feat: add list_pointcloud_topics function to retrieve PointCloud2 top…

…ics; update CHANGELOG and tests

CHANGELOG.rst

@@ -10,7 +10,10 @@ Unreleased
 
 Added
 ~~~~~~
+- list_pointcloud_topics at the package top level to list pointcloud2 topics
 - dask[dataframe] as a dependency for the CLI
+- livox test data
+
 
 0.10.0 - (2024-12-03)
 -------------

doc/sphinx/source/tutorial_notebooks/usage.ipynb

@@ -18,15 +18,13 @@
    "outputs": [],
    "source": [
     "import pointcloudset as pcs\n",
-    "\n",
-    "print(f\"package version: {pcs.__version__}\")\n",
     "from pathlib import Path\n",
-    "\n",
     "import matplotlib.pyplot as plt\n",
+    "import plotly.express as px\n",
     "\n",
-    "plt.rcParams[\"figure.figsize\"] = (20,10)\n",
+    "plt.rcParams[\"figure.figsize\"] = (20, 10)\n",
     "\n",
-    "import plotly.express as px\n",
+    "print(f\"package version: {pcs.__version__}\")\n",
     "\n",
     "%load_ext autoreload\n",
     "%autoreload 2\n",
@@ -37,14 +35,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Ignore the INFO messages, which comes from the rospy package.\n"
+    "## Reading a ROS file into the Dataset"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "testbag = Path().cwd().parent.joinpath(\"../../../tests/testdata/test.bag\")"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## Reading a ROS file into the Dataset"
+    "Lets check which pointcloud messages are there:"
    ]
   },
   {
@@ -53,7 +60,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testbag = Path().cwd().parent.joinpath(\"../../../tests/testdata/test.bag\")"
+    "topics = pcs.list_pointcloud_topics(testbag)\n",
+    "topics"
    ]
   },
   {
@@ -62,7 +70,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testset = pcs.Dataset.from_file(testbag,topic=\"/os1_cloud_node/points\",keep_zeros=False)"
+    "testset = pcs.Dataset.from_file(testbag, topic=topics[0], keep_zeros=False)"
    ]
   },
   {
@@ -190,7 +198,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "px.line(min_pointcloud,x=\"timestamp\", y=\"x min\")"
+    "px.line(min_pointcloud, x=\"timestamp\", y=\"x min\")"
    ]
   },
   {
@@ -232,7 +240,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testset.agg(\"min\",\"dataset\")"
+    "testset.agg(\"min\", \"dataset\")"
    ]
   },
   {
@@ -241,7 +249,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testset.agg([\"min\",\"max\",\"mean\"],\"point\")"
+    "testset.agg([\"min\", \"max\", \"mean\"], \"point\")"
    ]
   },
   {
@@ -250,7 +258,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testset.agg({\"x\":[\"max\",\"min\"]},\"point\")"
+    "testset.agg({\"x\": [\"max\", \"min\"]}, \"point\")"
    ]
   },
   {
@@ -259,7 +267,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "testset.agg({\"x\":\"max\"},\"point\")"
+    "testset.agg({\"x\": \"max\"}, \"point\")"
    ]
   },
   {
@@ -449,7 +457,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "newpointcloud = testpointcloud.limit(\"x\",-5,5).limit(\"intensity\",400,1000).filter(\"quantile\",\"reflectivity\", \">\",0.5)"
+    "newpointcloud = (\n",
+    "    testpointcloud.limit(\"x\", -5, 5).limit(\"intensity\", 400, 1000).filter(\"quantile\", \"reflectivity\", \">\", 0.5)\n",
+    ")"
    ]
   },
   {
@@ -481,7 +491,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "newpointcloud.plot(\"intensity\",hover_data=[\"range\"])"
+    "newpointcloud.plot(\"intensity\", hover_data=[\"range\"])"
    ]
   },
   {
@@ -500,7 +510,9 @@
    },
    "outputs": [],
    "source": [
-    "plane = newpointcloud.plane_segmentation(distance_threshold= 0.01,ransac_n= 3,num_iterations= 50, return_plane_model=True)\n",
+    "plane = newpointcloud.plane_segmentation(\n",
+    "    distance_threshold=0.01, ransac_n=3, num_iterations=50, return_plane_model=True\n",
+    ")\n",
     "print(len(plane))"
    ]
   },
@@ -530,9 +542,9 @@
    },
    "outputs": [],
    "source": [
-    "clusters = newpointcloud.get_cluster(eps=0.5, min_points= 10)\n",
-    "cluster1 = newpointcloud.take_cluster(1,clusters)\n",
-    "cluster2 = newpointcloud.take_cluster(2,clusters)\n",
+    "clusters = newpointcloud.get_cluster(eps=0.5, min_points=10)\n",
+    "cluster1 = newpointcloud.take_cluster(1, clusters)\n",
+    "cluster2 = newpointcloud.take_cluster(2, clusters)\n",
     "print(len(cluster1))\n",
     "print(len(cluster2))"
    ]
@@ -552,7 +564,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "newpointcloud.plot(color=None, overlay={\"Cluster 1\": cluster1,\"Cluster 2\": cluster2}, hover_data=[\"intensity\"])"
+    "newpointcloud.plot(color=None, overlay={\"Cluster 1\": cluster1, \"Cluster 2\": cluster2}, hover_data=[\"intensity\"])"
    ]
   },
   {
@@ -570,7 +582,7 @@
    "outputs": [],
    "source": [
     "def isolate_target(frame: pcs.PointCloud) -> pcs.PointCloud:\n",
-    "    return frame.limit(\"x\",0,1).limit(\"y\",0,1)"
+    "    return frame.limit(\"x\", 0, 1).limit(\"y\", 0, 1)"
    ]
   },
   {
