def poledir(d, i, r):
if d and i and r:
x, y, z = dir_to_xyz(d, i, r)
x, y, z = round(x, 1), round(y, 1), round(z, 1)
return (dbc.ListGroup([
dbc.Row([
dbc.Col([
dbc.ListGroupItemText("X",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(x),
],
width=4),
dbc.Col([
dbc.ListGroupItemText("Y",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(y),
],
width=4),
dbc.Col([
dbc.ListGroupItemText("Z",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(z),
],
width=4),
])
]))
def poledir(x, y, z):
if x and y and z:
dec, inc, mag = xyz_to_dir(x, y, z, "MAG")
return (dbc.ListGroup([
dbc.Row([
dbc.Col([
dbc.ListGroupItemText("Declination",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(dec),
],
width=4),
dbc.Col([
dbc.ListGroupItemText("Inclination",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(inc),
],
width=4),
dbc.Col([
dbc.ListGroupItemText("Magnitude",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(mag),
],
width=4),
])
]))
def get_port_view(name, port):
return [
dbc.Row(html.H3(name), align='center', justify='center'),
dbc.Row(dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{port["Returns"]:.2%}'),
dbc.ListGroupItemText('RETURNS')
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{port["Volatility"]:.4f}'),
dbc.ListGroupItemText("VOLATILITY")
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{port["Sharpe Ratio"]:.4f}'),
dbc.ListGroupItemText("SHARPE RATIO")
]),
],
horizontal=True),
align='center',
justify='center'),
dbc.Row(dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{weight:.2%}'),
dbc.ListGroupItemText(symbol)
]) for symbol, weight in port['Expected Weights'].items()
],
horizontal=True),
align='center',
justify='center'),
html.Hr()
]
def show_news_list(self, zipcode="21029", radius=70):
colors = ['primary', 'secondary', 'success', 'warning', 'danger', 'info']
color_cycle = cycle(colors)
try:
news_list = self.get_local_news_by_zipcode(zipcode, radius)
except BaseException as ex:
print('-' * 60)
traceback.print_exc(file=sys.stdout)
print('-' * 60)
news_list = []
try:
# return html.Ol([
# html.Li([
# html.A(x['title'], href=x['url'], target='_blank'),
# html.Div(x['publishedAt'], style={'size': 1, 'color': "blue"})
# ])
# for x in news_list])
return dbc.ListGroup(
[
dbc.ListGroupItem(
[
dbc.ListGroupItemHeading(html.H5(x['title'])),
dbc.ListGroupItemText(html.H6(x['publishedAt'])),
],
href=x['url'], target='_blank', color=next(color_cycle)
) for x in news_list
]
)
except BaseException:
print('-' * 60)
traceback.print_exc(file=sys.stdout)
print('-' * 60)
return html.Ol("API call limit")
def make_list_item(song,unique_id):
name = song.name
artist = song.artist
external_url = song.url
uri = song.uri
heading = dbc.ListGroupItemText("{} - {}".format(name, artist))
return dbc.ListGroupItem(heading,id=unique_id, key=str(uri))
def poledir(lat, lon, dec, inc, a95):
if lat and lon and dec and inc and a95:
PLat, PLon, dp, dm, PaleoLat = paleo_pole(lat, lon, dec, inc, a95)
return (dbc.ListGroup([
dbc.Row([
dbc.Col([
dbc.ListGroupItemText("PLat",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(PLat),
],
width=3),
dbc.Col([
dbc.ListGroupItemText("PLon",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(PLon),
],
width=3),
dbc.Col([
dbc.ListGroupItemText("dp/dm",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(str(dp) + "/" + str(dm)),
],
width=3),
dbc.Col([
dbc.ListGroupItemText("PaleoLat",
style={
"margin-bottom": "-2px",
}),
dbc.ListGroupItem(PaleoLat),
],
width=3)
])
])
# html.P(
# "PLat: " + str(PLat) + " PLon: " + str(PLon) +
# " dp/dm: " + str(dp)+"/"+str(dm) + " PaleoLat: " + str(PaleoLat),
# className="text-center"
# ),
)
def macro_component():
"""
The main macro panel
:return:
"""
title = "Macro Data"
output_row = dbc.Row(
dbc.Tabs(
id="macro-tab-selector",
active_tab="ust-curve",
children=[
dbc.Tab(label="US Treasury Curve",
tab_id="ust-curve",
children=[subpanel.usd_treasury_curve()]),
dbc.Tab(
label="USD Swap Curve",
tab_id="usd-swap-curve",
children=[
subpanel.usd_swap_curve(),
dbc.Col([
html.A(
dbc.Button("Data Citations",
className="mr-1",
id="usd-swap-citations-button"))
],
width=4),
dbc.Popover(
[
dbc.PopoverHeader("USD Swap Citations"),
dbc.PopoverBody([
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(
f"ICE USD Swap {yr} Yr"),
