def check_session_id_signature(session_id, secret_key=settings.secret_key_bytes(),
signed=settings.sign_sessions()):
"""Check the signature of a session ID, returning True if it's valid.
The server uses this function to check whether a session ID
was generated with the correct secret key. If signed sessions are disabled,
this function always returns True.
Args:
session_id (str) : The session ID to check
secret_key (str, optional) : Secret key (default: value of 'BOKEH_SECRET_KEY' env var)
signed (bool, optional) : Whether to check anything (default: value of
'BOKEH_SIGN_SESSIONS' env var)
"""
secret_key = _ensure_bytes(secret_key)
if signed:
pieces = session_id.split('-', 1)
if len(pieces) != 2:
return False
base_id = pieces[0]
provided_signature = pieces[1]
expected_signature = _signature(base_id, secret_key)
# hmac.compare_digest() uses a string compare algorithm that doesn't
# short-circuit so we don't allow timing analysis
# encode_utf8 is used to ensure that strings have same encoding
return hmac.compare_digest(encode_utf8(expected_signature), encode_utf8(provided_signature))
else:
return True
def P():
if request.method == 'GET':
html = render_template(
'projections.html',
total_disp=1, NS_disp=1,
)
return encode_utf8(html)
else:
app.vars['agep'] = request.form['agep']
app.vars['bwp'] = request.form['bwp']
app.vars['totalp'] = request.form['totalp']
if app.vars['agep'] == 'Ruben Olmedo':
html = render_template(
'projections.html',
total_disp='A new WR of 305.5', NS_disp='OVER 9000!!!!',
)
return encode_utf8(html)
else:
if app.vars['agep']== '' or app.vars['bwp'] == '' or app.vars['totalp']== '':
html = render_template(
'projections.html',
total_disp=1, NS_disp=1,
)
return encode_utf8(html)
else:
agep = float(app.vars['agep'])
bwp = float(app.vars['bwp'])
totalp = float(app.vars['totalp'])
#NSp = round(-approx(bwp)+totalp, 2)
#for index, row in recent_data.iterrows():
#if abs(row['Age']-agep)<=2 and abs(row['NSC']-NSp)<=2:
#comparison = (row['LC'],row['CC'],row['Birth'],row['Year'],row['Year']+1)
comparison = (5933, 15, 2016-agep, agep,2016)
NSp2 = nei_model_pred.predict(comparison)
NSp = round(-approx(bwp)+totalp, 2)
NSp3 = round(NSp2[0],2)
total_disp = NSp-NSp3+totalp
html = render_template(
'projections.html',
total_disp=total_disp, NS_disp=NSp3,
)
return encode_utf8(html)
def plot_titles():
session_id = request.args.get("session_id")
df_file = get_sess(session_id)['df_file']
df = load_csv(session_id)
ind = indeed_scrape.Indeed("kw")
df['jobtitle'] = df['jobtitle'].apply(lambda x: x.lower())
df['jobtitle'] = df['jobtitle'].apply(lambda x:' '.join(ind._split_on_spaces(x)))
df['jobtitle'] = df['jobtitle'].apply(lambda x: re.sub('[^a-z\d\s]', '', x))
num = df.shape[0]
title_de_duped = ind.summary_similarity(df, 'jobtitle', 80)
grp = title_de_duped.groupby("jobtitle").count().sort("url", ascending=False)
cities = grp.index.tolist()
counts = grp['city'] # any key will do here
dff = pd.DataFrame({'kw':cities,
'count':counts
})
kws = get_sess(session_id)['keyword'][0]
p = plot_fig(dff, num, kws)
script, div = components(p)
session_string = "?session_id=%s" % session_id
page = render_template('titles.html', div=div, script=script, session_id=session_string)
return encode_utf8(page)
def graph():
# request was a POST
StockTicker = request.form['stock']
Type = request.form['type']
api_url = 'https://www.quandl.com/api/v1/datasets/WIKI/%s.json' % StockTicker
session = requests.Session()
session.mount('http://', requests.adapters.HTTPAdapter(max_retries=3))
raw_data = session.get(api_url)
json_dat = raw_data.json()
data = json_dat["data"]
df = pd.DataFrame(data, columns= json_dat["column_names"])
df['Date'] = pd.to_datetime(df['Date'])
df = df[df["Date"] >= start]
p1 = figure(x_axis_type = "datetime")
p1.title = "Stock Closing Prices"
p1.grid.grid_line_alpha=0.3
p1.xaxis.axis_label = 'Date'
p1.yaxis.axis_label = 'Price'
p1.line(df["Date"], df[Type], color='#A6CEE3', legend=StockTicker)
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(p1, INLINE)
return encode_utf8(render_template('graph.html', script=script, div=div))
def graph():
df = app.vars['data']
# Create a line plot from our data.
p = figure(width=700, height=500, x_axis_type="datetime",
title="Data from Quandle WIKI set")
for category in app.vars['features']:
p.line(pd.to_datetime(df['Date']), df[category],
color=app.vars['color'][category], line_width=1,
legend=app.vars['ticker'] + ": " + category)
p.legend.orientation = "top_right"
# Configure resources to include BokehJS inline in the document.
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
css_files=INLINE.css_files,
)
script, div = components(p, INLINE)
html = render_template(
'graph.html',
ticker=app.vars['ticker'],
plot_script=script, plot_div=div, plot_resources=plot_resources
)
return encode_utf8(html)
def plot_data():
# get data
x = []
y = []
colors = []
i = 0
with open("time_dep.csv", "r") as f:
while True:
line = f.readline()
if len(line) == 0:
break
items = line.split(',')
x.append(float(items[0]))
y.append(float(items[1]))
fig = figure(title="Taxi trips versus Day", plot_width=600, plot_height=400, x_axis_type="datetime", toolbar_location="below")
fig.line(x, y)
fig.xaxis[0].formatter = DatetimeTickFormatter(formats=dict(days=["%a"]))
fig.yaxis.axis_label = 'Number of Trips'
script, div = components(fig, INLINE)
html = flask.render_template(
'layout.html', #'layout.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def graph():
app.symbol = request.form['symbol']
try:
graph_html = build_graph(str(app.symbol))
return encode_utf8(graph_html)
except KeyError:
return render_template('error.html')
def get_data():
if request.method == "POST":
session_id = mk_random_string()
logging.info("session id: %s" % session_id)
type_ = request.form['type_']
kws = request.form['kw'].lower()
kws = indeed_scrape.Indeed._split_on_spaces(kws)
kws = " ".join(kws) #enter into DB normalized
# key used for sql to recover other info
to_sql({'session_id':session_id,
'type_':type_,
'keyword':kws,
'ind':0,
'end':0,
'count_thres':50
})
logging.info("running get_data:%s" % time.strftime("%d-%m-%Y:%H:%M:%S"))
logging.info("type:%s" % type_)
logging.info("key words:%s" % kws)
session_string = "?session_id=%s" % session_id
html = render_template('output.html', session_id=session_string)
return encode_utf8(html)
def plot_cities():
session_id = request.args.get("session_id")
logging.info("session id:%s" % session_id)
df = load_csv(session_id)
count = df.groupby("city").count()['url']
cities = count.index.tolist()
num_posts = df.shape[0]
df_city = pd.DataFrame({'kw':cities, 'count':count})
df_city.sort('count', ascending=False, inplace=True)
df_city.reset_index(inplace=True)
# hack
df_city[df_city['count'] == 0] = None
df_city.dropna(inplace=True)
n = df_city.shape[0]
if n > 20:
end = 20
else:
end = n
kws = get_sess(session_id)['keyword'][0]
slice = df_city.loc[0:end, :].copy()
p = plot_fig(slice, num_posts, kws)
script, div = components(p)
session_string = "?session_id=%s" % session_id
page = render_template('cities.html', div=div, script=script, session_id=session_string)
return encode_utf8(page)
def polynomial():
""" Very simple embeding of a polynomial chart """
# Grab input arguments from the URL
# This is automated by the button
args = flask.request.args
# Get all the form arguments in their url with defaults
color = colors[getitem(args,'color','Black')]
fig = figure(width=800, height=350,x_axis_type='datetime', title='%s closing prices for last 30 days' % st)
fig.line(dates, closing_prices, line_width=2, color=color, alpha=0.2, legend='close')
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Price'
