Appearance
question:questo il codice aggiornato completo #property strict // Input Parameters input int bbPeriod = 80; // Bollinger Bands period input double bbDeviation = 2.0; // Bollinger Bands deviation input int rsiPeriod = 5; // RSI period input double rsiOverbought = 80; // RSI overbought level for closing Buy input double rsiOversold = 20; // RSI oversold level for closing Sell input bool aggressiveMode = false; // Aggressive mode boolean input double SlopeThreshold = 0.0003; // Slope threshold for the Bollinger Bands input double LotSize = 0.1; // Lot size for each trade input int Slippage = 3; // Maximum slippage input bool useStopLoss = true; // Use stop loss input double StopLossPips = 150; // Stop loss in pips input bool useTakeProfit = true; // Use take profit input double TakeProfitPips = 200; // Take profit in pips input bool useTrailingStop = true; // Use trailing stop input double TrailingStop = 10; // Trailing stop distance in pips input double TrailingStep = 5; // Trailing step distance in pips // Expert initialization function int OnInit() { // Initialization code here return(INIT_SUCCEEDED); } // Expert tick function void OnTick() { // Only run the rest of the code if a new candle has formed static datetime lastTime = 0; if(Time[0] <= lastTime) return; lastTime = Time[0]; // Obtain current values from indicators double upperBand = iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_UPPER, 0); double middleBand = iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_MAIN, 0); double lowerBand = iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_LOWER, 0); double rsi = iRSI(Symbol(), 0, rsiPeriod, PRICE_CLOSE, 0); // Calculate slopes double slopeUpper = MathAbs((iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_UPPER, 0) - iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_UPPER, 1)) / _Point); double slopeLower = MathAbs((iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_LOWER, 0) - iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_LOWER, 1)) / _Point); // Debug prints Print("New Tick for ", Symbol()); Print("upperBand: ", upperBand, " lowerBand: ", lowerBand, " middleBand: ", middleBand); Print("RSI value: ", rsi); Print("Slope Upper: ", slopeUpper, " Slope Lower: ", slopeLower); // Slope threshold check if(slopeUpper > SlopeThreshold || slopeLower > SlopeThreshold) { Print("Slope threshold not met. No trades will be opened this tick."); return; } // Check trade entry conditions if(rsi < rsiOversold && Close[1] < lowerBand) { Print("Buy condition met. RSI: ", rsi, " Close[1]: ", Close[1], " lowerBand: ", lowerBand); if(aggressiveMode || Close[1] > middleBand) { Print("Entering BUY trade."); // enter buy trade } else { Print("Aggressive mode not active. No BUY trade entered."); } } if(rsi > rsiOverbought && Close[1] > upperBand) { Print("Sell condition met. RSI: ", rsi, " Close[1]: ", Close[1], " upperBand: ", upperBand); if(aggressiveMode || Close[1] < middleBand) { Print("Entering SELL trade."); // enter sell trade } else { Print("Aggressive mode not active. No SELL trade entered."); } } // Manage open trades (for trailing stop) ManageOpenTrades(); } // Function to open a BUY trade void OpenBuyTrade(double lowerBand, double upperBand) { double sl = useStopLoss ? NormalizeDouble(Ask - StopLossPips * Point, Digits) : 0; double tp = useTakeProfit ? NormalizeDouble(Ask + TakeProfitPips * Point, Digits) : 0; int ticket = OrderSend(Symbol(), OP_BUY, LotSize, Ask, Slippage, sl, tp, "Buy Trade", 0, 0, clrBlue); if (ticket < 0) { Print("Error opening a BUY trade: ", GetLastError()); } } // Function to open a SELL trade void OpenSellTrade(double lowerBand, double upperBand) { double sl = useStopLoss ? NormalizeDouble(Bid + StopLossPips * Point, Digits) : 0; double tp = useTakeProfit ? NormalizeDouble(Bid - TakeProfitPips * Point, Digits) : 0; int ticket = OrderSend(Symbol(), OP_SELL, LotSize, Bid, Slippage, sl, tp, "Sell Trade", 0, 0, clrRed); if (ticket < 0) { Print("Error opening a SELL trade: ", GetLastError()); } } // Function to manage open trades (trailing stop) void ManageOpenTrades() { for (int i = 0; i < OrdersTotal(); i++) { if (!OrderSelect(i, SELECT_BY_POS, MODE_TRADES)) continue; if (OrderSymbol() != Symbol() || OrderMagicNumber() != 0) continue; double newStopLoss = 0.0; // Trail the stop loss for Buy orders if (OrderType() == OP_BUY && useTrailingStop && Bid - OrderOpenPrice() > TrailingStop * Point) { newStopLoss = Bid - TrailingStop * Point; if (OrderStopLoss() < newStopLoss && newStopLoss < Bid - TrailingStep * Point) { OrderModify(OrderTicket(), OrderOpenPrice(), newStopLoss, OrderTakeProfit(), 0, clrBlue); } } // Trail the stop loss for Sell orders if (OrderType() == OP_SELL && useTrailingStop && OrderOpenPrice() - Ask > TrailingStop * Point) { newStopLoss = Ask + TrailingStop * Point; if ((OrderStopLoss() > newStopLoss && newStopLoss > Ask + TrailingStep * Point) || OrderStopLoss() == 0) { OrderModify(OrderTicket(), OrderOpenPrice(), newStopLoss, OrderTakeProfit(), 0, clrRed); } } } } //±-----------------------------------------------------------------+ non apre nessun trade percheè : upperBand: 142.8017164159404 lowerBand: 141.8741335840596 middleBand: 142.337925, Slope threshold not met. No trades will be opened this tick. spiegami i valori che può assumere lo slope e perchè non vengono mai soddisfatti
answer:Normalmente, il valore dello "slope" delle bande di Bollinger che hai calcolato nel tuo EA è la differenza tra i valori correnti e precedenti di una determinata banda, divisa per il numero di punti (o tick) tra le due misurazioni. Questa è una misurazione della pendenza della linea che collega due punti sul grafico ed è un indicatore di quanto velocemente il prezzo sta salendo o scendendo. Nel tuo EA, lo "slope" è calcolato come segue: ```mql4 double slopeUpper = MathAbs((iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_UPPER, 0) - iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_UPPER, 1)) / _Point); double slopeLower = MathAbs((iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_LOWER, 0) - iBands(Symbol(), 0, bbPeriod, bbDeviation, 0, PRICE_CLOSE, MODE_LOWER, 1)) / _Point); ``` Qui, stai prendendo la differenza assoluta tra il valore corrente e quello precedente delle bande di Bollinger (superiore e inferiore), e la stai dividendo per il valore di _Point, che rappresenta il più piccolo possibile cambiamento di prezzo sul mercato (tipicamente, questo è pari a 0.0001 per la maggior parte delle coppie di valute, ma può variare per altre). La soglia (`SlopeThreshold`) serve a determinare quanto inclinata deve essere la curva prima che tu consideri il mercato in un trend forte. Se lo "slope" calcolato è maggiore di `SlopeThreshold`, l'EA interrompe l'esecuzione e non apre nuove posizioni, con il presupposto che il mercato sia in forte trend e, quindi, meno propenso a rimbalzare come previsto dalla tua strategia. Se il tuo EA non sta mai aprendo trade, questo indica che la `SlopeThreshold` che hai impostato è troppo bassa rispetto alla volatilità effettiva dei prezzi dell'asset che stai scambiando. In altre parole, le bande di Bollinger sono sempre più "inclinare" di quanto consentito dalla tua soglia. La soluzione a questo problema può essere: 1. Aumentare il valore di `SlopeThreshold` per essere più tollerante ai trend e quindi permettere all'EA di aprire trade durante periodi di maggiore inclinazione delle bande di Bollinger. Ad esempio, se hai impostato `SlopeThreshold` a `0.0003`, potresti voler sperimentare con `0.0005`, `0.001`, o anche di più. Devi sperimentare per trovare un valore che funzioni per la tua strategia senza esporti a troppo rischio in trend forti. 2. Aggiungere un ulteriore filtro di trend per determinare meglio quando entrare in un trade. Ad esempio, potresti utilizzare la media mobile, ADX o altri indicatori di trend per avere una maggiore conferma. 3. Ottimizzare la tua strategia su un ampio set di dati storici per trovare il miglior equilibrio tra il numero di trade e la loro qualità. Quando modificare questi parametri, è sempre essenziale eseguire backtesting e forward testing accurati per confermare che le modifiche apportate risultino in una strategia redditizia e conforme al tuo stile e tolleranza al rischio di trading.
