def newapplet():
theme = request.args.get('theme', 'default')
INLINE = Resources(
mode="inline",
minified=False,
)
templname = "stocks_custom.html"
js_resources = JS_RESOURCES.render(js_raw=INLINE.js_raw,
js_files=INLINE.js_files)
css_resources = CSS_RESOURCES.render(css_raw=INLINE.css_raw,
css_files=INLINE.css_files)
p = create_main_plot(theme)
plot_script, extra_divs = components({
"main_plot":
p,
"selection_plot":
create_selection_plot(p, theme),
})
themes = ["default", "dark"]
options = {k: 'selected="selected"' if theme == k else "" for k in themes}
return render_template(
templname,
theme=theme,
extra_divs=extra_divs,
plot_script=plot_script,
js_resources=js_resources,
css_resources=css_resources,
theme_options=options,
)
def newapplet():
theme = request.args.get('theme', 'default')
INLINE = Resources(mode="inline", minified=False,)
templname = "stocks_custom.html"
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
p = create_main_plot(theme)
plot_script, extra_divs = components(
{
"main_plot": p,
"selection_plot": create_selection_plot(p, theme),
}
)
themes = ["default", "dark"]
options = { k: 'selected="selected"' if theme == k else "" for k in themes}
return render_template(
templname,
theme = theme,
extra_divs = extra_divs,
plot_script = plot_script,
js_resources=js_resources,
css_resources=css_resources,
theme_options=options,
)
def graphstocks(ssymbol):
""" Very simple embedding of a polynomial chart"""
# Grab the inputs arguments from the URL
# This is automated by the button
args = ["ADAM"]
args = request.args
# Get all the form arguments in the url with defaults
color = colors[getitem(args, 'color', 'Black')]
_from = int(getitem(args, '_from', 0))
to = int(getitem(args, 'to', 10))
# Create a polynomial line graph
#x = list(range(_from, to + 1))
#fig = figure(title="Polynomial")
#fig.line(x, [i ** 2 for i in x], color=color, line_width=2)
AAPL= pd.read_csv("https://ichart.yahoo.com/table.csv?s="+ssymbol+"&a=0&b=1&c=2000&d=0&e=1&f=2010",parse_dates=['Date'])
data = dict(AAPL=AAPL['Adj Close'], Date=AAPL['Date'])
tsline = TimeSeries(data,x='Date', y='AAPL', ylabel='Stock Prices', legend=True)
#tsline=TimeSeries(data,x='Date', y=['AAPL'], color=['AAPL'], dash=['AAPL'],
# title="Timeseries", ylabel = 'Stock Prices', legend=True)
# tspoint=TimeSeries(data,x='Date',y=[ssymbol], dash=[ssymbol],title="Timeseries",ylabel='Stock Prices', legend=True)
output_file("timeseries.html")
fig=vplot(tsline)
# Configure resources to include BokehJS inline in the document.
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
#from: http://bokeh.pydata.org/en/0.11.1/docs/releases/0.11.0.html
# Before:
#html = file_html(layout, None, title=title, template=template, js_resources=js_resources, css_resources=css_resources)
#v0.11:
#
#html = file_html(layout, resources=(js_resources, css_resources), title=title, template=template)
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(fig, INLINE)
html = render_template(
'embed.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
color=color,
_from=_from,
to=to
)
return encode_utf8(html)
def model():
pTOOLS = "crosshair,hover,pan,box_zoom,reset,save"
p2 = figure(tools=pTOOLS,background_fill="#dbe0eb",
x_range = (0,100),
y_range =(80,100),
x_axis_label='Decision Boundary (score)',
y_axis_label='Precision',
title='Recall and Precision',
plot_height=600,
plot_width=800)
