扩展指标

2026-07-09 05:08:16 +08:00
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+Quick Start
+===========
+
+Installation
+------------
+
+.. code-block:: bash
+
+   pip install ferro-ta
+
+   # For Pandas support:
+   pip install ferro-ta pandas
+
+   # For benchmarks:
+   pip install ferro-ta pytest-benchmark
+
+Basic Usage
+-----------
+
+All functions accept NumPy arrays and return NumPy arrays:
+
+.. code-block:: python
+
+   import numpy as np
+   from ferro_ta import SMA, EMA, RSI, MACD, BBANDS, ATR
+
+   close = np.array([44.34, 44.09, 44.15, 43.61, 44.33, 44.83, 45.10, 45.15, 43.61, 44.33])
+   high  = close + 0.5
+   low   = close - 0.5
+
+   # Single output
+   sma  = SMA(close, timeperiod=5)
+   ema  = EMA(close, timeperiod=5)
+   rsi  = RSI(close, timeperiod=5)
+   atr  = ATR(high, low, close, timeperiod=5)
+
+   # Multi output
+   upper, middle, lower = BBANDS(close, timeperiod=5)
+   macd_line, signal, histogram = MACD(close)
+
+Pandas Integration
+------------------
+
+All functions transparently accept ``pandas.Series`` and preserve the index:
+
+.. code-block:: python
+
+   import pandas as pd
+   from ferro_ta import SMA, BBANDS
+
+   idx   = pd.date_range("2024-01-01", periods=10, freq="D")
+   close = pd.Series([44.34, 44.09, 44.15, 43.61, 44.33,
+                      44.83, 45.10, 45.15, 43.61, 44.33], index=idx)
+
+   sma = SMA(close, timeperiod=3)           # → pd.Series, same index
+   upper, mid, lower = BBANDS(close, timeperiod=3)  # → tuple of pd.Series
+
+Streaming / Live Trading
+------------------------
+
+Use the :mod:`ferro_ta.streaming` module for bar-by-bar processing:
+
+.. code-block:: python
+
+   from ferro_ta.streaming import StreamingSMA, StreamingRSI, StreamingATR
+
+   sma = StreamingSMA(period=5)
+   rsi = StreamingRSI(period=14)
+   atr = StreamingATR(period=14)
+
+   for bar in live_feed:
+       current_sma = sma.update(bar.close)
+       current_rsi = rsi.update(bar.close)
+       current_atr = atr.update(bar.high, bar.low, bar.close)
+
+Extended Indicators
+-------------------
+
+.. code-block:: python
+
+   from ferro_ta import VWAP, SUPERTREND, ICHIMOKU, DONCHIAN, PIVOT_POINTS
+   import numpy as np
+
+   high  = np.array([...])
+   low   = np.array([...])
+   close = np.array([...])
+   vol   = np.array([...])
+
+   # VWAP
+   vwap = VWAP(high, low, close, vol)
+   rolling_vwap = VWAP(high, low, close, vol, timeperiod=14)
+
+   # Supertrend
+   st_line, direction = SUPERTREND(high, low, close, timeperiod=7, multiplier=3.0)
+
+   # Ichimoku Cloud
+   tenkan, kijun, senkou_a, senkou_b, chikou = ICHIMOKU(high, low, close)
+
+   # Donchian Channels
+   dc_upper, dc_mid, dc_lower = DONCHIAN(high, low, timeperiod=20)
+
+   # Pivot Points
+   pivot, r1, s1, r2, s2 = PIVOT_POINTS(high, low, close, method="classic")
+
+Derivatives Analytics
+---------------------
+
+.. code-block:: python
+
+   from ferro_ta.analysis.options import greeks, option_price
+   from ferro_ta.analysis.futures import basis
+
+   call_price = option_price(100.0, 100.0, 0.05, 1.0, 0.20, option_type="call")
+   call_greeks = greeks(100.0, 100.0, 0.05, 1.0, 0.20, option_type="call")
+   front_basis = basis(100.0, 103.0)
+
+See :doc:`derivatives` for the full analytics surface, including implied
+volatility inversion, smile metrics, strike selection, futures curve tools,
+strategy schemas, and multi-leg payoff helpers.