Status when starting a new project on Chat GPT

This commit is contained in:
DaM
2026-03-01 16:50:15 +01:00
parent 547a909965
commit 2ec51d0daa
10 changed files with 1232 additions and 510 deletions

View File

@@ -21,27 +21,11 @@ from src.risk.sizing.percent_risk import PercentRiskSizer
# --------------------------------------------------
# Strategy registry (con metadata de parámetros)
# --------------------------------------------------
from src.strategies.registry import STRATEGY_REGISTRY
from src.strategies.moving_average import MovingAverageCrossover
from src.strategies.rsi_strategy import RSIStrategy
from src.strategies.buy_and_hold import BuyAndHold
STRATEGY_REGISTRY = {
"moving_average": {
"class": MovingAverageCrossover,
"params": ["fast_period", "slow_period"],
},
"rsi": {
"class": RSIStrategy,
"params": ["rsi_period", "overbought", "oversold"],
},
"buy_and_hold": {
"class": BuyAndHold,
"params": [],
},
}
# --------------------------------------------------
# Helpers
# --------------------------------------------------
@@ -49,15 +33,24 @@ STRATEGY_REGISTRY = {
def list_available_strategies() -> List[Dict[str, Any]]:
"""
Devuelve metadata completa para UI.
Usa parameters_schema() como fuente de verdad.
"""
out = []
for sid, entry in STRATEGY_REGISTRY.items():
out: List[Dict[str, Any]] = []
for strategy_id, strategy_class in STRATEGY_REGISTRY.items():
if not hasattr(strategy_class, "parameters_schema"):
continue
schema = strategy_class.parameters_schema()
out.append({
"strategy_id": sid,
"name": entry["class"].__name__,
"params": entry["params"],
"tags": [], # puedes rellenar más adelante
"strategy_id": strategy_id,
"name": strategy_class.__name__,
"params": list(schema.keys()),
"parameters_schema": schema, # 🔥 ahora enviamos schema completo
"tags": [],
})
return out
@@ -67,7 +60,7 @@ def _build_stop_loss(stop_schema) -> object | None:
if stop_schema.type == "fixed":
return FixedStop(stop_fraction=float(stop_schema.stop_fraction))
if stop_schema.type == "trailing":
return TrailingStop(stop_fraction=float(stop_schema.stop_fraction))
return TrailingStop(trailing_fraction=float(stop_schema.stop_fraction))
if stop_schema.type == "atr":
return ATRStop(
atr_period=int(stop_schema.atr_period),
@@ -94,27 +87,6 @@ def _accumulate_equity(initial: float, returns_pct: List[float]) -> List[float]:
return eq
def _build_param_values(min_v: float, max_v: float, step: float) -> List[float]:
min_v = float(min_v)
max_v = float(max_v)
step = float(step)
# Valor único si min == max
if min_v == max_v:
return [min_v]
# Valor único si step <= 1
if step <= 1:
return [min_v]
values = []
v = min_v
while v <= max_v:
values.append(v)
v += step
return values
# --------------------------------------------------
# Main
# --------------------------------------------------
@@ -162,14 +134,21 @@ def inspect_strategies_config(
step_td = pd.Timedelta(days=int(payload.wf.step_days or payload.wf.test_days))
overall_status = "ok"
log.info(f"🔥 Strategies received: {len(payload.strategies)}")
results: List[Dict[str, Any]] = []
series: Dict[str, Any] = {"strategies": {}} if include_series else {}
log.info(f"🔥 Strategies received: {len(payload.strategies)}")
for sel in payload.strategies:
sid = sel.strategy_id
entry = STRATEGY_REGISTRY.get(sid)
