class BqplotImageLayerState(ImageLayerState):
c_min = DDCProperty(docstring='The lower level used for the contours')
c_max = DDCProperty(docstring='The upper level used for the contours')
level_mode = DDSCProperty(0, docstring='How to distribute the contour levels')
n_levels = DDCProperty(5, docstring='The number of levels, in Linear mode')
levels = CallbackProperty(docstring='List of values where to create the contour lines')
labels = CallbackProperty(docstring='List of labels for each contour')
contour_percentile = DDSCProperty(docstring='The percentile value used to '
'automatically calculate levels for '
'the contour')
contour_colors = CallbackProperty(["red", "orange", "yellow", "green", "blue"])
bitmap_visible = CallbackProperty(True, 'whether to show the image as a bitmap')
contour_visible = CallbackProperty(False, 'whether to show the image as contours')
def __init__(self, *args, **kwargs):
super(BqplotImageLayerState, self).__init__(*args, **kwargs)
BqplotImageLayerState.level_mode.set_choices(self, ['Linear', 'Custom'])
percentile_display = {100: 'Min/Max',
99.5: '99.5%',
99: '99%',
95: '95%',
90: '90%',
'Custom': 'Custom'}
BqplotImageLayerState.contour_percentile.set_choices(self, [100, 99.5, 99, 95, 90,
'Custom'])
BqplotImageLayerState.contour_percentile.set_display_func(self, percentile_display.get)
self.contour_lim_helper = StateAttributeLimitsHelper(self, attribute='attribute',
percentile='contour_percentile',
lower='c_min', upper='c_max')
self.add_callback('n_levels', self._update_levels)
self.add_callback('c_min', self._update_levels)
self.add_callback('c_max', self._update_levels)
self.add_callback('level_mode', self._update_levels)
self.add_callback('levels', self._update_labels)
self._update_levels()
def _update_priority(self, name):
# if levels and level_mode get modified at the same time
# make sure externally 'levels' is set first, so we then
# can overwrite levels when we switch to Linear mode
# this is tested in test_contour_state
if name == 'levels':
return 10
return 0
def _update_levels(self, ignore=None):
if self.level_mode == "Linear":
# TODO: this is exclusive begin/end point, is that a good choise?
self.levels = np.linspace(self.c_min, self.c_max, self.n_levels+2)[1:-1].tolist()
def _update_labels(self, ignore=None):
# TODO: we may want to have ways to configure this in the future
self.labels = ["{0:.4g}".format(level) for level in self.levels]
class TutorialLayerState(MatplotlibLayerState):
# cmap is stuff used for colormap
linewidth = CallbackProperty(1, docstring='line width')
cmap_mode = DDSCProperty(
docstring="Whether to use color to encode an attribute")
cmap_att = DDSCProperty(docstring="The attribute to use for the color")
cmap_vmin = DDCProperty(docstring="The lower level for the colormap")
cmap_vmax = DDCProperty(docstring="The upper level for the colormap")
cmap = DDCProperty(docstring="The colormap to use (when in colormap mode)")
def __init__(self, viewer_state=None, layer=None, **kwargs):
super(TutorialLayerState, self).__init__(viewer_state=viewer_state,
layer=layer)
# set choices basically poplutes drop down menus
TutorialLayerState.cmap_mode.set_choices(self, ['Fixed', 'Linear'])
self.cmap_att_helper = ComponentIDComboHelper(self,
'cmap_att',
numeric=True,
categorical=False)
self.add_callback('layer', self._on_layers_change)
# kind of initializing. not having this line
# made errors for cmap initialization- didn't pull
# up linear part
# thanks tom
self._on_layers_change()
def _on_layers_change(self, layer=None):
# not exactly sure of this
with delay_callback(self, 'cmap_vmin', 'cmap_vmax'):
self.cmap_att_helper.set_multiple_data([self.layer])
# not having this line threw None resulting in an error- can't
# iterate over None....
# this initializes some colormap
# thanks tom
self.cmap = colormaps.members[0][1]
class Scatter3dLayerState(ScatterLayerState):
vz_att = DDSCProperty(docstring="The attribute to use for the z vector arrow")
def __init__(self, viewer_state=None, layer=None, **kwargs):
self.vz_att_helper = ComponentIDComboHelper(self, 'vz_att',
numeric=True, categorical=False)
super(Scatter3dLayerState, self).__init__(viewer_state=viewer_state, layer=layer)
# self.update_from_dict(kwargs)
def _on_layer_change(self, layer=None):
super(Scatter3dLayerState, self)._on_layer_change(layer=layer)
if self.layer is None:
self.vz_att_helper.set_multiple_data([])
else:
self.vz_att_helper.set_multiple_data([self.layer])
class DendrogramViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a dendrogram viewer.
"""
height_att = DDSCProperty()
parent_att = DDSCProperty()
order_att = DDSCProperty()
y_log = DDCProperty(False)
select_substruct = DDCProperty(True)
reference_data = DDCProperty()
_layout = DDCProperty()
def __init__(self, **kwargs):
super(DendrogramViewerState, self).__init__()
self.add_callback('layers', self._layers_changed)
self.height_att_helper = ComponentIDComboHelper(self, 'height_att')
self.parent_att_helper = ComponentIDComboHelper(self, 'parent_att')
self.order_att_helper = ComponentIDComboHelper(self, 'order_att')
self.add_callback('height_att', self._update_layout)
self.add_callback('parent_att', self._update_layout)
self.add_callback('order_att', self._update_layout)
self.add_callback('reference_data', self._on_reference_data_change)
self.update_from_dict(kwargs)
def _on_reference_data_change(self, data):
if self.reference_data is None:
return
self.height_att = self.reference_data.find_component_id('height')
self.parent_att = self.reference_data.find_component_id('parent')
self.order_att = self.height_att
def _update_layout(self, att):
if self.height_att is None or self.parent_att is None or self.order_att is None or self.reference_data is None:
self._layout = None
else:
height = self.reference_data[self.height_att].ravel()
parent = self.reference_data[self.parent_att].astype(int).ravel()
order = self.reference_data[self.order_att].ravel()
x, y = dendrogram_layout(parent, height, order)
self._layout = Layout(x, y)
def _layers_changed(self, *args):
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self.height_att_helper.set_multiple_data(layers_data)
self.parent_att_helper.set_multiple_data(layers_data)
self.order_att_helper.set_multiple_data(layers_data)
for layer in layers_data:
if isinstance(layer, Data):
self.reference_data = layer
break
self._layers_data_cache = layers_data
class ScatterViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a scatter viewer.
"""
x_att = DDSCProperty(docstring='The attribute to show on the x-axis',
default_index=0)
y_att = DDSCProperty(docstring='The attribute to show on the y-axis',
default_index=1)
dpi = DDCProperty(
72,
docstring=
'The resolution (in dots per inch) of density maps, if present')
def __init__(self, **kwargs):
super(ScatterViewerState, self).__init__()
self.limits_cache = {}
self.x_lim_helper = StateAttributeLimitsHelper(
self,
attribute='x_att',
lower='x_min',
upper='x_max',
log='x_log',
margin=0.04,
limits_cache=self.limits_cache)
self.y_lim_helper = StateAttributeLimitsHelper(
self,
attribute='y_att',
lower='y_min',
upper='y_max',
log='y_log',
margin=0.04,
limits_cache=self.limits_cache)
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
pixel_coord=True,
world_coord=True)
self.y_att_helper = ComponentIDComboHelper(self,
'y_att',
pixel_coord=True,
world_coord=True)
self.update_from_dict(kwargs)
self.add_callback('x_log', self._reset_x_limits)
self.add_callback('y_log', self._reset_y_limits)
def _reset_x_limits(self, *args):
if self.x_att is None:
return
self.x_lim_helper.percentile = 100
self.x_lim_helper.update_values(force=True)
def _reset_y_limits(self, *args):
if self.y_att is None:
return
self.y_lim_helper.percentile = 100
self.y_lim_helper.update_values(force=True)
def reset_limits(self):
self._reset_x_limits()
self._reset_y_limits()
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
def flip_y(self):
"""
Flip the y_min/y_max limits.
"""
self.y_lim_helper.flip_limits()
@property
def x_categories(self):
return self._categories(self.x_att)
@property
def y_categories(self):
return self._categories(self.y_att)
def _categories(self, cid):
categories = []
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
if layer.data.get_kind(cid) == 'categorical':
categories.append(layer.data.get_data(cid).categories)
except IncompatibleAttribute:
pass
if len(categories) == 0:
return None
else:
return np.unique(np.hstack(categories))
@property
def x_kinds(self):
return self._component_kinds(self.x_att)
@property
def y_kinds(self):
return self._component_kinds(self.y_att)
def _component_kinds(self, cid):
# Construct list of component kinds over all layers
kinds = set()
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
kinds.add(layer.data.get_kind(cid))
except IncompatibleAttribute:
pass
return kinds
def _layers_changed(self, *args):
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self.x_att_helper.set_multiple_data(self.layers_data)
self.y_att_helper.set_multiple_data(self.layers_data)
self._layers_data_cache = layers_data
class HistogramViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a histogram viewer.
