[Example] Refactor example library

.github/workflows/presubmit.yml

@@ -85,7 +85,7 @@ jobs:
           export PATH=$TAICHI_REPO_DIR/bin:$PATH
           export PATH=$TAICHI_REPO_DIR/taichi-llvm/bin/:$PATH
           export PYTHONPATH=$TAICHI_REPO_DIR/python
-          python examples/laplace.py
+          python examples/algorithm/laplace.py
           ti diagnose
           ./build/taichi_cpp_tests
           ti test -vr2 -t2
@@ -139,7 +139,7 @@ jobs:
           export PATH=$TAICHI_REPO_DIR/bin:$PATH
           export PATH=$TAICHI_REPO_DIR/taichi-llvm/bin/:$PATH
           export PYTHONPATH=$TAICHI_REPO_DIR/python
-          python examples/laplace.py
+          python examples/algorithm/laplace.py
           ti diagnose
           [ "$RUN_CPP_TESTS" = "ON" ] && ./build/taichi_cpp_tests
           ti test -vr2 -t2
@@ -173,7 +173,7 @@ jobs:
           export PYTHONPATH=$TAICHI_REPO_DIR/python
           export DISPLAY=:1
           glewinfo
-          $PYTHON examples/laplace.py
+          $PYTHON examples/algorithm/laplace.py
           ti diagnose
           ti test -vr2 -t2
 
@@ -230,7 +230,7 @@ jobs:
           $env:PATH += ";C:\taichi_clang\bin"
           $env:PATH += ";$env:TAICHI_REPO_DIR\bin"
           python -c "import taichi"
-          python examples/laplace.py
+          python examples/algorithm/laplace.py
           python bin/taichi diagnose
           python bin/taichi test -Cvr2 -t2
         env:

.github/workflows/release.yml

@@ -51,7 +51,7 @@ jobs:
           export PATH=$TAICHI_REPO_DIR/bin:$PATH
           export PATH=$TAICHI_REPO_DIR/taichi-llvm/bin/:$PATH
           export PYTHONPATH=$TAICHI_REPO_DIR/python
-          python examples/laplace.py
+          python examples/algorithm/laplace.py
           ti diagnose
           ti test -vr2 -t2
 

examples/laplace.py → examples/algorithm/laplace.py

@@ -1,18 +1,20 @@
 import taichi as ti
 
 ti.init(arch=ti.cpu)
+
+N = 16
+
 x, y = ti.field(ti.f32), ti.field(ti.f32)
 
-ti.root.dense(ti.ij, 16).place(x, y)
+ti.root.dense(ti.ij, N).place(x, y)
 
 
 @ti.kernel
 def laplace():
     for i, j in x:
-        if (i + j) % 3 == 0:
-            y[i, j] = 4.0 * x[i, j] - x[i - 1,
-                                        j] - x[i + 1,
-                                               j] - x[i, j - 1] - x[i, j + 1]
+        if (i + j) % 3 == 0 and 1 <= i < N - 1 and 1 <= j < N - 1:
+            y[i, j] = 4.0 * x[i, j] \
+                    - x[i - 1, j] - x[i + 1, j] - x[i, j - 1] - x[i, j + 1]
         else:
             y[i, j] = 0.0
 

