def options_layout(self, inital_args_kwargs):
options = html.Div([
html.Div([
Label("Rotation axis"),
dcc.Input(
value="[1, 0, 0]",
id=self.id("gb_rotation_axis"),
type="text",
className="input",
),
]),
html.Br(),
html.Div([
Label("Choose Σ"),
dcc.Dropdown(
id=self.id("gb_sigma_options"),
options=[],
placeholder="...",
),
]),
html.Br(),
html.Div([
Label("Choose rotation angle"),
dcc.Dropdown(
id=self.id("gb_rotation_options"),
options=[],
placeholder="...",
),
]),
html.Br(),
html.Div([
Label("Grain width"),
dcc.Slider(
id=self.id("gb_expand_times"),
min=1,
max=6,
step=1,
value=2,
marks={
2: "2",
4: "4",
6: "6"
},
),
]),
html.Br(),
html.Div([
Label("Distance between grains in Å"),
dcc.Input(
value="0.0",
id=self.id("gb_vacuum_thickness"),
type="text",
className="input",
),
]),
html.Br(),
html.Div([
Label("Plane"),
dcc.Input(
value="None",
id=self.id("gb_plane"),
type="text",
className="input",
),
]),
])
return options
url = "https://api.weatherbit.io/v2.0/current"
api_key = ""
app = dash.Dash(__name__)
server = app.server
app.layout = html.Div([
html.Div([
html.H1("Прогноз погоды"),
html.Br()
],className='header'),
html.Div([
html.H4("Меня интересует погода в:"),
dcc.Input(id="city-input", value="Москва", type="text"),
html.Button(id='submit-button', n_clicks=0, children='Submit'),
html.Br()
], className='user-input'),
html.Div([
html.Div([
html.Img(id='weather-icon'),
html.Div(id="weather-description")
], className='grid-item'),
html.Div([
html.Img(src=app.get_asset_url("thermometer.png")),
html.Div(id="temperature")
], className='grid-item'),
html.Div([
html.Img(src=app.get_asset_url("humidity.png")),
),
html.
H3('Weapon stats were pulled from in game menus and use a python based computer vision script to determine the +/- of attachments'
),
html.
H3('Data is compiled and charted out for you to min/max everything.'
),
html.Br(),
html.H3('Good Hunting'),
html.Br(),
html.Hr(),
html.Br(),
html.H2("WHAT'S YOUR GAMERTAG?"),
dcc.Input(
id="gamertag",
type='text',
value='John Wick',
style={'textAlign': 'center'},
),
html.Br(),
html.Br(),
html.H2("NAME YOUR BUILD"),
dcc.Input(
id="guncode",
type='text',
value='YeetCannon5000',
style={'textAlign': 'center'},
),
html.Br(),
html.Br(),
html.Div(style={
'textAlign': 'center',
html.H1("Find TeeTimes", className="display-3"),
html.P(
"View all available TeeTimes - For Golfbroes",
className="lead",
),
],
fluid=True,
),
],
fluid=True,
style={'margin-bottom': '0px'},
className="mb-3"),
dbc.Row([
dbc.Col(
dcc.Input(id="Username",
type='text',
placeholder="Username",
className="mb-3"), ),
dbc.Col([
dcc.Input(id="Password",
type='password',
placeholder="Password",
className="mb-3"),
]),
dbc.Col([
dcc.DatePickerSingle(id='date-picker',
min_date_allowed=TODAYS_DATE,
max_date_allowed=MAX_DATE,
initial_visible_month=TODAYS_DATE,
date=TODAYS_DATE,
display_format='DD/MM/YYYY',
className="mb-3"),
def create_app_ui():
# Create the UI of the Webpage here
main_layout = html.Div(
style={
#'textAlign':'center',
'backgroundColor': '#F9E79F'
#'background-image': 'url(https://cdn.pixabay.com/photo/2016/11/29/01/13/background-1866485_1280.jpg)'
},
children=[
