# ros2_numpy
Note: This is the same as the original ros_numpy package by eric-wieser and ros2_numpy package by box-robotics just edited to be OS independent and installable using pip.
### Pointcloud manipulation is updated `ros2_numpy.pointcloud2` to be compatible with ROS2. It now gives a structured numpy array with the fields `x`, `y`, `z`, `rgb`, `intensity`. The `rgb` field is a 3-tuple of uint8 values. The `intensity` field is a float32 value. The `x`, `y`, `z` fields are float32 values.
<br>
This project is a fork of [ros2_numpy](https://github.com/Box-Robotics/ros2_numpy) to work with ROS 2. It provides tools for converting ROS messages to and from numpy arrays. In the ROS 2 port, the module has been renamed to
`ros2_numpy`. Users are encouraged to update their application code to import
the module as shown below.
```
pip install ros2-numpy
import ros2_numpy as rnp
```
Prefacing your calls like `rnp.numpify(...)` or `rnp.msgify(...)` should help
future proof your codebase while the ROS 2 ports are API compatible.
This module contains two core functions:
* `arr = numpify(msg, ...)` - try to get a numpy object from a message
* `msg = msgify(MessageType, arr, ...)` - try and convert a numpy object to a message
Currently supports:
* `sensor_msgs.msg.PointCloud2` ↔ structured `np.array`:
```python
data = np.zeros(100, dtype=[
('x', np.float32),
('y', np.float32),
('vectors', np.float32, (3,))
])
data['x'] = np.arange(100)
data['y'] = data['x']*2
data['vectors'] = np.arange(100)[:,np.newaxis]
msg = ros2_numpy.msgify(PointCloud2, data)
```
```
data = ros2_numpy.numpify(msg)
```
* `sensor_msgs.msg.Image` ↔ 2/3-D `np.array`, similar to the function of `cv_bridge`, but without the dependency on `cv2`
* `nav_msgs.msg.OccupancyGrid` ↔ `np.ma.array`
* `geometry.msg.Vector3` ↔ 1-D `np.array`. `hom=True` gives `[x, y, z, 0]`
* `geometry.msg.Point` ↔ 1-D `np.array`. `hom=True` gives `[x, y, z, 1]`
* `geometry.msg.Quaternion` ↔ 1-D `np.array`, `[x, y, z, w]`
* `geometry.msg.Transform` ↔ 4×4 `np.array`, the homogeneous transformation matrix
* `geometry.msg.Pose` ↔ 4×4 `np.array`, the homogeneous transformation matrix from the origin
Support for more types can be added with:
```python
@ros2_numpy.converts_to_numpy(SomeMessageClass)
def convert(my_msg):
return np.array(...)
@ros2_numpy.converts_from_numpy(SomeMessageClass)
def convert(my_array):
return SomeMessageClass(...)
```
Any extra args or kwargs to `numpify` or `msgify` will be forwarded to your conversion function
## Future work
* Add simple conversions for:
* `geometry_msgs.msg.Inertia`
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"description": "# ros2_numpy\n\nNote: This is the same as the original ros_numpy package by eric-wieser and ros2_numpy package by box-robotics just edited to be OS independent and installable using pip.\n\n### Pointcloud manipulation is updated `ros2_numpy.pointcloud2` to be compatible with ROS2. It now gives a structured numpy array with the fields `x`, `y`, `z`, `rgb`, `intensity`. The `rgb` field is a 3-tuple of uint8 values. The `intensity` field is a float32 value. The `x`, `y`, `z` fields are float32 values.\n\n<br>\n\nThis project is a fork of [ros2_numpy](https://github.com/Box-Robotics/ros2_numpy) to work with ROS 2. It provides tools for converting ROS messages to and from numpy arrays. In the ROS 2 port, the module has been renamed to\n`ros2_numpy`. Users are encouraged to update their application code to import\nthe module as shown below.\n\n```\npip install ros2-numpy\nimport ros2_numpy as rnp\n```\n\nPrefacing your calls like `rnp.numpify(...)` or `rnp.msgify(...)` should help\nfuture proof your codebase while the ROS 2 ports are API compatible.\n\nThis module contains two core functions:\n\n* `arr = numpify(msg, ...)` - try to get a numpy object from a message\n* `msg = msgify(MessageType, arr, ...)` - try and convert a numpy object to a message\n\nCurrently supports:\n\n* `sensor_msgs.msg.PointCloud2` ↔ structured `np.array`:\n\n ```python\n data = np.zeros(100, dtype=[\n ('x', np.float32),\n ('y', np.float32),\n ('vectors', np.float32, (3,))\n ])\n data['x'] = np.arange(100)\n data['y'] = data['x']*2\n data['vectors'] = np.arange(100)[:,np.newaxis]\n\n msg = ros2_numpy.msgify(PointCloud2, data)\n ```\n\n ```\n data = ros2_numpy.numpify(msg)\n ```\n\n* `sensor_msgs.msg.Image` ↔ 2/3-D `np.array`, similar to the function of `cv_bridge`, but without the dependency on `cv2`\n* `nav_msgs.msg.OccupancyGrid` ↔ `np.ma.array`\n* `geometry.msg.Vector3` ↔ 1-D `np.array`. `hom=True` gives `[x, y, z, 0]`\n* `geometry.msg.Point` ↔ 1-D `np.array`. `hom=True` gives `[x, y, z, 1]`\n* `geometry.msg.Quaternion` ↔ 1-D `np.array`, `[x, y, z, w]`\n* `geometry.msg.Transform` ↔ 4×4 `np.array`, the homogeneous transformation matrix\n* `geometry.msg.Pose` ↔ 4×4 `np.array`, the homogeneous transformation matrix from the origin\n\nSupport for more types can be added with:\n\n```python\n@ros2_numpy.converts_to_numpy(SomeMessageClass)\ndef convert(my_msg):\n return np.array(...)\n\n@ros2_numpy.converts_from_numpy(SomeMessageClass)\ndef convert(my_array):\n return SomeMessageClass(...)\n```\n\nAny extra args or kwargs to `numpify` or `msgify` will be forwarded to your conversion function\n\n\n## Future work\n\n* Add simple conversions for:\n\n * `geometry_msgs.msg.Inertia`\n",
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