# Setting the second y axis range name and range
p2.extra_y_ranges = {"foo": Range1d(start=-5, end=105)}
# Adding the second axis to the plot.
p2.add_layout(LinearAxis(y_range_name="foo",axis_label="Recall",
axis_label_text_color = "red",
major_label_text_color = "red"), 'right')
source1 = ColumnDataSource(
data=dict(precision = crit_r_c[1]*100, recall = crit_r_c[2]*100.0/153546,
risk = 100 - crit_r_c[1]*100, miss = 100- crit_r_c[2]*100.0/153546))
source2 = ColumnDataSource(
data=dict(precision = crit_r_c[1]*100, recall = crit_r_c[2]*100.0/153546,
risk = 100 - crit_r_c[1]*100, miss = 100- crit_r_c[2]*100.0/153546))
p2.line(crit_r_c[0],crit_r_c[1]*100,line_color="blue", line_width=20, alpha=0.7,source=source1)
p2.line(crit_r_c[0],crit_r_c[2]*100.0/153546,line_color="red", line_width=20, alpha=0.7,y_range_name="foo",source=source2)
hover = p2.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
('Decison Boundary (score)', '$x'),
("Precision (%)","@precision"),
("Risk (%)", "@risk"),
("Recall (%)", "@recall"),
("Missed Opportunity (%)", "@miss"),
])
js_resources2 = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files)
css_resources2 = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files)
p2script, p2div = components(p2, INLINE)
html = flask.render_template(
'model.html',
plot_script2=p2script, plot_div2=p2div,
js_resources=js_resources2,
css_resources=css_resources2)
return encode_utf8(html)
def test_file_html_handles_css_only_resources():
css_resources = CSSResources()
template = Template("<head>{{ bokeh_css }}</head><body></body>")
output = embed.file_html(_embed_test_plot,
None,
"title",
template=template,
css_resources=css_resources)
rendered_css = CSS_RESOURCES.render(css_raw=css_resources.css_raw)
assert output == "<head>%s</head><body></body>" % rendered_css
def graphstocks(ssymbol, sdate, edate,color):
stock = ssymbol
if color not in colors:
color="Black"
api_url='https://www.quandl.com/api/v3/datasets/WIKI/%(symbol)s.json?api_key=%(key)s&start_date=%(sdate)s&end_date=%(edate)s' % {"symbol":stock, "key":YOURAPIKEY,"sdate":sdate, "edate":edate}
session = requests.Session()
session.mount('http://', requests.adapters.HTTPAdapter(max_retries=3))
raw_data=session.get(api_url)
aapl_stock=raw_data.json()
color="Black"
cnames = aapl_stock['dataset']['column_names']
df = pandas.DataFrame(aapl_stock['dataset']['data'],columns=cnames) # create dataframe and assign column names
df['Date']=pandas.to_datetime(df['Date']) # convert Date column to DateTime in place
tsline = TimeSeries(df,x='Date', y='Close', ylabel=ssymbol+' Stock Prices', legend=True, color=colors[color])
fig=vplot(tsline)
# Configure resources to include BokehJS inline in the document.
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
#from: http://bokeh.pydata.org/en/0.11.1/docs/releases/0.11.0.html
# Before:
#html = file_html(layout, None, title=title, template=template, js_resources=js_resources, css_resources=css_resources)
#v0.11:
#
#html = file_html(layout, resources=(js_resources, css_resources), title=title, template=template)
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(fig, INLINE)
html = render_template(
'embed.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
color=color,
_from=sdate,
to=edate,
symbol_lulu=ssymbol
)
return encode_utf8(html)
def polynomial():
""" Very simple embedding of a polynomial chart"""
# Grab the inputs arguments from the URL
# This is automated by the button
args = flask.request.args
# Get all the form arguments in the url with defaults
color = colors[getitem(args, 'color', 'Black')]
_from = int(getitem(args, '_from', 0))
to = int(getitem(args, 'to', 10))
# Create a polynomial line graph
x = list(range(_from, to + 1))
fig = figure(title="Polynomial")
fig.line(x, [i ** 2 for i in x], color=color, line_width=2)
