def generate_solution(n_clicks, city, coords, df_time, cache):
if n_clicks and city and coords and df_time and n_clicks > 0:
tic = time.time()
df_time = parse_contents(df_time)
solution, cities, edges = make_plot_data(
cities=parse_contents(city),
paths=parse_contents(coords),
time=df_time)
solving_time = time.time() - tic
# Save solution
fh.save_solution(solution, df_time.time.values[0])
# Generate html elements
output = [html.H3(children='The magic TSP graph'), comp.vbar()]
output += comp.stats(solving_time, solution, cities)
# Cache data
cache = {'cities': prepare_data(cities), 'edges': list(edges)}
return output, cache
if n_clicks is not None and n_clicks > 0:
return [html.P('no data')], dict()
return None, dict()
def upload_paths(content, cities, name):
if content:
if '.csv' not in name:
return html.Div(comp.error('Only .csv files ar supported!')),
df = parse_contents(content)
cities = parse_contents(cities)
result = fh.validate_paths(df, cities)
if not result.status:
return comp.error(result.msg)
return comp.upload_table(name, df)
return [None]
def show_graph(n_clicks, city, coords, info):
if n_clicks is not None \
and city is not None \
and coords is not None \
and info is not None \
and n_clicks > 0:
# to check loading
time.sleep(2)
graph_data = tsp(cities=parse_contents(city),
coords=parse_contents(coords),
info=parse_contents(info))
return [
html.H3(children='The magic TSP graph'), Vbar.component,
MainGraph.component
]
def upload_coordinates(content, name):
if content is not None:
if '.csv' not in name:
return html.Div(['Only .csv files ar supported!']),
df = parse_contents(content)
result = fh.validate_paths(df)
if not result.status:
return html.P(result.msg),
return comp.upload_table(name, df),
return None,
def upload_info(content, name):
if content is not None:
if '.csv' not in name:
return [
html.Div(['Only .csv files ar supported!']), {
'visibility': 'hidden'
}
]
df = parse_contents(content)
result = fh.validate_time(df)
if not result.status:
return html.P(result.msg),
return comp.upload_table(name, df),
return None,
def upload_time_solution(old_solution, content, name):
if old_solution and content:
if '.txt' not in name:
return html.Div(comp.error('Only .txt files ar supported!')),
result = fh.validate_solution(content)
if not result.status:
return comp.error(result.msg)
return [html.Div([html.P(f'File {name} successfully uploaded!')])]
if content:
if '.csv' not in name:
return [html.Div(comp.error('Only .csv files ar supported!'))]
df = parse_contents(content)
result = fh.validate_time(df)
if not result.status:
return comp.error(result.msg)
return comp.upload_table(name, df)
return [None]
def generate_solution(old_solution, exact, n_clicks, city, paths, df_time, n_sim, time_limit, cache):
global CLICKS
if old_solution and n_clicks and n_clicks > CLICKS:
solution_content = df_time
if solution_content:
CLICKS += 1
solution = fh.solution_to_output(solution_content)
if city and paths:
paths = parse_contents(paths)
if paths.shape[0] > 0:
mean_time = np.mean(paths.travel_time.values)
else:
mean_time = 0.0
cities, edges = data_from_solution(cities=parse_contents(city),
paths=paths,
solution=solution)
else:
mean_time = 0.0
cities, edges = data_from_solution(cities=None,
paths=None,
solution=solution)
# Save solution
fh.save_solution(solution, solution.time_left, new=False)
# Generate html elements
output = [html.H3(children='Solution'), comp.vbar()]
output += comp.stats(0.0, solution, cities, new=False, mean_time=mean_time)
# Cache data
cache = {'cities': prepare_data(cities), 'edges': list(edges)}
return output, cache
# New solution
elif n_clicks and city and paths and df_time and n_clicks > CLICKS:
CLICKS += 1
tic = time.time()
df_time = parse_contents(df_time)
paths = parse_contents(paths)
if paths.shape[0] > 0:
mean_time = np.mean(paths.travel_time.values)
else:
mean_time = 0.0
solution, cities, edges = make_plot_data(cities=parse_contents(city),
paths=paths,
time=df_time,
simulations=n_sim,
time_limit=time_limit,
exact=exact)
solving_time = time.time() - tic
# Save solution
fh.save_solution(solution, df_time.time.values[0])
# Generate html elements
output = [html.H3(children='Solution'), comp.vbar()]
output += comp.stats(solving_time, solution, cities, input_time=df_time.time.values[0], mean_time=mean_time)
# Cache data
cache = {'cities': prepare_data(cities), 'edges': list(edges)}
return output, cache
return [None], None
