def _setup_plot(self):
have_data = self.data is not None
if self._pen_data is None:
if have_data and self.color_var > 0:
color_var = self.colorvar_model[self.color_var]
if is_discrete(color_var):
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values))
else:
palette = None
color_data = colors(self.data, color_var, palette)
pen_data = [
QtGui.QPen(QtGui.QColor(r, g, b)) for r, g, b in color_data
]
else:
pen_data = QtGui.QPen(Qt.black)
self._pen_data = pen_data
if self._shape_data is None:
if have_data and self.shape_var > 0:
Symbols = pg.graphicsItems.ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[self.shape_var]
data = numpy.array(self.data[:, shape_var]).ravel()
data = data % (len(Symbols) - 1)
data[numpy.isnan(data)] = len(Symbols) - 1
shape_data = symbols[data.astype(int)]
else:
shape_data = "o"
self._shape_data = shape_data
if self._size_data is None:
MinPointSize = 1
point_size = 8 + MinPointSize
if have_data and self.size_var > 0:
size_var = self.sizevar_model[self.size_var]
size_data = numpy.array(self.data[:, size_var]).ravel()
dmin, dmax = numpy.nanmin(size_data), numpy.nanmax(size_data)
if dmax - dmin > 0:
size_data = (size_data - dmin) / (dmax - dmin)
size_data = MinPointSize + size_data * point_size
else:
size_data = point_size
item = pg.ScatterPlotItem(x=self.embeding[:, 0],
y=self.embeding[:, 1],
pen=self._pen_data,
symbol=self._shape_data,
brush=QtGui.QBrush(Qt.transparent),
size=size_data,
antialias=True)
# plot(x, y, colors=plot.colors(data[:, color_var]),
# point_size=data[:, size_var],
# symbol=data[:, symbol_var])
self.plot.addItem(item)
def _setup_plot(self):
have_data = self.data is not None
if self._pen_data is None:
if have_data and self.color_var > 0:
color_var = self.colorvar_model[self.color_var]
if is_discrete(color_var):
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values)
)
else:
palette = None
color_data = colors(self.data, color_var, palette)
pen_data = [QtGui.QPen(QtGui.QColor(r, g, b))
for r, g, b in color_data]
else:
pen_data = QtGui.QPen(Qt.black)
self._pen_data = pen_data
if self._shape_data is None:
if have_data and self.shape_var > 0:
Symbols = pg.graphicsItems.ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[self.shape_var]
data = numpy.array(self.data[:, shape_var]).ravel()
data = data % (len(Symbols) - 1)
data[numpy.isnan(data)] = len(Symbols) - 1
shape_data = symbols[data.astype(int)]
else:
shape_data = "o"
self._shape_data = shape_data
if self._size_data is None:
MinPointSize = 1
point_size = 8 + MinPointSize
if have_data and self.size_var > 0:
size_var = self.sizevar_model[self.size_var]
size_data = numpy.array(self.data[:, size_var]).ravel()
dmin, dmax = numpy.nanmin(size_data), numpy.nanmax(size_data)
if dmax - dmin > 0:
size_data = (size_data - dmin) / (dmax - dmin)
size_data = MinPointSize + size_data * point_size
else:
size_data = point_size
item = pg.ScatterPlotItem(
x=self.embedding[:, 0], y=self.embedding[:, 1],
pen=self._pen_data, symbol=self._shape_data,
brush=QtGui.QBrush(Qt.transparent),
size=size_data,
antialias=True
)
# plot(x, y, colors=plot.colors(data[:, color_var]),
# point_size=data[:, size_var],
# symbol=data[:, symbol_var])
self.plot.addItem(item)
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 _setup_plot(self):
have_data = self.data is not None
have_matrix_transposed = self.matrix is not None and not self.matrix.axis
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)
if self._pen_data is None:
if have_data and self.color_index > 0:
color_var = self.colorvar_model[self.color_index]
if is_discrete(color_var):
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values)
)
else:
palette = None
color_data = colors(self.data, color_var, palette)
pen_data = [make_pen(QtGui.QColor(r, g, b, self.symbol_opacity),
cosmetic=True)
for r, g, b in color_data]
elif have_matrix_transposed and self.colorvar_model[self.color_index] == 'Attribute names':
attr = attributes(self.matrix)
palette = colorpalette.ColorPaletteGenerator(len(attr))
color_data = [palette.getRGB(i) for i in range(len(attr))]
pen_data = [make_pen(QtGui.QColor(r, g, b, self.symbol_opacity),
cosmetic=True)
for r, g, b in color_data]
else:
pen_data = make_pen(QtGui.QColor(Qt.darkGray), cosmetic=True)
self._pen_data = pen_data
if self._shape_data is None:
if have_data and self.shape_index > 0:
Symbols = ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[self.shape_index]
data = column(self.data, shape_var)
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[self.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
if have_data and self.size_index == 1:
# size by stress
size_data = stress(self.embedding, self._effective_matrix.X)
size_data = scale(size_data)
size_data = MinPointSize + size_data * point_size
elif have_data and self.size_index > 0:
size_var = self.sizevar_model[self.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
if self._label_data is None:
if have_data and self.label_index > 0:
label_var = self.labelvar_model[self.label_index]
label_data = column(self.data, label_var)
label_data = [label_var.repr_val(val) for val in label_data]
label_items = [pg.TextItem(text, anchor=(0.5, 0))
for text in label_data]
elif have_matrix_transposed and self.labelvar_model[self.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
item = ScatterPlotItem(
x=self.embedding[:, 0], y=self.embedding[:, 1],
pen=self._pen_data, symbol=self._shape_data,
brush=QtGui.QBrush(Qt.transparent),
size=size_data,
antialias=True
)
self.plot.addItem(item)
if self._label_data is not None:
for (x, y), text_item in zip(self.embedding, self._label_data):
self.plot.addItem(text_item)
text_item.setPos(x, y)
def _setup_plot(self):
have_data = self.data is not None
have_matrix_transposed = self.matrix is not None and not self.matrix.axis
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)
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
if have_data and self.color_index > 0:
color_var = self.colorvar_model[self.color_index]
if color_var.is_discrete:
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values))
else:
palette = None
color_data = mdsplotutils.color_data(
self.data, color_var, plotstyle=mdsplotutils.plotstyle)
color_data = numpy.hstack((color_data,
numpy.full((len(color_data), 1),
self.symbol_opacity)))
pen_data = mdsplotutils.pen_data(color_data, pointflags)
elif have_matrix_transposed and self.colorvar_model[
self.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))
pen_data = mdsplotutils.pen_data(color_data, pointflags)
else:
pen_data = make_pen(QtGui.QColor(Qt.darkGray), cosmetic=True)
pen_data = numpy.full(len(self.data), pen_data, dtype=object)
self._pen_data = pen_data
if self._shape_data is None:
if have_data and self.shape_index > 0:
Symbols = ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[self.shape_index]
data = column(self.data, shape_var)
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[
self.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
if have_data and self.size_index == 1:
# size by stress
size_data = stress(self.embedding, self._effective_matrix.X)
size_data = scale(size_data)
size_data = MinPointSize + size_data * point_size
elif have_data and self.size_index > 0:
size_var = self.sizevar_model[self.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
if self._label_data is None:
if have_data and self.label_index > 0:
label_var = self.labelvar_model[self.label_index]
label_data = column(self.data, label_var)
label_data = [label_var.repr_val(val) for val in label_data]
label_items = [
pg.TextItem(text, anchor=(0.5, 0)) for text in label_data
]
elif have_matrix_transposed and self.labelvar_model[
self.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
self._scatter_item = item = ScatterPlotItem(
x=self.embedding[:, 0],
y=self.embedding[:, 1],
pen=self._pen_data,
symbol=self._shape_data,
brush=QtGui.QBrush(Qt.transparent),
size=size_data,
data=numpy.arange(len(self.data)),
antialias=True)
self.plot.addItem(item)
if self._label_data is not None:
for (x, y), text_item in zip(self.embedding, self._label_data):
self.plot.addItem(text_item)
text_item.setPos(x, y)
def _setup_plot(self):
have_data = self.data is not None
have_matrix_transposed = self.matrix is not None and not self.matrix.axis
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)
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
if have_data and self.color_index > 0:
color_var = self.colorvar_model[self.color_index]
if color_var.is_discrete:
palette = colorpalette.ColorPaletteGenerator(
len(color_var.values)
)
else:
palette = None
color_data = mdsplotutils.color_data(
self.data, color_var, plotstyle=mdsplotutils.plotstyle)
color_data = numpy.hstack(
(color_data,
numpy.full((len(color_data), 1), self.symbol_opacity))
)
pen_data = mdsplotutils.pen_data(color_data, pointflags)
elif have_matrix_transposed and self.colorvar_model[self.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)
)
pen_data = mdsplotutils.pen_data(color_data, pointflags)
else:
pen_data = make_pen(QtGui.QColor(Qt.darkGray), cosmetic=True)
pen_data = numpy.full(len(self.data), pen_data, dtype=object)
self._pen_data = pen_data
if self._shape_data is None:
if have_data and self.shape_index > 0:
Symbols = ScatterPlotItem.Symbols
symbols = numpy.array(list(Symbols.keys()))
shape_var = self.shapevar_model[self.shape_index]
data = column(self.data, shape_var)
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[self.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
if have_data and self.size_index == 1:
# size by stress
size_data = stress(self.embedding, self._effective_matrix.X)
size_data = scale(size_data)
size_data = MinPointSize + size_data * point_size
elif have_data and self.size_index > 0:
size_var = self.sizevar_model[self.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
if self._label_data is None:
if have_data and self.label_index > 0:
label_var = self.labelvar_model[self.label_index]
