import numpy as np
from astropy.coordinates import SkyCoord
from astropy.table import QTable
from functools import cached_property
from glue.core import BaseData
from glue_jupyter.bqplot.image import BqplotImageView
from glue_jupyter.table import TableViewer
from scipy.interpolate import interp1d
from specutils import Spectrum1D
from jdaviz.core.events import (AddDataToViewerMessage,
RemoveDataFromViewerMessage,
TableClickMessage)
from jdaviz.core.astrowidgets_api import AstrowidgetsImageViewerMixin
from jdaviz.core.registries import viewer_registry
from jdaviz.core.freezable_state import FreezableBqplotImageViewerState
from jdaviz.configs.default.plugins.viewers import JdavizViewerMixin
from jdaviz.configs.specviz.plugins.viewers import SpecvizProfileView
__all__ = ['MosvizImageView', 'MosvizProfile2DView',
'MosvizProfileView', 'MosvizTableViewer']
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@viewer_registry("mosviz-image-viewer", label="Image 2D (Mosviz)")
class MosvizImageView(JdavizViewerMixin, BqplotImageView, AstrowidgetsImageViewerMixin):
# categories: zoom resets, zoom, pan, subset, select tools, shortcuts
tools_nested = [
['jdaviz:homezoom', 'jdaviz:prevzoom'],
['jdaviz:boxzoom'],
['jdaviz:panzoom'],
['jdaviz:sidebar_plot', 'jdaviz:sidebar_export']
]
default_class = None
_state_cls = FreezableBqplotImageViewerState
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.init_astrowidgets_api()
self._subscribe_to_layers_update()
self.state.show_axes = False # Axes are wrong anyway
self.figure.fig_margin = {'left': 0, 'bottom': 0, 'top': 0, 'right': 0}
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def data(self, cls=None):
return [layer_state.layer.get_object(cls=cls or self.default_class)
for layer_state in self.state.layers
if hasattr(layer_state, 'layer') and
isinstance(layer_state.layer, BaseData)]
# NOTE: This is currently only for debugging. It is not used in app.
def _mark_targets(self):
table_data = self.jdaviz_app.data_collection['MOS Table']
if ("R.A." not in table_data.component_ids() or
"Dec." not in table_data.component_ids()):
return
ra = table_data["R.A."]
dec = table_data["Dec."]
sky = SkyCoord(ra, dec, unit='deg')
t = QTable({'coord': sky})
self.add_markers(t, use_skycoord=True, marker_name='Targets')
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@viewer_registry("mosviz-profile-2d-viewer", label="Spectrum 2D (Mosviz)")
class MosvizProfile2DView(JdavizViewerMixin, BqplotImageView):
# Due to limitations in CCDData and 2D data that has spectral and spatial
# axes, the default conversion class must handle cubes
default_class = Spectrum1D
# categories: zoom resets, zoom, pan, subset, select tools, shortcuts
tools_nested = [
['mosviz:homezoom'],
['mosviz:boxzoom', 'mosviz:xrangezoom', 'jdaviz:yrangezoom'],
['mosviz:panzoom', 'mosviz:panzoom_x', 'jdaviz:panzoom_y'],
['bqplot:xrange'],
['jdaviz:sidebar_plot', 'jdaviz:sidebar_export']
]
_state_cls = FreezableBqplotImageViewerState
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self._subscribe_to_layers_update()
# Setup viewer option defaults
self.state.aspect = 'auto'
self.session.hub.subscribe(self, AddDataToViewerMessage,
handler=self._on_viewer_data_changed)
self.session.hub.subscribe(self, RemoveDataFromViewerMessage,
handler=self._on_viewer_data_changed)
for k in ('x_min', 'x_max'):
self.state.add_callback(k, self._handle_x_axis_orientation)
@cached_property
def reference_spectral_axis(self):
return self.state.reference_data.get_object().spectral_axis.value
@cached_property
def pixel_to_world_interp(self):
pixels = range(len(self.reference_spectral_axis))
return interp1d(pixels, self.reference_spectral_axis)
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def pixel_to_world_limits(self, limits):
if not len(limits) == 2:
raise ValueError("limits must be length 2")
pixels = np.arange(0, len(self.reference_spectral_axis))
