def convert_shapefiles(pred=None, node_threshold=None):
# Run with MPI: mpirun -n 8 prep_shapefiles.py
nfie_version = 'node-threshold-10000'
name_uid = 'GRIDCODE'
storage_dir_shp = os.path.expanduser(
'/media/benkoziol/Extra Drive 1/data/nfie/linked_catchment_shapefiles')
storage_dir_esmf = os.path.expanduser(
'/media/benkoziol/Extra Drive 1/data/nfie/node-thresholded-10000')
esmf_name_template = 'esmf_format_{cid}_{nfie_version}.nc'
log.info('Starting conversion for: {}'.format(nfie_version))
for dirpath, dirnames, filenames in os.walk(
os.path.join(storage_dir_shp, storage_dir_shp)):
for fn in filenames:
if fn.endswith('.shp'):
log.debug(fn)
if pred is not None and not pred(fn):
continue
cid = re.search('linked_(.*).shp', fn).group(1)
path_catchment_shp = os.path.join(dirpath, fn)
esmf_name = esmf_name_template.format(
cid=cid, nfie_version=nfie_version)
path_esmf_format_nc = os.path.join(storage_dir_esmf, esmf_name)
log.info('Converting {}'.format(path_catchment_shp))
# log.debug((path_esmf_format_nc, path_catchment_shp, name_uid))
try:
convert_to_esmf_format(path_esmf_format_nc,
path_catchment_shp,
name_uid,
node_threshold=node_threshold)
except:
log.exception(path_catchment_shp)
def make_shapefiles_and_esmf_format():
log.level = logbook.DEBUG
template_shapefile = 'single_element_{gridcode}_{node_count}.shp'
template_esmf_format = 'esmf_single_element_{gridcode}_{node_count}.nc'
to_process = get_representative_nodes()
for tp in to_process:
log.debug(tp)
gridcode = tp['gridcode']
node_count = tp['node_count']
filename_shapefile = template_shapefile.format(gridcode=gridcode, node_count=node_count)
filename_esmf_format = template_esmf_format.format(gridcode=gridcode, node_count=node_count)
# Extract the element and write the shapefile.
sink_path = join(WD, filename_shapefile)
source_path = get_source_shapefile(SHAPEFILE_DIR, tp['name'])
log.debug(source_path)
found = False
with fiona.open(source_path) as source:
with fiona.open(sink_path, 'w', **source.meta) as sink:
for record in source:
if record['properties']['GRIDCODE'] == gridcode:
found = True
sink.write(record)
break
assert found
# Convert the shapefile to ESMF format.
path_out_nc = join(WD, filename_esmf_format)
path_in_shp = sink_path
convert_to_esmf_format(path_out_nc, path_in_shp, 'GRIDCODE')
def run_create_linked_shapefile():
log.level = INFO
name_uid = 'GRIDCODE'
output_variable = 'pr'
directory_shapefiles = expanduser('~/storage/catchment_shapefiles')
directory_linked_shapefiles = expanduser('~/storage/linked_catchment_shapefiles')
directory_weighted_data = expanduser('~/storage/catchment_weighted_data')
if MPI_RANK == 0:
weighted_data_files = filter(lambda x: x.startswith('pr_weighted'), listdir(directory_weighted_data))
weighted_data_files = [weighted_data_files[slc[0]: slc[1]] for slc in create_sections(len(weighted_data_files))]
else:
weighted_data_files = None
weighted_data_files = MPI_COMM.scatter(weighted_data_files, root=0)
for ii in weighted_data_files:
path_output_data = join(directory_weighted_data, ii)
# log.debug(ii)
res = re.search('pr_weighted-catchments_esmf_(.*)_', ii).groups()[0]
# log.debug(res.groups()[0])
shapefile_directory = join(directory_shapefiles, res)
path_in_shp = check_output(['find', shapefile_directory, '-name', '*Catchment.shp']).strip()
path_linked_shp = join(directory_linked_shapefiles, 'linked_{}.shp'.format(res))
log.debug((path_in_shp, path_linked_shp))
log.info('Creating linked shapefile for: {}'.format(path_output_data))
create_linked_shapefile(name_uid, output_variable, path_in_shp, path_linked_shp, path_output_data)
def get_representative_nodes():
"""Get elements with a reasonable distribution of node counts."""
