jgtml

📘 Usage Guide

This guide provides detailed instructions on how to use the Trading Echo Lattice system to bridge trading signals and memory structures.

🧬 Basic Concepts

Before diving into specific commands, let’s understand the key concepts:

• Signal Crystallization: The process of transforming trading signals into persistent memory structures
• Memory Lattice: A recursive knowledge network in Upstash Redis where signals are stored with their relationships
• Recursive Analysis: Analysis methods that recognize patterns across different dimensions (time, instrument, signal type)
• Trading Adapter: The bridge that connects to JGTML trading systems and extracts signal data

🚀 Command Line Interface

The Trading Echo Lattice provides a command-line interface (CLI) for all operations.

Getting Help

# Show all available commands
python -m garden_one.trading_echo_lattice.cli --help

# Get help for a specific command
python -m garden_one.trading_echo_lattice.cli process --help

Initializing the Memory Lattice

Before processing signals, you should initialize the memory lattice with essential knowledge structures:

python -m garden_one.trading_echo_lattice.cli init

This creates reference data and indexes in the memory lattice that help organize signals and analysis results.

Processing Trading Signals

The core functionality is processing trading signals and storing them in the memory lattice:

python -m garden_one.trading_echo_lattice.cli process -i SPX500 -t D1,H4,H1 -d S,B

This command:

• Processes the SPX500 instrument
• Analyzes the D1, H4, and H1 timeframes
• Processes both Sell (S) and Buy (B) signals
• Stores the results in the memory lattice

Options:

• -i, --instrument: Trading instrument (e.g., SPX500, EUR/USD)
• -t, --timeframes: Comma-separated timeframes (e.g., D1,H4,H1)
• -d, --directions: Comma-separated directions (B,S)
• -f, --force-refresh: Force refresh data from source
• --no-higher-tf: Disable higher timeframe influence analysis

Analyzing Signal Performance

To analyze the performance of signals stored in the memory lattice:

python -m garden_one.trading_echo_lattice.cli analyze -i SPX500 -t D1 -s mouth_is_open

This analyzes all “mouth_is_open” signals for SPX500 on the D1 timeframe.

Options:

• -i, --instrument: Trading instrument (optional, analyzes all if omitted)
• -t, --timeframe: Timeframe (optional, analyzes all if omitted)
• -s, --signal-type: Signal type (optional, analyzes all if omitted)
• -l, --limit: Maximum signals to analyze (default 100)

Searching for High-Quality Signals

To find high-quality signal combinations in the memory lattice:

python -m garden_one.trading_echo_lattice.cli search -i SPX500 --min-win-rate 60

This searches for signal combinations for SPX500 with at least 60% win rate.

Options:

• -i, --instrument: Trading instrument
• -t, --timeframe: Timeframe (optional)
• -s, --signal-type: Signal type (optional)
• --min-win-rate: Minimum win rate threshold (default 60.0)
• -l, --limit: Maximum signals to analyze (default 100)

🔄 Advanced Usage

Working with Different Namespaces

You can segment your memory lattice data using different namespaces:

# Initialize a separate namespace for experimental signals
python -m garden_one.trading_echo_lattice.cli -n experimental init

# Process signals in the experimental namespace
python -m garden_one.trading_echo_lattice.cli -n experimental process -i SPX500 -t D1

Batch Processing Multiple Instruments

For processing multiple instruments, you can create a shell script:

#!/bin/bash
# batch_process.sh

INSTRUMENTS=("SPX500" "EUR/USD" "GBP/USD" "AUD/USD")
TIMEFRAMES="D1,H4"
DIRECTIONS="B,S"

for instrument in "${INSTRUMENTS[@]}"; do
  echo "Processing $instrument..."
  python -m garden_one.trading_echo_lattice.cli process -i "$instrument" -t "$TIMEFRAMES" -d "$DIRECTIONS"
  sleep 2
done

Make it executable and run it:

chmod +x batch_process.sh
./batch_process.sh

Quiet Mode for Scripts

For scripting purposes, use the quiet mode to suppress output:

python -m garden_one.trading_echo_lattice.cli -q process -i SPX500 -t D1

🧪 Example Workflows

1. Daily Trading Signal Analysis

# Refresh and process today's signals
python -m garden_one.trading_echo_lattice.cli process -i SPX500 -t D1,H4 -d S -f

# Search for high-quality combinations
python -m garden_one.trading_echo_lattice.cli search -i SPX500 --min-win-rate 70

2. Multi-Instrument Performance Analysis

# Process multiple instruments
python -m garden_one.trading_echo_lattice.cli process -i EUR/USD -t D1,H4,H1 -d B,S
python -m garden_one.trading_echo_lattice.cli process -i GBP/USD -t D1,H4,H1 -d B,S

# Analyze specific signal types across instruments
python -m garden_one.trading_echo_lattice.cli analyze -s mouth_is_open -t D1

3. Long-term Pattern Discovery

# Process long-term timeframes
python -m garden_one.trading_echo_lattice.cli process -i SPX500 -t W1,D1 -d S

# Analyze how weekly patterns influence daily signals
python -m garden_one.trading_echo_lattice.cli search -i SPX500 -t D1 --min-win-rate 60

🔍 Understanding Output

The system provides detailed output on the console. Here’s how to interpret it:

• Processing output: Shows the number of signals processed for each timeframe and direction
• Analysis output: Displays win rates, profit/loss metrics, and signal counts
• Search output: Lists high-quality signal combinations with their performance metrics

For more detailed output, you can explore the data directly in Upstash Redis using their console interface.

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🧠 Mia: The usage patterns recursively build knowledge in the memory lattice.
🌸 Miette: Each command is like tending a different part of your trading garden, watching patterns bloom across time!
🎵 JeremyAI: The rhythmic invocation of processing and analysis creates a harmonic progression that gradually reveals market wisdom.

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