Expand documentation for Cartesian projections

examples/projections/nongeo/cartesian_linear.py

@@ -2,8 +2,21 @@
 Cartesian linear
 ================
 
-**X**\ *width*/[*height*]: Give the *width* of the figure and the optional
-*height*.
+**X**\ *width*\ [/*height*] or **x**\ *x-scale*\ [/*y-scale*]
+
+Give the *width* of the figure and the optional *height*.
+The lower-case version **x** is similar to **X** but expects
+an *x-scale* and an optional *y-scale*.
+
+The Cartesian linear projection is primarily designed for regular
+floating point data. To plot geographical data in a linear
+projection, see the upstream GMT documentation
+:gmt-docs:`Geographic coordinates
+<cookbook/coordinate-transformations.html#geographic-coordinates>`.
+To make the linear plot using calendar date/time as input
+coordinates, see the GMT documentation
+:gmt-docs:`Calendar time coordinates
+<cookbook/coordinate-transformations.html#calendar-time-coordinates>`.
 """
 import pygmt
 

examples/projections/nongeo/cartesian_logarithmic.py

@@ -2,9 +2,14 @@
 Cartesian logarithmic
 =====================
 
-**X**\ *width*\ [**l**]/[*height*\ [**l**]]: Give the *width* of the figure and
-the optional *height*. Each axis with a logarithmic transformation
-requires **l** after its size argument.
+**X**\ *width*\ [**l**][/*height*\ [**l**]] or
+**x**\ *x-scale*\ [**l**][/*y-scale*\ [**l**]]
+
+Give the *width* of the figure and the optional *height*.
+The lower-case version **x** is similar to **X** but expects
+an *x-scale* and an optional *y-scale*.
+Each axis with a logarithmic transformation requires **l** after
+its size argument.
 """
 import numpy as np
 import pygmt

examples/projections/nongeo/cartesian_power.py

@@ -2,10 +2,14 @@
 Cartesian power
 ===============
 
-**X**\ *width*\ [**p**\ *pvalue*]/[*height*\ [**p**\ *pvalue*]]: Give the
-*width* of the figure and the optional argument *height*. Each axis with
-a power transformation requires **p** and the exponent for that axis
-after its size argument.
+**X**\ *width*\ [**p**\ *pvalue*][/*height*\ [**p**\ *pvalue*]] or
+**x**\ *x-scale*\ [**p**\ *pvalue*][/*y-scale*\ [**p**\ *pvalue*]]
+
+Give the *width* of the figure and the optional argument *height*.
+The lower-case version **x** is similar to **X** but expects
+an *x-scale* and an optional *y-scale*.
+Each axis with a power transformation requires **p** and the exponent
+for that axis after its size argument.
 """
 import numpy as np
 import pygmt