def setLayout(self, options): self.layout = html.Div([ html.Header([ html.A(html.Img(src='assets/hexa.png', id='logo')), html.H1('ANALYSIS'), dcc.Dropdown( id='dropdown-1', options=[{ 'label': i, 'value': i } for i in options], value='', ), html.Div(id='depDropdown'), html.Button('Actualiser les données', id='button-1'), ]), html.Div(id='output'), visdcc.Run_js(id='javascript-1'), html.Footer([ html.Nav([ html.Ul([ html.Li(html.Div(id='case-1')), html.Li(html.Div(id='case-2')), html.Li(html.Div(id='case-3')) ]) ]), html.Button(id='invisible_button', style={'display': 'none'}), visdcc.Run_js(id='javascript-2'), ], id='footer') ])
def rightPanel(hide_twinRow=False): return dbc.Col( id='rightPanel', style={ 'background-color': '#111', 'color': '#FFF' }, width=9, children=[ html.P(id='msgBox', children=''), html.H3('e-NABLE on G+, Wikifactory, and hub.e-NABLE.org...'), html.Br(), searchBox, dcc.Markdown(""" * **Mouse over** a data point to see author and date. * **Click** on a data point to view the Thread in the **Selected Thread** Panel""" ), dropDown, #html.P(), visdcc.Run_js(id='javascript'), twinRow(hide_twinRow), dcc.Graph(id='bothFig', figure=fullFigs['bothFig'], style={'background-color': '#111'}) ])
def Base(session_id): return html.Div([ dcc.Store(id='session-id', data=session_id, storage_type='session'), dcc.Location(id='url', refresh=False), html.Div(id='page-content'), visdcc.Run_js(id='javascript-exe'), html.Div(id='javascript-exe-modal-div') ])
def get_criptocoins_market(): return html.Div(children=[ html.Div([ html.Br(), html.Label('View BINANCE Market Graph: '), dcc.Input(id="txt_cryptocoin_market", type="text", placeholder="^binance", value="^binance") ]), html.Div(dcc.Graph(id="cryptocoin-market-graph")), visdcc.Run_js(id="javascript") ])
def interactive_menu(output_elem_id): """ Create the necessary elements for the sidemenus to become interactive. Args: output_elem_id (str): The id for the div with the contents \ of the sidemenu. Returns: list: Dash elements, the sidebar, its buttons, and the \ JS script to be run. """ return [ # The second sidebar with the tab-specific menu html.Div( id="sidenav2", className="sidenav2", children=[ # Close button for the sidebar html.A(html.I(className="fas fa-times"), className="closebtn2", id="closebtn2"), # Contents of the sidebar html.Div(id=output_elem_id), ]), # Open button for the sidebar html.Span(id="open_menu2", className="open_menu2", children=[ html.I(className="fas fa-angle-double-right"), ]), # Interactivity: opening/closing the sidebar resizes # the main div and hides/shows appropriate menu buttons visdcc.Run_js(id='close_sidebar', run=""" // show the button for opening the submenu var elem = document.getElementById("open_menu2"); elem.style.display = "inline-block"; // and bind the appropriate function to it elem.onclick = function(){openNav2()}; // do the same for the close button var elem2 = document.getElementById("closebtn2"); elem2.onclick = function(){closeNav2()}; """) ]
def generate_control_card_tab2(): """ Build a div that containing controls (button) for graphs. Currently contains: - dropdown menu to choose topic - dropdown menu to choose alert ID based on previously chosen topic. Returns --------- div: A Div containing controls for graphs in tab 2. """ return html.Div( id="control-card", children=[ html.P("Select Topic"), # Topic list dcc.Dropdown(id="topic-select", options=[{ "label": i, "value": i } for i in topic_list], value=topic_list[0], clearable=False, style={ 'width': '100%', 'display': 'inline-block' }), html.Br(), # Alert ID list html.P("Select Alert"), dcc.Dropdown(id="alerts-dropdown", placeholder="Select an alert ID", clearable=False, style={ 'width': '300px', 'display': 'inline-block' }), html.Br(), html.Div(id='container-button-timestamp'), html.Div([visdcc.Run_js(id='aladin-lite-div')], style={ 'width': '300px', 'height': '300px' }) ], )
def resume_tweets(df, type='share'): list_twt = [] for i in list(range(30)): user = df['id_user'].to_list()[i] tweet = int(df['tweet_id'].to_list()[i]) is_rt = df['is_RT'].to_list()[i] link = df['retweeted_url'].to_list()[i] if link == None: link = df['quote_url'].to_list()[i] else: pass if link == None: link = "https://twitter.com/{user}/status/{tweet}" else: pass if type == 'share': text = f"#{i+1} Most Shared - Total Shares: {df['count'].to_list()[i]} " else: text = f"#{i+1} Most Retweeted - Total Shares: {df['count'].to_list()[i]}" list_twt.append( html.Div([ html.Div(f"{text}", style={ 'textAlign': 'center', 'fontWeight': 'bold', "direction": "ltr", 'fontSize': '18px' }), html.Blockquote(html.A(href=link), className="twitter-tweet", style={'width': "498px"}) ], style={"margin": "48px 0"})) list_twt.append(visdcc.Run_js(id="javascript", run="twttr.widgets.load()")) return list_twt
