Source code for launch_tools.csv_tools

 1"""Contains snippets that can can import/export vehicle positions from/to csv files."""
 2from __future__ import annotations
 3
 4# pyright: reportUnknownMemberType=none
 5# pyright: reportUnknownVariableType=information
 6from typing import TYPE_CHECKING
 7if TYPE_CHECKING:
 8    from os import PathLike
 9
10import carla
11import pandas as pd
12
13__all__ = [
14    "csv_to_transformations",
15    "transform_to_pandas",
16    "vehicle_location_to_dataframe",
17]
18
19# A dataframe template to store the locations of vehicles
20LOC_DF = pd.DataFrame(columns=["x", "y", "z", "pitch", "yaw", "roll"])
21
22# -----------------------------------
23
24

[docs]
25def transform_to_pandas(transform: carla.Transform) -> pd.Series[float]:
26    """
27    Format a :py:class:`carla.Transform` object to a :py:class:`pandas.Series`.
28    """
29    loc = transform.location
30    rot = transform.rotation
31    return pd.Series({"x": loc.x, "y": loc.y, "z": loc.z,
32                   "pitch": rot.pitch, "yaw": rot.yaw, "roll": rot.roll})

33
34

[docs]
35def vehicle_location_to_dataframe(vehicles: list[carla.Actor]) -> pd.DataFrame:
36    """
37    Exports the locations of vehicles to a :py:class:`pandas.Dataframe`.
38    """
39    df = LOC_DF.copy()
40    for i, v in enumerate(vehicles):
41        df.loc[i] = transform_to_pandas(v.get_transform())
42    return df

43
44

[docs]
45def csv_to_transformations(path: str | PathLike[str]) -> list[carla.Transform]:
46    """
47    Read a csv file and return a list of Transform objects.
48    Expected columns: :code:`x, y, z, pitch, yaw, roll`.
49    """
50    df = pd.read_csv(path)  # pyright: ignore
51    transformations: list[carla.Transform] = []
52    for _, data in df.iterrows():  # pyright: ignore
53        loc = carla.Location(data.x, data.y, data.z)  # type: ignore[attr-defined]
54        rot = carla.Rotation(pitch=data.pitch, yaw=data.yaw, roll=data.roll)  # type: ignore[attr-defined]
55        t = carla.Transform(loc, rot)
56        transformations.append(t)
57    return transformations