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)
averagedDensity = np.average(density, axis=1)
normalized_density = averagedDensity / 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)
# Get Minima
min_density = find_rossby_density(normalized_density, averaged_vorticity)
# Print Update
print "%d: %.3f, %.3f" % (frame, min_density, 1.0 / min_density)
# Store Data
gap_depth_over_time[i] = 1.0 / min_density
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 polish(density,
frame,
shift_i,
size,
cavity_cutoff=0.92,
scale_density=1,
scale_sizes=1):
""" Step 1: get rid of inner cavity, scale dust densities to different grain size, and only keep dust with negative vorticity """
# Cavity
if cavity_cutoff is not None:
cavity_cutoff_i = np.searchsorted(rad, cavity_cutoff)
density[:cavity_cutoff_i] = 0.0
outer_cutoff = 2.75
outer_cutoff_i = np.searchsorted(rad, outer_cutoff)
density[outer_cutoff_i:] = 0.0
# Scale
density *= scale_density
size *= scale_sizes
if negative_vorticity_only > 0:
tmp_density = density[1:, 1:]
# Get rid of dust where there is positive vorticity
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)
# Remember to shift the vorticity!
vorticity = np.roll(vorticity, shift_i, axis=1)
tmp_density[vorticity > 0] = 0.0
density[1:, 1:] = tmp_density
# Get rid of dust where density is below a threshold
gas_density = fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta) / surface_density_zero
gas_density = np.roll(gas_density, shift_i, axis=1)
threshold = negative_vorticity_only
density[gas_density < threshold] = 0.0
return density, size
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
if mpi:
density = Fields("./", 'gas', frame).get_field("dens").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)
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, :, :]
dz = z_angles[1] - z_angles[0]
surface_density = np.sum(density[:, :, :], axis=0) * dz
normalized_midplane_density = midplane_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
normalized_density = surface_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
vorticity = utilVorticity.velocity_curl(midplane_vrad,
midplane_vtheta,
rad,
theta,
rossby=rossby,
residual=residual)
averaged_vorticity = np.average(vorticity, axis=1)
delta_midplane_vtheta = midplane_vtheta - np.average(midplane_vtheta,
axis=1)
delta_midplane_velocity = midplane_vrad * delta_midplane_vtheta
scale_height_function = scale_height * np.power(rad, 1.0 + flaring_index)
omega_function = np.power(rad, -1.5)
sound_speed = scale_height_function * omega_function
alpha = midplane_vrad * delta_midplane_vtheta / np.power(sound_speed, 2.0)
average_alpha = np.average(alpha, axis=1)
### Plot ###
x = rad
y = average_alpha
result, = plot.plot(x,
y,
linewidth=linewidth,
c="b",
label="min",
zorder=90)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(10**(-8), 3 * 10**(-1))
plot.yscale('log')
#plot.yticks(np.arange(y_range[0], y_range[1] + 1e-9, 0.005))
# 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"$<\Delta v_r \Delta v_{\phi}> / c_s^2$", 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
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()[0], 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/averagedReynoldsStress_%04d.png" % (save_directory,
frame)
else:
save_fn = "%s/v%04d_averagedReynoldsStress_%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 add_to_plot(frame, fig, ax, frame_i):
# Declare Subplot
#ax = plot.subplot(1, num_frames, frame_i, sharex = prev_ax, sharey = prev_ax, aspect = "equal")
# Taper
if frame_i == 1:
taper_time = 10
else:
taper_time = 750
# Change directories
cwd = os.getcwd()
os.chdir(directories[frame_i - 1])
# Data
vrad = (fromfile("gasvrad%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvtheta%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)
# Shift
density = (fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta)) / surface_density_zero
dust_density = (fromfile("gasddens%d.dat" % frame).reshape(
num_rad, num_theta))
if center:
if taper_time < 10.1:
shift_c = az.get_azimuthal_peak(dust_density, fargo_par)
else:
if center == "lookup":
shift_c = az.get_lookup_shift(frame)
elif option == "away":
shift_c = az.shift_away_from_minimum(dust_density, fargo_par)
elif center == "threshold":
threshold = util.get_threshold(size)
shift_c = az.get_azimuthal_center(dust_density,
fargo_par,
threshold=threshold *
surface_density_zero / 100.0)
else:
shift_c = 0 # Do not center
vorticity = np.roll(vorticity, shift_c)
density = np.roll(density, shift_c)
### Plot ###
x = rad
y = theta * (180.0 / np.pi)
result = ax.pcolormesh(x, y, np.transpose(vorticity), cmap=cmap)
#if frame_i == 2:
# cbar = fig.colorbar(result)
result.set_clim(clim[0], clim[1])
if use_contours:
levels = np.linspace(low_contour, high_contour, num_levels)
