from __future__ import absolute_import, division, print_function, \
unicode_literals
import numpy
import xarray
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def add_critical_land_blockages(dsMask, dsBlockages):
"""
Add the masks associated with one or more transects to the land mask
Parameters
----------
dsMask : xarray.Dataset
The mask to which critical blockages should be added
dsBlockages : xarray.Dataset
The transect masks defining critical land regions that should block
ocean flow (e.g. the Antarctic Peninsula)
Returns
-------
dsMask : xarray.Dataset
The mask with critical blockages included
"""
dsMask = dsMask.copy()
nTransects = dsBlockages.sizes['nTransects']
for transectIndex in range(nTransects):
dsMask.regionCellMasks[:, 0] = numpy.maximum(
dsBlockages.transectCellMasks[:, transectIndex],
dsMask.regionCellMasks[:, 0])
return dsMask
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def widen_transect_edge_masks(dsMask, dsMesh, latitude_threshold=43.0):
"""
Alter critical passages at polar latitudes to be at least two cells wide, to
avoid sea ice blockage
Parameters
----------
dsMask : xarray.Dataset
The mask to which critical blockages should be added
dsMesh : xarray.Dataset
The transect masks defining critical land regions that should block
ocean flow (e.g. the Antarctic Peninsula)
latitude_threshold : float
Minimum latitude, degrees, for transect widening
Returns
-------
dsMask : xarray.Dataset
The mask with critical blockages included
"""
latitude_threshold_radians = numpy.deg2rad(latitude_threshold)
dsMask = dsMask.copy()
maxEdges = dsMesh.sizes['maxEdges']
latMask = numpy.abs(dsMesh.latEdge) > latitude_threshold_radians
edgeMask = numpy.logical_and(
latMask, dsMask.transectEdgeMasks == 1)
for iEdge in range(maxEdges):
eoc = dsMesh.edgesOnCell[:, iEdge]-1
mask = numpy.logical_and(eoc >= 0,
edgeMask[eoc])
# cells with a neighboring transect edge should be masked to 1
dsMask['transectCellMasks'] = dsMask.transectCellMasks.where(
numpy.logical_not(mask), 1).astype(int)
return dsMask
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def add_land_locked_cells_to_mask(dsMask, dsMesh, latitude_threshold=43.0,
nSweeps=10):
"""
Find ocean cells that are land-locked, and alter the cell mask so that they
are counted as land cells.
Parameters
----------
dsMask : xarray.Dataset
A land-mask data set
dsMesh : xarray.Dataset
MPAS Mesh data set
latitude_threshold : float, optional
Minimum latitude, in degrees, for transect widening
nSweeps : int, optional
Maximum number of sweeps to search for land-locked cells
Returns
-------
dsMask : xarray.Dataset
A copy of the land-mask data set with land-locked cells added to the
mask for the first region
"""
dsMask = xarray.Dataset(dsMask)
dsMesh = dsMesh.copy(deep=True)
landMask = dsMask.regionCellMasks.max(dim='nRegions') > 0
dsMask['landMaskDiagnostic'] = xarray.where(landMask, 1, 0)
print("Running add_land_locked_cells_to_mask.py. Total number of cells: "
"{}".format(dsMesh.sizes['nCells']))
cellsOnCell = dsMesh.cellsOnCell - 1
nEdgesOnCell = dsMesh.nEdgesOnCell
nextCellsOnCell = cellsOnCell.copy(deep=True)
prevCellsOnCell = cellsOnCell.copy(deep=True)
for iEdgeOnCell in range(nextCellsOnCell.shape[1]):
iP1 = numpy.mod(iEdgeOnCell + 1, nEdgesOnCell)
nextCellsOnCell[:, iEdgeOnCell] = cellsOnCell[:, iP1]
iM1 = numpy.mod(iEdgeOnCell - 1, nEdgesOnCell)
prevCellsOnCell[:, iEdgeOnCell] = cellsOnCell[:, iM1]
dsMesh['cellsOnCell'] = cellsOnCell
dsMesh['nextCellsOnCell'] = nextCellsOnCell
dsMesh['prevCellsOnCell'] = prevCellsOnCell
dsMesh['latCell'] = numpy.rad2deg(dsMesh.latCell)
dsMesh['lonCell'] = numpy.rad2deg(dsMesh.lonCell)
landMask, removable = _remove_cells_with_isolated_edges1(
dsMask, dsMesh, landMask, latitude_threshold)
landMask = _remove_cells_with_isolated_edges2(
dsMask, dsMesh, landMask, removable, nSweeps)
oceanMask = _flood_fill(dsMask, dsMesh, landMask, removable)
landMask = _revert_cells_with_connected_edges(
dsMask, dsMesh, oceanMask, landMask, removable, nSweeps)
return dsMask
def _remove_cells_with_isolated_edges1(dsMask, dsMesh, landMask,
latitude_threshold):
print("Step 1: Searching for land-locked cells. Remove cells that only "
"have isolated active edges.")