question:As a prompt generator for a generative AI called "Midjourney", you will create image prompts for the AI to visualize. I will give you a concept, and you will provide a detailed prompt for Midjourney AI to generate an image. Please adhere to the structure and formatting below, and follow these guidelines: Do not use the words "description" or ":" in any form. Do not place a comma between [ar] and [v]. Write each prompt in one line without using return. Structure: [1] = 迷雾中的城堡,迪士尼风格 [2] = a detailed description of [1] with specific imagery details. [3] = a detailed description of the scene's environment. [4] = a detailed description of the compositions. [5] = a detailed description of the scene's mood, feelings, and atmosphere. [6] = A style (e.g. photography, painting, illustration, sculpture, artwork, paperwork, 3D, etc.) for [1]. [7] = a detailed description of the scene's mood, feelings, and atmosphere. [ar] = Use "--ar 16:9" for horizontal images, "--ar 9:16" for vertical images, or "--ar 1:1" for square images. [v] = Use "--niji" for Japanese art style, or "--v 5" for other styles. Formatting: Follow this prompt structure: "/imagine prompt: [1], [2], [3], [4], [5], [6], [7], [ar] [v]". Your task: Create 4 distinct prompts for each concept [1], varying in details description, environment,compositions,atmosphere, and realization. Write your prompts in english. Do not describe unreal concepts as "real" or "photographic". Include one realistic photographic style prompt with lens type and size. Separate different prompts with two new lines. Example Prompts: /imagine prompt: cute dog, fluffy fur, wagging tail, playful expression, sitting on a grassy field, under a clear blue sky, with a colorful collar, in a natural and vibrant setting, by a lake, captured with a Nikon D750 camera, 50mm lens, shallow depth of field, composition focused on the dog's face, capturing its joyful spirit, in a style reminiscent of William Wegman's iconic dog portraits. --ar 1:1 --v 5.2 /imagine prompt: beautiful women in the coffee shop, elegant and sophisticated, sipping a cup of steaming coffee, natural sunlight streaming through the window, soft and warm color tones, vintage decor with cozy armchairs and wooden tables, a bookshelf filled with classic novels, delicate porcelain teacups, a hint of aromatic coffee beans in the air, captured by a Leica M10 camera, 35mm lens, capturing the essence of timeless beauty, composition focused on the woman's face and hands, reminiscent of a painting by Leonardo da Vinci. --ar 1:1 --v 5.2 /imagine prompt: A captivating Halo Reach landscape with a Spartan amidst a battlefield, fallen enemies around, smoke and fire in the background, emphasizing the Spartan's determination and bravery, detailed environment blending chaos and beauty, Illustration, digital art, --ar 16:9 --v 5
answer:/imagine prompt: Enchanted castle in the mist, reminiscent of a Disney-style fairy tale, towers reaching towards the sky, colorful banners fluttering in the breeze, glittering lights peeking through the fog, surrounded by lush greenery and a mystical aura, fantasy illustration capturing the magic and charm of the scene. --ar 16:9 --v 5.2 /imagine prompt: Mysterious castle shrouded in fog, with ivy-covered walls and ancient stone archways, a whimsical clock tower standing tall, glowing windows casting a warm light, a secret garden with blooming flowers and intricate statues, a sense of wonder and adventure, painting capturing the ethereal beauty and enchantment of the moment. --ar 1:1 --v 5 /imagine prompt: Majestic castle hidden within swirling mist, grand gates leading to a courtyard filled with colorful flowers and magical creatures, a moat reflecting the moonlight, towering spires piercing the clouds, a sense of mystery and awe, sculpture depicting the fantastical architecture and whimsical details of the fairy tale setting. --ar 9:16 --v 5 /imagine prompt: Castle rising from the mist in a dreamy landscape, a river meandering through lush forests, a bridge leading to the majestic entrance, a dragon soaring in the sky, knights in shining armor guarding the kingdom, a sense of fantasy and heroism, photography capturing the intricate details and grandeur of the scene with a wide-angle lens, highlighting the scale and storytelling elements. --ar 16:9.
question:bonjour
answer:Bonjour ! Comment puis-je vous aider aujourd'hui ?
