def test_nest(self):
min1 = minerals.Murakami_etal_2012.fe_periclase()
min2 = minerals.SLB_2005.periclase()
ca = burnman.composite( [(min1,1.0)] )
c = burnman.composite( [(ca,0.4),(min2, 0.6)] )
c.set_method("slb3")
c.set_state(5e9,1000)
(f,m) = c.unroll()
mins=",".join([a.to_string() for a in m])
self.assertArraysAlmostEqual(f,[0.4,0.6])
self.assertEqual(mins,",".join([min1.to_string(),min2.to_string()]))
def test_nest(self):
min1 = minerals.Murakami_etal_2012.fe_periclase()
min2 = minerals.SLB_2005.periclase()
ca = burnman.composite([(min1, 1.0)])
c = burnman.composite([(ca, 0.4), (min2, 0.6)])
c.set_method("slb3")
c.set_state(5e9, 1000)
(f, m) = c.unroll()
mins = ",".join([a.to_string() for a in m])
self.assertArraysAlmostEqual(f, [0.4, 0.6])
self.assertEqual(mins, ",".join([min1.to_string(), min2.to_string()]))
def test_unroll(self):
min1 = minerals.Murakami_etal_2012.fe_periclase()
min2 = minerals.SLB_2005.periclase()
(f,m) = burnman.composite( [(min1,1.0)] ).unroll()
mins=",".join([a.to_string() for a in m])
self.assertEqual(f,[1.0])
self.assertEqual(mins,"'burnman.minerals.Murakami_etal_2012.fe_periclase'")
(f,m) = burnman.composite( [(min1,0.4),(min2,0.6)] ).unroll()
self.assertEqual(f,[0.4,0.6])
c1 = burnman.composite( [(min1,1.0)] )
c2 = burnman.composite( [(min2,1.0)] )
c = burnman.composite( [(min1,0.1),(c1,0.4),(c2,0.5)] )
(f,m) = c.unroll()
mins=",".join([a.to_string() for a in m])
self.assertEqual(f,[0.1,0.4,0.5])
self.assertEqual(mins,min1.to_string()+','+min1.to_string()+','+min2.to_string())
c1 = burnman.composite( [ (min1,0.1), (min2,0.9) ] )
c2 = burnman.composite( [(min2,1.0)] )
c = burnman.composite( [(min1,0.3),(c1,0.1),(c2,0.6)] )
(f,m) = c.unroll()
mins=",".join([a.to_string() for a in m])
self.assertArraysAlmostEqual(f,[0.3,0.01,0.09,0.6])
self.assertEqual(mins,",".join([min1.to_string(),min1.to_string(),min2.to_string(),min2.to_string()]))
def calc_velocities(mg_pv_K, mg_pv_K_prime, mg_pv_G, mg_pv_G_prime, fe_pv_K,
fe_pv_K_prime, fe_pv_G, fe_pv_G_prime):
method = 'slb3' #slb3|slb2|mgd3|mgd2
amount_perovskite = 0.95
rock = burnman.composite([
(minerals.SLB_2005.mg_fe_perovskite(0.1), amount_perovskite),
(minerals.SLB_2005.ferropericlase(0.5), 1.0 - amount_perovskite)
])
mg_pv = rock.staticphases[0].mineral.base_materials[0]
fe_pv = rock.staticphases[0].mineral.base_materials[1]
mg_pv.params['K_0'] = mg_pv_K
mg_pv.params['Kprime_0'] = mg_pv_K_prime
mg_pv.params['G_0'] = mg_pv_G
mg_pv.params['Gprime_0'] = mg_pv_G_prime
fe_pv.params['K_0'] = fe_pv_K
fe_pv.params['Kprime_0'] = fe_pv_K_prime
fe_pv.params['G_0'] = fe_pv_G
fe_pv.params['Gprime_0'] = fe_pv_G_prime
rock.set_method(method)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(
rock, seis_p, temperature)
return mat_vp, mat_vs, mat_rho
def test_rock(self):
amount_perovskite = 0.3
rock = burnman.composite( ( ( minerals.SLB_2005.mg_fe_perovskite(0.1), amount_perovskite ),
(minerals.SLB_2005.ferropericlase(0.2), 1.0-amount_perovskite) ) )
rock.set_method('slb2')
(fr,phases)=rock.unroll()
self.assertAlmostEqual(fr[0], 0.3, 2)
self.assertAlmostEqual(fr[1], 0.7, 2)
def test_rock(self):
amount_perovskite = 0.3
rock = burnman.composite(
((minerals.SLB_2005.mg_fe_perovskite(0.1), amount_perovskite),
(minerals.SLB_2005.ferropericlase(0.2), 1.0 - amount_perovskite)))
rock.set_method('slb2')
(fr, phases) = rock.unroll()
self.assertAlmostEqual(fr[0], 0.3, 2)
self.assertAlmostEqual(fr[1], 0.7, 2)
def calc_velocities(a,b,c):
method = 'slb3' #slb3|slb2|mgd3|mgd2
amount_perovskite = a
rock = burnman.composite( [ ( minerals.SLB_2005.mg_fe_perovskite(b), amount_perovskite ),
(minerals.SLB_2005.ferropericlase(c), 1.0-amount_perovskite) ] )
rock.set_method(method)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(rock,seis_p, temperature)
return mat_vp, mat_vs, mat_rho
def eval(uncertain):
rock = burnman.composite ( [ (my_perovskite(uncertain), 1.0) ])
rock.set_method('slb3')
temperature = burnman.geotherm.adiabatic(seis_p,1900*uncertain[8],rock)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = \
burnman.velocities_from_rock(rock, seis_p, temperature, burnman.averaging_schemes.voigt_reuss_hill())
return seis_p, mat_vs, mat_vphi, mat_rho
def test_1(self):
rock = burnman.composite ( ( (mypericlase(), 1.0),) )
rock.set_method('slb3')
rho, v_p, v_s, v_phi, K_vrh, G_vrh = \
burnman.velocities_from_rock(rock, [10e9,], [300,])
self.assertAlmostEqual(3791.392, rho[0], 2)
self.assertAlmostEqual(10285.368, v_p[0], 2)
self.assertAlmostEqual(6308.811, v_s[0], 2)
self.assertAlmostEqual(7260.900, v_phi[0], 2)
self.assertAlmostEqual(199.884, K_vrh[0]/1.e9, 2)
self.assertAlmostEqual(150.901, G_vrh[0]/1.e9, 2)
def test_two_different(self):
rock = burnman.composite ( [ (minerals.SLB_2005.periclase(), 1.0),
(minerals.SLB_2005.fe_perovskite(), 0.0) ] )
rock.set_method('slb3')
rho, v_p, v_s, v_phi, K_vrh, G_vrh = \
