Source code for mpas_tools.ocean.moc

from __future__ import absolute_import, division, print_function, \

import xarray
import numpy
import logging
import sys
from geometric_features.aggregation.ocean import moc

import mpas_tools.mesh.conversion
from 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) # make sure both cells on the dummy edge at the end are out of range cellsOnEdgeInRange[-1, :] = False southernBoundaryEdges = [] southernBoundaryEdgeSigns = [] southernBoundaryVertices = [] for iRegion in range(nRegions): name = mocMask.regionNames[iRegion].values.astype('U') 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' 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]' done.') startEdge = numpy.argmin(latEdge[isMOCBoundaryEdge]) startEdge = edgesMOCBoundary[startEdge] minLat = latEdge[startEdge]' 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)' done: {} edges in transect.'.format(len(edgeSequence))) 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='|S{}'.format(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='|S{}'.format(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 != 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