def build_legned(slider_val, dim):
# '''
# Description: Creates the legend that displays the words that correspond to each topic.
# Color coded to match the cluster color in the graph.
# Params: Threshold slider value and the dimension of 2d or 3d.
# Returns: List of words that correspond to each cluster.
# '''
global cluster_obj
leg = cluster_obj.make_legend()
list_of_lis = []
for item, value in leg.items():
list_of_lis.append(html.Li(item, style={'color': value}))
return list_of_lis
def Chapter(name, href=None, caption=None):
linkComponent = html.A if href.startswith('http') else dcc.Link
return html.Div([
html.Li(
linkComponent(
name,
href=href,
style={'paddingLeft': 0},
id=href
)
),
html.Small(dcc.Markdown(s(caption or '')), style={
'display': 'block',
'marginTop': '-10px' if caption else ''
}) if caption else None
])
def __unwrap_section_and_points(self, section, points):
layout = html.Div([
html.Div(
html.H5(
self.__format_string(section, self.data),
style={"color": self.colors["subtitle"]},
)),
html.Div(
html.Ul([
html.Li(html.P(self.__format_string(item, self.data)))
for item in points
]),
style={"color": self.colors["text"]},
),
])
return layout
def Chapter(name, href=None, caption=None):
linkComponent = html.A if href.startswith('http') else dcc.Link
return html.Div(className='toc--chapter',
children=[
html.Li(
linkComponent(name,
href=relpath(href),
id=href,
className='toc--chapter-link'), ),
html.Small(className='toc--chapter-content',
children=Markdown(s(caption or '')),
style={
'display': 'block',
'marginTop': '-10px' if caption else ''
}) if caption else None
])
def stats(solve_time: float,
solution,
cities: list,
mean_time: float,
input_time: int = 0,
new: bool = True):
"""
Reusable component for solution statistics.
Parameters
----------
solve_time: time of solving
solution: Output object
cities: list of Cities
input_time: time provided in time.csv
new: True if for a new solution (requires time.csv)
Returns
-------
html div
"""
if new:
worked_time = input_time - solution.time_left
time_left = solution.time_left
else:
worked_time = solution.time_left
time_left = '?'
return [
html.Div([
html.Li(html.P(f'Solving time: {solve_time:.4f}')),
html.Li(
html.P(f"Path: {', '.join([c.name for c in solution.path])}")),
html.Li(html.P(f'Time worked: {worked_time}')),
html.Li(html.P(f'Time left: {time_left}')),
html.Li(html.P(f'Earned / total: {solution.total}')),
html.Li(
html.
P(f'Mean quantity: {float(np.mean([c.value for c in cities])):.2f}'
)),
html.Li(html.P(f'Mean time: {mean_time:.2f}')),
html.A('Download',
href="/tmp/solution",
target='blank',
style={
'font-size': '16pt',
'text-transform': 'uppercase'
})
])
]
def build_layout():
return html.Div(
[
nav.LAYOUT,
dbc.Row(html.Hr(), style={'height': '3%'}),
html.H2(children='Downloads', style={"text-align": "center"}),
dbc.Row(html.Hr(), style={'height': '3%'}),
html.Div(['Download tumor datasets as tab-separated files.']),
dbc.Row(html.Hr(), style={'height': '3%'}),
html.Ul(
id="file-list",
children=[html.Li(file_download_link(filename)) for filename in get_files()]
),
footer.LAYOUT
],
style={"padding-left": "10%", "padding-right": "10%", "width": "100%"}
)
def get_fire_header(selected_fires):
# TODO: handle multiple fires ?
if len(selected_fires) >= 1:
return [
dbc.Alert(children=[
html.Div("Fire{} represented in the graphs below:".format(
"s" if len(selected_fires) > 1 else "")),
html.Ul(children=[
html.Li(children=[html.Span(sf['flat_summary']['id'])])
for sf in selected_fires
])
],
color="secondary"
)
]
return []
def upload_file(uploaded_filenames, uploaded_file_contents):
upload_directory = 'static/upload/'
if uploaded_filenames is not None and uploaded_file_contents is not None:
for name, data in zip(uploaded_filenames, uploaded_file_contents):
data = data.encode("utf8").split(b";base64,")[1]
with open(os.path.join(upload_directory, name), "wb") as fp:
fp.write(base64.decodebytes(data))
app.compass_module = Module.read_from_file(
os.path.join(upload_directory, name))
bf = len(app.compass_module.biological_features)
ss = len(app.compass_module.sample_sets)
return [
html.Li("File uploaded!"),
html.
