def test_component_unit_header(tmpdir):
from astropy import units as u
filename = tmpdir.join('test3.fits').strpath
data = Data(x=np.arange(6).reshape(2, 3),
y=(np.arange(6) * 2).reshape(2, 3),
z=(np.arange(6) * 2).reshape(2, 3))
wcs = WCS()
data.coords = WCSCoordinates(wcs=wcs)
unit1 = data.get_component("x").units = u.m / u.s
unit2 = data.get_component("y").units = u.Jy
unit3 = data.get_component("z").units = ""
fits_writer(filename, data)
with fits.open(filename) as hdulist:
assert len(hdulist) == 3
bunit = hdulist['x'].header.get('BUNIT')
assert u.Unit(bunit) == unit1
bunit = hdulist['y'].header.get('BUNIT')
assert u.Unit(bunit) == unit2
bunit = hdulist['z'].header.get('BUNIT')
assert bunit == unit3
def to_data(self, obj):
coords = SpectralCoordinates(obj.spectral_axis)
data = Data(coords=coords)
data['flux'] = obj.flux
data[
'uncertainty'] = obj.uncertainty.array if obj.uncertainty is not None else np.ones(
obj.flux.shape)
data['mask'] = obj.mask if hasattr(
obj, 'mask') and obj.mask is not None else np.zeros(
obj.flux.shape).astype(bool)
data.get_component('flux').units = str(obj.unit)
data.get_component('uncertainty').units = str(obj.unit)
data.meta.update(obj.meta)
return data
def to_data(self, obj):
coords = SpectralCoordinates(obj.spectral_axis)
data = Data(coords=coords)
data['flux'] = obj.flux
data.get_component('flux').units = str(obj.unit)
data.meta.update(obj.meta)
return data
def to_data(self, obj):
if obj.wcs is None:
coords = None
else:
coords = WCSCoordinates(wcs=obj.wcs)
data = Data(coords=coords)
data['data'] = obj.data
data.get_component('data').units = str(obj.unit)
data.meta.update(obj.meta)
return data
def vue_collapse(self, *args, **kwargs):
# Collapsing over the spectral axis. Cut out the desired spectral
# region. Defaults to the entire spectrum.
spec_min = float(self.spectral_min) * u.Unit(self.spectral_unit)
spec_max = float(self.spectral_max) * u.Unit(self.spectral_unit)
with warnings.catch_warnings():
warnings.filterwarnings('ignore',
message='No observer defined on WCS')
spec = spectral_slab(self._selected_cube, spec_min, spec_max)
# Spatial-spatial image only.
collapsed_spec = spec.collapse(self.selected_func.lower(),
axis=-1).T # Quantity
data = Data()
data['flux'] = collapsed_spec.value
data.get_component('flux').units = str(collapsed_spec.unit)
self._label_counter += 1
label = f"Collapsed {self._label_counter} {self._selected_data.label}"
self.data_collection[label] = data
# Link the new dataset pixel-wise to the original dataset. In general
# direct pixel to pixel links are the most efficient and should be
# used in cases like this where we know there is a 1-to-1 mapping of
# pixel coordinates.
# Spatial-spatial image only.
pix_id_1 = self._selected_data.pixel_component_ids[
0] # Pixel Axis 0 [z]
pix_id_1c = self.data_collection[label].pixel_component_ids[
0] # Pixel Axis 0 [y]
pix_id_2 = self._selected_data.pixel_component_ids[
1] # Pixel Axis 1 [y]
pix_id_2c = self.data_collection[label].pixel_component_ids[
1] # Pixel Axis 1 [x]
self.data_collection.add_link(
[LinkSame(pix_id_1, pix_id_1c),
LinkSame(pix_id_2, pix_id_2c)])
snackbar_message = SnackbarMessage(
f"Data set '{self._selected_data.label}' collapsed successfully.",
color="success",
sender=self)
self.hub.broadcast(snackbar_message)
