class adjustWCSToReferenceConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_wcsCorrected",
optional=True)
method = config.ChoiceField("Alignment method",
str,
allowed={
"header": "Use WCS in header",
"sources": "Match sources in images"
},
default="sources")
fallback = config.ChoiceField("Fallback method",
str,
allowed={"header": "Use WCS in header"},
default="header",
optional=True)
first_pass = config.RangeField(
"Search radius for source matching (arcseconds)", float, 5., min=0)
min_sources = config.RangeField(
"Minimum number of sources required to use source matching",
int,
3,
min=1)
cull_sources = config.Field("Use only point sources for alignment?", bool,
False)
rotate = config.Field("Allow rotation for alignment?", bool, False)
scale = config.Field("Allow magnification for alignment?", bool, False)
class removePatternNoiseConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_patternNoiseRemoved",
optional=True)
force = config.Field("Force cleaning even if noise increases?", bool,
False)
hsigma = config.RangeField("High rejection threshold (sigma)",
float,
3.,
min=0)
lsigma = config.RangeField("Low rejection threshold (sigma)",
float,
3.,
min=0)
pattern_x_size = config.RangeField("Pattern x size (pixels)",
int,
16,
min=4)
pattern_y_size = config.RangeField("Pattern y size (pixels)",
int,
4,
min=4)
subtract_background = config.Field(
"Subtract median from each pattern box?", bool, True)
class makeBPMConfig(config.Config):
override_thresh = config.ChoiceField(
"Apply user-specified thresholds, overriding any default calculation?",
bool, {True: 'Must be True where no default algorithm is implemented'},
default=True,
optional=False)
dark_lo_thresh = config.Field("Low rejection threshold for dark (ADU)",
float,
None,
optional=True)
dark_hi_thresh = config.Field("High rejection threshold for dark (ADU)",
float,
None,
optional=True)
flat_lo_thresh = config.RangeField(
"Low rejection threshold for normalized flat",
float,
None,
max=1.0,
optional=True)
flat_hi_thresh = config.RangeField(
"High rejection threshold for normalized flat",
float,
None,
min=1.0,
optional=True)
def validate(self):
config.Config.validate(self)
if self.dark_lo_thresh is not None and \
self.dark_hi_thresh is not None and \
self.dark_lo_thresh >= self.dark_hi_thresh:
raise ValueError(
"dark_hi_thresh must be greater than dark_lo_thresh")
class rejectInputsConfig(config.Config):
at_start = config.RangeField(
"Number of files to remove from start of list", int, 0, min=0)
at_end = config.RangeField("Number of files to remove from end of list",
int,
0,
min=0)
class extract1DSpectraConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_extracted", optional=True)
method = config.ChoiceField("Extraction method",
str,
allowed={
"standard": "no weighting",
"weighted": "inverse-variance weighted",
"optimal": "optimal extraction"
},
default="standard")
width = config.RangeField("Width of extraction aperture (pixels)",
float,
None,
min=1,
optional=True)
grow = config.RangeField("Source aperture avoidance region (pixels)",
float,
10,
min=0,
optional=True)
subtract_sky = config.Field(
"Subtract sky spectra if the data have not been sky corrected?", bool,
True)
debug = config.Field("Draw extraction apertures on image display?", bool,
False)
class applyDQPlaneConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_dqPlaneApplied",
optional=True)
replace_flags = config.RangeField("DQ bitmask for pixels to replace",
int,
65529,
min=0)
replace_value = config.Field("Replacement value [mean|median|<value>]",
(str, float),
"median",
check=replace_valueCheck)
inner = config.RangeField("Inner filter radius (pixels)",
float,
None,
min=1,
optional=True)
outer = config.RangeField("Outer filter radius (pixels)",
float,
None,
min=1,
optional=True)
max_iters = config.RangeField("Maximum number of iterations",
int,
1,
min=1)
def validate(self):
config.Config.validate(self)
if self.inner is not None and self.outer is not None and self.outer < self.inner:
raise ValueError("Outer radius must be larger than inner radius")
class resampleToCommonFrameConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_align", optional=True)
w1 = config.RangeField("Starting wavelength (nm)",
float,
None,
min=0.,
optional=True)
w2 = config.RangeField("Ending wavelength (nm)",
float,
None,
min=0.,
optional=True)
dw = config.RangeField("Dispersion (nm/pixel)",
float,
None,
min=0.01,
optional=True)
