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add config helper for cubic data like cubeviz and rampviz
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,93 @@ | ||
| from jdaviz.core.helpers import CubeConfigHelper | ||
| from jdaviz.core.events import SliceSelectSliceMessage | ||
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| __all__ = ['Rampviz'] | ||
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| class Rampviz(CubeConfigHelper): | ||
| """Rampviz Helper class""" | ||
| _default_configuration = 'rampviz' | ||
| _default_profile_viewer_reference_name = "integration-viewer" | ||
| _default_diff_viewer_reference_name = "diff-viewer" | ||
| _default_group_viewer_reference_name = "group-viewer" | ||
| _default_image_viewer_reference_name = "image-viewer" | ||
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| _loaded_flux_cube = None | ||
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| def __init__(self, *args, **kwargs): | ||
| super().__init__(*args, **kwargs) | ||
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| def load_data(self, data, data_label=None, override_cube_limit=False, **kwargs): | ||
| """ | ||
| Load and parse a data cube with Cubeviz. | ||
| (Note that only one cube may be loaded per Cubeviz instance.) | ||
| Parameters | ||
| ---------- | ||
| data : str, `~astropy.io.fits.HDUList`, or ndarray | ||
| A string file path, astropy FITS object pointing to the | ||
| data cube, a spectrum object, or a Numpy array cube. | ||
| If plain array is given, axes order must be ``(x, y, z)``. | ||
| data_label : str or `None` | ||
| Data label to go with the given data. If not given, | ||
| one will be automatically generated. | ||
| override_cube_limit : bool | ||
| Override internal cube count limitation and load the data anyway. | ||
| Setting this to `True` is not recommended unless you know what | ||
| you are doing. | ||
| **kwargs : dict | ||
| Extra keywords accepted by Jdaviz application-level parser. | ||
| """ | ||
| if not override_cube_limit and len(self.app.state.data_items) != 0: | ||
| raise RuntimeError('Only one cube may be loaded per Cubeviz instance') | ||
| if data_label: | ||
| kwargs['data_label'] = data_label | ||
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| super().load_data(data, parser_reference="cubeviz-data-parser", **kwargs) | ||
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| def select_group(self, group_index): | ||
| """ | ||
| Select the slice closest to the provided wavelength. | ||
| Parameters | ||
| ---------- | ||
| group_index : float | ||
| Group index to select in units of the x-axis of the integration. | ||
| The nearest group will be selected if "snap to slice" is enabled | ||
| in the slice plugin. | ||
| """ | ||
| if not isinstance(group_index, int): | ||
| raise TypeError("group_index must be an integer") | ||
| if slice < 0: | ||
| raise ValueError("group_index must be positive") | ||
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| msg = SliceSelectSliceMessage(value=group_index, sender=self) | ||
| self.app.hub.broadcast(msg) | ||
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| def get_data(self, data_label=None, spatial_subset=None, | ||
| temporal_subset=None, cls=None, use_display_units=False): | ||
| """ | ||
| Returns data with name equal to ``data_label`` of type ``cls`` with subsets applied from | ||
| ``spectral_subset``, if applicable. | ||
| Parameters | ||
| ---------- | ||
| data_label : str, optional | ||
| Provide a label to retrieve a specific data set from data_collection. | ||
| spatial_subset : str, optional | ||
| Spatial subset applied to data. Only applicable if ``data_label`` points to a cube or | ||
| image. To extract a spectrum from a cube, use the spectral extraction plugin instead. | ||
| temporal_subset : str, optional | ||
| cls : `~specutils.Spectrum1D`, `~astropy.nddata.CCDData`, optional | ||
| The type that data will be returned as. | ||
| Returns | ||
| ------- | ||
| data : cls | ||
| Data is returned as type cls with subsets applied. | ||
| """ | ||
| return self._get_data(data_label=data_label, spatial_subset=spatial_subset, | ||
| temporal_subset=temporal_subset, | ||
| cls=cls, use_display_units=use_display_units) |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,177 @@ | ||
| import os | ||
| import numpy as np | ||
| from astropy.io import fits | ||
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| from jdaviz.utils import download_uri_to_path | ||
| from jdaviz.configs.cubeviz.plugins.parsers import ( | ||
| _parse_ndarray, _parse_hdulist, _parse_gif | ||
| ) | ||
| from jdaviz.core.registries import data_parser_registry | ||
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| try: | ||
| from roman_datamodels import datamodels as rdd | ||
| except ImportError: | ||
| HAS_ROMAN_DATAMODELS = False | ||
| else: | ||
| HAS_ROMAN_DATAMODELS = True | ||
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| @data_parser_registry("rampviz-data-parser") | ||
| def parse_data(app, file_obj, data_type=None, data_label=None, | ||
| parent=None, cache=None, local_path=None, timeout=None): | ||
| """ | ||
| Attempts to parse a data file and auto-populate available viewers in | ||
| rampviz. | ||
| Parameters | ||
| ---------- | ||
| app : `~jdaviz.app.Application` | ||
| The application-level object used to reference the viewers. | ||
| file_obj : str | ||
| The path to a cube-like data file. | ||
| data_type : str, {'flux', 'mask', 'uncert'} | ||
| The data type used to explicitly differentiate parsed data. | ||
| data_label : str, optional | ||
| The label to be applied to the Glue data component. | ||
| parent : str, optional | ||
| Data label for "parent" data to associate with the loaded data as "child". | ||
| cache : None, bool, or str | ||
| Cache the downloaded file if the data are retrieved by a query | ||
| to a URL or URI. | ||
| local_path : str, optional | ||
| Cache remote files to this path. This is only used if data is | ||
| requested from `astroquery.mast`. | ||
