import numpy as np
from glue_jupyter.bqplot.profile import BqplotProfileView
from glue_jupyter.bqplot.image import BqplotImageView
from glue_jupyter.bqplot.scatter.layer_artist import BqplotScatterLayerState
from glue_jupyter.table import TableViewer
from jdaviz.configs.imviz.helper import layer_is_image_data
from jdaviz.components.toolbar_nested import NestedJupyterToolbar
from jdaviz.core.registries import viewer_registry
from jdaviz.utils import ColorCycler, get_subset_type
__all__ = ['JdavizViewerMixin']
viewer_registry.add("g-profile-viewer", label="Profile 1D", cls=BqplotProfileView)
viewer_registry.add("g-image-viewer", label="Image 2D", cls=BqplotImageView)
viewer_registry.add("g-table-viewer", label="Table", cls=TableViewer)
[docs]class JdavizViewerMixin:
toolbar = None
tools_nested = []
_prev_limits = None
_native_mark_classnames = ('Lines', 'LinesGL', 'FRBImage', 'Contour')
def __init__(self, *args, **kwargs):
# NOTE: anything here most likely won't be called by viewers because of inheritance order
super().__init__(*args, **kwargs)
# Allow each viewer to cycle through colors for each new addition to the viewer:
self.color_cycler = ColorCycler()
@property
def native_marks(self):
"""
Return all marks that are Lines/LinesGL objects (and not subclasses)
"""
return [m for m in self.figure.marks
if m.__class__.__name__ in self._native_mark_classnames]
@property
def custom_marks(self):
"""
Return all marks that are not Lines/LinesGL objects (but can be subclasses)
"""
return [m for m in self.figure.marks
if m.__class__.__name__ not in self._native_mark_classnames]
def _subscribe_to_layers_update(self):
# subscribe to new layers
self._expected_subset_layers = []
self._layers_with_defaults_applied = []
self.state.add_callback('layers', self._on_layers_update)
def _get_layer(self, label):
for layer in self.state.layers:
if layer.layer.label == label:
return layer
def _apply_layer_defaults(self, layer_state):
if hasattr(layer_state, 'as_steps'):
if layer_state.layer.label != layer_state.layer.data.label:
# then this is a subset, so default based on the parent data layer
layer_state.as_steps = self._get_layer(layer_state.layer.data.label).as_steps
else:
# default to not plotting with as_steps (despite glue defaulting to True)
layer_state.as_steps = False
# whenever as_steps changes, we need to redraw the uncertainties (if enabled)
layer_state.add_callback('as_steps', self._show_uncertainty_changed)
def _expected_subset_layer_default(self, layer_state):
if self.__class__.__name__ == 'CubevizImageView':
# Do not override default for subsets as for some reason
# this isn't getting called when they're first added, but rather when
# the next state change is made (for example: manually changing the visibility)
return
# default visibility based on the visibility of the "parent" data layer
layer_state.visible = self._get_layer(layer_state.layer.data.label).visible
def _update_layer_icons(self):
# update visible_layers (TODO: move this somewhere that can update on color change, etc)
def _get_layer_color(layer):
if isinstance(layer, BqplotScatterLayerState):
# then this could be a scatter layer in an image viewer,
# so we'll ignore the color_mode
return layer.color
if getattr(self.state, 'color_mode', None) == 'Colormaps':
for subset in self.jdaviz_app.data_collection.subset_groups:
if subset.label == layer.layer.label:
# then we still want to show the color for a subset
return layer.color
# then this is a data-layer in colormap mode, so we'll ignore the color
return ''
return layer.color
def _get_layer_linewidth(layer):
linewidth = getattr(layer, 'linewidth', 0)
return min(linewidth, 6)
def _get_layer_info(layer):
if self.__class__.__name__ == 'CubevizProfileView' and len(layer.layer.data.shape) == 3:
suffix = f" (collapsed: {self.state.function})"
else:
suffix = ""
if 'Trace' in layer.layer.data.meta:
return "mdi-chart-line-stacked", ""
