plt.style.use("dark_background") fig = plt.figure(figsize=(14, 7), facecolor=BG_CLR) ax = fig.add_subplot(1, 1, 1) ax.set_facecolor(BG_CLR) # volume bars on left ax2 = ax.twinx() delta = df.index[1] - df.index[0] w = delta * 0.8 raw_max = df["Volume"].max() scaled = df["Volume"] * VOLUME_SCALE cols = ["green" if c >= o else "red" for c, o in zip(df["Close"], df["Open"])] ax2.bar(df.index, scaled, width=w, color=cols, alpha=0.5, align="center", zorder=0) ax2.set_ylim(0, raw_max * 1.1) ax2.spines["right"].set_visible(False) ax2.spines["left"].set_visible(True) ax2.yaxis.set_label_position("left") ax2.yaxis.set_ticks_position("left") ax2.tick_params(axis="y", colors="#666666") ax2.set_ylabel("Vol (scaled)", color="#666666") # price line ax.plot(df.index, df["Close"], lw=1, color=PRICE_CLR, zorder=3) # ATR bands, levels, markers for idx, lvl, prob in levels: top = lvl + atr_now bot = lvl - atr_now ax.fill_between(df.index, bot, top, color=LINE_CLR, alpha=0.1, zorder=1) ax.hlines(lvl, df.index[idx], df.index[-1], colors=LINE_CLR, lw=2, zorder=2) ax.text(df.index[idx] - delta*0.2, lvl, f"{prob*100:.1f}% {lvl:.2f}", color=LINE_CLR, fontsize=8, ha="right", va="center", zorder=4) ax.scatter(df.index[idx], df["Close"].iat[idx], s=40, marker="o", color=LINE_CLR, zorder=5) # price-by-volume on right ax3 = fig.add_axes([0.92, 0.1, 0.06, 0.8], sharey=ax) bins = np.linspace(df["Low"].min(), df["High"].max(), 30) vol_p, edges = np.histogram(df["Close"], bins=bins, weights=df["Volume"]) centers = (edges[:-1] + edges[1:]) / 2 ax3.barh(centers, vol_p, height=edges[1]-edges[0], color="#666666", alpha=0.5) ax3.invert_xaxis() ax3.axis("off") # styling ax.spines["top"].set_visible(False) ax.spines["left"].set_visible(False) ax.spines["bottom"].set_visible(False) ax.yaxis.tick_right() ax.tick_params(axis="x", colors="#666666") ax.tick_params(axis="y", colors="#666666") ax.grid(False) ax.set_title(f"{TICKER} • Key price levels above {PROB_THRESHOLD} probability from {START_DATE} to {END_DATE}", color="#ffffff", pad=10) ax.xaxis.set_major_locator(mdates.AutoDateLocator()) ax.xaxis.set_major_formatter(mdates.DateFormatter("%Y-%m")) # adjust margins instead of tight_layout fig.subplots_adjust(left=0.05, right=0.90) plt.show()

Mapping Price Interest with Logistic Filters

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