className="mb-3", color="dark", outline=True, size="sm", block=True), dbc.Collapse( [ dbc.FormGroup([ dbc.Checklist( options=[{ "label": "Semi-log Plot", "value": False }], value=False, #HACK: notice that this is a boolean id="log-scale-toggle", switch=True, ), dbc.Tooltip( "Plot y-axis using a logarithmic scale (Default: False)", target="log-scale-toggle", placement='right', offset=0, ), ]), dbc.FormGroup([ dbc.Checklist( options=[{ "label": "Plot Actual Deaths and Cases", "value": True }], value=[True], #HACK: Notice that this is a list
nterms_base = dbc.FormGroup([ dbc.Label("Number of base terms"), dbc.Input(placeholder="1", value=1, type="number", id='nterms_base', debounce=True, min=0, max=4), dbc.Label("Number of band terms"), dbc.Input(placeholder="1", value=1, type="number", id='nterms_band', debounce=True, min=0, max=4), dbc.Label("Set manually the period (days)"), dbc.Input(placeholder="Optional", value=None, type="number", id='manual_period', debounce=True) ], style={ 'width': '100%', 'display': 'inline-block' }) submit_varstar_button = dbc.Button('Fit data',
def get_dcf_current_year_input_overrides(): return [ dbc.Form([ dbc.FormGroup([ dbc.Label("Revenue (M$)", html_for="year0-revenue"), dbc.Input(type="number", id="year0-revenue", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("R&D (M$)", html_for="year0-randd"), dbc.Input(type="number", id="year0-randd", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("CapEx (M$)", html_for="year0-capex"), dbc.Input(type="number", id="year0-capex", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("EBIT excl. Reinvestment (M$)", html_for="year0-ebit"), dbc.Input(type="number", id="year0-ebit", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Past Revenue CAGR (%)", html_for="year0-rgr"), dbc.Input( type="number", id="year0-rgr", disabled=True, ), ]), dbc.FormGroup([ dbc.Label("Cash and Equivalents (M$)", html_for="cash"), dbc.Input(type="number", value=0, id="cash", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Common Shares Outstanding (Millions)", html_for="shares-outstanding"), dbc.Input(type="number", value=0, id="shares-outstanding", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Minority Interests (M$)", html_for="minority-interests"), dbc.Input(type="number", value=0, id="minority-interests", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Nonoperating Assets (M$)", html_for="nonoperating-assets"), dbc.Input(type="number", value=0, id="nonoperating-assets", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Employee Options Value (M$)", html_for="options-value"), dbc.Input(type="number", value=0, id="options-value", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Book Value of Longterm Debt (M$)", html_for="debt-book-value"), dbc.Input(type="number", value=0, id="debt-book-value", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Interest Expense (M$)", html_for="interest-expense"), dbc.Input(type="number", value=0, id="interest-expense", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Convertible Debt Book Value (M$)", html_for="convertible-debt-book-value"), dbc.Input(type="number", value=0, id="convertible-debt-book-value", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Convertible Market Value (M$)", html_for="convertible-market-value"), dbc.Input(type="number", value=0, id="convertible-market-value", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Preferred Equity Number of Shares (Millions)", html_for="preferred-num-shares"), dbc.Input(type="number", value=0, id="preferred-num-shares", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Preferred Price per share ($)", html_for="preferred-price-pershare"), dbc.Input(type="number", value=70, id="preferred-price-pershare", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Preferred Dividend per share ($)", html_for="preferred-dividend-pershare"), dbc.Input(type="number", value=5, min=0.01, step=0.01, id="preferred-dividend-pershare", placeholder="Enter number", debounce=True), ]), dbc.FormGroup([ dbc.Label("Debt Value of Operating Leases (M$)", html_for="debt-value-op-leases"), dbc.Input(type="number", value=0, id="debt-value-op-leases", placeholder="Enter number", debounce=True), ]), ], inline=True), dbc.Form([ dbc.FormGroup([ dbc.Label("Average Maturity Duration (years)", html_for="average-maturity"), dcc.Slider( id="average-maturity", min=2, max=10, step=0.25, value=3, marks={v: str(v) for v in range(2, 11)}, ) ]), dbc.FormGroup([ dbc.Label("Pretax Cost of Debt (%)", html_for="pretax-cost-debt"), dcc.Slider( id="pretax-cost-debt", min=2, max=10, step=0.25, value=4, marks={v: str(v) for v in range(2, 11)}, ) ]), dbc.FormGroup([ dbc.Label("Convertible Debt Portion of Market Value (%)", html_for="convertible-debt-portion"), dcc.Slider( id="convertible-debt-portion", min=0, max=100, step=5, value=0, marks={v: str(v) for v in range(0, 101, 5)}, ) ]), ]) ]
