Merge branch 'main' into static-earth-relief/grdvolume

Author: seisman

examples/gallery/histograms/blockm.py

@@ -10,7 +10,7 @@
 import pygmt
 
 # Load sample data
-data = pygmt.datasets.load_japan_quakes()
+data = pygmt.datasets.load_sample_data(name="japan_quakes")
 # Select only needed columns
 data = data[["longitude", "latitude", "depth_km"]]
 

examples/gallery/histograms/rose.py

@@ -10,7 +10,7 @@
 
 # Load sample compilation of fracture lengths and azimuth as
 # hypothetically digitized from geological maps
-data = pygmt.datasets.load_fractures_compilation()
+data = pygmt.datasets.load_sample_data(name="fractures")
 
 fig = pygmt.Figure()
 

examples/gallery/images/track_sampling.py

@@ -18,7 +18,7 @@
 
 # Load sample grid and point datasets
 grid = pygmt.datasets.load_earth_relief()
-points = pygmt.datasets.load_ocean_ridge_points()
+points = pygmt.datasets.load_sample_data(name="ocean_ridge_points")
 # Sample the bathymetry along the world's ocean ridges at specified track
 # points
 track = pygmt.grdtrack(points=points, grid=grid, newcolname="bathymetry")

examples/tutorials/basics/plot.py

@@ -14,10 +14,10 @@
 
 ###############################################################################
 # For example, let's load the sample dataset of tsunami generating earthquakes
-# around Japan (:func:`pygmt.datasets.load_japan_quakes`). The data is loaded
-# as a :class:`pandas.DataFrame`.
+# around Japan (:func:`pygmt.datasets.load_sample_data(name="japan_quakes")`).
+# The data is loaded as a :class:`pandas.DataFrame`.
 
-data = pygmt.datasets.load_japan_quakes()
+data = pygmt.datasets.load_sample_data(name="japan_quakes")
 
 # Set the region for the plot to be slightly larger than the data bounds.
 region = [

pygmt/src/blockm.py

@@ -147,6 +147,18 @@ def blockmean(data=None, x=None, y=None, z=None, outfile=None, **kwargs):
           is not set.
         - None if ``outfile`` is set (filtered output will be stored in file
           set by ``outfile``).
+
+    Example
+    -------
+    >>> import pygmt  # doctest: +SKIP
+    >>> # Load a table of ship observations of bathymetry off Baja California
+    >>> data = pygmt.datasets.load_sample_data(
+    ...     name="bathymetry"
+    ... )  # doctest: +SKIP
+    >>> # Calculate block mean values within 5 by 5 minute bins
+    >>> data_bmean = pygmt.blockmean(
+    ...     data=data, region=[245, 255, 20, 30], spacing="5m"
+    ... )  # doctest: +SKIP
     """
     return _blockm(
         block_method="blockmean", data=data, x=x, y=y, z=z, outfile=outfile, **kwargs
@@ -225,6 +237,18 @@ def blockmedian(data=None, x=None, y=None, z=None, outfile=None, **kwargs):
           is not set.
         - None if ``outfile`` is set (filtered output will be stored in file
           set by ``outfile``).
+
+    Example
+    -------
+    >>> import pygmt  # doctest: +SKIP
+    >>> # Load a table of ship observations of bathymetry off Baja California
+    >>> data = pygmt.datasets.load_sample_data(
+    ...     name="bathymetry"
+    ... )  # doctest: +SKIP
+    >>> # Calculate block median values within 5 by 5 minute bins
+    >>> data_bmedian = pygmt.blockmedian(
+    ...     data=data, region=[245, 255, 20, 30], spacing="5m"
+    ... )  # doctest: +SKIP
     """
     return _blockm(
         block_method="blockmedian", data=data, x=x, y=y, z=z, outfile=outfile, **kwargs
@@ -303,6 +327,18 @@ def blockmode(data=None, x=None, y=None, z=None, outfile=None, **kwargs):
           is not set.
         - None if ``outfile`` is set (filtered output will be stored in file
           set by ``outfile``).
+
+    Example
+    -------
+    >>> import pygmt  # doctest: +SKIP
+    >>> # Load a table of ship observations of bathymetry off Baja California
+    >>> data = pygmt.datasets.load_sample_data(
+    ...     name="bathymetry"
+    ... )  # doctest: +SKIP
+    >>> # Calculate block mode values within 5 by 5 minute bins
+    >>> data_bmode = pygmt.blockmode(
+    ...     data=data, region=[245, 255, 20, 30], spacing="5m"
+    ... )  # doctest: +SKIP
     """
     return _blockm(
         block_method="blockmode", data=data, x=x, y=y, z=z, outfile=outfile, **kwargs

