pygmt.filter1d: Improve performance by getting rid of temporary files

Author: seisman

pygmt/src/filter1d.py

@@ -2,11 +2,11 @@
 filter1d - Time domain filtering of 1-D data tables
 """
 
-import pandas as pd
+from typing import Literal
+
 from pygmt.clib import Session
 from pygmt.exceptions import GMTInvalidInput
 from pygmt.helpers import (
-    GMTTempFile,
     build_arg_string,
     fmt_docstring,
     use_alias,
@@ -20,7 +20,12 @@
     F="filter_type",
     N="time_col",
 )
-def filter1d(data, output_type="pandas", outfile=None, **kwargs):
+def filter1d(
+    data,
+    output_type: Literal["pandas", "numpy", "file"] = "pandas",
+    outfile: str | None = None,
+    **kwargs,
+):
     r"""
     Time domain filtering of 1-D data tables.
 
@@ -38,6 +43,14 @@ def filter1d(data, output_type="pandas", outfile=None, **kwargs):
 
     Parameters
     ----------
+    output_type
+        Desired output type of the result data.
+        - ``pandas`` will return a :class:`pandas.DataFrame` object.
+        - ``numpy`` will return a :class:`numpy.ndarray` object.
+        - ``file`` will save the result to the file given by the ``outfile`` parameter.
+    outfile
+        File name for saving the result data. Required if ``output_type`` is ``"file"``.
+        If specified, ``output_type`` will be forced to be ``"file"``.
     filter_type : str
         **type**\ *width*\ [**+h**].
         Set the filter **type**. Choose among convolution and non-convolution
@@ -91,48 +104,26 @@ def filter1d(data, output_type="pandas", outfile=None, **kwargs):
         left-most column is 0, while the right-most is (*n_cols* - 1)
         [Default is ``0``].
 
-    output_type : str
-        Determine the format the xyz data will be returned in [Default is
-        ``pandas``]:
-
-            - ``numpy`` - :class:`numpy.ndarray`
-            - ``pandas``- :class:`pandas.DataFrame`
-            - ``file`` - ASCII file (requires ``outfile``)
-    outfile : str
-        The file name for the output ASCII file.
-
     Returns
     -------
-    ret : pandas.DataFrame or numpy.ndarray or None
+    ret
         Return type depends on ``outfile`` and ``output_type``:
-
-        - 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`` [Default is
-          :class:`pandas.DataFrame`])
+        - 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``)
     """
     if kwargs.get("F") is None:
         raise GMTInvalidInput("Pass a required argument to 'filter_type'.")
 
     output_type = validate_output_table_type(output_type, outfile=outfile)
 
-    with GMTTempFile() as tmpfile:
-        with Session() as lib:
-            with lib.virtualfile_in(check_kind="vector", data=data) as vintbl:
-                if outfile is None:
-                    outfile = tmpfile.name
-                lib.call_module(
-                    module="filter1d",
-                    args=build_arg_string(kwargs, infile=vintbl, outfile=outfile),
-                )
-
-        # Read temporary csv output to a pandas table
-        if outfile == tmpfile.name:  # if user did not set outfile, return pd.DataFrame
-            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
-
-        if output_type == "numpy":
-            result = result.to_numpy()
-    return result
+    with Session() as lib:
+        with (
+            lib.virtualfile_in(check_kind="vector", data=data) as vintbl,
+            lib.virtualfile_out(kind="dataset", fname=outfile) as vouttbl,
+        ):
+            lib.call_module(
+                module="filter1d",
+                args=build_arg_string(kwargs, infile=vintbl, outfile=vouttbl),
+            )
+        return lib.virtualfile_to_dataset(output_type=output_type, vfname=vouttbl)

pygmt/tests/test_filter1d.py

@@ -2,15 +2,11 @@
 Test pygmt.filter1d.
 """
 
-from pathlib import Path
-
 import numpy as np
 import pandas as pd
 import pytest
 from pygmt import filter1d
 from pygmt.datasets import load_sample_data
-from pygmt.exceptions import GMTInvalidInput
-from pygmt.helpers import GMTTempFile
 
 
 @pytest.fixture(scope="module", name="data")
@@ -29,57 +25,6 @@ def test_filter1d_no_outfile(data):
     assert result.shape == (671, 2)
 
 
-def test_filter1d_file_output(data):
-    """
-    Test that filter1d returns a file output when it is specified.
-    """
-    with GMTTempFile(suffix=".txt") as tmpfile:
-        result = filter1d(
-            data=data, filter_type="g5", outfile=tmpfile.name, output_type="file"
-        )
-        assert result is None  # return value is None
-        assert Path(tmpfile.name).stat().st_size > 0  # check that outfile exists
-
-
-def test_filter1d_invalid_format(data):
-    """
-    Test that filter1d fails with an incorrect format for output_type.
-    """
-    with pytest.raises(GMTInvalidInput):
-        filter1d(data=data, filter_type="g5", output_type="a")
-
-
-def test_filter1d_no_filter(data):
-    """
-    Test that filter1d fails with an argument is missing for filter.
-    """
-    with pytest.raises(GMTInvalidInput):
-        filter1d(data=data)
-
-
-def test_filter1d_no_outfile_specified(data):
-    """
-    Test that filter1d fails when outpput_type is set to 'file' but no output file name
-    is specified.
-    """
-    with pytest.raises(GMTInvalidInput):
-        filter1d(data=data, filter_type="g5", output_type="file")
-
-
-def test_filter1d_outfile_incorrect_output_type(data):
-    """
-    Test that filter1d raises a warning when an outfile filename is set but the
-    output_type is not set to 'file'.
-    """
-    with pytest.warns(RuntimeWarning):
-        with GMTTempFile(suffix=".txt") as tmpfile:
-            result = filter1d(
-                data=data, filter_type="g5", outfile=tmpfile.name, output_type="numpy"
-            )
-            assert result is None  # return value is None
-            assert Path(tmpfile.name).stat().st_size > 0  # check that outfile exists
-
-
 @pytest.mark.benchmark
 def test_filter1d_format(data):
     """