countries = country() #end this block #controls controls = dbc.Card( [ dbc.Row( [ dbc.Col( dbc.FormGroup([ dbc.Label("Choose a Country:"), dcc.Dropdown( id="country-selector", options=[{ "label": x, "value": x } for x in countries], value="All" #, multi = True ) ])), ], align='center') ], body=True) # inicialisation Graph graph = dcc.Graph(id='graph') #general layout app.layout = dbc.Container(
import dash_bootstrap_components as dbc import dash_html_components as html import dash_core_components as dcc search_string_input = dbc.FormGroup( [ dbc.Label("Search String", html_for="search-string-row", width=2), dbc.Col( dbc.Input( type="text", id="search-string", placeholder="Enter title"), width=10, ), ], row=True, ) date_input = dbc.FormGroup( [ dbc.Label("Date", html_for="date-row", width=2), dbc.Col( dcc.DatePickerRange(id="date-row", display_format="Y"), width=10, ), ], row=True, ) n_input = dbc.FormGroup( [ dbc.Label("Number of results", html_for="n-row", width=2), dbc.Col(
import dash_core_components as dcc import dash_html_components as html import dash_bootstrap_components as dbc from dash.dependencies import Input, Output, State from app import app, ADMINS from flask_login import login_user username_input = dbc.FormGroup([ dbc.Label("Entrer votre nom d'administrateur"), dbc.Input(placeholder="Nom", type="text", id="uname-box") ]) pwd_input = dbc.FormGroup([ dbc.Label("Entrer votre mot de passe"), dbc.Input(placeholder="Mot de passe", type="password", id="pwd-box") ]) layout = html.Div([ dcc.Location(id="url_login", refresh=True), dbc.Row( dbc.Col( dbc.Form([ dbc.Alert( "Nom d'utilisateur ou mot de passe incorrect", id="output-state", color="danger", dismissable=True, ), username_input, pwd_input, dbc.Button(children="Login",
def make_item(i, d=False): return dbc.Card([ dbc.CardHeader( html.H1( dbc.Button(f"Loan #{i}", color="link", id=f"loan-{i}-toggle", disabled=d, style={"font-size": "20px"}))), dbc.Collapse( html.P([ html.Br(), dbc.FormGroup([ dbc.Label("Please Enter the loan amount", size="md"), dbc.InputGroup([ dbc.InputGroupAddon("$", addon_type="prepend"), dbc.Input(placeholder="Please Enter the loan amount", type="number", min=0, bs_size="md", inputMode="numeric", id=f'loan-input{i}'), ]), ], className="mx-2"), dbc.FormGroup([ dbc.Label("Please Enter the interest rate:", size="md"), dbc.InputGroup([ dbc.Input(placeholder="Please Enter the interest rate", type="number", min=0, bs_size="md", inputMode="numeric", id=f'rate-input{i}'), dbc.InputGroupAddon("%", addon_type="append") ]), ], className="mx-2"), dbc.FormGroup([ dbc.Label("Please Enter the payment:", size="md"), dbc.InputGroup([ dbc.InputGroupAddon("$", addon_type="prepend"), dbc.Input(placeholder="Please Enter the payment", type="number", min=0, bs_size="md", inputMode="numeric", id=f'payment-input{i}'), ]), ], className="mx-2"), dbc.FormGroup([ dbc.Label("Please Enter the extra payment:", size="md"), dbc.InputGroup([ dbc.InputGroupAddon("$", addon_type="prepend"), dbc.Input(placeholder="Please Enter the extra payment", type="number", min=0, bs_size="md", inputMode="numeric", id=f'expayment-input{i}'), ]), ], className="mx-2"), dbc.ButtonGroup([ dbc.Button("Submit", outline=True, id=f"button-submit{i}", color="success", className="mr-1", n_clicks=0), dbc.Button("Clear", outline=True, id=f"button-clear{i}", color="warning", className="mr-1", n_clicks=0) ], className="mx-2 mb-2") ], className="w-100 mb-3"), id=f"collapse-{i}", ), ])
drop_down_list = [ dbc.DropdownMenuItem("First"), dbc.DropdownMenuItem(divider=True), dbc.DropdownMenuItem("Links", header=True), dbc.DropdownMenuItem("Internal link", href="/l/components/alerts"), dbc.DropdownMenuItem("External link", href="https://baidu.com"), dbc.DropdownMenuItem(divider=True), dbc.DropdownMenuItem("Disabled", disabled=True), dbc.DropdownMenuItem("Active", active=True) ] # --------------------------------------------------------------------------------------- email_input = dbc.FormGroup(children=[ dbc.Label("Email", html_for="example-email"), dbc.Input(type="email", id="example-email", placeholder="Enter email"), dbc.FormText("Are you on email? You simply have to be these days", color="secondary"), ]) password_input = dbc.FormGroup(children=[ dbc.Label("Password", html_for="example-password"), dbc.Input(type="password", id="example-password", placeholder="Enter password"), dbc.FormText("A password stops mean people taking your stuff", color="secondary"), ]) # --------------------------------------------------------------------------------------- email_input_row = dbc.FormGroup(children=[ dbc.Label("Email", html_for="example-email-row", width=2), dbc.Col(dbc.Input(type="email", id="example-email-row", placeholder="Enter email"), width=10) ], row=True)
