname="elevation",
+)
+
+# Plot water masses
+fig.plot(
+    x=[0, 15],
+    y=[0, 0],
+    fill="lightblue",  # Fill the polygon in "lightblue"
+    # Draw a 0.25-points thick black solid outline
+    pen="0.25p,black,solid",
+    close="+y-8000",  # Force closed polygon
+)
+
+# Plot elevation along the survey line
+fig.plot(
+    x=track_df.p,
+    y=track_df.elevation,
+    fill="gray",  # Fill the polygon in "gray"
+    # Draw a 1-point thick black solid outline
+    pen="1p,black,solid",
+    close="+y-8000",  # Force closed polygon
+)
+
+fig.show()