Allow passing in pandas dataframes to x2sys_cross

pygmt/tests/test_x2sys_cross.py

@@ -31,7 +31,8 @@ def fixture_tracks():
     Load track data from the sample bathymetry file
     """
     dataframe = load_sample_bathymetry()
-    return [dataframe.query(expr="bathymetry > -20")]  # reduce size of dataset
+    dataframe.columns = ["x", "y", "z"]  # longitude, latitude, bathymetry
+    return [dataframe.query(expr="z > -20")]  # reduce size of dataset
 
 
 def test_x2sys_cross_input_file_output_file(mock_x2sys_home):
@@ -76,25 +77,57 @@ def test_x2sys_cross_input_file_output_dataframe(mock_x2sys_home):
 def test_x2sys_cross_input_dataframe_output_dataframe(mock_x2sys_home, tracks):
     """
     Run x2sys_cross by passing in one dataframe, and output external crossovers
-    to a pandas.DataFrame. Not actually implemented yet, wait for
-    https://github.com/GenericMappingTools/gmt/issues/3717
+    to a pandas.DataFrame.
     """
     with TemporaryDirectory(prefix="X2SYS", dir=os.getcwd()) as tmpdir:
         tag = os.path.basename(tmpdir)
         x2sys_init(tag=tag, fmtfile="xyz", force=True)
 
-        with pytest.raises(NotImplementedError):
-            _ = x2sys_cross(tracks=tracks, tag=tag, coe="i", verbose="i")
+        output = x2sys_cross(tracks=tracks, tag=tag, coe="i", verbose="i")
 
-        # assert isinstance(output, pd.DataFrame)
-        # assert output.shape == (4, 12)
-        # columns = list(output.columns)
-        # assert columns[:6] == ["x", "y", "t_1", "t_2", "dist_1", "dist_2"]
-        # assert columns[6:] == ["head_1","head_2","vel_1","vel_2","z_X","z_M"]
-        # assert output.dtypes["t_1"].type == np.datetime64
-        # assert output.dtypes["t_2"].type == np.datetime64
+        assert isinstance(output, pd.DataFrame)
+        assert output.shape == (14, 12)
+        columns = list(output.columns)
+        assert columns[:6] == ["x", "y", "i_1", "i_2", "dist_1", "dist_2"]
+        assert columns[6:] == ["head_1", "head_2", "vel_1", "vel_2", "z_X", "z_M"]
+        assert output.dtypes["i_1"].type == np.object_
+        assert output.dtypes["i_2"].type == np.object_
+
+    return output
 
-    # return output
+
+def test_x2sys_cross_input_two_dataframes(mock_x2sys_home):
+    """
+    Run x2sys_cross by passing in two pandas.DataFrame tables with a time
+    column, and output external crossovers to a pandas.DataFrame
+    """
+    with TemporaryDirectory(prefix="X2SYS", dir=os.getcwd()) as tmpdir:
+        tag = os.path.basename(tmpdir)
+        x2sys_init(
+            tag=tag, fmtfile="xyz", suffix="xyzt", units=["de", "se"], force=True
+        )
+
+        # Add a time row to the x2sys fmtfile
+        with open(file=os.path.join(tmpdir, "xyz.fmt"), mode="a") as fmtfile:
+            fmtfile.write("time\ta\tN\t0\t1\t0\t%g\n")
+
+        # Create pandas.DataFrame track tables
+        tracks = []
+        for i in range(2):
+            np.random.seed(seed=i)
+            track = pd.DataFrame(data=np.random.rand(10, 3), columns=("x", "y", "z"))
+            track["time"] = pd.date_range(start=f"2020-{i}1-01", periods=10, freq="ms")
+            tracks.append(track)
+
+        output = x2sys_cross(tracks=tracks, tag=tag, coe="e", verbose="i")
+
+        assert isinstance(output, pd.DataFrame)
+        assert output.shape == (30, 12)
+        columns = list(output.columns)
+        assert columns[:6] == ["x", "y", "t_1", "t_2", "dist_1", "dist_2"]
+        assert columns[6:] == ["head_1", "head_2", "vel_1", "vel_2", "z_X", "z_M"]
+        assert output.dtypes["t_1"].type == np.datetime64
+        assert output.dtypes["t_2"].type == np.datetime64
 
 
 def test_x2sys_cross_input_two_filenames(mock_x2sys_home):
@@ -131,7 +164,7 @@ def test_x2sys_cross_invalid_tracks_input_type(tracks):
     Run x2sys_cross using tracks input that is not a pandas.DataFrame (matrix)
     or str (file) type, which would raise a GMTInvalidInput error.
     """
-    invalid_tracks = tracks[0].to_xarray().bathymetry
+    invalid_tracks = tracks[0].to_xarray().z
     assert data_kind(invalid_tracks) == "grid"
     with pytest.raises(GMTInvalidInput):
         x2sys_cross(tracks=[invalid_tracks])

pygmt/x2sys.py

@@ -2,6 +2,9 @@
 GMT supplementary X2SYS module for crossover analysis.
 """
 import contextlib
+import os
+import re
+from pathlib import Path
 
 import pandas as pd
 
@@ -14,10 +17,30 @@
     dummy_context,
     fmt_docstring,
     kwargs_to_strings,
+    unique_name,
     use_alias,
 )
 
 
+@contextlib.contextmanager
+def tempfile_from_dftrack(track, suffix):
+    """
+    Saves a pandas.DataFrame track table to a temporary tab-separated ASCII
+    text file with a suffix (e.g. 'xyz').
+    """
+    try:
+        tmpfilename = f"track-{unique_name()[:7]}.{suffix}"
+        track.to_csv(
+            path_or_buf=tmpfilename,
+            sep="\t",
+            index=False,
+            date_format="%Y-%m-%dT%H:%M:%S.%fZ",
+        )
+        yield tmpfilename
+    finally:
+        os.remove(tmpfilename)
+
+
 @fmt_docstring
 @use_alias(
     D="fmtfile",
@@ -263,8 +286,23 @@ def x2sys_cross(tracks=None, outfile=None, **kwargs):
             if kind == "file":
                 file_contexts.append(dummy_context(track))
             elif kind == "matrix":
-                raise NotImplementedError(f"{type(track)} inputs are not supported yet")
-                # file_contexts.append(lib.virtualfile_from_matrix(track.values))
+                # find suffix (-E) of trackfiles used (e.g. xyz, csv, etc) from
+                # $X2SYS_HOME/TAGNAME/TAGNAME.tag file using regex search
+                lastline = (
+                    Path(os.environ["X2SYS_HOME"], kwargs["T"], f"{kwargs['T']}.tag")
+                    .read_text()
+                    .strip()
+                    .split("\n")[-1]
+                )  # e.g. "-Dxyz -Etsv -I1/1"
+                try:
+                    # 1st try to match file extension after -E
+                    suffix = re.search(pattern=r"-E(\S*)", string=lastline).group(1)
+                except AttributeError:  # 'NoneType' object has no attribute 'group'
+                    # 2nd try to match file extension after -D
+                    suffix = re.search(pattern=r"-D(\S*)", string=lastline).group(1)
+
+                # Save pandas.DataFrame track data to temporary file
+                file_contexts.append(tempfile_from_dftrack(track=track, suffix=suffix))
             else:
                 raise GMTInvalidInput(f"Unrecognized data type: {type(track)}")