colors = generate_colors(num_levels)
plot.contour(x,
y,
np.transpose(density),
levels=levels,
origin='upper',
linewidths=1,
colors=colors,
alpha=0.8)
# Axes
y_min = 0
y_max = 360
plot.xlim(x_min, x_max)
plot.ylim(y_min, y_max)
angles = np.linspace(y_min, y_max, 7)
plot.yticks(angles)
# Annotate Axes
time = fargo_par["Ninterm"] * fargo_par["DT"]
orbit = (time / (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
#title = readTitle()
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
if frame_i == 1:
plot.ylabel(r"$\phi$ $\mathrm{(degrees)}$", fontsize=fontsize + 2)
#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)
title2 = r"$t = %d$ $\mathrm{orbits}}$ [$m_\mathrm{p}(t)\ =\ %.2f$ $M_\mathrm{J}$]" % (
orbit, current_mass)
plot.title("%s" % (title2), y=1.015, fontsize=fontsize + 1)
plot.text(x_mid,
y_text * (plot.ylim()[-1] - plot.ylim()[0]) + plot.ylim()[0],
title1,
horizontalalignment='center',
bbox=dict(facecolor='none',
edgecolor='black',
linewidth=1.5,
pad=7.0),
fontsize=fontsize + 2)
# Text
text_mass = r"$M_\mathrm{p} = %d$ $M_\mathrm{J}$" % (int(planet_mass))
text_visc = r"$\nu = 10^{%d}$" % (int(np.log(viscosity) / np.log(10)))
#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))
if frame_i == 1:
plot.text(-0.84 * x_range / 2.0 + x_mid,
y_text * (plot.ylim()[-1] - plot.ylim()[0]) + plot.ylim()[0],
text_mass,
fontsize=fontsize,
color='black',
horizontalalignment='right')
if frame_i == 2:
plot.text(0.84 * x_range / 2.0 + x_mid,
y_text * (plot.ylim()[-1] - plot.ylim()[0]) + plot.ylim()[0],
text_visc,
fontsize=fontsize,
color='black',
horizontalalignment='left')
# Label colorbar
# Add Colorbar (Source: http://stackoverflow.com/questions/23270445/adding-a-colorbar-to-two-subplots-with-equal-aspect-ratios)
if frame_i < 5:
# Only for last frame
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="6%", pad=0.2)
#cax = fig.add_axes([0.9, 0.1, 0.03, 0.8])
cbar = fig.colorbar(result, cax=cax)
if frame_i == 2:
if rossby:
cbar_name = r"$\mathrm{Rossby}$ $\mathrm{number}$"
else:
cbar_name = r"$\mathrm{Vorticity}$"
cbar.set_label(cbar_name,
fontsize=fontsize,
rotation=270,
labelpad=32)
#if frame_i != num_frames:
# fig.delaxes(cax) # to balance out frames that don't have colorbar with the one that does
# Set Aspect Ratio
#unit_aspect_ratio = (360) / (x_range)
#ax.set_aspect(1.12 / unit_aspect_ratio)
# Return to previous directory
os.chdir(cwd)
return ax
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 add_to_plot(i):
# Identify Subplot
frame = frames[i]; number = i + 1
ax = plot.subplot(1, 4, number)
# Data
if mpi:
density = Fields("./", 'gas', frame).get_field("dens").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)
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, :, :]
dz = z_angles[1] - z_angles[0]
surface_density = np.sum(density[:, :, :], axis = 0) * dz
normalized_midplane_density = midplane_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
normalized_density = surface_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
vorticity = utilVorticity.velocity_curl(midplane_vrad, midplane_vtheta, rad, theta, rossby = rossby, residual = residual)
### Plot ###
x = rad
y = theta * (180.0 / np.pi)
result = ax.pcolormesh(x, y, np.transpose(vorticity), cmap = cmap)
result.set_clim(clim[0], clim[1])
# Contours
if use_contours:
levels = np.linspace(low_contour, high_contour, num_levels)
colors = generate_colors(num_levels)
plot.contour(x, y, np.transpose(normalized_density), levels = levels, origin = 'upper', linewidths = 1, colors = colors)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(0, 360)
angles = np.linspace(0, 360, 7)
plot.yticks(angles)
# 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]
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize = fontsize)
if number == 1:
plot.ylabel(r"$\phi$ [degrees]", fontsize = fontsize)
x_range = x_max - x_min; x_mid = x_min + x_range / 2.0
y_text = 1.14
title = r"$t = %d$ [$m_\mathrm{p}=%.2f$ $M_\mathrm{J}$]" % (orbit, current_mass)
plot.title("%s" % (title), y = 1.035, fontsize = fontsize + 1)
# Add Colorbar (Source: http://stackoverflow.com/questions/23270445/adding-a-colorbar-to-two-subplots-with-equal-aspect-ratios)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size = "6%", pad = 0.2)
#cax = fig.add_axes([0.9, 0.1, 0.03, 0.8])
cbar = fig.colorbar(result, cax = cax)
# Label colorbar
if rossby:
cbar_name = r"$\mathrm{Rossby}$ $\mathrm{number}$"
else:
cbar_name = r"$\mathrm{Vorticity}$"
cbar.set_label(cbar_name, fontsize = fontsize, rotation = 270, labelpad = 25)
if number != len(frames):
fig.delaxes(cax) # to balance out frames that don't have colorbar with the one that does
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
vrad = (fromfile("gasvrad%d.dat" % frame).reshape(num_rad, num_theta)
) # add a read_vrad to util.py!
