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Merged
Achille-V merged 5 commits into from
Jul 17, 2026
Merged

Update to multi_dataset_analysis #63

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4d31c48
Correction methods_config.json
Achille-V Jul 13, 2026
95fd0d8
Merge branch 'task_dFC_hybrid' of https://github.com/Achille-V/dFC in…
Achille-V Jul 13, 2026
4717568
Lower memory request for run_ML.sh
Achille-V Jul 14, 2026
ed4544b
Added separation for hybrid methods in multi_dataset_analysis
Achille-V Jul 16, 2026
9433063
Adding hybrid set to ml_results.py
Achille-V Jul 17, 2026
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68 changes: 63 additions & 5 deletions task_dFC/multi_dataset_analysis/ml_results.py
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Original file line number Diff line number Diff line change
Expand Up @@ -56,9 +56,47 @@
"DiscreteHMM",
]
)

HYBRID_METHODS = frozenset(
[
"AdaptiveDccRandom_hybrid_ensemble",
"AdaptiveEdgeKalman_hybrid",
"AdaptiveQuantumReservoir_hybrid",
"AdaptiveRandomSparse_hybrid",
"AdaptiveRobustDifferential_hybrid_ensemble",
"ChangepointMultiscaleExp_hybrid_ensemble",
"ChangepointRobustExp_hybrid",
"DccChangepointSparse_hybrid",
"DccEdgeExponential_hybrid",
"DccKalmanVolatility_hybrid_ensemble",
"DifferentialEdgeKalman_hybrid",
"EdgeKalmanExp_hybrid_ensemble",
"EdgeRandomReservoir_hybrid_ensemble",
"EdgeStftQuantum_hybrid",
"KalmanReservoirMultiscale_hybrid",
"MultiscaleDccKalman_hybrid",
"QuantumMultiscaleKalman_hybrid_ensemble",
"QuantumRandomExp_hybrid",
"RandomFourierKalman_hybrid",
"ReservoirChangepointRobust_hybrid_ensemble",
"ReservoirEdgeDcc_hybrid",
"RobustDifferentialStft_hybrid",
"RobustSparseEdge_hybrid",
"RobustVolatilitySliding_hybrid_ensemble",
"SlidingVolatilityDcc_hybrid",
"SparseDccExp_hybrid_ensemble",
"StftEdgeAdaptive_hybrid_ensemble",
"StftExpKalman_hybrid",
"StftQuantumSparse_hybrid_ensemble",
"VolatilityAdaptiveEdge_hybrid"
]
)

_AIGM_COLOR = "#0077B6"
_HYBRID_COLOR = "#30AC30"
_NON_AIGM_COLOR = "#E63946"
_NON_AIGM_LABEL_COLOR = "#D4721A"
_HYBRID_LABEL_COLOR = "#30AC30"
_METRIC_SHORT = {
"Logistic regression balanced accuracy": "LogReg BA",
"SVM balanced accuracy": "SVM BA",
Expand Down Expand Up @@ -487,6 +525,9 @@ def _highlight_nonaigm_labels(ax):
for label in ax.get_yticklabels():
if label.get_text() in NON_AIGM_METHODS:
label.set_color(_NON_AIGM_LABEL_COLOR)
for label in ax.get_yticklabels():
if label.get_text() in HYBRID_METHODS:
label.set_color(_HYBRID_LABEL_COLOR)


def _build_experiment_legend(
Expand Down Expand Up @@ -922,13 +963,14 @@ def plot_aigm_comparison(

df_best = df_best.copy()
df_best["group"] = df_best["dFC method"].apply(
lambda m: "Non-AIGM" if m in NON_AIGM_METHODS else "AIGM"
lambda m: "Non-AIGM" if m in NON_AIGM_METHODS else "Hybrid" if m in HYBRID_METHODS else "AIGM"
)

