def get_velocity(args_here):
# Unwrap Args
i, frame = args_here
# Data
if mpi:
density = Fields("./", 'gas', frame).get_field("dens").reshape(num_z, num_rad, num_theta)
vz = Fields("./", 'gas', frame).get_field("vz").reshape(num_z, num_rad, num_theta)
vrad = Fields("./", 'gas', frame).get_field("vy").reshape(num_z, num_rad, num_theta)
vtheta = Fields("./", 'gas', frame).get_field("vx").reshape(num_z, num_rad, num_theta)
else:
density = fromfile("gasdens%d.dat" % frame).reshape(num_z, num_rad, num_theta)
vz = (fromfile("gasvz%d.dat" % frame).reshape(num_z, num_rad, num_theta)) # add a read_vrad to util.py!
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_z, num_rad, num_theta)) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_z, num_rad, num_theta)) # add a read_vrad to util.py!
midplane_density = density[num_z / 2 + args.sliver, :, :]
midplane_vrad = vrad[num_z / 2 + args.sliver, :, :]
midplane_vtheta = vtheta[num_z / 2 + args.sliver, :, :]
midplane_vz = vz[num_z / 2 + args.sliver, :, :]
dz = z_angles[1] - z_angles[0]
surface_density = np.sum(density[:, :, :], axis = 0) * dz
averagedDensity = np.average(surface_density, axis = -1)
average_midplane_vz = np.average(np.abs(midplane_vz), axis = -1)
composite_vz[i, :] = average_midplane_vz
peak, _ = az.get_radial_peak(averagedDensity, fargo_par)
composite_peak[i] = peak
def get_contrasts(args_here):
# Unwrap Args
i, frame = args_here
# Get Data
density = fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta) / surface_density_zero
averagedDensity = np.average(density, axis=-1)
peak_rad, peak_density = az.get_radial_peak(averagedDensity, fargo_par)
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=True,
residual=True)
#vorticity, shift_c = shift_data(vorticity, fargo_par, reference_density = density)
# Find minimum
start_rad_i = np.searchsorted(rad, peak_rad - 0.1) # Is this necessary?
end_rad_i = np.searchsorted(rad, peak_rad + 1.0)
azimuthal_profile = vorticity[start_rad_i:end_rad_i]
rossby_number_over_time[i] = np.min(azimuthal_profile)
rossby_number_over_time_98[i] = np.percentile(azimuthal_profile, 0.2)
rossby_number_over_time_95[i] = np.percentile(azimuthal_profile, 0.5)
print i, frame, rossby_number_over_time[i], rossby_number_over_time_98[
i], rossby_number_over_time_95[i]
def get_rossby_number(args_here):
# Unwrap Args
i, frame, directory = args_here
if frame == 8800:
frame = 8801 # Remove problem frame
# Get Data
density = fromfile("../%s/gasdens%d.dat" % (directory, frame)).reshape(
num_rad, num_theta) / surface_density_zero
averagedDensity = np.average(density, axis=-1)
peak_rad, peak_density = az.get_radial_peak(averagedDensity, fargo_par)
vrad = (fromfile("../%s/gasvy%d.dat" % (directory, frame)).reshape(
num_rad, num_theta)) # add a read_vrad to util.py!
vtheta = (fromfile("../%s/gasvx%d.dat" % (directory, frame)).reshape(
num_rad, num_theta)) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=True,
residual=True)
#vorticity, shift_c = shift_data(vorticity, fargo_par, reference_density = density)
# Find minimum
start_rad = min([peak_rad - 0.05, 1.5])
start_rad_i = np.searchsorted(rad, start_rad) # Is this necessary?
end_rad_i = np.searchsorted(rad, 2.5)
azimuthal_profile = vorticity[start_rad_i:end_rad_i]
rossby_number_over_time[i] = np.percentile(azimuthal_profile, 0.25)
print i, frame, rossby_number_over_time[i]
def get_total_mass(args, num_scale_heights=3):
# Args
i, frame = args
# Get Data
density = util.read_dust_data(frame, fargo_par) # Dust!!!!
