def read_excel(file='slab++.xlsx'):
wb = open_workbook(file)
sheet = wb.sheets()[0]
number_of_rows = sheet.nrows
number_of_columns = sheet.ncols
items = []
rows = []
slabs= Catalog()
for row in range(4, number_of_rows):
slab= Slab()
values = []
for col in range(number_of_columns):
par=str(sheet.cell(3,col).value)
if par:
print(par)
value = sheet.cell(row,col).value
print(par,value)
try:
slab.params[par]= float(value)
except:
slab.params[par] = str(value)
# save temperature at 600 km using thermal parameter
phi = slab.params['thermalPar']
z = 6.0
Ta = 1338.0
Tz = Ta * (1.0 - ( (2.0/np.pi)*np.exp(-1.0*( (np.power(np.pi,2.0)*z)/ (np.power(2.32,2.0) * phi) )) ) )
slab.params['Temp600'] = Tz
print(Tz)
print(slab.params)
slabs.append(slab)
return slabs
def read_slabdata(slabcat=None):
'''
Creates slab objects for the slabs identified by Fukao & Obayashi (2013)
'''
slabs = {}
#This dictionary contains information about the boundaries of the slabs mentioned in the
#Fukao and Obayashi paper
#The coordinates are entered as follows:
#[minlon,minlat,maxlon,maxlat]
slabs['Honshu'] = {'Bounds' : [109,35,159,45]}
slabs['Bonin'] = {'Bounds' : [109,23,159,35]}
slabs['Mariana'] = {'Bounds' : [120,8.3,152,25]}
slabs['Java'] = {'Bounds' : [89,-10,129,19]}
slabs['Phillippine'] = {'Bounds' : [114,5,128,18]}
slabs['Tonga'] = {'Bounds' : [157,-26,190,-10]}
slabs['Kermadec'] = {'Bounds' : [157,-37,190,-26]}
slabs['Peruvian'] = {'Bounds' : [270,-15,307,6.7]}
slabs['Chilean'] = {'Bounds' : [270,-45,307,-15]}
slabs['Central_American'] = {'Bounds' : [249,4.5,282,33]}
#For these two regions, we need an oblique box. The coodinates are entered as follows
#[upper left,lower left,lower right,upper right]
slabs['Kurile_N'] = {'Bounds' : [134.5,65.5,130.5,61.5,158.5,43,162.5,47]}
slabs['Kurile_S'] = {'Bounds' : [127.5,58.5,123.5,54.5,151.5,36,155.5,40]}
if slabcat:
FukaoSlabs = slabcat
else:
FukaoSlabs = Catalog()
for slabname in slabs:
newslab = Slab(slabname)
#add directory to the slabs
newslab.add_Fukao_slab_details(slabs[slabname])
FukaoSlabs.append(newslab)
return FukaoSlabs
def run_game():
""" 入口程序 """
pygame.init()
myset = Mysetting()
screen = pygame.display.set_mode((myset.screen_w, myset.screen_h))
pygame.display.set_caption('play slab')
stats = SlabballStats(myset)
slab = Slab(myset, screen)
balls = Group()
sbf.create_ball(balls, screen, myset)
while True:
sbf.check_events(slab)
if stats.game_active:
sbf.slap_ball_update(slab, balls, screen, myset)
sbf.update_balls(myset, balls, screen, stats)
sbf.update_screen(myset, screen, balls, slab)
def test_slab():
from itertools import product
comm = MPI.COMM_WORLD
sizes = (7, 8, 9, 16, 17, 24)
types = 'fdgFDG'
atol = dict(f=1e-6, d=1e-14, g=1e-15)
for typecode in types:
for M, N, P in product(sizes, sizes, sizes):
if P % 2: continue
fft = Slab(comm, (M, N, P), typecode)
shape = fft.forward_input_array.shape
dtype = fft.forward_input_array.dtype
U = np.random.random(shape).astype(dtype)
F = fft.forward(U)
V = fft.backward(F)
fft.destroy()
assert np.allclose(U, V, atol=atol[typecode.lower()], rtol=0)
def read_syracuse_thermal(sub='d80'):
file = open('data/syracuseetal_parameters_'+sub+'.txt','r')