group_order = ["AIGM", "Non-AIGM"]
group_order = ["Hybrid","AIGM", "Non-AIGM"]
n_aigm = df_best[df_best["group"] == "AIGM"]["dFC method"].nunique()
n_non_aigm = df_best[df_best["group"] == "Non-AIGM"]["dFC method"].nunique()
group_labels = [f"AIGM\n(n={n_aigm} methods)", f"Non-AIGM\n(n={n_non_aigm} methods)"]
n_hybrid = df_best[df_best["group"] == "Hybrid"]["dFC method"].nunique()
group_labels = [f"Hybrid\n(n={n_hybrid} methods)",f"AIGM\n(n={n_aigm} methods)", f"Non-AIGM\n(n={n_non_aigm} methods)"]
df_best["group_label"] = df_best["group"].map(dict(zip(group_order, group_labels)))

fig, ax = plt.subplots(figsize=(9, 4))
Expand All @@ -953,7 +995,7 @@ def plot_aigm_comparison(

# One point per (method × experiment), colored by group
rng = np.random.default_rng(42)
group_colors = {"AIGM": _AIGM_COLOR, "Non-AIGM": _NON_AIGM_COLOR}
group_colors = {"AIGM": _AIGM_COLOR, "Non-AIGM": _NON_AIGM_COLOR, "Hybrid": _HYBRID_COLOR}
for i, (group, label) in enumerate(zip(group_order, group_labels)):
vals = df_best[df_best["group"] == group]["score"].dropna().values
y_jit = i + rng.uniform(-0.18, 0.18, len(vals))
Expand All @@ -970,7 +1012,9 @@ def plot_aigm_comparison(
# Mann-Whitney p-value
aigm_vals = df_best[df_best["group"] == "AIGM"]["score"].dropna().values
non_aigm_vals = df_best[df_best["group"] == "Non-AIGM"]["score"].dropna().values
if len(aigm_vals) >= 2 and len(non_aigm_vals) >= 2:
hybrid_vals = df_best[df_best["group"] == "Hybrid"]["score"].dropna().values
#Ajouter version pour p-value AIGM vs Hybrid
if len(aigm_vals) >= 2 and len(non_aigm_vals) >= 2:
_, pval = mannwhitneyu(aigm_vals, non_aigm_vals, alternative="two-sided")
pstr = "p<0.001" if pval < 0.001 else f"p={pval:.3f}"
ax.text(
Expand All @@ -984,6 +1028,20 @@ def plot_aigm_comparison(
fontweight="bold",
bbox=dict(boxstyle="round,pad=0.3", fc="white", ec="#BBBBBB", alpha=0.9),
)
if len(aigm_vals) >= 2 and len(hybrid_vals) >= 2:
_, pval = mannwhitneyu(aigm_vals, hybrid_vals, alternative="two-sided")
pstr = "p<0.001" if pval < 0.001 else f"p={pval:.3f}"
ax.text(
0.97,
0.03,
pstr,
transform=ax.transAxes,
ha="right",
va="top",
fontsize=11,
fontweight="bold",
bbox=dict(boxstyle="round,pad=0.3", fc="white", ec="#BBBBBB", alpha=0.9),
)

