fix: match Python figure styling to MATLAB reference

examples/paper/example01_mepsc_poisson.py

@@ -83,7 +83,7 @@ def _maybe_export(fig, export_dir: Path | None, name: str, dpi: int = 250):
     if export_dir is not None:
         export_dir.mkdir(parents=True, exist_ok=True)
         png_path = export_dir / f"{name}.png"
-        fig.savefig(png_path, dpi=dpi, bbox_inches="tight")
+        fig.savefig(png_path, dpi=dpi, facecolor="w", edgecolor="none")
         saved.append(png_path)
         print(f"  Saved {png_path}")
     return saved
@@ -149,8 +149,8 @@ def run_example01(*, export_figures: bool = False, export_dir: Path | None = Non
     spikeCollConst.plot(handle=ax)
     ax.set_title("Neural Raster with constant Mg$^{2+}$ Concentration",
                  fontweight="bold", fontsize=12)
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
-    ax.set_ylabel("mEPSCs", fontsize=12, fontweight="bold")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel("mEPSCs", fontname="Arial", fontsize=12, fontweight="bold")
     ax.set_yticks([0, 1])
 
     # (2,2,2): Inverse Gaussian transform (ACF)
@@ -165,13 +165,10 @@ def run_example01(*, export_figures: bool = False, export_dir: Path | None = Non
     ax.plot(np.asarray(lam.time, dtype=float),
             np.asarray(lam.data[:, 0], dtype=float),
             "b", linewidth=2)
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
-    ax.set_ylabel(lam.ylabel if hasattr(lam, "ylabel") else "spikes/sec",
-                  fontsize=12, fontweight="bold")
-    ax.legend(["$\\lambda_{const}$"], loc="upper right")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel(r"$\lambda(t)$ [Hz]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.legend(["$\\lambda_{const}$"], loc="upper right", fontsize=14)
 
-    fig1.suptitle("Example 01 — Figure 1: Constant Mg$^{2+}$ Summary",
-                  fontsize=14, fontweight="bold")
     fig1.tight_layout()
     figure_files.extend(_maybe_export(fig1, export_dir, "fig01_constant_mg_summary"))
 
@@ -194,18 +191,17 @@ def run_example01(*, export_figures: bool = False, export_dir: Path | None = Non
     ax = axes2[0]
     nstConst.plot(handle=ax)
     ax.set_yticks([0, 1])
-    ax.set_ylabel("mEPSCs", fontsize=12, fontweight="bold")
+    ax.set_ylabel("mEPSCs", fontname="Arial", fontsize=12, fontweight="bold")
     ax.set_title("Neural Raster with constant Mg$^{2+}$ Concentration",
                  fontweight="bold", fontsize=12)
 
     ax = axes2[1]
     nstWashout.plot(handle=ax)
     ax.set_yticks([0, 1])
-    ax.set_ylabel("mEPSCs", fontsize=12, fontweight="bold")
+    ax.set_ylabel("mEPSCs", fontname="Arial", fontsize=12, fontweight="bold")
     ax.set_title("Neural Raster with decreasing Mg$^{2+}$ Concentration",
                  fontweight="bold", fontsize=12)
 
-    fig2.suptitle("Example 01 — Figure 2: Constant vs Decreasing Mg$^{2+}$", fontsize=14, fontweight="bold")
     fig2.tight_layout()
     figure_files.extend(_maybe_export(fig2, export_dir, "fig02_washout_raster_overview"))
 
@@ -281,13 +277,11 @@ def run_example01(*, export_figures: bool = False, export_dir: Path | None = Non
     if lam.data.shape[1] > 1:
         ax.plot(t, np.asarray(lam.data[:, 1], dtype=float), "g", linewidth=2)
     ax.set_ylim(0, 5)
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
-    ax.set_ylabel(lam.ylabel if hasattr(lam, "ylabel") else "spikes/sec",
-                  fontsize=12, fontweight="bold")
-    ax.legend(["$\\lambda_{const}$", "$\\lambda_{const-epoch}$"], loc="upper right")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel(r"$\lambda(t)$ [Hz]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.legend(["$\\lambda_{const}$", "$\\lambda_{const-epoch}$"],
+              loc="upper right", fontsize=14)
 
