from jdaviz.configs.specviz import Specviz
from jdaviz.core.helpers import ConfigHelper
from jdaviz.core.events import SnackbarMessage
from jdaviz.configs.default.plugins.line_lists.line_list_mixin import LineListMixin
from jdaviz.configs.specviz2d.plugins.spectral_extraction.spectral_extraction import SpectralExtraction # noqa
__all__ = ['Specviz2d']
[docs]
class Specviz2d(ConfigHelper, LineListMixin):
"""Specviz2D Helper class"""
_default_configuration = "specviz2d"
_default_spectrum_viewer_reference_name = "spectrum-viewer"
_default_spectrum_2d_viewer_reference_name = "spectrum-2d-viewer"
_default_table_viewer_reference_name = "table-viewer"
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
@property
def specviz(self):
"""
A Specviz helper (`~jdaviz.configs.specviz.helper.Specviz`) for the Jdaviz
application that is wrapped by Specviz2d.
"""
if not hasattr(self, '_specviz'):
self._specviz = Specviz(app=self.app)
return self._specviz
[docs]
def load_data(self, spectrum_2d=None, spectrum_1d=None, spectrum_1d_label=None,
spectrum_2d_label=None, show_in_viewer=True, ext=1,
transpose=False):
"""
Load and parse a pair of corresponding 1D and 2D spectra.
Parameters
----------
spectrum_2d: str
A spectrum as translatable container objects (e.g.,
``Spectrum1D``) that can be read by glue-jupyter. Alternatively,
can be a string file path.
spectrum_1d: str or Spectrum1D
A spectrum as translatable container objects (e.g.,
``Spectrum1D``) that can be read by glue-jupyter. Alternatively,
can be a string file path.
spectrum_1d_label : str
String representing the label for the data item loaded via
``spectrum_1d``.
spectrum_2d_label : str
String representing the label for the data item loaded via
``spectrum_2d``.
show_in_viewer : bool
Show data in viewer(s).
ext : int, optional
Extension of the input ``spectrum_2d`` file to load. Defaults to 1.
transpose : bool, optional
Flag to transpose the 2D data array before loading. Useful for uncalibrated
data that is dispersed vertically, to change it to horizontal dispersion.
"""
if spectrum_2d is None and spectrum_1d is None:
raise ValueError('Must provide spectrum_2d or spectrum_1d but none given.')
if spectrum_2d_label is None:
spectrum_2d_label = "Spectrum 2D"
elif spectrum_2d_label[-2:] != "2D":
spectrum_2d_label = "{} 2D".format(spectrum_2d_label)
if spectrum_1d_label is None:
spectrum_1d_label = spectrum_2d_label.replace("2D", "1D")
load_1d = False
if spectrum_2d is not None:
self.app.load_data(spectrum_2d, parser_reference="mosviz-spec2d-parser",
data_labels=spectrum_2d_label,
show_in_viewer=False, add_to_table=False,
ext=ext, transpose=transpose)
# Passing show_in_viewer into app.load_data does not work anymore,
# so we force it to show here.
if show_in_viewer:
self.app.add_data_to_viewer(
self._default_spectrum_2d_viewer_reference_name, spectrum_2d_label
)
# Collapse the 2D spectrum to 1D if no 1D spectrum provided
if spectrum_1d is None:
# create a non-interactive (so that it does not create duplicate marks with the
# plugin-instance created later) instance of the SpectralExtraction plugin,
# and use the defaults to generate the initial 1D extracted spectrum
spext = SpectralExtraction(
app=self.app, interactive=False,
spectrum_viewer_reference_name=self._default_spectrum_viewer_reference_name,
spectrum_2d_viewer_reference_name=(
self._default_spectrum_2d_viewer_reference_name
)
)
# for some reason, the trailets are resetting to their default values even
# though _trace_dataset_selected was called internally to set them to reasonable
# new defaults. We'll just call it again manually.
spext._trace_dataset_selected()
try:
spext.export_extract_spectrum(add_data=True)
except Exception:
msg = SnackbarMessage(
"Automatic spectrum extraction failed. See the spectral extraction"
" plugin to perform a custom extraction",
color='error', sender=self, timeout=10000)
else:
# Warn that this shouldn't be used for science
msg = SnackbarMessage(
"The extracted 1D spectrum was generated automatically."
" See the spectral extraction plugin for details or to"
" perform a custom extraction.",
color='warning', sender=self, timeout=10000)
self.app.hub.broadcast(msg)
else:
load_1d = True
else:
load_1d = True
if load_1d:
self.app.load_data(
spectrum_1d, data_label=spectrum_1d_label,
parser_reference="specviz-spectrum1d-parser",
show_in_viewer=show_in_viewer,
)
[docs]
def load_trace(self, trace, data_label, show_in_viewer=True):
"""
Load a trace object and load into the spectrum-2d-viewer
Parameters
----------
trace : Trace
A specreduce trace object
data_label : str
String representing the label
show_in_viewer : bool
Whether to load into the spectrum-2d-viewer.
"""
self.app.add_data(trace, data_label=data_label)
if show_in_viewer:
self.app.add_data_to_viewer(
self._default_spectrum_2d_viewer_reference_name, data_label
)
[docs]
def get_data(self, data_label=None, spectral_subset=None, cls=None):
"""
Returns data with name equal to data_label of type cls with subsets applied from
spectral_subset.
Parameters
----------
data_label : str, optional
Provide a label to retrieve a specific data set from data_collection.
spectral_subset : str, optional
Spectral subset applied to data.
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, spectral_subset=spectral_subset, cls=cls)