# Find Center
avgDensity = np.average(density, axis=-1)
peak_rad, peak_density = az.get_radial_peak(avgDensity, fargo_par)
# Zoom in on annulus
start_rad = peak_rad - 0.5 * num_scale_heights * scale_height
end_rad = peak_rad + 0.5 * num_scale_heights * scale_height
start_rad_i = np.searchsorted(rad, start_rad)
end_rad_i = np.searchsorted(rad, end_rad)
rad_annulus = rad[start_rad_i:end_rad_i]
density_annulus = density[start_rad_i:end_rad_i]
# Multiply by Grid Cell size
dr = rad[1] - rad[0]
dphi = theta[1] - theta[0]
density_annulus = (
dr * dphi
) * rad_annulus[:, None] * density_annulus # (r * dr * d\phi) * \rho
# Calculate and store total mass
total_mass = np.sum(density_annulus)
total_masses[i] = total_mass
def get_min(args_here):
# Unwrap Args
i, frame, directory = args_here
# Get Data
density = fromfile("../%s/gasdens%d.dat" % (directory, frame)).reshape(
num_rad, num_theta)
avg_density = np.average(density, axis=1)
normalized_density = avg_density / surface_density_zero
# Get Minima
radial_peak_a, _ = az.get_radial_peak(avg_density, fargo_par, end=1.6)
# Print Update
print "%d: %.3f" % (frame, radial_peak_a)
# Store Data
radial_peak_over_time[i] = radial_peak_a
def get_extents(args_here):
# Unwrap Args
i, frame = args_here
# Get Data
density = fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta) / surface_density_zero
avg_density = np.average(density, axis=1)
azimuthal_extent = az.get_extent(density, fargo_par, threshold=1.0)
radial_extent, radial_peak = az.get_radial_extent(density,
fargo_par,
threshold=1.0)
radial_peak_a, _ = az.get_radial_peak(avg_density, fargo_par)
azimuthal_extent_over_time[i] = azimuthal_extent * (180.0 / np.pi)
radial_extent_over_time[i] = radial_extent / scale_height
radial_peak_over_time[i] = radial_peak
radial_peak_over_time_a[i] = radial_peak_a
print i, frame, azimuthal_extent_over_time[i], radial_extent_over_time[
i], radial_peak_over_time[i], radial_peak_over_time_a[i]
def find_rossby_density(averaged_density, averaged_vorticity):
# Maximum Condition (and its derivative)
maximum_condition = (averaged_density[1:] / averaged_vorticity) * (
np.power(scale_height, 2) / np.power(rad[1:], 1))
dr = rad[1] - rad[0]
diff_maximum_condition = np.diff(maximum_condition) / dr
# Diagnostics
peak_rad, peak_density = az.get_radial_peak(averaged_density, fargo_par)
peak_rad_i = np.searchsorted(rad, peak_rad)
inner_limit_i = np.searchsorted(
rad, 1.1) # Make inner limit a variable in the future
outer_limit_i = np.searchsorted(
rad, 2.0) # Make outer limit a variable in the future
inner_max_diff_i = np.argmax(
diff_maximum_condition[inner_limit_i:peak_rad_i])
inner_max_diff_i += inner_limit_i # put the "inner disk" back
rossby_min_density = averaged_density[
inner_max_diff_i] # Density at location with the steepest gradient in the maximum condition (c_s^2 * density / vorticity)
return rossby_min_density
def make_plot(frame, show = False):
# Set up figure
fig = plot.figure(figsize = (7, 6), dpi = dpi)
ax = fig.add_subplot(111)
# Data
field = "dens"
if mpi:
density = Fields("./", 'dust1', frame).get_field(field).reshape(num_z, num_rad, num_theta)
else:
density = fromfile("dust1dens%d.dat" % frame).reshape(num_z, num_rad, num_theta)
scale_height_function = np.zeros(num_rad)
mean_function = np.zeros(num_rad)
meridional_density = np.average(density, axis = -1)
for i in range(num_rad):
popt, pcov = curve_fit(gaussian, z_angles, meridional_density[:, i])
(A, mean, sigma) = popt
scale_height_function[i] = sigma # scale height (as an angle)
mean_function[i] = np.abs(mean - np.pi / 2.0)
### Plot ###
x = rad
y = scale_height_function / scale_height
y2 = (mean_function + scale_height_function) / scale_height
result, = plot.plot(x, y, linewidth = linewidth, c = "b", zorder = 99)
result2, = plot.plot(x, y2, linewidth = linewidth - 1, c = "r", zorder = 90)
if args.zero:
density_zero = fromfile("gasdens0.dat").reshape(num_rad, num_theta)
averagedDensity_zero = np.average(density_zero, axis = 1)
normalized_density_zero = averagedDensity_zero / surface_density_zero
x = rad
y_zero = normalized_density_zero
result = plot.plot(x, y_zero, linewidth = linewidth, zorder = 0)
if args.compare is not None:
directory = args.compare
density_compare = (fromfile("%s/gasdens%d.dat" % (directory, frame)).reshape(num_rad, num_theta))
averagedDensity_compare = np.average(density_compare, axis = 1)
normalized_density_compare = averagedDensity_compare / surface_density_zero
### Plot ###
x = rad
y_compare = normalized_density_compare
result = plot.plot(x, y_compare, linewidth = linewidth, alpha = 0.6, zorder = 99, label = "compare")
plot.legend()
if args.derivative:
twin = ax.twinx()
### Plot ###
dr = rad[1] - rad[0]
normalized_density_derivative = np.diff(normalized_density) / dr
x2 = rad[1:]
y2 = normalized_density_derivative
result = twin.plot(x2, y2, c = "purple", linewidth = linewidth, alpha = 0.6, zorder = 99, label = "derivative")
plot.legend()
twin.set_ylim(-10, 10)
# Axes
if args.max_y is None:
max_y = 1.1 * max(y)
else:
max_y = args.max_y
ax.set_xlim(x[0], x[-1])
ax.set_ylim(0, max_y)
# Annotate Axes
orbit = (dt / (2 * np.pi)) * frame
if orbit >= taper_time:
current_mass = planet_mass
else:
current_mass = np.power(np.sin((np.pi / 2) * (1.0 * orbit / taper_time)), 2) * planet_mass
#current_mass += accreted_mass[frame]
#title = readTitle()
unit = "r_\mathrm{p}"
ax.set_xlabel(r"Radius [$%s$]" % unit, fontsize = fontsize)
ax.set_ylabel(r"Dust Scale Height $H_d$ $/$ $h$", fontsize = fontsize)
#if title is None:
# plot.title("Dust Density Map\n(t = %.1f)" % (orbit), fontsize = fontsize + 1)
#else:
# plot.title("Dust Density Map\n%s\n(t = %.1f)" % (title, orbit), fontsize = fontsize + 1)
x_range = x[-1] - x[0]; x_mid = x[0] + x_range / 2.0
y_text = 1.14
alpha_coefficent = "3"
if scale_height == 0.08:
alpha_coefficent = "1.5"
elif scale_height == 0.04:
alpha_coefficent = "6"
#title1 = r"$T_\mathrm{growth} = %d$ $\mathrm{orbits}$" % (taper_time)
#title1 = r"$\Sigma_0 = %.3e$ $M_c = %.2f\ M_J$ $A = %.2f$" % (surface_density_zero, planet_mass, accretion)
title1 = r"$h/r = %.2f$ $\alpha \approx %s \times 10^{%d}$ $A = %.2f$" % (scale_height, alpha_coefficent, int(np.log(viscosity) / np.log(10)) + 2, accretion)
title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{Jup}$]" % (orbit, current_mass)
plot.title("%s" % (title2), y = 1.015, fontsize = fontsize + 1)
ax.text(x_mid, y_text * plot.ylim()[-1], title1, horizontalalignment = 'center', bbox = dict(facecolor = 'none', edgecolor = 'black', linewidth = 1.5, pad = 7.0), fontsize = fontsize + 2)
# Text
text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{Jup}$" % (int(planet_mass))
text_visc = r"$\alpha_\mathrm{disk} = 3 \times 10^{%d}$" % (int(np.log(viscosity) / np.log(10)) + 2)
#plot.text(-0.9 * box_size, 2, text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'left', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(0.9 * box_size, 2, text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'right', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(-0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'right')
#plot.text(0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'left')
if args.maximum_condition:
bump, _ = az.get_radial_peak(normalized_density, fargo_par, end = 1.6)
plot.plot([bump, bump], [0, max_y], c = "b", linewidth = linewidth - 2, alpha = alpha, linestyle = "--", zorder = 20)
twin = ax.twinx()
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_rad, num_theta)) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_rad, num_theta)) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad, vtheta, rad, theta, rossby = rossby, residual = residual)
averaged_vorticity = np.average(vorticity, axis = 1)
#averaged_density = np.average(normalized_density, axis = 1) # normalized_density
maximum_condition = (normalized_density[1:] / averaged_vorticity) * (np.power(scale_height, 2) / np.power(rad[1:], 1))
x2 = rad[1:]
y2 = maximum_condition
result2, = twin.plot(x2, y2, c = 'darkviolet', linewidth = linewidth, zorder = 99)
bump, _ = az.get_radial_peak(maximum_condition, fargo_par, end = 1.6)
plot.plot([bump, bump], y2_range, c = "darkviolet", linewidth = linewidth - 2, alpha = alpha, linestyle = "--", zorder = 20)
# Axes
twin.set_ylim(y2_range[0], y2_range[1])
twin.set_yticks(np.arange(y2_range[0], y2_range[1] + 1e-9, 0.005))
twin.set_ylabel(r"$\Sigma$ $/$ ($\nabla \times v$)$_\mathrm{z}$", fontsize = fontsize, rotation = 270, labelpad = 25)
tkw = dict(size=4, width=1.5)
ax.tick_params(axis = 'y', colors = result.get_color(), **tkw)
twin.tick_params(axis = 'y', colors = result2.get_color(), **tkw)
# Save, Show, and Close
if version is None:
save_fn = "%s/dustScaleHeight_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_dustScaleHeight_%04d.png" % (save_directory, version, frame)
plot.savefig(save_fn, bbox_inches = 'tight', dpi = dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def get_rossby_criteria(args_here):
# Unwrap Args
i, frame, directory = args_here
# Data
normalized_density = (fromfile(
"../%s/gasdens%d.dat" %
(directory, frame)).reshape(num_rad, num_theta)) / surface_density_zero
vrad = (fromfile("../%s/gasvy%d.dat" % (directory, frame)).reshape(
num_rad, num_theta)) # add a read_vrad to util.py!
vtheta = (fromfile("../%s/gasvx%d.dat" % (directory, frame)).reshape(
num_rad, num_theta)) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=rossby,
residual=residual)
averaged_vorticity = np.average(vorticity, axis=1)
averaged_density = np.average(normalized_density, axis=1)
maximum_condition = (averaged_density[1:] / averaged_vorticity) * (
np.power(scale_height, 2) / np.power(rad[1:], 1))
dr = rad[1] - rad[0]
diff_maximum_condition = np.diff(maximum_condition) / dr
# Diagnostics
peak_rad, peak_density = az.get_radial_peak(averaged_density, fargo_par)
peak_rad_i = np.searchsorted(rad, peak_rad)
inner_limit_i = np.searchsorted(
rad, 1.1) # Make inner limit a variable in the future
outer_limit_i = np.searchsorted(
rad, 2.0) # Make outer limit a variable in the future
inner_max_diff_i = np.argmax(
diff_maximum_condition[inner_limit_i:peak_rad_i])
outer_max_diff_i = np.argmin(
diff_maximum_condition[peak_rad_i:outer_limit_i])
inner_max_diff_i += inner_limit_i # put the "inner disk" back
outer_max_diff_i += peak_rad_i
# Alternate: For inner rossby rad, use minimum in vorticity profile
inner_rossby_rad, _ = az.get_radial_peak(-1.0 * averaged_vorticity,
