def generate_main_window(
self, data_table_columns: List[Dict[str, str]]
) -> html.Div:
return html.Div(
children=[
html.Div(
[
html.Div(
sd_material_ui.RaisedButton(
id=self.id_button_options, label="Options"
),
style={"display": "inline-block"},
),
html.Div(
sd_material_ui.RaisedButton(
id=self.id_button_update, label="Update Graphs"
),
style={
"display": "inline-block",
"margin-left": "15px",
},
),
],
style={"margin-bottom": "5px"},
),
core.Loading(
id=self.id_loader_graph,
children=[
sd_material_ui.Paper([core.Graph(id=self.id_plot)])
],
),
core.Loading(
id=self.id_loader_data_table,
children=[
sd_material_ui.Paper(
[
dash_table.DataTable(
id=self.id_data_table,
columns=data_table_columns,
data=self.df_func().to_dict("records"),
page_size=50,
sort_action="native",
sort_mode="multi",
export_format="csv",
)
]
)
],
type="circle",
),
]
)
def hide_graph(clicked: int, timestamp, data, content):
if timestamp is None:
raise PreventUpdate
xs = data.get('lastXs')
ys = data.get('lastYs')
if len(xs) > 1:
x_prev = xs[-2]
y_prev = ys[-2]
x = xs[-1]
y = ys[-1]
else:
x_prev = y_prev = x = y = None
KNOB = sd_material_ui.Paper(zDepth=1,
style=dict(height=625, width=750),
children=[
html.Div([
daq.Knob(label="Gradient Ranges",
value=7,
size=500,
color={
"gradient": True,
"ranges": {
"red": [0, 5],
"yellow": [5, 9],
"green": [9, 10]
}
},
style=dict(
position='relative',
top='25px',
left='0px'))
])
]),
if x_prev != x or y_prev != y: # Moved
return content
else:
if content is None or content == []:
return KNOB
elif content:
return []
spacer,
# Test SDSubheader
sd_material_ui.Subheader(children=['This is a subheader']),
spacer,
sd_material_ui.Subheader(children=['This is a subheader with an inset'],
inset=True),
spacer,
# Test SDPaper
sd_material_ui.Paper(
zDepth=5,
circle=True,
style=dict(
height=100,
width=100,
margin=20,
textAlign='center',
display='inline-block',
),
),
spacer,
sd_material_ui.Paper(
children=[
sd_material_ui.FontIcon(
className='material-icons',
iconName='help',
color='green',
)
],
zDepth=4,
]),
sd_material_ui.Divider(),
html.Div([
spacer,
]),
html.Div([
html.Div([
html.Div([
html.P([html.Strong('Test for Collapse Transition and Paper/Card')]),
sd_material_ui.CollapseTransition(id='transition-collapse', visible=True, children=[
sd_material_ui.Paper([
html.H3('Paper Title'),
sd_material_ui.Card([
html.P('Card Text')
]),
])
]),
sd_material_ui.Toggle(id='transition-input', toggled=True, label='Show element?'),
]),
spacer,
html.Div([
html.P([html.Strong('Test for Fade Transition')]),
sd_material_ui.FadeTransition(id='transition-fade', visible=True, children=[
sd_material_ui.Card([
html.P('Card Text')
]),
]),
style={
"fontSize": 20,
"fontFamily": "sans serif",
"textAlign": "center",
"padding": 30,
},
),
html.Br(),
html.Div(
sd.Paper(
html.Div(
id="object_threshold",
style={
"fontSize": 20,
"fontWeight": "bold"
},
),
style={
"padding": 50,
"background-color": "rgb(222,222,222)",
},
),
style={
"width": "45%",
"display": "inline-block",
"textAlign": "center",
},
),
html.Div(
sd.Paper(
html.Div(
handle='.handle',
children=[
html.Div([
sd_material_ui.Paper(children=[
sd_material_ui.IconButton(
id='button1',
iconClassName='fas fa-grip-lines',
iconStyle={
'color': 'grey',
'width': 50,
'height': 50,
'position': 'relative',
'top': '2px',
'left': '-12px'
},
tooltip='Drag Me',
touch=True,
tooltipPosition='bottom-right')
],
zDepth=3,
circle=True,
style=dict(
height=50,
width=50,
textAlign='center',
position='relative',
display='inline-block',
top='25px',
left='-25px'))
],
className='handle no-print'),
dash_table.DataTable(
children=sd_material_ui.Paper([
daq.BooleanSwitch(label='Simple Moving Average', id='0', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Exponential Moving Average', id='1', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Weighted Moving Average', id='2', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Double Exponential Moving Average', id='3', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Triple Exponential Moving Average', id='4', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Triangular Moving Average', id='5', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Kaufman Adaptive Moving Average', id='6', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='MESA Adaptive Moving Average', id='7', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Triple Exponential Moving Average', id='8', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Moving Average Convergence/Divergence', id='9', on=False,
labelPosition='right'),
# {'daq.BooleanSwitch(label'='', id='', on=False, labelPosition='right'), MACDEXT
daq.BooleanSwitch(label='Stochastic Oscillator Values', id='10', on=False,
labelPosition='right'),
