def test_distortions_ex1():
e_x1 = [-14.95369787, 88.60095332, 999.76814675, 2019.84941119]
e_y1 = [1202.73558767, 898.46492016, 192.1974284, -26.51887593]
x0 = [1, 100, 1000, 1990]
y0 = [1200, 900, 200, 5]
x1, y1 = exvp(x0, y0)
assert numpy.allclose(x1, e_x1)
assert numpy.allclose(y1, e_y1)
def test_distortions_ex1():
e_x1 = [-14.95369787, 88.60095332, 999.76814675, 2019.84941119]
e_y1 = [1202.73558767, 898.46492016, 192.1974284, -26.51887593]
x0 = [1, 100, 1000, 1990]
y0 = [1200, 900, 200, 5]
x1, y1 = exvp(x0, y0)
assert numpy.allclose(x1, e_x1)
assert numpy.allclose(y1, e_y1)
def test_distortions_ex2():
"""Inverse transformation, not very precise"""
x0 = [1, 100, 1000, 1990]
y0 = [1200, 900, 200, 5]
p_x1 = [16.20132521, 110.97939823, 1000.22549019, 1962.80728145]
p_y1 = [1197.39342201, 901.47856688, 207.58843519, 33.71359561]
x1, y1 = exvp(p_x1, p_y1)
assert numpy.allclose(x1, x0, rtol=2e-2)
assert numpy.allclose(y1, y0, rtol=2e-2)
def test_distortions_ex2():
"""Inverse transformation, not very precise"""
x0 = [1, 100, 1000, 1990]
y0 = [1200, 900, 200, 5]
p_x1 = [16.20132521, 110.97939823, 1000.22549019, 1962.80728145]
p_y1 = [1197.39342201, 901.47856688, 207.58843519, 33.71359561]
x1, y1 = exvp(p_x1, p_y1)
assert numpy.allclose(x1, x0, rtol=2e-2)
assert numpy.allclose(y1, y0, rtol=2e-2)
def compute_slits(self, hdulist, csu_conf):
self.logger.debug('finding borders of slits')
self.logger.debug('not strictly necessary...')
data = hdulist[0].data
self.logger.debug('dtype of data %s', data.dtype)
self.logger.debug('median filter (3x3)')
image_base = ndi.filters.median_filter(data, size=3)
# Cast as original type for skimage
self.logger.debug('casting image to unit16 (for skimage)')
iuint16 = np.iinfo(np.uint16)
image = np.clip(image_base, iuint16.min, iuint16.max).astype(np.uint16)
self.logger.debug('compute Sobel filter')
# FIXME: compute sob and sob_v is redundant
sob = filt.sobel(image)
self.save_intermediate_array(sob, 'sobel_image.fits')
sob_v = filt.sobel_v(image)
self.save_intermediate_array(sob_v, 'sobel_v_image.fits')
# Compute detector coordinates of bars
all_coords_virt = np.empty((110, 2))
all_coords_real = np.empty((110, 2))
# Origin of coordinates is 1
for bar in csu_conf.bars.values():
all_coords_virt[bar.idx - 1] = bar.xpos, bar.y0
# Origin of coordinates is 1 for this function
_x, _y = dist.exvp(all_coords_virt[:, 0], all_coords_virt[:, 1])
all_coords_real[:, 0] = _x
all_coords_real[:, 1] = _y
# FIXME: hardcoded value
h = 16
slit_h_virt = 16.242
slit_h_tol = 3
slits_bb = {}
mask1 = np.zeros_like(hdulist[0].data)
for idx in range(EMIR_NBARS):
lbarid = idx + 1
rbarid = lbarid + EMIR_NBARS
ref_x_l_v, ref_y_l_v = all_coords_virt[lbarid - 1]
ref_x_r_v, ref_y_r_v = all_coords_virt[rbarid - 1]
ref_x_l_d, ref_y_l_d = all_coords_real[lbarid - 1]
ref_x_r_d, ref_y_r_d = all_coords_real[rbarid - 1]
width_v = ref_x_r_v - ref_x_l_v
# width_d = ref_x_r_d - ref_x_l_d
if (ref_y_l_d >= 2047 + h) or (ref_y_l_d <= 1 - h):
# print('reference y position is outlimits, skipping')
continue
if width_v < 5:
# print('width is less than 5 pixels, skipping')
continue
plot = False
regionw = 12
px1 = coor_to_pix_1d(ref_x_l_d) - 1