# Configure resources to include BokehJS inline in the document.
plot_resources = RESOURCES.render(
js_raw = INLINE.js_raw,
css_raw = INLINE.css_raw,
js_files = INLINE.js_files,
css_files = INLINE.css_files
)
script, div = components(fig, INLINE)
html = flask.render_template(
'embed.html',
plot_script = script, plot_div=div, plot_resources=plot_resources,
color=color
)
return encode_utf8(html)
def set(self, key, val):
_data = self.shelve_module.open('bokeh.server')
try:
key = encode_utf8(key)
_data[key] = json.dumps(val)
finally:
_data.close()
def plot_cities():
session_id = request.args.get("session_id")
logging.info("session id:%s" % session_id)
df = load_csv(session_id)
count = df.groupby("city").count()['url']
cities = count.index.tolist()
num_posts = df.shape[0]
df_city = pd.DataFrame({'kw':cities, 'count':count})
df_city.sort('count', ascending=False, inplace=True)
df_city.reset_index(inplace=True)
n = df_city.shape[0]
if n > 20:
end = 20
else:
end = n
p = plot_fig(df_city.loc[0:end,:], num_posts, 'Posts Per City in the Analysis:Top 20')
script, div = components(p)
session_string = "?session_id=%s" % session_id
page = render_template('cities.html', div=div, script=script, session_id=session_string)
return encode_utf8(page)
def plot_data():
"""Obtains post data and produces two graphs:
volume of posts mentioning 'dengue' versus time; and
volume of posts versus neighborhood
"""
(df, df_volume, df_by_location) = get_data()
script1, div1 = volumeGraph(df_volume)
script2, div2 = locationGraph(df_by_location)
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
css_files=INLINE.css_files,
)
html = flask.render_template(
'embed.html',
plot_script1=script1,
plot_div1=div1,
plot_script2=script2,
plot_div2=div2,
plot_resources=plot_resources
)
return encode_utf8(html)
def plot_titles():
session_id = request.args.get("session_id")
df_file = get_sess(session_id)['df_file']
df = load_csv(session_id)
ind = indeed_scrape.Indeed("kw")
df['jobtitle'] = df['jobtitle'].apply(lambda x: x.lower())
df['jobtitle'] = df['jobtitle'].apply(lambda x:' '.join(ind._split_on_spaces(x)))
df['jobtitle'] = df['jobtitle'].apply(lambda x: re.sub('[^a-z\d\s]', '', x))
title_de_duped = ind.summary_similarity(df, 'jobtitle', 80)
grp = title_de_duped.groupby("jobtitle").count().sort("url", ascending=False)
cities = grp.index.tolist()
counts = grp['city'] # any key will do here
row = u'<tr><td>%s</td><td>%s</td></tr>'
rows = u''
for cty, cnt in zip(cities, counts):
try:
cty = cty.encode("utf-8", "ignore")
rows += row % (cty, cnt)
except:
continue
session_string = "?session_id=%s" % session_id
page = render_template('titles.html', rows=rows, session_id=session_string)
return encode_utf8(page)
def get(self, *args, **kwargs):
session = yield self.get_session()
element_id = self.get_argument("bokeh-autoload-element", default=None)
if not element_id:
self.send_error(status_code=400, reason='No bokeh-autoload-element query parameter')
return
resources = self.application.resources(self.request)
websocket_url = self.application.websocket_url_for_request(self.request, self.bokeh_websocket_path)
# TODO: yes, this should resuse code from bokeh.embed more directly
render_items = [dict(sessionid=session.id, elementid=element_id, use_for_title=True)]
script = _script_for_render_items(None, render_items, websocket_url=websocket_url, wrap_script=False)
js = AUTOLOAD_JS.render(
js_urls = resources.js_files,
css_urls = resources.css_files,
js_raw = resources.js_raw + [script],
css_raw = resources.css_raw_str,
elementid = element_id,
)
self.set_header("Content-Type", 'application/javascript')
self.write(encode_utf8(js))
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:
break
items = line.split(',')
x.append(float(items[0]))
y.append(float(items[1]))
#z = int(items[2][:-1])
colors.append("#%02x%02x%02x" % (255, 0, 0))
i += 1
fig = figure(title="Data", plot_width=600, plot_height=400, toolbar_location="below")
fig.scatter(x, y, radius=0.1, fill_color=colors, fill_alpha=0.6, line_color=None)
script, div = components(fig, INLINE)
html = flask.render_template(
'figure.html', #'layout.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def extract_zip(zip_name, exclude_term=None):
"""Extracts a zip file to its containing directory."""