examples/algorithm/marching_squares.py

@@ -0,0 +1,107 @@
+# Marching squares algorithm
+# https://en.wikipedia.org/wiki/Marching_squares
+
+import numpy as np
+
+import taichi as ti
+
+ti.init(arch=ti.cpu)
+
+N = 128
+
+edge_table_np = np.array(
+    [
+        [[-1, -1], [-1, -1]],  # Case 0
+        [[3, 0], [-1, -1]],  # Case 1
+        [[0, 1], [-1, -1]],  # Case 2
+        [[1, 3], [-1, -1]],  # Case 3
+        [[1, 2], [-1, -1]],  # Case 4
+        [[0, 1], [2, 3]],  # Case 5
+        [[0, 2], [-1, -1]],  # Case 6
+        [[2, 3], [-1, -1]],  # Case 7
+        [[2, 3], [-1, -1]],  # Case 8
+        [[0, 2], [-1, -1]],  # Case 9
+        [[0, 3], [1, 2]],  # Case 10
+        [[1, 2], [-1, -1]],  # Case 11
+        [[1, 3], [-1, -1]],  # Case 12
+        [[0, 1], [-1, -1]],  # Case 13
+        [[3, 0], [-1, -1]],  # Case 14
+        [[-1, -1], [-1, -1]],  # Case 15
+    ],
+    dtype=np.int32)
+
+pixels = ti.field(float, (N, N))
+
+edge_coords = ti.Vector.field(2, float, (N**2, 2))  # generated edges
+edge_table = ti.Vector.field(2, int, (16, 2))  # edge table (constant)
+edge_table.from_numpy(edge_table_np)
+
+
+@ti.func
+def gauss(x, sigma):
+    # Un-normalized Gaussian distribution
+    return ti.exp(-x**2 / (2 * sigma**2))
+
+
+@ti.kernel
+def touch(mx: float, my: float, size: float):
+    for I in ti.grouped(pixels):
+        mouse_pos = ti.Vector([mx, my]) + 0.5 / N
+        peak_center = gauss((I / N - 0.5).norm(), size)
+        peak_mouse = gauss((I / N - mouse_pos).norm(), size)
+        pixels[I] = peak_center + peak_mouse
+
+
+@ti.func
+def get_vertex(vertex_id):
+    # bottom edge
+    v = ti.Vector([0.5, 0.0])
+    # right edge
+    if vertex_id == 1:
+        v = ti.Vector([1.0, 0.5])
+    # top edge
+    elif vertex_id == 2:
+        v = ti.Vector([0.5, 1.0])
+    # left edge
+    elif vertex_id == 3:
+        v = ti.Vector([0.0, 0.5])
+    return v
+
+
+@ti.kernel
+def march(level: float) -> int:
+    n_edges = 0
+
+    for i, j in ti.ndrange(N - 1, N - 1):
+        case_id = 0
+        if pixels[i, j] > level: case_id |= 1
+        if pixels[i + 1, j] > level: case_id |= 2
+        if pixels[i + 1, j + 1] > level: case_id |= 4
+        if pixels[i, j + 1] > level: case_id |= 8
+
+        for k in range(2):
+            if edge_table[case_id, k][0] == -1:
+                break
+
+            n = ti.atomic_add(n_edges, 1)
+            for l in ti.static(range(2)):
+                vertex_id = edge_table[case_id, k][l]
+                edge_coords[n, l] = ti.Vector([i, j
+                                               ]) + get_vertex(vertex_id) + 0.5
+
+    return n_edges
+
+
+level = 0.2
+
+gui = ti.GUI('Marching squares')
+while gui.running and not gui.get_event(gui.ESCAPE):
+    touch(*gui.get_cursor_pos(), 0.05)
+    n_edges = march(level)
+    edge_coords_np = edge_coords.to_numpy()[:n_edges] / N
+    gui.set_image(ti.imresize(pixels, *gui.res) / level)
+    gui.lines(edge_coords_np[:, 0],
+              edge_coords_np[:, 1],
+              color=0xff66cc,
+              radius=1.5)
+    gui.show()

examples/quadtree.py → examples/algorithm/quadtree.py

@@ -9,10 +9,12 @@
 R = 7
 N = K**R
 
-Broot = ti.root
+Broot = None
 B = ti.root
 for r in range(R):
     B = B.bitmasked(ti.ij, (K, K))
+    if r == 0:
+        Broot = B
 
 qt = ti.field(ti.f32)
 B.place(qt)

examples/autodiff_minimization.py → examples/autodiff/minimization.py

@@ -2,6 +2,8 @@
 
 import taichi as ti
 
+ti.init(arch=ti.cpu)
+
 n = 8
 x = ti.field(dtype=ti.f32, shape=n, needs_grad=True)
 y = ti.field(dtype=ti.f32, shape=n)

examples/mnist.py → examples/autodiff/mnist.py

@@ -5,6 +5,8 @@
 
 import taichi as ti
 
+ti.init(arch=ti.gpu)
+
 # ti.runtime.print_preprocessed = True
 # ti.cfg.print_ir = True
 

examples/mnist_download_data.py → examples/autodiff/mnist_download_data.py

@@ -1,9 +1,10 @@
 # https://github.com/hsjeong5/MNIST-for-Numpy
 
-import numpy as np
-from urllib import request
 import gzip
 import pickle
+from urllib import request
+
+import numpy as np
 
 filename = [["training_images", "train-images-idx3-ubyte.gz"],
             ["test_images", "t10k-images-idx3-ubyte.gz"],

examples/autodiff_regression.py → examples/autodiff/regression.py

@@ -6,6 +6,8 @@
 import taichi as ti
 import taichi as tc
 
+ti.init(arch=ti.cpu)
+
 tc.set_gdb_trigger(True)
 
 number_coeffs = 4

examples/taichi_autodiff.py → examples/autodiff/simple_derivative.py

@@ -2,6 +2,8 @@
 
 import taichi as ti
 
+ti.init(arch=ti.cpu)
+
 N = 2048
 x, y = ti.field(ti.f32), ti.field(ti.f32)
 

examples/gui_image_io.py → examples/features/gui/gui_image_io.py

@@ -2,6 +2,8 @@
 
 import taichi as ti
 
+ti.init(arch=ti.cpu)
+
 pixel = ti.field(ti.u8, shape=(512, 512, 3))
 
 

examples/export_mesh.py → examples/features/io/export_mesh.py

@@ -1,6 +1,9 @@
-import taichi as ti
-import numpy as np
 import os
+
+import numpy as np
+
+import taichi as ti
+
 # A 2D grid with quad faces
 #     y
 #     |