dbc.ListGroupItemText(
dl.macro.get_usd_swap_citation(
yr))
]) for yr in dl.macro.maturities
])
])
],
id="usd-swap-citations",
is_open=False,
target="usd-swap-citations-button",
)
]),
dbc.Tab(label="Coming Soon...",
tab_id="coming-soon",
disabled=True)
]))
obj = panel_template(title, output_row)
return obj
def update_meta_data_list(series_data_dict, **kwargs):
model_name = kwargs["model_selector"]
model_description = series_data_dict["all_forecasts"][model_name][
"model_description"]
if model_description == model_name:
model_description = ""
model_cv_score = series_data_dict["all_forecasts"][model_name][
"cv_score"]
return dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Model Details"),
dbc.ListGroupItemText([
html.P(model_name),
html.P(model_description),
html.P("CV score: %f" % model_cv_score),
]),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Forecast Updated At"),
dbc.ListGroupItemText(
series_data_dict["forecasted_at"].strftime(
"%Y-%m-%d %H:%M:%S")),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Data Collected At"),
dbc.ListGroupItemText(
series_data_dict["downloaded_dict"]
["downloaded_at"].strftime("%Y-%m-%d %H:%M:%S")),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Data Source"),
dbc.ListGroupItemText([
html.A(
series_data_dict["data_source_dict"]["url"],
href=series_data_dict["data_source_dict"]["url"],
)
]),
]),
])
def tab_right_countries(dropdown):
if len(dropdown) == 0:
for country in top_4:
dropdown.append(country)
return html.Div([
html.Ul([
html.Li([
html.Div([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{country}:'),
html.Hr(),
dbc.ListGroupItemText(f'Confirmed cases: {df_tab_right.iloc[0][country]:,}'),
dbc.ListGroupItemText(f'Deaths: {df_tab_right.iloc[1][country]:,}'),
list_item('Mortality rate: ', float('%.2f'%(df_tab_right.iloc[2][country]*100)), '%'),
dbc.ListGroupItemText(f'Infection rate: {df_tab_right.iloc[3][country]*100:.2f}%'),
dbc.ListGroupItemText(f'Share out of global confirmed cases: {df_tab_right.iloc[4][country]*100:.4f}%'),
list_item('Share out of global deaths: ', float('%.4f'%(df_tab_right.iloc[5][country]*100)), '%'),
dbc.ListGroupItemText(f'Date of 1st confirmed case: {df_tab_right.iloc[6][country]}'),
list_item('Date of 1st confirmed death: ', df_tab_right.iloc[7][country], ''),
list_item('Policy Index: ', df_tab_right.iloc[8][country], ''),
dbc.ListGroupItemText(f'Population in 2019: {df_tab_right.iloc[9][country]:,}'),
], className="items") for country in dropdown
],
className='media-body border-0'
),
],
className='media border-0'
),
],
className='list-unstyled'
),
],
className="tabr overflow-auto"
)
def list_item(opening, data, ending):
'''
input:
info data about a statistic for a country
a string describing it
a string of eventual text after data
output:
if the data is valid returns an item, otherwise nothing
'''
if pd.isna(data) or data == 'None' or data == 0:
return
else:
return dbc.ListGroupItemText(f'{opening}{data}{ending}')
def display_rebalance_output(n_clicks, text_area: str, results):
if not n_clicks:
raise PreventUpdate
if not text_area:
raise PreventUpdate
if not results:
raise PreventUpdate
try:
portfolio = json.loads(text_area)
except (Exception):
return dbc.Alert("Invalid JSON format", color="danger"),
min_vol = results[MIN_VOL]['Expected Weights']
max_sharpe = results[MAX_SHARPE]['Expected Weights']
symbols = portfolio.keys()
with open('config.json', 'r') as file:
config = json.load(file)['crypto']
api_key = config['crypto_compare_api_key']
url = 'https://min-api.cryptocompare.com/data/pricemulti'
params = {"fsyms": ','.join(symbols), "tsyms": "USD", "api_key": api_key}
exchange_rate = requests.get(url, params=params).json()
usd_price = {key: value['USD'] for key, value in exchange_rate.items()}
display_result = {}
results = pd.DataFrame({"a": portfolio, 'usd_price': usd_price})
results['holding'] = results['a'] * results['usd_price']
results['w'] = results['holding'] / results['holding'].sum()
total_asset_value = results['holding'].sum()
for entry in [('Maximmum Sharpe Ratio', max_sharpe),
('Minimmum Volatitly', min_vol)]:
results['ew'] = pd.Series(entry[1])
results['ew_r'] = results['ew'] - results['w']
results['ew_usd'] = results['ew_r'] * \
results['holding'].sum()
results['ew_a'] = results['ew_usd'] / results['usd_price']