log.info(f"🧠 Step3 | Processing strategy: {sid}")
if entry is None:
results.append({
"strategy_id": sid,
@@ -183,10 +162,13 @@ def inspect_strategies_config(
"windows": [],
})
overall_status = "fail"
log.error(f"❌ Strategy not found in registry: {sid}")
continue
strategy_class = entry["class"]
valid_params = set(entry["params"])
strategy_class = STRATEGY_REGISTRY[sid]
schema = strategy_class.parameters_schema()
valid_params = set(schema.keys())
range_params = set(sel.parameters.keys())
@@ -209,17 +191,13 @@ def inspect_strategies_config(
continue
# --------------------------------------------------
# Convert ranges -> param_grid real
# Build fixed_params (VALIDATION MODE)
# --------------------------------------------------
param_grid = {}
fixed_params = {}
for pname, pvalue in sel.parameters.items():
fixed_params[pname] = pvalue
for pname, prange in sel.parameters.items():
values = _build_param_values(
min_v=prange.min,
max_v=prange.max,
step=prange.step,
)
param_grid[pname] = values
# Wrapper sizer
class _CappedSizer(type(base_sizer)):
@@ -248,7 +226,8 @@ def inspect_strategies_config(
try:
wf = WalkForwardValidator(
strategy_class=strategy_class,
param_grid=param_grid,
param_grid=None,
fixed_params=fixed_params,
data=df,
train_window=train_td,
test_window=test_td,
@@ -256,36 +235,47 @@ def inspect_strategies_config(
initial_capital=float(payload.account_equity),
commission=float(payload.commission),
slippage=float(payload.slippage),
optimizer_metric=str(payload.optimization.optimizer_metric),
position_sizer=capped_sizer,
stop_loss=stop_loss,
max_combinations=int(payload.optimization.max_combinations),
progress_callback=progress_callback,
)
wf_res = wf.run()
win_df: pd.DataFrame = wf_res["windows"]
if win_df is None or win_df.empty:
status = "fail"
msg = "WF produced no valid windows"
overall_status = "fail"
windows_out = []
oos_returns = []
oos_dd = []
warnings_list = []
n_windows = 0
if win_df is None or win_df.empty:
status = "warning"
msg = "No closed trades in OOS"
warnings_list.append("Walk-forward produced no closed trades.")
else:
oos_returns = win_df["return_pct"].tolist()
oos_dd = win_df["max_dd_pct"].tolist()
n_windows = len(win_df)
trades = win_df["trades"].astype(int).tolist()
too_few = sum(t < int(payload.optimization.min_trades_test) for t in trades)
too_few = sum(t < int(payload.wf.min_trades_test) for t in trades)
if too_few > 0:
warnings_list.append(
f"{too_few} test windows have fewer than {payload.wf.min_trades_test} trades"
)
windows_out = []
if warnings_list:
status = "warning"
msg = f"{too_few} windows below min_trades_test"
msg = "Validation completed with warnings"
if overall_status == "ok":
overall_status = "warning"
else:
status = "ok"
msg = "WF OK"
windows_out = []
for _, r in win_df.iterrows():
windows_out.append({
"window": int(r["window"]),
@@ -311,6 +301,7 @@ def inspect_strategies_config(
"strategy_id": sid,
"status": status,
"message": msg,
"warnings": warnings_list if status == "warning" else [],
"n_windows": int(len(windows_out)),
"oos_final_equity": oos_final,
"oos_total_return_pct": float(oos_total_return),
@@ -323,6 +314,7 @@ def inspect_strategies_config(
series["strategies"][sid] = {
"window_returns_pct": oos_returns,
"window_equity": eq_curve,
"window_trades": win_df["trades"].tolist(),
}
except Exception as e:

