def test_click_simple(dash_duo):
call_count = Value("i", 0)
app = Dash(__name__)
app.layout = html.Div(
[
html.Div(id="container"),
html.Button("Click", id="button", n_clicks=0),
html.Iframe(id="video", allow="fullscreen", referrerPolicy="origin"),
]
)
@app.callback(Output("container", "children"), Input("button", "n_clicks"))
def update_output(n_clicks):
call_count.value += 1
return "clicked {} times".format(n_clicks)
dash_duo.start_server(app)
dash_duo.find_element("#container")
dash_duo.wait_for_text_to_equal("#container", "clicked 0 times")
assert call_count.value == 1
dash_duo.percy_snapshot("html button initialization")
dash_duo.find_element("#button").click()
dash_duo.wait_for_text_to_equal("#container", "clicked 1 times")
assert call_count.value == 2
dash_duo.percy_snapshot("html button click")
assert not dash_duo.get_logs()
assert dash_duo.find_element("#video").get_attribute("allow") == "fullscreen"
assert dash_duo.find_element("#video").get_attribute("referrerpolicy") == "origin"
def show_document(match: dict):
url = f"/pdf/{match['pdf']}"
iframe = dbc.Row(
dbc.Col(html.Iframe(src=url, style={
"width": "100%",
"height": "100%"
})),
style={
"resize": "vertical",
"overflow-y": "hidden",
"height": "1000px",
"min-height": "100px",
},
)
title = match["title"].replace("_", " ")
title = " ".join([w.capitalize() for w in title.split()])
title = dbc.Row(dbc.Col(html.H3(title)))
date = html.A(
match["date"],
id={
"type": "link_date",
"date": match["date"]
},
href="#",
n_clicks=0,
style={
"text-decoration": "none",
"color": "inherit"
},
)
tags = html.P([
dbc.Badge(
tag,
id={
"type": "link_tag",
"tag": tag
},
href="#",
n_clicks=0,
color="primary",
className="mr-1",
) for tag in match["tags"]
])
data = dbc.Table(
[
html.Tbody([
html.Tr([html.Td("Date"), html.Td(date)]),
html.Tr([html.Td("Tags"), html.Td(tags)]),
])
],
striped=True,
)
return dbc.Row([dbc.Col([title, data], width=4), dbc.Col(iframe)])
def test_click_simple(dash_duo):
call_count = Value("i", 0)
app = Dash(__name__)
app.layout = html.Div([
html.Div(id="container"),
html.Button("Click", id="button", n_clicks=0),
html.Iframe(id="video", allow="fullscreen", referrerPolicy="origin"),
])
@app.callback(
Output("container", "children"),
Input("button", "n_clicks"),
# The new percy runner loads the page, so to get consistent behavior for
# call_count we need to skip the initial call
prevent_initial_call=True,
)
def update_output(n_clicks):
call_count.value += 1
return "clicked {} times".format(n_clicks)
dash_duo.start_server(app)
dash_duo.wait_for_text_to_equal("#container", "")
assert call_count.value == 0
dash_duo.find_element("#button").click()
dash_duo.wait_for_text_to_equal("#container", "clicked 1 times")
assert call_count.value == 1
dash_duo.percy_snapshot("html button click")
assert not dash_duo.get_logs()
assert dash_duo.find_element("#video").get_attribute(
"allow") == "fullscreen"
assert dash_duo.find_element("#video").get_attribute(
"referrerpolicy") == "origin"
if metrics_available:
samples_layout += [
dbc.Row([
dbc.Col(
html.Div(children='text diff'),
width=2,
class_name=
'mt-1 bg-light font-monospace text-break small rounded border',
),
dbc.Col(
html.Iframe(
id='_diff',
sandbox='',
srcDoc='',
style={
'border': 'none',
'width': '100%',
'height': '100%'
},
className='bg-light font-monospace text-break small',
),
class_name=
'mt-1 bg-light font-monospace text-break small rounded border',
),
])
]
samples_layout += [
dbc.Row(dbc.Col(html.Audio(id='player', controls=True), ),
class_name='mt-3 '),
dbc.Row(dbc.Col(dcc.Graph(id='signal-graph')), class_name='mt-3'),
]
def get_map_map(tab, dataset_selection, traveler, centrality_index, label_size,
