pygmt.grdtrack: Add 'output_type' parameter for output in pandas/numpy/file formats

pygmt/src/grdtrack.py

@@ -2,15 +2,18 @@
 grdtrack - Sample grids at specified (x,y) locations.
 """
 
+from typing import Literal
+
+import numpy as np
 import pandas as pd
 from pygmt.clib import Session
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.helpers import (
-    GMTTempFile,
     build_arg_string,
     fmt_docstring,
     kwargs_to_strings,
     use_alias,
+    validate_output_table_type,
 )
 
 __doctest_skip__ = ["grdtrack"]
@@ -44,7 +47,14 @@
     w="wrap",
 )
 @kwargs_to_strings(R="sequence", S="sequence", i="sequence_comma", o="sequence_comma")
-def grdtrack(grid, points=None, newcolname=None, outfile=None, **kwargs):
+def grdtrack(
+    grid,
+    points=None,
+    output_type: Literal["pandas", "numpy", "file"] = "pandas",
+    outfile: str | None = None,
+    newcolname=None,
+    **kwargs,
+) -> pd.DataFrame | np.ndarray | None:
     r"""
     Sample grids at specified (x,y) locations.
 
@@ -73,15 +83,12 @@ def grdtrack(grid, points=None, newcolname=None, outfile=None, **kwargs):
     points : str, {table-like}
         Pass in either a file name to an ASCII data table, a 2-D
         {table-classes}.
-
+    {output_type}
+    {outfile}
     newcolname : str
         Required if ``points`` is a :class:`pandas.DataFrame`. The name for the
         new column in the track :class:`pandas.DataFrame` table where the
         sampled values will be placed.
-
-    outfile : str
-        The file name for the output ASCII file.
-
     resample : str
         **f**\|\ **p**\|\ **m**\|\ **r**\|\ **R**\ [**+l**]
         For track resampling (if ``crossprofile`` or ``profile`` are set) we
@@ -258,13 +265,12 @@ def grdtrack(grid, points=None, newcolname=None, outfile=None, **kwargs):
 
     Returns
     -------
-    track: pandas.DataFrame or None
-        Return type depends on whether the ``outfile`` parameter is set:
+    ret
+        Return type depends on ``outfile`` and ``output_type``:
 
-        - :class:`pandas.DataFrame` table with (x, y, ..., newcolname) if
-          ``outfile`` is not set
-        - None if ``outfile`` is set (track output will be stored in file set
-          by ``outfile``)
+        - None if ``outfile`` is set (output will be stored in file set by ``outfile``)
+        - :class:`pandas.DataFrame` or :class:`numpy.ndarray` if ``outfile`` is not set
+          (depends on ``output_type``)
 
     Example
     -------
@@ -291,30 +297,27 @@ def grdtrack(grid, points=None, newcolname=None, outfile=None, **kwargs):
     if hasattr(points, "columns") and newcolname is None:
         raise GMTInvalidInput("Please pass in a str to 'newcolname'")
 
-    with GMTTempFile(suffix=".csv") as tmpfile:
-        with Session() as lib:
-            with (
-                lib.virtualfile_in(check_kind="raster", data=grid) as vingrd,
-                lib.virtualfile_in(
-                    check_kind="vector", data=points, required_data=False
-                ) as vintbl,
-            ):
-                kwargs["G"] = vingrd
-                if outfile is None:  # Output to tmpfile if outfile is not set
-                    outfile = tmpfile.name
-                lib.call_module(
-                    module="grdtrack",
-                    args=build_arg_string(kwargs, infile=vintbl, outfile=outfile),
-                )
+    output_type = validate_output_table_type(output_type, outfile=outfile)
 
-        # Read temporary csv output to a pandas table
-        if outfile == tmpfile.name:  # if user did not set outfile, return pd.DataFrame
-            try:
-                column_names = [*points.columns.to_list(), newcolname]
-                result = pd.read_csv(tmpfile.name, sep="\t", names=column_names)
-            except AttributeError:  # 'str' object has no attribute 'columns'
-                result = pd.read_csv(tmpfile.name, sep="\t", header=None, comment=">")
-        elif outfile != tmpfile.name:  # return None if outfile set, output in outfile
-            result = None
+    column_names = None
+    if output_type == "pandas" and isinstance(points, pd.DataFrame):
+        column_names = [*points.columns.to_list(), newcolname]
 
-    return result
+    with Session() as lib:
+        with (
+            lib.virtualfile_in(check_kind="raster", data=grid) as vingrd,
+            lib.virtualfile_in(
+                check_kind="vector", data=points, required_data=False
+            ) as vintbl,
+            lib.virtualfile_out(kind="dataset", fname=outfile) as vouttbl,
+        ):
+            kwargs["G"] = vingrd
+            lib.call_module(
+                module="grdtrack",
+                args=build_arg_string(kwargs, infile=vintbl, outfile=vouttbl),
+            )
+        return lib.virtualfile_to_dataset(
+            output_type=output_type,
+            vfname=vouttbl,
+            column_names=column_names,
+        )