page_2.py

import pandas as pd
import pandas_ta as ta
import streamlit as st
import plotly.graph_objects as go
from plotly.subplots import make_subplots
from modules.technical import TechnicalAnalysis

st.set_page_config(page_title="Technical Analysis", layout="wide")

# Load sample data (replace this with actual data)
data = pd.read_csv('data/brent_futures.csv')
data['Date'] = pd.to_datetime(data['Date'])
data.sort_values('Date', inplace=True)

# crudeData = TechnicalAnalysis('data/brent_futures.csv')

# Streamlit sidebar for user input
st.sidebar.title("Technical Analysis Settings")

# Allow user to choose which technical indicators to display using multiselect
indicators = st.sidebar.multiselect("Select Technical Indicators", 
                                    ['Simple Moving Average', 'Bollinger Bands', 'RSI', 'MACD', 'Stochastic Oscillator', 'ADX'],
                                    default=['Simple Moving Average'])

# Set lengths for technical indicators
with st.sidebar.expander("Simple Moving Average"):
    sma_length = st.number_input('Simple Moving Average Length', min_value=5, max_value=300, value=5, step=1)
with st.sidebar.expander("Bollinger Bands"):
    bb_length = st.number_input('Bollinger Bands Length', min_value=5, max_value=300, value=20, step=1)
with st.sidebar.expander("RSI"):
    rsi_length = st.number_input('RSI Length', min_value=1, max_value=300, value=5, step=1)
with st.sidebar.expander("MACD"):
    macd_fast_length = st.number_input("MACD Fast Length", min_value=5, max_value=300, value=12)
    macd_slow_length = st.number_input("MACD Slow Length", min_value=10, max_value=300, value=26)
    macd_signal_length = st.number_input("MACD Signal Length", min_value=5, max_value=300, value=9)
with st.sidebar.expander("Stochastic Oscillator"):
    stocho_fast_length = st.number_input("Stochastic Oscillator Length", min_value=5, max_value=300, value=14)
    stocho_slow_length = st.number_input("Stochastic Oscillator Length", min_value=5, max_value=300, value=28)
with st.sidebar.expander("ADX"):
    adx_length = st.number_input("ADX Length", min_value=5, max_value=50, value=14)

# Initialize indicator choices
moving_avg_choice = 'Simple Moving Average' in indicators
bb_choice = 'Bollinger Bands' in indicators
rsi_choice = 'RSI' in indicators
macd_choice = 'MACD' in indicators
stocho_choice = 'Stochastic Oscillator' in indicators
adx_choice = 'ADX' in indicators

# Calculate indicators based on user input
if moving_avg_choice:
    data['SMA'] = ta.sma(data['Close'], length=sma_length)
if bb_choice:
    bbands = ta.bbands(data['Close'], length=bb_length)
    data['BB_upper'], data['BB_middle'], data['BB_lower'] = bbands.iloc[:, 2], bbands.iloc[:, 1], bbands.iloc[:, 0]
if rsi_choice:
    data['RSI'] = ta.rsi(data['Close'], length=rsi_length)
if macd_choice:
    macd = ta.macd(data['Close'], fast=macd_fast_length, slow=macd_slow_length, signal=macd_signal_length)
    data['MACD'], data['MACD_Signal'], data['MACD_Hist'] = macd.iloc[:, 0], macd.iloc[:, 1], macd.iloc[:, 2]
if stocho_choice:
    stoch = ta.stoch(data['High'], data['Low'], data['Close'], k=stocho_fast_length, d=stocho_slow_length)
    data['Stochastic_k'] = stoch.iloc[:, 0]
    data['Stochastic_d'] = stoch.iloc[:, 1]
if adx_choice:
    adx = ta.adx(data['High'], data['Low'], data['Close'], length=adx_length)
    data['ADX'], data['ADX_DMP'], data['ADX_DMN'] = adx.iloc[:, 0], adx.iloc[:, 1], adx.iloc[:, 2]

# Dynamically calculate the number of rows based on selected options
rows = 1  # OHLC is mandatory
if rsi_choice:
    rows += 1
if macd_choice:
    rows += 1
if stocho_choice:
    rows += 1
if adx_choice:
    rows += 1
row_heights = [0.6] + [0.2] * (rows - 1)

# Create a subplot figure
subplot_titles = ['OHLC with Technical Indicators']
if rsi_choice:
    subplot_titles.append('RSI')
if macd_choice:
    subplot_titles.append('MACD')
if stocho_choice:
    subplot_titles.append('Stochastic Oscillator')
if adx_choice:
    subplot_titles.append('ADX')
subplot_titles.append('Volume')

fig = make_subplots(
    rows=rows + 1, cols=1,  # Extra row for Volume
    shared_xaxes=True,
    vertical_spacing=0.05,
    row_heights=row_heights + [0.2],
    subplot_titles=subplot_titles
)

# Plot OHLC candlestick
fig.add_trace(go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], name="OHLC"), row=1, col=1)

# Plot Moving Averages
if moving_avg_choice:
    fig.add_trace(go.Scatter(x=data['Date'], y=data['SMA'], mode='lines', name=f'SMA {sma_length}', line=dict(color='blue')), row=1, col=1)