node_size):
map_graph = diogenetGraph("map", dataset_selection, dataset_selection,
'locations_data.csv', 'travels_blacklist.csv')
if tab == "map_maps":
data = None
mapa = None
map_graph.current_centrality_index = centrality_index
if traveler == "All" or traveler == []:
map_graph.edges_filter = []
else:
for m_filter in traveler:
map_graph.set_edges_filter(m_filter)
map_graph.create_subgraph()
data = map_graph.get_map_data(min_weight=node_size[0],
max_weight=node_size[1])
df = pd.DataFrame(data)
#Folium base map configurations
url = 'https://basemap.nationalmap.gov/arcgis/rest/services/USGSImageryOnly/MapServer/tile/{z}/{y}/{x}'
attribution = '© <a href="https://developers.arcgis.com/">ArcGIS</a> '
base_map = folium.Map(location=[35, 30],
min_zoom=4,
max_zoom=7,
zoom_start=6,
tiles=None,
attr=attribution)
folium.TileLayer(
tiles=url,
show=True,
attr=attribution,
min_zoom=3,
max_zoom=8,
name="USGS - The National Map",
).add_to(base_map)
markers_source = folium.FeatureGroup(name='Source').add_to(base_map)
markers_target = folium.FeatureGroup(name='Target').add_to(base_map)
for i in range(len(df['Source'])):
#source marker
popup_source = folium.Popup(str(
"{} \n (lat = {:.1f}, \n lon={:.1f})".format(
df['Source'][i], df["SourceLatitude"][i],
df["SourceLongitude"][i])),
parse_html=True,
max_width=450)
tooltip_source = "{} (lat = {:.1f}, lon={:.1f})".format(
df['Source'][i], df["SourceLatitude"][i],
df["SourceLongitude"][i])
markers_source.add_child(
folium.CircleMarker(location=(float(df["SourceLatitude"][i]),
float(df["SourceLongitude"][i])),
popup=popup_source,
tooltip=tooltip_source,
fill=True,
color=df["SourceColor"][i],
fill_color=df["SourceColor"][i],
radius=int(df["SourceSize"][i] * 1.3)))
#target marker
popup_target = folium.Popup(str(
"{} \n (lat = {:.1f}, \n lon={:.1f})".format(
df['Destination'][i], df["DestLatitude"][i],
df["DestLongitude"][i])),
parse_html=True,
max_width=450)
tooltip_target = "{} (lat = {:.1f}, lon={:.1f})".format(
df['Destination'][i], df["DestLatitude"][i],
df["DestLongitude"][i])
markers_target.add_child(
folium.CircleMarker(location=(float(df["DestLatitude"][i]),
float(df["DestLongitude"][i])),
popup=popup_target,
tooltip=tooltip_target,
fill=True,
color=df["DestinationColor"][i],
fill_color=df["DestinationColor"][i],
radius=int(df["DestinationSize"][i] *
1.3)))
# travel info line
folium.PolyLine(
[[df["SourceLatitude"][i], df["SourceLongitude"][i]],
[df["DestLatitude"][i], df["DestLongitude"][i]]],
popup=folium.Popup(str("{} travel from {} to {}".format(
df['Philosopher'][i], df["Source"][i],
df["Destination"][i])),
parse_html=True,
max_width=450),
tooltip="{} travel from {} to {}".format(
df['Philosopher'][i], df["Source"][i],
df["Destination"][i]),
color='#ced4da',
weight=1.5,
).add_to(base_map)
suffix = ".html"
temp_file_name = next(tempfile._get_candidate_names()) + suffix
full_filename = os.path.abspath(
os.path.join(os.path.dirname(__file__), '.', 'assets',
temp_file_name))
#saving folium .html file
folium.LayerControl().add_to(base_map)
base_map.save(full_filename)
return [
html.Iframe(src=app.get_asset_url(f'{temp_file_name}'),
style={
"height": "100%",
"width": "100%"
})
]
if tab == "map_metrics":
if traveler == "All":
all_travelers = sorted(list(set(map_graph.get_edges_names())))
map_graph.edges_filter = []
for m_filter in all_travelers:
map_graph.set_edges_filter(m_filter)
map_graph.create_subgraph()
elif traveler == []:
all_travelers = sorted(list(set(map_graph.get_edges_names())))
map_graph.edges_filter = []
for m_filter in all_travelers:
map_graph.set_edges_filter(m_filter)
map_graph.create_subgraph()
else:
map_graph.edges_filter = []
for m_filter in traveler:
map_graph.set_edges_filter(m_filter)
map_graph.create_subgraph()
def round_list_values(list_in):
return [round(value, 4) for value in list_in]
calculated_network_betweenness = list(
pd.DataFrame.from_dict(
nx.betweenness_centrality(
map_graph.networkx_subgraph).items())[1])
calculated_network_degree = list(
pd.DataFrame.from_dict(
nx.degree_centrality(map_graph.networkx_subgraph).items())[1])
calculated_network_closeness = list(
pd.DataFrame.from_dict(
nx.closeness_centrality(
map_graph.networkx_subgraph).items())[1])
calculated_network_eigenvector = list(
pd.DataFrame.from_dict(
nx.eigenvector_centrality(
map_graph.networkx_subgraph).items())[1])
calculated_degree = [
round(value) for value in map_graph.calculate_degree()
]
calculated_betweenness = round_list_values(
map_graph.calculate_betweenness())
calculated_closeness = round_list_values(
map_graph.calculate_closeness())
calculated_eigenvector = round_list_values(
map_graph.calculate_eigenvector())
dict_map_data_tables = {
"City": map_graph.get_vertex_names(),
"Degree": round_list_values(calculated_network_degree),
"Betweeness": round_list_values(calculated_network_eigenvector),
"Closeness": round_list_values(calculated_network_closeness),
"Eigenvector": round_list_values(calculated_network_eigenvector),
}
df_map_data_tables = pd.DataFrame(dict_map_data_tables)
dt_map = dash_table.DataTable(id='table-map',
columns=[{
"name": i,
"id": i,
'deletable': True
} for i in df_map_data_tables.columns],
style_data_conditional=[{
'if': {
'row_index': 'odd'
},
'backgroundColor':
'rgb(220, 220, 220)',
}],
style_cell={'textAlign': 'center'},
style_header={'textAlign': 'center'},
page_current=0,
page_size=20,
page_action='custom',
sort_mode='single',
sort_by=[{
'column_id': 'Degree',
'direction': 'asc'
}])
foot_note = html.Div(children=[
html.Span('Metrics obtained using the algorithms of '),
html.A('Networkx',
href='https://networkx.org/documentation/stable/',
target='_blank')
])
return [
html.H6('Centrality Scores', className="mt-1 mb-2"),
html.Hr(className='py-0'), dt_map, foot_note
]
if tab == "map_graphs":
map_graph.current_centrality_index = centrality_index
graph_layout = "fr"
pvis_graph = None
if traveler == "All" or traveler == []:
#map_graph.edges_filter = []
pvis_graph = map_graph.get_pyvis(
min_weight=node_size[0],
max_weight=node_size[1],
min_label_size=label_size[0],
max_label_size=label_size[1],
layout=graph_layout,
)
else:
for m_filter in traveler:
map_graph.set_edges_filter(m_filter)
map_graph.create_subgraph()
pvis_graph = map_graph.get_pyvis()
if pvis_graph:
suffix = ".html"
temp_file_name = next(tempfile._get_candidate_names()) + suffix
full_filename = os.path.abspath(
os.path.join(os.path.dirname(__file__), '.', 'assets',
temp_file_name))
pvis_graph.write_html(full_filename)
return [
html.Iframe(src=app.get_asset_url(f'{temp_file_name}'),
style={
"height": "100%",
"width": "100%"
})
]
figure={
'data':
generate_flow_history_chart(),
'layout':
go.Layout(height=772, title='Nutrition Funding history')
})
],
className='twelve columns'),
html.Div([
dcc.Graph(
id='funding-chart-wfp-sankey',
figure={
'data': [generate_sankey_chart()],
'layout':
go.Layout(
height=772,
title='WFP Funding source and destination (15 largest)')
})
],
className='twelve columns'),
html.Div([
html.H4('WFP Market Prices Explorer'),
html.Iframe(
width=900,
height=500,
src=
'//data.humdata.org/widget/WFP?type=WFP&datastore_id=bd88a565-bf6f-4827-b07b-fb3a65bbb01a&data_link_url=https%3A%2F%2Fdata.humdata.org%2Fdataset%2Fwfp-food-prices&embedded=true&title=Food+Market+Prices'
)
])
])
def get_visuals(self):
"""Returns a diciontary with both dash and notebook ready visualization.