zip_dir = os.path.dirname(os.path.abspath(zip_name))
try:
with zipfile.ZipFile(zip_name) as z:
# write each zipped file out if it isn't a directory
files = [zip_file for zip_file in z.namelist() if not zip_file.endswith('/')]
print('Extracting %i files from %r.' % (len(files), zip_name))
for zip_file in files:
# remove any provided extra directory term from zip file
if exclude_term:
dest_file = zip_file.replace(exclude_term, '')
else:
dest_file = zip_file
dest_file = os.path.normpath(os.path.join(zip_dir, dest_file))
dest_dir = os.path.dirname(dest_file)
# make directory if it does not exist
if not os.path.isdir(dest_dir):
os.makedirs(dest_dir)
# read file from zip, then write to new directory
data = z.read(zip_file)
with open(dest_file, 'wb') as f:
f.write(encode_utf8(data))
except zipfile.error as e:
print("Bad zipfile (%r): %s" % (zip_name, e))
raise e
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#module-bokeh.resources
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
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, plot_resources=plot_resources,
color=color, _from=_from, to=to
)
return encode_utf8(html)
def second_stock():
n = app_stock.vars['name']
ss = "WIKI/" + n + ".4"
mydata = quandl.get(ss, encoding='latin1', parse_dates=['Date'], dayfirst=True, index_col='Date', trim_start="2016-05-05", trim_end="2016-06-05", returns = "numpy", authtoken="ZemsPswo-xM16GFxuKP2")
mydata = pd.DataFrame(mydata)
#mydata['Date'] = mydata['Date'].astype('datetime64[ns]')
x = mydata['Date']
y = mydata['Close']
p = figure(title="Stock close price", x_axis_label='Date', y_axis_label='close price', plot_height = 300, plot_width = 550)
p.line(x, y, legend="Price in USD", line_width=3, color = "#2222aa")
# 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 = INLINE.render_js()
css_resources = INLINE.render_css()
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/user_guide/embedding.html#components
script, div = components(p, INLINE)
html = flask.render_template(
'stockgraph.html',
ticker = app_stock.vars['name'],
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def polynomial():
""" Very simple embedding of a polynomial chart
"""
# Grab the inputs arguments from the URL
args = flask.request.args
# Get all the form arguments in the url with defaults
color = getitem(args, 'color', 'Black')
_from = int(getitem(args, '_from', 0))
to = int(getitem(args, 'to', 10))
# Create a polynomial line graph with those arguments
x = list(range(_from, to + 1))
fig = figure(title="Polynomial")
fig.line(x, [i ** 2 for i in x], color=colors[color], line_width=2)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(fig)
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 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 get(self, key):
_data = shelve.open("bokeh.server")
key = encode_utf8(key)
data = _data.get(key, None)
if data is None:
return None
attrs = json.loads(decode_utf8(data))
_data.close()
return attrs
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 root():
html = flask.render_template(
'layout.html',
# plot_script=script,
# plot_div=div,
# plot_div2=div2,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def get(self, key):
_data = self.shelve_module.open('bokeh.server')
try:
key = encode_utf8(key)
data = _data.get(key, None)
if data is None:
return None
attrs = json.loads(decode_utf8(data))
finally:
_data.close()
return attrs
def root():
global plot_scripts
html = flask.render_template(
'layout.html',
plot_script=plot_scripts[0],
plot_div=plot_scripts[1],
plot_div2=plot_scripts[2],
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def stock():
""" Very simple plot of stock closing price for last month or so"""
# Grab the inputs arguments from the URL
# This is automated by the button
args = flask.request.args
return 'ALA'
# Get all the form arguments in the url with defaults
if 'company' in args.keys() and args['company']:
company = args['company']
else:
company = 'GOOG'
cl = requests.get("https://www.quandl.com/api/v3/datasets/WIKI/%s.json?order=asc&rows=31&start_date=2015-07-01&end_date=2015-09-03" % (company))
if cl.status_code == 200:
c2=cl.content
stock=simplejson.loads(c2)
abb=stock['dataset']['dataset_code']
datanames=stock['dataset']['column_names']
data=stock['dataset']['data']
dataorg=pd.DataFrame(data,columns=datanames)
dataorg['Date']=pd.to_datetime(dataorg['Date'])
else:
######## THIS IS NOT RECOMMENDED, because now it just returns an error message if not find the ticker.
return 'Error! Ticker does not exist!'
# Create a graph
fig = figure(x_axis_type="datetime")
fig.line(dataorg.Date,dataorg.Close)
fig.title="Stock closing price (%s), from 07-01-2015 " % (company)
# fig.xaxis_axis_label='Date'
# fig.yaxis_axis_label='Price'
# Configure resources to include BokehJS inline in the document.
# For more details see:
# http://bokeh.pydata.org/en/latest/docs/reference/resources_embedding.html#module-bokeh.resources
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
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, plot_resources=plot_resources,
# color=color,
company=company
)
return encode_utf8(html)
def main(ipynb):
print("running %s" % ipynb)
with io.open(ipynb, encoding='utf8') as f:
nb = read(f, NO_CONVERT)
test_notebook(nb)
base, ext = os.path.splitext(ipynb)
exportHtml = HTMLExporter()
(body, resources) = exportHtml.from_notebook_node(nb)
outfile = ipynb + ".html"
open(outfile, 'w').write(encode_utf8(body))
print("wrote %s" % outfile)
def search():
ticker = request.form['ticker']
url = "https://www.quandl.com/api/v3/datasets/WIKI/" + ticker + "/data.json"
payload = {'api_key':'9o4vcpiASzqaA6dczzzZ','start_date': '2015-11-01', 'end_date': '2015-11-30'}
res = requests.get(url, params=payload)
raw_data = json.loads(res.text)
date_strings = [x[0] for x in raw_data["dataset_data"]["data"]]
close_price = [x[4] for x in raw_data["dataset_data"]["data"]]
date = pd.to_datetime(pd.Series(date_strings))
p = figure(title="Stock Price for "+ticker+" (source: Quandl WIKI)", x_axis_label="Date",y_axis_label="Price", x_axis_type="datetime")
p.line(date ,close_price, legend="Close Price", line_width=3)
script, div = components(p, INLINE)
html = render_template('results.html', plot_script=script, plot_div=div)
return encode_utf8(html)
def check_for_low_count_using_title():
session_id = request.args.get("session_id")
logging.debug("session id:%s" % session_id)
df = load_csv(session_id)
logging.debug("title count:%i" % df.shape[0])
string = "<br><p><i>Your search by job title returned a small number of job \
postings. Click 'NEW SEARCH' and use the 'keyword' search.</i></p><br>"
if df.shape[0] < 25:
return encode_utf8(string)
else:
return ""
def get(self, *args, **kwargs):
session = yield self.get_session()
element_id = self.get_argument("bokeh-autoload-element", default=None)
if not element_id:
self.send_error(status_code=400, reason='No bokeh-autoload-element query parameter')
return
resources = self.application.resources(self.request)
websocket_url = self.application.websocket_url_for_request(self.request, self.bokeh_websocket_path)
js = AUTOLOAD_JS.render(
docs_json = None,
js_urls = resources.js_files,
css_files = resources.css_files,
elementid = element_id,
sessionid = session.id,
websocket_url = websocket_url
)
self.set_header("Content-Type", 'application/javascript')
self.write(encode_utf8(js))
def index():
# Static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
plot_script = ""
plot_div = ""
articles = ""
# Initialize the ticker registry (only once though)
tickers_init()
# Parse form data
if request.method == 'POST':
ticker = request.form.get('ticker').strip().upper()
close = request.form.get('close')
opening = request.form.get('open')
high = request.form.get('high')
low = request.form.get('low')
# Go get stock info
df = alpha_vantage(ticker)
if df is not None:
plot_script, plot_div = create_figure(df, ticker,
[opening, close, high, low])
articles = get_news(ticker)
else:
flash('Stock ticker not found.')
