5f7702469e
- Removed v10 TradingView indicator (moneyline_v10_momentum_dots.pinescript) - Removed v10 penalty system from signal-quality.ts (-30/-25 point penalties) - Removed backtest result files (sweep_*.csv) - Updated copilot-instructions.md to remove v10 references - Simplified direction-specific quality thresholds (LONG 90+, SHORT 80+) Rationale: - 1,944 parameter combinations tested in backtest - All top results IDENTICAL (568 trades, $498 P&L, 61.09% WR) - Momentum parameters had ZERO impact on trade selection - Profit factor 1.027 too low (barely profitable after fees) - Max drawdown -$1,270 vs +$498 profit = terrible risk-reward - v10 penalties were blocking good trades (bug: applied to wrong positions) Keeping v9 as production system - simpler, proven, effective.
85 lines
2.5 KiB
Python
85 lines
2.5 KiB
Python
from typing import Any, List
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from numpy.lib.index_tricks import AxisConcatenator
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from numpy.ma.core import (
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dot as dot,
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mask_rowcols as mask_rowcols,
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)
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__all__: List[str]
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def count_masked(arr, axis=...): ...
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def masked_all(shape, dtype = ...): ...
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def masked_all_like(arr): ...
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class _fromnxfunction:
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__name__: Any
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__doc__: Any
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def __init__(self, funcname): ...
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def getdoc(self): ...
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def __call__(self, *args, **params): ...
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class _fromnxfunction_single(_fromnxfunction):
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def __call__(self, x, *args, **params): ...
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class _fromnxfunction_seq(_fromnxfunction):
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def __call__(self, x, *args, **params): ...
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class _fromnxfunction_allargs(_fromnxfunction):
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def __call__(self, *args, **params): ...
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atleast_1d: _fromnxfunction_allargs
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atleast_2d: _fromnxfunction_allargs
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atleast_3d: _fromnxfunction_allargs
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vstack: _fromnxfunction_seq
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row_stack: _fromnxfunction_seq
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hstack: _fromnxfunction_seq
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column_stack: _fromnxfunction_seq
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dstack: _fromnxfunction_seq
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stack: _fromnxfunction_seq
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hsplit: _fromnxfunction_single
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diagflat: _fromnxfunction_single
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def apply_along_axis(func1d, axis, arr, *args, **kwargs): ...
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def apply_over_axes(func, a, axes): ...
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def average(a, axis=..., weights=..., returned=...): ...
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def median(a, axis=..., out=..., overwrite_input=..., keepdims=...): ...
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def compress_nd(x, axis=...): ...
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def compress_rowcols(x, axis=...): ...
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def compress_rows(a): ...
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def compress_cols(a): ...
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def mask_rows(a, axis = ...): ...
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def mask_cols(a, axis = ...): ...
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def ediff1d(arr, to_end=..., to_begin=...): ...
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def unique(ar1, return_index=..., return_inverse=...): ...
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def intersect1d(ar1, ar2, assume_unique=...): ...
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def setxor1d(ar1, ar2, assume_unique=...): ...
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def in1d(ar1, ar2, assume_unique=..., invert=...): ...
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def isin(element, test_elements, assume_unique=..., invert=...): ...
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def union1d(ar1, ar2): ...
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def setdiff1d(ar1, ar2, assume_unique=...): ...
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def cov(x, y=..., rowvar=..., bias=..., allow_masked=..., ddof=...): ...
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def corrcoef(x, y=..., rowvar=..., bias = ..., allow_masked=..., ddof = ...): ...
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class MAxisConcatenator(AxisConcatenator):
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concatenate: Any
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@classmethod
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def makemat(cls, arr): ...
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def __getitem__(self, key): ...
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class mr_class(MAxisConcatenator):
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def __init__(self): ...
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mr_: mr_class
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def flatnotmasked_edges(a): ...
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def notmasked_edges(a, axis=...): ...
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def flatnotmasked_contiguous(a): ...
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def notmasked_contiguous(a, axis=...): ...
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def clump_unmasked(a): ...
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def clump_masked(a): ...
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def vander(x, n=...): ...
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def polyfit(x, y, deg, rcond=..., full=..., w=..., cov=...): ...
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