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.. image:: https://badge.fury.io/py/mdal.svg :target: https://badge.fury.io/py/mdal
MDAL Python integration allows you to access and manipulation geospatial mesh data sets using MDAL_ in Python.
Currently, this integration can:
meshio_Open3D_.. _MDAL: https://www.mdal.xyz/ .. _meshio: https://github.com/nschloe/meshio .. _Open3D: http://www.open3d.org/
Drivers .......
['2DM Mesh File', 'XMS Tin Mesh File', 'Selafin File', 'Esri TIN', 'Stanford PLY Ascii Mesh File', 'Flo2D', 'HEC-RAS 2D', 'TUFLOW FV', 'AnuGA', 'UGRID Results', 'GDAL NetCDF', 'GDAL Grib', 'DAT', 'Binary DAT', 'TUFLOW XMDF', 'XDMF']
Conda ................................................................................
MDAL Python support is installable via Conda:
.. code-block::
conda install -c conda-forge mdal-pythonPyPI ...............................................................................
MDAL Python support can be installed using pip
.. note::
The previous mdal-python package is deprecated and will not updated beyond 1.0.3. Use the mdal package instead... code-block::
pip install mdal
This will ONLY work if there is a valid and working installation of MDAL on the device and accessible through the device library search path.
.. note::
As of version 1.1.0, this package has been written to the NumPy 2.0 ABI. This should work with any version of NumPy >= 1.25 and Python >=3.9GitHub ................................................................................
The repository for MDAL's Python extension is available at https://github.com/ViRGIS-Team/mdal-python
The basic usage can be seen in this code snippet:
.. code-block:: python
from mdal import Datasource, Info, last_status, PyMesh, drivers, MDAL_DataLocation
print(f"MDAL Version: {Info.version}")
print(f"MDAL Driver Count :{Info.driver_count}")
print(last_status().name)
for driver in Info.drivers:
print(driver)
ds = Datasource("data/ply/test_mesh.ply")
print(ds.meshes)
with ds.load(0) as mesh:
print(f"Driver : {mesh.driver_name}")
print(f"Format : {mesh.get_metadata('format')}")
print(f"Vertex Count : {mesh.vertex_count}")
print(f"Face Count : {mesh.face_count}")
print(f"Largest Face: {mesh.largest_face}")
print(f"Edge Count : {mesh.edge_count}")
print(f"CRS : {mesh.projection}")
print(f"Mesh extent : {mesh.extent}")
print(f"Metadata : {mesh.metadata}")
print(f"CRS Metadata : {mesh.get_metadata('crs')}")
mesh.add_metadata("test", "value")
print(f"Metadate set eqiuality : {mesh.get_metadata('test') == 'value'}")
vertex = mesh.vertices
print(f"Vertex Array Shape : {vertex.shape}")
faces = mesh.faces
print(f"Face Array Shape : {faces.shape}")
edges = mesh.edges
print(f"Edges Array Shape : {edges.shape}")
print("")
group = mesh.group(0)
print(f"DatasetGroup Name : {group.name}")
print(f"DatasetGroup Location : {group.location.name}")
print(f"Dataset Count : {group.dataset_count}")
print(f"Group has scalar values : {group.has_scalar}")
print(f"Group has temporal values : {group.is_temporal}")
print(f"Reference Time : {group.reference_time}")
print(f"Maximum Vertical Level Count : {group.level_count}")
print(f"Minimum / Maximum ; {group.minmax}")
print(f"Metadata : {group.metadata}")
print(f"Name Metadata : {group.get_metadata('name')}")
group.add_metadata("test", "value")
print(
f"Metadate set eqiuality : {group.get_metadata('test') == 'value'}")
print("")
for i in range(0, group.dataset_count):
data = group.data(i)
time = group.dataset_time(i)
print(f"Dataset Shape for time {time} : {data.shape}")
print("")
test = PyMesh()
test.vertices = mesh.vertices
test.faces = mesh.faces
test.edges = mesh.edges
print(f"Mesh Copy Equality : {test == mesh}")
print(
f"Mesh Vertex Size equality: {test.vertex_count == mesh.vertex_count}")
print(f"Mesh Face Size equality: {test.face_count == mesh.face_count}")
test.save("data/save_test.nc")
test2 = PyMesh(drivers()[0])
print(f"Mesh created by Driver : {test2.driver_name}")
ds2 = Datasource("data/save_test.nc")
test4 = ds2.load(0)
print(f"Save equality : {test4 == test}")
del(test)
del(test4)
mesh.save("save_test.ply")
with Datasource("data/ply/all_features.ply").load(0) as mesh:
mesh.save("save_test_2.ply")
with Datasource("save_test_2.ply").load(0) as mesh2:
print(f"Save equality 2 : {mesh == mesh2}")
with Datasource("data/tuflowfv/withMaxes/trap_steady_05_3D.nc").load() as mesh:
group = mesh.groups[1]
a, b, c = group.volumetric(0)
ds2 = Datasource("test_vol.ply")
with ds2.add_mesh() as mesh2:
mesh2.vertices = mesh.vertices
mesh2.faces = mesh.faces
print(f"Vertex Count :{mesh.vertex_count}")
print(f"Face Count : {mesh.face_count}")
group2 = mesh2.add_group(
"test", location=MDAL_DataLocation.DataOnVolumes)
group2.add_volumetric(group.data(), a, b)
print(f"Level Count: {group2.level_count}")
print(f"Location: {group2.location}")
print(f"MinMax: {group2.minmax}")
print(f"Dataset Count: {group2.dataset_count}")
data = group2.data(0)
print(f"Data Value Count: {len(data)}")
print(f"{data}")
print(f"{group2.volumetric(0)}")
a, b, c = group2.volumetric(0)
print(f"Number of Extrusion values : {len(b)}")
mesh2.save()
with ds2.load() as mesh3:
mesh3.info()
group3 = mesh3.groups[1]
print(f"{group3.location}")
d, e, f = group3.volumetric(0)
print(f"{group3.volumetric(0)}")
print(f"{group3.data(0)}")
print("Mesh Equality : {mesh2 == mesh3}")
"""deep copy test"""
with Datasource("data/ply/all_features.ply").load() as mesh:
with ds.add_mesh("test") as mesh2:
mesh2.deep_copy(mesh)
mesh2.data_copy(mesh)
print(f"{mesh2.info()}")
print("all finished !")There is read and write integration with the meshio package. Any MDAL mesh can be converted to a meshio object and vice versa.
This integration is beta at the moment.
There are the following constraints:
.. code-block:: python
from mdal import Datasource,MDAL_transform
"""meshio tests"""
with Datasource("data/ply/all_features.ply").load() as mesh:
mio = MDAL_transform.to_meshio(mesh)
print(f"{mio}")
mio.write("test.vtk")
group = mesh.group(1)
mio2 = MDAL_transform.to_meshio(group)
print(f"{mio2}")
mesh2 = MDAL_transform.from_meshio(mio)
print(f"{mesh2.info()}")
print(f"{mesh2.group(0).data()}")
print(f"{mesh2.vertex_count}")
print(f"{mesh2.face_count}")
with Datasource("test_vol.ply").load() as mesh:
group = mesh.group(1)
mio2 = MDAL_transform.to_meshio(group)
print(f"{mio2}")
print("all finished !")There is read-only integration with Open3D.
The MDAL_transform.to_triangle_mesh function converts any MDAL mesh to an Open3D TriangleMesh. The function can take as an argument an MDAL mesh or Dataset Group. In the former case if there are colour Datasets then these are converted to the TraingleMesh colours. In the later case, the data is converted to a false colur using a simple process - scalar data is loaded into the red values and vector data to the red and blue values.
The MDAL_transform.to_point_cloud converts a MDAL volumetric DatasetGroup to an Open3D PointCloud with the data values converted to color as above.
.. note:: Open3D is NOT loaded as dependency. If these commands are used in an environment without Open3D, they will fail with a user friendly message.
This integration is beta at the moment.
.. code-block:: python
from mdal import Datasource, MDAL_transform
import numpy as np
import open3d as o3d
"""
Open3d Tests
"""
with Datasource("data/ply/test_mesh.ply").load() as mesh:
tm = MDAL_transform.to_triangle_mesh(mesh)
print(tm)
tm2 = o3d.io.read_triangle_mesh("data/ply/test_mesh.ply")
tmc = np.asarray(tm.vertex_colors)
tmc2 = np.asarray(tm2.vertex_colors)
for i in range(len(tmc)):
value = tmc[i] - tmc2[i]
if not (value == [0, 0, 0]).all():
print(value)
break
with Datasource("test_vol.ply").load() as mesh:
pc = MDAL_transform.to_point_cloud(mesh.group(1))
print(pc)
print("all finished !").. note::
About Python Versions. MDAL supports 3.8, 3.9 and 3.10. Open3D supports 3.6, 3.7 and 3.8. Therefore,
if you want to use Open3D, the Python version should be pinned to 3.8 before you start.The documentation is currently WIP and can be found at https://virgis-team.github.io/mdal-python/html/index.html
pip install cython)pip install numpy)pip install packaging)pip install scikit-build)This package borrowed heavily from the PDAL-Python_ package.
.. _PDAL-Python: https://github.com/PDAL/python