import dash_bootstrap_components as dbc text_input = dbc.FormGroup([ dbc.Label("Text"), dbc.Input(placeholder="Input goes here...", type="text"), dbc.FormText("Type something in the box above"), ])
def find_virus_columns(virus): return [ x for x in df.columns.tolist() if re.compile(r'[SR1|SR2|winter]_P*{virus}V*$'.format( virus=virus)).search(x) ] left_column = dbc.Card([ dbc.FormGroup([ dbc.Label("Season"), dcc.Dropdown( id="season_inspection", options=[{ "label": col, "value": col } for col in ["summer", "winter", "summer and winter"]], value="summer", ), ]), dbc.FormGroup([ dbc.Label("Disease"), dcc.Dropdown( id="disease_type", options=[{ "label": col, "value": col } for col in ["MOS", "LR", "MIX", "ST", "BRR"]], value="LR", ),
def get_app(server=None): if server: app = dash.Dash(__name__, server=server, url_base_pathname='/overfitting_class/', external_stylesheets=[dbc.themes.BOOTSTRAP]) else: app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP]) app.title = "โมเดลสำหรับจำแนกที่เฉพาะเจาะจง/ง่ายเกินไป" ## data = load_breast_cancer() X = data['data'][:, :2] y = data['target'] fn = ['รัศมีเฉลี่ย', 'ความขรุขระ'] cn = ['มะเร็ง/เนื้อร้าย', 'เนื้องอก'] x_train, x_test, y_train, y_test = train_test_split(X, y, test_size=0.4, random_state=42) plot_step = 0.1 x_min, x_max = x_train[:, 0].min() - 1, x_train[:, 0].max() + 1 y_min, y_max = x_train[:, 1].min() - 1, x_train[:, 1].max() + 1 xx, yy = np.meshgrid(np.arange(x_min, x_max, plot_step), np.arange(y_min, y_max, plot_step)) # train_acc = [] # test_acc = [] # for i in range(1,16): # clf = tree.DecisionTreeClassifier(max_depth=i) # clf = clf.fit(x_train, y_train) # acc_tr = accuracy_score(y_train, clf.predict(x_train)) # acc_te = accuracy_score(y_test, clf.predict(x_test)) # train_acc.append(acc_tr) # test_acc.append(acc_te) def get_fig(depth=4): clf = tree.DecisionTreeClassifier(max_depth=depth) clf = clf.fit(x_train, y_train) acc_tr = accuracy_score(y_train, clf.predict(x_train)) acc_te = accuracy_score(y_test, clf.predict(x_test)) Z = clf.predict(np.c_[xx.ravel(), yy.ravel()]) Z = Z.reshape(xx.shape) fig = go.Figure( data=go.Heatmap( z=Z, x=np.arange(x_min, x_max, plot_step), y=np.arange(y_min, y_max, plot_step), colorscale=[[0, '#ef553b'], [1, '#636efa']], opacity=0.2, colorbar=dict(), showscale=False # colorbar=dict(nticks=10, ticks='outside', # ticklen=5, tickwidth=1, # showticklabels=True, # tickangle=0, tickfont_size=12) ), layout=go.Layout( uirevision=True, margin=dict(b=0, l=0, r=0, t=40), xaxis=dict(range=[x_min, x_max]), xaxis_title=fn[0], yaxis=dict(range=[y_min, y_max]), yaxis_title=fn[1], )) colors = ['239, 85, 59', '99, 110, 250'] symbols = ['circle', 'square'] for i, (color, symbol) in enumerate(zip(colors, symbols)): idx = np.where(y_train == i) fig.add_trace( go.Scatter( x=x_train[idx, 0].squeeze(), y=x_train[idx, 1].squeeze(), mode='markers', name=cn[i] + ' train', marker_color='rgb(' + color + ')', )) # for i, color in enumerate(colors): # idx = np.where(y_train == i) # fig.add_trace(go.Scatter(x=x_train[idx, 0].squeeze(), y=x_train[idx, 1].squeeze(), # mode='markers', # name=data.target_names[i], # marker_color=color, # opacity=0.8)) for i, color in enumerate(colors): idx = np.where(y_test == i) fig.add_trace( go.Scatter(x=x_test[idx, 0].squeeze(), y=x_test[idx, 1].squeeze(), mode='markers', name=cn[i] + ' test', marker_color='rgba(' + color + ', 0.4)', marker_line_color='rgba(' + color + ', 1.0)', marker_line_width=1)) # fig.add_trace(go.Scatter(x=x_test[idx, 0].squeeze(), y=x_test[idx, 1].squeeze(), # mode='markers', # name=data.target_names[i] + ' test', # marker_color=color, # opacity=0.3)) return fig, acc_tr, acc_te fig, acc_tr, acc_te = get_fig() depth_marks = {i: '' for i in range(1, 11)} depth_marks[1] = '1' depth_marks[10] = '10' controls = dbc.Card( [ dbc.FormGroup([ html.H5([ "Max Depth ", dbc.Badge("4", className="ml-1", color="primary", id='depth-label') ]), dcc.Slider(id='depth-slider-id', min=1, max=10, step=None, marks=depth_marks, value=4), ]), html.Div([ html.H5([" ความแม่นยำ "]), html.H6([ " ความแม่นยำ บน training data = ", dbc.Badge(f'{acc_tr:.3f}', className="ml-1", color="success", id='accuracy-train-id') ]), html.H6([ " ความแม่นยำ บน test data = ", dbc.Badge(f'{acc_te:.3f}', className="ml-1", color="danger", id='accuracy-test-id') ]), ]) ], body=True, ) ## Main layout app.layout = dbc.Container( [ html. H1("โมเดลที่เฉพาะเจาะจงเกินไป VS โมเดลที่ง่ายเกินไป (Overfitting/Underfitting in Classification)" ), html.Div(children=''' ในแบบฝึกหัดนี้ ให้นักเรียนลองเปลี่ยนค่าตัวแปร depth ของ Decision Tree แล้วดูว่าเมื่อใดก่อให้เกิดโมเดลที่เฉพาะเจาะจงเกินไป (overfitting) และ โมเดลที่ง่ายเกินไป (underfitting) โดยการวาดกราฟเส้นระหว่างความแม่นยำกับค่าตัวแปร depth ของ Decision Tree ของทั้ง training data และ test data '''), html.Hr(), dbc.Row( [ dbc.Col(controls, md=4), dbc.Col(dcc.Graph(id="graph-id", figure=fig), md=8), ], align="center", ), ], fluid=True, ) # app.layout = html.Div([ # html.H1(children='Overfitting/Underfitting in Classification'), # html.Div(children=''' # ในแบบฝึกหัดนี้ ให้นักเรียนลองเปลี่ยนค่า hyperparamter depth ของ Decision Tree แล้วดูว่าเมื่อใดเกิด overfitting/underfitting # '''), # html.Div(children=[ # # dcc.Markdown('### ชุดข้อมูล'), # # dcc.Dropdown( # # options=[ # # {'label': 'มะเร็งเต้านม', 'value': 'breast_cancer'}, # # ], # # value='breast_cancer' # # ), # dcc.Markdown('### Max Depth'), # dcc.Slider( # id='depth-slider-id', # min=1, # max=16, # marks={i: '{}'.format(i) for i in [1, 4, 7, 10, 13, 16]}, # value=4, # ), # dcc.Graph(figure=go.Figure([go.Scatter(x=list(range(1,16)), y=train_acc, mode='markers', name="Train"), # go.Scatter(x=list(range(1,16)), y=test_acc, mode='lines+markers', name="Test")], # layout=go.Layout( # title='ข้อมูลที่ใช้ Train โมเดล', # xaxis=dict(range=[0, 17]), # xaxis_title='Depth', # yaxis=dict(range=[0, 1.1]), # yaxis_title='Accuracy', # ))) # ], # style={'width': '40%', 'display': 'inline-block', 'vertical-align': 'top'} # ), # html.Div(children=[ # dcc.Graph(id='graph-id', figure=fig), # html.Div([ # html.Div(id='accuracy-train-id', children=f'Train Accuracy = {acc_tr:.3f}'), # html.Div(id='accuracy-test-id', children=f'Test Accuracy = {acc_te:.3f}') # ], # style={'textAlign': 'center'} # ) # ], # style={'width': '50%', 'display': 'inline-block'} # ) # ]) @app.callback([ Output(component_id='depth-label', component_property='children'), Output(component_id='graph-id', component_property='figure'), Output(component_id='accuracy-train-id', component_property='children'), Output(component_id='accuracy-test-id', component_property='children') ], [Input(component_id='depth-slider-id', component_property='value')]) def update_under_div(depth): fig, acc_tr, acc_te = get_fig(depth) return [f'{depth}', fig, f'{acc_tr:.3f}', f'{acc_te:.3f}'] return app
app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP ]) # https://bootswatch.com/default/ modal = html.Div([ dbc.Button("Add comment", id="open"), dbc.Modal( [ dbc.ModalHeader("All About Berlin"), dbc.ModalBody( dbc.Form( [ dbc.FormGroup( [ dbc.Label("Name", className="mr-2"), dbc.Input(type="text", placeholder="Enter your name"), ], className="mr-3", ), dbc.FormGroup( [ dbc.Label("Email", className="mr-2"), dbc.Input(type="email", placeholder="Enter email"), ], className="mr-3", ), dbc.FormGroup( [ dbc.Label("Comment", className="mr-2"), dbc.Input(type="text",
'https://codepen.io/chriddyp/pen/bWLwgP.css', { 'href': 'https://stackpath.bootstrapcdn.com/bootstrap/4.1.3/css/bootstrap.min.css', 'rel': 'stylesheet', 'integrity': 'sha384-MCw98/SFnGE8fJT3GXwEOngsV7Zt27NXFoaoApmYm81iuXoPkFOJwJ8ERdknLPMO', 'crossorigin': 'anonymous' } ] email_input = html.Div([ dbc.FormGroup([ dbc.Label("Email"), dbc.Input(id="email-input", type="email", value=""), dbc.FormText("We only accept gmail..."), dbc.FormFeedback("That looks like a gmail address :-)", valid=True), dbc.FormFeedback( "Sorry, we only accept gmail for some reason...", valid=False, ), ]) ]) form = dbc.Form( [ dbc.FormGroup( [ dbc.Label("Email", className="mr-2"), dbc.Input(type="email", placeholder="Enter email"), ], className="mr-3", ),
controls1 = dbc.FormGroup([ html.P('Modelos de Regresión', style=CARD_TEXT_STYLE), dcc.Dropdown( id='dropdown', options=[{ 'label': 'Modelo Regresión', 'value': 'Modelo Regresion' }, { 'label': 'Modelo Ridge', 'value': 'Modelo Ridge' }, { 'label': 'Modelo Lasso', 'value': 'Modelo Lasso' }, { 'label': 'Modelo Huber', 'value': 'Modelo Huber' }, { 'label': 'Resultado Real', 'value': 'Real' }], value=['Modelo Regresion', 'Real'], # default value multi=True), html.Br(), html.P('Cantidad de Cajas Unitarias', style=CARD_TEXT_STYLE), dcc.RangeSlider(id='range_slider', min=mincuota, max=maxcuota, step=stepcuota, value=[mincuota, maxcuota], marks={ mincuota: str(mincuota), quartil1: str(quartil1), quartil2: str(quartil2), quartil3: str(quartil3), maxcuota: str(maxcuota) }), html.Br(), html.P('Gastos logísticos', style=CARD_TEXT_STYLE), dbc.Input(id="input_gastos", placeholder="Gastos Logísticos", type="number", value=400000), html.Br(), dbc.Button(id='submit_button', n_clicks=0, children='Actualizar', color='primary', block=True) ])
} for i in range(10)]) mdf = pd.DataFrame([{'----': "Upload a Metadata File"}]) upload_file_name = "" db_engine = None table_obj = None entity_names = ['Connect to a db first'] pill_button = {'border-radius': '40px'} # Defining fields for db connections hostname_input = dbc.FormGroup( [ dbc.Label("Hostname", width=2), dbc.Col( dbc.Input(id="db-field-1", type="email", placeholder="Enter host connection information"), width=10, ), ], row=True, ) user_input = dbc.FormGroup( [ dbc.Label("User", html_for="example-email-row", width=2), dbc.Col( dbc.Input( id="db-field-2", type="User", placeholder="Enter User Name"), width=10, ), ], row=True,
