def compute_score(self, state):
attrs = [self.attrs[i] for i in state]
domain = Domain(attributes=attrs, class_vars=[self.attr_color])
data = self.data.transform(domain)
radviz_xy, _, mask = radviz(data, attrs)
y = data.Y[mask]
return -self._evaluate_projection(radviz_xy, y)
def compute_score(self, state):
attrs = [self.attrs[i] for i in state]
domain = Domain(attributes=attrs, class_vars=[self.attr_color])
data = self.data.transform(domain)
radviz_xy, _, mask = radviz(data, attrs)
y = data.Y[mask]
return -self._evaluate_projection(radviz_xy, y)
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 setup_plot(self):
if self.data is None:
return
self.__replot_requested = False
self.clear_messages()
if len(self.model_selected) < 2:
self.Warning.no_features()
self.graph.clear()
return
r = radviz(self.data, self.model_selected)
self._embedding_coords = r[0]
self.graph.set_points(r[1])
self.valid_data = r[2]
if self._embedding_coords is None or \
np.any(np.isnan(self._embedding_coords)):
self.Warning.invalid_embedding()
self.graph.reset_graph()
def _manual_move(self):
self.__replot_requested = False
res = radviz(self.data, self.model_selected, self.graph.get_points())
self._embedding_coords = res[0]
if self._rand_indices is not None:
# save widget state
selection = self.graph.selection
valid_data = self.valid_data.copy()
data = self.data.copy()
ec = self._embedding_coords.copy()
# plot subset
self.__plot_random_subset(selection)
# restore widget state
self.graph.selection = selection
self.valid_data = valid_data
self.data = data
self._embedding_coords = ec
else:
self.graph.update_coordinates()
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 get_embedding(self):
self.valid_data = None
if self.data is None:
return None
self.Warning.no_features.clear()
if len(self.model_selected) < 2:
self.Warning.no_features()
return None
ec, proj, msk = radviz(self.data, self.model_selected, self.projection)
angle = np.arctan2(*proj.T[::-1])
self.projection = np.vstack((np.cos(angle), np.sin(angle))).T
self.valid_data = msk
self.Warning.invalid_embedding.clear()
if ec is None or np.any(np.isnan(ec)):
self.Warning.invalid_embedding()
return None
embedding = np.full((len(self.data), 2), np.nan)
embedding[self.valid_data] = ec
return embedding
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 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