def replot_series(self):
"""
This function replot just series connected with centroids and
uses animation for that
"""
km = self.k_means
k = km.k
series = []
# plot lines between centroids and points
if self.lines_to_centroids:
for i, (c, pts) in enumerate(zip(
km.centroids, km.centroids_belonging_points)):
series.append(dict(
data=list(
chain.from_iterable(([p[0], p[1]], [c[0], c[1]])
for p in pts)),
type="line",
showInLegend=False,
lineWidth=0.2,
enableMouseTracking=False,
color="#ccc"))
# plot data points
for i, points in enumerate(km.centroids_belonging_points):
series.append(dict(
data=points,
type="scatter",
showInLegend=False,
color=rgb_hash_brighter(
self.colors[i % len(self.colors)], 0.5)))
self.scatter.add_series(series)
self.scatter.remove_last_series(k * 2 if self.lines_to_centroids else k)
def complete_replot(self):
"""
This function performs complete replot of the graph without animation
"""
try:
attr_x = self.data.domain[self.attr_x]
attr_y = self.data.domain[self.attr_y]
except KeyError:
return
# plot centroids
options = dict(series=[])
n_colors = len(self.colors)
km = self.k_means
options['series'].append(
dict(data=[{
'x': p[0],
'y': p[1],
'marker': {
'fillColor': self.colors[i % n_colors]
}
} for i, p in enumerate(km.centroids)],
type="scatter",
draggableX=True,
draggableY=True,
cursor="move",
zIndex=10,
marker=dict(symbol='square', radius=8)))
# plot lines between centroids and points
if self.lines_to_centroids:
for i, (c, pts) in enumerate(
zip(km.centroids, km.centroids_belonging_points)):
options['series'].append(
dict(data=list(
chain.from_iterable(
([p[0], p[1]], [c[0], c[1]]) for p in pts)),
type="line",
lineWidth=0.2,
enableMouseTracking=False,
color="#ccc"))
# plot data points
for i, points in enumerate(km.centroids_belonging_points):
options['series'].append(
dict(data=points,
type="scatter",
color=rgb_hash_brighter(self.colors[i % len(self.colors)],
0.3)))
# highcharts parameters
kwargs = dict(
xAxis_title_text=attr_x.name,
yAxis_title_text=attr_y.name,
tooltip_headerFormat="",
tooltip_pointFormat="<strong>%s:</strong> {point.x:.2f} <br/>"
"<strong>%s:</strong> {point.y:.2f}" % (self.attr_x, self.attr_y))
# plot
self.scatter.chart(options, **kwargs)
def test_rgb_hash_brighter(self):
# calculated manually
matches = [["#1F7ECA", "#56a5e5"], ["#CCCC33", "#dbdb70"],
["#993322", "#d55a46"], ["#663366", "#ab58ab"]]
for hash1, hash2 in matches:
self.assertEqual(
rgb_hash_brighter(hash1, 0.3).lower(), hash2.lower())
def complete_replot(self):
"""
This function performs complete replot of the graph without animation
"""
try:
attr_x = self.data.domain[self.attr_x]
attr_y = self.data.domain[self.attr_y]
except KeyError:
return
# plot centroids
options = dict(series=[])
n_colors = len(self.colors)
km = self.k_means
options['series'].append(
dict(
data=[{'x': p[0], 'y': p[1],
'marker':{'fillColor': self.colors[i % n_colors]}}
for i, p in enumerate(km.centroids)],
type="scatter",
draggableX=True,
draggableY=True,
cursor="move",
zIndex=10,
marker=dict(symbol='square', radius=8)))
# plot lines between centroids and points
if self.lines_to_centroids:
for i, (c, pts) in enumerate(zip(
km.centroids, km.centroids_belonging_points)):
options['series'].append(dict(
data=list(
chain.from_iterable(([p[0], p[1]], [c[0], c[1]])
for p in pts)),
type="line",
lineWidth=0.2,
enableMouseTracking=False,
color="#ccc"))
# plot data points
for i, points in enumerate(km.centroids_belonging_points):
options['series'].append(dict(
data=points,
type="scatter",
color=rgb_hash_brighter(
