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