from __future__ import absolute_import, division, print_function, \
unicode_literals
import xarray
import matplotlib.pyplot as plt
import cartopy.crs as ccrs
import cartopy
from mpas_tools.mesh.conversion import convert
from mpas_tools.io import write_netcdf
from mpas_tools.mesh.creation.jigsaw_driver import jigsaw_driver
from mpas_tools.mesh.creation.jigsaw_to_netcdf import jigsaw_to_netcdf
from mpas_tools.viz.colormaps import register_sci_viz_colormaps
[docs]def build_spherical_mesh(cellWidth, lon, lat, earth_radius,
out_filename='base_mesh.nc', plot_cellWidth=True,
dir='./'):
"""
Build an MPAS mesh using JIGSAW with the given cell sizes as a function of
latitude and longitude.
The result is a mesh file stored in ``out_filename`` as well as several
intermediate files: ``mesh.log``, ``mesh-HFUN.msh``, ``mesh.jig``,
``mesh-MESH.msh``, ``mesh.msh``, and ``mesh_triangles.nc``.
Parameters
----------
cellWidth : ndarray
m x n array of cell width in km
lon : ndarray
longitude in degrees (length n and between -180 and 180)
lat : ndarray
longitude in degrees (length m and between -90 and 90)
earth_radius : float
Earth radius in meters
out_filename : str, optional
The file name of the resulting MPAS mesh
plot_cellWidth : bool, optional
Whether to produce a plot of ``cellWidth``. If so, it will be written to
``cellWidthGlobal.png``.
dir : str, optional
A directory in which a temporary directory will be added with files
produced during mesh conversion and then deleted upon completion.
"""
da = xarray.DataArray(cellWidth,
dims=['lat', 'lon'],
coords={'lat': lat, 'lon': lon},
name='cellWidth')
cw_filename = 'cellWidthVsLatLon.nc'
da.to_netcdf(cw_filename)
if plot_cellWidth:
register_sci_viz_colormaps()
fig = plt.figure(figsize=[16.0, 8.0])
ax = plt.axes(projection=ccrs.PlateCarree())
ax.set_global()
im = ax.imshow(cellWidth, origin='lower',
transform=ccrs.PlateCarree(),
extent=[-180, 180, -90, 90], cmap='3Wbgy5',
zorder=0)
ax.add_feature(cartopy.feature.LAND, edgecolor='black', zorder=1)
gl = ax.gridlines(
crs=ccrs.PlateCarree(),
draw_labels=True,
linewidth=1,
color='gray',
alpha=0.5,
linestyle='-', zorder=2)
gl.top_labels = False
gl.right_labels = False
plt.title(
'Grid cell size, km, min: {:.1f} max: {:.1f}'.format(
cellWidth.min(),cellWidth.max()))
plt.colorbar(im, shrink=.60)
fig.canvas.draw()
plt.tight_layout()
plt.savefig('cellWidthGlobal.png', bbox_inches='tight')
plt.close()
print('Step 1. Generate mesh with JIGSAW')
jigsaw_driver(cellWidth, lon, lat, on_sphere=True,
earth_radius=earth_radius)
print('Step 2. Convert triangles from jigsaw format to netcdf')
jigsaw_to_netcdf(msh_filename='mesh-MESH.msh',
output_name='mesh_triangles.nc', on_sphere=True,
sphere_radius=earth_radius)
print('Step 3. Convert from triangles to MPAS mesh')
write_netcdf(convert(xarray.open_dataset('mesh_triangles.nc'), dir=dir),
out_filename)
[docs]def build_planar_mesh(cellWidth, x, y, geom_points, geom_edges,
out_filename='base_mesh.nc'):
"""
Build a planar MPAS mesh
Parameters
----------
cellWidth : ndarray
m x n array of cell width in km
x, y : ndarray
arrays defining planar coordinates in meters
geom_points : ndarray
list of point coordinates for bounding polygon for the planar mesh
geom_edges : ndarray
list of edges between points in ``geom_points`` that define the
bounding polygon
out_filename : str, optional
The file name of the resulting MPAS mesh
"""
da = xarray.DataArray(cellWidth,
dims=['y', 'x'],
coords={'y': y, 'x': x},
name='cellWidth')
cw_filename = 'cellWidthVsXY.nc'
da.to_netcdf(cw_filename)
print('Step 1. Generate mesh with JIGSAW')
jigsaw_driver(
cellWidth,
x,
y,
on_sphere=False,
geom_points=geom_points,
geom_edges=geom_edges)
print('Step 2. Convert triangles from jigsaw format to netcdf')
jigsaw_to_netcdf(msh_filename='mesh-MESH.msh',
output_name='mesh_triangles.nc', on_sphere=False)
print('Step 3. Convert from triangles to MPAS mesh')
write_netcdf(convert(xarray.open_dataset('mesh_triangles.nc')),
out_filename)