def CreateGauge(percentage, scaleInfo):
gaugeFig = Plot(x_range=Range1d(start=-1.25, end=1.25), y_range=Range1d(start=-1.25, end=1.25), plot_width=250, plot_height=250)
gaugeFig.title.text = "Scale " + str(scaleInfo.Num) + ": " + scaleInfo.Name
gaugeFig.title.align = 'center'
gaugeFig.toolbar_location = None
gaugeFig.border_fill_color = "#101010"
gaugeFig.background_fill_color = "#101010"
gaugeFig.title.text_color = "white"
gaugeFig.outline_line_color = None
glyph = AnnularWedge(x=0, y=0, inner_radius=.7, outer_radius=1, start_angle=math.pi / 2 - (2 * math.pi),
end_angle=math.pi / 2, fill_color="#444444", name="back")
glyph2 = AnnularWedge(x=0, y=0, inner_radius=.7, outer_radius=1, start_angle=math.pi / 2 - (2 * math.pi * percentage),
end_angle=math.pi / 2, fill_color=gaugeColors[(scaleInfo.Num - 1) % len(gaugeColors)], name="front")
PercentageText = Label(text_align='center', text=str(round((percentage * scaleInfo.MaxCapacity), 1)),text_color = 'white',
text_font_size="35px")
lowerText = Label(text_align='center', y=-0.25, text=scaleInfo.Units, text_color='white')
lowerText2 = Label(text_align='center', y=-0.48, text="Of " + str(scaleInfo.MaxCapacity), text_color='white')
gaugeFig.add_glyph(glyph)
gaugeFig.add_glyph(glyph2)
gaugeFig.add_layout(PercentageText)
gaugeFig.add_layout(lowerText)
gaugeFig.add_layout(lowerText2)
return gaugeFig
def test_no_border_or_background_fill(output_file_url, selenium, screenshot):
# Have body background-color that should appear through the no-fill plot
template = Template("""
<!doctype html>
<html lang="en">
<head>
{{ bokeh_js }}
{{ bokeh_css}}
<style>
body { background-color: lightblue; }
</style>
</head>
<body>
{{ plot_script }}
{{ plot_div }}
</body>
</html>
""")
plot = Plot(plot_height=HEIGHT,
plot_width=WIDTH,
x_range=Range1d(0, 10),
y_range=Range1d(0, 10),
toolbar_location=None)
# This is the no-fill that we're testing
plot.background_fill_color = None
plot.border_fill_color = None
plot.add_glyph(Circle(x=3, y=3, size=50, fill_color='#ffffff'))
plot.add_glyph(Circle(x=6, y=6, size=50, fill_color='#ffffff'))
plot.add_layout(
LinearAxis(major_label_text_color='#ffffff',
major_label_text_font_size="30pt"), 'left')
plot.add_layout(
LinearAxis(major_label_text_color='#ffffff',
major_label_text_font_size="30pt"), 'below')
html = file_html(plot, INLINE, template=template)
# filename has to match test function + '.html' light
filepath = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_no_border_or_background_fill.html")
with io.open(filepath, "w", encoding="utf-8") as f:
f.write(decode_utf8(html))
selenium.get(output_file_url)
assert has_no_console_errors(selenium)
assert screenshot.is_valid()
def test_no_border_or_background_fill(output_file_url, selenium, screenshot):
# Have body background-color that should appear through the no-fill plot
template = Template("""
<!doctype html>
<html lang="en">
<head>
{{ bokeh_js }}
{{ bokeh_css}}
<style>
body { background-color: lightblue; }
</style>
</head>
<body>
{{ plot_script }}
{{ plot_div }}
</body>
</html>
""")
plot = Plot(plot_height=HEIGHT, plot_width=WIDTH,
x_range=Range1d(0, 10), y_range=Range1d(0, 10),
toolbar_location=None)
# This is the no-fill that we're testing
plot.background_fill_color = None
plot.border_fill_color = None
plot.add_glyph(Circle(x=3, y=3, size=50, fill_color='#ffffff'))
plot.add_glyph(Circle(x=6, y=6, size=50, fill_color='#ffffff'))
plot.add_layout(LinearAxis(major_label_text_color='#ffffff',
major_label_text_font_size="30pt"),
'left')
plot.add_layout(LinearAxis(major_label_text_color='#ffffff',
major_label_text_font_size="30pt"),
'below')
html = file_html(plot, INLINE, template=template)
# filename has to match test function + '.html' light
filepath = os.path.join(os.path.dirname(os.path.abspath(__file__)),
"test_no_border_or_background_fill.html")
with io.open(filepath, "w", encoding="utf-8") as f:
f.write(decode_utf8(html))
selenium.get(output_file_url)
assert has_no_console_errors(selenium)
screenshot.assert_is_valid()
def render_minimal_graph():
print('rendering minimal graph')
N = 8
node_indices = list(range(N))
plot = Plot(
sizing_mode='stretch_both',
x_range=(-1.1, 1.1), y_range=(-1.1, 1.1),
tools="", toolbar_location=None)
graph_renderer = GraphRenderer()
graph_renderer.node_renderer.glyph = Oval(
height=0.1, width=0.2, fill_color="fill_color", )
graph_renderer.node_renderer.data_source.data = dict(
index=node_indices,
fill_color=Spectral8)
graph_renderer.edge_renderer.data_source.data = dict(
start=[0]*N,
end=node_indices)
