How to use the pdal.Pipeline function in pdal

def test_metadata(self):
        """Can we fetch PDAL metadata"""
        json = self.fetch_json('sort.json')
        r = pdal.Pipeline(json)
        r.validate()
        r.execute()
        metadata = r.metadata
        import json
        j = json.loads(metadata)
        self.assertEqual(j["metadata"]["readers.las"][0]["count"], 1065)

def test_merged_arrays(self):
        """Can we fetch multiple point views from merged PDAL data """
        json = self.fetch_json('chip.json')
        r = pdal.Pipeline(json)
        r.validate()
        r.execute()
        arrays = r.arrays
        self.assertEqual(len(arrays), 43)

def test_execution(self):
        """Can we execute a PDAL pipeline"""
        x = self.fetch_json('sort.json')
        r = pdal.Pipeline(x)
        r.validate()
        r.execute()
        self.assertGreater(len(r.pipeline), 200)

def test_validate(self):
        """Do we complain with bad pipelines"""
        r = pdal.Pipeline(bad_json)
        with self.assertRaises(RuntimeError):
            r.validate()

sys.exit(1)

# read the pdal file and project the points
json = u"""
{
  "pipeline": [
    "%s",
    {
        "type":"filters.reprojection",
        "out_srs":"EPSG:4326"
    }
  ]
}"""
print("Loading Point Cloud")
json = json % args.source_points
pipeline = pdal.Pipeline(json)
pipeline.validate()  # check if our JSON and options were good
# this causes a segfault at the end of the program
# pipeline.loglevel = 8  # really noisy
count = pipeline.execute()
arrays = pipeline.arrays
arrayX = arrays[0]['X']
arrayY = arrays[0]['Y']
arrayZ = arrays[0]['Z']
pipeline = None

# Sort the points by height so that higher points project last
print("Sorting by Height")
heightIdx = numpy.argsort(arrayZ)
arrayX = arrayX[heightIdx]
arrayY = arrayY[heightIdx]
arrayZ = arrayZ[heightIdx]

def execute(self):
        """
        Shortcut to execute and return the results of the pipeline.
        """
        # TODO: do some validation before calling execute

        # TODO: some exception/error handling around pdal
        pipeline = pdal.Pipeline(json.dumps(self.spec))
        # pipeline.validate() # NOTE: disabling this because it causes segfaults in certain cases
        pipeline.execute()

        return pipeline.arrays[0] # NOTE: are there situation where arrays has multiple elements?

json = {
    "pipeline": [
        {
            "type":"readers.las",
            "filename":filename,
        },
        {
            "type":"filters.transformation",
            #"matrix":"0.4 -1  0  1  1  0  0  2  0  0  1  3  0  0  0  1",
            "matrix":t,
        },
    ]
}
tic()
pipeline = pdal.Pipeline(unicode(js.dumps(json)))
#pipeline.validate() # check if our JSON and options were good
pipeline.loglevel = 0 #really noisy
count = pipeline.execute()
arrays = pipeline.arrays

toc()

tic()
pipeline = pdal.Pipeline(unicode(js.dumps(json)))

#pipeline.validate() # check if our JSON and options were good
#pipeline.loglevel = 8 #really noisy
count = pipeline.execute()
arrays = pipeline.arrays

toc()

raise RuntimeError("Error: driver {} does not supports Create().".format(driver))

    # read the pdal file and project the points
    json = u"""
    {
      "pipeline": [
        "%s",
        {
            "type":"filters.reprojection",
            "out_srs":"EPSG:4326"
        }
      ]
    }"""
    print("Loading Point Cloud")
    json = json % args.source_points
    pipeline = pdal.Pipeline(json)
    pipeline.validate()  # check if our JSON and options were good
    # this causes a segfault at the end of the program
    # pipeline.loglevel = 8  # really noisy
    pipeline.execute()
    arrays = pipeline.arrays
    arrayX = arrays[0]['X']
    arrayY = arrays[0]['Y']
    arrayZ = arrays[0]['Z']
    pipeline = None

    # Sort the points by height so that higher points project last
    print("Sorting by Height")
    heightIdx = numpy.argsort(arrayZ)
    arrayX = arrayX[heightIdx]
    arrayY = arrayY[heightIdx]
    arrayZ = arrayZ[heightIdx]