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Add a tool to create transect cell and edge fields with edge sign and distance #7
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# Python Transect Tools | ||
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## compute_transects.py | ||
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Computes transport through sections. | ||
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Example call: | ||
``` | ||
./compute_transects.py | ||
-k transect_masks.nc | ||
-m MPAS_mesh.nc | ||
-t 'RUN_PATH/analysis_members/timeSeriesStatsMonthly.*.nc' | ||
-n 'all' | ||
``` | ||
To create the `transect_masks.nc` file, load e3sm-unified and: | ||
``` | ||
MpasMaskCreator.x MPAS_mesh.nc transect_masks.nc -f transect_definitions.geojson | ||
``` | ||
where the `transect_definitions.geojson` file includes a sequence of lat/lon | ||
points for each transect. | ||
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On LANL IC, example file is at | ||
``` | ||
/usr/projects/climate/mpeterse/analysis_input_files/geojson_files/SingleRegionAtlanticWTransportTransects.geojson | ||
``` | ||
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## create_transect_masks.py | ||
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Requires a conda environment with: | ||
* `python` | ||
* `geometric_features` | ||
* `matplotlib` | ||
* `mpas_tools` | ||
* `netcdf4` | ||
* `numpy` | ||
* `scipy` | ||
* `shapely` | ||
* `xarray` | ||
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The tools creates cell and edge masks, distance along the transect of cells | ||
and edges in the mask, and the edge sign on edges. It also includes | ||
information (distance, cell and edge indices, interpolation weights, etc.) | ||
along the transect itself to aid plotting. | ||
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The required inputs are an MPAS mesh file and a geojson file or the name of an | ||
ocean transect from `geometric_features`. The required output is a filename | ||
with the masks and other information about the transect. | ||
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## cut_closed_transect.py | ||
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If a transect is a closed loop, the path of edges and edge signs don't work | ||
correctly (the shortest path between the beginning and end of the transect is | ||
trivial and involves a single edge). To avoid this, we provide a tool for | ||
cutting a square (in lat/lon space) out of the transect to sever the loop. | ||
The user provides a latitude and longitude (used to locate the closest point) | ||
on the transect and the size of the square to cut out. | ||
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#!/usr/bin/env python | ||
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import argparse | ||
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import numpy as np | ||
import xarray as xr | ||
from geometric_features import read_feature_collection | ||
from geometric_features import GeometricFeatures | ||
from mpas_tools.cime.constants import constants | ||
from mpas_tools.logging import LoggingContext | ||
from mpas_tools.io import write_netcdf | ||
from mpas_tools.mesh.mask import compute_mpas_transect_masks | ||
from mpas_tools.parallel import create_pool | ||
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from transect.vert import compute_transect | ||
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def combine_transect_datasets(ds_mesh, fc_transect, out_filename, pool, | ||
logger): | ||
""" | ||
Combine transects masks on cells and edges with a dataset for plotting | ||
that describes how the transect slices through cell and edge geometry. | ||
Add fields on edges and cells that define the (mean) distance along the | ||
transect for each cell or edge in the transect | ||
""" | ||
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earth_radius = constants['SHR_CONST_REARTH'] | ||
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ds_mask = compute_mpas_transect_masks(dsMesh=ds_mesh, fcMask=fc_transect, | ||
earthRadius=earth_radius, | ||
maskTypes=('cell', 'edge',), | ||
logger=logger, | ||
pool=pool, addEdgeSign=True) | ||
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feature = fc_transect.features[0] | ||
geom_type = feature['geometry']['type'] | ||
if geom_type == 'LineString': | ||
coordinates = [feature['geometry']['coordinates']] | ||
elif geom_type == 'MultiLineString': | ||
coordinates = feature['geometry']['coordinates'] | ||
else: | ||
raise ValueError( | ||
f'Unexpected geometry type for the transect {geom_type}') | ||
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lon = [] | ||
lat = [] | ||
for coords in coordinates: | ||
lon_local, lat_local = zip(*coords) | ||
lon.extend(lon_local) | ||
lat.extend(lat_local) | ||
lon = xr.DataArray(data=lon, dims='nTransectPoints') | ||
lat = xr.DataArray(data=lat, dims='nTransectPoints') | ||
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layer_thickness = ds_mesh.layerThickness | ||
bottom_depth = ds_mesh.bottomDepth | ||
min_level_cell = ds_mesh.minLevelCell | ||
max_level_cell = ds_mesh.maxLevelCell | ||
