Great to see the 2.2.0 update has been pushed to conda-forge. However I am now running into a different issue.
Again I am trying to use a numpy structured array as input:
>>> point_cloud[0:1]
array([(122312.202, 489447.885, -0.23, 8, 1, 1, 1, 2, 30817)], dtype=[('X', '<f8'), ('Y', '<f8'), ('Z', '<f8'), ('Intensity', '<u2'), ('ReturnNumber', 'u1'), ('NumberOfReturns', 'u1'), ('Classification', 'u1'), ('UserData', 'u1'), ('PointSourceId', '<u2')])If I try to use the following pdal pipeline:
PDAL_PIPELINE = """
{
"pipeline": [
{
"type": "filters.eigenvalues",
"knn": 10
}
]
}
"""
pipeline = pdal.Pipeline(
PDAL_PIPELINE,
arrays=[point_cloud]
)
pipeline.validate()
pipeline.execute()
result = pipeline.arraysIt returns:
pdal/libpdalpython.pyx in pdal.libpdalpython.PyPipeline.validate()
RuntimeError: readers.memoryview: Can't provide `shape` option when Fields contain X, Y and Z.
I am trying to figure out what's going wrong, but I'm a bit lost. As far as I know I am not providing a shape as I am using a structured array with an X, Y, and Z column.
I am using a conda environment on ubuntu with python 3.7, PDAL 2.0.1, python-pdal 2.2.0, numpy 1.16.4.
Great to see the 2.2.0 update has been pushed to conda-forge. However I am now running into a different issue.
Again I am trying to use a numpy structured array as input:
If I try to use the following pdal pipeline:
It returns:
I am trying to figure out what's going wrong, but I'm a bit lost. As far as I know I am not providing a shape as I am using a structured array with an
X,Y, andZcolumn.I am using a conda environment on ubuntu with python 3.7, PDAL 2.0.1, python-pdal 2.2.0, numpy 1.16.4.