fx w_axis

app.py

@@ -271,28 +271,26 @@ def plot_expression_RIGID(arousal, dominance, valence):
         verticalalignment="top",
     )
 
-
 def explode(data):
-    '''replicate 16 x 16 x 16 cube to edges array 31 x 31 x 31'''
-    size = np.array(data.shape)*2
-    data_e = np.zeros(size - 1, dtype=data.dtype)
-    data_e[::2, ::2, ::2] = data
-    return data_e
-
+    """
+    Expands a 3D array by creating gaps between voxels.
+    This function is used to create the visual separation between the voxels.
+    """
+    shape_orig = np.array(data.shape)
+    shape_new = shape_orig * 2 - 1
+    retval = np.zeros(shape_new, dtype=data.dtype)
+    retval[::2, ::2, ::2] = data
+    return retval
 
 def plot_expression(arousal, dominance, valence):
-
     '''_h = cuda tensor (N_PIX, N_PIX, N_PIX)'''
 
-    N_PIX=5
+    N_PIX = 5
     _h = np.random.rand(N_PIX, N_PIX, N_PIX) * 1e-3
     adv = np.array([arousal, .994 - dominance, valence]).clip(0, .99)
     arousal, dominance, valence = (adv * N_PIX).astype(np.int64)  # find voxel
     _h[arousal, dominance, valence] = .22
 
-
-
-
     filled = np.ones((N_PIX, N_PIX, N_PIX), dtype=bool)
 
     # upscale the above voxel image, leaving gaps
@@ -333,37 +331,26 @@ def plot_expression(arousal, dominance, valence):
     ax.set_ylabel('dominance', fontsize=10, labelpad=10)
     ax.grid(False)
 
- 
-
-
     ax.plot([N_PIX, N_PIX], [0, N_PIX + .2], [N_PIX, N_PIX], 'g', linewidth=1)
     ax.plot([0, N_PIX], [N_PIX, N_PIX + .24], [N_PIX, N_PIX], 'k', linewidth=1)
-
-    # Bottom face lines
-    # ax.plot([0, N_PIX + line_extension], [0, 0], [0, 0], 'y', linewidth=1)
-    # ax.plot([0, 0], [0, N_PIX + line_extension], [0, 0], 'r', linewidth=1)
-    # ax.plot([N_PIX, N_PIX + line_extension], [0, N_PIX], [0, 0], 'm', linewidth=1)
-    # ax.plot([0, N_PIX], [N_PIX, N_PIX + line_extension], [0, 0], 'c', linewidth=1)
-
-    # Vertical lines
-    # ax.plot([0, 0], [0, 0], [0, N_PIX + line_extension], 'b', linewidth=1)
-    # ax.plot([N_PIX, N_PIX], [0, 0], [0, N_PIX + line_extension], 'w', linewidth=1)
-    # ax.plot([N_PIX, N_PIX], [N_PIX, N_PIX], [0, N_PIX + line_extension], 'orange', linewidth=1)
-    # ax.plot([0, 0], [N_PIX, N_PIX], [0, N_PIX + line_extension], 'lime', linewidth=1)
     
-    # # Missing lines on the top face
+    # Missing lines on the top face
     ax.plot([0, 0], [0, N_PIX], [N_PIX, N_PIX], 'darkred', linewidth=1)
     ax.plot([0, N_PIX], [0, 0], [N_PIX, N_PIX], 'darkblue', linewidth=1)
 
     # Set pane colors after plotting the lines
-    ax.w_xaxis.set_pane_color((0.8, 0.8, 0.8, 0.5))
-    ax.w_yaxis.set_pane_color((0.8, 0.8, 0.8, 0.5))
-    ax.w_zaxis.set_pane_color((0.8, 0.8, 0.8, 0.0))
+    # UPDATED: Replaced `w_xaxis` with `xaxis` and `w_yaxis` with `yaxis`.
+    ax.xaxis.set_pane_color((0.8, 0.8, 0.8, 0.5))
+    ax.yaxis.set_pane_color((0.8, 0.8, 0.8, 0.5))
+    ax.zaxis.set_pane_color((0.8, 0.8, 0.8, 0.0))
 
     # Restore the limits to prevent the plot from expanding
     ax.set_xlim(0, N_PIX)
     ax.set_ylim(0, N_PIX)
     ax.set_zlim(0, N_PIX)
+
+    #plt.show()
+
 # ------