Inheritance diagram for lsst.pipe.tasks.fit_coadd_multiband.CoaddMultibandFitInputConnections:
Public Member Functions | |
| adjustQuantum (self, inputs, outputs, label, data_id) | |
Static Public Attributes | |
| cat_ref | |
| cats_meas | |
| coadds | |
| models_psf | |
| models_scarlet | |
Detailed Description
Definition at line 56 of file fit_coadd_multiband.py.
Member Function Documentation
◆ adjustQuantum()
| lsst.pipe.tasks.fit_coadd_multiband.CoaddMultibandFitInputConnections.adjustQuantum | ( | self, | |
| inputs, | |||
| outputs, | |||
| label, | |||
| data_id ) |
Validates the `lsst.daf.butler.DatasetRef` bands against the
subtask's list of bands to fit and drops unnecessary bands.
Parameters
----------
inputs : `dict`
Dictionary whose keys are an input (regular or prerequisite)
connection name and whose values are a tuple of the connection
instance and a collection of associated `DatasetRef` objects.
The exact type of the nested collections is unspecified; it can be
assumed to be multi-pass iterable and support `len` and ``in``, but
it should not be mutated in place. In contrast, the outer
dictionaries are guaranteed to be temporary copies that are true
`dict` instances, and hence may be modified and even returned; this
is especially useful for delegating to `super` (see notes below).
outputs : `Mapping`
Mapping of output datasets, with the same structure as ``inputs``.
label : `str`
Label for this task in the pipeline (should be used in all
diagnostic messages).
data_id : `lsst.daf.butler.DataCoordinate`
Data ID for this quantum in the pipeline (should be used in all
diagnostic messages).
Returns
-------
adjusted_inputs : `Mapping`
Mapping of the same form as ``inputs`` with updated containers of
input `DatasetRef` objects. All inputs involving the 'band'
dimension are adjusted to put them in consistent order and remove
unneeded bands.
adjusted_outputs : `Mapping`
Mapping of updated output datasets; always empty for this task.
Raises
------
lsst.pipe.base.NoWorkFound
Raised if there are not enough of the right bands to run the task
on this quantum.
Definition at line 96 of file fit_coadd_multiband.py.
96 def adjustQuantum(self, inputs, outputs, label, data_id):
97 """Validates the `lsst.daf.butler.DatasetRef` bands against the
98 subtask's list of bands to fit and drops unnecessary bands.
99
100 Parameters
101 ----------
102 inputs : `dict`
103 Dictionary whose keys are an input (regular or prerequisite)
104 connection name and whose values are a tuple of the connection
105 instance and a collection of associated `DatasetRef` objects.
106 The exact type of the nested collections is unspecified; it can be
107 assumed to be multi-pass iterable and support `len` and ``in``, but
108 it should not be mutated in place. In contrast, the outer
109 dictionaries are guaranteed to be temporary copies that are true
110 `dict` instances, and hence may be modified and even returned; this
111 is especially useful for delegating to `super` (see notes below).
112 outputs : `Mapping`
113 Mapping of output datasets, with the same structure as ``inputs``.
114 label : `str`
115 Label for this task in the pipeline (should be used in all
116 diagnostic messages).
117 data_id : `lsst.daf.butler.DataCoordinate`
118 Data ID for this quantum in the pipeline (should be used in all
119 diagnostic messages).
120
121 Returns
122 -------
123 adjusted_inputs : `Mapping`
124 Mapping of the same form as ``inputs`` with updated containers of
125 input `DatasetRef` objects. All inputs involving the 'band'
126 dimension are adjusted to put them in consistent order and remove
127 unneeded bands.
128 adjusted_outputs : `Mapping`
129 Mapping of updated output datasets; always empty for this task.
130
131 Raises
132 ------
133 lsst.pipe.base.NoWorkFound
134 Raised if there are not enough of the right bands to run the task
135 on this quantum.
136 """
137 # Check which bands are going to be fit
138 bands_fit, bands_read_only = self.config.get_band_sets()
139 bands_needed = bands_fit + [band for band in bands_read_only if band not in bands_fit]
140
141 adjusted_inputs = {}
142 for connection_name, (connection, dataset_refs) in inputs.items():
143 # Datasets without bands in their dimensions should be fine
144 if 'band' in connection.dimensions:
145 datasets_by_band = {dref.dataId['band']: dref for dref in dataset_refs}
147 raise pipeBase.NoWorkFound(
148 f'DatasetRefs={dataset_refs} have data with bands in the'
149 f' set={set(datasets_by_band.keys())},'
150 f' which is not a superset of the required bands={bands_needed} defined by'
151 f' {self.config.__class__}.fit_coadd_multiband='
152 f'{self.config.fit_coadd_multiband._value.__class__}\'s attributes'
153 f' bands_fit={bands_fit} and bands_read_only()={bands_read_only}.'
154 f' Add the required bands={set(bands_needed).difference(datasets_by_band.keys())}.'
155 )
156 # Adjust all datasets with band dimensions to include just
157 # the needed bands, in consistent order.
158 adjusted_inputs[connection_name] = (
159 connection,
160 [datasets_by_band[band] for band in bands_needed]
161 )
162
163 # Delegate to super for more checks.
164 inputs.update(adjusted_inputs)
165 super().adjustQuantum(inputs, outputs, label, data_id)
166 return adjusted_inputs, {}
167
168
Member Data Documentation
◆ cat_ref
|
static |
Initial value:
= cT.Input(
doc="Reference multiband source catalog",
name="{name_coadd}Coadd_ref",
storageClass="SourceCatalog",
dimensions=("tract", "patch", "skymap"),
)
Definition at line 61 of file fit_coadd_multiband.py.
◆ cats_meas
|
static |
Initial value:
= cT.Input(
doc="Deblended single-band source catalogs",
name="{name_coadd}Coadd_meas",
storageClass="SourceCatalog",
dimensions=("tract", "patch", "band", "skymap"),
multiple=True,
)
Definition at line 67 of file fit_coadd_multiband.py.
◆ coadds
|
static |
Initial value:
= cT.Input(
doc="Exposures on which to run fits",
name="{name_coadd}Coadd_calexp",
storageClass="ExposureF",
dimensions=("tract", "patch", "band", "skymap"),
multiple=True,
)
Definition at line 74 of file fit_coadd_multiband.py.
◆ models_psf
|
static |
Initial value:
= cT.Input(
doc="Input PSF model parameter catalog",
# Consider allowing independent psf fit method
name="{name_coadd}Coadd_psfs_{name_method}",
storageClass="ArrowAstropy",
dimensions=("tract", "patch", "band", "skymap"),
multiple=True,
)
Definition at line 81 of file fit_coadd_multiband.py.
◆ models_scarlet
|
static |
Initial value:
= pipeBase.connectionTypes.Input(
doc="Multiband scarlet models produced by the deblender",
name="{name_coadd}Coadd_scarletModelData",
storageClass="ScarletModelData",
dimensions=("tract", "patch", "skymap"),
)
Definition at line 89 of file fit_coadd_multiband.py.
The documentation for this class was generated from the following file:
- /j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/pipe_tasks/g95921f966b+dffe86973d/python/lsst/pipe/tasks/fit_coadd_multiband.py