def _build_component(self) -> html.Div: timer = dcc.Interval(id=self.timer_id, interval=self._update_interval_s * 1000, n_intervals=0) scroller = visdcc.Run_js(id=self.js_id, run='') self.console = dcc.Textarea(id=self.console_id, contentEditable='false', style={ 'height': '100%', 'width': '100%', 'borderWidth': '1px', 'borderRadius': '5px', 'borderStyle': 'dashed' }, persistence_type='session', persistence=True) return html.Div(id=self.id_, children=[timer, self.console, scroller], style={'height': '100%'})
def _build_component(self) -> html.Div: timer = dcc.Interval( id=self.timer_id, interval=self._update_interval_s * 1000, n_intervals=0 ) scroller = visdcc.Run_js(id=self.js_id, run="") self.console = dcc.Textarea( id=self.console_id, contentEditable="false", style={ "height": "100%", "width": "100%", "borderWidth": "1px", "borderRadius": "5px", "borderStyle": "dashed", }, persistence_type="session", persistence=True, ) return html.Div( id=self.id_, children=[timer, self.console, scroller], style={"height": "100%"}, )
def layout(name): # even if there is one object ID, this returns several alerts results = client.scan("", "key:key:{}".format(name[1:]), "*", 0, True, True) layout_ = html.Div( [ html.Br(), dbc.Row([ dbc.Col( [ title(name), html.Br(), html.Div([visdcc.Run_js(id='aladin-lite-div')], style={ 'width': '100%', 'height': '25pc' }), card_download(results) ], width={"size": 3}, ), dbc.Col(tabs(results), width=8) ], justify="around", no_gutters=True), html.Div(id='object-data', style={'display': 'none'}), html.Div(id='object-upper', style={'display': 'none'}) ], className='home', style={ 'background-image': 'linear-gradient(rgba(255,255,255,0.5), rgba(255,255,255,0.5)), url(/assets/background.png)', 'background-size': 'contain' }) return layout_
className='message-body', id='crawlShow', style={ 'overflow': 'scroll', 'height': '60vh' }) ], className='message is-link', style={'width': '100%'}) ], className='tile is-8 search_input'), ], id='showPanel', className='tile is-ancestor', style={'display': 'none'}), visdcc.Run_js(id='crawlScript'), visdcc.Run_js(id='crawlScript1'), dcc.ConfirmDialog(id='confirm', message='ć·ČçŹćèżèŻ„çšæ·ïŒæŻćŠéæ°çŹć?'), html.Div([ html.Div('', className='tile is-4'), html.Div([ html.Div( [ html.Header([ html.Div('æ„èŻąç»æ', id='crawled-title', className='card-header-title') ], className='card-header'), html.Div([ html.Div([
def f1(server): dash_app1 = dash.Dash(__name__, server=server, external_stylesheets=external_stylesheets) lowess = sm.nonparametric.lowess dash_app1.index_string = temp ##### Functions ============================= def make_lowess(series): series = pd.Series(series) endog = series.values exog = series.index.values smooth = lowess(endog, exog) index, data = np.transpose(smooth) return pd.Series(data, index=pd.to_datetime(index)) #### Data preparation ============================================== df_group = pd.read_pickle("./data.pkl") df_group = df_group.replace({'ć»șç©ćæ _': 'ć„æż(1æż1滳1èĄ)'}, {'ć»șç©ćæ _': 'ć„æż(1æż1滳1èĄ)'}, regex=False) df_group = df_group.replace({'ć»șç©ćæ _': 'äœćź 性æš(11ć±€ć«ä»„äžæé»æąŻ)'}, {'ć»șç©ćæ _': 'äœćź 性æš(11ć±€ć«ä»„äžæé»æąŻ)'}, regex=False) df_group = df_group.replace({'ć»șç©ćæ _': 'ć ŹćŻ(5æšć«ä»„äžçĄé»æąŻ)'}, {'ć»șç©ćæ _': 'ć ŹćŻ(5æšć«ä»„äžçĄé»æąŻ)'}, regex=False) df_group = df_group.replace({'ć»șç©ćæ _': 'ćșéą(ćșéȘ)'}, {'ć»șç©ćæ _': 'ćșéą(ćșéȘ)'}, regex=False) df_group = df_group.replace({'ć»șç©ćæ _': 'èŻć»(10ć±€ć«ä»„äžæé»æąŻ)'}, {'ć»șç©ćæ _': 'èŻć»(10ć±€ć«ä»„äžæé»æąŻ)'}, regex=False) ##### Lines ================================= all_area = list(np.unique(np.array(df_group['ééźćžć_']))) all_type = list(np.unique(np.array(df_group['ć»șç©ćæ _']))) all_y = ['ćźćčć ćčłæčć Źć°ș_count', 'ćźćčć ćčłæčć Źć°ș_median', 'date_diff_median'] dash_app1.layout = html.Div(children=[ html.Button('open url', id='button'), visdcc.Run_js(id='javascript'), html.Div(children=[ html.Div([ html.Div([ html.Label('Y'), dcc.Dropdown(id='my_y', options=[{ 'label': p, 'value': p } for p in all_y], multi=False, value="ćźćčć ćčłæčć Źć°ș_count"), ]), html.Div([ html.Label('ééźćžć'), dcc.Dropdown(id='my_area', options=[{ 'label': p, 'value': p } for p in all_area], multi=True, value=all_area[0:4]), ]), html.Div(children=[ html.Label('ć»șç©ćæ '), dcc.Dropdown(id='my_type', options=[{ 'label': v, 'value': v } for v in all_type], multi=True, value=all_type[0:6]), html.Button(id='submit-button-state', n_clicks=0, children='Submit', style={ 'float': 'right', 'margin': '10px 0px 10px 0px' }), html.Button("Fix Sc", id="fix"), ]) ], className="three_columns"), html.Div(children=[ html.Div(children=[dcc.Graph(id="graph")]), ], className="nine_columns") ], className="Main", id="MainPower") ]) @dash_app1.callback(Output('javascript', 'run'), [Input("button", "n_clicks")]) def myfun(x): return """let titleEls = document.getElementsByClassName("three_columns")[0]; let btn = document.getElementById("fix"); btn.addEventListener("click",function(){ titleEls.classList.toggle("A"); btn.classList.toggle("click"); console.log("toggle"); }); """ @dash_app1.callback(Output('graph', 'figure'), Input('submit-button-state', 'n_clicks'), State('my_y', 'value'), State('my_area', 'value'), State('my_type', 'value')) def set_cities_options(n_clicks, my_y, my_area, my_type): # pdb.set_trace() if type(my_area) == type(''): my_area = [my_area] if type(my_type) == type(''): my_type = [my_type] # pdb.set_trace() df_plot = df_group[df_group['ééźćžć_'].isin(my_area) & df_group['ć»șç©ćæ _'].isin(my_type)] df_plot['k'] = df_plot.groupby(['ć»șç©ćæ _', 'ééźćžć_'])[my_y].transform(make_lowess) fig = px.line( df_plot, x="date_", y=[my_y, 'k'], # height=700, width=1000, facet_col="ééźćžć_", facet_row="ć»șç©ćæ _", template= 'plotly', # "plotly", "plotly_white", "plotly_dark", "ggplot2", "seaborn", "simple_white", "none" # color_discrete_map={ # my_y: "#456987", # "k": "#147852" # } ) fig.for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1])) # pdb.set_trace() # fig.data[0].mode='markers+lines' # for i in fig.data[0:3]: # i.mode = 'markers+lines' fig.update_xaxes(matches='x', tickangle=-45, title=None) fig.update_yaxes(matches=None, title=None, showticklabels=True, visible=True) fig.update_layout(showlegend=False) return fig return dash_app1
html.Div([ 'æȘæ„èŻąć°çšæ·ïŒèŻ·ć èżèĄ', html.A('çŹć', href='/crawling'), ], className='notification is-danger is-light nosearch', id='nosearch', style={'display': 'none'}), html.Div([ html.Div(id='analyseResult1'), html.Div(id='analyseResult2'), html.Div(id='analyseResult3'), html.Div(id='analyseResult4'), html.Div(id='analyseResult5'), ], id='analyseResult'), visdcc.Run_js(id='similarScript'), visdcc.Run_js(id='addlistenScript'), ]) @app.callback( Output('info_analyse', 'style'), [Input('startAnalyse', 'n_clicks')], ) def hiddenInfo(n): return {'display': 'none'} @app.callback( [Output('addlistenScript', 'run'), Output('similarPanel', 'style')],
import visdcc import pandas as pd app = dash.Dash(__name__) app.layout = html.Div([ html.H1('These are data from G+ and Wikifactory.'), html.Span('Filter posts by title or author: '), dcc.Input(id='filter', placeholder='Filter by title or author...', type='text', value=''), html. P('Mouse over a data point to see the title. Click on a data point go to a URL.' ), visdcc.Run_js(id='javascript'), dcc.Graph(id='graph') ]) from PeopleAndPostsOver import df """ The populaterizer filters and populates the graph. It gets its input from filter """ @app.callback(Output('graph', 'figure'), [Input('filter', 'value')]) def populaterizer(value): #filter! query = df.texts.str.contains(value, case=False) newdf = df[query]
[html.Tr( [html.Td( df.iloc[i, j], id = '{}_{}_{}'.format(id, i, j) ) for j in range(len(df.columns))] ) for i in range(len(df))] ) return html.Table([Thead, Tbody], id = id, className = "display") df = pd.DataFrame({'name': ['Jacky', 'Mei', 'Jay', 'Sandy', 'Jerry', 'Jimmy', 'Jeff', 'Jacky', 'Mei', 'Jay', 'Sandy', 'Jerry', 'Jimmy', 'Jeff', 'Jacky', 'Mei', 'Jay', 'Sandy', 'Jerry', 'Jimmy', 'Jeff'], 'age': [18, 71, 14, 56, 22, 28, 15, 18, 71, 14, 56, 22, 28, 15, 18, 71, 14, 56, 22, 28, 15]}, columns = ['name', 'age']) app.layout = html.Div([ html.Button('Add mousemove event', id = 'button'), visdcc.Run_js(id = 'javascript', run = "$('#datatable').DataTable()"), html.Br(), html.Div( generate_html_table_from_df(df, id = 'datatable'), style = {'width': '40%'} ), html.Div(id = 'output_div') ]) @app.callback( Output('javascript', 'run'), [Input('button', 'n_clicks')]) def myfun(x): if x is None: return '' return ''' var target = $('#datatable')[0]