step = 1000
start = 0
stop = 60000
limit = 50
record_names = ['name', 'gridcode', 'node_count']
ranges = []
to_process = []
s = Session()
while start < stop:
ranges.append([start, start + step])
start += step
for ctr, select_range in enumerate(ranges):
log.debug(select_range)
q = s.query(VectorProcessingUnit.name, Catchment.gridcode, Catchment.node_count).join(Catchment)
q = q.filter(Catchment.node_count >= select_range[0]).filter(Catchment.node_count < select_range[1])
q = q.order_by(func.random()).limit(limit)
for idx, record in enumerate(q):
to_process.append(dict(zip(record_names, record)))
s.close()
return to_process
def run_create_linked_shapefile():
log.level = INFO
name_uid = 'GRIDCODE'
output_variable = 'pr'
directory_shapefiles = expanduser('~/storage/catchment_shapefiles')
directory_linked_shapefiles = expanduser(
'~/storage/linked_catchment_shapefiles')
directory_weighted_data = expanduser('~/storage/catchment_weighted_data')
if MPI_RANK == 0:
weighted_data_files = filter(lambda x: x.startswith('pr_weighted'),
listdir(directory_weighted_data))
weighted_data_files = [
weighted_data_files[slc[0]:slc[1]]
for slc in create_sections(len(weighted_data_files))
]
else:
weighted_data_files = None
weighted_data_files = MPI_COMM.scatter(weighted_data_files, root=0)
for ii in weighted_data_files:
path_output_data = join(directory_weighted_data, ii)
# log.debug(ii)
res = re.search('pr_weighted-catchments_esmf_(.*)_', ii).groups()[0]
# log.debug(res.groups()[0])
shapefile_directory = join(directory_shapefiles, res)
path_in_shp = check_output(
['find', shapefile_directory, '-name', '*Catchment.shp']).strip()
path_linked_shp = join(directory_linked_shapefiles,
'linked_{}.shp'.format(res))
log.debug((path_in_shp, path_linked_shp))
log.info('Creating linked shapefile for: {}'.format(path_output_data))
create_linked_shapefile(name_uid, output_variable, path_in_shp,
path_linked_shp, path_output_data)
def from_shapefile(path,
name_uid,
mesh_name='mesh',
path_rtree=None,
use_ragged_arrays=False,
with_connectivity=True,
allow_multipart=False,
node_threshold=None,
driver_kwargs=None,
debug=False,
dest_crs=None,
split_interiors=True):
"""
Create a flexible mesh from a target shapefile.
>>> path = '/input/target.shp'
>>> name_uid = 'UID'
>>> fm = FlexibleMesh.from_shapefile(path, name_uid)
:param path: Path to the target shapefile.
:type path: str
:param name_uid: Name of the integer unique identifier in the target shapefile. This value will be maintained on
the output mesh object.
:type name_uid: str
:param mesh_name: Name of the mesh catalog variable.
:type mesh: str
:param path_rtree: Path to a serialized spatial index object created using ``rtree``. Use :func:`pyugrid.flexible_mesh.helpers.create_rtree_file`
to create a persistent ``rtree`` spatial index file.
:type path_rtree: str
:rtype: :class:`pyugrid.flexible_mesh.core.FlexibleMesh`
"""
# tdk: update doc
from utools.io.geom_manager import GeometryManager
if debug:
slc = [0, 1]
else:
slc = None
log.debug('creating geometry manager')
log.debug(('driver_kwargs', driver_kwargs))
gm = GeometryManager(name_uid,
path=path,
path_rtree=path_rtree,
allow_multipart=allow_multipart,
node_threshold=node_threshold,
slc=slc,
driver_kwargs=driver_kwargs,
dest_crs=dest_crs,
split_interiors=split_interiors)
log.debug('geometry manager created')
ret = get_flexible_mesh(gm,
mesh_name,
use_ragged_arrays,
with_connectivity=with_connectivity)
log.debug('mesh collection returned')
return ret
def convert(source_uid, source, esmf_format, feature_class, config_path,
dest_crs_index, node_threshold, split, debug):
from utools.prep.prep_shapefiles import convert_to_esmf_format
log_entry('info',
'Started converting to ESMF format: {}'.format(source),
rank=0)