# start of layout code (this is the part networkX helps to build!
# the layout...)
circ = [i*2*math.pi/8 for i in node_indices]
x = [math.cos(i) for i in circ]
y = [math.sin(i) for i in circ]
graph_layout = dict(zip(node_indices, zip(x, y)))
graph_renderer.layout_provider = StaticLayoutProvider(
graph_layout=graph_layout)
plot.axis.axis_line_width = 0
plot.grid.grid_line_width = 0
plot.xaxis.major_tick_line_color = None # turn off x-axis major ticks
plot.xaxis.minor_tick_line_color = None # turn off x-axis minor ticks
plot.yaxis.major_tick_line_color = None # turn off y-axis major ticks
plot.yaxis.minor_tick_line_color = None # turn off y-axis minor ticks
plot.xaxis.major_label_text_color = None # Remove label x axis
plot.yaxis.major_label_text_color = None # Remove label x axis
plot.border_fill_color = None
plot.outline_line_color = None
plot.renderers.append(graph_renderer)
return plot
def render_from_fb_combined():
print('rendering from facebook_combined.txt')
df = pd.read_csv('facebook_combined.txt', sep=" ", header=None)
G = nx.from_pandas_edgelist(df.head(1000), 0, 1)
print(nx.info(G))
plot = Plot(background_fill_color="white",
sizing_mode="stretch_both",
x_range=Range1d(-0.5, 0.5), y_range=Range1d(-0.5, 0.5))
graph_renderer = from_networkx(
G, nx.spring_layout, scale=1, center=(0, 0))
graph_renderer.node_renderer.glyph = Circle(
size=15, fill_color=Spectral4[0])
graph_renderer.edge_renderer.glyph = MultiLine(
line_alpha=0.8, line_width=1)
plot.add_tools(WheelZoomTool())
plot.add_tools(ResetTool())
plot.add_tools(PanTool())
plot.add_tools(HoverTool(
tooltips=[("user", "datracka"), ("url", "https://twitter.com/datracka")]))
plot.add_tools(PointDrawTool(
renderers=[], empty_value='black'))
plot.axis.axis_line_width = 0
plot.grid.grid_line_width = 0
plot.xaxis.major_tick_line_color = None # turn off x-axis major ticks
plot.xaxis.minor_tick_line_color = None # turn off x-axis minor ticks
plot.yaxis.major_tick_line_color = None # turn off y-axis major ticks
plot.yaxis.minor_tick_line_color = None # turn off y-axis minor ticks
plot.xaxis.major_label_text_color = None # Remove label x axis
plot.yaxis.major_label_text_color = None # Remove label x axis
plot.border_fill_color = None
plot.outline_line_color = None
plot.renderers.append(graph_renderer)
return plot
from bokeh.io import save
from bokeh.models import Circle, LinearAxis, Plot, Range1d
template ="""
{% block preamble %}
<style>
body { background-color: lightblue; }
</style>
{% endblock %}
"""
plot = Plot(plot_width=600, plot_height=600,
x_range=Range1d(0, 10), y_range=Range1d(0, 10),
toolbar_location=None)
# This is the no-fill that we're testing
plot.background_fill_color = None
plot.border_fill_color = None
plot.add_glyph(Circle(x=3, y=3, size=50, fill_color='#ffffff'))
plot.add_glyph(Circle(x=6, y=6, size=50, fill_color='#ffffff'))
yaxis = LinearAxis(major_label_text_color='#ffffff', major_label_text_font_size="40px")
plot.add_layout(yaxis, 'left')
xaxis = LinearAxis(major_label_text_color='#ffffff', major_label_text_font_size="40px")
plot.add_layout(xaxis, 'below')
save(plot, template=template)
def make_calendar(sp500_data_lst,
djia_data_lst,
nasdaq_data_lst,
twitter_data_lst,
holiday_lst,
nyt_data_lst,
approval_data_lst,
generic_dem_lst,
generic_rep_lst,
plot_wid,
plot_ht,
year,
month,
firstweekday="Sun"):
firstweekday = list(day_abbrs).index(firstweekday)
calendar = Calendar(firstweekday=firstweekday)
