def __init__(self):
super().__init__()
self.data = None
self.distributions = None
self.contingencies = None
self.var = self.cvar = None
varbox = gui.widgetBox(self.controlArea, "Variable")
self.varmodel = itemmodels.VariableListModel()
self.groupvarmodel = []
self.varview = QtGui.QListView(
selectionMode=QtGui.QListView.SingleSelection)
self.varview.setSizePolicy(QtGui.QSizePolicy.Minimum,
QtGui.QSizePolicy.Expanding)
self.varview.setModel(self.varmodel)
self.varview.setSelectionModel(
itemmodels.ListSingleSelectionModel(self.varmodel))
self.varview.selectionModel().selectionChanged.connect(
self._on_variable_idx_changed)
varbox.layout().addWidget(self.varview)
box = gui.widgetBox(self.controlArea, "Precision")
gui.separator(self.controlArea, 4, 4)
box2 = gui.widgetBox(box, orientation="horizontal")
self.l_smoothing_l = gui.widgetLabel(box2, "Smooth")
gui.hSlider(box2,
self,
"smoothing_index",
minValue=0,
maxValue=len(self.smoothing_facs) - 1,
callback=self._on_set_smoothing,
createLabel=False)
self.l_smoothing_r = gui.widgetLabel(box2, "Precise")
self.cb_disc_cont = gui.checkBox(
gui.indentedBox(box, sep=4),
self,
"disc_cont",
"Bin continuous variables",
callback=self._on_groupvar_idx_changed,
tooltip="Show continuous variables as discrete.")
box = gui.widgetBox(self.controlArea, "Group by")
self.icons = gui.attributeIconDict
self.groupvarview = gui.comboBox(
box,
self,
"groupvar_idx",
callback=self._on_groupvar_idx_changed,
valueType=str,
contentsLength=12)
box2 = gui.indentedBox(box, sep=4)
self.cb_rel_freq = gui.checkBox(
box2,
self,
"relative_freq",
"Show relative frequencies",
callback=self._on_relative_freq_changed,
tooltip=
"Normalize probabilities so that probabilities for each group-by value sum to 1."
)
gui.separator(box2)
self.cb_prob = gui.comboBox(
box2,
self,
"show_prob",
label="Show probabilities",
orientation="horizontal",
callback=self._on_relative_freq_changed,
tooltip=
"Show probabilities for a chosen group-by value (at each point probabilities for all group-by values sum to 1)."
)
self.plotview = pg.PlotWidget(background=None)
self.plotview.setRenderHint(QtGui.QPainter.Antialiasing)
self.mainArea.layout().addWidget(self.plotview)
w = QtGui.QLabel()
w.setSizePolicy(QtGui.QSizePolicy.Expanding, QtGui.QSizePolicy.Fixed)
self.mainArea.layout().addWidget(w, Qt.AlignCenter)
self.ploti = pg.PlotItem()
self.plot = self.ploti.vb
self.ploti.hideButtons()
self.plotview.setCentralItem(self.ploti)
self.plot_prob = pg.ViewBox()
self.ploti.hideAxis('right')
self.ploti.scene().addItem(self.plot_prob)
self.ploti.getAxis("right").linkToView(self.plot_prob)
self.ploti.getAxis("right").setLabel("Probability")
self.plot_prob.setZValue(10)
self.plot_prob.setXLink(self.ploti)
self.update_views()
self.ploti.vb.sigResized.connect(self.update_views)
self.plot_prob.setRange(yRange=[0, 1])
self.inline_graph_report()
def disable_mouse(plot):
plot.setMouseEnabled(False, False)
plot.setMenuEnabled(False)
disable_mouse(self.plot)
disable_mouse(self.plot_prob)
self.tooltip_items = []
self.plot.scene().installEventFilter(
HelpEventDelegate(self.help_event, self))
pen = QtGui.QPen(self.palette().color(QtGui.QPalette.Text))
for axis in ("left", "bottom"):
self.ploti.getAxis(axis).setPen(pen)
self._legend = LegendItem()
self._legend.setParentItem(self.plot)
self._legend.hide()
self._legend.anchor((1, 0), (1, 0))
def _setup_plot(self):
have_data = self.data is not None
have_matrix_transposed = self.matrix is not None and not self.matrix.axis
plotstyle = mdsplotutils.plotstyle
size = self._effective_matrix.shape[0]
def column(data, variable):
a, _ = data.get_column_view(variable)
return a.ravel()
def attributes(matrix):
return matrix.row_items.domain.attributes
def scale(a):
dmin, dmax = numpy.nanmin(a), numpy.nanmax(a)
if dmax - dmin > 0:
return (a - dmin) / (dmax - dmin)
else:
return numpy.zeros_like(a)
def jitter(x, factor=1, rstate=None):
if rstate is None:
rstate = numpy.random.RandomState()
elif not isinstance(rstate, numpy.random.RandomState):
rstate = numpy.random.RandomState(rstate)
span = numpy.nanmax(x) - numpy.nanmin(x)
if span < numpy.finfo(x.dtype).eps * 100:
span = 1
a = factor * span / 100.
