def __init__(self):
# pylint: disable=missing-docstring
super().__init__()
self.data = self.discrete_data = None
self.attrs = []
self.input_features = None
self.areas = []
self.selection = set()
self.attr_box = gui.hBox(self.mainArea)
model = VariableListModel()
model.wrap(self.attrs)
combo_args = dict(
widget=self.attr_box, master=self, contentsLength=12,
callback=self.update_attr, sendSelectedValue=True, valueType=str,
model=model)
fixed_size = (QSizePolicy.Fixed, QSizePolicy.Fixed)
self.attrXCombo = gui.comboBox(value="attrX", **combo_args)
gui.widgetLabel(self.attr_box, "\u2715", sizePolicy=fixed_size)
self.attrYCombo = gui.comboBox(value="attrY", **combo_args)
self.vizrank, self.vizrank_button = SieveRank.add_vizrank(
self.attr_box, self, "Score Combinations", self.set_attr)
self.vizrank_button.setSizePolicy(*fixed_size)
self.canvas = QGraphicsScene()
self.canvasView = ViewWithPress(
self.canvas, self.mainArea, handler=self.reset_selection)
self.mainArea.layout().addWidget(self.canvasView)
self.canvasView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.canvasView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
box = gui.hBox(self.mainArea)
box.layout().addWidget(self.graphButton)
box.layout().addWidget(self.report_button)
def __init__(self):
super().__init__()
self.data = None
self.input_features = None
self.attrs = []
self.attr_box = gui.hBox(self.mainArea)
model = VariableListModel()
model.wrap(self.attrs)
self.attrXCombo = gui.comboBox(
self.attr_box, self, value="attrX", contentsLength=12,
callback=self.change_attr, sendSelectedValue=True, valueType=str)
self.attrXCombo.setModel(model)
gui.widgetLabel(self.attr_box, "\u2715").\
setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self.attrYCombo = gui.comboBox(
self.attr_box, self, value="attrY", contentsLength=12,
callback=self.change_attr, sendSelectedValue=True, valueType=str)
self.attrYCombo.setModel(model)
self.canvas = QGraphicsScene()
self.canvasView = ViewWithPress(self.canvas, self.mainArea,
handler=self.reset_selection)
self.mainArea.layout().addWidget(self.canvasView)
self.canvasView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.canvasView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
box = gui.hBox(self.mainArea)
box.layout().addWidget(self.graphButton)
box.layout().addWidget(self.report_button)
def __init__(self):
self.model_selected = VariableListModel(enable_dnd=True)
self.model_selected.removed.connect(self.__model_selected_changed)
self.model_other = VariableListModel(enable_dnd=True)
self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
None, self, "Suggest Features", self.__vizrank_set_attrs)
super().__init__()
def __init__(self):
self.model_selected = VariableListModel(enable_dnd=True)
self.model_selected.rowsInserted.connect(self.__model_selected_changed)
self.model_selected.rowsRemoved.connect(self.__model_selected_changed)
self.model_other = VariableListModel(enable_dnd=True)
self.vizrank, self.btn_vizrank = RadvizVizRank.add_vizrank(
None, self, "Suggest features", self.__vizrank_set_attrs
)
super().__init__()
class TestListModel(GuiTest):
def setUp(self):
self.widget = OWWidget()
self.widget.foo = None
self.attrs = VariableListModel()
self.view = gui.listView(
self.widget.controlArea, self.widget, "foo", model=self.attrs)
def test_select_callback(self):
widget = self.widget
view = self.view
self.assertIsNone(widget.foo)
a, b, c = (ContinuousVariable(x) for x in "abc")
self.attrs[:] = [a, b, c]
view.setCurrentIndex(self.attrs.index(0, 0))
self.assertIs(widget.foo, a)
view.setCurrentIndex(self.attrs.index(2, 0))
self.assertIs(widget.foo, c)
view.setSelectionMode(view.MultiSelection)
sel_model = view.selectionModel()
sel_model.clear()
view.setCurrentIndex(self.attrs.index(1, 0))
self.assertEqual(widget.foo, [b])
def test_select_callfront(self):
widget = self.widget
view = self.view
a, b, c = (ContinuousVariable(x) for x in "abc")
self.attrs[:] = [a, b, c]
widget.foo = b
selection = view.selectedIndexes()
self.assertEqual(len(selection), 1)
self.assertEqual(selection[0].row(), 1)
view.setSelectionMode(view.MultiSelection)
widget.foo = [a, c]
selection = view.selectedIndexes()
self.assertEqual(len(selection), 2)
self.assertEqual({selection[0].row(), selection[1].row()}, {0, 2})
widget.foo = []
selection = view.selectedIndexes()
self.assertEqual(len(selection), 0)
widget.foo = [2, "b"]
selection = view.selectedIndexes()
self.assertEqual(len(selection), 2)
self.assertEqual({selection[0].row(), selection[1].row()}, {1, 2})
def __init__(self):
super().__init__()
self.corpus = None
# Browse file box
fbox = gui.widgetBox(self.controlArea, "Corpus file", orientation=0)
self.file_widget = widgets.FileWidget(
recent_files=self.recent_files, icon_size=(16, 16),
on_open=self.open_file, dialog_format=self.dlgFormats,
dialog_title='Open Orange Document Corpus',
reload_label='Reload', browse_label='Browse',
allow_empty=False, minimal_width=250,
)
fbox.layout().addWidget(self.file_widget)
# Corpus info
ibox = gui.widgetBox(self.controlArea, "Corpus info", addSpace=True)
self.info_label = gui.label(ibox, self, "")
self.update_info()
# Used Text Features
fbox = gui.widgetBox(self.controlArea, orientation=0)
ubox = gui.widgetBox(fbox, "Used text features", addSpace=False)
self.used_attrs_model = VariableListModel(enable_dnd=True)
self.used_attrs_view = VariablesListItemView()
self.used_attrs_view.setModel(self.used_attrs_model)
ubox.layout().addWidget(self.used_attrs_view)
aa = self.used_attrs_model
aa.dataChanged.connect(self.update_feature_selection)
aa.rowsInserted.connect(self.update_feature_selection)
aa.rowsRemoved.connect(self.update_feature_selection)
# Ignored Text Features
ibox = gui.widgetBox(fbox, "Ignored text features", addSpace=False)
self.unused_attrs_model = VariableListModel(enable_dnd=True)
self.unused_attrs_view = VariablesListItemView()
self.unused_attrs_view.setModel(self.unused_attrs_model)
ibox.layout().addWidget(self.unused_attrs_view)
# Documentation Data Sets & Report
box = gui.hBox(self.controlArea)
self.browse_documentation = gui.button(
box, self, "Browse documentation corpora",
callback=lambda: self.file_widget.browse(
get_sample_corpora_dir()),
autoDefault=False,
)
# load first file
self.file_widget.select(0)
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2 = gui.comboBox(
box, self, 'ax2', label='Y axis:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal')
self.combo_ax1 = gui.comboBox(
box, self, 'ax1', label='Radial:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal')
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(
box, self, 'agg_func', label='Function:', orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.ExtendedSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def _create_layout(self):
box = gui.widgetBox(self.controlArea,
orientation='horizontal')
self.varmodel = VariableListModel(parent=self)
self.attr_combo = gui.comboBox(box, self, 'selected_attr',
orientation=Qt.Horizontal,
label='Region attribute:',
callback=self.on_attr_change,
sendSelectedValue=True)
self.attr_combo.setModel(self.varmodel)
self.map_combo = gui.comboBox(box, self, 'selected_map',
orientation=Qt.Horizontal,
label='Map type:',
callback=self.on_map_change,
items=Map.all)
hexpand = QSizePolicy(QSizePolicy.Expanding,
QSizePolicy.Fixed)
self.attr_combo.setSizePolicy(hexpand)
self.map_combo.setSizePolicy(hexpand)
url = urljoin('file:',
pathname2url(os.path.join(
os.path.dirname(__file__),
'resources',
'owgeomap.html')))
self.webview = gui.WebviewWidget(self.controlArea, self, url=QUrl(url))
self.controlArea.layout().addWidget(self.webview)
QTimer.singleShot(
0, lambda: self.webview.evalJS('REGIONS = {};'.format({Map.WORLD: CC_WORLD,
Map.EUROPE: CC_EUROPE,
Map.USA: CC_USA})))
class TestListModel(GuiTest):
def test_select(self):
widget = OWWidget()
widget.foo = None
self.attrs = VariableListModel()
view = gui.listView(widget.controlArea, widget, "foo", model=self.attrs)
self.assertIsNone(widget.foo)
a, b, c = (ContinuousVariable(x) for x in "abc")
self.attrs[:] = [a, b, c]
view.setCurrentIndex(self.attrs.index(0, 0))
self.assertIs(widget.foo, a)
view.setCurrentIndex(self.attrs.index(2, 0))
self.assertIs(widget.foo, c)
widget.foo = b
selection = view.selectedIndexes()
self.assertEqual(len(selection), 1)
self.assertEqual(selection[0].row(), 1)
def dropMimeData(self, mime, action, row, column, parent):
""" Ensure only one variable can be dropped onto the view.
"""
vars = mime.property('_items')
if vars is None or len(self) + len(vars) > 1:
return False
if action == Qt.IgnoreAction:
return True
return VariableListModel.dropMimeData(
self, mime, action, row, column, parent)
def __init__(self):
super().__init__()
self.data = None
self.subset_data = None
self.subset_indices = None
self._embedding_coords = None
self._rand_indices = None
self.__replot_requested = False
self.variable_x = ContinuousVariable("radviz-x")
self.variable_y = ContinuousVariable("radviz-y")
box = gui.vBox(self.mainArea, True, margin=0)
self.graph = OWRadvizGraph(self, box)
box.layout().addWidget(self.graph.plot_widget)
self.variables_selection = VariablesSelection()
self.model_selected = selected = VariableListModel(enable_dnd=True)
self.model_other = other = VariableListModel(enable_dnd=True)
self.variables_selection(self, selected, other, self.controlArea)
self.vizrank, self.btn_vizrank = RadvizVizRank.add_vizrank(
None, self, "Suggest features", self.vizrank_set_attrs)
# Todo: this button introduces some margin at the bottom?!
self.variables_selection.add_remove.layout().addWidget(
self.btn_vizrank)
g = self.graph.gui
g.point_properties_box(self.controlArea)
g.effects_box(self.controlArea)
g.plot_properties_box(self.controlArea)
self.graph.box_zoom_select(self.controlArea)
gui.auto_commit(self.controlArea, self, "auto_commit",
"Send Selection", "Send Automatically")
self.graph.view_box.started.connect(self._randomize_indices)
self.graph.view_box.moved.connect(self._manual_move)
self.graph.view_box.finished.connect(self._finish_manual_move)
def _setup_layout(self):
self.controlArea.setMinimumWidth(self.controlArea.sizeHint().width())
self.layout().setSizeConstraint(QLayout.SetFixedSize)
widget_box = widgetBox(self.controlArea, 'Info')
self.input_data_info = widgetLabel(widget_box, self._NO_DATA_INFO_TEXT)
self.connection_info = widgetLabel(widget_box, "")
widget_box = widgetBox(self.controlArea, 'Settings')
self.cb_image_attr = comboBox(
widget=widget_box,
master=self,
value='cb_image_attr_current_id',
label='Image attribute:',
orientation=Qt.Horizontal,
callback=self._cb_image_attr_changed
)
self.cb_embedder = comboBox(
widget=widget_box,
master=self,
value='cb_embedder_current_id',
label='Embedder:',
orientation=Qt.Horizontal,
callback=self._cb_embedder_changed
)
self.cb_embedder.setModel(VariableListModel(
[EMBEDDERS_INFO[e]['name'] for e in self.embedders]))
if not self.cb_embedder_current_id < len(self.embedders):
self.cb_embedder_current_id = 0
self.cb_embedder.setCurrentIndex(self.cb_embedder_current_id)
current_embedder = self.embedders[self.cb_embedder_current_id]
self.embedder_info = widgetLabel(
widget_box,
EMBEDDERS_INFO[current_embedder]['description']
)
self.auto_commit_widget = auto_commit(
widget=self.controlArea,
master=self,
value='_auto_apply',
label='Apply',
commit=self.commit
)
self.cancel_button = QPushButton(
'Cancel',
icon=self.style().standardIcon(QStyle.SP_DialogCancelButton),
)
self.cancel_button.clicked.connect(self.cancel)
hbox = hBox(self.controlArea)
hbox.layout().addWidget(self.cancel_button)
self.cancel_button.setDisabled(True)
def test_select(self):
widget = OWWidget()
widget.foo = None
self.attrs = VariableListModel()
view = gui.listView(widget.controlArea,
widget,
"foo",
model=self.attrs)
self.assertIsNone(widget.foo)
a, b, c = (ContinuousVariable(x) for x in "abc")
self.attrs[:] = [a, b, c]
view.setCurrentIndex(self.attrs.index(0, 0))
self.assertIs(widget.foo, a)
view.setCurrentIndex(self.attrs.index(2, 0))
self.assertIs(widget.foo, c)
widget.foo = b
selection = view.selectedIndexes()
self.assertEqual(len(selection), 1)
self.assertEqual(selection[0].row(), 1)
def __init__(self):
super().__init__()
self.data = self.discrete_data = None
self.areas = None
self.input_features = None
self.attrs = []
self.attr_box = gui.hBox(self.mainArea)
model = VariableListModel()
model.wrap(self.attrs)
self.attrXCombo = gui.comboBox(self.attr_box,
self,
value="attrX",
contentsLength=12,
callback=self.change_attr,
sendSelectedValue=True,
valueType=str)
self.attrXCombo.setModel(model)
gui.widgetLabel(self.attr_box, "\u2715").\
setSizePolicy(QSizePolicy.Fixed, QSizePolicy.Fixed)
self.attrYCombo = gui.comboBox(self.attr_box,
self,
value="attrY",
contentsLength=12,
callback=self.change_attr,
sendSelectedValue=True,
valueType=str)
self.attrYCombo.setModel(model)
self.canvas = QGraphicsScene()
self.canvasView = ViewWithPress(self.canvas,
self.mainArea,
handler=self.reset_selection)
self.mainArea.layout().addWidget(self.canvasView)
self.canvasView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.canvasView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
box = gui.hBox(self.mainArea)
box.layout().addWidget(self.graphButton)
box.layout().addWidget(self.report_button)
def __init__(self):
super().__init__()
self.corpus = None
# Browse file box
fbox = gui.widgetBox(self.controlArea, "Corpus file", orientation=0)
widget = widgets.FileWidget(recent_files=self.recent_files, icon_size=(16, 16), on_open=self.open_file,
directory_aliases={"Browse documentation corpora ...": get_sample_corpora_dir()},
dialog_format=self.dlgFormats, dialog_title='Open Orange Document Corpus',
allow_empty=False, reload_label='Reload', browse_label='Browse')
fbox.layout().addWidget(widget)
# Corpus info
ibox = gui.widgetBox(self.controlArea, "Corpus info", addSpace=True)
corp_info = "Corpus of 0 documents."
self.info_label = gui.label(ibox, self, corp_info)
# Used Text Features
fbox = gui.widgetBox(self.controlArea, orientation=0)
ubox = gui.widgetBox(fbox, "Used text features", addSpace=True)
self.used_attrs = VariableListModel(enable_dnd=True)
self.used_attrs_view = VariablesListItemView()
self.used_attrs_view.setModel(self.used_attrs)
ubox.layout().addWidget(self.used_attrs_view)
aa = self.used_attrs
aa.dataChanged.connect(self.update_feature_selection)
aa.rowsInserted.connect(self.update_feature_selection)
aa.rowsRemoved.connect(self.update_feature_selection)
# Ignored Text Features
ibox = gui.widgetBox(fbox, "Ignored text features", addSpace=True)
self.unused_attrs = VariableListModel(enable_dnd=True)
self.unused_attrs_view = VariablesListItemView()
self.unused_attrs_view.setModel(self.unused_attrs)
ibox.layout().addWidget(self.unused_attrs_view)
# load first file
widget.select(0)
def _setup_layout(self):
self.controlArea.setMinimumWidth(self.controlArea.sizeHint().width())
self.layout().setSizeConstraint(QLayout.SetFixedSize)
widget_box = widgetBox(self.controlArea, "Settings")
self.cb_image_attr = comboBox(
widget=widget_box,
master=self,
value="cb_image_attr_current_id",
label="Image attribute:",
orientation=Qt.Horizontal,
callback=self._cb_image_attr_changed,
)
self.cb_embedder = comboBox(
widget=widget_box,
master=self,
value="cb_embedder_current_id",
label="Embedder:",
orientation=Qt.Horizontal,
callback=self._cb_embedder_changed,
)
names = [
EMBEDDERS_INFO[e]["name"] +
(" (local)" if EMBEDDERS_INFO[e].get("is_local") else "")
for e in self.embedders
]
self.cb_embedder.setModel(VariableListModel(names))
if not self.cb_embedder_current_id < len(self.embedders):
self.cb_embedder_current_id = 0
self.cb_embedder.setCurrentIndex(self.cb_embedder_current_id)
current_embedder = self.embedders[self.cb_embedder_current_id]
self.embedder_info = widgetLabel(
widget_box, EMBEDDERS_INFO[current_embedder]["description"])
self.auto_commit_widget = auto_commit(
widget=self.controlArea,
master=self,
value="_auto_apply",
label="Apply",
commit=self.commit,
)
self.cancel_button = QPushButton(
"Cancel",
icon=self.style().standardIcon(QStyle.SP_DialogCancelButton),
)
self.cancel_button.clicked.connect(self.cancel)
hbox = hBox(self.controlArea)
hbox.layout().addWidget(self.cancel_button)
self.cancel_button.setDisabled(True)
def __init__(self):
# pylint: disable=missing-docstring
super().__init__()
self.data = self.discrete_data = None
self.attrs = []
self.input_features = None
self.areas = []
self.selection = set()
self.attr_box = gui.hBox(self.mainArea)
model = VariableListModel()
model.wrap(self.attrs)
combo_args = dict(widget=self.attr_box,
master=self,
contentsLength=12,
callback=self.update_attr,
sendSelectedValue=True,
valueType=str,
model=model)
fixed_size = (QSizePolicy.Fixed, QSizePolicy.Fixed)
self.attrXCombo = gui.comboBox(value="attrX", **combo_args)
gui.widgetLabel(self.attr_box, "\u2715", sizePolicy=fixed_size)
self.attrYCombo = gui.comboBox(value="attrY", **combo_args)
self.vizrank, self.vizrank_button = SieveRank.add_vizrank(
self.attr_box, self, "Score Combinations", self.set_attr)
self.vizrank_button.setSizePolicy(*fixed_size)
self.canvas = QGraphicsScene()
self.canvasView = ViewWithPress(self.canvas,
self.mainArea,
handler=self.reset_selection)
self.mainArea.layout().addWidget(self.canvasView)
self.canvasView.setVerticalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
self.canvasView.setHorizontalScrollBarPolicy(Qt.ScrollBarAlwaysOff)
box = gui.hBox(self.mainArea)
box.layout().addWidget(self.graphButton)
box.layout().addWidget(self.report_button)
def __init__(self):
self.data = None
box = gui.vBox(self.controlArea, 'Differencing')
gui.comboBox(box,
self,
'chosen_operation',
orientation=Qt.Horizontal,
items=[el.value for el in self.Operation],
label='Compute:',
callback=self.on_changed,
sendSelectedValue=True)
self.order_spin = gui.spin(
box,
self,
'diff_order',
1,
2,
label='Differencing order:',
callback=self.on_changed,
tooltip='The value corresponds to n-th order numerical '
'derivative of the series. \nThe order is fixed to 1 '
'if the shift period is other than 1.')
gui.spin(box,
self,
'shift_period',
1,
100,
label='Shift:',
callback=self.on_changed,
tooltip='Set this to other than 1 if you don\'t want to '
'compute differences for subsequent values but for '
'values shifted number of spaces apart. \n'
'If this value is different from 1, differencing '
'order is fixed to 1.')
gui.checkBox(box,
self,
'invert_direction',
label='Invert differencing direction',
callback=self.on_changed,
tooltip='Influences where the series is padded with nan '
'values — at the beginning or at the end.')
self.view = view = QListView(self,
selectionMode=QListView.ExtendedSelection)
self.model = model = VariableListModel(parent=self)
view.setModel(model)
view.selectionModel().selectionChanged.connect(self.on_changed)
box.layout().addWidget(view)
gui.auto_commit(box, self, 'autocommit', '&Apply')
def __init__(self):
hbox = gui.hBox(self.controlArea)
_properties = dict(alternatingRowColors=True,
defaultDropAction=Qt.MoveAction,
dragDropMode=QListView.DragDrop,
dragEnabled=True,
selectionMode=QListView.ExtendedSelection,
selectionBehavior=QListView.SelectRows,
showDropIndicator=True,
acceptDrops=True)
listview_avail = DnDListView(lambda: self.commit(), self,
**_properties)
self.model_avail = model = VariableListModel(parent=self,
enable_dnd=True)
listview_avail.setModel(model)
listview_key = DnDListView(lambda: self.commit(), self, **_properties)
self.model_key = model = VariableListModel(parent=self,
enable_dnd=True)
listview_key.setModel(model)
box = gui.vBox(hbox, 'Available Variables')
box.layout().addWidget(listview_avail)
box = gui.vBox(hbox, 'Group-By Key')
box.layout().addWidget(listview_key)
gui.comboBox(self.controlArea,
self,
'tiebreaker',
label='Which instance to select in each group:',
items=tuple(self.TIEBREAKERS.keys()),
callback=lambda: self.commit(),
sendSelectedValue=True)
gui.auto_commit(self.controlArea,
self,
'autocommit',
'Commit',
orientation=Qt.Horizontal)
def _create_layout(self):
box = gui.widgetBox(self.controlArea,
orientation='horizontal')
self.varmodel = VariableListModel(parent=self)
self.attr_combo = gui.comboBox(box, self, 'selected_attr',
orientation=Qt.Horizontal,
label='Region attribute:',
callback=self.on_attr_change,
sendSelectedValue=True)
self.attr_combo.setModel(self.varmodel)
self.map_combo = gui.comboBox(box, self, 'selected_map',
orientation=Qt.Horizontal,
label='Map type:',
callback=self.on_map_change,
items=Map.all)
hexpand = QSizePolicy(QSizePolicy.Expanding,
QSizePolicy.Fixed)
self.attr_combo.setSizePolicy(hexpand)
self.map_combo.setSizePolicy(hexpand)
url = urljoin('file:',
pathname2url(os.path.join(
os.path.dirname(__file__),
'resources',
'owdocmap.html')))
class Bridge(QObject):
@pyqtSlot(str)
def region_selected(_, regions):
return self.region_selected(regions)
self.webview = gui.WebviewWidget(self.controlArea, Bridge(), url=QUrl(url), debug=False)
self.controlArea.layout().addWidget(self.webview)
QTimer.singleShot(
0, lambda: self.webview.evalJS('REGIONS = {};'.format({Map.WORLD: CC_WORLD,
Map.EUROPE: CC_EUROPE,
Map.USA: CC_USA})))
def setData(self, data):
self.closeContext()
self.clear()
self.data = data
if data is not None:
domain = data.domain
self.allAttrs = (domain.class_vars + domain.metas +
domain.attributes)
self.stringAttrs = [a for a in domain.metas if a.is_string]
self.stringAttrs = sorted(self.stringAttrs,
key=lambda attr: 0
if "type" in attr.attributes else 1)
indices = [
i for i, var in enumerate(self.stringAttrs)
if var.attributes.get("type") == "image"
]
if indices:
self.imageAttr = indices[0]
self.imageAttrCB.setModel(VariableListModel(self.stringAttrs))
self.titleAttrCB.setModel(VariableListModel(self.allAttrs))
self.openContext(data)
self.imageAttr = max(
min(self.imageAttr,
len(self.stringAttrs) - 1), 0)
self.titleAttr = max(min(self.titleAttr,
len(self.allAttrs) - 1), 0)
if self.stringAttrs:
self.setupScene()
else:
self.info.setText("Waiting for input.\n")
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2_model = VariableListModel(parent=self)
self.combo_ax1_model = VariableListModel(parent=self)
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [_enum_str(i) for i in Spiralogram.AxesCategories]
self.combo_ax2 = gui.comboBox(
box, self, 'ax2', label='Y axis:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax2_model)
self.combo_ax1 = gui.comboBox(
box, self, 'ax1', label='Radial:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax1_model)
gui.checkBox(box, self, 'invert_date_order', 'Invert Y axis order',
callback=self.replot)
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(
box, self, 'agg_func', label='Function:', orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.SingleSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def __init__(self):
super().__init__()
self.distances = None
self.items = None
self.tablemodel = DistanceMatrixModel()
view = self.tableview = QTableView()
view.setEditTriggers(QTableView.NoEditTriggers)
view.setItemDelegate(TableBorderItem())
view.setModel(self.tablemodel)
view.setShowGrid(False)
for header in (view.horizontalHeader(), view.verticalHeader()):
header.setResizeMode(QHeaderView.ResizeToContents)
header.setHighlightSections(True)
header.setClickable(False)
view.verticalHeader().setDefaultAlignment(Qt.AlignRight
| Qt.AlignVCenter)
selmodel = SymmetricSelectionModel(view.model(), view)
view.setSelectionModel(selmodel)
view.setSelectionBehavior(QTableView.SelectItems)
self.mainArea.layout().addWidget(view)
settings_box = gui.widgetBox(self.mainArea, orientation="horizontal")
self.annot_combo = gui.comboBox(settings_box,
self,
"annotation_idx",
label="Labels: ",
orientation="horizontal",
callback=self._invalidate_annotations,
contentsLength=12)
self.annot_combo.setModel(VariableListModel())
self.annot_combo.model()[:] = ["None", "Enumeration"]
gui.rubber(settings_box)
self.report_button = gui.button(settings_box,
None,
"&Report",
callback=self.show_report)
self.report_button.setAutoDefault(0)
gui.separator(settings_box, 40)
gui.auto_commit(settings_box,
self,
"auto_commit",
"Send Selected Data",
"Auto send is on",
box=None)
# Signal must be connected after self.commit is redirected
selmodel.selectionChanged.connect(self.commit)
def __init__(self):
super().__init__()
self.distances = None
self.items = None
self.tablemodel = DistanceMatrixModel()
view = self.tableview = QTableView()
view.setEditTriggers(QTableView.NoEditTriggers)
view.setItemDelegate(TableBorderItem())
view.setModel(self.tablemodel)
view.setShowGrid(False)
for header in (view.horizontalHeader(), view.verticalHeader()):
header.setSectionResizeMode(QHeaderView.ResizeToContents)
header.setHighlightSections(True)
header.setSectionsClickable(False)
view.verticalHeader().setDefaultAlignment(Qt.AlignRight
| Qt.AlignVCenter)
selmodel = SymmetricSelectionModel(view.model(), view)
view.setSelectionModel(selmodel)
view.setSelectionBehavior(QTableView.SelectItems)
self.mainArea.layout().addWidget(view)
settings_box = gui.hBox(self.mainArea)
self.annot_combo = gui.comboBox(
settings_box,
self,
"annotation_idx",
label="Labels: ",
orientation=Qt.Horizontal,
callback=self._invalidate_annotations,
contentsLength=12,
)
self.annot_combo.setModel(VariableListModel())
self.annot_combo.model()[:] = ["None", "Enumeration"]
gui.rubber(settings_box)
acb = gui.auto_commit(
settings_box,
self,
"auto_commit",
"Send Selected",
"Send Automatically",
box=None,
)
acb.setFixedWidth(200)
# Signal must be connected after self.commit is redirected
selmodel.selectionChanged.connect(self.commit)
def _create_layout(self):
box = gui.widgetBox(self.controlArea,
orientation='horizontal')
self.varmodel = VariableListModel(parent=self)
self.attr_combo = gui.comboBox(box, self, 'selected_attr',
orientation=Qt.Horizontal,
label='Region attribute:',
callback=self.on_attr_change,
sendSelectedValue=True)
self.attr_combo.setModel(self.varmodel)
self.map_combo = gui.comboBox(box, self, 'selected_map',
orientation=Qt.Horizontal,
label='Map type:',
callback=self.on_map_change,
items=Map.all)
hexpand = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding,
QtGui.QSizePolicy.Fixed)
self.attr_combo.setSizePolicy(hexpand)
self.map_combo.setSizePolicy(hexpand)
html = '''
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<base href="{}/"/>
<style>
html, body, #map {{margin:0px;padding:0px;width:100%;height:100%;}}
</style>
<link href="resources/jquery-jvectormap-2.0.2.css" rel="stylesheet">
<script src="resources/jquery-2.1.4.min.js"></script>
<script src="resources/jquery-jvectormap-2.0.2.min.js"></script>
<script src="resources/jquery-jvectormap-world-mill-en.js"></script>
<script src="resources/jquery-jvectormap-europe-mill-en.js"></script>
<script src="resources/jquery-jvectormap-us-aea-en.js"></script>
<script src="resources/geomap-script.js"></script>
</head>
<body>
<div id="map"></div>
</body>
</html>'''.format(urljoin('file:', pathname2url(path.abspath(path.dirname(__file__)))))
self.webview = gui.WebviewWidget(self.controlArea, self, debug=False)
self.controlArea.layout().addWidget(self.webview)
self.webview.setHtml(html)
QTimer.singleShot(
0, lambda: self.webview.evalJS('REGIONS = {};'.format({Map.WORLD: CC_WORLD,
Map.EUROPE: CC_EUROPE,
Map.USA: CC_USA})))
def __init__(self):
self.data = None
self.plots = []
self.configs = []
self.forecasts = OrderedDict()
self.varmodel = VariableListModel(parent=self)
icon = QIcon(join(dirname(__file__), 'icons', 'LineChart-plus.png'))
self.add_button = button = QPushButton(icon, ' &Add plot', self)
button.clicked.connect(self.add_plot)
self.controlArea.layout().addWidget(button)
self.configsArea = gui.vBox(self.controlArea)
self.controlArea.layout().addStretch(1)
# TODO: allow selecting ranges that are sent to output as subset table
self.chart = highstock = Highstock(self, highchart='StockChart')
self.mainArea.layout().addWidget(highstock)
highstock.chart()
QTimer.singleShot(0, self.add_plot)
def set_corpus(self, corpus):
self.corpus = corpus
if corpus is not None:
self.strings_attrs = [a for a in self.corpus.domain.metas
if isinstance(a, StringVariable)]
self.tweet_attr_combo.setModel(VariableListModel(self.strings_attrs))
self.tweet_attr_combo.currentIndexChanged.emit(self.tweet_attr)
# select the first feature from 'text_features' if present
ind = [self.strings_attrs.index(tf)
for tf in corpus.text_features
if tf in self.strings_attrs]
if ind:
self.tweet_attr = ind[0]
self.commit()
def test_delegate(self):
cases = (
(DState(Default(Leave()), None, None), ""),
(DState(Leave(), None, None), "(leave)"),
(DState(MDL(), [1], None), "(entropy)"),
(DState(MDL(), [], None), "<removed>"),
(DState(EqualFreq(2), [1], None), "(equal frequency k=2)"),
(DState(EqualWidth(2), [1], None), "(equal width k=2)"),
(DState(Remove(), None, None), "(removed)"),
(DState(Custom([1]), None, None), "(custom)"),
)
delegate = DiscDelegate()
var = DiscreteVariable("C", ("a", "b"))
model = VariableListModel()
model.append(var)
for state, text in cases:
model.setData(model.index(0), state, Qt.UserRole)
option = QStyleOptionViewItem()
delegate.initStyleOption(option, model.index(0))
self.assertIn(text, option.text)
def __init__(self):
super().__init__()
self.network = None
self.auto_data = None
self.original_nodes = None
self.data = None
self.net_index = 0
hb = gui.widgetBox(self.controlArea, orientation=Qt.Horizontal)
self.filecombo = gui.comboBox(hb,
self,
"net_index",
callback=self.select_net_file,
minimumWidth=250)
gui.button(hb,
self,
'...',
callback=self.browse_net_file,
disabled=0,
icon=self.style().standardIcon(QStyle.SP_DirOpenIcon),
sizePolicy=(QSizePolicy.Maximum, QSizePolicy.Fixed))
gui.button(hb,
self,
'Reload',
callback=self.reload,
icon=self.style().standardIcon(QStyle.SP_BrowserReload),
sizePolicy=(QSizePolicy.Maximum, QSizePolicy.Fixed))
self.label_model = VariableListModel(placeholder="(Match by rows)")
self.label_model[:] = [None]
gui.comboBox(self.controlArea,
self,
"label_variable",
box=True,
label="Match node labels to data column: ",
orientation=Qt.Horizontal,
model=self.label_model,
callback=self.label_changed)
self.populate_comboboxes()
self.setFixedHeight(self.sizeHint().height())
self.reload()
def __init__(self):
self.data = None
box = gui.vBox(self.controlArea, 'Seasonal Adjustment')
gui.spin(box, self, 'n_periods', 2, 1000,
label='Season period:',
callback=self.on_changed,
tooltip='The expected length of full cycle. E.g., if you have '
'monthly data and the apparent season repeats every '
'year, you put in 12.')
