Update failing doctests with upstream dataset changes (#2988)

Author: seisman

pygmt/src/grd2xyz.py

@@ -138,8 +138,8 @@ def grd2xyz(grid, output_type="pandas", outfile=None, **kwargs):
     >>> xyz_dataframe = pygmt.grd2xyz(grid=grid, output_type="pandas")
     >>> xyz_dataframe.head(n=2)
         lon   lat  elevation
-    0  10.0  25.0      863.0
-    1  10.5  25.0      985.5
+    0  10.0  25.0      965.5
+    1  10.5  25.0      876.5
     """
     output_type = validate_output_table_type(output_type, outfile=outfile)
 

pygmt/src/grdclip.py

@@ -87,7 +87,7 @@ def grdclip(grid, **kwargs):
     ... )
     >>> # Report the minimum and maximum data values
     >>> [grid.data.min(), grid.data.max()]
-    [170.0, 2275.5]
+    [183.5, 1807.0]
     >>> # Create a new grid from an input grid. Set all values below 1,000 to
     >>> # 0 and all values above 1,500 to 10,000
     >>> new_grid = pygmt.grdclip(grid=grid, below=[1000, 0], above=[1500, 10000])

pygmt/src/grdhisteq.py

@@ -299,11 +299,11 @@ def compute_bins(
         >>> print(bins)
                 start    stop
         bin_id
-        0       170.0   389.0
-        1       389.0   470.5
-        2       470.5   571.0
-        3       571.0   705.0
-        4       705.0  2275.5
+        0       183.5   395.0
+        1       395.0   472.0
+        2       472.0   575.0
+        3       575.0   709.5
+        4       709.5  1807.0
 
         See Also
         --------

pygmt/src/grdproject.py

@@ -103,13 +103,10 @@ def grdproject(grid, **kwargs):
     >>> import pygmt
     >>> # Load a grid of @earth_relief_30m data, with a longitude range of
     >>> # 10° E to 30° E, and a latitude range of 15° N to 25° N
-    >>> grid = pygmt.datasets.load_earth_relief(
-    ...     resolution="30m", region=[10, 30, 15, 25]
-    ... )
-    >>> # Create a new grid from the input grid, set the projection to
-    >>> # Mercator, and set inverse to "True" to change from "geographic"
-    >>> # to "rectangular"
-    >>> new_grid = pygmt.grdproject(grid=grid, projection="M10c", inverse=True)
+    >>> region = [10, 30, 15, 25]
+    >>> grid = pygmt.datasets.load_earth_relief(resolution="30m", region=region)
+    >>> # Project the geographic gridded data onto a rectangular grid
+    >>> new_grid = pygmt.grdproject(grid=grid, projection="M10c", region=region)
     """
     if kwargs.get("J") is None:
         raise GMTInvalidInput("The projection must be specified.")

pygmt/src/grdvolume.py

@@ -94,11 +94,11 @@ def grdvolume(grid, output_type="pandas", outfile=None, **kwargs):
     ... )
     >>> print(output_dataframe)
         0             1             2           3
-    0  200  2.318187e+12  8.533727e+14  368.120722
-    1  250  2.272471e+12  7.383936e+14  324.929840
-    2  300  2.162074e+12  6.273066e+14  290.141086
-    3  350  2.018302e+12  5.222640e+14  258.764032
-    4  400  1.857370e+12  4.252699e+14  228.963499
+    0  200  2.323600e+12  8.523815e+14  366.836554
+    1  250  2.275864e+12  7.371655e+14  323.905736
+    2  300  2.166707e+12  6.258570e+14  288.851699
+    3  350  2.019284e+12  5.207732e+14  257.899955
+    4  400  1.870441e+12  4.236191e+14  226.480847
     """
     output_type = validate_output_table_type(output_type, outfile=outfile)