# Configure resources to include BokehJS inline in the document.
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(fig, INLINE)
html = flask.render_template(
'embed.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
color=color,
_from=_from,
to=to
)
return encode_utf8(html)
def polynomial():
""" Very simple embedding of a polynomial chart"""
# Grab the inputs arguments from the URL
# This is automated by the button
args = flask.request.args
# Get all the form arguments in the url with defaults
color = colors[getitem(args, 'color', 'Black')]
_from = int(getitem(args, '_from', 0))
to = int(getitem(args, 'to', 10))
# Create a polynomial line graph
x = list(range(_from, to + 1))
fig = figure(title="Polynomial")
fig.line(x, [i**2 for i in x], color=color, line_width=2)
# Configure resources to include BokehJS inline in the document.
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#bokeh-embed
js_resources = JS_RESOURCES.render(js_raw=INLINE.js_raw,
js_files=INLINE.js_files)
css_resources = CSS_RESOURCES.render(css_raw=INLINE.css_raw,
css_files=INLINE.css_files)
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(fig, INLINE)
html = flask.render_template('embed.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
color=color,
_from=_from,
to=to)
return encode_utf8(html)
{{ plot_div.blue }}
{{ plot_script }}
</body>
</html>
''')
resources = INLINE
js_resources = JS_RESOURCES.render(
js_raw=resources.js_raw,
js_files=resources.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=resources.css_raw,
css_files=resources.css_files
)
script, div = components({'red': red, 'blue': blue, 'green': green})
html = template.render(js_resources=js_resources,
css_resources=css_resources,
plot_script=script,
plot_div=div)
html_file = 'embed_multiple_responsive.html'
with open(html_file, 'w') as f:
f.write(html)
view(html_file)
app = flask.Flask(__name__)
colors = {
'Black': '#000000',
'Red': '#FF0000',
'Green': '#00FF00',
'Blue': '#0000FF',
}
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
@app.route("/figure1")
def plot_data():
# get data
x = []
y = []
colors = []
i = 0
with open("data.csv", "r") as f:
while True:
line = f.readline()
if len(line) == 0:
break
if i == 6:
def prediction():
args = session['loan']
Grade = args['sub_grade']
x = pd.DataFrame(args,index=[0])
x_dict = List2DictT.transform(x)
x_vect = DictVectorT.transform(x_dict)
x_y_prob = []
for RF in FinalTotModes[:-1]:
x_y_prob.append(RF.predict_proba(x_vect)[:,0])
y_pred = FinalTotModes[-1].predict_proba(np.array(x_y_prob).T)
YourLoan = int(y_pred[:,1]*100)
Loc = int(YourLoan/5)
xgrades =[i for i in ScoreByGrade.index]
Beats = ['%.2f' %(ScoreByGrade.PayoffProba.iloc[Loc]*100) +
' (your loan is better than %.2f%% of loans)' % (sum(ScoreByGrade[Grade].iloc[:Loc]))]
Median = MedianScore.loc[Grade].prob
MedianLoc = MedianLoc = int(Median)/5+1
TOOLS = "hover,pan,box_zoom,reset,save"
p = figure(background_fill='white',
x_range=[2,102],
x_axis_label='Score assigned by the model',
y_range = [0, int(max(ScoreByGrade[Grade]))+3],
title="Score of " + Grade + " loans",
y_axis_label='Counts per 100 loans',
tools = TOOLS,
plot_width=1000,
plot_height=600)
source1 = ColumnDataSource(
data=dict(payoffProb = ScoreByGrade.PayoffProba.values*100,
