explainability_renderer.py

"""explainability_renderer.py — PeVe v1.1"""
from __future__ import annotations
import numpy as np
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
from matplotlib.colors import LinearSegmentedColormap
from config import (BAND_COLORS, WINDOW_BP, SPLICE_PROB_HIGH, SPLICE_PROB_MODERATE,
                    ACTIVATION_NORM_HIGH, ACTIVATION_NORM_MODERATE, BIOCHEMICAL_RISK_ACTIVE)
from decision_engine import SynthesisResult, SpliceLayerOutput, ContextLayerOutput, ProteinLayerOutput

MECH_COLORS = {
    "RNA_Splicing":"#d73027","Protein_Biochemical":"#4575b4","Sequence_Context":"#74add1",
    "Mechanism_Ambiguity":"#f46d43","Protein_Truncation":"#313695",
    "Insufficient_Evidence":"#aaaaaa","Conflict_Manual_Review":"#762a83","Out_Of_Scope":"#cccccc",
}

def render_summary_card(result, chrom, pos, ref, alt):
    fig, ax = plt.subplots(figsize=(8, 2.8))
    ax.axis("off"); fig.patch.set_facecolor("#f8f9fa"); ax.set_facecolor("#f8f9fa")
    mcolor = MECH_COLORS.get(result.dominant_mechanism, "#888")
    rcolor = "#d73027" if result.conflict_report.requires_manual_review else "#1a9850"
    ax.text(0.02, 0.88, f"chr{chrom}:{pos}  {ref}>{alt}", transform=ax.transAxes,
            fontsize=13, fontweight="bold", color="#222")
    ax.text(0.02, 0.62, f"Dominant:  {result.dominant_mechanism.replace('_',' ')}",
            transform=ax.transAxes, fontsize=11, color="white",
            bbox=dict(facecolor=mcolor, boxstyle="round,pad=0.3", edgecolor="none"))
    ax.text(0.02, 0.35, f"Classification:  {result.final_classification}",
            transform=ax.transAxes, fontsize=10, color="#333")
    label = "⛔ MANUAL REVIEW REQUIRED" if result.conflict_report.requires_manual_review else "✓ No major conflicts"
    ax.text(0.02, 0.12, label, transform=ax.transAxes, fontsize=9, color=rcolor, fontstyle="italic")
    plt.tight_layout(); return fig

def render_saliency_heatmap(splice, ref, alt):
    fig, ax = plt.subplots(figsize=(10, 1.8))
    if splice.saliency_map is not None and len(splice.saliency_map) > 0:
        sal = np.array(splice.saliency_map, dtype=float)
        mn, mx = sal.min(), sal.max()
        if mx > mn: sal = (sal - mn)/(mx - mn)
        if len(sal) != WINDOW_BP:
            xo = np.linspace(0,1,len(sal)); xn = np.linspace(0,1,WINDOW_BP)
            sal = np.interp(xn, xo, sal)
        cmap = LinearSegmentedColormap.from_list("sal", ["#f7fbff","#6baed6","#08519c","#d73027"])
        ax.imshow(sal.reshape(1,-1), aspect="auto", cmap=cmap, vmin=0, vmax=1, extent=[0,WINDOW_BP,0,1])
    else:
        ax.text(0.5, 0.5, "Saliency map unavailable", ha="center", va="center",
                transform=ax.transAxes, color="#aaa"); ax.set_facecolor("#f0f0f0")
    ax.axvline(x=WINDOW_BP//2, color="#d73027", linewidth=2.5, linestyle="--", label=f"{ref}>{alt}")
    ax.set_xlabel("Position in 401bp window", fontsize=9); ax.set_yticks([])
    ax.set_title(f"RNA Saliency  |  splice_prob={splice.splice_prob:.3f}", fontsize=10)
    ax.legend(loc="upper right", fontsize=8); plt.tight_layout(); return fig

def render_activation_peak(context, ref, alt):
    fig, ax = plt.subplots(figsize=(10, 2.2))
    x = np.arange(WINDOW_BP); peak = context.activation_peak_position; norm = context.activation_norm
    profile = norm * np.exp(-0.5*((x-peak)/30)**2)
    ax.fill_between(x, profile, alpha=0.35, color="#4575b4")
    ax.plot(x, profile, color="#4575b4", linewidth=1.5, label="Activation profile")
    ax.axvline(x=WINDOW_BP//2, color="#d73027", linewidth=2, linestyle="--", label=f"Mutation ({ref}>{alt})")
    ax.axvline(x=peak, color="#1a9850", linewidth=1.5, linestyle=":", label=f"Peak (pos={peak})")
    ax.axhline(y=ACTIVATION_NORM_MODERATE, color="#fc8d59", linewidth=1, linestyle="--", alpha=0.7, label=f"Active thresh ({ACTIVATION_NORM_MODERATE})")
    ax.axhline(y=ACTIVATION_NORM_HIGH, color="#d73027", linewidth=1, linestyle="--", alpha=0.7, label=f"High thresh ({ACTIVATION_NORM_HIGH})")
    ax.set_xlim(0,WINDOW_BP); ax.set_ylim(0,max(1.0,norm+0.1))
    ax.set_xlabel("Position in 401bp window",fontsize=9); ax.set_ylabel("Activation",fontsize=9)
    ax.set_title(f"Sequence Context Activation  |  norm={context.activation_norm:.3f}, peak={peak}", fontsize=10)
    ax.legend(loc="upper right", fontsize=7); plt.tight_layout(); return fig