px2 = coor_to_pix_1d(ref_x_r_d) - 1
prow = coor_to_pix_1d(ref_y_l_d) - 1
comp_l, comp_r = calc0(image, sob_v, prow, px1, px2, regionw, h=h,
plot=plot, lbarid=lbarid, rbarid=rbarid,
plot2=False)
if np.any(np.isnan([comp_l, comp_r])):
self.logger.warning("converting NaN value, border of=%d", idx + 1)
self.logger.warning("skipping bar=%d", idx + 1)
continue
elif comp_l > comp_r:
# Not refining
self.logger.warning("computed left border of=%d greater than right border", idx + 1)
comp2_l, comp2_r = px1, px2
else:
region2 = 5
px21 = coor_to_pix_1d(comp_l)
px22 = coor_to_pix_1d(comp_r)
comp2_l, comp2_r = calc0(image, sob_v, prow, px21, px22, region2,
refine=True,
plot=plot, lbarid=lbarid, rbarid=rbarid,
plot2=False)
if np.any(np.isnan([comp2_l, comp2_r])):
self.logger.warning("converting NaN value, border of=%d", idx + 1)
comp2_l, comp2_r = comp_l, comp_r
elif comp2_l > comp2_r:
# Not refining
self.logger.warning("computed left border of=%d greater than right border", idx + 1)
comp2_l, comp2_r = comp_l, comp_r
# print('slit', lbarid, '-', rbarid, comp_l, comp_r)
# print('pos1', comp_l, comp_r)
# print('pos2', comp2_l, comp2_r)
xpos1_virt, _ = dist.pvex(comp2_l + 1, ref_y_l_d)
xpos2_virt, _ = dist.pvex(comp2_r + 1, ref_y_r_d)
y1_virt = ref_y_l_v - slit_h_virt - slit_h_tol
y2_virt = ref_y_r_v + slit_h_virt + slit_h_tol
_, y1 = dist.exvp(xpos1_virt + 1, y1_virt)
_, y2 = dist.exvp(xpos2_virt + 1, y2_virt)
# print(comp2_l, comp2_r, y1 - 1, y2 - 1)
cbb = BoundingBox.from_coordinates(comp2_l, comp2_r, y1 - 1, y2 - 1)
slits_bb[lbarid] = cbb
mask1[cbb.slice] = lbarid
self.save_intermediate_array(mask1, 'mask_slit_computed.fits')
return slits_bb
def find_bars(hdulist,
bars_nominal_positions,
csupos,
dtur,
average_box_row_size=7,
average_box_col_size=21,
fit_peak_npoints=3,
median_filter_size=5,
logger=None):
logger.debug('filtering image')
# Processed array
arr_median = median_filtering(hdulist, median_filter_size)
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
logger.debug('DTU shift is %s', vec)
# and the table of approx positions of the slits
barstab = bars_nominal_positions
# Currently, we only use fields 0 and 2
# of the nominal positions file
# Number or rows used
# These other parameters cab be tuned also
bstart = 1
bend = 2047
logger.debug('ignoring columns outside %d - %d', bstart, bend - 1)
# extract a region to average
# wy = (average_box_row_size // 2)
# wx = (average_box_col_size // 2)
# logger.debug('extraction window is %d rows, %d cols', 2 * wy + 1, 2 * wx + 1)
# Fit the peak with these points
# wfit = 2 * (fit_peak_npoints // 2) + 1
# logger.debug('fit with %d points', wfit)
# Minimum threshold
threshold = 5 * EMIR_RON
# Savitsky and Golay (1964) filter to compute the X derivative
# scipy >= xx has a savgol_filter function
# for compatibility we do it manually
allpos = {}
slits = numpy.zeros((EMIR_NBARS, 8), dtype='float')
logger.info('find peaks in derivative image')
for ks in [3, 5, 7, 9]:
logger.debug('kernel size is %d', ks)
# S and G kernel for derivative
kw = ks * (ks * ks - 1) / 12.0
coeffs_are = -numpy.arange((1 - ks) // 2, (ks - 1) // 2 + 1) / kw
logger.debug('kernel weights are %s', coeffs_are)