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ds_transect = compute_transect(lon, lat, ds_mesh, layer_thickness, | ||
bottom_depth, min_level_cell, | ||
max_level_cell, spherical=True) | ||
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ds = ds_mask | ||
for var in ds_transect.data_vars: | ||
ds[var] = ds_transect[var] | ||
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add_distance_field(ds, logger) | ||
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write_netcdf(ds, out_filename) | ||
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def add_distance_field(ds, logger): | ||
""" | ||
Add fields on edges and cells that define the (mean) distance along the | ||
transect for each cell or edge in the transect | ||
""" | ||
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dist_cell = np.zeros(ds.sizes['nCells']) | ||
count_cell = np.zeros(ds.sizes['nCells'], dtype=int) | ||
dist_edge = np.zeros(ds.sizes['nEdges']) | ||
count_edge = np.zeros(ds.sizes['nEdges'], dtype=int) | ||
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logger.info('Adding transect distance fields on cells and edges...') | ||
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for segment in range(ds.sizes['nSegments']): | ||
icell = ds.horizCellIndices.isel(nSegments=segment).values | ||
iedge = ds.horizEdgeIndices.isel(nSegments=segment).values | ||
# the distance for the midpoint of the segment is the mean | ||
# of the distances of the end points | ||
dist = 0.5 * (ds.dNode.isel(nHorizNodes=segment) + | ||
ds.dNode.isel(nHorizNodes=segment + 1)) | ||
dist_cell[icell] += dist | ||
count_cell[icell] += 1 | ||
dist_edge[iedge] += dist | ||
count_edge[iedge] += 1 | ||
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mask = count_cell > 0 | ||
dist_cell[mask] /= count_cell[mask] | ||
dist_cell[np.logical_not(mask)] = np.nan | ||
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mask = count_edge > 0 | ||
dist_edge[mask] /= count_edge[mask] | ||
dist_edge[np.logical_not(mask)] = np.nan | ||
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ds['transectDistanceCell'] = ('nCells', dist_cell) | ||
ds['transectDistanceEdge'] = ('nEdges', dist_edge) | ||
logger.info('Done.') | ||
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def main(): | ||
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parser = argparse.ArgumentParser(description=''' | ||
creates transect edge and cell masks along with edge sign and distance | ||
along the transect''') | ||
parser.add_argument('-m', dest='mesh_filename', | ||
help='MPAS-Ocean horizontal and vertical filename', | ||
required=True) | ||
parser.add_argument('-g', dest='geojson_filename', | ||
help='Geojson filename with transect', required=False) | ||
parser.add_argument('-f', dest='feature_name', | ||
help='Name of an ocean transect from ' | ||
'geometric_features', | ||
required=False) | ||
parser.add_argument('-o', dest='out_filename', | ||
help='Edge transect filename', required=True) | ||
parser.add_argument( | ||
"--process_count", required=False, dest="process_count", type=int, | ||
help="The number of processes to use to compute masks. The " | ||
"default is to use all available cores") | ||
parser.add_argument( | ||
"--multiprocessing_method", dest="multiprocessing_method", | ||
default='forkserver', | ||
help="The multiprocessing method use for python mask creation " | ||
"('fork', 'spawn' or 'forkserver')") | ||
args = parser.parse_args() | ||
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if args.geojson_filename is None and args.feature_name is None: | ||
raise ValueError('Must supply either a geojson file or a transect ' | ||
'name') | ||
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if args.geojson_filename is not None: | ||
fc_transect = read_feature_collection(args.geojson_filename) | ||
else: | ||
gf = GeometricFeatures() | ||
fc_transect = gf.read(componentName='ocean', objectType='transect', | ||
featureNames=[args.feature_name]) | ||
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ds_mesh = xr.open_dataset(args.mesh_filename) | ||
if 'Time' in ds_mesh.dims: | ||
ds_mesh = ds_mesh.isel(Time=0) | ||
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pool = create_pool(process_count=args.process_count, | ||
method=args.multiprocessing_method) | ||
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with LoggingContext('create_transect_masks') as logger: | ||
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combine_transect_datasets(ds_mesh, fc_transect, args.out_filename, | ||
pool, logger) | ||
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if __name__ == '__main__': | ||
main() |
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#!/usr/bin/env python | ||
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import argparse | ||
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import numpy as np | ||
from geometric_features import ( | ||
GeometricFeatures, | ||
read_feature_collection | ||
) | ||
from shapely.geometry import ( | ||
mapping, | ||
Polygon, | ||
shape | ||
) | ||
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def cut_transect(fc_transect, lat, lon, size, out_filename): | ||