burnman.velocities_from_rock(rock,[10e9,], [300,])
self.assertAlmostEqual(3791.392, rho[0], 2)
self.assertAlmostEqual(10285.368, v_p[0], 2)
self.assertAlmostEqual(6308.811, v_s[0], 2)
self.assertAlmostEqual(7260.900, v_phi[0], 2)
self.assertAlmostEqual(199.884, K_vrh[0]/1.e9, 2)
self.assertAlmostEqual(150.901, G_vrh[0]/1.e9, 2)
def calc_velocities(a, b, c):
method = 'slb3' #slb3|slb2|mgd3|mgd2
amount_perovskite = a
rock = burnman.composite([
(minerals.SLB_2005.mg_fe_perovskite(b), amount_perovskite),
(minerals.SLB_2005.ferropericlase(c), 1.0 - amount_perovskite)
])
rock.set_method(method)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(
rock, seis_p, temperature)
return mat_vp, mat_vs, mat_rho
def calculate_forward_problem(frac, pressures):
print frac
rock = burnman.composite([
(minerals.SLB_2011.mg_perovskite(), frac[2] * frac[0]),
(minerals.SLB_2011.fe_perovskite(), frac[2] * (1.0 - frac[0])),
(minerals.SLB_2011.periclase(), (1.0 - frac[2])),
(minerals.SLB_2011.wuestite(), 0.0 * (1.0 - frac[2]) * (1.0 - frac[0]))
])
rock.set_method('slb3')
temperature = burnman.geotherm.self_consistent(pressures, frac[1], rock)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(
rock, pressures, temperature)
return mat_rho, mat_vs, mat_vphi
def material_error(amount_perovskite):
rock = burnman.composite ( [ (minerals.Murakami_etal_2012.fe_perovskite(), amount_perovskite),
(minerals.Murakami_etal_2012.fe_periclase(), 1.0 - amount_perovskite) ] )
rock.set_method(method)
print "Calculations are done for:"
rock.debug_print()
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = \
burnman.velocities_from_rock(rock, seis_p, temperature, burnman.averaging_schemes.voigt_reuss_hill())
#[rho_err,vphi_err,vs_err]=burnman.compare_chifactor([mat_vs,mat_vphi,mat_rho],[seis_vs,seis_vphi,seis_rho])
[rho_err,vphi_err,vs_err]=burnman.compare_l2(depths,[mat_vs,mat_vphi,mat_rho],[seis_vs,seis_vphi,seis_rho])
return vs_err, vphi_err
def calc_velocities(ref_rho, K_0, K_prime, G_0, G_prime):
test = burnman.minerals_base.material()
test.params['V_0'] = 10.e-6
test.params['molar_mass'] = ref_rho*test.params['V_0']
test.params['K_0'] = K_0
test.params['Kprime_0'] = K_prime
test.params['G_0'] = G_0
test.params['Gprime_0'] = G_prime
rock = burnman.composite( [(test, 1.0 )] )
rock.set_method('bm3')
temperature = np.empty_like(seis_p)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(rock,seis_p, temperature)
return mat_rho, mat_vphi, mat_vs
def eval_material(amount_perovskite):
# rock = burnman.composite ( [ (minerals.Murakami_etal_2012.fe_perovskite(), amount_perovskite),
# (minerals.Murakami_etal_2012.fe_periclase(), 1.0 - amount_perovskite) ] )
rock = burnman.composite ( [ (minerals.SLB_2011_ZSB_2013.mg_fe_perovskite(0.07), amount_perovskite),
(minerals.SLB_2011.ferropericlase(0.2), 1.0 - amount_perovskite) ] )
# rock = burnman.composite ( [ (minerals.SLB_2011.mg_fe_perovskite(0.), amount_perovskite),
# (minerals.SLB_2011.ferropericlase(1.0), 1.0 - amount_perovskite) ] )
rock.set_method(method)
temperature = burnman.geotherm.adiabatic(seis_p,1900,rock)
print "Calculations are done for:"
rock.debug_print()
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = \
burnman.velocities_from_rock(rock, seis_p, temperature, burnman.averaging_schemes.voigt_reuss_hill())
#[rho_err,vphi_err,vs_err]=burnman.compare_chifactor(mat_vs,mat_vphi,mat_rho,seis_vs,seis_vphi,seis_rho)
return seis_p, mat_vs, mat_vphi, mat_rho
def eval_material(amount_perovskite):
# rock = burnman.composite ( [ (minerals.Murakami_etal_2012.fe_perovskite(), amount_perovskite),
# (minerals.Murakami_etal_2012.fe_periclase(), 1.0 - amount_perovskite) ] )
rock = burnman.composite([
(minerals.SLB_2011.mg_fe_perovskite(0.08), amount_perovskite),
(minerals.SLB_2011.ferropericlase(0.21), 1.0 - amount_perovskite)
])
# rock = burnman.composite ( [ (minerals.SLB_2011.mg_fe_perovskite(0.), amount_perovskite),
# (minerals.SLB_2011.ferropericlase(1.0), 1.0 - amount_perovskite) ] )
rock.set_method(method)
temperature = burnman.geotherm.adiabatic(seis_p, 1900, rock)
print "Calculations are done for:"
rock.debug_print()
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = \
burnman.velocities_from_rock(rock, seis_p, temperature, burnman.averaging_schemes.voigt_reuss_hill())
#[rho_err,vphi_err,vs_err]=burnman.compare_chifactor(mat_vs,mat_vphi,mat_rho,seis_vs,seis_vphi,seis_rho)
return seis_p, mat_vs, mat_vphi, mat_rho
def realize_pyrolite():
#approximate four component pyrolite model
x_pv = 0.67
x_fp = 0.33
pv_fe_num = 0.07
fp_fe_num = 0.2
mg_perovskite = minerals.SLB_2011_ZSB_2013.mg_perovskite(); realize_mineral(mg_perovskite)
fe_perovskite = minerals.SLB_2011_ZSB_2013.fe_perovskite(); realize_mineral(fe_perovskite)
wuestite = minerals.SLB_2011_ZSB_2013.wuestite(); realize_mineral(wuestite)
periclase = minerals.SLB_2011_ZSB_2013.periclase(); realize_mineral(periclase)
