def __init__(self, image_views, sv_streamctrl):
"""Initialize a disabled pixels overlay.
Args:
image_views (ImageView): Associated streamvis image view instances.
sv_streamctrl (StreamControl): A StreamControl instance of an application.
"""
self._detector_name = ""
self._ju_handler = None
self._sv_streamctrl = sv_streamctrl
self._source = ColumnDataSource(
dict(left=[], right=[], top=[], bottom=[]))
glyph = Quad(
left="left",
right="right",
top="top",
bottom="bottom",
line_alpha=0,
fill_alpha=0,
hatch_pattern="/",
hatch_color="white",
)
for image_view in image_views:
image_view.plot.add_glyph(self._source, glyph)
def __init__(self, scheduler, **kwargs):
self.scheduler = scheduler
ps = [p for p in scheduler.plugins if isinstance(p, AllProgress)]
if ps:
self.plugin = ps[0]
else:
self.plugin = AllProgress(scheduler)
self.source = ColumnDataSource(data=dict(name=[],
left=[],
right=[],
center=[],
color=[],
percent=[],
MB=[],
text=[]))
self.root = Plot(id='bk-nbytes-plot',
x_range=DataRange1d(),
y_range=DataRange1d(),
toolbar_location=None,
outline_line_color=None,
**kwargs)
self.root.add_glyph(
self.source,
Quad(top=1,
bottom=0,
left='left',
right='right',
fill_color='color',
fill_alpha=1))
self.root.add_layout(LinearAxis(), 'left')
self.root.add_layout(LinearAxis(), 'below')
hover = HoverTool(point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Percent:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@percent</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">MB:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@MB</span>
</div>
""")
self.root.add_tools(hover)
def __init__(self, **kwargs):
self.source = ColumnDataSource(data=dict(
name=[],
left=[],
right=[],
center=[],
color=[],
percent=[],
MB=[],
text=[],
))
self.root = Plot(id="bk-nbytes-plot",
x_range=DataRange1d(),
y_range=DataRange1d(),
toolbar_location=None,
outline_line_color=None,
**kwargs)
self.root.add_glyph(
self.source,
Quad(
top=1,
bottom=0,
left="left",
right="right",
fill_color="color",
fill_alpha=1,
),
)
self.root.add_layout(LinearAxis(), "left")
self.root.add_layout(LinearAxis(), "below")
hover = HoverTool(
point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Percent:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@percent</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">MB:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@MB</span>
</div>
""",
)
self.root.add_tools(hover)
def pyramid():
xdr = DataRange1d()
ydr = DataRange1d()
plot = Plot(title=None,
x_range=xdr,
y_range=ydr,
plot_width=600,
plot_height=600)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis(ticker=SingleIntervalTicker(interval=5))
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
male_quad = Quad(left="male",
right=0,
bottom="groups",
top="shifted",
fill_color="#3B8686")
male_quad_glyph = plot.add_glyph(source_pyramid, male_quad)
female_quad = Quad(left=0,
right="female",
bottom="groups",
top="shifted",
fill_color="#CFF09E")
female_quad_glyph = plot.add_glyph(source_pyramid, female_quad)
plot.add_layout(
Legend(items=[
("Male", [male_quad_glyph]),
("Female", [female_quad_glyph]),
]))
return plot
def add_background_stripe(x, index):
if divmod(index, 2)[1] == 1:
color = self.ODD_BOX_ANNOTATION_COLOR
else:
color = self.EVEN_BOX_ANNOTATION_COLOR
q = Quad(left=(x - self.dx // 2),
bottom=0,
right=(x + self.dx // 2),
top=self.plot.y_range.end,
line_color=None,
fill_color=color,
fill_alpha=0.2)
self.plot.add_glyph(q)
def __init__(self, image_views, sv_metadata, sv_streamctrl):
"""Initialize a intensity ROI overlay.
Args:
image_views (ImageView): Associated streamvis image view instances.
sv_metadata (MetadataHandler): A metadata handler to report metadata issues.
sv_streamctrl (StreamControl): A StreamControl instance of an application.