value=False), html.H4("Good đđŒ", id="good-header") ], align="center", justify="center") ], width=8) ]) ]) ]), html.Div(id='scroll-blocker', className='scroll'), ]), visdcc.Run_js(id='javascript', run=''' new fullScroll({ mainElement: "main", sections: ["intro", "plots"], displayDots: false }); ''') ]) @app.callback(Output("loc", "href"), [Input("start-button", "n_clicks")]) def get_started(n_clicks): return "#0" if n_clicks is None else "#1" @app.callback([ Output("title", "children"), Output("desc", "children"), Output("form", "children"),
import dash_html_components as html from data.others.home_background_script import script import visdcc from building_blocks import * from callbacks import * prefix="home" print("Loading "+prefix.capitalize()+" ...") layout=dbc.Col([ dbc.Col([ html.Canvas(id="fancy-network-background",style={"position":"absolute", "width":"100%", "height":"66vh", "padding":"0px", "z-index":"0"}),# "background": "linear-gradient(to top, rgba(230,245,249,0), rgba(230,245,249,0.5))" visdcc.Run_js(id="fancy_network_background_script", run=script), # html.Center(html.H1(html.Strong("COVIDrugNet"))), dbc.Row([ dbc.Col([ html.Img(src=app.get_asset_url("imgs/logo_wide.svg"), alt="COVID-19 Drugs Networker", style={"width":"100%"}), ], xs=10, lg=6, align="center", style={"position":"relative","z-index":"1"}), dbc.Col([ html.P("Visualize and Analyze Networks about Drugs and Targets Related to COVID-19", style={"text-align":"center","font-size":"x-large","font-weight":"bold","background":"white","box-shadow":"0rem 0rem 0.25rem white", "border-radius": "5rem"}), html.P("COVIDrugNet is a free and open web tool", style={"text-align":"center","font-size":"large","background":"white","box-shadow":"0rem 0rem 0.25rem white", "border-radius": "5rem", "margin-bottom":0}), html.P("based on networks and designed to support the exploration and investigation of the landscape of medicines currently in clinical trial for the treatment of COVID-19", style={"text-align":"center","font-size":"large","background":"white","box-shadow":"0rem 0rem 0.25rem white", "border-radius": "5rem", "margin-bottom":0}), html.P(["(according to ",html.A("DrugBank Dashboard dedicated to COVID-19", href="https://go.drugbank.com/covid-19", target="_blank", style={"color":"black"}),")"], style={"text-align":"center","font-size":"medium","background":"white","box-shadow":"0rem 0rem 0.25rem white", "border-radius": "5rem"}) ], xs=10, lg=3, align="center", style={"position":"relative","z-index":"1"}) ], justify="center", align="center", style={"padding-top":"7.5vh", "padding-bottom":"7.5vh"}), # html.Center(html.H4("Visualize and Analyze Networks about Drugs and Targets Related to COVID-19")), dbc.Row([ dbc.Col([
def calibration_layout(calibration_data): return dbc.Container( id="main-layout", className="float-left", style={"margin-left": "20px"}, children=[ visdcc.Run_js( "javascript"), # run javascript to refresh page on demand dcc.ConfirmDialog( id="confirm-calibration-dialog", message="Are you sure you want to set new calibration?"), dcc.ConfirmDialog( id="confirm-zoom-dialog", message="Are you sure you want to change the zoom level?"), dcc.ConfirmDialog( id="confirm-restore-calibration-dialog", message="Restore calibration to factory default?"), dbc.Row( # single bootstrap row className="mt-5", children=[ dbc.Col( xs= 12, # put content in columns when viewing on small devices sm=12, md=7, lg=7, children=[ calibration_display(VIDEO_STREAM_SRC, calibration_data) ]), dbc.Col( style={"text-align": "center"}, xs=12, sm=12, md=4, lg=4, children=[ html.Div( className="div-control-group", style={ "padding-bottom": "24px", "padding-top": "10px" }, children=[ zoom_slider( calibration_data.get("zoom_level", 1)), dbc.Button(html.Span( "Confirm Calibration", style={"font-size": "18px"}), style={ "width": "200px", "margin-top": "20px" }, id="calibration-btn", className= "align-self-center control-btn", size="lg", n_clicks=0, color="#00aacf"), dbc.Button( html.Span("Restore Calibration", style={"font-size": "18px"}), id="btn-restore-calib", className= "align-self-center control-btn", style={ "width": "200px", "margin-top": "20px", "margin-left": "20px" }, # style=style, size="lg", n_clicks=0, color="#00aacf"), ]) ]) ]) ])
[ dbc.CardHeader([ dbc.Row([ dbc.Col( html.H4("Imagen cargada"), width=8, ), dbc.Col( [ dbc.Button( "Habilitar cropper", id='cropper-enable', color="secondary", className="mr-1", block=True), visdcc.Run_js( id='enablecropjs'), ], width=4, ), ]), ]), dbc.CardBody([ html.Div(id='image-to-crop'), ]), dbc.CardFooter([ html.H6('Datos del cropper'), table, html.H6( 'Tipo de ĂĄrea a especificar'), dbc.Row([ dbc.Col([