return redirect(url_for('index'))
# Render our results (if any)
html = render_template('index.html',
js_resources=js_resources,
css_resources=css_resources,
plot_script=plot_script,
plot_div=plot_div,
articles=articles,
entries=TICKERS)
return encode_utf8(html)
def graph():
if request.method == 'POST':
symbol = request.form['ticker']
else:
dat = "method not post"
#get quandl data
quandlTicker = "WIKI/%s" % symbol
data = quandl.get(quandlTicker, start_date="2018-01-01")
data.index.name = 'Date'
data.reset_index(inplace=True)
fig = figure(x_axis_type="datetime", title="Stock Closing Price")
fig.grid.grid_line_alpha = 0.3
fig.xaxis.axis_label = 'Date'
fig.yaxis.axis_label = 'Price'
fig.line(data['Date'], data['Close'], color='#A6CEE3', legend=symbol)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# window_size = 30
# window = np.ones(window_size)/float(window_size)
# avg = np.convolve(data['Close'], window, 'same')
# return(output_file("graph.html", title="Stock Closing Price"))
script, div = components(fig)
html = render_template('graph.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources)
return encode_utf8(html)
def bokeh(filename):
#print(filename)
data = xr.open_dataarray(os.path.join(app.config['UPLOAD_FOLDER'], filename))
#print(data)
# init a basic bar chart:
# http://bokeh.pydata.org/en/latest/docs/user_guide/plotting.html#bars
pandas_data = data.sel(Meson_Number=15,Momentum_List='0 0 0').to_dataframe()
x = list(pandas_data.index)
y = pandas_data[pandas_data.columns[-1]].values
y = np.log(y/np.roll(y,-1))
print()
print(x)
print()
print(y)
print()
fig = figure(plot_width=600, plot_height=600)
fig.scatter(
x,
y,
color='navy'
)
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# render template
script, div = components(fig)
html = render_template(
'index.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def chart():
brand = request.form['brand']
response = get_data_from_api(brand=brand)
# print(response)
total = response['number_of_tweets']
positive = response['positive']
neutral = response['neutral']
negative = response['negative']
sentiments = ["Positive", "Neutral", "Negative"]
distribution = [positive, neutral, negative]
source = ColumnDataSource(data=dict(sentiments=sentiments, distribution=distribution))
p = figure(x_range=sentiments, plot_height=550, plot_width= 1000, title="Sentiment distribution", x_axis_label = 'Sentiments')
p.vbar(x='sentiments', top='distribution', width=0.9, source=source, legend_field="sentiments",
line_color=None, fill_color=factor_cmap('sentiments', palette=['#39DA00', '#FDB229', '#FF0445'], factors=sentiments))
p.xgrid.grid_line_color = None
p.y_range.start = 0
p.legend.orientation = "horizontal"
p.legend.location = "top_right"
p.background_fill_color = "#0B0022"
script, div = components(p)
pos = round((float(positive)/float(total))*100, 1)
neu = round((float(neutral)/float(total))*100, 1)
neg = round((float(negative) / float(total)) * 100, 1)
print(pos)
print(neu)
print(neg)
html = render_template("chart.html",
the_div=div,
the_script=script,
positive=pos,
neutral=neu,
negative=neg)
return encode_utf8(html)
def extract_zip(zip_name, exclude_term=None):
"""Extracts a zip file to its containing directory."""
zip_dir = os.path.dirname(os.path.abspath(zip_name))
try:
with zipfile.ZipFile(zip_name) as z:
# write each zipped file out if it isn't a directory
files = [
zip_file for zip_file in z.namelist()
if not zip_file.endswith('/')
]
print('Extracting %i files from %r.' % (len(files), zip_name))
for zip_file in files:
# remove any provided extra directory term from zip file
if exclude_term:
dest_file = zip_file.replace(exclude_term, '')
else:
dest_file = zip_file
dest_file = os.path.normpath(os.path.join(zip_dir, dest_file))
dest_dir = os.path.dirname(dest_file)
# make directory if it does not exist
if not os.path.isdir(dest_dir):
os.makedirs(dest_dir)
# read file from zip, then write to new directory
data = z.read(zip_file)
with open(dest_file, 'wb') as f:
f.write(encode_utf8(data))
except zipfile.error as e:
print("Bad zipfile (%r): %s" % (zip_name, e))
raise e
def dashboard():
CASSANDRA_HOST = ['192.168.0.101', '192.168.0.106']
CASSANDRA_PORT = 9042
CASSANDRA_DB = "cryptocoindb"
cluster = Cluster(contact_points=CASSANDRA_HOST, port=CASSANDRA_PORT)
session = cluster.connect(CASSANDRA_DB)
session.row_factory = pandas_factory
session.default_fetch_size = None
ndays = request.args.get('ndays', default=7, type=int)
print(ndays)
tblGainLoss, tblDailyGainLoss, coinHistory, tblCoins = getAllData(
ndays, session=session)
# tblGainLoss, tblCoins, coinHistory = getSomeValueFromA_Database()
# Grab the inputs arguments from the URL
# args = flask.request.args
l = layout(
[[[[GainLossPlot(tblGainLoss)], [MarketPlot(tblCoins, coinHistory)]],
WalletPlot(coinHistory)]],
repsonsive=True)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(l)
html = flask.render_template('old_dashboard.html',
title="BitCoin Dashboard",
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
active_page='projects',
footer='false')
return encode_utf8(html)
def index():
# Static resources:
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
plot_script = ""
plot_div = ""
# Parse form data
if request.method == 'POST':
ticker = request.form.get('ticker').strip().upper()
close = request.form.get('close')
opening = request.form.get('open')
high = request.form.get('high')
low = request.form.get('low')
# Get stock info from Alpha Vantage
df = alpha_vantage(ticker)
if df is not None:
plot_script, plot_div = create_plot(df, ticker,
[opening, close, high, low])
# TODO: the function below isn't working, Need to figure out how to get input from multiple forms.
# Use the index.html file in /template_tinkering and reference:
# https://github.com/thedataincubator/sql_heroku/blob/master/app/templates/index.html#L54
#plot_script, plot_div = create_candlesctick(df, ticker)
else:
flash('Stock ticker not found')
return redirect(url_for('index'))
# Render results is available
html = render_template('index.html',
js_resources=js_resources,
css_resources=css_resources,
plot_script=plot_script,
plot_div=plot_div,
entries=['AAPL', 'GOOG', 'MSFT'])
return encode_utf8(html)
def plot_data():
"""Obtains post data and produces two graphs:
volume of posts mentioning 'dengue' versus time; and
volume of posts versus neighborhood
"""
(df, df_volume, df_by_location) = get_data()
script1, div1 = volumeGraph(df_volume)
script2, div2 = locationGraph(df_by_location)
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
css_files=INLINE.css_files,
)
html = flask.render_template('embed.html',
plot_script1=script1,
plot_div1=div1,
plot_script2=script2,
plot_div2=div2,
plot_resources=plot_resources)
return encode_utf8(html)
def bokeh():
# but = Button(label="click me", width = 80, height = 10, button_type = 'primary')
#
# def onclick():
# if par.text == "":
# par.text = "Hello! World"
# else:
# par.text = ""
#
# but.on_click(onclick)
# par = Paragraph(text="", width = 80, height = 61, style = {'background-color':'#F2F3F4'})
# grid = column(but, Div(text = "", width = 10, height = 100), par)
#
# js_resources = INLINE.render_js()
# css_resources = INLINE.render_css()
# render template
# script, div = components(grid)
script = server_document(url="http://localhost:5006/bokeh_code")