# then the underlying data is cube-like and we're in the profile viewer, so we
# want to include the collapse function *unless* the layer is a spectral subset
for subset in self.jdaviz_app.data_collection.subset_groups:
if subset.label == layer.layer.label:
subset_type = get_subset_type(subset)
if subset_type == 'spatial':
return "mdi-chart-scatter-plot", suffix
else:
return "mdi-chart-bell-curve", ""
return "", suffix
visible_layers = {}
for layer in self.state.layers[::-1]:
if layer.visible:
prefix_icon, suffix = _get_layer_info(layer)
visible_layers[layer.layer.label] = {'color': _get_layer_color(layer),
'linewidth': _get_layer_linewidth(layer),
'prefix_icon': prefix_icon,
'suffix_label': suffix}
viewer_item = self.jdaviz_app._viewer_item_by_id(self.reference_id)
viewer_item['visible_layers'] = visible_layers
def _on_layers_update(self, layers=None):
if self.__class__.__name__ == 'MosvizTableViewer':
# MosvizTableViewer uses this as a mixin, but we do not need any of this layer
# logic there
return
viewer_item = self.jdaviz_app._viewer_item_by_id(self.reference_id)
if viewer_item is None:
return
selected_data_items = viewer_item.get('selected_data_items', {})
# update selected_data_items
for data_id, visibility in selected_data_items.items():
label = next((x['name'] for x in self.jdaviz_app.state.data_items
if x['id'] == data_id), None)
visibilities = []
for layer in self.state.layers:
if layer.layer.data.label == label:
visibilities.append(layer.visible)
if np.all(visibilities):
selected_data_items[data_id] = 'visible'
elif np.any(visibilities):
selected_data_items[data_id] = 'mixed'
else:
selected_data_items[data_id] = 'hidden'
self._update_layer_icons()
# we'll make a deepcopy so that we can remove entries from the self._expected_subset_layers
# to avoid recursion, but also handle multiple layers for the same subset
expected_subset_layers = self._expected_subset_layers[:]
for layer in self.state.layers:
layer_info = {'data_label': layer.layer.data.label,
'layer_label': layer.layer.label}
if layer_info not in self._layers_with_defaults_applied:
self._layers_with_defaults_applied.append(layer_info)
self._apply_layer_defaults(layer)
if layer.layer.label in expected_subset_layers:
if layer.layer.label in self._expected_subset_layers:
self._expected_subset_layers.remove(layer.layer.label)
self._expected_subset_layer_default(layer)
def _on_subset_create(self, msg):
if self.__class__.__name__ == 'MosvizTableViewer':
# MosvizTableViewer uses this as a mixin, but we do not need any of this layer
# logic there
return
# NOTE: the subscription to this method is handled in ConfigHelper
# we don't have access to the actual subset yet to tell if its spectral or spatial, so
# we'll store the name of this new subset and change the default linewidth when the
# layers are added
if msg.subset.label not in self._expected_subset_layers and msg.subset.label:
self._expected_subset_layers.append(msg.subset.label)
@property
def active_image_layer(self):
"""Active image layer in the viewer, if available."""
# Find visible layers
visible_layers = [layer for layer in self.state.layers
if (layer.visible and layer_is_image_data(layer.layer))]
if len(visible_layers) == 0:
return None
return visible_layers[-1]
@property
def tools(self):
# NOTE: this overrides the default list of tools for the BasicJupyterToolbar by
# returning a flattened version of self.tools_nested
return list(self.toolbar.tools.keys())
@property
def jdaviz_app(self):
"""The Jdaviz application tied to the viewer."""
return self.session.jdaviz_app
@property
def jdaviz_helper(self):
"""The Jdaviz configuration helper tied to the viewer."""
return self.jdaviz_app._jdaviz_helper
@property
def hub(self):
return self.session.hub
@property
def reference_id(self):
return self._reference_id
@property
def reference(self):
return self.jdaviz_app._viewer_item_by_id(self.reference_id).get('reference')
[docs] def set_plot_axes(self):
# individual viewers can override to set custom axes labels/ticks/styling
return