def serve_layout(self, sess_id): download_link = html.A(id=self.DS_ID + 'download-link', target='_blank', href='dimred/download?value=' + sess_id), layout = html.Div(children=[ dcc.Store(id=self.DS_ID + 'session_id', data=sess_id, storage_type='memory'), dcc.Store(id=self.DS_ID + 'location', storage_type='memory'), dcc.Store(id=self.DS_ID + 'currently_selected_data', storage_type='memory'), dcc.Store(id=self.DS_ID + 'all_selected_pool', storage_type='memory'), dcc.Store(id=self.DS_ID + 'all_selected_data', storage_type='memory'), dcc.Store(id=self.DS_ID + 'uploaded_data', storage_type='memory'), visdcc.Run_js(id=self.DS_ID + 'javascript'), html.Div(children=[ html.Div(children=[ html.Button('Done', id=self.DS_ID + 'close_selector', className="close_selector", n_clicks_timestamp=0), html.H4('Select Data:', id=self.DS_ID + 'path', style={ 'textAlign': 'center', 'margin': '0', 'paddingTop': '3rem' }), html.Div(children=[ html.Div( id=self.DS_ID + 'button_container', children=self.all_buttons, ), html.Div(children=[ html.Div(children=[ dcc.Dropdown( id=self.DS_ID + 'ratings_assignment', options=[{ 'label': x, 'value': x } for x in assignment_options], style={'width': '25vw'}, multi=True, placeholder='Select Assignment(s)'), dcc.Dropdown(id=self.DS_ID + 'ratings_prepost', options=[{ 'label': x, 'value': x } for x in [ 'All Pre/Post', 'Pre', 'Post' ]], style={'width': '25vw'}, multi=True, placeholder='Select Pre/Post'), dcc.Dropdown(id=self.DS_ID + 'ratings_type', options=[{ 'label': x, 'value': x } for x in [ 'All Types', 'Technology', 'Market', 'Organization' ]], style={'width': '25vw'}, multi=True, placeholder='Select Type'), html.Button('Add', id=self.DS_ID + 'ratings_add', n_clicks_timestamp=0) ], id=self.DS_ID + 'ratings_selectors', style={'display': 'flex'}), html.Div(children=[ dcc. Dropdown(id=self.DS_ID + 'decisionpoints_assignment', options=[{ 'label': x, 'value': x } for x in [assignment_options[0]] + assignment_options[2:]], style={'width': '25vw'}, multi=True, placeholder='Select Assignment(s)'), dcc.Dropdown( id=self.DS_ID + 'decisionpoints_prepost', options=[{ 'label': x, 'value': x } for x in ['All Pre/Post', 'Pre', 'Post'] ], style={'width': '25vw'}, multi=True, placeholder='Select Pre/Post'), html.Button('Add', id=self.DS_ID + 'decisionpoints_add', n_clicks_timestamp=0) ], id=self.DS_ID + 'decisionpoints_selectors', style={'display': 'flex'}), html.Div(children=[ html.Button('Add', id=self.DS_ID + 'pp_add', n_clicks_timestamp=0) ], id=self.DS_ID + 'pp_selectors', style={'display': 'flex'}), ], id=self.DS_ID + 'selector_container') ], style={ 'width': '100%', 'display': 'flex', 'justifyContent': 'center' }), ]), html.Div(children=[ html.Div(children=[ html.Div(children=[ html.H4('Currently Selected Data', style={'textAlign': 'center'}), html.Div(children=[ html.P('n=_, _ dropped', id=self.DS_ID + 'current_description') ], style={ 'height': '5vh', 'textAlign': 'center' }), html.Div(children=[ dash_table.DataTable(id=self.DS_ID + 'currently_selected', style_table={ 'height': '100%', 'overflowY': 'scroll' }, page_current=0, page_size=8, page_action='custom', fill_width=True) ], style={ 'flex': '1', 'minHeight': '0' }) ], style={ 'display': 'flex', 'flexDirection': 'column', 'width': '48%', 'margin': '1%' }), html.Div(children=[ download_link[0], dcc.Upload(id=self.DS_ID + 'upload_all_selected', children=[ html.Button( 'Upload', className='downloadButton', style={'left': '51%'}) ]), html.Button(id=self.DS_ID + 'download_all_selected', children=['Download'], className='downloadButton'), html.H4('All Selected Data', style={'textAlign': 'center'}), html.P('n = 0', id=self.DS_ID + 'all_selected_n', style={'textAlign': 'center'}), dcc.Dropdown(id=self.DS_ID + 'label', className='dropdown-spacing', placeholder='Label', style={} if (self.DS_ID == 'class____' or self.DS_ID == 'reg____') else {'display': 'none'}), dcc.Dropdown(id=self.DS_ID + 'all_selected_dropdown', className='dropdown-spacing', multi=True, value=[], placeholder='Data Sets'), html.Div(children=[ dash_table.DataTable( id=self.DS_ID + 'all_selected', style_table={ 'height': '100%', 'overflowY': 'scroll' }, page_current=0, page_size=6, page_action='custom', merge_duplicate_headers=True, fill_width=True) ], style={ 'flex': '1', 'minHeight': '0' }) ], style={ 'display': 'flex', 'flexDirection': 'column', 'width': '48%', 