"""
x_att = DDSCProperty(
docstring='The attribute to compute the histograms for')
cumulative = DDCProperty(False,
docstring='Whether to show the histogram as '
'a cumulative histogram')
normalize = DDCProperty(False,
docstring='Whether to normalize the histogram '
'(based on the total sum)')
hist_x_min = DDCProperty(docstring='The minimum value used to compute the '
'histogram')
hist_x_max = DDCProperty(docstring='The maxumum value used to compute the '
'histogram')
hist_n_bin = DDCProperty(docstring='The number of bins in the histogram')
common_n_bin = DDCProperty(True,
docstring='The number of bins to use for '
'all numerical components')
def __init__(self, **kwargs):
super(HistogramViewerState, self).__init__()
self.hist_helper = StateAttributeHistogramHelper(
self,
'x_att',
lower='hist_x_min',
upper='hist_x_max',
n_bin='hist_n_bin',
common_n_bin='common_n_bin')
self.x_lim_helper = StateAttributeLimitsHelper(self,
'x_att',
lower='x_min',
upper='x_max',
log='x_log')
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
pixel_coord=True,
world_coord=True)
self.update_from_dict(kwargs)
# This should be added after update_from_dict since we don't want to
# influence the restoring of sessions.
self.add_callback('hist_x_min', self.update_view_to_bins)
self.add_callback('hist_x_max', self.update_view_to_bins)
self.add_callback('x_log', self._reset_x_limits, priority=1000)
def _reset_x_limits(self, *args):
with delay_callback(self, 'hist_x_min', 'hist_x_max', 'x_min', 'x_max',
'x_log'):
self.x_lim_helper.percentile = 100
self.x_lim_helper.update_values(force=True)
self.update_bins_to_view()
def reset_limits(self):
self._reset_x_limits()
self.y_min = min(
getattr(layer, '_y_min', np.inf) for layer in self.layers)
self.y_max = max(getattr(layer, '_y_max', 0) for layer in self.layers)
def _update_priority(self, name):
if name == 'layers':
return 2
elif name.endswith('_log'):
return 0.5
elif name.endswith(('_min', '_max', '_bin')):
return 0
else:
return 1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
@avoid_circular
def update_bins_to_view(self, *args):
"""
Update the bins to match the current view.
"""
with delay_callback(self, 'hist_x_min', 'hist_x_max'):
if self.x_max > self.x_min:
self.hist_x_min = self.x_min
self.hist_x_max = self.x_max
else:
self.hist_x_min = self.x_max
self.hist_x_max = self.x_min
@avoid_circular
def update_view_to_bins(self, *args):
"""
Update the view to match the histogram interval
"""
with delay_callback(self, 'x_min', 'x_max'):
self.x_min = self.hist_x_min
self.x_max = self.hist_x_max
@property
def x_categories(self):
return self._categories(self.x_att)
def _categories(self, cid):
categories = []
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
if layer.data.get_kind(cid) == 'categorical':
categories.append(layer.data.get_data(cid).categories)
except IncompatibleAttribute:
pass
if len(categories) == 0:
return None
else:
return np.unique(np.hstack(categories))
@property
def x_kinds(self):
return self._component_kinds(self.x_att)
def _component_kinds(self, cid):
# Construct list of component kinds over all layers
kinds = set()
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
kinds.add(layer.data.get_kind(cid))
except IncompatibleAttribute:
pass
return kinds
@property
def bins(self):
"""
The position of the bins for the histogram based on the current state.
"""
if self.hist_x_min is None or self.hist_x_max is None or self.hist_n_bin is None:
return None
if self.x_log:
return np.logspace(np.log10(self.hist_x_min),
np.log10(self.hist_x_max), self.hist_n_bin + 1)
elif isinstance(self.hist_x_min, np.datetime64):
x_min = self.hist_x_min.astype(int)
x_max = self.hist_x_max.astype(self.hist_x_min.dtype).astype(int)
return np.linspace(x_min, x_max, self.hist_n_bin + 1).astype(
self.hist_x_min.dtype)
else:
return np.linspace(self.hist_x_min, self.hist_x_max,
self.hist_n_bin + 1)
@defer_draw
def _layers_changed(self, *args):
self.x_att_helper.set_multiple_data(self.layers_data)
class ProfileViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a Profile viewer.
"""
reference_data = DDSCProperty(
docstring='The dataset that is used to define the '
'available pixel/world components, and '
'which defines the coordinate frame in '
'which the images are shown')
x_att = DDSCProperty(docstring='The data component to use for the x-axis '
'of the profile (should be a pixel component)')
function = DDSCProperty(
docstring='The function to use for collapsing data')
normalize = DDCProperty(False,
docstring='Whether to normalize all profiles '
'to the [0:1] range')
# TODO: add function to use
def __init__(self, **kwargs):
super(ProfileViewerState, self).__init__()
self.ref_data_helper = ManualDataComboHelper(self, 'reference_data')
self.x_lim_helper = StateAttributeLimitsHelper(self,
'x_att',
lower='x_min',
upper='x_max')
self.add_callback('layers', self._layers_changed)
self.add_callback('reference_data', self._reference_data_changed)
self.add_callback('normalize', self._reset_y_limits)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
numeric=False,
categorical=False,
world_coord=True,
pixel_coord=True)
ProfileViewerState.function.set_choices(self, list(FUNCTIONS))
ProfileViewerState.function.set_display_func(self, FUNCTIONS.get)
self.update_from_dict(kwargs)
def _update_combo_ref_data(self):
self.ref_data_helper.set_multiple_data(self.layers_data)
def reset_limits(self):
with delay_callback(self, 'x_min', 'x_max', 'y_min', 'y_max'):
self.x_lim_helper.percentile = 100
self.x_lim_helper.update_values(force=True)
self._reset_y_limits()
def _reset_y_limits(self, *event):
if self.normalize:
self.y_min = -0.1
self.y_max = +1.1
def _update_priority(self, name):
if name == 'layers':
return 2
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
@defer_draw
def _layers_changed(self, *args):
self._update_combo_ref_data()
@defer_draw
def _reference_data_changed(self, *args):
if self.reference_data is None:
self.x_att_helper.set_multiple_data([])
else:
self.x_att_helper.set_multiple_data([self.reference_data])
if type(self.reference_data.coords) == Coordinates:
self.x_att = self.reference_data.pixel_component_ids[0]
else:
self.x_att = self.reference_data.world_component_ids[0]
class ScatterLayerState(MatplotlibLayerState):
"""
A state class that includes all the attributes for layers in a scatter plot.
"""
# General properties
style = DDSCProperty(docstring="The layer style")
size = DDCProperty(docstring="The size of the markers")
# Scatter layer
cmap_mode = DDSCProperty(
docstring="Whether to use color to encode an attribute")
cmap_att = DDSCProperty(docstring="The attribute to use for the color")
cmap_vmin = DDCProperty(docstring="The lower level for the colormap")
cmap_vmax = DDCProperty(docstring="The upper level for the colormap")
cmap = DDCProperty(docstring="The colormap to use (when in colormap mode)")
size_mode = DDSCProperty(
docstring="Whether to use size to encode an attribute")
size_att = DDSCProperty(docstring="The attribute to use for the size")
size_vmin = DDCProperty(docstring="The lower level for the size mapping")
size_vmax = DDCProperty(docstring="The upper level for the size mapping")
size_scaling = DDCProperty(1, docstring="Relative scaling of the size")
xerr_visible = DDCProperty(False, docstring="Whether to show x error bars")
yerr_visible = DDCProperty(False, docstring="Whether to show y error bars")
xerr_att = DDSCProperty(
docstring="The attribute to use for the x error bars")
yerr_att = DDSCProperty(
docstring="The attribute to use for the y error bars")
# Line plot layer
linewidth = DDCProperty(1, docstring="The line width")
linestyle = DDSCProperty(docstring="The line style")
def __init__(self, viewer_state=None, layer=None, **kwargs):
super(ScatterLayerState, self).__init__(viewer_state=viewer_state,
layer=layer)
self.limits_cache = {}
self.cmap_lim_helper = StateAttributeLimitsHelper(
self,
attribute='cmap_att',
lower='cmap_vmin',
upper='cmap_vmax',
limits_cache=self.limits_cache)
self.size_lim_helper = StateAttributeLimitsHelper(
self,
attribute='size_att',
lower='size_vmin',
upper='size_vmax',
limits_cache=self.limits_cache)
self.cmap_att_helper = ComponentIDComboHelper(self,
'cmap_att',
numeric=True,
categorical=False)
self.size_att_helper = ComponentIDComboHelper(self,
'size_att',
numeric=True,
categorical=False)
self.xerr_att_helper = ComponentIDComboHelper(self,
'xerr_att',
numeric=True,
categorical=False)
self.yerr_att_helper = ComponentIDComboHelper(self,
'yerr_att',
numeric=True,
categorical=False)
ScatterLayerState.style.set_choices(self, ['Scatter', 'Line'])
ScatterLayerState.cmap_mode.set_choices(self, ['Fixed', 'Linear'])
ScatterLayerState.size_mode.set_choices(self, ['Fixed', 'Linear'])
linestyle_display = {
'solid': '–––––––',
'dashed': '– – – – –',
'dotted': '· · · · · · · ·',
'dashdot': '– · – · – ·'
}
ScatterLayerState.linestyle.set_choices(
self, ['solid', 'dashed', 'dotted', 'dashdot'])
ScatterLayerState.linestyle.set_display_func(self,
linestyle_display.get)
self.add_callback('layer', self._on_layer_change)
if layer is not None:
self._on_layer_change()
self.cmap = colormaps.members[0][1]
self.size = self.layer.style.markersize
self._sync_size = keep_in_sync(self, 'size', self.layer.style,
'markersize')
self.update_from_dict(kwargs)
def _on_layer_change(self, layer=None):
with delay_callback(self, 'cmap_vmin', 'cmap_vmax', 'size_vmin',
'size_vmax'):
if self.layer is None:
self.cmap_att_helper.set_multiple_data([])
self.size_att_helper.set_multiple_data([])
else:
self.cmap_att_helper.set_multiple_data([self.layer])
self.size_att_helper.set_multiple_data([self.layer])
if self.layer is None:
self.xerr_att_helper.set_multiple_data([])
self.yerr_att_helper.set_multiple_data([])
else:
self.xerr_att_helper.set_multiple_data([self.layer])
self.yerr_att_helper.set_multiple_data([self.layer])
def flip_cmap(self):
"""
Flip the cmap_vmin/cmap_vmax limits.
