tvta-vision

"""
TradingView-Style Chart Image Generator
Generates realistic candlestick charts with indicators.
"""

import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib.patches import FancyBboxPatch
import matplotlib.patches as mpatches
import numpy as np
import pandas as pd
from typing import Optional, List, Dict, Any
import os

# TradingView color scheme
TV_BG = "#0e1117"
TV_FG = "#d1d4dc"
TV_GRID = "#1e222d"
TV_RED = "#ef5350"
TV_GREEN = "#26a69a"
TV_BLUE = "#2962ff"
TV_ORANGE = "#ff9800"
TV_PURPLE = "#ab47bc"
TV_YELLOW = "#ffeb3b"
TV_CYAN = "#00bcd4"


def generate_chart_image(
    df: pd.DataFrame,
    symbol: str,
    timeframe: str,
    output_path: str,
    indicators: Optional[Dict[str, Any]] = None,
    show_volume: bool = True,
    show_sma: Optional[List[int]] = None,
    show_ema: Optional[List[int]] = None,
    show_bollinger: bool = False,
    show_vwap: bool = False,
    show_support_resistance: bool = False,
    support_levels: Optional[List[float]] = None,
    resistance_levels: Optional[List[float]] = None,
    show_pattern_annotation: bool = False,
    pattern_name: Optional[str] = None,
    figsize: tuple = (12, 8),
    dpi: int = 150,
) -> str:
    """
    Generate a TradingView-style chart image.
    Returns the output file path.
    """
    # Determine subplot layout
    n_subplots = 1  # Main price chart
    if show_volume:
        n_subplots += 1
    if indicators and "rsi" in indicators:
        n_subplots += 1
    if indicators and "macd" in indicators:
        n_subplots += 1

    # Height ratios
    height_ratios = [3]
    if show_volume:
        height_ratios.append(0.8)
    if indicators and "rsi" in indicators:
        height_ratios.append(1.0)
    if indicators and "macd" in indicators:
        height_ratios.append(1.0)

    fig, axes = plt.subplots(
        n_subplots, 1,
        figsize=figsize,
        gridspec_kw={"height_ratios": height_ratios},
        sharex=True,
    )
    if n_subplots == 1:
        axes = [axes]

    fig.patch.set_facecolor(TV_BG)
    for ax in axes:
        ax.set_facecolor(TV_BG)
        ax.tick_params(colors=TV_FG, which="both")
        for spine in ax.spines.values():
            spine.set_color(TV_GRID)
        ax.grid(True, alpha=0.15, color=TV_GRID)

    ax_main = axes[0]
    date_nums = mdates.date2num(df.index)

    # Plot candlesticks
    up = df["close"] >= df["open"]
    down = ~up

    width = 0.6
    width2 = 0.1

    # Green candles (up)
    ax_main.bar(
        date_nums[up], df["close"][up] - df["open"][up],
        width, bottom=df["open"][up],
        color=TV_GREEN, edgecolor=TV_GREEN, linewidth=0.5,
    )
    ax_main.bar(
        date_nums[up], df["high"][up] - df["close"][up],
        width2, bottom=df["close"][up],
        color=TV_GREEN, edgecolor=TV_GREEN,
    )
    ax_main.bar(
        date_nums[up], df["open"][up] - df["low"][up],
        width2, bottom=df["low"][up],
        color=TV_GREEN, edgecolor=TV_GREEN,
    )

    # Red candles (down)
    ax_main.bar(
        date_nums[down], df["open"][down] - df["close"][down],
        width, bottom=df["close"][down],
        color=TV_RED, edgecolor=TV_RED, linewidth=0.5,
    )
    ax_main.bar(
        date_nums[down], df["high"][down] - df["open"][down],
        width2, bottom=df["open"][down],
        color=TV_RED, edgecolor=TV_RED,
    )
    ax_main.bar(
        date_nums[down], df["close"][down] - df["low"][down],
        width2, bottom=df["low"][down],
        color=TV_RED, edgecolor=TV_RED,
    )