fargo_par)
#inner_rossby_rad = rad[inner_max_diff_i]
outer_rossby_rad = rad[outer_max_diff_i]
difference = outer_rossby_rad - inner_rossby_rad
inner_rossby_value = diff_maximum_condition[inner_max_diff_i]
outer_rossby_value = diff_maximum_condition[
outer_max_diff_i] * -1.0 # absolute value
# Store Data
inner_rossby_rad_over_time[i] = inner_rossby_rad
peak_rad_over_time[i] = peak_rad
outer_rossby_rad_over_time[i] = outer_rossby_rad
rossby_rad_difference_over_time[i] = outer_rossby_rad - inner_rossby_rad
inner_peak_difference_over_time[i] = peak_rad - inner_rossby_rad
outer_peak_difference_over_time[i] = outer_rossby_rad - peak_rad
inner_rossby_value_over_time[i] = inner_rossby_value
outer_rossby_value_over_time[i] = outer_rossby_value
print i, frame, "Rad: ", inner_rossby_rad_over_time[i], peak_rad_over_time[
i], outer_rossby_rad_over_time[i]
print i, frame, "Diff:", rossby_rad_difference_over_time[
i], inner_peak_difference_over_time[
i], outer_peak_difference_over_time[i]
print i, frame, "Val: ", inner_rossby_value_over_time[
i], outer_rossby_value_over_time[i]
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
density = fromfile("gasdens%d.dat" % frame).reshape(num_rad, num_theta)
averagedDensity = np.average(density, axis=1)
radial_velocity = fromfile("gasvy%d.dat" % frame).reshape(
num_rad, num_theta)
azimuthal_velocity = fromfile("gasvx%d.dat" % frame).reshape(
num_rad, num_theta)
keplerian_velocity = rad * (np.power(
rad, -1.5) - 1) # in rotating frame, v_k = r * (r^-1.5 - r_p^-1.5)
sub_keplerian_velocity = keplerian_velocity - 0.5 * np.power(
scale_height, 2)
#azimuthal_velocity -= sub_keplerian_velocity[:, None]
radial_velocity -= np.average(radial_velocity, axis=1)[:, None]
azimuthal_velocity -= np.average(azimuthal_velocity, axis=1)[:, None]
sound_speed = scale_height * np.power(rad, -1.5)
stress = np.multiply(radial_velocity, azimuthal_velocity)
averagedStress = np.abs(
np.average(stress, axis=1) / np.power(sound_speed, 2))
### Plot ###
x = rad
y = averagedStress
result = plot.plot(x, y, linewidth=linewidth, zorder=99)
radial_peak_a, _ = az.get_radial_peak(averagedDensity, fargo_par, end=2.0)
plot.plot([radial_peak_a, radial_peak_a], [10**(-10), 10**(1)], c='k')
if args.zero:
density_zero = fromfile("gasdens0.dat").reshape(num_rad, num_theta)
averagedDensity_zero = np.average(density_zero, axis=1)
normalized_density_zero = averagedDensity_zero / surface_density_zero
x = rad
y_zero = normalized_density_zero
result = plot.plot(x, y_zero, linewidth=linewidth, zorder=0)
if args.compare is not None:
directory = args.compare
density_compare = (fromfile("%s/gasdens%d.dat" %
(directory, frame)).reshape(
num_rad, num_theta))
averagedDensity_compare = np.average(density_compare, axis=1)
normalized_density_compare = averagedDensity_compare / surface_density_zero
### Plot ###
x = rad
y_compare = normalized_density_compare
result = plot.plot(x,
y_compare,
linewidth=linewidth,
alpha=0.6,
zorder=99,
label="compare")
plot.legend()
# Axes
if args.max_y is None:
x_min_i = np.searchsorted(x, x_min)
x_max_i = np.searchsorted(x, x_max)
max_y = 1.1 * max(y[x_min_i:x_max_i])
else:
max_y = args.max_y
plot.xlim(x_min, x_max)
plot.ylim(10**(-5), 3 * 10**(-1))
plot.yscale('log')
# Annotate Axes
orbit = (dt / (2 * np.pi)) * frame
if orbit >= taper_time:
current_mass = planet_mass
else:
current_mass = np.power(
np.sin((np.pi / 2) * (1.0 * orbit / taper_time)), 2) * planet_mass
current_mass += accreted_mass[frame]
#title = readTitle()
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
plot.ylabel(r"$<\Delta v_r \Delta v_{\phi}> / c_s^2$", fontsize=fontsize)
#if title is None:
# plot.title("Dust Density Map\n(t = %.1f)" % (orbit), fontsize = fontsize + 1)
#else:
# plot.title("Dust Density Map\n%s\n(t = %.1f)" % (title, orbit), fontsize = fontsize + 1)
x_range = x_max - x_min
x_mid = x_min + x_range / 2.0
y_text = 1.14
#title1 = r"$T_\mathrm{growth} = %d$ $\mathrm{orbits}$" % (taper_time)
title1 = r"$\Sigma_0 = %.3e$ $M_c = %.2f\ M_J$ $A = %.2f$" % (
surface_density_zero, planet_mass, accretion)
title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{Jup}$]" % (
orbit, current_mass)
plot.title("%s" % (title2), y=1.015, fontsize=fontsize + 1)
#plot.text(x_mid, y_text * plot.ylim()[-1], title1, horizontalalignment = 'center', bbox = dict(facecolor = 'none', edgecolor = 'black', linewidth = 1.5, pad = 7.0), fontsize = fontsize + 2)
# Text
text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{Jup}$" % (int(planet_mass))
text_visc = r"$\alpha_\mathrm{disk} = 3 \times 10^{%d}$" % (
int(np.log(viscosity) / np.log(10)) + 2)
#plot.text(-0.9 * box_size, 2, text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'left', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(0.9 * box_size, 2, text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'right', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(-0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'right')
#plot.text(0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'left')
# Save, Show, and Close
if version is None:
save_fn = "%s/averagedStress_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_averagedStress_%04d.png" % (save_directory,