Li("The size is {bf} biological features and {ss} sample sets. Check the other Tabs!"
.format(bf=bf, ss=ss))
]
def serve_layout(_, user_key, __):
builder = AnnotationBuilder(local=True)
my_annotations = builder.get_annotations(user=user_key)
children = []
for annotation in my_annotations:
children.append(html.Li([
html.Span([token["text"] + " " for token in annotation.tokens[0]], style={"fontWeight": "bold"}),
html.Br(),
html.Span(annotation.doi),
html.Span(" "),
serve_ann_options(quote(annotation.doi, safe="")),
html.Br(),
html.Span(str(annotation.labels))
]))
return html.Div([html.H5("My Annotated Abstracts"),
html.Ol(children)])
def fine_class_table(value, dropdown):
datasets = json.loads(value)
df_fine = pd.read_json(datasets['df_fine_class'], orient='split')
df_fine = df_fine[df_fine['Variable'] == dropdown].drop(
'Variable', axis=1).reset_index()
df_fine = df_fine.rename(columns={'index': 'Group'})
df_coarse = pd.read_json(datasets['df_coarse'], orient='split')
df_coarse = df_coarse[df_coarse['Variable_name'] == dropdown].drop(
'Variable_name', axis=1).reset_index()
df_coarse = df_coarse.drop(
['WoE_lag', 'var_lag', 'index', 'group_pct', 'WoE_diff', 'yes'],
axis=1)
return html.Div([
html.Li(),
# =============================================================================
# dbc.Row([
# dbc.Col(dash_table.DataTable(
# id='fine_table',
# columns=[{"name": i, "id": i} for i in df_fine.columns],
# data=df_fine.to_dict('records'),
# ),md=6),
# dbc.Col(dcc.Graph(id='fine_graph',
# figure={"data": [{'x':df_fine['From/To'].values,
# 'y':df_fine['WoE'].values,
# 'type': 'bar',
# 'name':'Coarse Classing'}]}
# ),md=6),
# ],align="center", justify="center"),
# html.Li(),
# dbc.Row([
# dbc.Col(dash_table.DataTable(
# id='coarse_table',
# columns=[{"name": i, "id": i} for i in df_coarse.columns],
# data=df_coarse.to_dict('records'),
# ),md=6),
# dbc.Col(dcc.Graph(id='coarse_graph',
# figure={"data": [{'x':df_coarse['From/To'].values,
# 'y':df_coarse['WoE'].values,
# 'type': 'bar',
# 'name':'Coarse Classing'}]}
# ),md=6),
# ],align="center", justify="center"),
# =============================================================================
])
def set_vizier_list(n_clicks, radius, oid, dr):
if n_clicks == 0:
return ''
if radius is None:
return html.P('No radius is specified')
radius = float(radius)
ra, dec = find_ztf_oid.get_coord(oid, dr)
table_list = find_vizier.find(ra, dec, radius)
if len(table_list) == 0:
return html.P(
f'No vizier catalogs found within {radius} arcsec from {ra:.5f}, {dec:.5f}'
)
records = []
lengths = []
for catalog, table in zip(table_list.keys(), table_list.values()):
try:
description = vizier_catalog_details.description(catalog)
except NotFound:
description = catalog
n = len(table)
n_objects = str(n) if n < find_vizier.row_limit else f'≥{n}'
n_objects = f' ({n_objects} objects)' if n > LIST_MAXSHOW else ''
r = sorted(table['_r'])
if n > LIST_MAXSHOW:
r = r[:LIST_MAXSHOW - 1]
sep = ', '.join(f'{x}″' for x in r)
if n > LIST_MAXSHOW:
sep += ', …'
url = find_vizier.get_catalog_url(catalog, ra, dec, radius)
records.append(f'[{description}]({url}){n_objects}: {sep}')
lengths.append(len(description) + len(n_objects) + 2 + len(sep))
ul_column_width = max(lengths) + 2 # for bullet symbol
div = html.Div([
html.Ul([html.Li(dcc.Markdown(record)) for record in records],
style={
'columns': f'{ul_column_width}ch',
'list-style-type': 'none'
}),
])
return div
def make_sidebar_children(data, top_item, inherited_class="", child_class=""):
"""
Recursively generate a hierarchical list defined by data, starting at top_item, using Ul and Li objects
Ul and Li objects ids are defined by Dash id dicts so they can be subscribed to by a callback as a group
For each node, we generate:
* An Li object with children=item_name
* (If node is a middle node with additional children) a Ul object with children=[child_nodes, built recursively]
Args:
data (dict): Dict of lists of relationships within the nested list. For example:
{
"Item-1": ["Item-1-1", "Item-1-2", ...],
"Item-2": ["Item-2-1", "Item-2-2", ...],
"Item-1-1": ["Item-1-1-1", "Item-1-1-2", ...],
...