display_result[entry[0]] = results['ew_a'].to_dict()
return [html.H4(f'Total Asset Value: ${total_asset_value:.4f}'),
html.Hr()] +\
[dbc.Row(dbc.Col([
html.H5(name),
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f"{value:.5f} {key}"),
dbc.ListGroupItemText(f"{value*usd_price[key]:=.2f} USD"),
]) for key, value in ew.items()
], horizontal=True),
html.Hr()
]),
align='center', justify='center'
) for name, ew in display_result.items()] +\
[dbc.Label("* positive value is for buy" +
" and negative value is for sell")]
def make_activity_info_header(activity: Activity):
metrics = ActivityMetrics(activity=activity, config={'ftp': 290})
if activity.type == 'Run' or 'Walk':
return html.Div([])
line1 = dbc.ListGroup(
[
dbc.ListGroupItem([
dbc.ListGroupItemHeading(activity.name,
style={'font-size': '0.7rem'}),
dbc.ListGroupItemText(activity.date),
dbc.ListGroupItemText(""),
],
style={
'font-size': '0.6rem',
'line-height': '0.1em'
}),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Power",
style={'font-size': '0.7rem'}),
dbc.ListGroupItemText(f"{metrics.average_power}"),
dbc.ListGroupItemText(f"{metrics.normalized}"),
dbc.ListGroupItemText(f"{metrics.work}"),
],
style={
'font-size': '0.6rem',
'line-height': '0.1em'
}),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("HR",
style={'font-size': '0.7rem'}),
dbc.ListGroupItemText(f"{metrics.average_hr}"),
dbc.ListGroupItemText(f"{metrics.max_hr}"),
],
style={
'font-size': '0.6rem',
'line-height': '0.1em'
}),
],
horizontal=True,
className="mb-1",
style={'font-size': '0.8rem'},
)
line2 = dbc.ListGroup([])
list_group = html.Div([
line1,
line2,
])
return list_group
def make_transaction_group(df: pd.DataFrame):
"""Create a group of transactions"""
list_items = []
for idx, transaction in df.iterrows():
list_items.append(
dbc.ListGroupItem(
[
dbc.ListGroupItemHeading(html.H6(transaction.payee)),
dbc.ListGroupItemText([
html.P(transaction.display_name),
html.P(f"$ {transaction.total}")
]),
],
action=True,
))
return dbc.ListGroup(list_items)
def create_list_item(contents, filename, idx):
''' creates component from file'''
data = base64.b64decode(contents[contents.find(',')+1:].encode('ascii'))
data = ast.literal_eval(data.decode("UTF-8"))
v = jsonschema.Draft7Validator(schema)
for error in v.iter_errors(data):
error = {'JSON_FORMAT_ERROR': str(error.message)}
return
#kw = str('json-button-'+str(idx))
kw = idx
return dbc.ListGroupItem([
dbc.ListGroupItemHeading(filename),
dbc.ListGroupItemText(data['id']),
#html.Div(data['muestras'], style={'display': 'none'}),
#html.Div(data['data'], style={'display': 'none'})
],
id={
'role': 'data-button',
'index': kw
},
style=ITEM_STYLE,
action=True
)
def tab_right_provinces(BE_total_prov_merged):
temp_data = BE_total_prov_merged.copy()
return html.Div([
html.Ul([
html.Li([
html.Div([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(f'{prov}:'),
html.Hr(),
dbc.ListGroupItemText(
f"Confirmed cases: {int(temp_data.loc[temp_data['PROVINCE'] == prov]['Cumulative cases'].max()):,}",
color='info'),
dbc.ListGroupItemText(
f"Hospitalized: {int(temp_data.loc[temp_data['PROVINCE'] == prov].iloc[-1]['Hospitalized']):,}",
color='warning'),
dbc.ListGroupItemText(
f"ICU: {int(temp_data.loc[temp_data['PROVINCE'] == prov].iloc[-1]['ICU']):,}",
color='danger'),
dbc.ListGroupItemText(
f"Respiratory: {int(temp_data.loc[temp_data['PROVINCE'] == prov].iloc[-1]['Respiratory']):,}",
color='warning'),
dbc.ListGroupItemText(
f"Released from hospital: {int(temp_data.loc[temp_data['PROVINCE'] == prov].iloc[-1]['Released from hospital']):,}",
color='info'),
dbc.ListGroupItemText(
f"Total hospitalized: {int(temp_data.loc[temp_data['PROVINCE'] == prov].iloc[-1]['Total hospitalized']):,}",
color='warning'),
],
className="items")
for prov in sorted(
list(set(BE_total_prov_merged['PROVINCE'])))
],
className='media-body border-0'),
],
className='media border-0'),
],
className='list-unstyled'),
],
className="tabr overflow-auto")
num -= x / 20
styles.append({
'if': {
'state': 'active'
},
'backgroundColor': 'rgba(0, 116, 217, 0.3)',
'border': '0px solid rgb(0, 116, 217)'
})
return styles
page = html.Div(
[
dbc.ListGroupItem([
dbc.ListGroupItemHeading(html.H3('市场宽度')),
dbc.ListGroupItemText(
html.P('代表市场的涨跌的钟摆运动。当总数低于200-高于1000，进入极值区间。投资者在极值区操作最佳。')),