gui.radioButtons(box, self, 'decomposition', self.DECOMPOSITION_MODELS,
label='Decomposition model:',
orientation=Qt.Horizontal,
callback=self.on_changed)
self.view = view = QListView(self,
selectionMode=QListView.ExtendedSelection)
self.model = model = VariableListModel(parent=self)
view.setModel(model)
view.selectionModel().selectionChanged.connect(self.on_changed)
box.layout().addWidget(view)
gui.auto_commit(box, self, 'autocommit', '&Apply')
def __init__(self):
super().__init__()
self.distances = None
self.items = None
self.tablemodel = DistanceMatrixModel()
view = self.tableview = TableView()
view.setWordWrap(False)
view.setTextElideMode(Qt.ElideNone)
view.setEditTriggers(QTableView.NoEditTriggers)
view.setItemDelegate(
TableBorderItem(roles=(Qt.DisplayRole, Qt.BackgroundRole,
Qt.ForegroundRole)))
view.setModel(self.tablemodel)
view.setShowGrid(False)
for header in (view.horizontalHeader(), view.verticalHeader()):
header.setResizeContentsPrecision(1)
header.setSectionResizeMode(QHeaderView.ResizeToContents)
header.setHighlightSections(True)
header.setSectionsClickable(False)
view.verticalHeader().setDefaultAlignment(Qt.AlignRight
| Qt.AlignVCenter)
selmodel = SymmetricSelectionModel(view.model(), view)
selmodel.selectionChanged.connect(self.commit.deferred)
view.setSelectionModel(selmodel)
view.setSelectionBehavior(QTableView.SelectItems)
self.controlArea.layout().addWidget(view)
self.annot_combo = gui.comboBox(self.buttonsArea,
self,
"annotation_idx",
label="标签: ",
orientation=Qt.Horizontal,
callback=self._invalidate_annotations,
contentsLength=12)
self.annot_combo.setModel(VariableListModel())
self.annot_combo.model()[:] = ["无", "枚举"]
gui.rubber(self.buttonsArea)
acb = gui.auto_send(self.buttonsArea, self, "auto_commit", box=False)
acb.setFixedWidth(200)
def set_data(self, data):
self.closeContext()
self.clear()
self.Warning.no_valid_data.clear()
self.data = data
if data is not None:
domain = data.domain
self.allAttrs = (domain.class_vars + domain.metas +
domain.attributes)
self.stringAttrs = [a for a in domain.metas if a.is_string]
self.domainAttrs = len(domain.attributes)
self.stringAttrs = sorted(self.stringAttrs,
key=lambda attr: 0
if "type" in attr.attributes else 1)
indices = [
i for i, var in enumerate(self.stringAttrs)
if var.attributes.get("type") == "image"
]
if indices:
self.imageAttr = indices[0]
self.imageAttrCB.setModel(VariableListModel(self.stringAttrs))
# set label combo labels
self.label_model.set_domain(domain)
self.openContext(data)
self.label_attr = self.label_model[0]
self.imageAttr = max(
min(self.imageAttr,
len(self.stringAttrs) - 1), 0)
if self.is_valid_data():
self.image_grid = ImageGrid(data)
self.setup_scene()
else:
self.Warning.no_valid_data()
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2_model = VariableListModel(parent=self)
self.combo_ax1_model = VariableListModel(parent=self)
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [_enum_str(i) for i in Spiralogram.AxesCategories]
self.combo_ax2 = gui.comboBox(
box, self, 'ax2', label='Y axis:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax2_model)
self.combo_ax1 = gui.comboBox(
box, self, 'ax1', label='Radial:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax1_model)
gui.checkBox(box, self, 'invert_date_order', 'Invert Y axis order',
callback=self.replot)
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(
box, self, 'agg_func', label='Function:', orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.SingleSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def __init__(self):
self.data = None
box = gui.vBox(self.controlArea, 'Sequence')
group = gui.radioButtons(box,
self,
'radio_sequential',
callback=self.on_changed)
hbox = gui.hBox(box)
gui.appendRadioButton(group, 'Sequential attribute:', insertInto=hbox)
attrs_model = self.attrs_model = VariableListModel()
combo_attrs = self.combo_attrs = gui.comboBox(hbox,
self,
'selected_attr',
callback=self.on_changed,
sendSelectedValue=True)
combo_attrs.setModel(attrs_model)
gui.appendRadioButton(group,
'Sequence is implied by instance order',
insertInto=box)
gui.auto_commit(self.controlArea, self, 'autocommit', '&Apply')
def dataset(self, data):
self.clear()
self.data = data
if self.data:
# error check
if len(self.data) == 0:
self.Error.no_instances()
return
self._smiles_attrs = moleculeembedder.filter_string_attributes(data)
if not self._smiles_attrs:
self.Error.no_string_att()
return
# update selection
self.controls._smiles_attr.setModel(VariableListModel(self._smiles_attrs))
if self._smiles_attr == '' or self._smiles_attr is None:
self._smiles_attr = self._smiles_attrs[0]
if self._embedder == '' or self._embedder is None:
self._embedder = self._embedders[0]
self.commit()
def __init__(self):
super().__init__()
self.network = None
form = QFormLayout()
form.setFieldGrowthPolicy(form.AllNonFixedFieldsGrow)
gui.widgetBox(self.controlArea, box="Mode indicator", orientation=form)
form.addRow(
"Feature:",
gui.comboBox(None,
self,
"variable",
model=VariableListModel(),
callback=self.indicator_changed))
form.addRow(
"Connect:",
gui.comboBox(None,
self,
"connect_value",
callback=self.connect_combo_changed))
form.addRow(
"by:",
gui.comboBox(None,
self,
"connector_value",
callback=self.connector_combo_changed))
gui.comboBox(self.controlArea,
self,
"weighting",
box="Edge weights",
items=[x.name for x in twomode.Weighting],
callback=self.update_output)
self.lbout = gui.widgetLabel(gui.hBox(self.controlArea, "Output"), "")
self._update_combos()
self._set_output_msg()
def set_data(self, data):
self.Warning.clear()
self.set_input_data_summary(data)
if not data:
self._input_data = None
self.clear_outputs()
return
self._image_attributes = ImageEmbedder.filter_image_attributes(data)
if not self.cb_image_attr_current_id < len(self._image_attributes):
self.cb_image_attr_current_id = 0
self.cb_image_attr.setModel(VariableListModel(self._image_attributes))
self.cb_image_attr.setCurrentIndex(self.cb_image_attr_current_id)
if not self._image_attributes:
self._input_data = None
self.Warning.no_image_attribute()
self.clear_outputs()
return
self._input_data = data
self.commit()
def __init__(self):
self.data = None
self.plots = []
self.configs = []
self.forecasts = OrderedDict()
self.varmodel = VariableListModel(parent=self)
icon = QIcon(join(dirname(__file__), 'icons', 'LineChart-plus.png'))
self.add_button = button = QPushButton(icon, ' &Add plot', self)
button.clicked.connect(self.add_plot)
self.controlArea.layout().addWidget(button)
self.configsArea = gui.vBox(self.controlArea)
self.controlArea.layout().addStretch(1)
# TODO: allow selecting ranges that are sent to output as subset table
self.chart = highstock = Highstock(self, highchart='StockChart')
self.mainArea.layout().addWidget(highstock)
# highstock.evalJS('Highcharts.setOptions({navigator: {enabled:false}});')
highstock.chart(
# For some reason, these options don't work as global opts applied at Highstock init time
# Disable top range selector
rangeSelector_enabled=False,
rangeSelector_inputEnabled=False,
# Disable bottom miniview navigator (it doesn't update)
navigator_enabled=False, )
QTimer.singleShot(0, self.add_plot)
def __init__(self):
super().__init__()
self.data = None
self.projection = None
self.subset_data = None
self._subset_mask = None
self._selection = None
self.__replot_requested = False
self.n_cont_var = 0
#: Remember the saved state to restore
self.__pending_selection_restore = self.selection_indices
self.selection_indices = None
self.variable_x = None
self.variable_y = None
box = gui.vBox(self.mainArea, True, margin=0)
self.graph = OWLinProjGraph(self, box, "Plot", view_box=LinProjInteractiveViewBox)
box.layout().addWidget(self.graph.plot_widget)
plot = self.graph.plot_widget
SIZE_POLICY = (QSizePolicy.Minimum, QSizePolicy.Maximum)
self.variables_selection = VariablesSelection()
self.model_selected = VariableListModel(enable_dnd=True)
self.model_other = VariableListModel(enable_dnd=True)
self.variables_selection(self, self.model_selected, self.model_other)
self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
self.controlArea, self, "Suggest Features", self._vizrank)
self.variables_selection.add_remove.layout().addWidget(self.btn_vizrank)
box = gui.widgetBox(
self.controlArea, "Placement", sizePolicy=SIZE_POLICY)
self.radio_placement = gui.radioButtonsInBox(
box, self, "placement",
btnLabels=["Circular Placement",
"Linear Discriminant Analysis",
"Principal Component Analysis",
"Use input projection"],
callback=self._change_placement
)
self.viewbox = plot.getViewBox()
self.replot = None
g = self.graph.gui
box = g.point_properties_box(self.controlArea)
self.models = g.points_models
g.add_widget(g.JitterSizeSlider, box)
box.setSizePolicy(*SIZE_POLICY)
box = gui.widgetBox(self.controlArea, "Hide axes", sizePolicy=SIZE_POLICY)
self.rslider = gui.hSlider(
box, self, "radius", minValue=0, maxValue=100,
step=5, label="Radius", createLabel=False, ticks=True,
callback=self.update_radius)
self.rslider.setTickInterval(0)
self.rslider.setPageStep(10)
box = gui.vBox(self.controlArea, "Plot Properties")
box.setSizePolicy(*SIZE_POLICY)
g.add_widgets([g.ShowLegend,
g.ToolTipShowsAll,
g.ClassDensity,
g.LabelOnlySelected], box)
box = self.graph.box_zoom_select(self.controlArea)
box.setSizePolicy(*SIZE_POLICY)
self.icons = gui.attributeIconDict
p = self.graph.plot_widget.palette()
self.graph.set_palette(p)
gui.auto_commit(self.controlArea, self, "auto_commit", "Send Selection",
auto_label="Send Automatically")
self.graph.zoom_actions(self)
self._new_plotdata()
self._change_placement()
self.graph.jitter_continuous = True
class OWMovingTransform(widget.OWWidget):
name = 'Moving Transform'
description = 'Apply rolling window functions to the time series.'
icon = 'icons/MovingTransform.svg'
priority = 20
inputs = [("Time series", Table, 'set_data')]
outputs = [("Time series", Timeseries)]
want_main_area = False
non_overlapping = settings.Setting(False)
fixed_wlen = settings.Setting(5)
transformations = settings.Setting([])
autocommit = settings.Setting(False)
last_win_width = settings.Setting(5)
_NON_OVERLAPPING_WINDOWS = 'Non-overlapping windows'
UserAdviceMessages = [
widget.Message('Get the simple moving average (SMA) of a series '
'by setting the aggregation function to "{}".'.format(Mean),
'sma-is-mean'),
widget.Message('If "{}" is checked, the rolling windows don\t '
'overlap. Instead, they run through the series '
'side-to-side, so the resulting transformed series is '
'fixed-window-length-times shorter.'.format(_NON_OVERLAPPING_WINDOWS),
'non-overlapping')
]
def __init__(self):
self.data = None
box = gui.vBox(self.controlArea, 'Moving Transform')
def _disable_fixed_wlen():
fixed_wlen.setDisabled(not self.non_overlapping)
self.view.repaint()
self.on_changed()
gui.checkBox(box, self, 'non_overlapping',
label=self._NON_OVERLAPPING_WINDOWS,
callback=_disable_fixed_wlen,
tooltip='If this is checked, instead of rolling windows '
'through the series, they are applied side-to-side, '
'so the resulting output series will be some '
'length-of-fixed-window-times shorter.')
fixed_wlen = gui.spin(box, self, 'fixed_wlen', 2, 1000,
label='Fixed window width:',
callback=self.on_changed)
fixed_wlen.setDisabled(not self.non_overlapping)
# TODO: allow the user to choose left-aligned, right-aligned, or center-aligned window
class TableView(gui.TableView):
def __init__(self, parent):
super().__init__(parent,
editTriggers=(self.SelectedClicked |
self.CurrentChanged |
self.DoubleClicked |
self.EditKeyPressed),
)
self.horizontalHeader().setStretchLastSection(False)
agg_functions = ListModel(AGG_FUNCTIONS +
[Cumulative_sum, Cumulative_product],
parent=self)
self.setItemDelegateForColumn(0, self.VariableDelegate(parent))
self.setItemDelegateForColumn(1, self.SpinDelegate(parent))
self.setItemDelegateForColumn(2, self.ComboDelegate(self, agg_functions))
class _ItemDelegate(QStyledItemDelegate):
def updateEditorGeometry(self, widget, option, _index):
widget.setGeometry(option.rect)
class ComboDelegate(_ItemDelegate):
def __init__(self, parent=None, combo_model=None):
super().__init__(parent)
self._parent = parent
if combo_model is not None:
self._combo_model = combo_model
def createEditor(self, parent, _QStyleOptionViewItem, index):
combo = QComboBox(parent)
combo.setModel(self._combo_model)
return combo
def setEditorData(self, combo, index):
var = index.model().data(index, Qt.EditRole)
combo.setCurrentIndex(self._combo_model.indexOf(var))
def setModelData(self, combo, model, index):
var = self._combo_model[combo.currentIndex()]
model.setData(index, var, Qt.EditRole)
class VariableDelegate(ComboDelegate):
@property
def _combo_model(self):
return self._parent.var_model
class SpinDelegate(_ItemDelegate):
def paint(self, painter, option, index):
# Don't paint window length if non-overlapping windows set
if not self.parent().non_overlapping:
super().paint(painter, option, index)
def createEditor(self, parent, _QStyleOptionViewItem, _index):
# Don't edit window length if non-overlapping windows set
if self.parent().non_overlapping:
return None
spin = QSpinBox(parent, minimum=1, maximum=1000)
return spin
def setEditorData(self, spin, index):
spin.setValue(index.model().data(index, Qt.EditRole))
def setModelData(self, spin, model, index):
spin.interpretText()
model.setData(index, spin.value(), Qt.EditRole)
self.var_model = VariableListModel(parent=self)
self.table_model = model = PyTableModel(self.transformations,
parent=self, editable=True)
model.setHorizontalHeaderLabels(['Series', 'Window width', 'Aggregation function'])
model.dataChanged.connect(self.on_changed)
self.view = view = TableView(self)
view.setModel(model)
box.layout().addWidget(view)
hbox = gui.hBox(box)
from os.path import dirname, join
self.add_button = button = gui.button(
hbox, self, 'Add &Transform',
callback=self.on_add_transform)
button.setIcon(QIcon(join(dirname(__file__), 'icons', 'LineChart-plus.png')))
self.del_button = button = gui.button(
hbox, self, '&Delete Selected',
callback=self.on_del_transform)
QIcon.setThemeName('gnome') # Works for me
button.setIcon(QIcon.fromTheme('edit-delete'))
gui.auto_commit(box, self, 'autocommit', '&Apply')
def sizeHint(self):
return QSize(450, 600)
def on_add_transform(self):
if self.data is not None:
self.table_model.append([self.var_model[0], self.last_win_width, AGG_FUNCTIONS[0]])
self.commit()
def on_del_transform(self):
for row in sorted([mi.row() for mi in self.view.selectionModel().selectedRows(0)],
reverse=True):
del self.table_model[row]
if len(self.table_model):
selection_model = self.view.selectionModel()
selection_model.select(self.table_model.index(len(self.table_model) - 1, 0),
selection_model.Select | selection_model.Rows)
self.commit()
def set_data(self, data):
self.data = data = None if data is None else Timeseries.from_data_table(data)
self.add_button.setDisabled(not len(getattr(data, 'domain', ())))
self.table_model.clear()
if data is not None:
self.var_model.wrap([var for var in data.domain
if var.is_continuous and var is not data.time_variable])
self.on_changed()
def on_changed(self):
self.commit()
def commit(self):
data = self.data
if not data:
self.send(Output.TIMESERIES, None)
return
ts = moving_transform(data, self.table_model, self.non_overlapping and self.fixed_wlen)
self.send(Output.TIMESERIES, ts)
def __init__(self):
self.data = None
box = gui.vBox(self.controlArea, 'Moving Transform')
def _disable_fixed_wlen():
fixed_wlen.setDisabled(not self.non_overlapping)
self.view.repaint()
self.on_changed()
gui.checkBox(box, self, 'non_overlapping',
label=self._NON_OVERLAPPING_WINDOWS,
callback=_disable_fixed_wlen,
tooltip='If this is checked, instead of rolling windows '
'through the series, they are applied side-to-side, '
'so the resulting output series will be some '
'length-of-fixed-window-times shorter.')
fixed_wlen = gui.spin(box, self, 'fixed_wlen', 2, 1000,
label='Fixed window width:',
callback=self.on_changed)
fixed_wlen.setDisabled(not self.non_overlapping)
# TODO: allow the user to choose left-aligned, right-aligned, or center-aligned window
class TableView(gui.TableView):
def __init__(self, parent):
super().__init__(parent,
editTriggers=(self.SelectedClicked |
self.CurrentChanged |
self.DoubleClicked |
self.EditKeyPressed),
)
self.horizontalHeader().setStretchLastSection(False)
agg_functions = ListModel(AGG_FUNCTIONS +
[Cumulative_sum, Cumulative_product],
parent=self)
self.setItemDelegateForColumn(0, self.VariableDelegate(parent))
self.setItemDelegateForColumn(1, self.SpinDelegate(parent))
self.setItemDelegateForColumn(2, self.ComboDelegate(self, agg_functions))
class _ItemDelegate(QStyledItemDelegate):
def updateEditorGeometry(self, widget, option, _index):
widget.setGeometry(option.rect)
class ComboDelegate(_ItemDelegate):
def __init__(self, parent=None, combo_model=None):
super().__init__(parent)
self._parent = parent
if combo_model is not None:
self._combo_model = combo_model
def createEditor(self, parent, _QStyleOptionViewItem, index):
combo = QComboBox(parent)
combo.setModel(self._combo_model)
return combo
def setEditorData(self, combo, index):
var = index.model().data(index, Qt.EditRole)
combo.setCurrentIndex(self._combo_model.indexOf(var))
def setModelData(self, combo, model, index):
var = self._combo_model[combo.currentIndex()]
model.setData(index, var, Qt.EditRole)
class VariableDelegate(ComboDelegate):
@property
def _combo_model(self):
return self._parent.var_model
class SpinDelegate(_ItemDelegate):
def paint(self, painter, option, index):
# Don't paint window length if non-overlapping windows set
if not self.parent().non_overlapping:
super().paint(painter, option, index)
def createEditor(self, parent, _QStyleOptionViewItem, _index):
# Don't edit window length if non-overlapping windows set
if self.parent().non_overlapping:
return None
spin = QSpinBox(parent, minimum=1, maximum=1000)
return spin
def setEditorData(self, spin, index):
spin.setValue(index.model().data(index, Qt.EditRole))
def setModelData(self, spin, model, index):
spin.interpretText()
model.setData(index, spin.value(), Qt.EditRole)
self.var_model = VariableListModel(parent=self)
self.table_model = model = PyTableModel(self.transformations,
parent=self, editable=True)
model.setHorizontalHeaderLabels(['Series', 'Window width', 'Aggregation function'])
model.dataChanged.connect(self.on_changed)
self.view = view = TableView(self)
view.setModel(model)
box.layout().addWidget(view)
hbox = gui.hBox(box)
from os.path import dirname, join
self.add_button = button = gui.button(
hbox, self, 'Add &Transform',
callback=self.on_add_transform)
button.setIcon(QIcon(join(dirname(__file__), 'icons', 'LineChart-plus.png')))
self.del_button = button = gui.button(
hbox, self, '&Delete Selected',
callback=self.on_del_transform)
QIcon.setThemeName('gnome') # Works for me
button.setIcon(QIcon.fromTheme('edit-delete'))
gui.auto_commit(box, self, 'autocommit', '&Apply')
class OWGeoMap(widget.OWWidget):
name = "GeoMap"
priority = 20000
icon = "icons/GeoMap.svg"
inputs = [("Data", Table, "on_data")]
outputs = [('Corpus', Corpus)]
want_main_area = False
selected_attr = settings.Setting('')
selected_map = settings.Setting(0)
regions = settings.Setting([])
def __init__(self):
super().__init__()
self.data = None
self._create_layout()
@QtCore.pyqtSlot(str, result=str)
def region_selected(self, regions):
"""Called from JavaScript"""
if not regions:
self.regions = []
if not regions or self.data is None:
return self.send('Corpus', None)
self.regions = regions.split(',')
attr = self.data.domain[self.selected_attr]
if attr.is_discrete: return # TODO, FIXME: make this work for discrete attrs also
from Orange.data.filter import FilterRegex
filter = FilterRegex(attr, r'\b{}\b'.format(r'\b|\b'.join(self.regions)), re.IGNORECASE)
self.send('Corpus', self.data._filter_values(filter))
def _create_layout(self):
box = gui.widgetBox(self.controlArea,
orientation='horizontal')
self.varmodel = VariableListModel(parent=self)
self.attr_combo = gui.comboBox(box, self, 'selected_attr',
orientation=Qt.Horizontal,
label='Region attribute:',
callback=self.on_attr_change,
sendSelectedValue=True)
self.attr_combo.setModel(self.varmodel)
self.map_combo = gui.comboBox(box, self, 'selected_map',
orientation=Qt.Horizontal,
label='Map type:',
callback=self.on_map_change,
items=Map.all)
hexpand = QtGui.QSizePolicy(QtGui.QSizePolicy.Expanding,
QtGui.QSizePolicy.Fixed)
self.attr_combo.setSizePolicy(hexpand)
self.map_combo.setSizePolicy(hexpand)
html = '''
<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8">
<base href="{}/"/>
<style>
html, body, #map {{margin:0px;padding:0px;width:100%;height:100%;}}
</style>
<link href="resources/jquery-jvectormap-2.0.2.css" rel="stylesheet">
<script src="resources/jquery-2.1.4.min.js"></script>
<script src="resources/jquery-jvectormap-2.0.2.min.js"></script>
<script src="resources/jquery-jvectormap-world-mill-en.js"></script>
<script src="resources/jquery-jvectormap-europe-mill-en.js"></script>
<script src="resources/jquery-jvectormap-us-aea-en.js"></script>
<script src="resources/geomap-script.js"></script>
</head>
<body>
<div id="map"></div>
</body>
</html>'''.format(urljoin('file:', pathname2url(path.abspath(path.dirname(__file__)))))
self.webview = gui.WebviewWidget(self.controlArea, self, debug=False)
self.controlArea.layout().addWidget(self.webview)
self.webview.setHtml(html)
QTimer.singleShot(
0, lambda: self.webview.evalJS('REGIONS = {};'.format({Map.WORLD: CC_WORLD,
Map.EUROPE: CC_EUROPE,
Map.USA: CC_USA})))
def _repopulate_attr_combo(self, data):
vars = [a for a in chain(data.domain.metas,
data.domain.attributes,
data.domain.class_vars)
if a.is_string] if data else []
self.varmodel.wrap(vars)
# Select default attribute
self.selected_attr = next((var.name
for var in vars
if var.name.lower().startswith(('country', 'location', 'region'))),
vars[0].name if vars else '')
def on_data(self, data):
if data and not isinstance(data, Corpus):
data = Corpus.from_table(data.domain, data)
self.data = data
self._repopulate_attr_combo(data)
if not data:
self.region_selected('')
QTimer.singleShot(0, lambda: self.webview.evalJS('DATA = {}; renderMap();'))
else:
QTimer.singleShot(0, self.on_attr_change)
def on_map_change(self, map_code=''):
if map_code:
self.map_combo.setCurrentIndex(self.map_combo.findData(map_code))
else:
map_code = self.map_combo.itemData(self.selected_map)
inv_cc_map, cc_map = {Map.USA: (INV_CC_USA, CC_USA),
Map.WORLD: (INV_CC_WORLD, CC_WORLD),
Map.EUROPE: (INV_CC_EUROPE, CC_EUROPE)} [map_code]
# Set country counts in JS
data = defaultdict(int)
for cc in getattr(self, 'cc_counts', ()):
key = inv_cc_map.get(cc, cc)
if key in cc_map:
data[key] += self.cc_counts[cc]
# Draw the new map
self.webview.evalJS('DATA = {};'
'MAP_CODE = "{}";'
'SELECTED_REGIONS = {};'
'renderMap();'.format(dict(data),
map_code,
self.regions))
def on_attr_change(self):
if not self.selected_attr:
return
attr = self.data.domain[self.selected_attr]
self.cc_counts = Counter(chain.from_iterable(
set(name.strip() for name in CC_NAMES.findall(i.lower())) if len(i) > 3 else (i,)
for i in self.data.get_column_view(self.data.domain.index(attr))[0]))
# Auto-select region map
values = set(self.cc_counts)
if 0 == len(values - SET_CC_USA):
map_code = Map.USA
elif 0 == len(values - SET_CC_EUROPE):
map_code = Map.EUROPE
else:
map_code = Map.WORLD
self.on_map_change(map_code)
class OWLineChart(widget.OWWidget):
name = 'Line Chart'
description = "Visualize time series' sequence and progression."