month_days = [
None if not day else str(day)
for day in calendar.itermonthdays(year, month)
]
month_weeks = len(month_days) // 7
workday = "linen"
weekend = "lightsteelblue"
def weekday(date):
return (date.weekday() - firstweekday) % 7
def pick_weekdays(days):
return [days[i % 7] for i in range(firstweekday, firstweekday + 7)]
day_names = pick_weekdays(day_abbrs)
week_days = pick_weekdays([workday] * 5 + [weekend] * 2)
source = ColumnDataSource(data=dict(
days=list(day_names) * month_weeks,
weeks=sum([[str(week)] * 7 for week in range(month_weeks)], []),
month_days=month_days,
day_backgrounds=['white'] * len(month_days),
))
djia_data = [(dj_date, DJIA) for (dj_date, DJIA) in djia_data_lst
if dj_date.year == year and dj_date.month == month]
nasdaq_data = [(nas_date, NASDAQCOM)
for (nas_date, NASDAQCOM) in nasdaq_data_lst
if nas_date.year == year and nas_date.month == month]
sp500_data = [(sp500_date, SP500) for (sp500_date, SP500) in sp500_data_lst
if sp500_date.year == year and sp500_date.month == month]
holidays = [(holiday_date, Holiday)
for (holiday_date, Holiday) in holiday_lst
if holiday_date.year == year and holiday_date.month == month]
twitter_data = [
(twitter_date, topics) for (twitter_date, topics) in twitter_data_lst
if twitter_date.year == year and twitter_date.month == month
]
nyt_data = [(nyt_date, headlines) for (nyt_date, headlines) in nyt_data_lst
if nyt_date.year == year and nyt_date.month == month]
approval_data = [
(approval_date, approve_estimate)
for (approval_date, approve_estimate) in approval_data_lst
if approval_date.year == year and approval_date.month == month
]
approval_data.sort()
generic_dem = [(generic_date, dem_estimate)
for (generic_date, dem_estimate) in generic_dem_lst
if generic_date.year == year and generic_date.month == month
]
generic_dem.sort()
generic_rep = [(generic_date, rep_estimate)
for (generic_date, rep_estimate) in generic_rep_lst
if generic_date.year == year and generic_date.month == month
]
generic_rep.sort()
colors_djia = [DJIA for _, DJIA in djia_data]
colors_sp500 = [SP500 for _, SP500 in sp500_data]
colors_nasdaq = [NASDAQCOM for _, NASDAQCOM in nasdaq_data]
for i in range(len(colors_djia) - 1):
avg = np.mean([colors_djia[i], colors_sp500[i], colors_nasdaq[i]])
if 0 < avg <= 11000:
colors_djia[i] = '#E52700'
elif 11000 < avg <= 11100:
colors_djia[i] = '#E33A00'
elif 11100 < avg <= 11200:
colors_djia[i] = '#E14C00'
elif 11200 < avg <= 11300:
colors_djia[i] = '#DF5E00'
elif 11300 < avg <= 11400:
colors_djia[i] = '#DD6F00'
elif 11400 < avg <= 11500:
colors_djia[i] = '#DB8000'
elif 11500 < avg <= 11600:
colors_djia[i] = '#D99100'
elif 11600 < avg <= 11700:
colors_djia[i] = '#D7A100'
elif 11700 < avg <= 11800:
colors_djia[i] = '#D5B100'
elif 11800 < avg <= 11900:
colors_djia[i] = '#D3C100'
elif 11900 < avg <= 12000:
colors_djia[i] = '#D1D000'
elif 12000 < avg <= 12100:
colors_djia[i] = '#BECF00'
elif 12200 < avg <= 12300:
colors_djia[i] = '#ABCD00'
elif 12300 < avg <= 12400:
colors_djia[i] = '#99CB00'
elif 12400 < avg <= 12500:
colors_djia[i] = '#87C900'
elif 12500 < avg <= 12600:
colors_djia[i] = '#75C700'
elif 12500 < avg <= 12600:
colors_djia[i] = '#64C500'
else:
colors_djia[i] = '#53C300'
holiday_source = ColumnDataSource(data=dict(
month_djia=[DJIA for _, DJIA in djia_data],
month_nasdaq=[NASDAQCOM for _, NASDAQCOM in nasdaq_data],
month_sp500=[SP500 for _, SP500 in sp500_data],
