The flames_obs_redchain recipe =============================================================== .. data:: flames_obs_redchain Synopsis -------- Runs the full UVES-FIBRE reduction chain Description ----------- This recipe does a complete science reduction. It runs all necessary calibration recipes depending on the availability of raw/processed calibration frames. Input frames are all UVES-FIBER raw and reference frames: formatchecks, FIB_ARC_LAMP_FORM_RED, order definition frames, FIB_ORDER_FLAT_RED, biases, BIAS_RED, darks, DARK_RED, flats, SFLAT_RED, arc lamps, FIB_ARC_LAMP_RED, standard stars, FIB_STANDARD_RED a wavelength catalogue table,LINE_REFER_TABLE, and optionally a wavelength table of bright lines,LINE_INTMON_TABLE, used only for computing Quality Control parameters. a reference standard star flux table, FLUX_STD_TABLE, a table describing the atmospheric extintion,EXTCOEFF_TABLE. Optionally, science frames, SCIENCE_xxx, or UVES_SCI_POINT_xxx, or UVES_SCI_EXTND_xxx, or UVES_SCI_SLICER_xxx. For further details on the data reduction and the input frame types refer to the man page of the individual recipes. Constructor ----------- .. method:: cpl.Recipe("flames_obs_redchain") :noindex: Create an object for the recipe flames_obs_redchain. :: import cpl flames_obs_redchain = cpl.Recipe("flames_obs_redchain") Parameters ---------- .. py:attribute:: flames_obs_redchain.param.debug Whether or not to save intermediate results to local directory (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.backsubdegx Degree (in x) of polynomial used to estimate the background (mode=poly). (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.backsubdegy Degree (in y) of polynomial used to estimate the background (mode=poly). (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.backsubgrid Number of grid points (in x- and y-direction) used to estimate the background (mode=poly). (int; default: 50) [default=50]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.backsubkappa The value of kappa in the one-sided kappa-sigma clipping used to estimate the background (mode=poly). (float; default: 4.0) [default=4.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.backsubradiusy The height (in pixels) of the background sampling window is (2*radiusy + 1). This parameter is not corrected for binning. (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.defpol1 The degree of the bivarite fit (cross dispersion direction). If negative, the degree is optimized to give the best fit (int; default: -1) [default=-1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.defpol2 The degree of the bivarite fit (order number). If negative, the degree is optimized to give the best fit (int; default: -1) [default=-1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.kappa Used for kappa-sigma clipping of the final polynomial fit. If negative, no clipping is done (float; default: 4.0) [default=4.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.maxgap If the order line drops below detection threshold, the order tracing algorithm will try to jump a gap of maximum size 'maxgap' multiplied by the image width (float; default: 0.2) [default=0.2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.maxrms When fitting the orders with straight lines, this is the maximum allowed RMS relative to the median RMS of all orders (float; default: 100.0) [default=100.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.maxslope Maximum possible line slope (float; default: 0.2) [default=0.2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.minslope Minimum possible line slope. This should be the 'physical' slope on the chip, i.e. not taking binning factors into account, which is handled by the recipe (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.minthresh The minimum threshold value is (min + minthres*(max - min)). Here 'min' and 'max' are the lowest and highest pixel values in the central bin of the order (float; default: 0.2) [default=0.2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.mmethod Background subtraction method. If equal to 'median' the background is sampled using the median of a sub-window. If 'minimum', the minimum sub-window value is used. If 'no', no background subtraction is done. (str; default: 'median') [default="median"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.pthres In automatic mode, or if the number of orders to detect is read from a guess table, the detection of new lines stops when the intensity of a candidate line drops to less than 'pthres' times the intensity of the previous detection. (float; default: 0.2) [default=0.2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.radx Half X size of median filtering window (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.rady Half Y size of median filtering window (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.samplewidth Separation of sample traces (used by Hough transform) in input image (int; default: 50) [default=50]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.sloperes Resolution (width in pixels) of Hough space (int; default: 120) [default=120]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.tracestep The step size used when tracing the orders (int; default: 10) [default=10]. .. py:attribute:: flames_obs_redchain.param.flames_cal_orderpos.use_guess_tab If a Guess order table is provided this parameter set how it is used:0: No usage, 1: use it to set lower/upper Y raws where order are searched 2: the order table try to fully match the guess (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.ccd_rot_angle_off Offset on CCD rotation angle (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.cd_angle_off Offset on cross disperser angle (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.compute_regression_sw Compute regression? (bool; default: True) [default=True]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.def_pol1 Polynomial X deg (int; default: 4) [default=4]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.def_pol2 Polynomial Y deg (int; default: 5) [default=5]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.ech_angle_off Offset on echelle angle (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.kappa Kappa value in kappa sigma clipping on RESIDUAL between YFIT and Y columns (float; default: 4.5) [default=4.5]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.mbox_x Match box X size (int; default: 40) [default=40]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.mbox_y Match box Y size (int; default: 40) [default=40]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.tol Tolerance in kappa sigma clipping on RESIDUAL between YFIT and Y columns (float; default: 2.0) [default=2.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.trans_x Detector translation along X (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_predict.trans_y Detector translation along Y (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.bias_method Bias subtraction method, M for master bias frame, N for no bias subtraction, V to subtract a constant bias level defined by the parameter bias_value (str; default: 'M') [default="M"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.bias_value Bias value (only if bias_method = V) (int; default: 200) [default=200]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.clean_tmp_products Input data format (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.cubify Cubify switch (bool; default: True) [default=True]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.ext_method Extraction method (str; default: 'opt') [default="opt"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.fileprep Slitff* and Fibreff* file preparation. If fast extraction method is used it should be set to FALSE (bool; default: True) [default=True]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.filter_switch Filter switch (str; default: 'none') [default="none"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.sat_thr Saturation threshold (int; default: 55000) [default=55000]. .. py:attribute:: flames_obs_redchain.param.flames_cal_prep_sff_ofpos.save_flat_size To be sure to use the flat part of a slit flatsone may need to subtract this bit. The default value -1, is used for automatic setting: if WCEN=520 save_flat_size=0, else save_flat_size=2. Values explicitly set by user overwrite this rule. (int; default: -1) [default=-1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.alpha The parameter that controls the distance to the nearest neighbours (float; default: 0.1) [default=0.1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.degree Degrees of the global 2d dispersion polynomial. If a negative number is specified, the polynomial degrees are automatically selected by starting from (1, 1) and inreasing the degrees as long as the RMS residual decreases significantly (int; default: 4) [default=4]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.best (optimal extraction only) If false (fastest), the spectrum is extracted only once. If true (best), the spectrum is extracted twice, the second time using improved variance estimates based on the first iteration. Better variance estimates slightly improve the obtained signal to noise but at the cost of increased execution time (bool; default: True) [default=True]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.chunk In optimal extraction mode, the chunk size (in pixels) used for fitting the analytical profile (a fit of the analytical profile to single bins would suffer from low statistics). (int; default: 32) [default=32]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.kappa In optimal extraction mode, this is the threshold for bad (i.e. hot/cold) pixel rejection. If a pixel deviates more than kappa*sigma (where sigma is the uncertainty of the pixel flux) from the inferred spatial profile, its weight is set to zero. Range: [-1,100]. If this parameter is negative, no rejection is performed. (float; default: 10.0) [default=10.