icon = 'icons/LineChart.svg'
priority = 90
class Inputs:
time_series = Input("Time series", Table)
forecast = Input("Forecast", Timeseries, multiple=True)
attrs = settings.Setting({}) # Maps data.name -> [attrs]
graph_name = 'chart'
def __init__(self):
self.data = None
self.plots = []
self.configs = []
self.forecasts = OrderedDict()
self.varmodel = VariableListModel(parent=self)
icon = QIcon(join(dirname(__file__), 'icons', 'LineChart-plus.png'))
self.add_button = button = QPushButton(icon, ' &Add plot', self)
button.clicked.connect(self.add_plot)
self.controlArea.layout().addWidget(button)
self.configsArea = gui.vBox(self.controlArea)
self.controlArea.layout().addStretch(1)
# TODO: allow selecting ranges that are sent to output as subset table
self.chart = highstock = Highstock(self, highchart='StockChart')
self.mainArea.layout().addWidget(highstock)
# highstock.evalJS('Highcharts.setOptions({navigator: {enabled:false}});')
highstock.chart(
# For some reason, these options don't work as global opts applied at Highstock init time
# Disable top range selector
rangeSelector_enabled=False,
rangeSelector_inputEnabled=False,
# Disable bottom miniview navigator (it doesn't update)
navigator_enabled=False, )
QTimer.singleShot(0, self.add_plot)
def add_plot(self):
ax = self.chart.addAxis()
config = PlotConfigWidget(self, ax, self.varmodel)
# Connect the signals
config.sigSelection.connect(self.chart.setSeries)
config.sigLogarithmic.connect(self.chart.setLogarithmic)
config.sigType.connect(self.chart.setType)
config.sigClosed.connect(self.chart.removeAxis)
config.sigClosed.connect(lambda ax, widget: widget.setParent(None))
config.sigClosed.connect(lambda ax, widget:
self.add_button.setDisabled(False))
self.configs.append(config)
self.add_button.setDisabled(len(self.configs) >= 5)
self.configsArea.layout().addWidget(config)
@Inputs.time_series
def set_data(self, data):
# TODO: set xAxis resolution and tooltip time contents depending on
# data.time_delta. See: http://imgur.com/yrnlgQz
# If the same data is updated, short circuit to just updating the chart,
# retaining all panels and list view selections ...
if data is not None and self.data is not None and data.domain == self.data.domain:
self.data = Timeseries.from_data_table(data)
for config in self.configs:
config.selection_changed()
return
self.data = data = None if data is None else Timeseries.from_data_table(data)
if data is None:
self.varmodel.clear()
self.chart.clear()
return
if getattr(data.time_variable, 'utc_offset', False):
offset_minutes = data.time_variable.utc_offset.total_seconds() / 60
self.chart.evalJS('Highcharts.setOptions({global: {timezoneOffset: %d}});' % -offset_minutes) # Why is this negative? It works.
self.chart.chart()
self.chart.setXAxisType(
'datetime'
if (data.time_variable and
(getattr(data.time_variable, 'have_date', False) or
getattr(data.time_variable, 'have_time', False))) else
'linear')
self.varmodel.wrap([var for var in data.domain.variables
if var.is_continuous and var != data.time_variable])
@Inputs.forecast
def set_forecast(self, forecast, id):
if forecast is not None:
self.forecasts[id] = forecast
else:
self.forecasts.pop(id, None)
class OWSpiralogram(widget.OWWidget):
name = 'Spiralogram'
description = "Visualize time series' periodicity in a spiral heatmap."
icon = 'icons/Spiralogram.svg'
priority = 120
class Inputs:
time_series = Input("Time series", Table)
class Outputs:
time_series = Output("Time series", Timeseries)
settingsHandler = settings.DomainContextHandler()
ax1 = settings.ContextSetting('months of year')
ax2 = settings.ContextSetting('years')
agg_attr = settings.ContextSetting([])
agg_func = settings.ContextSetting(0)
invert_date_order = settings.Setting(False)
graph_name = 'chart'
class Error(widget.OWWidget.Error):
no_time_variable = widget.Msg(
'Spiralogram requires time series with a time variable.')
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2_model = VariableListModel(parent=self)
self.combo_ax1_model = VariableListModel(parent=self)
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [_enum_str(i) for i in Spiralogram.AxesCategories]
self.combo_ax2 = gui.comboBox(box,
self,
'ax2',
label='Y axis:',
callback=self.replot,
sendSelectedValue=True,
orientation='horizontal',
model=self.combo_ax2_model)
self.combo_ax1 = gui.comboBox(box,
self,
'ax1',
label='Radial:',
callback=self.replot,
sendSelectedValue=True,
orientation='horizontal',
model=self.combo_ax1_model)
gui.checkBox(box,
self,
'invert_date_order',
'Invert Y axis order',
callback=self.replot)
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(box,
self,
'agg_func',
label='Function:',
orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.SingleSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def attrlist_selectionChanged(self):
self.agg_attr = [
self.attrlist_model[i.row()]
for i in self.attrlist.selectionModel().selectedIndexes()
]
self.replot()
@Inputs.time_series
def set_data(self, data):
self.Error.clear()
self.data = data = None if data is None else Timeseries.from_data_table(
data)
if data is None:
self.commit()
return
if self.data.time_variable is None or not isinstance(
self.data.time_variable, TimeVariable):
self.Error.no_time_variable()
self.commit()
return
def init_combos():
for model in (self.combo_ax1_model, self.combo_ax2_model):
model.clear()
newmodel = []
if data is not None and data.time_variable is not None:
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [
_enum_str(i) for i in Spiralogram.AxesCategories
]
for var in data.domain.variables if data is not None else []:
if (var.is_primitive()
and (var is not data.time_variable or isinstance(
var, TimeVariable) and data.time_delta is None)):
newmodel.append(var)
if var.is_discrete:
for model in (self.combo_ax1_model, self.combo_ax2_model):
model.append(var)
self.attrlist_model.wrap(newmodel)
init_combos()
self.chart.clear()
self.closeContext()
self.ax2 = next((self.combo_ax2.itemText(i)
for i in range(self.combo_ax2.count())), '')
self.ax1 = next((self.combo_ax1.itemText(i)
for i in range(1, self.combo_ax1.count())), self.ax2)
self.agg_attr = [data.domain.variables[0]] if len(
data.domain.variables) else []
self.agg_func = 0
if getattr(data, 'time_variable', None) is not None:
self.openContext(data.domain)
if self.agg_attr:
self.attrlist.blockSignals(True)
self.attrlist.selectionModel().clear()
for attr in self.agg_attr:
try:
row = self.attrlist_model.indexOf(attr)
except ValueError:
continue
self.attrlist.selectionModel().select(
self.attrlist_model.index(row),
QItemSelectionModel.SelectCurrent)
self.attrlist.blockSignals(False)
self.replot()
def replot(self):
if not self.combo_ax1.count() or not self.agg_attr:
return self.chart.clear()
vars = self.agg_attr
func = AGG_FUNCTIONS[self.agg_func]
if any(var.is_discrete for var in vars) and func != Mode:
self.combo_func.setCurrentIndex(AGG_FUNCTIONS.index(Mode))
func = Mode
try:
ax1 = Spiralogram.AxesCategories[_enum_str(self.ax1, True)]
except KeyError:
ax1 = self.data.domain[self.ax1]
# TODO: Allow having only a single (i.e. radial) axis
try:
ax2 = Spiralogram.AxesCategories[_enum_str(self.ax2, True)]
except KeyError:
ax2 = self.data.domain[self.ax2]
self.chart.setSeries(self.data, vars, ax1, ax2, func)
def on_selection(self, indices):
self.indices = self.chart.selection_indices(indices)
self.commit()
def commit(self):
self.Outputs.time_series.send(
self.data[self.indices] if self.data else None)
class OWCorpus(OWWidget):
name = "语料库"
description = "加载文档语料库."
icon = "icons/TextFile.svg"
priority = 100
replaces = ["orangecontrib.text.widgets.owloadcorpus.OWLoadCorpus"]
class Inputs:
data = Input('Data', Table)
class Outputs:
corpus = Output('Corpus', Corpus)
want_main_area = False
resizing_enabled = True
dlgFormats = (
"所有可读文档 ({});;".format('*' + ' *'.join(FileFormat.readers.keys())) +
";;".join(
"{} (*{})".format(f.DESCRIPTION, ' *'.join(f.EXTENSIONS))
for f in sorted(set(FileFormat.readers.values()),
key=list(FileFormat.readers.values()).index)))
settingsHandler = PerfectDomainContextHandler(
match_values=PerfectDomainContextHandler.MATCH_VALUES_ALL)
recent_files = Setting([
"book-excerpts.tab",
"grimm-tales-selected.tab",
"election-tweets-2016.tab",
"friends-transcripts.tab",
"andersen.tab",
"chinese-example.tab",
])
used_attrs = ContextSetting([])
class Error(OWWidget.Error):
read_file = Msg("无法读取文件 {} ({})")
no_text_features_used = Msg("至少使用一个文本特征")
corpus_without_text_features = Msg("语料库没有文本特征")
def __init__(self):
super().__init__()
self.corpus = None
# Browse file box
fbox = gui.widgetBox(self.controlArea, "语料库文件", orientation=0)
self.file_widget = widgets.FileWidget(
recent_files=self.recent_files,
icon_size=(16, 16),
on_open=self.open_file,
dialog_format=self.dlgFormats,
dialog_title='打开语料库文档',
reload_label='重新加载',
browse_label='浏览',
allow_empty=False,
minimal_width=250,
)
fbox.layout().addWidget(self.file_widget)
# Corpus info
ibox = gui.widgetBox(self.controlArea, "语料库信息", addSpace=True)
self.info_label = gui.label(ibox, self, "")
self.update_info()
# Used Text Features
fbox = gui.widgetBox(self.controlArea, orientation=0)
ubox = gui.widgetBox(fbox, "已使用的文本特征", addSpace=False)
self.used_attrs_model = VariableListModel(enable_dnd=True)
self.used_attrs_view = VariablesListItemView()
self.used_attrs_view.setModel(self.used_attrs_model)
ubox.layout().addWidget(self.used_attrs_view)
aa = self.used_attrs_model
aa.dataChanged.connect(self.update_feature_selection)
aa.rowsInserted.connect(self.update_feature_selection)
aa.rowsRemoved.connect(self.update_feature_selection)
# Ignored Text Features
ibox = gui.widgetBox(fbox, "未使用的文本特征", addSpace=False)
self.unused_attrs_model = VariableListModel(enable_dnd=True)
self.unused_attrs_view = VariablesListItemView()
self.unused_attrs_view.setModel(self.unused_attrs_model)
ibox.layout().addWidget(self.unused_attrs_view)
# Documentation Data Sets & Report
box = gui.hBox(self.controlArea)
self.browse_documentation = gui.button(
box,
self,
"浏览语料库文档",
callback=lambda: self.file_widget.browse(get_sample_corpora_dir()),
autoDefault=False,
)
# load first file
self.file_widget.select(0)
def sizeHint(self):
return QSize(400, 300)
@Inputs.data
def set_data(self, data):
have_data = data is not None
# Enable/Disable command when data from input
self.file_widget.setEnabled(not have_data)
self.browse_documentation.setEnabled(not have_data)
if have_data:
self.open_file(data=data)
else:
self.file_widget.reload()
def open_file(self, path=None, data=None):
self.closeContext()
self.Error.clear()
self.unused_attrs_model[:] = []
self.used_attrs_model[:] = []
if data:
self.corpus = Corpus.from_table(data.domain, data)
elif path:
try:
self.corpus = Corpus.from_file(path)
self.corpus.name = os.path.splitext(os.path.basename(path))[0]
except BaseException as err:
self.Error.read_file(path, str(err))
else:
return
self.update_info()
self.used_attrs = list(self.corpus.text_features)
if not self.corpus.text_features:
self.Error.corpus_without_text_features()
self.Outputs.corpus.send(None)
return
self.openContext(self.corpus)
self.used_attrs_model.extend(self.used_attrs)
self.unused_attrs_model.extend([
f for f in self.corpus.domain.metas
if f.is_string and f not in self.used_attrs_model
])
def update_info(self):
def describe(corpus):
dom = corpus.domain
text_feats = sum(m.is_string for m in dom.metas)
other_feats = len(dom.attributes) + len(dom.metas) - text_feats
text = \
"{} 个文档, {} 个文本特征, {} 个其他特征.". \
format(len(corpus), text_feats, other_feats)
if dom.has_continuous_class:
text += "<br/>回归; 数值类."
elif dom.has_discrete_class:
text += "<br/>分类; 离散值含有 {} 种值.". \
format(len(dom.class_var.values))
elif corpus.domain.class_vars:
text += "<br/>多目标; {} 个目标变量.".format(
len(corpus.domain.class_vars))
else:
text += "<br/>数据没有目标变量"
text += "</p>"
return text
if self.corpus is None:
self.info_label.setText("没有加载语料库")
else:
self.info_label.setText(describe(self.corpus))
def update_feature_selection(self):
self.Error.no_text_features_used.clear()
# TODO fix VariablesListItemView so it does not emit
# duplicated data when reordering inside a single window
def remove_duplicates(l):
unique = []
for i in l:
if i not in unique:
unique.append(i)
return unique
if self.corpus is not None:
self.corpus.set_text_features(
remove_duplicates(self.used_attrs_model))
self.used_attrs = list(self.used_attrs_model)
if len(self.unused_attrs_model
) > 0 and not self.corpus.text_features:
self.Error.no_text_features_used()
# prevent sending "empty" corpora
dom = self.corpus.domain
empty = not (dom.variables or dom.metas) \
or len(self.corpus) == 0 \
or not self.corpus.text_features
self.Outputs.corpus.send(self.corpus if not empty else None)
def send_report(self):
def describe(features):
if len(features):
return ', '.join([f.name for f in features])
else:
return '(无)'
if self.corpus is not None:
domain = self.corpus.domain
self.report_items('Corpus', (
("File", self.file_widget.get_selected_filename()),
("Documents", len(self.corpus)),
("Used text features", describe(self.used_attrs_model)),
("Ignored text features", describe(self.unused_attrs_model)),
('Other features', describe(domain.attributes)),
('Target', describe(domain.class_vars)),
))
def __init__(self):
super().__init__()
self._axis_font = QFont()
self._axis_font.setPixelSize(12)
self._label_font = QFont()
self._label_font.setPixelSize(11)
self.dataset = None
self.stats = []
self.dist = self.conts = None
self.posthoc_lines = []
self.label_txts = self.mean_labels = self.boxes = self.labels = \
self.label_txts_all = self.attr_labels = self.order = []
self.scale_x = 1
self.scene_min_x = self.scene_max_x = self.scene_width = 0
self.label_width = 0
self.attrs = VariableListModel()
sorted_model = SortProxyModel(sortRole=Qt.UserRole)
sorted_model.setSourceModel(self.attrs)
sorted_model.sort(0)
box = gui.vBox(self.controlArea, "Variable")
view = self.attr_list = ListViewSearch()
view.setModel(sorted_model)
view.setSelectionMode(view.SingleSelection)
view.selectionModel().selectionChanged.connect(self.attr_changed)
view.setMinimumSize(QSize(30, 30))
# Any other policy than Ignored will let the QListBox's scrollbar
# set the minimal height (see the penultimate paragraph of
# http://doc.qt.io/qt-4.8/qabstractscrollarea.html#addScrollBarWidget)
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
box.layout().addWidget(view)
gui.checkBox(box,
self,
"order_by_importance",
"Order by relevance to subgroups",
tooltip="Order by 𝜒² or ANOVA over the subgroups",
callback=self.apply_attr_sorting)
self.group_vars = VariableListModel(placeholder="None")
sorted_model = SortProxyModel(sortRole=Qt.UserRole)
sorted_model.setSourceModel(self.group_vars)
sorted_model.sort(0)
box = gui.vBox(self.controlArea, "Subgroups")
view = self.group_list = ListViewSearch()
view.setModel(sorted_model)
view.selectionModel().selectionChanged.connect(self.grouping_changed)
view.setMinimumSize(QSize(30, 30))
# See the comment above
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
box.layout().addWidget(view)
gui.checkBox(box,
self,
"order_grouping_by_importance",
"Order by relevance to variable",
tooltip="Order by 𝜒² or ANOVA over the variable values",
callback=self.apply_group_sorting)
# TODO: move Compare median/mean to grouping box
# The vertical size policy is needed to let only the list views expand
self.display_box = gui.vBox(self.controlArea,
"Display",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Maximum))
gui.checkBox(self.display_box,
self,
"show_annotations",
"Annotate",
callback=self.update_graph)
self.compare_rb = gui.radioButtonsInBox(
self.display_box,
self,
'compare',
btnLabels=["No comparison", "Compare medians", "Compare means"],
callback=self.update_graph)
# The vertical size policy is needed to let only the list views expand
self.stretching_box = box = gui.vBox(self.controlArea,
box="Display",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Fixed))
self.stretching_box.sizeHint = self.display_box.sizeHint
gui.checkBox(box,
self,
'stretched',
"Stretch bars",
callback=self.update_graph,
stateWhenDisabled=False)
gui.checkBox(box,
self,
'show_labels',
"Show box labels",
callback=self.update_graph)
self.sort_cb = gui.checkBox(box,
self,
'sort_freqs',
"Sort by subgroup frequencies",
callback=self.update_graph,
stateWhenDisabled=False)
gui.vBox(self.mainArea)
self.box_scene = QGraphicsScene(self)
self.box_scene.selectionChanged.connect(self.on_selection_changed)
self.box_view = QGraphicsView(self.box_scene)
self.box_view.setRenderHints(QPainter.Antialiasing
| QPainter.TextAntialiasing
| QPainter.SmoothPixmapTransform)
self.box_view.viewport().installEventFilter(self)
self.mainArea.layout().addWidget(self.box_view)
self.stat_test = ""
self.mainArea.setMinimumWidth(300)
self.update_box_visibilities()
class OWCorpus(OWWidget):
name = "Corpus"
description = "Load a corpus of text documents."
icon = "icons/TextFile.svg"
priority = 100
replaces = ["orangecontrib.text.widgets.owloadcorpus.OWLoadCorpus"]
class Inputs:
data = Input('Data', Table)
class Outputs:
corpus = Output('Corpus', Corpus)
want_main_area = False
resizing_enabled = True
dlgFormats = (
"All readable files ({});;".format(
'*' + ' *'.join(FileFormat.readers.keys())) +
";;".join("{} (*{})".format(f.DESCRIPTION, ' *'.join(f.EXTENSIONS))
for f in sorted(set(FileFormat.readers.values()),
key=list(FileFormat.readers.values()).index)))
settingsHandler = PerfectDomainContextHandler(
match_values=PerfectDomainContextHandler.MATCH_VALUES_ALL
)
recent_files = Setting([
"book-excerpts.tab",
"grimm-tales-selected.tab",
"election-tweets-2016.tab",
"friends-transcripts.tab",
"andersen.tab",
])
used_attrs = ContextSetting([])
class Error(OWWidget.Error):
read_file = Msg("Can't read file {} ({})")
no_text_features_used = Msg("At least one text feature must be used.")
corpus_without_text_features = Msg("Corpus doesn't have any textual features.")
def __init__(self):
super().__init__()
self.corpus = None
# Browse file box
fbox = gui.widgetBox(self.controlArea, "Corpus file", orientation=0)
self.file_widget = widgets.FileWidget(
recent_files=self.recent_files, icon_size=(16, 16),
on_open=self.open_file, dialog_format=self.dlgFormats,
dialog_title='Open Orange Document Corpus',
reload_label='Reload', browse_label='Browse',
allow_empty=False, minimal_width=250,
)
fbox.layout().addWidget(self.file_widget)
# Corpus info
ibox = gui.widgetBox(self.controlArea, "Corpus info", addSpace=True)
self.info_label = gui.label(ibox, self, "")
self.update_info()
# Used Text Features
fbox = gui.widgetBox(self.controlArea, orientation=0)
ubox = gui.widgetBox(fbox, "Used text features", addSpace=False)
self.used_attrs_model = VariableListModel(enable_dnd=True)
self.used_attrs_view = VariablesListItemView()
self.used_attrs_view.setModel(self.used_attrs_model)
ubox.layout().addWidget(self.used_attrs_view)
aa = self.used_attrs_model
aa.dataChanged.connect(self.update_feature_selection)
aa.rowsInserted.connect(self.update_feature_selection)
aa.rowsRemoved.connect(self.update_feature_selection)
# Ignored Text Features
ibox = gui.widgetBox(fbox, "Ignored text features", addSpace=False)
self.unused_attrs_model = VariableListModel(enable_dnd=True)
self.unused_attrs_view = VariablesListItemView()
self.unused_attrs_view.setModel(self.unused_attrs_model)
ibox.layout().addWidget(self.unused_attrs_view)
# Documentation Data Sets & Report
box = gui.hBox(self.controlArea)
self.browse_documentation = gui.button(
box, self, "Browse documentation corpora",
callback=lambda: self.file_widget.browse(
get_sample_corpora_dir()),
autoDefault=False,
)
# load first file
self.file_widget.select(0)
def sizeHint(self):
return QSize(400, 300)
@Inputs.data
def set_data(self, data):
have_data = data is not None
# Enable/Disable command when data from input
self.file_widget.setEnabled(not have_data)
self.browse_documentation.setEnabled(not have_data)
if have_data:
self.open_file(data=data)
else:
self.file_widget.reload()
def open_file(self, path=None, data=None):
self.closeContext()
self.Error.clear()
self.unused_attrs_model[:] = []
self.used_attrs_model[:] = []
if data:
self.corpus = Corpus.from_table(data.domain, data)
elif path:
try:
self.corpus = Corpus.from_file(path)
self.corpus.name = os.path.splitext(os.path.basename(path))[0]
except BaseException as err:
self.Error.read_file(path, str(err))
else:
return
self.update_info()
self.used_attrs = list(self.corpus.text_features)
if not self.corpus.text_features:
self.Error.corpus_without_text_features()
self.Outputs.corpus.send(None)
return
self.openContext(self.corpus)
self.used_attrs_model.extend(self.used_attrs)
self.unused_attrs_model.extend(
[f for f in self.corpus.domain.metas
if f.is_string and f not in self.used_attrs_model])
def update_info(self):
def describe(corpus):
dom = corpus.domain
text_feats = sum(m.is_string for m in dom.metas)
other_feats = len(dom.attributes) + len(dom.metas) - text_feats
text = \
"{} document(s), {} text features(s), {} other feature(s).". \
format(len(corpus), text_feats, other_feats)
if dom.has_continuous_class:
text += "<br/>Regression; numerical class."
elif dom.has_discrete_class:
text += "<br/>Classification; discrete class with {} values.". \
format(len(dom.class_var.values))
elif corpus.domain.class_vars:
text += "<br/>Multi-target; {} target variables.".format(
len(corpus.domain.class_vars))
else:
text += "<br/>Data has no target variable."
text += "</p>"
return text
if self.corpus is None:
self.info_label.setText("No corpus loaded.")
else:
self.info_label.setText(describe(self.corpus))
def update_feature_selection(self):
self.Error.no_text_features_used.clear()
# TODO fix VariablesListItemView so it does not emit
# duplicated data when reordering inside a single window
def remove_duplicates(l):
unique = []
for i in l:
if i not in unique:
unique.append(i)
return unique
if self.corpus is not None:
self.corpus.set_text_features(
remove_duplicates(self.used_attrs_model))
self.used_attrs = list(self.used_attrs_model)
if len(self.unused_attrs_model) > 0 and not self.corpus.text_features:
self.Error.no_text_features_used()
# prevent sending "empty" corpora
dom = self.corpus.domain
empty = not (dom.variables or dom.metas) \
or len(self.corpus) == 0 \
or not self.corpus.text_features
self.Outputs.corpus.send(self.corpus if not empty else None)
def send_report(self):
def describe(features):
if len(features):
return ', '.join([f.name for f in features])
else:
return '(none)'
if self.corpus is not None:
domain = self.corpus.domain
self.report_items('Corpus', (
("File", self.file_widget.get_selected_filename()),
("Documents", len(self.corpus)),
("Used text features", describe(self.used_attrs_model)),
("Ignored text features", describe(self.unused_attrs_model)),
('Other features', describe(domain.attributes)),
('Target', describe(domain.class_vars)),
))
class OWBoxPlot(widget.OWWidget):
"""
Here's how the widget's functions call each other:
- `set_data` is a signal handler fills the list boxes and calls
`grouping_changed`.
