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'})
