def _peak_gauss_method(
i,
npix,
u,
v,
filt,
index_mask,
pixelsize,
innerpix,
innerpix_center,
fw_splodge=0.7,
hole_diam=0.8,
):
mf = np.zeros([npix, npix])
n_holes = index_mask.n_holes
l_B = np.sqrt(u**2 + v**2)
minbl = np.min(l_B) * filt[0]
if n_holes >= 15:
sampledisk_r = minbl / 2 / filt[0] * pixelsize * npix * 0.9
else:
sampledisk_r = minbl / 2.0 / filt[0] * pixelsize * npix * fw_splodge
xspot = float(np.round(v[i] * pixelsize * npix + npix / 2.0))
yspot = float(np.round(u[i] * pixelsize * npix + npix / 2.0))
mf = plot_circle(mf, xspot, yspot, sampledisk_r, display=False)
mf = np.roll(mf, npix // 2, axis=0)
mf = np.roll(mf, npix // 2, axis=1)
X = [np.arange(npix), np.arange(npix), 1]
splodge_fwhm = hole_diam / filt[0] * pixelsize * npix / 1.9
param = {
"A": 1,
"x0": -npix // 2 + yspot,
"y0": -npix // 2 + xspot,
"fwhm_x": splodge_fwhm,
"fwhm_y": splodge_fwhm,
"theta": 0,
}
gauss = gauss_2d_asym(X, param)
gauss = np.roll(gauss, npix // 2, axis=0)
gauss = np.roll(gauss, npix // 2, axis=1)
mfg = gauss / np.sum(gauss)
mf_gain_flat = mfg.ravel()
mf_gain_centered = norm_max(np.fft.fftshift(mfg).ravel())
mf_flat = norm_max(mf.ravel())
mf_centered = norm_max(np.fft.fftshift(mf).ravel())
mf_flat[innerpix] = 0.0
mf_gain_flat[innerpix] = 0.0
mf_centered[innerpix_center] = 0.0
mf_gain_centered[innerpix_center] = 0.0
mf = {
"flat": mf_flat,
"centered": mf_centered,
"gain_f": mf_gain_flat,
"gain_c": mf_gain_centered,
}
return dict2class(mf)
def _peak_gauss_method(i,
npix,
u,
v,
filt,
index_mask,
pixelsize,
innerpix,
innerpix_center,
fw_splodge=0.7,
hole_diam=0.8):
mf = np.zeros([npix, npix])
n_holes = index_mask.n_holes
l_B = np.sqrt(u**2 + v**2)
minbl = np.min(l_B) * filt[0]
if n_holes >= 15:
sampledisk_r = minbl / 2 / filt[0] * pixelsize * npix * 0.9
else:
sampledisk_r = minbl / 2. / \
filt[0] * pixelsize * npix * fw_splodge
xspot = float(np.round((v[i] * pixelsize * npix + npix / 2.)))
yspot = float(np.round((u[i] * pixelsize * npix + npix / 2.)))
mf = plot_circle(mf, xspot, yspot, sampledisk_r, display=False)
mf = np.roll(mf, npix // 2, axis=0)
mf = np.roll(mf, npix // 2, axis=1)
X = [np.arange(npix), np.arange(npix), 1]
splodge_fwhm = hole_diam / filt[0] * pixelsize * npix / 1.9
param = {
'A': 1,
'x0': -npix // 2 + yspot,
'y0': -npix // 2 + xspot,
'fwhm_x': splodge_fwhm,
'fwhm_y': splodge_fwhm,
'theta': 0
}
gauss = gauss_2d_asym(X, param)
gauss = np.roll(gauss, npix // 2, axis=0)
gauss = np.roll(gauss, npix // 2, axis=1)
mfg = gauss / np.sum(gauss)
mf_gain_flat = mfg.ravel()
mf_gain_centered = norm_max(np.fft.fftshift(mfg).ravel())
mf_flat = norm_max(mf.ravel())
mf_centered = norm_max(np.fft.fftshift(mf).ravel())
mf_flat[innerpix] = 0.
mf_gain_flat[innerpix] = 0.
mf_centered[innerpix_center] = 0.
mf_gain_centered[innerpix_center] = 0.
mf = {
'flat': mf_flat,
'centered': mf_centered,
'gain_f': mf_gain_flat,
'gain_c': mf_gain_centered
}
return dict2class(mf)
def tri_pix(array_size, sampledisk_r, verbose=True, display=True):
"""Compute all combination of triangle for a given splodge size"""
if array_size % 2 == 1:
cprint("\n! Warnings: image dimension must be even (%i)" % array_size, "red")
cprint("Possible triangle inside the splodge should be incorrect.\n", "red")
d = np.zeros([array_size, array_size])
d = plot_circle(d, array_size // 2, array_size // 2, sampledisk_r, display=False)
pvct_flat = np.where(d.ravel() > 0)
npx = len(pvct_flat[0])
for px1 in range(npx):
thispix1 = np.array(array_coords(pvct_flat[0][px1], array_size))
roll1 = np.roll(d, int(array_size // 2 - thispix1[0]), axis=0)
roll2 = np.roll(roll1, int(array_size // 2 - thispix1[1]), axis=1)
xcor_12 = d + roll2
valid_b12_vct = np.where(xcor_12.T.ravel() > 1)
thisntriv = len(valid_b12_vct[0])
thistrivct = np.zeros([3, thisntriv])
for px2 in range(thisntriv):
thispix2 = array_coords(valid_b12_vct[0][px2], array_size)
thispix3 = array_size * 1.5 - (thispix1 + thispix2)
bl3_px = thispix3[1] * array_size + (thispix3[0])
thistrivct[:, px2] = [pvct_flat[0][px1], valid_b12_vct[0][px2], bl3_px]
if px1 == 0:
l_pix1 = list(thistrivct[0, :])
l_pix2 = list(thistrivct[1, :])
l_pix3 = list(thistrivct[2, :])
else:
l_pix1.extend(list(thistrivct[0, :]))
l_pix2.extend(list(thistrivct[1, :]))
l_pix3.extend(list(thistrivct[2, :]))
closing_tri_pix = np.array([l_pix1, l_pix2, l_pix3]).astype(int)
n_trip = closing_tri_pix.shape[1]
if verbose:
print("Closing triangle in r = %2.1f: %i" % (sampledisk_r, n_trip))
cl_unique = clos_unique(closing_tri_pix)
c0 = array_size // 2
fw = 2 * sampledisk_r
if display:
import matplotlib.pyplot as plt
plt.figure(figsize=(5, 5))
plt.title(
"Splodge + unique triangle (tri = %i/%i, d = %i, r = %2.1f pix)"
% (cl_unique.shape[1], n_trip, array_size, sampledisk_r),
fontsize=10,
)
plt.imshow(d)
for i in range(cl_unique.shape[1]):
trip1 = cl_unique[:, i]
X, Y = array_coords(trip1, array_size)
X = list(X)
Y = list(Y)
X.append(X[0])
Y.append(Y[0])
plt.plot(X, Y, "-", lw=1)
plt.axis([c0 - fw, c0 + fw, c0 - fw, c0 + fw])
plt.tight_layout()
plt.show(block=False)
return closing_tri_pix