How to use the pytools.obj_array.make_obj_array function in pytools

@pytools.test.mark_test.opencl
def test_tree(ctx_getter, do_plot=False):
    ctx = ctx_getter()
    queue = cl.CommandQueue(ctx)

    #for dims in [2, 3]:
    for dims in [2]:
        nparticles = 10000
        dtype = np.float64

        from pyopencl.clrandom import RanluxGenerator
        rng = RanluxGenerator(queue, seed=15)

        from pytools.obj_array import make_obj_array
        particles = make_obj_array([
            rng.normal(queue, nparticles, dtype=dtype)
            for i in range(dims)])

        if do_plot:
            pt.plot(particles[0].get(), particles[1].get(), "x")

        from sumpy.tree import TreeBuilder
        tb = TreeBuilder(ctx)

        queue.finish()
        print "building..."
        tree = tb(queue, particles, max_particles_in_box=30)
        print "%d boxes, testing..." % tree.nboxes

        starts = tree.box_starts.get()
        pcounts = tree.box_particle_counts.get()

def output_zeros(self):
        from pytools.obj_array import make_obj_array
        return make_obj_array([
                cl.array.zeros(
                    self.queue,
                    self.tree.ntargets,
                    dtype=self.dtype)
                for k in self.code.out_kernels])

from six.moves import range

ctx = cl.create_some_context()
queue = cl.CommandQueue(ctx)

dims = 2
nparticles = 500

# -----------------------------------------------------------------------------
# generate some random particle positions
# -----------------------------------------------------------------------------
from pyopencl.clrandom import RanluxGenerator
rng = RanluxGenerator(queue, seed=15)

from pytools.obj_array import make_obj_array
particles = make_obj_array([
    rng.normal(queue, nparticles, dtype=np.float64)
    for i in range(dims)])

# -----------------------------------------------------------------------------
# build tree and traversals (lists)
# -----------------------------------------------------------------------------
from boxtree import TreeBuilder
tb = TreeBuilder(ctx)
tree, _ = tb(queue, particles, max_particles_in_box=5)

from boxtree.traversal import FMMTraversalBuilder
tg = FMMTraversalBuilder(ctx)
trav, _ = tg(queue, tree)

# ENDEXAMPLE

def dnabla(self, ambient_dim):
        from pymbolic.geometric_algebra import MultiVector
        from pytools.obj_array import make_obj_array
        return MultiVector(make_obj_array(
            [NablaComponent(axis, self.my_id)
                for axis in range(ambient_dim)]))

def src_derivative_dir(self):
        self.arguments["src_derivative_dir"] = \
                lp.GlobalArg("src_derivative_dir",
                        self.geometry_dtype, shape=("ntargets", self.dim),
                        order="C")
        from pytools.obj_array import make_obj_array
        return make_obj_array([
            parse("src_derivative_dir[itgt, %d]" % i)
            for i in range(self.dim)])

def u(self, q):
        return make_obj_array([
                rho_u_i/self.rho(q)
                for rho_u_i in self.rho_u(q)])

def normal(self):
        self.arguments["normal"] = \
                lp.GlobalArg("normal", self.geometry_dtype,
                        shape=("ntargets", self.dim), order="C")
        from pytools.obj_array import make_obj_array
        return make_obj_array([
            parse("normal[itgt, %d]" % i)
            for i in range(self.dim)])

logger.debug("tree build: start")

        # {{{ combine sources and targets into one array, if necessary

        prep_events = []

        if targets is None:
            # Targets weren't specified. Sources are also targets. Let's
            # call them "srcntgts".

            from pytools.obj_array import is_obj_array, make_obj_array
            if is_obj_array(particles):
                srcntgts = particles
            else:
                srcntgts = make_obj_array([
                    p.with_queue(queue).copy() for p in particles
                    ])

            assert source_radii is None
            assert target_radii is None

            srcntgt_radii = None

        else:
            # Here, we mash sources and targets into one array to give us one
            # big array of "srcntgts". In this case, a "srcntgt" is either a
            # source or a target, but not really both, as above. How will we be
            # able to tell which it was? Easy: We'll compare its 'user' id with
            # nsources. If it's >=, it's a target, otherwise it's a source.

            target_coord_dtype = single_valued(tgt_i.dtype for tgt_i in targets)

def stream_rhs(self, f_bar):
        return make_obj_array([
            self.get_advection_op(f_bar_alpha, e_alpha)
            for e_alpha, f_bar_alpha in
            zip(self.method.direction_vectors, f_bar)])