]),
html.Br(),
dash_table.DataTable(
id='martket-breadth',
columns=([{
'id': p,
'name': col[p]
} for p in df.columns]),
data=df.to_dict('records'),
style_header={
'backgroundColor': 'gold',
'fontWeight': 'bold',
'textAlign': 'center',
'height': '60px',
'whiteSpace': 'normal',
def similar_text_new(n_clicks, load_page, process_text, n_articles=10):
if process_text is None:
raise PreventUpdate
vec = CountVectorizer(decode_error="replace",
vocabulary=pickle.load(
open("model/feature.pkl", "rb")))
new_vec = vec.transform([process_text])
lda = pickle.load(open("model/lda_model.pkl", "rb"))
topic_dist = list(lda.transform(new_vec)[0])
store_vals = list()
for i in range(len(covid_papers)):
if (i in covid_papers.index):
store_vals.append((int(i), (sqrt(
mean_squared_error(topic_dist, [
float(i) for i in covid_papers.loc[
int(i), 'topic_dist'].strip('[]').split(', ')
])))))
most_similar = sorted(store_vals, key=itemgetter(1))
if n_clicks is None:
data = [
covid_papers.loc[
int(i[0]),
['title', 'url', 'abstract', 'authors', 'publish_time']]
for i in most_similar[1:(n_articles + 1)]
]
else:
data = [
covid_papers.loc[
int(i[0]),
['title', 'url', 'abstract', 'authors', 'publish_time']]
for i in most_similar[1:(n_articles + 1 + (n_articles * n_clicks))]
]
if load_page is None:
raise PreventUpdate
else:
out = []
for info in data:
out.append(
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItem(dbc.ListGroupItemHeading(info[0]),
href=info[1],
target="_blank"),
html.Br(),
dbc.ListGroupItemText(f"Authors: {info[3]}",
style={
'text-align': 'left',
'font-size': 'small'
}),
dbc.ListGroupItemText(f"Published: {info[4]}",
style={
'text-align': 'left',
'font-size': 'smaller'
}),
dbc.ListGroupItemText(info[2],
style={'text-align': 'justify'}),
])
],
flush=True))
out.append(html.Br())
out.append(
dbc.Button("Load More",
id='button',
outline=True,
color="primary",
className="mr-1",
style={
'margin-left': '46%',
'margin-bottom': '10%px',
'verticalAlign': 'middle'
}))
return out
return (fuzz.partial_ratio(x, y))
partial_match_vector = np.vectorize(partial_match)
combined_dataframe['score'] = partial_match_vector(
combined_dataframe['Match'], combined_dataframe['compare'])
combined_dataframe = combined_dataframe[combined_dataframe.score >= 80]
return combined_dataframe
attributes = html.Div([
dbc.Row([
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Rating"),
dbc.ListGroupItemText(id="rating"),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Genre"),
dbc.ListGroupItemText(id="Genre"),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Duration"),
dbc.ListGroupItemText(id="Duration"),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Director"),
dbc.ListGroupItemText(id="Director"),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Language"),
],
)
], color = "dark", outline = True,
)
infocard = dbc.Card(
[
dbc.CardHeader(html.H5("Metadata", className = 'text-left')),
dbc.CardBody(
[
dbc.ListGroup(
[
dbc.ListGroupItem(
[
dbc.ListGroupItemHeading("Hypo. Dist (km)"),
dbc.ListGroupItemText("", id = 'hypo-dist'),
]
),
dbc.ListGroupItem( [
dbc.ListGroupItemHeading("Epi. Dist (km)"),
dbc.ListGroupItemText("", id = 'epi-dist'),
],
),
], horizontal = True,
),
]
)
]
)
app.layout = dbc.Container(
def tab_left_regions(BE_reg_total_deaths, BE_reg_total_cases,
BE_reg_male_deaths, BE_reg_female_deaths,
BE_reg_male_cases, BE_reg_female_cases, BE_reg_pop,
region):
if region == 'Flanders':
index = 0
elif region == 'Wallonia':
index = 1
elif region == 'Brussels':
index = 2
return html.Div([
html.Ul([
html.Li([
html.Div([
dbc.ListGroupItem([
dbc.ListGroupItemText(
f"Confirmed cases: {int(BE_reg_total_cases.loc[region, 'CASES'].max()):,}",
color='info'),
dbc.ListGroupItemText(
f"Confirmed cases (female): {int(BE_reg_female_cases.loc[region, 'CASES'].max()):,}",
color='info'),
dbc.ListGroupItemText(
f"Confirmed cases (male): {int(BE_reg_male_cases.loc[region, 'CASES'].max()):,}",
color='info'),
dbc.ListGroupItemText(
f"Deaths: {int(BE_reg_total_deaths.loc[region, 'DEATHS'].max()):,}",
color='danger'),
dbc.ListGroupItemText(
f"Deaths (female): {int(BE_reg_female_deaths.loc[region, 'DEATHS'].max()):,}",
color='danger'),
dbc.ListGroupItemText(
f"Deaths (male): {int(BE_reg_male_deaths.loc[region, 'DEATHS'].max()):,}",