self.colors[i % len(self.colors)], 0.3)))
# highcharts parameters
kwargs = dict(
xAxis_title_text=attr_x.name,
yAxis_title_text=attr_y.name,
tooltip_headerFormat="",
tooltip_pointFormat="<strong>%s:</strong> {point.x:.2f} <br/>"
"<strong>%s:</strong> {point.y:.2f}" %
(self.attr_x, self.attr_y))
# plot
self.scatter.chart(options, **kwargs)
def test_rgb_hash_brighter(self):
# calculated manually
matches = [["#1F7ECA", "#56a5e5"],
["#CCCC33", "#dbdb70"],
["#993322", "#d55a46"],
["#663366", "#ab58ab"]]
for hash1, hash2 in matches:
self.assertEqual(
rgb_hash_brighter(hash1, 0.3).lower(), hash2.lower())
def complete_replot(self):
"""
This function performs complete replot of the graph without animation
"""
attr_x, attr_y = self.data.domain[self.attr_x], self.data.domain[self.attr_y]
# plot centroids
options = dict(series=[])
options['series'].append(dict(data=[{'x': p[0],
'y': p[1],
'marker':{'fillColor': self.colors[i % len(self.colors)]}}
for i, p in enumerate(self.k_means.centroids)],
type="scatter",
draggableX=True if self.k_means.step_completed else False,
draggableY=True if self.k_means.step_completed else False,
showInLegend=False,
zIndex=10,
marker=dict(symbol='diamond',
radius=10)))
# plot lines between centroids and points
if self.lines_to_centroids:
for i, c in enumerate(self.k_means.centroids):
options['series'].append(dict(data=list(
chain.from_iterable(([p[0], p[1]], [c[0], c[1]])
for p in self.k_means.centroids_belonging_points[i])),
type="line",
showInLegend=False,
lineWidth=0.2,
enableMouseTracking=False,
color="#ccc"))
# plot data points
for i, points in enumerate(self.k_means.centroids_belonging_points):
options['series'].append(dict(data=points,
type="scatter",
showInLegend=False,
color=rgb_hash_brighter(self.colors[i % len(self.colors)], 30)))
# highcharts parameters
kwargs = dict(
xAxis_title_text=attr_x.name,
yAxis_title_text=attr_y.name,
tooltip_headerFormat="",
tooltip_pointFormat="<strong>%s:</strong> {point.x:.2f} <br/>"
"<strong>%s:</strong> {point.y:.2f}" %
(self.attr_x, self.attr_y))
# plot
self.scatter.chart(options, **kwargs)
def replot(self):
"""
This function performs complete replot of the graph
"""
if self.data is None or self.selected_data is None:
self.set_empty_plot()
return
attr_x = self.data.domain[self.attr_x]
attr_y = self.data.domain[self.attr_y]
data_x = [v[0] for v in self.data[:, attr_x] if not isnan(v[0])]
data_y = [v[0] for v in self.data[:, attr_y] if not isnan(v[0])]
min_x = min(data_x)
max_x = max(data_x)
min_y = min(data_y)
max_y = max(data_y)
# just in cas that diff is 0
diff_x = (max_x - min_x) if abs(max_x - min_x) > 0.001 else 0.1
diff_y = (max_y - min_y) if abs(max_y - min_y) > 0.001 else 0.1
min_x, max_x = min_x - 0.03 * diff_x, max_x + 0.03 * diff_x
min_y, max_y = min_y - 0.03 * diff_y, max_y + 0.03 * diff_y
options = dict(series=[])
# gradient and contour
options['series'] += self.plot_gradient_and_contour(
min_x, max_x, min_y, max_y)
sd = self.selected_data
# data points
options['series'] += [
dict(
data=[list(p.attributes())
for p in sd
if (int(p.metas[0]) == _class and
all(v is not None for v in p.attributes()))],
type="scatter",
zIndex=10,
color=rgb_to_hex(tuple(
sd.domain.metas[0].colors[_class].tolist())),
showInLegend=True,
name=sd.domain.metas[0].values[_class])
for _class in range(len(sd.domain.metas[0].values))]
cls_domain = sd.domain.metas[0]
target_idx = cls_domain.values.index(self.target_class)
target_color = tuple(cls_domain.colors[target_idx].tolist())
other_color = (tuple(cls_domain.colors[(target_idx + 1) % 2].tolist())