landMaskNew = landMask.copy(deep=True)
active = numpy.logical_not(landMask)
removable = numpy.logical_and(
numpy.abs(dsMesh.latCell) >= latitude_threshold, active)
cellsOnCell = dsMesh.cellsOnCell
valid = numpy.logical_and(removable, cellsOnCell >= 0)
activeEdge = numpy.logical_and(valid, active[cellsOnCell])
nextCellsOnCell = dsMesh.nextCellsOnCell
valid = numpy.logical_and(removable, nextCellsOnCell >= 0)
activeNextEdge = numpy.logical_and(valid, active[nextCellsOnCell])
# which vertices have adjacent active edges on this cell?
activeAdjacentEdges = numpy.logical_and(activeEdge, activeNextEdge)
# which removable cells have no pairs of adjacent active cells?
noActiveAdjacentEdges = numpy.logical_and(
removable, numpy.logical_not(numpy.any(activeAdjacentEdges, axis=1)))
landMaskNew[noActiveAdjacentEdges] = 1
landLockedCounter = numpy.count_nonzero(noActiveAdjacentEdges)
dsMask.regionCellMasks[:, 0] = numpy.maximum(dsMask.regionCellMasks[:, 0],
1*noActiveAdjacentEdges)
dsMask.landMaskDiagnostic[noActiveAdjacentEdges] = 2
print(" Number of landLocked cells: {}".format(landLockedCounter))
return landMaskNew, removable
def _remove_cells_with_isolated_edges2(dsMask, dsMesh, landMask, removable,
nSweeps):
print("Step 2: Searching for land-locked cells. Remove cells that have "
"any isolated active edges.")
cellsOnCell = dsMesh.cellsOnCell
nextCellsOnCell = dsMesh.nextCellsOnCell
prevCellsOnCell = dsMesh.prevCellsOnCell
for iSweep in range(nSweeps):
landLockedCounter = 0
landMaskNew = landMask.copy(deep=True)
active = numpy.logical_not(landMask)
mask = numpy.logical_and(removable, active)
valid = numpy.logical_and(mask, cellsOnCell >= 0)
activeEdge = numpy.logical_and(valid, active[cellsOnCell])
valid = numpy.logical_and(mask, nextCellsOnCell >= 0)
activeNextEdge = numpy.logical_and(valid, active[nextCellsOnCell])
valid = numpy.logical_and(mask, prevCellsOnCell >= 0)
activePrevEdge = numpy.logical_and(valid, active[prevCellsOnCell])
# an edge is land-locked if it is active but neither neighbor is active
landLockedEdges = numpy.logical_and(
activeEdge,
numpy.logical_not(
numpy.logical_or(activePrevEdge, activeNextEdge)))
landLockedCells = numpy.any(landLockedEdges, axis=1)
landLockedCounter = numpy.count_nonzero(landLockedCells)
if landLockedCounter > 0:
landMaskNew[landLockedCells] = 1
dsMask.regionCellMasks[landLockedCells, 0] = 1
dsMask.landMaskDiagnostic[landLockedCells] = 3
landMask = landMaskNew
print(" Sweep: {} Number of landLocked cells removed: {}".format(
iSweep + 1, landLockedCounter))
if landLockedCounter == 0:
break
return landMask
def _flood_fill(dsMask, dsMesh, landMask, removable):
print("Step 3: Perform flood fill, starting from open ocean.")