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.method Extraction method. (2d/optimal not supported by uves_cal_wavecal, weighted supported only by uves_cal_wavecal, 2d not supported by uves_cal_response) (str; default: 'average') [default="average"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.oversample The oversampling factor used for the virtual resampling algorithm. If negative, the value 5 is used for S/N <=200, and the value 10 is used if the estimated S/N is > 200 (int; default: -1) [default=-1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.profile In optimal extraction mode, the kind of profile to use. 'gauss' gives a Gaussian profile, 'moffat' gives a Moffat profile with beta=4 and a possible linear sky contribution. 'virtual' uses a virtual resampling algorithm (i.e. measures and uses the actual object profile). 'constant' assumes a constant spatial profile and allows optimal extraction of wavelength calibration frames. 'auto' will automatically select the best method based on the estimated S/N of the object. For low S/N, 'moffat' or 'gauss' are recommended (for robustness). For high S/N, 'virtual' is recommended (for accuracy). In the case of virtual resampling, a precise determination of the order positions is required; therefore the order-definition is repeated using the (assumed non-low S/N) science frame (str; default: 'auto') [default="auto"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.extract.skymethod In optimal extraction mode, the sky subtraction method to use. 'median' estimates the sky as the median of pixels along the slit (ignoring pixels close to the object), whereas 'optimal' does a chi square minimization along the slit to obtain the best combined object and sky levels. The optimal method gives the most accurate sky determination but is also a bit slower than the median method (str; default: 'optimal') [default="optimal"]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.kappa Lines with residuals more then kappa stdev are rejected from the final fit (float; default: 4.0) [default=4.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.length Length (in pixels) of each extraction window. This parameter is also equal to the seperation of adjacent window centers, causing the extraction windows to always be aligned. The parameter is automatically adjusted according to the binning of the input raw frame. If negative, the extraction window length is determined automatically to cover the full slit (float; default: 7.0) [default=7.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.maxerror This parameter controls the graceful exit of the identification loop. If the RMS of the global fit exceeds this value (pix) the iteration stops (float; default: 20.0) [default=20.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.maxlines Maximum number of lines to detect. If zero, the default value (1600 for BLUE/REDL chip; 1400 for REDU chip) is used. (int; default: 0) [default=0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.minlines Minimum number of lines to detect. If zero, the default value (1100 for BLUE/REDL chips; 1000 for REDU chip) is used. (int; default: 0) [default=0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.nwindows Number of extraction windows per trace. The windows will be aligned (i.e. no overlap and no spacing between adjacent windows). Unless an offset is specified, the middle window(s) is centered on the trace (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.offset A global offset (in pixels) of all extraction windows (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.range Width (pix) of search window is 2*range + 1. This parameter is automatically adjusted according to binning. (int; default: 8) [default=8]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.rebin.scale Whether or not to multiply by the factor dx/dlambda (pixels per wavelength) during the rebinning to conserve the flux. This option is disabled as default because applying the flat field correction already ensures flux conservation. Therefore this parameter should be TRUE (for response and science data) only if reduce.ffmethd = no. (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.rebin.wavestep The bin size used for BLUE/REDL data (in w.l.u.) in wavelength space. If negative, a step size of 2/3 * ( average pixel size ) is used. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.rebin.wavestep_redu The bin size used for REDU data (in w.l.u.) in wavelength space. If negative, a step size of 2/3 * ( average pixel size ) is used. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.shiftmax The maximum shift (pix) in either direction compared to guess solution. This parameter is automatically corrected for binning (float; default: 10.0) [default=10.0]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.shiftstep The step size (pix) used when searching for the optimum shift. This parameter is automatically corrected for binning (float; default: 0.1) [default=0.1]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.shifttoler Tolerance (pix) when matching shifted lines. This parameter is not adjusted according to binning (float; default: 0.05) [default=0.05]. .. py:attribute:: flames_obs_redchain.param.flames_cal_wavecal.tolerance Tolerance of fit. If positive, the tolerance is in pixel units. If negative, abs(tolerance) is in wavelength units. Lines with residuals worse than the tolerance are excluded from the final fit. Unlike in previous versions, this parameter is not corrected for CCD binning. This rejection based on the absolute residual in pixel can be effectively disabled by setting the tolerance to a very large number (e.g. 9999). In that case outliers will be rejected using only kappa sigma clipping. (float; default: 0.6) [default=0.6]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.bias_method Bias subtraction method (str; default: 'M') [default="M"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.bias_value Bias value (only if bias_method = V) (int; default: 200) [default=200]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.bkg_max_io_win Background window number in each full inter order (int; default: 500) [default=500]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.bkg_xy_win_sz_x x maximum size of each background window: (int; default: 6) [default=6]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.bkg_xy_win_sz_y y maximum size of each background window: (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.clean_tmp_products Input data format (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.cor_def_off Correlation center offset? (float; default: 0.0) [default=0.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.cor_def_pnt Correlation sampling points? (int; default: 25) [default=25]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.cor_def_rng Correlation range size? (float; default: 6.0) [default=6.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.cor_max_fnd Find correlation maximum? (str; default: 'Y') [default="Y"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.corvel_iter Velocity correlation iteration number (SimCal) (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.cubify_sw Cubify switch (str; default: 'N') [default="N"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.drs_base_name Base name for science products (str; default: 'fxb') [default="fxb"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.drs_ext_w_siz Integration window size good: 10 (if fibre deconvolution works fine) (float; default: 10.0) [default=10.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.drs_k_s_thre Kappa sigma threshold (float; default: 10.0) [default=10.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.drs_maxyshift Half width of the interval to scan for correlation, when determining y shift (float; default: 3.0) [default=3.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.ext_method Extraction method (str; default: 'opt') [default="opt"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.filt_sw Filter switch (str; default: 'none') [default="none"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.merge Order merging method. If 'optimal', the flux in the overlapping region is set to the (optimally computed, using the uncertainties) average of single order spectra. If 'sum', the flux in the overlapping region is computed as the sum of the single order spectra. If flat-fielding is done, method 'optimal' is recommended, otherwise 'sum'. (str; default: 'optimal') [default="optimal"]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.merge_delt1 Order merging left hand (short wavelength) cut. To reduce the amount of order overlapping regions we allow to cut short and long wavelength ranges. This may reduce the ripple possibly introduced by the order merging. Suggested values are: 10 (W<=390), 12 (390=860) (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.merge_delt2 Order merging right hand (long wavelength) cut. To reduce the amount of order overlapping regions we allow to cut short and long wavelength ranges. This may reduce the ripple possibly introduced by the order merging. Suggested values is 4 for W<860, else 0 (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.pixel_thresh_max Pixel saturation threshold max (int; default: 55000) [default=55000]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.pixel_thresh_min Pixel saturation threshold min (int; default: -20) [default=-20]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.rebin.scale Whether or not to multiply by the factor dx/dlambda (pixels per wavelength) during the rebinning to conserve the flux. This option is disabled as default because applying the flat field correction already ensures flux conservation. Therefore this parameter should be TRUE (for response and science data) only if reduce.ffmethd = no. (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.rebin.wavestep The bin size used for BLUE/REDL data (in w.l.u.) in wavelength space. If negative, a step size of 2/3 * ( average pixel size ) is used. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.flames_obs_scired.rebin.wavestep_redu The bin size used for REDU data (in w.l.u.) in wavelength space. If negative, a step size of 2/3 * ( average pixel size ) is used. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.plotter Any plots produced by the recipe are redirected to the command specified by this parameter. The plotting command must contain the substring 'gnuplot' and must be able to parse gnuplot syntax on its standard input. Valid examples of such a command may include 'gnuplot -persist' and 'cat > mygnuplot$$.gp'. A finer control of the plotting options can be obtained by writing an executable script, e.g. my_gnuplot.pl, that executes gnuplot after setting the desired gnuplot options (e.g. set terminal pslatex color). To turn off plotting, set this parameter to 'no' (str; default: 'no') [default="no"]. .. py:attribute:: flames_obs_redchain.param.process_chip For RED arm data process the redl, redu, or both chip(s) (str; default: 'both') [default="both"]. .. py:attribute:: flames_obs_redchain.param.scired Whether or not to do science reduction. If false, only master calibration frames are created. If false, either zero or all necessary calibration frames must be provided for each arm (bool; default: True) [default=True]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.clean_traps Clean detector traps. If TRUE detector traps are interpolated.The bad pixels are replaced by the average of thenearest good pixels in the same column, or simply marked as bad. The positions of bad pixels are hard-coded (as function of UVES chip). (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.dc_mask_x x-size (pixel) of the mask starting at (x,y) = (1,1) (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.dc_mask_y y-size (pixel) of the mask starting at (x,y) = (1,1) (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.khigh Kappa used to clip high level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.klow Kappa used to clip low level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.niter Number of kappa sigma iterations, when method is set to 'mean' (int; default: 5) [default=5]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.pd_compute Determine Fixed Pattern Noise. If TRUE the Fixed Patter Noise power spectrum is determined.(as function of UVES chip). (bool; default: False) [default=False]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mbias.stack_method Method used to build master frame (str; default: 'median') [default="median"]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.khigh Kappa used to clip high level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.khigh Kappa used to clip high level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.klow Kappa used to clip low level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.klow Kappa used to clip low level values, when method is set to 'mean' (float; default: 5.0) [default=5.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.niter Number of kappa sigma iterations, when method is set to 'mean' (int; default: 5) [default=5]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.niter Number of kappa sigma iterations, when method is set to 'mean' (int; default: 5) [default=5]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.border_x X distance between the left hand side of the detector and the left hand side of the region [pix] (int; default: 100) [default=100]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.border_y X distance between the left hand side of the detector and the left hand side of the region [pix] (int; default: 100) [default=100]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.box_sx Region X size [pix] (int; default: 100) [default=100]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.box_sy Region Y size [pix] (int; default: 100) [default=100]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.num_x Number of regions along the X axis (where mean/med/rms are computed). (int; default: 4) [default=4]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.num_y Number of regions along the Y axis(where mean/med/rms are computed). (int; default: 4) [default=4]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.when When QC analysis is performed. 0: on each raw frame or 1: on the master frame (int; default: 0) [default=0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.stack_method Method used to build master frame (str; default: 'median') [default="median"]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mdark.stack_method Method used to build master frame (str; default: 'median') [default="median"]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.mmethod Background measuring method. If equal to 'median' the background is sampled using the median of a subwindow. If 'minimum', the subwindow minimum value is used. If 'no', no background subtraction is done. (str; default: 'median') [default="median"]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.npoints This is the number of columns in interorder space used to sample the background. (int; default: 82) [default=82]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.radiusy