month_twitter=[topics for _, topics in twitter_data],
month_holidays=[Holiday for _, Holiday in holidays],
nyt_days=[day_names[weekday(nyt_date)] for nyt_date, _ in nyt_data],
nyt_weeks=['0'] + [
str((weekday(nyt_date.replace(day=1)) + nyt_date.day) // 7)
for nyt_date, _ in nyt_data
],
month_nyt=[headlines for _, headlines in nyt_data],
month_approval=[
approve_estimate for _, approve_estimate in approval_data
],
month_generic_dem=[dem_estimate for _, dem_estimate in generic_dem],
month_generic_rep=[rep_estimate for _, rep_estimate in generic_rep],
day_backgrounds=colors_djia,
))
xdr = FactorRange(factors=list(day_names))
ydr = FactorRange(
factors=list(reversed([str(week) for week in range(month_weeks)])))
x_scale, y_scale = CategoricalScale(), CategoricalScale()
plot = Plot(x_range=xdr,
y_range=ydr,
x_scale=x_scale,
y_scale=y_scale,
plot_width=plot_wid,
plot_height=plot_ht)
plot.title.text = month_names[month] + " " + str(year)
plot.title.text_font_size = "14pt"
plot.title.text_color = "black"
plot.title.offset = 25
plot.min_border_left = 5
plot.min_border_top = 5
plot.min_border_bottom = 190
plot.border_fill_color = "white"
plot.background_fill_alpha = 0.5
plot.border_fill_alpha = 0.3
rect = Rect(x="days",
y="weeks",
width=0.9,
height=0.9,
fill_color="day_backgrounds",
line_color="silver")
plot.add_glyph(source, rect)
rect = Rect(x="nyt_days",
y="nyt_weeks",
width=0.9,
fill_color="day_backgrounds",
height=0.9)
rect_renderer = plot.add_glyph(holiday_source, rect)
text = Text(x="days",
y="weeks",
text="month_days",
text_align="center",
text_baseline="middle")
plot.add_glyph(source, text)
xaxis = CategoricalAxis()
xaxis.major_label_text_font_size = "10pt"
xaxis.major_label_standoff = 0
xaxis.major_tick_line_color = None
xaxis.axis_line_color = None
plot.add_layout(xaxis, 'above')
TOOLTIPS = """
<div style="height:100%; max-width:300px; min-width:200px;background-color: aliceblue; position:relative;">
<div>
<span style="font-size: 17px; font-weight: bold;"> Holiday: @month_holidays</span><br>
<span style="font-size: 15px; font-weight: bold; color: darkgrey;"> Trump Approval Rating: @month_approval{0,0.0}%</span><br>
<span style="font-size: 15px; font-weight: bold; color: blue;"> Generic Democrat: @month_generic_dem{0,0.0}%</span><br>
<span style="font-size: 15px; font-weight: bold; color: red;"> Generic Republican: @month_generic_rep{0,0.0}%</span><br>
<span style="font-size: 17px; font-weight: bold;"> NASDAQ: @month_nasdaq{0,0.00}</span><br>
<span style="font-size: 17px; font-weight: bold;"> DJIA: @month_djia{0,0.00}</span><br>
<span style="font-size: 17px; font-weight: bold;">S&P500: @month_sp500{0,0.00}</span><br>
</div>
<div>
<img
src="/static/img/nyt_logo.png" height="15" width="15"
style="float: left;"></img>
</div>
<div>
<span style="font-size: 17px; font-weight: bold;">NYT Headlines:</span>
<span style="font-size: 15px;">@month_nyt</span>
</div>
<div>
<img
src="/static/img/twitter_logo.png" height="15" width="15"
style="float: left;"></img>
</div>
<div>
<span style="font-size: 17px; color:blue; font-weight: bold;">Trending Tweets:</span>
<span style="font-size: 15px; color:blue;">@month_twitter</span>
</div>
</div>
"""
hover_tool = HoverTool(renderers=[rect_renderer], tooltips=TOOLTIPS)
# hover_tool = HoverTool(renderers=[rect_renderer], tooltips=[("Holiday", "@month_holidays"),("DJIA", "@month_djia{0,0.00}"),
# ("NASDAQ", "@month_nasdaq{0,0.00}"),("S&P500", "@month_sp500{0,0.00}"),("NYT Headlines", "@month_nyt"),("Trending Tweets","@month_twitter")])
plot.tools.append(hover_tool)