pygmt/tests/test_grdcut.py

@@ -1,23 +1,29 @@
 """
 Tests for grdcut.
 """
-import os
-
 import numpy as np
 import pytest
 import xarray as xr
 from pygmt import grdcut, load_dataarray
-from pygmt.datasets import load_earth_relief
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.helpers import GMTTempFile
+from pygmt.helpers.testing import load_static_earth_relief
 
 
 @pytest.fixture(scope="module", name="grid")
 def fixture_grid():
     """
     Load the grid data from the sample earth_relief file.
     """
-    return load_earth_relief(registration="pixel")
+    return load_static_earth_relief()
+
+
+@pytest.fixture(scope="module", name="region")
+def fixture_region():
+    """
+    Set the data region.
+    """
+    return [-53, -49, -20, -17]
 
 
 @pytest.fixture(scope="module", name="expected_grid")
@@ -27,55 +33,31 @@ def fixture_grid_result():
     """
     return xr.DataArray(
         data=[
-            [-5069.5, -5105.0, -4937.0, -4708.0],
-            [-4115.5, -4996.0, -4762.0, -4599.0],
-            [-656.0, -160.0, -3484.5, -3897.5],
+            [446.5, 481.5, 439.5, 553.0],
+            [757.0, 570.5, 538.5, 524.0],
+            [796.0, 886.0, 571.5, 638.5],
         ],
-        coords=dict(lon=[-2.5, -1.5, -0.5, 0.5], lat=[2.5, 3.5, 4.5]),
+        coords=dict(lon=[-52.5, -51.5, -50.5, -49.5], lat=[-19.5, -18.5, -17.5]),
         dims=["lat", "lon"],
     )
 
 
-def test_grdcut_file_in_file_out(expected_grid):
-    """
-    grdcut an input grid file, and output to a grid file.
-    """
-    with GMTTempFile(suffix=".nc") as tmpfile:
-        result = grdcut("@earth_relief_01d", outgrid=tmpfile.name, region=[-3, 1, 2, 5])
-        assert result is None  # return value is None
-        assert os.path.exists(path=tmpfile.name)  # check that outgrid exists
-        temp_grid = load_dataarray(tmpfile.name)
-        xr.testing.assert_allclose(a=temp_grid, b=expected_grid)
-
-
-def test_grdcut_file_in_dataarray_out(expected_grid):
-    """
-    grdcut an input grid file, and output as DataArray.
-    """
-    outgrid = grdcut("@earth_relief_01d", region=[-3, 1, 2, 5])
-    assert isinstance(outgrid, xr.DataArray)
-    assert outgrid.gmt.registration == 1  # Pixel registration
-    assert outgrid.gmt.gtype == 1  # Geographic type
-    # check information of the output grid
-    xr.testing.assert_allclose(a=outgrid, b=expected_grid)
-
-
-def test_grdcut_dataarray_in_file_out(grid, expected_grid):
+def test_grdcut_dataarray_in_file_out(grid, expected_grid, region):
     """
     grdcut an input DataArray, and output to a grid file.
     """
     with GMTTempFile(suffix=".nc") as tmpfile:
-        result = grdcut(grid, outgrid=tmpfile.name, region=[-3, 1, 2, 5])
+        result = grdcut(grid, outgrid=tmpfile.name, region=region)
         assert result is None  # grdcut returns None if output to a file
         temp_grid = load_dataarray(tmpfile.name)
         xr.testing.assert_allclose(a=temp_grid, b=expected_grid)
 
