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Use structured NumPy points.dtype.itemsize as default point_step in create_cloud #295

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Use structured NumPy points.dtype.itemsize as default point_step in create_cloud #295

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8 changes: 6 additions & 2 deletions sensor_msgs_py/sensor_msgs_py/point_cloud2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -250,7 +250,9 @@ def create_cloud(
for each point, with the elements of each iterable being the
values of the fields for that point (in the same order as
the fields parameter)
:param point_step: Point step size in bytes. Calculated from the given fields by default.
:param point_step: Point step size in bytes. If not provided, it is calculated
from the given fields, except when 'points' is a structured
NumPy array, in which case points.dtype.itemsize is used.
(Type: optional of integer)
:return: The point cloud as sensor_msgs.msg.PointCloud2
"""
Expand All @@ -266,7 +268,9 @@ def create_cloud(
points,
dtype=dtype_from_fields(fields, point_step))
else:
assert points.dtype == dtype_from_fields(fields, point_step), \
assert points.dtype == dtype_from_fields(
fields,
point_step or points.dtype.itemsize), \
'PointFields and structured NumPy array dtype do not match for all fields! \
Check their field order, names and types.'
else:
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8 changes: 8 additions & 0 deletions sensor_msgs_py/test/test_point_cloud2.py
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Original file line number Diff line number Diff line change
Expand Up @@ -296,10 +296,18 @@ def test_create_cloud(self):
def test_create_cloud_itemsize(self):

with self.assertRaises(AssertionError):
dtype_from_fields = point_cloud2.dtype_from_fields(fields)
point_cloud2.create_cloud(
Header(frame_id='frame'),
fields,
points_end_padding,
dtype_from_fields.itemsize)

thispcd = point_cloud2.create_cloud(
Header(frame_id='frame'),
fields,
points_end_padding)
self.assertEqual(thispcd.point_step, itemsize_end_padding)

thispcd = point_cloud2.create_cloud(
Header(frame_id='frame'),
Expand Down