View File

@@ -1,6 +1,6 @@
# src/backtest/walk_forward.py
# src/core/walk_forward.py
import pandas as pd
from typing import List, Dict, Optional
from typing import List, Dict, Optional, Callable, Any
from src.core.optimizer import ParameterOptimizer
from src.core.engine import Engine
from src.risk.sizing.base import PositionSizer
@@ -19,7 +19,7 @@ class WalkForwardValidator:
def __init__(
self,
strategy_class,
param_grid: dict,
param_grid: Optional[dict],
data: pd.DataFrame,
train_window: pd.Timedelta,
test_window: pd.Timedelta,
@@ -34,9 +34,12 @@ class WalkForwardValidator:
stop_loss: Optional[StopLoss] = None,
max_combinations: Optional[int] = None,
progress_callback: Optional[callable] = None,
fixed_params: Optional[dict] = None,
):
self.strategy_class = strategy_class
self.param_grid = param_grid
self.fixed_params = fixed_params
self.data = data.sort_index()
self.train_window = train_window
@@ -62,6 +65,13 @@ class WalkForwardValidator:
if not self.data.index.is_monotonic_increasing:
raise ValueError("data.index debe estar ordenado cronológicamente")
# ✅ Validación de modo (NUEVO, mínimo y claro)
if self.param_grid is not None and self.fixed_params is not None:
raise ValueError("WalkForwardValidator: usa param_grid (optimization) o fixed_params (validation), no ambos.")
if self.param_grid is None and self.fixed_params is None:
raise ValueError("WalkForwardValidator: debes pasar param_grid o fixed_params.")
# ------------------------------------------------------------------
# 🔹 GENERACIÓN DE VENTANAS TEMPORALES
# ------------------------------------------------------------------
@@ -186,6 +196,13 @@ class WalkForwardValidator:
continue
# 1⃣ Optimización TRAIN
best_train_metric = None
if self.fixed_params is not None:
# ✅ VALIDATION MODE: sin optimización
best_params = self.fixed_params
else:
# ✅ OPTIMIZATION MODE
optimizer = ParameterOptimizer(
strategy_class=self.strategy_class,
data=train_data,
@@ -261,6 +278,7 @@ class WalkForwardValidator:
"n_windows": len(rows),
"data_start": self.data.index.min(),
"data_end": self.data.index.max(),
"mode": "validation" if self.fixed_params is not None else "optimization"
},
"windows": pd.DataFrame(rows),
"raw_results": raw_results,

View File

@@ -10,7 +10,12 @@ class MovingAverageCrossover(Strategy):
"""
Estrategia de cruce de medias móviles
Señales:
Señales:@classmethod
def default_parameters(cls) -> dict:
return {
"fast_period": 10,
"slow_period": 30,
}
- BUY: Cruce alcista de medias + (ADX >= threshold si está activado)
- SELL: Cruce bajista de medias
- HOLD: En cualquier otro caso
@@ -28,6 +33,8 @@ class MovingAverageCrossover(Strategy):
Sin ADX todavía → primero evaluamos la señal “pura”
"""
strategy_id = "moving_average"
def __init__(
self,
fast_period: int = 20,
@@ -55,7 +62,38 @@ class MovingAverageCrossover(Strategy):
if self.ma_type not in ['sma', 'ema']:
raise ValueError("ma_type debe ser 'sma' o 'ema'")
# ------------------------------------------------------------------
@classmethod
def parameters_schema(cls) -> dict:
return {
"fast_period": {
"type": "int",
"min": 1,
"max": 500,
"default": 20,
},
"slow_period": {
"type": "int",
"min": 1,
"max": 500,
"default": 50,
},
"ma_type": {
"type": "enum",
"choices": ["sma", "ema"],
"default": "ema",
},
"use_adx": {
"type": "bool",
"default": False,
},
"adx_threshold": {
"type": "float",
"min": 1,
"max": 100,
"default": 20.0,
},
}
def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
"""

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@@ -0,0 +1,16 @@
# src/strategies/registry.py
from .moving_average import MovingAverageCrossover
from .rsi_strategy import RSIStrategy
from .buy_and_hold import BuyAndHold
ALL_STRATEGIES = [
MovingAverageCrossover,
RSIStrategy,
]
STRATEGY_REGISTRY = {
cls.strategy_id: cls
for cls in ALL_STRATEGIES
}

View File

@@ -20,6 +20,8 @@ class RSIStrategy(Strategy):
overbought_threshold: Umbral de sobrecompra (default: 70)
"""
strategy_id = "rsi"
def __init__(self, rsi_period: int = 14, oversold_threshold: float = 30, overbought_threshold: float = 70):
params = {
@@ -34,6 +36,30 @@ class RSIStrategy(Strategy):
self.oversold = oversold_threshold
self.overbought = overbought_threshold
@classmethod
def parameters_schema(cls) -> dict:
return {
"rsi_period": {
"type": "int",
"min": 1,
"max": 200,
"default": 14,
},
"oversold": {
"type": "float",
"min": 0,
"max": 100,
"default": 30,
},
"overbought": {
"type": "float",
"min": 0,
"max": 100,
"default": 70,
},
}
def init_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
"""
Calcula el RSI

