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%matplotlib inline
from pylab import polyfit
%run /home/ccadiou/rc_loader.py
from matplotlib.colors import LogNorm
FGM = dict()
kR = dict()
kZ = dict()
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for B in ["0", "4", "10", "100"]:
f = open("results/MRI_B"+B+"FGM")
FGM[B] = np.array([ [ float(e) for e in line.split() ] for line in f.readlines() ])
#FGM_masked[B] = np.ma.masked_less_equal(FGM/2.7e-6, 0)
f = open("results/MRI_B"+B+"kR")
kR[B] = np.array([ [ float(e) for e in line.split() ] for line in f.readlines() ])
f = open("results/MRI_B"+B+"kZ")
kZ[B] = np.array([ [ float(e) for e in line.split() ] for line in f.readlines() ])
n = 100
omega = np.fromfunction(lambda _, x : 30*(x+1)/n, (n, n))
dlogomegadlogr = np.fromfunction(lambda x, _ : -20*(x+1)/n, (n, n))
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for B in ["0", "4", "10", "100"]:
plt.rcParams.update(get_param("column", "normal"))
plt.figure()
plt.imshow(FGM[B]/omega, extent=(0, 30, -20, 0), interpolation='none', aspect='auto')
plt.colorbar()
plt.xlabel("$\Omega/\Omega_\star$")
plt.ylabel("$\partial\log\Omega/\partial\log r$")
plt.title("FGM [$\Omega_\odot$]")
plt.savefig("/home/ccadiou/pfs/simulations/current/figs/MRI_FGM_B"+B+".eps")
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for B in ["0", "4", "10", "100"]:
plt.rcParams.update(get_param("column", "normal"))
plt.figure()
Rsun = 6.96e10
OmegaSun = 2.7e-6
plt.imshow(FGM[B]/(kR[B]*kR[B])*(OmegaSun*Rsun**2), extent=(0, 30, -20, 0), interpolation='none', aspect='auto',
norm=LogNorm(vmax=1e16))
cb = plt.colorbar()
plt.xlabel("$\Omega$ [$\Omega_\odot$]")
plt.ylabel("$\partial\log\Omega/\partial\log r$")
cb.set_label("$\sigma/k_R^2$ [$\mathrm{cm}^2.\mathrm{s}^{-1}$]")
plt.savefig("/home/ccadiou/pfs/simulations/current/figs/MRI_diff_coeff_B"+B+".eps")
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plt.rcParams.update(get_param("text", 0.3))
fig, axes = plt.subplots(nrows=2, ncols=2)
(ax11, ax12, ax21, ax22) = axes.flat
B = "0"
ax11 = plt.subplot(221)
ax11.imshow(FGM[B]/(kR[B]*kR[B])*(OmegaSun*Rsun**2), extent=(0, 30, -20, 0), interpolation='none', aspect='auto',
norm=LogNorm(vmin=1e10, vmax=1e16))
ax11.tick_params(
axis='x', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
labelbottom='off') # labels along the bottom edge are offax12.tick_params(bottom='off')
ax11.set_ylabel("$\partial\log\Omega/\partial\log r$")
B = "4"
ax12 = plt.subplot(222)
ax12.imshow(FGM[B]/(kR[B]*kR[B])*(OmegaSun*Rsun**2), extent=(0, 30, -20, 0), interpolation='none', aspect='auto',
norm=LogNorm(vmin=1e10, vmax=1e16))
ax12.tick_params(
axis='x', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
bottom='off', # ticks along the bottom edge are off
top='off', # ticks along the top edge are off
labelbottom='off') # labels along the bottom edge are offax12.tick_params(bottom='off')
ax12.tick_params(
axis='y', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
right='off', # ticks along the bottom edge are off
left='off', # ticks along the top edge are off
labelleft='off') # labels along the bottom edge are offax12.tick_params(bottom='off')
B = "10"
ax21 = plt.subplot(223)
ax21.imshow(FGM[B]/(kR[B]*kR[B])*(OmegaSun*Rsun**2), extent=(0, 30, -20, 0), interpolation='none', aspect='auto',
norm=LogNorm(vmin=1e10, vmax=1e16))
ax21.tick_params(bottom='off', right='off')
ax21.set_xlabel("$\Omega$ [$\Omega_\odot$]")
ax21.set_ylabel("$\partial\log\Omega/\partial\log r$")
B = "100"
ax22 = plt.subplot(224)
im = ax22.imshow(FGM[B]/(kR[B]*kR[B])*(OmegaSun*Rsun**2), extent=(0, 30, -20, 0), interpolation='none', aspect='auto',
norm=LogNorm(vmin=1e8, vmax=1e16))
ax22.tick_params(
axis='y', # changes apply to the x-axis
which='both', # both major and minor ticks are affected
right='off', # ticks along the bottom edge are off
left='off', # ticks along the top edge are off
labelleft='off') # labels along the bottom edge are offax12.tick_params(bottom='off')
ax22.set_xlabel("$\Omega$ [$\Omega_\odot$]")
fig.subplots_adjust(wspace=0, hspace=0, right=0.85, bottom=0.2, left=0.1)
cbar_ax = fig.add_axes([0.87, 0.2, 0.02, 0.7])
cb = fig.colorbar(im, cax=cbar_ax)
cb.set_label("$\sigma/k_R^2$ [$cm^2/s$]")
#plt.tight_layout()
plt.savefig("/home/ccadiou/pfs/simulations/current/figs/MRI_multiple_B_diff_coeff.eps")
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