logger.debug('derive image in X direction')
arr_deriv = convolve1d(arr_median, coeffs_are, axis=-1)
# self.save_intermediate_array(arr_deriv, 'deriv_image_k%d.fits' % ks)
# Axis 0 is
#
# logger.debug('derive image in Y direction (with kernel=3)')
# arr_deriv_alt = convolve1d(arr_median_alt, ypos3_kernel, axis=0)
positions = []
logger.info('using bar parameters')
for idx in range(EMIR_NBARS):
params_l = barstab[idx]
params_r = barstab[idx + EMIR_NBARS]
lbarid = int(params_l[0])
# CSUPOS for this bar
rbarid = lbarid + EMIR_NBARS
current_csupos_l = csupos[lbarid - 1]
current_csupos_r = csupos[rbarid - 1]
logger.debug('CSUPOS for bar %d is %f', lbarid, current_csupos_l)
logger.debug('CSUPOS for bar %d is %f', rbarid, current_csupos_r)
ref_y_coor_virt = params_l[1] # Do I need to add vec[1]?
ref_x_l_coor_virt = params_l[3] + current_csupos_l * params_l[2]
ref_x_r_coor_virt = params_r[3] + current_csupos_r * params_r[2]
# Transform to REAL..
ref_x_l_coor, ref_y_l_coor = dist.exvp(ref_x_l_coor_virt,
ref_y_coor_virt)
ref_x_r_coor, ref_y_r_coor = dist.exvp(ref_x_r_coor_virt,
ref_y_coor_virt)
# FIXME: check if DTU has to be applied
# ref_y_coor = ref_y_coor + vec[1]
prow = coor_to_pix_1d(ref_y_l_coor) - 1
fits_row = prow + 1 # FITS pixel index
logger.debug('looking for bars with ids %d - %d', lbarid, rbarid)
logger.debug('ref Y virtual position is %7.2f', ref_y_coor_virt)
logger.debug('ref X virtual positions are %7.2f %7.2f',
ref_x_l_coor_virt, ref_x_r_coor_virt)
logger.debug('ref X positions are %7.2f %7.2f', ref_x_l_coor,
ref_x_r_coor)
logger.debug('ref Y positions are %7.2f %7.2f', ref_y_l_coor,
ref_y_r_coor)
# if ref_y_coor is outlimits, skip this bar
# ref_y_coor is in FITS format
if (ref_y_l_coor >= 2047 + 16) or (ref_y_l_coor <= 1 - 16):
logger.debug('reference y position is outlimits, skipping')
positions.append(
[lbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
positions.append(
[rbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
continue
# minimal width of the slit
minwidth = 0.9
if abs(ref_x_l_coor_virt - ref_x_r_coor_virt) < minwidth:
# FIXME: if width < minwidth fit peak in image
logger.debug('slit is less than %d virt pixels, skipping',
minwidth)
positions.append(
[lbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
positions.append(
[rbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
continue
# Left bar
# Dont add +1 to virtual pixels
logger.debug('measure left border (%d)', lbarid)
regionw = 10
bstart1 = coor_to_pix_1d(ref_x_l_coor - regionw)
bend1 = coor_to_pix_1d(ref_x_l_coor + regionw) + 1
centery, centery_virt, xpos1, xpos1_virt, fwhm, st = char_bar_peak_l(
arr_deriv, prow, bstart1, bend1, threshold)
insert1 = [
lbarid, centery + 1, centery_virt, fits_row, xpos1 + 1,
xpos1_virt, fwhm, st
]
positions.append(insert1)
# Right bar
# Dont add +1 to virtual pixels
logger.debug('measure rigth border (%d)', rbarid)
bstart2 = coor_to_pix_1d(ref_x_r_coor - regionw)
bend2 = coor_to_pix_1d(ref_x_r_coor + regionw) + 1
centery, centery_virt, xpos2, xpos2_virt, fwhm, st = char_bar_peak_r(
arr_deriv, prow, bstart2, bend2, threshold)