View File

@@ -10,6 +10,7 @@ from fastapi import APIRouter, Depends, HTTPException, Request
from fastapi.responses import JSONResponse, HTMLResponse
from src.data.storage import StorageManager
from src.strategies.registry import STRATEGY_REGISTRY
from src.calibration.strategies_inspector import (
inspect_strategies_config,
list_available_strategies,
@@ -37,22 +38,40 @@ def get_storage() -> StorageManager:
@router.get("/catalog")
def strategy_catalog():
strategies = list_available_strategies()
# Añadimos defaults sugeridos
for s in strategies:
s["parameters_meta"] = [
{
"name": p,
"type": "int",
"default_min": 10,
"default_max": 50,
"default_step": 10,
}
for p in s["params"]
]
enriched = []
for s in strategies:
strategy_id = s["strategy_id"]
strategy_class = STRATEGY_REGISTRY[strategy_id]
schema = strategy_class.parameters_schema()
parameters_meta = []
for name, meta in schema.items():
parameters_meta.append({
"name": name,
"type": meta.get("type"),
"default_value": meta.get("default"),
"choices": meta.get("choices"),
"min": meta.get("min"),
"max": meta.get("max"),
})
enriched.append({
"strategy_id": strategy_id,
"name": s["name"],
"params": list(schema.keys()),
"parameters_meta": parameters_meta,
})
return {"strategies": enriched}
return {"strategies": strategies}
@router.post("/inspect", response_model=CalibrationStrategiesInspectResponse)
def inspect_strategies(
@@ -147,9 +166,9 @@ def report_strategies(
"WF train_days": payload.wf.train_days,
"WF test_days": payload.wf.test_days,
"WF step_days": payload.wf.step_days or payload.wf.test_days,
"Optimizer metric": payload.optimization.optimizer_metric,
"Max combinations": payload.optimization.max_combinations,
"Min trades per window (test)": payload.wf.min_trades_test,
},
results=result,
)

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@@ -1,33 +1,24 @@
# src/web/api/v2/schemas/calibration_strategies.py
from typing import Any, Dict, List, Literal, Optional
from typing import Any, Dict, List, Literal, Optional, Union
from pydantic import BaseModel, Field
from .calibration_risk import StopConfigSchema, RiskConfigSchema, GlobalRiskRulesSchema
ParameterValue = Union[int, float, bool, str]
class WalkForwardConfigSchema(BaseModel):
train_days: int = Field(..., gt=0)
test_days: int = Field(..., gt=0)
step_days: Optional[int] = Field(None, gt=0) # if None => step = test_days
class OptimizationConfigSchema(BaseModel):
optimizer_metric: str = Field("sharpe_ratio")
max_combinations: int = Field(500, gt=0)
min_trades_train: int = Field(30, ge=0)
step_days: Optional[int] = Field(None, gt=0)
min_trades_test: int = Field(10, ge=0)
class ParameterRangeSchema(BaseModel):
min: float
max: float
step: float
class StrategySelectionSchema(BaseModel):
strategy_id: str
parameters: Dict[str, ParameterRangeSchema]
parameters: Dict[str, ParameterValue]
class CalibrationStrategiesInspectRequest(BaseModel):
@@ -42,7 +33,6 @@ class CalibrationStrategiesInspectRequest(BaseModel):
strategies: List[StrategySelectionSchema]
wf: WalkForwardConfigSchema
optimization: OptimizationConfigSchema
commission: float = Field(0.001, ge=0)
slippage: float = Field(0.0005, ge=0)