table_placeholder = dash_table.DataTable(id='table', style_as_list_view=True, page_size=20) ### CREATE POPUP ### create_button = dbc.Button("Create", id='create-button', color='info') MODAL_CREATE_BUTTON_STYLE = {'className': "mr-2", 'color': 'primary'} MODAL_CLOSE_BUTTON_STYLE = {'className': "mr-2", 'color': 'secondary'} create_account_name_input = dbc.FormGroup([ dbc.Label("Name"), dbc.Input(id='create-account-name-input', placeholder='Name', type='text', debounce=True) ], ) create_account_description_input = dbc.FormGroup([ dbc.Label("Description"), dbc.Input(id='create-account-description-input', placeholder='Description') ]) create_account_label_dropdown = dbc.FormGroup([ dbc.Label("Label"), dcc.Dropdown(id='create-account-label-dropdown', placeholder='Label', options=labels_options) ])
trust_name = dat_t['Var1'].values TRUST_OPTIONS = [] for i in range(len(trust_name)): d = { 'label': trust_name[i], 'value': trust_name[i] } TRUST_OPTIONS.append(d) TRUST_VALUES = 'NATIONAL' trust_select = dbc.FormGroup( [ dbc.Label("Select NHS Trust", html_for='trust'), dcc.Dropdown( id='trust', options=TRUST_OPTIONS, value=TRUST_VALUES, multi=False, ) ] ) date_range_picker = dbc.FormGroup( [ dbc.Label("Select Hospital Admission Dates", html_for='date_range'), dcc.DatePickerRange( id='date_range', min_date_allowed=dt(2020, 3, 10), max_date_allowed=dt(2020, 12, 31), initial_visible_month=dt(2020, 3, 5), start_date=dt(2020, 3, 10).date(),
] ) title = 'COVID Projections Tracker' app.title = title server = app.server #controls - adapted from https://dash-bootstrap-components.opensource.faculty.ai/examples/iris/ controls = dbc.Card( [ html.H4("Filters", className="card-title"), dbc.FormGroup( [ dbc.Label("Model"), dcc.Dropdown( id="model-dropdown", options=[ {"label": col, "value": col} for col in ['IHME'] ], value="IHME", ), ] ), dbc.FormGroup( [ dbc.Label("Location"), dcc.Dropdown( id="location-dropdown", options=[ {"label": col, "value": col} for col in df.location_name.unique() ], value="United States of America", ),
# Number of maximum loans loan_num = 3 loanNum = dbc.FormGroup([ dbc.Label("Please choose the number of loans in your loan portfolio", size='lg', color='black-50'), dbc.RadioItems( options=[ { "label": "1", "value": 1 }, { "label": "2", "value": 2 }, { "label": "3", "value": 3 }, ], value=1, id="loanNum-input", inline=True, style={'margin-left': '2px'}, ) ]) # Create loan table loan_table_df = main.compute_schedule(1.0, 1.0, 1.0, 1.0)
# Switch to cuda if available model.to(device) model.eval() # Define app app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP]) server = app.server controls = dbc.Card( [ dbc.FormGroup([ dbc.Label("Output Length (# Tokens)"), dcc.Slider( id="max-length", min=10, max=50, value=30, marks={i: str(i) for i in range(10, 51, 10)}, ), ]), dbc.FormGroup([ dbc.Label("Beam Size"), dcc.Slider( id="num-beams", min=2, max=6, value=4, marks={i: str(i) for i in [2, 4, 6]}, ),
'width': '100%', } controls = dbc.FormGroup( [ dcc.Dropdown( id='patchSize', options=[{ 'label': '99 X 99', 'value': 99 }, { 'label': '49 X 49', 'value': 49 } ], placeholder='Patch size' ), html.Br(), dbc.Button( id='submit_button', n_clicks=0, children='Train', color='primary', block=True ), ] ) # for parameter content sidebar = html.Div( [
align="center", no_gutters=True, ), ], sticky="top", ) # left side grouping of selction options form_card_group = dbc.Card( [ dbc.FormGroup([ dbc.Label("Choose a Stock Symbol"), dcc.Dropdown( id="stock-ticker-select", options=[{ "label": ticker, "value": ticker, } for ticker in tickers], multi=True, value=[tickers[0]], ), ]), dbc.FormGroup([ dbc.Label("Price"), dbc.Col( dbc.RadioItems( id="stock-ticker-price", options=[ { "label": "Open", "value": "open", },
def render_page_content(pathname): # 최초경로 출력 if pathname == '/': return [dbc.Jumbotron(['###안녕하세요###'])] # 페이지1 출력 elif pathname == '/page-1': return [ html.H1('카테고리별 평균 목표금액', style={'textAlign': 'center'}), multiple_input ] # 페이지2 출력 elif pathname == '/page-2': return [ html.H1('Grad School in Iran', style={'textAlign': 'center'}), dcc.Graph(year_df, id='bar-graph', x='funding_amounts', y="target_amounts") ] # 페이지3 출력 elif pathname == '/page-3': return [ html.Div([ dcc.Input(id='username', value='Initial Value', type='text'), html.Button(id='submit-button', type='submit', children='Submit'), html.Div(id='output_div') ]) ] # 페이지4 출력 elif pathname == '/dataframe': return [ html.Div([ dbc.Button('Download CSV', id='btn_csv', color='primary', style={'margin': '1rem'}), dcc.Download(id='download-dataframe-csv'), dbc.Table(generate_table(df, 5), bordered=True, dark=True, hover=True, responsive=True, striped=True), ]) ] elif pathname == '/system': # cate = str(request.form['cateinput']) types = ['text'] return [ html.Div([ dbc.FormGroup([ dbc.Input(id=f'my_{x}', value='립밤', placeholder='Enter category', type=f'{x}') for x in types ]), dbc.Table(id='update-dataframe') ]) ] # dbc.FormGroup([ # dbc.Label('카테고리 입력', html_for='cate-input'), # dbc.Input(id=f'my_{x}', value='립밤', placeholder='Enter category', type=f'{x}') for x in types, # dbc.FormText('카테고리를 입력하세요', color='secondary') # ]), else: # 에러메세지 출력 return dbc.Jumbotron([ html.H1('404:not found', className='text-danger'), html.Hr(), html.P(f'The pathname {pathname} was not recognised..') ])