@@ -644,7 +656,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "result.agg({\"x difference\":\"max\"},\"pointcloud\")"
+    "result.agg({\"x difference\": \"max\"}, \"pointcloud\")"
    ]
   },
   {
@@ -656,13 +668,10 @@
   }
  ],
  "metadata": {
-  "interpreter": {
-   "hash": "5d20601a78b69ce1e830e7a32b8a0e9b424dfcbdd55b4b97e0f1a14444bda345"
-  },
   "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "base"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -674,7 +683,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.9"
+   "version": "3.11.10"
   }
  },
  "nbformat": 4,

pointcloudset/__init__.py

@@ -1,4 +1,11 @@
 from .dataset import Dataset
+from .io.dataset.topics import list_pointcloud_topics
 from .pointcloud import PointCloud
 
 __version__ = "0.10.0"
+
+__all__ = [
+    "Dataset",
+    "PointCloud",
+    "list_pointcloud_topics",
+]

pointcloudset/io/dataset/topics.py

@@ -0,0 +1,11 @@
+from pathlib import Path
+
+from rosbags.highlevel import AnyReader
+
+
+def list_pointcloud_topics(bagfile: Path) -> list[str]:
+    """Returns a list of all pointcloud topics in a ROS1 bagfile or a directory containing ROS2 mcap file."""
+    with AnyReader([bagfile]) as reader:
+        all_topics = reader.topics
+
+    return [k for k, v in all_topics.items() if v.msgtype == "sensor_msgs/msg/PointCloud2"]

tests/cli/test_rosbagconvert.py

@@ -1,11 +1,12 @@
 from pathlib import Path
+from pydoc_data import topics
 
 import pytest
 import pytest_check as check
 from pyntcloud.io import TO_FILE
 from typer.testing import CliRunner
 
-from pointcloudset import Dataset
+from pointcloudset import Dataset, list_pointcloud_topics
 from pointcloudset.io.dataset.commandline import app
 
 TO_FILE_PYNTCLOUD = list(TO_FILE.keys())
@@ -32,14 +33,15 @@ def test_topics(ros_files):
 
 
 def test_convert_one_rosfile_to_dir(ros_files, tmp_path: Path):
+    topics = list_pointcloud_topics(ros_files)
     out_path = tmp_path.joinpath("cli")
     result = runner.invoke(
         app,
         [
             "convert",
             ros_files.as_posix(),
             "-t",
-            "/os1_cloud_node/points",
+            topics[0],
             "-d",
             out_path.as_posix(),
         ],
@@ -49,13 +51,11 @@ def test_convert_one_rosfile_to_dir(ros_files, tmp_path: Path):
     check.equal(out_path_real.exists(), True)
     read_dataset = Dataset.from_file(out_path_real)
     check.is_instance(read_dataset, Dataset)
-    check.equal(len(read_dataset), 2)
-    check.equal(len(read_dataset.timestamps), 2)
+    check.greater(len(read_dataset), 1)
+    check.greater(len(read_dataset.timestamps), 1)
 
 
-def test_convert_all_rosfiles_to_dir(
-    tmp_path: Path, testdata_path: Path, monkeypatch: pytest.MonkeyPatch
-):
+def test_convert_all_rosfiles_to_dir(tmp_path: Path, testdata_path: Path, monkeypatch: pytest.MonkeyPatch):
     monkeypatch.chdir(testdata_path)
     out_path = tmp_path.joinpath("cli_dirs")
     result = runner.invoke(
@@ -85,14 +85,15 @@ def test_convert_all_rosfiles_to_dir(
 
 @pytest.mark.parametrize("fileformat", TO_FILE_PYNTCLOUD)
 def test_convert_one_ros_file_frames_to_files(ros_files, tmp_path: Path, fileformat):
+    topics = list_pointcloud_topics(ros_files)
     out_path = tmp_path.joinpath("cli_files")
     result = runner.invoke(
         app,
         [
             "convert",
             ros_files.as_posix(),
             "-t",
-            "/os1_cloud_node/points",
+            topics[0],
             "-d",
             out_path.as_posix(),
             "-o",
@@ -103,7 +104,7 @@ def test_convert_one_ros_file_frames_to_files(ros_files, tmp_path: Path, filefor
     out_path_real = out_path.joinpath(ros_files.stem)
     check.equal(out_path_real.exists(), True)
     files = list(out_path_real.glob(f"*.{fileformat.lower()}"))
-    check.equal(len(files), 2)
+    check.greater(len(files), 1)
     check.equal(files[0].suffix.replace(".", ""), fileformat.lower())
 
 
@@ -135,9 +136,7 @@ def test_convert_one_ros_file_one_frame_to_files(ros_files, tmp_path: Path, file
     check.equal(files[0].suffix.replace(".", ""), fileformat.lower())
 
 
-def test_convert_all_bags_frames_files(
-    tmp_path: Path, testdata_path: Path, monkeypatch: pytest.MonkeyPatch
-):
+def test_convert_all_bags_frames_files(tmp_path: Path, testdata_path: Path, monkeypatch: pytest.MonkeyPatch):
     monkeypatch.chdir(testdata_path)
     out_path = tmp_path.joinpath("cli_dirs_frames")
     result = runner.invoke(
@@ -164,9 +163,7 @@ def test_convert_all_bags_frames_files(
 
 @pytest.mark.slow
 @pytest.mark.parametrize("filename", ["big_uncomp.bag", "big_comp.bag"])
-def test_convert_large_file_complete(
-    testdata_path_large: Path, tmp_path: Path, filename: str
-):
+def test_convert_large_file_complete(testdata_path_large: Path, tmp_path: Path, filename: str):
     if testdata_path_large.exists():
         len_target = 250
         testbag = testdata_path_large.joinpath(filename)