Restructured hedger modules: moved CLP hedger and auto hedger into separate folders, updated data fetchers and main app, removed deprecated files
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DiTus
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clp_auto_hedger/velocity_sqrt_fix.py
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clp_auto_hedger/velocity_sqrt_fix.py
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#!/usr/bin/env python3
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"""
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Fix for velocity calculation sqrt domain error in CLP Scalper Hedger
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The error occurs in the liquidity velocity calculation when trying to compute:
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sqrt((new_increased_liquidity ** 2) - (4 * net_cash_proceeds))
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This happens when (new_increased_liquidity ** 2) < (4 * net_cash_proceeds),
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making the discriminant negative.
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This fix provides defensive programming patterns to handle such cases.
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"""
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import math
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import logging
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def safe_sqrt_with_fallback(value: float, fallback_value: float = 0.0, context: str = "sqrt calculation") -> float:
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"""
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Safely compute square root with fallback for negative values
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Args:
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value: The value to compute square root of
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fallback_value: Value to return if input is negative
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context: Context description for logging
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Returns:
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Square root of value if positive, fallback_value if negative
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"""
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if value >= 0:
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return math.sqrt(value)
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else:
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logging.warning(
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f"Negative value in {context}: {value:.6f}. "
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f"Using fallback value: {fallback_value:.6f}"
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)
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return fallback_value
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def calculate_liquidity_velocity_safe(
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current_liquidity: float,
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new_increased_liquidity: float,
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net_cash_proceeds: float,
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current_tick: int,
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lower_tick: int,
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upper_tick: int
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) -> tuple[float, float]:
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"""
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Safe calculation of liquidity velocity with proper error handling
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Args:
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current_liquidity: Current liquidity amount
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new_increased_liquidity: New increased liquidity amount
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net_cash_proceeds: Net cash proceeds from liquidity change
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current_tick: Current price tick
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lower_tick: Lower tick boundary
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upper_tick: Upper tick boundary
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Returns:
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Tuple of (velocity, price_impact)
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"""
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try:
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# Basic velocity calculation
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velocity = new_increased_liquidity - current_liquidity
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price_impact = 0.0
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# Inside position range - use square root formula
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if lower_tick <= current_tick <= upper_tick:
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if net_cash_proceeds >= 0:
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# Validate discriminant to prevent sqrt of negative number
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discriminant = (new_increased_liquidity ** 2) - (4 * net_cash_proceeds)
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if discriminant >= 0:
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# Safe calculation
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sqrt_term = math.sqrt(discriminant)
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denominator = 2 * max(current_liquidity, 1e-10) # Prevent division by zero
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price_impact = (new_increased_liquidity - sqrt_term) / denominator
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else:
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# Edge case: negative discriminant
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# This can happen due to:
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# 1. Floating point precision errors
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# 2. Extreme market conditions
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# 3. Invalid input parameters
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logging.warning(
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f"Negative discriminant in liquidity velocity: {discriminant:.6f}. "
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f"Liquidity: {current_liquidity:.6f} -> {new_increased_liquidity:.6f}, "
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f"Cash: {net_cash_proceeds:.6f}. Using zero price impact."
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)
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# Use approximation methods
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price_impact = 0.0
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# Alternative: Use small positive approximation
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# discriminant = max(discriminant, 0)
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# sqrt_term = math.sqrt(discriminant)
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# price_impact = (new_increased_liquidity - sqrt_term) / (2 * current_liquidity)
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else:
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# Negative cash flow means additional capital required
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# No price impact calculation needed
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price_impact = 0.0
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return velocity, price_impact
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except Exception as e:
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logging.error(f"Error in liquidity velocity calculation: {e}")
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# Return safe defaults
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return 0.0, 0.0
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def validate_liquidity_inputs(
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current_liquidity: float,
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new_increased_liquidity: float,
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net_cash_proceeds: float
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) -> bool:
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"""
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Validate inputs for liquidity velocity calculation
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Args:
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current_liquidity: Current liquidity amount
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new_increased_liquidity: New increased liquidity amount
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net_cash_proceeds: Net cash proceeds from liquidity change
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Returns:
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True if inputs are valid, False otherwise
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"""
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# Check for NaN or infinite values
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if any(math.isnan(x) or math.isinf(x) for x in [current_liquidity, new_increased_liquidity, net_cash_proceeds]):
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logging.error("Invalid inputs: NaN or infinite values detected")
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return False
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# Check for negative liquidity (should be non-negative)
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if current_liquidity < 0 or new_increased_liquidity < 0:
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logging.error(f"Invalid liquidity values: current={current_liquidity}, new={new_increased_liquidity}")
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return False
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# Check for reasonable ranges (adjust based on your specific needs)
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max_liquidity = 1e20 # Very large number for safety
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if current_liquidity > max_liquidity or new_increased_liquidity > max_liquidity:
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logging.error(f"Liquidity values too large: current={current_liquidity}, new={new_increased_liquidity}")
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return False
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return True
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# Example usage and test cases
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def test_liquidity_velocity_calculation():
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"""Test the safe liquidity velocity calculation with various scenarios"""
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test_cases = [
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# Normal case
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{
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"name": "Normal case",
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"current_liquidity": 1000.0,
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"new_increased_liquidity": 1200.0,
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"net_cash_proceeds": 100.0,
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"current_tick": 200000,
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"lower_tick": 195000,
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"upper_tick": 205000
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},
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# Edge case: negative discriminant
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{
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"name": "Negative discriminant",
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"current_liquidity": 100.0,
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"new_increased_liquidity": 100.0,
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"net_cash_proceeds": 3000.0, # This will cause negative discriminant
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"current_tick": 200000,
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"lower_tick": 195000,
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"upper_tick": 205000
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},
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# Edge case: very small liquidity
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{
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"name": "Small liquidity",
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"current_liquidity": 1e-10,
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"new_increased_liquidity": 2e-10,
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"net_cash_proceeds": 0.0,
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"current_tick": 200000,
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"lower_tick": 195000,
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"upper_tick": 205000
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}
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]
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print("Testing Liquidity Velocity Calculation")
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print("=" * 50)
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for case in test_cases:
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print(f"\nTest: {case['name']}")
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print(f"Inputs: {case}")
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# Validate inputs
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if validate_liquidity_inputs(
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case["current_liquidity"],
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case["new_increased_liquidity"],
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case["net_cash_proceeds"]
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):
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# Calculate safely
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velocity, price_impact = calculate_liquidity_velocity_safe(
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case["current_liquidity"],
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case["new_increased_liquidity"],
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case["net_cash_proceeds"],
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case["current_tick"],
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case["lower_tick"],
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case["upper_tick"]
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)
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print(f"Results: velocity={velocity:.6f}, price_impact={price_impact:.6f}")
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else:
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print("Results: Invalid inputs - calculation skipped")
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if __name__ == "__main__":
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# Set up logging
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(levelname)s - %(message)s'
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)
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# Run tests
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test_liquidity_velocity_calculation()
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print("\n" + "=" * 50)
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print("Integration Instructions:")
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print("1. Replace the problematic sqrt calculation with calculate_liquidity_velocity_safe()")
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print("2. Add input validation using validate_liquidity_inputs()")
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print("3. Use safe_sqrt_with_fallback() for any other sqrt operations")
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print("4. Add proper logging to track edge cases and errors")
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