}
Note that this does not handle repeated names (eg: Item-1-1 cannot have the same name as Item-2)
top_item (str): The key in data that denotes the head of the hierarchy to generate
inherited_class (str): HTML class name to apply once to all levels of the list
child_class (str): HTML class name to apply once per step in the list (so Item 1-1 would have it once,
Item 1-1-1 would have it twice, etc.). Useful for incrementing tab behaviour
Returns:
(list): List of html elements for use as the children attribute of a html.Ul
"""
this_className = f"{inherited_class} {child_class}"
content = []
for name in data[top_item]:
content.append(html.Li(
children=name,
id=generate_checklist_li_id(name),
className=this_className,
))
if name in data:
nested_children = make_sidebar_children(data, name, inherited_class=this_className, child_class=child_class)
content.append(html.Ul(
id=generate_checklist_ul_id(name),
children=nested_children,
))
return content
def generate_carousel():
logger.debug("generate carousel")
headline_services = app_controller.get_club_headline_service(CLUB_NAME)
if not headline_services:
print("no headline")
return html.Div()
service_count = len(headline_services)
logger.debug("generate carouse al")
logger.debug("service count " + str(service_count))
carousel = html.Div(**{"data-ride": "carousel"},
id="carouselExampleIndicators",
className="carousel slide",
children=[
html.Ol(className="carousel-indicators", children=[
html.Li(**{"data-target":"#carouselExampleIndicators", "data-slide-to":str(i)}, className="active" if i ==0 else "") for i in range(service_count)
]),
html.Div(className="carousel-inner", children=[
html.Div(className="carousel-item active" if i ==0 else "carousel-item", children=[
html.Div(className="d-flex", children=[
dcc.Link(className="col",href="/service/book/{}".format(service.id), children=[
html.Img(className="img-fluid",
src=filestore.get_service_img_link(service.id, MAJOR_IMG),
alt="Second slide")
]),
dcc.Link(className="col",href="/service/book/{}".format(service.id), children=[
html.Img(className="img-fluid",
src=filestore.get_service_img_link_alt(service.id),
alt="Second slide")
])
])
]) for i, service in enumerate(headline_services)
]),
html.A(**{"data-slide":"prev"}, className="carousel-control-prev", href="#carouselExampleIndicators", role="button", children=[
html.Span(**{"aria-hidden":"true"}, className="carousel-control-prev-icon"),
html.Span("Previous", className="sr-only")
]),
html.A(**{"data-slide":"next"}, className="carousel-control-next", href="#carouselExampleIndicators", role="button", children=[
html.Span(**{"aria-hidden":"true"}, className="carousel-control-next-icon"),
html.Span("Next", className="sr-only")
]),
])
logger.debug("return carousel")
return carousel
def _largest_companies(self, c):
largest_companies = {}
count = 0
limit_largest = 10
for k in self.size_order[::-1]:
top = [i for i in self.data if i["EmployerSize"] == k]
if not top:
continue
largest_companies[k] = top
count += len(largest_companies[k])
if count > limit_largest:
break
list_items = []
total_len = 0
for k, v in largest_companies.items():
original_len = len(v)
len_left = limit_largest - total_len
if len_left < 3:
continue
list_items.append(
html.H4(className='f5',
children='{} employees ({:,.0f})'.format(
k, original_len)))
if original_len > len_left:
v = random.sample(v, len_left)
v = sorted(v, key=lambda x: x["EmployerName"])
list_items.append(
html.P('* showing a random sample of {} companies'.format(
len_left)))
list_items.append(