version, frame)
plot.savefig(save_fn, bbox_inches='tight', dpi=dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
density = fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta) / surface_density_zero
radial_velocity = fromfile("gasvy%d.dat" % frame).reshape(
num_rad, num_theta)
azimuthal_velocity = fromfile("gasvx%d.dat" % frame).reshape(
num_rad, num_theta)
shifted_density = np.roll(density, 1, axis=-1)
diff_density = density - shifted_density
keplerian_velocity = rad * (np.power(
rad, -1.5) - 1) # in rotating frame, v_k = r * (r^-1.5 - r_p^-1.5)
azimuthal_velocity -= keplerian_velocity[:, None]
# Extract Action
wave_locations = np.argmax(diff_density, axis=-1)
shift = np.searchsorted(theta, np.pi) - wave_locations
print_a = np.searchsorted(rad, 1.1)
print_b = np.searchsorted(rad, 1.4)
print(theta[wave_locations[print_a:print_b]] * (180.0 / np.pi))
print(theta[shift[print_a:print_b]] * (180.0 / np.pi))
left = np.searchsorted(theta, 177 * (np.pi / 180.0))
right = np.searchsorted(theta, 183 * (np.pi / 180.0))
centered_density = np.roll(density, shift, axis=-1)[:, left:right]
centered_radial_velocity = np.roll(radial_velocity, shift,
axis=-1)[:, left:right]
centered_azimuthal_velocity = np.roll(azimuthal_velocity, shift,
axis=-1)[:, left:right]
residual_density = centered_density - np.min(centered_density)
dr = rad[1] - rad[0]
dtheta = theta[1] - theta[0]
grid_size = rad * dr * dtheta
wave_action = np.sum(residual_density * centered_radial_velocity *
centered_azimuthal_velocity * rad[:, None] *
rad[:, None] * grid_size[:, None],
axis=-1)
### Plot ###
x = rad
y = wave_action
result = plot.plot(x, y, linewidth=linewidth, zorder=99)
result2 = plot.plot(x, -y, linewidth=linewidth, zorder=99)
# Axes
if args.max_y is None:
x_min_i = np.searchsorted(x, x_min)
x_max_i = np.searchsorted(x, x_max)
max_y1 = 1.1 * max(y[x_min_i:x_max_i])
max_y2 = 1.1 * max(-y[x_min_i:x_max_i])
max_y = np.max([max_y1, max_y2])
else:
max_y = args.max_y
plot.xlim(x_min, x_max)
plot.ylim(0, max_y)
# Reference
x_vortex, _ = az.get_radial_peak(np.average(density, axis=1),
fargo_par,
end=2.0)
plot.plot([x_vortex, x_vortex], [0, max_y], c="k", linewidth=1)
# Annotate Axes
orbit = (dt / (2 * np.pi)) * frame
if orbit >= taper_time:
current_mass = planet_mass
else:
current_mass = np.power(
np.sin((np.pi / 2) * (1.0 * orbit / taper_time)), 2) * planet_mass
current_mass += accreted_mass[frame]
#title = readTitle()
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
plot.ylabel(r"Wave Action", fontsize=fontsize)
#if title is None:
# plot.title("Dust Density Map\n(t = %.1f)" % (orbit), fontsize = fontsize + 1)
#else:
# plot.title("Dust Density Map\n%s\n(t = %.1f)" % (title, orbit), fontsize = fontsize + 1)
x_range = x_max - x_min
x_mid = x_min + x_range / 2.0
y_text = 1.14
#title1 = r"$T_\mathrm{growth} = %d$ $\mathrm{orbits}$" % (taper_time)
alpha_coefficent = "3"
if scale_height == 0.08:
alpha_coefficent = "1.5"
elif scale_height == 0.04:
alpha_coefficent = "6"
title1 = r"$h = %.2f$ $\alpha \approx %s \times 10^{%d}$ $A = %.2f$" % (
scale_height, alpha_coefficent,
int(np.log(viscosity) / np.log(10)) + 2, accretion)
#title1 = r"$\Sigma_0 = %.3e$ $M_c = %.2f\ M_J$ $A = %.2f$" % (surface_density_zero, planet_mass, accretion)
title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{Jup}$]" % (
orbit, current_mass)
plot.title("%s" % (title2), y=1.015, fontsize=fontsize + 1)
plot.text(x_mid,
y_text * plot.ylim()[-1],
title1,
horizontalalignment='center',
bbox=dict(facecolor='none',
edgecolor='black',
linewidth=1.5,
pad=7.0),
fontsize=fontsize + 2)
# Text
text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{Jup}$" % (int(planet_mass))
text_visc = r"$\alpha_\mathrm{disk} = 3 \times 10^{%d}$" % (
int(np.log(viscosity) / np.log(10)) + 2)
#plot.text(-0.9 * box_size, 2, text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'left', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(0.9 * box_size, 2, text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'right', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(-0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'right')
#plot.text(0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'left')
# Save, Show, and Close
if version is None:
save_fn = "%s/waveAction_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_waveAction_%04d.png" % (save_directory, version,
frame)
plot.savefig(save_fn, bbox_inches='tight', dpi=dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def make_plot(frame_range, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 5), dpi=dpi)
ax = fig.add_subplot(111)
# Data
for i, frame in enumerate(frame_range):
normalized_density = (fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta)) / surface_density_zero
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=rossby,
residual=residual)
averaged_vorticity = np.average(vorticity, axis=1)
averaged_density = np.average(normalized_density, axis=1)
maximum_condition = (averaged_density[1:] / averaged_vorticity) * (
np.power(scale_height, 2) / np.power(rad[1:], 1))
### Plot ###
x = rad[1:]
y = maximum_condition # Highlight middle two!
