def compute_fw_at_frac_max_1d_simple(Y, xc, X=None, f=0.5):
"""Compute the full width at fraction f of the maximum"""
yy = np.asarray(Y)
if yy.ndim != 1:
raise ValueError('array must be 1-d')
if yy.size == 0:
raise ValueError('array is empty')
if X is None:
xx = np.arange(yy.shape[0])
else:
xx = X
xpix = coor_to_pix_1d(xc - xx[0])
try:
peak = yy[xpix]
except IndexError:
raise ValueError('peak is out of array')
fwhm_x, _codex, _msgx = compute_fwhm_1d(xx, yy - f * peak, xc, xpix)
return peak, fwhm_x
def _locate_bar_gen(icut, epos, transform1, transform2):
"""Generic function for the fine position of the CSU"""
epos_pix = coor_to_pix_1d(epos)
# transform ->
epos_pix_s = transform1(epos_pix)
icut2 = transform2(icut)
#
try:
res = position_half_h(icut2, epos_pix_s)
xint_s, next_peak_s, wpos1_s, wpos2_s, background_level, half_height = res
#
xint = transform1(xint_s)
#
epos_f = xint
error = 0
except ValueError:
error = 2
epos_f = epos
return epos_pix, epos_f, error
def _locate_bar_gen(icut, epos, transform1, transform2):
"""Generic function for the fine position of the CSU"""
epos_pix = coor_to_pix_1d(epos)
# transform ->
epos_pix_s = transform1(epos_pix)
icut2 = transform2(icut)
#
try:
res = position_half_h(icut2, epos_pix_s)
xint_s, next_peak_s, wpos1_s, wpos2_s, background_level, half_height = res
#
xint = transform1(xint_s)
#
epos_f = xint
error = 0
except ValueError:
error = 2
epos_f = epos
return epos_pix, epos_f, error
def compute_fwhm_2d_simple(img, xc, yc):
X = np.arange(0, img.shape[1], 1.0)
Y = np.arange(0, img.shape[0], 1.0)
xpix = coor_to_pix_1d(xc - X[0])
ypix = coor_to_pix_1d(yc - Y[0])
peak = img[ypix, xpix]
res11 = img[ypix, :]
res22 = img[:, xpix]
fwhm_x, _codex, _msgx = compute_fwhm_1d(X, res11 - 0.5 * peak, xc, xpix)
fwhm_y, _codey, _msgy = compute_fwhm_1d(Y, res22 - 0.5 * peak, yc, ypix)
return peak, fwhm_x, fwhm_y
def compute_fwhm_2d_spline(img, xc, yc):
Y = np.arange(0.0, img.shape[1], 1.0)
X = np.arange(0.0, img.shape[0], 1.0)
xpix = coor_to_pix_1d(xc)
ypix = coor_to_pix_1d(yc)
# The image is already cropped
bb = itpl.RectBivariateSpline(X, Y, img)
