def plot_isophotes(axA, axB, dataset, contour_color, label, edge_in_pixel, contour_base, new_grid_size,
title=False, legend=False):
if dataset == evn38:
hdr, raw = read.fits_data(dataset.filename)
A = make_subimage(raw, dataset.pos_pix, "A_core", edge_in_pixel, edge_in_pixel)
B = make_subimage(raw, dataset.pos_pix, "B_core", edge_in_pixel, edge_in_pixel)
levs_A = measure.contour_levels(dataset.rms, A.max(), base = contour_base, step=math.sqrt(2))
levs_B = measure.contour_levels(dataset.rms, B.max(), base = contour_base, step=math.sqrt(2))
if dataset == vlba or dataset == gvlbi:
hdr, A_raw = read.fits_data(dataset.filenameA)
hdr, B_raw = read.fits_data(dataset.filenameB)
A = make_subimage(A_raw, dataset.pos_A_pix, "A_core", edge_in_pixel, edge_in_pixel)
B = make_subimage(B_raw, dataset.pos_B_pix, "B_core", edge_in_pixel, edge_in_pixel)
levs_A = measure.contour_levels(dataset.rms_A, A.max(), base = contour_base, step=math.sqrt(2))
levs_B = measure.contour_levels(dataset.rms_B, B.max(), base = contour_base, step=math.sqrt(2))
A = rebin(A, new_grid_size)
B = rebin(B, new_grid_size)
A_X, A_Y, A = recenter_data(A, (100, 100))
B_X, B_Y, B = recenter_data(B, (100, 100))
mu_A = dataset.mu_A
mu_B = dataset.mu_B
mu = mu_A.mean() / mu_B.mean()
cntrs = axA.contour(A_X, A_Y, A, levels = levs_A, colors = contour_color, lw=1)
axB.contour(B_X, B_Y, B, levels = levs_B, colors = contour_color, lw=1)
if title:
axA.set_title("%s (image A)"%label)
axB.set_title("%s (image B)"%label)
if legend:
axB.legend([cntrs.collections[0]], ["%s"%label])
return cntrs, axA, axB
top = - center[1] * scale
right = left + pixels.shape[1] * scale
bottom = top + pixels.shape[0] * scale
datas.append({
"scale": scale,
"top": top,
"left": left,
"right": right,
"bottom": bottom,
"data": pixels,
"rms": dataset.rms_A,
"base": dataset.base_A
})
for i, data in enumerate(datas):
levels = measure.contour_levels(data["rms"], data["data"].max(), base = data["base"], step=math.sqrt(2))
cnt = axA.contourf(
np.arange(data["left"], data["right"], data["scale"]),
np.arange(data["top"], data["bottom"], data["scale"]),
data["data"],
levels = levels, colors=colors[i],
alpha = 0.5
)
lines.append(cnt.collections[0])
## Image B
datas = []
for dataset in datasets:
if not hasattr(dataset, "filenameB"):
dataset.filenameB = dataset.filename
if not hasattr(dataset, "rms_B"):