vtheta = (fromfile("gasvtheta%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)
# Shift
density = (fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta)) / surface_density_zero
dust_density = (fromfile("gasddens%d.dat" % frame).reshape(
num_rad, num_theta))
if center:
if taper_time < 10.1:
shift_c = az.get_azimuthal_peak(dust_density, fargo_par)
else:
threshold = util.get_threshold(size)
shift_c = az.get_azimuthal_center(dust_density,
fargo_par,
threshold=threshold *
surface_density_zero / 100.0)
vorticity = np.roll(vorticity, shift_c)
density = np.roll(density, shift_c)
### Plot ###
x = rad
y = theta * (180.0 / np.pi)
result = ax.pcolormesh(x, y, np.transpose(vorticity), cmap=cmap)
cbar = fig.colorbar(result)
result.set_clim(clim[0], clim[1])
if use_contours:
levels = np.linspace(low_contour, high_contour, num_levels)
colors = generate_colors(num_levels)
plot.contour(x,
y,
np.transpose(density),
levels=levels,
origin='upper',
linewidths=1,
colors=colors,
alpha=0.8)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(0, 360)
angles = np.linspace(0, 360, 7)
plot.yticks(angles)
# Annotate Axes
time = fargo_par["Ninterm"] * fargo_par["DT"]
orbit = (time / (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
#title = readTitle()
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
plot.ylabel(r"$\phi$", 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)
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')
# Label colorbar
if rossby:
cbar_name = r"$\mathrm{Rossby}$ $\mathrm{number}$"
else:
cbar_name = r"$\mathrm{Vorticity}$"
cbar.set_label(cbar_name, fontsize=fontsize, rotation=270, labelpad=25)
# Save, Show, and Close
if version is None:
save_fn = "%s/vorticityMap_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_vorticityMap_%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, 6), 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)
averaged_vortensity = averaged_vorticity / averaged_density[1:]
### Plot ###
x = rad[1:]
y = averaged_vortensity
result = plot.plot(x,
y,
c=colors[i % len(colors)],
linewidth=linewidth,
linestyle=linestyles[i % 2],
zorder=99,
label=r"$t$ $=$ $%d$ $T_\mathrm{p}$" % frame)
plot.legend(loc="lower right", fontsize=fontsize - 7)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(y_range[0], y_range[1])
#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"($\nabla \times v$)$_\mathrm{z}$ $/$ $\Sigma$ [$v_\mathrm{K}$ $/$ $r_\mathrm{p}$ $\Sigma_0$]",
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)
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]
if version is None:
save_fn = "%s/averagedVortensity_%s_%04d-%04d-%04d.png" % (
save_directory, directory_name, args.frames[0], args.frames[1],
args.frames[2])
else:
save_fn = "%s/v%04d_averagedVortensity_%s_%04d-%04d-%04d.png" % (
save_directory, version, directory_name, args.frames[0],
args.frames[1], args.frames[2])
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 add_to_plot(i):
# Identify Subplot
frame = frames[i]
number = i + 1
ax = plot.subplot(1, 2, number)
# 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)
# Shift
if center:
normalized_density, vorticity, shift_c = shift_density(
normalized_density,
vorticity,
fargo_par,
reference_density=normalized_density)
### Plot ###
x = rad
y = theta * (180.0 / np.pi)
result = ax.pcolormesh(x, y, np.transpose(vorticity), cmap=cmap)
result.set_clim(clim[0], clim[1])
# Contours
if use_contours:
levels = np.linspace(low_contour, high_contour, num_levels)
colors = generate_colors(num_levels)
plot.contour(x,
y,
np.transpose(normalized_density),
levels=levels,
origin='upper',
linewidths=1,
colors=colors)
if quiver:
# Velocity
radial_velocity = np.array(
fromfile("gasvy%d.dat" % frame).reshape(num_rad,
num_theta)) # Radial
azimuthal_velocity = np.array(
fromfile("gasvx%d.dat" % frame).reshape(
num_rad, num_theta)) # Azimuthal
keplerian_velocity = rad * (np.power(rad, -1.5) - 1)
azimuthal_velocity -= keplerian_velocity[:, None]
if center:
radial_velocity = np.roll(radial_velocity, shift_c, axis=-1)