# Spatial-spatial image only.
if self.selected_viewer != 'None':
# replace the contents in the selected viewer with the results from this plugin
self.app.add_data_to_viewer(self.viewer_to_id.get(
self.selected_viewer),
label,
clear_other_data=True)
def to_data(self, obj):
coords = SpectralCoordinates(obj.spectral_axis)
data = Data(coords=coords)
data['flux'] = obj.flux
data.get_component('flux').units = str(obj.unit)
# Include uncertainties if they exist
if obj.uncertainty is not None:
data['uncertainty'] = obj.uncertainty.quantity
data.get_component('uncertainty').units = str(obj.uncertainty.unit)
data.meta.update(
{'uncertainty_type': obj.uncertainty.uncertainty_type})
# Include mask if it exists
if obj.mask is not None:
data['mask'] = obj.mask
data.meta.update(obj.meta)
return data
def to_data(self, obj):
# Glue expects spectral axis first for cubes (opposite of specutils).
# Swap the spectral axis to first here. to_object doesn't need this because
# Spectrum1D does it automatically on initialization.
if len(obj.flux.shape) == 3:
data = Data(coords=obj.wcs.swapaxes(-1, 0))
data['flux'] = np.swapaxes(obj.flux, -1, 0)
data.get_component('flux').units = str(obj.unit)
else:
if obj.flux.ndim == 1 and obj.wcs.world_n_dim == 1 and isinstance(
obj.wcs, GWCS):
data = Data(coords=SpectralCoordinates(obj.spectral_axis))
elif obj.flux.ndim == 2 and obj.wcs.world_n_dim == 1:
data = Data(coords=PaddedSpectrumWCS(obj.wcs))
else:
data = Data(coords=obj.wcs)
data['flux'] = obj.flux
data.get_component('flux').units = str(obj.unit)
# Include uncertainties if they exist
if obj.uncertainty is not None:
if len(obj.flux.shape) == 3:
data['uncertainty'] = np.swapaxes(obj.uncertainty.quantity, -1,
0)
else:
data['uncertainty'] = obj.uncertainty.quantity
data.get_component('uncertainty').units = str(obj.uncertainty.unit)
data.meta.update(
{'uncertainty_type': obj.uncertainty.uncertainty_type})
# Include mask if it exists
if obj.mask is not None:
if len(obj.flux.shape) == 3:
data['mask'] = np.swapaxes(obj.mask, -1, 0)
else:
data['mask'] = obj.mask
data.meta.update(obj.meta)
return data
def vue_collapse(self, *args, **kwargs):
try:
spec = self._selected_data.get_object(cls=SpectralCube)
except AttributeError:
snackbar_message = SnackbarMessage(
"Unable to perform collapse over selected data.",
color="error",
sender=self)
self.hub.broadcast(snackbar_message)
return
# If collapsing over the spectral axis, cut out the desired spectral
# region. Defaults to the entire spectrum.
if self.selected_axis == 0:
spec_min = float(self.spectral_min) * u.Unit(self.spectral_unit)
spec_max = float(self.spectral_max) * u.Unit(self.spectral_unit)
spec = spec.spectral_slab(spec_min, spec_max)
collapsed_spec = getattr(
spec, self.selected_func.lower())(axis=self.selected_axis)
data = Data(coords=collapsed_spec.wcs)
data['flux'] = collapsed_spec.filled_data[...]
data.get_component('flux').units = str(collapsed_spec.unit)
data.meta.update(collapsed_spec.meta)
self._label_counter += 1
label = f"Collapsed {self._label_counter} {self._selected_data.label}"