lower, upper = get_pointplot_limits(metric)
if metric == "SI":
Expand Down
32 changes: 0 additions & 32 deletions task_dFC/run_scripts_slurm/achillev@narval.alliancecan
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60 changes: 30 additions & 30 deletions task_dFC/run_scripts_slurm/methods_config.json
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Original file line number Diff line number Diff line change
Expand Up @@ -47,36 +47,36 @@
"dict_alpha": 0.1
},
"MEASURES_name_lst": [
"ADAPTIVE_DCC_RANDOM_HYBRID_ENSEMBLE",
"ADAPTIVE_EDGE_KALMAN_HYBRID",
"ADAPTIVE_QUANTUM_RESERVOIR_HYBRID",
"ADAPTIVE_RANDOM_SPARSE_HYBRID",
"ADAPTIVE_ROBUST_DIFFERENTIAL_HYBRID_ENSEMBLE",
"CHANGEPOINT_MULTISCALE_EXP_HYBRID_ENSEMBLE",
"CHANGEPOINT_ROBUST_EXP_HYBRID",
"DCC_CHANGEPOINT_SPARSE_HYBRID",
"DCC_EDGE_EXPONENTIAL_HYBRID",
"DCC_KALMAN_VOLATILITY_HYBRID_ENSEMBLE",
"DIFFERENTIAL_EDGE_KALMAN_HYBRID",
"EDGE_KALMAN_EXP_HYBRID_ENSEMBLE",
"EDGE_RANDOM_RESERVOIR_HYBRID_ENSEMBLE",
"EDGE_STFT_QUANTUM_HYBRID",
"KALMAN_RESERVOIR_MULTISCALE_HYBRID",
"MULTISCALE_DCC_KALMAN_HYBRID",
"QUANTUM_MULTISCALE_KALMAN_HYBRID_ENSEMBLE",
"QUANTUM_RANDOM_EXP_HYBRID",
"RANDOM_FOURIER_KALMAN_HYBRID",
"RESERVOIR_CHANGEPOINT_ROBUST_HYBRID_ENSEMBLE",
"RESERVOIR_EDGE_DCC_HYBRID",
"ROBUST_DIFFERENTIAL_STFT_HYBRID",
"ROBUST_SPARSE_EDGE_HYBRID",
"ROBUST_VOLATILITY_SLIDING_HYBRID_ENSEMBLE",
"SLIDING_VOLATILITY_DCC_HYBRID",
"SPARSE_DCC_EXP_HYBRID_ENSEMBLE",
"STFT_EDGE_ADAPTIVE_HYBRID_ENSEMBLE",
"STFT_EXP_KALMAN_HYBRID",
"STFT_QUANTUM_SPARSE_HYBRID_ENSEMBLE",
"VOLATILITY_ADAPTIVE_EDGE_HYBRID"
"AdaptiveDccRandom_hybrid_ensemble",
"AdaptiveEdgeKalman_hybrid",
"AdaptiveQuantumReservoir_hybrid",
"AdaptiveRandomSparse_hybrid",
"AdaptiveRobustDifferential_hybrid_ensemble",
"ChangepointMultiscaleExp_hybrid_ensemble",
"ChangepointRobustExp_hybrid",
"DccChangepointSparse_hybrid",
"DccEdgeExponential_hybrid",
"DccKalmanVolatility_hybrid_ensemble",
"DifferentialEdgeKalman_hybrid",
"EdgeKalmanExp_hybrid_ensemble",
"EdgeRandomReservoir_hybrid_ensemble",
"EdgeStftQuantum_hybrid",
"KalmanReservoirMultiscale_hybrid",
"MultiscaleDccKalman_hybrid",
"QuantumMultiscaleKalman_hybrid_ensemble",
"QuantumRandomExp_hybrid",
"RandomFourierKalman_hybrid",
"ReservoirChangepointRobust_hybrid_ensemble",
"ReservoirEdgeDcc_hybrid",
"RobustDifferentialStft_hybrid",
"RobustSparseEdge_hybrid",
"RobustVolatilitySliding_hybrid_ensemble",
"SlidingVolatilityDcc_hybrid",
"SparseDccExp_hybrid_ensemble",
"StftEdgeAdaptive_hybrid_ensemble",
"StftExpKalman_hybrid",
"StftQuantumSparse_hybrid_ensemble",
"VolatilityAdaptiveEdge_hybrid"
],
"alter_hparams": [],
"params_multi_analysis": {
Expand Down
2 changes: 1 addition & 1 deletion task_dFC/run_scripts_slurm/run_ML.sh
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Original file line number Diff line number Diff line change
Expand Up @@ -4,7 +4,7 @@
#SBATCH --output=logs/ML_out_%A_%a.txt # %A = array job ID, %a = task ID
#SBATCH --error=logs/ML_err_%A_%a.txt
#SBATCH --time=24:00:00
#SBATCH --mem=128G
#SBATCH --mem=64G
#SBATCH --requeue

DATASET_INFO="./dataset_info.json"
Expand Down
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