The height (in pixels) of the background sampling window is (2*radiusy + 1). This parameter is not corrected for binning. (int; default: 2) [default=2]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.sdegree Degree of interpolating splines. Currently only degree = 1 is supported (int; default: 1) [default=1]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.smoothx If spline interpolation is used to measure the background, the x-radius of the post-smoothing window is (smoothx * image_width). Here, 'image_width' is the image width after binning. If negative, the default values are used: (25.0/4096) for blue flat-field frames, (50.0/4096) for red flat-field frames, (300.0/4096) for blue science frames and (300.0/4096) for red science frames. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.backsub.smoothy If spline interpolation is used to measure the background, the y-radius of the post-smoothing window is (smoothy * image_height). Here, 'image_height' is the image height after binning. If negative, the default values are used: (100.0/2048) for blue flat-field frames, (300.0/2048) for red flat-field frames, (200.0/2048) for blue science frames and (500.0/2048) for red science frames. (float; default: -1.0) [default=-1.0]. .. py:attribute:: flames_obs_redchain.param.uves_cal_mflat.norm_method Method used to build master frame (str; default: 'explevel') [default="explevel"]. The following code snippet shows the default settings for the available parameters. :: import cpl flames_obs_redchain = cpl.Recipe("flames_obs_redchain") flames_obs_redchain.param.debug = False flames_obs_redchain.param.flames_cal_orderpos.backsubdegx = 2 flames_obs_redchain.param.flames_cal_orderpos.backsubdegy = 2 flames_obs_redchain.param.flames_cal_orderpos.backsubgrid = 50 flames_obs_redchain.param.flames_cal_orderpos.backsubkappa = 4.0 flames_obs_redchain.param.flames_cal_orderpos.backsubradiusy = 2 flames_obs_redchain.param.flames_cal_orderpos.defpol1 = -1 flames_obs_redchain.param.flames_cal_orderpos.defpol2 = -1 flames_obs_redchain.param.flames_cal_orderpos.kappa = 4.0 flames_obs_redchain.param.flames_cal_orderpos.maxgap = 0.2 flames_obs_redchain.param.flames_cal_orderpos.maxrms = 100.0 flames_obs_redchain.param.flames_cal_orderpos.maxslope = 0.2 flames_obs_redchain.param.flames_cal_orderpos.minslope = 0.0 flames_obs_redchain.param.flames_cal_orderpos.minthresh = 0.2 flames_obs_redchain.param.flames_cal_orderpos.mmethod = "median" flames_obs_redchain.param.flames_cal_orderpos.pthres = 0.2 flames_obs_redchain.param.flames_cal_orderpos.radx = 2 flames_obs_redchain.param.flames_cal_orderpos.rady = 1 flames_obs_redchain.param.flames_cal_orderpos.samplewidth = 50 flames_obs_redchain.param.flames_cal_orderpos.sloperes = 120 flames_obs_redchain.param.flames_cal_orderpos.tracestep = 10 flames_obs_redchain.param.flames_cal_orderpos.use_guess_tab = 1 flames_obs_redchain.param.flames_cal_predict.ccd_rot_angle_off = 0.0 flames_obs_redchain.param.flames_cal_predict.cd_angle_off = 0.0 flames_obs_redchain.param.flames_cal_predict.compute_regression_sw = True flames_obs_redchain.param.flames_cal_predict.def_pol1 = 4 flames_obs_redchain.param.flames_cal_predict.def_pol2 = 5 flames_obs_redchain.param.flames_cal_predict.ech_angle_off = 0.0 flames_obs_redchain.param.flames_cal_predict.kappa = 4.5 flames_obs_redchain.param.flames_cal_predict.mbox_x = 40 flames_obs_redchain.param.flames_cal_predict.mbox_y = 40 flames_obs_redchain.param.flames_cal_predict.tol = 2.0 flames_obs_redchain.param.flames_cal_predict.trans_x = 0.0 flames_obs_redchain.param.flames_cal_predict.trans_y = 0.0 flames_obs_redchain.param.flames_cal_prep_sff_ofpos.bias_method = "M" flames_obs_redchain.param.flames_cal_prep_sff_ofpos.bias_value = 200 flames_obs_redchain.param.flames_cal_prep_sff_ofpos.clean_tmp_products = False flames_obs_redchain.param.flames_cal_prep_sff_ofpos.cubify = True flames_obs_redchain.param.flames_cal_prep_sff_ofpos.ext_method = "opt" flames_obs_redchain.param.flames_cal_prep_sff_ofpos.fileprep = True flames_obs_redchain.param.flames_cal_prep_sff_ofpos.filter_switch = "none" flames_obs_redchain.param.flames_cal_prep_sff_ofpos.sat_thr = 55000 flames_obs_redchain.param.flames_cal_prep_sff_ofpos.save_flat_size = -1 flames_obs_redchain.param.flames_cal_wavecal.alpha = 0.1 flames_obs_redchain.param.flames_cal_wavecal.degree = 4 flames_obs_redchain.param.flames_cal_wavecal.extract.best = True flames_obs_redchain.param.flames_cal_wavecal.extract.chunk = 32 flames_obs_redchain.param.flames_cal_wavecal.extract.kappa = 10.0 flames_obs_redchain.param.flames_cal_wavecal.extract.method = "average" flames_obs_redchain.param.flames_cal_wavecal.extract.oversample = -1 flames_obs_redchain.param.flames_cal_wavecal.extract.profile = "auto" flames_obs_redchain.param.flames_cal_wavecal.extract.skymethod = "optimal" flames_obs_redchain.param.flames_cal_wavecal.kappa = 4.0 flames_obs_redchain.param.flames_cal_wavecal.length = 7.0 flames_obs_redchain.param.flames_cal_wavecal.maxerror = 20.0 