- `grouping_changed` handles changes of grouping attribute: it enables or
disables the box for ordering, orders attributes and calls `attr_changed`.
- `attr_changed` handles changes of attribute. It recomputes box data by
calling `compute_box_data`, shows the appropriate display box
(discrete/continuous) and then calls`layout_changed`
- `layout_changed` constructs all the elements for the scene (as lists of
QGraphicsItemGroup) and calls `display_changed`. It is called when the
attribute or grouping is changed (by attr_changed) and on resize event.
- `display_changed` puts the elements corresponding to the current display
settings on the scene. It is called when the elements are reconstructed
(layout is changed due to selection of attributes or resize event), or
when the user changes display settings or colors.
For discrete attributes, the flow is a bit simpler: the elements are not
constructed in advance (by layout_changed). Instead, layout_changed and
display_changed call display_changed_disc that draws everything.
"""
name = "Box Plot"
description = "Visualize the distribution of feature values in a box plot."
icon = "icons/BoxPlot.svg"
priority = 100
keywords = ["whisker"]
class Inputs:
data = Input("Data", Orange.data.Table)
class Outputs:
selected_data = Output("Selected Data", Orange.data.Table, default=True)
annotated_data = Output(ANNOTATED_DATA_SIGNAL_NAME, Orange.data.Table)
#: Comparison types for continuous variables
CompareNone, CompareMedians, CompareMeans = 0, 1, 2
settingsHandler = DomainContextHandler()
conditions = ContextSetting([])
attribute = ContextSetting(None)
order_by_importance = Setting(False)
group_var = ContextSetting(None)
show_annotations = Setting(True)
compare = Setting(CompareMeans)
stattest = Setting(0)
sig_threshold = Setting(0.05)
stretched = Setting(True)
show_labels = Setting(True)
sort_freqs = Setting(False)
auto_commit = Setting(True)
_sorting_criteria_attrs = {
CompareNone: "", CompareMedians: "median", CompareMeans: "mean"
}
_pen_axis_tick = QPen(Qt.white, 5)
_pen_axis = QPen(Qt.darkGray, 3)
_pen_median = QPen(QBrush(QColor(0xff, 0xff, 0x00)), 2)
_pen_paramet = QPen(QBrush(QColor(0x33, 0x00, 0xff)), 2)
_pen_dotted = QPen(QBrush(QColor(0x33, 0x00, 0xff)), 1)
_pen_dotted.setStyle(Qt.DotLine)
_post_line_pen = QPen(Qt.lightGray, 2)
_post_grp_pen = QPen(Qt.lightGray, 4)
for pen in (_pen_paramet, _pen_median, _pen_dotted,
_pen_axis, _pen_axis_tick, _post_line_pen, _post_grp_pen):
pen.setCosmetic(True)
pen.setCapStyle(Qt.RoundCap)
pen.setJoinStyle(Qt.RoundJoin)
_pen_axis_tick.setCapStyle(Qt.FlatCap)
_box_brush = QBrush(QColor(0x33, 0x88, 0xff, 0xc0))
_axis_font = QFont()
_axis_font.setPixelSize(12)
_label_font = QFont()
_label_font.setPixelSize(11)
_attr_brush = QBrush(QColor(0x33, 0x00, 0xff))
graph_name = "box_scene"
def __init__(self):
super().__init__()
self.stats = []
self.dataset = None
self.posthoc_lines = []
self.label_txts = self.mean_labels = self.boxes = self.labels = \
self.label_txts_all = self.attr_labels = self.order = []
self.scale_x = self.scene_min_x = self.scene_width = 0
self.label_width = 0
self.attrs = VariableListModel()
view = gui.listView(
self.controlArea, self, "attribute", box="Variable",
model=self.attrs, callback=self.attr_changed)
view.setMinimumSize(QSize(30, 30))
# Any other policy than Ignored will let the QListBox's scrollbar
# set the minimal height (see the penultimate paragraph of
# http://doc.qt.io/qt-4.8/qabstractscrollarea.html#addScrollBarWidget)
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
gui.separator(view.box, 6, 6)
self.cb_order = gui.checkBox(
view.box, self, "order_by_importance",
"Order by relevance",
tooltip="Order by 𝜒² or ANOVA over the subgroups",
callback=self.apply_sorting)
self.group_vars = DomainModel(
placeholder="None", separators=False,
valid_types=Orange.data.DiscreteVariable)
self.group_view = view = gui.listView(
self.controlArea, self, "group_var", box="Subgroups",
model=self.group_vars, callback=self.grouping_changed)
view.setEnabled(False)
view.setMinimumSize(QSize(30, 30))
# See the comment above
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
# TODO: move Compare median/mean to grouping box
# The vertical size policy is needed to let only the list views expand
self.display_box = gui.vBox(
self.controlArea, "Display",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Maximum),
addSpace=False)
gui.checkBox(self.display_box, self, "show_annotations", "Annotate",
callback=self.display_changed)
self.compare_rb = gui.radioButtonsInBox(
self.display_box, self, 'compare',
btnLabels=["No comparison", "Compare medians", "Compare means"],
callback=self.layout_changed)
# The vertical size policy is needed to let only the list views expand
self.stretching_box = box = gui.vBox(
self.controlArea, box="Display",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed))
self.stretching_box.sizeHint = self.display_box.sizeHint
gui.checkBox(
box, self, 'stretched', "Stretch bars",
callback=self.display_changed)
gui.checkBox(
box, self, 'show_labels', "Show box labels",
callback=self.display_changed)
self.sort_cb = gui.checkBox(
box, self, 'sort_freqs', "Sort by subgroup frequencies",
callback=self.display_changed)
gui.rubber(box)
gui.auto_commit(self.controlArea, self, "auto_commit",
"Send Selection", "Send Automatically")
gui.vBox(self.mainArea, addSpace=True)
self.box_scene = QGraphicsScene()
self.box_scene.selectionChanged.connect(self.commit)
self.box_view = QGraphicsView(self.box_scene)
self.box_view.setRenderHints(QPainter.Antialiasing |
QPainter.TextAntialiasing |
QPainter.SmoothPixmapTransform)
self.box_view.viewport().installEventFilter(self)
self.mainArea.layout().addWidget(self.box_view)
e = gui.hBox(self.mainArea, addSpace=False)
self.infot1 = gui.widgetLabel(e, "<center>No test results.</center>")
self.mainArea.setMinimumWidth(300)
self.stats = self.dist = self.conts = []
self.is_continuous = False
self.update_display_box()
def sizeHint(self):
return QSize(900, 500)
def eventFilter(self, obj, event):
if obj is self.box_view.viewport() and \
event.type() == QEvent.Resize:
self.layout_changed()
return super().eventFilter(obj, event)
def reset_attrs(self, domain):
self.attrs[:] = [
var for var in chain(
domain.class_vars, domain.metas, domain.attributes)
if var.is_primitive()]
# noinspection PyTypeChecker
@Inputs.data
def set_data(self, dataset):
if dataset is not None and (
not bool(dataset) or not len(dataset.domain) and not
any(var.is_primitive() for var in dataset.domain.metas)):
dataset = None
self.closeContext()
self.dataset = dataset
self.dist = self.stats = self.conts = []
self.group_var = None
self.attribute = None
if dataset:
domain = dataset.domain
self.group_vars.set_domain(domain)
self.group_view.setEnabled(len(self.group_vars) > 1)
self.reset_attrs(domain)
self.select_default_variables(domain)
self.openContext(self.dataset)
self.grouping_changed()
else:
self.reset_all_data()
self.commit()
def select_default_variables(self, domain):
# visualize first non-class variable, group by class (if present)
if len(self.attrs) > len(domain.class_vars):
self.attribute = self.attrs[len(domain.class_vars)]
elif self.attrs:
self.attribute = self.attrs[0]
if domain.class_var and domain.class_var.is_discrete:
self.group_var = domain.class_var
else:
self.group_var = None # Reset to trigger selection via callback
def apply_sorting(self):
def compute_score(attr):
if attr is group_var:
return 3
if attr.is_continuous:
# One-way ANOVA
col = data.get_column_view(attr)[0].astype(float)
groups = (col[group_col == i] for i in range(n_groups))
groups = (col[~np.isnan(col)] for col in groups)
groups = [group for group in groups if len(group)]
p = f_oneway(*groups)[1] if len(groups) > 1 else 2
else:
# Chi-square with the given distribution into groups
# (see degrees of freedom in computation of the p-value)
if not attr.values or not group_var.values:
return 2
observed = np.array(
contingency.get_contingency(data, group_var, attr))
observed = observed[observed.sum(axis=1) != 0, :]
observed = observed[:, observed.sum(axis=0) != 0]
if min(observed.shape) < 2:
return 2
expected = \
np.outer(observed.sum(axis=1), observed.sum(axis=0)) / \
np.sum(observed)
p = chisquare(observed.ravel(), f_exp=expected.ravel(),
ddof=n_groups - 1)[1]
if math.isnan(p):
return 2
return p
data = self.dataset
if data is None:
return
domain = data.domain
attribute = self.attribute
group_var = self.group_var
if self.order_by_importance and group_var is not None:
n_groups = len(group_var.values)
group_col = data.get_column_view(group_var)[0] if \
domain.has_continuous_attributes(
include_class=True, include_metas=True) else None
self.attrs.sort(key=compute_score)
else:
self.reset_attrs(domain)
self.attribute = attribute
def reset_all_data(self):
self.clear_scene()
self.infot1.setText("")
self.attrs.clear()
self.group_vars.set_domain(None)
self.group_view.setEnabled(False)
self.is_continuous = False
self.update_display_box()
def grouping_changed(self):
self.cb_order.setEnabled(self.group_var is not None)
self.apply_sorting()
self.attr_changed()
def select_box_items(self):
temp_cond = self.conditions.copy()
for box in self.box_scene.items():
if isinstance(box, FilterGraphicsRectItem):
box.setSelected(box.filter.conditions in
[c.conditions for c in temp_cond])
def attr_changed(self):
self.compute_box_data()
self.update_display_box()
self.layout_changed()
if self.is_continuous:
heights = 90 if self.show_annotations else 60
self.box_view.centerOn(self.scene_min_x + self.scene_width / 2,
-30 - len(self.stats) * heights / 2 + 45)
else:
self.box_view.centerOn(self.scene_width / 2,
-30 - len(self.boxes) * 40 / 2 + 45)
def compute_box_data(self):
attr = self.attribute
if not attr:
return
dataset = self.dataset
self.is_continuous = attr.is_continuous
if dataset is None or not self.is_continuous and not attr.values or \
self.group_var and not self.group_var.values:
self.stats = self.dist = self.conts = []
return
if self.group_var:
self.dist = []
self.conts = contingency.get_contingency(
dataset, attr, self.group_var)
if self.is_continuous:
stats, label_texts = [], []
for i, cont in enumerate(self.conts):
if np.sum(cont[1]):
stats.append(BoxData(cont, attr, i, self.group_var))
label_texts.append(self.group_var.values[i])
self.stats = stats
self.label_txts_all = label_texts
else:
self.label_txts_all = \
[v for v, c in zip(self.group_var.values, self.conts)
if np.sum(c) > 0]
else:
self.dist = distribution.get_distribution(dataset, attr)
self.conts = []
if self.is_continuous:
self.stats = [BoxData(self.dist, attr, None)]
self.label_txts_all = [""]
self.label_txts = [txts for stat, txts in zip(self.stats,
self.label_txts_all)
if stat.n > 0]
self.stats = [stat for stat in self.stats if stat.n > 0]
def update_display_box(self):
if self.is_continuous:
self.stretching_box.hide()
self.display_box.show()
self.compare_rb.setEnabled(self.group_var is not None)
else:
self.stretching_box.show()
self.display_box.hide()
self.sort_cb.setEnabled(self.group_var is not None)
def clear_scene(self):
self.closeContext()
self.box_scene.clearSelection()
self.box_scene.clear()
self.box_view.viewport().update()
self.attr_labels = []
self.labels = []
self.boxes = []
self.mean_labels = []
self.posthoc_lines = []
self.openContext(self.dataset)
def layout_changed(self):
attr = self.attribute
if not attr:
return
self.clear_scene()
if self.dataset is None or len(self.conts) == len(self.dist) == 0:
return
if not self.is_continuous:
self.display_changed_disc()
return
self.mean_labels = [self.mean_label(stat, attr, lab)
for stat, lab in zip(self.stats, self.label_txts)]
self.draw_axis()
self.boxes = [self.box_group(stat) for stat in self.stats]
self.labels = [self.label_group(stat, attr, mean_lab)
for stat, mean_lab in zip(self.stats, self.mean_labels)]
self.attr_labels = [QGraphicsSimpleTextItem(lab)
for lab in self.label_txts]
for it in chain(self.labels, self.attr_labels):
self.box_scene.addItem(it)
self.display_changed()
def display_changed(self):
if self.dataset is None:
return
if not self.is_continuous:
self.display_changed_disc()
return
self.order = list(range(len(self.stats)))
criterion = self._sorting_criteria_attrs[self.compare]
if criterion:
vals = [getattr(stat, criterion) for stat in self.stats]
overmax = max((val for val in vals if val is not None), default=0) \
+ 1
vals = [val if val is not None else overmax for val in vals]
self.order = sorted(self.order, key=vals.__getitem__)
heights = 90 if self.show_annotations else 60
for row, box_index in enumerate(self.order):
y = (-len(self.stats) + row) * heights + 10
for item in self.boxes[box_index]:
self.box_scene.addItem(item)
item.setY(y)
labels = self.labels[box_index]
if self.show_annotations:
labels.show()
labels.setY(y)
else:
labels.hide()
label = self.attr_labels[box_index]
label.setY(y - 15 - label.boundingRect().height())
if self.show_annotations:
label.hide()
else:
stat = self.stats[box_index]
if self.compare == OWBoxPlot.CompareMedians and \
stat.median is not None:
pos = stat.median + 5 / self.scale_x
elif self.compare == OWBoxPlot.CompareMeans or stat.q25 is None:
pos = stat.mean + 5 / self.scale_x
else:
pos = stat.q25
label.setX(pos * self.scale_x)
label.show()
r = QRectF(self.scene_min_x, -30 - len(self.stats) * heights,
self.scene_width, len(self.stats) * heights + 90)
self.box_scene.setSceneRect(r)
self.compute_tests()
self.show_posthoc()
self.select_box_items()
def display_changed_disc(self):
assert not self.is_continuous
self.clear_scene()
self.attr_labels = [QGraphicsSimpleTextItem(lab)
for lab in self.label_txts_all]
if not self.stretched:
if self.group_var:
self.labels = [
QGraphicsTextItem("{}".format(int(sum(cont))))
for cont in self.conts if np.sum(cont) > 0]
else:
self.labels = [
QGraphicsTextItem(str(int(sum(self.dist))))]
self.order = list(range(len(self.attr_labels)))
self.draw_axis_disc()
if self.group_var:
self.boxes = \
[self.strudel(cont, i) for i, cont in enumerate(self.conts)
if np.sum(cont) > 0]
self.conts = self.conts[np.sum(np.array(self.conts), axis=1) > 0]
if self.sort_freqs:
# pylint: disable=invalid-unary-operand-type
self.order = sorted(self.order, key=(-np.sum(self.conts, axis=1)).__getitem__)
else:
self.boxes = [self.strudel(self.dist)]
for row, box_index in enumerate(self.order):
y = (-len(self.boxes) + row) * 40 + 10
box = self.boxes[box_index]
bars, labels = box[::2], box[1::2]
self.__draw_group_labels(y, box_index)
if not self.stretched:
self.__draw_row_counts(y, box_index)
if self.show_labels and self.attribute is not self.group_var:
self.__draw_bar_labels(y, bars, labels)
self.__draw_bars(y, bars)
self.box_scene.setSceneRect(-self.label_width - 5,
-30 - len(self.boxes) * 40,
self.scene_width, len(self.boxes * 40) + 90)
self.infot1.setText("")
self.select_box_items()
def __draw_group_labels(self, y, row):
"""Draw group labels
Parameters
----------
y: int
vertical offset of bars
row: int
row index
"""
label = self.attr_labels[row]
b = label.boundingRect()
label.setPos(-b.width() - 10, y - b.height() / 2)
self.box_scene.addItem(label)
def __draw_row_counts(self, y, row):
"""Draw row counts
Parameters
----------
y: int
vertical offset of bars
row: int
row index
"""
assert not self.is_continuous
label = self.labels[row]
b = label.boundingRect()
if self.group_var:
right = self.scale_x * sum(self.conts[row])
else:
right = self.scale_x * sum(self.dist)
label.setPos(right + 10, y - b.height() / 2)
self.box_scene.addItem(label)
def __draw_bar_labels(self, y, bars, labels):
"""Draw bar labels
Parameters
----------
y: int
vertical offset of bars
bars: List[FilterGraphicsRectItem]
list of bars being drawn
labels: List[QGraphicsTextItem]
list of labels for corresponding bars
"""
label = bar_part = None
for text_item, bar_part in zip(labels, bars):
label = self.Label(
text_item.toPlainText())
label.setPos(bar_part.boundingRect().x(),
y - label.boundingRect().height() - 8)
label.setMaxWidth(bar_part.boundingRect().width())
self.box_scene.addItem(label)
def __draw_bars(self, y, bars):
"""Draw bars
Parameters
----------
y: int
vertical offset of bars
bars: List[FilterGraphicsRectItem]
list of bars to draw
"""
for item in bars:
item.setPos(0, y)
self.box_scene.addItem(item)
# noinspection PyPep8Naming
def compute_tests(self):
# The t-test and ANOVA are implemented here since they efficiently use
# the widget-specific data in self.stats.
# The non-parametric tests can't do this, so we use statistics.tests
# pylint: disable=comparison-with-itself
def stat_ttest():
d1, d2 = self.stats
if d1.n < 2 or d2.n < 2:
return np.nan, np.nan
pooled_var = d1.var / d1.n + d2.var / d2.n
# pylint: disable=comparison-with-itself
if pooled_var == 0 or np.isnan(pooled_var):
return np.nan, np.nan
df = pooled_var ** 2 / \
((d1.var / d1.n) ** 2 / (d1.n - 1) +
(d2.var / d2.n) ** 2 / (d2.n - 1))
t = abs(d1.mean - d2.mean) / math.sqrt(pooled_var)
p = 2 * (1 - scipy.special.stdtr(df, t))
return t, p
# TODO: Check this function
# noinspection PyPep8Naming
def stat_ANOVA():
if any(stat.n == 0 for stat in self.stats):
return np.nan, np.nan
n = sum(stat.n for stat in self.stats)
grand_avg = sum(stat.n * stat.mean for stat in self.stats) / n
var_between = sum(stat.n * (stat.mean - grand_avg) ** 2
for stat in self.stats)
df_between = len(self.stats) - 1
var_within = sum(stat.n * stat.var for stat in self.stats)
df_within = n - len(self.stats)
if var_within == 0 or df_within == 0 or df_between == 0:
return np.nan, np.nan
F = (var_between / df_between) / (var_within / df_within)
p = 1 - scipy.special.fdtr(df_between, df_within, F)
return F, p
if self.compare == OWBoxPlot.CompareNone or len(self.stats) < 2:
t = ""
elif any(s.n <= 1 for s in self.stats):
t = "At least one group has just one instance, " \
"cannot compute significance"
elif len(self.stats) == 2:
if self.compare == OWBoxPlot.CompareMedians:
t = ""
# z, p = tests.wilcoxon_rank_sum(
# self.stats[0].dist, self.stats[1].dist)
# t = "Mann-Whitney's z: %.1f (p=%.3f)" % (z, p)
else:
t, p = stat_ttest()
t = "" if np.isnan(t) else f"Student's t: {t:.3f} (p={p:.3f})"
else:
if self.compare == OWBoxPlot.CompareMedians:
t = ""
# U, p = -1, -1
# t = "Kruskal Wallis's U: %.1f (p=%.3f)" % (U, p)
else:
F, p = stat_ANOVA()
t = "" if np.isnan(F) else f"ANOVA: {F:.3f} (p={p:.3f})"
self.infot1.setText("<center>%s</center>" % t)
def mean_label(self, stat, attr, val_name):
label = QGraphicsItemGroup()
t = QGraphicsSimpleTextItem(
"%.*f" % (attr.number_of_decimals + 1, stat.mean), label)
t.setFont(self._label_font)
bbox = t.boundingRect()
w2, h = bbox.width() / 2, bbox.height()
t.setPos(-w2, -h)
tpm = QGraphicsSimpleTextItem(
" \u00b1 " + "%.*f" % (attr.number_of_decimals + 1, stat.dev),
label)
tpm.setFont(self._label_font)
tpm.setPos(w2, -h)
if val_name:
vnm = QGraphicsSimpleTextItem(val_name + ": ", label)
vnm.setFont(self._label_font)
vnm.setBrush(self._attr_brush)
vb = vnm.boundingRect()
label.min_x = -w2 - vb.width()
vnm.setPos(label.min_x, -h)
else:
label.min_x = -w2
return label
def draw_axis(self):
"""Draw the horizontal axis and sets self.scale_x"""
misssing_stats = not self.stats
stats = self.stats or [BoxData(np.array([[0.], [1.]]), self.attribute)]
mean_labels = self.mean_labels or [self.mean_label(stats[0], self.attribute, "")]
bottom = min(stat.a_min for stat in stats)
top = max(stat.a_max for stat in stats)
first_val, step = compute_scale(bottom, top)
while bottom <= first_val:
first_val -= step
bottom = first_val
no_ticks = math.ceil((top - first_val) / step) + 1
top = max(top, first_val + no_ticks * step)
gbottom = min(bottom, min(stat.mean - stat.dev for stat in stats))
gtop = max(top, max(stat.mean + stat.dev for stat in stats))
bv = self.box_view
viewrect = bv.viewport().rect().adjusted(15, 15, -15, -30)
self.scale_x = scale_x = viewrect.width() / (gtop - gbottom)