html = render_template('index.html', plot_script=script)
# div=div, js_resources=js_resources, css_resources=css_resources)
return encode_utf8(html)
def balances():
if not current_user.is_authenticated:
return redirect(url_for("user.login"))
user_id = current_user.user_id
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# render template
script, div = components(plot_balance_report(user_id))
html = render_template("report/balances.html",
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
title="Остатки на счетах",
current_month=get_current_month()["name"],
last_month=get_last_month()["name"],
accounts_list=sorted(
data_observer.get_all_account_names(user_id)))
return encode_utf8(html)
def example():
ticker = (request.form['ticker'])#new
start = dt.datetime(2019,1,1)
end = dt.datetime(2019,1,31)
#PULL DATA FROM WEB
df = web.DataReader(ticker, 'yahoo', start, end) #TSLA = tesla
ds = ColumnDataSource(df) #allows for calling the date as index below
#output_file("lines.html") ##if using this, add "from bokeh.plotting import figure, **output_file**, show
TOOLS="hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,save,box_select,poly_select,lasso_select"
p = figure(title="Stock price (adjusted close) for ticker '" + ticker + "', 2019 Jan 1 - 2019 Jan 31", x_axis_type='datetime', x_axis_label='Date', y_axis_label='Adjusted Closing Price', tools=TOOLS)
p.xaxis.formatter=DatetimeTickFormatter(
hours=["%d %B %Y"],
days=["%d %B %Y"],
months=["%d %B %Y"],
years=["%d %B %Y"],
)
p.xaxis.major_label_orientation = pi/4
p.line(source=ds, x='Date', y='Adj Close')
p.circle(source=ds, x='Date', y='Adj Close')
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# render template
script, div = components(p)
html = render_template(
'index.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
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 = INLINE.render_js()
css_resources = INLINE.render_css()
# 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 get(self, *args, **kwargs):
session = yield self.get_session()
element_id = self.get_argument("bokeh-autoload-element", default=None)
if not element_id:
self.send_error(status_code=400, reason='No bokeh-autoload-element query parameter')
return
resources = self.application.resources()
# TODO: yes, this should resuse code from bokeh.embed more directly
render_items = [dict(sessionid=session.id, elementid=element_id, use_for_title=False)]
script = _script_for_render_items(None, render_items, wrap_script=False)
js = AUTOLOAD_JS.render(
js_urls = resources.js_files,
css_urls = resources.css_files,
js_raw = resources.js_raw + [script],
css_raw = resources.css_raw_str,
elementid = element_id,
)
self.set_header("Content-Type", 'application/javascript')
self.write(encode_utf8(js))
def index():
# Create layout
c_map = climate_map()
ts = timeseries()
l = legend()
t = title()
map_legend = hplot(c_map, l)
layout = vplot(t, map_legend, ts)
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
css_files=INLINE.css_files,
)
script, div = components(layout, INLINE)
html = flask.render_template(
'embed.html',
plot_script=script,
plot_div=div,
plot_resources=plot_resources,
)
return encode_utf8(html)
def html_for_render_items(comm_js,
docs_json,
render_items,
template=None,
template_variables={}):
comm_js = wrap_in_script_tag(comm_js)
json_id = make_id()
json = escape(serialize_json(docs_json), quote=False)
json = wrap_in_script_tag(json, "application/json", json_id)
script = wrap_in_script_tag(script_for_render_items(json_id, render_items))
context = template_variables.copy()
context.update(
dict(
title='',
bokeh_js=comm_js,
plot_script=json + script,
docs=render_items,
base=NB_TEMPLATE_BASE,
macros=MACROS,
))
if len(render_items) == 1:
context["doc"] = context["docs"][0]
context["roots"] = context["doc"].roots
if template is None:
template = NB_TEMPLATE_BASE
elif isinstance(template, string_types):
template = _env.from_string("{% extends base %}\n" + template)
html = template.render(context)
return encode_utf8(html)
def bokeh():
global data_received
import logging
logging.warn("data %s" % data_received)
div = handle_data_recieved(data_received)
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
titles = [
"Biểu đồ thống kê số lượng vi phạm theo giờ trong ngày",
"Biểu đồ thống kê số lượng vi phạm theo ngày trong tuần",
"Biểu đồ thống kê số lượng vi phạm của từng loại phương tiện",
"Biểu đồ thống kê 10 bộ số xuất hiện thường xuyên",
"Biểu đồ thống kê 10 bộ số xuất hiện không thường xuyên"
]
# render template
html = render_template(
'index.html',
titles=titles,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def graph():
text = request.form.get('stock-ticker')
ti = text.upper()
mon = request.form.get('mon')
yr = request.form.get('yr')
day = '01'
if mon == '01':
mon2 = '12'
yr2 = yrs[yrs.index(yr) - 1]
else:
mon2 = months[months.index(mon) -
1] #making the selection the previous month
yr2 = yr
d1 = '%s-%s-%s' % (yr, mon, day)
d2 = '%s-%s-%s' % (yr2, mon2, day)
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
plot = create_stock_plot(ti, d1, d2)
script, div = components(plot)
html = render_template('graph.html',
stock_ticker=ti,
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources)
if ti:
return encode_utf8(html)
#return render_template('graph3.html', stock_ticker=ti, script=script, div=div)
else:
return 'Please enter a valid stock ticker', 400
def root():
""" Returns the spectrogram of audio data served from /data """
spectrogram = make_spectrogram()
resources = Resources("inline")
plot_resources = RESOURCES.render(
js_raw = resources.js_raw,
css_raw = resources.css_raw,
js_files = resources.js_files,
css_files = resources.css_files,
)
plot_script, plot_div = components(
spectrogram, resources
)
html = flask.render_template(
"spectrogram.html",
plot_resources = plot_resources,
plot_script = plot_script,
plot_div = plot_div,
)
return encode_utf8(html)
def index():
args = flask.request.args
selected_team = flask.request.values.get("selected_team", "LAA")
selected_year = int(flask.request.values.get("selected_year", "2012"))
p = create_plot(selected_team, selected_year)
plot_resources = RESOURCES.render(
js_raw=INLINE.js_raw,
css_raw=INLINE.css_raw,
js_files=INLINE.js_files,
css_files=INLINE.css_files,
)
script, div = components(p, INLINE)
html = flask.render_template(
'embed.html',
plot_script=script,
plot_div=div,
plot_resources=plot_resources,
selected_team=selected_team,
selected_year=selected_year,
years=distinct_years,
teams=distinct_teams,
)
return encode_utf8(html)
def plotDataset(ds,template='dataset.html',title='Dataset',color=None,*args, **kwargs):
ds = ds.copy()
ds.data.columns = ds.data.columns.astype(str)
# ts = TimeSeries(ds.data)
numlines=len(ds.data.columns)
if color is None:
color = ds.meta[ds.meta.columns[0]]
label = color
color = colorby(color)
# print color
# source = ColumnDataSource(data=ds.data)
source = ColumnDataSource(dict(xs=[ds.data.index.values]*ds.data.shape[1],