npix = config.RangeField("Number of pixels in spectrum",
int,
None,
min=2,
optional=True)
conserve = config.Field("Conserve flux?", bool, False)
order = config.RangeField("Order of interpolation", int, 1, min=0, max=5)
trim_data = config.Field("Trim to field of view of reference image?", bool,
False)
def validate(self):
config.Config.validate(self)
if [self.w1, self.w2, self.dw, self.npix].count(None) == 0:
raise ValueError("Maximum 3 of w1, w2, dw, npix must be specified")
if self.w1 is not None and self.w2 is not None and self.w2 <= self.w1:
raise ValueError(
"Ending wavelength must be greater than starting wavelength")
class linearizeSpectraConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_linearized", optional=True)
w1 = config.RangeField("Starting wavelength (nm)",
float,
None,
min=0.,
optional=True)
w2 = config.RangeField("Ending wavelength (nm)",
float,
None,
min=0.,
optional=True)
dw = config.RangeField("Dispersion (nm/pixel)",
float,
None,
min=0.01,
optional=True)
npix = config.RangeField("Number of pixels in spectrum",
int,
None,
min=2,
optional=True)
conserve = config.Field("Conserve flux?", bool, False)
def validate(self):
config.Config.validate(self)
if [self.w1, self.w2, self.dw, self.npix].count(None) not in (1, 4):
raise ValueError(
"Exactly 0 or 3 of w1, w2, dw, npix must be specified")
if self.w1 is not None and self.w2 is not None and self.w2 <= self.w1:
raise ValueError(
"Ending wavelength must be greater than starting wavelength")
class normalizeFlatConfig(config.core_1Dfitting_config):
suffix = config.Field("Filename suffix", str, "_normalized", optional=True)
center = config.RangeField("Central row/column to extract", int, None, min=1, optional=True)
nsum = config.RangeField("Number of lines to sum", int, 10, min=1)
def setDefaults(self):
self.order = 20
class subtractOverscanConfig(config.core_1Dfitting_config):
suffix = config.Field("Filename suffix",
str,
"_overscanSubtracted",
optional=True)
function = config.ChoiceField("Fitting function",
str,
allowed={
"none": "Row-by-row values",
"spline3": "Cubic spline",
"chebyshev": "Chebyshev polynomial"
},
default="spline3",
optional=False)
order = config.RangeField("Order of fitting function",
int,
None,
min=0,
optional=True)
nbiascontam = config.RangeField(
"Number of columns to exclude from averaging", int, 0, min=0)
def validate(self):
config.Config.validate(self)
if self.function == "poly" and self.order is None:
raise ValueError("Polynomial order must be specified")
if self.function == "spline" and self.order == 0:
raise ValueError("Must specify a positive spline order, or None")
class associateSkyConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_skyAssociated", optional=True)
time = config.RangeField("Maximum association time (seconds)", float, 600., min=0)
distance = config.RangeField("Minimum association distance (arcsec)", float, 3., min=0)
min_skies = config.RangeField("Minimum number of sky frames to associate",
int, 3, min=0, optional=True)
max_skies = config.RangeField("Maximum number of sky frames to associate",
int, None, min=1, optional=True)
use_all = config.Field("Use all frames as skies?", bool, False)
class flagCosmicRaysByStackingConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_CRMasked", optional=True)
hsigma = config.RangeField("High rejection threshold (sigma)",
float,
7.,
min=0)
dilation = config.RangeField("CR dilation radius (pixels)",
float,
1.,
min=0)
class thresholdFlatfieldConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_thresholdFlatfielded",
optional=True)
upper = config.RangeField("Upper limit of valid pixels", float, 10., min=1)
lower = config.RangeField("Lower limit of valid pixels",
float,
0.01,
max=1)
class distortionCorrectConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_distortionCorrected",
optional=True)
arc = config.ListField("Arc(s) with distortion map", (AstroData, str),
None,
optional=True,
single=True)
order = config.RangeField("Interpolation order", int, 3, min=0, max=5)
subsample = config.RangeField("Subsampling", int, 1, min=1)
class applyStackedObjectMaskConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_stackedObjMaskApplied",
optional=True)
source = config.Field("Stream containing stacked image", str, None)
order = config.RangeField("Order of interpolation", int, 1, min=0, max=5)
threshold = config.RangeField("Threshold for flagging pixels",
float,
0.01,
min=0.,
max=1.)
class skyCorrectFromSlitConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_skyCorrected",
optional=True)
order = config.RangeField("Sky spline fitting order",
int,
5,
min=1,
optional=True)
grow = config.RangeField("Aperture growth distance (pixels)",
float,
0,
min=0)
class detectSourcesConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_sourcesDetected",
optional=True)
mask = config.Field("Replace DQ-flagged pixels with median of image?",
bool, False)
replace_flags = config.RangeField("DQ bitmask for flagging if mask=True",
int,
249,
min=0)
set_saturation = config.Field("Inform SExtractor of saturation level?",
bool, False)
detect_minarea = config.RangeField(
"Minimum object detection area (pixels)", int, 8, min=1)
detect_thresh = config.RangeField(
"Detection threshold (standard deviations)", float, 2., min=0.1)
analysis_thresh = config.RangeField(
"Analysis threshold (standard deviations)", float, 2., min=0.1)
deblend_mincont = config.RangeField("Minimum deblending contrast",
float,
0.005,
min=0.)
phot_min_radius = config.RangeField(
"Minimum radius for photometry (pixels)", float, 3.5, min=1.0)
back_size = config.RangeField("Background mesh size (pixels)",
int,
32,
min=1)
back_filtersize = config.RangeField("Filtering scale for background",
int,
8,
min=1)
class addOIWFSToDQConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_oiwfsDqAdded",
optional=True)
contrast = config.RangeField("Fractional decrease in sky level",
float,
0.2,
min=0.001,
max=1.)
convergence = config.RangeField(
"Convergence required in sky level to stop dilation",
float,
2.0,
min=0.001)
class addIllumMaskToDQConfig(parameters_standardize.addIllumMaskToDQConfig):
shift = config.RangeField("User-defined shift for illumination mask",
int,
None,
min=-100,
max=100,
inclusiveMax=True,
optional=True)
max_shift = config.RangeField(
"Maximum (unbinned) pixel shift for illumination mask",
int,
20,
min=0,
max=100,
inclusiveMax=True)
class resampleToCommonFrameConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_align", optional=True)
order = config.RangeField("Order of interpolation", int, 1, min=0, max=5)
trim_data = config.Field("Trim to field of view of reference image?", bool,
False)
clean_data = config.Field("Clean bad pixels before interpolation?", bool,
False)
class calculateSensitivityConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_sensitivityCalculated",
optional=True)
filename = config.Field("Name of spectrophotometric data file",
str,
None,
optional=True)
order = config.RangeField("Order of spline fit", int, 6, min=1)
bandpass = config.RangeField("Bandpass width (nm) if not suuplied",
float,
5.,
min=0.1,
max=10.)
debug_plot = config.Field("Plot sensitivity curve?", bool, False)
class adjustWCSToReferenceConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_wcsCorrected",
optional=True)
method = config.ChoiceField("Alignment method",
str,
allowed={
"sources_wcs": "Match sources using WCS",
"sources_offsets":
"Match sources using telescope offsets",
"offsets": "Use telescope offsets only"
},
default="sources_wcs")
fallback = config.ChoiceField("Fallback method",
str,
allowed={
"sources_offsets":
"Match sources using telescope offsets",
"offsets": "Use telescope offsets only"
},
default="offsets",
optional=True)
tolerance = config.RangeField(
"Maximum distance from the header offset, "
"for the correlation method (arcsec)",
float,
1,
min=0.,
optional=True)
class getListConfig(config.Config):
purpose = config.Field("Purpose of list", str, None, optional=True)
max_frames = config.RangeField("Maximum number of frames",
int,
None,
min=1,
optional=True)
class addLatencyToDQConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_latencyAdded",
optional=True)
non_linear = config.Field("Flag non-linear pixels?", bool, False)
time = config.RangeField("Persistence time (seconds)", float, 120., min=0.)
