# -*- coding: utf-8 -*- """ Create a uniform mesh of Antarctica for plotting. """ from varglas.utilities import DataInput, MeshGenerator from varglas.data.data_factory import DataFactory from pylab import * thklim = 0 # create meshgrid for contour : bedmap2 = DataFactory.get_bedmap2() # process the data : dbm = DataInput(bedmap2, gen_space=False) dbm.set_data_val("H", 32767, thklim) m = MeshGenerator(dbm, 'mesh', '') m.create_contour('H', 0.0, 5) m.eliminate_intersections(dist=20) m.write_gmsh_contour(1000, boundary_extend=False) m.add_edge_attractor(1) #field, ifield, lcMin, lcMax, distMin, distMax m.add_threshold(2, 1, 3000, 3000, 1, 100000) m.finish(4) #m.create_2D_mesh('mesh') #FIXME: fails #m.convert_msh_to_xml('mesh', 'mesh')
from varglas.data.data_factory import DataFactory from varglas.utilities import DataInput, MeshGenerator from numpy import * from mpl_toolkits.basemap import Basemap # Get the Antarctica data sets bedmap2 = DataFactory.get_bedmap2() db2 = DataInput(bedmap2) # Get the grounding line by eliminating the shelves db2.set_data_val('mask',1,127) # Create a grounding line countour mg = MeshGenerator(db2, 'mesh', '') mg.create_contour('mask', 10, skip_pts=2) mg.eliminate_intersections(dist=20) cont = mg.longest_cont # Convert (x,y) coordinates to (lon,lat) cont_lons, cont_lats = db2.p(cont[:,0], cont[:,1], inverse = True) # Convert (x,y) coordinates to (lon,lat) cont_lons, cont_lats = db2.p(cont[:,0], cont[:,1], inverse = True) # Convert to basemap coordinates lat_0 = '-90' lat_ts = '-71' lon_0 = '0' height = 3333500*2 width = 3333500*2
@author: jake """ from pylab import * from varglas.data.data_factory import DataFactory from varglas.utilities import DataInput, MeshGenerator from numpy import * # Get the Antarctica data sets bedmap2 = DataFactory.get_bedmap2(thklim = 200) # Create a countour of the continent - without the ice shelves db2 = DataInput(bedmap2) db2.set_data_val('mask',1,127) mg = MeshGenerator(db2, 'mesh', '') mg.create_contour('mask', 0, skip_pts=4) mg.eliminate_intersections(dist=40) # Get the longest contour, which will be the coastline cont = mg.longest_cont # Load the glacier data glacier_data = loadtxt('glacier_data.out', delimiter = '|', dtype = 'str') names = array(glacier_data[:,0], dtype = 'str') lons = array(glacier_data[:,1], dtype = 'f') lats = array(glacier_data[:,2], dtype = 'f') # Convert lons and lats to x, y coordinates x, y = db2.p(lons,lats) # Next, eliminate glaciers that are too far from the coast