Github action: auto-update.

Author: github-actions[bot]

dev/_downloads/02a7a82499cf14d2702c9234035c44c4/plot_diffusion_advection_solver.zip

@@ -96,7 +96,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.13.3"
+      "version": "3.13.4"
     }
   },
   "nbformat": 4,

dev/_downloads/07795e165bda9881ff980becb31905ab/plot_diffusion_advection_solver.ipynb

@@ -154,7 +154,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.13.3"
+      "version": "3.13.4"
     }
   },
   "nbformat": 4,

dev/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip

@@ -107,7 +107,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.13.3"
+      "version": "3.13.4"
     }
   },
   "nbformat": 4,

dev/_downloads/09a1631d14c6eb51e552aa53b9f6d3e8/checkpoint_FNO_darcy.ipynb

@@ -96,7 +96,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.13.3"
+      "version": "3.13.4"
     }
   },
   "nbformat": 4,

dev/_downloads/1bff93ede268f57f2123a573685b3499/plot_darcy_flow_spectrum.zip

@@ -58,7 +58,7 @@
       },
       "outputs": [],
       "source": [
-        "x_in = torch.linspace(0, 2, nx)\ny_in = torch.linspace(0, 3, ny)\n\nx_in, y_in = torch.meshgrid(x_in, y_in)\ngrid_in = torch.stack([x_in.reshape(-1), y_in.reshape(-1)])\n\n# compute the correct quadrature weights\n# IMPORTANT: this needs to be done right in order for the DISCO convolution to be normalized proeperly\nw_x = 2*torch.ones_like(x_in) / nx\nw_y = 3*torch.ones_like(y_in) / ny\nq_in = (w_x * w_y).reshape(-1)"
+        "x_in = torch.linspace(0, 2, nx)\ny_in = torch.linspace(0, 3, ny)\n\nx_in, y_in = torch.meshgrid(x_in, y_in, indexing='ij')\ngrid_in = torch.stack([x_in.reshape(-1), y_in.reshape(-1)])\n\n# compute the correct quadrature weights\n# IMPORTANT: this needs to be done right in order for the DISCO convolution to be normalized proeperly\nw_x = 2*torch.ones_like(x_in) / nx\nw_y = 3*torch.ones_like(y_in) / ny\nq_in = (w_x * w_y).reshape(-1)"
       ]
     },
     {
@@ -112,7 +112,7 @@
       },
       "outputs": [],
       "source": [
-        "nxo = 90\nnyo = 120\n\nx_out = torch.linspace(0, 2, nxo)\ny_out = torch.linspace(0, 3, nyo)\n\nx_out, y_out = torch.meshgrid(x_out, y_out)\ngrid_out = torch.stack([x_out.reshape(-1), y_out.reshape(-1)])\n\n# compute the correct quadrature weights\nw_x = 2*torch.ones_like(x_out) / nxo\nw_y = 3*torch.ones_like(y_out) / nyo\nq_out = (w_x * w_y).reshape(-1)"
+        "nxo = 90\nnyo = 120\n\nx_out = torch.linspace(0, 2, nxo)\ny_out = torch.linspace(0, 3, nyo)\n\nx_out, y_out = torch.meshgrid(x_out, y_out, indexing='ij')\ngrid_out = torch.stack([x_out.reshape(-1), y_out.reshape(-1)])\n\n# compute the correct quadrature weights\nw_x = 2*torch.ones_like(x_out) / nxo\nw_y = 3*torch.ones_like(y_out) / nyo\nq_out = (w_x * w_y).reshape(-1)"
       ]
     },
     {
@@ -212,7 +212,7 @@
       "name": "python",
       "nbconvert_exporter": "python",
       "pygments_lexer": "ipython3",
-      "version": "3.13.3"
+      "version": "3.13.4"
     }
   },
   "nbformat": 4,