html.H1('Terrorism Analysis with Insights',
id='Main_title',
style={
'textAlign': 'center',
'backgroundColor': '#D1F2EB',
}),
html.H4('by Prateek Paul',
id='Sub_title',
style={'textAlign': 'center'}),
dcc.Tabs(
id="Tabs",
value="Map",
style={
'font-weight': 'bold',
},
children=[
dcc.Tab(
label="Map tool",
id="Map tool",
value="Map",
children=[
dcc.Tabs(id="subtabs",
value="WorldMap",
children=[
dcc.Tab(
label="World Map tool",
id="World",
value="WorldMap",
),
dcc.Tab(label="India Map tool",
id="India",
value="IndiaMap")
],
colors={
"border": "red",
"primary": "gold",
"background": "cornsilk"
}),
html.Br(),
dcc.Dropdown(
id='month',
options=month_list,
placeholder='Select Month',
multi=True,
style={
'width': '600px',
'padding': '10px',
'display': 'inline-block'
},
),
#html.Br(),
dcc.Dropdown(
id='date',
placeholder='Select Day',
multi=True,
style={
'width': '600px',
'padding': '10px',
'display': 'inline-block'
},
),
html.Br(),
dcc.Dropdown(
id='region-dropdown',
options=region_list,
placeholder='Select Region',
multi=True,
style={
'width': '390px',
'padding': '10px',
'display': 'inline-block'
},
),
#html.Br(),
dcc.Dropdown(
id='country-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select Country',
multi=True,
style={
'width': '390px',
'padding': '10px',
'display': 'inline-block'
},
),
#html.Br(),
dcc.Dropdown(
id='state-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select State or Province',
multi=True,
style={
'width': '390px',
'padding': '10px',
'display': 'inline-block'
},
),
html.Br(),
dcc.Dropdown(
id='city-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select City',
multi=True,
style={
'width': '600px',
'padding': '10px',
'display': 'inline-block'
},
),
#html.Br(),
dcc.Dropdown(
id='attacktype-dropdown',
options=
attack_type_list, #[{'label': 'All', 'value': 'All'}],
placeholder='Select Attack Type',
multi=True,
style={
'width': '600px',
'padding': '10px',
'display': 'inline-block'
},
),
html.Br(),
html.H5('Select the Year', id='year_title'),
dcc.RangeSlider(
id='year-slider',
min=min(year_list),
max=max(year_list),
value=[min(year_list),
max(year_list)],
marks=year_dict,
step=None),
html.Br()
]),
dcc.Tab(
label="Chart Tool",
id="chart tool",
value="Chart",
children=[
dcc.Tabs(
id="subtabs2",
value="WorldChart",
children=[
dcc.Tab(
label="World Chart tool",
id="WorldC",
value="WorldChart"), #, children = [
dcc.Tab(label="India Chart tool",
id="IndiaC",
value="IndiaChart")
],
colors={
"border": "red",
"primary": "gold",
"background": "cornsilk"
}),
html.Br(),
html.Br(),
dcc.Dropdown(
id="Chart_Dropdown",
options=chart_dropdown_values,
placeholder="Select option",
value="region_txt",
style={
'width': '90%',
'padding': '5px',
#'display':'inline-block'
},
),
#html.Br(),
#html.Br(),
html.Hr(),
dcc.Input(
id="search",
placeholder="Search Filter",
style={
'width': '60%',
'padding': '10px',
#'display':'inline-block'
},
),
html.Hr(),
html.Br(),
dcc.RangeSlider(
id='cyear_slider',
min=min(year_list),
max=max(year_list),
value=[min(year_list),
max(year_list)],
marks=year_dict,
step=None),
html.Br()
]),
]),
html.Div(id="graph-object", children="Graph will be shown here"),
html.
