Segment anchoring problem

Bắt đầu với các entry point add_lines và update_chart trong script được cung cấp, sau đó kiểm tra cách các trục của biểu đồ được xây dựng lại khi thu phóng và điều hướng. Tái hiện chuyển động của đường bằng CSV đính kèm và xác định hành vi neo dự kiến; issue không xác định tệp nào trong repository hoặc test nào.

Hello,
FX_NAS100, 5.csv

I hope I'm not out of line with the problem I can't solve.
I would like to draw a red line and a green line representing the amplitude of the US trading session on the NASDAQ100.
The history is in candlestick units of 5 minutes.
The two lines (for the historical period) should be drawn from the 15:30 candle to the 21:55 candle.
Tracing is correct at first, but the lines move as soon as you use the program's zoom or advance functions.
Perhaps tracing with “axhline” isn't the right solution; I've tried using the xplot method to exploit the position of the reference candle index, but I can't get anywhere.
Do you have any ideas for solving this problem?
Later, I want to draw other lines with different levels, but until I solve this problem, I'm stuck.

Thanks

import` pandas as pd
import mplfinance as mpf
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import tkinter as tk
from tkinter import ttk
import os
import matplotlib.pyplot as plt

df_bourse = pd.DataFrame([
    {'Année': 2022, 'Période': 'Été US', 'Début': '2022-03-14', 'Fin': '2022-03-28', 'Modedate': 1},
    {'Année': 2022, 'Période': 'Hiver US', 'Début': '2022-10-31', 'Fin': '2022-11-04', 'Modedate': 1},
    {'Année': 2023, 'Période': 'Été US', 'Début': '2023-03-13', 'Fin': '2023-03-24', 'Modedate': 1},
    {'Année': 2023, 'Période': 'Hiver US', 'Début': '2023-10-30', 'Fin': '2023-11-03', 'Modedate': 1},
    {'Année': 2024, 'Période': 'Été US', 'Début': '2024-03-11', 'Fin': '2024-03-28', 'Modedate': 1},
    {'Année': 2024, 'Période': 'Hiver US', 'Début': '2024-10-28', 'Fin': '2024-11-01', 'Modedate': 1}
])

df_bourse['Début'] = pd.to_datetime(df_bourse['Début'])
df_bourse['Fin'] = pd.to_datetime(df_bourse['Fin'])

csv_path = r"C:\Formation Python\FX_NAS100, 5.csv"
df = pd.read_csv(csv_path)
csv_filename = os.path.basename(csv_path)

df["time"] = pd.to_datetime(df["time"], unit='s')
df['date'] = df['time'].dt.date

def determine_modedate(date):
    for _, row in df_bourse.iterrows():
        if row['Début'].date() <= date <= row['Fin'].date():
            return row['Modedate']
    return 2

df['Modedate'] = df['date'].apply(determine_modedate)

df['amp_journée'] = 0.0
for day in df['date'].unique():
    day_data = df[df['date'] == day]
    if not day_data.empty:
        modedate = day_data['Modedate'].iloc[0]
        if modedate == 1:
            start_time = pd.to_datetime("14:30").time()
            end_time = pd.to_datetime("21:00").time()
        else:
            start_time = pd.to_datetime("15:30").time()
            end_time = pd.to_datetime("22:00").time()
        
        filtered_data = day_data[(day_data['time'].dt.time >= start_time) & (day_data['time'].dt.time <= end_time)]
        
        if not filtered_data.empty:
            high_max = filtered_data['high'].max()
            low_min = filtered_data['low'].min()
            amplitude = high_max - low_min
            df.loc[df['date'] == day, 'amp_journée'] = amplitude

percentages = [25, 50, 75, 100, 125, 150, 175, 200, 225, 250, 275]
for p in percentages:
    df[f'{p}%'] = df['amp_journée'] * (p / 100)
    df[f'-{p}%'] = df['amp_journée'] * (-p / 100)

cols = ['date', 'time', 'open', 'high', 'low', 'close', 'Modedate', 'amp_journée']
percentage_cols = [f'{p}%' for p in percentages] + [f'-{p}%' for p in percentages]
df = df[cols + percentage_cols]

# Interface graphique principale
root = tk.Tk()
root.title("Graphique en chandelier japonais")
root.state('zoomed')

frame = ttk.Frame(root)
frame.pack(fill=tk.BOTH, expand=True)

start_index = 0
num_candles = 100

# Champs pour les pas
step_frame = ttk.Frame(root)
step_frame.pack(side=tk.TOP, fill=tk.X)

tk.Label(step_frame, text="Pas graphique:").pack(side=tk.LEFT, padx=5)
graph_step_entry = ttk.Entry(step_frame, width=5)
graph_step_entry.insert(0, "30")
graph_step_entry.pack(side=tk.LEFT, padx=5)

tk.Label(step_frame, text="Pas zoom:").pack(side=tk.LEFT, padx=5)
zoom_step_entry = ttk.Entry(step_frame, width=5)
zoom_step_entry.insert(0, "30")
zoom_step_entry.pack(side=tk.LEFT, padx=5)