"""
self.cmap_lim_helper.flip_limits()
def flip_size(self):
"""
Flip the size_vmin/size_vmax limits.
"""
self.size_lim_helper.flip_limits()
class ScatterLayerState(MatplotlibLayerState):
"""
A state class that includes all the attributes for layers in a scatter plot.
"""
# Color
cmap_mode = DDSCProperty(
docstring="Whether to use color to encode an attribute")
cmap_att = DDSCProperty(docstring="The attribute to use for the color")
cmap_vmin = DDCProperty(docstring="The lower level for the colormap")
cmap_vmax = DDCProperty(docstring="The upper level for the colormap")
cmap = DDCProperty(docstring="The colormap to use (when in colormap mode)")
# Points
points_mode = DDSCProperty(
docstring='Whether to use markers or a density map')
# Markers
markers_visible = DDCProperty(True, docstring="Whether to show markers")
size = DDCProperty(docstring="The size of the markers")
size_mode = DDSCProperty(
docstring="Whether to use size to encode an attribute")
size_att = DDSCProperty(docstring="The attribute to use for the size")
size_vmin = DDCProperty(docstring="The lower level for the size mapping")
size_vmax = DDCProperty(docstring="The upper level for the size mapping")
size_scaling = DDCProperty(1, docstring="Relative scaling of the size")
fill = DDCProperty(True, docstring="Whether to fill the markers")
# Density map
density_map = DDCProperty(
False, docstring="Whether to show the points as a density map")
stretch = DDSCProperty(default='log',
docstring='The stretch used to render the layer, '
'which should be one of ``linear``, '
'``sqrt``, ``log``, or ``arcsinh``')
density_contrast = DDCProperty(
1, docstring="The dynamic range of the density map")
# Note that we keep the dpi in the viewer state since we want it to always
# be in sync between layers.
# Line
line_visible = DDCProperty(
False, docstring="Whether to show a line connecting all positions")
linewidth = DDCProperty(1, docstring="The line width")
linestyle = DDSCProperty(docstring="The line style")
# Errorbars
xerr_visible = DDCProperty(False, docstring="Whether to show x error bars")
yerr_visible = DDCProperty(False, docstring="Whether to show y error bars")
xerr_att = DDSCProperty(
docstring="The attribute to use for the x error bars")
yerr_att = DDSCProperty(
docstring="The attribute to use for the y error bars")
# Vectors
vector_visible = DDCProperty(False,
docstring="Whether to show vector plot")
vx_att = DDSCProperty(
docstring="The attribute to use for the x vector arrow")
vy_att = DDSCProperty(
docstring="The attribute to use for the y vector arrow")
vector_arrowhead = DDCProperty(False,
docstring="Whether to show vector arrow")
vector_mode = DDSCProperty(
default_index=0,
docstring="Whether to plot the vectors in cartesian or polar mode")
vector_origin = DDSCProperty(
default_index=1,
docstring=
"Whether to place the vector so that the origin is at the tail, middle, or tip"
)
vector_scaling = DDCProperty(
1, docstring="The relative scaling of the arrow length")
def __init__(self, viewer_state=None, layer=None, **kwargs):
super(ScatterLayerState, self).__init__(viewer_state=viewer_state,
layer=layer)
self.limits_cache = {}
self.cmap_lim_helper = StateAttributeLimitsHelper(
self,
attribute='cmap_att',
lower='cmap_vmin',
upper='cmap_vmax',
limits_cache=self.limits_cache)
self.size_lim_helper = StateAttributeLimitsHelper(
self,
attribute='size_att',
lower='size_vmin',
upper='size_vmax',
limits_cache=self.limits_cache)
self.cmap_att_helper = ComponentIDComboHelper(self,
'cmap_att',
numeric=True,
categorical=False)
self.size_att_helper = ComponentIDComboHelper(self,
'size_att',
numeric=True,
categorical=False)
self.xerr_att_helper = ComponentIDComboHelper(self,
'xerr_att',
numeric=True,
categorical=False)
self.yerr_att_helper = ComponentIDComboHelper(self,
'yerr_att',
numeric=True,
categorical=False)
self.vx_att_helper = ComponentIDComboHelper(self,
'vx_att',
numeric=True,
categorical=False)
self.vy_att_helper = ComponentIDComboHelper(self,
'vy_att',
numeric=True,
categorical=False)
points_mode_display = {
'auto': 'Density map or markers (auto)',
'markers': 'Markers',
'density': 'Density map'
}
ScatterLayerState.points_mode.set_choices(
self, ['auto', 'markers', 'density'])
ScatterLayerState.points_mode.set_display_func(self,
points_mode_display.get)
self.add_callback('points_mode', self._update_density_map_mode)
ScatterLayerState.cmap_mode.set_choices(self, ['Fixed', 'Linear'])
ScatterLayerState.size_mode.set_choices(self, ['Fixed', 'Linear'])
linestyle_display = {
'solid': '–––––––',
'dashed': '– – – – –',
'dotted': '· · · · · · · ·',
'dashdot': '– · – · – ·'
}
ScatterLayerState.linestyle.set_choices(
self, ['solid', 'dashed', 'dotted', 'dashdot'])
ScatterLayerState.linestyle.set_display_func(self,
linestyle_display.get)
ScatterLayerState.vector_mode.set_choices(self, ['Cartesian', 'Polar'])
vector_origin_display = {
'tail': 'Tail of vector',
'middle': 'Middle of vector',
'tip': 'Tip of vector'
}
ScatterLayerState.vector_origin.set_choices(self,
['tail', 'middle', 'tip'])
ScatterLayerState.vector_origin.set_display_func(
self, vector_origin_display.get)
stretch_display = {
'linear': 'Linear',
'sqrt': 'Square Root',
'arcsinh': 'Arcsinh',
'log': 'Logarithmic'
}
ScatterLayerState.stretch.set_choices(
self, ['linear', 'sqrt', 'arcsinh', 'log'])
ScatterLayerState.stretch.set_display_func(self, stretch_display.get)
self.add_callback('layer', self._on_layer_change)
if layer is not None:
self._on_layer_change()
self.cmap = colormaps.members[0][1]
self.size = self.layer.style.markersize
self._sync_size = keep_in_sync(self, 'size', self.layer.style,
'markersize')
self.update_from_dict(kwargs)
def _on_layer_change(self, layer=None):
with delay_callback(self, 'cmap_vmin', 'cmap_vmax', 'size_vmin',
'size_vmax', 'density_map'):
self._update_density_map_mode()
if self.layer is None:
self.cmap_att_helper.set_multiple_data([])
self.size_att_helper.set_multiple_data([])
else:
self.cmap_att_helper.set_multiple_data([self.layer])
self.size_att_helper.set_multiple_data([self.layer])
if self.layer is None:
self.xerr_att_helper.set_multiple_data([])
self.yerr_att_helper.set_multiple_data([])
else:
self.xerr_att_helper.set_multiple_data([self.layer])
self.yerr_att_helper.set_multiple_data([self.layer])
if self.layer is None:
self.vx_att_helper.set_multiple_data([])
self.vy_att_helper.set_multiple_data([])
else:
self.vx_att_helper.set_multiple_data([self.layer])
self.vy_att_helper.set_multiple_data([self.layer])
def _update_density_map_mode(self, *args):
if self.points_mode == 'auto':
if self.layer.size > 100000:
self.density_map = True
else:
self.density_map = False
elif self.points_mode == 'density':
self.density_map = True
else:
self.density_map = False
def flip_cmap(self):
"""
Flip the cmap_vmin/cmap_vmax limits.
"""
self.cmap_lim_helper.flip_limits()
def flip_size(self):
"""
Flip the size_vmin/size_vmax limits.
