Tiny improvements for the multi-parameter symbols example
Multi-parameter symbols
-------------------------
-The :meth:`pygmt.Figure.plot` method can plot individual multi-parameter symbols by passing
-the corresponding shortcuts listed below to the ``style`` parameter. Additionally, we must define
-the required parameters in a 2d list or numpy array (``[[parameters]]`` for a single symbol
-or ``[[parameters_1],[parameters_2],[parameters_i]]`` for several ones) or use an
+The :meth:`pygmt.Figure.plot` method can plot individual multi-parameter
+symbols by passing the corresponding shortcuts listed below to the ``style``
+parameter. Additionally, we must define the required parameters in a 2d list or
+numpy array (``[[parameters]]`` for a single symbol or
+``[[parameters_1],[parameters_2],[parameters_i]]`` for several ones) or use an
appropriately formatted input file and pass it to ``data``.
The following symbols are available:
@@ -14,49 +15,36 @@ The following symbols are available:
- **j**: rotated rectangle, ``[[lon, lat, direction, width, height]]``
- **r**: rectangle, ``[[lon, lat, width, height]]``
- **R**: rounded rectangle, ``[[lon, lat, width, height, radius]]``
-- **w**: pie wedge, ``[[lon, lat, radius, startdir, stopdir]]``, the last two arguments are
- directions given in degrees counter-clockwise from horizontal
-
-Upper-case versions **E**, **J**, and **W** are similar to **e**, **j** and **w** but expect geographic
-azimuths and distances.
+- **w**: pie wedge, ``[[lon, lat, radius, startdir, stopdir]]``, the last two
+ arguments are directions given in degrees counter-clockwise from horizontal
+Upper-case versions **E**, **J**, and **W** are similar to **e**, **j** and
+**w** but expect geographic azimuths and distances.
"""
-import numpy as np
import pygmt
fig = pygmt.Figure()
-
fig.basemap(region=[0, 6, 0, 2], projection="x3c", frame=True)
-###################
# ELLIPSE
-data = np.array([[0.5, 1, 45, 3, 1]])
-
+data = [[0.5, 1, 45, 3, 1]]
fig.plot(data=data, style="e", color="orange", pen="2p,black")
-###################
# ROTATED RECTANGLE
-data = np.array([[1.5, 1, 120, 5, 0.5]])
-
+data = [[1.5, 1, 120, 5, 0.5]]
fig.plot(data=data, style="j", color="red3", pen="2p,black")
-###################
# RECTANGLE
-data = np.array([[3, 1, 4, 1.5]])
-
+data = [[3, 1, 4, 1.5]]
fig.plot(data=data, style="r", color="dodgerblue", pen="2p,black")
-###################
# ROUNDED RECTANGLE
-data = np.array([[4.5, 1, 1.25, 4, 0.5]])
-
+data = [[4.5, 1, 1.25, 4, 0.5]]
fig.plot(data=data, style="R", color="seagreen", pen="2p,black")
-###################
# PIE WEDGE
-data = np.array([[5.5, 1, 2.5, 45, 330]])
-
+data = [[5.5, 1, 2.5, 45, 330]]
fig.plot(data=data, style="w", color="lightgray", pen="2p,black")
fig.show()