ys = [ds.data[name].values for name in ds.data], yslog = [np.log2(ds.data[name].values) for name in ds.data], color=color, label=label))
labelsource = ColumnDataSource(ds.meta)
colorsource = ColumnDataSource({k:colorby(ds.meta[k]) for k in ds.meta.columns.tolist()})
# if color is None:
# # color = viridis(numlines)
# color = colorby(range(numlines))
# else:
# # v = viridis(max(color)+1)
# # color = [v[c] for c in color]
# color = colorby(color)
fig = figure(title=title,plot_width=97*8,)
# plot = Plot()
# fig.line(ds.data.index.values, ds.data, line_width=2)
# fig.multi_line(xs=[ds.data.index.values]*ds.data.shape[1],
# ys = [ds.data[name].values for name in ds.data],
# line_color=color,
# line_width=5)
fig.multi_line('xs', 'ys', color='color', legend='label', source=source)
fig.legend.location = "top_left"
# glyph = MultiLine(xs="xs", ys="ys", line_color="", line_width=2)
# fig.add_glyph(source, glyph)
# plot.add_glyph(source, glyph)
callback = CustomJS(args=dict(source=source,colorsource=colorsource,labelsource=labelsource), code="""
var data = source.get('data');
var data2 = colorsource.get('data');
var data3 = labelsource.get('data');
var f = cb_obj.get('value')
color = data['color']
color2 = data2[f]
label = data['label']
label2 = data3[f]
for (i = 0; i < color.length; i++) {
color[i] = color2[i]
label[i] = label2[i]
}
source.trigger('change');
""")
logcallback = CustomJS(args=dict(source=source), code="""
var data = source.get('data');
data['ys'] = data['yslog']
source.trigger('change');
""")
menu = [(c,c) for c in ds.meta.columns]
dropdown = Dropdown(label="Color by", button_type="warning", menu=menu, callback=callback)
# layout = vform(dropdown, fig)
layout = column(dropdown, fig)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# script, div = components(ts)
script, div = components(layout)
# script, div = components(fig)
html = render_template(
template,
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
*args, **kwargs
)
return encode_utf8(html)
def heatmap():
selector_data = get_selector_data() # generate/retrieve data for selector menu
default_data = {'building': '6', 'point': '305', 'from': '2017-08-18', 'to': '2017-08-30'}
html = render_template('heatmap.html', selector_data=selector_data, data=default_data)
return encode_utf8(html)
def graphs_input():
if request.method == 'POST':
topic = request.form['topic']
sentence = request.form['sentence']
if sentence != '':
sentence = str(sentence)
with open('../pickles/lda_model_' + identifier + '.pkl',
'rb') as f:
lda_model = pickle.load(f)
bow = lda_model.id2word.doc2bow(sentence.split(' '))
topics = lda_model[bow]
topic = 0
prob = 0
for topic_and_prob in topics:
temp_topic = topic_and_prob[0]
temp_prob = topic_and_prob[1]
if temp_prob > prob:
topic = temp_topic
prob = temp_prob
topic += 1
else:
topic = int(topic)
script, div = get_components(topic=topic)
with open('../pickles/topic_dict_' + identifier + '.pkl', 'rb') as f:
topic_dict = pickle.load(f)
dates = topic_dict[topic]['date_published']
df = pd.DataFrame({'date_published': pd.Series(dates)})
df = df[df['date_published'] > date(2017, 5, 18)]
df = df['date_published'].dt.date.value_counts()
max_date = df.index[np.argmax(df.values)]
# script, div = make_bokeh_plot(topic_dict, topic)
anger_tones = topic_dict[topic]['Anger']
disgust_tones = topic_dict[topic]['Disgust']
fear_tones = topic_dict[topic]['Fear']
joy_tones = topic_dict[topic]['Joy']
sadness_tones = topic_dict[topic]['Sadness']
analytical_score = topic_dict[topic]['Analytical']
tone_mean = []
for i in range(5):
tone_mean.append(np.mean(anger_tones))
tone_mean.append(np.mean(disgust_tones))
tone_mean.append(np.mean(fear_tones))
tone_mean.append(np.mean(joy_tones))
tone_mean.append(np.mean(sadness_tones))
colors = ['red', 'green', 'purple', 'yellow', 'blue']
tone = ['Anger', 'Disgust', 'Fear', 'Joy', 'Sadness']
idx = np.argmax(tone_mean)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
html = render_template(
'graphs_input.html',
js_resources=js_resources,
css_resources=css_resources,
script=script,
div=div,
topic_num=topic,
word_cloud='src="../static/img/wordclouds/wordcloud_topic' +
str(topic) + '_' + identifier + '.png"',
mood_plot='src="../static/img/mood_plots/mood_by_site_plot_by_topic'
+ str(topic) + '_' + identifier + '.png"',
pos_neg_plot=
'src="../static/img/pos_neg_plots/pos_neg_by_site_plot_by_topic' +
str(topic) + '_' + identifier + '.png"',
tone_mean="{0:.1f}".format(tone_mean[idx] * 100),
tone=tone[idx],
color='color="' + colors[idx] + '"',
max_date=max_date,
date_plot='src="../static/img/coverage_plots/coverage_plot_by_topic'
+ str(topic) + '_' + identifier + '.png"')
return encode_utf8(html)
def test_file_html_handles_css_only_resources():
css_resources = CSSResources(mode="relative", components=["bokeh"])
template = Template("<head>{{ bokeh_css }}</head><body></body>")
output = embed.file_html(_embed_test_plot, (None, css_resources), "title", template=template)
html = encode_utf8("<head>%s</head><body></body>" % css_resources.render_css())
assert output == html
def plot_page(df, columns, request, page):
"""Render the Bokeh plot.
Inputs
------
df : pd.DataFrame
The DataFrame with the data
columns : list
Which columns to use for choices in the plot
request : flask
The request object from flask
page : str ('plot', 'plot_exo')
Which page to render (for combined ['plot_exo'] or just SWEET-Cat ['plot'])
Output
------
The rendered page with the plot
"""
colorscheme = 'Plasma'
if request.method == 'POST': # Something is being submitted
color = request.form['color']
x = str(request.form['x'])
y = str(request.form['y'])
z = str(request.form['z'])
z = None if z == 'None' else z
if (x not in columns) or (y not in columns):
return redirect(url_for(page))
if (z is not None) and (z not in columns):
return redirect(url_for(page))
colorscheme = str(request.form.get('colorscheme', colorscheme))
if colorscheme not in colorschemes.keys():
return redirect(url_for(page))
checkboxes = request.form.getlist("checkboxes")
if not checkboxes: # When [] is returned
checkboxes = ['']
if checkboxes[0] not in [[], '', 'h**o']:
return redirect(url_for(page))
df, x, y, z = extract(df, x, y, z, checkboxes)
# Setting the limits
x1, x2, y1, y2 = get_limits(request.form, x, y)
if x.name != session.get('x', None):
x1 = min(x)
x2 = max(x)
session['x'] = x.name
if y.name != session.get('y', None):
y1 = min(y)
y2 = max(y)
session['y'] = y.name
xscale = str(request.form['xscale'])
yscale = str(request.form['yscale'])
if xscale not in ['linear', 'log']:
return redirect(url_for(page))
if yscale not in ['linear', 'log']:
return redirect(url_for(page))
else:
if page == "plot_exo":
x = 'discovered'
y = 'plMass'
z = None
x1, x2 = 1985, 2020
y1, y2 = 0.0001, 200
session['x'] = 'discovered'
session['y'] = 'plMass'
session['z'] = 'None'
else:
x = 'teff'
y = 'lum'
z = 'logg'
x1, x2 = 8000, 2500
y1, y2 = 1e-3, 3000
session['x'] = 'teff'
session['y'] = 'lum'
session['z'] = 'logg'
yscale = 'log'
color = 'Orange'
xscale = 'linear'
checkboxes = []
df, x, y, z = extract(df, x, y, z, checkboxes)
# Check scale
xscale, yscale, error = check_scale(x, y, xscale, yscale)
stars = df['Star']
stars = list(stars.values) # Turn series into list.
