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z_input.append(int(dport))
proc.wait()
x = np.array(x_input,dtype=np.datetime64)
z = np.array(z_input)
y = np.array(y_input)
w = np.array(w_input)
colors = [
"#%02x%02x%02x" % (int(r), int(g), 150) for r, g in zip(50+z*2, 30+z*2)
]
title = "{} collected on {}/{}/{} at {}".format(source, date[0],date[1],date[2],h)
# Definition of the sequence numbers plot
p_seq = figure(width=1500, height=700, tools=TOOLS, x_axis_type="datetime", title="TCP sequence values in Honeypot {}".format(title))
p_seq.xaxis.axis_label = "Time"
p_seq.yaxis[0].formatter = BasicTickFormatter(use_scientific=False)
p_seq.scatter(x, y, color=colors, legend="seq values", alpha=0.5, )
hoverseq = p_seq.select(dict(type=HoverTool))
hoverseq.tooltips = [
("index", "$index"),
("timestamp", "@x"),
("number", "@y{0,0}")
]
# Definition of the acknowledgement numbers plot
p_ack = figure(width=1500, height=700, tools=TOOLS, x_axis_type="datetime", title="TCP acknowledgement values in Honeypot {}".format(title))
p_ack.xaxis.axis_label = "Time"
p_ack.yaxis[0].formatter = BasicTickFormatter(use_scientific=False)
p_ack.scatter(x, w, color=colors, legend="ack values", alpha=0.5, )
hoverack = p_ack.select(dict(type=HoverTool))
hoverack.tooltips = [
("index", "$index"),
("timestamp", "@x"),
("number", "@y{0,0}")
]
x="__x__values",
y="y",
text="text",
text_font_style="bold",
source=text_source,
)
p.line(
x=[-1.3 - 0.04 * (max_col_stringlength - len(col)), 0],
y=[0.5 - 0.3 * i, -(inner_radius + outer_radius) / 2],
line_color="black",
)
# Define hovertool and add to Pieplot:
if hovertool:
my_hover = HoverTool(renderers=[glyph])
if hovertool_string is None:
my_hover.tooltips = [
(xlabelname, "@__x__values_original"),
(col, "@{%s}" % col),
]
else:
my_hover.tooltips = hovertool_string
p.add_tools(my_hover)
return p
print("{} - {}".format(start_hour,end_hour))
# Export the plot into a png file
if export:
export_png(p, filename = "{}/{}.png".format(output_dir,output_name))
else:
ports = args.port_filter
minutes = 0
# For each period of time corresponding to the timeline
for nb in range(1,int(occurrence_num_hour+1)):
start_min = format(minutes, '02d')
it_minutes = minutes
start_hour, end_hour = string_timeline(h, start_min, format((minutes+timeline),'02d'))
title = " {} collected on {} between {} and {}".format(source, date, start_hour, end_hour)
# Definition of the sequence numbers plot
p_seq = figure(width=1500,height=700,tools=TOOLS, x_axis_type="datetime", title="TCP sequence values in Honeypot {}".format(title))
hoverseq = p_seq.select(dict(type=HoverTool))
hoverseq.tooltips = [
("index", "$index"),
("timestamp", "@x{%F %H:%M:%S}"),
("number", "@y{0,0}")
]
hoverseq.formatters = {
'x': 'datetime'}
p_seq.xaxis.axis_label = "Time"
p_seq.yaxis.axis_label = "Sequence Numbers"
p_seq.yaxis[0].formatter = BasicTickFormatter(use_scientific=False)
# Definition of the aclnowledgement numbers plot
p_ack = figure(width=1500,height=700,tools=TOOLS, x_axis_type="datetime", title="TCP acknowledgement values in Honeypot {}".format(title))
hoverack = p_ack.select(dict(type=HoverTool))
hoverack.tooltips = [
("index", "$index"),
("timestamp", "@x{%F %H:%M:%S}"),
digits_df["image"] = list(map(embeddable_image, digits.images))
datasource = ColumnDataSource(digits_df)
color_mapping = CategoricalColorMapper(
factors=[str(9 - x) for x in digits.target_names], palette=Spectral10
)
plot_figure = figure(
title="UMAP projection of the Digits dataset",
plot_width=600,
plot_height=600,
tools=("pan, wheel_zoom, reset"),
)
plot_figure.add_tools(
HoverTool(
tooltips="""
<div>
<div>
<img style="float: left; margin: 5px 5px 5px 5px" src="@image">
</div>
<div>
<span style="font-size: 16px; color: #224499">Digit:</span>
<span style="font-size: 18px">@digit</span>
</div>
</div>
"""
)
)
plot_figure.circle(
"x",
x = 1. * arange(len(d)) / (len(d) - 1)
mx=max(x) if max(x)>mx else mx
if sn == max(data.keys()):
ci=bp.circle(x,y, size=5, alpha=0.5, color='red', legend="current week: "+getWeekString(sn))
li=bp.line(x,y, line_width=2,line_color='red', legend="current week: "+getWeekString(sn))
else:
ci=bp.circle(x,y, size=5, alpha=0.5, color='gray')
li=bp.line(x,y, line_width=2,line_color='gray')
#hit_target =Circle(x,y, size=10,line_color=None, fill_color=None)
#c.select(dict(type=HoverTool)).tooltips = {"Week": "@week",m:"@"+m.lower()}
#hit_renderers.append(hit_renderer)
bp.add_tools(HoverTool(renderers=[li], tooltips={"Week": getWeekString(sn)}))
c+=1
#bp.text(,y[-1], line_width=2,line_color=OrRd9[c],legend=str(sn))