| timeout : float, optional | ||
| If downloading from a remote URI, set the timeout limit for | ||
| remote requests in seconds (passed to | ||
| `~astropy.utils.data.download_file` or | ||
| `~astroquery.mast.Conf.timeout`). | ||
| """ | ||
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| flux_viewer_reference_name = app._jdaviz_helper._default_group_viewer_reference_name | ||
| uncert_viewer_reference_name = app._jdaviz_helper._default_diff_viewer_reference_name | ||
| spectrum_viewer_reference_name = app._jdaviz_helper._default_profile_viewer_reference_name | ||
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| if data_type is not None and data_type.lower() not in ('flux', 'mask', 'uncert'): | ||
| raise TypeError("Data type must be one of 'flux', 'mask', or 'uncert' " | ||
| f"but got '{data_type}'") | ||
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| # If the file object is an hdulist or a string, use the generic parser for | ||
| # fits files. | ||
| # TODO: this currently only supports fits files. We will want to make this | ||
| # generic enough to work with other file types (e.g. ASDF). For now, this | ||
| # supports MaNGA and JWST data. | ||
| if isinstance(file_obj, fits.hdu.hdulist.HDUList): | ||
| _parse_hdulist( | ||
| app, file_obj, file_name=data_label, | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| uncert_viewer_reference_name=uncert_viewer_reference_name | ||
| ) | ||
| elif isinstance(file_obj, str): | ||
| if file_obj.lower().endswith('.gif'): # pragma: no cover | ||
| _parse_gif(app, file_obj, data_label, | ||
| flux_viewer_reference_name=flux_viewer_reference_name) | ||
| return | ||
| elif file_obj.lower().endswith('.asdf'): | ||
| if not HAS_ROMAN_DATAMODELS: | ||
| raise ImportError( | ||
| "ASDF detected but roman-datamodels is not installed." | ||
| ) | ||
| with rdd.open(file_obj) as pf: | ||
| _roman_3d_to_glue_data( | ||
| app, pf, data_label, | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| spectrum_viewer_reference_name=spectrum_viewer_reference_name, | ||
| uncert_viewer_reference_name=uncert_viewer_reference_name | ||
| ) | ||
| return | ||
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| # try parsing file_obj as a URI/URL: | ||
| file_obj = download_uri_to_path( | ||
| file_obj, cache=cache, local_path=local_path, timeout=timeout | ||
| ) | ||
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| file_name = os.path.basename(file_obj) | ||
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| with fits.open(file_obj) as hdulist: | ||
| _parse_hdulist( | ||
| app, hdulist, file_name=data_label or file_name, | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| uncert_viewer_reference_name=uncert_viewer_reference_name | ||
| ) | ||
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| elif isinstance(file_obj, np.ndarray) and file_obj.ndim == 3: | ||
| _parse_ndarray(app, file_obj, data_label=data_label, data_type=data_type, | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| uncert_viewer_reference_name=uncert_viewer_reference_name) | ||
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| app.get_tray_item_from_name("Spectral Extraction").disabled_msg = "" | ||
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| elif HAS_ROMAN_DATAMODELS and isinstance(file_obj, rdd.DataModel): | ||
| with rdd.open(file_obj) as pf: | ||
| _roman_3d_to_glue_data( | ||
| app, pf, data_label, | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| spectrum_viewer_reference_name=spectrum_viewer_reference_name, | ||
| uncert_viewer_reference_name=uncert_viewer_reference_name | ||
| ) | ||
|
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| else: | ||
| raise NotImplementedError(f'Unsupported data format: {file_obj}') | ||
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| def _roman_3d_to_glue_data( | ||
| app, file_obj, data_label, | ||
| flux_viewer_reference_name=None, | ||
| diff_viewer_reference_name=None, | ||
| integration_viewer_reference_name=None, | ||
| ): | ||
| """ | ||
| Parse a Roman 3D ramp cube file (Level 1), | ||
| usually with suffix '_uncal.asdf'. | ||
| """ | ||
| def _swap_axes(x): | ||
| # swap axes per the conventions of Roman cubes | ||
| # (group axis comes first) and the default in | ||
| # Cubeviz (wavelength axis expected last) | ||
| return np.swapaxes(x, 0, -1) | ||
|
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| # update viewer reference names for Roman ramp cubes: | ||
| # app._update_viewer_reference_name() | ||
|
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| data = file_obj.data | ||
|
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| if data_label is None: | ||
| data_label = app.return_data_label(file_obj) | ||
|
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| # last axis is the group axis, first two are spatial axes: | ||
| diff_data = np.vstack([ | ||
| # begin with a group of zeros, so | ||
| # that `diff_data.ndim == data.ndim` | ||
| np.zeros((1, *data[0].shape)), | ||
| np.diff(data, axis=0) | ||
| ]) | ||
|
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| # load the `data` cube into what's usually the "flux-viewer" | ||
| _parse_ndarray( | ||
| app, | ||
| file_obj=_swap_axes(data), | ||
| data_label=f"{data_label}[DATA]", | ||
| data_type="flux", | ||
| flux_viewer_reference_name=flux_viewer_reference_name, | ||
| ) | ||
|
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| # load the diff of the data cube | ||
| # into what's usually the "uncert-viewer" | ||
| _parse_ndarray( | ||
| app, | ||
| file_obj=_swap_axes(diff_data), | ||
| data_type="uncert", | ||
| data_label=f"{data_label}[DIFF]", | ||
| uncert_viewer_reference_name=diff_viewer_reference_name, | ||
| ) | ||
|
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| # the default collapse function in the profile viewer is "sum", | ||
| # but for ramp files, "median" is more useful: | ||
| viewer = app.get_viewer('integration-viewer') | ||
| viewer.state.function = 'median' |
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