"""
self._sv_metadata = sv_metadata
self._sv_streamctrl = sv_streamctrl
# ---- intensity ROIs
self._source = ColumnDataSource(
dict(left=[],
right=[],
bottom=[],
top=[],
text_x=[],
text_y=[],
text=[]))
quad_glyph = Quad(
left="left",
right="right",
bottom="bottom",
top="top",
fill_alpha=0,
line_color="white",
)
text_glyph = Text(
x="text_x",
y="text_y",
text="text",
text_align="right",
text_baseline="top",
text_color="white",
)
for image_view in image_views:
image_view.plot.add_glyph(self._source, quad_glyph)
image_view.plot.add_glyph(self._source, text_glyph)
# ---- toggle button
toggle = CheckboxGroup(labels=["Intensity ROIs"], default_size=145)
self.toggle = toggle
def get_hist(values,
bins=15,
width=DEF_WIDTH,
title=None,
js_on_event=None,
**kwargs):
hist_probs, edges = np.histogram(values, density=True, bins=bins)
hist_counts, edges = np.histogram(values, density=False, bins=bins)
source = ColumnDataSource(
dict(left=edges[:-1],
top=hist_probs,
right=edges[1:],
bottom=[0] * len(hist_probs),
count=hist_counts))
hover = HoverTool(tooltips=[('Count', '@count')])
xdr = DataRange1d()
ydr = DataRange1d()
hist = figure(plot_width=width,
toolbar_location=DEF_TOOL_LOC,
tools=DEF_TOOLS + [hover],
title=title,
x_range=xdr,
y_range=ydr,
**kwargs)
bars = Quad(top='top',
bottom='bottom',
left='left',
right='right',
fill_color="#036564",
line_color="#033649")
hist.add_glyph(source, bars)
if js_on_event is not None:
hist.js_on_event(js_on_event[0], js_on_event[1])
return hist
def __init__(self):
"""Initialize a progress bar widget.
"""
self._source = ColumnDataSource(
dict(left=[0],
right=[0],
top=[1],
bottom=[0],
text_x=[0.5],
text_y=[0.5],
text=[""]))
bar_glyph = Quad(
left="left",
right="right",
top="top",
bottom="bottom",
fill_color="limegreen",
line_alpha=0,
)
text_glyph = Text(
x="text_x",
y="text_y",
text="text",
text_align="center",
text_baseline="middle",
text_font_style="bold",
)
plot = Plot(
plot_width=310,
plot_height=40,
x_range=Range1d(0, 1, bounds=(0, 1)),
y_range=Range1d(0, 1, bounds=(0, 1)),
toolbar_location=None,
)
plot.add_glyph(self._source, bar_glyph)
plot.add_glyph(self._source, text_glyph)
self.widget = plot
def make_trace_figure(trace, tids):
tooltips = [("Task:", "@name"), ("Start:", "@start"),
("Duration:", "@duration")]
mint = min(trace['start'])
maxt = max(trace['end'])
plot = figure(width=1500,
height=800,
tooltips=tooltips,
y_range=tids,
x_range=(mint, maxt))
plot.xaxis.axis_label = "Time [s.]"
plot.yaxis.axis_label = "Thread/rank"
source = ColumnDataSource(trace)
rect = plot.add_glyph(
source,
Quad(left='start',
right='end',
top='top',
bottom='bottom',
fill_color='color',
line_color='color',
fill_alpha=0.9,
line_alpha=0.9))
## Create filter
text_input = TextInput(value="", title="Filter")
def text_input_fn(attr, old, new):
fil = text_input.value
new_trace = trace[trace['name'].str.contains(fil)]
print("Filtering using {}, originally {} rows, now {} rows".format(
fil, trace.shape[0], new_trace.shape[0]))
source.data = new_trace
print("Done filtering")
text_input.on_change('value', text_input_fn)
print("Done preparing plot...")
return text_input, plot
def add_as_zoom(self, image_view, line_color="red"):
"""Add an ImageView plot as a zoom view.