'margin': '1%' }), ], style={ 'display': 'flex', 'height': '100%' }), ], style={ 'flex': '1', 'marginTop': '1rem', 'minHeight': '0' }) ], id=self.DS_ID + 'selector', className="selector", style={'display': 'none'}), html.Div(children=[ html.Div(children=[ html.Div(children=[ html.H4("Select Questions", style={'marginRight': '2rem'}), html.Button("Select All", id=self.DS_ID + 'select_all_pp', n_clicks_timestamp=0), html.Button("Deselect All", id=self.DS_ID + 'deselect_all_pp', n_clicks_timestamp=0), html.Button('Close', id=self.DS_ID + 'close_pp_selector', n_clicks_timestamp=0, style={'marginLeft': 'auto'}), ], style={ 'display': 'flex', 'paddingBottom': '2rem' }), dash_table.DataTable( id=self.DS_ID + 'pp_table', columns=[{ "name": 'Questions', "id": 'Questions' }], data=[{ 'Questions': x } for x in pp_questions], style_cell={ 'textAlign': 'left', }, style_table={ 'maxHeight': '80vh', 'overflowY': 'scroll', }, style_data={'whiteSpace': 'normal'}, css=[{ 'selector': '.dash-cell div.dash-cell-value', 'rule': 'display: inline; white-space: inherit; overflow: inherit; text-overflow: inherit;' }], row_selectable="multi", filter_action='native', sort_action='native', fill_width=True) ], className='pp_container'), ], id=self.DS_ID + 'pp_questions_selector', className='pp_questions', style={'display': 'none'}), html.Div(children=[ html.Div(children=[ html.Div(children=[ html.H4("Select Concentrations", style={'marginRight': '2rem'}), html.Button("Select All", id=self.DS_ID + 'select_all_concentration', n_clicks_timestamp=0), html.Button("Deselect All", id=self.DS_ID + 'deselect_all_concentration', n_clicks_timestamp=0), html.Button('Close', id=self.DS_ID + 'close_concentration_selector', n_clicks_timestamp=0, style={'marginLeft': 'auto'}), ], style={ 'display': 'flex', 'paddingBottom': '2rem' }), dash_table.DataTable( id=self.DS_ID + 'concentration_table', columns=[{ "name": app_data.additional_questions[1][0], "id": app_data.additional_questions[1][0] }], data=[{ app_data.additional_questions[1][0]: x } for x in app_data.concentrations], style_cell={ 'textAlign': 'left', }, style_table={ 'maxHeight': '80vh', 'overflowY': 'scroll', }, style_data={'whiteSpace': 'normal'}, css=[{ 'selector': '.dash-cell div.dash-cell-value', 'rule': 'display: inline; white-space: inherit; overflow: inherit; text-overflow: inherit;' }], row_selectable="multi", filter_action='native', sort_action='native', fill_width=True) ], className='pp_container'), ], id=self.DS_ID + 'concentration_selector', className='pp_questions', style={'display': 'none'}), html.Div(children=[ html.Div(children=[ html.Div(children=[ html.H4("Select Companies", style={'marginRight': '2rem'}), html.Button("Select All", id=self.DS_ID + 'select_all_companies', n_clicks_timestamp=0), html.Button("Deselect All", id=self.DS_ID + 'deselect_all_companies', n_clicks_timestamp=0), html.Button('Close', id=self.DS_ID + 'close_companies_selector', n_clicks_timestamp=0, style={'marginLeft': 'auto'}), ], style={ 'display': 'flex', 'paddingBottom': '2rem' }), dash_table.DataTable( id=self.DS_ID + 'companies_table', columns=[{ "name": app_data.additional_questions[0][0], "id": app_data.additional_questions[0][0] }], data=[{ app_data.additional_questions[0][0]: x } for x in app_data.companies], style_cell={ 'textAlign': 'left', }, style_table={ 'maxHeight': '80vh', 'overflowY': 'scroll', }, style_data={'whiteSpace': 'normal'}, css=[{ 'selector': '.dash-cell div.dash-cell-value', 'rule': 'display: inline; white-space: inherit; overflow: inherit; text-overflow: inherit;' }], row_selectable="multi", filter_action='native', sort_action='native', fill_width=True) ], className='pp_container'), ], id=self.DS_ID + 'companies_selector', className='pp_questions', style={'display': 'none'}), ], style={ 'position': 'absolute', 'width': '100%', 'top': '5vh' }) return layout
if config.MLFLOW_URI is not None: mlflow.tracking.set_tracking_uri(config.MLFLOW_URI) df_select_init = pd.DataFrame() df_select_init['filename'] = [[]] * 1 df_select_init['_id'] = [[]] * 1 df_select_init['content_type'] = [[]] * 1 df_select_init['comments'] = [[]] * 1 df_labels_init = pd.DataFrame(config.DEFAULT_LABELS) layout = html.Div([ html.Div([ html.Div([ dcc.Store(id='store-shapes'), dcc.Store(id='polygon-data'), visdcc.Run_js(id='javascript-ctrl-click', run="$('#graph-image').Graph()"), visdcc.Run_js(id='javascript-ctrl-keyup', run="$('#graph-image').Graph()"), visdcc.Run_js(id='javascript-drag-color', run="$('#graph-image').Graph()"), html.Br(), html.Div([ html.Button(id='button-rect', n_clicks=0, title='rectangle marquee tool', style={ 'background-image': 'url(../assets/rect.png)', 'background-repeat': 'no-repeat', 'background-size': 'contain', 'background-position': 'center', 'height': '50px',