    # Plot moving averages
    if show_sma:
        colors = [TV_BLUE, TV_ORANGE, TV_PURPLE, TV_CYAN]
        for i, period in enumerate(show_sma):
            col = f"sma_{period}"
            if col in df.columns:
                ax_main.plot(
                    date_nums, df[col],
                    color=colors[i % len(colors)],
                    linewidth=0.8, alpha=0.8,
                    label=f"SMA {period}",
                )

    if show_ema:
        colors = [TV_YELLOW, TV_CYAN, TV_ORANGE, TV_BLUE]
        for i, period in enumerate(show_ema):
            col = f"ema_{period}"
            if col in df.columns:
                ax_main.plot(
                    date_nums, df[col],
                    color=colors[i % len(colors)],
                    linewidth=0.8, alpha=0.8, linestyle="--",
                    label=f"EMA {period}",
                )

    # Bollinger Bands
    if show_bollinger and "bb_upper" in df.columns:
        ax_main.plot(date_nums, df["bb_upper"], color=TV_BLUE, linewidth=0.5, alpha=0.5)
        ax_main.plot(date_nums, df["bb_lower"], color=TV_BLUE, linewidth=0.5, alpha=0.5)
        ax_main.fill_between(
            date_nums, df["bb_upper"], df["bb_lower"],
            color=TV_BLUE, alpha=0.05,
        )

    # VWAP
    if show_vwap and "vwap" in df.columns:
        ax_main.plot(
            date_nums, df["vwap"],
            color=TV_PURPLE, linewidth=0.8, alpha=0.7, linestyle=":",
            label="VWAP",
        )

    # Support/Resistance
    if show_support_resistance:
        if support_levels:
            for level in support_levels:
                ax_main.axhline(
                    y=level, color=TV_GREEN, linewidth=0.8,
                    linestyle="--", alpha=0.6,
                )
        if resistance_levels:
            for level in resistance_levels:
                ax_main.axhline(
                    y=level, color=TV_RED, linewidth=0.8,
                    linestyle="--", alpha=0.6,
                )

    # Pattern annotation
    if show_pattern_annotation and pattern_name:
        ax_main.annotate(
            pattern_name,
            xy=(date_nums[len(date_nums) // 2], df["high"].iloc[len(date_nums) // 2]),
            fontsize=10, color=TV_YELLOW,
            ha="center", va="bottom",
            bbox=dict(boxstyle="round,pad=0.3", facecolor=TV_BG, edgecolor=TV_YELLOW, alpha=0.8),
        )

    # Title
    ax_main.set_title(
        f"{symbol} | {timeframe}",
        color=TV_FG, fontsize=12, fontweight="bold",
    )

    # Volume subplot
    current_ax = 1
    if show_volume:
        ax_vol = axes[current_ax]
        vol_colors = [
            TV_GREEN if df["close"].iloc[i] >= df["open"].iloc[i] else TV_RED
            for i in range(len(df))
        ]
        ax_vol.bar(date_nums, df["volume"], width, color=vol_colors, alpha=0.7)
        ax_vol.set_ylabel("Volume", color=TV_FG, fontsize=8)
        if "volume_sma_20" in df.columns:
            ax_vol.plot(
                date_nums, df["volume_sma_20"],
                color=TV_ORANGE, linewidth=0.6, alpha=0.7,
            )
        current_ax += 1

    # RSI subplot
    if indicators and "rsi" in indicators and "rsi_14" in df.columns:
        ax_rsi = axes[current_ax]
        ax_rsi.plot(date_nums, df["rsi_14"], color=TV_PURPLE, linewidth=0.8)
        ax_rsi.axhline(y=70, color=TV_RED, linewidth=0.5, linestyle="--", alpha=0.5)
        ax_rsi.axhline(y=30, color=TV_GREEN, linewidth=0.5, linestyle="--", alpha=0.5)
        ax_rsi.fill_between(date_nums, 70, 100, color=TV_RED, alpha=0.05)
        ax_rsi.fill_between(date_nums, 0, 30, color=TV_GREEN, alpha=0.05)
        ax_rsi.set_ylim(0, 100)
        ax_rsi.set_ylabel("RSI", color=TV_FG, fontsize=8)
        current_ax += 1

