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

[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): # Define input_new, because if input is ImageModel, it will # get recreated as a SlitModel input_new = if isinstance(input_new, ImageModel): slit_model = datamodels.SlitModel() slit_model.update(input_new, only="PRIMARY") slit_model.update(input_new, only="SCI") slit_model.meta.wcs = input_new.meta.wcs = input_new = slit_model # If single DataModel input, wrap in a ModelContainer if not isinstance(input_new, ModelContainer): input_models = datamodels.ModelContainer([input_new]) input_models.meta.resample.output = input_new.meta.filename self.blendheaders = False else: input_models = input_new # 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':'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"No NIRSpec DIRZPARS reffile") kwargs = self._set_spec_defaults() kwargs['blendheaders'] = self.blendheaders # Update user-supplied kwargs kwargs['allowed_memory'] = self.allowed_memory # 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], only="PRIMARY") result.update(input_models[0], only="SCI") for container in containers.values(): resamp = resample_spec.ResampleSpecData(container, **self.drizpars) drizzled_models = resamp.do_drizzle() for model in drizzled_models: model.meta.cal_step.resample = "COMPLETE" model.meta.asn.pool_name = input_models.meta.pool_name model.meta.asn.table_name = input_models.meta.table_name # Delete the BUNIT keyword for the ERR extension, so that datamodels # doesn't create an empty ERR extension (just for that keyword) if hasattr(model.meta, "bunit_err") and model.meta.bunit_err is not None: del model.meta.bunit_err update_s_region_spectral(model) # Everything resampled to single output model if len(drizzled_models) == 1: result.slits.append(drizzled_models[0]) if container[0].meta.bunit_data is not None: result.slits[-1].meta.bunit_data = container[0].meta.bunit_data else: # When each input is resampled to its own output for model in drizzled_models: result.slits.append(model) result.slits[-1].meta.bunit_data = container[0].meta.bunit_data 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.ImageModel` The resampled output, one per source """ resamp = resample_spec.ResampleSpecData(input_models, **self.drizpars) if input_models[0].meta.exposure.type == "MIR_LRS-FIXEDSLIT": bb = input_models[0].meta.wcs.bounding_box ((x1, x2), (y1, y2)) = bb xmin = int(min(x1, x2)) ymin = int(min(y1, y2)) xmax = int(max(x1, x2)) ymax = int(max(y1, y2)) drizzled_models = resamp.do_drizzle(xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax) else: drizzled_models = resamp.do_drizzle() result = drizzled_models[0] result.meta.cal_step.resample = "COMPLETE" result.meta.asn.pool_name = input_models.meta.pool_name result.meta.asn.table_name = input_models.meta.table_name # Delete BUNIT keyword for ERR extension to prevent datamodels from # creating an empty ERR extension (just for the keyword) if hasattr(result.meta, "bunit_err") and result.meta.bunit_err is not None: del result.meta.bunit_err update_s_region_spectral(result) result.meta.bunit_data = drizzled_models[0].meta.bunit_data return result