H6('A Big Thanks to Forsk Coding School for helping and guiding me in this project',
id='End_title',
style={'textAlign': 'center'}),
])
return main_layout
def cross_over_drop_down(input, parents_prob, cross_over_points):
if input is None:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=None),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 0:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=0),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 1:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=1),
html.Span('Probability of which parents'),
dcc.Input(id='parents-probability', value=parents_prob),
html.Span('Number of Points'),
dcc.Input(id='cross-over-points-number', value=cross_over_points),
]
elif input == 2:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=2),
html.Span('Probability of which parents'),
dcc.Input(id='parents-probability', value=parents_prob),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 3:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=3),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 4:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=4),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 5:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=5),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 6:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=6),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 7:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=7),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 8:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=8),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points'),
dcc.Input(id='cross-over-points-number', value=cross_over_points),
]
elif input == 9:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=9),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 10:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=10),
html.Span('Probability of which parents', style={'display': 'None'}),
dcc.Input(id='parents-probability', value=parents_prob, style={'display': 'None'}),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
elif input == 11:
return [
html.Span('Cross over Algorithms'),
dcc.Dropdown(id='cross-over-dropdown',
options=cross_over_options,
value=11),
html.Span('Probability of which parents'),
dcc.Input(id='parents-probability', value=parents_prob),
html.Span('Number of Points', style={'display': 'None'}),
dcc.Input(id='cross-over-points-number', value=cross_over_points, style={'display': 'None'}),
]
)
# external_stylesheets = [dbc.themes.BOOTSTRAP]
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__,
external_stylesheets=external_stylesheets,
url_base_pathname='/nanoexplorer/')
app.config.suppress_callback_exceptions = True
app.layout = html.Div([
html.B("Dataset pattern: "),
dcc.Input(
id="input-pattern",
type="text",
debounce=True,
style={"min-width": "40%"},
value="/TTTT*/*NanoAODv7*/NANOAODSIM",
),
html.Hr(),
html.B("Matching datasets:"),
html.Div(id='table-datasets-container'),
html.Hr(),
html.B("Files:"),
html.Div(id='table-files-container'),
html.Hr(),
html.B("Branches:"),
html.Div(id='table-branches-container'),
html.Div(id="graphs"),
])
dcc.RangeSlider(
marks={i: 'Label {}'.format(i) for i in range(-5, 7)},
min=-5,
max=6,
value=[-3, 4]
)''',
style=styles.code_container),
html.Br(),
dcc.Link('More RangeSlider Examples and Reference',
href=tools.relpath("/dash-core-components/rangeslider")),
html.Hr(),
html.H2(
dcc.Link('Input',
href=tools.relpath('/dash-core-components/input'))),
rc.ComponentBlock('''import dash_core_components as dcc
dcc.Input(
placeholder='Enter a value...',
type='text',
value=''
)''',
style=styles.code_container),
html.Br(),
dcc.Link('More Input Examples and Reference',
href=tools.relpath("/dash-core-components/input")),
html.Hr(),
html.H2(
dcc.Link('Textarea',
href=tools.relpath('/dash-core-components/textarea'))),
rc.ComponentBlock('''import dash_core_components as dcc
'background-color': 'white'
}),
href='http://127.0.0.1:8080/home',
)),
html.Div(
children='Data Visualization',
style={
'color': 'black',
#'border': '2px green solid',
'padding': '20px',
'font-size': 'large',
'textAlign': 'center'
}),
html.P(html.Label('Start Time:')),
dcc.Input(id='start-time-input',
type='datetime-local',
value=dt.strftime(min_date, '%Y-%m-%dT%H:%M'),
className='form-control'),
html.P(html.Label('End Time:')),
dcc.Input(id='end-time-input',
type='datetime-local',
min=dt(1995, 8, 5),
max=dt(2017, 9, 19),
value=dt.strftime(max_date, '%Y-%m-%dT%H:%M'),
className='form-control'),
html.P(html.Button(id='submit-button', n_clicks=0, children='OK')),
html.P(html.Label('Channel selection :')),
dcc.Dropdown(id='drop_id',
options=[{
'label': 'Channel 1',
'value': 'ch1'
}, {
dcc.Graph(id='hashrate-graph', figure={}),
dcc.Graph(
id='revratio-graph',
figure={},
),
# dcc.Graph(
# id='intervals-graph',
# figure={},
# ),
dcc.Graph(
id='conftimes-graph',
figure={},
),
html.Div(id='profits', children=[]),
html.Div(children=(html.H4("Advanced configuration"))),
html.Div(children=(dcc.Input(
id='Seed', value=seed, type="number", name="Randomness seed"),
html.H6("Randomness seed")),
style={'display': 'flex'}),
html.Div(children=(dcc.Input(id='blocks',
value=params['num_blocks'],
type="number",
step=100,
min=100,
max=50000,
required=True,
persistence=True),
html.H6("Number of blocks to simulate")),
style={'display': 'flex'}),
# html.Div(children=(dcc.Input(id='', value=params[''], type="number",
# step=100, min=100, max=50000, required=True, persistence=True),
# -*- coding: utf-8 -*-
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output, State
external_stylesheets = ['https://codepen.io/chriddyp/pen/bWLwgP.css']
app = dash.Dash(__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
dcc.Input(id='input-1-state', type='text', value='Montréal'),
dcc.Input(id='input-2-state', type='text', value='Canada'),
html.Button(id='submit-button-state', n_clicks=0, children='Submit'),
html.Div(id='output-state')
])
@app.callback(
Output('output-state',
'children'), [Input('submit-button-state', 'n_clicks')],
[State('input-1-state', 'value'),
State('input-2-state', 'value')])
def update_output(n_clicks, input1, input2):
return u'''
The Button has been pressed {} times,
Input 1 is "{}",
and Input 2 is "{}"
'''.format(n_clicks, input1, input2)
def Contact():
# Form details
formspree_url="https://formspree.io/xqkdkggg"
mailing_list="*****@*****.**"
nav = Navbar()
footer = Footer()
name_input = dbc.FormGroup(
[
dbc.Row(
[
dbc.Col(html.Label("Topic", htmlFor="name-row"),width="auto"),
dbc.Col(
dcc.Input(
type="text",
id="name-row",
name="name",
className="form-control",
placeholder="Enter the topic of your message",
style={"width":"50%"},
),
width=True
),
],
)
],
)
email_input = dbc.FormGroup(
[
dbc.Row(
[
dbc.Col(html.Label("Email", htmlFor="email-row"),width="auto"),
dbc.Col(
[dcc.Input(
type="email",
id="email-row",
name="email",
className="form-control",
placeholder="Enter your email address",
style={"width":"50%"}
),
dcc.Input(
type="hidden",
name="_subject",
value="Covidanalytics Mailing List",
style={"width":"50%"},
)
],
width=True
),
],
)
],
)
text_input = dbc.FormGroup(
[
dbc.Row(
[
dbc.Col(dbc.Label("Text", html_for="message-row"),width="auto"),
dbc.Col(
[
dcc.Textarea(
placeholder="Your message goes here...",
className="form-control",
id="message-row",
name="message",
style={"width":"50%","marginLeft":5},
)
],
width=True
),
],
)
],
)
submit_button = html.Button("Submit", className="btn btn-primary", formEncType="submit")
form = html.Form([name_input, email_input, text_input, submit_button],
action=formspree_url,
method="POST")
body = dbc.Container([
dbc.Row(
[
dbc.Col(
[
html.P("We are happy to collaborate and help you take our research one step further. " +
"Feel free to send us an email using the following form."),
html.P(
["You can also reach out to us by sending an email to ",
html.A(
mailing_list,
href="mailto:%s" % mailing_list,
), "."
]
),
form
]
)
],
)
],
className="page-body",
)
layout = html.Div([nav, body, footer],className="site")
return layout
def all_layouts(self):
# Main plot
graph = html.Div(
[
dcc.Graph(
figure=go.Figure(layout=XRayDiffractionComponent.empty_plot_style),
id=self.id("xrd-plot"),
config={"displayModeBar": False},
)
]
)
# Radiation source selector
rad_source = html.Div([
html.P("Radiation Source"),
dcc.Dropdown(
id=self.id("rad-source"),
options=[
{"label": i, "value": i} for i in self.WAVELENGTHS.keys()
],
value="CuKa",
placeholder="Select a source...",
clearable=False
)
], style={'max-width':'200'}
)
# Shape factor input
shape_factor = html.Div(
[
html.P("Shape Factor, K "),
dcc.Input(
id=self.id("shape-factor"),
placeholder='0.94',
type='text',
value='0.94'
)
],style={'max-width':'200'}
)
# Peak profile selector (Gaussian, Lorentzian, Voigt)
peak_profile = html.Div([
html.P("Peak Profile"),
dcc.Dropdown(
id=self.id("peak-profile"),
options=[
{"label":'Gaussian',"value":'G'},
{"label":'Lorentzian',"value":'L'},
{"label":'Voigt',"value":'V'}
],
value="G",
clearable=False
)
], style={'max-width':'200'}
)
# Crystallite size selector (via Scherrer Equation)
crystallite_size = html.Div(
[
html.P("Scherrer Crystallite Size (nm)"),
html.Div([
dcc.Slider(
id=self.id("crystallite-slider"),
marks={i: '{}'.format(10 ** i) for i in range(-1,3)},
min=-1,
max=2,
value=0,
step=0.01
),
], style={'max-width':'500'}),
html.Div([
],id=self.id("crystallite-input"),style={"padding-top":"20px"})
]
)
return {"graph": graph,
"rad_source": rad_source,
"peak_profile": peak_profile,
"shape_factor": shape_factor,
"crystallite_size": crystallite_size
}
erc721 = json.loads(mockup_erc721)
df = df.append(erc721, sort=False)
df
#%%
app = dash.Dash()
#%%
app.layout = html.Div([
html.Div([
dcc.Input(id='input-box', type='text', style=dict(
width='60%',
height='44px',
border='2px solid rgb(147, 162, 173)',
margin='0 8px',
boxSizing='border-box'
)),
html.Button('Find', id='find-button', style=dict(
width='10%',
height='44px',
border='2px solid rgb(147, 162, 173)',
margin='0 8px',
boxSizing='border-box'
))
], style=dict(
position='relative',
display='flex',
justifyContent='center',
alignItems='center',
for data in p:
var_fit.append(data['var_fitness'])
avg_fit.append((data['avg_fitness']))
drop_down_logs.append({'label': file[:-7], 'value': len(logs)})
logs.append({'name': file[:-7], 'var_fit': var_fit, 'avg_fit': avg_fit})
# print(logs)
read_logs()
app = dash.Dash(name=__name__, external_stylesheets=external_stylesheets)
app.layout = html.Div([
html.Div([
html.Span('Name', style={'margin': '20px'}),
dcc.Input(id='name-input', placeholder='Enter name of experiment', style={'width': '50%'}),
], style={'width': '80%', 'align': 'right', 'display': 'inline-block', 'margin': '10px'},
id='name-div',
),
html.Div([
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=0),
html.Span('Probability', style={'display': 'None'}),
dcc.Input(id='mutation-probability', value='0.5', style={'display': 'None'}),
], style={'width': '80%', 'align': 'right', 'display': 'inline-block', 'margin': '10px'},
id='mutation-div',
),
html.Div([
maxk = max(model_keys)
return html.Div([
html.H5('Threshold:'),
dcc.Slider(id='mdl-slider',
min=mink,
max=maxk,
step=None,
value=10,
marks={k: str(k)
for k in model_keys})
])
pop_div = html.Div([
html.H5('Population:'),
dcc.Input(id="pop-input", type="number", value=20)
])
ren_div = html.Div([
html.H5('Releases Number:'),
dcc.Input(id="ren-input", type="number", value=20)
])
res_div = html.Div([
html.H5('Released Fraction:'),
dcc.Slider(id='res-slider',
min=0,
max=1,
step=0.15,
value=1,
marks=get_marks(0, 10 + 1, 1, 10))
def remaining_selection_drop_down(input, param_val):
if input is None:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=None),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 0:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=0),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 1:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=1),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 2:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=2),
html.Span('Parameter'),
dcc.Input(id='remaining_pop_parameter', value=param_val),
]
elif input == 3:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=3),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 4:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=4),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 5:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=5),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 6:
return [
html.Span('Remaining Selection Algorithms'),
dcc.Dropdown(id='remaining-selection-dropdown',
options=remaining_selection_options,
value=6),
html.Span('Parameter', style={'display': 'None'}),
dcc.Input(id='remaining_pop_parameter', value='1', style={'display': 'None'}),
]
elif input == 7:
return [
html.Span('Parents Selection Algorithms'),
dcc.Dropdown(id='parents-selection-dropdown',
options=parent_selection_options,
value=8),
]
elif input == 8:
return [
html.Span('Parents Selection Algorithms'),
dcc.Dropdown(id='parents-selection-dropdown',
options=parent_selection_options,
value=8),
]
'textAlign': 'center',
'width': '600px',
'padding': '10px',
'display': 'inline-block'
}),
html.Div(id='fasta_database_hidden_output', style={'display': 'none'})
]),
html.Br(),
html.Div([
html.H3("HLA alleles"),
"Enter the alleles, seperated by a semi colons",
dcc.Input(id='hla_alleles',
value='HLA-DRB1*15:01;HLA-DRB1*13:01',
style={
'width': '50%',
'height': '30px',
'lineHeight': '30px',
'borderWidth': '2px',
'textAlign': 'left',
'margin': '10px'
})
]),
html.Br(),
html.Div([
html.H3("Tissue Name"),
"Enter the tissue as defined in Gene expression table: ",
dcc.Input(id='tissue_name',
value='total PBMC',
style={
'width': '50%',
'height': '30px',
'lineHeight': '30px',
def mutation_drop_down(input, mutation_prob):
if input is None:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=None),
html.Span('Probability', style={'display': 'None'}),
dcc.Input(id='mutation-probability', value=mutation_prob, style={'display': 'None'}),
]
elif input == 0:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=0),
html.Span('Probability'),
dcc.Input(id='mutation-probability', value=mutation_prob),
]
elif input == 1:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=1),
html.Span('Probability'),
dcc.Input(id='mutation-probability', value=mutation_prob),
]
elif input == 2:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=2),
html.Span('Probability'),
dcc.Input(id='mutation-probability', value=mutation_prob),
]
elif input == 3:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=3),
html.Span('Probability', style={'display': 'None'}),
dcc.Input(id='mutation-probability', value=mutation_prob, style={'display': 'None'}),
]
elif input == 4:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=4),
html.Span('Probability', style={'display': 'None'}),
dcc.Input(id='mutation-probability', value=mutation_prob, style={'display': 'None'}),
]
elif input == 5:
return [
html.Span('Mutation Algorithms'),
dcc.Dropdown(id='mutation-dropdown',
options=mutation_options,
value=5),
html.Span('Probability'),
dcc.Input(id='mutation-probability', value=mutation_prob),
]
html.Button('Filter',
id='buttonsearch',
style=dict(width='100%'))
],
className='col-4'),
html.Div([], className='col-4')
],
className='row'),
html.Br(),
html.Br(),
html.Br(),
html.Div([
html.Div([
html.P('Max Rows : '),
dcc.Input(id='filterrowstable',
type='number',
value=10,
style=dict(width='100%'))
],
className='col-3')
],
className='row'),
html.Center([
html.H2('House Price Data', className='title'),
html.Div(id='tablediv',
children=generate_table(dfTable))
])
]),
dcc.Tab(label='Categorical Plots',
value='tab-2',
children=[
html.Div([
html.Label(
[
html.Div(["Scenario"]),
dcc.Dropdown(
id='scenario',
value=dashboard.scenarios_from(product_names[0])[0]
),
]
),
html.Label(
[
html.Div(["Outliers"]),
dcc.Input(
id="outlier",
placeholder="Enter a value...",
type="number",
value=0,
min=0,
max=5,
),
]
),
html.Label(
[
html.A(
html.Button('Download Excel', id='download-button'),
id='download-link',
),
]
),
]
)
import pandas as pd
data = pd.read_csv("data/cities_and_distances.csv")
data.reset_index(inplace=True)
data1 = data.iloc[:, 2:]
data1.index = data1.columns.values
dist_mat = data1
app = dash.Dash()
app.layout = html.Div(children=[
# an element to take the input
html.H1('Travelling Salesman problem using Genetic Algorithm'),
html.H3('Best solution so far'),
html.Img(src='data:image/png;base64,{}'.format(encoded_image.decode())),
html.P('Number of cities'),
html.Div(dcc.Input(id='number_of_cities', value=11, type='int')),
html.P('Initial Population size'),
html.Div(dcc.Input(id='initial_pop_size', value=1000, type='int')),
html.P('Elite Population size'),
html.Div(dcc.Input(id='nelite', value=500, type='int')),
html.P('Percentage of population to mutate'),
html.Div(dcc.Input(id='percentage_to_mutate', value=10, type='int')),
html.P('Percentage of population to crossover'),
html.Div(dcc.Input(id='percentage_to_crossover', value=80, type='int')),
html.P('Overall runs'),
html.Div(dcc.Input(id='noverall', value=500, type='int')),
# an element to handle the output
html.Button('Run the genetic algorithm', id='my-button'),
html.Div(id='output')
])
def create_app_ui():
# Create the UI of the Webpage here
main_layout = html.Div([
html.H1('Terrorism Analysis with Insights', id='Main_title'),
dcc.Tabs(
id="Tabs",
value="Map",
children=[
dcc.Tab(
label="Map tool",
id="Map tool",
value="Map",
children=[
dcc.Tabs(id="subtabs",
value="WorldMap",
children=[
