for i, data in enumerate(datas):
levels = measure.contour_levels(data["rms"], data["data"].max(), base = data["base"], step=math.sqrt(2))
axs[1].contour(
np.arange(data["left"], data["right"], data["scale"]),
np.arange(data["top"], data["bottom"], data["scale"]),
data["data"],
levels = levels, colors=colors[i]
)
axs[1].set_xlim(-20, 20)
axs[1].set_ylim(-20, 20)
axs[1].set_aspect("equal")
axs[1].set_xlabel("x1 (mas)")
axs[1].set_ylabel("x2 (mas)")
axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_Asadi), np.max(PA_Asadi), 10., True, '#bdbdbd')
axs[1] = func.plot_PA_wedge(axs[1], core_pos,
np.mean(PA_obs_Asadi) - np.std(PA_obs_Asadi),
np.mean(PA_obs_Asadi) + np.std(PA_obs_Asadi),
10., True, 'y')
axs[1] = func.plot_PA_wedge(axs[1], core_pos,
np.mean(PA_obs_Rusin) - np.std(PA_obs_Rusin),
np.mean(PA_obs_Rusin) + np.std(PA_obs_Rusin),
10., True, 'r')
leg = axs[-1].legend(lines, labels)
for legobj in leg.legendHandles:
legobj.set_linewidth(3.0)
for ax in axs:
axs[0], axs[1], xA_a, xB_a, yA_a, yB_a = func.pred_pos(
axs[0], axs[1], dataset, colors[i], xA_a, yA_a, xB_a, yB_a, plot=False
)
core_pos = (xB[0], yB[0])
# core_pos = (0.0, 0.0)
# for PA in PA_obs:
# axs[1] = func.plot_PA_line(axs[1], core_pos, PA, 30.0)
# for PA in PA_Asadi:
# axs[1] = func.plot_PA_line(axs[1], core_pos, PA, 30.0, '-k')
# for PA in PA_Rusin:
# axs[1] = func.plot_PA_line(axs[1], core_pos, PA, 30.0, '-b')
# axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_obs), np.max(PA_obs), 30., True, 'b')
# axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_Rusin), np.max(PA_Rusin), 30., True, 'c')
axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_Asadi), np.max(PA_Asadi), 30.0, True, "#bdbdbd")
axs[0].set_xlim(-80, 20)
axs[0].set_ylim(-30, 30)
axs[1].set_xlim(-40, 20)
axs[1].set_ylim(-30, 30)
axs[0].set_aspect("equal")
axs[1].set_aspect("equal")
xticks0 = axs[0].get_xticks()
yticks0 = axs[0].get_yticks()
xlabels0 = np.round(xticks0 * evn38.pixel_scale * 3600e3, 1)
ylabels0 = np.round(yticks0 * evn38.pixel_scale * 3600e3, 1)
axs[0].set_xticklabels(xlabels0)
axs[0].set_yticklabels(ylabels0)
# Plot predicted position angles
# core_pos = (0.0, 0.0)
# axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_Asadi), np.max(PA_Asadi), 10., True, '#bdbdbd')
axs[1].set_xlim(-30, 10)
axs[1].set_ylim(-10, 10)
axs[1].set_aspect("equal")
axs[1].set_xlabel("x1 (mas)")
axs[1].set_ylabel("x2 (mas)")
# pas = func.draw_straight_line(axs[0], 'y', -(imAxmas - imAxmas[0]), imAymas - imAymas[0])
# pbs = func.draw_straight_line(axs[1], 'y', -(imBxmas - imBxmas[0]), imBymas - imBymas[0])
# pac = func.draw_curved_line(axs[0], 'r', -(imAxmas - imAxmas[0]), imAymas - imAymas[0])
# pbc = func.draw_curved_line(axs[1], 'r', -(imBxmas - imBxmas[0]), imBymas - imBymas[0])
#axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PA_Asadi), np.max(PA_Asadi), 10., True, '#bdbdbd')
axs[1] = func.plot_PA_wedge(axs[1], core_pos, np.min(PAs), np.max(PAs), 10., True, '#bdbdbd')
for ax in axs:
xticks = ax.get_xticks()
xlabels = [-int(i) for i in xticks]
ax.set_xticklabels(xlabels)
legend1 = plt.legend(lines, labels, loc='upper left', frameon=False)
for legobj in legend1.legendHandles:
legobj.set_linewidth(3.0)
axs[1] = plt.gca().add_artist(legend1)
plt.legend([constraint_line, match_line, free_line],
["constraints", "${\it match}$ model", "${\it free}$ model"],
loc='center left', scatterpoints=1, frameon=False)
plt.savefig("../figs/overplot_sims.png")