return plot
def showGraph(self):
curdoc().theme = 'dark_minimal'
graph_plot = Plot(plot_width=1600,
plot_height=900,
x_range=Range1d(-1.1, 1.1),
y_range=Range1d(-1.1, 1.1))
if self._methood:
graph_plot.title.text = (
"Graph %s \nTotal Nodes: %i \nTotal Edges: %i \n Node threshold:"
"%i \n edge threshold: %i \n Total COMM: %i \n Method: %s" %
(self._path[1], self.G.number_of_nodes(),
self.G.number_of_edges(), self.nodeThres, self.edgeThres,
len(self.partition), self._methood))
else:
graph_plot.title.text = "Graph %s. \nTotal Nodes: %i \nTotal Edges: %i \n Node threshold: %i \n edge threshold: %i" % (
self._path[1], self.G.number_of_nodes(),
self.G.number_of_edges(), self.nodeThres, self.edgeThres)
graph_renderer = from_networkx(self.G,
nx.spring_layout,
scale=1,
center=(0, 0))
graph_renderer.node_renderer.glyph = Circle(size='size',
fill_color='colors')
graph_renderer.node_renderer.hover_glyph = Circle(size=18,
fill_color='#E84A5F')
graph_renderer.node_renderer.glyph.properties_with_values()
graph_renderer.edge_renderer.glyph = MultiLine(line_color="#f2f2f2",
line_alpha=0.8,
line_width=0.4)
graph_renderer.edge_renderer.hover_glyph = MultiLine(
line_color='#e09e8f', line_width=3)
graph_renderer.node_renderer.data_source.data[
'hashtag'] = self.data.ht.values
graph_renderer.node_renderer.data_source.data[
'frequency'] = self.data.frq.values
graph_renderer.node_renderer.data_source.data[
'degree'] = self.data.degree.values
graph_renderer.node_renderer.data_source.data['ix'] = list(
self.data.index)
graph_renderer.node_renderer.data_source.data[
'strength'] = self.data.strength.values
graph_renderer.node_renderer.data_source.data['size'] = np.log(
(self.data.degree.values + 1) * 3) * 6
if self.community:
graph_renderer.node_renderer.data_source.data[
'colors'] = self.data.color.values
graph_renderer.node_renderer.data_source.data[
'community'] = self.data.community.values
node_hover_tool = HoverTool(tooltips=[(
"hashtag",
"@hashtag"), ("freq", "@frequency"), (
'degree',
'@degree'), ('strength',
'@strength'), ('community',
'@community'), ('ix', '@ix')])
else:
graph_renderer.node_renderer.data_source.data['colors'] = [
'red'
] * self.G.number_of_nodes()
node_hover_tool = HoverTool(
tooltips=[("hashtag", "@hashtag"), (
"freq",
"@frequency"), ('degree',
'@degree'), ('strength',
'@strength'), ('ix', '@ix')])
graph_plot.add_tools(node_hover_tool, BoxZoomTool(), ResetTool(),
WheelZoomTool())
graph_plot.toolbar.active_scroll = graph_plot.select_one(WheelZoomTool)
graph_renderer.inspection_policy = NodesAndLinkedEdges()
graph_renderer.selection_policy = NodesAndLinkedEdges()
graph_plot.toolbar.active_inspect = [node_hover_tool]
graph_plot.renderers.append(graph_renderer)
graph_plot.background_fill_color = '#0d0d0d'
graph_plot.background = 'black'
graph_plot.border_fill_color = '#1a1a1a'
if self.partition:
legend = Legend(items=[
LegendItem(label="coverage: %f" %
nx.community.coverage(self.G, self.partition),
index=0),
LegendItem(label="performance: %f" %
nx.community.performance(self.G, self.partition),
index=1),
LegendItem(label="modularity: %f" %
nx.community.modularity(self.G, self.partition),
index=2)
])
graph_plot.add_layout(legend)
output_file(self._path[0] + "Graph_NT" + str(self.nodeThres) + "ET" +
str(self.edgeThres) + ".html")
show(graph_plot)
return