""" | ||
Cut a square out of the given closed-loop transect to break the loop. | ||
""" | ||
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# find the closest point in the transect to the specificed lat/lon | ||
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feature = fc_transect.features[0] | ||
coordinates = feature['geometry']['coordinates'] | ||
feature_type = feature['geometry']['type'] | ||
if feature_type == 'LineString': | ||
coordinates = [coordinates] | ||
elif feature_type != 'MultiLineString': | ||
raise ValueError( | ||
f'Unexpected geometry type for transect {feature_type}') | ||
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min_dist = None | ||
center_lon = None | ||
center_lan = None | ||
for coords in coordinates: | ||
lon_local, lat_local = zip(*coords) | ||
dist = np.sqrt((np.array(lon_local) - lon)**2 + | ||
(np.array(lat_local) - lat)**2) | ||
index_min = np.argmin(dist) | ||
if min_dist is None or dist[index_min] < min_dist: | ||
center_lon = lon_local[index_min] | ||
center_lan = lat_local[index_min] | ||
min_dist = dist[index_min] | ||
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square = Polygon([(center_lon - 0.5 * size, center_lan - 0.5 * size), | ||
(center_lon - 0.5 * size, center_lan + 0.5 * size), | ||
(center_lon + 0.5 * size, center_lan + 0.5 * size), | ||
(center_lon + 0.5 * size, center_lan - 0.5 * size), | ||
(center_lon - 0.5 * size, center_lan - 0.5 * size)]) | ||
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feature = fc_transect.features[0] | ||
transect_shape = shape(feature['geometry']) | ||
transect_shape = transect_shape.difference(square) | ||
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# now sort the coordinates so the start and end of the transect are at the | ||
# dividing point | ||
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feature['geometry'] = mapping(transect_shape) | ||
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feature_type = feature['geometry']['type'] | ||
if feature_type == 'MultiLineString': | ||
coordinates = feature['geometry']['coordinates'] | ||
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# reorder the LineStrings so the first one starts right after the cut | ||
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closest = None | ||
min_dist = None | ||
for index, coords in enumerate(coordinates): | ||
lon_first, lat_first = coords[0] | ||
dist = np.sqrt((lon_first - lon)**2 + (lat_first - lat)**2) | ||
if min_dist is None or dist < min_dist: | ||
closest = index | ||
min_dist = dist | ||
new_coords = list(coordinates[closest:]) | ||
new_coords.extend(list(coordinates[:closest])) | ||
feature['geometry']['coordinates'] = tuple(new_coords) | ||
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fc_transect.to_geojson(out_filename) | ||
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def main(): | ||
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parser = argparse.ArgumentParser(description=''' | ||
cut the given transect loop as close as possible to the given | ||
latitude and longitude''') | ||
parser.add_argument('-g', dest='geojson_filename', | ||
help='Geojson filename with transect', required=False) | ||
parser.add_argument('-f', dest='feature_name', | ||
help='Name of an ocean transect from ' | ||
'geometric_features', | ||
required=False) | ||
parser.add_argument('--lat', dest='lat', type=float, | ||
help='The approx. latitude at which to cut the loop', | ||
required=True) | ||
parser.add_argument('--lon', dest='lon', type=float, | ||
help='The approx. longitude at which to cut the loop', | ||
required=True) | ||
parser.add_argument('--size', dest='size', type=float, | ||
help='The size in degrees of the square used to cut ' | ||
'the loop', | ||
required=True) | ||
parser.add_argument('-o', dest='out_filename', | ||
help='The geojson file with the cut transect to write ' | ||
'out', | ||
required=True) | ||
args = parser.parse_args() | ||
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if args.geojson_filename is None and args.feature_name is None: | ||
raise ValueError('Must supply either a geojson file or a transect ' | ||
'name') | ||
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if args.geojson_filename is not None: | ||
fc_transect = read_feature_collection(args.geojson_filename) | ||
else: | ||
gf = GeometricFeatures() | ||
fc_transect = gf.read(componentName='ocean', objectType='transect', | ||
featureNames=[args.feature_name]) | ||
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cut_transect(fc_transect, args.lat, args.lon, args.size, args.out_filename) | ||
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if __name__ == '__main__': | ||
main() |
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""" | ||
Copied from Polaris | ||
""" |
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To me, this part is the important new addition.
The
transect
module is just here because the version in Polaris (which this is a copy of) is cleaner than the version in MPAS-Tools but we don't have a way to use it in QuickViz because Polaris isn't a simple conda package that can be installed from conda-forge.