# This centery/centery_virt should be equal to ref_y_coor_virt
insert2 = [
rbarid, centery + 1, centery_virt, fits_row, xpos2 + 1,
xpos2_virt, fwhm, st
]
positions.append(insert2)
# FIXME: hardcoded value
y1_virt = ref_y_coor_virt - 16.242
y2_virt = ref_y_coor_virt + 16.242
_, y1 = dist.exvp(xpos1_virt + 1, y1_virt + 1)
_, y2 = dist.exvp(xpos2_virt + 1, y2_virt + 1)
# Update positions
msg = 'bar %d, centroid-y %9.4f centroid-y virt %9.4f, ' \
'row %d, x-pos %9.4f x-pos virt %9.4f, FWHM %6.3f, status %d'
logger.debug(msg, *positions[-2])
logger.debug(msg, *positions[-1])
if ks == 5:
slits[lbarid - 1] = numpy.array(
[xpos1, y2, xpos2, y2, xpos2, y1, xpos1, y1])
# FITS coordinates
slits[lbarid - 1] += 1.0
logger.debug('inserting bars %d-%d into "slits"', lbarid,
rbarid)
allpos[ks] = numpy.asarray(
positions, dtype='float') # GCS doesn't like lists of lists
return allpos, slits
def find_bars(hdulist, bars_nominal_positions, csupos, dtur,
average_box_row_size=7, average_box_col_size=21, fit_peak_npoints=3,
median_filter_size=5, logger=None):
logger.debug('filtering image')
# Processed array
arr_median = median_filtering(hdulist, median_filter_size)
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
logger.debug('DTU shift is %s', vec)
# and the table of approx positions of the slits
barstab = bars_nominal_positions
# Currently, we only use fields 0 and 2
# of the nominal positions file
# Number or rows used
# These other parameters cab be tuned also
bstart = 1
bend = 2047
logger.debug('ignoring columns outside %d - %d', bstart, bend - 1)
# extract a region to average
# wy = (average_box_row_size // 2)
# wx = (average_box_col_size // 2)
# logger.debug('extraction window is %d rows, %d cols', 2 * wy + 1, 2 * wx + 1)
# Fit the peak with these points
# wfit = 2 * (fit_peak_npoints // 2) + 1
# logger.debug('fit with %d points', wfit)
# Minimum threshold
threshold = 5 * EMIR_RON
# Savitsky and Golay (1964) filter to compute the X derivative
# scipy >= xx has a savgol_filter function
# for compatibility we do it manually
allpos = {}
slits = numpy.zeros((EMIR_NBARS, 8), dtype='float')
logger.info('find peaks in derivative image')
for ks in [3, 5, 7, 9]:
logger.debug('kernel size is %d', ks)
# S and G kernel for derivative
kw = ks * (ks * ks - 1) / 12.0
coeffs_are = -numpy.arange((1 - ks) // 2, (ks - 1) // 2 + 1) / kw
logger.debug('kernel weights are %s', coeffs_are)
logger.debug('derive image in X direction')
arr_deriv = convolve1d(arr_median, coeffs_are, axis=-1)
# self.save_intermediate_array(arr_deriv, 'deriv_image_k%d.fits' % ks)
# Axis 0 is
#
# logger.debug('derive image in Y direction (with kernel=3)')
# arr_deriv_alt = convolve1d(arr_median_alt, ypos3_kernel, axis=0)
positions = []
logger.info('using bar parameters')
for idx in range(EMIR_NBARS):
params_l = barstab[idx]
params_r = barstab[idx + EMIR_NBARS]
lbarid = int(params_l[0])
# CSUPOS for this bar
rbarid = lbarid + EMIR_NBARS
current_csupos_l = csupos[lbarid - 1]
current_csupos_r = csupos[rbarid - 1]
logger.debug('CSUPOS for bar %d is %f', lbarid, current_csupos_l)
logger.debug('CSUPOS for bar %d is %f', rbarid, current_csupos_r)
ref_y_coor_virt = params_l[1] # Do I need to add vec[1]?
