Spaces:
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progress bar
Browse files
app.py
CHANGED
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@@ -114,143 +114,145 @@ with st.form("choose_model"):
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st.info('No model selected.')
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if submitted:
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fname=f'performance_for_{option}_model.csv'
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st.info(f'as of {option} on {curr_date} 👇🏽', icon="🔮")
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st.info('No model selected.')
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if submitted:
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my_bar = st.progress(0)
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fname=f'performance_for_{option}_model.csv'
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if option == '06:30':
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from model_day import *
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fname='performance_for_open_model.csv'
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my_bar.progress(0.33, 'Loading data...')
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data, df_final, final_row = get_data()
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# st.success("✅ Historical data")
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my_bar.progress(0.66, "Training models...")
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def train_models():
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res1, xgbr, seq2 = walk_forward_validation_seq(df_final.dropna(), 'Target_clf', 'Target', 200, 1)
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return res1, xgbr, seq2
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res1, xgbr, seq2 = train_models()
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# st.success("✅ Models trained")
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my_bar.progress(0.99, "Getting new prediction...")
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# Get last row
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new_pred = data.loc[final_row, model_cols]
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new_pred = pd.DataFrame(new_pred).T
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# new_pred_show = pd.DataFrame(index=[new_pred.columns], columns=[new_pred.index], data=[[v] for v in new_pred.values])
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# last_date = datetime.datetime.strptime(data.loc[final_row], '%Y-%m-%d')
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curr_date = final_row + BDay(1)
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curr_date = curr_date.strftime('%Y-%m-%d')
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new_pred['BigNewsDay'] = new_pred['BigNewsDay'].astype(float)
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new_pred['Quarter'] = new_pred['Quarter'].astype(int)
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new_pred['Perf5Day'] = new_pred['Perf5Day'].astype(bool)
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new_pred['Perf5Day_n1'] = new_pred['Perf5Day_n1'].astype(bool)
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new_pred['DaysGreen'] = new_pred['DaysGreen'].astype(float)
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new_pred['DaysRed'] = new_pred['DaysRed'].astype(float)
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new_pred['CurrentGap'] = new_pred['CurrentGap'].astype(float)
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new_pred['RangePct'] = new_pred['RangePct'].astype(float)
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new_pred['RangePct_n1'] = new_pred['RangePct_n1'].astype(float)
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new_pred['RangePct_n2'] = new_pred['RangePct_n2'].astype(float)
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new_pred['OHLC4_VIX'] = new_pred['OHLC4_VIX'].astype(float)
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new_pred['OHLC4_VIX_n1'] = new_pred['OHLC4_VIX_n1'].astype(float)
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new_pred['OHLC4_VIX_n2'] = new_pred['OHLC4_VIX_n2'].astype(float)
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# new_pred['OHLC4_Current_Trend'] = new_pred['OHLC4_Current_Trend'].astype(bool)
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# new_pred['OHLC4_Trend'] = new_pred['OHLC4_Trend'].astype(bool)
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new_pred['OpenL1'] = new_pred['OpenL1'].astype(float)
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new_pred['OpenL2'] = new_pred['OpenL2'].astype(float)
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new_pred['OpenH1'] = new_pred['OpenH1'].astype(float)
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new_pred['OpenH2'] = new_pred['OpenH2'].astype(float)
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new_pred['L1TouchPct'] = new_pred['L1TouchPct'].astype(float)
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new_pred['L2TouchPct'] = new_pred['L2TouchPct'].astype(float)
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new_pred['H1TouchPct'] = new_pred['H1TouchPct'].astype(float)
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new_pred['H2TouchPct'] = new_pred['H2TouchPct'].astype(float)
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new_pred['L1BreakPct'] = new_pred['L1BreakPct'].astype(float)
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new_pred['L2BreakPct'] = new_pred['L2BreakPct'].astype(float)
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new_pred['H1BreakPct'] = new_pred['H1BreakPct'].astype(float)
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new_pred['H2BreakPct'] = new_pred['H2BreakPct'].astype(float)
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new_pred['H1BreakTouchPct'] = new_pred['H1BreakTouchPct'].astype(float)
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new_pred['H2BreakTouchPct'] = new_pred['H2BreakTouchPct'].astype(float)
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new_pred['L1BreakTouchPct'] = new_pred['L1BreakTouchPct'].astype(float)
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new_pred['L2BreakTouchPct'] = new_pred['L2BreakTouchPct'].astype(float)
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seq_proba = seq_predict_proba(new_pred, xgbr, seq2)
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else:
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from model_intra import *
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idx = times_list.index(option)
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my_bar.progress(0.33, 'Loading data...')
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data, df_final, final_row = get_data(idx)
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# st.success("✅ Historical data")
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my_bar.progress(0.66, "Training models...")