return x + (rstate.random_sample(x.shape) - 0.5) * a
if self._pen_data is None:
if self._selection_mask is not None:
pointflags = numpy.where(
self._selection_mask,
mdsplotutils.Selected, mdsplotutils.NoFlags)
else:
pointflags = None
color_index = self.cb_color_value.currentIndex()
if have_data and color_index > 0:
color_var = self.colorvar_model[color_index]
if color_var.is_discrete:
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values)
)
plotstyle = plotstyle.updated(discrete_palette=palette)
else:
palette = None
color_data = mdsplotutils.color_data(
self.data, color_var, plotstyle=plotstyle)
color_data = numpy.hstack(
(color_data,
numpy.full((len(color_data), 1), self.symbol_opacity,
dtype=float))
)
pen_data = mdsplotutils.pen_data(color_data * 0.8, pointflags)
brush_data = mdsplotutils.brush_data(color_data)
elif have_matrix_transposed and \
self.colorvar_model[color_index] == 'Attribute names':
attr = attributes(self.matrix)
palette = colorpalette.ColorPaletteGenerator(len(attr))
color_data = [palette.getRGB(i) for i in range(len(attr))]
color_data = numpy.hstack((
color_data,
numpy.full((len(color_data), 1), self.symbol_opacity,
dtype=float))
)
pen_data = mdsplotutils.pen_data(color_data * 0.8, pointflags)
brush_data = mdsplotutils.brush_data(color_data)
else:
pen_data = make_pen(QtGui.QColor(Qt.darkGray), cosmetic=True)
if self._selection_mask is not None:
pen_data = numpy.array(
[pen_data, plotstyle.selected_pen])
pen_data = pen_data[self._selection_mask.astype(int)]
else:
pen_data = numpy.full(self._effective_matrix.dim, pen_data,
dtype=object)
brush_data = numpy.full(
size, pg.mkColor((192, 192, 192, self.symbol_opacity)),
dtype=object)
if self._subset_mask is not None and have_data and \
self._subset_mask.shape == (size, ):
# clear brush fill for non subset data
brush_data[~self._subset_mask] = QtGui.QBrush(Qt.NoBrush)
self._pen_data = pen_data
self._brush_data = brush_data
if self._shape_data is None:
shape_index = self.cb_shape_value.currentIndex()
if have_data and shape_index > 0:
Symbols = ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[shape_index]
data = column(self.data, shape_var).astype(numpy.float)
data = data % (len(Symbols) - 1)
data[numpy.isnan(data)] = len(Symbols) - 1
shape_data = symbols[data.astype(int)]
elif have_matrix_transposed and \
self.shapevar_model[shape_index] == 'Attribute names':
Symbols = ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
attr = [i % (len(Symbols) - 1)
for i, _ in enumerate(attributes(self.matrix))]
shape_data = symbols[attr]
else:
shape_data = "o"
self._shape_data = shape_data
if self._size_data is None:
MinPointSize = 3
point_size = self.symbol_size + MinPointSize
size_index = self.cb_size_value.currentIndex()
if have_data and size_index == 1:
# size by stress
size_data = stress(self.embedding, self._effective_matrix)
size_data = scale(size_data)
size_data = MinPointSize + size_data * point_size
elif have_data and size_index > 0:
size_var = self.sizevar_model[size_index]
size_data = column(self.data, size_var)
size_data = scale(size_data)
size_data = MinPointSize + size_data * point_size
else:
size_data = point_size
