Apply formatting suggestions from code review

Co-authored-by: Dongdong Tian <[email protected]>

Author: weiji14

examples/tutorials/subplots.py

@@ -13,7 +13,7 @@
 - Use :meth:`pygmt.Figure.subplot` to define the layout of the subplots.
 
 The first method is easier to use and should handle simple cases involving a
-couple of subplots. For more advanced subplot layouts however, we recommend the
+couple of subplots. For more advanced subplot layouts, however, we recommend the
 use of :meth:`pygmt.Figure.subplot` which offers finer grained control, and
 this is what the tutorial below will cover.
 """
@@ -31,9 +31,9 @@
 # Define subplot layout
 # ---------------------
 #
-# The :meth:`pygmt.Figure.subplot` command is used to setup the layout, size,
+# The :meth:`pygmt.Figure.subplot` function is used to set up the layout, size,
 # and other attributes of the figure. It divides the whole canvas into regular
-# grid areas with n rows and m columns. Each grid area can contain an
+# grid areas with *n* rows and *m* columns. Each grid area can contain an
 # individual subplot. For example:
 
 ###############################################################################
@@ -44,30 +44,30 @@
 
 ###############################################################################
 # will define our figure to have a 2 row and 3 column grid layout.
-# ``figsize=("15c", "6c")`` defines the overall size of the figure to be 15cm
-# wide by 6cm high. Using ``frame="lrtb"`` allows us to customize the map frame
+# ``figsize=("15c", "6c")`` defines the overall size of the figure to be 15 cm
+# wide by 6 cm high. Using ``frame="lrtb"`` allows us to customize the map frame
 # for all subplots instead of setting them individually. The figure layout will
 # look like the following:
 
 with fig.subplot(nrows=2, ncols=3, figsize=("15c", "6c"), frame="lrtb"):
-    for index in range(2 * 3):
-        i = index // 3  # row
-        j = index % 3  # column
-        with fig.set_panel(panel=index):  # sets the current panel
-            fig.text(
-                position="MC",
-                text=f"index: {index}, row: {i}, col: {j}",
-                region=[0, 1, 0, 1],
-            )
+    for i in range(2):  # row number starting from 0
+        for j in range(3):  # column number starting from 0
+            index = i * 3 + j  # index number starting from 0
+            with fig.set_panel(panel=index):  # sets the current panel
+                fig.text(
+                    position="MC",
+                    text=f"index: {index}; row: {i}, col: {j}",
+                    region=[0, 1, 0, 1],
+                )
 fig.show()
 
 ###############################################################################
-# The :meth:`pygmt.Figure.set_panel` command activates a specified subplot, and
-# all subsequent plotting commands will take place in that subplot panel. This
+# The :meth:`pygmt.Figure.set_panel` function activates a specified subplot, and
+# all subsequent plotting functions will take place in that subplot panel. This
 # is similar to matplotlib's ``plt.sca`` method. In order to specify a subplot,
 # you will need to provide the identifier for that subplot via the ``panel``
-# argument. Pass in either the ``index`` number, or a tuple like
-# (``row``, ``col``) to ``panel``.
+# argument. Pass in either the *index* number, or a tuple/list like
+# (*row*, *col*) to ``panel``.
 
 ###############################################################################
 # .. note::
@@ -78,7 +78,7 @@
 
 ###############################################################################
 # For example, to activate the subplot on the top right corner (index: 2) at
-# ``row=0`` and ``col=2``, so that all subsequent plotting commands happen
+#  *row*\=0 and *col*\=2, so that all subsequent plotting commands happen
 # there, you can use the following command:
 
 ###############################################################################
@@ -91,7 +91,7 @@
 # Making your first subplot
 # -------------------------
 # Next, let's use what we learned above to make a 2 row by 2 column subplot
-# figure. We'll also pick up on some new parameters to configure our subplot.
+# figure. We'll also pick up on some new arguments to configure our subplot.
 
 fig = pygmt.Figure()
 with fig.subplot(
@@ -118,9 +118,9 @@
 
 ###############################################################################
 # In this example, we define a 2-row, 2-column (2x2) subplot layout using
-# :meth:`pygmt.Figure.subplot`. The overall figure dimensions is set to be 15cm
-# wide and 6cm high (``figsize=["15c", "6c"]``). In addition, we used some
-# optional parameters to fine tune some details of the figure creation:
+# :meth:`pygmt.Figure.subplot`. The overall figure dimensions is set to be 15 cm
+# wide and 6 cm high (``figsize=["15c", "6c"]``). In addition, we use some
+# optional arguments to fine-tune some details of the figure creation:
 #
 # - ``autolabel=True``: Each subplot is automatically labelled abcd
 # - ``margins=["0.1c", "0.2c"]``: adjusts the space between adjacent subplots.
@@ -154,7 +154,7 @@
 # --------------------------
 # In the example above with the four subplots, the two subplots for each row
 # have the same Y-axis range, and the two subplots for each column have the
-# same X-axis range. You can use the **layout** option to set a common X and/or
+# same X-axis range. You can use the ``layout`` argument to set a common X and/or
 # Y axis between subplots.
 
 fig = pygmt.Figure()

pygmt/src/subplot.py

@@ -148,7 +148,7 @@ def subplot(self, nrows=1, ncols=1, **kwargs):
     with Session() as lib:
         try:
             arg_str = " ".join(["begin", f"{nrows}x{ncols}", build_arg_string(kwargs)])
-            lib.call_module(module="subplot", args=arg_str)
+            lib.call_module("subplot", arg_str)
             yield
         finally:
             v_arg = build_arg_string({"V": kwargs.get("V")})