    # MACD subplot
    if indicators and "macd" in indicators and "macd" in df.columns:
        ax_macd = axes[current_ax]
        ax_macd.plot(date_nums, df["macd"], color=TV_BLUE, linewidth=0.8, label="MACD")
        ax_macd.plot(date_nums, df["macd_signal"], color=TV_ORANGE, linewidth=0.8, label="Signal")
        macd_hist = df["macd_histogram"]
        hist_colors = [TV_GREEN if v >= 0 else TV_RED for v in macd_hist]
        ax_macd.bar(date_nums, macd_hist, width, color=hist_colors, alpha=0.5)
        ax_macd.axhline(y=0, color=TV_FG, linewidth=0.3)
        ax_macd.set_ylabel("MACD", color=TV_FG, fontsize=8)
        ax_macd.legend(
            loc="upper left", fontsize=7,
            facecolor=TV_BG, edgecolor=TV_GRID, labelcolor=TV_FG,
        )
        current_ax += 1

    # X-axis formatting
    ax = axes[-1]
    ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
    ax.xaxis.set_major_locator(mdates.AutoDateLocator())
    plt.xticks(rotation=30, ha="right")

    # Legend (only if there are labeled artists)
    handles, labels = ax_main.get_legend_handles_labels()
    if handles:
        ax_main.legend(
            loc="upper left", fontsize=7,
            facecolor=TV_BG, edgecolor=TV_GRID, labelcolor=TV_FG,
        )

    plt.tight_layout()
    fig.savefig(output_path, dpi=dpi, bbox_inches="tight", facecolor=TV_BG)
    plt.close(fig)

    return output_path


def generate_chart_grid(
    df: pd.DataFrame,
    symbol: str,
    timeframe: str,
    output_path: str,
    n_candles: int = 60,
    start_idx: int = 0,
) -> str:
    """Generate a clean chart with a specific window of candles."""
    end_idx = min(start_idx + n_candles, len(df))
    window = df.iloc[start_idx:end_idx]

    if len(window) < 20:
        return ""

    return generate_chart_image(
        window, symbol, timeframe, output_path,
        show_volume=True,
        show_sma=[20, 50],
        show_ema=[9],
        show_bollinger=False,
        show_vwap=False,
    )

	"""
	TradingView-Style Chart Image Generator
	Generates realistic candlestick charts with indicators.
	"""

	import matplotlib
	matplotlib.use("Agg")
	import matplotlib.pyplot as plt
	import matplotlib.dates as mdates
	from matplotlib.patches import FancyBboxPatch
	import matplotlib.patches as mpatches
	import numpy as np
	import pandas as pd
	from typing import Optional, List, Dict, Any
	import os

	# TradingView color scheme
	TV_BG = "#0e1117"
	TV_FG = "#d1d4dc"
	TV_GRID = "#1e222d"
	TV_RED = "#ef5350"
	TV_GREEN = "#26a69a"
	TV_BLUE = "#2962ff"
	TV_ORANGE = "#ff9800"
	TV_PURPLE = "#ab47bc"
	TV_YELLOW = "#ffeb3b"
	TV_CYAN = "#00bcd4"


	def generate_chart_image(
	df: pd.DataFrame,
	symbol: str,
	timeframe: str,
	output_path: str,
	indicators: Optional[Dict[str, Any]] = None,
	show_volume: bool = True,
	show_sma: Optional[List[int]] = None,
	show_ema: Optional[List[int]] = None,
	show_bollinger: bool = False,
	show_vwap: bool = False,
	show_support_resistance: bool = False,
	support_levels: Optional[List[float]] = None,
	resistance_levels: Optional[List[float]] = None,
	show_pattern_annotation: bool = False,
	pattern_name: Optional[str] = None,
	figsize: tuple = (12, 8),
	dpi: int = 150,
	) -> str:
	"""
	Generate a TradingView-style chart image.