dbc.Row( dbc.Col(html.H1(children='Your Ideal Zodiac Partner'), width = {'offset': 2}) ), dbc.Row( dbc.Col(html.Div(children='''Take this quiz and find out about your ideal life partner.'''), width = {'offset': 2}) ), html.Br(), html.Br(), dbc.Row([dbc.Col([ dbc.Form([ dbc.FormGroup([ dbc.Label('Name?'), dbc.Input(id="name", placeholder = 'Type here', type = 'text', style = {'width': '80%'}), ]), dbc.FormGroup([ dbc.Label("What's your Zodiac sign?", html_for = 'dropdown'), dcc.Dropdown( options=[ {'label': 'Aquarius (January 20 - February 18)', 'value': 'Aquarius'}, {'label': 'Pisces (February 19 - March 20)', 'value': 'Pisces'}, {'label': 'Aries (March 21 - April 19)', 'value': 'Aries'}, {'label': 'Taurus (April 20 - May 20)', 'value': 'Taurus'}, {'label': 'Gemini (May 21 - June 20)', 'value': 'Gemini'}, {'label': 'Cancer (June 21 - July 22)', 'value': 'Cancer'}, {'label': 'Leo (July 23 - August 22)', 'value': 'Leo'}, {'label': 'Virgo (August 23 - September 22)', 'value': 'Virgo'}, {'label': 'Libra (September 23 - October 22)', 'value': 'Libra'},
server = Flask(__name__) app = dash.Dash(server=server, external_stylesheets=external_stylesheets) controls = dbc.Card( [ dbc.FormGroup( [ dbc.Label("Select Stock"), dcc.Dropdown( id="my-dropdown", options=[ # {'label': 'Google', 'value': 'GOOGL'}, # {'label': 'Tata Motors', 'value': 'TATAMOTORS'}, {'label': 'Reliance', 'value': 'RELIANCE'}, {'label': 'Indigo', 'value': 'INDIGO'}, {'label': 'Infosys', 'value': 'INFY'}, {'label': 'IRCTC', 'value': 'IRCTC'}, {'label': 'Aurobindo Pharma', 'value': 'AUROPHARMA'}, # {'label': 'AT&T Inc.', 'value': 'T'} ], value='RELIANCE', ), html.Br(), ] ), ], body=True, )
dash_app = Dash( __name__, server=app, external_stylesheets=[dbc.themes.DARKLY], # routes_pathname_prefix='/dash_app/', url_base_pathname='/dash_app/') covid_df = pd.read_csv('./src/static/owid-covid-data.csv') data_input = dbc.FormGroup([ dbc.Label('Select data', html_for='dropdown'), dcc.Dropdown(id='data_dropdown', options=[{ 'label': 'COVID-19 Dataset', 'value': 'covid' }, { 'label': 'Upload your own', 'value': 'upload' }], value='covid', style={'color': 'rgb(230, 230, 230)'}) ]) plotly_input = dbc.FormGroup([ dbc.Label('Plot Type'), dcc.Dropdown(id='type_dropdown', options=[{ 'label': 'line', 'value': 'line' }, { 'label': 'scatter',
DF = pd.read_csv('./data/unc.csv') YEARS_DF = DF['Año'].unique() TIPOS_DE_DELITO = DF['Tipo de delito'].unique() with open('./geo/mexico.geojson') as f: STATES = json.load(f) app.layout = html.Div([ dbc.FormGroup( [ dbc.Label("Tipo de delito"), dcc.Dropdown( id="in-delito", value=TIPOS_DE_DELITO[0], options=[ {"label": col, "value": col} for col in DF['Tipo de delito'].unique() ] ), ] ), dcc.Slider( id='in-year-slider', min=0, max=len(YEARS_DF), marks={i: str(YEARS_DF[i]) for i in range(len(YEARS_DF))}, value=0, ), dcc.Graph(id="delito-map")
# dict with quarters as values used for slider d = dict(zip(range(0, 9), adj.keys())) d = {int(k): v for k, v in d.items()} # list for centrality measures used for dropdown ls_centrality = ['degree', 'betweenness', 'closeness', 'eigenvector', 'mean'] BS = "https://stackpath.bootstrapcdn.com/bootstrap/4.4.1/css/bootstrap.min.css" app = dash.Dash(__name__, external_stylesheets=[BS]) control_centrality = dbc.Card([ dbc.FormGroup([ dbc.Label("Node definition:"), dcc.Dropdown(id="centrality", options=[{ "label": i, "value": i } for i in ls_centrality], value="degree"), ]), ]) control_quarter = dbc.Card([ dbc.Label("Quarter:"), dcc.Slider( id="quarter", min=0, max=9, step=None, marks=d, value=0, )
def init_regression(server): options = [ 'year', 'ratings_count', 'labels_count', 'reviews_count', 'is_natural', 'winery_ratings_count', 'winery_ratings_average', 'winery_labels_count', 'winery_wines_count', 'users_count', 'regions_count', 'wines_count', 'wineries_count', 'median_price', 'bold', 'tannic', 'sweet', 'oaky', 'black fruit', 'red fruit', 'earthy', 'spices', 'ageing', 'yeasty', 'dried fruit', 'citrus', 'tree fruit', 'vegetal', 'floral', 'tropical', 'beef', 'lamb', 'veal', 'poultry', 'pork', 'shellfish', 'vegetarian', 'game', 'spicy-food', 'types' ] #Mangler total flavors dict_options = [ 'year', 'ratings_count', 'labels_count', 'reviews_count', 'is_natural', 'winery_ratings_count', 