| """Figure 4 panel-drawing engines. |
| |
| 4A/4B share one scatter engine (predicted vs measured solvent-induced shift, implicit vs explicit |
| prediction column); 4C is a dumbbell plot of per-solvent fit RMSE vs experimental shift range. The |
| notebook supplies the data table and the styling dicts (highlight map, order, palette, markers / |
| colors) as arguments and calls `save_panel(...)` to draw and write the PNG. |
| """ |
| import matplotlib.pyplot as plt |
| import seaborn as sns |
| from adjustText import adjust_text |
|
|
|
|
| def draw_shift_scatter(ax, shift_df, pred_col, highlight_map, order, palette, markers, limits=(-0.25, 2.0)): |
| """Figure 4A/4B: scatter predicted vs experimental solvent-induced shift, colored by solvent.""" |
| df = shift_df[shift_df["solvent"].isin(highlight_map)].copy() |
| df["Solvent"] = df["solvent"].map(highlight_map) |
| sns.scatterplot(data=df, x="exp_diff", y=pred_col, hue="Solvent", style="Solvent", |
| hue_order=order, style_order=order, palette=palette, |
| markers=markers, s=60, alpha=0.6, edgecolor=None, ax=ax) |
| lo, hi = limits |
| ax.plot([lo, hi], [lo, hi], linestyle="--", alpha=0.35, linewidth=0.6, color="k") |
| ax.set_xlim(lo, hi); ax.set_ylim(lo, hi); ax.set_box_aspect(1) |
| ax.set_xlabel(r"Experimental Solvent-Induced Shift (Δδ vs. CDCl3, $^{1}\mathrm{H}$ ppm)", |
| fontsize=13, labelpad=10) |
| ax.set_ylabel(r"Predicted Solvent-Induced Shift (Δδ vs. CDCl3, $^{1}\mathrm{H}$ ppm)", |
| fontsize=13, labelpad=10) |
| leg = ax.get_legend() |
| if leg is not None: |
| leg.set_title(None) |
| for side in ax.spines: |
| ax.spines[side].set_linewidth(0.6) |
| ax.tick_params(labelsize=10, length=1.5, width=0.6) |
|
|
|
|
| def save_panel(draw_fn, save_path, figsize=(6, 6)): |
| """Create a figure/axes, call `draw_fn(ax)`, then save and show the panel as a PNG.""" |
| sns.set_theme(style="ticks", context="paper") |
| fig, ax = plt.subplots(figsize=figsize) |
| draw_fn(ax) |
| fig.tight_layout() |
| fig.savefig(save_path, dpi=200, bbox_inches="tight") |
| plt.show() |
|
|
|
|
| def draw_rmse_dumbbell(ax, rows, labels, colors): |
| """Figure 4C: dumbbell plot of implicit vs explicit solvent-correction RMSE per solvent.""" |
| rows_sorted = sorted(rows, key=lambda r: r["range"]) |
| xs = [r["range"] for r in rows_sorted] |
| for r in rows_sorted: |
| ax.plot([r["range"], r["range"]], [r["implicit"], r["explicit"]], |
| color="#cccccc", lw=1.5, zorder=1) |
| ax.scatter(xs, [r["implicit"] for r in rows_sorted], s=60, marker="D", |
| color=colors["Implicit (PCM)"], alpha=0.85, edgecolors="none", |
| label="Implicit (PCM)", zorder=2) |
| ax.scatter(xs, [r["explicit"] for r in rows_sorted], s=60, marker="o", |
| color=colors["Explicit (Desmond)"], alpha=0.85, edgecolors="none", |
| label="Explicit (Desmond)", zorder=2) |
| |
| xr = max(xs) - min(xs); yv = [r[k] for r in rows_sorted for k in ("implicit", "explicit")] |
| ax.set_xlim(min(xs) - 0.06 * xr, max(xs) + 0.10 * xr) |
| ax.set_ylim(min(yv) - 0.06 * (max(yv) - min(yv)), max(yv) + 0.10 * (max(yv) - min(yv))) |
| texts = [ax.text(r["range"], 0.5 * (r["implicit"] + r["explicit"]), labels[r["solvent"]], |
| fontsize=10, color="black", va="center", ha="left") for r in rows_sorted] |
| adjust_text(texts, ax=ax, arrowprops=dict(arrowstyle="-", color="gray", lw=0.5, alpha=0.8)) |
| ax.legend(loc="upper left", framealpha=0.9, fontsize=11) |
| ax.set_box_aspect(1) |
| ax.set_xlabel(r"Range of Solvent-Induced Shifts ($^{1}\mathrm{H}$ ppm)", fontsize=13, labelpad=10) |
| ax.set_ylabel(r"Predicted Solvent-Induced Shift RMSE ($^{1}\mathrm{H}$ ppm)", fontsize=13, labelpad=10) |
| for side in ax.spines: |
| ax.spines[side].set_linewidth(0.6) |
| ax.tick_params(labelsize=10, length=1.5, width=0.6) |
|
|