# We assume that the peak is in the center...
peak = bb(xc, yc)[0, 0]
U = X
V = bb.ev(U, [yc for _ in U]) - 0.5 * peak
fwhm_x, _codex, _msgx = compute_fwhm_1d(U, V, yc, ypix)
U = Y
V = bb.ev([xc for _ in U], U) - 0.5 * peak
fwhm_y, _codey, _msgy = compute_fwhm_1d(U, V, xc, xpix)
return peak, fwhm_x, fwhm_y
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 run(self, rinput):
self.logger.info('starting processing for bars detection')
flow = self.init_filters(rinput)
hdulist = basic_processing_with_combination(rinput, flow=flow)
hdr = hdulist[0].header
self.set_base_headers(hdr)
try:
rotang = hdr['ROTANG']
tsutc1 = hdr['TSUTC1']
dtub, dtur = datamodel.get_dtur_from_header(hdr)
csupos = datamodel.get_csup_from_header(hdr)
csusens = datamodel.get_cs_from_header(hdr)
except KeyError as error:
self.logger.error(error)
raise numina.exceptions.RecipeError(error)
self.logger.debug('finding bars')
# Processed array
arr = hdulist[0].data
# Median filter of processed array (two times)
mfilter_size = rinput.median_filter_size
self.logger.debug('median filtering X, %d columns', mfilter_size)
arr_median = median_filter(arr, size=(1, mfilter_size))
self.logger.debug('median filtering X, %d rows', mfilter_size)
arr_median = median_filter(arr_median, size=(mfilter_size, 1))
# Median filter of processed array (two times) in the other direction
# for Y coordinates
self.logger.debug('median filtering Y, %d rows', mfilter_size)
arr_median_alt = median_filter(arr, size=(mfilter_size, 1))
self.logger.debug('median filtering Y, %d columns', mfilter_size)
arr_median_alt = median_filter(arr_median_alt, size=(1, mfilter_size))
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
self.logger.debug('DTU shift is %s', vec)
# and the table of approx positions of the slits
barstab = rinput.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
self.logger.debug('ignoring columns outside %d - %d',bstart, bend-1)
# extract a region to average
wy = (rinput.average_box_row_size // 2)
wx = (rinput.average_box_col_size // 2)
self.logger.debug('extraction window is %d rows, %d cols',2*wy+1, 2*wx+1)
# Fit the peak with these points
wfit = 2 * (rinput.fit_peak_npoints // 2) + 1
self.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 = {}
ypos3_kernel = None
slits = numpy.zeros((EMIR_NBARS, 8), dtype='float')
self.logger.info('start finding bars')
for ks in [3, 5, 7, 9]:
self.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
if ks == 3:
ypos3_kernel = coeffs_are
self.logger.debug('kernel weights are %s', coeffs_are)
self.logger.debug('derive image in X direction')
arr_deriv = convolve1d(arr_median, coeffs_are, axis=-1)
# Axis 0 is
#
self.logger.debug('derive image in Y direction (with kernel=3)')
arr_deriv_alt = convolve1d(arr_median_alt, ypos3_kernel, axis=0)
positions = []
for coords in barstab:
lbarid = int(coords[0])
rbarid = lbarid + EMIR_NBARS
ref_y_coor = coords[1] + vec[1]
poly_coeffs = coords[2:]
prow = coor_to_pix_1d(ref_y_coor) - 1
fits_row = prow + 1 # FITS pixel index
# A function that returns the center of the bar
# given its X position
def center_of_bar(x):
# Pixel values are 0-based
return polyval(x+1-vec[0], poly_coeffs) + vec[1] - 1
self.logger.debug('looking for bars with ids %d - %d', lbarid, rbarid)
self.logger.debug('reference y position is Y %7.2f', ref_y_coor)
# if ref_y_coor is outlimits, skip this bar
# ref_y_coor is in FITS format
if (ref_y_coor >= 2047) or (ref_y_coor <= 1):
self.logger.debug('reference y position is outlimits, skipping')