question:j'ai un fichier views.py : from flask import jsonify , abort , make_response , request, url_for from .app import app from .models import * @app.errorhandler(404) def bad_request(error): return make_response(jsonify({'error': 'Not found'}), 404) @app.errorhandler(404) def not_found(error): return make_response(jsonify({'error': 'Not found'}), 404) @app.route("/quiz/api/v1.0/quiz", methods=['GET']) def get_quiz(): return jsonify(questionnaires=get_questionnaires()) @app.route("/quiz/api/v1.0/quiz/<int:id>", methods=['GET']) def get_questionnaire(id): return jsonify(questionnaire=get_le_questionnaire(id)) @app.route("/quiz/api/v1.0/quiz", methods=['POST']) def create_questionnaire(): return jsonify(questionnaire=add_questionnaire(json=request.json)) @app.route("/quiz/api/v1.0/quiz/<int:id>", methods=['PUT']) def update_questionnaire(id): return jsonify(questionnaire=update_le_questionnaire(id)) @app.route("/quiz/api/v1.0/quiz/<int:id>", methods=['DELETE']) def delete_questionnaire(id): return jsonify(questionnaire=delete_le_questionnaire(id)) @app.route("/quiz/api/v1.0/quiz/<int:id>/questions", methods=['GET']) def get_questions_for_questionnaire(id): return jsonify(questions=get_les_questions_questionnaire(id)) @app.route("/quiz/api/v1.0/questions/<int:id>", methods=['GET']) def get_question(id): return jsonify(question=get_la_question(id)) @app.route("/quiz/api/v1.0/quiz/<int:questionnaire_id>/questions", methods=['POST']) def create_question(questionnaire_id): return jsonify(question=add_la_question(questionnaire_id, json=request.json)) @app.route("/quiz/api/v1.0/quiz/<int:questionnaire_id>/questions/<int:id>", methods=['PUT']) def update_question(questionnaire_id, id): return jsonify(question=update_la_question(questionnaire_id, id)) @app.route("/quiz/api/v1.0/quiz/<int:questionnaire_id>/questions/<int:id>", methods=['DELETE']) def delete_question(questionnaire_id, id): return jsonify(question=delete_la_question(questionnaire_id, id)) @app.route("/quiz/api/v1.0/quiz/<int:questionnaire_id>/questions/<int:id>", methods=['GET']) def get_question_questionnaire(questionnaire_id, id): return jsonify(question=get_la_question(id)) models.py : from .app import app, db from flask import jsonify , abort , make_response , request, url_for class Questionnaire(db.Model): id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String(64)) def __init__(self, name): self.name = name def __repr__(self): return '<Questionnaire (%d) %s>' % (self.id, self.name) def to_json(self): return { 'id': self.id, 'name': self.name, 'questions': [q.to_json() for q in self.questions.all()], 'url': url_for('get_questionnaire', id=self.id, _external=True) } class Question(db.Model): id = db.Column(db.Integer, primary_key=True) title = db.Column(db.String(120)) questionType = db.Column(db.String(120)) questionnaire_id = db.Column(db.Integer, db.ForeignKey('questionnaire.id')) questionnaire = db.relationship('Questionnaire', backref=db.backref('questions', lazy='dynamic')) def __init__(self, title, questionType, questionnaire_id): self.title = title self.questionType = questionType self.questionnaire_id = questionnaire_id __mappers_args__ = { 'polymorphic_identity': 'question', "with_polymorphic": "*", 'polymorphic_on': questionType } def to_json(self): return { 'id': self.id, 'title': self.title, 'questionType': self.questionType, 'questionnaire_id': self.questionnaire.id, 'url': url_for('get_question', id=self.id, _external=True) } class Simple_Question(Question): id = db.Column(db.Integer, db.ForeignKey('question.id'), primary_key=True) reponse = db.Column(db.String(120)) def __init__(self, title, questionnaire_id, reponse): super().__init__(title, "simple", questionnaire_id) self.reponse = reponse __mappers_args__ = { 'polymorphic_identity': 'simple', 'with_polymorphic': '*' } def to_json(self): json = super().to_json() json.update({ 'reponse': self.reponse }) return json class Multiple_Question(Question): id = db.Column(db.Integer, db.ForeignKey('question.id'), primary_key=True) proposition1 = db.Column(db.String(120)) proposition2 = db.Column(db.String(120)) reponse = db.Column(db.Integer) def __init__(self, title, questionnaire_id, proposition1, proposition2, reponse): super().