# init flood fill to 0 for water, -1 for land, 1 for known open ocean
floodFill = xarray.where(
numpy.logical_and(removable, numpy.logical_not(landMask)), 0, -1)
latCell = dsMesh.latCell
lonCell = dsMesh.lonCell
cellsOnCell = dsMesh.cellsOnCell
# North Pole
mask = latCell > 84.0
openOceanMask = mask
# Arctic
mask = numpy.logical_and(
numpy.logical_and(lonCell > 160.0, lonCell < 230.0),
latCell > 73.0)
openOceanMask = numpy.logical_or(openOceanMask, mask)
# North Atlantic
mask = numpy.logical_and(
numpy.logical_and(lonCell > 315.0, lonCell < 340.0),
numpy.logical_and(latCell > 15.0, latCell < 45.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
mask = numpy.logical_and(
numpy.logical_and(lonCell > 290.0, lonCell < 300.0),
numpy.logical_and(latCell > 72.0, latCell < 75.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
mask = numpy.logical_and(
numpy.logical_and(lonCell > 0.0, lonCell < 10.0),
numpy.logical_and(latCell > 70.0, latCell < 75.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
# North Pacific
mask = numpy.logical_and(
numpy.logical_and(lonCell > 150.0, lonCell < 225.0),
numpy.logical_and(latCell > 0.0, latCell < 45.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
# South Atlantic
mask = numpy.logical_and(
numpy.logical_and(lonCell > 0.0, lonCell < 5.0),
numpy.logical_and(latCell > -60.0, latCell < 0.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
# South Pacific
mask = numpy.logical_and(
numpy.logical_and(lonCell > 180.0, lonCell < 280.0),
numpy.logical_and(latCell > -60.0, latCell < -10.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
# Southern Ocean
mask = numpy.logical_and(
numpy.logical_and(lonCell > 0.0, lonCell < 165.0),
numpy.logical_and(latCell > -60.0, latCell < -45.0))
openOceanMask = numpy.logical_or(openOceanMask, mask)
mask = numpy.logical_and(floodFill == 0, openOceanMask)
floodFill[mask] = 1
nFloodableCells = numpy.count_nonzero(floodFill == 0)
print(" Initial number of flood cells: {}".format(nFloodableCells))
dsMask.landMaskDiagnostic[floodFill == 1] = 5
# sweep over neighbors of known open ocean points
for iSweep in range(dsMesh.sizes['nCells']):
newFloodCellsThisSweep = 0
mask = floodFill == 0
cellIndices = numpy.nonzero(mask.values)[0]
for iCellOnCell in range(cellsOnCell.shape[1]):
neighbors = cellsOnCell[cellIndices, iCellOnCell]
filledNeighbors = numpy.logical_and(neighbors >= 0,
floodFill[neighbors] == 1)
fillIndices = cellIndices[filledNeighbors.values]
if(len(fillIndices) > 0):
floodFill[fillIndices] = 1
newFloodCellsThisSweep += len(fillIndices)
print(" Sweep {} new flood cells this sweep: {}".format(
iSweep, newFloodCellsThisSweep))
if (newFloodCellsThisSweep == 0):
break
oceanMask = (floodFill == 1)
print('oceanMask:', numpy.count_nonzero(oceanMask))
return oceanMask
def _revert_cells_with_connected_edges(dsMask, dsMesh, oceanMask, landMask,
removable, nSweeps):
print("Step 4: Searching for land-locked cells, step 3: revert cells with "
"connected active edges")
cellsOnCell = dsMesh.cellsOnCell
nextCellsOnCell = dsMesh.nextCellsOnCell
prevCellsOnCell = dsMesh.prevCellsOnCell
for iSweep in range(nSweeps):
landMaskNew = numpy.array(landMask)
# only remove a cell that was added in Step 2,
# _remove_cells_with_isolated_edges2
mask = numpy.logical_and(removable, dsMask.landMaskDiagnostic == 3)
notLand = numpy.logical_not(landMask)
valid = numpy.logical_and(mask, cellsOnCell >= 0)
oceanEdge = numpy.logical_and(valid, oceanMask[cellsOnCell])
valid = numpy.logical_and(mask, nextCellsOnCell >= 0)
activeNextEdge = numpy.logical_and(valid, notLand[nextCellsOnCell])
valid = numpy.logical_and(mask, prevCellsOnCell >= 0)
activePrevEdge = numpy.logical_and(valid, notLand[prevCellsOnCell])
reactivate = numpy.any(
numpy.logical_and(
oceanEdge,
numpy.logical_or(activePrevEdge, activeNextEdge)), axis=1)
landLockedCounter = numpy.count_nonzero(reactivate)
if landLockedCounter > 0:
landMaskNew[reactivate] = 0
dsMask.regionCellMasks[reactivate, 0] = 0
oceanMask[reactivate] = 1
dsMask.landMaskDiagnostic[reactivate] = 4
landMask = landMaskNew
print(" Sweep: {} Number of land-locked cells returned: {}".format(
iSweep + 1, landLockedCounter))
if landLockedCounter == 0:
break
return landMask