positions.append([lbarid, fits_row, fits_row, 1, 0, 3])
positions.append([rbarid, fits_row, fits_row, 1, 0, 3])
continue
# Left bar
self.logger.debug('measure left border (%d)', lbarid)
centery, xpos, fwhm, st = char_bar_peak_l(arr_deriv, prow, bstart, bend, threshold,
center_of_bar, wx=wx, wy=wy, wfit=wfit)
xpos1 = xpos
positions.append([lbarid, centery+1, fits_row, xpos+1, fwhm, st])
# Right bar
self.logger.debug('measure rigth border (%d)', rbarid)
centery, xpos, fwhm, st = char_bar_peak_r(arr_deriv, prow, bstart, bend, threshold,
center_of_bar, wx=wx, wy=wy, wfit=wfit)
positions.append([rbarid, centery+1, fits_row, xpos+1, fwhm, st])
xpos2 = xpos
#
if st == 0:
self.logger.debug('measure top-bottom borders')
try:
y1, y2, statusy = char_bar_height(arr_deriv_alt, xpos1, xpos2, centery, threshold,
wh=35, wfit=wfit)
except Exception as error:
self.logger.warning('Error computing height: %s', error)
statusy = 44
if statusy in [0, 40]:
# Main border is detected
positions[-1][1] = y2 + 1
positions[-2][1] = y2 + 1
else:
# Update status
positions[-1][-1] = 4
positions[-2][-1] = 4
else:
self.logger.debug('slit is not complete')
y1, y2 = 0, 0
# Update positions
self.logger.debug('bar %d centroid-y %9.4f, row %d x-pos %9.4f, FWHM %6.3f, status %d', *positions[-2])
self.logger.debug('bar %d centroid-y %9.4f, row %d x-pos %9.4f, FWHM %6.3f, status %d', *positions[-1])
if ks == 5:
slits[lbarid - 1] = [xpos1, y2, xpos2, y2, xpos2, y1, xpos1, y1]
# FITS coordinates
slits[lbarid - 1] += 1.0
self.logger.debug('inserting bars %d-%d into "slits"', lbarid, rbarid)
allpos[ks] = numpy.asarray(positions, dtype='float') # GCS doesn't like lists of lists
self.logger.debug('end finding bars')
result = self.create_result(frame=hdulist,
slits=slits,
positions9=allpos[9],
positions7=allpos[7],
positions5=allpos[5],
positions3=allpos[3],
DTU=dtub,
ROTANG=rotang,
TSUTC1=tsutc1,
csupos=csupos,
csusens=csusens,
)
return result
def run(self, rinput):
logger = logging.getLogger('numina.recipes.emir')
logger.info('starting processing for bars detection')
flow = self.init_filters(rinput)
hdulist = basic_processing_with_combination(rinput, flow=flow)
hdr = hdulist[0].header
self.set_base_headers(hdr)
try:
rotang = hdr['ROTANG']
dtub, dtur = datamodel.get_dtur_from_header(hdr)
csupos = datamodel.get_csup_from_header(hdr)
csusens = datamodel.get_cs_from_header(hdr)
except KeyError as error:
logger.error(error)
raise numina.exceptions.RecipeError(error)
logger.debug('finding bars')
arr = hdulist[0].data
# Median filter
logger.debug('median filtering')
mfilter_size = rinput.median_filter_size
arr_median = median_filter(arr, size=mfilter_size)
# Image is mapped between 0 and 1
# for the full range [0: 2**16]
logger.debug('image scaling to 0-1')
arr_grey = normalize_raw(arr_median)
# Find borders
logger.debug('find borders')
canny_sigma = rinput.canny_sigma
# These threshols corespond roughly with
# value x (2**16 - 1)
high_threshold = rinput.canny_high_threshold
low_threshold = rinput.canny_low_threshold
edges = canny(arr_grey,
sigma=canny_sigma,
high_threshold=high_threshold,
low_threshold=low_threshold)
# Number or rows used
# These other parameters cab be tuned also
total = 5
maxdist = 1.0
bstart = 100
bend = 1900
positions = []
nt = total // 2
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
logger.debug('DTU shift is %s', vec)
# Based on the 'edges image'
# and the table of approx positions of the slits
barstab = rinput.bars_nominal_positions
# Currently, we only use fields 0 and 2
# of the nominal positions file
for coords in barstab:
lbarid = int(coords[0])
rbarid = lbarid + 55
ref_y_coor = coords[2] + vec[1]
prow = coor_to_pix_1d(ref_y_coor) - 1
fits_row = prow + 1 # FITS pixel index
logger.debug('looking for bars with ids %d - %d', lbarid, rbarid)
logger.debug('reference y position is Y %7.2f', ref_y_coor)
# Find the position of each bar
bpos = find_position(edges, prow, bstart, bend, total)
nbars_found = len(bpos)
# If no bar is found, append and empty token
if nbars_found == 0:
logger.debug('bars %d, %d not found at row %d', lbarid, rbarid,
fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
elif nbars_found == 2:
# Order values by increasing X
centl, centr = sorted(bpos, key=lambda cen: cen[0])
c1 = centl[0]
c2 = centr[0]
logger.debug('bars found at row %d between %7.2f - %7.2f',
fits_row, c1, c2)
# Compute FWHM of the collapsed profile
cslit = arr_grey[prow - nt:prow + nt + 1, :]
pslit = cslit.mean(axis=0)
# Add 1 to return FITS coordinates
epos, epos_f, error = locate_bar_l(pslit, c1)
thisres1 = lbarid, fits_row, epos + 1, epos_f + 1, error
epos, epos_f, error = locate_bar_r(pslit, c2)
thisres2 = rbarid, fits_row, epos + 1, epos_f + 1, error
elif nbars_found == 1:
logger.warning(
'only 1 edge found at row %d, not yet implemented',
fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
else:
logger.warning(
'3 or more edges found at row %d, not yet implemented',
fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
positions.append(thisres1)
positions.append(thisres2)
logger.debug('end finding bars')
result = self.create_result(
frame=hdulist,
positions=positions,
DTU=dtub,
ROTANG=rotang,
csupos=csupos,
csusens=csusens,
param_median_filter_size=rinput.median_filter_size,
param_canny_high_threshold=rinput.canny_high_threshold,
param_canny_low_threshold=rinput.canny_low_threshold)
return result
def run(self, rinput):
logger = logging.getLogger('numina.recipes.emir')
logger.info('starting processing for bars detection')
flow = self.init_filters(rinput)
hdulist = basic_processing_with_combination(rinput, flow=flow)
hdr = hdulist[0].header
self.set_base_headers(hdr)
try:
rotang = hdr['ROTANG']
dtub, dtur = datamodel.get_dtur_from_header(hdr)
csupos = datamodel.get_csup_from_header(hdr)
csusens = datamodel.get_cs_from_header(hdr)
except KeyError as error:
logger.error(error)
raise numina.exceptions.RecipeError(error)
logger.debug('finding bars')
arr = hdulist[0].data
# Median filter
logger.debug('median filtering')
mfilter_size = rinput.median_filter_size
arr_median = median_filter(arr, size=mfilter_size)
# Image is mapped between 0 and 1
# for the full range [0: 2**16]
logger.debug('image scaling to 0-1')
arr_grey = normalize_raw(arr_median)
# Find borders
logger.debug('find borders')
canny_sigma = rinput.canny_sigma
# These threshols corespond roughly with
# value x (2**16 - 1)
high_threshold = rinput.canny_high_threshold
low_threshold = rinput.canny_low_threshold
edges = canny(arr_grey, sigma=canny_sigma,
high_threshold=high_threshold,
low_threshold=low_threshold)
# Number or rows used
# These other parameters cab be tuned also
total = 5
maxdist = 1.0
bstart = 100
bend = 1900
positions = []
nt = total // 2
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
logger.debug('DTU shift is %s', vec)
# Based on the 'edges image'
# and the table of approx positions of the slits
barstab = rinput.bars_nominal_positions
# Currently, we only use fields 0 and 2
# of the nominal positions file
for coords in barstab:
lbarid = int(coords[0])
rbarid = lbarid + 55