# we'll use interpolation when possible, but also want to fit a line between
# the outermost edge of the data within the limits
line_edges_pix = np.array([max((min(pixels), min(limits))),
min((max(pixels), max(limits)))])
if line_edges_pix[0] > line_edges_pix[1]:
# then the limits are entirely out of range, so use the whole range
# when fitting the linear approximation
line_edges_pix = np.array([min(pixels), max(pixels)])
line_edges_world = self.pixel_to_world_interp(line_edges_pix)
line_coeffs = np.polyfit(line_edges_pix, line_edges_world, deg=1)
def pixel_to_world_line(pixel):
return line_coeffs[0] * pixel + line_coeffs[1]
def map_pixel_to_world(pixel):
if pixels[0] <= pixel <= pixels[-1]:
# interpolate directly
return float(self.pixel_to_world_interp(pixel))
else:
# use the line model to extrapolate
return pixel_to_world_line(pixel)
invert = (-1) ** sum((self.inverted_x_axis, limits[0] > limits[1]))
out_lims = list(map(map_pixel_to_world, limits))[::invert]
return out_lims
@cached_property
def world_to_pixel_interp(self):
pixels = range(len(self.reference_spectral_axis))
return interp1d(self.reference_spectral_axis, pixels)
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def world_to_pixel_limits(self, limits):
if not len(limits) == 2:
raise ValueError("limits must be length 2")
# we'll use interpolation when possible, but also want to fit a line between
# the outermost edge of the data within the limits
line_edges_world = np.array([max((min(self.reference_spectral_axis), min(limits))),
min((max(self.reference_spectral_axis), max(limits)))])
if line_edges_world[0] > line_edges_world[1]:
# then the limits are entirely out of range, so use the whole range
# when fitting the linear approximation
line_edges_world = np.array([min(self.reference_spectral_axis),
max(self.reference_spectral_axis)])
line_edges_pixels = self.world_to_pixel_interp(line_edges_world)
line_coeffs = np.polyfit(line_edges_world, line_edges_pixels, deg=1)
def world_to_pixel_line(world):
return line_coeffs[0] * world + line_coeffs[1]
def map_world_to_pixel(world):
if min(self.reference_spectral_axis) <= world <= max(self.reference_spectral_axis):
# interpolate directly
return float(self.world_to_pixel_interp(world))
else:
# use the line model to extrapolate
return world_to_pixel_line(world)
invert = (-1) ** sum((self.inverted_x_axis, limits[0] > limits[1]))
out_lims = list(map(map_world_to_pixel, limits))[::invert]
return out_lims
def _on_viewer_data_changed(self, msg):
if msg.viewer_reference != self.reference:
return
# clear cached properties that are based on reference data - this is probably
# overly-conservative and we might be able to limit the clearing for only when
# reference data is changed (perhaps with a callback on the state for reference_data)
for attr in ('reference_spectral_axis', 'inverted_x_axis',
'pixel_to_world_interp', 'world_to_pixel_interp'):
if attr in self.__dict__:
del self.__dict__[attr]
if len(self.data()):
self._handle_x_axis_orientation()
@cached_property
def inverted_x_axis(self):
return self.reference_spectral_axis[0] > self.reference_spectral_axis[-1]
def _handle_x_axis_orientation(self, *args):
x_scales = self.scales['x']
limits = [x_scales.min, x_scales.max]
limits_inverted = limits[0] > limits[1]
if limits_inverted == self.inverted_x_axis:
return
with x_scales.hold_sync():
x_scales.min = max(limits) if self.inverted_x_axis else min(limits)
x_scales.max = min(limits) if self.inverted_x_axis else max(limits)
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def data(self, cls=None, statistic=None):
return [layer_state.layer.get_object(statistic=statistic,
cls=cls or self.default_class)
for layer_state in self.state.layers
if hasattr(layer_state, 'layer') and
isinstance(layer_state.layer, BaseData)]
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def set_plot_axes(self):
self.figure.axes[0].label = "x: pixels"
self.figure.axes[1].label = "y: pixels"
self.figure.axes[1].tick_format = None
self.figure.axes[1].label_location = "middle"