-    fig3.suptitle("Example 01 — Figure 3: Piecewise Baseline Comparison",
-                  fontsize=14, fontweight="bold")
     fig3.tight_layout()
     figure_files.extend(_maybe_export(fig3, export_dir, "fig03_piecewise_baseline_comparison"))
 

examples/paper/example02_whisker_stimulus_thalamus.py

@@ -60,7 +60,7 @@ def _maybe_export(fig, export_dir: Path | None, name: str, dpi: int = 250):
     if export_dir is not None:
         export_dir.mkdir(parents=True, exist_ok=True)
         png_path = export_dir / f"{name}.png"
-        fig.savefig(png_path, dpi=dpi, bbox_inches="tight")
+        fig.savefig(png_path, dpi=dpi, facecolor="w", edgecolor="none")
         saved.append(png_path)
         print(f"  Saved {png_path}")
     return saved
@@ -150,28 +150,32 @@ def run_example02(*, export_figures: bool = False, export_dir: Path | None = Non
     nstView.setMaxTime(viewWindow)
     nstView.plot(handle=ax)
     ax.set_yticks([0, 1])
-    ax.set_title("Neural Raster", fontweight="bold", fontsize=12)
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
-    ax.set_ylabel("Spikes", fontsize=12, fontweight="bold")
+    ax.set_title("Neural Raster", fontweight="bold", fontsize=16, fontname="Arial")
+    ax.set_xlabel("")
+    ax.set_xticklabels([])
+    ax.set_ylabel("spikes", fontname="Arial", fontsize=12, fontweight="bold")
 
-    # Subplot 2: Stimulus displacement (first 21 s)
+    # Subplot 2: Stimulus displacement (first 21 s, black line matching MATLAB)
     ax = axes1[1]
     stimView = stim.getSigInTimeWindow(0, viewWindow)
-    stimView.plot(handle=ax)
-    ax.set_ylabel("Displacement [mm]", fontsize=12, fontweight="bold")
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
-
-    # Subplot 3: Stimulus velocity (derivative, first 21 s)
+    stimView.plot(handle=ax, plotPropsIn=[["k"]])
+    ax.get_legend().remove() if ax.get_legend() else None
+    ax.set_ylabel("Displacement [mm]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_xlabel("")
+    ax.set_xticklabels([])
+    ax.set_title("Stimulus - Whisker Displacement", fontweight="bold", fontsize=16, fontname="Arial")
+
+    # Subplot 3: Stimulus velocity (derivative, first 21 s, black line matching MATLAB)
     ax = axes1[2]
     stimDeriv = stim.derivative
     stimDerivView = stimDeriv.getSigInTimeWindow(0, viewWindow)
-    stimDerivView.plot(handle=ax)
+    stimDerivView.plot(handle=ax, plotPropsIn=[["k"]])
+    ax.get_legend().remove() if ax.get_legend() else None
     ax.set_ylim(-80, 80)
-    ax.set_ylabel("Velocity", fontsize=12, fontweight="bold")
-    ax.set_xlabel("time [s]", fontsize=12, fontweight="bold")
+    ax.set_ylabel("Displacement Velocity [mm/s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_title("Displacement Velocity", fontweight="bold", fontsize=16, fontname="Arial")
 
-    fig1.suptitle("Example 02 — Figure 1: Data Overview",
-                  fontsize=14, fontweight="bold")
     fig1.tight_layout()
     figure_files.extend(_maybe_export(
         fig1, export_dir, "fig01_data_overview"))
@@ -380,8 +384,6 @@ def run_example02(*, export_figures: bool = False, export_dir: Path | None = Non
     ax_coeff = fig2.add_subplot(gs[4:7, 1])
     modelCompare.plotCoeffs(handle=ax_coeff)
 
