from __future__ import absolute_import, division, print_function, \
unicode_literals
import xarray
import numpy
import logging
import sys
from geometric_features.aggregation.ocean import moc
import mpas_tools.mesh.conversion
from mpas_tools.io import write_netcdf
[docs]def make_moc_basins_and_transects(gf, mesh_filename,
mask_and_transect_filename,
geojson_filename=None,
mask_filename=None,
logger=None,
dir=None):
"""
Builds features defining the ocean basins and southern transects used in
computing the meridional overturning circulation (MOC)
Parameters
----------
gf : geometric_features.GeometricFeatures
An object that knows how to download and read geometric features
mesh_filename : str
A file with MPAS mesh information
mask_and_transect_filename : str
A file to write the MOC region masks and southern-boundary transects to
geojson_filename : str, optional
A file to write MOC regions to
mask_filename : str, optional
A file to write MOC region masks to
logger : ``logging.Logger``, optional
A logger for the output if not stdout
dir : str, optional
A directory in which a temporary directory will be added with files
produced during conversion and then deleted upon completion.
Returns
-------
fc : geometric_features.FeatureCollection
The new feature collection
"""
# Authors
# -------
# Xylar Asay-Davis
fcMOC = moc(gf)
if geojson_filename is not None:
fcMOC.to_geojson(geojson_filename)
dsMesh = xarray.open_dataset(mesh_filename)
dsMasks = mpas_tools.mesh.conversion.mask(dsMesh=dsMesh, fcMask=fcMOC,
logger=logger, dir=dir)
if mask_filename is not None:
write_netcdf(dsMasks, mask_filename, char_dim_name='StrLen')
dsMasksAndTransects = add_moc_southern_boundary_transects(dsMasks, dsMesh,
logger=logger)
write_netcdf(dsMasksAndTransects, mask_and_transect_filename,
char_dim_name='StrLen')
[docs]def add_moc_southern_boundary_transects(dsMask, dsMesh, logger=None):
"""
Parameters
----------
dsMask : ``xarray.Dataset``
Region masks defining MOC basins
dsMesh : ``xarray.Dataset``, optional
An MPAS mesh on which the masks should be created
logger : ``logging.Logger``, optional
A logger for the output if not stdout
Returns
-------
dsMask : ``xarray.Dataset``
Region masks defining MOC basins and the corresponding southern-boundary
transects
"""
useStdout = logger is None
if useStdout:
logger = logging.getLogger()
logger.addHandler(logging.StreamHandler(sys.stdout))
logger.setLevel(logging.INFO)
southernBoundaryEdges, southernBoundaryEdgeSigns, \
southernBoundaryVertices = \
_extract_southern_boundary(dsMesh, dsMask, latBuffer=3.*numpy.pi/180.,
logger=logger)
_add_transects_to_moc(dsMesh, dsMask, southernBoundaryEdges,
southernBoundaryEdgeSigns,
southernBoundaryVertices)
if useStdout:
logger.handlers = []
return dsMask
def _extract_southern_boundary(mesh, mocMask, latBuffer, logger):
"""
Extracts the southern boundary of each region mask in mocMask. Mesh info
is taken from mesh. latBuffer is a number of radians above the southern-
most point that should be considered to definitely be in the southern
boundary.
"""
nCells = mesh.dims['nCells']
nEdges = mesh.dims['nEdges']
nRegions = mocMask.dims['nRegions']
assert(mocMask.dims['nCells'] == nCells)
# convert to python zero-based indices
cellsOnEdge = mesh.variables['cellsOnEdge'].values-1
verticesOnEdge = mesh.variables['verticesOnEdge'].values-1
edgesOnVertex = mesh.variables['edgesOnVertex'].values-1
latEdge = mesh.variables['latEdge'].values
cellsOnEdgeInRange = numpy.logical_and(cellsOnEdge >= 0,
cellsOnEdge < nCells)
southernBoundaryEdges = []
southernBoundaryEdgeSigns = []
southernBoundaryVertices = []
for iRegion in range(nRegions):
name = mocMask.regionNames[iRegion].values.astype('U')
logger.info(name)
cellMask = mocMask.variables['regionCellMasks'][:, iRegion].values
# land cells are outside not in the MOC region
cellsOnEdgeMask = numpy.zeros(cellsOnEdge.shape, bool)
# set mask values for cells that are in range (not land)
cellsOnEdgeMask[cellsOnEdgeInRange] = \
cellMask[cellsOnEdge[cellsOnEdgeInRange]] == 1
logger.info(' computing edge sign...')
edgeSign = numpy.zeros(nEdges)
# positive sign if the first cell on edge is in the region
mask = numpy.logical_and(cellsOnEdgeMask[:, 0],
numpy.logical_not(cellsOnEdgeMask[:, 1]))
edgeSign[mask] = -1.
