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80 lines
4.0 KiB
Python
80 lines
4.0 KiB
Python
from _decimal import Decimal
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from math import exp
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from hummingbot.strategy_v2.utils.distributions import Distributions
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def normalize(values):
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total = sum(values)
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return [val / total for val in values]
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def distribution_inputs(column, dist_type_name, levels=3, default_values=None):
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if dist_type_name == "Spread":
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dist_type = column.selectbox(
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f"Type of {dist_type_name} Distribution",
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("Manual", "GeoCustom", "Geometric", "Fibonacci", "Logarithmic", "Arithmetic", "Linear"),
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key=f"{column}_{dist_type_name.lower()}_dist_type",
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# Set the default value
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)
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else:
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dist_type = column.selectbox(
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f"Type of {dist_type_name} Distribution",
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("Manual", "Geometric", "Fibonacci", "Logarithmic", "Arithmetic"),
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key=f"{column}_{dist_type_name.lower()}_dist_type",
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# Set the default value
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)
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base, scaling_factor, step, ratio, manual_values = None, None, None, None, None
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if dist_type != "Manual":
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start = column.number_input(f"{dist_type_name} Start Value", value=1.0,
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key=f"{column}_{dist_type_name.lower()}_start")
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if dist_type == "Logarithmic":
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base = column.number_input(f"{dist_type_name} Log Base", value=exp(1),
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key=f"{column}_{dist_type_name.lower()}_base")
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scaling_factor = column.number_input(f"{dist_type_name} Scaling Factor", value=2.0,
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key=f"{column}_{dist_type_name.lower()}_scaling")
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elif dist_type == "Arithmetic":
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step = column.number_input(f"{dist_type_name} Step", value=0.3,
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key=f"{column}_{dist_type_name.lower()}_step")
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elif dist_type == "Geometric":
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ratio = column.number_input(f"{dist_type_name} Ratio", value=2.0,
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key=f"{column}_{dist_type_name.lower()}_ratio")
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elif dist_type == "GeoCustom":
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ratio = column.number_input(f"{dist_type_name} Ratio", value=2.0,
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key=f"{column}_{dist_type_name.lower()}_ratio")
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elif dist_type == "Linear":
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step = column.number_input(f"{dist_type_name} End", value=1.0,
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key=f"{column}_{dist_type_name.lower()}_end")
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else:
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if default_values:
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manual_values = [column.number_input(f"{dist_type_name} for level {i + 1}", value=value * 100.0,
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key=f"{column}_{dist_type_name.lower()}_{i}") for i, value in
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enumerate(default_values)]
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else:
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manual_values = [column.number_input(f"{dist_type_name} for level {i + 1}", value=i + 1.0,
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key=f"{column}_{dist_type_name.lower()}_{i}") for i, value in range(levels)]
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start = None # As start is not relevant for Manual type
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return dist_type, start, base, scaling_factor, step, ratio, manual_values
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def get_distribution(dist_type, n_levels, start, base=None, scaling_factor=None, step=None, ratio=None,
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manual_values=None):
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distribution = []
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if dist_type == "Manual":
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distribution = manual_values
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elif dist_type == "Linear":
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distribution = Distributions.linear(n_levels, start, step)
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elif dist_type == "Fibonacci":
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distribution = Distributions.fibonacci(n_levels, start)
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elif dist_type == "Logarithmic":
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distribution = Distributions.logarithmic(n_levels, base, scaling_factor, start)
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elif dist_type == "Arithmetic":
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distribution = Distributions.arithmetic(n_levels, start, step)
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elif dist_type == "Geometric":
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distribution = Distributions.geometric(n_levels, start, ratio)
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elif dist_type == "GeoCustom":
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distribution = [Decimal("0")] + Distributions.geometric(n_levels - 1, start, ratio)
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return [float(val) for val in distribution]
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