def render_shap_bar(protein):
    shap = protein.shap_feature_contributions
    if not shap:
        fig, ax = plt.subplots(figsize=(6,2))
        ax.text(0.5,0.5,"SHAP values unavailable",ha="center",va="center",transform=ax.transAxes,color="#aaa")
        ax.axis("off"); plt.tight_layout(); return fig
    feats = list(shap.keys()); vals = [shap[f] for f in feats]
    colors = ["#d73027" if v>0 else "#4575b4" for v in vals]
    fig, ax = plt.subplots(figsize=(7, max(2.5, 0.5*len(feats)+1)))
    bars = ax.barh(feats, vals, color=colors, edgecolor="white", height=0.6)
    ax.axvline(x=0, color="#333", linewidth=1)
    ax.set_xlabel("SHAP contribution (positive=pathogenic)",fontsize=9)
    ax.set_title(f"Layer 3 Features  |  biochemical_risk={protein.biochemical_risk_score:.3f}",fontsize=10)
    for bar, v in zip(bars, vals):
        ax.text(v+(0.005 if v>=0 else -0.005), bar.get_y()+bar.get_height()/2,
                f"{v:+.3f}", va="center", ha="left" if v>=0 else "right", fontsize=8)
    ax.legend(handles=[mpatches.Patch(color="#d73027",label="Pathogenic"),
                       mpatches.Patch(color="#4575b4",label="Benign")], fontsize=8, loc="lower right")
    plt.tight_layout(); return fig

def render_band_gauges(result, splice, context, protein):
    fig, axes = plt.subplots(1,3,figsize=(10,2)); fig.patch.set_facecolor("#f8f9fa")
    datasets = [
        ("RNA Splice", splice.splice_prob, [(SPLICE_PROB_HIGH,"High"),(SPLICE_PROB_MODERATE,"Moderate")], result.activation_levels.splice_band),
        ("Seq Context", context.activation_norm, [(ACTIVATION_NORM_HIGH,"High"),(ACTIVATION_NORM_MODERATE,"Moderate")], result.activation_levels.context_band),
        ("Protein", protein.biochemical_risk_score, [(BIOCHEMICAL_RISK_ACTIVE,"Active")],
         "Active" if result.activation_levels.protein_active else "Inactive"),
    ]
    for ax, (title, value, bands, cband) in zip(axes, datasets):
        ax.set_facecolor("#f8f9fa"); ax.set_xlim(0,1); ax.set_ylim(0,1); ax.axis("off")
        ax.set_title(title, fontsize=9, pad=4)
        bar_color = BAND_COLORS.get(cband, "#888")
        ax.barh(0.3, 1.0, height=0.25, color="#e0e0e0", left=0, align="edge")
        ax.barh(0.3, value, height=0.25, color=bar_color, left=0, align="edge", alpha=0.85)
        for thresh, lbl in bands:
            ax.axvline(x=thresh, color="#333", linewidth=1.2, linestyle="--", alpha=0.7)
            ax.text(thresh, 0.58, f"{thresh}", ha="center", fontsize=6.5, color="#333")
        ax.text(max(0.01, value-0.01), 0.3+0.125, f"{value:.3f}", va="center",
                fontsize=8, fontweight="bold", color="white" if value>0.4 else "#333")
        ax.text(0.5, 0.08, cband, ha="center", fontsize=9, color=bar_color,
                fontweight="bold", transform=ax.transAxes)
    plt.suptitle("Mechanism Activation Bands", fontsize=10, y=1.02)
    plt.tight_layout(); return fig

def render_conflict_table(result):
    rows = []
    for c in result.conflict_report.major_conflicts:
        rows.append(f'<tr><td style="color:#d73027;font-weight:bold;padding:4px 8px">⛔ MAJOR</td>'
                    f'<td style="padding:4px 8px">{c.replace("MAJOR: ","")}</td></tr>')
    for c in result.conflict_report.minor_conflicts:
        rows.append(f'<tr><td style="color:#fc8d59;font-weight:bold;padding:4px 8px">⚠ MINOR</td>'
                    f'<td style="padding:4px 8px">{c.replace("MINOR: ","")}</td></tr>')
    if not rows:
        rows = ['<tr><td colspan="2" style="color:#1a9850;padding:4px 8px">✓ No conflicts detected</td></tr>']
    hc = "#d73027" if result.conflict_report.requires_manual_review else "#1a9850"
    rt = "MANUAL REVIEW REQUIRED" if result.conflict_report.requires_manual_review else "No Review Required"
    return f"""<div style="font-family:monospace;font-size:13px">
      <div style="color:{hc};font-weight:bold;margin-bottom:8px">
        {rt} ({result.conflict_report.conflict_score_major} major, {result.conflict_report.conflict_score_minor} minor)
      </div>
      <table style="border-collapse:collapse;width:100%;background:#fafafa">
        <thead><tr style="background:#eee"><th style="padding:4px 8px;text-align:left">Tier</th>
        <th style="padding:4px 8px;text-align:left">Description</th></tr></thead>
        <tbody>{"".join(rows)}</tbody>
      </table></div>"""