self.data_collection[label] = data
# Link the new dataset pixel-wise to the original dataset. In general
# direct pixel to pixel links are the most efficient and should be
# used in cases like this where we know there is a 1-to-1 mapping of
# pixel coordinates. Here which axes are linked to which depends on
# the selected axis.
(i1, i2), (i1c, i2c) = AXES_MAPPING[self.selected_axis]
pix_id_1 = self._selected_data.pixel_component_ids[i1]
pix_id_1c = self.data_collection[label].pixel_component_ids[i1c]
pix_id_2 = self._selected_data.pixel_component_ids[i2]
pix_id_2c = self.data_collection[label].pixel_component_ids[i2c]
self.data_collection.add_link(LinkSame(pix_id_1, pix_id_1c))
self.data_collection.add_link(LinkSame(pix_id_2, pix_id_2c))
snackbar_message = SnackbarMessage(
f"Data set '{self._selected_data.label}' collapsed successfully.",
color="success",
sender=self)
self.hub.broadcast(snackbar_message)
def load_data(self, data_filenames):
"""
Load the data based on the extensions defined in the matching YAML file. THen
create the datacube and return it.
:param data_filename:
:return:
"""
print("in load data")
label = None
data = None
for data_filename in data_filenames.split(','):
hdulist = fits.open(data_filename)
print(hdulist)
if not label:
label = "{}: {}".format(self._name,
splitext(basename(data_filename))[0])
data = Data(label=label)
# this attribute is used to indicate to the cubeviz layout that
# this is a cubeviz-specific data component.
data.meta[CUBEVIZ_LAYOUT] = self._name
data_coords_set = False
for ii, hdu in enumerate(hdulist):
if 'NAXIS' in hdu.header and hdu.header['NAXIS'] == 3:
# Set the coords based on the first 3D HDU
if not data_coords_set:
data.coords = coordinates_from_header(hdu.header)
data_coords_set = True
component_name = str(ii)
if 'EXTNAME' in hdu.header:
component_name = hdu.header['EXTNAME']
# The data must be floating point as spectralcube is expecting floating point data
data.add_component(component=hdu.data.astype(np.float),
label=component_name)
if 'BUNIT' in hdu.header:
c = data.get_component(component_name)
c.units = self.get_units(hdu.header)
# For the purposes of exporting, we keep a reference to the original HDUList object
data._cubeviz_hdulist = hdulist
return data
def vue_collapse(self, *args, **kwargs):
try:
spec = self._selected_data.get_object(cls=SpectralCube)
except AttributeError:
snackbar_message = SnackbarMessage(
f"Unable to perform collapse over selected data.",
color="error",
sender=self)
self.hub.broadcast(snackbar_message)
return
collapsed_spec = getattr(spec, self.selected_func.lower())(
axis=self.selected_axis)
data = Data(coords=collapsed_spec.wcs)
data['flux'] = collapsed_spec.filled_data[...]
data.get_component('flux').units = str(collapsed_spec.unit)
data.meta.update(collapsed_spec.meta)
label = f"Collapsed {self._selected_data.label}"
self.data_collection[label] = data
# Link the new dataset pixel-wise to the original dataset. In general
# direct pixel to pixel links are the most efficient and should be
# used in cases like this where we know there is a 1-to-1 mapping of
# pixel coordinates. Here which axes are linked to which depends on
# the selected axis.
(i1, i2), (i1c, i2c) = AXES_MAPPING[self.selected_axis]
self.data_collection.add_link(LinkSame(self._selected_data.pixel_component_ids[i1],
self.data_collection[label].pixel_component_ids[i1c]))
self.data_collection.add_link(LinkSame(self._selected_data.pixel_component_ids[i2],
self.data_collection[label].pixel_component_ids[i2c]))
snackbar_message = SnackbarMessage(
f"Data set '{self._selected_data.label}' collapsed successfully.",
color="success",
sender=self)
self.hub.broadcast(snackbar_message)
def load_data(self, data_filenames):
"""
Load the data based on the extensions defined in the matching YAML file. THen
create the datacube and return it.