# In principle we should repeat this until convergence since the new
# scaling is too conservative. (No chance am I doing this.)
mlb = min(stat.mean + mean_lab.min_x / scale_x
for stat, mean_lab in zip(stats, mean_labels))
if mlb < gbottom:
gbottom = mlb
self.scale_x = scale_x = viewrect.width() / (gtop - gbottom)
self.scene_min_x = gbottom * scale_x
self.scene_width = (gtop - gbottom) * scale_x
val = first_val
decimals = max(3, 4 - int(math.log10(step)))
while True:
l = self.box_scene.addLine(val * scale_x, -1, val * scale_x, 1,
self._pen_axis_tick)
l.setZValue(100)
t = self.box_scene.addSimpleText(
repr(round(val, decimals)) if not misssing_stats else "?",
self._axis_font)
t.setFlags(
t.flags() | QGraphicsItem.ItemIgnoresTransformations)
r = t.boundingRect()
t.setPos(val * scale_x - r.width() / 2, 8)
if val >= top:
break
val += step
self.box_scene.addLine(
bottom * scale_x - 4, 0, top * scale_x + 4, 0, self._pen_axis)
def draw_axis_disc(self):
"""
Draw the horizontal axis and sets self.scale_x for discrete attributes
"""
assert not self.is_continuous
if self.stretched:
if not self.attr_labels:
return
step = steps = 10
else:
if self.group_var:
max_box = max(float(np.sum(dist)) for dist in self.conts)
else:
max_box = float(np.sum(self.dist))
if max_box == 0:
self.scale_x = 1
return
_, step = compute_scale(0, max_box)
step = int(step) if step > 1 else 1
steps = int(math.ceil(max_box / step))
max_box = step * steps
bv = self.box_view
viewrect = bv.viewport().rect().adjusted(15, 15, -15, -30)
self.scene_width = viewrect.width()
lab_width = max(lab.boundingRect().width() for lab in self.attr_labels)
lab_width = max(lab_width, 40)
lab_width = min(lab_width, self.scene_width / 3)
self.label_width = lab_width
right_offset = 0 # offset for the right label
if not self.stretched and self.labels:
if self.group_var:
rows = list(zip(self.conts, self.labels))
else:
rows = [(self.dist, self.labels[0])]
# available space left of the 'group labels'
available = self.scene_width - lab_width - 10
scale_x = (available - right_offset) / max_box
max_right = max(sum(dist) * scale_x + 10 +
lbl.boundingRect().width()
for dist, lbl in rows)
right_offset = max(0, max_right - max_box * scale_x)
self.scale_x = scale_x = \
(self.scene_width - lab_width - 10 - right_offset) / max_box
self.box_scene.addLine(0, 0, max_box * scale_x, 0, self._pen_axis)
for val in range(0, step * steps + 1, step):
l = self.box_scene.addLine(val * scale_x, -1, val * scale_x, 1,
self._pen_axis_tick)
l.setZValue(100)
t = self.box_scene.addSimpleText(str(val), self._axis_font)
t.setPos(val * scale_x - t.boundingRect().width() / 2, 8)
if self.stretched:
self.scale_x *= 100
def label_group(self, stat, attr, mean_lab):
def centered_text(val, pos):
t = QGraphicsSimpleTextItem(
"%.*f" % (attr.number_of_decimals + 1, val), labels)
t.setFont(self._label_font)
bbox = t.boundingRect()
t.setPos(pos - bbox.width() / 2, 22)
return t
def line(x, down=1):
QGraphicsLineItem(x, 12 * down, x, 20 * down, labels)
def move_label(label, frm, to):
label.setX(to)
to += t_box.width() / 2
path = QPainterPath()
path.lineTo(0, 4)
path.lineTo(to - frm, 4)
path.lineTo(to - frm, 8)
p = QGraphicsPathItem(path)
p.setPos(frm, 12)
labels.addToGroup(p)
labels = QGraphicsItemGroup()
labels.addToGroup(mean_lab)
m = stat.mean * self.scale_x
mean_lab.setPos(m, -22)
line(m, -1)
if stat.median is not None:
msc = stat.median * self.scale_x
med_t = centered_text(stat.median, msc)
med_box_width2 = med_t.boundingRect().width() / 2
line(msc)
if stat.q25 is not None:
x = stat.q25 * self.scale_x
t = centered_text(stat.q25, x)
t_box = t.boundingRect()
med_left = msc - med_box_width2
if x + t_box.width() / 2 >= med_left - 5:
move_label(t, x, med_left - t_box.width() - 5)
else:
line(x)
if stat.q75 is not None:
x = stat.q75 * self.scale_x
t = centered_text(stat.q75, x)
t_box = t.boundingRect()
med_right = msc + med_box_width2
if x - t_box.width() / 2 <= med_right + 5:
move_label(t, x, med_right + 5)
else:
line(x)
return labels
def box_group(self, stat, height=20):
def line(x0, y0, x1, y1, *args):
return QGraphicsLineItem(x0 * scale_x, y0, x1 * scale_x, y1, *args)
scale_x = self.scale_x
box = []
whisker1 = line(stat.a_min, -1.5, stat.a_min, 1.5)
whisker2 = line(stat.a_max, -1.5, stat.a_max, 1.5)
vert_line = line(stat.a_min, 0, stat.a_max, 0)
mean_line = line(stat.mean, -height / 3, stat.mean, height / 3)
for it in (whisker1, whisker2, mean_line):
it.setPen(self._pen_paramet)
vert_line.setPen(self._pen_dotted)
var_line = line(stat.mean - stat.dev, 0, stat.mean + stat.dev, 0)
var_line.setPen(self._pen_paramet)
box.extend([whisker1, whisker2, vert_line, mean_line, var_line])
if stat.q25 is not None and stat.q75 is not None:
mbox = FilterGraphicsRectItem(
stat.conditions, stat.q25 * scale_x, -height / 2,
(stat.q75 - stat.q25) * scale_x, height)
mbox.setBrush(self._box_brush)
mbox.setPen(QPen(Qt.NoPen))
mbox.setZValue(-200)
box.append(mbox)
if stat.median is not None:
median_line = line(stat.median, -height / 2,
stat.median, height / 2)
median_line.setPen(self._pen_median)
median_line.setZValue(-150)
box.append(median_line)
return box
def strudel(self, dist, group_val_index=None):
attr = self.attribute
ss = np.sum(dist)
box = []
if ss < 1e-6:
cond = [FilterDiscrete(attr, None)]
if group_val_index is not None:
cond.append(FilterDiscrete(self.group_var, [group_val_index]))
box.append(FilterGraphicsRectItem(cond, 0, -10, 1, 10))
cum = 0
for i, v in enumerate(dist):
if v < 1e-6:
continue
if self.stretched:
v /= ss
v *= self.scale_x
cond = [FilterDiscrete(attr, [i])]
if group_val_index is not None:
cond.append(FilterDiscrete(self.group_var, [group_val_index]))
rect = FilterGraphicsRectItem(cond, cum + 1, -6, v - 2, 12)
rect.setBrush(QBrush(QColor(*attr.colors[i])))
rect.setPen(QPen(Qt.NoPen))
if self.stretched:
tooltip = "{}: {:.2f}%".format(attr.values[i],
100 * dist[i] / sum(dist))
else:
tooltip = "{}: {}".format(attr.values[i], int(dist[i]))
rect.setToolTip(tooltip)
text = QGraphicsTextItem(attr.values[i])
box.append(rect)
box.append(text)
cum += v
return box
def commit(self):
self.conditions = [item.filter for item in
self.box_scene.selectedItems() if item.filter]
selected, selection = None, []
if self.conditions:
selected = Values(self.conditions, conjunction=False)(self.dataset)
selection = np.in1d(
self.dataset.ids, selected.ids, assume_unique=True).nonzero()[0]
self.Outputs.selected_data.send(selected)
self.Outputs.annotated_data.send(
create_annotated_table(self.dataset, selection))
def show_posthoc(self):
def line(y0, y1):
it = self.box_scene.addLine(x, y0, x, y1, self._post_line_pen)
it.setZValue(-100)
self.posthoc_lines.append(it)
while self.posthoc_lines:
self.box_scene.removeItem(self.posthoc_lines.pop())
if self.compare == OWBoxPlot.CompareNone or len(self.stats) < 2:
return
if self.compare == OWBoxPlot.CompareMedians:
crit_line = "median"
else:
crit_line = "mean"
xs = []
height = 90 if self.show_annotations else 60
y_up = -len(self.stats) * height + 10
for pos, box_index in enumerate(self.order):
stat = self.stats[box_index]
x = getattr(stat, crit_line)
if x is None:
continue
x *= self.scale_x
xs.append(x * self.scale_x)
by = y_up + pos * height
line(by + 12, 3)
line(by - 12, by - 25)
used_to = []
last_to = to = 0
for frm, frm_x in enumerate(xs[:-1]):
for to in range(frm + 1, len(xs)):
if xs[to] - frm_x > 1.5:
to -= 1
break
if to in (last_to, frm):
continue
for rowi, used in enumerate(used_to):
if used < frm:
used_to[rowi] = to
break
else:
rowi = len(used_to)
used_to.append(to)
y = - 6 - rowi * 6
it = self.box_scene.addLine(frm_x - 2, y, xs[to] + 2, y,
self._post_grp_pen)
self.posthoc_lines.append(it)
last_to = to
def get_widget_name_extension(self):
return self.attribute.name if self.attribute else None
def send_report(self):
self.report_plot()
text = ""
if self.attribute:
text += "Box plot for attribute '{}' ".format(self.attribute.name)
if self.group_var:
text += "grouped by '{}'".format(self.group_var.name)
if text:
self.report_caption(text)
class Label(QGraphicsSimpleTextItem):
"""Boxplot Label with settable maxWidth"""
# Minimum width to display label text
MIN_LABEL_WIDTH = 25
# padding bellow the text
PADDING = 3
__max_width = None
def maxWidth(self):
return self.__max_width
def setMaxWidth(self, max_width):
self.__max_width = max_width
def paint(self, painter, option, widget):
"""Overrides QGraphicsSimpleTextItem.paint
If label text is too long, it is elided
to fit into the allowed region
"""
if self.__max_width is None:
width = option.rect.width()
else:
width = self.__max_width
if width < self.MIN_LABEL_WIDTH:
# if space is too narrow, no label
return
fm = painter.fontMetrics()
text = fm.elidedText(self.text(), Qt.ElideRight, width)
painter.drawText(
option.rect.x(),
option.rect.y() + self.boundingRect().height() - self.PADDING,
text)
class OWGeoMap(widget.OWWidget):
name = "GeoMap"
priority = 20000
icon = "icons/GeoMap.svg"
inputs = [("Data", Table, "on_data")]
outputs = [('Corpus', Corpus)]
want_main_area = False
selected_attr = settings.Setting('')
selected_map = settings.Setting(0)
regions = settings.Setting([])
def __init__(self):
super().__init__()
self.data = None
self._create_layout()
@pyqtSlot(str)
def region_selected(self, regions):
"""Called from JavaScript"""
if not regions:
self.regions = []
if not regions or self.data is None:
return self.send('Corpus', None)
self.regions = regions.split(',')
attr = self.data.domain[self.selected_attr]
if attr.is_discrete: return # TODO, FIXME: make this work for discrete attrs also
from Orange.data.filter import FilterRegex
filter = FilterRegex(attr, r'\b{}\b'.format(r'\b|\b'.join(self.regions)), re.IGNORECASE)
self.send('Corpus', self.data._filter_values(filter))
def _create_layout(self):
box = gui.widgetBox(self.controlArea,
orientation='horizontal')
self.varmodel = VariableListModel(parent=self)
self.attr_combo = gui.comboBox(box, self, 'selected_attr',
orientation=Qt.Horizontal,
label='Region attribute:',
callback=self.on_attr_change,
sendSelectedValue=True)
self.attr_combo.setModel(self.varmodel)
self.map_combo = gui.comboBox(box, self, 'selected_map',
orientation=Qt.Horizontal,
label='Map type:',
callback=self.on_map_change,
items=Map.all)
hexpand = QSizePolicy(QSizePolicy.Expanding,
QSizePolicy.Fixed)
self.attr_combo.setSizePolicy(hexpand)
self.map_combo.setSizePolicy(hexpand)
url = urljoin('file:',
pathname2url(os.path.join(
os.path.dirname(__file__),
'resources',
'owgeomap.html')))
self.webview = gui.WebviewWidget(self.controlArea, self, url=QUrl(url))
self.controlArea.layout().addWidget(self.webview)
QTimer.singleShot(
0, lambda: self.webview.evalJS('REGIONS = {};'.format({Map.WORLD: CC_WORLD,
Map.EUROPE: CC_EUROPE,
Map.USA: CC_USA})))
def _repopulate_attr_combo(self, data):
vars = [a for a in chain(data.domain.metas,
data.domain.attributes,
data.domain.class_vars)
if a.is_string] if data else []
self.varmodel.wrap(vars)
# Select default attribute
self.selected_attr = next((var.name
for var in vars
if var.name.lower().startswith(('country', 'location', 'region'))),
vars[0].name if vars else '')
def on_data(self, data):
if data and not isinstance(data, Corpus):
data = Corpus.from_table(data.domain, data)
self.data = data
self._repopulate_attr_combo(data)
if not data:
self.region_selected('')
QTimer.singleShot(0, lambda: self.webview.evalJS('DATA = {}; renderMap();'))
else:
QTimer.singleShot(0, self.on_attr_change)
def on_map_change(self, map_code=''):
if map_code:
self.map_combo.setCurrentIndex(self.map_combo.findData(map_code))
else:
map_code = self.map_combo.itemData(self.selected_map)
inv_cc_map, cc_map = {Map.USA: (INV_CC_USA, CC_USA),
Map.WORLD: (INV_CC_WORLD, CC_WORLD),
Map.EUROPE: (INV_CC_EUROPE, CC_EUROPE)}[map_code]
# Set country counts for JS
data = defaultdict(int)
for locations in self._iter_locations():
keys = set(inv_cc_map.get(loc, loc) for loc in locations)
for key in keys:
if key in cc_map:
data[key] += 1
# Draw the new map
self.webview.evalJS('DATA = {};'
'MAP_CODE = "{}";'
'SELECTED_REGIONS = {};'
'renderMap();'.format(dict(data),
map_code,
self.regions))
def on_attr_change(self):
if not self.selected_attr:
return
values = set(chain.from_iterable(self._iter_locations()))
# Auto-select region map
if 0 == len(values - SET_CC_USA):
map_code = Map.USA
elif 0 == len(values - SET_CC_EUROPE):
map_code = Map.EUROPE
else:
map_code = Map.WORLD
self.on_map_change(map_code)
def _iter_locations(self):
""" Iterator that yields an iterable per documents with all its's
locations. """
attr = self.data.domain[self.selected_attr]
for i in self.data.get_column_view(self.data.domain.index(attr))[0]:
if len(i) > 3:
yield map(lambda x: x.strip(), CC_NAMES.findall(i.lower()))
else:
yield (i, )
class OWBoxPlot(widget.OWWidget):
"""
Here's how the widget's functions call each other:
- `set_data` is a signal handler fills the list boxes and calls
`grouping_changed`.
- `grouping_changed` handles changes of grouping attribute: it enables or
disables the box for ordering, orders attributes and calls `attr_changed`.
- `attr_changed` handles changes of attribute. It recomputes box data by
calling `compute_box_data`, shows the appropriate display box
(discrete/continuous) and then calls`layout_changed`
- `layout_changed` constructs all the elements for the scene (as lists of
QGraphicsItemGroup) and calls `display_changed`. It is called when the
attribute or grouping is changed (by attr_changed) and on resize event.
- `display_changed` puts the elements corresponding to the current display
settings on the scene. It is called when the elements are reconstructed
(layout is changed due to selection of attributes or resize event), or
when the user changes display settings or colors.
For discrete attributes, the flow is a bit simpler: the elements are not
constructed in advance (by layout_changed). Instead, layout_changed and
display_changed call display_changed_disc that draws everything.
"""
name = "箱形图"
description = "在方框图中可视化特征值的分布。"
icon = "icons/BoxPlot.svg"
priority = 100
keywords = ["whisker"]
class Inputs:
data = Input("数据", Orange.data.Table)
class Outputs:
selected_data = Output("所选数据", Orange.data.Table, default=True)
annotated_data = Output(ANNOTATED_DATA_SIGNAL_NAME, Orange.data.Table)
#: Comparison types for continuous variables
CompareNone, CompareMedians, CompareMeans = 0, 1, 2
settingsHandler = DomainContextHandler()
conditions = ContextSetting([])
attribute = ContextSetting(None)
order_by_importance = Setting(False)
group_var = ContextSetting(None)
show_annotations = Setting(True)
compare = Setting(CompareMeans)
stattest = Setting(0)
sig_threshold = Setting(0.05)
stretched = Setting(True)
show_labels = Setting(True)
sort_freqs = Setting(False)
auto_commit = Setting(True)
_sorting_criteria_attrs = {
CompareNone: "",
CompareMedians: "median",
CompareMeans: "mean"
}
_pen_axis_tick = QPen(Qt.white, 5)
_pen_axis = QPen(Qt.darkGray, 3)
_pen_median = QPen(QBrush(QColor(0xff, 0xff, 0x00)), 2)
_pen_paramet = QPen(QBrush(QColor(0x33, 0x00, 0xff)), 2)
_pen_dotted = QPen(QBrush(QColor(0x33, 0x00, 0xff)), 1)
_pen_dotted.setStyle(Qt.DotLine)
_post_line_pen = QPen(Qt.lightGray, 2)
_post_grp_pen = QPen(Qt.lightGray, 4)
for pen in (_pen_paramet, _pen_median, _pen_dotted, _pen_axis,
_pen_axis_tick, _post_line_pen, _post_grp_pen):
pen.setCosmetic(True)
pen.setCapStyle(Qt.RoundCap)
pen.setJoinStyle(Qt.RoundJoin)
_pen_axis_tick.setCapStyle(Qt.FlatCap)
_box_brush = QBrush(QColor(0x33, 0x88, 0xff, 0xc0))
_axis_font = QFont()
_axis_font.setPixelSize(12)
_label_font = QFont()
_label_font.setPixelSize(11)
_attr_brush = QBrush(QColor(0x33, 0x00, 0xff))
graph_name = "盒式布景"
def __init__(self):
super().__init__()
self.stats = []
self.dataset = None
self.posthoc_lines = []
self.label_txts = self.mean_labels = self.boxes = self.labels = \
self.label_txts_all = self.attr_labels = self.order = []
self.p = -1.0
self.scale_x = self.scene_min_x = self.scene_width = 0
self.label_width = 0
self.attrs = VariableListModel()
view = gui.listView(self.controlArea,
self,
"attribute",
box="变量",
model=self.attrs,
callback=self.attr_changed)
view.setMinimumSize(QSize(30, 30))
# Any other policy than Ignored will let the QListBox's scrollbar
# set the minimal height (see the penultimate paragraph of
# http://doc.qt.io/qt-4.8/qabstractscrollarea.html#addScrollBarWidget)
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
gui.separator(view.box, 6, 6)
self.cb_order = gui.checkBox(view.box,
self,
"order_by_importance",
"按相关性排序",
tooltip="由𝜒²或方差对子群排序",
callback=self.apply_sorting)
self.group_vars = DomainModel(placeholder="无",
separators=False,
valid_types=Orange.data.DiscreteVariable)
self.group_view = view = gui.listView(self.controlArea,
self,
"group_var",
box="子群",
model=self.group_vars,
callback=self.grouping_changed)
view.setEnabled(False)
view.setMinimumSize(QSize(30, 30))
# See the comment above
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
# TODO: move Compare median/mean to grouping box
# The vertical size policy is needed to let only the list views expand
self.display_box = gui.vBox(self.controlArea,
"Display",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Maximum),
addSpace=False)
gui.checkBox(self.display_box,
self,
"show_annotations",
"Annotate",
callback=self.display_changed)
self.compare_rb = gui.radioButtonsInBox(
self.display_box,
self,
'compare',
btnLabels=["无比较", "中位数比较", "均值比较"],
callback=self.layout_changed)
# The vertical size policy is needed to let only the list views expand
self.stretching_box = box = gui.vBox(self.controlArea,
box="显示",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Fixed))
self.stretching_box.sizeHint = self.display_box.sizeHint
gui.checkBox(box,
self,
'stretched',
"拉杆",
callback=self.display_changed)
gui.checkBox(box,
self,
'show_labels',
"显示框标签",
callback=self.display_changed)
self.sort_cb = gui.checkBox(box,
self,
'sort_freqs',
"按子组频率排序",
callback=self.display_changed)
gui.rubber(box)
gui.auto_commit(self.controlArea, self, "auto_commit", "选中发送", "自动发送")
gui.vBox(self.mainArea, addSpace=True)
self.box_scene = QGraphicsScene()
self.box_scene.selectionChanged.connect(self.commit)
self.box_view = QGraphicsView(self.box_scene)
self.box_view.setRenderHints(QPainter.Antialiasing
| QPainter.TextAntialiasing
| QPainter.SmoothPixmapTransform)
self.box_view.viewport().installEventFilter(self)
self.mainArea.layout().addWidget(self.box_view)
e = gui.hBox(self.mainArea, addSpace=False)
self.infot1 = gui.widgetLabel(e, "<center>没有测试结果。</center>")
self.mainArea.setMinimumWidth(600)
self.stats = self.dist = self.conts = []
self.is_continuous = False
self.update_display_box()
def sizeHint(self):
return QSize(100, 500) # Vertical size is regulated by mainArea
def eventFilter(self, obj, event):
if obj is self.box_view.viewport() and \
event.type() == QEvent.Resize:
self.layout_changed()
return super().eventFilter(obj, event)
def reset_attrs(self, domain):
self.attrs[:] = [
var for var in chain(domain.class_vars, domain.metas,
domain.attributes) if var.is_primitive()
]
# noinspection PyTypeChecker
@Inputs.data
def set_data(self, dataset):
if dataset is not None and (not bool(dataset)
or not len(dataset.domain) and
not any(var.is_primitive()
for var in dataset.domain.metas)):
dataset = None
self.closeContext()
self.dataset = dataset
self.dist = self.stats = self.conts = []
self.group_var = None
self.attribute = None
if dataset:
domain = dataset.domain
self.group_vars.set_domain(domain)
self.group_view.setEnabled(len(self.group_vars) > 1)
self.reset_attrs(domain)
self.select_default_variables(domain)
self.openContext(self.dataset)
self.grouping_changed()
else:
self.reset_all_data()
self.commit()
def select_default_variables(self, domain):
# visualize first non-class variable, group by class (if present)
if len(self.attrs) > len(domain.class_vars):
self.attribute = self.attrs[len(domain.class_vars)]
elif self.attrs:
self.attribute = self.attrs[0]
if domain.class_var and domain.class_var.is_discrete:
self.group_var = domain.class_var
else:
self.group_var = None # Reset to trigger selection via callback
def apply_sorting(self):
def compute_score(attr):
if attr is group_var:
return 3
if attr.is_continuous:
# One-way ANOVA
col = data.get_column_view(attr)[0].astype(float)
groups = (col[group_col == i] for i in range(n_groups))
groups = (col[~np.isnan(col)] for col in groups)
groups = [group for group in groups if len(group)]
p = f_oneway(*groups)[1] if len(groups) > 1 else 2
else:
# Chi-square with the given distribution into groups
# (see degrees of freedom in computation of the p-value)
if not attr.values or not group_var.values:
return 2
observed = np.array(
contingency.get_contingency(data, group_var, attr))
observed = observed[observed.sum(axis=1) != 0, :]
observed = observed[:, observed.sum(axis=0) != 0]
if min(observed.shape) < 2:
return 2
expected = \
np.outer(observed.sum(axis=1), observed.sum(axis=0)) / \
np.sum(observed)
p = chisquare(observed.ravel(),
f_exp=expected.ravel(),
ddof=n_groups - 1)[1]
if math.isnan(p):
return 2
return p
data = self.dataset
if data is None:
return
domain = data.domain
attribute = self.attribute
group_var = self.group_var
if self.order_by_importance and group_var is not None:
n_groups = len(group_var.values)
group_col = data.get_column_view(group_var)[0] if \
domain.has_continuous_attributes(
include_class=True, include_metas=True) else None
self.attrs.sort(key=compute_score)
else:
self.reset_attrs(domain)
self.attribute = attribute
def reset_all_data(self):
self.clear_scene()
self.infot1.setText("")
self.attrs.clear()
self.group_vars.set_domain(None)
self.group_view.setEnabled(False)
self.is_continuous = False
self.update_display_box()
def grouping_changed(self):
self.cb_order.setEnabled(self.group_var is not None)
self.apply_sorting()
self.attr_changed()
def select_box_items(self):
temp_cond = self.conditions.copy()
for box in self.box_scene.items():
if isinstance(box, FilterGraphicsRectItem):
box.setSelected(
box.filter.conditions in [c.conditions for c in temp_cond])
def attr_changed(self):
self.compute_box_data()
self.update_display_box()
self.layout_changed()
if self.is_continuous:
heights = 90 if self.show_annotations else 60
self.box_view.centerOn(self.scene_min_x + self.scene_width / 2,
-30 - len(self.stats) * heights / 2 + 45)
else:
self.box_view.centerOn(self.scene_width / 2,
-30 - len(self.boxes) * 40 / 2 + 45)
def compute_box_data(self):
attr = self.attribute
if not attr:
return
dataset = self.dataset
self.is_continuous = attr.is_continuous
if dataset is None or not self.is_continuous and not attr.values or \
self.group_var and not self.group_var.values:
self.stats = self.dist = self.conts = []
return
if self.group_var:
self.dist = []
self.conts = contingency.get_contingency(dataset, attr,
self.group_var)
if self.is_continuous:
stats, label_texts = [], []
for i, cont in enumerate(self.conts):
if np.sum(cont[1]):
stats.append(BoxData(cont, attr, i, self.group_var))
label_texts.append(self.group_var.values[i])
self.stats = stats
self.label_txts_all = label_texts
else:
self.label_txts_all = \
[v for v, c in zip(self.group_var.values, self.conts)
if np.sum(c) > 0]
else:
self.dist = distribution.get_distribution(dataset, attr)
self.conts = []
if self.is_continuous:
self.stats = [BoxData(self.dist, attr, None)]
self.label_txts_all = [""]
self.label_txts = [
txts for stat, txts in zip(self.stats, self.label_txts_all)
if stat.n > 0
]
self.stats = [stat for stat in self.stats if stat.n > 0]
def update_display_box(self):
if self.is_continuous:
self.stretching_box.hide()
self.display_box.show()
self.compare_rb.setEnabled(self.group_var is not None)
else:
self.stretching_box.show()
self.display_box.hide()
self.sort_cb.setEnabled(self.group_var is not None)
def clear_scene(self):
self.closeContext()
self.box_scene.clearSelection()
self.box_scene.clear()
self.box_view.viewport().update()
self.attr_labels = []
self.labels = []
self.boxes = []
self.mean_labels = []
self.posthoc_lines = []
self.openContext(self.dataset)
def layout_changed(self):
attr = self.attribute
if not attr:
return
self.clear_scene()
if self.dataset is None or len(self.conts) == len(self.dist) == 0:
return
if not self.is_continuous:
self.display_changed_disc()
return
self.mean_labels = [
self.mean_label(stat, attr, lab)
for stat, lab in zip(self.stats, self.label_txts)
]
self.draw_axis()
self.boxes = [self.box_group(stat) for stat in self.stats]
self.labels = [
self.label_group(stat, attr, mean_lab)
for stat, mean_lab in zip(self.stats, self.mean_labels)
]
self.attr_labels = [
QGraphicsSimpleTextItem(lab) for lab in self.label_txts
]
for it in chain(self.labels, self.attr_labels):
self.box_scene.addItem(it)
self.display_changed()
def display_changed(self):
if self.dataset is None:
return
if not self.is_continuous:
self.display_changed_disc()
return
self.order = list(range(len(self.stats)))
criterion = self._sorting_criteria_attrs[self.compare]
if criterion:
vals = [getattr(stat, criterion) for stat in self.stats]
overmax = max((val for val in vals if val is not None), default=0) \
+ 1
vals = [val if val is not None else overmax for val in vals]
self.order = sorted(self.order, key=vals.__getitem__)
heights = 90 if self.show_annotations else 60
for row, box_index in enumerate(self.order):
y = (-len(self.stats) + row) * heights + 10
for item in self.boxes[box_index]:
self.box_scene.addItem(item)
item.setY(y)
labels = self.labels[box_index]
if self.show_annotations:
labels.show()
labels.setY(y)
else:
labels.hide()
label = self.attr_labels[box_index]
label.setY(y - 15 - label.boundingRect().height())
if self.show_annotations:
label.hide()
else:
stat = self.stats[box_index]
if self.compare == OWBoxPlot.CompareMedians and \
stat.median is not None:
pos = stat.median + 5 / self.scale_x
elif self.compare == OWBoxPlot.CompareMeans or stat.q25 is None:
pos = stat.mean + 5 / self.scale_x
else:
pos = stat.q25
label.setX(pos * self.scale_x)
label.show()
r = QRectF(self.scene_min_x, -30 - len(self.stats) * heights,
self.scene_width,
len(self.stats) * heights + 90)
self.box_scene.setSceneRect(r)
self.compute_tests()
self.show_posthoc()
self.select_box_items()
def display_changed_disc(self):
assert not self.is_continuous
self.clear_scene()
self.attr_labels = [
QGraphicsSimpleTextItem(lab) for lab in self.label_txts_all
]
if not self.stretched:
if self.group_var:
self.labels = [
QGraphicsTextItem("{}".format(int(sum(cont))))
for cont in self.conts if np.sum(cont) > 0
]
else:
self.labels = [QGraphicsTextItem(str(int(sum(self.dist))))]
self.order = list(range(len(self.attr_labels)))
self.draw_axis_disc()
if self.group_var:
self.boxes = \
[self.strudel(cont, i) for i, cont in enumerate(self.conts)
if np.sum(cont) > 0]
self.conts = self.conts[np.sum(np.array(self.conts), axis=1) > 0]
if self.sort_freqs:
# pylint: disable=invalid-unary-operand-type
self.order = sorted(
self.order, key=(-np.sum(self.conts, axis=1)).__getitem__)
else:
self.boxes = [self.strudel(self.dist)]
for row, box_index in enumerate(self.order):
y = (-len(self.boxes) + row) * 40 + 10
box = self.boxes[box_index]
bars, labels = box[::2], box[1::2]
self.__draw_group_labels(y, box_index)
if not self.stretched:
self.__draw_row_counts(y, box_index)
if self.show_labels and self.attribute is not self.group_var:
self.__draw_bar_labels(y, bars, labels)
self.__draw_bars(y, bars)
self.box_scene.setSceneRect(-self.label_width - 5,
-30 - len(self.boxes) * 40,
self.scene_width,
len(self.boxes * 40) + 90)
self.infot1.setText("")
self.select_box_items()
def __draw_group_labels(self, y, row):
"""Draw group labels
Parameters
----------
y: int
vertical offset of bars
row: int
row index
"""
label = self.attr_labels[row]
b = label.boundingRect()
label.setPos(-b.width() - 10, y - b.height() / 2)
self.box_scene.addItem(label)
def __draw_row_counts(self, y, row):
"""Draw row counts
Parameters
----------
y: int
vertical offset of bars
row: int
row index
"""
assert not self.is_continuous
label = self.labels[row]
b = label.boundingRect()
if self.group_var:
right = self.scale_x * sum(self.conts[row])
else:
right = self.scale_x * sum(self.dist)
label.setPos(right + 10, y - b.height() / 2)
self.box_scene.addItem(label)
def __draw_bar_labels(self, y, bars, labels):
"""Draw bar labels
Parameters
----------
y: int
vertical offset of bars
bars: List[FilterGraphicsRectItem]
list of bars being drawn
labels: List[QGraphicsTextItem]
list of labels for corresponding bars
"""
label = bar_part = None
for text_item, bar_part in zip(labels, bars):
label = self.Label(text_item.toPlainText())
label.setPos(bar_part.boundingRect().x(),
y - label.boundingRect().height() - 8)
label.setMaxWidth(bar_part.boundingRect().width())
self.box_scene.addItem(label)
def __draw_bars(self, y, bars):
"""Draw bars
Parameters
----------
y: int
vertical offset of bars
bars: List[FilterGraphicsRectItem]
list of bars to draw
"""
for item in bars:
item.setPos(0, y)
self.box_scene.addItem(item)
# noinspection PyPep8Naming
def compute_tests(self):
