| |
| import argparse |
| import json |
| from pathlib import Path |
|
|
| import numpy as np |
| import matplotlib |
|
|
| matplotlib.use("Agg") |
| import matplotlib.pyplot as plt |
|
|
| ROOT = Path(__file__).resolve().parents[2] |
| CACHE = ROOT / "data" / "p53" / "fig_data" |
|
|
|
|
| FIGSIZE = (7.2, 6.0) |
| HEIGHT_RATIOS, HSPACE, WSPACE = [1.15, 1.0], 0.42, 0.32 |
| RC = { |
| "font.size": 8, |
| "axes.labelsize": 8.5, |
| "axes.titlesize": 8.5, |
| "xtick.labelsize": 7.5, |
| "ytick.labelsize": 7.5, |
| "legend.fontsize": 7, |
| "axes.spines.top": False, |
| "axes.spines.right": False, |
| "pdf.fonttype": 42, |
| "ps.fonttype": 42, |
| } |
| ACC = "#2f6fb5" |
| HI = "#c8412b" |
| NULL_GREY = "#c9c9c9" |
| CMAP = "RdBu_r" |
| CLIP_PCT = 98 |
| BAR_W, BAR_DX = 0.32, 0.17 |
| YLIM_B = (-0.12, 1.12) |
| TITLES = { |
| "a": "a Ligand $\\times$ conformer interaction $\\gamma$\n" |
| " (ligand, cavity-volume and receptor main effects removed)", |
| "b": "b Preference survives removing\n between-stratum contrasts", |
| "c": "c Preference lives inside states", |
| } |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--out", type=Path, default=ROOT / "figures" / "p53_preference.pdf") |
| ap.add_argument("--png", action="store_true") |
| a = ap.parse_args() |
|
|
| npz = CACHE / "preference.npz" |
| if not npz.exists(): |
| raise SystemExit( |
| f"missing {npz}\nrun paper_figures/data/p53_preference_data.py first" |
| ) |
| d = np.load(npz, allow_pickle=True) |
| S = json.loads((CACHE / "preference.json").read_text()) |
|
|
| gamma, strat = d["gamma"], d["strat"] |
| lig_order, rec_order = d["lig_order"], d["rec_order"] |
| n_lig, n_rec = gamma.shape |
| labs = np.unique(strat) |
| Gp = gamma[np.ix_(lig_order, rec_order)] |
|
|
| plt.rcParams.update(RC) |
| fig = plt.figure(figsize=FIGSIZE) |
| gs = fig.add_gridspec( |
| 2, 2, height_ratios=HEIGHT_RATIOS, hspace=HSPACE, wspace=WSPACE |
| ) |
|
|
| p = fig.add_subplot(gs[0, :]) |
| lim = np.percentile(np.abs(Gp), CLIP_PCT) |
| im = p.imshow( |
| Gp, aspect="auto", cmap=CMAP, vmin=-lim, vmax=lim, interpolation="nearest" |
| ) |
| b0, centres = 0, [] |
| for l in labs: |
| n = int((strat == l).sum()) |
| centres.append(b0 + n / 2 - 0.5) |
| b0 += n |
| if b0 < n_rec: |
| p.axvline(b0 - 0.5, color="k", lw=0.8) |
| p.set_xticks(centres) |
| p.set_xticklabels([f"stratum {int(l) + 1}" for l in labs]) |
| p.tick_params(axis="x", length=0) |
| p.set_xlabel(f"{n_rec} receptor conformers, grouped by structural stratum") |
| p.set_ylabel(f"{n_lig} ligands (clustered)") |
| p.set_yticks([]) |
| p.set_title(TITLES["a"], loc="left", fontweight="bold", pad=6) |
| cb = fig.colorbar(im, ax=p, pad=0.012, fraction=0.021) |
| cb.set_label("$\\gamma$ (blue = better than expected)", fontsize=6.5) |
| cb.ax.tick_params(labelsize=6) |
|
|
| p = fig.add_subplot(gs[1, 0]) |
| series = [ |
| ("all\nreceptors", d["obs_all"], d["nul_all"]), |
| ("within\nstratum only", d["obs_within"], d["nul_within"]), |
| ] |
| for i, (nm, o, nl) in enumerate(series): |
| p.bar( |
| i - BAR_DX, |
| o.mean(), |
| BAR_W, |
| yerr=o.std(), |
| color=ACC, |
| capsize=2.5, |
| label="observed" if i == 0 else None, |
| ) |
| p.bar( |
| i + BAR_DX, |
| nl.mean(), |
| BAR_W, |
| yerr=nl.std(), |
| color=NULL_GREY, |
| capsize=2.5, |
| label="permuted" if i == 0 else None, |
| ) |
| p.text( |
| i - BAR_DX, |
| o.mean() / 2, |
| f"{o.mean():.3f}", |
| ha="center", |
| va="center", |
| fontsize=7.5, |
| color="w", |
| fontweight="bold", |
| ) |
| p.axhline(0, color="k", lw=0.7) |
| p.set_xticks(range(len(series))) |
| p.set_xticklabels([s[0] for s in series]) |
| p.set_ylabel("split-half Spearman of\nligand-preference structure") |
| p.set_ylim(*YLIM_B) |
| p.legend(frameon=False, loc="upper center", ncol=2, columnspacing=1.0) |
| p.set_title(TITLES["b"], loc="left", fontweight="bold") |
|
|
| p = fig.add_subplot(gs[1, 1]) |
| fw, fb = float(d["frac_within"]), float(d["frac_between"]) |
| p.bar([0], [100 * fw], 0.5, color=ACC, label="within strata") |
| p.bar([0], [100 * fb], 0.5, bottom=[100 * fw], color=HI, label="between strata") |
| p.text( |
| 0, |
| 100 * fw / 2, |
| f"{100 * fw:.1f}%", |
| ha="center", |
| va="center", |
| color="w", |
| fontweight="bold", |
| fontsize=9, |
| ) |
| p.text( |
| 0, |
| 100 * fw + 100 * fb / 2 + 3, |
| f"{100 * fb:.1f}%", |
| ha="center", |
| va="center", |
| color=HI, |
| fontweight="bold", |
| fontsize=8, |
| ) |
| p.set_xlim(-0.6, 1.4) |
| p.set_xticks([]) |
| p.set_ylabel("share of $\\mathrm{var}(\\gamma)$ (%)") |
| p.legend(frameon=False, loc="center right") |
| p.set_title(TITLES["c"], loc="left", fontweight="bold") |
|
|
| a.out.parent.mkdir(parents=True, exist_ok=True) |
| fig.savefig(a.out, format="pdf", bbox_inches="tight") |
| print(f"-> {a.out}") |
| if a.png: |
| fig.savefig(a.out.with_suffix(".png"), dpi=200, bbox_inches="tight") |
| print(f"-> {a.out.with_suffix('.png')}") |
| print( |
| f" (cache: {S['n_ligands']} ligands, {S['n_receptors']} receptors, " |
| f"{S['n_splits']} splits, within {100 * S['frac_within']:.1f}%)" |
| ) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