:param data_filename:
:return:
"""
label = None
data = None
ifucube = IFUCube()
for data_filename in data_filenames.split(','):
hdulist = ifucube.open(data_filename, fix=self._check_ifu_valid)
# Good in this case means the file has 3D data and can be loaded by SpectralCube.read
if self._check_ifu_valid and not ifucube.get_good():
# Popup takes precedence and accepting continues operation and canceling closes the program
self.popup_ui.ifucube_log.setText(ifucube.get_log_output())
self.popup_ui.setModal(True)
self.popup_ui.show()
self.popup_ui.button_accept.clicked.connect(self._accept_button_click)
self.popup_ui.button_cancel.clicked.connect(self._reject_button_click)
if not label:
label = "{}: {}".format(self._name, splitext(basename(data_filename))[0])
data = Data(label=label)
# this attribute is used to indicate to the cubeviz layout that
# this is a cubeviz-specific data component.
data.meta[CUBEVIZ_LAYOUT] = self._name
data_coords_set = False
for ii, hdu in enumerate(hdulist):
if 'NAXIS' in hdu.header and hdu.header['NAXIS'] == 3:
# Set the coords based on the first 3D HDU
if not data_coords_set:
data.coords = coordinates_from_header(hdu.header)
data_coords_set = True
component_name = str(ii)
if 'EXTNAME' in hdu.header:
component_name = hdu.header['EXTNAME']
# The data must be floating point as spectralcube is expecting floating point data
data.add_component(component=hdu.data.astype(np.float), label=component_name)
if 'BUNIT' in hdu.header:
c = data.get_component(component_name)
c.units = self.get_units(hdu.header)
else:
# Creates a unique component name
component_name = str(ii)
data.add_component(component=hdu.data.astype(np.float), label=component_name)
# For the purposes of exporting, we keep a reference to the original HDUList object
data._cubeviz_hdulist = hdulist
return data
def to_data(self, obj):
data = Data(coords=obj.wcs)
data['data'] = obj.data
data.get_component('data').units = str(obj.unit)
data.meta.update(obj.meta)
return data
def to_data(self, obj):
data = Data(coords=obj.wcs)
data['flux'] = obj.filled_data[...]
data.get_component('flux').units = str(obj.unit)
data.meta.update(obj.meta)
return data
def load_data(self, data_filenames):
"""
Load the data based on the extensions defined in the matching YAML file. THen
create the datacube and return it.
:param data_filename:
:return:
"""
label = None
data = None
ifucube = IFUCube()
for data_filename in data_filenames.split(','):
hdulist = ifucube.open(data_filename, fix=self._check_ifu_valid)
# Good in this case means the file has 3D data and can be loaded by SpectralCube.read
if self._check_ifu_valid and not ifucube.get_good():
# Popup takes precedence and accepting continues operation and canceling closes the program
self.popup_ui.ifucube_log.setText(ifucube.get_log_output())
self.popup_ui.setModal(True)
self.popup_ui.show()
self.popup_ui.button_accept.clicked.connect(
self._accept_button_click)
self.popup_ui.button_cancel.clicked.connect(
self._reject_button_click)
if not label:
label = "{}: {}".format(self._name,
splitext(basename(data_filename))[0])
data = Data(label=label)
# this attribute is used to indicate to the cubeviz layout that
# this is a cubeviz-specific data component.
data.meta[CUBEVIZ_LAYOUT] = self._name
data_coords_set = False
for ii, hdu in enumerate(hdulist):
if 'NAXIS' in hdu.header and hdu.header['NAXIS'] == 3:
# Set the coords based on the first 3D HDU
if not data_coords_set:
data.coords = coordinates_from_header(hdu.header)
data_coords_set = True
component_name = str(ii)
if 'EXTNAME' in hdu.header:
component_name = hdu.header['EXTNAME']
# The data must be floating point as spectralcube is expecting floating point data
data.add_component(component=hdu.data.astype(np.float),
label=component_name)
if 'BUNIT' in hdu.header:
c = data.get_component(component_name)
c.units = self.get_units(hdu.header)
else:
# Creates a unique component name
component_name = str(ii)
data.add_component(component=hdu.data.astype(np.float),
label=component_name)
# For the purposes of exporting, we keep a reference to the original HDUList object
data._cubeviz_hdulist = hdulist
return data
