Pipeline modules

This page contains a list of all available pipeline modules and a short description of what they are used for. Reading modules import data into the database, writing modules export data from the database, and processing modules run a specific task of the data reduction or analysis. More details on the design of the pipeline can be found in the Architecture section.

Note

All PynPoint classes ending with Module in their name (e.g. FitsReadingModule) are pipeline modules that can be added to an instance of Pypeline (see Pypeline section).

Important

The pipeline modules with multiprocessing functionalities are indicated with “CPU” in parentheses. The number of parallel processes can be set with the CPU parameter in the configuration file and the number of images that is simultaneously loaded into the memory with the MEMORY parameter. Pipeline modules that apply (in parallel) a function to subsets of images use a number of images per subset equal to MEMORY divided by CPU.

Important

The pipeline modules that are compatible with both regular imaging and integral field spectroscopy datasets (i.e. 3D and 4D data) are indicated with “IFS” in parentheses. All other modules are only compatible with regular imaging.

Reading modules

• FitsReadingModule (IFS): Import FITS files and relevant header information into the database.

• Hdf5ReadingModule: Import datasets and attributes from an HDF5 file (as created by PynPoint).

• AttributeReadingModule: Import a list of values as dataset attribute.

• ParangReadingModule: Import a list of parallactic angles as dataset attribute.

• WavelengthReadingModule: Import a list of calibrated wavelengths as dataset attribute.

• NearReadingModule (CPU): Import VLT/VISIR data for the NEAR experiment.

Writing modules

• FitsWritingModule: Export a dataset from the database to a FITS file.

• Hdf5WritingModule: Export part of the database to a new HDF5 file.

• TextWritingModule: Export a dataset to an ASCII file.

• AttributeWritingModule: Export a list of attribute values to an ASCII file.

• ParangWritingModule: Export the parallactic angles of a dataset to an ASCII file.

Processing modules

Background subtraction

• SimpleBackgroundSubtractionModule: Simple background subtraction for dithering datasets.

• MeanBackgroundSubtractionModule: Mean background subtraction for dithering datasets.

• LineSubtractionModule (CPU): Subtraction of striped detector artifacts.

• NoddingBackgroundModule: Background subtraction for nodding datasets.

Bad pixel cleaning

• BadPixelSigmaFilterModule (CPU): Find and replace bad pixels with a sigma filter.

• BadPixelInterpolationModule (CPU): Interpolate bad pixels with a spectral deconvolution technique.

• BadPixelMapModule: Create a bad pixel map from dark and flat images.

• BadPixelTimeFilterModule (CPU): Sigma clipping of bad pixels along the time dimension.

• ReplaceBadPixelsModule (CPU): Replace bad pixels based on a bad pixel map.

Basic processing

• SubtractImagesModule: Subtract two stacks of images.

• AddImagesModule: Add two stacks of images

• RotateImagesModule: Rotate a stack of images.

• RepeatImagesModule: Repeat a stack of images.

Centering

• StarAlignmentModule (CPU): Align the images with a cross-correlation.

• FitCenterModule (CPU): Fit the PSF with a 2D Gaussian or Moffat function.

• ShiftImagesModule: Shift a stack of images.

• WaffleCenteringModule (IFS): Use the waffle spots to center the images.

Dark and flat correction

• DarkCalibrationModule: Dark frame subtraction.

• FlatCalibrationModule: Flat field correction.

Denoising

• WaveletTimeDenoisingModule (CPU): Wavelet-based denoising in the time domain.

• TimeNormalizationModule (CPU): Normalize a stack of images.

Detection limits

• ContrastCurveModule (CPU): Compute a contrast curve.

• MassLimitsModule: Calculate mass limits from a contrast curve and an isochrones model grid.

Extract star

• StarExtractionModule (CPU): Locate and crop the position of the star.

• ExtractBinaryModule (CPU): Extract a PSF which rotates across a stack of images.

Filters

• GaussianFilterModule: Apply a Gaussian filter to the images.

Flux and position

• FakePlanetModule: Inject an artificial planet in a dataset.

• SimplexMinimizationModule: Determine the flux and position with a simplex minimization.

• FalsePositiveModule: Compute the signal-to-noise ratio and false positive fraction.

• MCMCsamplingModule (CPU): Estimate the flux and position of a planet with MCMC sampling.

• AperturePhotometryModule (CPU): Compute the integrated flux at a position.

• SystematicErrorModule: Compute the systematic errors on the flux and position.

Frame selection

• RemoveFramesModule: Remove images by their index number.

• FrameSelectionModule: Frame selection to remove low-quality image.

• RemoveLastFrameModule: Remove the last image of a VLT/NACO dataset.

• RemoveStartFramesModule: Remove images at the beginning of each original data cube.

• ImageStatisticsModule (CPU): Compute statistics of the pixel values for each image.

• FrameSimilarityModule (CPU): Compute different similarity measures of a set of images.

• SelectByAttributeModule: Select images by the ascending/descending attribute values.

• ResidualSelectionModule: Frame selection on the residuals of the PSF subtraction.

Image resizing

• CropImagesModule (IFS): Crop the images.

• ScaleImagesModule (CPU): Resample the images (spatially and/or in flux).

• AddLinesModule: Add pixel lines on the sides of the images.

• RemoveLinesModule: Remove pixel lines from the sides of the images.

PCA background subtraction

• PCABackgroundPreparationModule: Preparation for the PCA-based background subtraction.

• PCABackgroundSubtractionModule: PCA-based background subtraction.

• DitheringBackgroundModule: Wrapper for background subtraction of dithering datasets.

PSF preparation

• PSFpreparationModule (IFS): Mask the images before the PSF subtraction.

• AngleInterpolationModule: Interpolate the parallactic angles between the start and end values.

• AngleCalculationModule: Calculate the parallactic angles.

• SortParangModule (IFS): Sort the images by parallactic angle.

• SDIpreparationModule: Prepare the images for SDI.

PSF subtraction

• PcaPsfSubtractionModule (CPU, IFS): PSF subtraction with PCA.

• ClassicalADIModule (CPU): PSF subtraction with classical ADI.

Stacking

• StackAndSubsetModule: Stack and/or select a random subset of the images.

• StackCubesModule: Collapse each original data cube separately.

• DerotateAndStackModule (IFS): Derotate and/or stack the images.

• CombineTagsModule: Combine multiple database tags into a single dataset.