File diff suppressed because it is too large Load Diff

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@@ -187,7 +187,7 @@
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header">
<h3 class="card-title">Walk-Forward & Optimization</h3>
<h3 class="card-title">Walk-Forward Validation (OOS)</h3>
</div>
<div class="card-body">
<div class="row g-3">
@@ -203,26 +203,10 @@
<label class="form-label">Step days (optional)</label>
<input id="wf_step_days" class="form-control" type="number" step="1" value="">
</div>
<div class="col-md-3">
<label class="form-label">Metric</label>
<select id="opt_metric" class="form-select">
<option value="sharpe_ratio">sharpe_ratio</option>
<option value="total_return">total_return</option>
<option value="max_drawdown">max_drawdown</option>
</select>
</div>
<div class="col-md-3">
<label class="form-label">Max combinations</label>
<input id="opt_max_combinations" class="form-control" type="number" step="1" value="300">
</div>
<div class="col-md-3">
<label class="form-label">Min trades (train)</label>
<input id="opt_min_trades_train" class="form-control" type="number" step="1" value="30">
</div>
<div class="col-md-3">
<label class="form-label">Min trades (test)</label>
<input id="opt_min_trades_test" class="form-control" type="number" step="1" value="10">
<label class="form-label">Min trades per window (test)</label>
<input id="wf_min_trades_test" class="form-control" type="number" step="1" value="10">
</div>
<div class="col-md-3">
@@ -262,7 +246,7 @@
</small>
</div>
<div class="mt-3 text-secondary">
Cada estrategia incluye un <b>param_grid</b> en JSON.
Cada estrategia utiliza parámetros fijos (validación OOS sin grid).
</div>
</div>
</div>