:return: Dash and notebook visuals
:rtype: dict
"""
D = self.D
visuals = {"notebook":{},"dash":{}}
r = self.r
visuals["dash"]["D[r,r]"] = pyrplib.style.get_standard_data_table(self.D.loc[r.index,:].loc[:,r.index].reset_index(),"D_r_r")
visuals["notebook"]["D[r,r]"] = self.D.loc[r.index,:].loc[:,r.index]
Xstar_r_r = self.xstar_r_r
visuals["dash"]["X*[r,r]"] = pyrplib.style.get_standard_data_table(Xstar_r_r.reset_index(),"X_r_r")
visuals["notebook"]["X*[r,r]"] = Xstar_r_r
# 'Red/Green plot':
xstar_width_height = len(Xstar_r_r) * 10
xstar_g=pyrankability.plot.show_single_xstar(Xstar_r_r)#centroid_x)
xstar_g = xstar_g.properties(
width=xstar_width_height,
height=xstar_width_height
)
visuals["notebook"]["X* (red/green)"] = xstar_g
plot_html = io.StringIO()
xstar_g.save(plot_html, 'html')
visuals["dash"]["X* (red/green)"] = html.Iframe(
id='xstar_plot',
height=str(xstar_width_height + 150),
width=str(xstar_width_height + 150),
sandbox='allow-scripts',
srcDoc=plot_html.getvalue(),
style={'border-width': '0px'}
)
# 'X*':
xstar_width_height = len(Xstar_r_r) * 10
xstar_g=pyrankability.plot.show_single_xstar(Xstar_r_r,red_green=False)
xstar_g = xstar_g.properties(
width=xstar_width_height,
height=xstar_width_height
)
visuals["notebook"]["X* (greyscale)"] = xstar_g
plot_html = io.StringIO()
xstar_g.save(plot_html, 'html')
visuals["dash"]["X* (greyscale)"] = html.Iframe(
id='xstar2_plot',
height=str(xstar_width_height + 150),
width=str(xstar_width_height + 150),
sandbox='allow-scripts',
srcDoc=plot_html.getvalue(),
style={'border-width': '0px'}
)
if len(self.solutions) > 1:
# nearest and farthest
outlier_solution = pd.Series(self.outlier_solution,
index=D.index[np.array(self.outlier_solution)].astype(str),
name="Farthest from Centroid")
centroid_solution = pd.Series(self.centroid_solution,
index=D.index[np.array(self.centroid_solution)].astype(str),
name="Closest to Centroid")
spider_g = pyrankability.plot.spider(outlier_solution,centroid_solution)
spider_width = 700
spider_height = 30 * len(outlier_solution)
spider_g = spider_g.properties(
width = spider_width,
height = spider_height
).interactive()
visuals["notebook"]["Nearest and Farthest"] = spider_g
tmpfile = StringIO()
spider_g.save(tmpfile, 'html')
visuals["dash"]["Nearest and Farthest"] = html.Iframe(
id='nearest_farthest',
height=str(spider_height + 100),
width=str(spider_width + 400),
sandbox='allow-scripts',
# Once this function returns, tmpfile is garbage collected and may be
# the reason for 'view source' not working.
# TODO: Look into the return of getvalue() and implications that has on 'srcDoc'
srcDoc=tmpfile.getvalue(),
style={'border-width': '0px'}
)
# Farthest pair
#farthest_pair
first,second = self.farthest_pair
first_solution = pd.Series(first,
index=D.index[np.array(first)].astype(str),
name="Solution 1")
second_solution = pd.Series(second,
index=D.index[np.array(second)].astype(str),
name="Solution 2")
spider_g = pyrankability.plot.spider(first_solution,second_solution)
spider_width = 500
spider_height = 30 * len(second)
spider_g = spider_g.properties(
width = spider_width,
height = spider_height
).interactive()
visuals["notebook"]["Farthest Pair"] = spider_g
tmpfile = StringIO()
spider_g.save(tmpfile, 'html')
visuals["dash"]["Farthest Pair"] = html.Iframe(
id='farthest_pair',
height=str(spider_height + 100),
width=str(spider_width + 600),
sandbox='allow-scripts',
# Once this function returns, tmpfile is garbage collected and may be
# the reason for 'view source' not working.
# TODO: Look into the return of getvalue() and implications that has on 'srcDoc'
srcDoc=tmpfile.getvalue(),
style={'border-width': '0px'}
)
visuals["notebook"]["OBJECTIVE"] = self.obj
visuals["dash"]["OBJECTIVE"] = self.obj
visuals["notebook"]["BETA"] = self.beta
visuals["dash"]["BETA"] = self.beta
if len(self.solutions) > 1:
visuals["notebook"]["TAU Farthest Pair"] = self.tau_farthest_pair
visuals["notebook"]["TAU Closest Pair"] = self.tau_closest_pair
visuals["dash"]["TAU Farthest Pair"] = self.tau_farthest_pair
visuals["dash"]["TAU Closest Pair"] = self.tau_closest_pair
visuals["notebook"]["Number of optimal solutions found"] = len(self.solutions)
visuals["dash"]["Number of optimal solutions found"] = len(self.solutions)
return visuals
value='Mitte',
clearable=False,
options=[{
'label': x,
'value': x
} for x in sorted(df.District.unique())])
],
width=6),
]),
dbc.Row([
dbc.Col(
[
html.Iframe(
id='scatter-plot',
srcDoc=None, # here is where we will put the graph we make
style={
'border-width': '5',
'width': '100%',
'height': '500px'
}),
],
width=6),
dbc.Col(
[
html.Iframe(
id='bar-plot',
srcDoc=None, # here is where we will put the graph we make
style={
'border-width': '5',
'width': '100%',
'height': '500px'
}),
html.Div(
[
html.Div([
dcc.Graph(id='bar_chart',
style={'height': '650px'},
figure=bargraph)
]), # , className = "fourteen columns"
],
className="row"),
html.Div(
[
html.Div([dcc.Graph(id='pie_chart', figure=piechart)
]), # , className = "eleven columns"
],
className="row"),
html.Div([
html.Iframe(height='800px', width='100%', srcDoc=df_to_html(df)),
]),
],
style={'backgroundColor': '#0091C7'}) # #70E3A0
# end = time.time()
# t_time = end - start
# print(t_time)
if __name__ == '__main__':
app.run_server(debug=False)
# from waitress import serve
# serve(app, host="0.0.0.0", port=8080)
className='mr-4',
style={'width': '15rem'})
], ),
dbc.Row([
dbc.Col(rows, width=12, lg=4, style={'margin-top': '2rem'}),
dbc.Col(id='result-col', width=12, lg=8),
],
className='mt-4'),
],
id='simulation-container'),
dbc.Container(
[
html.Iframe(
src='/documentation/index.html',
style={
'width': '100%',
'height': '100%'
},
)
],
id='documentation-container',
className='p-0',
),
html.Footer([
html.A("FMPy %s" % fmpy.__version__,
href='https://github.com/CATIA-Systems/FMPy',
className='d-block text-muted small'),
],
className='my-4 pt-3 border-top')
])
import pandas as pd
from dash import html, Dash
from folium import Map, Marker
from folium.plugins import MarkerCluster
from dash.exceptions import PreventUpdate
from dash.dependencies import Input, Output
from dashboard.components.box import box
layout = html.Div([
html.Div(id="qtd_sem_latlon"),
html.Iframe(
id="map",
srcDoc=Map(height="89%")._repr_html_(),
width="100%",
height="800px",
),
])
def init_app(app: Dash) -> Dash:
@app.callback(
Output(component_id="qtd_sem_latlon", component_property="children"),
Output("map", "srcDoc"),
Input("filtered_data", "data"),
)
def create_map(data):
if not data:
raise PreventUpdate
df = pd.DataFrame(data)
def serve_layout():
global cached_layout
if cached_layout is None:
logger.debug("Create new layout")
fig_filter = FigureFilter()
try:
range_slider = dcc.RangeSlider(
id='date-slider',
min=min_millis,
max=max_millis,
step=step,
marks=marks,
value=[min_millis, max_millis],
)
summary_tab = [
dbc.Container(dbc.Row(id="summary-cards",
children=create_card(
figures.SUMMARY_CARDS)),
fluid=True),
fig_filter.add_graph(dcc.Graph(id="consumption_fig"),
"start_at", ["consumption_km"],
figures.consumption_fig),
fig_filter.add_graph(dcc.Graph(id="consumption_fig_by_speed"),
"speed_average", ["consumption_km"] * 2,
figures.consumption_fig_by_speed),
fig_filter.add_graph(dcc.Graph(id="consumption_graph_by_temp"),
"consumption_by_temp",
["consumption_km"] * 2,
figures.consumption_fig_by_temp)
]
maps = fig_filter.add_map(
dcc.Graph(id="trips_map", style={"height": '90vh'}), "lat",
["long", "start_at"], figures.trips_map)
fig_filter.add_table("trips", figures.table_fig)
fig_filter.add_table("chargings", figures.battery_table)
fig_filter.src = {
"trips": trips.get_trips_as_dict(),
"chargings": chargings
}
fig_filter.set_clientside_callback(dash_app)
create_callback()
except (IndexError, TypeError, NameError, AssertionError, NameError,
AttributeError):
summary_tab = figures.ERROR_DIV
maps = figures.ERROR_DIV
logger.warning(
"Failed to generate figure, there is probably not enough data yet",
exc_info_debug=True)
range_slider = html.Div()
figures.battery_table = figures.ERROR_DIV
data_div = html.Div([
*fig_filter.get_store(),
html.Div([
range_slider,
dbc.Tabs([
dbc.Tab(label="Summary",
tab_id="summary",
children=summary_tab),
dbc.Tab(
label="Trips",
tab_id="trips",
id="tab_trips",
children=[
html.Div(id="tab_trips_fig",
children=figures.table_fig),
dbc.Modal(
[
dbc.ModalHeader("Altitude"),
dbc.ModalBody(
html.Div(id="tab_trips_popup_graph")),
dbc.ModalFooter(
dbc.Button("Close",
id="tab_trips_popup-close",
className="ml-auto")),
],
id="tab_trips_popup",
size="xl",
)
]),
dbc.Tab(label="Charge",
tab_id="charge",
id="tab_charge",
children=[
figures.battery_table,
dbc.Modal(
[
dbc.ModalHeader("Charging speed"),
dbc.ModalBody(
html.Div(
id="tab_battery_popup_graph")),
dbc.ModalFooter(
dbc.Button(
"Close",
id="tab_battery_popup-close",
className="ml-auto")),
],
id="tab_battery_popup",
size="xl",
)
]),
dbc.Tab(label="Map", tab_id="map", children=[maps]),
dbc.Tab(label="Control",
tab_id="control",
children=html.Iframe(
src=request.url_root + "control?header=false",
style={
"position": "absolute",
"height": "100%",
"width": "100%",
"border": "none"
}))
],
id="tabs",
active_tab="summary",
persistence=True),
html.Div(id=EMPTY_DIV)
])
])
cached_layout = data_div
return cached_layout