self._size_data = size_data
if self._label_data is None:
label_index = self.cb_label_value.currentIndex()
if have_data and label_index > 0:
label_var = self.labelvar_model[label_index]
label_data = column(self.data, label_var)
label_data = [label_var.str_val(val) for val in label_data]
label_items = [pg.TextItem(text, anchor=(0.5, 0), color=0.0)
for text in label_data]
elif have_matrix_transposed and \
self.labelvar_model[label_index] == 'Attribute names':
attr = attributes(self.matrix)
label_items = [pg.TextItem(str(text), anchor=(0.5, 0))
for text in attr]
else:
label_items = None
self._label_data = label_items
emb_x, emb_y = self.embedding[:, 0], self.embedding[:, 1]
if self.jitter > 0:
_, jitter_factor = self.JitterAmount[self.jitter]
emb_x = jitter(emb_x, jitter_factor, rstate=42)
emb_y = jitter(emb_y, jitter_factor, rstate=667)
if self.connected_pairs and self.__draw_similar_pairs:
if self._similar_pairs is None:
# This code requires storing lower triangle of X (n x n / 2
# doubles), n x n / 2 * 2 indices to X, n x n / 2 indices for
# argsort result. If this becomes an issue, it can be reduced to
# n x n argsort indices by argsorting the entire X. Then we
# take the first n + 2 * p indices. We compute their coordinates
# i, j in the original matrix. We keep those for which i < j.
# n + 2 * p will suffice to exclude the diagonal (i = j). If the
# number of those for which i < j is smaller than p, we instead
# take i > j. Among those that remain, we take the first p.
# Assuming that MDS can't show so many points that memory could
# become an issue, I preferred using simpler code.
m = self._effective_matrix
n = len(m)
p = (n * (n - 1) // 2 * self.connected_pairs) // 100
indcs = numpy.triu_indices(n, 1)
sorted = numpy.argsort(m[indcs])[:p]
self._similar_pairs = fpairs = numpy.empty(2 * p, dtype=int)
fpairs[::2] = indcs[0][sorted]
fpairs[1::2] = indcs[1][sorted]
for i in range(int(len(emb_x[self._similar_pairs]) / 2)):
item = QtGui.QGraphicsLineItem(
emb_x[self._similar_pairs][i * 2],
emb_y[self._similar_pairs][i * 2],
emb_x[self._similar_pairs][i * 2 + 1],
emb_y[self._similar_pairs][i * 2 + 1]
)
pen = QtGui.QPen(QtGui.QBrush(QtGui.QColor(204, 204, 204)), 2)
pen.setCosmetic(True)
item.setPen(pen)
self.plot.addItem(item)
data = numpy.arange(size)
self._scatter_item = item = ScatterPlotItem(
x=emb_x, y=emb_y,
pen=self._pen_data, brush=self._brush_data, symbol=self._shape_data,
size=self._size_data, data=data,
antialias=True
)
self.plot.addItem(item)
if self._label_data is not None:
if self.label_only_selected:
if self._selection_mask is not None:
for (x, y), text_item, selected \
in zip(self.embedding, self._label_data,
self._selection_mask):
if selected:
self.plot.addItem(text_item)
text_item.setPos(x, y)
else:
for (x, y), text_item in zip(self.embedding, self._label_data):
self.plot.addItem(text_item)
text_item.setPos(x, y)
self._legend_item = LegendItem()
viewbox = self.plot.getViewBox()
self._legend_item.setParentItem(self.plot.getViewBox())
self._legend_item.setZValue(viewbox.zValue() + 10)
self._legend_item.restoreAnchor(self.legend_anchor)
color_var = shape_var = None
color_index = self.cb_color_value.currentIndex()
