def choose_axis(i, axis):
# Orbit Number
time = float(fargo_par["Ninterm"]) * float(fargo_par["DT"])
orbit = int(round(time / (2 * np.pi), 0)) * i
# Set up figure
fig = plot.figure(figsize=(700 / my_dpi, 600 / my_dpi), dpi=my_dpi)
ax = fig.add_subplot(111)
# Axis
angles = np.linspace(0, 2 * np.pi, 7)
degree_angles = ["%d" % d_a for d_a in np.linspace(0, 360, 7)]
plot.ylim(0, 2 * np.pi)
plot.yticks(angles, degree_angles)
if axis == "zoom":
x = (rad - 1) / scale_height
prefix = "zoom_"
plot.xlim(0, 40) # to match the ApJL paper
xlabel = r"($r - r_p$) $/$ $h$"
else:
x = rad
prefix = ""
plot.xlim(float(fargo_par["Rmin"]), float(fargo_par["Rmax"]))
xlabel = "Radius"
# Data
density = (fromfile("gasdens%d.dat" % i).reshape(num_rad, num_theta))
normalized_density = density / surface_density_zero
torque_map = util.torque(rad, theta, normalized_density)
abs_torque = np.abs(torque_map)
log_torque = np.log(abs_torque) / np.log(10) # log torque in base 10
### Plot ###
result = ax.pcolormesh(x, theta, np.transpose(log_torque), cmap=cmap)
fig.colorbar(result)
result.set_clim(clim[0], clim[1])
# Annotate
plot.xlabel(xlabel, fontsize=fontsize)
plot.ylabel(r"$\phi$", fontsize=fontsize)
plot.title("Torque Map at Orbit %d" % orbit, fontsize=fontsize + 1)
# Save and Close
plot.savefig("%s/%storqueMap_%03d.png" % (save_directory, prefix, i),
bbox_inches='tight',
dpi=my_dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def choose_axis(i, axis):
# Orbit Number
time = float(fargo_par["Ninterm"]) * float(fargo_par["DT"])
orbit = int(round(time / (2 * np.pi), 0)) * i
# Set up figure
fig = plot.figure(figsize = (700 / my_dpi, 600 / my_dpi), dpi = my_dpi)
ax = fig.add_subplot(111)
# Axis
angles = np.linspace(0, 2 * np.pi, 7)
degree_angles = ["%d" % d_a for d_a in np.linspace(0, 360, 7)]
plot.ylim(0, 2 * np.pi)
plot.yticks(angles, degree_angles)
if axis == "zoom":
x = (rad - 1) / scale_height
prefix = "zoom_"
plot.xlim(0, 40) # to match the ApJL paper
xlabel = r"($r - r_p$) $/$ $h$"
else:
x = rad
prefix = ""
plot.xlim(float(fargo_par["Rmin"]), float(fargo_par["Rmax"]))
xlabel = "Radius"
# Data
density = (fromfile("gasdens%d.dat" % i).reshape(num_rad, num_theta))
normalized_density = density / surface_density_zero
torque_map = util.torque(rad, theta, normalized_density, )
abs_torque = np.abs(torque_map)
log_torque = np.log(abs_torque) / np.log(10) # log torque in base 10
### Plot ###
result = ax.pcolormesh(x, theta, np.transpose(abs_torque), cmap = cmap)
fig.colorbar(result)
result.set_clim(clim[0], clim[1])
# Annotate
plot.xlabel(xlabel, fontsize = fontsize)
plot.ylabel(r"$\phi$", fontsize = fontsize)
plot.title("Torque Map at Orbit %d" % orbit, fontsize = fontsize + 1)
# Save and Close
plot.savefig("%s/%storqueMap_%03d.png" % (save_directory, prefix, i), bbox_inches = 'tight', dpi = my_dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
def choose_axis(i, axis):
# Orbit Number
time = float(fargo_par["Ninterm"]) * float(fargo_par["DT"])
orbit = int(round(time / (2 * np.pi), 0)) * i
# Set up figure
fig = plot.figure(figsize = (700 / my_dpi, 600 / my_dpi), dpi = my_dpi)
ax = fig.add_subplot(111, polar = True)
# Axis
angles = np.linspace(0, 2 * np.pi, 7)
degree_angles = ["%d" % d_a for d_a in np.linspace(0, 360, 7)]
plot.ylim(0, 2 * np.pi)
plot.yticks(angles, degree_angles)
# Axis
if axis == "zoom":
prefix = "zoom_"
rmax = 2.4 # to match ApJL paper
else:
prefix = ""
rmax = float(fargo_par["Rmax"])
plot.xticks([], []) # Angles
plot.yticks([rmax], ["%.1f" % rmax]) # Max Radius
plot.ylim(0, rmax)
# Data
density = (fromfile("gasdens%d.dat" % i).reshape(num_rad, num_theta))
normalized_density = density / surface_density_zero
torque_map = util.torque(rad, theta, normalized_density, planet_mass = planet_mass)
abs_torque = np.abs(torque_map)
log_torque = np.log(abs_torque) / np.log(10) # log torque in base 10
### Plot ###
result = ax.pcolormesh(theta, rad, log_torque, cmap = cmap)
fig.colorbar(result)
result.set_clim(clim[0], clim[1])
# Annotate
plot.title("Torque Map at Orbit %d" % orbit, fontsize = fontsize + 1)
# Save and Close
plot.savefig("%s/%storqueMap_%03d.png" % (save_directory, prefix, i), bbox_inches = 'tight', dpi = my_dpi)
if show:
plot.show()
plot.close(fig) # Close Figure (to avoid too many figures)
for frame in range(num_frames):
density = (fromfile("gasdens%d.dat" % frame).reshape(num_rad, num_theta))
normalized_density = density / surface_density_zero
vrad = (fromfile("gasvrad%d.dat" % frame).reshape(num_rad, num_theta))
vtheta = (fromfile("gasvtheta%d.dat" % frame).reshape(num_rad, num_theta))
vorticity = curl(vrad, vtheta, rad, theta)
vortensity = vorticity / normalized_density[1:, 1:]
averaged_w = np.average(vortensity, axis=1)
### Vortex Torque ###
# the vortex is any cell where the vortensity is between the thresholds of 0.0 and 0.2
#vortex_indices = np.where(vortensity < 0.2 and vortensity > 0.0)
torqueMap = util.torque(rad, theta, density)
vortexTorque = np.sum(torqueMap[(vortensity < 0.2) & (vortensity > 0.0)])
### Get Phase Too ###
outer_disk_start = np.searchsorted(
rad, 1.2) # look for min vortensity beyond r = 1.2
outer_disk_end = np.searchsorted(
rad, 2.5) # look for min vortensity before r = 2.5
vortex_rad_outer_index = np.argmin(
averaged_w[outer_disk_start:outer_disk_end])
vortex_rad_index = vortex_rad_outer_index + outer_disk_start
# Check 10 + 1 + 10 profiles
dr = 10 # 10 indices
vortex_width = range(vortex_rad_index - dr, vortex_rad_index + dr + 1)
a = "Frame".center(column_widths[0])
b = "Total".center(column_widths[1])
c = "Inner".center(column_widths[2])
d = "Outer".center(column_widths[3])
e = "Inner (+)".center(column_widths[4])
f = "Inner (-)".center(column_widths[5])
g = "Outer (+)".center(column_widths[6])
h = "Outer (-)".center(column_widths[7])
first_line = "%s %s %s %s %s %s %s %s\n" % (a, b, c, d, e, f, g, h)
dat_file.write(first_line)
dat_file.close()
#### Calculate Data and Write to Files ####
for frame in range(num_frames):
density = (fromfile("gasdens%d.dat" % frame).reshape(num_rad, num_theta))
torqueMap = util.torque(rad, theta, density)
inner_torque_halves = util.inner_torque_contributions(rad, theta, torqueMap)
outer_torque_halves = util.outer_torque_contributions(rad, theta, torqueMap)
inner_torque = inner_torque_halves[0] + inner_torque_halves[1]
outer_torque = outer_torque_halves[0] + outer_torque_halves[1]
net_torque = inner_torque + outer_torque
# Format into strings
scaling = 10**6 # multiply by one million to make things readable
a = ("%d" % frame).center(column_widths[0])
b = ("%.8f" % (net_torque * scaling)).center(column_widths[1])
c = ("%.8f" % (inner_torque * scaling)).center(column_widths[2])
d = ("%.8f" % (outer_torque * scaling)).center(column_widths[3])
e = ("%.8f" % (inner_torque_halves[0] * scaling)).center(column_widths[4])