ref_x_l_coor_virt = params_l[3] + current_csupos_l * params_l[2]
ref_x_r_coor_virt = params_r[3] + current_csupos_r * params_r[2]
# Transform to REAL..
ref_x_l_coor, ref_y_l_coor = dist.exvp(ref_x_l_coor_virt, ref_y_coor_virt)
ref_x_r_coor, ref_y_r_coor = dist.exvp(ref_x_r_coor_virt, ref_y_coor_virt)
# FIXME: check if DTU has to be applied
# ref_y_coor = ref_y_coor + vec[1]
prow = coor_to_pix_1d(ref_y_l_coor) - 1
fits_row = prow + 1 # FITS pixel index
logger.debug('looking for bars with ids %d - %d', lbarid, rbarid)
logger.debug('ref Y virtual position is %7.2f', ref_y_coor_virt)
logger.debug('ref X virtual positions are %7.2f %7.2f', ref_x_l_coor_virt, ref_x_r_coor_virt)
logger.debug('ref X positions are %7.2f %7.2f', ref_x_l_coor, ref_x_r_coor)
logger.debug('ref Y positions are %7.2f %7.2f', ref_y_l_coor, ref_y_r_coor)
# if ref_y_coor is outlimits, skip this bar
# ref_y_coor is in FITS format
if (ref_y_l_coor >= 2047 + 16) or (ref_y_l_coor <= 1 - 16):
logger.debug('reference y position is outlimits, skipping')
positions.append([lbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
positions.append([rbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
continue
# minimal width of the slit
minwidth = 0.9
if abs(ref_x_l_coor_virt - ref_x_r_coor_virt) < minwidth:
# FIXME: if width < minwidth fit peak in image
logger.debug('slit is less than %d virt pixels, skipping', minwidth)
positions.append([lbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
positions.append([rbarid, fits_row, fits_row, fits_row, 1, 1, 0, 3])
continue
# Left bar
# Dont add +1 to virtual pixels
logger.debug('measure left border (%d)', lbarid)
regionw = 10
bstart1 = coor_to_pix_1d(ref_x_l_coor - regionw)
bend1 = coor_to_pix_1d(ref_x_l_coor + regionw) + 1
centery, centery_virt, xpos1, xpos1_virt, fwhm, st = char_bar_peak_l(arr_deriv,
prow, bstart1, bend1,
threshold)
insert1 = [lbarid, centery + 1, centery_virt, fits_row, xpos1 + 1, xpos1_virt, fwhm, st]
positions.append(insert1)
# Right bar
# Dont add +1 to virtual pixels
logger.debug('measure rigth border (%d)', rbarid)
bstart2 = coor_to_pix_1d(ref_x_r_coor - regionw)
bend2 = coor_to_pix_1d(ref_x_r_coor + regionw) + 1
centery, centery_virt, xpos2, xpos2_virt, fwhm, st = char_bar_peak_r(arr_deriv, prow, bstart2, bend2,
threshold)
# This centery/centery_virt should be equal to ref_y_coor_virt
insert2 = [rbarid, centery + 1, centery_virt, fits_row, xpos2 + 1, xpos2_virt, fwhm, st]
positions.append(insert2)
# FIXME: hardcoded value
y1_virt = ref_y_coor_virt - 16.242
y2_virt = ref_y_coor_virt + 16.242
_, y1 = dist.exvp(xpos1_virt + 1, y1_virt + 1)
_, y2 = dist.exvp(xpos2_virt + 1, y2_virt + 1)
# Update positions
msg = 'bar %d, centroid-y %9.4f centroid-y virt %9.4f, ' \
'row %d, x-pos %9.4f x-pos virt %9.4f, FWHM %6.3f, status %d'
logger.debug(msg, *positions[-2])
logger.debug(msg, *positions[-1])
if ks == 5:
slits[lbarid - 1] = numpy.array([xpos1, y2, xpos2, y2, xpos2, y1, xpos1, y1])
# FITS coordinates
slits[lbarid - 1] += 1.0
logger.debug('inserting bars %d-%d into "slits"', lbarid, rbarid)
allpos[ks] = numpy.asarray(positions, dtype='float') # GCS doesn't like lists of lists
return allpos, slits