distribution = ScoreByGrade[Grade].values,
scores = ['%d-%d' %(i-4,i) for i in ScoreByGrade.index]))
source2 = ColumnDataSource(
data=dict(payoffProb = Beats, distribution =[ScoreByGrade[Grade].iloc[Loc]],
scores = ['%d-%d' %(i-4,i) for i in [ScoreByGrade.index[Loc]]]))
source3 = ColumnDataSource(
data=dict(payoffProb = [ScoreByGrade.PayoffProba.iloc[MedianLoc]*100],
distribution =[ScoreByGrade[Grade].iloc[MedianLoc]],
scores = ['%d' %(Median) ]))
p.rect(xgrades, ScoreByGrade[Grade]/2, 0.6*5, ScoreByGrade[Grade],
fill_color="#08c994",source = source1)
p.rect([xgrades[Loc]], ScoreByGrade[Grade].iloc[Loc]/2, 0.6*5, ScoreByGrade[Grade].iloc[Loc],
fill_color="#ff5a00",source = source2, legend='Score of your loan')
# p.xaxis.major_label_orientation = np.pi/6
p.rect([Median], (int(max(ScoreByGrade[Grade]))+1)/2.0, 0.15*5, (int(max(ScoreByGrade[Grade]))+1),
fill_color="black",source = source3, legend='Average Score')
# p.line([Median,Median],[0,int(max(ScoreByGrade[Grade]))+1],
# line_color="black", line_width=10, legend='Average Score',
# source = source3)
hover = p.select(dict(type=HoverTool))
hover.tooltips = OrderedDict([
("Score","@scores"),
("Within 100 loans", "@distribution in this group"),
('Payoff chance (%)', '@payoffProb'),
])
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
script, div = components(p, INLINE)
if YourLoan>=60:
ShouldOrNot = 'SHOULD'
tmplt ="result_success.html"
elif YourLoan>=50:
ShouldOrNot = 'MAY'
tmplt ="result_success.html"
elif YourLoan>=40:
ShouldOrNot = 'may NOT'
tmplt ="result_failure.html"
else:
ShouldOrNot = 'should NOT'
tmplt ="result_failure.html"
pTOOLS = "crosshair,hover,pan,box_zoom,reset,save"
p2 = figure(background_fill='white',
x_axis_label='Score assigned by the model',
title="Score versus Success rate",
y_axis_label='Success rate (%)',
tools = pTOOLS,
plot_width=1000,
plot_height=600)
p2.line(ScoreByGrade.index,ScoreByGrade.PayoffProba*100,line_color="blue", line_width=20, alpha=0.7)
r2 = p2.circle(Median,ScoreByGrade.PayoffProba.iloc[MedianLoc]*100-3,color="black",legend='Average Loan')
r = p2.circle(YourLoan,ScoreByGrade.PayoffProba.iloc[Loc]*100-3,color="#ff5a00",legend='Your Loan')
def glyy(r,colors):
glyph = r.glyph
glyph.size = 40
glyph.fill_alpha = 0.5
glyph.line_color = colors
glyph.line_dash = [6, 3]
glyph.line_width = 2
glyy(r,"#ff5a00")
glyy(r2,"black")
p2.grid.grid_line_alpha=0.7
p2.legend.orientation = "top_left"
hover2 = p2.select(dict(type=HoverTool))
hover2.tooltips = OrderedDict([
('Score', "$x"),
('Payoff chance (%)', '$y')])
js_resources2 = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files)
css_resources2 = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files)
p2script, p2div = components(p2, INLINE)
html = flask.render_template(
tmplt,
plot_script=script, plot_div=div,
plot_script2=p2script, plot_div2=p2div,
js_resources=js_resources,
css_resources=css_resources,
score=YourLoan,
beats="%.2f" %(sum(ScoreByGrade[Grade].iloc[:Loc])),
prob="%.2f" %(ScoreByGrade.PayoffProba.iloc[Loc]*100),
invest=ShouldOrNot)
return encode_utf8(html)
def static_html(template, title="bokehutils plot", resources=INLINE, css_raw=None, template_variables=None):
"""Render static html document.
This is a minor modification of :py:meth:`bokeh.embed.file_html`.
Args:
template (Template): a Jinja2 HTML document template
title (str): a title for the HTML document ``<title>`` tags.
resources (Resources): a resource configuration for BokehJS assets
css_raw (list): a list of file names for inclusion in the raw css
template_variables (dict): variables to be used in the Jinja2
template. In contrast to :py:meth:`bokeh.embed.file_html`,
this is where plot objects are placed. The plot objects will
be automagically split into script and div components. If
used, the following variable names will be overwritten:
title, js_resources, css_resources
Returns:
html : standalone HTML document with embedded plot
"""
# From bokeh.resources
def _inline(paths):
strings = []
for path in paths:
begin = "/* BEGIN %s */" % path
middle = open(path, 'rb').read().decode("utf-8")
end = "/* END %s */" % path
strings.append(begin + '\n' + middle + '\n' + end)
return strings
# Assume we always have resources
js_resources = resources
css_resources = resources
bokeh_js = ''
if js_resources:
bokeh_js = JS_RESOURCES.render(js_raw=js_resources.js_raw, js_files=js_resources.js_files)
bokeh_css = ''
_css_raw = css_resources.css_raw
if css_raw:
tmp = lambda: _inline(css_raw)
_css_raw += tmp()
if css_resources:
bokeh_css = CSS_RESOURCES.render(css_raw=_css_raw, css_files=css_resources.css_files)
# Hack to get on-the-fly double mapping
def _update(template_variables):
tmp = {}
for k, v in template_variables.items():
if (isinstance(v, Widget)):
tmp.update({k: [{'script': s, 'div': d}
for s, d in [components(v, resources)]][0]})
elif (isinstance(v, dict)):
if not v:
tmp.update(v)
else:
v.update(_update(v))
else:
tmp.update({k: v})
return tmp
template_variables.update(_update(template_variables))
template_variables_full = \
template_variables.copy() if template_variables is not None else {}
template_variables_full.update(
{
'title' : title,
'bokeh_js' : bokeh_js,
'bokeh_css' : bokeh_css,
}
)
html = template.render(template_variables_full)
return encode_utf8(html)
def output():
ALL = request.args.get('ALL')
if ALL == "ALL":
input_team = ['ATL', 'BOS', 'BKN', 'CHA', 'CHI', 'CLE', 'DAL',
'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL',
'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC',
'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR',
'UTA', 'WAS']
else:
ATL = request.args.get('ATL')
BOS = request.args.get('BOS')
BKN = request.args.get('BKN')
CHA = request.args.get('CHA')
CHI = request.args.get('CHI')
CLE = request.args.get('CLE')
DAL = request.args.get('DAL')
DET = request.args.get('DET')
GSW = request.args.get('GSW')
HOU = request.args.get('HOU')
IND = request.args.get('IND')
LAC = request.args.get('LAC')
LAL = request.args.get('LAL')
MEM = request.args.get('MEM')
MIA = request.args.get('MIA')
MIL = request.args.get('MIL')
NOP = request.args.get('NOP')
OKC = request.args.get('OKC')
ORL = request.args.get('ORL')
PHO = request.args.get('PHO')
POR = request.args.get('POR')
SAC = request.args.get('SAC')
SAS = request.args.get('SAS')
TOR = request.args.get('TOR')
UTA = request.args.get('UTA')
WAS = request.args.get('WAS')
teams = [ATL, BOS, BKN, CHA, CHI, CLE, DAL, DET, GSW, HOU, IND,
LAC, LAL, MEM, MIA, MIL, NOP, OKC, ORL, PHO, POR, SAC,
SAS, TOR, UTA, WAS]
input_team = []
for team in teams:
if team:
input_team += [team]
if len(input_team) < 1:
input_team = ['ATL', 'BOS', 'BKN', 'CHA', 'CHI', 'CLE', 'DAL',
'DEN', 'DET', 'GSW', 'HOU', 'IND', 'LAC', 'LAL',
'MEM', 'MIA', 'MIL', 'MIN', 'NOP', 'NYK', 'OKC',
'ORL', 'PHI', 'PHO', 'POR', 'SAC', 'SAS', 'TOR',
'UTA', 'WAS']
# Grab data off database
sql = "SELECT * FROM results"
df = pd.read_sql_query(sql, g.db)