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def train_models():
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res1, xgbr = walk_forward_validation(df_final.dropna(), 'Target_clf', 120, 1)
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return res1, xgbr
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res1, xgbr = train_models()
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# st.success("✅ Models trained")
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my_bar.progress(0.99, "Getting new prediction...")
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my_bar.empty()
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# Get last row
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new_pred = data.loc[final_row, model_cols]
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new_pred = pd.DataFrame(new_pred).T
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# new_pred_show = pd.DataFrame(index=[new_pred.columns], columns=[new_pred.index], data=[[v] for v in new_pred.values])
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# last_date = datetime.datetime.strptime(data.loc[final_row], '%Y-%m-%d')
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curr_date = final_row + BDay(1)
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curr_date = curr_date.strftime('%Y-%m-%d')
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new_pred['BigNewsDay'] = new_pred['BigNewsDay'].astype(float)
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new_pred['Quarter'] = new_pred['Quarter'].astype(int)
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new_pred['Perf5Day'] = new_pred['Perf5Day'].astype(bool)
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new_pred['Perf5Day_n1'] = new_pred['Perf5Day_n1'].astype(bool)
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new_pred['DaysGreen'] = new_pred['DaysGreen'].astype(float)
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new_pred['DaysRed'] = new_pred['DaysRed'].astype(float)
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new_pred['CurrentHigh30toClose'] = new_pred['CurrentHigh30toClose'].astype(float)
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new_pred['CurrentLow30toClose'] = new_pred['CurrentLow30toClose'].astype(float)
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new_pred['CurrentClose30toClose'] = new_pred['CurrentClose30toClose'].astype(float)
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new_pred['CurrentRange30'] = new_pred['CurrentRange30'].astype(float)
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new_pred['GapFill30'] = new_pred['GapFill30'].astype(float)
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new_pred['CurrentGap'] = new_pred['CurrentGap'].astype(float)
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new_pred['RangePct'] = new_pred['RangePct'].astype(float)
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new_pred['RangePct_n1'] = new_pred['RangePct_n1'].astype(float)
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new_pred['RangePct_n2'] = new_pred['RangePct_n2'].astype(float)
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new_pred['OHLC4_VIX'] = new_pred['OHLC4_VIX'].astype(float)
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new_pred['OHLC4_VIX_n1'] = new_pred['OHLC4_VIX_n1'].astype(float)
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new_pred['OHLC4_VIX_n2'] = new_pred['OHLC4_VIX_n2'].astype(float)
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# new_pred['OpenL1'] = new_pred['OpenL1'].astype(float)
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# new_pred['OpenL2'] = new_pred['OpenL2'].astype(float)
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# new_pred['OpenH1'] = new_pred['OpenH1'].astype(float)
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# new_pred['OpenH2'] = new_pred['OpenH2'].astype(float)
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new_pred['L1TouchPct'] = new_pred['L1TouchPct'].astype(float)
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new_pred['L2TouchPct'] = new_pred['L2TouchPct'].astype(float)
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new_pred['H1TouchPct'] = new_pred['H1TouchPct'].astype(float)
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new_pred['H2TouchPct'] = new_pred['H2TouchPct'].astype(float)
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new_pred['L1BreakPct'] = new_pred['L1BreakPct'].astype(float)
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new_pred['L2BreakPct'] = new_pred['L2BreakPct'].astype(float)
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new_pred['H1BreakPct'] = new_pred['H1BreakPct'].astype(float)
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new_pred['H2BreakPct'] = new_pred['H2BreakPct'].astype(float)
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new_pred['H1BreakTouchPct'] = new_pred['H1BreakTouchPct'].astype(float)
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new_pred['H2BreakTouchPct'] = new_pred['H2BreakTouchPct'].astype(float)
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new_pred['L1BreakTouchPct'] = new_pred['L1BreakTouchPct'].astype(float)
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new_pred['L2BreakTouchPct'] = new_pred['L2BreakTouchPct'].astype(float)
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new_pred['H1BreakH2TouchPct'] = new_pred['H1BreakH2TouchPct'].astype(float)
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new_pred['L1BreakL2TouchPct'] = new_pred['L1BreakL2TouchPct'].astype(float)
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new_pred['GreenProbas'] = new_pred['GreenProbas'].astype(float)
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new_pred['OHLC4_Current_Trend'] = new_pred['OHLC4_Current_Trend'].astype(bool)
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new_pred['OHLC4_Trend'] = new_pred['OHLC4_Trend'].astype(bool)
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new_pred['H1TouchGreenPct'] = new_pred['H1TouchGreenPct'].astype(float)
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new_pred['L1TouchRedPct'] = new_pred['L1TouchRedPct'].astype(float)
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seq_proba = seq_predict_proba(new_pred, xgbr)
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st.info(f'as of {option} on {curr_date} 👇🏽', icon="🔮")
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