-    fig2.suptitle("Example 02 — Figure 2: Lag & History Selection",
-                  fontsize=14, fontweight="bold")
     figure_files.extend(_maybe_export(
         fig2, export_dir, "fig02_lag_and_model_comparison"))
 

examples/paper/example03_psth_and_ssglm.py

@@ -199,36 +199,38 @@ def run_part_a(data_dir, export_dir=None):
     # Top-left: CIF
     ax = axes1[0, 0]
     ax.plot(time, lambdaData, "b", linewidth=2)
-    ax.set_title("Simulated CIF", fontweight="bold", fontsize=14)
-    ax.set_xlabel("time [s]")
-    ax.set_ylabel("spikes/sec")
+    ax.set_title("Simulated Conditional Intensity Function (CIF)",
+                 fontweight="bold", fontsize=14, fontname="Arial")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel(r"$\lambda(t)$ [spikes/sec]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.legend([r"$\lambda_1$"], loc="upper right", fontsize=14)
 
     # Bottom-left: simulated raster
     ax = axes1[1, 0]
     spikeCollSim.plot(handle=ax)
     ax.set_yticks(range(0, numRealizations + 1, 5))
-    ax.set_title(f"{numRealizations} Simulated Sample Paths",
-                 fontweight="bold", fontsize=14)
-    ax.set_xlabel("time [s]")
-    ax.set_ylabel("Trial [k]")
+    ax.set_title(f"{numRealizations} Simulated Point Process Sample Paths",
+                 fontweight="bold", fontsize=14, fontname="Arial")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel("Trial [k]", fontname="Arial", fontsize=12, fontweight="bold")
 
     # Top-right: real cell 6 raster
     ax = axes1[0, 1]
     spikeCollReal1.plot(handle=ax)
     ax.set_yticks(range(0, numTrials + 1, 2))
     ax.set_title("Response to Moving Visual Stimulus (Neuron 6)",
-                 fontweight="bold", fontsize=14)
-    ax.set_xlabel("time [s]")
-    ax.set_ylabel("Trial [k]")
+                 fontweight="bold", fontsize=14, fontname="Arial")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel("Trial [k]", fontname="Arial", fontsize=12, fontweight="bold")
 
     # Bottom-right: real cell 1 raster
     ax = axes1[1, 1]
     spikeCollReal2.plot(handle=ax)
     ax.set_yticks(range(0, numTrials + 1, 2))
     ax.set_title("Response to Moving Visual Stimulus (Neuron 1)",
-                 fontweight="bold", fontsize=14)
-    ax.set_xlabel("time [s]")
-    ax.set_ylabel("Trial [k]")
+                 fontweight="bold", fontsize=14, fontname="Arial")
+    ax.set_xlabel("time [s]", fontname="Arial", fontsize=12, fontweight="bold")
+    ax.set_ylabel("Trial [k]", fontname="Arial", fontsize=12, fontweight="bold")
 
     fig1.tight_layout()
 
@@ -496,7 +498,8 @@ def run_part_b(data_dir, export_dir=None):
     # ------------------------------------------------------------------
     # Figure 5: True/PSTH/SSGLM stimulus effect surfaces
     # Match MATLAB: mesh(trial, time, data) with view([90 -90]) → top-down
-    # Using pcolormesh for clean 2D rendering matching MATLAB's top-down mesh
+    # MATLAB orientation: time [s] on x-axis, Trial [k] on y-axis
+    # (matches fig03 bottom-panel "True Conditional Intensity Function")
     # ------------------------------------------------------------------
     fig5, axes5 = plt.subplots(3, 1, figsize=(14, 9))
     trial_axis = np.arange(1, numRealizations + 1)
@@ -509,12 +512,17 @@ def run_part_b(data_dir, export_dir=None):
     ]
     for ax, (data, title_str) in zip(axes5, surfaces):
         # data is (T, K) — time on rows, trials on columns
-        # MATLAB: imagesc shows trial on x, time on y
-        ax.pcolormesh(trial_axis, basis_time[:T_act], data, cmap="viridis",
+        # Transpose so trials are on y-axis and time on x-axis,
+        # matching MATLAB nSTATPaperExamples_15.png orientation.
+        ax.pcolormesh(basis_time[:T_act], trial_axis, data.T, cmap="viridis",
                       shading="auto")
-        ax.set_ylabel("time [s]")
+        ax.set_xlabel("time [s]")
+        ax.set_ylabel("Trial [k]")
         ax.set_title(title_str, fontweight="bold", fontsize=14)
-    axes5[-1].set_xlabel("Trial [k]")
+    # Remove redundant per-subplot x-labels except the bottom one
+    for ax in axes5[:-1]:
+        ax.set_xlabel("")
+        ax.set_xticklabels([])
 