dcc.Tab(label="World Map tool",
id="World",
value="WorldMap"),
dcc.Tab(label="India Map tool",
id="India",
value="IndiaMap")
]),
dcc.Dropdown(id='month',
options=month_list,
placeholder='Select Month',
multi=True),
dcc.Dropdown(id='date',
placeholder='Select Day',
multi=True),
dcc.Dropdown(id='region-dropdown',
options=region_list,
placeholder='Select Region',
multi=True),
dcc.Dropdown(id='country-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select Country',
multi=True),
dcc.Dropdown(id='state-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select State or Province',
multi=True),
dcc.Dropdown(id='city-dropdown',
options=[{
'label': 'All',
'value': 'All'
}],
placeholder='Select City',
multi=True),
dcc.Dropdown(
id='attacktype-dropdown',
options=
attack_type_list, #[{'label': 'All', 'value': 'All'}],
placeholder='Select Attack Type',
multi=True),
html.H5('Select the Year', id='year_title'),
dcc.RangeSlider(id='year-slider',
min=min(year_list),
max=max(year_list),
value=[min(year_list),
max(year_list)],
marks=year_dict,
step=None),
html.Br()
]),
dcc.Tab(label="Chart Tool",
id="chart tool",
value="Chart",
children=[
dcc.Tabs(
id="subtabs2",
value="WorldChart",
children=[
dcc.Tab(
label="World Chart tool",
id="WorldC",
value="WorldChart",
children=[
html.Br(),
dcc.Dropdown(
id="Chart_Dropdown",
options=chart_dropdown_values,
placeholder="Select option",
value="region_txt"),
html.Br(),
html.Hr(),
dcc.Input(
id="search",
placeholder="Search Filter"),
html.Hr(),
html.Br()
]),
dcc.Tab(label="India Chart tool",
id="IndiaC",
value="IndiaChart",
children=[])
]),
])
]),
html.Div(id="graph-object", children="Graph will be shown here")
])
return main_layout
app_name = os.environ['DASH_APP_NAME']
else:
app_name = 'dash-text-annotationsplot'
layout = html.Div([
html.Div([html.H1("Monthly Temperature Highs and Lows")], style={'textAlign': "center"}),
html.Div([html.Div([dcc.Dropdown(id='value-selected', options=[{"label": i, 'value': i} for i in df.columns[1:]],
value=['High 2007', 'Low 2000'], multi=True)],
style={"display": "block", "margin-left": "auto", "margin-right": "auto", "width": "60%"})],
className="row"),
dcc.Graph(id="my-graph"),
html.Div([html.H6("Text-Annotations", className="row",
style={"display": "block", "text-align": "center", "text-decoration": "underline"}),
html.Div([dcc.Dropdown(id='x-input', options=[{"label": i, "value": i} for i in month],
placeholder="Select month", value='', className="three columns"),
dcc.Input(id='y-input', type='number', placeholder="Input temperature", value='',
className="three columns"),
dcc.Input(id='text-input', type='text', placeholder="Input text", value='',
className="two columns"),
html.Button(id='submit-button', children="Submit", className="two columns"),
html.Button(id='remove-button', children="Remove", className="two columns"), ], className="row",
style={"display": "block", "margin-left": "auto", "margin-right": "auto", "width": "100%"})])
], className="container")
@app.callback(
Output("my-graph", "figure"),
[Input("value-selected", "value"), Input("remove-button", 'n_clicks'), Input('submit-button', 'n_clicks')],
[State('x-input', 'value'), State('y-input', 'value'), State('text-input', 'value')])
def update_graph(selected, remove, n_clicks, x_value, y_value, text):
dropdown = {"High 2014": "High Temperature in 2014", "Low 2014": "Low Temperature in 2014",
"High 2007": "High Temperature in 2007", "Low 2007": "Low Temperature in 2007",
from dash.dependencies import Input, Output, State
import pandas_datareader.data as web # requires v0.6.0 or later
from datetime import datetime
import pandas as pd
from dotenv import load_dotenv
load_dotenv()
import os
TIINGO_API_KEY = os.getenv("TIINGO_API_KEY")
app = dash.Dash()
app.layout = html.Div([
html.H1('Stock Ticker Dashboard'),
html.H3('Enter a stock symbol:'),
dcc.Input(id='my_ticker_symbol', value='TSLA'),
dcc.Graph(id='my_graph', figure={'data': [{
'x': [1, 2],
'y': [3.4]
}]})
])
@app.callback(Output('my_graph', 'figure'),
[Input('my_ticker_symbol', 'value')])
def update_graph(stock_ticker):
start = datetime(2017, 1, 1)
end = datetime(2020, 10, 10)
df = web.get_data_tiingo(stock_ticker, start, end, api_key=TIINGO_API_KEY)
df.index = df.index.get_level_values('date')
fig = {
html.Div([
html.Div(id='container_col_select',
children=dcc.Dropdown(id='col_select',
options=[{
'label': c.replace('_', ' ').title(),
