How to use the pyntcloud.PyntCloud function in pyntcloud

def test_voxelgrid_sampling_return_type(simple_pyntcloud, sampling_method):
    voxelgrid_id = simple_pyntcloud.add_structure("voxelgrid")

    sample = simple_pyntcloud.get_sample(
        sampling_method,
        voxelgrid_id=voxelgrid_id)
    assert type(sample) == DataFrame

    sample = simple_pyntcloud.get_sample(
        sampling_method,
        voxelgrid_id=voxelgrid_id,
        as_PyntCloud=True)
    assert type(sample) == PyntCloud

def test_regular_bounding_box_changes_the_shape_of_the_bounding_box(x, y, z):

    cloud = PyntCloud(pd.DataFrame(
        data={
            "x": np.array(x, dtype=np.float32),
            "y": np.array(y, dtype=np.float32),
            "z": np.array(z, dtype=np.float32)
    }))

    voxelgrid = VoxelGrid(points=cloud.xyz, n_x=2, n_y=2, n_z=2, regular_bounding_box=False)
    voxelgrid.compute()

    irregular_last_centroid = voxelgrid.voxel_centers[-1]

    voxelgrid = VoxelGrid(points=cloud.xyz, n_x=2, n_y=2, n_z=2)
    voxelgrid.compute()

    regular_last_centroid = voxelgrid.voxel_centers[-1]

def test_to_file(tmpdir, diamond, extension, color, mesh):
    extra_write_args = {}
    if mesh:
        extra_write_args["also_save"] = ["mesh"]
    if extension == ".ply":
        extra_write_args["as_text"] = False
    if extension == "_ascii.ply":
        extra_write_args["as_text"] = True

    diamond.to_file(str(tmpdir.join("written{}".format(extension))), **extra_write_args)

    written_file = PyntCloud.from_file(str(tmpdir.join("written{}".format(extension))))

    assert_points_xyz(written_file)
    if color:
        assert_points_color(written_file)
    if mesh:
        assert_mesh(written_file)

def test_voxelgrid_sampling():

    cloud = PyntCloud.from_file(path + "/data/voxelgrid.ply")

    with pytest.raises(TypeError):
        cloud.get_sample("voxelgrid_centers")

    vg_id = cloud.add_structure("voxelgrid")

    with pytest.raises(KeyError):
        cloud.get_sample("voxelgrid_centers", voxelgrid=vg_id[:-2])

    sample = cloud.get_sample("voxelgrid_centers", voxelgrid=vg_id)

    assert point_in_array_2D([0.25, 0.25, 0.25], sample.values)

    sample = cloud.get_sample("voxelgrid_centroids", voxelgrid=vg_id)

    assert point_in_array_2D([0.2, 0.2, 0.2], sample.values)

import os
import pytest
from pyntcloud import PyntCloud


path = os.path.abspath(os.path.dirname(__file__))
cloud = PyntCloud.from_file(path + "/data/test_data_filters.ply")


def test_kdtree_filters():
    """filters.f_kdtree.

    - Raise TypeError when missing required arguments
    - Raise KeyError when structure.id is invalid
    - Raise TypeError when wrong argument is given (k instead of r)
    - Manually check known result.

    """
    with pytest.raises(TypeError):
        cloud.get_filter("ROR")

    kdtree = cloud.add_structure("kdtree")

# not dataframe
    with pytest.raises(TypeError):
        PyntCloud(points)

    points = pd.DataFrame(points)

    # not x, y, z
    with pytest.raises(ValueError):
        PyntCloud(points)

    points = pd.DataFrame(points.values, columns=["x", "y", "z"])

    assert PyntCloud(points)

    cloud = PyntCloud(points)

    cloud.add_structure("voxelgrid")

    assert len(cloud.structures) == 1

    # dummy filter
    x_above_05 = cloud.points["x"] > 0.5
    cloud.points = cloud.points[x_above_05]

    assert len(cloud.structures) == 0

def ply2gii(in_file, metadata, out_file=None):
    """Convert from ply to GIfTI"""
    from pathlib import Path
    from numpy import eye
    from nibabel.gifti import (
        GiftiMetaData,
        GiftiCoordSystem,
        GiftiImage,
        GiftiDataArray,
    )
    from pyntcloud import PyntCloud

    in_file = Path(in_file)
    surf = PyntCloud.from_file(str(in_file))

    # Update centroid metadata
    metadata.update(
        zip(
            ("SurfaceCenterX", "SurfaceCenterY", "SurfaceCenterZ"),
            ["%.4f" % c for c in surf.centroid],
        )
    )

    # Prepare data arrays
    da = (
        GiftiDataArray(
            data=surf.xyz.astype("float32"),
            datatype="NIFTI_TYPE_FLOAT32",
            intent="NIFTI_INTENT_POINTSET",
            meta=GiftiMetaData.from_dict(metadata),

def write_df(path, df):
    pc = PyntCloud(df)
    pc.to_file(path)

def pointcloud2ply(vertices, normals, out_file=None):
    """Converts the file to PLY format"""
    from pathlib import Path
    import pandas as pd
    from pyntcloud import PyntCloud

    df = pd.DataFrame(np.hstack((vertices, normals)))
    df.columns = ["x", "y", "z", "nx", "ny", "nz"]
    cloud = PyntCloud(df)

    if out_file is None:
        out_file = Path("pointcloud.ply").resolve()

    cloud.to_file(str(out_file))
    return out_file