# negative sign if the second cell on edge is in the region
mask = numpy.logical_and(cellsOnEdgeMask[:, 1],
numpy.logical_not(cellsOnEdgeMask[:, 0]))
edgeSign[mask] = 1.
isMOCBoundaryEdge = edgeSign != 0.
edgesMOCBoundary = numpy.arange(nEdges)[isMOCBoundaryEdge]
logger.info(' done.')
startEdge = numpy.argmin(latEdge[isMOCBoundaryEdge])
startEdge = edgesMOCBoundary[startEdge]
minLat = latEdge[startEdge]
logger.info(' getting edge sequence...')
# follow the boundary from this point to get a loop of edges
# Note: it is possible but unlikely that the southern-most point is
# not within bulk region of the MOC mask if the region is not a single
# shape
edgeSequence, edgeSequenceSigns, vertexSequence = \
_get_edge_sequence_on_boundary(startEdge, edgeSign, edgesOnVertex,
verticesOnEdge)
logger.info(f' done: {len(edgeSequence)} edges in transect.')
aboveSouthernBoundary = latEdge[edgeSequence] > minLat + latBuffer
# find and eliminate the longest contiguous sequence (if any) from the
# edge sequence that is above the possible region of the soutehrn
# boundary
belowToAbove = \
numpy.logical_and(numpy.logical_not(aboveSouthernBoundary[0:-1]),
aboveSouthernBoundary[1:])
aboveToBelow = \
numpy.logical_and(aboveSouthernBoundary[0:-1],
numpy.logical_not(aboveSouthernBoundary[1:]))
startIndices = numpy.arange(1, len(edgeSequence))[belowToAbove]
endIndices = numpy.arange(1, len(edgeSequence))[aboveToBelow]
assert(len(startIndices) == len(endIndices))
if len(startIndices) == 0:
# the whole sequence is the southern boundary
southernBoundaryEdges.append(edgeSequence)
southernBoundaryEdgeSigns.append(edgeSequenceSigns)
southernBoundaryVertices.append(vertexSequence)
continue
# there are some parts of the sequence above the boundary. Let's
# eliminate the longest one.
aboveLength = endIndices - startIndices
longest = numpy.argmax(aboveLength)
# we want all the indices in the sequence *not* part of the longest
indices = numpy.arange(endIndices[longest],
startIndices[longest] + len(edgeSequence))
indices = numpy.mod(indices, len(edgeSequence))
southernBoundaryEdges.append(edgeSequence[indices])
southernBoundaryEdgeSigns.append(edgeSequenceSigns[indices])
# we want one extra vertex in the vertex sequence
indices = numpy.arange(endIndices[longest],
startIndices[longest] + len(edgeSequence) + 1)
indices = numpy.mod(indices, len(edgeSequence))
southernBoundaryVertices.append(vertexSequence[indices])
return southernBoundaryEdges, southernBoundaryEdgeSigns, \
southernBoundaryVertices
def _add_transects_to_moc(mesh, mocMask, southernBoundaryEdges,
southernBoiundaryEdgeSigns, southernBoundaryVertices):
"""
Creates transect fields in mocMask from the edges, edge signs and
vertices defining the southern boundaries. Mesh info (nEdges and
nVertices) is taken from the mesh file.