"""
self.size_lim_helper.flip_limits()
@property
def cmap_name(self):
return colormaps.name_from_cmap(self.cmap)
@classmethod
def __setgluestate__(cls, rec, context):
# Patch for glue files produced with glue v0.11
if 'style' in rec['values']:
style = context.object(rec['values'].pop('style'))
if style == 'Scatter':
rec['values']['markers_visible'] = True
rec['values']['line_visible'] = False
elif style == 'Line':
rec['values']['markers_visible'] = False
rec['values']['line_visible'] = True
return super(ScatterLayerState, cls).__setgluestate__(rec, context)
class ProfileLayerState(MatplotlibLayerState):
"""
A state class that includes all the attributes for layers in a Profile plot.
"""
linewidth = DDCProperty(1, docstring='The width of the line')
attribute = DDSCProperty(docstring='The attribute shown in the layer')
v_min = DDCProperty(docstring='The lower level shown')
v_max = DDCProperty(docstring='The upper level shown')
percentile = DDSCProperty(docstring='The percentile value used to '
'automatically calculate levels')
_viewer_callbacks_set = False
_profile_cache = None
def __init__(self, layer=None, viewer_state=None, **kwargs):
super(ProfileLayerState, self).__init__(layer=layer, viewer_state=viewer_state)
self.attribute_att_helper = ComponentIDComboHelper(self, 'attribute',
numeric=True, categorical=False)
percentile_display = {100: 'Min/Max',
99.5: '99.5%',
99: '99%',
95: '95%',
90: '90%',
'Custom': 'Custom'}
ProfileLayerState.percentile.set_choices(self, [100, 99.5, 99, 95, 90, 'Custom'])
ProfileLayerState.percentile.set_display_func(self, percentile_display.get)
self.add_callback('layer', self._update_attribute, priority=1000)
if layer is not None:
self._update_attribute()
self.update_from_dict(kwargs)
def _update_attribute(self, *args):
if self.layer is not None:
self.attribute_att_helper.set_multiple_data([self.layer])
@property
def independent_x_att(self):
return is_convertible_to_single_pixel_cid(self.layer, self.viewer_state.x_att) is not None
def normalize_values(self, values):
return (np.asarray(values) - self.v_min) / (self.v_max - self.v_min)
def reset_cache(self, *args):
self._profile_cache = None
@property
def viewer_state(self):
return self._viewer_state
@viewer_state.setter
def viewer_state(self, viewer_state):
self._viewer_state = viewer_state
@property
def profile(self):
self.update_profile()
return self._profile_cache
def update_profile(self, update_limits=True):
if self._profile_cache is not None:
return self._profile_cache
if not self.visible:
return
if not self._viewer_callbacks_set:
self.viewer_state.add_callback('x_att', self.reset_cache, priority=100000)
self.viewer_state.add_callback('function', self.reset_cache, priority=100000)
if self.is_callback_property('attribute'):
self.add_callback('attribute', self.reset_cache, priority=100000)
self._viewer_callbacks_set = True
if self.viewer_state is None or self.viewer_state.x_att is None or self.attribute is None:
raise IncompatibleDataException()
# Check what pixel axis in the current dataset x_att corresponds to
pix_cid = is_convertible_to_single_pixel_cid(self.layer, self.viewer_state.x_att_pixel)
if pix_cid is None:
raise IncompatibleDataException()
# If we get here, then x_att does correspond to a single pixel axis in
# the cube, so we now prepare a list of axes to collapse over.
axes = tuple(i for i in range(self.layer.ndim) if i != pix_cid.axis)
# We now get the y values for the data
# TODO: in future we should optimize the case where the mask is much
# smaller than the data to just average the relevant 'spaxels' in the
# data rather than collapsing the whole cube.
if isinstance(self.layer, Subset):
data = self.layer.data
subset_state = self.layer.subset_state
else:
data = self.layer
subset_state = None
profile_values = data.compute_statistic(self.viewer_state.function, self.attribute, axis=axes, subset_state=subset_state)
if np.all(np.isnan(profile_values)):
self._profile_cache = [], []
else:
axis_view = [0] * data.ndim
axis_view[pix_cid.axis] = slice(None)
axis_values = data[self.viewer_state.x_att, tuple(axis_view)]
self._profile_cache = axis_values, profile_values
if update_limits:
self.update_limits(update_profile=False)
def update_limits(self, update_profile=True):
with delay_callback(self, 'v_min', 'v_max'):
if update_profile:
self.update_profile(update_limits=False)
if self._profile_cache is not None and len(self._profile_cache[1]) > 0:
self.v_min = np.nanmin(self._profile_cache[1])
self.v_max = np.nanmax(self._profile_cache[1])
class ImageViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for an image viewer.
"""
x_att = DDCProperty(
docstring='The component ID giving the pixel component '
'shown on the x axis')
y_att = DDCProperty(
docstring='The component ID giving the pixel component '
'shown on the y axis')
x_att_world = DDSCProperty(
docstring='The component ID giving the world component '
'shown on the x axis',
default_index=-1)
y_att_world = DDSCProperty(
docstring='The component ID giving the world component '
'shown on the y axis',
default_index=-2)
aspect = DDCProperty(
'equal',
docstring='Whether to enforce square pixels (``equal``) '
'or fill the axes (``auto``)')
reference_data = DDSCProperty(
docstring='The dataset that is used to define the '
'available pixel/world components, and '
'which defines the coordinate frame in '
'which the images are shown')
slices = DDCProperty(docstring='The current slice along all dimensions')
color_mode = DDCProperty('Colormaps',
docstring='Whether each layer can have '
'its own colormap (``Colormaps``) or '
'whether each layer is assigned '
'a single color (``One color per layer``)')
def __init__(self, **kwargs):
super(ImageViewerState, self).__init__()
self.limits_cache = {}
self.x_lim_helper = StateAttributeLimitsHelper(
self,
attribute='x_att',
lower='x_min',
upper='x_max',
limits_cache=self.limits_cache)
self.y_lim_helper = StateAttributeLimitsHelper(
self,
attribute='y_att',
lower='y_min',
upper='y_max',
limits_cache=self.limits_cache)
self.ref_data_helper = ManualDataComboHelper(self, 'reference_data')
self.xw_att_helper = ComponentIDComboHelper(self,
'x_att_world',
numeric=False,
categorical=False,
visible=False,
world_coord=True)
self.yw_att_helper = ComponentIDComboHelper(self,
'y_att_world',
numeric=False,
categorical=False,
visible=False,
world_coord=True)
self.add_callback('reference_data',
self._reference_data_changed,
priority=1000)
self.add_callback('layers', self._layers_changed, priority=1000)
self.add_callback('x_att', self._on_xatt_change, priority=500)
self.add_callback('y_att', self._on_yatt_change, priority=500)
self.add_callback('x_att_world', self._update_att, priority=500)
self.add_callback('y_att_world', self._update_att, priority=500)
self.add_callback('x_att_world',
self._on_xatt_world_change,
priority=1000)
self.add_callback('y_att_world',
self._on_yatt_world_change,
priority=1000)
self.update_from_dict(kwargs)
def _reference_data_changed(self, *args):
with delay_callback(self, 'x_att_world', 'y_att_world', 'slices'):
self._update_combo_att()
self._set_default_slices()
def _layers_changed(self, *args):
# The layers callback gets executed if anything in the layers changes,
# but we only care about whether the actual set of 'layer' attributes
# for all layers change.
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self._update_combo_ref_data()
self._set_reference_data()
self._update_syncing()
self._layers_data_cache = layers_data
def _update_syncing(self):
# If there are multiple layers for a given dataset, we disable the
# syncing by default.
layer_state_by_data = defaultdict(list)
for layer_state in self.layers:
if isinstance(layer_state.layer, Data):
layer_state_by_data[layer_state.layer].append(layer_state)
for data, layer_states in layer_state_by_data.items():
if len(layer_states) > 1:
for layer_state in layer_states:
if layer_state.global_sync:
layer_state.global_sync = False
def _update_combo_ref_data(self):
self.ref_data_helper.set_multiple_data(self.layers_data)
def _update_combo_att(self):
with delay_callback(self, 'x_att_world', 'y_att_world'):
if self.reference_data is None:
self.xw_att_helper.set_multiple_data([])
self.yw_att_helper.set_multiple_data([])
else:
self.xw_att_helper.set_multiple_data([self.reference_data])
self.yw_att_helper.set_multiple_data([self.reference_data])
def _update_priority(self, name):
if name == 'layers':
return 3
elif name == 'reference_data':
return 2
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
@defer_draw
def _update_att(self, *args):
# Need to delay the callbacks here to make sure that we get a chance to
# update both x_att and y_att otherwise could end up triggering image
# slicing with two pixel components that are the same.
with delay_callback(self, 'x_att', 'y_att'):
if self.x_att_world is not None:
index = self.reference_data.world_component_ids.index(
self.x_att_world)
self.x_att = self.reference_data.pixel_component_ids[index]
if self.y_att_world is not None:
index = self.reference_data.world_component_ids.index(
self.y_att_world)
self.y_att = self.reference_data.pixel_component_ids[index]
@defer_draw
def _on_xatt_change(self, *args):
if self.x_att is not None:
self.x_att_world = self.reference_data.world_component_ids[
self.x_att.axis]
@defer_draw
def _on_yatt_change(self, *args):
if self.y_att is not None:
self.y_att_world = self.reference_data.world_component_ids[
self.y_att.axis]
@defer_draw
def _on_xatt_world_change(self, *args):
if self.x_att_world is not None and self.x_att_world == self.y_att_world:
world_ids = self.reference_data.world_component_ids
if self.x_att_world == world_ids[-1]:
self.y_att_world = world_ids[-2]
else:
self.y_att_world = world_ids[-1]
@defer_draw
def _on_yatt_world_change(self, *args):
if self.y_att_world is not None and self.y_att_world == self.x_att_world:
world_ids = self.reference_data.world_component_ids
if self.y_att_world == world_ids[-1]:
self.x_att_world = world_ids[-2]
else:
self.x_att_world = world_ids[-1]
def _set_reference_data(self):
if self.reference_data is None:
for layer in self.layers:
if isinstance(layer.layer, Data):
self.reference_data = layer.layer
return
def _set_default_slices(self):
# Need to make sure this gets called immediately when reference_data is changed
if self.reference_data is None:
self.slices = ()
else:
self.slices = (0, ) * self.reference_data.ndim
@property
def numpy_slice_aggregation_transpose(self):
"""
Returns slicing information usable by Numpy.