html.Ul(className='list pl0',
children=[
html.Li(className='f6 mv1 lh-copy',
children=[
correct_titlecase(i["EmployerName"])
]) for i in v
]))
total_len += original_len
return self.show_figure(html.Div(list_items), "Largest Companies")
def update_map(data):
"""
Callback mettant à jour la map après un click sur un département ou une ville
"""
global selected_dept, selected_city
links = [
html.Li("Carte de France", className="selected", id="cdf-button"),
]
city_locations = []
if data is not None and len(data["points"][0]["customdata"][0]) == 2:
selected_dept = data["points"][0]["customdata"][0]
# On update les graphs
vote_histogram_dept.update(vote_dataset_dept,
current_dept=selected_dept)
vote_pie_dept.update(vote_dataset_dept, current_dept=selected_dept)
# On Update la map
locations = base_locations.copy()
city_locations = load_dept(selected_dept)
locations["features"] = list(
filter(lambda x: not x["properties"]["code"] == selected_dept,
locations["features"]))
chloropeth_map.update(vote_dataset_dept, vote_dataset_city, locations,
city_locations)
chloropeth_map.generate_map()
elif data is not None:
selected_city = data["points"][0]["customdata"][0]
# On update l'histogramme
vote_histogram_city.update(vote_dataset_city,
current_city=selected_city)
vote_pie_city.update(vote_dataset_city, current_city=selected_city)
# On met à jour les liens
if selected_dept != "-1":
links.append(html.Li("Info du département", id="idd-button"))
else:
links.append(
html.Li("Info du département", id="idd-button", className="hide"))
if selected_city != "-1":
links.append(html.Li("Info de la ville", id="idv-button"))
else:
links.append(
html.Li("Info de la ville", id="idv-button", className="hide"))
links.append(html.Li("Synthèse de l'analyse", id="synth-button"))
return (chloropeth_map.map_panel, links)
def build_loc_mode_hover_children(loc_mode):
if loc_mode is None:
return None
loc_mode_cfg = LOC_MODE_INFO[loc_mode]
return [
html.I(className='ico-help-outline', style=dict(color='white')),
html.Div(
[
html.Div([html.Span('View', className='mr-3'), loc_mode_cfg['url']]),
html.Ul(
[html.Li(e, style={'listStyleType': 'disc'}, className='mb-3') for e in loc_mode_cfg['examples']],
className='pt-3 mb-0'
)
],
className='hoverable__content build-code',
style=dict(width='auto', whiteSpace='nowrap', left='-2em', top='auto')
)
]
def get_color_legend():
"""
color legend beneath the table to identify meaning of highlights
:return: unordered list with color information
"""
return html.Ul(children=[
html.Li("No data sent for 2 days", className='red'),
html.Li("Sensor was not chosen", className='not-clean'),
html.Li("Left study too early", className='blue'),
html.Li("Study duration reached, not left", className='light-green'),
html.Li("Study duration reached, left", className='dark-green'),
html.Li("Multiple QR Codes of one user active", className='orange')
])
def get_breadcrumb(parts):
if not parts:
return html.Div()
breadcrumbs = html.Nav(
html.Ul(
[
html.Li(
dcc.Link(name, href=link),
className=(None if idx != len(parts) - 1 else "is-active"),
)
for idx, (name, link) in enumerate(parts.items())
]
),
className="breadcrumb",
)
return breadcrumbs
def createCard(
name="Placeholder",
imageLink="https://via.placeholder.com/69",
contList=["Placeholder", "Placeholder", "Placeholder"],
):
contListHTML = []
for i in contList:
contListHTML.append(html.Li(i))
card = dbc.Card(children=[
dbc.CardHeader(html.H4(name)),
dbc.CardImg(src=imageLink),
dbc.CardBody(children=[
html.H5("Contribution:"),