html.Div([ dcc.Graph(id='bankrupcy_proba-graph') ], id='prediction-graph-div') ] ) ] )] ) ) ]), visdcc.Run_js(id='javascript', run=''' new fullScroll({ mainElement: 'main', sections:['title-section', 'map-section','prediction-section'], displayDots: true, dotsPosition: 'right', animateTime: 0.7, animateFunction: 'ease' }); ''' ), ] ) @app.callback( Output('map', 'figure'), [ Input('year-slider', 'value'), Input('map-type-radiobuttons', 'value'), Input('selected-voivodeship-indices', 'children'), ])
dbc.Row([ dbc.Col(filters, width=2), dbc.Col([ search_bar, html.Div(results, id='results_box', style={ "maxHeight": "550px", "overflowY": "scroll" }), html.Br(), pagination_buttons ], width=8), dbc.Col(top_tags, width=2) ]), visdcc.Run_js(id='scroll_top') ]) # PROJECT PAGE # instructions graph_text = dcc.Markdown(""" Learn more about this project and discover related projects. The figure below displays this project's top 7 most related projects. The size of the connection represents the strength of the relationship between projects. Different color projects represent different clusters of related projects. **Click and drag to move individual nodes. Hover over nodes or relationships for more info.** """) project_layout = html.Div([
COEFFICIENTS_PATH = "{}/coefficients.json".format(PATH) DATA_PATH = "{}/data.json".format(PATH) NORMALIZED_DATA_PATH = "{}/normalizedData.json".format(PATH) TEXT_PATH = "text.json" app = dash.Dash(__name__, external_stylesheets=[dbc.themes.COSMO]) server = app.server app.title = "Unessay" devMode = False data = appUtil.getDataFrame(DATA_PATH) normalizedData = appUtil.getDataFrame(NORMALIZED_DATA_PATH) coefficients = appUtil.getDataFrame(COEFFICIENTS_PATH) text = appUtil.getTextObject(TEXT_PATH) app.layout = html.Div(children=[ visdcc.Run_js(id='intro1'), visdcc.Run_js(id='mon1'), visdcc.Run_js(id='dat1'), visdcc.Run_js(id='mod1'), visdcc.Run_js(id='viz1'), visdcc.Run_js(id='gd1'), visdcc.Run_js(id='bd1'), visdcc.Run_js(id='cnc1'), dbc.Row([ dbc.Col([html.Div([])], md=4), dbc.Col(dbc.Row(html.H1(children='Machine Learning in Organizations'), justify="center"), md=4), dbc.Col(getHeader(), align="right") ]), html.Div(id='data', style={'display': 'none'}),
import sd_material_ui import visdcc import uuid import pickle import pandas as pd import os static_dir = os.path.dirname(__file__) SideBar = [ html.Img(id="app_logo", src=encode_image(os.path.join(static_dir, "assets/images/y2d.png"))), html.Br(), visdcc.Run_js(id='theme_javascript'), html.Div(html.A('Dark/Light theme'), id="dark_theme", n_clicks=0, className="nav_item"), # Collapsible button with external links html.Div(html.A([ html.Span('External links'), html.I(className="fa fa-caret-down", id="external_links_caret"), ]), id='button_collapse', n_clicks=0, className="nav_item"), # Stuff inside the collapsible html.Div(
style={'display': 'inline-block'}), html.Div( id='heatmap-good-graph3', style={'display': 'inline-block'}), ]), ], style={'display': 'inline-block'}) ]) ])), ]), visdcc.Run_js(id='javascript', run=''' new fullScroll({ mainElement: 'main', sections:['barplot-section', 'scatter-section', 'scatter-3d-section', 'piechart-section', 'heatmap-section'], displayDots: true, dotsPosition: 'right', animateTime: 0.7, animateFunction: 'ease' }); '''), ]) @app.callback([ dash.dependencies.Output('barplot-good-graph', 'children'), dash.dependencies.Output('barplot-explanation', 'children'), dash.dependencies.Output('barplot-wrong-answer', 'style'), dash.dependencies.Output('barplot-good-answer', 'style'), dash.dependencies.Output('barplot-number-of-clicks', 'children') ], [
authorizedLayout = html.Div(id='authorizedContent', children='Your app goes here') # Layout to display when the user is not authorized # You can use the redirect layout instead to return the user to the signin page unauthaurizedLayout = html.Div(children=[ html.H1(id='title', children='Unauthaurized user'), html.A( id='signout', href=routes["SIGNIN"], children="Return to signin page") ]) # Use this layout to redirect the user to another page (signin page?) # Use this to run JS inside dash: https://github.com/jimmybow/visdcc#3-visdccrun_js- redirectLayout = html.Div(children=[ visdcc.Run_js(id='javascript', run='window.location.replace("' + routes['SIGNINFULLPATH'] + '");') # visdcc.Run_js(id = 'javascript', run='window.location.replace("http://*****:*****@app.callback(Output('pageContent', 'children'), [Input('url', 'pathname')]) def on_load(path): if path == '/revoke': session.logout()