result = plot.plot(x,
y,
c=colors[i % len(colors)],
linewidth=linewidth + np.ceil(i / 10.0),
linestyle=linestyles[i % 2],
zorder=99 - abs(1.5 - i),
label=r"$t$ $=$ $%d$ $T_\mathrm{p}$" % frame)
# Reference line for pressure bump
if scale_height == 0.08:
bump, _ = az.get_radial_peak(averaged_density, fargo_par, end=3.0)
else:
bump, _ = az.get_radial_peak(averaged_density, fargo_par, end=1.6)
plot.plot([bump, bump],
y_range,
c=colors[i % len(colors)],
linewidth=linewidth,
linestyle="--",
zorder=20)
legend = plot.legend(loc="upper right",
fontsize=fontsize - 4,
framealpha=1.0,
fancybox=False)
legend.set_zorder(150)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(y_range[0], y_range[1])
plot.yticks(np.arange(y_range[0], y_range[1] + 1e-9, 0.005))
#plot.ylim(10**(-3), 3.0)
#plot.yscale("log")
# Annotate Axes
orbit = (dt / (2 * np.pi)) * frame
if orbit >= taper_time:
current_mass = planet_mass
else:
current_mass = np.power(
np.sin((np.pi / 2) * (1.0 * orbit / taper_time)), 2) * planet_mass
current_mass += accreted_mass[frame]
#title = readTitle()
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
plot.ylabel(
r"$L_\mathrm{iso}$ $\equiv$ $c_s^2$ $\Sigma$ $/$ ($\nabla \times v$)$_\mathrm{z}$",
fontsize=fontsize)
#if title is None:
# plot.title("Dust Density Map\n(t = %.1f)" % (orbit), fontsize = fontsize + 1)
#else:
# plot.title("Dust Density Map\n%s\n(t = %.1f)" % (title, orbit), fontsize = fontsize + 1)
x_range = x_max - x_min
x_mid = x_min + x_range / 2.0
y_text = 1.14
alpha_coefficent = "3"
if scale_height == 0.08:
alpha_coefficent = "1.5"
elif scale_height == 0.04:
alpha_coefficent = "6"
#title1 = r"$T_\mathrm{growth} = %d$ $\mathrm{orbits}$" % (taper_time)
#title1 = r"$h = %.2f$ $\alpha \approx %s \times 10^{%d}$ $A = %.2f$" % (scale_height, alpha_coefficent, int(np.log(viscosity) / np.log(10)) + 2, accretion)
#title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{Jup}$]" % (orbit, current_mass)
title1 = title = r"$h = %.2f$ $\Sigma_0 = %.3e$ (2-D)" % (
scale_height, surface_density_zero)
plot.title("%s" % (title1), y=1.015, fontsize=fontsize + 1)
#plot.text(x_mid, y_text * plot.ylim()[-1], title1, horizontalalignment = 'center', bbox = dict(facecolor = 'none', edgecolor = 'black', linewidth = 1.5, pad = 7.0), fontsize = fontsize + 2)
# Text
text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{Jup}$" % (int(planet_mass))
text_visc = r"$\alpha_\mathrm{disk} = 3 \times 10^{%d}$" % (
int(np.log(viscosity) / np.log(10)) + 2)
#plot.text(-0.9 * box_size, 2, text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'left', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(0.9 * box_size, 2, text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'right', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(-0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'right')
#plot.text(0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'left')
if args.start is not None:
text_start = r"$t_\mathrm{start}$ $=$ $%d$ $T_\mathrm{p}$" % args.start
plot.text(0.55,
0.0025,
text_start,
fontsize=fontsize - 4,
color='black',
horizontalalignment='left')
if args.end is not None:
text_end = r"$t_\mathrm{end}$ $=$ $%d$ $T_\mathrm{p}$" % args.end
plot.text(0.55,
0.0015,
text_end,
fontsize=fontsize - 4,
color='black',
horizontalalignment='left')
# Save, Show, and Close
directory_name = os.getcwd().split("/")[-1].split("-")[0]
frame_string = ""
for frame in frame_range:
frame_string += ("%04d-" % frame)
frame_string = frame_string[:-1] # get rid of trailing '-'
if version is None:
save_fn = "%s/maximumCondition_%s_%s.png" % (
save_directory, directory_name, frame_string)
else:
save_fn = "%s/v%04d_maximumCondition_%s_%s.png" % (
save_directory, version, directory_name, frame_string)
plot.savefig(save_fn, bbox_inches='tight', dpi=dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def get_extents(args_here):
# Unwrap Args
i, frame = args_here
if frame in problem_frames:
frame += 3 # switch to an adjacent frame
# Get Data
density = fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta) / surface_density_zero
avg_density = np.average(density, axis=1)
peak_rad, peak_density = az.get_radial_peak(avg_density, fargo_par)
normal = True
if frame > check_rossby:
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=True,
residual=True)
# Find minimum
if accretion > 0.015:
start_rad = min([peak_rad - 0.05, 1.5])
start_rad_i = np.searchsorted(rad, start_rad) # Is this necessary?
end_rad_i = np.searchsorted(rad, 2.5)
else:
start_rad_i = np.searchsorted(rad, 1.0) # Is this necessary?
end_rad_i = np.searchsorted(rad, 1.8)
zoom_vorticity = vorticity[start_rad_i:end_rad_i]
min_rossby_number = np.percentile(zoom_vorticity, 0.25)
if min_rossby_number < -0.15:
normal = False # Compressible regime from Surville+ 15
if normal:
azimuthal_extent = az.get_extent(
density, fargo_par, threshold=args.threshold
) # Use 0.9 for h = 0.08 (Add as a parameter)
radial_extent, radial_peak = az.get_radial_extent(
density, fargo_par, threshold=args.threshold)
radial_peak_a, _ = az.get_radial_peak(avg_density, fargo_par)
azimuthal_extent_over_time[i] = azimuthal_extent * (180.0 / np.pi)
radial_extent_over_time[i] = radial_extent / scale_height
radial_peak_over_time[i] = radial_peak_a # radial_peak
#radial_peak_over_time_a[i] = radial_peak_a
else:
# Shift everything
density, vorticity, shift_c = shift_density(density,
vorticity,
fargo_par,
reference_density=density)
# Locate minimum
if accretion > 0.015:
start_rad = min([peak_rad - 0.05, 1.5])
start_rad_i = np.searchsorted(rad, start_rad) # Is this necessary?