	Returns the output file path.
	"""
	# Determine subplot layout
	n_subplots = 1 # Main price chart
	if show_volume:
	n_subplots += 1
	if indicators and "rsi" in indicators:
	n_subplots += 1
	if indicators and "macd" in indicators:
	n_subplots += 1

	# Height ratios
	height_ratios = [3]
	if show_volume:
	height_ratios.append(0.8)
	if indicators and "rsi" in indicators:
	height_ratios.append(1.0)
	if indicators and "macd" in indicators:
	height_ratios.append(1.0)

	fig, axes = plt.subplots(
	n_subplots, 1,
	figsize=figsize,
	gridspec_kw={"height_ratios": height_ratios},
	sharex=True,
	)
	if n_subplots == 1:
	axes = [axes]

	fig.patch.set_facecolor(TV_BG)
	for ax in axes:
	ax.set_facecolor(TV_BG)
	ax.tick_params(colors=TV_FG, which="both")
	for spine in ax.spines.values():
	spine.set_color(TV_GRID)
	ax.grid(True, alpha=0.15, color=TV_GRID)

	ax_main = axes[0]
	date_nums = mdates.date2num(df.index)

	# Plot candlesticks
	up = df["close"] >= df["open"]
	down = ~up

	width = 0.6
	width2 = 0.1

	# Green candles (up)
	ax_main.bar(
	date_nums[up], df["close"][up] - df["open"][up],
	width, bottom=df["open"][up],
	color=TV_GREEN, edgecolor=TV_GREEN, linewidth=0.5,
	)
	ax_main.bar(
	date_nums[up], df["high"][up] - df["close"][up],
	width2, bottom=df["close"][up],
	color=TV_GREEN, edgecolor=TV_GREEN,
	)
	ax_main.bar(
	date_nums[up], df["open"][up] - df["low"][up],
	width2, bottom=df["low"][up],
	color=TV_GREEN, edgecolor=TV_GREEN,
	)

	# Red candles (down)
	ax_main.bar(
	date_nums[down], df["open"][down] - df["close"][down],
	width, bottom=df["close"][down],
	color=TV_RED, edgecolor=TV_RED, linewidth=0.5,
	)
	ax_main.bar(
	date_nums[down], df["high"][down] - df["open"][down],
	width2, bottom=df["open"][down],
	color=TV_RED, edgecolor=TV_RED,
	)
	ax_main.bar(
	date_nums[down], df["close"][down] - df["low"][down],
	width2, bottom=df["low"][down],
	color=TV_RED, edgecolor=TV_RED,
	)

	# Plot moving averages
	if show_sma:
	colors = [TV_BLUE, TV_ORANGE, TV_PURPLE, TV_CYAN]
	for i, period in enumerate(show_sma):
	col = f"sma_{period}"
	if col in df.columns:
	ax_main.plot(
	date_nums, df[col],
	color=colors[i % len(colors)],
	linewidth=0.8, alpha=0.8,
	label=f"SMA {period}",
	)

	if show_ema:
	colors = [TV_YELLOW, TV_CYAN, TV_ORANGE, TV_BLUE]
	for i, period in enumerate(show_ema):
	col = f"ema_{period}"
	if col in df.columns:
	ax_main.plot(
	date_nums, df[col],
	color=colors[i % len(colors)],
	linewidth=0.8, alpha=0.8, linestyle="--",
	label=f"EMA {period}",
	)

	# Bollinger Bands
	if show_bollinger and "bb_upper" in df.columns:
	ax_main.plot(date_nums, df["bb_upper"], color=TV_BLUE, linewidth=0.5, alpha=0.5)
	ax_main.plot(date_nums, df["bb_lower"], color=TV_BLUE, linewidth=0.5, alpha=0.5)
	ax_main.fill_between(
	date_nums, df["bb_upper"], df["bb_lower"],
	color=TV_BLUE, alpha=0.05,
	)

	# VWAP
	if show_vwap and "vwap" in df.columns:
	ax_main.plot(
	date_nums, df["vwap"],
	color=TV_PURPLE, linewidth=0.8, alpha=0.7, linestyle=":",
	label="VWAP",
	)

	# Support/Resistance
	if show_support_resistance:
	if support_levels:
	for level in support_levels:
	ax_main.axhline(
	y=level, color=TV_GREEN, linewidth=0.8,
	linestyle="--", alpha=0.6,
	)
	if resistance_levels:
	for level in resistance_levels:
	ax_main.axhline(
	y=level, color=TV_RED, linewidth=0.8,
	linestyle="--", alpha=0.6,
	)

