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from edgeeda.viz import export_trials
import pandas as pd, matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt, os, glob, json
out='runs/plots_quick'
os.makedirs(out, exist_ok=True)
# Load trials
df = export_trials('runs/experiment.sqlite')
print('rows:', len(df))
print('columns:', list(df.columns))
# Basic runtime histogram
runtimes = pd.to_numeric(df['runtime_sec'], errors='coerce').dropna()
if not runtimes.empty:
plt.figure(); runtimes.hist(bins=10)
plt.xlabel('runtime_sec'); plt.tight_layout(); plt.savefig(os.path.join(out,'runtime_hist.png'), dpi=200); plt.close()
print('wrote runtime_hist.png')
else:
print('no runtime data to plot')
# return_code counts
plt.figure(); df['return_code'].value_counts().plot(kind='bar')
plt.xlabel('return_code'); plt.tight_layout(); plt.savefig(os.path.join(out,'return_code_counts.png'), dpi=200); plt.close()
print('wrote return_code_counts.png')
# metadata availability
has_meta = df['metadata_path'].fillna('').apply(lambda x: bool(str(x).strip()))
plt.figure(); has_meta.value_counts().plot(kind='bar'); plt.xticks([0,1],['no metadata','has metadata']); plt.tight_layout(); plt.savefig(os.path.join(out,'metadata_counts.png'), dpi=200); plt.close()
print('wrote metadata_counts.png')
# learning curve from reward, if present
if 'reward' in df.columns:
r = pd.to_numeric(df['reward'], errors='coerce').dropna()
if not r.empty:
df2 = df.copy()
df2['reward'] = pd.to_numeric(df2['reward'], errors='coerce')
df2 = df2.dropna(subset=['reward']).sort_values('id')
best = df2['reward'].cummax()
plt.figure(); plt.plot(df2['id'].values, best.values)
plt.xlabel('trial id'); plt.ylabel('best reward so far'); plt.tight_layout(); plt.savefig(os.path.join(out,'learning_curve.png'), dpi=200); plt.close()
print('wrote learning_curve.png')
else:
print('no rewards to plot')
else:
print('reward column missing')
# area vs wns if metrics present
areas=[]; wnss=[]
for _, r in df.iterrows():
mj = r.get('metrics') or r.get('metrics_json') or r.get('metrics_json')
if not mj:
continue
if isinstance(mj, str):
try:
m = json.loads(mj)
except Exception:
continue
else:
m = mj
a = m.get('design__die__area') or m.get('finish__design__die__area')
w = m.get('timing__setup__wns') or m.get('finish__timing__setup__wns')
if a is None or w is None:
continue
try:
areas.append(float(a)); wnss.append(float(w))
except Exception:
pass
if areas:
plt.figure(); plt.scatter(areas, wnss); plt.xlabel('die area'); plt.ylabel('WNS'); plt.tight_layout(); plt.savefig(os.path.join(out,'area_vs_wns.png'), dpi=200); plt.close()
print('wrote area_vs_wns.png')
else:
print('no area/wns metrics to plot')
print('files:', glob.glob(out+'/*'))
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