hover = HoverTool(tooltips=[
("{}".format(x.name), "$x"),
("{}".format(y.name), "$y"),
("Star", "@star"),
])
num_points = count(x, y, [x1, x2], [y1, y2])
title = '{} vs. {}:\tNumber of objects in plot: {}'.format(
x.name, y.name, num_points)
tools = "crosshair,pan,wheel_zoom,box_zoom,reset,box_select,lasso_select,save".split(
',')
fig = figure(title=title,
tools=tools + [hover],
plot_width=800,
plot_height=400,
toolbar_location='above',
x_range=[x1, x2],
y_range=[y1, y2],
x_axis_type=xscale,
y_axis_type=yscale)
if z is not None: # Add colours and a colorbar
COLORS, pallete = colorschemes[colorscheme]
groups = pd.qcut(z.values, len(COLORS), duplicates="drop")
c = [COLORS[xx] for xx in groups.codes]
source = ColumnDataSource(data=dict(x=x, y=y, c=c, star=stars))
color_mapper = LinearColorMapper(palette=pallete,
low=z.min(),
high=z.max())
color_bar = ColorBar(color_mapper=color_mapper,
label_standoff=12,
border_line_color=None,
location=(0, 0))
fig.add_layout(color_bar, 'right')
fig.circle('x',
'y',
source=source,
size=10,
color='c',
fill_alpha=0.2,
line_color=None)
z = z.name
fig.xaxis.axis_label = x.name
fig.yaxis.axis_label = y.name
color_bar.title = z
else: # Simple colorbar
source = ColumnDataSource(data=dict(x=x, y=y, star=stars))
fig.circle('x',
'y',
source=source,
size=10,
color=colors[color],
fill_alpha=0.2,
line_color=None)
fig.xaxis.axis_label = x.name
fig.yaxis.axis_label = y.name
# Horizontal histogram
hhist, hedges, hmax = scaled_histogram(x, num_points, xscale)
ph = figure(toolbar_location=None,
plot_width=fig.plot_width,
plot_height=200,
x_range=fig.x_range,
y_range=(-hmax * 0.1, hmax),
min_border=10,
min_border_left=50,
y_axis_location="right",
x_axis_type=xscale)
ph.xgrid.grid_line_color = None
ph.yaxis.major_label_orientation = np.pi / 4
ph.background_fill_color = "#fafafa"
ph.quad(bottom=0,
left=hedges[:-1],
right=hedges[1:],
top=hhist,
color="white",
line_color=colors[color])
# Vertical histogram
vhist, vedges, vmax = scaled_histogram(y, num_points, yscale)
pv = figure(toolbar_location=None,
plot_width=200,
plot_height=fig.plot_height,
x_range=(-vmax * 0.1, vmax),
y_range=fig.y_range,
min_border=10,
y_axis_location="right",
y_axis_type=yscale)
pv.ygrid.grid_line_color = None
pv.xaxis.major_label_orientation = np.pi / 4
pv.background_fill_color = "#fafafa"
pv.quad(left=0,
bottom=vedges[:-1],
top=vedges[1:],
right=vhist,
color="white",
line_color=colors[color])
layout = column(row(fig, pv), row(ph, Spacer(width=200, height=200)))
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(layout)
if error is not None:
flash('Scale was changed from log to linear')
html = render_template('plot.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
color=color,
colors=colors,
x=x.name,
y=y.name,
z=z,
x1=x1,
x2=x2,
y1=y1,
y2=y2,
xscale=xscale,
yscale=yscale,
checkboxes=checkboxes,
columns=columns,
colorschemes=colorschemes,
colorscheme=colorscheme)
return encode_utf8(html)
def index():
form = InputForm(request.form)
if request.method == 'POST' and form.validate():
veg, fylke, hpfra, hptil, mfra, mtil = form.veg.data, form.fylke.data, form.hpfra.data, form.hptil.data, form.mfra.data, form.mtil.data
viseside = True
else:
viseside = False
veg = 'fv241'
fylke = '14'
hpfra = 1
hptil = 10
mfra = 0
mtil = 10000
if hpfra == hptil:
vegref = str(fylke) + '00' + veg + 'hp' + str(hpfra) + 'm' + str(
mfra) + '-' + str(mtil)
else:
vegref = str(fylke) + '00' + veg + 'hp' + str(hpfra) + 'm' + str(
mfra) + '-' + 'hp' + str(hptil) + 'm' + str(mtil)
df = data.hentData(vegref)
fig_skredtype = plot.plot_skredtype(df, vegref)
fig_maaned = plot.plot_maaned(df, vegref)
fig_losneområde = plot.plot_losneomrade(df, vegref)
fig_steinmaaned = plot.plot_steinmaaned(df, vegref)
fig_snomaaned = plot.plot_snomaaned(df, vegref)
#fig_steinm = plot.plot_steinmaaned(df, vegref)
fig_aar = plot.plot_aar(df, vegref)
fig_volumomraade = plot.plot_volumomraade(df, vegref)
fig_steinlosneomrade = plot.plot_steinlosneomrade(df, vegref)
#grid_oversikt = gridplot([fig_skredtype, fig_maaned, fig_losneområde, fig_aar], ncols=1, plot_width=500)
#grid_skredtype = gridplot([fig_steinmaaned, fig_snomaaned], ncols=1, plot_width=500)
#gird_samlaplot = gridplot([], ncols=1, plot_width=500, plot_height=500)
# grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# render template
script_skredtype, div_skredtype = components(fig_skredtype)
script_maaned, div_maaned = components(fig_maaned)
script_aar, div_aar = components(fig_aar)
script_steinmaaned, div_steinmaaned = components(fig_steinmaaned)
script_snomaaned, div_snomaaned = components(fig_snomaaned)
script_losneområde, div_losneområde = components(fig_losneområde)
script_volumomraade, div_volumomraade = components(fig_volumomraade)
script_steinlosneområde, div_steinlosneområde = components(
fig_steinlosneomrade)
html = render_template('index.html',
script_skredtype=script_skredtype,
div_skredtype=div_skredtype,
script_maaned=script_maaned,
div_maaned=div_maaned,
script_aar=script_aar,
div_aar=div_aar,
script_losneområde=script_losneområde,
div_losneområde=div_losneområde,
script_steinmaaned=script_steinmaaned,
div_steinmaaned=div_steinmaaned,
script_steinlosneområde=script_steinlosneområde,
div_steinlosneområde=div_steinlosneområde,
script_snomaaned=script_snomaaned,
div_snomaaned=div_snomaaned,
script_volumomraade=script_volumomraade,
div_volumomraade=div_volumomraade,
js_resources=js_resources,
css_resources=css_resources,
form=form,
vegref=vegref,
viseside=viseside)
return encode_utf8(html)
def map_ptsd():
# Grab the inputs arguments from the URL
args = flask.request.args
# Get all the form arguments in the url with defaults
metric = getitem(args, 'metric', 'PTSD Rate')
year = getitem(args, 'year', '2014')
# connect to database
eng = create_engine("mysql://%s:%s@localhost/va_open" %
(os.getenv("MYSQL_USER"), os.getenv("MYSQL_PASS")))
# execute query
with open('ptsd_rate_by_state.sql', 'r') as fid:
ptsd_table = pd.read_sql_query(fid.read(), eng)
# separate years
p14 = ptsd_table.query('year == 2014').reset_index(drop=True)
p15 = ptsd_table.query('year == 2015').reset_index(drop=True)
col_add = ['total_served', 'total_ptsd']
if year == '2014':
ptsd_table = p14
elif year == '2015':
ptsd_table = p15
elif year == '2015+2014':
ptsd_table = p15
ptsd_table[col_add] += p14[col_add]
# get the state boundaries
state_table = pd.DataFrame(us_states.data).T
# merge tables
ptsd_table = pd.merge(state_table,
ptsd_table,
how='inner',
left_index=True,
right_on='state')
ptsd_table['ptsd_rate'] = (100 * ptsd_table.total_ptsd /
ptsd_table.total_served)
# create data source for map
src = ColumnDataSource({
'lons': ptsd_table['lons'].tolist(),
'lats': ptsd_table['lats'].tolist(),
'ptsd_rate': ptsd_table['ptsd_rate'],
'total_served': ptsd_table['total_served'],