     fig5.tight_layout()
     print("  Figure 5: Stimulus effect surfaces (top-down mesh)")
@@ -613,7 +621,7 @@ def run_example03(*, export_figures: bool = False, export_dir: Path | None = Non
         export_dir.mkdir(parents=True, exist_ok=True)
         for name, fig in all_figs.items():
             path = export_dir / f"{name}.png"
-            fig.savefig(str(path), dpi=150, bbox_inches="tight")
+            fig.savefig(str(path), dpi=250, facecolor="w", edgecolor="none")
             print(f"  Saved {path}")
 
     plt.show()

examples/paper/example04_place_cells_continuous_stimulus.py

@@ -252,15 +252,19 @@ def run_example04(*, export_figures: bool = False, export_dir: Path | None = Non
     fig1, axes1 = plt.subplots(2, 2, figsize=(12, 10))
     for i, cidx in enumerate(exampleCells):
         ax = axes1.flat[i]
-        ax.plot(x1, y1, "b-", linewidth=0.5, alpha=0.5)
+        h1, = ax.plot(x1, y1, "b", linewidth=0.5)
         n = neurons1[min(cidx, nCells1 - 1)]
         xn = np.asarray(n["xN"].item(), dtype=float).ravel()
         yn = np.asarray(n["yN"].item(), dtype=float).ravel()
-        ax.plot(xn, yn, "r.", markersize=7)
-        ax.set_title(f"Cell {cidx + 1}", fontweight="bold", fontsize=12)
+        h2, = ax.plot(xn, yn, "r.", markersize=7)
+        ax.set_title(f"Cell#{cidx + 1}", fontweight="bold", fontsize=12, fontname="Arial")
+        ax.set_xlabel("X Position")
+        ax.set_ylabel("Y Position")
+        ax.set_xticks([-1, -0.5, 0, 0.5, 1])
+        ax.set_yticks([-1, -0.5, 0, 0.5, 1])
         ax.set_aspect("equal")
-    fig1.suptitle("Animal 1 — Example Place Cells", fontweight="bold",
-                  fontsize=14)
+        if i == 3:
+            ax.legend([h1, h2], ["Animal Path", "Location at time of spike"])
     fig1.tight_layout()
 
     # ==================================================================
@@ -359,10 +363,12 @@ def _plot_heatmaps(fit_results, nCells, title_prefix, design_gauss,
             axesG[row, col].set_visible(False)
             axesZ[row, col].set_visible(False)
 
-        figG.suptitle(f"{title_prefix} — Gaussian Place Fields",
-                      fontweight="bold", fontsize=14)
-        figZ.suptitle(f"{title_prefix} — Zernike Place Fields",
-                      fontweight="bold", fontsize=14)
+        # Match MATLAB sgtitle format: "Gaussian Place Fields - Animal#N"
+        animal_num = title_prefix.replace("Animal ", "")
+        figG.suptitle(f"Gaussian Place Fields - Animal#{animal_num}",
+                      fontweight="bold", fontsize=12)
+        figZ.suptitle(f"Zernike Place Fields - Animal#{animal_num}",
+                      fontweight="bold", fontsize=12)
         figG.tight_layout()
         figZ.tight_layout()
         return figG, figZ
@@ -430,7 +436,7 @@ def _plot_heatmaps(fit_results, nCells, title_prefix, design_gauss,
         export_dir.mkdir(parents=True, exist_ok=True)
         for name, fig in all_figs.items():
             path = export_dir / f"{name}.png"
-            fig.savefig(str(path), dpi=150, bbox_inches="tight")
+            fig.savefig(str(path), dpi=250, facecolor="w", edgecolor="none")
             print(f"  Saved {path}")
 
     plt.show()

examples/paper/example05_decoding_ppaf_pphf.py

@@ -896,7 +896,7 @@ def run_example05(*, export_figures=False, export_dir=None, show=False):
         ]
         for i, fig in enumerate(figures):
             path = export_dir / f"{fig_names[i]}.png"
-            fig.savefig(path, dpi=150, bbox_inches="tight")
+            fig.savefig(path, dpi=250, facecolor="w", edgecolor="none")
             print(f"  Saved: {path}")
 
     if show: