def fitplane(afile1, afile2, xfile1, xfile2, options):
xy, alpha1, sx, sy = readalpha(afile1)
xy, alpha2, sx, sy = readalpha(afile2)
alpha2 -= alpha1
alpha2 *= options.gain
if options.removespikes:
for m in range(ch):
# that's what you would like, but medfilt2d returns bad data
# for the edge (i.e., zero or random). Use a wrapper
# alpha2[:,:,m]= medfilt2d(alpha2[:,:,m], kernel_size=ks)
alpha2[:, :, m] = median_2D(alpha2[:, :, m],
kernel_size=options.median)
clip = options.clip
xd, yd, ch = shape(alpha2)
nr = (xd - 2 * clip) * (yd - 2 * clip)
x = xy[clip:xd - clip, clip:yd - clip, 0].reshape(nr)
y = xy[clip:xd - clip, clip:yd - clip, 1].reshape(nr)
shx = alpha2[clip:xd - clip, clip:yd - clip, 0].reshape(nr)
shy = alpha2[clip:xd - clip, clip:yd - clip, 1].reshape(nr)
if ch == 3:
defoc = alpha2[clip:xd - clip, clip:yd - clip, 2].mean()
else:
defoc = 0.0
ut = zeros((4, nr), float64)
k = 0
#for i in range(2):
# for j in range(2):
# ut[k,:] = x**i * y**j
# k += 1
ut[0, :] = ones(nr)
ut[1, :] = y
ut[2, :] = x
ut[3, :] = x * y
kk = inner(linalg.inv(inner(ut, ut)), ut.transpose())
kxx = inner(kk, shx)
kxy = inner(kk, shy)
X, Y = mgrid[0:sy, 0:sx]
fitx = int16(
(100 * (kxx[1] * X + kxx[2] * Y + kxx[3] * Y * X + kxx[0])).round())
fity = int16(
(100 * (kxy[1] * X + kxy[2] * Y + kxy[3] * Y * X + kxy[0])).round())
mm = max(abs(array([fitx.min(), fitx.max(), fity.min(), fity.max()])))
pyana.writeto(xfile1, pyana.getdata(xfile1) + fitx)
pyana.writeto(xfile2, pyana.getdata(xfile2) + fity)
# pyana.writeto(xfile1, pyana.getdata(xfile1)+fitx, comments=' ')
# pyana.writeto(xfile2, pyana.getdata(xfile2)+fity, comments=' ')
return mm, defoc
def _anaload(path): """ Load ana file using pyana. @param path File to load @return Data if successful, False otherwise. """ import pyana try: data = pyana.getdata(path) except: return False return data
def interpolate_fringe(stacked,
imean,
wav_path='wav.8542.f0',
do=1,
pca=[0],
edge=[0, -1]):
'''
Interpolate fringe from wing points onto entire line.
INPUT:
stacked : stacked cube from stack_cube()
imean : a 3d pol cube. Probably output of stack_cube()
wav : name of wav file
'''
print(wav_path)
wav = pa.getdata(wav_path)
we = (1.0 - wav / wav.max()) / 2
if pca[-1] <> 0:
#pick 2 first and last frames and do PCA on them.
stacked_shape = stacked.shape
print(stacked_shape)
print('Using PCA to interpolate fringes...')
p0, p1, p2, p3 = pca
if pca[-1] == 99: #use last frame
#we only apply this to S2 and S3
s2 = np.stack([
PCA(stacked[1, p0:p1], PCA_N=1),
PCA(stacked[1, p2:], PCA_N=1)
],
axis=0)
s3 = np.stack([
PCA(stacked[2, p0:p1], PCA_N=1),
PCA(stacked[2, p2:], PCA_N=1)
],
axis=0)
s0 = np.zeros_like(s2)
stot = np.stack([s0, s2, s3, s0], axis=0)
else:
s1 = np.stack(
[PCA(stacked[0, p0:p1], 0),
PCA(stacked[0, p2:p3], 0)], axis=0)
s2 = np.stack(
[PCA(stacked[1, p0:p1], 0),
PCA(stacked[1, p2:p3], 0)], axis=0)
s3 = np.stack(
[PCA(stacked[2, p0:p1], 0),
PCA(stacked[2, p2:p3], 0)], axis=0)
s4 = np.stack(
[PCA(stacked[3, p0:p1], 0),
PCA(stacked[3, p2:p3], 0)], axis=0)
stot = np.stack([s1, s2, s3, s4], axis=0)
fringe = np.zeros(stacked.shape)
for ii in range(wav.size):
fringe[1, ii, :, :] = (
stot[1, edge[0], :, :] * we[ii] / imean[0, edge[0]] +
(1.0 - we[ii]) * stot[1, edge[1], :, :] /
imean[0, edge[1]]) * imean[0, ii]
fringe[2, ii, :, :] = (
stot[2, edge[0], :, :] * we[ii] / imean[0, edge[0]] +
(1.0 - we[ii]) * stot[2, edge[1], :, :] /
imean[0, edge[1]]) * imean[0, ii]
#Take outer two frames (asssume to be flat save for fringes.) and then make a interpolated mean fringe as function of the wavelength.
else:
fringe = stacked * 0
for ii in range(wav.size):
fringe[1, ii, :, :] = (
stacked[1, edge[0], :, :] * we[ii] / imean[0, edge[0]] +
(1.0 - we[ii]) * stacked[1, edge[1], :, :] /
imean[0, edge[1]]) * imean[0, ii]
fringe[2, ii, :, :] = (
stacked[2, edge[0], :, :] * we[ii] / imean[0, edge[0]] +
(1.0 - we[ii]) * stacked[2, edge[1], :, :] /
imean[0, edge[1]]) * imean[0, ii]
print(fringe.shape)
if do:
stacked[1:3] = stacked[1:3] - fringe[1:3]
result = stacked
result_shape = result.shape
result_shape = np.append(1, result_shape)
result = result.reshape(result_shape)
return result
