"""
Create a grounding line contour.
"""
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'
from varglas.data.data_factory import DataFactory
from varglas.mesh.mesh_factory import MeshFactory
from varglas.utilities import DataInput
from varglas.model import Model
from varglas.solvers import SteadySolver, TransientSolver
from varglas.physical_constants import IceParameters
from varglas.helper import default_nonlin_solver_params
from fenics import set_log_active, parameters
set_log_active(True)
thklim = 50.0
vara = DataFactory.get_searise(thklim=thklim)
mesh = MeshFactory.get_greenland_coarse()
dsr = DataInput(vara, mesh=mesh)
S = dsr.get_spline_expression('S')
B = dsr.get_spline_expression('B')
SMB = dsr.get_spline_expression('adot')
T_s = dsr.get_spline_expression('T')
q_geo = dsr.get_spline_expression('q_geo')
U_ob = dsr.get_spline_expression('U_ob')
Tn = vara['Tn']['map_data']
# create the model :
model = Model()
model.set_mesh(mesh)
model.set_geometry(S, B, deform=True)
model.set_parameters(IceParameters())
# -*- 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')
# Output directory
out_dir = 'results_dir3/'
#set_log_active(True)
parameters["allow_extrapolation"] = True
mesh = Mesh('data/meshes/ant_mesh.xml')
# Get a bunch of data to use in the simulation
thklim = 100.0
measures = DataFactory.get_ant_measures(res=900)
bedmap1 = DataFactory.get_bedmap1(thklim=thklim)
bedmap2 = DataFactory.get_bedmap2(thklim=thklim)
dm = DataInput(measures, mesh=mesh)
db1 = DataInput(bedmap1, mesh=mesh)
db2 = DataInput(bedmap2, mesh=mesh)
# Fix some stuff?
db2.data['B'] = db2.data['S'] - db2.data['H']
db2.set_data_val('H', 32767, thklim)
db2.data['S'] = db2.data['B'] + db2.data['H']
S = db2.get_spline_expression("S")
B = db2.get_spline_expression("B")
T_s = db1.get_spline_expression("srfTemp")
q_geo = db1.get_spline_expression("q_geo")
adot = db1.get_spline_expression("adot")
# Create a model for the sole purpose of deforming the full continent mesh
# Get the full continent mesh
""" Script that takes in lat,lon gps coordinates and returns the x,y coordinates.""" from pylab import * from mpl_toolkits.basemap import Basemap from varglas.data.data_factory import DataFactory from varglas.utilities import DataInput from fenics import * # Get the Antarctica data sets bedmap2 = DataFactory.get_bedmap2(thklim=200) data = bedmap2["mask"]["map_data"][::-1] db2 = DataInput(bedmap2) # These are the original coordinates of the domain x0 = -376234 y0 = -456870 x1 = -291856 y1 = -505791 x2 = 102477 y2 = 177085 x3 = 17833 y3 = 225849 # Convert to (lon, lat) coordinates lon0, lat0 = db2.p(x0, y0, inverse=True) lon1, lat1 = db2.p(x1, y1, inverse=True) lon2, lat2 = db2.p(x2, y2, inverse=True) lon3, lat3 = db2.p(x3, y3, inverse=True)
""" Script that takes in lat,lon gps coordinates and returns the x,y coordinates.""" from pylab import * from mpl_toolkits.basemap import Basemap from varglas.data.data_factory import DataFactory from varglas.utilities import DataInput from fenics import * # Get the Antarctica data sets bedmap2 = DataFactory.get_bedmap2(thklim = 200) data = bedmap2['mask']['map_data'][::-1] db2 = DataInput(bedmap2) x0 = -376234 y0 = -456870 x1 = -291856 y1 = -505791 x2 = 102477 y2 = 177085 x3 = 17833 y3 = 225849 lon0, lat0 = db2.p(x0,y0,inverse = True) lon1, lat1 = db2.p(x1,y1,inverse = True) lon2, lat2 = db2.p(x2,y2,inverse = True) lon3, lat3 = db2.p(x3,y3,inverse = True)
"""
Create a continent contour.
"""
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)
# 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 to basemap coordinates
lat_0 = '-90'
lat_ts = '-71'
lon_0 = '0'
height = 3333500*2
width = 3333500*2
m = Basemap(width=width, height=height, resolution='h',
projection="stere", lat_ts=lat_ts, lon_0=lon_0, lat_0=lat_0)
"""
Create contours for the Antarctic ice shelves so we can plot them.