# Sync with Spectrum1D viewer (that is also used by other viz).
# Make it so y axis label is not covering tick numbers.
self.figure.fig_margin["left"] = 95
self.figure.fig_margin["bottom"] = 60
self.figure.send_state('fig_margin') # Force update
self.figure.axes[0].label_offset = "40"
self.figure.axes[1].label_offset = "-70"
# NOTE: with tick_style changed below, the default responsive ticks in bqplot result
# in overlapping tick labels. For now we'll hardcode at 8, but this could be removed
# (default to None) if/when bqplot auto ticks react to styling options.
self.figure.axes[1].num_ticks = 8
for i in (0, 1):
self.figure.axes[i].tick_style = {'font-size': 15, 'font-weight': 600}
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@viewer_registry("mosviz-profile-viewer", label="Profile 1D")
class MosvizProfileView(SpecvizProfileView):
# categories: zoom resets, zoom, pan, subset, select tools, shortcuts
tools_nested = [
['mosviz:homezoom'],
['mosviz:boxzoom', 'mosviz:xrangezoom', 'jdaviz:yrangezoom'], # noqa
['mosviz:panzoom', 'mosviz:panzoom_x', 'jdaviz:panzoom_y'], # noqa
['bqplot:xrange'],
['jdaviz:selectline'],
['jdaviz:sidebar_plot', 'jdaviz:sidebar_export']
]
[docs]
def set_plot_axes(self):
super().set_plot_axes()
self.figure.axes[1].num_ticks = 5
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@viewer_registry("mosviz-table-viewer", label="Table (Mosviz)")
class MosvizTableViewer(TableViewer, JdavizViewerMixin):
def __init__(self, session, *args, **kwargs):
super().__init__(session, *args, **kwargs)
self.figure_widget.observe(self._on_row_selected, names=['highlighted'])
# enable scrolling: # https://github.com/glue-viz/glue-jupyter/pull/287
self.widget_table.scrollable = True
self._selected_data = {}
self._shared_image = False
self.row_selection_in_progress = False
self._on_row_selected_begin = None
self._on_row_selected_end = None
@property
def _default_table_viewer_reference_name(self):
return self.jdaviz_helper._default_table_viewer_reference_name
@property
def _default_spectrum_viewer_reference_name(self):
return self.jdaviz_helper._default_spectrum_viewer_reference_name
@property
def _default_spectrum_2d_viewer_reference_name(self):
return self.jdaviz_helper._default_spectrum_2d_viewer_reference_name
@property
def _default_image_viewer_reference_name(self):
return self.jdaviz_helper._default_image_viewer_reference_name
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def redraw(self):
