Move landice conda package scripts

conda_package/mpas_tools/landice/boundary.py

@@ -0,0 +1,58 @@
+import sys
+from optparse import OptionParser
+from datetime import datetime
+
+import netCDF4
+
+
+def mark_domain_boundaries_dirichlet():
+    """
+    This script marks all of the boundary cells in a domain as Dirichlet
+    velocity boundaries.
+    """
+
+    print("== Gathering information.  (Invoke with --help for more details. "
+          "All arguments are optional)\n")
+    parser = OptionParser()
+    parser.description = __doc__
+    parser.add_option(
+        "-f", "--file", dest="inputFile",
+        help="name of file to be modified.",
+        default="landice_grid.nc", metavar="FILENAME")
+    parser.add_option(
+        "-t", "--time", dest="time",
+        help="time level to modify",
+        default=0, type="int",  metavar="FILENAME")
+    for option in parser.option_list:
+        if option.default != ("NO", "DEFAULT"):
+            option.help += (" " if option.help else "") + "[default: %default]"
+    options, args = parser.parse_args()
+
+    print("  Input file: {}".format(options.inputFile))
+    print("  Time level: {}".format(options.time))
+
+    f = netCDF4.Dataset(options.inputFile, 'r+')
+    nCells = len(f.dimensions['nCells'])
+    mask = f.variables['dirichletVelocityMask'][options.time, :, :]
+    cONc = f.variables['cellsOnCell'][:]
+    nEdgesOnCell = f.variables['nEdgesOnCell'][:]
+
+    mask[:] = 0
+    for i in range(nCells):
+        nE = nEdgesOnCell[i]
+        if min(cONc[i, :nE]) == 0:
+            mask[i, :] = 1
+    f.variables['dirichletVelocityMask'][options.time, :, :] = mask[:]
+
+    # Update history attribute of netCDF file
+    thiscommand = datetime.now().strftime("%a %b %d %H:%M:%S %Y") + ": " + \
+        " ".join(sys.argv[:])
+    if hasattr(f, 'history'):
+        newhist = '\n'.join([thiscommand, getattr(f, 'history')])
+    else:
+        newhist = thiscommand
+    setattr(f, 'history', newhist)
+
+    f.close()
+
+    print('\nMarking boundary cells completed.')

conda_package/mpas_tools/landice/cull.py

@@ -0,0 +1,251 @@
+import sys
+import numpy as np
+from optparse import OptionParser
+from netCDF4 import Dataset as NetCDFFile
+from datetime import datetime
+import matplotlib.pyplot as plt
+
+
+def define_cull_mask():
+    """
+    Script for adding a field named cullMask to an MPAS land ice grid for use
+    with the MpasCellCuller tool that actually culls the unwanted cells.
+    """
+
+    print("** Gathering information.")
+    parser = OptionParser()
+    parser.add_option(
+        "-f", "--file", dest="file",
+        help="grid file to modify; default: landice_grid.nc",
+        metavar="FILE")
+    parser.add_option(
+        "-m", "--method", dest="method",
+        help="method to use for marking cells to cull.  Supported methods: "
+             "'noIce', 'numCells', 'distance', 'radius', 'edgeFraction'",
+        metavar="METHOD")
+    parser.add_option(
+        "-n", "--numCells", dest="numCells", default=5,
+        help="number of cells to keep beyond ice extent",
+        metavar="NUM")
+    parser.add_option(
+        "-d", "--distance", dest="distance", default=50,
+        help="numeric value to use for the various methods: distance "
+             "method->distance (km), radius method->radius (km), edgeFraction "
+             "method->fraction of width or height",
+        metavar="DIST")
+    parser.add_option(
+        "-p", "--plot", dest="makePlot",
+        help="Include to have the script generate a plot of the resulting "
+             "mask, default=false",
+        default=False, action="store_true")
+    options, args = parser.parse_args()
+
+    if not options.file:
+        print("No grid filename provided. Using landice_grid.nc.")