if len(cls_domain.values) == 2 else (170, 170, 170))
# highcharts parameters
kwargs = dict(
xAxis_title_text=attr_x.name,
yAxis_title_text=attr_y.name,
xAxis_min=min_x,
xAxis_max=max_x,
yAxis_min=min_y,
yAxis_max=max_y,
colorAxis=dict(
labels=dict(enabled=False),
stops=[
[0, rgb_hash_brighter(rgb_to_hex(other_color), 0.5)],
[0.5, '#ffffff'],
[1, rgb_hash_brighter(rgb_to_hex(target_color), 0.5)]],
tickInterval=0.2, min=0, max=1),
plotOptions_contour_colsize=(max_y - min_y) / 1000,
plotOptions_contour_rowsize=(max_x - min_x) / 1000,
legend=dict(
enabled=self.legend_enabled,
layout='vertical',
align='right',
verticalAlign='top',
floating=True,
backgroundColor='rgba(255, 255, 255, 0.3)',
symbolWidth=0,
symbolHeight=0),
tooltip_headerFormat="",
tooltip_pointFormat="<strong>%s:</strong> {point.x:.2f} <br/>"
"<strong>%s:</strong> {point.y:.2f}" %
(self.attr_x, self.attr_y))
self.scatter.chart(options, **kwargs)
self.plot_contour()
def replot(self):
"""
This function performs complete replot of the graph
"""
if self.data is None or self.selected_data is None:
self.set_empty_plot()
return
attr_x = self.data.domain[self.attr_x]
attr_y = self.data.domain[self.attr_y]
data_x = [v[0] for v in self.data[:, attr_x] if not isnan(v[0])]
data_y = [v[0] for v in self.data[:, attr_y] if not isnan(v[0])]
min_x = min(data_x)
max_x = max(data_x)
min_y = min(data_y)
max_y = max(data_y)
# just in cas that diff is 0
diff_x = (max_x - min_x) if abs(max_x - min_x) > 0.001 else 0.1
diff_y = (max_y - min_y) if abs(max_y - min_y) > 0.001 else 0.1
min_x, max_x = min_x - 0.03 * diff_x, max_x + 0.03 * diff_x
min_y, max_y = min_y - 0.03 * diff_y, max_y + 0.03 * diff_y
options = dict(series=[])
# gradient and contour
options['series'] += self.plot_gradient_and_contour(
min_x, max_x, min_y, max_y)
sd = self.selected_data
# data points
options['series'] += [
dict(data=[
list(p.attributes()) for p in sd
if (p.metas[0] == _class and all(v is not None
for v in p.attributes()))
],
type="scatter",
zIndex=10,
color=rgb_to_hex(
tuple(sd.domain.metas[0].colors[_class].tolist())),
showInLegend=True,
name=sd.domain.metas[0].values[_class])
for _class in range(len(sd.domain.metas[0].values))
]
# add nan values as a gray dots
options['series'] += [
dict(data=[
list(p.attributes()) for p in sd if np.isnan(p.metas[0])
],
type="scatter",
zIndex=10,
color=rgb_to_hex((160, 160, 160)),
showInLegend=False)
]
cls_domain = sd.domain.metas[0]
target_idx = cls_domain.values.index(self.target_class)
target_color = tuple(cls_domain.colors[target_idx].tolist())
other_color = (tuple(cls_domain.colors[(target_idx + 1) % 2].tolist())
if len(cls_domain.values) == 2 else (170, 170, 170))
# highcharts parameters
kwargs = dict(
xAxis_title_text=attr_x.name,
yAxis_title_text=attr_y.name,
xAxis_min=min_x,
xAxis_max=max_x,
yAxis_min=min_y,
yAxis_max=max_y,
colorAxis=dict(
labels=dict(enabled=False),
stops=[[0, rgb_hash_brighter(rgb_to_hex(other_color), 0.5)],
[0.5, '#ffffff'],
[1, rgb_hash_brighter(rgb_to_hex(target_color), 0.5)]],
tickInterval=0.2,
min=0,
max=1),
plotOptions_contour_colsize=(max_y - min_y) / 1000,
plotOptions_contour_rowsize=(max_x - min_x) / 1000,
legend=dict(enabled=self.legend_enabled,
layout='vertical',
align='right',
verticalAlign='top',
floating=True,
backgroundColor='rgba(255, 255, 255, 0.3)',
symbolWidth=0,
symbolHeight=0),
tooltip_headerFormat="",
tooltip_pointFormat="<strong>%s:</strong> {point.x:.2f} <br/>"
"<strong>%s:</strong> {point.y:.2f}" % (self.attr_x, self.attr_y))
self.scatter.chart(options, **kwargs)
self.plot_contour()