	# Pattern annotation
	if show_pattern_annotation and pattern_name:
	ax_main.annotate(
	pattern_name,
	xy=(date_nums[len(date_nums) // 2], df["high"].iloc[len(date_nums) // 2]),
	fontsize=10, color=TV_YELLOW,
	ha="center", va="bottom",
	bbox=dict(boxstyle="round,pad=0.3", facecolor=TV_BG, edgecolor=TV_YELLOW, alpha=0.8),
	)

	# Title
	ax_main.set_title(
	f"{symbol} \| {timeframe}",
	color=TV_FG, fontsize=12, fontweight="bold",
	)

	# Volume subplot
	current_ax = 1
	if show_volume:
	ax_vol = axes[current_ax]
	vol_colors = [
	TV_GREEN if df["close"].iloc[i] >= df["open"].iloc[i] else TV_RED
	for i in range(len(df))
	]
	ax_vol.bar(date_nums, df["volume"], width, color=vol_colors, alpha=0.7)
	ax_vol.set_ylabel("Volume", color=TV_FG, fontsize=8)
	if "volume_sma_20" in df.columns:
	ax_vol.plot(
	date_nums, df["volume_sma_20"],
	color=TV_ORANGE, linewidth=0.6, alpha=0.7,
	)
	current_ax += 1

	# RSI subplot
	if indicators and "rsi" in indicators and "rsi_14" in df.columns:
	ax_rsi = axes[current_ax]
	ax_rsi.plot(date_nums, df["rsi_14"], color=TV_PURPLE, linewidth=0.8)
	ax_rsi.axhline(y=70, color=TV_RED, linewidth=0.5, linestyle="--", alpha=0.5)
	ax_rsi.axhline(y=30, color=TV_GREEN, linewidth=0.5, linestyle="--", alpha=0.5)
	ax_rsi.fill_between(date_nums, 70, 100, color=TV_RED, alpha=0.05)
	ax_rsi.fill_between(date_nums, 0, 30, color=TV_GREEN, alpha=0.05)
	ax_rsi.set_ylim(0, 100)
	ax_rsi.set_ylabel("RSI", color=TV_FG, fontsize=8)
	current_ax += 1

	# MACD subplot
	if indicators and "macd" in indicators and "macd" in df.columns:
	ax_macd = axes[current_ax]
	ax_macd.plot(date_nums, df["macd"], color=TV_BLUE, linewidth=0.8, label="MACD")
	ax_macd.plot(date_nums, df["macd_signal"], color=TV_ORANGE, linewidth=0.8, label="Signal")
	macd_hist = df["macd_histogram"]
	hist_colors = [TV_GREEN if v >= 0 else TV_RED for v in macd_hist]
	ax_macd.bar(date_nums, macd_hist, width, color=hist_colors, alpha=0.5)
	ax_macd.axhline(y=0, color=TV_FG, linewidth=0.3)
	ax_macd.set_ylabel("MACD", color=TV_FG, fontsize=8)
	ax_macd.legend(
	loc="upper left", fontsize=7,
	facecolor=TV_BG, edgecolor=TV_GRID, labelcolor=TV_FG,
	)
	current_ax += 1

	# X-axis formatting
	ax = axes[-1]
	ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m-%d"))
	ax.xaxis.set_major_locator(mdates.AutoDateLocator())
	plt.xticks(rotation=30, ha="right")

	# Legend (only if there are labeled artists)
	handles, labels = ax_main.get_legend_handles_labels()
	if handles:
	ax_main.legend(
	loc="upper left", fontsize=7,
	facecolor=TV_BG, edgecolor=TV_GRID, labelcolor=TV_FG,
	)

	plt.tight_layout()
	fig.savefig(output_path, dpi=dpi, bbox_inches="tight", facecolor=TV_BG)
	plt.close(fig)

	return output_path


	def generate_chart_grid(
	df: pd.DataFrame,
	symbol: str,
	timeframe: str,
	output_path: str,
	n_candles: int = 60,
	start_idx: int = 0,
	) -> str:
	"""Generate a clean chart with a specific window of candles."""
	end_idx = min(start_idx + n_candles, len(df))
	window = df.iloc[start_idx:end_idx]

	if len(window) < 20:
	return ""

	return generate_chart_image(
	window, symbol, timeframe, output_path,
	show_volume=True,
	show_sma=[20, 50],
	show_ema=[9],
	show_bollinger=False,
	show_vwap=False,
	)