def population():
xdr = FactorRange(factors=years)
ydr = DataRange1d()
x_scale = CategoricalScale()
plot = Plot(x_range=xdr,
y_range=ydr,
x_scale=x_scale,
plot_width=600,
plot_height=150,
toolbar_location=None)
plot.add_layout(CategoricalAxis(major_label_orientation=pi / 4), 'below')
known = Line(x="x", y="y", line_color="violet", line_width=2)
known_glyph = plot.add_glyph(source_known, known)
predicted = Line(x="x",
y="y",
line_color="violet",
line_width=2,
line_dash="dashed")
predicted_glyph = plot.add_glyph(source_predicted, predicted)
legend = Legend(location="bottom_right",
items=[("known", [known_glyph]),
("predicted", [predicted_glyph])])
plot.add_layout(legend)
return plot
def pyramid():
xdr = DataRange1d()
ydr = FactorRange(factors=groups)
y_scale = CategoricalScale()
plot = Plot(x_range=xdr,
y_range=ydr,
y_scale=y_scale,
plot_width=600,
plot_height=500,
toolbar_location=None)
xaxis = LinearAxis()
plot.add_layout(xaxis, 'below')
plot.add_layout(CategoricalAxis(), 'left')
plot.add_layout(Grid(dimension=0, ticker=xaxis.ticker))
m = HBar(left="value", right=0, y="group", height=1, fill_color="#3B8686")
mglyph = plot.add_glyph(source_pyramid_m, m)
f = HBar(left=0, right="value", y="group", height=1, fill_color="#CFF09E")
fglyph = plot.add_glyph(source_pyramid_f, f)
plot.add_layout(Legend(items=[("Male", [mglyph]), ("Female", [fglyph])]))
return plot
def test_reset_triggers_factorrange_callbacks(self, single_plot_page):
source = ColumnDataSource(dict(x=["a", "b"], y=["a", "a"]))
plot = Plot(plot_height=400,
plot_width=400,
x_scale=CategoricalScale(),
x_range=FactorRange(factors=["a", "b", "c"]),
y_scale=CategoricalScale(),
y_range=FactorRange(factors=["a", "b", "c"]),
min_border=0)
plot.add_glyph(source, Circle(x='x', y='y', size=20))
plot.add_tools(ResetTool(), ZoomInTool())
plot.x_range.callback = CustomJS(code=COUNT("xrcb"))
plot.x_range.js_on_change('start', CustomJS(code=COUNT("xrstart")))
plot.x_range.js_on_change('end', CustomJS(code=COUNT("xrend")))
plot.y_range.callback = CustomJS(code=COUNT("yrcb"))
plot.y_range.js_on_change('start', CustomJS(code=COUNT("yrstart")))
plot.y_range.js_on_change('end', CustomJS(code=COUNT("yrend")))
page = single_plot_page(plot)
# Change the ranges using a zoom in tool
button = page.get_toolbar_button('zoom-in')
button.click()
results = page.results
assert results['xrcb'] == 1
assert results['xrstart'] == 1
assert results['xrend'] == 1
assert results['yrcb'] == 1
assert results['yrstart'] == 1
assert results['yrend'] == 1
# Click the reset tool and check the callback was called
button = page.get_toolbar_button('reset')
button.click()
results = page.results
assert results['xrcb'] == 3
assert results['xrstart'] == 2
assert results['xrend'] == 2
assert results['yrcb'] == 3
assert results['yrstart'] == 2
assert results['yrend'] == 2
assert page.has_no_console_errors()
def test__check_compatible_scale_and_ranges_incompat_factor_scale_and_numeric_range(
) -> None:
plot = Plot(x_scale=CategoricalScale(), x_range=DataRange1d())
check = plot._check_compatible_scale_and_ranges()
assert check != []
def test__check_compatible_scale_and_ranges_compat_factor() -> None:
plot = Plot(x_scale=CategoricalScale(), x_range=FactorRange())
check = plot._check_compatible_scale_and_ranges()
assert check == []
for name in groups.__all__:
group = getattr(groups, name)
data.extend([(str(x), x.to_hex(), group.__name__) for x in group])
css3_colors = pd.DataFrame(data, columns=["Name", "Color", "Group"])
source = ColumnDataSource(
dict(
names=list(css3_colors.Name),
groups=list(css3_colors.Group),
colors=list(css3_colors.Color),
))
xdr = FactorRange(factors=list(css3_colors.Group.unique()))
ydr = FactorRange(factors=list(reversed(css3_colors.Name)))
x_scale, y_scale = CategoricalScale(), CategoricalScale()
plot = Plot(x_range=xdr,
y_range=ydr,
x_scale=x_scale,
y_scale=y_scale,
plot_width=600,
plot_height=2000)
plot.title.text = "CSS3 Color Names"
rect = Rect(x="groups",
y="names",
width=1,
height=1,
fill_color="colors",
line_color=None)
def make_calendar(year, month, firstweekday="Mon"):
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 = sum([week_days]*month_weeks, []),
))
holidays = [ (date, summary.replace("(US-OPM)", "").strip()) for (date, summary) in us_holidays
if date.year == year and date.month == month and "(US-OPM)" in summary ]
holidays_source = ColumnDataSource(data=dict(
holidays_days = [ day_names[weekday(date)] for date, _ in holidays ],
holidays_weeks = [ str((weekday(date.replace(day=1)) + date.day) // 7) for date, _ in holidays ],
month_holidays = [ summary for _, summary in holidays ],
))
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=300, plot_height=300, outline_line_color=None)
plot.title.text = month_names[month]
plot.title.text_font_size = "16px"
plot.title.text_color = "darkolivegreen"
plot.title.offset = 25
plot.min_border_left = 0
plot.min_border_bottom = 5
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="holidays_days", y="holidays_weeks", width=0.9, height=0.9, fill_color="pink", line_color="indianred")
rect_renderer = plot.add_glyph(holidays_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 = "11px"
xaxis.major_label_standoff = 0
xaxis.major_tick_line_color = None
xaxis.axis_line_color = None
plot.add_layout(xaxis, 'above')
hover_tool = HoverTool(renderers=[rect_renderer], tooltips=[("Holiday", "@month_holidays")])
plot.tools.append(hover_tool)
return plot
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