perovskite = helper_solid_solution( [ mg_perovskite, fe_perovskite], [1.0-pv_fe_num, pv_fe_num])
ferropericlase = helper_solid_solution( [ periclase, wuestite], [1.0-fp_fe_num, fp_fe_num])
pyrolite = burnman.composite( [ (perovskite, x_pv), (ferropericlase, x_fp) ] )
pyrolite.set_method('slb3')
anchor_temperature = normal(loc = 1935.0, scale = 200.0)
return pyrolite, anchor_temperature
def test_unroll(self):
min1 = minerals.Murakami_etal_2012.fe_periclase()
min2 = minerals.SLB_2005.periclase()
(f, m) = burnman.composite([(min1, 1.0)]).unroll()
mins = ",".join([a.to_string() for a in m])
self.assertEqual(f, [1.0])
self.assertEqual(mins,
"'burnman.minerals.Murakami_etal_2012.fe_periclase'")
(f, m) = burnman.composite([(min1, 0.4), (min2, 0.6)]).unroll()
self.assertEqual(f, [0.4, 0.6])
c1 = burnman.composite([(min1, 1.0)])
c2 = burnman.composite([(min2, 1.0)])
c = burnman.composite([(min1, 0.1), (c1, 0.4), (c2, 0.5)])
(f, m) = c.unroll()
mins = ",".join([a.to_string() for a in m])
self.assertEqual(f, [0.1, 0.4, 0.5])
self.assertEqual(
mins,
min1.to_string() + ',' + min1.to_string() + ',' + min2.to_string())
c1 = burnman.composite([(min1, 0.1), (min2, 0.9)])
c2 = burnman.composite([(min2, 1.0)])
c = burnman.composite([(min1, 0.3), (c1, 0.1), (c2, 0.6)])
(f, m) = c.unroll()
mins = ",".join([a.to_string() for a in m])
self.assertArraysAlmostEqual(f, [0.3, 0.01, 0.09, 0.6])
self.assertEqual(
mins, ",".join([
min1.to_string(),
min1.to_string(),
min2.to_string(),
min2.to_string()
]))
def make_rock():
#approximate four component pyrolite model
x_pv = 0.67
x_fp = 0.33
pv_fe_num = 0.07
fp_fe_num = 0.2
mg_perovskite = minerals.SLB_2011_ZSB_2013.mg_perovskite()
fe_perovskite = minerals.SLB_2011_ZSB_2013.fe_perovskite()
wuestite = minerals.SLB_2011_ZSB_2013.wuestite()
periclase = minerals.SLB_2011_ZSB_2013.periclase()
perovskite = helper_solid_solution([mg_perovskite, fe_perovskite],
[1.0 - pv_fe_num, pv_fe_num])
ferropericlase = helper_solid_solution([periclase, wuestite],
[1.0 - fp_fe_num, fp_fe_num])
pyrolite = burnman.composite([(perovskite, x_pv), (ferropericlase, x_fp)])
pyrolite.set_method('slb3')
anchor_temperature = 1935.0
return pyrolite, anchor_temperature
def calc_velocities(mg_pv_K,mg_pv_K_prime,mg_pv_G,mg_pv_G_prime,fe_pv_K,fe_pv_K_prime,fe_pv_G,fe_pv_G_prime):
method = 'slb3' #slb3|slb2|mgd3|mgd2
amount_perovskite = 0.95
rock = burnman.composite( [ ( minerals.SLB_2005.mg_fe_perovskite(0.1), amount_perovskite ),
(minerals.SLB_2005.ferropericlase(0.5), 1.0-amount_perovskite) ] )
mg_pv = rock.staticphases[0].mineral.base_materials[0]
fe_pv = rock.staticphases[0].mineral.base_materials[1]
mg_pv.params['K_0'] = mg_pv_K
mg_pv.params['Kprime_0'] = mg_pv_K_prime
mg_pv.params['G_0'] = mg_pv_G
mg_pv.params['Gprime_0'] = mg_pv_G_prime
fe_pv.params['K_0'] = fe_pv_K
fe_pv.params['Kprime_0'] = fe_pv_K_prime
fe_pv.params['G_0'] = fe_pv_G
fe_pv.params['Gprime_0'] = fe_pv_G_prime
rock.set_method(method)
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = burnman.velocities_from_rock(rock,seis_p, temperature)
return mat_vp, mat_vs, mat_rho
table_brown = read_table("input_geotherm/brown_81.txt")
table_brown_depth = np.array(table_brown)[:, 0]
table_brown_temperature = np.array(table_brown)[:, 1]
table_anderson = read_table("input_geotherm/anderson_82.txt")
table_anderson_depth = np.array(table_anderson)[:, 0]
table_anderson_temperature = np.array(table_anderson)[:, 1]
# test geotherm
if __name__ == "__main__":
p = np.arange(1.0e9, 128.0e9, 3e9)
pyrolite = burnman.composite([
(burnman.minerals.SLB_2011.mg_fe_perovskite(0.2), 0.8),
(burnman.minerals.SLB_2011.ferropericlase(0.4), 0.2)
])
pyrolite.set_method('slb3')
pyrolite.set_state(40.e9, 2000)
t1 = anderson(p)
t2 = brown_shankland(p)
t3 = adiabatic(p, 1600, pyrolite)
p1, = pyplot.plot(p, t1, 'x--r')
p2, = pyplot.plot(p, t2, '*-g')
p3, = pyplot.plot(p, t3, '*-b')
pyplot.legend([p1, p2, p3], ["anderson", "brown", "adiabatic"], loc=4)
pyplot.show()
#this could also be loaded from a file, just uncomment this
#table = tools.read_table("input_geotherm/example_geotherm.txt")
table_pressure = np.array(table)[:,0]
table_temperature = np.array(table)[:,1]
my_geotherm_interpolate = lambda p: [ burnman.tools.lookup_and_interpolate\
(table_pressure, table_temperature, x) for x in p]
temperature5 = my_geotherm_interpolate(pressures)
#finally, we can also calculate a self consistent
#geotherm for an assemblage of minerals
#based on self compression of the composite rock.
#First we need to define an assemblage
pyrolite = burnman.composite( [ (minerals.SLB_2005.mg_fe_perovskite(0.1), 0.7),
(minerals.SLB_2005.ferropericlase(0.4), 0.3) ] )
pyrolite.set_method("mgd3")
#next, define an anchor temperature at which we are starting.
#Perhaps 1500 K for the upper mantle
T0 = 1500.
#then generate temperature values using the self consistent function.
