xticks = ax.get_xticks()
yticks = ax.get_yticks()
# xlabels = np.round(xticks * evn38.pixel_scale * 3600e3, 1)
# ylabels = np.round(yticks * evn38.pixel_scale * 3600e3, 1)
# ax.set_xticklabels(xlabels)
# ax.set_yticklabels(ylabels)
if i in[0, 1]:
# ax = func.draw_beam(ax,
# evn38.beam_size[0] / evn38.pixel_scale,
# evn38.beam_size[1] / evn38.pixel_scale,
# evn38.beam_PA)
ax = func.draw_beam(ax,
vlba.beam_size[0] / vlba.pixel_scale,
vlba.beam_size[1] / vlba.pixel_scale,
vlba.beam_PA)
xlabels = np.round(xticks * vlba.pixel_scale * 3600e3, 1)
ylabels = np.round(yticks * vlba.pixel_scale * 3600e3, 1)
ax.set_xticklabels(xlabels)
ax.set_yticklabels(ylabels)
elif i in [2, 3]:
ax = func.draw_beam(ax,
evn38.beam_size[0] / evn38.pixel_scale,
evn38.beam_size[1] / evn38.pixel_scale,
evn38.beam_PA)
xlabels = np.round(xticks * evn38.pixel_scale * 3600e3, 1)
ylabels = np.round(yticks * evn38.pixel_scale * 3600e3, 1)
ax.set_xticklabels(xlabels)
ax.set_yticklabels(ylabels)
elif i in [4, 5]:
for i, data in enumerate(datas):
levels = measure.contour_levels(data["rms"], data["data"].max(), base = data["base"], step=math.sqrt(2))
axA = axs[i*2]
cnt = axA.contour(
np.arange(data["left"], data["right"], data["scale"]),
np.arange(data["top"], data["bottom"], data["scale"]),
data["data"],
levels = levels, colors=colors[i], lw=3
)
lines.append(cnt.collections[0])
axA.set_xlim(-30, 10)
axA.set_ylim(-10, 10)
axA.set_aspect("equal")
axA.set_ylabel("x2 (mas)")
axA.set_xlabel("x1 (mas)")
axA = func.draw_beam(axA, data["beam_size"][0]*3600e3, data["beam_size"][1]*3600e3, data["beam_PA"], x1=-28, x2=-7)
## Image B
datas = []
for dataset in datasets:
if not hasattr(dataset, "filenameB"):
dataset.filenameB = dataset.filename
if not hasattr(dataset, "beam_size_B"):
dataset.beam_size_B = dataset.beam_size
if not hasattr(dataset, "beam_PA_B"):
dataset.beam_PA_B = dataset.beam_PA
if not hasattr(dataset, "rms_B"):
dataset.rms_B = dataset.rms
if not hasattr(dataset, "base_B"):
dataset.base_B = dataset.base
pixels = pf.getdata(dataset.filenameB)[0,0,:,:]