This returns two objects: the first is an object that can be used to
slice Numpy arrays and return a 2D array, and the second object is a
boolean indicating whether to transpose the result.
"""
if self.reference_data is None:
return None
slices = []
agg_func = []
for i in range(self.reference_data.ndim):
if i == self.x_att.axis or i == self.y_att.axis:
slices.append(slice(None))
agg_func.append(None)
else:
if isinstance(self.slices[i], AggregateSlice):
slices.append(self.slices[i].slice)
agg_func.append(self.slices[i].function)
else:
slices.append(self.slices[i])
transpose = self.y_att.axis > self.x_att.axis
return slices, agg_func, transpose
@property
def wcsaxes_slice(self):
"""
Returns slicing information usable by WCSAxes.
This returns an iterable of slices, and including ``'x'`` and ``'y'``
for the dimensions along which we are not slicing.
"""
if self.reference_data is None:
return None
slices = []
for i in range(self.reference_data.ndim):
if i == self.x_att.axis:
slices.append('x')
elif i == self.y_att.axis:
slices.append('y')
else:
if isinstance(self.slices[i], AggregateSlice):
slices.append(self.slices[i].center)
else:
slices.append(self.slices[i])
return slices[::-1]
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
def flip_y(self):
"""
Flip the y_min/y_max limits.
"""
self.y_lim_helper.flip_limits()
class ProfileViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a Profile viewer.
"""
x_att_pixel = DDCProperty(
docstring='The component ID giving the pixel component '
'shown on the x axis')
x_att = DDSCProperty(
docstring='The component ID giving the pixel or world component '
'shown on the x axis')
reference_data = DDSCProperty(
docstring='The dataset that is used to define the '
'available pixel/world components, and '
'which defines the coordinate frame in '
'which the images are shown')
function = DDSCProperty(
docstring='The function to use for collapsing data')
normalize = DDCProperty(False,
docstring='Whether to normalize all profiles '
'to the [0:1] range')
# TODO: add function to use
def __init__(self, **kwargs):
super(ProfileViewerState, self).__init__()
self.ref_data_helper = ManualDataComboHelper(self, 'reference_data')
self.add_callback('layers', self._layers_changed)
self.add_callback('reference_data', self._reference_data_changed)
self.add_callback('x_att', self._update_att)
self.add_callback('normalize', self._reset_y_limits)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
numeric=False,
categorical=False,
pixel_coord=True)
ProfileViewerState.function.set_choices(self, list(FUNCTIONS))
ProfileViewerState.function.set_display_func(self, FUNCTIONS.get)
self.update_from_dict(kwargs)
def _update_combo_ref_data(self):
self.ref_data_helper.set_multiple_data(self.layers_data)
def reset_limits(self):
with delay_callback(self, 'x_min', 'x_max', 'y_min', 'y_max'):
self._reset_x_limits()
self._reset_y_limits()
@property
def _display_world(self):
return (isinstance(getattr(self.reference_data, 'coords', None),
Coordinates)
and type(self.reference_data.coords) != Coordinates)
@defer_draw
def _update_att(self, *args):
if self.x_att is not None:
if self._display_world:
if self.x_att in self.reference_data.pixel_component_ids:
self.x_att_pixel = self.x_att
else:
index = self.reference_data.world_component_ids.index(
self.x_att)
self.x_att_pixel = self.reference_data.pixel_component_ids[
index]
else:
self.x_att_pixel = self.x_att
self._reset_x_limits()
def _reset_x_limits(self, *event):
# NOTE: we don't use AttributeLimitsHelper because we need to avoid
# trying to get the minimum of *all* the world coordinates in the
# dataset. Instead, we use the same approach as in the layer state below
# and in the case of world coordinates we use online the spine of the
# data.
if self.reference_data is None or self.x_att_pixel is None:
return
data = self.reference_data
if self.x_att in data.pixel_component_ids:
x_min, x_max = -0.5, data.shape[self.x_att.axis] - 0.5
else:
axis = data.world_component_ids.index(self.x_att)
axis_view = [0] * data.ndim
axis_view[axis] = slice(None)
axis_values = data[self.x_att, tuple(axis_view)]
x_min, x_max = np.nanmin(axis_values), np.nanmax(axis_values)
with delay_callback(self, 'x_min', 'x_max'):
self.x_min = x_min
self.x_max = x_max
def _reset_y_limits(self, *event):
if self.normalize:
with delay_callback(self, 'y_min', 'y_max'):
self.y_min = -0.1
self.y_max = +1.1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
with delay_callback(self, 'x_min', 'x_max'):
self.x_min, self.x_max = self.x_max, self.x_min
@defer_draw
def _layers_changed(self, *args):
self._update_combo_ref_data()
@defer_draw
def _reference_data_changed(self, *args):
# This signal can get emitted if just the choices but not the actual
# reference data change, so we check here that the reference data has
# actually changed
if self.reference_data is not getattr(self, '_last_reference_data',
None):
self._last_reference_data = self.reference_data
if self.reference_data is None:
self.x_att_helper.set_multiple_data([])
else:
self.x_att_helper.set_multiple_data([self.reference_data])
if self._display_world:
self.x_att_helper.world_coord = True
self.x_att = self.reference_data.world_component_ids[0]
else:
self.x_att_helper.world_coord = False
self.x_att = self.reference_data.pixel_component_ids[0]
class ScatterViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a scatter viewer.
"""
x_att = DDSCProperty(docstring='The attribute to show on the x-axis',
default_index=0)
y_att = DDSCProperty(docstring='The attribute to show on the y-axis',
default_index=1)
dpi = DDCProperty(
72,
docstring=
'The resolution (in dots per inch) of density maps, if present')
plot_mode = DDSCProperty(
docstring=
"Whether to plot the data in cartesian, polar or another projection")
angle_unit = DDSCProperty(
docstring=
"When plotting in polar mode, whether to use radians or degrees for the angles"
)
def __init__(self, **kwargs):
super(ScatterViewerState, self).__init__()
self.limits_cache = {}
self.x_lim_helper = StateAttributeLimitsHelper(
self,
attribute='x_att',
lower='x_min',
upper='x_max',
log='x_log',
margin=0.04,
limits_cache=self.limits_cache)
self.y_lim_helper = StateAttributeLimitsHelper(
self,
attribute='y_att',
lower='y_min',
upper='y_max',
log='y_log',
margin=0.04,
limits_cache=self.limits_cache)
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
pixel_coord=True,
world_coord=True)
self.y_att_helper = ComponentIDComboHelper(self,
'y_att',
pixel_coord=True,
world_coord=True)
self.plot_mode_helper = ComboHelper(self, 'plot_mode')
self.plot_mode_helper.choices = [
proj for proj in get_projection_names()
if proj not in ['3d', 'scatter_density']
]
self.plot_mode_helper.selection = 'rectilinear'
self.angle_unit_helper = ComboHelper(self, 'angle_unit')
self.angle_unit_helper.choices = ['radians', 'degrees']
self.angle_unit_helper.selection = 'radians'
self.update_from_dict(kwargs)
self.add_callback('x_log', self._reset_x_limits)
self.add_callback('y_log', self._reset_y_limits)
if self.using_polar:
self.full_circle()
def _reset_x_limits(self, *args):
if self.x_att is None:
return
self.x_lim_helper.percentile = 100
self.x_lim_helper.update_values(force=True)
def _reset_y_limits(self, *args):
if self.y_att is None:
return
self.y_lim_helper.percentile = 100
self.y_lim_helper.update_values(force=True)
def reset_limits(self):
if not self.using_polar:
self._reset_x_limits()
self._reset_y_limits()
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
def flip_y(self):
"""
Flip the y_min/y_max limits.