flames_obs_redchain.param.flames_cal_wavecal.maxlines = 0 flames_obs_redchain.param.flames_cal_wavecal.minlines = 0 flames_obs_redchain.param.flames_cal_wavecal.nwindows = 1 flames_obs_redchain.param.flames_cal_wavecal.offset = 0.0 flames_obs_redchain.param.flames_cal_wavecal.range = 8 flames_obs_redchain.param.flames_cal_wavecal.rebin.scale = False flames_obs_redchain.param.flames_cal_wavecal.rebin.wavestep = -1.0 flames_obs_redchain.param.flames_cal_wavecal.rebin.wavestep_redu = -1.0 flames_obs_redchain.param.flames_cal_wavecal.shiftmax = 10.0 flames_obs_redchain.param.flames_cal_wavecal.shiftstep = 0.1 flames_obs_redchain.param.flames_cal_wavecal.shifttoler = 0.05 flames_obs_redchain.param.flames_cal_wavecal.tolerance = 0.6 flames_obs_redchain.param.flames_obs_scired.bias_method = "M" flames_obs_redchain.param.flames_obs_scired.bias_value = 200 flames_obs_redchain.param.flames_obs_scired.bkg_max_io_win = 500 flames_obs_redchain.param.flames_obs_scired.bkg_xy_win_sz_x = 6 flames_obs_redchain.param.flames_obs_scired.bkg_xy_win_sz_y = 2 flames_obs_redchain.param.flames_obs_scired.clean_tmp_products = False flames_obs_redchain.param.flames_obs_scired.cor_def_off = 0.0 flames_obs_redchain.param.flames_obs_scired.cor_def_pnt = 25 flames_obs_redchain.param.flames_obs_scired.cor_def_rng = 6.0 flames_obs_redchain.param.flames_obs_scired.cor_max_fnd = "Y" flames_obs_redchain.param.flames_obs_scired.corvel_iter = 1 flames_obs_redchain.param.flames_obs_scired.cubify_sw = "N" flames_obs_redchain.param.flames_obs_scired.drs_base_name = "fxb" flames_obs_redchain.param.flames_obs_scired.drs_ext_w_siz = 10.0 flames_obs_redchain.param.flames_obs_scired.drs_k_s_thre = 10.0 flames_obs_redchain.param.flames_obs_scired.drs_maxyshift = 3.0 flames_obs_redchain.param.flames_obs_scired.ext_method = "opt" flames_obs_redchain.param.flames_obs_scired.filt_sw = "none" flames_obs_redchain.param.flames_obs_scired.merge = "optimal" flames_obs_redchain.param.flames_obs_scired.merge_delt1 = -1.0 flames_obs_redchain.param.flames_obs_scired.merge_delt2 = -1.0 flames_obs_redchain.param.flames_obs_scired.pixel_thresh_max = 55000 flames_obs_redchain.param.flames_obs_scired.pixel_thresh_min = -20 flames_obs_redchain.param.flames_obs_scired.rebin.scale = False flames_obs_redchain.param.flames_obs_scired.rebin.wavestep = -1.0 flames_obs_redchain.param.flames_obs_scired.rebin.wavestep_redu = -1.0 flames_obs_redchain.param.plotter = "no" flames_obs_redchain.param.process_chip = "both" flames_obs_redchain.param.scired = True flames_obs_redchain.param.uves_cal_mbias.clean_traps = False flames_obs_redchain.param.uves_cal_mbias.dc_mask_x = 1 flames_obs_redchain.param.uves_cal_mbias.dc_mask_y = 1 flames_obs_redchain.param.uves_cal_mbias.khigh = 5.0 flames_obs_redchain.param.uves_cal_mbias.klow = 5.0 flames_obs_redchain.param.uves_cal_mbias.niter = 5 flames_obs_redchain.param.uves_cal_mbias.pd_compute = False flames_obs_redchain.param.uves_cal_mbias.stack_method = "median" flames_obs_redchain.param.uves_cal_mdark.khigh = 5.0 flames_obs_redchain.param.uves_cal_mdark.khigh = 5.0 flames_obs_redchain.param.uves_cal_mdark.klow = 5.0 flames_obs_redchain.param.uves_cal_mdark.klow = 5.0 flames_obs_redchain.param.uves_cal_mdark.niter = 5 flames_obs_redchain.param.uves_cal_mdark.niter = 5 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.border_x = 100 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.border_y = 100 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.box_sx = 100 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.box_sy = 100 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.num_x = 4 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.num_y = 4 flames_obs_redchain.param.uves_cal_mdark.qc_dark.reg.when = 0 flames_obs_redchain.param.uves_cal_mdark.stack_method = "median" flames_obs_redchain.param.uves_cal_mdark.stack_method = "median" flames_obs_redchain.param.uves_cal_mflat.backsub.mmethod = "median" flames_obs_redchain.param.uves_cal_mflat.backsub.npoints = 82 flames_obs_redchain.param.uves_cal_mflat.backsub.radiusy = 2 flames_obs_redchain.param.uves_cal_mflat.backsub.sdegree = 1 flames_obs_redchain.param.uves_cal_mflat.backsub.smoothx = -1.0 flames_obs_redchain.param.uves_cal_mflat.backsub.smoothy = -1.0 flames_obs_redchain.param.uves_cal_mflat.norm_method = "explevel" You may also set or overwrite some or all parameters by the recipe parameter `param`, as shown in the following example: :: import cpl flames_obs_redchain = cpl.Recipe("flames_obs_redchain") [...] res = flames_obs_redchain( ..., param = {"debug":False, "flames_cal_orderpos.backsubdegx":2}) .. seealso:: `cpl.Recipe `_ for more information about the recipe object. Bug reports ----------- Please report any problems to `Jonas M. Larsen `_. Alternatively, you may send a report to the `ESO User Support Department `_. Copyright --------- This file is part of the FLAMES/UVES Pipeline Copyright (C) 2004, 2005, 2006, 2007 European Southern Observatory This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02111-1307 USA .. codeauthor:: Jonas M. Larsen