def scatter2d(self, x=None, y=None, data=None, widget='bqplot', color=None, size=None, viewer_state=None, layer_state=None):
if widget == 'bqplot':
from .bqplot import BqplotScatterView
viewer_cls = BqplotScatterView
elif widget == 'matplotlib':
from .matplotlib.scatter import ScatterJupyterViewer
viewer_cls = ScatterJupyterViewer
else:
raise ValueError("Widget type should be 'bqplot' or 'matplotlib'")
if data is None and len(self._data) != 1:
raise ValueError('There is more than 1 data set in the data collection, please pass a data argument')
data = data or self._data[0]
viewer_state_obj = viewer_cls._state_cls()
viewer_state_obj.x_att_helper.append_data(data)
viewer_state_obj.y_att_helper.append_data(data)
viewer_state = viewer_state or {}
if x is not None:
viewer_state['x_att'] = data.id[x]
if x is not None:
viewer_state['y_att'] = data.id[y]
viewer_state_obj.update_from_dict(viewer_state)
view = self.new_data_viewer(viewer_cls, data=data, state=viewer_state_obj)
layer_state = layer_state or {}
_update_not_none(layer_state, color=color, size=size)
view.layers[0].state.update_from_dict(layer_state)
return view
def histogram1d(self, x=None, data=None, widget='bqplot', color=None, x_min=None, x_max=None, hist_n_bin=None, normalize=False, cumulative=False, viewer_state=None, layer_state=None):
if widget == 'bqplot':
from .bqplot import BqplotHistogramView
viewer_cls = BqplotHistogramView
elif widget == 'matplotlib':
from .matplotlib.histogram import HistogramJupyterViewer
viewer_cls = HistogramJupyterViewer
else:
raise ValueError("Widget type should be 'bqplot' or 'matplotlib'")
if data is None and len(self._data) != 1:
raise ValueError('There is more than 1 data set in the data collection, please pass a data argument')
data = data or self._data[0]
state = viewer_cls._state_cls()
state.x_att_helper.append_data(data)
viewer_state_obj = viewer_cls._state_cls()
viewer_state_obj.x_att_helper.append_data(data)
viewer_state = viewer_state or {}
if x is not None:
viewer_state['x_att'] = data.id[x]
# x_min and x_max get set to the hist_x_min/max in glue.viewers.histogram.state
# for this API it make more sense to call it x_min and x_max, and for consistency with the rest
_update_not_none(viewer_state, hist_x_min=x_min, hist_x_max=x_max, hist_n_bin=hist_n_bin,
normalize=normalize, cumulative=cumulative)
viewer_state_obj.update_from_dict(viewer_state)
view = self.new_data_viewer(viewer_cls, data=data, state=viewer_state_obj)
layer_state = layer_state or {}
_update_not_none(layer_state, color=color)
view.layers[0].state.update_from_dict(layer_state)
return view
def add_data(self, data, color=None, alpha=None, **layer_state):
result = super().add_data(data)
if not result:
return
layer = list(self._layer_artist_container[data])[-1]
layer_state = dict(layer_state)
_update_not_none(layer_state, color=color, alpha=alpha)
layer.state.update_from_dict(layer_state)
return True
def add_data(self, data, color=None, alpha=None, **layer_state):
# Check if data already exists in viewer
if not self.allow_duplicate_data and data in self._layer_artist_container:
return None
if self.large_data_size is not None and data.size >= self.large_data_size:
proceed = self.warn('Add large data set?',
'Data set {0:s} has {1:d} points, and '
'may render slowly.'.format(
data.label, data.size),
default='Cancel',
setting='show_large_data_warning')
if not proceed:
return None
if data not in self.session.data_collection:
raise IncompatibleDataException("Data not in DataCollection")
# Create layer artist and add to container
layer = self.get_data_layer_artist(data)
if layer is None:
return None
self._layer_artist_container.append(layer)
layer_state = dict(layer_state)
_update_not_none(layer_state, color=color, alpha=alpha)
layer.update()
layer.state.update_from_dict(layer_state)
# Add existing subsets to viewer
for subset in data.subsets:
self.add_subset(subset)
return layer
def scatter2d(self,
*,
data=None,
x=None,
y=None,
widget='bqplot',
color=None,
size=None,
viewer_state=None,
layer_state=None,
show=True):
"""
Open an interactive 2d scatter plot viewer.
Parameters
----------
data : str or `~glue.core.data.Data`, optional
The initial dataset to show in the viewer. Additional
datasets can be added later using the ``add_data`` method on
the viewer object.
x : str or `~glue.core.component_id.ComponentID`, optional
The attribute to show on the x axis.
y : str or `~glue.core.component_id.ComponentID`, optional
The attribute to show on the y axis.
widget : {'bqplot', 'matplotlib'}
Whether to use bqplot or Matplotlib as the front-end.
color : str or tuple, optional
The color to use for the markers. Note that this will have the
effect of setting the data color for all viewers.
size : int or float
The size to use for the markers. Note that this will have the
effect of setting the marker size for all viewers.
viewer_state : `~glue.viewers.common.state.ViewerState`
The initial state for the viewer (advanced).
layer_state : `~glue.viewers.common.state.LayerState`
The initial state for the data layer (advanced).
show : bool, optional
Whether to show the view immediately (`True`) or whether to only
show it later if the ``show()`` method is called explicitly
(`False`).