"""
self.y_lim_helper.flip_limits()
@property
def using_polar(self):
return self.plot_mode == 'polar'
@property
def using_degrees(self):
return self.using_polar and self.angle_unit == 'degrees'
@property
def using_radians(self):
return self.using_polar and self.angle_unit == 'radians'
def full_circle(self):
if not self.using_polar:
return
self.x_min = 0
self.x_max = 2 * np.pi
@property
def x_categories(self):
return self._categories(self.x_att)
@property
def y_categories(self):
return self._categories(self.y_att)
def _categories(self, cid):
categories = []
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
if layer.data.get_kind(cid) == 'categorical':
categories.append(layer.data.get_data(cid).categories)
except IncompatibleAttribute:
pass
if len(categories) == 0:
return None
else:
return np.unique(np.hstack(categories))
@property
def x_kinds(self):
return self._component_kinds(self.x_att)
@property
def y_kinds(self):
return self._component_kinds(self.y_att)
def _component_kinds(self, cid):
# Construct list of component kinds over all layers
kinds = set()
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
kinds.add(layer.data.get_kind(cid))
except IncompatibleAttribute:
pass
return kinds
def _layers_changed(self, *args):
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self.x_att_helper.set_multiple_data(self.layers_data)
self.y_att_helper.set_multiple_data(self.layers_data)
self._layers_data_cache = layers_data
class HistogramViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a histogram viewer.
"""
x_att = DDSCProperty(
docstring='The attribute to compute the histograms for')
cumulative = DDCProperty(False,
docstring='Whether to show the histogram as '
'a cumulative histogram')
normalize = DDCProperty(False,
docstring='Whether to normalize the histogram '
'(based on the total sum)')
hist_x_min = DDCProperty(docstring='The minimum value used to compute the '
'histogram')
hist_x_max = DDCProperty(docstring='The maxumum value used to compute the '
'histogram')
hist_n_bin = DDCProperty(docstring='The number of bins in the histogram')
common_n_bin = DDCProperty(True,
docstring='The number of bins to use for '
'all numerical components')
def __init__(self, **kwargs):
super(HistogramViewerState, self).__init__()
self.hist_helper = StateAttributeHistogramHelper(
self,
'x_att',
lower='hist_x_min',
upper='hist_x_max',
n_bin='hist_n_bin',
common_n_bin='common_n_bin')
self.x_lim_helper = StateAttributeLimitsHelper(self,
'x_att',
lower='x_min',
upper='x_max',
log='x_log')
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self, 'x_att')
self.update_from_dict(kwargs)
def _update_priority(self, name):
if name == 'layers':
return 2
elif name.endswith('_log'):
return 0.5
elif name.endswith(('_min', '_max', '_bin')):
return 0
else:
return 1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
def update_bins_to_view(self):
"""
Update the bins to match the current view.
"""
with delay_callback(self, 'hist_x_min', 'hist_x_max'):
if self.x_max > self.x_min:
self.hist_x_min = self.x_min
self.hist_x_max = self.x_max
else:
self.hist_x_min = self.x_max
self.hist_x_max = self.x_min
def _get_x_components(self):
if self.x_att is None:
return []
# Construct list of components over all layers
components = []
for layer_state in self.layers:
if isinstance(layer_state.layer, Data):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
components.append(layer.get_component(self.x_att))
except IncompatibleAttribute:
pass
return components
@property
def bins(self):
"""
The position of the bins for the histogram based on the current state.
"""
if self.x_log:
return np.logspace(np.log10(self.hist_x_min),
np.log10(self.hist_x_max), self.hist_n_bin + 1)
else:
return np.linspace(self.hist_x_min, self.hist_x_max,
self.hist_n_bin + 1)
@defer_draw
def _layers_changed(self, *args):
self.x_att_helper.set_multiple_data(self.layers_data)
class ImageViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for an image viewer.
"""
x_att = DDCProperty(
docstring='The component ID giving the pixel component '
'shown on the x axis')
y_att = DDCProperty(
docstring='The component ID giving the pixel component '
'shown on the y axis')
x_att_world = DDSCProperty(
docstring='The component ID giving the world component '
'shown on the x axis',
default_index=-1)
y_att_world = DDSCProperty(
docstring='The component ID giving the world component '
'shown on the y axis',
default_index=-2)
aspect = DDSCProperty(
0,
docstring='Whether to enforce square pixels (``equal``) '
'or fill the axes (``auto``)')
reference_data = DDSCProperty(
docstring='The dataset that is used to define the '
'available pixel/world components, and '
'which defines the coordinate frame in '
'which the images are shown')
slices = DDCProperty(docstring='The current slice along all dimensions')
color_mode = DDSCProperty(0,
docstring='Whether each layer can have '
'its own colormap (``Colormaps``) or '
'whether each layer is assigned '
'a single color (``One color per layer``)')
dpi = DDCProperty(
72,
docstring=
'The resolution (in dots per inch) of density maps, if present')
def __init__(self, **kwargs):
super(ImageViewerState, self).__init__()
self.limits_cache = {}
# NOTE: we don't need to use StateAttributeLimitsHelper here because
# we can simply call reset_limits below when x/y attributes change.
# Using StateAttributeLimitsHelper makes things a lot slower.
self.ref_data_helper = ManualDataComboHelper(self, 'reference_data')
self.xw_att_helper = ComponentIDComboHelper(self,
'x_att_world',
numeric=False,
categorical=False)
self.yw_att_helper = ComponentIDComboHelper(self,
'y_att_world',
numeric=False,
categorical=False)
self.add_callback('reference_data',
self._reference_data_changed,
priority=1000)
self.add_callback('layers', self._layers_changed, priority=1000)
self.add_callback('x_att', self._on_xatt_change, priority=500)
self.add_callback('y_att', self._on_yatt_change, priority=500)
self.add_callback('x_att_world', self._update_att, priority=500)
self.add_callback('y_att_world', self._update_att, priority=500)
self.add_callback('x_att_world',
self._on_xatt_world_change,
priority=1000)
self.add_callback('y_att_world',
self._on_yatt_world_change,
priority=1000)
aspect_display = {'equal': 'Square Pixels', 'auto': 'Automatic'}
ImageViewerState.aspect.set_choices(self, ['equal', 'auto'])
ImageViewerState.aspect.set_display_func(self, aspect_display.get)
ImageViewerState.color_mode.set_choices(
self, ['Colormaps', 'One color per layer'])
self.update_from_dict(kwargs)
def reset_limits(self):
if self.reference_data is None or self.x_att is None or self.y_att is None:
return
nx = self.reference_data.shape[self.x_att.axis]
ny = self.reference_data.shape[self.y_att.axis]
with delay_callback(self, 'x_min', 'x_max', 'y_min', 'y_max'):
self.x_min = -0.5
self.x_max = nx - 0.5
self.y_min = -0.5
self.y_max = ny - 0.5
# We need to adjust the limits in here to avoid triggering all
# the update events then changing the limits again.
self._adjust_limits_aspect()
@property
def _display_world(self):
return isinstance(getattr(self.reference_data, 'coords', None),
Coordinates)
def _reference_data_changed(self, *args):
# This signal can get emitted if just the choices but not the actual
# reference data change, so we check here that the reference data has
# actually changed
if self.reference_data is not getattr(self, '_last_reference_data',
None):
self._last_reference_data = self.reference_data
with delay_callback(self, 'x_att_world', 'y_att_world', 'slices'):
if self._display_world:
self.xw_att_helper.pixel_coord = False
self.yw_att_helper.pixel_coord = False
self.xw_att_helper.world_coord = True
self.yw_att_helper.world_coord = True
else:
self.xw_att_helper.pixel_coord = True
self.yw_att_helper.pixel_coord = True
self.xw_att_helper.world_coord = False
self.yw_att_helper.world_coord = False
self._update_combo_att()
self._set_default_slices()
def _layers_changed(self, *args):
# The layers callback gets executed if anything in the layers changes,
# but we only care about whether the actual set of 'layer' attributes
# for all layers change.
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self._update_combo_ref_data()
self._set_reference_data()
self._update_syncing()
self._layers_data_cache = layers_data
def _update_syncing(self):
# If there are multiple layers for a given dataset, we disable the
# syncing by default.
layer_state_by_data = defaultdict(list)
for layer_state in self.layers:
if isinstance(layer_state.layer, BaseData):
layer_state_by_data[layer_state.layer].append(layer_state)
for data, layer_states in layer_state_by_data.items():
if len(layer_states) > 1:
for layer_state in layer_states:
# Scatter layers don't have global_sync so we need to be
# careful here and make sure we return a default value
if getattr(layer_state, 'global_sync', False):
layer_state.global_sync = False
def _update_combo_ref_data(self):
self.ref_data_helper.set_multiple_data(self.layers_data)
def _update_combo_att(self):
with delay_callback(self, 'x_att_world', 'y_att_world'):
if self.reference_data is None:
self.xw_att_helper.set_multiple_data([])
self.yw_att_helper.set_multiple_data([])
else:
self.xw_att_helper.set_multiple_data([self.reference_data])
self.yw_att_helper.set_multiple_data([self.reference_data])
def _update_priority(self, name):
if name == 'layers':
return 3
elif name == 'reference_data':
return 2
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
@defer_draw
def _update_att(self, *args):