df = df.drop('index', axis = 1)
df = df[df['team'].isin(input_team)]
df = df.sort_values('points', ascending = False)
df = df.reset_index().drop('index', axis = 1)
# Round values for display purposes
for col in ['avg_pm','pred','points']:
df[col] = np.round(df[col], 1)
entries = [dict(lineup = df['lineup'][row],
team = df['team'][row],
opponent = df['opponent'][row],
month = df['month'][row],
day = df['dayofmonth'][row],
base = df['avg_pm'][row],
pred = df['pred'][row],
points = df['points'][row]) for row in range(df.shape[0])]
# Get dimensions of screen with Tkinter
root = tk.Tk()
scr_width = root.winfo_screenwidth()
scr_height = root.winfo_screenheight()
wide = scr_width * 0.4
height = scr_height * 0.45
# MAKE PLOT DATA
pred = np.array(df['pred'])
y_test = np.array(df['points'])
avg_pm = np.array(df['avg_pm'])
# Configure resources to include BokehJS inline in the document.
js_resources = JS_RESOURCES.render(
js_raw=INLINE.js_raw,
js_files=INLINE.js_files
)
css_resources = CSS_RESOURCES.render(
css_raw=INLINE.css_raw,
css_files=INLINE.css_files
)
source = ColumnDataSource(data = dict(x = y_test,
y = pred,
lineup = np.array(df['lineup']),
base = np.array(df['avg_pm']),
month = np.array(df['month']),
day = np.array(df['dayofmonth']),
team = np.array(df['team']),
opponent = np.array(df['opponent'])
)
)
# create a new plot with the tools above, and explicit ranges
TOOLS = "resize, pan, wheel_zoom, box_zoom, reset, hover"
p = figure(tools = TOOLS, x_range=(-175,175), y_range=(-175, 175),
plot_width = int(wide), plot_height = int(height))
# Plot fill quadrant 1 and 4
p.patch([0, 0, 5000, 5000], [0, 5000, 5000, 0],
alpha = 0.3, color = (6, 110, 10))
p.patch([0, 0, -5000, -5000],[0, -5000, -5000, 0],
alpha = 0.3, color = (6, 110, 10))
# Plot results
p.line(np.arange(-2000,2000,100), np.arange(-2000,2000,100),
line_width = 2, color = "grey", legend = "Perfect Prediction")
p.circle('x', 'y', source = source, radius=3,
color = (153, 0, 51), alpha = 0.9, legend = "New Model")
# Plot styling
p.text(50, 150, text = ['True Positive:'], text_font_size="10pt")
p.text(50, 135, text = ['Favorable Matchup'], text_font_size="10pt")
p.text(-120, -135, text = ['True Negative:'], text_font_size="10pt")
p.text(-120, -150, text = ['Unfavorable Matchup'], text_font_size="10pt")
p.text(80, -135, text = ['False Negative:'], text_font_size="10pt")
p.text(80, -150, text = ['Missed Opportunity'], text_font_size="10pt")
p.text(-150, 100, text = ['False Positive:'], text_font_size="10pt")
p.text(-150, 85, text = ['Mistaken Prediction'], text_font_size="10pt")
p.legend.orientation = "top_left"
p.xaxis.axis_label = 'Actual +/- (points/48min)'
p.yaxis.axis_label = 'Predicted +/- (points/48min)'
hover = p.select(dict(type=HoverTool))
hover.point_policy = "follow_mouse"
hover.tooltips = OrderedDict([("Lineup", "@lineup"),
("Team", "@team"),
("Opponent", "@opponent"),
("(Month, Day)", "(@month, @day)"),
("Actual", "@x"),
("Prediction", "@y"),
("Base Model", "@base")])
plot_script, plot_div = components(p)
# convert input_team to a string for html and then passed to img function
input_team = ','.join(input_team)
"""
# Debugging
output_file("tt2.html")
f = open('tfile', 'w')
f.write(plot_script)
f.close()
show(p)
"""
html = render_template("result.html", input_team = input_team,
entries = entries, wide = wide, height = height,
plot_script = plot_script, plot_div = plot_div,
js_resources=js_resources,
css_resources=css_resources)
return encode_utf8(html)
def static_html(template,
title="bokehutils plot",
resources=INLINE,
css_raw=None,
template_variables=None):
"""Render static html document.