azimuthal_velocity = np.roll(azimuthal_velocity,
shift_c,
axis=-1)
# Sub-sample the grid
start_i = np.searchsorted(rad, start_quiver)
end_i = np.searchsorted(rad, end_quiver)
x_q = x[start_i:end_i]
y_q = y[:]
u = np.transpose(radial_velocity)[:, start_i:end_i]
v = np.transpose(azimuthal_velocity)[:, start_i:end_i]
plot.quiver(x_q[::rate_x],
y_q[::rate_y],
u[::rate_y, ::rate_x],
v[::rate_y, ::rate_x],
scale=scale)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(0, 360)
angles = np.linspace(0, 360, 7)
plot.yticks(angles)
# 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]
#current_gap_depth = get_gap_depth(normalized_density)
unit = "r_\mathrm{p}"
plot.xlabel(r"Radius [$%s$]" % unit, fontsize=fontsize)
if number == 1:
plot.ylabel(r"$\phi$ [degrees]", fontsize=fontsize)
x_range = x_max - x_min
x_mid = x_min + x_range / 2.0
y_text = 1.14
title = r"$t = %d$ [$m_\mathrm{p}=%.2f$ $M_\mathrm{J}$]" % (
orbit, current_mass)
#title = r"$t = %d$ [$\delta_\mathrm{gap}=%.1f$]" % (orbit, current_gap_depth)
plot.title("%s" % (title), y=1.035, fontsize=fontsize + 1)
# Add Colorbar (Source: http://stackoverflow.com/questions/23270445/adding-a-colorbar-to-two-subplots-with-equal-aspect-ratios)
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size="6%", pad=0.2)
#cax = fig.add_axes([0.9, 0.1, 0.03, 0.8])
cbar = fig.colorbar(result, cax=cax)
# Label colorbar
if rossby:
cbar_name = r"$\mathrm{Rossby}$ $\mathrm{number}$"
else:
cbar_name = r"$\mathrm{Vorticity}$"
cbar.set_label(cbar_name, fontsize=fontsize, rotation=270, labelpad=25)
if number != len(frames):
fig.delaxes(
cax
) # to balance out frames that don't have colorbar with the one that does
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
normalized_density = (fromfile("gasdens%d.dat" % frame).reshape(
num_rad, num_theta)) / surface_density_zero
averaged_density = np.average(normalized_density, axis=1)
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=False,
residual=False)
averaged_vorticity = np.average(vorticity, axis=1)
#keplerian_velocity = 0.0 # put in rotating frame of spiral waves (it's already in rotating frame!)
keplerian_velocity = rad * (np.power(
rad, -1.5) - 1) # in rotating frame, v_k = r * (r^-1.5 - r_p^-1.5)
keplerian_frequency = np.power(rad, -1.5)
#vtheta -= keplerian_velocity
averaged_vtheta = np.average(vtheta, axis=1)
dr = rad[1] - rad[0]
averaged_dvtheta = np.diff(averaged_vtheta) / dr
sound_speed_sq = np.power(scale_height * rad * keplerian_frequency, 2)
diff_sound_speed_sq = np.diff(sound_speed_sq) / dr
mach_number = averaged_vtheta / (scale_height * rad * keplerian_frequency
) # u_perp / c_s
coefficient_one = -1.0 * np.power(np.power(mach_number, 2) - 1,
2) / np.power(mach_number, 2)
coefficient_two = np.power(mach_number, 2) - 1
coefficient_three = -1.0 * np.power(mach_number, 2) - 1 / averaged_vtheta
vorticityJump = coefficient_one[1:] * averaged_dvtheta + coefficient_two[
1:] * averaged_vorticity + coefficient_three[1:] * diff_sound_speed_sq
### Plot ###
x = rad[1:]
y = vorticityJump
result = plot.plot(x, y, linewidth=linewidth, zorder=99)
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
plot.xlim(x_min, x_max)
plot.ylim(y_range[0], y_range[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"$\Delta \omega$", 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 = 1.5
#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/averagedVorticityJump_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_averagedVorticityJump%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)
host = fig.add_subplot(111)
# 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))
### Plot ###
x = rad[1:]
y = maximum_condition
result, = host.plot(x, y, c = 'darkviolet', linewidth = linewidth + 1, zorder = 99, label = "Condition")
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])
host.set_yticks(np.arange(y_range[0], y_range[1] + 1e-9, 0.005))
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"$\Sigma$ $/$ ($\nabla \times v$)$_\mathrm{z}$", 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"$h/r = %.2f$ $\alpha \approx %s \times 10^{%d}$ $A = %.2f$" % (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)
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)
# 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)
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 make_plot(z_level, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
if mpi:
density = Fields("./", 'gas', frame).get_field("dens").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)
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 + z_level, :, :]
midplane_vrad = vrad[num_z / 2 + z_level, :, :]
midplane_vtheta = vtheta[num_z / 2 + z_level, :, :]
dz = z_angles[1] - z_angles[0]
surface_density = np.sum(density[:, :, :], axis=0) * dz
normalized_midplane_density = midplane_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
normalized_density = surface_density / surface_density_zero # / np.sqrt(2.0 * np.pi) / scale_height_function[:, None]
vorticity = utilVorticity.velocity_curl(midplane_vrad,
midplane_vtheta,
rad,
theta,
rossby=rossby,
residual=residual)
# Shift
if center:
normalized_density, vorticity, shift_c = shift_density(
normalized_density,
vorticity,
fargo_par,
reference_density=normalized_density)
### Plot ###
x = rad
y = theta * (180.0 / np.pi)
result = ax.pcolormesh(x, y, np.transpose(vorticity), cmap=cmap)
cbar = fig.colorbar(result)
result.set_clim(clim[0], clim[1])
if use_contours:
levels = np.linspace(low_contour, high_contour, num_levels)
colors = generate_colors(num_levels)
plot.contour(x,
y,
np.transpose(normalized_density),
levels=levels,
origin='upper',
linewidths=1,
colors=colors,
alpha=0.8)
if quiver:
# Velocity
radial_velocity = vrad
azimuthal_velocity = vtheta
keplerian_velocity = rad * (np.power(rad, -1.5) - 1)
azimuthal_velocity -= keplerian_velocity[:, None]
if center:
radial_velocity = np.roll(radial_velocity, shift_c, axis=-1)
azimuthal_velocity = np.roll(azimuthal_velocity, shift_c, axis=-1)
# Sub-sample the grid
start_i = np.searchsorted(rad, start_quiver)
end_i = np.searchsorted(rad, end_quiver)
x_q = x[start_i:end_i]
y_q = y[:]
u = np.transpose(radial_velocity)[:, start_i:end_i]
v = np.transpose(azimuthal_velocity)[:, start_i:end_i]
plot.quiver(x_q[::rate_x],
y_q[::rate_y],
u[::rate_y, ::rate_x],
v[::rate_y, ::rate_x],
scale=scale)
# Axes
plot.xlim(x_min, x_max)
plot.ylim(0, 360)
angles = np.linspace(0, 360, 7)
plot.yticks(angles)
# Annotate Axes
time = fargo_par["Ninterm"] * fargo_par["DT"]
orbit = (time / (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"$\phi$", 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)
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')
# Label colorbar
if rossby:
cbar_name = r"$\mathrm{Rossby}$ $\mathrm{number}$"
else:
cbar_name = r"$\mathrm{Vorticity}$"
cbar.set_label(cbar_name, fontsize=fontsize, rotation=270, labelpad=25)
# Save, Show, and Close
if version is None:
save_fn = "%s/vorticityMap_%04d-z%04d.png" % (save_directory, frame,
z_level)
else:
save_fn = "%s/v%04d_vorticityMap_%04d-z%04d.png" % (
save_directory, version, frame, z_level)
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
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)
vortex_tracker = np.percentile(normalized_density, 98, axis = 1)[1:] * np.percentile(vorticity, 2, axis = 1)
### Plot ###
x = rad[1:]
y = vortex_tracker
result = plot.plot(x, y, linewidth = linewidth, zorder = 99)
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
plot.xlim(x_min, x_max)
plot.ylim(y_range[0], y_range[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"($\nabla \times v$)$_\mathrm{z}$ $\times$ $\Sigma$ [$\Sigma_0$ $v_\mathrm{K}$ $/$ $r_\mathrm{p}$]", 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 = -0.14
#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()[0], 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/radialVortexTracker_%04d.png" % (save_directory, frame)
else:
save_fn = "%s/v%04d_radialVortexTracker_%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)
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)