# This takes more time than the above methods
temperature6 = burnman.geotherm.adiabatic(pressures, T0, pyrolite)
#you can also look at burnman/geotherm.py to see how the geotherms are implemented
plt.plot(pressures/1e9,temperature1,'-r',label="Brown, Shankland")
plt.plot(pressures/1e9,temperature2,'-c',label="Anderson")
plt.plot(pressures/1e9,temperature3,'-g',label="Watson, Baxter")
plt.plot(pressures/1e9,temperature4,'-b',label="handwritten linear")
molar_fraction = [1. - fe_num, 0.0 + fe_num]
mb.helper_solid_solution.__init__(self, base_materials, molar_fraction)
#define the P-T path
pressure = np.linspace(28.0e9, 129e9, 25.)
temperature_bs = burnman.geotherm.brown_shankland(pressure)
temperature_an = burnman.geotherm.anderson(pressure)
#seismic model for comparison:
seismic_model = burnman.seismic.prem() # pick from .prem() .slow() .fast() (see burnman/seismic.py)
depths = map(seismic_model.depth, pressure)
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(depths)
#pure perovskite
perovskitite = burnman.composite( ( (perovskite(0.06), 1.0),) )
perovskitite.set_method(method)
#pure periclase
periclasite = burnman.composite( ( (ferropericlase(0.21), 1.0),))
periclasite.set_method(method)
#pyrolite (80% perovskite)
pyrolite = burnman.composite( ( (perovskite(0.06), 0.834),
(ferropericlase(0.21), 0.166) ) )
pyrolite.set_method(method)
#preferred mixture?
amount_perovskite = 0.92
preferred_mixture = burnman.composite( ( (perovskite(0.06), amount_perovskite),
(ferropericlase(0.21), 1.0-amount_perovskite) ) )
###Input Model 1
#INPUT for method_1
""" choose 'slb' (finite-strain 2nd order sheer modulus, stixrude and lithgow-bertelloni, 2005)
or 'mgd' (mie-gruneisen-debeye, matas et al. 2007)
or 'bm' (birch-murnaghan, if you choose to ignore temperature (your choice in geotherm will not matter in this case))
or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005)"""
method = 'slb2'
#Input composition of model 1. See example_composition for potential choices. We'll just choose something simple here
amount_perovskite_1 = 1.0
rock_1 = burnman.composite(
((minerals.Murakami_etal_2012.fe_perovskite(), amount_perovskite_1),
(minerals.Murakami_etal_2012.fe_periclase(),
1.0 - amount_perovskite_1)))
rock_1.set_method(method)
#input pressure range for first model. This could be from a seismic model or something you create. For this example we will create an array
seis_p_1 = np.arange(28.5e9, 133e9, 4.75e9)
#seismic model for comparison:
seismic_model = burnman.seismic.prem(
) # pick from .prem() .slow() .fast() (see burnman/seismic.py)
depths = map(seismic_model.depth, seis_p_1)
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(
depths)
temperature_bs = burnman.geotherm.brown_shankland(seis_p)
temperature_an = burnman.geotherm.anderson(seis_p)
##Now onto the second model parameters
#INPUT for method_1
""" choose 'slb' (finite-strain 2nd order sheer modulus, stixrude and lithgow-bertelloni, 2005)
or 'mgd' (mie-gruneisen-debeye, matas et al. 2007)
or 'bm' (birch-murnaghan, if you choose to ignore temperature (your choice in geotherm will not matter in this case))
or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005)"""
method = 'mgd2'
# Input for model M_pyrolite as defined in Matas et al. 2007 table 3. Molar proportions are converted to atomic fractions
#weight_percents = {'Mg':0.297882, 'Fe': 0.0489699, 'Si':0.1819, 'Ca':0.0228576, 'Al':0.0116446}
#phase_fractions,relative_molar_percent = burnman.calculate_phase_percents(weight_percents)
rock = burnman.composite( ( (minerals.Matas_etal_2007.mg_perovskite(),.620 ),
(minerals.Matas_etal_2007.fe_perovskite(), .078 ),
(minerals.Matas_etal_2007.periclase(), .268 ),
(minerals.Matas_etal_2007.wuestite(), .034 )))
rock2 = burnman.composite( ( (minerals.Matas_etal_2007.mg_perovskite(),.62 ),
(minerals.Matas_etal_2007.fe_perovskite(), .078/1.46 ),
(minerals.Matas_etal_2007.periclase(), .268 ),
(minerals.Matas_etal_2007.wuestite(), .034/1.46 )))
#KD is 2... doesn't match either
#rock2 = burnman.composite( ( (minerals.Matas_mg_perovskite(),.3574 ),
# (minerals.Matas_fe_perovskite(), .0536 ),
# (minerals.Matas_periclase(), .1656 ),
# (minerals.Matas_wuestite(), .0124 )))
#input pressure range for first model. This could be from a seismic model or something you create. For this example we will create an array
rock.set_method(method)
rock2.set_method(method)
seis_p_1 = np.arange(28e9, 128e9, 4.8e9)
temperature_bs = burnman.geotherm.brown_shankland(seis_p_1)
#seismic model for comparison:
# pick from .prem() .slow() .fast() (see burnman/seismic.py)
seismic_model = burnman.seismic.prem()
number_of_points = 40 #set on how many depth slices the computations should be done
# we will do our computation and comparison at the following depth values:
depths = np.linspace(700e3, 2800e3, number_of_points)
#alternatively, we could use the values where prem is defined:
#depths = seismic_model.internal_depth_list()
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(
depths)
# here we use the Brown & Shankland geotherm
temperature = burnman.geotherm.brown_shankland(seis_p)
# We create one mineral that contains spin transitions
rock = burnman.composite([(minerals.Murakami_etal_2012.fe_periclase(), 1.0)
])
# The mineral Murakami_fe_periclase is derived from minerals.helper_spin_transition
# which contains the logic to switch between two other minerals based on the
# current pressure. The mineral is implemented similar to the following lines:
#
# class Murakami_fe_periclase(helper_spin_transition):
# def __init__(self):
# helper_spin_transition.__init__(self, 63.0e9, Murakami_fe_periclase_LS(), Murakami_fe_periclase_HS())
#
# Note the reference to the low spin and high spin minerals (_LS and _HS).
# Set method, here set to 'slb2' as the shear wave moduli in
# Murakami et al. 2012 were fit to second order
rock.set_method('slb2')
#at room pressure/temperature
'Gprime_0': 1.7, #pressure derivative of shear modulus
'molar_mass': .055845, #molar mass in units of [kg/mol]
'n': 1, #number of atoms per formula unit
'Debye_0': 998.85, #Debye temperature for material.