html.Ul(children=contListHTML, className="card-text")
])
],
style={"width": "15rem"})
return card
def gen_navbar(brand,
items,
barClass='navbar-dark bg-dark p-1',
brandClass='col-sm-3 col-md-2 mr-0',
listClass='px-3',
itemLiClass='text-nowrap',
itemAClass=''):
item_list = []
for key in items:
item_list.append(
html.Li(html.A(key,
href=items[key],
className=f"nav-link {itemAClass}"),
className=f"nav-item {itemLiClass}"))
return html.Nav([
html.A(brand, className=f"navbar-brand {brandClass}"),
html.Ul(item_list, className=f"navbar-nav {listClass}")
],
className=f"navbar {barClass}")
def update_output(n_clicks, value):
indexer = Indexer()
results = indexer.search(value)
li_children = []
for no, result in enumerate(results, 1):
url, title, snippet = result
if title:
li = html.Li(children=[
html.A(title, href=url),
dcc.Markdown(children=snippet),
])
li_children.append(li)
ol = html.Ol(children=li_children)
return ol
def set_features_list(oid, dr, min_mjd, max_mjd):
try:
features = light_curve_features(oid,
dr,
min_mjd=min_mjd,
max_mjd=max_mjd)
except NotFound:
return 'Not available'
items = [
f'**{k}**: {v:.4g}'
for k, v in sorted(features.items(), key=lambda item: item[0])
]
column_width = max(map(len, items)) - 2
div = html.Div(
html.Ul([html.Li(dcc.Markdown(text)) for text in items],
style={'list-style-type': 'none'}),
style={'columns': f'{column_width}ch'},
)
return div
def get_wordcloud(hoverData):
pers = hoverData["points"][0]["theta"]
msg = df[df.Author == pers].reset_index(drop=True)["Message"]
photo = df[df.Author == pers].reset_index(drop=True)["Photo"][0]
X = vectorizer.fit_transform(msg)
words = vectorizer.get_feature_names()
#plt.figure(figsize=[7,7])
#wordcloud_ke = WordCloud( background_color="white", mode="RGBA", max_words=30, mask=mask).generate(" ".join(list(msg)))
#fig=plt.imshow(wordcloud_ke .recolor(color_func=image_colors), interpolation="bilinear")
#fig = mpl_to_plotly(fig)
child = html.Div([
html.H3(children=pers),
html.Img(src=photo, style={
'height': '20%',
'width': '20%'
}),
html.Ul([html.Li(x) for x in words])
])
return child
def _candidates_list(self):
return self.show_figure(
html.Ul(
className='list pl0',
children=[
html.Li(className=
'f6 mv1 lh-copy cf pa2 bg-light-gray near-black',
children=[
html.Img(className='w3 fr person-photo',
src=c["image_url"])
if c["image_url"] else None,
html.Span(className='f5 b',
children=c["name"]),
html.Br(),
html.Span(className='f6',
children=c["party_name"]),
]) for c in self.data.get("candidates", [])
]), 'Candidates for 2019 Election')
def burn_into_video_button(n_clicks, store_s, selection, video_file_name):
if store_s is None or n_clicks == 0:
raise PreventUpdate
video_file = Path(f"{APP_DATA_DIR}/{video_file_name}")
video_subs_file_name = (
f"{Path(video_file_name).stem}_{'_'.join(selection)}_subs.mp4")
def select(sb: SubtitleBlock, selection):
sb.name_texts = [(n, t) for n, t in sb.name_texts if n in selection]
return sb
subtitle_blocks = [
select(SubtitleBlock(**d), selection) for d in json.loads(store_s)
]
with NamedTemporaryFile(suffix=".ass") as f:
create_ass_file(
subtitle_blocks,
f.name,
styles={name: StyleConfig(fontsize=10.0)
for name in selection},
)
subprocess.check_output(
f"/usr/bin/ffmpeg -y -i '{video_file}' -vf ass={f.name} '{APP_DATA_DIR}/{video_subs_file_name}'",
shell=True,
)
return [
html.H5(f"{video_subs_file_name}"),
html.Video(
controls=True,
id="movie_player",
src=f"/files/{video_subs_file_name}",
autoPlay=False,
style={"width": "100%"},
),
html.Li(
html.A(
"download video-file",