ref_y_coor = coords[2] + vec[1]
prow = coor_to_pix_1d(ref_y_coor) - 1
fits_row = prow + 1 # FITS pixel index
logger.debug('looking for bars with ids %d - %d', lbarid, rbarid)
logger.debug('reference y position is Y %7.2f', ref_y_coor)
# Find the position of each bar
bpos = find_position(edges, prow, bstart, bend, total)
nbars_found = len(bpos)
# If no bar is found, append and empty token
if nbars_found == 0:
logger.debug('bars %d, %d not found at row %d', lbarid, rbarid, fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
elif nbars_found == 2:
# Order values by increasing X
centl, centr = sorted(bpos, key=lambda cen: cen[0])
c1 = centl[0]
c2 = centr[0]
logger.debug('bars found at row %d between %7.2f - %7.2f', fits_row, c1, c2)
# Compute FWHM of the collapsed profile
cslit = arr_grey[prow-nt:prow+nt+1,:]
pslit = cslit.mean(axis=0)
# Add 1 to return FITS coordinates
epos, epos_f, error = locate_bar_l(pslit, c1)
thisres1 = lbarid, fits_row, epos + 1, epos_f + 1, error
epos, epos_f, error = locate_bar_r(pslit, c2)
thisres2 = rbarid, fits_row, epos + 1, epos_f + 1, error
elif nbars_found == 1:
logger.warning('only 1 edge found at row %d, not yet implemented', fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
else:
logger.warning('3 or more edges found at row %d, not yet implemented', fits_row)
thisres1 = (lbarid, fits_row, 0, 0, 1)
thisres2 = (rbarid, fits_row, 0, 0, 1)
positions.append(thisres1)
positions.append(thisres2)
logger.debug('end finding bars')
result = self.create_result(frame=hdulist,
positions=positions,
DTU=dtub,
ROTANG=rotang,
csupos=csupos,
csusens=csusens,
param_median_filter_size=rinput.median_filter_size,
param_canny_high_threshold=rinput.canny_high_threshold,
param_canny_low_threshold=rinput.canny_low_threshold
)
return result
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 run(self, rinput):
self.logger.info('starting processing for bars detection')
flow = self.init_filters(rinput)
hdulist = basic_processing_with_combination(rinput, flow=flow)
hdr = hdulist[0].header
self.set_base_headers(hdr)
try:
rotang = hdr['ROTANG']
tsutc1 = hdr['TSUTC1']
dtub, dtur = datamodel.get_dtur_from_header(hdr)
csupos = datamodel.get_csup_from_header(hdr)
csusens = datamodel.get_cs_from_header(hdr)
except KeyError as error:
self.logger.error(error)
raise numina.exceptions.RecipeError(error)
self.logger.debug('finding bars')
# Processed array
arr = hdulist[0].data
# Median filter of processed array (two times)
mfilter_size = rinput.median_filter_size
self.logger.debug('median filtering X, %d columns', mfilter_size)
arr_median = median_filter(arr, size=(1, mfilter_size))
self.logger.debug('median filtering X, %d rows', mfilter_size)
arr_median = median_filter(arr_median, size=(mfilter_size, 1))
# Median filter of processed array (two times) in the other direction
# for Y coordinates
self.logger.debug('median filtering Y, %d rows', mfilter_size)
arr_median_alt = median_filter(arr, size=(mfilter_size, 1))
self.logger.debug('median filtering Y, %d columns', mfilter_size)
arr_median_alt = median_filter(arr_median_alt, size=(1, mfilter_size))
xfac = dtur[0] / EMIR_PIXSCALE
yfac = -dtur[1] / EMIR_PIXSCALE
vec = [yfac, xfac]
self.logger.debug('DTU shift is %s', vec)
# and the table of approx positions of the slits
barstab = rinput.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
self.logger.debug('ignoring columns outside %d - %d', bstart, bend - 1)
# extract a region to average
wy = (rinput.average_box_row_size // 2)
wx = (rinput.average_box_col_size // 2)