# Plot Bollinger Bands
if bb_choice:
    fig.add_trace(go.Scatter(x=data['Date'], y=data['BB_upper'], mode='lines', name='BB Upper', line=dict(color='purple')), row=1, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['BB_middle'], mode='lines', name='BB Middle', line=dict(color='gray')), row=1, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['BB_lower'], mode='lines', name='BB Lower', line=dict(color='purple')), row=1, col=1)

# Plot RSI
if rsi_choice:
    fig.add_trace(go.Scatter(x=data['Date'], y=data['RSI'], mode='lines', name=f'RSI {rsi_length}', line=dict(color='magenta')), row=2, col=1)

# Plot MACD
if macd_choice:
    macd_row = 2 if not rsi_choice else 3
    fig.add_trace(go.Scatter(x=data['Date'], y=data['MACD'], mode='lines', name='MACD', line=dict(color='blue')), row=macd_row, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['MACD_Signal'], mode='lines', name='MACD Signal', line=dict(color='red')), row=macd_row, col=1)
    fig.add_trace(go.Bar(x=data['Date'], y=data['MACD_Hist'], name='MACD Hist', marker=dict(color='green')), row=macd_row, col=1)

# Plot Stochastic Oscillator
if stocho_choice:
    stocho_row = 2 if not rsi_choice and not macd_choice else (3 if (not rsi_choice) or (not macd_choice) else 4)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['Stochastic_k'], mode='lines', name='Stochastic K', line=dict(color='blue')), row=stocho_row, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['Stochastic_d'], mode='lines', name='Stochastic D', line=dict(color='red')), row=stocho_row, col=1)
# Plot ADX
if adx_choice:
    adx_row = 2 if not rsi_choice and not macd_choice and not stocho_choice else (
        3 if (not macd_choice and not stocho_choice) or (not macd_choice and not rsi_choice) or (not stocho_choice and not rsi_choice) else (
            4 if (not stocho_choice) or (not macd_choice) or (not rsi_choice) else 5))
    fig.add_trace(go.Scatter(x=data['Date'], y=data['ADX'], mode='lines', name='ADX', line=dict(color='darkgreen')), row=adx_row, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['ADX_DMP'], mode='lines', name='ADX DMP', line=dict(color='lightgreen')), row=adx_row, col=1)
    fig.add_trace(go.Scatter(x=data['Date'], y=data['ADX_DMN'], mode='lines', name='ADX DMN', line=dict(color='orange')), row=adx_row, col=1)

# Plot Volume
fig.add_trace(go.Bar(x=data['Date'], y=data['Volume'], name='Volume', marker=dict(color='darkgreen')), row=rows + 1, col=1)

# Customize layout
fig.update_layout(
    title='Brent Crude Oil Futures',
    height=700,
    showlegend=True,
    dragmode='pan',
    xaxis_rangeslider_visible=False,  # Hide default range slider
)

config = {'scrollZoom': True}

# Enable dynamic range for y-axes
fig.update_yaxes(autorange=True)

# Show the plot in Streamlit
st.plotly_chart(fig, config=config)

st.subheader('Technical Analysis Data')
st.dataframe(data)

st.markdown("""
    ## Notes for improvements
    - Add interactive elements to allow users to customize the technical indicators
    - Add features such as backtesting, alerts, and notifications, line annotations, etc.
            """)



# ta = TechnicalAnalysis('data/brent_futures.csv')

# # Allow user to input settings
# length_ma = st.number_input("Moving Average Length", min_value=2, value=20)
# rsi_button = st.checkbox("Show RSI", value=False)
# bb_button = st.checkbox("Show Bollinger Bands", value=False)
# macd_button = st.checkbox("Show MACD", value=False)

# # Calculate moving average
# ta.moving_average(length=length_ma)

# # Conditionally calculate and show indicators
# if rsi_button:
#     ta.rsi()

# if bb_button:
#     ta.bollinger_bands()

# if macd_button:
#     ta.macd()

# # Fetch the updated data
# data = ta.get_data()

# # Plot data using Plotly
# fig = go.Figure()

# # Add candlestick
# fig.add_trace(go.Candlestick(x=data.index, open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], name='Candlestick'))

# # Add moving average
# fig.add_trace(go.Scatter(x=data.index, y=data[f'MA_{length_ma}'], mode='lines', name=f'MA {length_ma}'))

# # Add indicators if toggled
# if rsi_button:
#     fig.add_trace(go.Scatter(x=data.index, y=data[f'RSI_14'], mode='lines', name='RSI'))

# if bb_button:
#     fig.add_trace(go.Scatter(x=data.index, y=data['BB_upper'], mode='lines', name='BB Upper'))
#     fig.add_trace(go.Scatter(x=data.index, y=data['BB_middle'], mode='lines', name='BB Middle'))
#     fig.add_trace(go.Scatter(x=data.index, y=data['BB_lower'], mode='lines', name='BB Lower'))

# if macd_button:
#     fig.add_trace(go.Scatter(x=data.index, y=data['MACD'], mode='lines', name='MACD'))
#     fig.add_trace(go.Scatter(x=data.index, y=data['MACD_Signal'], mode='lines', name='MACD Signal'))

# # Display the chart
# st.plotly_chart(fig)