def server_layout(mode=None): #return the layout of the GUI session_id = str(uuid.uuid4()) #variable, distribution selection panel selection_panel = html.Div(id='selection-panel',children=[ html.Div(id='selected-column-panel',children=[ html.Div(id='selected-column-sec1-panel',children=[ drc.NamedDropdown( name='Select series', id='selected-series', searchable=False, clearable=False ), dcc.Checklist( id='apply-log-transform', options=[{'label':' Apply log transform','value':'logtransform'} ]), ]), drc.NamedTextarea( id='series-characteristics', name='Series characteristics', cols='50', rows='2', readOnly='readOnly' ), ]), html.Div(id='apply-panel',children=[ html.Div(id='apply-sec1-panel',children=[ drc.NamedDropdown( id='fitted-distributions', name='Fitted distribution', options=[ {'label': ' '+ v[0], 'value': k} for k,v in dist_par_template.items() if k != 'native' and v[2] ], value='normal', searchable=False, clearable=False ), ]), # html.Div(id='apply-sec1b-panel',children=[ # drc.NamedDropdown( # id='plotting-distributions', # name='Probability scale', # options=[ # {'label': ' '+ v[0], 'value': k} # for k,v in dist_par_template.items() if v[2] # ], # value='native', # searchable=False, # clearable=False # ), # ]), html.Div(id='apply-sec2a-panel',children=[ html.Button('Fit',id='fit-button',n_clicks=0), ]), #dcc.Checklist( # id='show-y-log', # options=[{'label':' Show y-axis in log scale','value':'true'} #]), ]), html.Label(id='graph-refresh'), dcc.Store( id='graph-refresh-hidden', data=0 ), html.Div(id='message-panel',children=[""]), ]) #variable, distribution selection panel par_panel = html.Div(id='fitted-panel',children=[ html.Div(id='fitted-sec1-panel',children=[ drc.NamedTextarea( id='fitted-par', name='Estimated distribution parameters', readOnly='readOnly', cols= 40, rows= 3 ), drc.NamedTextarea( id='estimated-quantiles', name='Estimated quantiles', readOnly='readOnly', cols= 40, rows= 3 ), ]) ]) upload_panel = html.Div(id='last-card',children=[ dcc.Upload( id='upload-data', children=html.Div([ 'Drag and Drop or ', html.A('Select File') ]), style={ 'lineHeight': '60px', 'borderWidth': '1px', 'borderStyle': 'dashed', 'borderRadius': '5px', 'textAlign': 'center', } ), html.Label('''File upload limited to < %0.0f Kb, containing no more than %d rows and %d columns'''%(configs['max_file_size']/1024,configs['max_file_rows'],configs['max_file_cols'])), html.Label('',id='data-filename'), html.Label('',id='data-description'), html.Div(id='table-panel',children=[ dash_table.DataTable( id='attribute-table', columns=[], row_selectable='multi', editable=False, style_header={ 'textAlign': 'center', 'fontWeight': 'bold', 'color': 'black', }, style_cell={ 'padding': '2px', '--selected-background': 'grey', 'color': 'black', }, style_data_conditional=[ { 'if': {'row_index': 'odd'}, 'backgroundColor': 'rgb(248, 248, 248)' } ], #locale_format= '0.3', ) ],style={'visibility':'none','display':'none'}), ]) chart_panel = html.Div(id='chart-panel',children=[ dcc.Loading(id = "loading-icon", children=[ dcc.Graph( id='graph', figure={ }, responsive=True, config=graph_config, style={'display':'none'} ) ]), ], style={'visibility':'none'}) layout = html.Div( id="body", className="container scalable", children=[ visdcc.Run_js(id = 'chart-updated-js'), visdcc.Run_js(id = 'chart-unupdated-js'), visdcc.Run_js(id = 'error-display-js'), dcc.Store(id='error-display',data=''), html.Title(title=configs['title']), #hidden session id #row 1 for title html.Div(id='top-panel',children=[ html.H5(id='app-title',children= '''Distribution Fitting and Analysis Tool. This tool is only for demostration porpuses''', style={"margin-bottom": "0px"}, ), ],className="row flex-display"), #second row layout html.Div(id='main-panel',children=[ html.Div(id='left-panel',children=[ upload_panel ]), html.Div(id='output-panel',children=[ selection_panel, par_panel, chart_panel ],style={'visibility':'none','display':'none'}), ]), #row 4 is the footer html.Div(id='footer-panel',children=[ ''' A web application built on top of Dash (v%s) (framework for Python) by Exequiel SepĂșlveda and Dmitri Kavetski.'''%(dash.__version__) ]), ], ) return layout