Skip to content

fix: match example05 hybrid fig06 to MATLAB (means only) #70

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
iahncajigas merged 1 commit into from
Mar 22, 2026
Merged

fix: match example05 hybrid fig06 to MATLAB (means only) #70

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
30 changes: 3 additions & 27 deletions examples/paper/example05_decoding_ppaf_pphf.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -735,8 +735,8 @@ def _plot_part_c(result):

fig5.tight_layout()

# ── Figure 6: 4×3 decode — matches MATLAB HybridFilterExample.m ──
# MATLAB overlays *individual* dashed traces first, then thick means on top.
# ── Figure 6: 4×3 decode — matches MATLAB example05_decoding_ppaf_pphf.m ──
# MATLAB example05 plots ONLY means (thick solid lines), no individual traces.
fig6 = plt.figure(figsize=(14, 9))

S_estAll = result["S_estAll"] # (n_sims, T)
Expand All @@ -745,7 +745,6 @@ def _plot_part_c(result):
MU_estNTAll = result["MU_estNTAll"]
X_estAll = result["X_estAll"] # (6, T, n_sims)
X_estNTAll = result["X_estNTAll"]
n_sims = result["n_sims"]

# Pre-create all subplots
ax_s = fig6.add_subplot(4, 3, (1, 4))
Expand All @@ -756,30 +755,7 @@ def _plot_part_c(result):
ax_xv = fig6.add_subplot(4, 3, 11)
ax_yv = fig6.add_subplot(4, 3, 12)

# --- Individual traces (thin dashed, matching MATLAB loop) ---
for n in range(n_sims):
# State traces
ax_s.plot(time, S_estAll[n, :], "b-.", linewidth=0.5)
ax_s.plot(time, S_estNTAll[n, :], "g-.", linewidth=0.5)
# Movement probability
ax_p.plot(time, MU_estAll[n, 1, :], "b-.", linewidth=0.5)
ax_p.plot(time, MU_estNTAll[n, 1, :], "g-.", linewidth=0.5)
# 2D path
ax_2d.plot(100 * X_estAll[0, :, n], 100 * X_estAll[1, :, n], "b-.",
linewidth=0.5)
ax_2d.plot(100 * X_estNTAll[0, :, n], 100 * X_estNTAll[1, :, n], "g-.",
linewidth=0.5)
# Position/velocity traces
ax_xp.plot(time, 100 * X_estAll[0, :, n], "b-.", linewidth=0.5)
ax_xp.plot(time, 100 * X_estNTAll[0, :, n], "g-.", linewidth=0.5)
ax_yp.plot(time, 100 * X_estAll[1, :, n], "b-.", linewidth=0.5)
ax_yp.plot(time, 100 * X_estNTAll[1, :, n], "g-.", linewidth=0.5)
ax_xv.plot(time, 100 * X_estAll[2, :, n], "b-.", linewidth=0.5)
ax_xv.plot(time, 100 * X_estNTAll[2, :, n], "g-.", linewidth=0.5)
ax_yv.plot(time, 100 * X_estAll[3, :, n], "b-.", linewidth=0.5)
ax_yv.plot(time, 100 * X_estNTAll[3, :, n], "g-.", linewidth=0.5)

# --- Mean traces (thick solid, on top) ---
# --- Mean traces (thick solid — MATLAB plots only means, no individual) ---
mS_est = np.mean(S_estAll, axis=0)
mS_estNT = np.mean(S_estNTAll, axis=0)
mMU_est = np.mean(MU_estAll, axis=0)
Expand Down
Loading