[Fix] Update plotting imports and thread handling in Pepper class (#382)

- plt.subplot does not work reliably with async/ threads.
- Bug in thread run that would fail with env set (string to number)

Reviewed-on: enviPath/enviPy#382
Co-authored-by: Tobias O <tobias.olenyi@envipath.com>
Co-committed-by: Tobias O <tobias.olenyi@envipath.com>
This commit is contained in:
2026-05-12 06:43:26 +12:00
committed by jebus
parent 9d70db2ca2
commit 734b02767e
2 changed files with 7 additions and 6 deletions

View File

@ -46,7 +46,7 @@ class PepperPrediction(PropertyPrediction):
import matplotlib.patches as mpatches import matplotlib.patches as mpatches
import numpy as np import numpy as np
from matplotlib import pyplot as plt from matplotlib.figure import Figure
from scipy import stats from scipy import stats
""" """
@ -101,7 +101,8 @@ class PepperPrediction(PropertyPrediction):
mask_red = x > vp mask_red = x > vp
# Plot # Plot
fig, ax = plt.subplots(figsize=(9, 5.5)) fig = Figure(figsize=(9, 5.5))
ax = fig.subplots()
ax.plot(x, y, color="#1f4e79", lw=2, label="Lognormal PDF") ax.plot(x, y, color="#1f4e79", lw=2, label="Lognormal PDF")
if np.any(mask_green): if np.any(mask_green):
@ -146,13 +147,12 @@ class PepperPrediction(PropertyPrediction):
] ]
ax.legend(handles=patches, frameon=True) ax.legend(handles=patches, frameon=True)
plt.tight_layout() fig.tight_layout()
# --- Export to SVG string --- # --- Export to SVG string ---
buf = io.StringIO() buf = io.StringIO()
fig.savefig(buf, format="svg", bbox_inches="tight") fig.savefig(buf, format="svg", bbox_inches="tight")
svg = buf.getvalue() svg = buf.getvalue()
plt.close(fig)
buf.close() buf.close()
return svg return svg

View File

@ -187,8 +187,9 @@ class Pepper:
groups = [group for group in dataset.group_by("structure_id")] groups = [group for group in dataset.group_by("structure_id")]
# Unless explicitly set compute everything serial # Unless explicitly set compute everything serial
if os.environ.get("N_PEPPER_THREADS", 1) > 1: n_threads = int(os.environ.get("N_PEPPER_THREADS", 1))
results = Parallel(n_jobs=os.environ["N_PEPPER_THREADS"])( if n_threads > 1:
results = Parallel(n_jobs=n_threads)(
delayed(compute_bayes_per_group)(group[1]) delayed(compute_bayes_per_group)(group[1])
for group in dataset.group_by("structure_id") for group in dataset.group_by("structure_id")
) )