# The t-test and ANOVA are implemented here since they efficiently use
# the widget-specific data in self.stats.
# The non-parametric tests can't do this, so we use statistics.tests
def stat_ttest():
d1, d2 = self.stats
if d1.n == 0 or d2.n == 0:
return np.nan, np.nan
pooled_var = d1.var / d1.n + d2.var / d2.n
df = pooled_var ** 2 / \
((d1.var / d1.n) ** 2 / (d1.n - 1) +
(d2.var / d2.n) ** 2 / (d2.n - 1))
if pooled_var == 0:
return np.nan, np.nan
t = abs(d1.mean - d2.mean) / math.sqrt(pooled_var)
p = 2 * (1 - scipy.special.stdtr(df, t))
return t, p
# TODO: Check this function
# noinspection PyPep8Naming
def stat_ANOVA():
if any(stat.n == 0 for stat in self.stats):
return np.nan, np.nan
n = sum(stat.n for stat in self.stats)
grand_avg = sum(stat.n * stat.mean for stat in self.stats) / n
var_between = sum(stat.n * (stat.mean - grand_avg)**2
for stat in self.stats)
df_between = len(self.stats) - 1
var_within = sum(stat.n * stat.var for stat in self.stats)
df_within = n - len(self.stats)
F = (var_between / df_between) / (var_within / df_within)
p = 1 - scipy.special.fdtr(df_between, df_within, F)
return F, p
if self.compare == OWBoxPlot.CompareNone or len(self.stats) < 2:
t = ""
elif any(s.n <= 1 for s in self.stats):
t = "At least one group has just one instance," \
"cannot compute significance"
elif len(self.stats) == 2:
if self.compare == OWBoxPlot.CompareMedians:
t = ""
# z, self.p = tests.wilcoxon_rank_sum(
# self.stats[0].dist, self.stats[1].dist)
# t = "Mann-Whitney's z: %.1f (p=%.3f)" % (z, self.p)
else:
t, self.p = stat_ttest()
t = "Student's t: %.3f (p=%.3f)" % (t, self.p)
else:
if self.compare == OWBoxPlot.CompareMedians:
t = ""
# U, self.p = -1, -1
# t = "Kruskal Wallis's U: %.1f (p=%.3f)" % (U, self.p)
else:
F, self.p = stat_ANOVA()
t = "ANOVA: %.3f (p=%.3f)" % (F, self.p)
self.infot1.setText("<center>%s</center>" % t)
def mean_label(self, stat, attr, val_name):
label = QGraphicsItemGroup()
t = QGraphicsSimpleTextItem(
"%.*f" % (attr.number_of_decimals + 1, stat.mean), label)
t.setFont(self._label_font)
bbox = t.boundingRect()
w2, h = bbox.width() / 2, bbox.height()
t.setPos(-w2, -h)
tpm = QGraphicsSimpleTextItem(
" \u00b1 " + "%.*f" % (attr.number_of_decimals + 1, stat.dev),
label)
tpm.setFont(self._label_font)
tpm.setPos(w2, -h)
if val_name:
vnm = QGraphicsSimpleTextItem(val_name + ": ", label)
vnm.setFont(self._label_font)
vnm.setBrush(self._attr_brush)
vb = vnm.boundingRect()
label.min_x = -w2 - vb.width()
vnm.setPos(label.min_x, -h)
else:
label.min_x = -w2
return label
def draw_axis(self):
"""Draw the horizontal axis and sets self.scale_x"""
misssing_stats = not self.stats
stats = self.stats or [BoxData(np.array([[0.], [1.]]), self.attribute)]
mean_labels = self.mean_labels or [
self.mean_label(stats[0], self.attribute, "")
]
bottom = min(stat.a_min for stat in stats)
top = max(stat.a_max for stat in stats)
first_val, step = compute_scale(bottom, top)
while bottom <= first_val:
first_val -= step
bottom = first_val
no_ticks = math.ceil((top - first_val) / step) + 1
top = max(top, first_val + no_ticks * step)
gbottom = min(bottom, min(stat.mean - stat.dev for stat in stats))
gtop = max(top, max(stat.mean + stat.dev for stat in stats))
bv = self.box_view
viewrect = bv.viewport().rect().adjusted(15, 15, -15, -30)
self.scale_x = scale_x = viewrect.width() / (gtop - gbottom)
# In principle we should repeat this until convergence since the new
# scaling is too conservative. (No chance am I doing this.)
mlb = min(stat.mean + mean_lab.min_x / scale_x
for stat, mean_lab in zip(stats, mean_labels))
if mlb < gbottom:
gbottom = mlb
self.scale_x = scale_x = viewrect.width() / (gtop - gbottom)
self.scene_min_x = gbottom * scale_x
self.scene_width = (gtop - gbottom) * scale_x
val = first_val
decimals = max(3, 4 - int(math.log10(step)))
while True:
l = self.box_scene.addLine(val * scale_x, -1, val * scale_x, 1,
self._pen_axis_tick)
l.setZValue(100)
t = self.box_scene.addSimpleText(
repr(round(val, decimals)) if not misssing_stats else "?",
self._axis_font)
t.setFlags(t.flags() | QGraphicsItem.ItemIgnoresTransformations)
r = t.boundingRect()
t.setPos(val * scale_x - r.width() / 2, 8)
if val >= top:
break
val += step
self.box_scene.addLine(bottom * scale_x - 4, 0, top * scale_x + 4, 0,
self._pen_axis)
def draw_axis_disc(self):
"""
Draw the horizontal axis and sets self.scale_x for discrete attributes
"""
assert not self.is_continuous
if self.stretched:
if not self.attr_labels:
return
step = steps = 10
else:
if self.group_var:
max_box = max(float(np.sum(dist)) for dist in self.conts)
else:
max_box = float(np.sum(self.dist))
if max_box == 0:
self.scale_x = 1
return
_, step = compute_scale(0, max_box)
step = int(step) if step > 1 else 1
steps = int(math.ceil(max_box / step))
max_box = step * steps
bv = self.box_view
viewrect = bv.viewport().rect().adjusted(15, 15, -15, -30)
self.scene_width = viewrect.width()
lab_width = max(lab.boundingRect().width() for lab in self.attr_labels)
lab_width = max(lab_width, 40)
lab_width = min(lab_width, self.scene_width / 3)
self.label_width = lab_width
right_offset = 0 # offset for the right label
if not self.stretched and self.labels:
if self.group_var:
rows = list(zip(self.conts, self.labels))
else:
rows = [(self.dist, self.labels[0])]
# available space left of the 'group labels'
available = self.scene_width - lab_width - 10
scale_x = (available - right_offset) / max_box
max_right = max(
sum(dist) * scale_x + 10 + lbl.boundingRect().width()
for dist, lbl in rows)
right_offset = max(0, max_right - max_box * scale_x)
self.scale_x = scale_x = \
(self.scene_width - lab_width - 10 - right_offset) / max_box
self.box_scene.addLine(0, 0, max_box * scale_x, 0, self._pen_axis)
for val in range(0, step * steps + 1, step):
l = self.box_scene.addLine(val * scale_x, -1, val * scale_x, 1,
self._pen_axis_tick)
l.setZValue(100)
t = self.box_scene.addSimpleText(str(val), self._axis_font)
t.setPos(val * scale_x - t.boundingRect().width() / 2, 8)
if self.stretched:
self.scale_x *= 100
def label_group(self, stat, attr, mean_lab):
def centered_text(val, pos):
t = QGraphicsSimpleTextItem(
"%.*f" % (attr.number_of_decimals + 1, val), labels)
t.setFont(self._label_font)
bbox = t.boundingRect()
t.setPos(pos - bbox.width() / 2, 22)
return t
def line(x, down=1):
QGraphicsLineItem(x, 12 * down, x, 20 * down, labels)
def move_label(label, frm, to):
label.setX(to)
to += t_box.width() / 2
path = QPainterPath()
path.lineTo(0, 4)
path.lineTo(to - frm, 4)
path.lineTo(to - frm, 8)
p = QGraphicsPathItem(path)
p.setPos(frm, 12)
labels.addToGroup(p)
labels = QGraphicsItemGroup()
labels.addToGroup(mean_lab)
m = stat.mean * self.scale_x
mean_lab.setPos(m, -22)
line(m, -1)
if stat.median is not None:
msc = stat.median * self.scale_x
med_t = centered_text(stat.median, msc)
med_box_width2 = med_t.boundingRect().width() / 2
line(msc)
if stat.q25 is not None:
x = stat.q25 * self.scale_x
t = centered_text(stat.q25, x)
t_box = t.boundingRect()
med_left = msc - med_box_width2
if x + t_box.width() / 2 >= med_left - 5:
move_label(t, x, med_left - t_box.width() - 5)
else:
line(x)
if stat.q75 is not None:
x = stat.q75 * self.scale_x
t = centered_text(stat.q75, x)
t_box = t.boundingRect()
med_right = msc + med_box_width2
if x - t_box.width() / 2 <= med_right + 5:
move_label(t, x, med_right + 5)
else:
line(x)
return labels
def box_group(self, stat, height=20):
def line(x0, y0, x1, y1, *args):
return QGraphicsLineItem(x0 * scale_x, y0, x1 * scale_x, y1, *args)
scale_x = self.scale_x
box = []
whisker1 = line(stat.a_min, -1.5, stat.a_min, 1.5)
whisker2 = line(stat.a_max, -1.5, stat.a_max, 1.5)
vert_line = line(stat.a_min, 0, stat.a_max, 0)
mean_line = line(stat.mean, -height / 3, stat.mean, height / 3)
for it in (whisker1, whisker2, mean_line):
it.setPen(self._pen_paramet)
vert_line.setPen(self._pen_dotted)
var_line = line(stat.mean - stat.dev, 0, stat.mean + stat.dev, 0)
var_line.setPen(self._pen_paramet)
box.extend([whisker1, whisker2, vert_line, mean_line, var_line])
if stat.q25 is not None and stat.q75 is not None:
mbox = FilterGraphicsRectItem(stat.conditions, stat.q25 * scale_x,
-height / 2,
(stat.q75 - stat.q25) * scale_x,
height)
mbox.setBrush(self._box_brush)
mbox.setPen(QPen(Qt.NoPen))
mbox.setZValue(-200)
box.append(mbox)
if stat.median is not None:
median_line = line(stat.median, -height / 2, stat.median,
height / 2)
median_line.setPen(self._pen_median)
median_line.setZValue(-150)
box.append(median_line)
return box
def strudel(self, dist, group_val_index=None):
attr = self.attribute
ss = np.sum(dist)
box = []
if ss < 1e-6:
cond = [FilterDiscrete(attr, None)]
if group_val_index is not None:
cond.append(FilterDiscrete(self.group_var, [group_val_index]))
box.append(FilterGraphicsRectItem(cond, 0, -10, 1, 10))
cum = 0
for i, v in enumerate(dist):
if v < 1e-6:
continue
if self.stretched:
v /= ss
v *= self.scale_x
cond = [FilterDiscrete(attr, [i])]
if group_val_index is not None:
cond.append(FilterDiscrete(self.group_var, [group_val_index]))
rect = FilterGraphicsRectItem(cond, cum + 1, -6, v - 2, 12)
rect.setBrush(QBrush(QColor(*attr.colors[i])))
rect.setPen(QPen(Qt.NoPen))
if self.stretched:
tooltip = "{}: {:.2f}%".format(attr.values[i],
100 * dist[i] / sum(dist))
else:
tooltip = "{}: {}".format(attr.values[i], int(dist[i]))
rect.setToolTip(tooltip)
text = QGraphicsTextItem(attr.values[i])
box.append(rect)
box.append(text)
cum += v
return box
def commit(self):
self.conditions = [
item.filter for item in self.box_scene.selectedItems()
if item.filter
]
selected, selection = None, []
if self.conditions:
selected = Values(self.conditions, conjunction=False)(self.dataset)
selection = np.in1d(self.dataset.ids,
selected.ids,
assume_unique=True).nonzero()[0]
self.Outputs.selected_data.send(selected)
self.Outputs.annotated_data.send(
create_annotated_table(self.dataset, selection))
def show_posthoc(self):
def line(y0, y1):
it = self.box_scene.addLine(x, y0, x, y1, self._post_line_pen)
it.setZValue(-100)
self.posthoc_lines.append(it)
while self.posthoc_lines:
self.box_scene.removeItem(self.posthoc_lines.pop())
if self.compare == OWBoxPlot.CompareNone or len(self.stats) < 2:
return
if self.compare == OWBoxPlot.CompareMedians:
crit_line = "median"
else:
crit_line = "mean"
xs = []
height = 90 if self.show_annotations else 60
y_up = -len(self.stats) * height + 10
for pos, box_index in enumerate(self.order):
stat = self.stats[box_index]
x = getattr(stat, crit_line)
if x is None:
continue
x *= self.scale_x
xs.append(x * self.scale_x)
by = y_up + pos * height
line(by + 12, 3)
line(by - 12, by - 25)
used_to = []
last_to = to = 0
for frm, frm_x in enumerate(xs[:-1]):
for to in range(frm + 1, len(xs)):
if xs[to] - frm_x > 1.5:
to -= 1
break
if to in (last_to, frm):
continue
for rowi, used in enumerate(used_to):
if used < frm:
used_to[rowi] = to
break
else:
rowi = len(used_to)
used_to.append(to)
y = -6 - rowi * 6
it = self.box_scene.addLine(frm_x - 2, y, xs[to] + 2, y,
self._post_grp_pen)
self.posthoc_lines.append(it)
last_to = to
def get_widget_name_extension(self):
return self.attribute.name if self.attribute else None
def send_report(self):
self.report_plot()
text = ""
if self.attribute:
text += "Box plot for attribute '{}' ".format(self.attribute.name)
if self.group_var:
text += "grouped by '{}'".format(self.group_var.name)
if text:
self.report_caption(text)
class Label(QGraphicsSimpleTextItem):
"""Boxplot Label with settable maxWidth"""
# Minimum width to display label text
MIN_LABEL_WIDTH = 25
# padding bellow the text
PADDING = 3
__max_width = None
def maxWidth(self):
return self.__max_width
def setMaxWidth(self, max_width):
self.__max_width = max_width
def paint(self, painter, option, widget):
"""Overrides QGraphicsSimpleTextItem.paint
If label text is too long, it is elided
to fit into the allowed region
"""
if self.__max_width is None:
width = option.rect.width()
else:
width = self.__max_width
if width < self.MIN_LABEL_WIDTH:
# if space is too narrow, no label
return
fm = painter.fontMetrics()
text = fm.elidedText(self.text(), Qt.ElideRight, width)
painter.drawText(
option.rect.x(),
option.rect.y() + self.boundingRect().height() - self.PADDING,
text)
def __init__(self):
super().__init__()
self.stats = []
self.dataset = None
self.posthoc_lines = []
self.label_txts = self.mean_labels = self.boxes = self.labels = \
self.label_txts_all = self.attr_labels = self.order = []
self.p = -1.0
self.scale_x = self.scene_min_x = self.scene_width = 0
self.label_width = 0
self.attrs = VariableListModel()
view = gui.listView(self.controlArea,
self,
"attribute",
box="变量",
model=self.attrs,
callback=self.attr_changed)
view.setMinimumSize(QSize(30, 30))
# Any other policy than Ignored will let the QListBox's scrollbar
# set the minimal height (see the penultimate paragraph of
# http://doc.qt.io/qt-4.8/qabstractscrollarea.html#addScrollBarWidget)
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
gui.separator(view.box, 6, 6)
self.cb_order = gui.checkBox(view.box,
self,
"order_by_importance",
"按相关性排序",
tooltip="由𝜒²或方差对子群排序",
callback=self.apply_sorting)
self.group_vars = DomainModel(placeholder="无",
separators=False,
valid_types=Orange.data.DiscreteVariable)
self.group_view = view = gui.listView(self.controlArea,
self,
"group_var",
box="子群",
model=self.group_vars,
callback=self.grouping_changed)
view.setEnabled(False)
view.setMinimumSize(QSize(30, 30))
# See the comment above
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
# TODO: move Compare median/mean to grouping box
# The vertical size policy is needed to let only the list views expand
self.display_box = gui.vBox(self.controlArea,
"Display",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Maximum),
addSpace=False)
gui.checkBox(self.display_box,
self,
"show_annotations",
"Annotate",
callback=self.display_changed)
self.compare_rb = gui.radioButtonsInBox(
self.display_box,
self,
'compare',
btnLabels=["无比较", "中位数比较", "均值比较"],
callback=self.layout_changed)
# The vertical size policy is needed to let only the list views expand
self.stretching_box = box = gui.vBox(self.controlArea,
box="显示",
sizePolicy=(QSizePolicy.Minimum,
QSizePolicy.Fixed))
self.stretching_box.sizeHint = self.display_box.sizeHint
gui.checkBox(box,
self,
'stretched',
"拉杆",
callback=self.display_changed)
gui.checkBox(box,
self,
'show_labels',
"显示框标签",
callback=self.display_changed)
self.sort_cb = gui.checkBox(box,
self,
'sort_freqs',
"按子组频率排序",
callback=self.display_changed)
gui.rubber(box)
gui.auto_commit(self.controlArea, self, "auto_commit", "选中发送", "自动发送")
gui.vBox(self.mainArea, addSpace=True)
self.box_scene = QGraphicsScene()
self.box_scene.selectionChanged.connect(self.commit)
self.box_view = QGraphicsView(self.box_scene)
self.box_view.setRenderHints(QPainter.Antialiasing
| QPainter.TextAntialiasing
| QPainter.SmoothPixmapTransform)
self.box_view.viewport().installEventFilter(self)
self.mainArea.layout().addWidget(self.box_view)
e = gui.hBox(self.mainArea, addSpace=False)
self.infot1 = gui.widgetLabel(e, "<center>没有测试结果。</center>")
self.mainArea.setMinimumWidth(600)
self.stats = self.dist = self.conts = []
self.is_continuous = False
self.update_display_box()
class OWSpiralogram(widget.OWWidget):
name = 'Spiralogram'
description = "Visualize time series' periodicity in a spiral heatmap."
icon = 'icons/Spiralogram.svg'
priority = 120
class Inputs:
time_series = Input("Time series", Table)
class Outputs:
time_series = Output("Time series", Timeseries)
settingsHandler = settings.DomainContextHandler()
ax1 = settings.ContextSetting('months of year')
ax2 = settings.ContextSetting('years')
agg_attr = settings.ContextSetting([])
agg_func = settings.ContextSetting(0)
invert_date_order = settings.Setting(False)
graph_name = 'chart'
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2_model = VariableListModel(parent=self)
self.combo_ax1_model = VariableListModel(parent=self)
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [_enum_str(i) for i in Spiralogram.AxesCategories]
self.combo_ax2 = gui.comboBox(
box, self, 'ax2', label='Y axis:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax2_model)
self.combo_ax1 = gui.comboBox(
box, self, 'ax1', label='Radial:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal',
model=self.combo_ax1_model)
gui.checkBox(box, self, 'invert_date_order', 'Invert Y axis order',
callback=self.replot)
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(
box, self, 'agg_func', label='Function:', orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.SingleSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def attrlist_selectionChanged(self):
self.agg_attr = [self.attrlist_model[i.row()]
for i in self.attrlist.selectionModel().selectedIndexes()]
self.replot()
@Inputs.time_series
def set_data(self, data):
self.data = data = None if data is None else Timeseries.from_data_table(data)
def init_combos():
for model in (self.combo_ax1_model, self.combo_ax2_model):
model.clear()
newmodel = []
if data is not None and data.time_variable is not None:
for model in (self.combo_ax1_model, self.combo_ax2_model):
model[:] = [_enum_str(i) for i in Spiralogram.AxesCategories]
for var in data.domain.variables if data is not None else []:
if (var.is_primitive() and
(var is not data.time_variable or
isinstance(var, TimeVariable) and data.time_delta is None)):
newmodel.append(var)
if var.is_discrete:
for model in (self.combo_ax1_model, self.combo_ax2_model):
model.append(var)
self.attrlist_model.wrap(newmodel)
init_combos()
self.chart.clear()
if data is None:
self.commit()
return
self.closeContext()
self.ax2 = next((self.combo_ax2.itemText(i)
for i in range(self.combo_ax2.count())), '')
self.ax1 = next((self.combo_ax1.itemText(i)
for i in range(1, self.combo_ax1.count())), self.ax2)
self.agg_attr = [data.domain.variables[0]] if len(data.domain.variables) else []
self.agg_func = 0
if getattr(data, 'time_variable', None) is not None:
self.openContext(data.domain)
if self.agg_attr:
self.attrlist.blockSignals(True)
self.attrlist.selectionModel().clear()
for attr in self.agg_attr:
try:
row = self.attrlist_model.indexOf(attr)
except ValueError:
continue
self.attrlist.selectionModel().select(
self.attrlist_model.index(row),
QItemSelectionModel.SelectCurrent)
self.attrlist.blockSignals(False)
self.replot()
def replot(self):
if not self.combo_ax1.count() or not self.agg_attr:
return self.chart.clear()
vars = self.agg_attr
func = AGG_FUNCTIONS[self.agg_func]
if any(var.is_discrete for var in vars) and func != Mode:
self.combo_func.setCurrentIndex(AGG_FUNCTIONS.index(Mode))
func = Mode
try:
ax1 = Spiralogram.AxesCategories[_enum_str(self.ax1, True)]
except KeyError:
ax1 = self.data.domain[self.ax1]
# TODO: Allow having only a sinle (i.e. radial) axis
try:
ax2 = Spiralogram.AxesCategories[_enum_str(self.ax2, True)]
except KeyError:
ax2 = self.data.domain[self.ax2]
self.chart.setSeries(self.data, vars, ax1, ax2, func)
def on_selection(self, indices):
self.indices = self.chart.selection_indices(indices)
self.commit()
def commit(self):
self.Outputs.time_series.send(self.data[self.indices] if self.data else None)
class OWLinearProjection(widget.OWWidget):
name = "Linear Projection"
description = "A multi-axis projection of data onto " \
"a two-dimensional plane."
icon = "icons/LinearProjection.svg"
priority = 240
selection_indices = settings.Setting(None, schema_only=True)
class Inputs:
data = Input("Data", Table, default=True)
data_subset = Input("Data Subset", Table)
projection = Input("Projection", Table)
class Outputs:
selected_data = Output("Selected Data", Table, default=True)
annotated_data = Output(ANNOTATED_DATA_SIGNAL_NAME, Table)
components = Output("Components", Table)
Placement = Enum("Placement",
dict(Circular=0,
LDA=1,
PCA=2,
Projection=3),
type=int,
qualname="OWLinearProjection.Placement")
Component_name = {Placement.Circular: "C", Placement.LDA: "LD", Placement.PCA: "PC"}
Variable_name = {Placement.Circular: "circular",
Placement.LDA: "lda",
Placement.PCA: "pca",
Placement.Projection: "projection"}
jitter_sizes = [0, 0.1, 0.5, 1.0, 2.0]
settings_version = 3
settingsHandler = settings.DomainContextHandler()
variable_state = settings.ContextSetting({})
placement = settings.Setting(Placement.Circular)
radius = settings.Setting(0)
auto_commit = settings.Setting(True)
resolution = 256
graph = settings.SettingProvider(OWLinProjGraph)
ReplotRequest = QEvent.registerEventType()
vizrank = settings.SettingProvider(LinearProjectionVizRank)
graph_name = "graph.plot_widget.plotItem"
class Warning(widget.OWWidget.Warning):
no_cont_features = widget.Msg("Plotting requires numeric features")
not_enough_components = widget.Msg("Input projection has less than 2 components")
trivial_components = widget.Msg(
"All components of the PCA are trivial (explain 0 variance). "
"Input data is constant (or near constant).")
class Error(widget.OWWidget.Error):
proj_and_domain_match = widget.Msg("Projection and Data domains do not match")
no_valid_data = widget.Msg("No projection due to invalid data")
def __init__(self):
super().__init__()
self.data = None
self.projection = None
self.subset_data = None
self._subset_mask = None
self._selection = None
self.__replot_requested = False
self.n_cont_var = 0
#: Remember the saved state to restore
self.__pending_selection_restore = self.selection_indices
self.selection_indices = None
self.variable_x = None
self.variable_y = None
box = gui.vBox(self.mainArea, True, margin=0)
self.graph = OWLinProjGraph(self, box, "Plot", view_box=LinProjInteractiveViewBox)
box.layout().addWidget(self.graph.plot_widget)
plot = self.graph.plot_widget
SIZE_POLICY = (QSizePolicy.Minimum, QSizePolicy.Maximum)
self.variables_selection = VariablesSelection()
self.model_selected = VariableListModel(enable_dnd=True)
self.model_other = VariableListModel(enable_dnd=True)
self.variables_selection(self, self.model_selected, self.model_other)
self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
self.controlArea, self, "Suggest Features", self._vizrank)
self.variables_selection.add_remove.layout().addWidget(self.btn_vizrank)
box = gui.widgetBox(
self.controlArea, "Placement", sizePolicy=SIZE_POLICY)
self.radio_placement = gui.radioButtonsInBox(
box, self, "placement",
btnLabels=["Circular Placement",
"Linear Discriminant Analysis",
"Principal Component Analysis",
"Use input projection"],
callback=self._change_placement
)
self.viewbox = plot.getViewBox()
self.replot = None
g = self.graph.gui
box = g.point_properties_box(self.controlArea)
self.models = g.points_models
g.add_widget(g.JitterSizeSlider, box)
box.setSizePolicy(*SIZE_POLICY)
box = gui.widgetBox(self.controlArea, "Hide axes", sizePolicy=SIZE_POLICY)
self.rslider = gui.hSlider(
box, self, "radius", minValue=0, maxValue=100,
step=5, label="Radius", createLabel=False, ticks=True,
callback=self.update_radius)
self.rslider.setTickInterval(0)
self.rslider.setPageStep(10)
box = gui.vBox(self.controlArea, "Plot Properties")
box.setSizePolicy(*SIZE_POLICY)
g.add_widgets([g.ShowLegend,
g.ToolTipShowsAll,
g.ClassDensity,
g.LabelOnlySelected], box)
box = self.graph.box_zoom_select(self.controlArea)
box.setSizePolicy(*SIZE_POLICY)
self.icons = gui.attributeIconDict
p = self.graph.plot_widget.palette()
self.graph.set_palette(p)
gui.auto_commit(self.controlArea, self, "auto_commit", "Send Selection",
auto_label="Send Automatically")
self.graph.zoom_actions(self)
self._new_plotdata()
self._change_placement()
self.graph.jitter_continuous = True
def reset_graph_data(self):
if self.data is not None:
self.graph.rescale_data()
self._update_graph(reset_view=True)
def keyPressEvent(self, event):
super().keyPressEvent(event)
self.graph.update_tooltip(event.modifiers())
def keyReleaseEvent(self, event):
super().keyReleaseEvent(event)
self.graph.update_tooltip(event.modifiers())
def _vizrank(self, attrs):
self.variables_selection.display_none()
self.model_selected[:] = attrs[:]
self.model_other[:] = [var for var in self.model_other if var not in attrs]
def _change_placement(self):
placement = self.placement
p_Circular = self.Placement.Circular
p_LDA = self.Placement.LDA
self.variables_selection.set_enabled(placement in [p_Circular, p_LDA])
self._vizrank_color_change()
self.rslider.setEnabled(placement != p_Circular)
self._setup_plot()
self.commit()
def _get_min_radius(self):
return self.radius * np.max(np.linalg.norm(self.plotdata.axes, axis=1)) / 100 + 1e-5
def update_radius(self):
# Update the anchor/axes visibility
pd = self.plotdata
assert pd is not None
if pd.hidecircle is None:
return
min_radius = self._get_min_radius()
for anchor, item in zip(pd.axes, pd.axisitems):
item.setVisible(np.linalg.norm(anchor) > min_radius)
pd.hidecircle.setRect(QRectF(-min_radius, -min_radius, 2 * min_radius, 2 * min_radius))
def _new_plotdata(self):
self.plotdata = namespace(
valid_mask=None,
embedding_coords=None,
axisitems=[],
axes=[],
variables=[],
data=None,
hidecircle=None
)
def _anchor_circle(self, variables):
# minimum visible anchor radius (radius)
min_radius = self._get_min_radius()
axisitems = []
for anchor, var in zip(self.plotdata.axes, variables[:]):
axitem = AnchorItem(line=QLineF(0, 0, *anchor), text=var.name,)
axitem.setVisible(np.linalg.norm(anchor) > min_radius)
axitem.setPen(pg.mkPen((100, 100, 100)))
axitem.setArrowVisible(True)
self.viewbox.addItem(axitem)
axisitems.append(axitem)
self.plotdata.axisitems = axisitems
if self.placement == self.Placement.Circular:
return
hidecircle = QGraphicsEllipseItem()
hidecircle.setRect(QRectF(-min_radius, -min_radius, 2 * min_radius, 2 * min_radius))
_pen = QPen(Qt.lightGray, 1)
_pen.setCosmetic(True)
hidecircle.setPen(_pen)
self.viewbox.addItem(hidecircle)
self.plotdata.hidecircle = hidecircle
def update_colors(self):
self._vizrank_color_change()
def clear(self):
# Clear/reset the widget state
self.data = None
self.model_selected.clear()
self.model_other.clear()
self._clear_plot()
self.selection_indices = None
def _clear_plot(self):
self.Warning.trivial_components.clear()
for axisitem in self.plotdata.axisitems:
self.viewbox.removeItem(axisitem)
if self.plotdata.hidecircle:
self.viewbox.removeItem(self.plotdata.hidecircle)
self._new_plotdata()
self.graph.hide_axes()
def invalidate_plot(self):
"""
Schedule a delayed replot.
