def shift_density(normalized_density,
fargo_par,
option="away",
reference_density=None,
frame=None):
""" shift density based on option """
if reference_density is None:
reference_density = normalized_density
# Options
if option == "peak":
shift_c = az.get_azimuthal_peak(reference_density, fargo_par)
elif option == "threshold":
threshold = util.get_threshold(fargo_par["PSIZE"])
shift_c = az.get_azimuthal_center(reference_density,
fargo_par,
threshold=threshold)
elif option == "away":
shift_c = az.shift_away_from_minimum(reference_density, fargo_par)
elif option == "lookup":
shift_c = az.get_lookup_shift(frame)
else:
print "Invalid centering option. Choose (cm-)peak, (cm-)threshold, (cm-)away, or lookup"
# Shift
shifted_density = np.roll(normalized_density, shift_c)
return shifted_density, shift_c
def center_vortex(density, frame, reference_density=None):
""" Step 2: center the vortex so that the peak is at 180 degrees """
if taper_time < 1.1:
for i, size in enumerate(sizes):
shift_i = az.get_azimuthal_peak(density[:, :, i], fargo_par)
density[:, :, i] = np.roll(density[:, :, i], shift_i, axis=1)
return density
elif taper_time > 1.1:
for i, size_name in enumerate(size_names):
if center == "lookup":
pass
#shift_i = az.get_lookup_shift(frame, directory = "../%s-size" % size_name)
elif center == "threshold":
threshold = util.get_threshold(size) * surface_density_zero
shift_i = az.get_azimuthal_center(density[:, :, i],
fargo_par,
threshold=threshold)
elif center == "away":
shift_i = az.shift_away_from_minimum(reference_density,
fargo_par)
else:
print "invalid centering option"
density[:, :, i] = np.roll(density[:, :, i], shift_i, axis=1)
return density
def measure_peak_offset(args):
# Unpack
i, frame = args
intensity_polar = util.read_data(frame,
'polar_intensity',
fargo_par,
id_number=id_number)
# Shift and get peak
shift_c = az.shift_away_from_minimum(intensity_polar, fargo_par)
intensity_polar = np.roll(intensity_polar, shift_c, axis=-1)
peak_r_i, peak_phi_i = az.get_peak(intensity_polar, fargo_par)
# Return peak relative to the center, where the edges are set by a threshold
intensity_polar /= np.max(intensity_polar) # normalize
intensity_polar_at_peak = intensity_polar[
peak_r_i, :] # take azimuthal profile
left_index = az.my_searchsorted(intensity_polar_at_peak, threshold)
right_index = len(intensity_polar_at_peak) - az.my_searchsorted(
intensity_polar_at_peak[::-1], threshold) - 1
# Convert to theta
left_theta = theta[left_index] * (180.0 / np.pi)
right_theta = theta[right_index] * (180.0 / np.pi)
center_theta = left_theta + (right_theta - left_theta) / 2.0
peak_theta = theta[peak_phi_i] * (180.0 / np.pi)
peak_offset = peak_theta - center_theta
print i, frame, peak_offset, center_theta, peak_theta
# Store in mp_array
peak_offsets[i] = peak_offset
def make_plot(frame, show=False):
# Set up figure
fig = plot.figure(figsize=(7, 6), dpi=dpi)
ax = fig.add_subplot(111)
# Data
intensity_polar = util.read_data(frame,
'polar_intensity',
fargo_par,
id_number=id_number)
if normalize:
intensity_polar /= np.max(intensity_polar)
_, azimuthal_profile = az.get_profiles(intensity_polar,
fargo_par,
args,
shift=None)
# Get Shift
gas_density = util.read_data(frame, 'gas', fargo_par, directory="../../")
# Shift gas density with center of dust density
shift = az.shift_away_from_minimum(gas_density, fargo_par)
### Plot ###
x = theta * (180.0 / np.pi) - 180.0
plot.plot(x, azimuthal_profile, linewidth=linewidth, alpha=alpha)
if args.compare is not None:
for i, directory in enumerate(args.compare):
intensity_polar_c = util.read_data(frame,
'polar_intensity',
fargo_par,
id_number=id_number,
directory=directory)
if normalize:
intensity_polar_c /= np.max(intensity_polar_c)
_, azimuthal_profile_c = az.get_profiles(intensity_polar_c,
fargo_par,
args,
shift=None)
plot.plot(x,
azimuthal_profile_c,
linewidth=linewidth,
alpha=alpha,
label="%s" % i)
plot.legend(loc="upper left")
# Locate Planet
if shift is None:
planet_loc = theta[0]
else:
if shift < -len(theta):
shift += len(theta)
planet_loc = theta[shift] * (180.0 / np.pi) - 180.0
plot.scatter(planet_loc, 0, c="k", s=150, marker="D", zorder=100) # planet
# Label star and planet
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]
# Axes
max_x = 180
plot.xlim(-max_x, max_x)
angles = np.linspace(-max_x, max_x, 7)
plot.xticks(angles)
if max_y is None:
plot.ylim(0, plot.ylim()[-1]) # No Input
else:
plot.ylim(0, max_y) # Input
# Annotate Axes
time = fargo_par["Ninterm"] * fargo_par["DT"]
orbit = (time / (2 * np.pi)) * frame
current_mass = util.get_current_mass(orbit,
taper_time,
planet_mass=planet_mass)
plot.xlabel(r"$\phi - \phi_\mathrm{center}$ $\mathrm{(degrees)}$",
fontsize=fontsize + 2)
plot.ylabel(r"$I$ / $I_\mathrm{max}$", fontsize=fontsize)
# Title
title = "\n" + r"$t$ $=$ $%.1f$ " % (
orbit) + "[$m_p(t)$ $=$ $%.2f$ $M_J$]" % (current_mass)
plot.title("%s" % (title), fontsize=fontsize + 1)
# Save, Show, and Close
if version is None:
save_fn = "%s/id%04d_azimuthalIntensityProfiles_%04d.png" % (
save_directory, id_number, frame)
else:
save_fn = "%s/v%04d_id%04d_azimuthalIntensityProfiles_%04d.png" % (
save_directory, version, id_number, 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
intensity_cart = util.read_data(frame, 'cartesian_intensity', fargo_par, id_number = id_number)
xs, ys, xs_grid, ys_grid = sq.get_cartesian_grid(rad)
# Get Shift
gas_density = util.read_data(frame, 'gas', fargo_par, directory = "../../")
# Shift gas density with center of dust density
shift = az.shift_away_from_minimum(gas_density, fargo_par)
# Normalize
if normalize:
intensity_cart /= np.max(intensity_cart)
# Arcseconds or Planet Radii
if arc:
arc_weight = planet_radius / distance # related to parallax
else:
arc_weight = 1
### Plot ###
result = plot.pcolormesh(xs * arc_weight, ys * arc_weight, np.transpose(intensity_cart), cmap = cmap)
result.set_clim(clim[0], clim[1])
# Get rid of interior
circle = plot.Circle((0, 0), min(rad) * arc_weight, color = "black")
ax.add_artist(circle)
# Add beam size
beam = plot.Circle((1.7 * arc_weight, 1.7 * arc_weight), (beam_size / 2) * arc_weight, color = "white")
fig.gca().add_artist(beam)
# Add planet orbit
planet_orbit = plot.Circle((0, 0), 1 * arc_weight, color = "white", fill = False, alpha = 0.8, linestyle = "dashed", zorder = 50)
ax.add_artist(planet_orbit)
# Locate Planet
if shift < -len(theta):
shift += len(theta)
planet_theta = theta[shift]
planet_theta += (np.pi / 2.0) # Note: the conversion from polar to cartesian rotates everything forward by 90 degrees
planet_theta = planet_theta % (2 * np.pi) - (np.pi) # Keep -np.pi < theta < np.pi
planet_x = np.cos(planet_theta)
planet_y = np.sin(planet_theta)
# Label star and planet
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]
planet_size = current_mass / planet_mass
plot.scatter(0, 0, c = "white", s = 300, marker = "*", zorder = 100) # star
plot.scatter(planet_x * arc_weight, planet_y * arc_weight, c = "white", s = int(70), marker = "D", zorder = 100) # planet
# Axes
box_size = args.box * arc_weight
plot.xlim(-box_size, box_size)
plot.ylim(-box_size, box_size)
plot.axes().set_aspect('equal')
ax.spines['bottom'].set_color('w'); ax.spines['top'].set_color('w'); ax.spines['left'].set_color('w'); ax.spines['right'].set_color('w')
ax.tick_params(colors = 'white', labelcolor = 'black', width = 1, length = 5)
# Annotate Axes
if arc:
unit = "^{\prime\prime}"
else:
unit = "r_\mathrm{p}"
ax.set_xlabel(r"$x$ [$%s$]" % unit, fontsize = fontsize)
ax.set_ylabel(r"$y$ [$%s$]" % unit, fontsize = fontsize)
# Title
title = r"$t$ $=$ $%.1f$ [$m_p(t)$ $=$ $%.2f$ $M_J$]" % (orbit, current_mass)
plot.title("%s" % (title), y = 1.015, fontsize = fontsize + 1)
#plot.title("Intensity Map (t = %.1f)" % (orbit), fontsize = fontsize + 1)
taper_title = r"$T_\mathrm{growth} = %d$" % taper_time
#plot.text(0.0 * box_size, 2 * arc_weight, taper_title, fontsize = fontsize, color = 'white', horizontalalignment = 'center', bbox=dict(facecolor = 'black', edgecolor = 'white', pad = 10.0), zorder = 100)
# Add Colorbar (Source: http://stackoverflow.com/questions/23270445/adding-a-colorbar-to-two-subplots-with-equal-aspect-ratios)
if colorbar:
# Only for last frame
divider = make_axes_locatable(ax)
cax = divider.append_axes("right", size = "8%", pad = 0.2)
#cax = fig.add_axes([0.9, 0.1, 0.03, 0.8])
cbar = fig.colorbar(result, cax = cax)
cbar.set_label("Normalized Intensity", fontsize = fontsize, rotation = 270, labelpad = 25)
# Save, Show, and Close
if version is None:
save_fn = "%s/id%04d_intensityCartGrid_%04d.png" % (save_directory, id_number, frame)
else:
save_fn = "%s/v%04d_id%04d_intensityCartGrid_%04d.png" % (save_directory, version, id_number, 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 add_to_plot(i):
# Identify Subplot
frame = frames[i]
number = i + 1
ax = plot.subplot(1, 2, number)
# Data
intensity_cart = util.read_data(frame,
'cartesian_intensity',
fargo_par,
id_number=id_number)
xs, ys, xs_grid, ys_grid = sq.get_cartesian_grid(rad)
# Get Shift
gas_density = util.read_data(frame,
'gas',
fargo_par,
directory="../../")
# Shift gas density with center of dust density
shift = az.shift_away_from_minimum(gas_density, fargo_par)
# Normalize
if normalize:
intensity_cart /= np.max(intensity_cart)
# Arcseconds or Planet Radii
if arc:
arc_weight = planet_radius / distance # related to parallax
else:
arc_weight = 1
### Plot ###
result = plot.pcolormesh(xs * arc_weight,
ys * arc_weight,
np.transpose(intensity_cart),
cmap=cmap)
result.set_clim(clim[0], clim[1])
# Get rid of interior
circle = plot.Circle((0, 0), min(rad) * arc_weight, color="black")
ax.add_artist(circle)
# Add beam size
beam = plot.Circle((1.7 * arc_weight, 1.7 * arc_weight),
(beam_size / 2) * arc_weight,
color="white")
fig.gca().add_artist(beam)
# Add planet orbit
planet_orbit = plot.Circle((0, 0),
1 * arc_weight,
color="white",
fill=False,
alpha=0.8,
linestyle="dashed",
zorder=50)
ax.add_artist(planet_orbit)
# Locate Planet
if shift < -len(theta):
shift += len(theta)
planet_theta = theta[shift]
planet_theta += (
np.pi / 2.0
) # Note: the conversion from polar to cartesian rotates everything forward by 90 degrees
planet_theta = planet_theta % (2 * np.pi) - (
np.pi) # Keep -np.pi < theta < np.pi
planet_x = np.cos(planet_theta)
planet_y = np.sin(planet_theta)
# Label star and planet
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]
plot.scatter(0, 0, c="white", s=250, marker="*", zorder=100) # star
plot.scatter(planet_x * arc_weight,
planet_y * arc_weight,
c="white",
s=60,
marker="D",
zorder=100) # planet
# Axes
box_size = args.box * arc_weight
ax.set_xlim(-box_size, box_size)
ax.set_ylim(-box_size, box_size)
ax.set_aspect('equal')
ax.spines['bottom'].set_color('w')
ax.spines['top'].set_color('w')
ax.spines['left'].set_color('w')
ax.spines['right'].set_color('w')
ax.tick_params(colors='white',
labelcolor='black',
width=1,
length=5,
direction="in")
# Annotate Axes
if arc:
ticks = np.arange(-0.3, 0.31, 0.1)
ax.set_xticks(ticks)
ax.set_xticklabels(["", "-0.2", "", "0.0", "", "0.2", ""])
ax.set_yticks(ticks)
unit = "^{\prime\prime}"
else:
unit = "r_\mathrm{p}"
ax.set_xlabel(r"$x$ [$%s$]" % unit, fontsize=fontsize)
if number == 1:
ax.set_ylabel(r"$y$ [$%s$]" % unit, fontsize=fontsize)
# Title
title = r"$t = %d$ [$m_\mathrm{p}=%.2f$ $M_\mathrm{J}$]" % (
orbit, current_mass)
plot.title("%s" % (title), y=1.035, fontsize=fontsize)
# Add Colorbar (Source: http://stackoverflow.com/questions/23270445/adding-a-colorbar-to-two-subplots-with-equal-aspect-ratios)
if args.colorbar:
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)
cbar.set_label(r"Normalized Intensity",
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
