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data fixes; indicator=>workspace sync

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This commit is contained in:
Tim Olson
2026-03-31 20:29:12 -04:00
parent 998f69fa1a
commit cd28e18e52
45 changed files with 1324 additions and 1239 deletions
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48
gateway/src/harness/subagents/research/memory/usage-examples.md
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@@ -112,10 +112,12 @@ fig, ax = api.charting.plot_ohlc(
### Adding Indicator Panels
Use **pandas-ta** for all indicator calculations. Do not write manual rolling/ewm implementations.
```python
from dexorder.api import get_api
import asyncio
import pandas as pd
import pandas_ta as ta
api = get_api()
@@ -127,8 +129,9 @@ df = asyncio.run(api.data.historical_ohlc(
end_time="2021-12-21"
))
# Calculate a simple moving average
df['sma_20'] = df['close'].rolling(window=20).mean()
# Calculate indicators using pandas-ta
df['sma_20'] = ta.sma(df['close'], length=20)
df['rsi'] = ta.rsi(df['close'], length=14)
# Create chart
fig, ax = api.charting.plot_ohlc(df, title="BTC/USDT with SMA")
@@ -138,7 +141,6 @@ ax.plot(df.index, df['sma_20'], label="SMA 20", color="blue", linewidth=2)
ax.legend()
# Add RSI indicator panel below
df['rsi'] = calculate_rsi(df['close'], 14) # Your RSI calculation
rsi_ax = api.charting.add_indicator_panel(
fig, df,
columns=["rsi"],
@@ -149,12 +151,40 @@ rsi_ax.axhline(70, color='red', linestyle='--', alpha=0.5)
rsi_ax.axhline(30, color='green', linestyle='--', alpha=0.5)
```
### Multi-Output Indicators
Some pandas-ta indicators return a DataFrame. Extract the columns you need:
```python
import pandas_ta as ta
# MACD returns: MACD_12_26_9, MACDh_12_26_9, MACDs_12_26_9
macd_df = ta.macd(df['close'], fast=12, slow=26, signal=9)
df['macd'] = macd_df.iloc[:, 0] # MACD line
df['macd_hist'] = macd_df.iloc[:, 1] # Histogram
df['macd_signal'] = macd_df.iloc[:, 2] # Signal line
# Bollinger Bands returns: BBL, BBM, BBU, BBB, BBP
bb_df = ta.bbands(df['close'], length=20, std=2.0)
df['bb_upper'] = bb_df.iloc[:, 2] # BBU
df['bb_mid'] = bb_df.iloc[:, 1] # BBM
df['bb_lower'] = bb_df.iloc[:, 0] # BBL
# Stochastic returns: STOCHk, STOCHd
stoch_df = ta.stoch(df['high'], df['low'], df['close'], k=14, d=3, smooth_k=3)
df['stoch_k'] = stoch_df.iloc[:, 0]
df['stoch_d'] = stoch_df.iloc[:, 1]
# ATR (uses high, low, close)
df['atr'] = ta.atr(df['high'], df['low'], df['close'], length=14)
```
## Complete Example
```python
from dexorder.api import get_api
import asyncio
import pandas as pd
import pandas_ta as ta
# Get API instance
api = get_api()
@@ -168,9 +198,9 @@ df = asyncio.run(api.data.historical_ohlc(
extra_columns=["volume"]
))
# Add some analysis
df['sma_20'] = df['close'].rolling(window=20).mean()
df['sma_50'] = df['close'].rolling(window=50).mean()
# Add moving averages using pandas-ta
df['sma_20'] = ta.sma(df['close'], length=20)
df['ema_50'] = ta.ema(df['close'], length=50)
# Create chart with volume
fig, ax = api.charting.plot_ohlc(
@@ -182,7 +212,7 @@ fig, ax = api.charting.plot_ohlc(
# Overlay moving averages
ax.plot(df.index, df['sma_20'], label="SMA 20", color="blue", linewidth=1.5)
ax.plot(df.index, df['sma_50'], label="SMA 50", color="red", linewidth=1.5)
ax.plot(df.index, df['ema_50'], label="EMA 50", color="red", linewidth=1.5)
ax.legend()
# Print summary statistics