color='danger'),
dbc.ListGroupItemText(
f"Mortality rate: {(BE_reg_total_deaths.loc[region, 'DEATHS'].max()/BE_reg_pop.iloc[index]['Total'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Mortality rate (female): {(BE_reg_female_deaths.loc[region, 'DEATHS'].max()/BE_reg_pop.iloc[index]['Female'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Mortality rate (male): {(BE_reg_male_deaths.loc[region, 'DEATHS'].max()/BE_reg_pop.iloc[index]['Male'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Infection rate: {(BE_reg_total_cases.loc[region, 'CASES'].max()/BE_reg_pop.iloc[index]['Total'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Infection rate (female): {(BE_reg_female_cases.loc[region, 'CASES'].max()/BE_reg_pop.iloc[index]['Female'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Infection rate (male): {(BE_reg_male_cases.loc[region, 'CASES'].max()/BE_reg_pop.iloc[index]['Male'])*100:.2f}%",
color='warning'),
dbc.ListGroupItemText(
f"Population in 2019: {int(BE_reg_pop.iloc[index]['Total']):,}",
color='success'),
dbc.ListGroupItemText(
f"Population in 2019 (female): {int(BE_reg_pop.iloc[index]['Female']):,}",
color='success'),
dbc.ListGroupItemText(
f"Population in 2019 (male): {int(BE_reg_pop.iloc[index]['Male']):,}",
color='success'),
],
className="items")
],
className='media-body'),
],
className='media'),
],
className='list-unstyled'),
],
className="tabcard overflow-auto")
def layout(url):
project = get_project_from_url(url)
if project is None:
return [
dbc.Row(className="mt-5", children=
dbc.Col(width=12, children=[
html.H3("Project not found"),
html.P([
"Go back to the ",
dcc.Link("homepage", href="/")
]),
])
)
]
return [
crumbs([("Home", "/"), (project.name, "/" + project.slug)]),
dbc.Row(
dbc.Col(width=12, children=[
dbc.Row([
dbc.Col(width=9, children=
html.Div(className="bg-white pt-3 px-4 pb-2 mb-3 border border shadow-sm", children=[
html.H3(f"{project.name}"),
html.Hr(),
dbc.Tabs([
dbc.Tab(label='Overview', tab_id="tab-overview"),
dbc.Tab(label='FlexiScatter', tab_id="tab-flexiscatter")
],
id="project-tabs",
active_tab='tab-overview'),
html.Div(id="content")
]),
),
dbc.Col(width=3, children=[
html.Div(
className="bg-white pt-3 pb-2 mb-3 border border-primary shadow-sm",
children=[
html.H3([
f"Combinations ",
dbc.Badge(f" {project.combinations.count()} ",
color='info')
], className="d-flex justify-content-between align-items-center px-3 mb-0"),
html.Span(f"in {project.name}, sorted by target", className='small px-3'),
dbc.ListGroup(className='combinations-list mt-2', flush=True, children=[
dbc.ListGroupItem(
href=c.url,
action=True,
children=[
dbc.ListGroupItemHeading(
f"{c.lib1.name} + {c.lib2.name}"),
dbc.ListGroupItemText(
f"{c.lib1.target} + {c.lib2.target}")
]
) for c in project.combinations
])
])
])
])
])
),
html.Div(className="d-none", id='project-id', children=project.id)
]
),
]
)
list_group = html.Div(
[
html.H2("ListGroup"),
dbc.ListGroup(
[
dbc.ListGroupItem("Item 1", color="primary", action=True),
dbc.ListGroupItem("Item 2"),
dbc.ListGroupItem("Item 3"),
dbc.ListGroupItem(
[
dbc.ListGroupItemHeading("Item 4 heading"),
dbc.ListGroupItemText("Item 4 text"),
]
),
]
),
]
)
popover = html.Div(
[
html.H2("Popover"),
html.P(
["Click on the word ", html.Span("popover", id="popover-target")]
),
dbc.Popover(
[
# 不显示图例
showlegend=False,
legend=dict(x=0, y=1.0),
margin=dict(l=20, r=20, t=40, b=40)),
),
style={
'height': 500,
'width': "100%"
},
config={
'responsive': True,
'autosizable': True,
'showAxisDragHandles': True,
'staticPlot': False, # 静态图
'displayModeBar': False # 关闭工具箱
},
id='swpt_graph',
)
page = html.Div(children=[
dbc.ListGroupItem(
[
dbc.ListGroupItemHeading(html.H3('美联储干预市场的力度')),
dbc.ListGroupItemText(html.P('Glod Holdings 与 U.S All Rates数据以后更新。')),
]
),
fed_assets_graph,
html.Hr(),
liq_swap_graph],
className="container")
def get_stats(data: dict):
return [
dbc.Col([
html.H5('Social Stats'),
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(" ".join(key.title().split("_"))),
dbc.ListGroupItemText(value)
]) for key, value in data['community_data'].items()
if value is not None
] + [
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Alexa Ranking'),
dbc.ListGroupItemText(data['public_interest_stats']
['alexa_rank'])
])
])