# Need to delay the callbacks here to make sure that we get a chance to
# update both x_att and y_att otherwise could end up triggering image
# slicing with two pixel components that are the same.
with delay_callback(self, 'x_att', 'y_att'):
if self.x_att_world is not None:
if self._display_world:
index = self.reference_data.world_component_ids.index(
self.x_att_world)
self.x_att = self.reference_data.pixel_component_ids[index]
else:
self.x_att = self.x_att_world
if self.y_att_world is not None:
if self._display_world:
index = self.reference_data.world_component_ids.index(
self.y_att_world)
self.y_att = self.reference_data.pixel_component_ids[index]
else:
self.y_att = self.y_att_world
@defer_draw
def _on_xatt_change(self, *args):
if self.x_att is not None:
if self._display_world:
self.x_att_world = self.reference_data.world_component_ids[
self.x_att.axis]
else:
self.x_att_world = self.x_att
@defer_draw
def _on_yatt_change(self, *args):
if self.y_att is not None:
if self._display_world:
self.y_att_world = self.reference_data.world_component_ids[
self.y_att.axis]
else:
self.y_att_world = self.y_att
@defer_draw
def _on_xatt_world_change(self, *args):
if self.x_att_world is not None and self.x_att_world == self.y_att_world:
world_ids = self.reference_data.world_component_ids
if self.x_att_world == world_ids[-1]:
self.y_att_world = world_ids[-2]
else:
self.y_att_world = world_ids[-1]
@defer_draw
def _on_yatt_world_change(self, *args):
if self.y_att_world is not None and self.y_att_world == self.x_att_world:
world_ids = self.reference_data.world_component_ids
if self.y_att_world == world_ids[-1]:
self.x_att_world = world_ids[-2]
else:
self.x_att_world = world_ids[-1]
def _set_reference_data(self):
if self.reference_data is None:
for layer in self.layers:
if isinstance(layer.layer, BaseData):
self.reference_data = layer.layer
return
def _set_default_slices(self):
# Need to make sure this gets called immediately when reference_data is changed
if self.reference_data is None:
self.slices = ()
else:
self.slices = (0, ) * self.reference_data.ndim
@property
def numpy_slice_aggregation_transpose(self):
"""
Returns slicing information usable by Numpy.
This returns two objects: the first is an object that can be used to
slice Numpy arrays and return a 2D array, and the second object is a
boolean indicating whether to transpose the result.
"""
if self.reference_data is None:
return None
slices = []
agg_func = []
for i in range(self.reference_data.ndim):
if i == self.x_att.axis or i == self.y_att.axis:
slices.append(slice(None))
agg_func.append(None)
else:
if isinstance(self.slices[i], AggregateSlice):
slices.append(self.slices[i].slice)
agg_func.append(self.slices[i].function)
else:
slices.append(self.slices[i])
transpose = self.y_att.axis > self.x_att.axis
return slices, agg_func, transpose
@property
def wcsaxes_slice(self):
"""
Returns slicing information usable by WCSAxes.
This returns an iterable of slices, and including ``'x'`` and ``'y'``
for the dimensions along which we are not slicing.
"""
if self.reference_data is None:
return None
slices = []
for i in range(self.reference_data.ndim):
if i == self.x_att.axis:
slices.append('x')
elif i == self.y_att.axis:
slices.append('y')
else:
if isinstance(self.slices[i], AggregateSlice):
slices.append(self.slices[i].center)
else:
slices.append(self.slices[i])
return slices[::-1]
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
with delay_callback(self, 'x_min', 'x_max'):
self.x_min, self.x_max = self.x_max, self.x_min
def flip_y(self):
"""
Flip the y_min/y_max limits.
"""
with delay_callback(self, 'y_min', 'y_max'):
self.y_min, self.y_max = self.y_max, self.y_min
class ImageLayerState(BaseImageLayerState):
"""
A state class that includes all the attributes for data layers in an image plot.
"""
attribute = DDSCProperty(docstring='The attribute shown in the layer')
v_min = DDCProperty(docstring='The lower level shown')
v_max = DDCProperty(docstring='The upper level shown')
percentile = DDSCProperty(docstring='The percentile value used to '
'automatically calculate levels')
contrast = DDCProperty(1, docstring='The contrast of the layer')
bias = DDCProperty(0.5,
docstring='A constant value that is added to the '
'layer before rendering')
cmap = DDCProperty(docstring='The colormap used to render the layer')
stretch = DDSCProperty(docstring='The stretch used to render the layer, '
'which should be one of ``linear``, '
'``sqrt``, ``log``, or ``arcsinh``')
global_sync = DDCProperty(True,
docstring='Whether the color and transparency '
'should be synced with the global '
'color and transparency for the data')
def __init__(self, layer=None, viewer_state=None, **kwargs):
super(ImageLayerState, self).__init__(layer=layer,
viewer_state=viewer_state)
self.attribute_lim_helper = StateAttributeLimitsHelper(
self,
attribute='attribute',
percentile='percentile',
lower='v_min',
upper='v_max')
self.attribute_att_helper = ComponentIDComboHelper(self,
'attribute',
numeric=True,
categorical=False)
percentile_display = {
100: 'Min/Max',
99.5: '99.5%',
99: '99%',
95: '95%',
90: '90%',
'Custom': 'Custom'
}
ImageLayerState.percentile.set_choices(
self, [100, 99.5, 99, 95, 90, 'Custom'])
ImageLayerState.percentile.set_display_func(self,
percentile_display.get)
stretch_display = {
'linear': 'Linear',
'sqrt': 'Square Root',
'arcsinh': 'Arcsinh',
'log': 'Logarithmic'
}
ImageLayerState.stretch.set_choices(
self, ['linear', 'sqrt', 'arcsinh', 'log'])
ImageLayerState.stretch.set_display_func(self, stretch_display.get)
self.add_callback('global_sync', self._update_syncing)
self.add_callback('layer', self._update_attribute)
self._update_syncing()
if layer is not None:
self._update_attribute()
self.update_from_dict(kwargs)
if self.cmap is None:
self.cmap = colormaps.members[0][1]
def _update_attribute(self, *args):
if self.layer is not None:
self.attribute_att_helper.set_multiple_data([self.layer])
self.attribute = self.layer.main_components[0]
def _update_priority(self, name):
if name == 'layer':
return 3
elif name == 'attribute':
return 2
elif name == 'global_sync':
return 1.5
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
def _update_syncing(self, *args):
if self.global_sync:
self._sync_color.enable_syncing()
self._sync_alpha.enable_syncing()
else:
self._sync_color.disable_syncing()
self._sync_alpha.disable_syncing()
def _get_image(self, view=None):
return self.layer[self.attribute, view]
def flip_limits(self):
"""
Flip the image levels.
"""
self.attribute_lim_helper.flip_limits()
def reset_contrast_bias(self):
with delay_callback(self, 'contrast', 'bias'):
self.contrast = 1
self.bias = 0.5
class ProfileViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a Profile viewer.
"""
x_att_pixel = DDCProperty(docstring='The component ID giving the pixel component '
'shown on the x axis')
x_att = DDSCProperty(docstring='The component ID giving the pixel or world component '
'shown on the x axis')
reference_data = DDSCProperty(docstring='The dataset that is used to define the '
'available pixel/world components, and '
'which defines the coordinate frame in '
'which the images are shown')
function = DDSCProperty(docstring='The function to use for collapsing data')
normalize = DDCProperty(False, docstring='Whether to normalize all profiles '
'to the [0:1] range')
# TODO: add function to use
def __init__(self, **kwargs):
super(ProfileViewerState, self).__init__()
self.ref_data_helper = ManualDataComboHelper(self, 'reference_data')
self.add_callback('layers', self._layers_changed)
self.add_callback('reference_data', self._reference_data_changed, echo_old=True)
self.add_callback('x_att', self._update_att)
self.add_callback('normalize', self._reset_y_limits)
self.x_att_helper = ComponentIDComboHelper(self, 'x_att',
numeric=False, datetime=False, categorical=False,
pixel_coord=True)
ProfileViewerState.function.set_choices(self, list(FUNCTIONS))
ProfileViewerState.function.set_display_func(self, FUNCTIONS.get)
self.update_from_dict(kwargs)
def _update_combo_ref_data(self):
self.ref_data_helper.set_multiple_data(self.layers_data)
def reset_limits(self):
with delay_callback(self, 'x_min', 'x_max', 'y_min', 'y_max'):
self._reset_x_limits()
self._reset_y_limits()
@property
def _display_world(self):
return getattr(self.reference_data, 'coords', None) is not None
@defer_draw
def _update_att(self, *args):
if self.x_att is not None:
if self._display_world:
if self.x_att in self.reference_data.pixel_component_ids:
self.x_att_pixel = self.x_att
else:
index = self.reference_data.world_component_ids.index(self.x_att)
self.x_att_pixel = self.reference_data.pixel_component_ids[index]
else:
self.x_att_pixel = self.x_att
self._reset_x_limits()
def _reset_x_limits(self, *event):
