Merge pull request #99 from xylar/reorganize-remapper

A major reorganization of the `Remapper`

Author: xylar

Diff for: examples/make_mpas_to_Antarctic_stereo_mapping.py renamed to examples/make_mpas_to_antarctic_stereo_mapping.py

@@ -19,45 +19,46 @@
 resolution.
 """
 
-import xarray
+import xarray as xr
 
-from pyremap import MpasCellMeshDescriptor, Remapper, get_polar_descriptor
+from pyremap import Remapper, get_polar_descriptor
 
 
 # replace with the MPAS mesh name
-inGridName = 'oQU240'
+src_mesh_name = 'oQU240'
 
 # replace with the path to the desired mesh or restart file
 # As an example, use:
 # https://web.lcrc.anl.gov/public/e3sm/inputdata/ocn/mpas-o/oQU240/ocean.QU.240km.151209.nc
-inGridFileName = 'ocean.QU.240km.151209.nc'
+src_mesh_filename = 'ocean.QU.240km.151209.nc'
 
-inDescriptor = MpasCellMeshDescriptor(inGridFileName, inGridName)
+# Configure the remapper to build the mapping file using 4 MPI tasks and
+# bilinear remapping
+remapper = Remapper(ntasks=4, method='bilinear')
 
-# modify the size and resolution of the Antarctic grid as desired
-outDescriptor = get_polar_descriptor(Lx=6000., Ly=5000., dx=10., dy=10.,
-                                     projection='antarctic')
-outGridName = outDescriptor.meshName
+remapper.src_from_mpas(filename=src_mesh_filename, mesh_name=src_mesh_name)
 
-mappingFileName = f'map_{inGridName}_to_{outGridName}_bilinear.nc'
+# modify the size and resolution of the Antarctic grid as desired
+remapper.dst_descriptor = get_polar_descriptor(
+    lx=6000., ly=5000., dx=10., dy=10., projection='antarctic')
 
-remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
+dst_grid_name = remapper.dst_descriptor.mesh_name
 
-# conservative remapping with 4 MPI tasks (using mpirun)
-remapper.esmf_build_map(method='bilinear', mpi_tasks=4)
+# build the mapping file
+remapper.build_map()
 
 # select the SST at the initial time as an example data set
-srcFileName = f'temp_{inGridName}.nc'
-ds = xarray.open_dataset(inGridFileName)
-dsOut = xarray.Dataset()
-dsOut['temperature'] = ds['temperature'].isel(nVertLevels=0, Time=0)
-dsOut.to_netcdf(srcFileName)
+src_filename = f'temp_{src_mesh_name}.nc'
+ds = xr.open_dataset(src_mesh_filename)
+ds_out = xr.Dataset()
+ds_out['temperature'] = ds['temperature'].isel(nVertLevels=0, Time=0)
+ds_out.to_netcdf(src_filename)
 
 # do remapping with ncremap
-outFileName = f'temp_{outGridName}_file.nc'
-remapper.remap_file(srcFileName, outFileName)
+out_filename = f'temp_{dst_grid_name}_file.nc'
+remapper.ncremap(src_filename, out_filename)
 
 # do remapping again, this time with python remapping
-outFileName = f'temp_{outGridName}_array.nc'
-dsOut = remapper.remap(dsOut)
-dsOut.to_netcdf(outFileName)
+out_filename = f'temp_{dst_grid_name}_array.nc'
+ds_out = remapper.remap_numpy(ds_out)
+ds_out.to_netcdf(out_filename)

Diff for: examples/make_mpas_to_lat_lon_mapping.py

@@ -19,34 +19,45 @@
 resolution.
 """
 
-import xarray
+import xarray as xr
+
+from pyremap import Remapper, get_lat_lon_descriptor
 
-from pyremap import MpasCellMeshDescriptor, Remapper, get_lat_lon_descriptor
 
 # replace with the MPAS mesh name
-inGridName = 'oQU240'
+src_mesh_name = 'oQU240'
 
 # replace with the path to the desired mesh or restart file
 # As an example, use:
 # https://web.lcrc.anl.gov/public/e3sm/inputdata/ocn/mpas-o/oQU240/ocean.QU.240km.151209.nc
-inGridFileName = 'ocean.QU.240km.151209.nc'
+src_mesh_filename = 'ocean.QU.240km.151209.nc'
+
+# Configure the remapper to build the mapping file using 1 MPI tasks and
+# bilinear remapping
+remapper = Remapper(ntasks=1, method='bilinear')
 
-inDescriptor = MpasCellMeshDescriptor(inGridFileName, inGridName)
+remapper.src_from_mpas(filename=src_mesh_filename, mesh_name=src_mesh_name)
 
 # modify the resolution of the global lat-lon grid as desired
-outDescriptor = get_lat_lon_descriptor(dLon=0.5, dLat=0.5)
-outGridName = outDescriptor.meshName
+remapper.dst_descriptor = get_lat_lon_descriptor(dlon=0.5, dlat=0.5)
 