self.logger.debug('extraction window is %d rows, %d cols', 2 * wy + 1,
2 * wx + 1)
# Fit the peak with these points
wfit = 2 * (rinput.fit_peak_npoints // 2) + 1
self.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 = {}
ypos3_kernel = None
slits = numpy.zeros((EMIR_NBARS, 8), dtype='float')
self.logger.info('start finding bars')
for ks in [3, 5, 7, 9]:
self.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
if ks == 3:
ypos3_kernel = coeffs_are
self.logger.debug('kernel weights are %s', coeffs_are)
self.logger.debug('derive image in X direction')
arr_deriv = convolve1d(arr_median, coeffs_are, axis=-1)
# Axis 0 is
#
self.logger.debug('derive image in Y direction (with kernel=3)')
arr_deriv_alt = convolve1d(arr_median_alt, ypos3_kernel, axis=0)
positions = []
for coords in barstab:
lbarid = int(coords[0])
rbarid = lbarid + EMIR_NBARS
ref_y_coor = coords[1] + vec[1]
poly_coeffs = coords[2:]
prow = coor_to_pix_1d(ref_y_coor) - 1
fits_row = prow + 1 # FITS pixel index
# A function that returns the center of the bar
# given its X position
def center_of_bar(x):
# Pixel values are 0-based
return polyval(x + 1 - vec[0], poly_coeffs) + vec[1] - 1
self.logger.debug('looking for bars with ids %d - %d', lbarid,
rbarid)
self.logger.debug('reference y position is Y %7.2f',
ref_y_coor)
# if ref_y_coor is outlimits, skip this bar
# ref_y_coor is in FITS format
if (ref_y_coor >= 2047) or (ref_y_coor <= 1):
self.logger.debug(
'reference y position is outlimits, skipping')
positions.append([lbarid, fits_row, fits_row, 1, 0, 3])
positions.append([rbarid, fits_row, fits_row, 1, 0, 3])
continue
# Left bar
self.logger.debug('measure left border (%d)', lbarid)
centery, xpos, fwhm, st = char_bar_peak_l(arr_deriv,
prow,
bstart,
bend,
threshold,
center_of_bar,
wx=wx,
wy=wy,
wfit=wfit)
xpos1 = xpos
positions.append(
[lbarid, centery + 1, fits_row, xpos + 1, fwhm, st])
# Right bar
self.logger.debug('measure rigth border (%d)', rbarid)
centery, xpos, fwhm, st = char_bar_peak_r(arr_deriv,
prow,
bstart,
bend,
threshold,
center_of_bar,
wx=wx,
wy=wy,
wfit=wfit)
positions.append(
[rbarid, centery + 1, fits_row, xpos + 1, fwhm, st])
xpos2 = xpos
#
if st == 0:
self.logger.debug('measure top-bottom borders')
try:
y1, y2, statusy = char_bar_height(arr_deriv_alt,
xpos1,
xpos2,
centery,
threshold,
wh=35,
wfit=wfit)
except Exception as error:
self.logger.warning('Error computing height: %s',
error)
statusy = 44
if statusy in [0, 40]:
# Main border is detected
positions[-1][1] = y2 + 1
positions[-2][1] = y2 + 1
else:
# Update status
positions[-1][-1] = 4
positions[-2][-1] = 4
else:
self.logger.debug('slit is not complete')
y1, y2 = 0, 0
# Update positions
self.logger.debug(
'bar %d centroid-y %9.4f, row %d x-pos %9.4f, FWHM %6.3f, status %d',
*positions[-2])
self.logger.debug(
'bar %d centroid-y %9.4f, row %d x-pos %9.4f, FWHM %6.3f, status %d',
*positions[-1])
if ks == 5:
slits[lbarid -
1] = [xpos1, y2, xpos2, y2, xpos2, y1, xpos1, y1]
# FITS coordinates
slits[lbarid - 1] += 1.0
self.logger.debug('inserting bars %d-%d into "slits"',
lbarid, rbarid)
allpos[ks] = numpy.asarray(
positions, dtype='float') # GCS doesn't like lists of lists
self.logger.debug('end finding bars')
result = self.create_result(
frame=hdulist,
slits=slits,
positions9=allpos[9],
positions7=allpos[7],
positions5=allpos[5],
positions3=allpos[3],
DTU=dtub,
ROTANG=rotang,
TSUTC1=tsutc1,
csupos=csupos,
csusens=csusens,
)
return result
def char_bar_height(arr_deriv_alt,
xpos1,
xpos2,
centery,
threshold,
wh=35,
wfit=3):