+        options.file = "landice_grid.nc"
+
+    if not options.method:
+        raise ValueError("No method selected for choosing cells to mark for "
+                         "culling")
+    else:
+        maskmethod = options.method
+
+    f = NetCDFFile(options.file, 'r+')
+
+    xCell = f.variables['xCell'][:]
+    yCell = f.variables['yCell'][:]
+    nCells = len(f.dimensions['nCells'])
+
+    # -- Get needed fields from the file --
+
+    # Initialize to cull no cells
+    cullCell = np.zeros((nCells, ), dtype=np.int8)
+
+    thicknessMissing = True
+    try:
+        thickness = f.variables['thickness'][0, :]
+        print('Using thickness field at time 0')
+        thicknessMissing = False
+    except KeyError:
+        print("The field 'thickness' is not available.  Some culling methods "
+              "will not work.")
+
+    # =====  Various methods for defining the mask ====
+
+    # =========
+    # only keep cells with ice
+    if maskmethod == 'noIce':
+        print("Method: remove cells without ice")
+        if thicknessMissing:
+            raise ValueError("Unable to perform 'numCells' method because "
+                             "thickness field was missing.")
+
+        cullCell[thickness == 0.0] = 1
+
+    # =========
+    # add a buffer of X cells around the ice
+    elif maskmethod == 'numCells':
+        print("Method: remove cells beyond a certain number of cells from "
+              "existing ice")
+
+        if thicknessMissing:
+            raise ValueError("Unable to perform 'numCells' method because "
+                             "thickness field was missing.")
+
+        buffersize = int(options.numCells)  # number of cells to expand
+        print("Using a buffer of {} cells".format(buffersize))
+
+        keepCellMask = np.copy(cullCell[:])
+        keepCellMask[:] = 0
+        cellsOnCell = f.variables['cellsOnCell'][:]
+        nEdgesOnCell = f.variables['nEdgesOnCell'][:]
+
+        # mark the cells with ice first
+        keepCellMask[thickness > 0.0] = 1
+        print('Num of cells with ice: {}'.format(sum(keepCellMask)))
+
+        for i in range(buffersize):
+            print(f'Starting buffer loop {i + 1}')
+            # make a copy to edit that can be edited without changing the
+            # original
+            keepCellMaskNew = np.copy(keepCellMask)
+            ind = np.nonzero(keepCellMask == 0)[0]
+            for i in range(len(ind)):
+                iCell = ind[i]
+                neighbors = cellsOnCell[iCell, :nEdgesOnCell[iCell]] - 1
+                keep = False
+                for n in neighbors:
+                    if n >= 0:
+                        if keepCellMask[n] == 1:
+                            keepCellMaskNew[iCell] = 1
+        # after we've looped over all cells assign the new mask to the variable
+        # we need (either for another loop around the domain or to write out)
+        keepCellMask = np.copy(keepCellMaskNew)
+        print(f'Num of cells to keep: {keepCellMask.sum()}')
+
+        # Now convert the keepCellMask to the cullMask
+        # Flip the mask for which ones to cull
+        cullCell[:] = np.absolute(keepCellMask[:]-1)
+
+    # =========
+    # remove cells beyond a certain distance of ice extent
+    elif maskmethod == 'distance':
+
+        print("Method: remove cells beyond a certain distance from existing "
+              "ice")
+
+        if thicknessMissing:
+            raise ValueError("Unable to perform 'numCells' method because "
+                             "thickness field was missing.")