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@@ -0,0 +1,366 @@
{% extends "layout.html" %}
{% block content %}
<div class="container-xl">
<!-- ========================= -->
<!-- Wizard header -->
<!-- ========================= -->
<div class="d-flex align-items-center mb-4">
<!-- Back arrow -->
<div class="me-3">
<a href="/calibration/risk" class="btn btn-outline-secondary btn-icon">
<svg xmlns="http://www.w3.org/2000/svg"
class="icon icon-tabler icon-tabler-arrow-left"
width="24" height="24" viewBox="0 0 24 24"
stroke-width="2" stroke="currentColor"
fill="none" stroke-linecap="round" stroke-linejoin="round">
<path stroke="none" d="M0 0h24v24H0z"/>
<path d="M15 6l-6 6l6 6"/>
</svg>
</a>
</div>
<div class="flex-grow-1 text-center">
<h2 class="mb-0">Calibración · Paso 3 · Strategies</h2>
<div class="text-secondary">Optimización + Walk Forward (OOS)</div>
</div>
<!-- Forward arrow (disabled until OK) -->
<div class="ms-3">
<a
id="next-step-btn"
href="#"
class="btn btn-outline-secondary btn-icon"
aria-disabled="true"
title="Next step not implemented yet"
>
<svg xmlns="http://www.w3.org/2000/svg"
class="icon icon-tabler icon-tabler-arrow-right"
width="24" height="24" viewBox="0 0 24 24"
stroke-width="2" stroke="currentColor"
fill="none" stroke-linecap="round" stroke-linejoin="round">
<path stroke="none" d="M0 0h24v24H0z"/>
<path d="M9 6l6 6l-6 6"/>
</svg>
</a>
</div>
</div>
<!-- ========================= -->
<!-- Context -->
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header">
<h3 class="card-title">Context</h3>
</div>
<div class="card-body">
<div class="row g-3">
<div class="col-md-4">
<label class="form-label">Symbol</label>
<input id="symbol" class="form-control" placeholder="BTC/USDT">
</div>
<div class="col-md-4">
<label class="form-label">Timeframe</label>
<input id="timeframe" class="form-control" placeholder="1h">
</div>
<div class="col-md-4">
<label class="form-label">Account equity</label>
<input id="account_equity" class="form-control" type="number" step="0.01" value="10000">
</div>
</div>
<div class="mt-3 text-secondary">
Tip: Symbol y timeframe se cargan desde Step 1 (localStorage). Si no aparecen, rellénalos manualmente.
</div>
</div>
</div>
<!-- ========================= -->
<!-- Risk & Stops -->
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header d-flex justify-content-between align-items-center">
<h3 class="card-title mb-0">Risk & Stops(Step 2)</h3>
<div class="form-check form-switch m-0">
<input class="form-check-input" type="checkbox" id="lock_inherited" checked>
<label class="form-check-label" for="lock_inherited">
Bloquear parámetros heredados
</label>
</div>
</div>
<div class="card-body">
<!-- ================= -->
<!-- Risk Configuration -->
<!-- ================= -->
<h4 class="mb-3">Risk Configuration</h4>
<div class="row g-3 mb-4">
<div class="col-md-4">
<label class="form-label">Risk per Trade (%)</label>
<input id="risk_fraction" class="form-control inherited-field" type="number" step="0.01">
</div>
<div class="col-md-4">
<label class="form-label">Max Position Size (%)</label>
<input id="max_position_fraction" class="form-control inherited-field" type="number" step="0.1">
</div>
</div>
<!-- ================= -->
<!-- Stop Configuration -->
<!-- ================= -->
<h4 class="mb-3">Stop Configuration</h4>
<div class="row g-3 mb-4">
<div class="col-md-4">
<label class="form-label">Stop Type</label>
<select id="stop_type" class="form-select inherited-field">
<option value="fixed">fixed</option>
<option value="trailing">trailing</option>
<option value="atr">atr</option>
</select>
</div>
<div id="stop_fraction_group" class="col-md-4">
<label class="form-label">Stop fraction (%)</label>
<input id="stop_fraction" class="form-control inherited-field" type="number" step="0.01">
</div>
<div id="atr_group" class="col-md-4 d-none">
<label class="form-label">ATR period</label>
<input id="atr_period" class="form-control inherited-field" type="number">
</div>
<div id="atr_multiplier_group" class="col-md-4 d-none">
<label class="form-label">ATR multiplier</label>
<input id="atr_multiplier" class="form-control inherited-field" type="number" step="0.1">
</div>
</div>
<!-- ================= -->
<!-- Global Rules -->
<!-- ================= -->
<h4 class="mb-3">Global Rules</h4>
<div class="row g-3 mb-4">
<div class="col-md-4">
<label class="form-label">Max Drawdown (%)</label>
<input id="max_drawdown_pct" class="form-control inherited-field" type="number" step="0.1">
</div>
</div>
<!-- ================= -->
<!-- Optional Parameters -->
<!-- ================= -->
<h4 class="mb-3">Optional Parameters</h4>
<div class="row g-3">
<div class="col-md-4">
<label class="form-label">Daily loss limit (%)</label>
<input id="daily_loss_limit_pct" class="form-control optional-field" type="number" step="0.1">
</div>
<div class="col-md-4">
<label class="form-label">Max consecutive losses</label>
<input id="max_consecutive_losses" class="form-control optional-field" type="number">
</div>
<div class="col-md-4">
<label class="form-label">Cooldown bars</label>
<input id="cooldown_bars" class="form-control optional-field" type="number">
