pygmt.x2sys_cross: Refactor to use virtualfiles for output tables [BREAKING CHANGE: Dummy times in 3rd and 4th columns now have np.timedelta64 type]

pygmt/src/x2sys_cross.py

@@ -5,13 +5,12 @@
 import contextlib
 import os
 from pathlib import Path
+from typing import Any
 
 import pandas as pd
-from packaging.version import Version
 from pygmt.clib import Session
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.helpers import (
-    GMTTempFile,
     build_arg_list,
     data_kind,
     fmt_docstring,
@@ -71,7 +70,11 @@ def tempfile_from_dftrack(track, suffix):
     Z="trackvalues",
 )
 @kwargs_to_strings(R="sequence")
-def x2sys_cross(tracks=None, outfile=None, **kwargs):
+def x2sys_cross(
+    tracks=None,
+    outfile: str | None = None,
+    **kwargs,
+):
     r"""
     Calculate crossovers between track data files.
 
@@ -102,11 +105,7 @@ def x2sys_cross(tracks=None, outfile=None, **kwargs):
         set it will default to $GMT_SHAREDIR/x2sys]. (**Note**: MGD77 files
         will also be looked for via $MGD77_HOME/mgd77_paths.txt and .gmt
         files will be searched for via $GMT_SHAREDIR/mgg/gmtfile_paths).
-
-    outfile : str
-        Optional. The file name for the output ASCII txt file to store the
-        table in.
-
+    {outfile}
     tag : str
         Specify the x2sys TAG which identifies the attributes of this data
         type.
@@ -183,68 +182,56 @@ def x2sys_cross(tracks=None, outfile=None, **kwargs):
 
     Returns
     -------
-    crossover_errors : :class:`pandas.DataFrame` or None
-        Table containing crossover error information.
-        Return type depends on whether the ``outfile`` parameter is set:
-
-        - :class:`pandas.DataFrame` with (x, y, ..., etc) if ``outfile`` is not
-          set
-        - None if ``outfile`` is set (track output will be stored in the set in
-          ``outfile``)
+    crossover_errors
+        Table containing crossover error information. A :class:`pandas.DataFrame` object
+        is returned if ``outfile`` is not set, otherwise ``None`` is returned and output
+        will be stored in file set by ``outfile``.
     """
-    with Session() as lib:
-        file_contexts = []
-        for track in tracks:
-            kind = data_kind(track)
-            if kind == "file":
+    # Determine output type based on 'outfile' parameter
+    output_type = "pandas" if outfile is None else "file"
+
+    file_contexts: list[contextlib.AbstractContextManager[Any]] = []
+    for track in tracks:
+        match data_kind(track):
+            case "file":
                 file_contexts.append(contextlib.nullcontext(track))
-            elif kind == "matrix":
+            case "matrix":
                 # find suffix (-E) of trackfiles used (e.g. xyz, csv, etc) from
                 # $X2SYS_HOME/TAGNAME/TAGNAME.tag file
-                lastline = (
-                    Path(os.environ["X2SYS_HOME"], kwargs["T"], f"{kwargs['T']}.tag")
-                    .read_text(encoding="utf8")
-                    .strip()
-                    .split("\n")[-1]
-                )  # e.g. "-Dxyz -Etsv -I1/1"
+                tagfile = Path(
+                    os.environ["X2SYS_HOME"], kwargs["T"], f"{kwargs['T']}.tag"
+                )
+                # Last line is like "-Dxyz -Etsv -I1/1"
+                lastline = tagfile.read_text().splitlines()[-1]
                 for item in sorted(lastline.split()):  # sort list alphabetically
                     if item.startswith(("-E", "-D")):  # prefer -Etsv over -Dxyz
                         suffix = item[2:]  # e.g. tsv (1st choice) or xyz (2nd choice)
 
                 # Save pandas.DataFrame track data to temporary file
                 file_contexts.append(tempfile_from_dftrack(track=track, suffix=suffix))
-            else:
+            case _:
                 raise GMTInvalidInput(f"Unrecognized data type: {type(track)}")
 
-        with GMTTempFile(suffix=".txt") as tmpfile:
+    with Session() as lib:
+        with lib.virtualfile_out(kind="dataset", fname=outfile) as vouttbl:
             with contextlib.ExitStack() as stack:
                 fnames = [stack.enter_context(c) for c in file_contexts]
-                if outfile is None:
-                    outfile = tmpfile.name
                 lib.call_module(
                     module="x2sys_cross",
-                    args=build_arg_list(kwargs, infile=fnames, outfile=outfile),
-                )
-
-            # Read temporary csv output to a pandas table
-            if outfile == tmpfile.name:  # if outfile isn't set, return pd.DataFrame
-                # Read the tab-separated ASCII table
-                date_format_kwarg = (
-                    {"date_format": "ISO8601"}
-                    if Version(pd.__version__) >= Version("2.0.0")
-                    else {}
+                    args=build_arg_list(kwargs, infile=fnames, outfile=vouttbl),
                 )
-                table = pd.read_csv(
-                    tmpfile.name,
-                    sep="\t",
-                    header=2,  # Column names are on 2nd row
-                    comment=">",  # Skip the 3rd row with a ">"
-                    parse_dates=[2, 3],  # Datetimes on 3rd and 4th column
-                    **date_format_kwarg,  # Parse dates in ISO8601 format on pandas>=2
+                result = lib.virtualfile_to_dataset(
+                    vfname=vouttbl, output_type=output_type, header=2
                 )
-                # Remove the "# " from "# x" in the first column
-                table = table.rename(columns={table.columns[0]: table.columns[0][2:]})
-            elif outfile != tmpfile.name:  # if outfile is set, output in outfile only
-                table = None
 
-    return table
+                # Convert 3rd and 4th columns to datetime or timedelta.
+                # These two columns have names "t_1"/"t_2" or "i_1"/"i_2".
+                # "t_1"/"t_2" means they are absolute datetimes.
+                # "i_1"/"i_2" means they are dummy times relative to unix epoch.
+                if output_type == "pandas":
+                    t_or_i = result.columns[2][0]
+                    to_func = {"t": pd.to_datetime, "i": pd.to_timedelta}[t_or_i]
+                    result[result.columns[2:4]] = result[result.columns[2:4]].apply(
+                        to_func, unit="s"
+                    )
+                return result

pygmt/tests/test_x2sys_cross.py

@@ -50,7 +50,11 @@ def test_x2sys_cross_input_file_output_file():
         x2sys_init(tag=tag, fmtfile="xyz", force=True)
         outfile = tmpdir_p / "tmp_coe.txt"
         output = x2sys_cross(
-            tracks=["@tut_ship.xyz"], tag=tag, coe="i", outfile=outfile
+            tracks=["@tut_ship.xyz"],
+            tag=tag,
+            coe="i",
+            outfile=outfile,
+            output_type="file",
         )
 
         assert output is None  # check that output is None since outfile is set
@@ -98,8 +102,8 @@ def test_x2sys_cross_input_dataframe_output_dataframe(tracks):
         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_
+        assert output.dtypes["i_1"].type == np.timedelta64
+        assert output.dtypes["i_2"].type == np.timedelta64
 
 
 @pytest.mark.usefixtures("mock_x2sys_home")
@@ -159,8 +163,8 @@ def test_x2sys_cross_input_dataframe_with_nan(tracks):
         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_
+        assert output.dtypes["i_1"].type == np.timedelta64
+        assert output.dtypes["i_2"].type == np.timedelta64
 
 
 @pytest.mark.usefixtures("mock_x2sys_home")