# NOTE: we don't use AttributeLimitsHelper because we need to avoid
# trying to get the minimum of *all* the world coordinates in the
# dataset. Instead, we use the same approach as in the layer state below
# and in the case of world coordinates we use online the spine of the
# data.
if self.reference_data is None or self.x_att_pixel is None:
return
data = self.reference_data
if self.x_att in data.pixel_component_ids:
x_min, x_max = -0.5, data.shape[self.x_att.axis] - 0.5
else:
axis = data.world_component_ids.index(self.x_att)
axis_view = [0] * data.ndim
axis_view[axis] = slice(None)
axis_values = data[self.x_att, tuple(axis_view)]
x_min, x_max = np.nanmin(axis_values), np.nanmax(axis_values)
with delay_callback(self, 'x_min', 'x_max'):
self.x_min = x_min
self.x_max = x_max
def _reset_y_limits(self, *event):
if self.normalize:
with delay_callback(self, 'y_min', 'y_max'):
self.y_min = -0.1
self.y_max = +1.1
else:
y_min, y_max = np.inf, -np.inf
for layer in self.layers:
try:
profile = layer.profile
except Exception: # e.g. incompatible subset
continue
if profile is not None:
x, y = profile
if len(y) > 0:
y_min = min(y_min, np.nanmin(y))
y_max = max(y_max, np.nanmax(y))
with delay_callback(self, 'y_min', 'y_max'):
if y_max > y_min:
self.y_min = y_min
self.y_max = y_max
else:
self.y_min = 0
self.y_max = 1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
with delay_callback(self, 'x_min', 'x_max'):
self.x_min, self.x_max = self.x_max, self.x_min
@defer_draw
def _layers_changed(self, *args):
self._update_combo_ref_data()
@defer_draw
def _reference_data_changed(self, before=None, after=None):
# A callback event for reference_data is triggered if the choices change
# but the actual selection doesn't - so we avoid resetting the WCS in
# this case.
if before is after:
return
for layer in self.layers:
layer.reset_cache()
# This signal can get emitted if just the choices but not the actual
# reference data change, so we check here that the reference data has
# actually changed
if self.reference_data is not getattr(self, '_last_reference_data', None):
self._last_reference_data = self.reference_data
with delay_callback(self, 'x_att'):
if self.reference_data is None:
self.x_att_helper.set_multiple_data([])
else:
self.x_att_helper.set_multiple_data([self.reference_data])
if self._display_world:
self.x_att_helper.world_coord = True
self.x_att = self.reference_data.world_component_ids[0]
else:
self.x_att_helper.world_coord = False
self.x_att = self.reference_data.pixel_component_ids[0]
self._update_att()
self.reset_limits()
def _update_priority(self, name):
if name == 'layers':
return 2
elif name == 'reference_data':
return 1.5
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
class ScatterViewerState(MatplotlibDataViewerState):
"""
A state class that includes all the attributes for a scatter viewer.
"""
x_att = DDSCProperty(docstring='The attribute to show on the x-axis',
default_index=0)
y_att = DDSCProperty(docstring='The attribute to show on the y-axis',
default_index=1)
dpi = DDCProperty(
72,
docstring=
'The resolution (in dots per inch) of density maps, if present')
def __init__(self, **kwargs):
super(ScatterViewerState, self).__init__()
self.limits_cache = {}
self.x_lim_helper = StateAttributeLimitsHelper(
self,
attribute='x_att',
lower='x_min',
upper='x_max',
log='x_log',
margin=0.05,
limits_cache=self.limits_cache)
self.y_lim_helper = StateAttributeLimitsHelper(
self,
attribute='y_att',
lower='y_min',
upper='y_max',
log='y_log',
margin=0.05,
limits_cache=self.limits_cache)
self.add_callback('layers', self._layers_changed)
self.x_att_helper = ComponentIDComboHelper(self,
'x_att',
pixel_coord=True,
world_coord=True)
self.y_att_helper = ComponentIDComboHelper(self,
'y_att',
pixel_coord=True,
world_coord=True)
self.update_from_dict(kwargs)
self.add_callback('x_log', self._reset_x_limits)
self.add_callback('y_log', self._reset_y_limits)
def _reset_x_limits(self, *args):
self.x_lim_helper.percentile = 100
self.x_lim_helper.update_values(force=True)
def _reset_y_limits(self, *args):
self.y_lim_helper.percentile = 100
self.y_lim_helper.update_values(force=True)
def reset_limits(self):
self._reset_x_limits()
self._reset_y_limits()
def _update_priority(self, name):
if name == 'layers':
return 2
elif name.endswith('_log'):
return 0.5
elif name.endswith(('_min', '_max')):
return 0
else:
return 1
def flip_x(self):
"""
Flip the x_min/x_max limits.
"""
self.x_lim_helper.flip_limits()
def flip_y(self):
"""
Flip the y_min/y_max limits.
"""
self.y_lim_helper.flip_limits()
def _get_x_components(self):
return self._get_components(self.x_att)
def _get_y_components(self):
return self._get_components(self.y_att)
def _get_components(self, cid):
# Construct list of components over all layers
components = []
for layer_state in self.layers:
if isinstance(layer_state.layer, Data):
layer = layer_state.layer
else:
layer = layer_state.layer.data
try:
components.append(layer.data.get_component(cid))
except IncompatibleAttribute:
pass
return components
def _layers_changed(self, *args):
layers_data = self.layers_data
layers_data_cache = getattr(self, '_layers_data_cache', [])
if layers_data == layers_data_cache:
return
self.x_att_helper.set_multiple_data(self.layers_data)
self.y_att_helper.set_multiple_data(self.layers_data)
self._layers_data_cache = layers_data
class ProfileLayerState(MatplotlibLayerState):
"""
A state class that includes all the attributes for layers in a Profile plot.
"""
linewidth = DDCProperty(1, docstring='The width of the line')
attribute = DDSCProperty(docstring='The attribute shown in the layer')
v_min = DDCProperty(docstring='The lower level shown')
v_max = DDCProperty(docstring='The upper leven shown')
percentile = DDSCProperty(docstring='The percentile value used to '
'automatically calculate levels')
def __init__(self, layer=None, viewer_state=None, **kwargs):
super(ProfileLayerState, self).__init__(layer=layer,
viewer_state=viewer_state)
self.attribute_att_helper = ComponentIDComboHelper(self,
'attribute',
numeric=True,
categorical=False)
percentile_display = {
100: 'Min/Max',
99.5: '99.5%',
99: '99%',
95: '95%',
90: '90%',
'Custom': 'Custom'
}
ProfileLayerState.percentile.set_choices(
self, [100, 99.5, 99, 95, 90, 'Custom'])
ProfileLayerState.percentile.set_display_func(self,
percentile_display.get)
self.add_callback('layer', self._update_attribute, priority=1000)
self.add_callback('layer', self._update_profile, priority=1000)
self.add_callback('attribute', self._update_profile, priority=1000)
if layer is not None:
self._update_attribute()
self.update_from_dict(kwargs)
def _update_attribute(self, *args):
if self.layer is not None:
self.attribute_att_helper.set_multiple_data([self.layer])
@property
def independent_x_att(self):
return is_convertible_to_single_pixel_cid(
self.layer, self.viewer_state.x_att) is not None
def normalize_values(self, values):
return (np.asarray(values) - self.v_min) / (self.v_max - self.v_min)
@property
def viewer_state(self):
return self._viewer_state
@viewer_state.setter
def viewer_state(self, viewer_state):
self._viewer_state = viewer_state
if viewer_state is not None:
self._viewer_state.add_callback('x_att',
self._update_profile,
priority=1000)
self._viewer_state.add_callback('function',
self._update_profile,
priority=1000)
self._update_profile()
@property
def profile(self):
return self._profile
def _update_profile(self, *event):
if self.viewer_state is None or self.viewer_state.x_att is None or self.attribute is None:
self._profile = None, None
return
# Check what pixel axis in the current dataset x_att corresponds to
pix_cid = is_convertible_to_single_pixel_cid(self.layer,
self.viewer_state.x_att)
if pix_cid is None:
self._profile = None, None
return
# If we get here, then x_att does correspond to a single pixel axis in
# the cube, so we now prepare a list of axes to collapse over.
axes = tuple(i for i in range(self.layer.ndim) if i != pix_cid.axis)
# We now get the y values for the data
# TODO: in future we should optimize the case where the mask is much
# smaller than the data to just average the relevant 'spaxels' in the
# data rather than collapsing the whole cube.
try:
if isinstance(self.layer, Data):
data = self.layer
data_values = data[self.attribute]
else:
data = self.layer.data
if isinstance(self.layer.subset_state, SliceSubsetState):
data_values = self.layer.subset_state.to_array(
self.layer.data, self.attribute)
else:
# We need to force a copy *and* convert to float just in case
data_values = np.array(data[self.attribute], dtype=float)
mask = self.layer.to_mask()
if np.sum(mask) == 0:
self._profile = [], []
return
data_values[~mask] = np.nan
except IncompatibleAttribute:
self._profile = None, None
return
# Collapse along all dimensions except x_att
if self.layer.ndim > 1:
with warnings.catch_warnings():
warnings.simplefilter("ignore", category=RuntimeWarning)
profile_values = self.viewer_state.function(data_values,
axis=axes)
else:
profile_values = data_values
# Finally, we get the coordinate values for the requested axis
axis_view = [0] * data.ndim
axis_view[pix_cid.axis] = slice(None)
axis_values = data[self.viewer_state.x_att, axis_view]
with delay_callback(self, 'v_min', 'v_max'):
self._profile = axis_values, profile_values
self.v_min = nanmin(profile_values)
self.v_max = nanmax(profile_values)