-mappingFileName = f'map_{inGridName}_to_{outGridName}_bilinear.nc'
+dst_grid_name = remapper.dst_descriptor.mesh_name
 
+# build the mapping file
+remapper.build_map()
 
-remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
+# select the SST at the initial time as an example data set
+src_filename = f'temp_{src_mesh_name}.nc'
+ds = xr.open_dataset(src_mesh_filename)
+ds_out = xr.Dataset()
+ds_out['temperature'] = ds['temperature'].isel(nVertLevels=0, Time=0)
+ds_out.to_netcdf(src_filename)
 
-remapper.esmf_build_map(method='bilinear', mpi_tasks=1)
+# do remapping with ncremap
+out_filename = f'temp_{dst_grid_name}_file.nc'
+remapper.ncremap(src_filename, out_filename)
 
-outFileName = f'temp_{outGridName}.nc'
-ds = xarray.open_dataset(inGridFileName)
-dsOut = xarray.Dataset()
-dsOut['temperature'] = ds['temperature']
-dsOut = remapper.remap(dsOut)
-dsOut.to_netcdf(outFileName)
+# do remapping again, this time with python remapping
+out_filename = f'temp_{dst_grid_name}_array.nc'
+ds_out = remapper.remap_numpy(ds_out)
+ds_out.to_netcdf(out_filename)

Diff for: examples/make_mpas_vertex_to_Antarctic_stereo_mapping.py renamed to examples/make_mpas_vertex_to_antarctic_stereo_mapping.py

@@ -22,45 +22,46 @@
 import numpy as np
 import xarray as xr
 
-from pyremap import MpasVertexMeshDescriptor, Remapper, get_polar_descriptor
+from pyremap import Remapper, get_polar_descriptor
 
 
 # replace with the MPAS mesh name
-inGridName = 'oQU240'
+src_mesh_name = 'oQU240_vertex'
 
 # replace with the path to the desired mesh or restart file
 # As an example, use:
 # https://web.lcrc.anl.gov/public/e3sm/inputdata/ocn/mpas-o/oQU240/ocean.QU.240km.151209.nc
-inGridFileName = 'ocean.QU.240km.151209.nc'
+src_mesh_filename = 'ocean.QU.240km.151209.nc'
 
-inDescriptor = MpasVertexMeshDescriptor(inGridFileName, inGridName)
+# Configure the remapper to build the mapping file using 4 MPI tasks and
+# conservative remapping
+remapper = Remapper(ntasks=4, method='conserve')
 
-# modify the size and resolution of the Antarctic grid as desired
-outDescriptor = get_polar_descriptor(Lx=6000., Ly=5000., dx=10., dy=10.,
-                                     projection='antarctic')
-outGridName = outDescriptor.meshName
+remapper.src_from_mpas(filename=src_mesh_filename, mesh_name=src_mesh_name,
+                       mesh_type='vertex')
 
-mappingFileName = f'map_{inGridName}_vertex_to_{outGridName}_conserve.nc'
+# modify the size and resolution of the Antarctic grid as desired
+remapper.dst_descriptor = get_polar_descriptor(
+    lx=6000., ly=5000., dx=10., dy=10., projection='antarctic')
 
-remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
+dst_grid_name = remapper.dst_descriptor.mesh_name
 
-# conservative remapping with 4 MPI tasks (using mpirun)
-remapper.esmf_build_map(method='conserve', mpi_tasks=4,
-                        parallel_exec='mpirun', include_logs=True)
+# build the mapping file
+remapper.build_map()
 
 # select the SST at the initial time as an example data set
-srcFileName = f'vertex_id_{inGridName}.nc'
-ds = xr.open_dataset(inGridFileName)
-dsOut = xr.Dataset()
-dsOut['indexToVertexID'] = ds['indexToVertexID'].astype(float)
-dsOut['random'] = ('nVertices', np.random.random(ds.sizes['nVertices']))
-dsOut.to_netcdf(srcFileName)
+src_filename = f'vertex_id_{src_mesh_name}.nc'
+ds = xr.open_dataset(src_mesh_filename)
+ds_out = xr.Dataset()
+ds_out['indexToVertexID'] = ds['indexToVertexID'].astype(float)
+ds_out['random'] = ('nVertices', np.random.random(ds.sizes['nVertices']))
+ds_out.to_netcdf(src_filename)
 
 # do remapping with ncremap
-outFileName = f'vertex_id_{outGridName}_file.nc'
-remapper.remap_file(srcFileName, outFileName)
+out_filename = f'vertex_id_{dst_grid_name}_file.nc'
+remapper.ncremap(src_filename, out_filename)
 
 # do remapping again, this time with python remapping
-outFileName = f'vertex_id_{outGridName}_array.nc'
-dsOut = remapper.remap(dsOut)
-dsOut.to_netcdf(outFileName)
+out_filename = f'vertex_id_{dst_grid_name}_array.nc'
+ds_out = remapper.remap_numpy(ds_out)
+ds_out.to_netcdf(out_filename)