#See Stixrude & Lithgow-Bertelloni, 2005 for values
'grueneisen_0': 1.368, #Gruneisen parameter for material.
#See Stixrude & Lithgow-Bertelloni, 2005 for values
'q_0': 0.917, #isotropic strain derivative of gruneisen
#parameter. Values in Stixrude & Lithgow-Bertelloni, 2005
'eta_s_0': 3.0} #full strain derivative of gruneisen parameter
#parameter. Values in Stixrude & Lithgow-Bertelloni, 2005
rock = burnman.composite( [(own_material(), 1.0)] )
#seismic model for comparison: (see burnman/seismic.py)
seismic_model = burnman.seismic.prem() # pick from .prem() .slow() .fast()
number_of_points = 20 #set on how many depth slices the computations should be done
depths = np.linspace(700e3,2800e3, number_of_points)
#depths = seismic_model.internal_depth_list()
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(depths)
temperature = burnman.geotherm.brown_shankland(seis_p)
rock.set_method(method)
print "Calculations are done for:"
rock.debug_print()
"""
import os, sys, numpy as np, matplotlib.pyplot as plt
#hack to allow scripts to be placed in subdirectories next to burnman:
if not os.path.exists('burnman') and os.path.exists('../burnman'):
sys.path.insert(1, os.path.abspath('..'))
import burnman
from burnman import minerals
if __name__ == "__main__":
#Input composition.
amount_perovskite = 0.95
rock = burnman.composite([(minerals.Murakami_etal_2012.fe_perovskite(),
amount_perovskite),
(minerals.Murakami_etal_2012.fe_periclase_LS(),
1.0 - amount_perovskite)])
#(min pressure, max pressure, pressure step)
seis_p = np.arange(25e9, 125e9, 5e9)
#Input adiabat potential temperature
T0 = 1500.0
#Now we'll calculate the models for each method
""" 'slb2' (finite-strain 2nd order shear modulus,
stixrude and lithgow-bertelloni, 2005)
or 'slb3 (finite-strain 3rd order shear modulus,
stixrude and lithgow-bertelloni, 2005)
or 'mgd3' (mie-gruneisen-debeye 3rd order shear modulus,
matas et al. 2007)
weight_percents_pyro = {
'Mg': 0.228,
'Fe': 0.0626,
'Si': 0.21,
'Ca': 0.,
'Al': 0.
}
phase_fractions_pyro,relative_molar_percent_pyro = \
burnman.calculate_phase_percents(weight_percents_pyro)
#input initial distribution coefficent. See example_partition_coefficient.py
#for explanation
Kd_0 = .5
iron_content = lambda p,t: burnman.calculate_partition_coefficient\
(p,t,relative_molar_percent_pyro, Kd_0)
pyrolite = burnman.composite( [ (minerals.SLB_2005.mg_fe_perovskite_pt_dependent(iron_content,0),\
phase_fractions_pyro['pv'] ),
(minerals.SLB_2005.ferropericlase_pt_dependent(iron_content,1), \
phase_fractions_pyro['fp'] ) ] )
#input pressure range for first model.
seis_p_1 = np.arange(25e9, 125e9, 5e9)
#input your geotherm.
temperature_1 = burnman.geotherm.brown_shankland(seis_p_1)
##Now onto the second model parameters
##input second method
#Input composition of model enstatite chondrites. See example_composition for ways of inputting composition.
#this could also be loaded from a file, just uncomment this
#table = tools.read_table("input_geotherm/example_geotherm.txt")
table_pressure = np.array(table)[:,0]
table_temperature = np.array(table)[:,1]
my_geotherm_interpolate = lambda p: [ burnman.tools.lookup_and_interpolate\
(table_pressure, table_temperature, x) for x in p]
temperature4 = my_geotherm_interpolate(pressures)
#finally, we can also calculate a self consistent
#geotherm for an assemblage of minerals
#based on self compression of the composite rock.
#First we need to define an assemblage
pyrolite = burnman.composite( [ (minerals.SLB_2005.mg_fe_perovskite(0.1), 0.7),
(minerals.SLB_2005.ferropericlase(0.4), 0.3) ] )
pyrolite.set_method("mgd3")
#next, define an anchor temperature at which we are starting.
#Perhaps 1500 K for the upper mantle
T0 = 1500.
#then generate temperature values using the self consistent function.
# This takes more time than the above methods
temperature5 = burnman.geotherm.adiabatic(pressures, T0, pyrolite)
#you can also look at burnman/geotherm.py to see how the geotherms are implemented
plt.plot(pressures/1e9,temperature1,'-r',label="Brown, Shankland")
plt.plot(pressures/1e9,temperature2,'-c',label="Anderson")
plt.plot(pressures/1e9,temperature3,'-b',label="handwritten linear")
plt.plot(pressures/1e9,temperature4,'-k',label="handwritten from table")
(your choice in geotherm will not matter in this case))"""
method = 'slb3'
# To compute seismic velocities and other properties, we need to supply
# burnman with a list of minerals (phases) and their molar abundances. Minerals
# are classes found in burnman.minerals and are derived from
# burnman.minerals.material.
# Here are a few ways to define phases and molar_abundances:
#Example 1: two simple fixed minerals
if True:
amount_perovskite = 0.95
rock = burnman.composite ( [ (minerals.SLB_2011.mg_perovskite(), amount_perovskite),
(minerals.SLB_2011.periclase(), \
1.0-amount_perovskite) ] )
#Example 2: specify fixed iron content
if False:
amount_perovskite = 0.95
rock = burnman.composite( [ (minerals.SLB_2011.mg_fe_perovskite(0.2), amount_perovskite), \
(minerals.SLB_2011.ferropericlase(0.2), 1.0-amount_perovskite) ] )
#Example 3: input weight percentages
#See comments in example_partition_coef.py for references to
#partition coefficent calculation
if False:
weight_percents = {'Mg':0.213, 'Fe': 0.08, 'Si':0.27, 'Ca':0., 'Al':0.}
Kd_0 = .59 #Fig 5 Nakajima et al 2012
or 'bm' (birch-murnaghan, if you choose to ignore temperature
(your choice in geotherm will not matter in this case))"""
method = 'slb3'