'winery_ratings_average', 'winery_labels_count', 'winery_wines_count', 'users_count', 'regions_count', 'wines_count', 'wineries_count', 'median_price', 'bold', 'tannic', 'sweet', 'oaky', 'black fruit', 'red fruit', 'earthy', 'spices', 'ageing', 'yeasty', 'dried fruit', 'citrus', 'tree fruit', 'vegetal', 'floral', 'types', 'foods' ] #Mangler total flavors TASTES = [ 'tropical', 'beef', 'lamb', 'veal', 'poultry', 'pork', 'shellfish', 'vegetarian', 'game', 'spicy-food' ] UPPER_WIDTH = 1 UPPER_TEXT_WIDTH = 6 SUBSECTION_WIDTHS = '13%' predictor_app = Dash( server=server, title='Beyond The Grape Predictor', update_title=None, routes_pathname_prefix='/predict/', external_stylesheets=[dbc.themes.BOOTSTRAP, 'styles.css'], external_scripts=[dbc.themes.BOOTSTRAP, 'styles.css']) pipeline = load("app/static/models/xbg_wine_model.joblib") foods = dbc.FormGroup( [ dbc.Label("Foods", html_for="food-checklist-row", width=2), dbc.Col( dcc.Checklist(options=[{ 'label': 'Beef', 'value': 'beef' }, { 'label': 'Chicken', 'value': 'chicken' }, { 'label': 'Pork', 'value': 'pork' }, { 'label': 'Lamb', 'value': 'lamb' }, { 'label': 'Veal', 'value': 'veal' }, { 'label': 'Poultry', 'value': 'poultry' }, { 'label': 'Shellfish', 'value': 'shellfish' }, { 'label': 'Vegetarian', 'value': 'vegetarian' }, { 'label': 'Game', 'value': 'game' }, { 'label': 'Spicy food', 'value': 'spicy-food' }, { 'label': 'Tropical', 'value': 'tropical' }], value=['beef', 'chicken', 'pork'], id='food-checklist-row', labelStyle={ 'display': 'inline-block', 'margin': '5px' }), width=7, ), ], row=True, ) types = dbc.FormGroup( [ dbc.Label("Wine type", html_for="types", width=2), dbc.Col( dcc.RadioItems(options=[ { 'label': 'Red', 'value': 'red' }, { 'label': 'White', 'value': 'white' }, ], value='red', id='types', labelStyle={ 'display': 'inline-block', 'margin': '5px' }), width=7, ), ], row=True, ) # ---------------------------------------------------- Mapping ---------------------------------------------------- predictor_app.layout = html.Div( [ html.Section([ html.Div([ html.H1('Beyond The Grape rating predictor', className='mx-auto my-0 text-uppercase', style={ 'text-align': 'center', 'color': 'darkslategrey' }) ], style={'margin': '3%'}), html.Div( [ # ---------------------------------------------------- Section 1 ---------------------------------------------------- dbc.Form([foods, types]), html.Div( [ dbc.Form( [ numeric_form_group( 'year', 'Year', UPPER_TEXT_WIDTH, UPPER_WIDTH, 2002, 1960, 2020, 1), numeric_form_group( 'median_price', 'Price', UPPER_TEXT_WIDTH, UPPER_WIDTH, 550, 50, 6000, 50), numeric_form_group('ratings_count', '# Ratings', UPPER_TEXT_WIDTH, UPPER_WIDTH, 2000, 0, step=100), numeric_form_group('labels_count', '# Labels', UPPER_TEXT_WIDTH, UPPER_WIDTH, 20, 1, step=1), numeric_form_group('reviews_count', '# Reviews', UPPER_TEXT_WIDTH, UPPER_WIDTH, 1000, 0, step=50) ], style={ 'float': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), # ---------------------------------------------------- Section 2 ---------------------------------------------------- dbc.Form( [ numeric_form_group( 'tannic', 'Tannic', UPPER_TEXT_WIDTH, UPPER_WIDTH, 30, 0, 100, 1), numeric_form_group( 'sweet', 'Sweet', UPPER_TEXT_WIDTH, UPPER_WIDTH, 30, 0, 100, 1), numeric_form_group( 'bold', 'Bold', UPPER_TEXT_WIDTH, UPPER_WIDTH, 30, 0, 100, 1), numeric_form_group( 'black fruit', 'Black Fruit', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'red fruit', 'Red Fruit', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), ], style={ 'float': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), # ---------------------------------------------------- Section 3 ---------------------------------------------------- dbc.Form( [ numeric_form_group( 'earthy', 'Earthy', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'is_natural', 'Is Natural', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0, 0, 1, 1), numeric_form_group( 'winery_ratings_count', '# Winery Ratings', UPPER_TEXT_WIDTH, UPPER_WIDTH, 1000, 0, step=100), numeric_form_group( 'winery_ratings_average', 'winery_ratings_average', UPPER_TEXT_WIDTH, UPPER_WIDTH, 4, 0, 5, 0.1), numeric_form_group( 'winery_labels_count', '# winery Labels', UPPER_TEXT_WIDTH, UPPER_WIDTH, 20, 0, 10000, 10), ], style={ 'float': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), # ---------------------------------------------------- Section 4 ---------------------------------------------------- dbc.Form( [ numeric_form_group( 'winery_wines_count', '#Winery Wines', UPPER_TEXT_WIDTH, UPPER_WIDTH, 20, 0, 10000, 10), numeric_form_group('users_count', '# Users', UPPER_TEXT_WIDTH, UPPER_WIDTH, 600, 0, step=100), numeric_form_group('regions_count', '# Regions', UPPER_TEXT_WIDTH, UPPER_WIDTH, 7, 0, step=1), numeric_form_group('wines_count', 'Wines count', UPPER_TEXT_WIDTH, UPPER_WIDTH, 40, 