slabs=Catalog() # Initialize Catalog object
for line in file.readlines():
val = line.split()
if val[0]!= '#':# skip comments at top of file
name = val[0]
savei=0
for i in range(1,4): # Read in slab names that are more than one string in lenght
try:
float(val[i])
break
except:
savei=i
name = name + ' ' +val[i]
slab=Slab(name) # Initialize slab object
slab.params['transition_depth'] = float(val[savei+1])
slab.params['transition_T'] = float(val[savei+2])
slab.params['slab_T'] = float(val[savei+3])
slab.params['moho_T'] = float(val[savei+4])
slab.params['max_mantle_T'] = float(val[savei+5])
slab.params['max_mantle_T_depth'] = float(val[savei+6])
slab.params['transition_offset'] = float(val[savei+7])
slab.params['slab_surface_T_30km']= float(val[savei+8])
slab.params['slab_surface_T_240km'] = float(val[savei+9])
slab.params['min_slab_T_240km'] = float(val[savei+10])
slabs.append(slab) # Add slab object to catalot
return slabs
def read_syracuse():
file = open('data/syracuseetal_table1.txt','r')
slabs=Catalog() # Initialize Catalog object
for line in file.readlines():
val = line.split()
if val[0]!= '#':# skip comments at top of file
name = val[0]
savei=0
for i in range(1,4): # Read in slab names that are more than one string in lenght
try:
float(val[i])
break
except:
savei=i
name = name + ' ' +val[i]
print(val,savei)
slab=Slab(name) # Initialize slab object
slab.params['lon']= float(val[savei+1])
slab.params['lat'] = float(val[savei+2])
slab.params['H'] = float(val[savei+3])
slab.params['arc_trench_distance'] = float(val[savei+4])
slab.params['slab_dip'] = float(val[savei+5])
slab.params['Vc'] = float(val[savei+6])
slab.params['age'] = float(val[savei+7])
slab.params['decent_rate'] = float(val[savei+8])
slab.params['thermal_parameter'] = float(val[savei+9])
slab.params['sediment_thickness'] = float(val[savei+10])
slab.params['subducted_sediment_thickness'] = float(val[savei+11])
slab.params['upper_plate_type'] = val[savei+12]
#slab.upper_plate_thickness = float(val[savei+12])
#slab.upper_plate_age = float(val[savei+13])
slabs.append(slab) # Add slab object to catalot
return slabs
# Example usage
import numpy as np
import matplotlib.pyplot as plt
from slab import Slab
slab_dirichlet = Slab(Bi=np.inf, L=0.02, D=9e-7, c_L=2., c_inf=0., num_eigv=30)
slab_noflux = Slab(Bi=0., L=0.02, D=9e-7, c_L=2., c_inf=0., num_eigv=30)
x = np.linspace(0, 0.02, 1000)
for t in np.logspace(-2, 3, 100):
plt.plot(x, slab_dirichlet.evaluate(x, t), 'b')
plt.plot(x, slab_noflux.evaluate(x, t), 'r')
plt.show()
def read_slabdata(slabcat=None):
'''
Read in the slab1.0 data as a catalog of slabs object. The argument options allows one to
append these slabs to an existing catalog
'''
slabdir='data/slab1.0/'
#Names given to the slab 1.0 slabs
slabbounds = {}
slabbounds['Alaska'] = {'Filename' : 'alu_slab1.0_clip.grd'}
slabbounds['Cascadia'] = {'Filename' :'cas_slab1.0_clip.grd'}
slabbounds['Izu-Bonin'] = {'Filename' : 'izu_slab1.0_clip.grd'}
slabbounds['Mexico'] = {'Filename' : 'mex_slab1.0_clip.grd'}
slabbounds['Tonga'] = {'Filename' : 'ker_slab1.0_clip.grd'}
slabbounds['Japan'] = {'Filename' : 'kur_slab1.0_clip.grd'}