'total_ptsd': ptsd_table['total_ptsd'],
'name': ptsd_table['name']
})
# generate color map
cmap = LinearColorMapper(palette=palette)
# create figure
us_map = figure(width=1200,
x_axis_location=None,
y_axis_location=None,
tools="hover",
title="Rates of Post Traumatic Stress (2015)")
us_map.grid.grid_line_color = None
us_map.patches('lons',
'lats',
source=src,
line_color='black',
fill_color={
'field': metric,
'transform': cmap
})
us_map.x_range = Range1d(-130, -60)
us_map.y_range = Range1d(20, 55)
# program hover tool
hover = us_map.select_one(HoverTool)
hover.tooltips = [("State", "@name"),
("Total Veterans Enrolled", "@total_served"),
("Total PTSD", "@total_ptsd (@ptsd_rate{int}%)")]
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components(us_map)
html = flask.render_template('embed.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
metric=metric,
year=year)
return encode_utf8(html)
def Ope():
if not request.method in ['POST']:
return redirect(url_for('main.index'))
files = request.files.getlist("ope[]")
app.logger.debug('files={}'.format(files))
opes = []
del_files = []
upload_dir = current_app.config['APP_UPLOAD']
for f in files:
filename = secure_filename(f.filename)
ope = os.path.join(upload_dir, filename)
f.save(ope)
del_files.append(ope)
if filename.lower().endswith(".ope"):
opes.append(ope)
app.logger.debug('opes={}'.format(opes))
try:
targets = helper.ope(opes, upload_dir, app.logger)
#errors = helper.format_error(targets, app.logger)
except Exception as e:
app.logger.error('Error: invalid ope file. {}'.format(e))
err_msg = "Plot Error: {}".format(e)
#errors.append(err_msg)
delete_files(del_files)
return render_template('target_visibility.html', errors=[err_msg])
#filepath = tempfile.NamedTemporaryFile().name
#filepath = os.path.join(current_app.config['APP_UPLOAD'], filename)
mysite = helper.site(request.form.get('site'))
mydate = request.form.get('date')
#app.logger.debug('targets={}'.format(targets))
#app.logger.debug('filepath={}'.format(filepath))
app.logger.debug('mydate={}'.format(mydate))
delete_files(del_files)
try:
#fig = helper.populate_target2(targets, mysite, mydate, filepath, app.logger)
fig = helper.populate_interactive_target(target_list=targets,
mysite=mysite,
mydate=mydate,
logger=app.logger)
except Exception as e:
app.logger.error('Error: failed to populate ope plot. {}'.format(e))
err_msg = "Plot Error: {}".format(e)
#errors.append(err_msg)
return render_template('target_visibility.html', errors=[err_msg])
else:
# Grab the static resources
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
# render template
script, div = components(fig)
html = render_template('target_visibility.html',
plot_script=script,
plot_div=div,
js_resources=js_resources,
css_resources=css_resources,
errors=None)
return encode_utf8(html)
def graph():
ajax_input = dict(x_time=[],
x1_time=[],
y=[],
y_female=[],
y_male=[],
x_female_proj=[],
y_female_proj=[],
x_male_proj=[],
y_male_proj=[],
y_female_avg_viewing=[],
y_male_avg_viewing=[])
source = AjaxDataSource(data=ajax_input,
data_url='http://127.0.0.1:5000/data',
polling_interval=ajax_refresh_inter *
1000) #adapter=adapter)
p = figure(plot_height=300,
plot_width=800,
x_axis_type="datetime",
tools="wheel_zoom,reset",
title="People Viewing Statistics")
p.line(x='x_time',
y='y',
line_dash="4 4",
line_width=3,
color='gray',
source=source)
p.vbar(x='x_time',
top='y_female',
width=200,
alpha=0.5,
color='red',
legend='female',
source=source) #female
p.vbar(x='x1_time',
top='y_male',
width=200,
alpha=0.5,
color='blue',
legend='male',
source=source) #male
p.xaxis.formatter = DatetimeTickFormatter(milliseconds=["%X"],
seconds=["%X"],
minutes=["%X"],
hours=["%X"])
p.y_range = DataRange1d(start=0,
range_padding=5) #padding leave margin on the top
p.legend.orientation = "horizontal" #legend horizontal
p.xaxis.axis_label = 'Time'
p.yaxis.axis_label = 'Number'
# p.x_range.follow = "end"
# p.x_range.follow_interval = timedelta(seconds=30)
p2 = figure(plot_height=300,
plot_width=800,
tools="wheel_zoom,reset",
title="Project Viewing Statistics")
p2.vbar(x='x_female_proj',
top='y_female_proj',
width=f2_vbar_interval,
alpha=0.5,
color='red',
legend='female',
source=source) #female
p2.vbar(x='x_male_proj',
top='y_male_proj',
width=f2_vbar_interval,
alpha=0.5,
color='blue',
legend='male',
source=source) #male
p2.xaxis.ticker = [2, 6, 10, 14]
p2.xaxis.major_label_overrides = {2: 'P1', 6: 'P2', 10: 'P3', 14: 'P4'}
# avg_view_male = LabelSet(x='x_male_proj', y='y_male_proj', text='y_male_avg_viewing', level='glyph',
# x_offset=0, y_offset=5, source=source, render_mode='canvas')
# avg_view_female = LabelSet(x='x_female_proj', y='y_female_proj', text='y_female_avg_viewing', level='glyph',
# x_offset=0, y_offset=5, source=source, render_mode='canvas')
#
# p2.add_layout(avg_view_male)
# p2.add_layout(avg_view_female)
p2.x_range = DataRange1d(start=0, end=16) #padding leave margin on the top
p2.y_range = DataRange1d(start=0,
range_padding=5) #padding leave margin on the top
p2.legend.orientation = "horizontal"
p2.xaxis.axis_label = 'Project'
p2.yaxis.axis_label = 'Number'
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
script, div = components((p, p2))
html = render_template(
'embed.html',
plot_script=script,
plot_div=div[0],
plot_div2=div[1],
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
def correlation():
"the scatter plot"
args = flask.request.args
xattr = args.get("x", "atomic_number")
yattr = args.get("y", "covalent_radius_pyykko")
categ = args.get("categ", "name_series")
data = get_data()
properties = get_property_names(data)
categories = get_category_names()
fig = Figure(title="{} vs {}".format(properties[xattr], properties[yattr]),
plot_width=PLOT_WIDTH,
plot_height=PLOT_HEIGHT,
tools="box_zoom,pan,resize,save,reset",
toolbar_location="above",
toolbar_sticky=False,
)
fig.xaxis.axis_label = properties[xattr]
fig.yaxis.axis_label = properties[yattr]
ccm = get_color_mapper(categ, data)
if categ == "None":
legend = None
color_dict = "#1F77B4"
else:
legend = categ
color_dict = {"field": categ, "transform": ccm}
fig.circle(x=xattr, y=yattr, fill_alpha=0.7, size=10,
source=ColumnDataSource(data=data),
fill_color=color_dict,
line_color=color_dict,
legend=legend)
if categ != "None":
fig.legend.location = (0, 0)
fig.legend.plot = None
fig.add_layout(fig.legend[0], "right")
hover = HoverTool(tooltips=HOVER_TOOLTIPS)
fig.add_tools(hover)
script, div = components(fig)
js_resources = INLINE.render_js()
css_resources = INLINE.render_css()
html = render_template(
"correlations.html",
plot_script=script,
plot_div=div,
properties=properties,
categories=categories,
xselected=xattr,
yselected=yattr,
catselected=categ,
js_resources=js_resources,
css_resources=css_resources,
)
return encode_utf8(html)