'value': c}
for c in sample_df.columns]),
style={'display': 'inline-block', 'width': '30%', 'margin-left': '7%'}),
# DataFrame filter containers
html.Div([
html.Div(children=dcc.RangeSlider(id='num_filter',
updatemode='drag')),
html.Div(children=html.Div(id='rng_slider_vals'), ),
], id='container_num_filter', ),
html.Div(id='container_str_filter',
children=dcc.Input(id='str_filter')),
html.Div(id='container_bool_filter',
children=dcc.Dropdown(id='bool_filter',
options=[{'label': str(tf), 'value': tf}
for tf in [True, False]])),
html.Div(id='container_cat_filter',
children=dcc.Dropdown(id='cat_filter', multi=True,
options=[{'label': day, 'value': day}
for day in sample_df['category'].unique()])),
html.Div([
dcc.DatePickerRange(id='date_filter',
initial_visible_month= pd.datetime(2019, 5, 10)),
], id='container_date_filter'),
]),
DataTable(id='table',
import dash
import dash_core_components as dcc
import dash_html_components as html
from dash.dependencies import Input, Output
import plotly.graph_objs as go
import numpy as np
import pandas as pd
df = pd.read_csv('OldFaithful.csv')
colors = {'background': '#111111', 'text': '#7FDBFF'}
app = dash.Dash()
app.layout = html.Div([
dcc.Input(id='my-id', value='Initial Text', type='text'),
html.Div(id='my-div')
])
@app.callback(Output(component_id='my-div', component_property='children'),
[Input(component_id='my-id', component_property='value')])
def update_output_div(input_value):
return "You entered : {}".format(input_value)
if __name__ == '__main__':
app.run_server()
),
),
dbc.NavbarToggler(id="navbar-toggler"),
],
color="dark",
dark=True
),
html.Button(
id='button',
style={"width": "10%", "display": "inline-block"},
children='Update',
n_clicks=0,
),
dcc.Input(
id="input",
type='text',
style={"width": "30%"},
value='',
),
html.Button(
id="input-button",
style={"width": "10%", "left": 0, "display": "inline-block"},
children="Import",
n_clicks=0,
),
html.Div(
id="data",
style={"display": "none"},
),
dcc.Dropdown(
id="dropmenu",
)
app.title = 'Dashboard mpg'
app.layout = html.Div([
html.H1('Cars Data Analytics'),
html.H3('1870-1983'
),
dcc.Tabs(id="tabs", value='tab-1', children=[
dcc.Tab(label = 'Cars 1970 - 1982 Data', value = 'tab-1', children = [
html.Div([
html.Div([
html.P('Find Car By: '),
dcc.Input(
id = 'filternametable',
type = 'text',
value = '',
style = dict(width='100%')
)
], className = 'col-4'),
html.Div([
html.P('Filter Model Year : '),
dcc.Dropdown(
id='filterModelYear',
options=[i for i in [{ 'label': 'All year', 'value': '' },
{ 'label': '1970', 'value': '70' },
{ 'label': '1971', 'value': '71' },
{ 'label': '1972', 'value': '72' },
{ 'label': '1973', 'value': '73' },
{ 'label': '1974', 'value': '74' },
{ 'label': '1975', 'value': '75' },
{ 'label': '1976', 'value': '76' },
def render_content(tab):
if tab == 'tab-1':
return html.Div([
html.P('Enter UserID[1 - 1002]'),
dcc.Input(id='input-box', value='1', type='text', style={'borderRadius': '5px'}),
#plotted graphs
dcc.Graph(id='agg_det'),
html.Div(id='inter', children=[
dcc.Graph(id='pers_det'),
dcc.Graph(id='performance')
], style={'columnCount': 2}),
#recommendations
html.H5('Recommendations', style={'color': '#CA0009', 'marginLeft': '2%'}),
html.Div([
html.H6('Products', style=styles['sub-menu']),
html.Div(id='prods', style=styles['sub-sub']),
html.H6('Tips', style=styles['sub-menu']),
html.Div(id='recoms', style=styles['sub-sub'])
])
], style=styles['main'])
elif tab == 'tab-2':
return html.Div([
html.Div([
dcc.Markdown('''
Follow Procedure Below to check your carbon_footprint
And possible improvements you can make
*Click on the Download File Button
*Fill in your details
*Consumption column is in count of units columns
*Quality_of_Life_Importance__1_10 column is range of 100%
*For Type of Energy Selection:
*Input 1 for Yes
*Input 0 for No
*Drag and Drop or Select File to Upload File
***Please note, your data will be added to database to improve results
'''),
html.A(
html.Button('Download File'),
id='download',
href="/dash/urlToDownload"
),
], style={'margin': '0px 0px 0px 30px'}),
dcc.Upload(
id='upload-data',
children=html.Div([
'Drag and Drop or ',
html.A('Select File')
]),
style={
'width': '95%',
'height': '60px',
'lineHeight': '60px',
'borderWidth': '1px',
'borderStyle': 'dashed',
'borderRadius': '5px',
'textAlign': 'center',
'margin': '0px 0px 0px 30px'
},
),
html.Div(id='show-data')
])