</div>
</div>
</div>
</div>
<!-- ========================= -->
<!-- WF + Optimizer config -->
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header">
<h3 class="card-title">Walk-Forward & Optimization</h3>
</div>
<div class="card-body">
<div class="row g-3">
<div class="col-md-3">
<label class="form-label">Train days</label>
<input id="wf_train_days" class="form-control" type="number" step="1" value="120">
</div>
<div class="col-md-3">
<label class="form-label">Test days</label>
<input id="wf_test_days" class="form-control" type="number" step="1" value="30">
</div>
<div class="col-md-3">
<label class="form-label">Step days (optional)</label>
<input id="wf_step_days" class="form-control" type="number" step="1" value="">
</div>
<div class="col-md-3">
<label class="form-label">Metric</label>
<select id="opt_metric" class="form-select">
<option value="sharpe_ratio">sharpe_ratio</option>
<option value="total_return">total_return</option>
<option value="max_drawdown">max_drawdown</option>
</select>
</div>
<div class="col-md-3">
<label class="form-label">Max combinations</label>
<input id="opt_max_combinations" class="form-control" type="number" step="1" value="300">
</div>
<div class="col-md-3">
<label class="form-label">Min trades (train)</label>
<input id="opt_min_trades_train" class="form-control" type="number" step="1" value="30">
</div>
<div class="col-md-3">
<label class="form-label">Min trades (test)</label>
<input id="opt_min_trades_test" class="form-control" type="number" step="1" value="10">
</div>
<div class="col-md-3">
<label class="form-label">Commission</label>
<input id="commission" class="form-control" type="number" step="0.0001" value="0.001">
</div>
<div class="col-md-3">
<label class="form-label">Slippage</label>
<input id="slippage" class="form-control" type="number" step="0.0001" value="0.0005">
</div>
</div>
</div>
</div>
<!-- ========================= -->
<!-- Strategy selection -->
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header">
<h3 class="card-title">Strategies</h3>
<div class="card-actions">
<button id="refresh_strategies_btn" class="btn btn-sm btn-outline-secondary">Refresh</button>
</div>
</div>
<div class="card-body">
<div id="strategies_container" class="d-flex flex-column gap-4"></div>
<div class="card p-3">
<div class="d-flex justify-content-between">
<strong>Total combinations</strong>
<span id="combination_counter">0</span>
</div>
</div>
<div class="mt-2 text-end">
<small class="text-muted">
Estimated WF time:
<span id="wf_time_estimate">~ 0 sec</span>
</small>
</div>
<div class="mt-3 text-secondary">
Cada estrategia incluye un <b>param_grid</b> en JSON.
</div>
</div>
</div>
<!-- ========================= -->
<!-- Actions -->
<!-- ========================= -->
<div class="d-flex gap-2 mb-4">
<button id="validate_strategies_btn" class="btn btn-primary">
Validate (WF)
</button>
<button id="report_strategies_btn" class="btn btn-outline-primary">
Generate PDF report
</button>
</div>
<!-- ========================= -->
<!-- Prograss Bar -->
<!-- ========================= -->
<div id="wf_progress_card" class="card mb-4">
<div class="card-header">
<h3 class="card-title">Walk-Forward Progress</h3>
</div>
<div class="card-body">
<div class="progress mb-2">
<div
id="wfProgressBar"
class="progress-bar progress-bar-striped progress-bar-animated"
role="progressbar"
style="width: 0%"
>
0%
</div>
</div>
<div id="wf_progress_text" class="text-secondary small">
Waiting to start...
</div>
</div>
</div>
<!-- ========================= -->
<!-- Results -->
<!-- ========================= -->
<div class="card mb-4">
<div class="card-header">
<h3 class="card-title">Results</h3>
<div class="card-actions">
<span id="strategies_status_badge" class="badge bg-secondary">—</span>
</div>
</div>
<div class="card-body">
<div id="strategies_message" class="mb-3 text-secondary">Run validation to see results.</div>
<div class="row g-3">
<div class="col-md-4">
<label class="form-label">Strategy plot</label>
<select id="plot_strategy_select" class="form-select"></select>
</div>
</div>
<div class="mt-3">
<div id="plot_equity" style="height: 320px;"></div>
</div>
<div class="mt-3">
<div id="plot_returns" style="height: 320px;"></div>
</div>
<hr class="my-4">
<div id="strategies_table_wrap"></div>
<details class="mt-3">
<summary class="text-secondary">Debug JSON</summary>
<pre id="strategies_debug" class="mt-2" style="max-height: 300px; overflow:auto;"></pre>
</details>
</div>
</div>
<!-- ========================= -->
<!-- PDF Viewer -->
<!-- ========================= -->
<div id="pdf_viewer_section" class="card mb-4 d-none">
<div class="card-header">
<h3 class="card-title">Strategies Report (PDF)</h3>
<div class="card-actions">
<button id="close_pdf_btn" class="btn btn-sm btn-outline-secondary">Close</button>
</div>
</div>
<div class="card-body">
<iframe id="pdf_frame" style="width: 100%; height: 800px; border: none;"></iframe>
</div>
</div>
</div>
<script src="https://cdn.plot.ly/plotly-2.27.0.min.js"></script>
<script src="/static/js/pages/calibration_strategies.js"></script>
{% endblock %}