]),
dbc.Col([
html.H5('Github Stats'),
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading(" ".join(key.title().split("_"))),
dbc.ListGroupItemText(value)
]) for key, value in data['developer_data'].items()
if not isinstance(value, dict)
])
]),
dbc.Col([
html.H5('Community Stats'),
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Market Cap Rank'),
dbc.ListGroupItemText(data['market_cap_rank'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('CoinGecko Rank'),
dbc.ListGroupItemText(data['coingecko_rank'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('CoinGecko Score'),
dbc.ListGroupItemText(data['coingecko_score'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Developer Score'),
dbc.ListGroupItemText(data['developer_score'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Community Score'),
dbc.ListGroupItemText(data['community_score'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Liquidity Score'),
dbc.ListGroupItemText(data['liquidity_score'])
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading('Public Interest Score'),
dbc.ListGroupItemText(data['public_interest_score'])
]),
])
])
]
html.Span(
"На этой странице представлены данные о землетрясениях в Байкальском регионе. Все данные получены с "
),
html.A("сайта БФ ФИЦ ЕГС РАН",
href="http://seis-bykl.ru",
target='_blank'),
html.Br(),
html.A("Сообщить о проблеме",
href="https://github.com/rishm069/earthquakes38",
target='_blank'),
html.Br(),
dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Селектор"),
dbc.ListGroupItemText(
"Селектор позволяет выбрать отображение на карте всех землетрясений за текущий год ('Землетрясения за текущий год'), только последнего землетрясения ('Последнее землетрясение') или все землетрясения с 1994 года ('Исторические данные')"
),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Таблица"),
dbc.ListGroupItemText(
"Таблица позволяет выбирать землетрясения для отображения на карте: по умолчанию отображаются все землетрясения, при выборе одного и более землетрясений на карте будут отмечены только эти землятресения. Данные можно сортировать и фильтровать с помощью таблицы, например:"
),
dbc.ListGroupItemText(
"'-09-' в столбце 'Дата' покажет только данные за Сентябрь"
),
html.Img(
style={
'height': '100%',
'width': '100%'
},
width=6,
lg=6,
md=6,
xs=12,
),
dbc.Col(
dbc.ListGroup(
[
dbc.ListGroupItem([
html.Img(
src="assets/github_pr.PNG",
style={"width": "64px"},
),
dbc.ListGroupItemHeading(
f"{num_done}"),
dbc.ListGroupItemText(
"pull requests"),
]),
# dbc.ListGroupItem(
# [
# html.Img(
# src="assets/jira_story.SVG",
# style={"width": "64px"},
# ),
# dbc.ListGroupItemHeading(f"{num_done['Story']} "),
# dbc.ListGroupItemText("stories"),
# ]
# ),
],
horizontal=True,
),
width=6,
xs=12,
),
dbc.Col(
dbc.ListGroup(
[
dbc.ListGroupItem(
[
html.Img(
src="assets/jira_bug.SVG",
style={"width": "64px"},
),
dbc.ListGroupItemHeading(
f"{num_done['Bug'] if 'Bug' in num_done.keys() else 0}"
),
dbc.ListGroupItemText(
"bugs"
),
]
),
dbc.ListGroupItem(
[
html.Img(
src="assets/jira_story.SVG",
style={"width": "64px"},
),
dbc.ListGroupItemHeading(
f"{num_done['Story']} "
),
dbc.ListGroupItemText(
"stories"
),
def input_session():
return dbc.ListGroup([
dbc.ListGroupItem([html.H4("Client Input Assumptions")]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Plan Information", style={"font-family":"NotoSans-SemiBold","font-size":"1.2rem"}),
dbc.ListGroupItemText([
dbc.Row([
dbc.Col("Plan Type", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "MAPD", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Members", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "150,000", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Age Distribution", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col([
dbc.Button("···", id = 'button-popover-age', size="sm", color='primary', style={"border-radius":"10rem"}),
dbc.Popover([
dbc.PopoverHeader("Age Distribution", style={"font-family":"NotoSans-SemiBold","font-size":"1rem"}),
dbc.PopoverBody([dbc.Row([
dbc.Col("Age Band", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col("Member %", style={"font-family":"NotoSans-Regular","font-size":"1rem"})
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("<65", style={"font-family":"NotoSans-Regular","font-size":"0.8rem"}),