end_rad_i = np.searchsorted(rad, 2.5)
else:
start_rad_i = np.searchsorted(rad, 1.0) # Is this necessary?
end_rad_i = np.searchsorted(rad, 1.8)
zoom_vorticity = vorticity[start_rad_i:end_rad_i]
min_rossby_number = np.percentile(zoom_vorticity, 0.25)
abs_zoom_vorticity = np.abs(zoom_vorticity - min_rossby_number)
minimum_location = np.argmin(abs_zoom_vorticity)
rad_min_i, theta_min_i = np.unravel_index(minimum_location,
np.shape(zoom_vorticity))
# Locate radial and azimuthal center
left_side = zoom_vorticity[rad_min_i, :theta_min_i]
right_side = zoom_vorticity[rad_min_i, theta_min_i:]
front_side = zoom_vorticity[:rad_min_i, theta_min_i]
back_side = zoom_vorticity[rad_min_i:, theta_min_i]
if frame < extreme_cutoff:
cutoff = -0.04
else:
cutoff = -0.12 # Extreme! (neglects "vortex" that develops around the minimum)
left_i = theta_min_i - az.my_searchsorted(
left_side[::-1], cutoff) # at location of minimum
right_i = theta_min_i + az.my_searchsorted(right_side, cutoff)
front_i = rad_min_i - az.my_searchsorted(front_side[::-1], cutoff)
back_i = rad_min_i + az.my_searchsorted(back_side, cutoff)
radial_center_i = start_rad_i + int((front_i + back_i) / 2.0)
azimuthal_center_i = int((left_i + right_i) / 2.0)
radial_center = (rad[start_rad_i + front_i] +
rad[start_rad_i + back_i]) / 2.0
azimuthal_center = (
(theta[left_i] + theta[right_i]) / 2.0) * (180.0 / np.pi)
print i, frame, rad[start_rad_i + rad_min_i], theta[theta_min_i] * (
180.0 / np.pi), "Minimum Rossby Number"
print i, frame, rad[start_rad_i + front_i], radial_center, rad[
start_rad_i + back_i], "Radial: Left, Center, Right"
print i, frame, theta[left_i] * (
180.0 / np.pi), azimuthal_center, theta[right_i] * (
180.0 / np.pi), "Azimuthal: Left, Center, Right"
# Measure radial and azimuthal extents
left_side = vorticity[radial_center_i, :azimuthal_center_i]
right_side = vorticity[radial_center_i, azimuthal_center_i:]
front_side = vorticity[:radial_center_i, azimuthal_center_i]
back_side = vorticity[radial_center_i:, azimuthal_center_i]
left_i = azimuthal_center_i - az.my_searchsorted(
left_side[::-1], cutoff) # relative to center
right_i = azimuthal_center_i + az.my_searchsorted(right_side, cutoff)
front_i = radial_center_i - az.my_searchsorted(front_side[::-1],
cutoff)
back_i = radial_center_i + az.my_searchsorted(back_side, cutoff)
radial_peak_over_time[i] = radial_center
radial_extent_over_time[i] = (rad[back_i] -
rad[front_i]) / scale_height
azimuthal_extent_over_time[i] = theta[right_i - left_i] * (180.0 /
np.pi)
print i, frame, rad[front_i], radial_center, rad[
back_i], "Final Radial: Left, Center, Right"
print i, frame, theta[left_i] * (
180.0 / np.pi), azimuthal_center, theta[right_i] * (
180.0 / np.pi), "Final Azimuthal: Left, Center, Right"
#contrasts_over_time[i] = az.get_contrast(density, fargo_par)
print i, frame, azimuthal_extent_over_time[i], radial_extent_over_time[
i], radial_peak_over_time[i]
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
host = fig.add_subplot(111)
twin = host.twinx()
# Data
normalized_density = (fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta)) / surface_density_zero
vrad = (fromfile("gasvy%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvx%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vorticity = utilVorticity.velocity_curl(vrad,
vtheta,
rad,
theta,
rossby=rossby,
residual=residual)
averaged_vorticity = np.average(vorticity, axis=1)
averaged_density = np.average(normalized_density, axis=1)
maximum_condition = (averaged_density[1:] / averaged_vorticity) * (
np.power(scale_height, 2) / np.power(rad[1:], 1))
dr = rad[1] - rad[0]
diff_maximum_condition = np.diff(maximum_condition) / dr
# Diagnostics
peak_rad, peak_density = az.get_radial_peak(averaged_density, fargo_par)
peak_rad_i = np.searchsorted(rad, peak_rad)
inner_limit_i = np.searchsorted(
rad, 1.1) # Make inner limit a variable in the future
outer_limit_i = np.searchsorted(
rad, 2.0) # Make outer limit a variable in the future
inner_max_diff_i = np.argmax(
diff_maximum_condition[inner_limit_i:peak_rad_i])
outer_max_diff_i = np.argmin(
diff_maximum_condition[peak_rad_i:outer_limit_i])
inner_max_diff_i += inner_limit_i # put the "inner disk" back
outer_max_diff_i += peak_rad_i
inner_rossby_rad = rad[inner_max_diff_i]
outer_rossby_rad = rad[outer_max_diff_i]
difference = outer_rossby_rad - inner_rossby_rad
inner_rossby_value = diff_maximum_condition[inner_max_diff_i]
outer_rossby_value = diff_maximum_condition[
outer_max_diff_i] * -1.0 # absolute value
### Plot ###
x = rad[1:]
y = maximum_condition
result, = host.plot(x,
y,
c='b',
linewidth=linewidth + 1,
zorder=99,
label="Condition")
x2 = x[:-1]