Args:
image_plot (ImageView): Associated streamvis image view instance.
line_color (str, optional): Zoom border box color. Defaults to 'red'.
"""
# ---- add quad glyph of zoom area to the main plot
area_source = ColumnDataSource(
dict(
left=[image_view.x_start],
right=[image_view.x_end],
bottom=[image_view.y_start],
top=[image_view.y_end],
))
area_rect = Quad(
left="left",
right="right",
bottom="bottom",
top="top",
line_color=line_color,
line_width=2,
fill_alpha=0,
)
self.plot.add_glyph(area_source, area_rect)
x_range_cb = CustomJS(args=dict(source=area_source),
code=js_move_zoom.format(start="left",
end="right"))
y_range_cb = CustomJS(args=dict(source=area_source),
code=js_move_zoom.format(start="bottom",
end="top"))
image_view.plot.x_range.js_on_change("start", x_range_cb)
image_view.plot.x_range.js_on_change("end", x_range_cb)
image_view.plot.y_range.js_on_change("start", y_range_cb)
image_view.plot.y_range.js_on_change("end", y_range_cb)
self.zoom_views.append(image_view)
def __init__(self,
nplots,
plot_height=350,
plot_width=700,
lower=0,
upper=1000,
nbins=100):
"""Initialize histogram plots.
Args:
nplots (int): Number of histogram plots that will share common controls.
plot_height (int, optional): Height of plot area in screen pixels. Defaults to 350.
plot_width (int, optional): Width of plot area in screen pixels. Defaults to 700.
lower (int, optional): Initial lower range of the bins. Defaults to 0.
upper (int, optional): Initial upper range of the bins. Defaults to 1000.
nbins (int, optional): Initial number of the bins. Defaults to 100.
"""
# Histogram plots
self.plots = []
self._plot_sources = []
for ind in range(nplots):
plot = Plot(
x_range=DataRange1d(),
y_range=DataRange1d(),
plot_height=plot_height,
plot_width=plot_width,
toolbar_location="left",
)
# ---- tools
plot.toolbar.logo = None
# share 'pan', 'boxzoom', and 'wheelzoom' tools between all plots
if ind == 0:
pantool = PanTool()
boxzoomtool = BoxZoomTool()
wheelzoomtool = WheelZoomTool()
plot.add_tools(pantool, boxzoomtool, wheelzoomtool, SaveTool(),
ResetTool())
# ---- axes
plot.add_layout(LinearAxis(), place="below")
plot.add_layout(LinearAxis(major_label_orientation="vertical"),
place="left")
# ---- grid lines
plot.add_layout(Grid(dimension=0, ticker=BasicTicker()))
plot.add_layout(Grid(dimension=1, ticker=BasicTicker()))
# ---- quad (single bin) glyph
plot_source = ColumnDataSource(dict(left=[], right=[], top=[]))
plot.add_glyph(
plot_source,
Quad(left="left",
right="right",
top="top",
bottom=0,
fill_color="steelblue"),
)
self.plots.append(plot)
self._plot_sources.append(plot_source)
self._counts = []
self._empty_counts()
# Histogram controls
# ---- histogram range toggle button
def auto_toggle_callback(state):
if state: # Automatic
lower_spinner.disabled = True
upper_spinner.disabled = True
else: # Manual
lower_spinner.disabled = False
upper_spinner.disabled = False
auto_toggle = CheckboxGroup(labels=["Auto Hist Range"],
active=[0],
default_size=145)
auto_toggle.on_click(auto_toggle_callback)
self.auto_toggle = auto_toggle
# ---- histogram lower range
def lower_spinner_callback(_attr, _old_value, new_value):
self.upper_spinner.low = new_value + STEP
self._empty_counts()
lower_spinner = Spinner(
title="Lower Range:",
high=upper - STEP,
value=lower,
step=STEP,
disabled=bool(auto_toggle.active),