slabbounds['Philippines'] = {'Filename' : 'phi_slab1.0_clip.grd'}
slabbounds['Ryukyu'] = {'Filename' : 'ryu_slab1.0_clip.grd'}
slabbounds['Vanautu'] = {'Filename' : 'van_slab1.0_clip.grd'}
slabbounds['Scotia'] = {'Filename' : 'sco_slab1.0_clip.grd'}
slabbounds['Solomon'] = {'Filename' : 'sol_slab1.0_clip.grd'}
slabbounds['South_America'] = {'Filename' : 'sam_slab1.0_clip.grd'}
slabbounds['Sumatra'] = {'Filename' : 'sum_slab1.0_clip.grd'}
#try:
# os.chdir(slabdir)
#except:
# print('Data directory %s does not exist!' %slabdir)
slab_ncs = glob.glob(slabdir+'*.grd')
#Create a catalog object for the slab1.0 slabs
if slabcat:
Slabs = slabcat
else:
Slabs=Catalog()
for slab in slab_ncs:
infile = netcdf.netcdf_file(slab, 'r')
filevariables = infile.variables.keys()
lats = infile.variables[filevariables[0]][:]
lons = infile.variables[filevariables[1]][:]
#This is a lat x lon array
depths = infile.variables[filevariables[2]][:]
infile.close()
minlat = min(lats)
maxlat = max(lats)
minlon = min(lons)
maxlon = max(lons)
boundingbox = [minlon,maxlon,minlat,maxlat]
for name in slabbounds:
if slabbounds[name]['Filename'] == slab.split('/')[-1].strip():
#create a Slab object
newslab = Slab(name)
slabbounds[name]['Lat_array'] = lats
slabbounds[name]['Lon_array'] = lons
slabbounds[name]['Depth_array'] = depths
slabbounds[name]['Bounding_box'] = boundingbox
#Add sub-dicionary to the slab object
newslab.add_slab1_details(slabbounds[name])
Slabs.append(newslab)
break
return Slabs,slabbounds
def read_seracuse():
file = open('data/syracuseetal_parameters.txt','r')
slabs=Catalog()
for line in file.readlines():
val = line.split()
name = val[0]
savei=0
for i in range(1,4):
try:
float(val[i])
break
except:
savei=i
name = name + ' ' +val[i]
slab=Slab(name)
slab.transition_depth = float(val[savei+1])
slab.transition_T = float(val[savei+2])
slab.slab_T = float(val[savei+3])
slab.moho_T = float(val[savei+4])
slab.max_mantle_T = float(val[savei+5])
slab.max_mantle_T_depth = float(val[savei+6])
slab.transition_offset = float(val[savei+7])
slab.slab_surface_T_30km = float(val[savei+8])
slab.slab_surface_T_240km = float(val[savei+9])
slab.min_slab_T_240km = float(val[savei+10])
slabs.append(slab)
return slabs
# Example usage
import numpy as np
import matplotlib.pyplot as plt
from slab import Slab
slab_dirichlet = Slab(Bi=np.inf, L=0.02, D=9e-7, c_L=2.0, c_inf=0.0, num_eigv=30)
slab_noflux = Slab(Bi=0.0, L=0.02, D=9e-7, c_L=2.0, c_inf=0.0, num_eigv=30)
x = np.linspace(0, 0.02, 1000)
for t in np.logspace(-2, 3, 100):
plt.plot(x, slab_dirichlet.evaluate(x, t), "b")
plt.plot(x, slab_noflux.evaluate(x, t), "r")
plt.show()
V = 1000000.
A = 0.001
Bi = 1e-12
L = 1.
D = 1e-5
c_L = 1.
c_inf = 0.
maxt = 100000
dt = 1000
num_elements = 200
times, numeric_uptake, _ = dogbone(V,A,1.,c_L,D,L,num_elements,maxt,dt)
x = np.linspace(0.,L,num_elements)
analytic_uptake = []
for t in times:
analytic = Slab(Bi,L,D,c_L,c_inf)
analytic_c = analytic.evaluate(x,t)
analytic_uptake.append(np.trapz(analytic_c,x))
print A*np.array(analytic_uptake)
print numeric_uptake
plt.plot(times,A*np.array(analytic_uptake),'-')
plt.plot(times,np.array(numeric_uptake),'.')
plt.show()