href=f"/download/{urlquote(video_subs_file_name)}",
)),
]
def get_layout(nav_items=[]):
# create navigation layout
return html.Nav(children=[
html.Button('×',
className='close-nav bg-transparent border-0 col-white'),
html.A(html.Img(
src='/assets/images/logo_1.png',
height=50,
),
href='/',
className='d-block text-center my-2'),
html.Ul(children=[
html.Li(html.A(children=nav_item['label'],
href=nav_item['target'])) for nav_item in nav_items
]),
html.Form(
children=[
html.Button(
children=[
dbc.Row(children=[
dbc.Col(children=[
html.B(current_user.get_username()),
html.Span('Logout')
],
className='d-flex flex-column p-0'),
dbc.Col(children=[
html.Span(html.I(className='fa fa-user-circle',
**{'aria-hidden': True}),
className='m-auto')
],
className='d-flex flex-column pr-0')
],
className='m-auto')
],
type='submit',
className='bg-black col-white border-0 logout-button px-0')
],
action='/logout',
method='post',
)
],
id='sidebar')
def most_sales_prod():
most_sales = df.groupby(['product',
'year'])['quantity'].sum().reset_index()
most_sales_top = most_sales.sort_values(by=['quantity'],
ascending=False).iloc[0:10]
return html.Div([
html.H4('Most Selling Products',
style={
'text-align': 'center',
'color': 'white'
}),
html.Ul(children=[html.Li(i) for i in most_sales_top['product']],
style={
'textAlign': 'left',
'color': '#839496',
'fontSize': 18,
'height': '333px',
'padding-top': '15px'
})
])
def change_card_content(value):
html_key = df_work.iloc[value - 1, :]["location_key"]
src = './assets/{}.html'.format(html_key)
return [
dbc.CardHeader(df_work.iloc[value - 1, :]["time"]),
dbc.CardBody([
html.H4(df_work.iloc[value - 1, :]["company"],
className="card-title"),
html.P(df_work.iloc[value - 1, :]["Role"],
className="card-title",
style={"fontSize": "1.171875rem"}),
html.P(
df_work.iloc[value - 1, :]["location"],
className="card-text",
),
]),
], [
html.Li([string], className="ul")
for string in df_work.iloc[value - 1, :]["Experience"].split("\n")
], src
def render_article_links(pathname):
response = requests.get(
'https://www.cnblogs.com/feffery/tag/Dash/',
headers={
'User-Agent':
'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.114 Safari/537.36'
})
tree = etree.HTML(response.text)
posts = [(href, title.strip()) for href, title in zip(
tree.xpath("//div[@class='postTitl2']/a/@href"),
tree.xpath("//div[@class='postTitl2']/a/span/text()"))]
return [
html.Li(
dcc.Link(title,
href=f'/article-{href.split("/")[-1]}',
target='_blank')) for href, title in posts
]
def getFooter(app):
return dbc.Row(
[
dbc.Col(
[
html.B('Business Problem:'),
html.P('Nowadays industry and government have a need of selecting and' + \
' knowing the skills and potential of their future collaborators.'),
html.B('Data:'),
html.P('Pruebas Saber Pro from the Colombian Institute for Tertiary Education' + \
' Fomentation (ICFES).'
),
html.H5('DS4A advisors:'),
html.P('German Prieto - [email protected], Jimmy Jing ' + \
' - [email protected] ')
],
md=6
), # fin de dbc.Col
dbc.Col(
[
html.B('Participants'),
html.Ul(
[
html.Li('Alfonso Cervantes Barragán ([email protected])'),
html.Li('Rafael García ([email protected])'),
html.Li('Luis Guzmán ([email protected])'),
html.Li('Julián Rincón ([email protected])'),
html.Li('Jorge Vélez ([email protected])'),
html.Li('Ricardo Villanueva ([email protected])'),
html.Li('Eduardo Zurek ([email protected])')
]
) ## fin de html.UL
],
md=6
) # fin de dbc.Col
],
style={'padding': '10px', 'color': 'white', 'background-color': 'black'}
) # fin de dbc.Row