# To compute seismic velocities and other properties, we need to supply
# burnman with a list of minerals (phases) and their molar abundances. Minerals
# are classes found in burnman.minerals and are derived from
# burnman.minerals.material.
# Here are a few ways to define phases and molar_abundances:
#Example 1: two simple fixed minerals
if True:
amount_perovskite = 0.95
rock = burnman.composite ( [ (minerals.SLB_2011.mg_perovskite(), amount_perovskite),
(minerals.SLB_2011.periclase(), \
1.0-amount_perovskite) ] )
#Example 2: specify fixed iron content
if False:
amount_perovskite = 0.95
rock = burnman.composite( [ (minerals.SLB_2011.mg_fe_perovskite(0.2), amount_perovskite), \
(minerals.SLB_2011.ferropericlase(0.2), 1.0-amount_perovskite) ] )
#Example 3: input weight percentages
#See comments in example_partition_coef.py for references to
#partition coefficent calculation
if False:
weight_percents = {
'Mg': 0.213,
# the library, including the ability to make composites, and compute
# thermoelastic properties of them. The minerals module includes
# the mineral physical parameters for the predefined minerals in
# BurnMan
import burnman
from burnman import minerals
if __name__ == "__main__":
# This is the first actual work done in this example. We define
# composite object and name it "rock". A composite is made by
# giving burnman.composite a list of minerals and their molar fractions.
# Here "rock" has two constituent minerals: it is 80% Mg perovskite
# and 20% periclase. More minerals may be added by simply extending
# the list given to burnman.composite
rock = burnman.composite ( [ (minerals.SLB_2011.mg_perovskite(), 0.80),\
(minerals.SLB_2011.periclase(), 0.20) ] )
# Here we create and load the PREM seismic velocity model, which will be
# used for comparison with the seismic velocities of the "rock" composite
seismic_model = burnman.seismic.prem()
# We create an array of 20 depths at which we want to evaluate PREM, and then
# query the seismic model for the pressure, density, P wave speed, S wave
# speed, and bulk sound velocity at those depths
depths = np.linspace(750e3, 2800e3, 20)
pressure, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(depths)
# Now we get an array of temperatures at which will be used for computing
# the seismic properties of the rock. Here we use the Brown+Shankland (1981)
stixrude and lithgow-bertelloni, 2005) or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005) or 'mgd3' (mie-gruneisen-debeye 3rd order shear modulus, matas et al. 2007) or 'mgd2' (mie-gruneisen-debeye 2nd order shear modulus, matas et al. 2007) or 'bm2' (birch-murnaghan 2nd order, if you choose to ignore temperature (your choice in geotherm will not matter in this case)) or 'bm3' (birch-murnaghan 3rd order, if you choose to ignore temperature (your choice in geotherm will not matter in this case))""" amount_perovskite = 0.6 method = 'slb3' rock = burnman.composite( [ (minerals.SLB_2005.mg_perovskite(), amount_perovskite), (minerals.SLB_2005.periclase(), 1.0-amount_perovskite) ] ) rock.set_method(method) perovskitite = burnman.composite( [ (minerals.SLB_2005.mg_perovskite(), 1.0), ] ) perovskitite.set_method(method) periclasite = burnman.composite( [ (minerals.SLB_2005.periclase(), 1.0), ] ) periclasite.set_method(method) #seismic model for comparison: # pick from .prem() .slow() .fast() (see burnman/seismic.py) seismic_model = burnman.seismic.prem() #set on how many depth slices the computations should be done number_of_points = 20 # we will do our computation and comparison at the following depth values: depths = np.linspace(700e3, 2800e3, number_of_points)
# the library, including the ability to make composites, and compute
# thermoelastic properties of them. The minerals module includes
# the mineral physical parameters for the predefined minerals in
# BurnMan
import burnman
from burnman import minerals
if __name__ == "__main__":
# This is the first actual work done in this example. We define
# composite object and name it "rock". A composite is made by
# giving burnman.composite a list of minerals and their molar fractions.
# Here "rock" has two constituent minerals: it is 80% Mg perovskite
# and 20% periclase. More minerals may be added by simply extending
# the list given to burnman.composite
rock = burnman.composite ( [ (minerals.SLB_2011.mg_perovskite(), 0.80),\
(minerals.SLB_2011.periclase(), 0.20) ] )
# Here we create and load the PREM seismic velocity model, which will be
# used for comparison with the seismic velocities of the "rock" composite
seismic_model = burnman.seismic.prem()
# We create an array of 20 depths at which we want to evaluate PREM, and then
# query the seismic model for the pressure, density, P wave speed, S wave
# speed, and bulk sound velocity at those depths
depths = np.linspace(750e3, 2800e3, 20)
pressure, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(
depths)
# Now we get an array of temperatures at which will be used for computing
# the seismic properties of the rock. Here we use the Brown+Shankland (1981)
# geotherm for mapping pressure to temperature
#at room pressure/temperature
'Gprime_0': 1.7, #pressure derivative of shear modulus
'molar_mass': .055845, #molar mass in units of [kg/mol]
'n': 1, #number of atoms per formula unit
'Debye_0': 998.85, #Debye temperature for material.
#See Stixrude & Lithgow-Bertelloni, 2005 for values
'grueneisen_0': 1.368, #Gruneisen parameter for material.
#See Stixrude & Lithgow-Bertelloni, 2005 for values
'q_0': 0.917, #isotropic strain derivative of gruneisen
#parameter. Values in Stixrude & Lithgow-Bertelloni, 2005
'eta_s_0': 3.0
} #full strain derivative of gruneisen parameter
#parameter. Values in Stixrude & Lithgow-Bertelloni, 2005
rock = burnman.composite([(own_material(), 1.0)])
#seismic model for comparison: (see burnman/seismic.py)
seismic_model = burnman.seismic.prem() # pick from .prem() .slow() .fast()
number_of_points = 20 #set on how many depth slices the computations should be done
depths = np.linspace(700e3, 2800e3, number_of_points)
#depths = seismic_model.internal_depth_list()
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(
depths)
temperature = burnman.geotherm.brown_shankland(seis_p)
rock.set_method(method)
print "Calculations are done for:"
rock.debug_print()
- Each method for calculating velocity profiles currently included within BurnMan
"""
import os, sys, numpy as np, matplotlib.pyplot as plt
#hack to allow scripts to be placed in subdirectories next to burnman:
if not os.path.exists('burnman') and os.path.exists('../burnman'):
sys.path.insert(1,os.path.abspath('..'))
import burnman
from burnman import minerals
if __name__ == "__main__":
#Input composition.
