from ml.non_linear_classification import non_separable_train
layout = html.Div([
common.navbar("Classification - Linearly Non-Separable"),
html.Div([], style = {'padding': '30px'}),
html.Br(),
html.Div([
html.H2("Load and Select a file from all the cleaned files:"),
dbc.Button("Load Cleaned File", color="primary", id = 'nlcl-load-cleaned-files', className="mr-2", style={'display': 'inline-block'}),
dbc.Button("Clear", color="secondary", id = 'nlcl-clear-db', className="mr-2", style={'display': 'inline-block'})
],style = {'margin': '10px'}),
html.Div([
dcc.Dropdown(
id = 'nlcl-selected-cleaned-file',
options = common.get_options('clean'),
value = None,
multi = False
)],
style = {'margin': '10px', 'width': '50%'}),
html.Div([], id = "nlcl-clear-db-do-nothing"),
html.Div([],id = "nlcl-selected-div")
])
@app.callback(
Output("nlcl-selected-cleaned-file", "options"),
[Input('nlcl-load-cleaned-files', 'n_clicks')]
)
def selected_file(n_clicks):
return common.get_options('clean')
def selected_file(n_clicks):
return common.get_options('clean')
def upload_data(contents, filename):
"""Upload Files and Regenerate the file list."""
if contents:
for i in range(len(filename)):
FileUtils.upload(filename[i], contents[i])
return common.get_options('raw')