# {'daq.BooleanSwitch(label'='', id='', on=False, labelPosition='right'), STOCHF
daq.BooleanSwitch(label='Relative Strength Index', id='11', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Stochastic Relative Strength Index', id='12', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Williams %R Values', id='13', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Average Directional Movement Index', id='14', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Absolute Price Oscillator Values', id='15', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Percentage Price Oscillator Values', id='16', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Momentum Values', id='17', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Balance of Power Values', id='18', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Commodity Channel Index', id='19', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Chande Momentum Oscillator Values', id='20', on=False,
labelPosition='right'),
# {'daq.BooleanSwitch(label'='Rate of Change Values', id='', on=False, labelPosition='right'), # Save as default indicator
daq.BooleanSwitch(label='AROON Values', id='21', on=False, labelPosition='right'),
daq.BooleanSwitch(label='AROON OScillator Values', id='22', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Money Flow Index', id='23', on=False, labelPosition='right'),
# {'daq.BooleanSwitch(label'='', id='', on=False, labelPosition='right'), TRIX
daq.BooleanSwitch(label='Ultimate Oscillator Values', id='24', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Directional Movement Index', id='25', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Minus Directional Indicator Values', id='26', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Plus Directional Indicator Values', id='27', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Minus Directional Movement Values', id='28', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Plus Directional Movement Values', id='29', on=False,
labelPosition='right'),
# {'daq.BooleanSwitch(label'='', id='', on=False, labelPosition='right'), # BBands by default
daq.BooleanSwitch(label='Midpoint Values', id='30', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Midprice Values', id='31', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Parabolic SAR Values', id='32', on=False, labelPosition='right'),
daq.BooleanSwitch(label='True Range Values', id='33', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Average True Range Values', id='34', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Normalized Average True Range Values', id='35', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Chaikin A/D Line Values', id='36', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Chaikin A/D Oscialltor Values', id='37', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='On-balance Volume Values', id='38', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform', id='39', on=False, labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform: Sine Wave', id='40', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform: Trend vs Cycle', id='41', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform: Dominant Cycle Period', id='42', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform: Dominant Cycle Phase', id='43', on=False,
labelPosition='right'),
daq.BooleanSwitch(label='Hilbert Transform: Phasor Components', id='44', on=False,
labelPosition='right'),
])),
def predict_stocks_decision_daily(json_data, figure):
"""
Callback to get stock data from the hidden div and perform RL to predict the optimal decision to make.
"""
# Parse
json_res = json.loads(json_data)
series = json_res["Time Series (Daily)"]
days = [day for day in series]
closing = [float(series[day]["4. close"]) for day in days]
# Get the last 100 days stock prices
model_input = closing[:100]
model_input = [float(numeric_string) for numeric_string in model_input]
model_input = np.reshape(model_input, (1, 1, 100))
# Load model
json_file = open('models/dqn_model.json', 'r')
loaded_model_json = json_file.read()
json_file.close()
loaded_model = model_from_json(loaded_model_json)
# load weights into new model
loaded_model.load_weights("models/dqn_weights.h5")
# Run model
decisions = loaded_model.predict(model_input)
# Reset for future model predictions
K.clear_session()
# Render output
if np.argmax(decisions) == 0: # Stay
return sd_material_ui.Paper(
children=[
sd_material_ui.FontIcon(className='material-icons',
iconName='trending_flat',
hoverColor="#1125ff"),
html.P('The Deep Q Network advices to ignore this stock')
],
zDepth=2,
rounded=True,
style=dict(height=150,
width=150,
margin=20,
textAlign='center',
display='inline-block'),
),
elif (np.argmax(decisions) == 1): # Buy
return sd_material_ui.Paper(
children=[
sd_material_ui.FontIcon(className='material-icons',
iconName='trending_up',
hoverColor="#56fc0a"),
html.P('The Deep Q Network advices to invest in this stock')
],
zDepth=2,
rounded=True,
style=dict(height=150,
width=150,
margin=20,
textAlign='center',
display='inline-block'),
),
else: # Sell
return sd_material_ui.Paper(
children=[
sd_material_ui.FontIcon(className='material-icons',
iconName='trending_down',
hoverColor="#fc000c"),
html.P('The Deep Q Network advices to sell this stock')
],
zDepth=2,
rounded=True,
style=dict(height=150,
width=150,
margin=20,
textAlign='center',
display='inline-block'),
),