# Fenêtre pour afficher le DataFrame
def show_dataframe():
    df_window = tk.Toplevel(root)
    df_window.title("Tableau des données")
    df_window.state('zoomed')

    tree_frame = ttk.Frame(df_window)
    tree_frame.pack(fill=tk.BOTH, expand=True)

    tree_scroll_y = ttk.Scrollbar(tree_frame, orient=tk.VERTICAL)
    tree_scroll_x = ttk.Scrollbar(tree_frame, orient=tk.HORIZONTAL)
    tree = ttk.Treeview(tree_frame, yscrollcommand=tree_scroll_y.set, xscrollcommand=tree_scroll_x.set)

    tree_scroll_y.pack(side=tk.RIGHT, fill=tk.Y)
    tree_scroll_x.pack(side=tk.BOTTOM, fill=tk.X)
    tree_scroll_y.config(command=tree.yview)
    tree_scroll_x.config(command=tree.xview)

    tree.pack(fill=tk.BOTH, expand=True)

    df_display = df.copy().reset_index()
    numeric_columns = ['amp_journée'] + [col for col in df_display.columns if '%' in col] + ['open', 'high', 'low', 'close']
    for column in numeric_columns:
        if column in df_display.columns:
            df_display[column] = df_display[column].round(2)

    tree["columns"] = ["index"] + list(df_display.columns)[1:]
    tree["show"] = "headings"

    tree.heading("index", text="Index")
    tree.column("index", width=50, anchor='center')

    for column in df_display.columns[1:]:
        tree.heading(column, text=column)
        if column == 'time':
            tree.column(column, width=200, anchor='center')
        else:
            tree.column(column, width=100, anchor='center')

    for _, row in df_display.iterrows():
        tree.insert("", "end", values=[row['index']] + list(row)[1:])

    # Champ de saisie pour l'index
    index_frame = ttk.Frame(df_window)
    index_frame.pack(side=tk.TOP, fill=tk.X)
    tk.Label(index_frame, text="Index:").pack(side=tk.LEFT, padx=5)
    index_entry = ttk.Entry(index_frame, width=10)
    index_entry.pack(side=tk.LEFT, padx=5)

    def select_by_index(event=None):
        index = index_entry.get()
        if index.isdigit():
            index = int(index)
            for item in tree.get_children():
                if int(tree.item(item)['values'][0]) == index:
                    tree.selection_set(item)
                    tree.see(item)
                    break

    index_entry.bind('<Return>', select_by_index)

    df_window.mainloop()

btn_show_df = ttk.Button(root, text="Afficher le tableau", command=show_dataframe)
btn_show_df.pack(side=tk.TOP, pady=5)

# Ajouter une ligne rouge et verte
def add_lines(ax, df_slice):
    try:
        unique_dates = df_slice['date'].unique()
        for date in unique_dates:
            daily_data = df_slice[df_slice['date'] == date]
            if daily_data.empty:
                continue
            
            modedate = daily_data['Modedate'].iloc[0]
            if modedate == 1:
                start_time = pd.to_datetime("14:30").time()
                end_time = pd.to_datetime("21:00").time()
            else:
                start_time = pd.to_datetime("15:30").time()
                end_time = pd.to_datetime("21:55").time()
            
            filtered_data = daily_data[
                (daily_data['time'].dt.time >= start_time) & 
                (daily_data['time'].dt.time <= end_time)
            ]
            
            if filtered_data.empty:
                continue
            
            max_high = filtered_data['high'].max()
            min_low = filtered_data['low'].min()
            
            time_range = df_slice['time']
            xmin = (pd.Timestamp.combine(date, start_time) - time_range.min()).total_seconds() / (time_range.max() - time_range.min()).total_seconds()
            xmax = (pd.Timestamp.combine(date, end_time) - time_range.min()).total_seconds() / (time_range.max() - time_range.min()).total_seconds()
            
            ax.axhline(y=max_high, color='red', linestyle='--', xmin=xmin, xmax=xmax)
            ax.axhline(y=min_low, color='green', linestyle='--', xmin=xmin, xmax=xmax)
    except Exception as e:
        pass

# fonction pour gérer le mouvement de la souris
def on_mouse_move(event):
    if event.inaxes:
        x, y = event.xdata, event.ydata
        ax = event.inaxes
        