# Overload to hide components - we do this via overloading instead of
# checking for changes in self.figure_widget.data because some components
# might be added inplace to the dataset.
if self.figure_widget.data is None:
self.figure_widget.hidden_components = []
else:
components_str = [cid.label for cid in self.figure_widget.data.main_components]
hidden = []
for colname in ('Images', '1D Spectra', '2D Spectra'):
if colname in components_str:
hidden.append(self.figure_widget.data.id[colname])
self.figure_widget.hidden_components = hidden
super().redraw()
@property
def nrows(self):
return self.widget_table.get_state()['total_length']
@property
def current_row(self):
return self.widget_table.highlighted
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def select_row(self, n):
if n < 0 or n >= self.nrows:
raise ValueError("n must be between 0 and {}".format(self.nrows-1))
# compute and set the appropriate page
# NOTE: traitlets won't detect internal changes to a dict
options = self.widget_table.get_state()['options']
page = int(n / options['itemsPerPage']) + 1
if options['page'] != page:
self.widget_table.set_state({'options': {**options, 'page': page}})
self.widget_table.send_state()
# select and highlight the row
self.widget_table.highlighted = n
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def next_row(self):
current_row = self.current_row
new_row = 0 if current_row == self.nrows - 1 else current_row + 1
self.select_row(new_row)
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def prev_row(self):
current_row = self.current_row
new_row = self.nrows - 1 if current_row == 0 else current_row - 1
self.select_row(new_row)
def _on_row_selected(self, event):
if self._on_row_selected_begin:
self._on_row_selected_begin(event)
self.row_selection_in_progress = True
# Grab the index of the latest selected row
selected_index = event['new']
mos_data = self.session.data_collection['MOS Table']
# plugin data entries: select all in new row, deselect all others
for data_item in self.jdaviz_app.data_collection:
if data_item.meta.get('Plugin') is not None:
if data_item.meta.get('mosviz_row') == selected_index:
self.session.hub.broadcast(AddDataToViewerMessage(
self._default_spectrum_viewer_reference_name, data_item.label, sender=self))
else:
self.session.hub.broadcast(RemoveDataFromViewerMessage(
self._default_spectrum_viewer_reference_name, data_item.label, sender=self))
for component in mos_data.components:
comp_data = mos_data.get_component(component).data
selected_data = comp_data[selected_index]
if component.label == '1D Spectra':
prev_data = self._selected_data.get(self._default_spectrum_viewer_reference_name)
if prev_data != selected_data:
if prev_data:
# This covers the cases where data is unit converted
# and the name is modified
all_prev_data = [x
for x in self.session.data_collection.labels
if prev_data in x]
for modified_prev_data in all_prev_data:
if modified_prev_data:
remove_data_from_viewer_message = RemoveDataFromViewerMessage(
self._default_spectrum_viewer_reference_name,
modified_prev_data, sender=self
)
# reset the counter in the spectrum viewer's color cycler
# so that the newly selected row is displayed in gray and
# future additions will have other colors:
spectrum_viewer = self.jdaviz_app.get_viewer(
self._default_spectrum_viewer_reference_name
)
spectrum_viewer.color_cycler.reset()
self.session.hub.broadcast(remove_data_from_viewer_message)
add_data_to_viewer_message = AddDataToViewerMessage(
self._default_spectrum_viewer_reference_name,
selected_data, sender=self
)
self.session.hub.broadcast(add_data_to_viewer_message)
self._selected_data[
self._default_spectrum_viewer_reference_name
] = selected_data
if component.label == '2D Spectra':
prev_data = self._selected_data.get(self._default_spectrum_2d_viewer_reference_name)
if prev_data != selected_data:
if prev_data:
remove_data_from_viewer_message = RemoveDataFromViewerMessage(
self._default_spectrum_2d_viewer_reference_name,
prev_data, sender=self
)
self.session.hub.broadcast(remove_data_from_viewer_message)
add_data_to_viewer_message = AddDataToViewerMessage(
self._default_spectrum_2d_viewer_reference_name,
selected_data, sender=self
)
self.session.hub.broadcast(add_data_to_viewer_message)
self._selected_data[
self._default_spectrum_2d_viewer_reference_name
] = selected_data
if component.label == 'Images':
prev_data = self._selected_data.get(self._default_image_viewer_reference_name)
if prev_data != selected_data:
if prev_data:
remove_data_from_viewer_message = RemoveDataFromViewerMessage(
self._default_image_viewer_reference_name, prev_data, sender=self)
self.session.hub.broadcast(remove_data_from_viewer_message)
add_data_to_viewer_message = AddDataToViewerMessage(
self._default_image_viewer_reference_name, selected_data, sender=self)
self.session.hub.broadcast(add_data_to_viewer_message)
self._selected_data[self._default_image_viewer_reference_name] = selected_data
message = TableClickMessage(selected_index=selected_index,
shared_image=self._shared_image,
sender=self)
self.session.hub.broadcast(message)
self.row_selection_in_progress = False
if self._on_row_selected_end:
self._on_row_selected_end(event)
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def set_plot_axes(self, *args, **kwargs):
return