dbc.Col(dbc.Input(value = "12%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("65-74", style={"font-family":"NotoSans-Regular","font-size":"0.8rem"}),
dbc.Col(dbc.Input(value = "48%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("75-84", style={"font-family":"NotoSans-Regular","font-size":"0.8rem"}),
dbc.Col(dbc.Input(value = "27%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col(">=85", style={"font-family":"NotoSans-Regular","font-size":"0.8rem"}),
dbc.Col(dbc.Input(value = "13%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col(dbc.Button("Save", id = 'popover-age-submit', size="sm", color='primary')),
], style={"padding":"2rem","text-align":"center"}),
], style={"font-family":"NotoSans-Regular","font-size":"1rem", "padding-left":"1rem", "padding-right":"1rem"}),
],id = 'popover-age', is_open = False, target = 'button-popover-age')
])
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Gender Distribution", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Region", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "Northeast", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("MSA (if applicable)", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "New York-Newark-Jersey City, NY-NJ-PA MSA", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Formulary Tier for Entresto", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "Preferred Brand", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Copayment for Entresto by Channel and Days of Supply", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
]),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Drug Information", style={"font-family":"NotoSans-SemiBold","font-size":"1.2rem"}),
dbc.ListGroupItemText([
dbc.Row([
dbc.Col("Entresto Pricing Information", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "$9.6 / unit (tablet)", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Assumptions for Each Measure", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(html.A('Download the template file'), style={"font-family":"NotoSans-Regular","font-size":"1rem","text-decoration":"underline","color":"#1357DD"}),
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col(
dcc.Upload(
id = 'upload-data',
children = html.Div([
'Select Related Files to Upload'
],style={"font-family":"NotoSans-Regular","font-size":"1rem","text-decoration":"underline","color":"#1357DD"}),
style={
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '10px'
}
),style={"padding-top":"1rem"}, width=12),
]),
dbc.Row([
html.Div(id = 'output-data-upload', style={"text-align":"center","padding":"0.5rem","font-family":"NotoSans-Regular","font-size":"0.6rem"}),
], style={"padding-top":"1rem"}),
]),
]),
dbc.ListGroupItem([html.H4("Modeling Assumptions")]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("CHF Prevalence Rate & Severity Assumptions", style={"font-family":"NotoSans-SemiBold","font-size":"1.2rem"}),
dbc.ListGroupItemText([
dbc.Row([
dbc.Col("Projected CHF Patients as a % of Total Plan Members", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "13.6%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Comorbidity Condition %CHF Comorbidity Condition %", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
]),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("CHF Patient Cost and Utilization Assumptions", style={"font-family":"NotoSans-SemiBold","font-size":"1.2rem"}),
dbc.ListGroupItemText([
dbc.Row([
dbc.Col("CHF Patient Cost Assumptions", style={"font-family":"NotoSans-Regular","font-size":"1.2rem"}),
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Cost PPPY (Per Patient Per Year) Before Taking Entresto", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "$ 42,000", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Related Cost as a % of Total Cost", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "60%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Cost PPPY by Service Category", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Cost PPPY by Patient Cohort", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Patient Cost Trend Assumptions", style={"font-family":"NotoSans-Regular","font-size":"1.2rem"}),