"""
if widget == 'bqplot':
from .bqplot.scatter import BqplotScatterView
viewer_cls = BqplotScatterView
elif widget == 'matplotlib':
from .matplotlib.scatter import ScatterJupyterViewer
viewer_cls = ScatterJupyterViewer
else:
raise ValueError("Widget type should be 'bqplot' or 'matplotlib'")
data = validate_data_argument(self.data_collection, data)
viewer_state_obj = viewer_cls._state_cls()
viewer_state_obj.x_att_helper.append_data(data)
viewer_state_obj.y_att_helper.append_data(data)
viewer_state = viewer_state or {}
if x is not None:
viewer_state['x_att'] = data.id[x]
if y is not None:
viewer_state['y_att'] = data.id[y]
viewer_state_obj.update_from_dict(viewer_state)
view = self.new_data_viewer(viewer_cls,
data=data,
state=viewer_state_obj,
show=show)
layer_state = layer_state or {}
_update_not_none(layer_state, color=color, size=size)
view.layers[0].state.update_from_dict(layer_state)
return view
def histogram1d(self,
*,
data=None,
x=None,
widget='bqplot',
color=None,
x_min=None,
x_max=None,
n_bin=None,
normalize=False,
cumulative=False,
viewer_state=None,
layer_state=None,
show=True):
"""
Open an interactive histogram viewer.
Parameters
----------
data : str or `~glue.core.data.Data`, optional
The initial dataset to show in the viewer. Additional
datasets can be added later using the ``add_data`` method on
the viewer object.
x : str or `~glue.core.component_id.ComponentID`, optional
The attribute to show on the x axis.
widget : {'bqplot', 'matplotlib'}
Whether to use bqplot or Matplotlib as the front-end.
color : str or tuple, optional
The color to use for the data. Note that this will have the
effect of setting the data color for all viewers.
x_min : float, optional
The lower value of the range to compute the histogram in.
x_max : float, optional
The upper value of the range to compute the histogram in.
n_bin : int, optional
The number of bins in the histogram.
normalize : bool, optional
Whether to normalize the histogram.
cumulative : bool, optional
Whether to show a cumulative histogram.
viewer_state : `~glue.viewers.common.state.ViewerState`
The initial state for the viewer (advanced).
layer_state : `~glue.viewers.common.state.LayerState`
The initial state for the data layer (advanced).
show : bool, optional
Whether to show the view immediately (`True`) or whether to only
show it later if the ``show()`` method is called explicitly
(`False`).
"""
if widget == 'bqplot':
from .bqplot.histogram import BqplotHistogramView
viewer_cls = BqplotHistogramView
elif widget == 'matplotlib':
from .matplotlib.histogram import HistogramJupyterViewer
viewer_cls = HistogramJupyterViewer
else:
raise ValueError("Widget type should be 'bqplot' or 'matplotlib'")
data = validate_data_argument(self.data_collection, data)
viewer_state_obj = viewer_cls._state_cls()
viewer_state_obj.x_att_helper.append_data(data)
viewer_state = viewer_state or {}
if x is not None:
viewer_state['x_att'] = data.id[x]
# x_min and x_max get set to the hist_x_min/max in
# glue.viewers.histogram.state for this API it make more sense to call
# it x_min and x_max, and for consistency with the rest
_update_not_none(viewer_state,
hist_x_min=x_min,
hist_x_max=x_max,
hist_n_bin=n_bin,
normalize=normalize,
cumulative=cumulative)
viewer_state_obj.update_from_dict(viewer_state)
view = self.new_data_viewer(viewer_cls,
data=data,
state=viewer_state_obj,
show=show)
layer_state = layer_state or {}
_update_not_none(layer_state, color=color)
view.layers[0].state.update_from_dict(layer_state)
return view
def scatter2d(self,
x=None,
y=None,
data=None,
widget='bqplot',
color=None,
size=None,
viewer_state=None,
layer_state=None):
"""
Open an interactive 2d scatter plot viewer.
Parameters
----------
x : str or `~glue.core.component_id.ComponentID`, optional
The attribute to show on the x axis.
y : str or `~glue.core.component_id.ComponentID`, optional
The attribute to show on the y axis.
data : `~glue.core.data.Data`, optional
The initial dataset to show in the viewer. Additional
datasets can be added later using the ``add_data`` method on
the viewer object.
widget : {'bqplot', 'matplotlib'}
Whether to use bqplot or Matplotlib as the front-end.
color : str or tuple, optional
The color to use for the markers. Note that this will have the
effect of setting the data color for all viewers.
size : int or float
The size to use for the markers. Note that this will have the
effect of setting the marker size for all viewers.
viewer_state : `~glue.viewers.common.state.ViewerState`
The initial state for the viewer (advanced).
layer_state : `~glue.viewers.common.state.LayerState`
The initial state for the data layer (advanced).
"""
if widget == 'bqplot':
from .bqplot.scatter import BqplotScatterView
viewer_cls = BqplotScatterView
elif widget == 'matplotlib':
from .matplotlib.scatter import ScatterJupyterViewer
viewer_cls = ScatterJupyterViewer
else:
raise ValueError("Widget type should be 'bqplot' or 'matplotlib'")
if data is None:
if len(self._data) != 1:
raise ValueError(
'There is more than one data set in the data collection, please pass a data argument'
)
else:
data = self._data[0]
viewer_state_obj = viewer_cls._state_cls()
viewer_state_obj.x_att_helper.append_data(data)
viewer_state_obj.y_att_helper.append_data(data)
viewer_state = viewer_state or {}
if x is not None:
viewer_state['x_att'] = data.id[x]
if x is not None:
viewer_state['y_att'] = data.id[y]
viewer_state_obj.update_from_dict(viewer_state)
view = self.new_data_viewer(viewer_cls,
data=data,
state=viewer_state_obj)
layer_state = layer_state or {}
_update_not_none(layer_state, color=color, size=size)
view.layers[0].state.update_from_dict(layer_state)
return view