no_olympics_glyph = Text(x=x[-1], y=y[-1], x_offset=100, text=["%s of %s portals"%(len(d), cnts[sn])],
text_align="right", text_baseline="top",
text_font_size="9pt", text_font_style="italic", text_color="black")
bp.add_glyph(no_olympics_glyph)
bp.x_range=Range1d(0, mx*1.2)
bp.background_fill_color = "#fafafa"
bp.legend.location = "top_left"
return bp
def contig_circle():
""" Create contig circle. """
hover = HoverTool(tooltips=[
('Length', '@contigs')])
hover.point_policy = "follow_mouse"
plot = figure(x_axis_type=None, y_axis_type=None, tools=[hover])
plot.annular_wedge(x=0, y=0, inner_radius=0.5, outer_radius=0.7,
start_angle='start', end_angle='stop', color='colors',
alpha=0.9, source=contig_src)
plot.title = 'Contig lengths'
return plot
fig.line(x=[-2,2],y=[.75,.75],color="black",line_width=3)
fig.multi_line(xs=[[-2.75,-2],[-1.75,-1.0],[-0.75,0],[.25,1],[1.25,2]],
ys=[[0,0.75],[0,0.75],[0,0.75],[0,0.75],[0,0.75]],
color="black",
line_width=3)
fig.line(x='x',y='y',source=Bottom_Line,color="black",line_width=3)
fig.line(x='x',y='y',source=Linking_Line,color="black",line_width=3)
fig.toolbar.logo = None
glob_vars["spring"].plot(fig,width=2)
glob_vars["damper"].plot(fig,width=2)
glob_vars["mass"].plot(fig)
arrow = fig.add_layout(Arrow(end=NormalHead(fill_color="red"), line_color="red", line_width=2,
x_start='x1', y_start='y1', x_end='x2', y_end='y2', source=arrow_line))
# time plot
hover = HoverTool(tooltips=[("time","@t s"), ("displacement","@s m")])
Displacement = figure(title="", y_range=(2,-2), x_range=Range1d(bounds=(0,1000), start=0, end=20), height=550, \
toolbar_location="right", tools=[hover,"ywheel_zoom,xwheel_pan,pan,reset"]) #ywheel_zoom,xwheel_pan,reset,
Displacement.line(x='t',y='s',source=displacement,color="#e37222",line_width=2,legend="Total Displacement",muted_color="#e37222",muted_alpha=0.2)
Displacement.axis.major_label_text_font_size="12pt"
Displacement.axis.axis_label_text_font_style="normal"
Displacement.axis.axis_label_text_font_size="14pt"
Displacement.xaxis.axis_label="Time [s]"
Displacement.yaxis.axis_label="Displacement [u/(F/k)]"
Displacement.legend.location="top_right"
Displacement.legend.click_policy="mute"
Displacement.toolbar.logo = None
#maximum displacement against time of impulse to time period ratio plot
Dis_max = figure(title="", tools="", x_range=(0,3.0), y_range=(0,4), width=600, height=600)
Dis_max.circle(x='time', y='omega', source=omega_max, color="#a2ad00")
p = figure(plot_width=400, plot_height=400,
title="Harvest Plot", x_axis_type='datetime',
tools='pan, wheel_zoom, box_zoom, reset, resize, save, hover')
p.line(x="timestamp", y="relevant_pages", color=GREEN, line_width=0.2,
legend="relevant", source=self.source)
p.scatter(x="timestamp", y="relevant_pages", fill_alpha=0.6,
color=GREEN, source=self.source)
p.line(x="timestamp", y="downloaded_pages", color=DARK_GRAY, line_width=0.2,
legend="downloaded", source=self.source)
p.scatter(x="timestamp", y="downloaded_pages", fill_alpha=0.6,
color=DARK_GRAY, source=self.source)
hover = p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
("harvest_rate", "@harvest_rate"),
])
p.legend.orientation = "top_left"
script, div = components(p)
return (script, div)
color="black",
alpha=0.3,
)
rect = self.root.square(
x="x",
y="y",
size=10,
color=node_colors,
source=self.node_source,
view=node_view,
**{"legend_field" if BOKEH_VERSION >= "1.4" else "legend": "state"},
)
self.root.xgrid.grid_line_color = None
self.root.ygrid.grid_line_color = None
hover = HoverTool(
point_policy="follow_mouse",
tooltips="<b>@name</b>: @state",
renderers=[rect],
)
tap = TapTool(callback=OpenURL(url="info/task/@key.html"), renderers=[rect])
rect.nonselection_glyph = None
self.root.add_tools(hover, tap)
self.max_items = config.get("distributed.dashboard.graph-max-items", 5000)
content=data['Gene_Name'],
annot=data['annotation'],
))
interact_viz = figure(plot_width=900, plot_height=900,
title=method, tools="pan,wheel_zoom,box_zoom,reset,hover,previewsave",
x_axis_type=None, y_axis_type=None, min_border=1)
interact_viz.scatter(x='x', y='y',
source=source,
color='color',
alpha=0.8, size=10,
legend=method)
# hover tools
hover = interact_viz.select(dict(type=HoverTool))
hover.tooltips = [("gene", "@content")]
interact_viz.legend.location = "top_left"
plot_filename = method + "_interactive_plot.html"
output_file(str(self.cfg.unsuperv_figs_out / plot_filename))
save(interact_viz)
if show_plot:
show(interact_viz)
if save_plot:
interact_viz.output_backend = "svg"
plot_filename = method + '_interactive_plot.svg'
export_svgs(interact_viz, filename=(self.cfg.unsuperv_figs_out / plot_filename))