Source code for jwst.resample.resample_spec_step

__all__ = ["ResampleSpecStep"]

from .. import datamodels
from ..datamodels import MultiSlitModel, ModelContainer, ImageModel
from . import resample_spec, ResampleStep
from ..exp_to_source import multislit_to_container
from ..assign_wcs.util import update_s_region_spectral


# Force use of all DQ flagged data except for DO_NOT_USE and NON_SCIENCE
GOOD_BITS = '~DO_NOT_USE+NON_SCIENCE'


[docs]class ResampleSpecStep(ResampleStep): """ ResampleSpecStep: Resample input data onto a regular grid using the drizzle algorithm. Parameters ----------- input : `~jwst.datamodels.MultiSlitModel`, `~jwst.datamodels.ModelContainer`, Association A singe datamodel, a container of datamodels, or an association file """
[docs] def process(self, input): input_new = datamodels.open(input) # Convert ImageModel to SlitModel (needed for MIRI LRS) if isinstance(input_new, ImageModel): input_new = datamodels.SlitModel(input_new) if isinstance(input_new, ModelContainer): input_models = input_new try: output = input_models.meta.asn_table.products[0].name except AttributeError: # NIRSpec MOS data goes through this path, as the container # is only ModelContainer-like, and doesn't have an asn_table # attribute attached. Output name handling gets done in # _process_multislit() via the update method # TODO: the container-like object should retain asn_table output = None else: input_models = datamodels.ModelContainer([input_new]) output = input_new.meta.filename self.blendheaders = False # Get the drizpars reference file for reftype in self.reference_file_types: ref_filename = self.get_reference_file(input_models[0], reftype) if ref_filename != 'N/A': self.log.info('Drizpars reference file: {}'.format(ref_filename)) kwargs = self.get_drizpars(ref_filename, input_models) else: # Deal with NIRSpec, which currently has no default drizpars reffile self.log.info("No NIRSpec DIRZPARS reffile") kwargs = self._set_spec_defaults() kwargs['blendheaders'] = self.blendheaders kwargs['allowed_memory'] = self.allowed_memory kwargs['output'] = output # Call resampling self.drizpars = kwargs if isinstance(input_models[0], MultiSlitModel): result = self._process_multislit(input_models) elif len(input_models[0].data.shape) != 2: # resample can only handle 2D images, not 3D cubes, etc raise RuntimeError("Input {} is not a 2D image.".format(input_models[0])) else: # result is a SlitModel result = self._process_slit(input_models) # Update ASNTABLE in output result.meta.asn.table_name = input_models[0].meta.asn.table_name result.meta.filetype = 'resampled' return result
def _process_multislit(self, input_models): """ Resample MultiSlit data Parameters ---------- input : `~jwst.datamodels.ModelContainer` A container of `~jwst.datamodels.MultiSlitModel` Returns ------- result : `~jwst.datamodels.MultiSlitModel` The resampled output, one per source """ containers = multislit_to_container(input_models) result = datamodels.MultiSlitModel() result.update(input_models[0]) for container in containers.values(): resamp = resample_spec.ResampleSpecData(container, **self.drizpars) drizzled_models = resamp.do_drizzle() for model in drizzled_models: update_s_region_spectral(model) result.slits.append(model) result.meta.cal_step.resample = "COMPLETE" result.meta.asn.pool_name = input_models.asn_pool_name result.meta.asn.table_name = input_models.asn_table_name result.meta.resample.pixel_scale_ratio = self.pixel_scale_ratio result.meta.resample.pixfrac = self.pixfrac return result def _process_slit(self, input_models): """ Resample Slit data Parameters ---------- input : `~jwst.datamodels.ModelContainer` A container of `~jwst.datamodels.ImageModel` or `~jwst.datamodels.SlitModel` Returns ------- result : `~jwst.datamodels.SlitModel` The resampled output """ resamp = resample_spec.ResampleSpecData(input_models, **self.drizpars) drizzled_models = resamp.do_drizzle() result = drizzled_models[0] result.meta.cal_step.resample = "COMPLETE" result.meta.asn.pool_name = input_models.asn_pool_name result.meta.asn.table_name = input_models.asn_table_name result.meta.bunit_data = drizzled_models[0].meta.bunit_data result.meta.resample.pixel_scale_ratio = self.pixel_scale_ratio result.meta.resample.pixfrac = self.pixfrac update_s_region_spectral(result) return result