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Annual PPPY Cost Trend Before Taking Entresto", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "7%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Annual PPPY Cost Trend by Service Category", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Annual PPPY Cost Trend by Patient Cohort", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Patient Utilization Assumptions", style={"font-family":"NotoSans-Regular","font-size":"1.2rem"}),
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Projected Inpatient Admissions PPPY Before Taking Entresto", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "1.4", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Related Inpatient Admissions as a % of Total Admissions", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "80%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Inpatient Admissions PPPY by Medical Condition", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Total Inpatient Admissions PPPY by Patient Cohort", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("CHF Patient Utilization Trend Assumptions", style={"font-family":"NotoSans-Regular","font-size":"1.2rem"}),
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Annual PPPY Inpatient Utilization Trend Before Taking Entresto", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "5.4%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Annual PPPY Inpatient Utilization Trend by Patient Cohort", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
]),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("Entresto Utilization Assumptions", style={"font-family":"NotoSans-SemiBold","font-size":"1.2rem"}),
dbc.ListGroupItemText([
dbc.Row([
dbc.Col("Projected Entresto Utilizer as a % of Total CHF Population", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "7%", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Entresto Utilizer Monthly Ramp Up Rate", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Button("···", size="sm", color='primary', style={"border-radius":"10rem"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Average Entresto Script PPPY (Per Patient Per Year)", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "6.9", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
dbc.Row([
dbc.Col("Average Units/ Script", style={"font-family":"NotoSans-Regular","font-size":"1rem"}),
dbc.Col(dbc.Input(value = "70", bs_size="sm", style={"border-radius":"5rem","padding-left":"1rem","padding-right":"1rem","color":"#000","font-family":"NotoSans-Regular"}))
], style={"padding-top":"1rem"}),
]),
]),
],
style={"border-radius":"0.5rem"})
import dash_bootstrap_components as dbc
list_group = dbc.ListGroup([
dbc.ListGroupItem([
dbc.ListGroupItemHeading("This item has a heading"),
dbc.ListGroupItemText("And some text underneath"),
]),
dbc.ListGroupItem([
dbc.ListGroupItemHeading("This item also has a heading"),
dbc.ListGroupItemText("And some more text underneath too"),
]),
])
dbc.ListGroupItemText([
dbc.Row(html.P("age -- age in years")),
dbc.Row(html.P("sex -- (1 = male; 0 = female)")),
dbc.Row(
html.
P("cp -- chest pain type (0 - Typical Angina (Heart related), 1 - Atypical Angina (Non-heart related), 2 - Non-Anginal pain (Non-heart related), 3 - Asymptomatic (No disease)"
)),
dbc.Row(
html.
P("trestbps -- resting blood pressure (in mm Hg on admission to the hospital)"
)),
dbc.Row(
html.
P("chol -- serum cholestoral in mg/dl (health levels are < 200mg/dl)"
)),
dbc.Row(
html.
P("fbs -- (fasting blood sugar > 120 mg/dl) (1 = true; 0 = false)"
)),
dbc.Row(
html.
P("restecg -- resting electrocardiographic results ( 0 = normal, 1 = ST-T wave abnormality, 2= probable or definite left ventricular hypertrophy by Estes' criteria )"
)),
dbc.Row(html.P("thalach -- maximum heart rate achieved")),
dbc.Row(
html.P("exang -- exercise induced angina (1 = yes; 0 = no)")),
dbc.Row(
html.
P("oldpeak -- ST depression induced by exercise relative to rest"
)),
dbc.Row(
html.
P("slope -- the slope of the peak exercise ST segment (1 = upsloping, 2 = flat, 3 = downsloping)"
)),
dbc.Row(
html.P(
"ca -- number of major vessels (0-3) colored by flourosopy"
)),
dbc.Row(
html.
P("thal -- (1 = normal; 2 = fixed defect; 3 = reversable defect)"
)),
dbc.Row(
html.P("target -- (1 -heart problem or 0 - no heart problem)"))
]),
