ResampleData¶
- class jwst.resample.resample.ResampleData(input_models, output=None, single=False, blendheaders=True, pixfrac=1.0, kernel='square', fillval='INDEF', wht_type='ivm', good_bits=0, pscale_ratio=1.0, pscale=None, **kwargs)[source]¶
Bases:
object
This is the controlling routine for the resampling process.
Notes
This routine performs the following operations:
1. Extracts parameter settings from input model, such as pixfrac, weight type, exposure time (if relevant), and kernel, and merges them with any user-provided values. 2. Creates output WCS based on input images and define mapping function between all input arrays and the output array. 3. Updates output data model with output arrays from drizzle, including a record of metadata from all input models.
- Parameters:
input_models (list of objects) – list of data models, one for each input image
output (str) – filename for output
kwargs (dict) –
Other parameters.
Note
output_shape
is in thex, y
order.Note
in_memory
controls whether or not the resampled array fromresample_many_to_many()
should be kept in memory or written out to disk and deleted from memory. Default value isTrue
to keep all products in memory.
Methods Summary
blend_output_metadata
(output_model)Create new output metadata based on blending all input metadata.
Pick the correct drizzling mode based on self.single
drizzle_arrays
(insci, inwht, input_wcs, ...)Low level routine for performing 'drizzle' operation on one image.
Resample many inputs to many outputs where outputs have a common frame.
Resample and coadd many inputs to a single output.
resample_variance_array
(name, output_model, ...)Resample variance arrays from self.input_models to the output_model
update_exposure_times
(output_model)Modify exposure time metadata in-place
Methods Documentation
- blend_output_metadata(output_model)[source]¶
Create new output metadata based on blending all input metadata.
- static drizzle_arrays(insci, inwht, input_wcs, output_wcs, outsci, outwht, outcon, uniqid=1, xmin=0, xmax=0, ymin=0, ymax=0, iscale=1.0, pixfrac=1.0, kernel='square', fillval='INDEF', wtscale=1.0)[source]¶
Low level routine for performing ‘drizzle’ operation on one image.
The interface is compatible with STScI code. All images are Python ndarrays, instead of filenames. File handling (input and output) is performed by the calling routine.
- Parameters:
insci (2d array) – A 2d numpy array containing the input image to be drizzled.
inwht (2d array) – A 2d numpy array containing the pixel by pixel weighting. Must have the same dimensions as insci. If none is supplied, the weighting is set to one.
input_wcs (gwcs.WCS object) – The world coordinate system of the input image.
output_wcs (gwcs.WCS object) – The world coordinate system of the output image.
outsci (2d array) – A 2d numpy array containing the output image produced by drizzling. On the first call it should be set to zero. Subsequent calls it will hold the intermediate results. This is modified in-place.
outwht (2d array) – A 2d numpy array containing the output counts. On the first call it should be set to zero. On subsequent calls it will hold the intermediate results. This is modified in-place.
outcon (2d or 3d array, optional) – A 2d or 3d numpy array holding a bitmap of which image was an input for each output pixel. Should be integer zero on first call. Subsequent calls hold intermediate results. This is modified in-place.
uniqid (int, optional) – The id number of the input image. Should be one the first time this function is called and incremented by one on each subsequent call.
xmin (int, optional) – This and the following three parameters set a bounding rectangle on the input image. Only pixels on the input image inside this rectangle will have their flux added to the output image. Xmin sets the minimum value of the x dimension. The x dimension is the dimension that varies quickest on the image. All four parameters are zero based, counting starts at zero.
xmax (int, optional) – Sets the maximum value of the x dimension on the bounding box of the input image. If
xmax = 0
, no maximum will be set in the x dimension (all pixels in a row of the input image will be resampled).ymin (int, optional) – Sets the minimum value in the y dimension on the bounding box. The y dimension varies less rapidly than the x and represents the line index on the input image.
ymax (int, optional) – Sets the maximum value in the y dimension. If
ymax = 0
, no maximum will be set in the y dimension (all pixels in a column of the input image will be resampled).iscale (float, optional) – A scale factor to be applied to pixel intensities of the input image before resampling.
pixfrac (float, optional) – The fraction of a pixel that the pixel flux is confined to. The default value of 1 has the pixel flux evenly spread across the image. A value of 0.5 confines it to half a pixel in the linear dimension, so the flux is confined to a quarter of the pixel area when the square kernel is used.
kernel (str, optional) – The name of the kernel used to combine the input. The choice of kernel controls the distribution of flux over the kernel. The kernel names are: “square”, “gaussian”, “point”, “tophat”, “turbo”, “lanczos2”, and “lanczos3”. The square kernel is the default.
fillval (str, optional) – The value a pixel is set to in the output if the input image does not overlap it. The default value of INDEF does not set a value.
- Returns:
A tuple with three values (a version string, the number of pixels)
on the input image that do not overlap the output image, and the
number of complete lines on the input image that do not overlap the
output input image.
- resample_many_to_many()[source]¶
Resample many inputs to many outputs where outputs have a common frame.
Coadd only different detectors of the same exposure, i.e. map NRCA5 and NRCB5 onto the same output image, as they image different areas of the sky.
Used for outlier detection
- resample_many_to_one()[source]¶
Resample and coadd many inputs to a single output.
Used for stage 3 resampling