label_data = column(self.data, label_var)
label_data = [label_var.repr_val(val) for val in label_data]
label_items = [pg.TextItem(text, anchor=(0.5, 0))
for text in label_data]
elif have_matrix_transposed and self.labelvar_model[self.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
self._scatter_item = item = ScatterPlotItem(
x=self.embedding[:, 0], y=self.embedding[:, 1],
pen=self._pen_data, symbol=self._shape_data,
brush=QtGui.QBrush(Qt.transparent),
size=size_data, data=numpy.arange(len(self.data)),
antialias=True
)
self.plot.addItem(item)
if self._label_data is not None:
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()
self._legend_item.setParentItem(self.plot.getViewBox())
self._legend_item.anchor(*self.legend_anchor)
color_var = shape_var = None
if have_data and 1 <= self.color_index < len(self.colorvar_model):
color_var = self.colorvar_model[self.color_index]
assert isinstance(color_var, Orange.data.Variable)
if have_data and 1 <= self.shape_index < len(self.shapevar_model):
shape_var = self.shapevar_model[self.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=mdsplotutils.plotstyle)
for color, symbol, text in legend_data:
self._legend_item.addItem(
ScatterPlotItem(pen=color, brush=color, symbol=symbol,
size=10),
text
)
else:
self._legend_item.hide()
def call_filter(
self,
filter_type,
filter_band,
first_cutoff,
second_cutoff,
order,
max_ripple,
min_attenuation):
"""
Call specified filter function on all audio clips
:param filter_type: type of filter
:param filter_band: band of filter
:param first_cutoff: first cutoff frequency
:param second_cutoff: second cutoff frequency
:param order: filter order
:param max_ripple: the maximum ripple
:param min_attenuation: the minimum attenuatio
:return: Void
"""
if self.data is None:
return
filterBand = (''.join(c for c in filter_band if c not in "-")).lower()
filterType = self.convertTypeToStr(filter_type)
error = None
self.X = []
self.metas = []
try:
for i in range(len(self.data.metas)):
if self.data.X != []:
input_data = self.data.X[i]
else:
input_data = read(self.data.metas[i][1])[1]
if len(input_data.shape) > 1:
input_data = input_data[:, 0]
if filterType == "FIR" or filterType == "butter" or filterType == "bessel":
if filterBand == "lowpass" or filterBand == "highpass":
filtered = st.filter_signal(input_data,
ftype=filterType,
band=filterBand,
order=order,
frequency=first_cutoff,
sampling_rate=self.data.metas[i][-1])
else:
filtered = st.filter_signal(input_data, ftype=filterType, band=filterBand, order=order,
frequency=[first_cutoff, second_cutoff],
sampling_rate=self.data.metas[i][-1])
elif filterType == "cheby1":
if filterBand == "lowpass" or filterBand == "highpass":
filtered = st.filter_signal(input_data,
ftype=filterType,
band=filterBand,
order=order,
frequency=first_cutoff,
sampling_rate=self.data.metas[i][-1],
rp=max_ripple)
else:
filtered = st.filter_signal(input_data, ftype=filterType, band=filterBand, order=order,
frequency=[first_cutoff, second_cutoff], sampling_rate=self.data.metas[i][-1],
rp=max_ripple)
elif filterType == "cheby2":
if filterBand == "lowpass" or filterBand == "highpass":
filtered = st.filter_signal(input_data,
ftype=filterType,
band=filterBand,
order=order,
frequency=first_cutoff,
sampling_rate=self.data.metas[i][-1],
rs=min_attenuation)
else:
filtered = st.filter_signal(input_data, ftype=filterType, band=filterBand, order=order,
frequency=[first_cutoff, second_cutoff], sampling_rate=self.data.metas[i][-1],
rs=min_attenuation)
else:
if filterBand == "lowpass" or filterBand == "highpass":
filtered = st.filter_signal(input_data,
ftype=filterType,
band=filterBand,
order=order,
frequency=first_cutoff,
sampling_rate=self.data.metas[i][-1],
rp=max_ripple,
rs=min_attenuation)
else:
filtered = st.filter_signal(input_data,
ftype=filterType,
band=filterBand,
order=order,
frequency=[first_cutoff,
second_cutoff],
sampling_rate=self.data.metas[i][-1],
rp=max_ripple,
rs=min_attenuation)
self.new_tmp_dir = os.path.dirname(
self.data.metas[i][1]) + os.sep + "filtered-" + self.tmp_dir_id + os.sep
if not os.path.exists(self.new_tmp_dir):
os.makedirs(self.new_tmp_dir)
self.new_tmp_dirs.append(self.new_tmp_dir)
filename = self.new_tmp_dir + self.data.metas[i][0] + ".wav"
self.metas.append([self.data.metas[i][0],
filename,
self.data.metas[i][2],
self.data.metas[i][3],
self.data.metas[i][4]])
data = filtered["signal"]
data = data / data.max()
data = data * (2 ** 15 - 1)
data = data.astype(numpy.int16)
write(filename, self.data.metas[i][-1], data)
except Exception as ex:
error = ex
if not error:
self.info.setStyleSheet(success_green)
self.info.setText(
filter_type +
" " +
filter_band +
" " +
"filter successful!")
orange_table = Orange.data.Table.from_numpy(
self.data.domain, numpy.empty((len(self.data.Y), 0), dtype=float),
self.data.Y, self.metas
)
self.send("Filtered data", orange_table)
if error:
self.info.setStyleSheet(error_red)
self.info.setText("An error occurred:\n{}".format(error))
return