 
-def test_grdcut_dataarray_in_dataarray_out(grid, expected_grid):
+def test_grdcut_dataarray_in_dataarray_out(grid, expected_grid, region):
     """
     grdcut an input DataArray, and output as DataArray.
     """
-    outgrid = grdcut(grid, region=[-3, 1, 2, 5])
+    outgrid = grdcut(grid, region=region)
     assert isinstance(outgrid, xr.DataArray)
     xr.testing.assert_allclose(a=outgrid, b=expected_grid)
 

pygmt/tests/test_grdfill.py

@@ -7,20 +7,20 @@
 import pytest
 import xarray as xr
 from pygmt import grdfill, load_dataarray
-from pygmt.datasets import load_earth_relief
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.helpers import GMTTempFile
+from pygmt.helpers.testing import load_static_earth_relief
 
 
 @pytest.fixture(scope="module", name="grid")
 def fixture_grid():
     """
-    Load the grid data from the sample earth_relief file and set value(s) to
-    NaN.
+    Load the grid data from the static_earth_relief file and set value(s) to
+    NaN and inf.
     """
-    grid = load_earth_relief(registration="pixel", region=[125, 130, -25, -20])
-    grid[2:4, 1:3] = np.nan
-    grid[0:2, 2:4] = np.inf
+    grid = load_static_earth_relief()
+    grid[3:6, 3:5] = np.nan
+    grid[6:8, 2:4] = np.inf
     return grid
 
 
@@ -31,15 +31,39 @@ def fixture_grid_result():
     """
     return xr.DataArray(
         data=[
-            [442.5, 439.0, np.inf, np.inf, 508.0],
-            [393.0, 364.5, np.inf, np.inf, 506.5],
-            [362.0, 20.0, 20.0, 373.5, 402.5],
-            [321.5, 20.0, 20.0, 356.0, 422.5],
-            [282.5, 318.0, 326.5, 379.5, 383.5],
+            [347.5, 344.5, 386.0, 640.5, 617.0, 579.0, 646.5, 671.0],
+            [383.0, 284.5, 344.5, 394.0, 491.0, 556.5, 578.5, 618.5],
+            [373.0, 367.5, 349.0, 352.5, 419.5, 428.0, 570.0, 667.5],
+            [557.0, 435.0, 385.5, 20.0, 20.0, 496.0, 519.5, 833.5],
+            [561.5, 539.0, 446.5, 20.0, 20.0, 553.0, 726.5, 981.0],
+            [310.0, 521.5, 757.0, 20.0, 20.0, 524.0, 686.5, 794.0],
+            [521.5, 682.5, np.inf, np.inf, 571.5, 638.5, 739.5, 881.5],
+            [308.0, 595.5, np.inf, np.inf, 580.0, 770.0, 927.0, 920.0],
+            [601.0, 526.5, 535.0, 299.0, 398.5, 645.0, 797.5, 964.0],
+            [494.5, 488.5, 357.0, 254.5, 286.0, 484.5, 653.5, 930.0],
+            [450.5, 395.5, 366.0, 248.0, 250.0, 354.5, 550.0, 797.5],
+            [345.5, 320.0, 335.0, 292.0, 207.5, 247.0, 325.0, 346.5],
+            [349.0, 313.0, 325.5, 247.0, 191.0, 225.0, 260.0, 452.5],
+            [347.5, 331.5, 309.0, 282.0, 190.0, 208.0, 299.5, 348.0],
         ],
         coords=dict(
-            lon=[125.5, 126.5, 127.5, 128.5, 129.5],
-            lat=[-24.5, -23.5, -22.5, -21.5, -20.5],
+            lon=[-54.5, -53.5, -52.5, -51.5, -50.5, -49.5, -48.5, -47.5],
+            lat=[
+                -23.5,
+                -22.5,
+                -21.5,
+                -20.5,
+                -19.5,
+                -18.5,
+                -17.5,
+                -16.5,
+                -15.5,
+                -14.5,
+                -13.5,
+                -12.5,
+                -11.5,
+                -10.5,
+            ],
         ),
         dims=["lat", "lon"],
     )