default_size=145,
)
lower_spinner.on_change("value", lower_spinner_callback)
self.lower_spinner = lower_spinner
# ---- histogram upper range
def upper_spinner_callback(_attr, _old_value, new_value):
self.lower_spinner.high = new_value - STEP
self._empty_counts()
upper_spinner = Spinner(
title="Upper Range:",
low=lower + STEP,
value=upper,
step=STEP,
disabled=bool(auto_toggle.active),
default_size=145,
)
upper_spinner.on_change("value", upper_spinner_callback)
self.upper_spinner = upper_spinner
# ---- histogram number of bins
def nbins_spinner_callback(_attr, _old_value, _new_value):
self._empty_counts()
nbins_spinner = Spinner(title="Number of Bins:",
low=1,
value=nbins,
default_size=145)
nbins_spinner.on_change("value", nbins_spinner_callback)
self.nbins_spinner = nbins_spinner
# ---- histogram log10 of counts toggle button
def log10counts_toggle_callback(state):
self._empty_counts()
for plot in self.plots:
if state:
plot.yaxis[0].axis_label = "log⏨(Counts)"
else:
plot.yaxis[0].axis_label = "Counts"
log10counts_toggle = CheckboxGroup(labels=["log⏨(Counts)"],
default_size=145)
log10counts_toggle.on_click(log10counts_toggle_callback)
self.log10counts_toggle = log10counts_toggle
h=0.4,
url=dict(value="https://static.bokeh.org/logos/logo.png"),
anchor="center")),
("line", Line(x="x", y="y", line_color="#F46D43")),
("multi_line",
MultiLine(xs="xs", ys="ys", line_color="#8073AC", line_width=2)),
("multi_polygons",
MultiPolygons(xs="xsss",
ys="ysss",
line_color="#8073AC",
fill_color="#FB9A99",
line_width=2)),
("patch", Patch(x="x", y="y", fill_color="#A6CEE3")),
("patches", Patches(xs="xs", ys="ys", fill_color="#FB9A99")),
("quad",
Quad(left="x", right="xp01", top="y", bottom="ym01",
fill_color="#B3DE69")),
("quadratic",
Quadratic(x0="x",
y0="y",
x1="xp02",
y1="y",
cx="xp01",
cy="yp01",
line_color="#4DAF4A",
line_width=3)),
("ray",
Ray(x="x",
y="y",
length=45,
angle=-0.7,
line_color="#FB8072",
def get_plot(raw, today):
dfs, cats = get_sources_and_categories(raw)
# Some times
first_day = raw.loc[0, 'timestamp']
one_week_ago = today - datetime.timedelta(weeks=1)
two_weeks_ago = today - datetime.timedelta(weeks=2)
one_week_forward = today + datetime.timedelta(weeks=1)
# The ranges
all_range = Range1d(start=first_day, end=today)
month_range = Range1d(start=two_weeks_ago, end=one_week_forward)
week_range = Range1d(start=one_week_ago, end=today)
# Selection indicators
highlight = Quad(
left='start', right='end', bottom=0, top=12,
fill_color='white', line_color=COLOR_PRIMARY_CONTRAST, fill_alpha=0.2,
)
lowlight = Quad(
left='start', right='end', bottom=0, top=12,
fill_color=COLOR_PRIMARY, line_color=COLOR_PRIMARY_CONTRAST, fill_alpha=0.5,
)
# Make the complete timeline plot
all_plot = _make_base_plot(dfs, cats, all_range)
detail_selection_source = ColumnDataSource({
'start': [all_range.start, month_range.end],
'end': [month_range.start, all_range.end]
})
all_plot.add_glyph(detail_selection_source, lowlight)
# add a second axis to all_layout plot for presentation
year_ticker = DatetimeTicker(desired_num_ticks=4)
year_ticks = DatetimeTickFormatter(
formats={
'years': ["%Y"],
'months': ["%Y"],
'days': ["%Y"],
'hours': ["%Y"]
}
)
all_plot.add_layout(
DatetimeAxis(formatter=year_ticks, ticker=year_ticker, **AXIS_PROPERTIES),
'below'
)
# Make the detail plot
detail_plot = _make_base_plot(dfs, cats, month_range)
detail_plot.add_tools(PanTool(dimensions=['width']))
detail_plot.add_tools(WheelZoomTool(dimensions=['width']))
detail_plot.add_tools(ResetTool())
week_selection_source = ColumnDataSource({'start': [week_range.start], 'end': [week_range.end]})
detail_plot.add_glyph(week_selection_source, highlight)
detail_code = """
// Update the month selection box on the all_data plot when month pans
var detail_selection_data = detail_selection_source.get('data');
var detail_start = cb_obj.get('frame').get('x_range').get('start');
var detail_end = cb_obj.get('frame').get('x_range').get('end');
new_detail_selection = {
'start': [detail_selection_data['start'][0], detail_end],
'end': [detail_start, detail_selection_data['end'][1]]
};
detail_selection_source.set('data', new_detail_selection);
// Always make sure the week highlight box on detail is visible and centered
var x = moment.duration(detail_end - detail_start).asWeeks() / 2.4;
var start = moment(detail_start);
var week_end = start.add(x, 'weeks').format('x');
$("#one_week_before").text(start.format('ddd, DD MMM YYYY'));
var newStart = start.format('YYYY-MM-DD');
var week_start = start.add(6, 'days').format('x');
$("#today").text(start.format('ddd, DD MMM YYYY'));
new_week_selection = {
'start': [week_start, ],
'end': [week_end, ]
};
week_selection_source.set('data', new_week_selection);
var url = '/timesheet/?start=' + newStart;
$("#timesheet_submit").attr('href', url).addClass("mdl-button--colored");
"""
detail_xrange_callback = CustomJS(args={}, code=detail_code)
detail_xrange_callback.args['detail_selection_source'] = detail_selection_source
detail_xrange_callback.args['week_selection_source'] = week_selection_source
detail_plot.x_range.callback = detail_xrange_callback
return all_plot, detail_plot
fill_alpha='qfillalpha',hatch_pattern='qhatch',source=ptree.leaf_cds,name='leaf_node')#,fill_alpha=0,line_alpha=0)
#qglyph=Quad(left='nodebox_lefts',right='nodebox_rights',bottom='nodebox_bottoms',top='nodebox_tops',fill_color='qcolor',line_alpha=0,\
# hatch_pattern='qhatch')#,fill_alpha=0,line_alpha=0)
#p1.add_glyph(ptree.leaf_cds,qglyph,name='leaf_node')#'leaf_node')#self.ntype)
p1.x_range=Range1d(0,ptree.branch_edgecoords.boundbox.xmax,bounds='auto')
ptree.leaf_cds.add(['normal' for _ in ptree.leaf_cds.data['gbacc']],'rpnl_tfstyle')
ptree.leaf_cds.add(['4pt' for _ in ptree.leaf_cds.data['gbacc']],'rpnl_tfsize')
#ptree.leaf_cds.add(['blank' for _ in ptree.leaf_cds.data['gbacc']],'rpnl_tfsize')
textglyph=Text(x=1,y='nodebox_bottoms',text='gbacc',text_font_size='rpnl_tfsize')#,text_font_style='rpnl_tfstyle')#,text_font='Arial')#,text_align='center')#,name='leaf_node')
p2.add_glyph(ptree.leaf_cds,textglyph)
p2selquad=Quad(left=0,right=1,bottom='nodebox_bottoms',top='nodebox_tops',hatch_pattern="qhatch",hatch_alpha=0.5,fill_color=None,line_color=None)
p2.add_glyph(ptree.leaf_cds,p2selquad)
leafdict=ptree.leaf_cds.data.copy()
eckeepers=[x is not None for x in leafdict['ecs']]
ecdict={}
for key in leafdict:
ecdict[key]=[]
for x,keepvalue in enumerate(eckeepers):
if keepvalue:
ecdict[key].append(leafdict[key][x])
ec_cds=ColumnDataSource(ecdict)
ecqglyph=Quad(left=0,right=2,fill_color='blue',fill_alpha=0.5,line_alpha=0,bottom='nodebox_bottoms',top='nodebox_tops',hatch_pattern="qhatch",hatch_alpha=0.5)
p2.add_glyph(ec_cds,ecqglyph,name='metadata')#'leaf_node')#self.ntype)
pdbkeepers=[x is not None for x in leafdict['pdbids']]
x = np.linspace(-2, 2, N)
y = x**2
source = ColumnDataSource(dict(
left=x,
top=y,
right=x-x**3/10 + 0.3,
bottom=y-x**2/10 + 0.5,
)
)
plot = Plot(
title=None, plot_width=300, plot_height=300,
min_border=0, toolbar_location=None)
glyph = Quad(left="left", right="right", top="top", bottom="bottom", fill_color="#b3de69")
plot.add_glyph(source, glyph)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
yaxis = LinearAxis()
plot.add_layout(yaxis, 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
plot.add_layout(Grid(dimension=1, ticker=yaxis.ticker))
curdoc().add_root(plot)
show(plot)
def __init__(self, **kwargs):
data = progress_quads(dict(all={}, memory={}, erred={}, released={}))
self.source = ColumnDataSource(data=data)
x_range = DataRange1d()
y_range = Range1d(-8, 0)
self.root = Plot(id='bk-task-progress-plot',
x_range=x_range,
y_range=y_range,
toolbar_location=None,
**kwargs)
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='left',
right='right',
fill_color="#aaaaaa",
line_color="#aaaaaa",
fill_alpha=0.2))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='left',
right='released-loc',
fill_color="color",
line_color="color",
fill_alpha=0.6))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='released-loc',
right='memory-loc',
fill_color="color",
line_color="color",
fill_alpha=1.0))
self.root.add_glyph(
self.source,
Quad(top='top',
bottom='bottom',
left='erred-loc',
right='erred-loc',
fill_color='#000000',
line_color='#000000',
fill_alpha=0.3))
self.root.add_glyph(
self.source,
Text(text='show-name',
y='bottom',
x='left',
x_offset=5,
text_font_size=value('10pt')))
self.root.add_glyph(
self.source,
Text(text='done',
y='bottom',
x='right',
x_offset=-5,
text_align='right',
text_font_size=value('10pt')))
hover = HoverTool(point_policy="follow_mouse",
tooltips="""
<div>
<span style="font-size: 14px; font-weight: bold;">Name:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@name</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">All:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@all</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Memory:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@memory</span>
</div>
<div>
<span style="font-size: 14px; font-weight: bold;">Erred:</span>
<span style="font-size: 10px; font-family: Monaco, monospace;">@erred</span>
</div>
""")
self.root.add_tools(hover)
df = DataFrame(
data=[(p.type, p.name, p.pretty_size, p.box.x0, p.box.y0,
p.box.x0 + p.box.dx, p.box.y0 + p.box.dy)
for p in result.get_boxes()],
columns=['type', 'name', 'size', 'left', 'bottom', 'right', 'top'])
source = ColumnDataSource(df)
'''
Get most common file types
Create a color mapper based on color types
Create a Quad glyph with this color mapper
'''
types = df.type.value_counts()[:len(palette)].index
color_mapper = CategoricalColorMapper(palette=sample(palette, len(types)),
factors=list(types))
glyph = Quad(fill_color={'field': 'type', 'transform': color_mapper})
'''
Make a boker.figure of requested size
Add data/glyph
Show the figure
'''
plot = figure(title=title,
plot_width=args.wide,
plot_height=args.tall,
toolbar_location=None,
x_axis_location=None,
y_axis_location=None,
tooltips=[("Location", "@name"), ("Size", "@size")])
plot.add_glyph(source, glyph)