"""
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()
db2 = DataInput(bedmap2)
# Just get the ice shelves
db2.set_data_val('mask',127,0)
mg = MeshGenerator(db2, 'mesh', '')
mg.create_contour('mask', 0, skip_pts=2)
mg.eliminate_intersections(dist=20)
# Get the two longest contours, which I'm assuming are the two major ice shelves
cl = mg.c.allsegs[0]
contour_lens = array(map(len, cl))
sorted_indexes = contour_lens.argsort()
shelf1 = cl[sorted_indexes[-1]]
shelf2 = cl[sorted_indexes[-2]]
# Convert to (lon, lat coordinates)
shelf1_lons, shelf1_lats = db2.p(shelf1[:,0], shelf1[:,1], inverse = True)
shelf2_lons, shelf2_lats = db2.p(shelf2[:,0], shelf2[:,1], inverse = True)
import varglas.model as model
# Output directory
out_dir = 'age_bp/'
set_log_active(True)
# Load my mesh
mesh = Mesh('data/meshes/ant_mesh.xml')
# Get a bunch of data to use in the simulation
thklim = 100.0
bedmap1 = DataFactory.get_bedmap1(thklim=thklim)
bedmap2 = DataFactory.get_bedmap2(thklim=thklim)
db1 = DataInput(bedmap1, mesh=mesh)
db2 = DataInput(bedmap2, mesh=mesh)
# This code is
db2.data['B'] = db2.data['S'] - db2.data['H']
db2.set_data_val('H', 32767, thklim)
db2.data['S'] = db2.data['B'] + db2.data['H']
S = db2.get_spline_expression("S")
B = db2.get_spline_expression("B")
adot = db1.get_spline_expression("adot")
# Setup the model
model = model.Model()
model.set_mesh(mesh)
model.set_geometry(S, B, deform=True)
"""
Created on Fri Jul 25 10:48:09 2014
@author: jake
"""
from varglas.data.data_factory import DataFactory
from varglas.utilities import DataInput
from fenics import *
# Load a mesh
mesh = Mesh("meshes/mesh_5km.xml")
# plot(mesh, interactive = True)
# create meshgrid for contour :
bedmap2 = DataFactory.get_bedmap2()
# process the data :
dbm = DataInput(bedmap2)
# Project some data onto the mesh
print "Here."
# bed = dbm.get_interpolation("B",near = True,kx=1,ky=1)
# bed = dbm.get_projection("B",near = False,kx=1,ky=1)
bed = dbm.get_spline_expression("B")
Q = FunctionSpace(mesh, "CG", 1)
bed = project(bed, Q)
File("data/bed_5km.xml") << bed
from varglas.mesh.mesh_factory import MeshFactory
from varglas.utilities import DataInput
from fenics import *
import varglas.model as model
# Have to set this to true because my mesh doesn't match up with Evan's pefectly
# due to different levels of refinement
parameters["allow_extrapolation"] = True
# Load my mesh
mesh = Mesh("meshes/ant_mesh.xml")
# Use bedmap for surface and bed elevation
thklim = 100.0
bedmap2 = DataFactory.get_bedmap2(thklim=thklim)
db2 = DataInput(bedmap2, mesh=mesh)
# Deform the mesh so it matches Evan's
db2.data["B"] = db2.data["S"] - db2.data["H"]
db2.set_data_val("H", 32767, thklim)
db2.data["S"] = db2.data["B"] + db2.data["H"]
S = db2.get_spline_expression("S")
B = db2.get_spline_expression("B")
# Create a model for the sole purpose of deforming the full continent mesh
full_mesh = MeshFactory.get_antarctica_3D_gradS_detailed()
mesh_model = model.Model()
mesh_model.set_mesh(full_mesh)
mesh_model.set_geometry(S, B, deform=True)
"""
Created on Mon Jul 28 16:12:36 2014
@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)
""" Script that takes in lat,lon gps coordinates and returns the x,y coordinates."""
from pylab import *
from mpl_toolkits.basemap import Basemap
from varglas.data.data_factory import DataFactory
from varglas.utilities import DataInput
from fenics import *
# Get the Antarctica data sets
bedmap2 = DataFactory.get_bedmap2()
db2 = DataInput(bedmap2)
# Load the domain coordinates
domain_coords = loadtxt("data/new_domain.out")
domain_lons, domain_lats = db2.p(domain_coords[:, 0], domain_coords[:, 1], inverse=True)
# Setup the basemap projection
proj = "stere"
lat_0 = "-90"
lat_ts = "-71"
lon_0 = "0"
width = 3333500 * 2
height = 3333500 * 2
# Plot all the points
m = Basemap(width=width, height=height, resolution="h", projection="stere", lat_ts=lat_ts, lon_0=lon_0, lat_0=lat_0)
# Convert the domain (lon, lat) coordinates to basemap coordinates
domain_xs, domain_ys = m(domain_lons, domain_lats)
# Close the rectangle
domain_xs = append(domain_xs, domain_xs[0])
domain_ys = append(domain_ys, domain_ys[0])