amount_perovskite = 0.95
rock = burnman.composite( [ (minerals.Murakami_etal_2012.fe_perovskite(), amount_perovskite),
(minerals.Murakami_etal_2012.fe_periclase_LS(), 1.0-amount_perovskite) ] )
#(min pressure, max pressure, pressure step)
seis_p = np.arange(25e9, 125e9, 5e9)
#Input adiabat potential temperature
T0 = 1500.0
#Now we'll calculate the models for each method
""" 'slb2' (finite-strain 2nd order shear modulus,
stixrude and lithgow-bertelloni, 2005)
or 'slb3 (finite-strain 3rd order shear modulus,
stixrude and lithgow-bertelloni, 2005)
or 'mgd3' (mie-gruneisen-debeye 3rd order shear modulus,
matas et al. 2007)
or 'mgd2' (mie-gruneisen-debeye 2nd order shear modulus,
return temperature*top/bottom
table_brown = read_table("input_geotherm/brown_81.txt")
table_brown_depth = np.array(table_brown)[:,0]
table_brown_temperature = np.array(table_brown)[:,1]
table_anderson = read_table("input_geotherm/anderson_82.txt")
table_anderson_depth = np.array(table_anderson)[:,0]
table_anderson_temperature = np.array(table_anderson)[:,1]
# test geotherm
if __name__ == "__main__":
p = np.arange(1.0e9,128.0e9,3e9)
pyrolite = burnman.composite( [ (burnman.minerals.SLB_2011.mg_fe_perovskite(0.2), 0.8), (burnman.minerals.SLB_2011.ferropericlase(0.4), 0.2) ] )
pyrolite.set_method('slb3')
pyrolite.set_state(40.e9, 2000)
t1 = anderson(p)
t2 = brown_shankland(p)
t3 = adiabatic(p, 1600, pyrolite)
p1,=pyplot.plot(p,t1,'x--r')
p2,=pyplot.plot(p,t2,'*-g')
p3,=pyplot.plot(p,t3,'*-b')
pyplot.legend([p1,p2,p3],[ "anderson", "brown", "adiabatic"], loc=4)
pyplot.show()
#define the P-T path
pressure = np.linspace(28.0e9, 129e9, 25.)
temperature_bs = burnman.geotherm.brown_shankland(pressure)
temperature_an = burnman.geotherm.anderson(pressure)
#seismic model for comparison:
seismic_model = burnman.seismic.prem(
) # pick from .prem() .slow() .fast() (see burnman/seismic.py)
depths = map(seismic_model.depth, pressure)
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(
depths)
#pure perovskite
perovskitite = burnman.composite(((perovskite(0.06), 1.0), ))
perovskitite.set_method(method)
#pure periclase
periclasite = burnman.composite(((ferropericlase(0.21), 1.0), ))
periclasite.set_method(method)
#pyrolite (80% perovskite)
pyrolite = burnman.composite(
((perovskite(0.06), 0.834), (ferropericlase(0.21), 0.166)))
pyrolite.set_method(method)
#preferred mixture?
amount_perovskite = 0.92
preferred_mixture = burnman.composite(
((perovskite(0.06), amount_perovskite), (ferropericlase(0.21),
#input weight percentages and distribution coefficient
#See comments in burnman/composition.py for references to
#partition coefficent calculation
weight_percents = {'Mg':0.213, 'Fe': 0.08, 'Si':0.27, 'Ca':0., 'Al':0.}
phase_fractions,relative_molar_percent = \
burnman.calculate_phase_percents(weight_percents)
Kd_0 = .5 #Fig 5 Nakajima et al 2012
iron_content = lambda p,t: \
burnman.calculate_partition_coefficient(p,t,relative_molar_percent,Kd_0)
rock = burnman.composite ( [ (minerals.SLB_2005.mg_fe_perovskite_pt_dependent(iron_content,1),\
phase_fractions['pv'] ),
(minerals.SLB_2005.ferropericlase_pt_dependent(iron_content,0),\
phase_fractions['fp'] ) ] )
#seismic model for comparison:
seismic_model = burnman.seismic.prem() # pick from .prem() .slow() .fast()
#(see burnman/seismic.py)
number_of_points = 20 #set on how many depth slices the computations should be done
# we will do our computation and comparison at the following depth values:
depths = np.linspace(700e3, 2800e3, number_of_points)
#alternatively, we could use the values where prem is defined:
#depths = seismic_model.internal_depth_list()
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(depths)
temperature = burnman.geotherm.brown_shankland(seis_p)
#INPUT for method_1
""" choose 'slb' (finite-strain 2nd order sheer modulus, stixrude and lithgow-bertelloni, 2005)
or 'mgd' (mie-gruneisen-debeye, matas et al. 2007)
or 'bm' (birch-murnaghan, if you choose to ignore temperature (your choice in geotherm will not matter in this case))
or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005)"""
method = 'bm3'
# Input for model M_pyrolite as defined in Matas et al. 2007 table 3. Molar proportions are converted to atomic fractions
#weight_percents = {'Mg':0.297882, 'Fe': 0.0489699, 'Si':0.1819, 'Ca':0.0228576, 'Al':0.0116446}
#phase_fractions,relative_molar_percent = burnman.calculate_phase_percents(weight_percents)
rock = burnman.composite(
((minerals.SLB2011_mg_perovskite(),
0.5 * 1.00), (minerals.SLB2011_fe_perovskite(),
.9 * 0.0), (minerals.SLB2011_periclase(), 0.5 * 1.00),
(minerals.SLB2011_wuestite(), 0.1 * 0.0)))
rock2 = burnman.composite(
((minerals.mg_perovskite(), .62), (minerals.fe_perovskite(),
.078 / 1.5),
(minerals.periclase(), .28), (minerals.wuestite(), .034 / 1.5)))
#KD is 2... doesn't match either
#rock2 = burnman.composite( ( (minerals.Matas_mg_perovskite(),.3574 ),
# (minerals.Matas_fe_perovskite(), .0536 ),
# (minerals.Matas_periclase(), .1656 ),
# (minerals.Matas_wuestite(), .0124 )))
#input pressure range for first model. This could be from a seismic model or something you create. For this example we will create an array
rock.set_method(method)
rock2.set_method(method)
seis_p_1 = np.arange(28e9, 128e9, 4.8e9)
#INPUT for method_1
""" choose 'slb' (finite-strain 2nd order sheer modulus, stixrude and lithgow-bertelloni, 2005)
or 'mgd' (mie-gruneisen-debeye, matas et al. 2007)
or 'bm' (birch-murnaghan, if you choose to ignore temperature (your choice in geotherm will not matter in this case))
