update darcy dataset for mesh size and readme

README.md

@@ -73,11 +73,11 @@ Training data is generated on **random simple polygons** with varying numbers of
 
 | Subset | Samples | Polygons × Batch | Vertices | Mesh Size |
 |---|---|---|---|---|
-| `laplace2d_simple` | 20,000 | 250 × 10 | 3–12 | 0.1 |
-| `laplace2d_mixed_simple` | 40,000 | 10 × 20 | 3–12 | 0.1 |
-| `darcy2d_simple` | 40,000 | 250 × 10 | 3–16 | 0.1 |
-| `heat2d_simple` | 80,000 | 160 × 50 | 3–12 | 0.1 |
-| `nonlinear_poisson2d_simple` | 20,000 | 250 × 10 | 3–12 | 0.1 |
+| `laplace2d_simple` | 20,000 | 2000 × 10 | 3–12 | 0.1 |
+| `laplace2d_mixed_simple` | 40,000 | 2000 × 20 | 3–12 | 0.1 |
+| `darcy2d_simple` | 40,000 | 2500 × 10 | 3–16 | 0.1 |
+| `heat2d_simple` | 80,000 | 1600 × 50 | 3–12 | 0.1 |
+| `nonlinear_poisson2d_simple` | 20,000 | 2000 × 10 | 3–12 | 0.1 |
 
 > **Note:** Each random polygon is reused for multiple samples (the "Batch" count) with different boundary conditions and/or coefficient fields. Coordinates are shifted by $[0.5, 0.5]$ to center domains around the origin.
 
@@ -224,7 +224,7 @@ f_source = qf[:, 3]  # (N,)
 
 ```python
 # Load Heat equation data (time-dependent)
-with open("data/2d/heat2d_simple_100000_train.pkl", "rb") as f:
+with open("data/2d/heat2d_simple_80000_train.pkl", "rb") as f:
     datalist = pickle.load(f)
 
 sol, alpha, (bc,) = datalist[0]

darcy2d_simple_2500_test.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1e0810974f522b9c74821fc98c2da3179b8cf504d436dc3ec7b72e7bc5942fee
-size 17501663
+oid sha256:c2de63e4e8e278a0ecba54d82311f151921e576426e34217e26ff5aae777cb33
+size 17355636

darcy2d_simple_40000_train.pkl

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:403dd6836758a45615217f7286984943d520cf20c9a4a40c7cb50f510fa30737
-size 276414108
+oid sha256:48b35d4e6982fad7cbfd1c6e1a124b202abb734f3cf52cb6b0ffe70d9a0a5714
+size 276251850