y2 = diff_maximum_condition
result2, = twin.plot(x2,
y2,
c='purple',
linewidth=linewidth,
zorder=99,
label="Derivative")
# Reference
y_min = y_range[0]
y_max = y_range[-1]
host.plot([inner_rossby_rad, inner_rossby_rad],
[y_min, y_min + 0.7 * (y_max - y_min)],
c='k',
linewidth=1,
zorder=201)
host.plot([peak_rad, peak_rad], [y_min, y_min + 0.8 * (y_max - y_min)],
c='k',
linewidth=1,
zorder=201)
host.plot([outer_rossby_rad, outer_rossby_rad],
[y_min, y_min + 0.7 * (y_max - y_min)],
c='k',
linewidth=1,
zorder=201)
twin.plot([x_min, x_max], [0, 0], c='k', linewidth=1, zorder=1)
if args.zero:
density_zero = fromfile("gasdens0.dat").reshape(num_rad, num_theta)
averagedDensity_zero = np.average(density_zero, axis=1)
normalized_density_zero = averagedDensity_zero / surface_density_zero
x = rad
y_zero = normalized_density_zero
result = plot.plot(x, y_zero, linewidth=linewidth, zorder=0)
if args.compare is not None:
directory = args.compare
density_compare = (fromfile("%s/gasdens%d.dat" %
(directory, frame)).reshape(
num_rad, num_theta))
averagedDensity_compare = np.average(density_compare, axis=1)
normalized_density_compare = averagedDensity_compare / surface_density_zero
### Plot ###
x = rad
y_compare = normalized_density_compare
result = plot.plot(x,
y_compare,
linewidth=linewidth,
alpha=0.6,
zorder=99,
label="compare")
plot.legend(loc="upper left")
# Axes
host.set_xlim(x_min, x_max)
host.set_ylim(y_range[0], y_range[1])
twin.set_ylim(y2_range[0], y2_range[1])
tkw = dict(size=4, width=1.5)
host.tick_params(axis='y', colors=result.get_color(), **tkw)
twin.tick_params(axis='y', colors=result2.get_color(), **tkw)
# Annotate Axes
orbit = (dt / (2 * np.pi)) * frame
if orbit >= taper_time:
current_mass = planet_mass
else:
current_mass = np.power(
np.sin((np.pi / 2) * (1.0 * orbit / taper_time)), 2) * planet_mass
current_mass += accreted_mass[frame]
#title = readTitle()
unit = "r_\mathrm{p}"
host.set_xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
host.set_ylabel(r"$c_s^2$ $\Sigma$ $/$ ($\nabla \times v$)$_\mathrm{z}$",
fontsize=fontsize)
#if title is None:
# plot.title("Dust Density Map\n(t = %.1f)" % (orbit), fontsize = fontsize + 1)
#else:
# plot.title("Dust Density Map\n%s\n(t = %.1f)" % (title, orbit), fontsize = fontsize + 1)
x_range = x_max - x_min
x_mid = x_min + x_range / 2.0
y_text = 1.14
alpha_coefficent = "3"
if scale_height == 0.08:
alpha_coefficent = "1.5"
elif scale_height == 0.04:
alpha_coefficent = "6"
#title1 = r"$T_\mathrm{growth} = %d$ $\mathrm{orbits}$" % (taper_time)
#title1 = r"$\Sigma_0 = %.3e$ $M_c = %.2f\ M_J$ $A = %.2f$" % (surface_density_zero, planet_mass, accretion)
title1 = r"$h = %.2f$ $\alpha \approx %s \times 10^{%d}$ $A = %.2f$" % (
scale_height, alpha_coefficent,
int(np.log(viscosity) / np.log(10)) + 2, accretion)
title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{Jup}$]" % (
orbit, current_mass)
plot.title("%s" % (title2), y=1.015, fontsize=fontsize + 1)
host.text(x_mid,
y_text * y_range[-1],
title1,
horizontalalignment='center',
bbox=dict(facecolor='none',
edgecolor='black',
linewidth=1.5,
pad=7.0),
fontsize=fontsize + 2)
# Text
x_text = x_min + 0.75 * (x_max - x_min)
y_text = 0.95 * y_range[-1]
linebreak = 0.04 * y_range[-1]
host.text(x_text,
y_text - 0.0 * linebreak,
r"$r_1 = %.2f$ ($%.3f$)" %
(inner_rossby_rad, inner_rossby_value),
color='black')
host.text(x_text,
y_text - 1.0 * linebreak,
r"$r_2 = %.2f$ ($%.3f$)" %
(outer_rossby_rad, outer_rossby_value),
color='black')
host.text(x_text,
y_text - 2.0 * linebreak,
r"$\Delta r = %.2f$" % difference,
color='black')
#text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{Jup}$" % (int(planet_mass))
#text_visc = r"$\alpha_\mathrm{disk} = 3 \times 10^{%d}$" % (int(np.log(viscosity) / np.log(10)) + 2)
#plot.text(-0.9 * box_size, 2, text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'left', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(0.9 * box_size, 2, text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'right', bbox=dict(facecolor = 'white', edgecolor = 'black', pad = 10.0))
#plot.text(-0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_mass, fontsize = fontsize, color = 'black', horizontalalignment = 'right')
#plot.text(0.84 * x_range / 2.0 + x_mid, y_text * plot.ylim()[-1], text_visc, fontsize = fontsize, color = 'black', horizontalalignment = 'left')
# Save, Show, and Close
if version is None:
save_fn = "%s/maximumCondition_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_maximumCondition_%04d.png" % (save_directory,
version, frame)
plot.savefig(save_fn, bbox_inches='tight', dpi=dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)