"""
if not self.__replot_requested:
self.__replot_requested = True
QApplication.postEvent(self, QEvent(self.ReplotRequest), Qt.LowEventPriority - 10)
def init_attr_values(self):
self.graph.set_domain(self.data)
def _vizrank_color_change(self):
is_enabled = False
if self.data is None:
self.btn_vizrank.setToolTip("There is no data.")
return
vars = [v for v in chain(self.data.domain.variables, self.data.domain.metas) if
v.is_primitive and v is not self.graph.attr_color]
self.n_cont_var = len(vars)
if self.placement not in [self.Placement.Circular, self.Placement.LDA]:
msg = "Suggest Features works only for Circular and " \
"Linear Discriminant Analysis Projection"
elif self.graph.attr_color is None:
msg = "Color variable has to be selected"
elif self.graph.attr_color.is_continuous and self.placement == self.Placement.LDA:
msg = "Suggest Features does not work for Linear Discriminant Analysis Projection " \
"when continuous color variable is selected."
elif len(vars) < 3:
msg = "Not enough available continuous variables"
else:
is_enabled = True
msg = ""
self.btn_vizrank.setToolTip(msg)
self.btn_vizrank.setEnabled(is_enabled)
self.vizrank.stop_and_reset(is_enabled)
@Inputs.projection
def set_projection(self, projection):
self.Warning.not_enough_components.clear()
if projection and len(projection) < 2:
self.Warning.not_enough_components()
projection = None
if projection is not None:
self.placement = self.Placement.Projection
self.projection = projection
@Inputs.data
def set_data(self, data):
"""
Set the input dataset.
Args:
data (Orange.data.table): data instances
"""
def sql(data):
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.information("Data has been sampled")
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
return data
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
state = {key: (source_ind, np.inf) for key, (source_ind, _) in state.items()}
self.openContext(data.domain)
selected_keys = [key for key, (sind, _) in self.variable_state.items() if sind == 0]
if set(selected_keys).issubset(set(state.keys())):
pass
if self.__pending_selection_restore is not None:
self._selection = np.array(self.__pending_selection_restore, dtype=int)
self.__pending_selection_restore = None
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected), list(self.model_other)])
return selected, other
self.closeContext()
self.clear()
self.Warning.no_cont_features.clear()
self.information()
data = sql(data)
if data is not None:
domain = data.domain
vars = [var for var in chain(domain.variables, domain.metas) if var.is_continuous]
if not len(vars):
self.Warning.no_cont_features()
data = None
self.data = data
self.init_attr_values()
if data is not None and len(data):
self._initialize(data)
self.model_selected[:], self.model_other[:] = settings(data)
self.vizrank.stop_and_reset()
self.vizrank.attrs = self.data.domain.attributes if self.data is not None else []
def _check_possible_opt(self):
def set_enabled(is_enabled):
for btn in self.radio_placement.buttons:
btn.setEnabled(is_enabled)
self.variables_selection.set_enabled(is_enabled)
p_Circular = self.Placement.Circular
p_LDA = self.Placement.LDA
p_Input = self.Placement.Projection
if self.data:
set_enabled(True)
domain = self.data.domain
if not domain.has_discrete_class or len(domain.class_var.values) < 2:
self.radio_placement.buttons[p_LDA].setEnabled(False)
if self.placement == p_LDA:
self.placement = p_Circular
if not self.projection:
self.radio_placement.buttons[p_Input].setEnabled(False)
if self.placement == p_Input:
self.placement = p_Circular
self._setup_plot()
else:
self.graph.new_data(None)
self.rslider.setEnabled(False)
set_enabled(False)
self.commit()
@Inputs.data_subset
def set_subset_data(self, subset):
"""
Set the supplementary input subset dataset.
Args:
subset (Orange.data.table): subset of data instances
"""
self.subset_data = subset
self._subset_mask = None
self.controls.graph.alpha_value.setEnabled(subset is None)
def handleNewSignals(self):
if self.data is not None and self.subset_data is not None:
# Update the plot's highlight items
dataids = self.data.ids.ravel()
subsetids = np.unique(self.subset_data.ids)
self._subset_mask = np.in1d(dataids, subsetids, assume_unique=True)
self._check_possible_opt()
self._change_placement()
self.commit()
def customEvent(self, event):
if event.type() == OWLinearProjection.ReplotRequest:
self.__replot_requested = False
self._setup_plot()
self.commit()
else:
super().customEvent(event)
def closeContext(self):
self.variable_state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
super().closeContext()
def _initialize(self, data):
# Initialize the GUI controls from data's domain.
vars = [v for v in chain(data.domain.metas, data.domain.attributes) if v.is_continuous]
self.model_other[:] = vars[3:]
self.model_selected[:] = vars[:3]
def prepare_plot_data(self, variables):
def projection(variables):
if set(self.projection.domain.attributes).issuperset(variables):
axes = self.projection[:2, variables].X
elif set(f.name for f in
self.projection.domain.attributes).issuperset(f.name for f in variables):
axes = self.projection[:2, [f.name for f in variables]].X
else:
self.Error.proj_and_domain_match()
axes = None
return axes
def get_axes(variables):
self.Error.proj_and_domain_match.clear()
axes = None
if self.placement == self.Placement.Circular:
axes = LinProj.defaultaxes(len(variables))
elif self.placement == self.Placement.LDA:
axes = self._get_lda(self.data, variables)
elif self.placement == self.Placement.Projection and self.projection:
axes = projection(variables)
return axes
coords = [column_data(self.data, var, dtype=float) for var in variables]
coords = np.vstack(coords)
p, N = coords.shape
assert N == len(self.data), p == len(variables)
axes = get_axes(variables)
if axes is None:
return None, None, None
assert axes.shape == (2, p)
valid_mask = ~np.isnan(coords).any(axis=0)
coords = coords[:, valid_mask]
X, Y = np.dot(axes, coords)
if X.size and Y.size:
X = normalized(X)
Y = normalized(Y)
return valid_mask, np.stack((X, Y), axis=1), axes.T
def _setup_plot(self):
self._clear_plot()
if self.data is None:
return
self.__replot_requested = False
names = get_unique_names([v.name for v in chain(self.data.domain.variables,
self.data.domain.metas)],
["{}-x".format(self.Variable_name[self.placement]),
"{}-y".format(self.Variable_name[self.placement])])
self.variable_x = ContinuousVariable(names[0])
self.variable_y = ContinuousVariable(names[1])
if self.placement in [self.Placement.Circular, self.Placement.LDA]:
variables = list(self.model_selected)
elif self.placement == self.Placement.Projection:
variables = self.model_selected[:] + self.model_other[:]
elif self.placement == self.Placement.PCA:
variables = [var for var in self.data.domain.attributes if var.is_continuous]
if not variables:
self.graph.new_data(None)
return
if self.placement == self.Placement.PCA:
valid_mask, ec, axes = self._get_pca()
variables = self._pca.orig_domain.attributes
else:
valid_mask, ec, axes = self.prepare_plot_data(variables)
self.plotdata.variables = variables
self.plotdata.valid_mask = valid_mask
self.plotdata.embedding_coords = ec
self.plotdata.axes = axes
if any(e is None for e in (valid_mask, ec, axes)):
return
if not sum(valid_mask):
self.Error.no_valid_data()
self.graph.new_data(None, None)
return
self.Error.no_valid_data.clear()
self._anchor_circle(variables=variables)
self._plot()
def _plot(self):
domain = self.data.domain
new_metas = domain.metas + (self.variable_x, self.variable_y)
domain = Domain(attributes=domain.attributes, class_vars=domain.class_vars, metas=new_metas)
valid_mask = self.plotdata.valid_mask
array = np.zeros((len(self.data), 2), dtype=np.float)
array[valid_mask] = self.plotdata.embedding_coords
self.plotdata.data = data = self.data.transform(domain)
data[:, self.variable_x] = array[:, 0].reshape(-1, 1)
data[:, self.variable_y] = array[:, 1].reshape(-1, 1)
subset_data = data[self._subset_mask & valid_mask]\
if self._subset_mask is not None and len(self._subset_mask) else None
self.plotdata.data = data
self.graph.new_data(data[valid_mask], subset_data)
if self._selection is not None:
self.graph.selection = self._selection[valid_mask]
self.graph.update_data(self.variable_x, self.variable_y, False)
def _get_lda(self, data, variables):
domain = Domain(attributes=variables, class_vars=data.domain.class_vars)
data = data.transform(domain)
lda = LinearDiscriminantAnalysis(solver='eigen', n_components=2)
lda.fit(data.X, data.Y)
scalings = lda.scalings_[:, :2].T
if scalings.shape == (1, 1):
scalings = np.array([[1.], [0.]])
return scalings
def _get_pca(self):
data = self.data
MAX_COMPONENTS = 2
ncomponents = 2
DECOMPOSITIONS = [PCA] # TruncatedSVD
cls = DECOMPOSITIONS[0]
pca_projector = cls(n_components=MAX_COMPONENTS)
pca_projector.component = ncomponents
pca_projector.preprocessors = cls.preprocessors + [Normalize()]
pca = pca_projector(data)
variance_ratio = pca.explained_variance_ratio_
cumulative = np.cumsum(variance_ratio)
self._pca = pca
if not np.isfinite(cumulative[-1]):
self.Warning.trivial_components()
coords = pca(data).X
valid_mask = ~np.isnan(coords).any(axis=1)
# scale axes
max_radius = np.min([np.abs(np.min(coords, axis=0)), np.max(coords, axis=0)])
axes = pca.components_.T.copy()
axes *= max_radius / np.max(np.linalg.norm(axes, axis=1))
return valid_mask, coords, axes
def _update_graph(self, reset_view=False):
self.graph.zoomStack = []
if self.graph.data is None:
return
self.graph.update_data(self.variable_x, self.variable_y, reset_view)
def update_density(self):
self._update_graph(reset_view=False)
def selection_changed(self):
if self.graph.selection is not None:
self._selection = np.zeros(len(self.data), dtype=np.uint8)
self._selection[self.plotdata.valid_mask] = self.graph.selection
self.selection_indices = self._selection.tolist()
else:
self._selection = self.selection_indices = None
self.commit()
def prepare_data(self):
pass
def commit(self):
def prepare_components():
if self.placement in [self.Placement.Circular, self.Placement.LDA]:
attrs = [a for a in self.model_selected[:]]
axes = self.plotdata.axes
elif self.placement == self.Placement.PCA:
axes = self._pca.components_.T
attrs = [a for a in self._pca.orig_domain.attributes]
if self.placement != self.Placement.Projection:
domain = Domain([ContinuousVariable(a.name, compute_value=lambda _: None)
for a in attrs],
metas=[StringVariable(name='component')])
metas = np.array([["{}{}".format(self.Component_name[self.placement], i + 1)
for i in range(axes.shape[1])]],
dtype=object).T
components = Table(domain, axes.T, metas=metas)
components.name = 'components'
else:
components = self.projection
return components
selected = annotated = components = None
if self.data is not None and self.plotdata.data is not None:
components = prepare_components()
graph = self.graph
mask = self.plotdata.valid_mask.astype(int)
mask[mask == 1] = graph.selection if graph.selection is not None \
else [False * len(mask)]
selection = np.array([], dtype=np.uint8) if mask is None else np.flatnonzero(mask)
name = self.data.name
data = self.plotdata.data
if len(selection):
selected = data[selection]
selected.name = name + ": selected"
selected.attributes = self.data.attributes
if graph.selection is not None and np.max(graph.selection) > 1:
annotated = create_groups_table(data, mask)
else:
annotated = create_annotated_table(data, selection)
annotated.attributes = self.data.attributes
annotated.name = name + ": annotated"
self.Outputs.selected_data.send(selected)
self.Outputs.annotated_data.send(annotated)
self.Outputs.components.send(components)
def send_report(self):
if self.data is None:
return
def name(var):
return var and var.name
def projection_name():
name = ("Circular Placement",
"Linear Discriminant Analysis",
"Principal Component Analysis",
"Input projection")
return name[self.placement]
caption = report.render_items_vert((
("Projection", projection_name()),
("Color", name(self.graph.attr_color)),
("Label", name(self.graph.attr_label)),
("Shape", name(self.graph.attr_shape)),
("Size", name(self.graph.attr_size)),
("Jittering", self.graph.jitter_size != 0 and "{} %".format(self.graph.jitter_size))))
self.report_plot()
if caption:
self.report_caption(caption)
@classmethod
def migrate_settings(cls, settings_, version):
if version < 2:
settings_["point_width"] = settings_["point_size"]
if version < 3:
settings_graph = {}
settings_graph["jitter_size"] = settings_["jitter_value"]
settings_graph["point_width"] = settings_["point_width"]
settings_graph["alpha_value"] = settings_["alpha_value"]
settings_graph["class_density"] = settings_["class_density"]
settings_["graph"] = settings_graph
@classmethod
def migrate_context(cls, context, version):
if version < 2:
domain = context.ordered_domain
c_domain = [t for t in context.ordered_domain if t[1] == 2]
d_domain = [t for t in context.ordered_domain if t[1] == 1]
for d, old_val, new_val in ((domain, "color_index", "attr_color"),
(d_domain, "shape_index", "attr_shape"),
(c_domain, "size_index", "attr_size")):
index = context.values[old_val][0] - 1
context.values[new_val] = (d[index][0], d[index][1] + 100) \
if 0 <= index < len(d) else None
if version < 3:
context.values["graph"] = {
"attr_color": context.values["attr_color"],
"attr_shape": context.values["attr_shape"],
"attr_size": context.values["attr_size"]
}
class OWLinearProjection(OWAnchorProjectionWidget):
name = "Linear Projection"
description = "A multi-axis projection of data onto " \
"a two-dimensional plane."
icon = "icons/LinearProjection.svg"
priority = 240
keywords = []
Placement = Enum("Placement", dict(Circular=0, LDA=1, PCA=2),
type=int, qualname="OWLinearProjection.Placement")
Projection_name = {Placement.Circular: "Circular Placement",
Placement.LDA: "Linear Discriminant Analysis",
Placement.PCA: "Principal Component Analysis"}
settings_version = 5
placement = Setting(Placement.Circular)
selected_vars = ContextSetting([])
vizrank = SettingProvider(LinearProjectionVizRank)
GRAPH_CLASS = OWLinProjGraph
graph = SettingProvider(OWLinProjGraph)
class Error(OWAnchorProjectionWidget.Error):
no_cont_features = Msg("Plotting requires numeric features")
def __init__(self):
self.model_selected = VariableListModel(enable_dnd=True)
self.model_selected.rowsInserted.connect(self.__model_selected_changed)
self.model_selected.rowsRemoved.connect(self.__model_selected_changed)
self.model_other = VariableListModel(enable_dnd=True)
self.vizrank, self.btn_vizrank = LinearProjectionVizRank.add_vizrank(
None, self, "Suggest Features", self.__vizrank_set_attrs)
super().__init__()
def _add_controls(self):
self._add_controls_variables()
self._add_controls_placement()
super()._add_controls()
self.graph.gui.add_control(
self._effects_box, gui.hSlider, "Hide radius:", master=self.graph,
value="hide_radius", minValue=0, maxValue=100, step=10,
createLabel=False, callback=self.__radius_slider_changed
)
self.controlArea.layout().removeWidget(self.control_area_stretch)
self.control_area_stretch.setParent(None)
def _add_controls_variables(self):
self.variables_selection = VariablesSelection(
self, self.model_selected, self.model_other, self.controlArea
)
self.variables_selection.add_remove.layout().addWidget(
self.btn_vizrank
)
def _add_controls_placement(self):
box = gui.widgetBox(
self.controlArea, True,
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Maximum)
)
self.radio_placement = gui.radioButtonsInBox(
box, self, "placement",
btnLabels=[self.Projection_name[x] for x in self.Placement],
callback=self.__placement_radio_changed
)
@property
def continuous_variables(self):
if self.data is None or self.data.domain is None:
return []
dom = self.data.domain
return [v for v in chain(dom.variables, dom.metas) if v.is_continuous]
@property
def effective_variables(self):
return self.model_selected[:]
def __vizrank_set_attrs(self, attrs):
if not attrs:
return
self.model_selected[:] = attrs[:]
self.model_other[:] = [var for var in self.continuous_variables
if var not in attrs]
def __model_selected_changed(self):
self.selected_vars = [(var.name, vartype(var)) for var
in self.model_selected]
self.projection = None
self._check_options()
self.init_projection()
self.setup_plot()
self.commit()
def __placement_radio_changed(self):
self.controls.graph.hide_radius.setEnabled(
self.placement != self.Placement.Circular)
self.projection = self.projector = None
self._init_vizrank()
self.init_projection()
self.setup_plot()
self.commit()
def __radius_slider_changed(self):
self.graph.update_radius()
def colors_changed(self):
super().colors_changed()
self._init_vizrank()
def set_data(self, data):
super().set_data(data)
if self.data is not None and len(self.selected_vars):
d, selected = self.data.domain, [v[0] for v in self.selected_vars]
self.model_selected[:] = [d[attr] for attr in selected]
self.model_other[:] = [d[attr.name] for attr in
self.continuous_variables
if attr.name not in selected]
elif self.data is not None:
self.model_selected[:] = self.continuous_variables[:3]
self.model_other[:] = self.continuous_variables[3:]
self._check_options()
self._init_vizrank()
def _check_options(self):
buttons = self.radio_placement.buttons
for btn in buttons:
btn.setEnabled(True)
if self.data is not None:
has_discrete_class = self.data.domain.has_discrete_class
if not has_discrete_class or len(np.unique(self.data.Y)) < 2:
buttons[self.Placement.LDA].setEnabled(False)
if self.placement == self.Placement.LDA:
self.placement = self.Placement.Circular
self.controls.graph.hide_radius.setEnabled(
self.placement != self.Placement.Circular)
def _init_vizrank(self):
is_enabled, msg = False, ""
if self.data is None:
msg = "There is no data."
elif self.attr_color is None:
msg = "Color variable has to be selected"
elif self.attr_color.is_continuous and \
self.placement == self.Placement.LDA:
msg = "Suggest Features does not work for Linear " \
"Discriminant Analysis Projection when " \
"continuous color variable is selected."
elif len([v for v in self.continuous_variables
if v is not self.attr_color]) < 3:
msg = "Not enough available continuous variables"
elif len(self.data[self.valid_data]) < 2:
msg = "Not enough valid data instances"
else:
is_enabled = not np.isnan(self.data.get_column_view(
self.attr_color)[0].astype(float)).all()
self.btn_vizrank.setToolTip(msg)
self.btn_vizrank.setEnabled(is_enabled)
if is_enabled:
self.vizrank.initialize()
def check_data(self):
def error(err):
err()
self.data = None
super().check_data()
if self.data is not None:
if not len(self.continuous_variables):
error(self.Error.no_cont_features)
def init_attr_values(self):
super().init_attr_values()
self.selected_vars = []
def init_projection(self):
if not len(self.effective_variables):
return
if self.placement == self.Placement.Circular:
self.projector = CircularPlacement()
elif self.placement == self.Placement.LDA:
self.projector = LDA(solver="eigen", n_components=2)
elif self.placement == self.Placement.PCA:
self.projector = PCA(n_components=2)
self.projector.component = 2
self.projector.preprocessors = PCA.preprocessors + [Normalize()]
super().init_projection()
def get_coordinates_data(self):
def normalized(a):
span = np.max(a, axis=0) - np.min(a, axis=0)
span[span == 0] = 1
return (a - np.mean(a, axis=0)) / span
embedding = self.get_embedding()
if embedding is None:
return None, None
norm_emb = normalized(embedding[self.valid_data])
return (norm_emb.ravel(), np.zeros(len(norm_emb), dtype=float)) \
if embedding.shape[1] == 1 else norm_emb.T
def _get_send_report_caption(self):
def projection_name():
return self.Projection_name[self.placement]
return report.render_items_vert((
("Projection", projection_name()),
("Color", self._get_caption_var_name(self.attr_color)),
("Label", self._get_caption_var_name(self.attr_label)),
("Shape", self._get_caption_var_name(self.attr_shape)),
("Size", self._get_caption_var_name(self.attr_size)),
("Jittering", self.graph.jitter_size != 0 and
"{} %".format(self.graph.jitter_size))))
def clear(self):
if self.model_selected:
self.model_selected.clear()
if self.model_other:
self.model_other.clear()
super().clear()
@classmethod
def migrate_settings(cls, settings_, version):
if version < 2:
settings_["point_width"] = settings_["point_size"]
if version < 3:
settings_graph = {}
settings_graph["jitter_size"] = settings_["jitter_value"]
settings_graph["point_width"] = settings_["point_width"]
settings_graph["alpha_value"] = settings_["alpha_value"]
settings_graph["class_density"] = settings_["class_density"]
settings_["graph"] = settings_graph
if version < 4:
if "radius" in settings_:
settings_["graph"]["hide_radius"] = settings_["radius"]
if "selection_indices" in settings_ and \
settings_["selection_indices"] is not None:
selection = settings_["selection_indices"]
settings_["selection"] = [(i, 1) for i, selected in
enumerate(selection) if selected]
if version < 5:
if "placement" in settings_ and \
settings_["placement"] not in cls.Placement:
settings_["placement"] = cls.Placement.Circular
@classmethod
def migrate_context(cls, context, version):
if version < 2:
domain = context.ordered_domain
c_domain = [t for t in context.ordered_domain if t[1] == 2]
d_domain = [t for t in context.ordered_domain if t[1] == 1]
for d, old_val, new_val in ((domain, "color_index", "attr_color"),
(d_domain, "shape_index", "attr_shape"),
(c_domain, "size_index", "attr_size")):
index = context.values[old_val][0] - 1
context.values[new_val] = (d[index][0], d[index][1] + 100) \
if 0 <= index < len(d) else None
if version < 3:
context.values["graph"] = {
"attr_color": context.values["attr_color"],
"attr_shape": context.values["attr_shape"],
"attr_size": context.values["attr_size"]
}
if version == 3:
values = context.values
values["attr_color"] = values["graph"]["attr_color"]
values["attr_size"] = values["graph"]["attr_size"]
values["attr_shape"] = values["graph"]["attr_shape"]
values["attr_label"] = values["graph"]["attr_label"]
def _add_controls(self):
self._value_var_model = VariableListModel()
sorted_model = SortProxyModel(sortRole=Qt.UserRole)
sorted_model.setSourceModel(self._value_var_model)
sorted_model.sort(0)
view = self._value_var_view = ListViewSearch()
view.setModel(sorted_model)
view.setMinimumSize(QSize(30, 100))
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
view.selectionModel().selectionChanged.connect(
self.__value_var_changed)
self._group_var_model = VariableListModel(placeholder="None")
sorted_model = SortProxyModel(sortRole=Qt.UserRole)
sorted_model.setSourceModel(self._group_var_model)
sorted_model.sort(0)
view = self._group_var_view = ListViewSearch()
view.setModel(sorted_model)
view.setMinimumSize(QSize(30, 100))
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
view.selectionModel().selectionChanged.connect(
self.__group_var_changed)
box = gui.vBox(self.controlArea, "Variable")
box.layout().addWidget(self._value_var_view)
gui.checkBox(box,
self,
"order_by_importance",
"Order by relevance to subgroups",
tooltip="Order by 𝜒² or ANOVA over the subgroups",
callback=self.apply_value_var_sorting)
box = gui.vBox(self.controlArea, "Subgroups")
box.layout().addWidget(self._group_var_view)
gui.checkBox(box,
self,
"order_grouping_by_importance",
"Order by relevance to variable",
tooltip="Order by 𝜒² or ANOVA over the variable values",
callback=self.apply_group_var_sorting)
box = gui.vBox(self.controlArea,
"Display",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Maximum))
gui.checkBox(box,
self,
"show_box_plot",
"Box plot",
callback=self.__show_box_plot_changed)
gui.checkBox(box,
self,
"show_strip_plot",
"Strip plot",
callback=self.__show_strip_plot_changed)
gui.checkBox(box,
self,
"show_rug_plot",
"Rug plot",
callback=self.__show_rug_plot_changed)
self._order_violins_cb = gui.checkBox(
box,
self,
"order_violins",
"Order subgroups",
callback=self.__order_violins_changed,
)
gui.radioButtons(box,
self,
"orientation_index", ["Horizontal", "Vertical"],
label="Orientation: ",
orientation=Qt.Horizontal,
callback=self.__orientation_changed)
box = gui.vBox(self.controlArea,
"Density Estimation",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Maximum))
gui.comboBox(box,
self,
"kernel_index",
items=self.KERNEL_LABELS,
label="Kernel:",
labelWidth=60,
orientation=Qt.Horizontal,
callback=self.__kernel_changed)
self._scale_combo = gui.comboBox(box,
self,
"scale_index",
items=self.SCALE_LABELS,
label="Scale:",
labelWidth=60,
orientation=Qt.Horizontal,
callback=self.__scale_changed)
def __init__(self):
super().__init__()
self.stats = []
self.dataset = None
self.posthoc_lines = []
self.label_txts = self.mean_labels = self.boxes = self.labels = \
self.label_txts_all = self.attr_labels = self.order = []
self.scale_x = self.scene_min_x = self.scene_width = 0
self.label_width = 0
self.attrs = VariableListModel()
view = gui.listView(
self.controlArea, self, "attribute", box="Variable",
model=self.attrs, callback=self.attr_changed)
view.setMinimumSize(QSize(30, 30))
# Any other policy than Ignored will let the QListBox's scrollbar
# set the minimal height (see the penultimate paragraph of
# http://doc.qt.io/qt-4.8/qabstractscrollarea.html#addScrollBarWidget)
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
gui.separator(view.box, 6, 6)
self.cb_order = gui.checkBox(
view.box, self, "order_by_importance",
"Order by relevance",
tooltip="Order by 𝜒² or ANOVA over the subgroups",
callback=self.apply_sorting)
self.group_vars = DomainModel(
placeholder="None", separators=False,
valid_types=Orange.data.DiscreteVariable)
self.group_view = view = gui.listView(
self.controlArea, self, "group_var", box="Subgroups",
model=self.group_vars, callback=self.grouping_changed)
view.setEnabled(False)
view.setMinimumSize(QSize(30, 30))
# See the comment above
view.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Ignored)
# TODO: move Compare median/mean to grouping box
# The vertical size policy is needed to let only the list views expand
self.display_box = gui.vBox(
self.controlArea, "Display",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Maximum),
addSpace=False)
gui.checkBox(self.display_box, self, "show_annotations", "Annotate",
callback=self.display_changed)
self.compare_rb = gui.radioButtonsInBox(
self.display_box, self, 'compare',
btnLabels=["No comparison", "Compare medians", "Compare means"],
callback=self.layout_changed)
# The vertical size policy is needed to let only the list views expand
self.stretching_box = box = gui.vBox(
self.controlArea, box="Display",
sizePolicy=(QSizePolicy.Minimum, QSizePolicy.Fixed))
self.stretching_box.sizeHint = self.display_box.sizeHint
gui.checkBox(
box, self, 'stretched', "Stretch bars",
callback=self.display_changed)
gui.checkBox(
box, self, 'show_labels', "Show box labels",
callback=self.display_changed)
self.sort_cb = gui.checkBox(
box, self, 'sort_freqs', "Sort by subgroup frequencies",
callback=self.display_changed)
gui.rubber(box)
gui.auto_commit(self.controlArea, self, "auto_commit",
"Send Selection", "Send Automatically")
gui.vBox(self.mainArea, addSpace=True)
self.box_scene = QGraphicsScene()
self.box_scene.selectionChanged.connect(self.commit)
self.box_view = QGraphicsView(self.box_scene)
self.box_view.setRenderHints(QPainter.Antialiasing |
QPainter.TextAntialiasing |
QPainter.SmoothPixmapTransform)
self.box_view.viewport().installEventFilter(self)
self.mainArea.layout().addWidget(self.box_view)
e = gui.hBox(self.mainArea, addSpace=False)
self.infot1 = gui.widgetLabel(e, "<center>No test results.</center>")
self.mainArea.setMinimumWidth(300)
self.stats = self.dist = self.conts = []
self.is_continuous = False
self.update_display_box()
class OWSpiralogram(widget.OWWidget):
name = 'Spiralogram'
description = "Visualize time series' periodicity in a spiral heatmap."
icon = 'icons/Spiralogram.svg'
priority = 120
inputs = [("Time series", Table, 'set_data')]
outputs = [("Time series", Timeseries)]
ax1 = settings.Setting('months of year')
ax2 = settings.Setting('years')
agg_attr = settings.Setting([])
agg_func = settings.Setting(0)
def __init__(self):
self.data = None
self.indices = []
box = gui.vBox(self.controlArea, 'Axes')
self.combo_ax2 = gui.comboBox(
box, self, 'ax2', label='Y axis:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal')
self.combo_ax1 = gui.comboBox(
box, self, 'ax1', label='Radial:', callback=self.replot,
sendSelectedValue=True, orientation='horizontal')
box = gui.vBox(self.controlArea, 'Aggregation')
self.combo_func = gui.comboBox(
box, self, 'agg_func', label='Function:', orientation='horizontal',
callback=self.replot)
func_model = ListModel(AGG_FUNCTIONS, parent=self)
self.combo_func.setModel(func_model)
self.attrlist_model = VariableListModel(parent=self)
self.attrlist = QListView(selectionMode=QListView.ExtendedSelection)
self.attrlist.setModel(self.attrlist_model)
self.attrlist.selectionModel().selectionChanged.connect(
self.attrlist_selectionChanged)
box.layout().addWidget(self.attrlist)
gui.rubber(self.controlArea)
self.chart = chart = Spiralogram(self,
selection_callback=self.on_selection)
self.mainArea.layout().addWidget(chart)
def attrlist_selectionChanged(self):
self.agg_attr = [self.attrlist_model[i.row()]
for i in self.attrlist.selectionModel().selectedIndexes()]
self.replot()
def set_data(self, data):
self.data = data = None if data is None else Timeseries.from_data_table(data)
def init_combos():
for combo in (self.combo_ax1, self.combo_ax2):
combo.clear()
self.attrlist_model[:] = []
for i in Spiralogram.AxesCategories:
for combo in (self.combo_ax1, self.combo_ax2):
combo.addItem(_enum_str(i))
for var in data.domain if data is not None else []:
if (var.is_primitive() and
(var is not data.time_variable or
isinstance(var, TimeVariable) and data.time_delta is None)):
self.attrlist_model.append(var)
if var.is_discrete:
for combo in (self.combo_ax1, self.combo_ax2):
combo.addItem(gui.attributeIconDict[var], var.name)
init_combos()
self.chart.clear()
if data is None:
self.commit()
return
self.ax1 = 'months of year'
self.ax2 = 'years'
self.replot()
def replot(self):
vars = self.agg_attr
func = AGG_FUNCTIONS[self.agg_func]
# TODO test discrete
if any(var.is_discrete for var in vars) and func != Mode:
self.combo_func.setCurrentIndex(AGG_FUNCTIONS.index(Mode))
return
try:
ax1 = Spiralogram.AxesCategories[_enum_str(self.ax1, True)]
except KeyError:
ax1 = self.data.domain[self.ax1]
# TODO: Allow having only a sinle (i.e. radial) axis
try:
ax2 = Spiralogram.AxesCategories[_enum_str(self.ax2, True)]
except KeyError:
ax2 = self.data.domain[self.ax2]
self.chart.setSeries(self.data, vars, ax1, ax2, func)
def on_selection(self, indices):
self.indices = self.chart.selection_indices(indices)
self.commit()
def commit(self):
self.send('Time series', self.data[self.indices] if self.data else None)
class OWRadviz(widget.OWWidget):
name = "Radviz"
description = "Radviz"
icon = "icons/Radviz.svg"
priority = 240
class Inputs:
data = Input("Data", Table, default=True)
data_subset = Input("Data Subset", Table)
class Outputs:
selected_data = Output("Selected Data", Table, default=True)
annotated_data = Output(ANNOTATED_DATA_SIGNAL_NAME, Table)
components = Output("Components", Table)
settings_version = 1
settingsHandler = settings.DomainContextHandler()
variable_state = settings.ContextSetting({})
auto_commit = settings.Setting(True)
graph = settings.SettingProvider(OWRadvizGraph)
vizrank = settings.SettingProvider(RadvizVizRank)
jitter_sizes = [0, 0.1, 0.5, 1.0, 2.0]
ReplotRequest = QEvent.registerEventType()
graph_name = "graph.plot_widget.plotItem"
class Information(widget.OWWidget.Information):
sql_sampled_data = widget.Msg("Data has been sampled")
class Warning(widget.OWWidget.Warning):
no_features = widget.Msg("At least 2 features have to be chosen")
class Error(widget.OWWidget.Error):
sparse_data = widget.Msg("Sparse data is not supported")
no_features = widget.Msg("At least 3 numeric or categorical variables are required")
no_instances = widget.Msg("At least 2 data instances are required")
def __init__(self):
super().__init__()
self.data = None
self.subset_data = None
self._subset_mask = None
self._selection = None # np.array
self.__replot_requested = False
self._new_plotdata()
self.variable_x = ContinuousVariable("radviz-x")
self.variable_y = ContinuousVariable("radviz-y")
box = gui.vBox(self.mainArea, True, margin=0)
self.graph = OWRadvizGraph(self, box, "Plot", view_box=RadvizInteractiveViewBox)
self.graph.hide_axes()
box.layout().addWidget(self.graph.plot_widget)
plot = self.graph.plot_widget
SIZE_POLICY = (QSizePolicy.Minimum, QSizePolicy.Maximum)
self.variables_selection = VariablesSelection()
self.model_selected = VariableListModel(enable_dnd=True)
self.model_other = VariableListModel(enable_dnd=True)
self.variables_selection(self, self.model_selected, self.model_other)
self.vizrank, self.btn_vizrank = RadvizVizRank.add_vizrank(
self.controlArea, self, "Suggest features", self.vizrank_set_attrs)
self.btn_vizrank.setSizePolicy(*SIZE_POLICY)
self.variables_selection.add_remove.layout().addWidget(self.btn_vizrank)
self.viewbox = plot.getViewBox()
self.replot = None
g = self.graph.gui
pp_box = g.point_properties_box(self.controlArea)
pp_box.setSizePolicy(*SIZE_POLICY)
self.models = g.points_models
box = gui.vBox(self.controlArea, "Plot Properties")
box.setSizePolicy(*SIZE_POLICY)
g.add_widget(g.JitterSizeSlider, box)
g.add_widgets([g.ShowLegend, g.ClassDensity, g.LabelOnlySelected], box)
zoom_select = self.graph.box_zoom_select(self.controlArea)
zoom_select.setSizePolicy(*SIZE_POLICY)
self.icons = gui.attributeIconDict
p = self.graph.plot_widget.palette()
self.graph.set_palette(p)
gui.auto_commit(self.controlArea, self, "auto_commit", "Send Selection",
auto_label="Send Automatically")
self.graph.zoom_actions(self)
self._circle = QGraphicsEllipseItem()
self._circle.setRect(QRectF(-1., -1., 2., 2.))
self._circle.setPen(pg.mkPen(QColor(0, 0, 0), width=2))
def resizeEvent(self, event):
self._update_points_labels()
def keyPressEvent(self, event):
super().keyPressEvent(event)
self.graph.update_tooltip(event.modifiers())
def keyReleaseEvent(self, event):
super().keyReleaseEvent(event)
self.graph.update_tooltip(event.modifiers())
def vizrank_set_attrs(self, attrs):
if not attrs:
return
self.variables_selection.display_none()
self.model_selected[:] = attrs[:]
self.model_other[:] = [v for v in self.model_other if v not in attrs]
def _new_plotdata(self):
self.plotdata = namespace(
valid_mask=None,
embedding_coords=None,
points=None,
arcarrows=[],
point_labels=[],
rand=None,
data=None,
)
def update_colors(self):
self._vizrank_color_change()
self.cb_class_density.setEnabled(self.graph.can_draw_density())
def sizeHint(self):
return QSize(800, 500)
def clear(self):
"""
Clear/reset the widget state
"""
self.data = None
self.model_selected.clear()
self.model_other.clear()
self._clear_plot()
def _clear_plot(self):
self._new_plotdata()
self.graph.plot_widget.clear()
def invalidate_plot(self):
"""
Schedule a delayed replot.
"""
if not self.__replot_requested:
self.__replot_requested = True
QApplication.postEvent(self, QEvent(self.ReplotRequest), Qt.LowEventPriority - 10)
def init_attr_values(self):
self.graph.set_domain(self.data)
def _vizrank_color_change(self):
attr_color = self.graph.attr_color
is_enabled = self.data is not None and not self.data.is_sparse() and \
(len(self.model_other) + len(self.model_selected)) > 3 and len(self.data) > 1
self.btn_vizrank.setEnabled(
is_enabled and attr_color is not None
and not np.isnan(self.data.get_column_view(attr_color)[0].astype(float)).all())
self.vizrank.initialize()
@Inputs.data
def set_data(self, data):
"""
Set the input dataset and check if data is valid.
Args:
data (Orange.data.table): data instances
"""
def sql(data):
self.Information.sql_sampled_data.clear()
if isinstance(data, SqlTable):
if data.approx_len() < 4000:
data = Table(data)
else:
self.Information.sql_sampled_data()
data_sample = data.sample_time(1, no_cache=True)
data_sample.download_data(2000, partial=True)
data = Table(data_sample)
return data
def settings(data):
# get the default encoded state, replacing the position with Inf
state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
state = {key: (source_ind, np.inf) for key, (source_ind, _) in state.items()}
self.openContext(data.domain)
selected_keys = [key
for key, (sind, _) in self.variable_state.items()
if sind == 0]
if set(selected_keys).issubset(set(state.keys())):
pass
# update the defaults state (the encoded state must contain
# all variables in the input domain)
state.update(self.variable_state)
# ... and restore it with saved positions taking precedence over
# the defaults
selected, other = VariablesSelection.decode_var_state(
state, [list(self.model_selected), list(self.model_other)])
return selected, other
def is_sparse(data):
if data.is_sparse():
self.Error.sparse_data()
data = None
return data
def are_features(data):
domain = data.domain
vars = [var for var in chain(domain.class_vars, domain.metas, domain.attributes)
if var.is_primitive()]
if len(vars) < 3:
self.Error.no_features()
data = None
return data
def are_instances(data):
if len(data) < 2:
self.Error.no_instances()
data = None
return data
self.clear_messages()
self.btn_vizrank.setEnabled(False)
self.closeContext()
self.clear()
self.information()
self.Error.clear()
for f in [sql, is_sparse, are_features, are_instances]:
if data is None:
break
data = f(data)
if data is not None:
self.data = data
self.init_attr_values()
domain = data.domain
vars = [v for v in chain(domain.metas, domain.attributes)
if v.is_primitive()]
self.model_selected[:] = vars[:5]
self.model_other[:] = vars[5:] + list(domain.class_vars)
self.model_selected[:], self.model_other[:] = settings(data)
self._selection = np.zeros(len(data), dtype=np.uint8)
self.invalidate_plot()
else:
self.data = None
@Inputs.data_subset
def set_subset_data(self, subset):
"""
Set the supplementary input subset dataset.
Args:
subset (Orange.data.table): subset of data instances
"""
self.subset_data = subset
self._subset_mask = None
self.controls.graph.alpha_value.setEnabled(subset is None)
def handleNewSignals(self):
if self.data is not None:
self._clear_plot()
if self.subset_data is not None and self._subset_mask is None:
dataids = self.data.ids.ravel()
subsetids = np.unique(self.subset_data.ids)
self._subset_mask = np.in1d(
dataids, subsetids, assume_unique=True)
self.setup_plot(reset_view=True)
self.cb_class_density.setEnabled(self.graph.can_draw_density())
else:
self.init_attr_values()
self.graph.new_data(None)
self._vizrank_color_change()
self.commit()
def customEvent(self, event):
if event.type() == OWRadviz.ReplotRequest:
self.__replot_requested = False
self._clear_plot()
self.setup_plot(reset_view=True)
else:
super().customEvent(event)
def closeContext(self):
self.variable_state = VariablesSelection.encode_var_state(
[list(self.model_selected), list(self.model_other)]
)
super().closeContext()
def prepare_radviz_data(self, variables):
ec, points, valid_mask = radviz(self.data, variables, self.plotdata.points)
self.plotdata.embedding_coords = ec
self.plotdata.points = points
self.plotdata.valid_mask = valid_mask
def setup_plot(self, reset_view=True):
if self.data is None:
return
self.graph.jitter_continuous = True
self.__replot_requested = False
variables = list(self.model_selected)
if len(variables) < 2:
self.Warning.no_features()
self.graph.new_data(None)
return
self.Warning.clear()
self.prepare_radviz_data(variables)
if self.plotdata.embedding_coords is None:
return
domain = self.data.domain
new_metas = domain.metas + (self.variable_x, self.variable_y)
domain = Domain(attributes=domain.attributes,
class_vars=domain.class_vars,
metas=new_metas)
mask = self.plotdata.valid_mask
array = np.zeros((len(self.data), 2), dtype=np.float)
array[mask] = self.plotdata.embedding_coords
data = self.data.transform(domain)
data[:, self.variable_x] = array[:, 0].reshape(-1, 1)
data[:, self.variable_y] = array[:, 1].reshape(-1, 1)
subset_data = data[self._subset_mask & mask]\
if self._subset_mask is not None and len(self._subset_mask) else None
self.plotdata.data = data
self.graph.new_data(data[mask], subset_data)
if self._selection is not None:
self.graph.selection = self._selection[self.plotdata.valid_mask]
self.graph.update_data(self.variable_x, self.variable_y, reset_view=reset_view)
self.graph.plot_widget.addItem(self._circle)
self.graph.scatterplot_points = ScatterPlotItem(
x=self.plotdata.points[:, 0],
y=self.plotdata.points[:, 1]
)
self._update_points_labels()
self.graph.plot_widget.addItem(self.graph.scatterplot_points)
def randomize_indices(self):
ec = self.plotdata.embedding_coords
self.plotdata.rand = np.random.choice(len(ec), MAX_POINTS, replace=False) \
if len(ec) > MAX_POINTS else None
def manual_move(self):
self.__replot_requested = False
if self.plotdata.rand is not None:
rand = self.plotdata.rand
valid_mask = self.plotdata.valid_mask
data = self.data[valid_mask]
selection = self._selection[valid_mask]
selection = selection[rand]
ec, _, valid_mask = radviz(data, list(self.model_selected), self.plotdata.points)
assert sum(valid_mask) == len(data)
data = data[rand]
ec = ec[rand]
data_x = data.X
data_y = data.Y
data_metas = data.metas
else:
self.prepare_radviz_data(list(self.model_selected))
ec = self.plotdata.embedding_coords
valid_mask = self.plotdata.valid_mask
data_x = self.data.X[valid_mask]
data_y = self.data.Y[valid_mask]
data_metas = self.data.metas[valid_mask]
selection = self._selection[valid_mask]
attributes = (self.variable_x, self.variable_y) + self.data.domain.attributes
domain = Domain(attributes=attributes,
class_vars=self.data.domain.class_vars,
metas=self.data.domain.metas)
data = Table.from_numpy(domain, X=np.hstack((ec, data_x)), Y=data_y, metas=data_metas)
self.graph.new_data(data, None)
self.graph.selection = selection
self.graph.update_data(self.variable_x, self.variable_y, reset_view=True)
self.graph.plot_widget.addItem(self._circle)
self.graph.scatterplot_points = ScatterPlotItem(
x=self.plotdata.points[:, 0], y=self.plotdata.points[:, 1])
self._update_points_labels()
self.graph.plot_widget.addItem(self.graph.scatterplot_points)
def _update_points_labels(self):
if self.plotdata.points is None:
return
for point_label in self.plotdata.point_labels:
self.graph.plot_widget.removeItem(point_label)
self.plotdata.point_labels = []
sx, sy = self.graph.view_box.viewPixelSize()
for row in self.plotdata.points:
ti = TextItem()
metrics = QFontMetrics(ti.textItem.font())
text_width = ((RANGE.width())/2. - np.abs(row[0])) / sx
name = row[2].name
ti.setText(name)
ti.setTextWidth(text_width)
ti.setColor(QColor(0, 0, 0))
br = ti.boundingRect()
width = metrics.width(name) if metrics.width(name) < br.width() else br.width()
width = sx * (width + 5)
height = sy * br.height()
ti.setPos(row[0] - (row[0] < 0) * width, row[1] + (row[1] > 0) * height)
self.plotdata.point_labels.append(ti)
self.graph.plot_widget.addItem(ti)
def _update_jitter(self):
self.invalidate_plot()
def reset_graph_data(self, *_):
if self.data is not None:
self.graph.rescale_data()
self._update_graph()
def _update_graph(self, reset_view=True, **_):
self.graph.zoomStack = []
if self.graph.data is None:
return
self.graph.update_data(self.variable_x, self.variable_y, reset_view=reset_view)
def update_density(self):
self._update_graph(reset_view=True)
def selection_changed(self):
if self.graph.selection is not None:
self._selection[self.plotdata.valid_mask] = self.graph.selection
self.commit()
def prepare_data(self):
pass
def commit(self):
selected = annotated = components = None
graph = self.graph
if self.plotdata.data is not None:
name = self.data.name
data = self.plotdata.data
mask = self.plotdata.valid_mask.astype(int)
mask[mask == 1] = graph.selection if graph.selection is not None \
else [False * len(mask)]
selection = np.array([], dtype=np.uint8) if mask is None else np.flatnonzero(mask)
if len(selection):
selected = data[selection]
selected.name = name + ": selected"
selected.attributes = self.data.attributes
if graph.selection is not None and np.max(graph.selection) > 1:
annotated = create_groups_table(data, mask)
else:
annotated = create_annotated_table(data, selection)
annotated.attributes = self.data.attributes
annotated.name = name + ": annotated"
comp_domain = Domain(
self.plotdata.points[:, 2],
metas=[StringVariable(name='component')])
metas = np.array([["RX"], ["RY"], ["angle"]])
angle = np.arctan2(np.array(self.plotdata.points[:, 1].T, dtype=float),
np.array(self.plotdata.points[:, 0].T, dtype=float))
components = Table.from_numpy(
comp_domain,
X=np.row_stack((self.plotdata.points[:, :2].T, angle)),
metas=metas)
components.name = name + ": components"
self.Outputs.selected_data.send(selected)
self.Outputs.annotated_data.send(annotated)
self.Outputs.components.send(components)
def send_report(self):
if self.data is None:
return
def name(var):
return var and var.name
caption = report.render_items_vert((
("Color", name(self.graph.attr_color)),
("Label", name(self.graph.attr_label)),
("Shape", name(self.graph.attr_shape)),
("Size", name(self.graph.attr_size)),
("Jittering", self.graph.jitter_size != 0 and "{} %".format(self.graph.jitter_size))))
self.report_plot()
if caption:
self.report_caption(caption)
def __init__(self):
super().__init__()
self.data = None
self.subset_data = None
self._subset_mask = None
self._selection = None # np.array
self.__replot_requested = False
self._new_plotdata()
self.variable_x = ContinuousVariable("radviz-x")
self.variable_y = ContinuousVariable("radviz-y")
box = gui.vBox(self.mainArea, True, margin=0)
self.graph = OWRadvizGraph(self, box, "Plot", view_box=RadvizInteractiveViewBox)
self.graph.hide_axes()
box.layout().addWidget(self.graph.plot_widget)
plot = self.graph.plot_widget
SIZE_POLICY = (QSizePolicy.Minimum, QSizePolicy.Maximum)
self.variables_selection = VariablesSelection()
self.model_selected = VariableListModel(enable_dnd=True)
self.model_other = VariableListModel(enable_dnd=True)
self.variables_selection(self, self.model_selected, self.model_other)
self.vizrank, self.btn_vizrank = RadvizVizRank.add_vizrank(
self.controlArea, self, "Suggest features", self.vizrank_set_attrs)
self.btn_vizrank.setSizePolicy(*SIZE_POLICY)
self.variables_selection.add_remove.layout().addWidget(self.btn_vizrank)
self.viewbox = plot.getViewBox()
self.replot = None
g = self.graph.gui
pp_box = g.point_properties_box(self.controlArea)
pp_box.setSizePolicy(*SIZE_POLICY)
self.models = g.points_models
box = gui.vBox(self.controlArea, "Plot Properties")
box.setSizePolicy(*SIZE_POLICY)
g.add_widget(g.JitterSizeSlider, box)
g.add_widgets([g.ShowLegend, g.ClassDensity, g.LabelOnlySelected], box)
zoom_select = self.graph.box_zoom_select(self.controlArea)
zoom_select.setSizePolicy(*SIZE_POLICY)
self.icons = gui.attributeIconDict
p = self.graph.plot_widget.palette()
self.graph.set_palette(p)
gui.auto_commit(self.controlArea, self, "auto_commit", "Send Selection",
auto_label="Send Automatically")
self.graph.zoom_actions(self)
self._circle = QGraphicsEllipseItem()
self._circle.setRect(QRectF(-1., -1., 2., 2.))
self._circle.setPen(pg.mkPen(QColor(0, 0, 0), width=2))
class OWRadviz(OWAnchorProjectionWidget):
name = "Radviz"
description = "Display Radviz projection"
icon = "icons/Radviz.svg"
priority = 241
keywords = ["viz"]
settings_version = 2
selected_vars = ContextSetting([])
vizrank = SettingProvider(RadvizVizRank)
GRAPH_CLASS = OWRadvizGraph
graph = SettingProvider(OWRadvizGraph)
class Warning(OWAnchorProjectionWidget.Warning):
no_features = widget.Msg("Radviz requires at least two features.")
invalid_embedding = widget.Msg("No projection for selected features")
removed_vars = widget.Msg("Categorical variables with more than"
" two values are not shown.")
class Error(OWAnchorProjectionWidget.Error):
no_features = widget.Msg(
"At least three numeric or categorical variables are required"
)
def __init__(self):
self.model_selected = VariableListModel(enable_dnd=True)
self.model_selected.rowsInserted.connect(self.__model_selected_changed)
self.model_selected.rowsRemoved.connect(self.__model_selected_changed)
self.model_other = VariableListModel(enable_dnd=True)
self.vizrank, self.btn_vizrank = RadvizVizRank.add_vizrank(
None, self, "Suggest features", self.__vizrank_set_attrs
)
super().__init__()
def _add_controls(self):
self.variables_selection = VariablesSelection(
self, self.model_selected, self.model_other, self.controlArea
)
self.variables_selection.add_remove.layout().addWidget(
self.btn_vizrank
)
super()._add_controls()
self.controlArea.layout().removeWidget(self.control_area_stretch)
self.control_area_stretch.setParent(None)
@property
def primitive_variables(self):
if self.data is None or self.data.domain is None:
return []
dom = self.data.domain
return [v for v in chain(dom.variables, dom.metas)
if v.is_continuous or v.is_discrete and len(v.values) == 2]
@property
def effective_variables(self):
return self.model_selected[:]
def __vizrank_set_attrs(self, attrs):
if not attrs:
return
self.model_selected[:] = attrs[:]
self.model_other[:] = [var for var in self.primitive_variables
if var not in attrs]
def __model_selected_changed(self):
self.selected_vars = [(var.name, vartype(var)) for var
in self.model_selected]
self.Warning.no_features.clear()
if len(self.model_selected) < 2:
self.Warning.no_features()
return
self.init_projection()
self.setup_plot()
self.commit()
def colors_changed(self):
super().colors_changed()
self._init_vizrank()
def set_data(self, data):
super().set_data(data)
if self.data is not None and len(self.selected_vars):
d, selected = self.data.domain, [v[0] for v in self.selected_vars]
self.model_selected[:] = [d[name] for name in selected]
self.model_other[:] = [d[attr.name] for attr in
self.primitive_variables
if attr.name not in selected]
elif self.data is not None:
d, variables = self.data.domain, self.primitive_variables
class_var = [variables.pop(variables.index(d.class_var))] \
if d.class_var in variables else []
self.model_selected[:] = variables[:5]
self.model_other[:] = variables[5:] + class_var
self._init_vizrank()
def _init_vizrank(self):
is_enabled = self.data is not None and \
len(self.primitive_variables) > 3 and \
self.attr_color is not None and \
not np.isnan(self.data.get_column_view(
self.attr_color)[0].astype(float)).all() and \
len(self.data[self.valid_data]) > 1 and \
np.all(np.nan_to_num(np.nanstd(self.data.X, 0)) != 0)
self.btn_vizrank.setEnabled(is_enabled)
if is_enabled:
self.vizrank.initialize()
def check_data(self):
def error(err):
err()
self.data = None
super().check_data()
if self.data is not None:
if len(self.primitive_variables) < 3:
error(self.Error.no_features)
else:
domain = self.data.domain
vars_ = chain(domain.variables, domain.metas)
n_vars = sum(v.is_primitive() for v in vars_)
if len(self.primitive_variables) < n_vars:
self.Warning.removed_vars()
def init_attr_values(self):
super().init_attr_values()
self.selected_vars = []
def _manual_move(self, anchor_idx, x, y):
angle = np.arctan2(y, x)
super()._manual_move(anchor_idx, np.cos(angle), np.sin(angle))
def _send_components_x(self):
components_ = super()._send_components_x()
angle = np.arctan2(*components_[::-1])
return np.row_stack((components_, angle))
def _send_components_metas(self):
return np.vstack((super()._send_components_metas(), ["angle"]))
def clear(self):
if self.model_selected:
self.model_selected.clear()
if self.model_other:
self.model_other.clear()
super().clear()
self.projector = RadViz()
@classmethod
def migrate_context(cls, context, version):
if version < 2:
values = context.values
values["attr_color"] = values["graph"]["attr_color"]
values["attr_size"] = values["graph"]["attr_size"]
values["attr_shape"] = values["graph"]["attr_shape"]
values["attr_label"] = values["graph"]["attr_label"]