class resampleToCommonFrameConfig(
parameters_resample.resampleToCommonFrameConfig):
pixel_scale = config.RangeField(
"Output pixel scale (arcseconds) if no reference provided",
float,
0.02,
min=0.01,
max=1.0)
pa = config.RangeField(
"Output position angle (E of N) if no reference provided",
float,
0.0,
min=-180,
max=360)
def setDefaults(self):
self.force_affine = False
class findSourceAperturesConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_aperturesFound",
optional=True)
max_apertures = config.RangeField("Maximum number of sources to find",
int,
None,
min=1,
optional=True)
percentile = config.RangeField(
"Percentile to determine signal for each spatial pixel",
float,
95,
min=1,
max=100,
optional=True)
section = config.Field(
"Pixel section(s) for measuring the spatial profile",
str,
None,
optional=True,
check=check_section)
min_sky_region = config.RangeField(
"Minimum number of contiguous pixels "
"between sky lines",
int,
20,
min=1)
use_snr = config.Field(
"Use signal-to-noise ratio rather than data to find peaks?", bool,
True)
threshold = config.RangeField(
"Threshold for automatic width determination",
float,
0.01,
min=0,
max=1)
sizing_method = config.ChoiceField(
"Method for automatic width determination",
str,
allowed={
"peak": "height relative to peak",
"integral": "integrated flux"
},
default="peak")
class normalizeFlatConfig(config.Config):
suffix = config.Field("Filename suffix", str, "_normalized", optional=True)
spectral_order = config.Field("Fitting order in spectral direction",
(int, str),
20,
check=flat_order_check)
threshold = config.RangeField(
"Threshold for flagging unilluminated pixels", float, 0.01, min=0)
hsigma = config.RangeField("High rejection threshold (sigma)",
float,
3.,
min=0)
lsigma = config.RangeField("Low rejection threshold (sigma)",
float,
3.,
min=0)
grow = config.RangeField("Growth radius for bad pixels", int, 0, min=0)
class determineAstrometricSolutionConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_astrometryCorrected",
optional=True)
initial = config.RangeField(
"Search radius for cross-correlation (arcseconds)", float, 5., min=1)
final = config.RangeField("Search radius for object matching (arcseconds)",
float,
1.,
min=0)
# None => False if 'qa' in mode else True
full_wcs = config.Field(
"Recompute positions using full WCS rather than offsets?",
bool,
None,
optional=True)
class dilateObjectMaskConfig(config.Config):
suffix = config.Field("Filename suffix",
str,
"_objmaskDilated",
optional=True)
dilation = config.RangeField("Dilation radius (pixels)", float, 1., min=0)
repeat = config.Field("Allow dilation of already-dilated image?", bool,
False)
class calculateSensitivityConfig(config.core_1Dfitting_config):
suffix = config.Field("Filename suffix", str, "_sensitivityCalculated", optional=True)
filename = config.Field("Name of spectrophotometric data file", str, None, optional=True)
bandpass = config.RangeField("Bandpass width (nm) if not supplied",
float, 5., min=0.1, max=10.)
debug_airmass0 = config.Field("Calculate sensitivity curve at zero airmass?",
bool, False)
regions = config.Field("Sample regions", str, None, optional=True,
check=validate_regions_float)
debug_plot = config.Field("Plot sensitivity curve?", bool, False)
interactive_spline = config.Field("Interactive spline selection?", bool, False)
niter = config.RangeField("Maximum number of clipping iterations to perform of spline fit", int, 3, min=1)
grow = config.RangeField("Radius to reject pixels adjacent to masked pixels of spline fit", int, 0, min=0)
interactive = config.Field("Display interactive fitter?", bool, False)
def setDefaults(self):
del self.grow