or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005)"""
method = 'bm3'
# Input for model M_pyrolite as defined in Matas et al. 2007 table 3. Molar proportions are converted to atomic fractions
#weight_percents = {'Mg':0.297882, 'Fe': 0.0489699, 'Si':0.1819, 'Ca':0.0228576, 'Al':0.0116446}
#phase_fractions,relative_molar_percent = burnman.calculate_phase_percents(weight_percents)
rock = burnman.composite( ( (minerals.SLB2011_mg_perovskite(),0.5*1.00),
(minerals.SLB2011_fe_perovskite(), .9*0.0 ),
(minerals.SLB2011_periclase(), 0.5*1.00 ),
(minerals.SLB2011_wuestite(), 0.1*0.0 )))
rock2 = burnman.composite( ( (minerals.mg_perovskite(),.62 ),
(minerals.fe_perovskite(), .078/1.5 ),
(minerals.periclase(), .28 ),
(minerals.wuestite(), .034/1.5 )))
#KD is 2... doesn't match either
#rock2 = burnman.composite( ( (minerals.Matas_mg_perovskite(),.3574 ),
# (minerals.Matas_fe_perovskite(), .0536 ),
# (minerals.Matas_periclase(), .1656 ),
# (minerals.Matas_wuestite(), .0124 )))
#input pressure range for first model. This could be from a seismic model or something you create. For this example we will create an array
rock.set_method(method)
rock2.set_method(method)
seis_p_1 = np.arange(28e9, 128e9, 4.8e9)
temperature_bs = burnman.geotherm.brown_shankland(seis_p_1)
#INPUT for method_1
""" choose 'slb' (finite-strain 2nd order sheer modulus, stixrude and lithgow-bertelloni, 2005)
or 'mgd' (mie-gruneisen-debeye, matas et al. 2007)
or 'bm' (birch-murnaghan, if you choose to ignore temperature (your choice in geotherm will not matter in this case))
or 'slb3 (finite-strain 3rd order shear modulus, stixrude and lithgow-bertelloni, 2005)"""
method = 'mgd2'
# Input for model M_pyrolite as defined in Matas et al. 2007 table 3. Molar proportions are converted to atomic fractions
#weight_percents = {'Mg':0.297882, 'Fe': 0.0489699, 'Si':0.1819, 'Ca':0.0228576, 'Al':0.0116446}
#phase_fractions,relative_molar_percent = burnman.calculate_phase_percents(weight_percents)
rock = burnman.composite(
((minerals.Matas_etal_2007.mg_perovskite(),
.620), (minerals.Matas_etal_2007.fe_perovskite(),
.078), (minerals.Matas_etal_2007.periclase(), .268),
(minerals.Matas_etal_2007.wuestite(), .034)))
rock2 = burnman.composite(
((minerals.Matas_etal_2007.mg_perovskite(),
.62), (minerals.Matas_etal_2007.fe_perovskite(),
.078 / 1.46), (minerals.Matas_etal_2007.periclase(), .268),
(minerals.Matas_etal_2007.wuestite(), .034 / 1.46)))
#KD is 2... doesn't match either
#rock2 = burnman.composite( ( (minerals.Matas_mg_perovskite(),.3574 ),
# (minerals.Matas_fe_perovskite(), .0536 ),
# (minerals.Matas_periclase(), .1656 ),
# (minerals.Matas_wuestite(), .0124 )))
#input pressure range for first model. This could be from a seismic model or something you create. For this example we will create an array
rock.set_method(method)
rock2.set_method(method)
#seismic model for comparison:
# pick from .prem() .slow() .fast() (see burnman/seismic.py)
seismic_model = burnman.seismic.prem()
number_of_points = 40 #set on how many depth slices the computations should be done
# we will do our computation and comparison at the following depth values:
depths = np.linspace(700e3, 2800e3, number_of_points)
#alternatively, we could use the values where prem is defined:
#depths = seismic_model.internal_depth_list()
seis_p, seis_rho, seis_vp, seis_vs, seis_vphi = seismic_model.evaluate_all_at(depths)
# here we use the Brown & Shankland geotherm
temperature = burnman.geotherm.brown_shankland(seis_p)
# We create one mineral that contains spin transitions
rock = burnman.composite ( [(minerals.Murakami_etal_2012.fe_periclase(), 1.0)] )
# The mineral Murakami_fe_periclase is derived from minerals.helper_spin_transition
# which contains the logic to switch between two other minerals based on the
# current pressure. The mineral is implemented similar to the following lines:
#
# class Murakami_fe_periclase(helper_spin_transition):
# def __init__(self):
# helper_spin_transition.__init__(self, 63.0e9, Murakami_fe_periclase_LS(), Murakami_fe_periclase_HS())
#
# Note the reference to the low spin and high spin minerals (_LS and _HS).
# Set method, here set to 'slb2' as the shear wave moduli in
# Murakami et al. 2012 were fit to second order
rock.set_method('slb2')
stixrude and lithgow-bertelloni, 2005)
or 'slb3 (finite-strain 3rd order shear modulus,
stixrude and lithgow-bertelloni, 2005)
or 'mgd3' (mie-gruneisen-debeye 3rd order shear modulus,
matas et al. 2007)
or 'mgd2' (mie-gruneisen-debeye 2nd order shear modulus,
matas et al. 2007)
or 'bm2' (birch-murnaghan 2nd order, if you choose to ignore temperature
(your choice in geotherm will not matter in this case))
or 'bm3' (birch-murnaghan 3rd order, if you choose to ignore temperature
(your choice in geotherm will not matter in this case))"""
method = 'mgd3'
#specify material
amount_perovskite = 0.95
rock = burnman.composite( [(minerals.SLB_2005.mg_fe_perovskite(0.7), amount_perovskite),
(minerals.SLB_2005.ferropericlase(0.5), 1.0-amount_perovskite) ] )
#define some pressure range
pressures = np.arange(25e9,130e9,5e9)
temperature = burnman.geotherm.brown_shankland(pressures)
rock.set_method(method) #append method of calculation to suite of minerals chosen
#Begin calculating velocities and density as depth
print "Calculations are done for:"
rock.debug_print()
mat_rho, mat_vp, mat_vs, mat_vphi, mat_K, mat_G = \
burnman.velocities_from_rock(rock, pressures, temperature, \
burnman.averaging_schemes.voigt_reuss_hill())