This is a minor modification of :py:meth:`bokeh.embed.file_html`.
Args:
template (Template): a Jinja2 HTML document template
title (str): a title for the HTML document ``<title>`` tags.
resources (Resources): a resource configuration for BokehJS assets
css_raw (list): a list of file names for inclusion in the raw css
template_variables (dict): variables to be used in the Jinja2
template. In contrast to :py:meth:`bokeh.embed.file_html`,
this is where plot objects are placed. The plot objects will
be automagically split into script and div components. If
used, the following variable names will be overwritten:
title, js_resources, css_resources
Returns:
html : standalone HTML document with embedded plot
"""
# From bokeh.resources
def _inline(paths):
strings = []
for path in paths:
begin = "/* BEGIN %s */" % path
middle = open(path, 'rb').read().decode("utf-8")
end = "/* END %s */" % path
strings.append(begin + '\n' + middle + '\n' + end)
return strings
# Assume we always have resources
js_resources = resources
css_resources = resources
bokeh_js = ''
if js_resources:
bokeh_js = JS_RESOURCES.render(js_raw=js_resources.js_raw,
js_files=js_resources.js_files)
bokeh_css = ''
_css_raw = css_resources.css_raw
if css_raw:
tmp = lambda: _inline(css_raw)
_css_raw += tmp()
if css_resources:
bokeh_css = CSS_RESOURCES.render(css_raw=_css_raw,
css_files=css_resources.css_files)
# Hack to get on-the-fly double mapping
def _update(template_variables):
tmp = {}
for k, v in template_variables.items():
if (isinstance(v, Widget)):
tmp.update({
k: [{
'script': s,
'div': d
} for s, d in [components(v, resources)]][0]
})
elif (isinstance(v, dict)):
if not v:
tmp.update(v)
else:
v.update(_update(v))
else:
tmp.update({k: v})
return tmp
template_variables.update(_update(template_variables))
template_variables_full = \
template_variables.copy() if template_variables is not None else {}
template_variables_full.update({
'title': title,
'bokeh_js': bokeh_js,
'bokeh_css': bokeh_css,
})
html = template.render(template_variables_full)
return encode_utf8(html)
def test_file_html_handles_css_only_resources():
css_resources = CSSResources()
template = Template("<head>{{ bokeh_css }}</head><body></body>")
output = embed.file_html(_embed_test_plot, None, "title", template=template, css_resources=css_resources)
rendered_css = CSS_RESOURCES.render(css_raw=css_resources.css_raw)
assert output == "<head>%s</head><body></body>" % rendered_css
<h3>Green - pan with resize & responsive (should maintain new aspect ratio)</h3>
{{ plot_div.green }}
<h3>Blue - pan no responsive</h3>
{{ plot_div.blue }}
{{ plot_script }}
</body>
</html>
''')
resources = INLINE
js_resources = JS_RESOURCES.render(js_raw=resources.js_raw,
js_files=resources.js_files)
css_resources = CSS_RESOURCES.render(css_raw=resources.css_raw,
css_files=resources.css_files)
script, div = components({'red': red, 'blue': blue, 'green': green})
html = template.render(js_resources=js_resources,
css_resources=css_resources,
plot_script=script,
plot_div=div)
html_file = 'embed_multiple_responsive.html'
with open(html_file, 'w') as f:
f.write(html)
view(html_file)