        # Effacer les lignes précédentes
        for line in ax.lines:
            if line.get_label() in ['crosshair_h', 'crosshair_v']:
                line.remove()
        
        # Dessiner les nouvelles lignes
        ax.axhline(y=y, color='black', linewidth=0.5, label='crosshair_h')
        ax.axvline(x=x, color='black', linewidth=0.5, label='crosshair_v')
        
        # Mettre à jour les données dans la fenêtre
        if df_slice is not None and len(df_slice) > 0:
            index = max(0, min(int(x), len(df_slice) - 1))
            data = df_slice.iloc[index]
            info_text = f"Index: {start_index + index}\nOpen: {data['open']:.2f}\nHigh: {data['high']:.2f}\nLow: {data['low']:.2f}\nClose: {data['close']:.2f}\nTime: {data['time']}"
            info_window.set(info_text)
            
            # Mise à jour des valeurs X et Y
            x_value.set(f"X: {data['time']}")
            y_value.set(f"Y: {y:.2f}")
        
        # Redessiner le graphique
        fig.canvas.draw_idle()

# Evènement molette de la sourie
def on_scroll(event):
    global num_candles
    if event.button == 'up':
        num_candles = max(num_candles - int(zoom_step_entry.get()), 10)
    elif event.button == 'down':
        num_candles += int(zoom_step_entry.get())
    update_chart()

# Fonctions pour le graphique
def update_chart():
    global start_index, num_candles, df_slice, fig
    plt.close('all')  # Ferme toutes les figures existantes
    df_slice = df.iloc[start_index:start_index + num_candles]
    if df_slice.empty:
        return
    df_ohlc = df_slice[['time', 'open', 'high', 'low', 'close']].copy()
    df_ohlc.set_index('time', inplace=True)
    fig, axlist = mpf.plot(df_ohlc, type='candle', style='charles', title=csv_filename,
                           ylabel='Prix', volume=False, returnfig=True)
    ax = axlist[0]
    add_lines(ax, df_slice)
    if hasattr(frame, "canvas"):
        frame.canvas.get_tk_widget().destroy()
    canvas = FigureCanvasTkAgg(fig, master=frame)
    canvas.draw()
    canvas.get_tk_widget().pack(side=tk.TOP, fill=tk.BOTH, expand=1)
    frame.canvas = canvas
    fig.canvas.mpl_connect('motion_notify_event', on_mouse_move)
    fig.canvas.mpl_connect('scroll_event', on_scroll)

def increase_candles():
    global num_candles
    num_candles += int(zoom_step_entry.get())
    update_chart()

def decrease_candles():
    global num_candles
    num_candles = max(num_candles - int(zoom_step_entry.get()), 10)  # Minimum de 10 chandeliers
    update_chart()

def move_right():
    global start_index
    start_index += int(graph_step_entry.get())
    update_chart()

def move_left():
    global start_index
    start_index = max(start_index - int(graph_step_entry.get()), 0)
    update_chart()

# Boutons
button_frame = ttk.Frame(root)
button_frame.pack(side=tk.BOTTOM, fill=tk.X)

plus_button = ttk.Button(button_frame, text="+", command=decrease_candles)
plus_button.pack(side=tk.LEFT, padx=5, pady=5)

minus_button = ttk.Button(button_frame, text="-", command=increase_candles)
minus_button.pack(side=tk.LEFT, padx=5, pady=5)

left_button = ttk.Button(button_frame, text="←", command=move_left)
left_button.pack(side=tk.LEFT, padx=5, pady=5)

right_button = ttk.Button(button_frame, text="→", command=move_right)
right_button.pack(side=tk.LEFT, padx=5, pady=5)

# Fenêtre d'information
info_frame = ttk.Frame(root)
info_frame.pack(side=tk.BOTTOM, fill=tk.X)

# Sous-frame pour les informations centrées
center_info_frame = ttk.Frame(info_frame)
center_info_frame.pack(side=tk.LEFT, expand=True)

info_window = tk.StringVar()
info_label = ttk.Label(center_info_frame, textvariable=info_window, justify=tk.LEFT)
info_label.pack(pady=10)

# Sous-frame pour les valeurs X et Y à droite
xy_info_frame = ttk.Frame(info_frame)
xy_info_frame.pack(side=tk.RIGHT)

x_value = tk.StringVar()
y_value = tk.StringVar()
x_label = ttk.Label(xy_info_frame, textvariable=x_value, justify=tk.LEFT)
y_label = ttk.Label(xy_info_frame, textvariable=y_value, justify=tk.LEFT)
x_label.pack(padx=10, anchor='w')
y_label.pack(padx=10, anchor='w')

update_chart()
root.mainloop()