+
+        dist = float(options.distance)
+        print(f"Using a buffer distance of {dist} km")
+        # convert to m
+        dist = dist * 1000.0
+
+        keepCellMask = np.copy(cullCell[:])
+        keepCellMask[:] = 0
+        cellsOnCell = f.variables['cellsOnCell'][:]
+        nEdgesOnCell = f.variables['nEdgesOnCell'][:]
+        xCell = f.variables['xCell'][:]
+        yCell = f.variables['yCell'][:]
+
+        # mark the cells with ice first
+        keepCellMask[thickness > 0.0] = 1
+        print('Num of cells with ice: {}'.format(sum(keepCellMask)))
+
+        # find list of margin cells
+        iceCells = np.nonzero(keepCellMask == 1)[0]
+        marginMask = np.zeros((nCells, ), dtype=np.int8)
+        for i in range(len(iceCells)):
+            iCell = iceCells[i]
+            # the -1 converts from the fortran indexing in the variable to
+            # python indexing
+            for neighbor in cellsOnCell[iCell, :nEdgesOnCell[iCell]] - 1:
+                if thickness[neighbor] == 0.0:
+                    marginMask[iCell] = 1
+                    continue  # stop searching neighbors
+
+        # loop over margin cells
+        marginCells = np.nonzero(marginMask == 1)[0]
+        for i in range(len(marginCells)):
+            iCell = marginCells[i]
+            # for each margin cell, find all cells within specified distance
+            ind = np.nonzero(((xCell - xCell[iCell])**2 + (yCell - yCell[iCell])**2)**0.5 < dist)[0]
+            keepCellMask[ind] = 1
+
+        print(f'Num of cells to keep: {keepCellMask.sum()}')
+
+        # Now convert the keepCellMask to the cullMask
+        # Flip the mask for which ones to cull
+        cullCell[:] = np.absolute(keepCellMask[:] - 1)
+
+    # =========
+    # cut out beyond some radius (good for the dome)
+    elif maskmethod == 'radius':
+        dist = float(options.distance)
+        print(f"Method: remove cells beyond a radius of {dist} km from center "
+              f"of mesh")
+        xc = (xCell.max() - xCell.min()) / 2.0 + xCell.min()
+        yc = (yCell.max() - yCell.min()) / 2.0 + yCell.min()
+        ind = np.nonzero(((xCell[:] - xc)**2 + (yCell[:] - yc)**2)**0.5 > dist*1000.0)
+        cullCell[ind] = 1
+
+    # =========
+    # cut off some fraction of the height/width on all 4 sides - useful for
+    # cleaning up a mesh from periodic_general
+    elif maskmethod == 'edgeFraction':
+        frac = float(options.distance)
+        print("Method: remove a fraction from all 4 edges of {}".format(frac))
+        if frac >= 0.5:
+            raise ValueError("fraction cannot be >=0.5.")
+        if frac < 0.0:
+            raise ValueError("fraction cannot be <0.")
+
+        cullCell[:] = 0
+        width = xCell.max() - xCell.min()
+        height = yCell.max() - yCell.min()
+        ind = np.nonzero(xCell[:] < (xCell.min() + width * frac))
+        cullCell[ind] = 1
+        ind = np.nonzero(xCell[:] > (xCell.max() - width * frac))
+        cullCell[ind] = 1
+        ind = np.nonzero(yCell[:] < (yCell.min() + height * frac))
+        cullCell[ind] = 1
+        ind = np.nonzero(yCell[:] > (yCell.max() - height * frac))
+        cullCell[ind] = 1
+
+    # =========
+    else:
+        raise ValueError("no valid culling method selected.")
+    # =========
+
+    print(f'Num of cells to cull: {sum(cullCell[:])}')
+
+    # =========
+    # Try to add the new variable
+    if 'cullCell' not in f.variables:
+        # Get the datatype for integer
+        datatype = f.variables['indexToCellID'].dtype
+        f.createVariable('cullCell', datatype, ('nCells',))
+    f.variables['cullCell'][:] = cullCell
+
+    # Update history attribute of netCDF file
+    thiscommand = datetime.now().strftime("%a %b %d %H:%M:%S %Y") + ": " + \
+        " ".join(sys.argv[:])
+    if hasattr(f, 'history'):
+        newhist = '\n'.join([thiscommand, getattr(f, 'history')])
+    else:
+        newhist = thiscommand
+    setattr(f, 'history', newhist)
+
+    # --- make a plot only if requested ---
+    if options.makePlot:
+        fig = plt.figure(1, facecolor='w')
+        ax = fig.add_subplot(111, aspect='equal')
+        plt.scatter(xCell[:], yCell[:], 50, cullCell[:], edgecolors='none')  #, vmin=minval, vmax=maxval)
+        plt.colorbar()
+        plt.draw()
+        plt.show()
+
+    f.close()
+    print("cullMask generation complete.")