logger = logging.getLogger('emir.recipes.bardetect')
pcentery = coor_to_pix_1d(centery)
slicey = slice_create(pcentery, wh, start=1, stop=2047)
ref_pcentery = pcentery - slicey.start
mm = arr_deriv_alt[slicey, xpos1:xpos2 + 1].mean(axis=-1)
idxs_t = find_peaks_indexes(mm, window_width=3, threshold=threshold)
idxs_u = find_peaks_indexes(-mm, window_width=3, threshold=threshold)
# Peaks on the right
status = 0
npeaks_u = len(idxs_u)
if npeaks_u == 0:
# This is a problem, no peak on the right
b2 = 0
status = 4
logger.debug('no bottom border found')
else:
# Filter over reference
g_idxs_u = idxs_u[idxs_u >= ref_pcentery]
if len(g_idxs_u) == 0:
logger.debug('no peak over center')
b2 = 0
status = 4
else:
x_u, y_u = refine_peaks(-mm, g_idxs_u, window_width=wfit)
# Select the peak with max derivative
if len(x_u) == 0 or len(y_u) == 0:
logger.warning("no 1st peak found after refine")
b2 = 0
status = 4
else:
idmax = y_u.argmax()
b2 = x_u[idmax]
b2val = y_u[idmax]
logger.debug('main border in %f', slicey.start + b2)
# peaks on the left
npeaks_t = len(idxs_t)
if npeaks_t == 0:
# This is a problem, no peak on the left
b1 = 0
logger.debug('no top border found')
status = 40 + status
else:
g_idxs_t = idxs_t[idxs_t <= ref_pcentery]
if len(g_idxs_t) == 0:
logger.debug('no peak under center')
b1 = 0
status = 40 + status
else:
x_t, y_t = refine_peaks(mm, g_idxs_t, window_width=wfit)
# Select the peak with max derivative
if len(x_t) == 0 or len(y_t) == 0:
logger.warning("no 2nd peak found after refine")
b1 = 0
status = 40 + status
else:
idmax = y_t.argmax()
b1 = x_t[idmax]
b1val = y_t[idmax]
logger.debug('second border in %f', slicey.start + b1)
return slicey.start + b1, slicey.start + b2, status
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 char_bar_height(arr_deriv_alt, xpos1, xpos2, centery, threshold, wh=35, wfit=3):
logger = logging.getLogger('emir.recipes.bardetect')
pcentery = coor_to_pix_1d(centery)
slicey = slice_create(pcentery, wh, start=1, stop=2047)
ref_pcentery = pcentery - slicey.start
mm = arr_deriv_alt[slicey, xpos1:xpos2 + 1].mean(axis=-1)
idxs_t = find_peaks_indexes(mm, window_width=3,threshold=threshold)
idxs_u = find_peaks_indexes(-mm, window_width=3,threshold=threshold)
# Peaks on the right
status = 0
npeaks_u = len(idxs_u)
if npeaks_u == 0:
# This is a problem, no peak on the right
b2 = 0
status = 4
logger.debug('no bottom border found')
else:
# Filter over reference
g_idxs_u = idxs_u[idxs_u >= ref_pcentery]
if len(g_idxs_u) == 0:
logger.debug('no peak over center')
b2 = 0
status = 4
else:
x_u, y_u = refine_peaks(-mm, g_idxs_u, window_width=wfit)
# Select the peak with max derivative
if len(x_u) == 0 or len(y_u) == 0:
logger.warning("no 1st peak found after refine")
b2 = 0
status = 4
else:
idmax = y_u.argmax()
b2 = x_u[idmax]
b2val = y_u[idmax]
logger.debug('main border in %f', slicey.start + b2)
# peaks on the left
npeaks_t = len(idxs_t)
if npeaks_t == 0:
# This is a problem, no peak on the left
b1 = 0
logger.debug('no top border found')
status = 40 + status
else:
g_idxs_t = idxs_t[idxs_t <= ref_pcentery]
if len(g_idxs_t) == 0:
logger.debug('no peak under center')
b1 = 0
status = 40 + status
else:
x_t, y_t = refine_peaks(mm, g_idxs_t, window_width=wfit)
# Select the peak with max derivative
if len(x_t) == 0 or len(y_t) == 0:
logger.warning("no 2nd peak found after refine")
b1 = 0
status = 40 + status
else:
idmax = y_t.argmax()
b1 = x_t[idmax]
b1val = y_t[idmax]
logger.debug('second border in %f', slicey.start + b1)
return slicey.start + b1, slicey.start + b2, status