"""
nTransects = len(southernBoundaryEdges)
nEdges = mesh.dims['nEdges']
nVertices = mesh.dims['nVertices']
maxEdgesInTransect = numpy.amax([len(southernBoundaryEdges[iTransect])
for iTransect in range(nTransects)])
maxVerticesInTransect = \
numpy.amax([len(southernBoundaryVertices[iTransect])
for iTransect in range(nTransects)])
transectEdgeMasks = numpy.zeros((nEdges, nTransects),
numpy.int32)
transectEdgeMaskSigns = numpy.zeros((nEdges, nTransects),
numpy.int32)
transectEdgeGlobalIDs = numpy.zeros((nTransects, maxEdgesInTransect),
numpy.int32)
transectVertexMasks = numpy.zeros((nVertices, nTransects),
numpy.int32)
transectVertexGlobalIDs = numpy.zeros((nTransects, maxVerticesInTransect),
numpy.int32)
for iTransect in range(nTransects):
transectEdgeMasks[southernBoundaryEdges[iTransect], iTransect] = 1
transectEdgeMaskSigns[southernBoundaryEdges[iTransect], iTransect] \
= southernBoiundaryEdgeSigns[iTransect]
transectCount = len(southernBoundaryEdges[iTransect])
transectEdgeGlobalIDs[iTransect, 0:transectCount] \
= southernBoundaryEdges[iTransect] + 1
transectVertexMasks[southernBoundaryVertices[iTransect], iTransect] = 1
transectCount = len(southernBoundaryVertices[iTransect])
transectVertexGlobalIDs[iTransect, 0:transectCount] \
= southernBoundaryVertices[iTransect] + 1
mocMask['transectEdgeMasks'] = \
(('nEdges', 'nTransects'), transectEdgeMasks)
mocMask['transectEdgeMaskSigns'] = (('nEdges', 'nTransects'),
transectEdgeMaskSigns)
mocMask['transectEdgeGlobalIDs'] = (('nTransects', 'maxEdgesInTransect'),
transectEdgeGlobalIDs)
mocMask['transectVertexMasks'] = (('nVertices', 'nTransects'),
transectVertexMasks)
mocMask['transectVertexGlobalIDs'] = \
(('nTransects', 'maxVerticesInTransect'), transectVertexGlobalIDs)
if 'nRegionsInGroup' not in mocMask:
nRegions = mocMask.sizes['nRegions']
nRegionGroups = 2
nRegionsInGroup = nRegions*numpy.ones(nRegionGroups, dtype=int)
regionsInGroup = numpy.zeros((nRegionGroups, nRegions), dtype=int)
regionGroupNames = ['MOCBasinRegionsGroup', 'all']
regionNames = mocMask.regionNames.values
nChar = 64
for index in range(nRegionGroups):
regionsInGroup[index, :] = numpy.arange(1, nRegions+1)
mocMask['nRegionsInGroup'] = (('nRegionGroups',), nRegionsInGroup)
mocMask['regionsInGroup'] = (('nRegionGroups', 'maxRegionsInGroup'),
regionsInGroup)
mocMask['regionGroupNames'] = \
(('nRegionGroups',), numpy.zeros((nRegionGroups,),
dtype=f'|S{nChar}'))
for index in range(nRegionGroups):
mocMask['regionGroupNames'][index] = regionGroupNames[index]
# we need to make sure the region names use the same string length
mocMask['regionNames'] = \
(('nRegions',), numpy.zeros((nRegions,),
dtype=f'|S{nChar}'))
for index in range(nRegions):
mocMask['regionNames'][index] = regionNames[index]
mocMask['transectNames'] = mocMask.regionNames.rename(
{'nRegions': 'nTransects'})
mocMask['nTransectsInGroup'] = mocMask.nRegionsInGroup.rename(
{'nRegionGroups': 'nTransectGroups'})
mocMask['transectsInGroup'] = mocMask.regionsInGroup.rename(
{'nRegionGroups': 'nTransectGroups',
'maxRegionsInGroup': 'maxTransectsInGroup'})
mocMask['transectGroupNames'] = mocMask.regionGroupNames.rename(
{'nRegionGroups': 'nTransectGroups'})
def _get_edge_sequence_on_boundary(startEdge, edgeSign, edgesOnVertex,
verticesOnEdge):
"""
Follows the boundary from a starting edge to produce a sequence of
edges that form a closed loop.
startEdge is an edge on the boundary that will be both the start and
end of the loop.
isBoundaryEdge is a mask that indicates which edges are on the
boundary
returns lists of edges, edge signs and vertices
"""
iEdge = startEdge
edgeSequence = []
vertexSequence = []
while True:
assert(edgeSign[iEdge] == 1. or edgeSign[iEdge] == -1.)
if edgeSign[iEdge] == 1.:
v = 0
else:
v = 1
iVertex = verticesOnEdge[iEdge, v]
eov = edgesOnVertex[iVertex, :]
# find the edge that is not iEdge but is on the boundary
nextEdge = -1
for edge in eov:
if edge != -1 and edge != iEdge and edgeSign[edge] != 0:
nextEdge = edge
break
assert(nextEdge != -1)
edgeSequence.append(iEdge)
vertexSequence.append(iVertex)
iEdge = nextEdge
if iEdge == startEdge:
break
edgeSequence = numpy.array(edgeSequence)
edgeSequenceSigns = edgeSign[edgeSequence]
vertexSequence = numpy.array(vertexSequence)
return edgeSequence, edgeSequenceSigns, vertexSequence