html.Div(children=[
#dcc.Markdown(children=’’’### Forecast Model for Laundry System: ‘’’),
#Add filters for the data
html.Div([
html.Div([html.Label(‘Choose Data to Show:’),
dcc.RadioItems(id=‘dataselector’, options=[
{‘label’: ‘View Data Only’, ‘value’: 1},
{‘label’: ‘View Data and Forecast’, ‘value’: 2},
{‘label’: ‘View Forecast Only’, ‘value’: 3}
], value=2, labelStyle={‘display’: ‘inline-block’})
], style={‘width’: ‘30%’, ‘display’: ‘inline-block’}),
# html.Div([html.Label(‘Choose Month:’),
#dcc.Dropdown(id=‘date-dropdown’, multi=True
#,options=date_dict, value=values_date_default, multi=True
# )], style={‘width’: ‘49%’, ‘display’: ‘inline-block’, ‘float’: ‘right’})
], style={‘borderBottom’: ‘thin lightgrey dotted’, ‘padding’: ‘20px 5px’}),
html.Div([html.Label('Choose Laundry Status to Forecast:'),
dcc.Dropdown(id='select-dataset',
options=[{'label': 'Entry Laundry Items', 'value': 1},
{'label': 'Sorting Laundry Items', 'value': 2},
{'label': 'Processing Laundry Items', 'value': 3},
{'label': 'Complete Laundry Items', 'value': 4}],
placeholder='Select Here to Forecast', value='',style={}),
], style={'backgroundColor': '#ebebe0','margin-top':'10px', 'padding': '10', 'borderRadius': '5px','display': 'inline-block', 'width': '100%', 'verticalAlign': 'middle'}),
]),
html.Div(id='output-data-upload'),
html.Div(dte.DataTable(data=[{}]), style={'display': 'none'}),
#Graph
html.Div([dcc.Graph(id='graph-daily')], style={'backgroundColor': '#fbebe0','margin-top':'10px','padding': '10 10','borderRadius': '5px', 'display': 'inline-block', 'width': '100%',}),
#Choose Forecasting Model
html.Div([html.Label('Choose Forecasting Model:'),
dcc.Dropdown(id='model-dropdown',
options=[
{'label': 'ARIMA Time Series', 'value': 1},
{'label': 'FB Prophet', 'value': 2},
{'label': 'Average Forecast', 'value': 3}], value=3)
], style={'width': '100%','display': 'inline-block', 'float': 'left'}),
#Take ARIMA Inputs
html.Div([
html.Div(dcc.Input(id='arima-p', type='number', placeholder='AR(p)='), style={'display': 'inline-block'}),
html.Div(dcc.Input(id='arima-d', type='number', placeholder='I(d)='), style={'display': 'inline-block'}),
html.Div(dcc.Input(id='arima-q', type='number', placeholder='MA(q)='), style={'display': 'inline-block'}),
html.Button('Submit ARIMA Parameters ', id='arima-submit', className='button-primary'),
html.Div(id='output-container-button',
children='Enter ARIMA parameters and click Submit to refresh forecast!')], id='arima-inputblock'),
#Take Moving Average Inputs
html.Div([
html.Div(dcc.Input(id='n_weeks', type='number', placeholder='#Week for averaging = 3'), style={'display': 'inline-block'}),
html.Div(dcc.Input(id='period', type='number', placeholder='Period = 3'), style={'display': 'inline-block'}),
html.Button('Update Moving Average Forecast ', id='movingavg-submit', className='button-primary'),
html.Div(id='output-container-button-ma',
children='Enter Moving Average parameters and click Submit to refresh forecast!')], id='movingavg-inputblock'),
#Stores df-to-json for a forecast method
html.Div(id='intermediate-value', style={'display': 'none'}),
#Stores uploded data converted to df-to-json
html.Div(id='upload-data-df', style={'display': 'none'}),
])
def return_a_textbox(value):
‘’’
‘’’
if value:
return html.Div([
html.Div(dcc.Input(id=‘input-box’, type=‘text’)),
html.Button(‘Submit’, id=‘button’),
html.Div(id=‘output-container-button’,
children=‘Enter a value and press submit’)])
#--------------------------------------------------------
#Show ARIMA input parameters block
@app.callback(
Output(‘arima-inputblock’, ‘style’),
[Input(‘model-dropdown’, ‘value’)])
def update_arimablock(value):
if value ==1:
return {‘display’: ‘block’, ‘padding’: ‘20 0’}
else:
return {‘display’: ‘none’}
#--------------------------------------------------------
#Show ARIMA input parameters block
@app.callback(
Output(‘movingavg-inputblock’, ‘style’),
[Input(‘model-dropdown’, ‘value’)])
def update_movingavgblock(value):
if value ==3:
return {‘display’: ‘block’, ‘padding’: ‘20 0’}
else:
return {‘display’: ‘none’}
#--------------------------------------------------------
#Generate forecasts - Forecast dataframe is generated
@app.callback(
Output(‘intermediate-value’, ‘children’),
[Input(‘upload-data-df’, ‘children’),
Input(‘model-dropdown’, ‘value’),
Input(‘arima-submit’, ‘n_clicks’),
Input(‘movingavg-submit’, ‘n_clicks’)],
[State(‘arima-p’, ‘value’),
State(‘arima-d’, ‘value’),
State(‘arima-q’, ‘value’),
State(‘n_weeks’, ‘value’),
State(‘period’, ‘value’)])
def update_daily_view(uploaded_df, modelselected, arima_n_clicks, ma_n_clicks, arimap=1, arimad=0, arimaq=1,n_weeks_ma=3, period_ma=2):
#print("-----Printing Uploaded Data------")
print(uploaded_df)
print("-----Printing Uploaded Data Done ------")
df = pd.read_json(uploaded_df, orient='split').dropna()
#df['Date'] = pd.to_datetime(df'Date', format='%Y-%m-%d %H:%M', )
print("Print data here:",df)
#print("Model Selected:", modelselected)
#print(dcc.__version__)
if modelselected ==1: #1=ARIMA
df_final = fcst.fcst_wklyavg(df, stop_at_futuredates=1)
arima_fcst = forecast_models.forecast_ARIMA(df, p=arimap, d=arimad, q=arimaq)
df_final['Forecast'][df.shape[0]:] = arima_fcst[0][0]
print("modelselected 1")
#return df_final.to_json(date_format='iso', orient='split')
elif modelselected == 2: #2= FB Prophet
df_final = fcst.fcst_wklyavg(df, stop_at_futuredates=1)
print('--------------Empty forecast dataframe generated-----------')
print(df_final.tail())
prophetfcst = forecast_models.forecast_FBProphet(df, futureperiod=30)
df_final['Forecast'][df.shape[0]:] = prophetfcst['yhat'][df.shape[0]:]
df_final = plot_error_range(df, df_final, prophetfcst)
#return df_final.to_json(date_format='iso', orient='split')
df_final = df_final.rename(columns={'ds':'Date', 'yhat':'Forecast'})
print("modelselected 2")
elif modelselected ==3: #3=Moving Average
df_final = fcst.fcst_wklyavg(df, n_week=n_weeks_ma, data_period=period_ma)
print(df_final.tail())
print("modelselected 3")
print("Print final data here:",df_final)
return df_final.to_json(date_format='iso', orient='split')