0, step=10), numeric_form_group('wineries_count', 'Wineries count', UPPER_TEXT_WIDTH, UPPER_WIDTH, 80, 0, step=10) ], style={ 'float': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), # ---------------------------------------------------- Section 5 ---------------------------------------------------- dbc.Form( [ numeric_form_group( 'oaky', 'Oaky', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'spices', 'Spices', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'ageing', 'Ageing', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'yeasty', 'Yeasty', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'dried fruit', 'Dried Fruit', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1) ], style={ 'float': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), # ---------------------------------------------------- Section 6 ---------------------------------------------------- dbc.Form( [ numeric_form_group( 'citrus', 'Citrus', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'tree fruit', 'Tree Fruit', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'vegetal', 'Vegetal', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1), numeric_form_group( 'floral', 'Floral', UPPER_TEXT_WIDTH, UPPER_WIDTH, 0.2, 0, 1, 0.1) ], style={ 'text-align': 'left', 'margin': '1%', 'width': SUBSECTION_WIDTHS }), ], style={ 'display': 'flex', 'justify-content': 'center' }), ], style={'text-align': 'center'}), html.Div([html.P('')], style={'margin': '5%'}), ]), html.H2(' '), html.H2(id="output_pred", className="predictions_container", style={ 'text-align': 'center', 'margin': '150px', 'color': 'darkslategrey' }), ], style={ 'background-image': 'url("assets/background.jpg")', 'height': '100vh', 'background-size': 'cover' }) #Init callback of input fields @predictor_app.callback( dash.dependencies.Output('output_pred', 'children'), [ #dash.dependencies.Input('submit_button', 'n_clicks'), dash.dependencies.Input('year', 'value'), dash.dependencies.Input('ratings_count', 'value'), dash.dependencies.Input('labels_count', 'value'), dash.dependencies.Input('reviews_count', 'value'), dash.dependencies.Input('is_natural', 'value'), dash.dependencies.Input('winery_ratings_count', 'value'), dash.dependencies.Input('winery_ratings_average', 'value'), dash.dependencies.Input('winery_labels_count', 'value'), dash.dependencies.Input('winery_wines_count', 'value'), dash.dependencies.Input('users_count', 'value'), dash.dependencies.Input('regions_count', 'value'), dash.dependencies.Input('wines_count', 'value'), dash.dependencies.Input('wineries_count', 'value'), dash.dependencies.Input('median_price', 'value'), dash.dependencies.Input('bold', 'value'), dash.dependencies.Input('tannic', 'value'), dash.dependencies.Input('sweet', 'value'), dash.dependencies.Input('oaky', 'value'), dash.dependencies.Input('black fruit', 'value'), dash.dependencies.Input('red fruit', 'value'), dash.dependencies.Input('earthy', 'value'), dash.dependencies.Input('spices', 'value'), dash.dependencies.Input('ageing', 'value'), dash.dependencies.Input('yeasty', 'value'), dash.dependencies.Input('dried fruit', 'value'), dash.dependencies.Input('citrus', 'value'), dash.dependencies.Input('tree fruit', 'value'), dash.dependencies.Input('vegetal', 'value'), dash.dependencies.Input('floral', 'value'), dash.dependencies.Input('types', 'value'), dash.dependencies.Input('food-checklist-row', 'value'), ]) def calculate_rating(*args): #Establish dataframe input d = pd.DataFrame() for o, i in zip(dict_options, args): d[o] = [i] for taste in TASTES: d[taste] = 1 if taste in list(d['foods'][0]) else 0 d['types'] = 1 if 'red' in list(d['types'][0]) else 0 del d['foods'] #Ordring columns to fit XGB model d = d[[ 'year', 'ratings_count', 'labels_count', 'reviews_count', 'is_natural', 'winery_ratings_count', 'winery_ratings_average', 'winery_labels_count', 'winery_wines_count', 'users_count', 'regions_count', 'wines_count', 'wineries_count', 'median_price', 'bold', 'tannic', 'sweet', 'oaky', 'black fruit', 'red fruit', 'earthy', 'spices', 'ageing', 'yeasty', 'dried fruit', 'citrus', 'tree fruit', 'vegetal', 'floral', 'tropical', 'beef', 'lamb', 'veal', 'poultry', 'pork', 'shellfish', 'vegetarian', 'game', 'spicy-food', 'types' ]] print(d) #Used for decomposition and debugging predictions = pipeline.predict(d)[0] return 'Predicted rating {}'.format(round(float(predictions), 3)) return predictor_app.server
}), ), dbc.Row([ dbc.FormGroup([ dbc.RadioItems(options=[ { 'label': 'All Departures', 'value': 'Total Rate' }, { 'label': 'Layoffs', 'value': 'Layoff Rate' }, { 'label': 'Resignation', 'value': 'Resignation Rate' }, { 'label': 'Retirement', 'value': 'Retirement Rate' }, { 'label': 'Voluntary', 'value': 'Voluntary Rate' }, ], value='Total Rate', id='departure-input', inline=True), ]) ], style={'margin': '0px 0px 0px 0px'})