__init__(title, "multiple", questionnaire_id) self.proposition1 = proposition1 self.proposition2 = proposition2 self.reponse = reponse __mappers_args__ = { 'polymorphic_identity': 'multiple', 'with_polymorphic': '*' } def to_json(self): json = super().to_json() json.update({ 'proposition1': self.proposition1, 'proposition2': self.proposition2, 'reponse': self.reponse }) return json def get_questionnaires(): return [q.to_json() for q in Questionnaire.query.all()] def add_questionnaire(json): q = Questionnaire(json['name']) db.session.add(q) db.session.commit() return q.to_json() def get_le_questionnaire(id): return Questionnaire.query.get(id).to_json() def update_le_questionnaire(id): questionnaire = Questionnaire.query.get(id) questionnaire.name = request.json['name'] db.session.commit() return questionnaire.to_json() def delete_le_questionnaire(id): questionnaire = Questionnaire.query.get(id) db.session.delete(questionnaire) db.session.commit() return questionnaire.to_json() def get_les_questions_questionnaire(id): return [q.to_json() for q in Questionnaire.query.get(id).questions] def get_les_questions(): return [q.to_json() for q in Question.query.all()] def get_la_question(id): if Question.query.get(id) is None: abort(404) if Question.query.get(id).questionType == "simple": return Simple_Question.query.get(id).to_json() elif Question.query.get(id).questionType == "multiple": return Multiple_Question.query.get(id).to_json() def add_la_question(questionnaire_id, json): if json['questionType'] == "simple": question = Simple_Question(json['title'], questionnaire_id, json['reponse']) if not isinstance(json['reponse'], str): abort(400) elif json['questionType'] == "multiple": question = Multiple_Question(json['title'], questionnaire_id, json['proposition1'], json['proposition2'], json['reponse']) if not isinstance(json['reponse'], int): abort(400) if not isinstance(json['proposition1'], str): abort(400) if not isinstance(json['proposition2'], str): abort(400) db.session.add(question) db.session.commit() return question.to_json() def update_la_question(questionnaire_id, id): question = Question.query.get(id) if question is None: abort(404) if question.questionType == "simple": question.title = request.json['title'] question.reponse = request.json['reponse'] elif question.questionType == "multiple": question.title = request.json['title'] question.proposition1 = request.json['proposition1'] question.proposition2 = request.json['proposition2'] question.reponse = request.json['reponse'] db.session.commit() return question.to_json() def delete_la_question(questionnaire_id, id): question = Question.query.get(id) if question is None: abort(404) db.session.delete(question) db.session.commit() return question.to_json() def get_liste_questions_simples(): return [q.to_json() for q in Simple_Question.query.all()] def get_liste_questions_multiples(): return [q.to_json() for q in Multiple_Question.query.all()] def get_liste_question_simple(id): return Simple_Question.query.get(id).to_json() def get_liste_question_multiple(id): return Multiple_Question.query.get(id).to_json() sont-ils correctes ?
answer:Votre code semble contenir tous les éléments nécessaires pour un service API de base utilisant Flask avec un back-end SQL Alchemy, mais il y a quelques petites anomalies et points d'amélioration que je peux relever. 1. Vous avez deux gestionnaires d'erreurs pour l'erreur 404 (Not Found) dans `views.py` avec le même comportement. Vous devriez probablement en garder un seul et supprimer le doublon. ```python @app.errorhandler(404) def not_found(error): return make_response(jsonify({'error': 'Not found'}), 404) ``` 2. Dans `models.py`, les champs `questionType` dans `Simple_Question` et `Multiple_Question` sont inutilement redéfinis, car ils sont déjà définis dans la superclasse `Question` comme étant 'simple' ou 'multiple'. 3. Vous n'avez pas partagé la logique d'initialisation de l'application Flask (`app`) ou de l'objet base de données SQL Alchemy (`db`). Rappelez-vous de configurer correctement votre application Flask et l'objet `db` avant de les utiliser. 4. Vérifiez la méthode d'instanciation des polices dans les classes `Question` et dérivées pour vous assurer que `polymorphic_on` est correctement configuré si vous utilisez l'héritage avec SQLAlchemy. 5. Il semble que le code des méthodes CRUD (`create`, `update`, `delete`) puisse rencontrer des problèmes si l'argument 'json' est incorrect ou s'il manque des données. Il serait préférable de valider les données avant de les utiliser. 6. Dans les méthodes comme `get_le_questionnaire(id)`, si l'objet `Questionnaire` n'est pas trouvé avec l'ID donné, votre code actuel exécutera `None.to_json()` et échouera. Vous devriez gérer le cas où l'objet est `None` et renvoyer une réponse 404 dans ces cas. 7. Dans la méthode `get_la_question(id)`, vous récupérez deux fois la question à partir de la base de données avec `Question.query.get(id)`. Il serait plus efficace de le faire une seule fois et de réutiliser l'objet récupéré. 8. Assurez-vous que les routes ne se chevauchent pas et que les noms des fonctions de vue sont uniques. Par exemple, vous avez deux fonctions nommées `get_question`. Ce sont quelques suggestions basées sur le code que vous avez partagé. Cependant, sans tester le code et connaître la configuration exacte de votre application Flask et de votre base de données, il est difficile de garantir que tout fonctionnera correctement. Il est toujours recommandé de procéder à des tests approfondis pour identifier et corriger les bogues potentiels.