if have_data and 1 <= color_index < len(self.colorvar_model):
color_var = self.colorvar_model[color_index]
assert isinstance(color_var, Orange.data.Variable)
shape_index = self.cb_shape_value.currentIndex()
if have_data and 1 <= shape_index < len(self.shapevar_model):
shape_var = self.shapevar_model[shape_index]
assert isinstance(shape_var, Orange.data.Variable)
if shape_var is not None or \
(color_var is not None and color_var.is_discrete):
legend_data = mdsplotutils.legend_data(
color_var, shape_var, plotstyle=plotstyle)
for color, symbol, text in legend_data:
self._legend_item.addItem(
ScatterPlotItem(pen=color, brush=color, symbol=symbol,
size=10),
escape(text)
)
else:
self._legend_item.hide()
def __init__(self):
super().__init__()
self.varmodel = itemmodels.VariableListModel()
self.groupvarmodel = []
self.distributions = [
distribution.value for distribution in self.available_distributions
]
box = gui.vBox(self.controlArea, 'Tests')
gui.radioButtonsInBox(
box,
self,
'test_idx',
btnLabels=[test.name for test in self.available_tests],
callback=self.test_changed,
)
box = gui.vBox(self.controlArea, 'Distributions')
self.distribution_choose = gui.radioButtonsInBox(
box,
self,
'distribution_idx',
btnLabels=self.distributions,
callback=self.distribution_changed,
)
self.column_chose = gui.comboBox(
self.controlArea,
self,
'column_idx',
box='Selected column',
items=[],
orientation=Qt.Horizontal,
callback=self.column_changed,
)
self.available_columns = itemmodels.VariableListModel(parent=self)
self.column_chose.setModel(self.available_columns)
self.infolabel = gui.widgetLabel(box, "<center>p-value: </center>")
self.mainArea.setMinimumWidth(800)
self.own_distribution_choose = gui.comboBox(
self.controlArea,
self,
'own_distribution_idx',
box='Own distribution',
items=[],
orientation=Qt.Horizontal,
callback=self.column_changed,
)
self.own_distribution_choose.setModel(self.available_columns)
self.data = None
self.plotview = pg.PlotWidget(background=None)
self.plotview.setRenderHint(QPainter.Antialiasing)
self.mainArea.layout().addWidget(self.plotview)
w = QLabel()
w.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Fixed)
self.mainArea.layout().addWidget(w, Qt.AlignCenter)
self.ploti = pg.PlotItem()
self.box_scene = self.ploti.vb
self.ploti.hideButtons()
self.plotview.setCentralItem(self.ploti)
self.plot_prob = pg.ViewBox()
self.ploti.scene().addItem(self.plot_prob)
self.ploti.getAxis("right").linkToView(self.plot_prob)
self.ploti.getAxis("right").setLabel("Probability")
self.plot_prob.setZValue(10)
self.plot_prob.setXLink(self.ploti)
self.update_views()
self.ploti.vb.sigResized.connect(self.update_views)
self.plot_prob.setRange(yRange=[0, 1])
def disable_mouse(box_scene):
box_scene.setMouseEnabled(False, False)
box_scene.setMenuEnabled(False)
disable_mouse(self.box_scene)
disable_mouse(self.plot_prob)
self.tooltip_items = []
pen = QPen(self.palette().color(QPalette.Text))
for axis in ("left", "bottom"):
self.ploti.getAxis(axis).setPen(pen)
self._legend = LegendItem()
self._legend.setParentItem(self.box_scene)
self._legend.hide()
self._legend.anchor((1, 0), (1, 0))
self.test_changed()