# Set the feature class name even if it is None. Feature class name is required for a file geodatabase.
driver_kwargs = {'feature_class': feature_class}
# If there is a destination CRS, read in the value and convert to a spatial reference object for the geometry
# manager.
if dest_crs_index is not None:
log.debug(('dest_crs_index', dest_crs_index))
dest_crs_index = dest_crs_index.split(',')
if len(dest_crs_index) == 1:
crs_section = None
crs_option = dest_crs_index[0]
elif len(dest_crs_index) == 2:
crs_section, crs_option = dest_crs_index
else:
raise NotImplementedError(len(dest_crs_index))
sp = SafeConfigParser()
sp.read(config_path)
crs_wkt = sp.get(crs_section, crs_option)
dest_crs = osgeo.osr.SpatialReference()
dest_crs.ImportFromWkt(crs_wkt)
else:
dest_crs = None
convert_to_esmf_format(esmf_format,
source,
source_uid,
node_threshold=node_threshold,
driver_kwargs=driver_kwargs,
debug=debug,
dest_crs=dest_crs,
split_interiors=split)
log_entry('info',
'Finished converting to ESMF format: {}'.format(source),
rank=0)
def test_coordinates(self):
path = '/home/benkoziol/data/pmesh/catchment_shapefiles/NHDPlusTX/NHDPlus12/NHDPlusCatchment/Catchment.shp'
with fiona.open(path, 'r') as source:
for record in source:
log.debug(record['properties']['GRIDCODE'])
geom = shape(record['geometry'])
if isinstance(geom, MultiPolygon):
itr = geom
else:
itr = [geom]
for polygon in itr:
polygon = get_oriented_and_valid_geometry(polygon)
self.assertTrue(polygon.exterior.is_ccw)
coords = np.array(polygon.exterior.coords)
try:
self.assertTrue(coords.shape[0] > 1)
except AssertionError:
log.error('AssertionError GRIDCODE={}'.format(
record['properties']['GRIDCODE']))
continue
def convert_to_esmf_format(path_out_nc,
path_in_shp,
name_uid,
node_threshold=None,
debug=False,
driver_kwargs=None,
dest_crs=None,
with_connectivity=False,
dataset_kwargs=None):
polygon_break_value = UgridToolsConstants.POLYGON_BREAK_VALUE
log.debug('loading flexible mesh')
coll = from_shapefile(path_in_shp,
name_uid,
use_ragged_arrays=True,
with_connectivity=with_connectivity,
allow_multipart=True,
node_threshold=node_threshold,
debug=debug,
driver_kwargs=driver_kwargs,
dest_crs=dest_crs)
log.debug('writing flexible mesh')
convert_collection_to_esmf_format(coll,
path_out_nc,
polygon_break_value=polygon_break_value,
face_uid_name=name_uid,
dataset_kwargs=dataset_kwargs)
# validate_esmf_format(ds, name_uid, path_in_shp)
log.debug('success')
def make_weight_files():
n_jobs = 16
to_process = []
log.level = logbook.INFO
for ctr, l in enumerate(listdir(WD)):
# if ctr > 20: break
if l.endswith('.nc'):
path_out_weights_nc = join(ESMF_WEIGHTS_OUTPUT_DIR, 'weights_' + l)
esmf_format = join(WD, l)
log.debug(path_out_weights_nc)
log.debug(esmf_format)
search = re.search('esmf_single_element_(.+)_(.+).nc', l)
gridcode, node_count = search.group(1), search.group(2)
kwds = {'esmf_format': esmf_format,
'path_out_weights_nc': path_out_weights_nc,
'gridcode': int(gridcode),
'node_count': int(node_count)}
to_process.append(kwds)
log.debug(kwds)
rtimes = Parallel(n_jobs=n_jobs)(delayed(make_weight_file)(**k) for k in to_process)
for idx, k in enumerate(to_process):
k['time'] = rtimes[idx]
log.info(to_process)
def convert_collection_to_esmf_format(fmobj,
filename,
polygon_break_value=None,
start_index=0,
face_uid_name=None,
dataset_kwargs=None):
"""
Convert to an ESMF format NetCDF files. Only supports ragged arrays.
:param fm: Flexible mesh object to convert.
:type fm: :class:`pyugrid.flexible_mesh.core.FlexibleMesh`
:param ds: An open netCDF4 dataset object.
:type ds: :class:`netCDF4.Dataset`
"""
dataset_kwargs = dataset_kwargs or {}
# tdk: doc
# face_areas = fmobj.face_areas
# face_coordinates = fmobj.face_coordinates
# if face_uid_name is None:
# face_uid_value = None
# else:
# face_uid_value = fmobj.data[face_uid_name].data
# faces = fmobj.faces
# nodes = fmobj.nodes
face_areas = fmobj['face_areas']
face_coordinates = fmobj['face_coordinates']
if face_uid_name is not None:
face_uid_value = fmobj[face_uid_name]
else:
face_uid_value = None
faces = fmobj['face']
nodes = fmobj['nodes']
# float_dtype = np.float32
# int_dtype = np.int32
# Transform ragged array to one-dimensional array.
num_element_conn_data = [e.shape[0] for e in faces.flat]
length_connection_count = sum(num_element_conn_data)
element_conn_data = np.zeros(length_connection_count, dtype=faces[0].dtype)
start = 0
for ii in faces.flat:
element_conn_data[start:start + ii.shape[0]] = ii
start += ii.shape[0]
####################################################################################################################
# from ocgis.new_interface.variable import Variable, VariableCollection
# coll = VariableCollection()
#
# coll.add_variable(Variable('nodeCoords', value=nodes, dtype=float_dtype,
# dimensions=['nodeCount', 'coordDim'], units='degrees'))
#
# elementConn = Variable('elementConn', value=element_conn_data, dimensions='connectionCount',
# attrs={'long_name': 'Node indices that define the element connectivity.',
# 'start_index': start_index})
# if polygon_break_value is not None:
# elementConn.attrs['polygon_break_value'] = polygon_break_value
# coll.add_variable(elementConn)
#
# coll.add_variable(Variable('numElementConn', value=num_element_conn_data, dimensions='elementCount',
# dtype=int_dtype, attrs={'long_name': 'Number of nodes per element.'}))
#
# coll.add_variable(Variable('centerCoords', value=face_coordinates, dimensions=['elementCount', 'coordDim'],
# units='degrees', dtype=float_dtype))
#
# if face_uid_name is not None:
# coll.add_variable(Variable(face_uid_name, value=face_uid_value, dimensions='elementCount',
# attrs={'long_name': 'Element unique identifier.'}))
#
# coll.add_variable(Variable('elementArea', value=face_areas, dimensions='elementCount',
# attrs={'units': 'degrees', 'long_name': 'Element area in native units.'},
# dtype=float_dtype))
#
# coll.attrs['gridType'] = 'unstructured'
# coll.attrs['version'] = '0.9'
# coll.attrs['coordDim'] = 'longitude latitude'
#
# coll.write(ds)
node_counts = MPI_COMM.gather(nodes.shape[0])
element_counts = MPI_COMM.gather(faces.shape[0])
length_connection_counts = MPI_COMM.gather(length_connection_count)
if MPI_RANK == 0:
ds = nc.Dataset(filename, 'w', **dataset_kwargs)
try:
# Dimensions -----------------------------------------------------------------------------------------------
node_count_size = sum(node_counts)
element_count_size = sum(element_counts)
connection_count_size = sum(length_connection_counts)
node_count = ds.createDimension('nodeCount', node_count_size)
element_count = ds.createDimension('elementCount',
element_count_size)
coord_dim = ds.createDimension('coordDim', 2)
# element_conn_vltype = ds.createVLType(fm.faces[0].dtype, 'elementConnVLType')
connection_count = ds.createDimension('connectionCount',
connection_count_size)
# Variables ------------------------------------------------------------------------------------------------
node_coords = ds.createVariable('nodeCoords', nodes.dtype,
(node_count.name, coord_dim.name))
node_coords.units = 'degrees'
element_conn = ds.createVariable('elementConn',
element_conn_data.dtype,
(connection_count.name, ))
element_conn.long_name = 'Node indices that define the element connectivity.'
if polygon_break_value is not None:
element_conn.polygon_break_value = polygon_break_value
element_conn.start_index = start_index
num_element_conn = ds.createVariable('numElementConn', np.int32,
(element_count.name, ))
num_element_conn.long_name = 'Number of nodes per element.'
center_coords = ds.createVariable(
'centerCoords', face_coordinates.dtype,
(element_count.name, coord_dim.name))
center_coords.units = 'degrees'
if face_uid_value is not None:
uid = ds.createVariable(face_uid_name,
face_uid_value.dtype,
dimensions=(element_count.name, ))
uid.long_name = 'Element unique identifier.'
element_area = ds.createVariable('elementArea', nodes.dtype,
(element_count.name, ))
element_area.units = 'degrees'
element_area.long_name = 'Element area in native units.'
# Global Attributes ----------------------------------------------------------------------------------------
ds.gridType = 'unstructured'
ds.version = '0.9'
setattr(ds, coord_dim.name, "longitude latitude")
# element_mask = ds.createVariable('elementMask', np.int32, (element_count.name,))
finally:
ds.close()
# Fill variable values -----------------------------------------------------------------------------------------
node_coords_start = 0
node_coords_stop = None
element_conn_start = 0
element_conn_stop = None
for rank_to_write in range(MPI_SIZE):
log.debug(('node_coords_start', node_coords_start))
if MPI_RANK == rank_to_write:
ds = nc.Dataset(filename, mode='a')
try:
node_coords = ds.variables['nodeCoords']
element_conn = ds.variables['elementConn']
num_element_conn = ds.variables['numElementConn']
center_coords = ds.variables['centerCoords']
element_area = ds.variables['elementArea']
if face_uid_value is not None:
uid = ds.variables[face_uid_name]
node_coords_stop = node_coords_start + nodes.shape[0]
element_conn_stop = element_conn_start + element_conn_data.shape[
0]
node_coords[node_coords_start:node_coords_stop] = nodes
log.debug(('element_conn indices', element_conn_start,
element_conn_stop))
element_conn[
element_conn_start:element_conn_stop] = element_conn_data
start, stop = fmobj['section']
num_element_conn[start:stop] = num_element_conn_data
center_coords[start:stop] = face_coordinates
element_area[start:stop] = face_areas
if face_uid_value is not None:
uid[start:stop] = face_uid_value
finally:
ds.close()
node_coords_start = MPI_COMM.bcast(node_coords_stop,
root=rank_to_write)
element_conn_start = MPI_COMM.bcast(element_conn_stop,
root=rank_to_write)
MPI_COMM.Barrier()
def get_variables(gm, use_ragged_arrays=False, with_connectivity=True):
"""
:param gm: The geometry manager containing geometries to convert to mesh variables.
:type gm: :class:`pyugrid.flexible_mesh.helpers.GeometryManager`
:param pack: If ``True``, de-deduplicate shared coordinates.
:type pack: bool
:returns: A tuple of arrays with index locations corresponding to:
===== ================ =============================
Index Name Type
===== ================ =============================
0 face_nodes :class:`numpy.ma.MaskedArray`
1 face_edges :class:`numpy.ma.MaskedArray`
2 edge_nodes :class:`numpy.ndarray`
3 node_x :class:`numpy.ndarray`
4 node_y :class:`numpy.ndarray`
5 face_links :class:`numpy.ndarray`
6 face_ids :class:`numpy.ndarray`
7 face_coordinates :class:`numpy.ndarray`
===== ================ =============================
Information on individual variables may be found here: https://github.com/ugrid-conventions/ugrid-conventions/blob/9b6540405b940f0a9299af9dfb5e7c04b5074bf7/ugrid-conventions.md#2d-flexible-mesh-mixed-triangles-quadrilaterals-etc-topology
:rtype: tuple (see table for array types)
:raises: ValueError
"""
# tdk: update doc
if len(gm) < MPI_SIZE:
raise ValueError(
'The number of geometries must be greater than or equal to the number of processes.'
)
pbv = UgridToolsConstants.POLYGON_BREAK_VALUE
result = get_face_variables(gm, with_connectivity=with_connectivity)
face_links, nmax_face_nodes, face_ids, face_coordinates, cdict, n_coords, face_areas, section = result
# Find the start index for each rank.
all_n_coords = MPI_COMM.gather(n_coords)
if MPI_RANK == 0:
all_idx_start = [0] * MPI_SIZE
for idx in range(len(all_n_coords)):
if idx == 0:
continue
else:
all_idx_start[idx] = all_n_coords[idx -
1] + all_idx_start[idx - 1]
else:
all_idx_start = None
idx_start = MPI_COMM.scatter(all_idx_start)
log.debug(('idx_start', idx_start))
face_nodes, coordinates, edge_nodes = get_coordinate_dict_variables(
cdict, n_coords, polygon_break_value=pbv, idx_start=idx_start)
face_edges = face_nodes
face_ids = np.array(cdict.keys(), dtype=np.int32)
if not use_ragged_arrays:
new_arrays = []
for a in (face_links, face_nodes, face_edges):
new_arrays.append(
get_rectangular_array_from_object_array(
a, (a.shape[0], nmax_face_nodes)))
face_links, face_nodes, face_edges = new_arrays
return face_nodes, face_edges, edge_nodes, coordinates, face_links, face_ids, face_coordinates, face_areas, section