Diff for: examples/remap_stereographic.py

@@ -9,65 +9,64 @@
 Usage: Copy this script into the main MPAS-Analysis directory (up one level).
 """
 
-import numpy
-import xarray
 import argparse
 
+import numpy as np
+import xarray as xr
+
 from pyremap import Remapper, ProjectionGridDescriptor
 from pyremap.polar import get_antarctic_stereographic_projection
 
 
 parser = argparse.ArgumentParser(
     description=__doc__, formatter_class=argparse.RawTextHelpFormatter)
-parser.add_argument('-i', dest='inFileName', required=True, type=str,
-                    help="Input file name")
-parser.add_argument('-o', dest='outFileName', required=True, type=str,
-                    help="Output file name")
+parser.add_argument('-i', dest='in_filename', required=True, type=str,
+                    help='Input file name')
+parser.add_argument('-o', dest='out_filename', required=True, type=str,
+                    help='Output file name')
 parser.add_argument('-r', dest='resolution', required=True, type=float,
-                    help="Output resolution")
-parser.add_argument('-m', dest='method', required=False, default="bilinear",
-                    help="Method: {'bilinear', 'neareststod', 'conserve'}")
-parser.add_argument('-t', dest='mpiTasks', required=False, type=int, default=1,
-                    help="Number of MPI tasks (default = 1)")
+                    help='Output resolution')
+parser.add_argument('-m', dest='method', required=False, default='bilinear',
+                    help='Method: {"bilinear", "neareststod", "conserve"}')
+parser.add_argument('-t', dest='mpi_tasks', required=False, type=int,
+                    default=1,
+                    help='Number of MPI tasks (default = 1)')
 args = parser.parse_args()
 
 
 if args.method not in ['bilinear', 'neareststod', 'conserve']:
     raise ValueError(f'Unexpected method {args.method}')
 
-dsIn = xarray.open_dataset(args.inFileName)
+ds_in = xr.open_dataset(args.in_filename)
 
-x = dsIn.x.values
-y = dsIn.y.values
-dx = int((x[1] - x[0]) / 1000.)
-Lx = int((x[-1] - x[0]) / 1000.)
-Ly = int((y[-1] - y[0]) / 1000.)
+x = ds_in.x.values
+y = ds_in.y.values
+dx = int((x[1] - x[0]) / 1000.0)
+lx = int((x[-1] - x[0]) / 1000.0)
+ly = int((y[-1] - y[0]) / 1000.0)
 
-inMeshName = f'{Lx}x{Ly}km_{dx}km_Antarctic_stereo'
+src_mesh_name = f'{lx}x{ly}km_{dx}km_Antarctic_stereo'
 
 projection = get_antarctic_stereographic_projection()
 
-inDescriptor = ProjectionGridDescriptor.create(projection, x, y, inMeshName)
-
-outRes = args.resolution * 1e3
-
-nxOut = int((x[-1] - x[0]) / outRes + 0.5) + 1
-nyOut = int((y[-1] - y[0]) / outRes + 0.5) + 1
-
-xOut = x[0] + outRes * numpy.arange(nxOut)
-yOut = y[0] + outRes * numpy.arange(nyOut)
+remapper = Remapper(ntasks=args.mpi_tasks, method=args.method)
+remapper.src_descriptor = ProjectionGridDescriptor.create(
+    projection, x, y, src_mesh_name)
 
+out_res = args.resolution * 1e3
 
-outMeshName = f'{Lx}x{Ly}km_{args.resolution}km_Antarctic_stereo'
+nx_out = int((x[-1] - x[0]) / out_res + 0.5) + 1
+ny_out = int((y[-1] - y[0]) / out_res + 0.5) + 1
 
-outDescriptor = ProjectionGridDescriptor.create(projection, xOut, yOut,
-                                                outMeshName)
+x_out = x[0] + out_res * np.arange(nx_out)
+y_out = y[0] + out_res * np.arange(ny_out)
 
-mappingFileName = f'map_{inMeshName}_to_{outMeshName}_{args.method}.nc'
+dst_mesh_name = f'{lx}x{ly}km_{args.resolution}km_Antarctic_stereo'
 
-remapper = Remapper(inDescriptor, outDescriptor, mappingFileName)
+remapper.dst_descriptor = ProjectionGridDescriptor.create(
+    projection, x_out, y_out, dst_mesh_name)
 
-remapper.esmf_build_map(method=args.method, mpi_tasks=args.mpiTasks)
+remapper.build_map()
 
-dsOut = remapper.remap(dsIn, renormalizationThreshold=0.01)
-dsOut.to_netcdf(args.outFileName)
+ds_out = remapper.remap_numpy(ds_in, renormalization_threshold=0.01)
+ds_out.to_netcdf(args.out_filename)