P0: normalize experiment imports and document homotopy checks

Author: flengyel

docs/homotopy_constraint_verification.md

@@ -0,0 +1,48 @@
+# `homotopy_constraint_verification.py` documentation
+
+## Location
+- Script: `experiments/homotopy_constraint_verification.py`
+
+## Purpose
+This script validates a combinatorial horn-index characterization by direct tensor-face computation.
+
+For each tested tensor shape and horn index `j`, it compares two sets:
+- `compute_missing_indices_dask(shape, j)` from `horn_map_reduce.py`
+- the set of basis indices `m` such that `d_i(E_m) = 0` for every face `i != j`
+
+## Algorithm
+For each `(shape, horn_j)`:
+1. Compute `n = min(shape) - 1` and skip if `horn_j` is out of range.
+2. Compute `expected_indices = compute_missing_indices_dask(shape, horn_j)`.
+3. Enumerate all multi-indices `m` in the shape.
+4. For each horn face index `i` (`0..n`, excluding `horn_j`):
+   - Build standard basis tensor `E_m`.
+   - Compute `face(E_m, i)`.
+   - Collect `m` where the face is the zero tensor.
+5. Intersect these zero-face index sets over all `i != horn_j`.
+6. Compare the intersection against `expected_indices` and report pass/fail.
+
+## Outputs
+The script prints:
+- per-case headers with shape and horn index,
+- counts from the combinatorial method and constraint method,
+- per-case pass/fail result,
+- final overall summary.
+
+## Logging
+- No file logger is configured.
+- All reporting is written to standard output.
+
+## Run
+From repository root, either use editable install:
+
+```powershell
+.\.venv\Scripts\python.exe experiments\homotopy_constraint_verification.py
+```
+
+Or run with explicit source path:
+
+```powershell
+$env:PYTHONPATH = 'src'
+.\.venv\Scripts\python.exe experiments\homotopy_constraint_verification.py
+```

docs/homotopy_constraint_verification_with_independence_test.md

@@ -0,0 +1,54 @@
+# `homotopy_constraint_verification_with_independence_test.py` documentation
+
+## Location
+- Script: `experiments/homotopy_constraint_verification_with_independence_test.py`
+
+## Purpose
+This script performs two empirical checks over standard basis tensors:
+1. linear independence of non-zero face images for each fixed face map,
+2. horn-constraint equivalence between combinatorial missing indices and direct face-zero constraints.
+
+## Algorithm
+### Step 1: Linear independence check
+For each tested `shape` and face index `i` in `0..dimen(shape_tensor)`:
+1. Enumerate basis tensors `E_m`.
+2. Compute `face(E_m, i)`.
+3. Keep non-zero face images and flatten them to vectors.
+4. Form a matrix of those vectors.
+5. Compare matrix rank to number of vectors.
+- Equal: reports independent.
+- Not equal: reports dependent.
+
+### Step 2: Constraint equivalence check
+For each tested `shape` and horn index `j` in `0..dimen(shape_tensor)`:
+1. Compute `expected_indices = compute_missing_indices_dask(shape, j)`.
+2. Enumerate all basis indices `m`.
+3. For every face index `i != j`, collect indices where `face(E_m, i)` is zero.
+4. Intersect those sets across all `i != j`.
+5. Compare the intersection with `expected_indices`.
+
+## Outputs
+The script prints:
+- section headers for both steps,
+- per-case counts and rank results in Step 1,
+- per-case combinatorial/constraint counts in Step 2,
+- pass/fail status per case,
+- final summary lines for each step.
+
+## Logging
+- No file logger is configured.
+- All reporting is written to standard output.
+
+## Run
+From repository root, either use editable install:
+
+```powershell
+.\.venv\Scripts\python.exe experiments\homotopy_constraint_verification_with_independence_test.py
+```
+
+Or run with explicit source path:
+
+```powershell
+$env:PYTHONPATH = 'src'
+.\.venv\Scripts\python.exe experiments\homotopy_constraint_verification_with_independence_test.py
+```

experiments/Gemini_hallicination.py

@@ -21,8 +21,8 @@
 # Let's check with our code. Gemini produced the following Python code to construct the hypermatrix.
 
 import numpy as np
-from .tensor_ops import n_hypergroupoid_conjecture, n_hypergroupoid_comparison, is_degen, bdry, horn
-from .tensor_ops import face, kan_condition, filler
+from simplicial_tensors.tensor_ops import n_hypergroupoid_conjecture, n_hypergroupoid_comparison, is_degen, bdry, horn
+from simplicial_tensors.tensor_ops import face, kan_condition, filler
 
 
 a = np.array([0, 1, 2])

experiments/fixed_index_face_independence.py

@@ -1,17 +1,8 @@
-import numpy as np
 import itertools
 
-# We will use the 'face' function from your tensor_ops.py file.
-# Ensure tensor_ops.py is in the same directory as this script.
-try:
-    from .tensor_ops import face
-except ImportError:
-    print("Error: Could not import 'face' from tensor_ops.py.")
-    print("Please ensure tensor_ops.py is in the same directory.")
-    # Define a dummy function to avoid crashing the script
-    def face(m, i):
-        print("DUMMY FACE FUNCTION: tensor_ops.py not found.")
-        return np.array([])
+import numpy as np
+
+from simplicial_tensors.tensor_ops import face
 
 def standard_basis_tensor(idx, shape):
     """
@@ -89,3 +80,4 @@ def main():
 if __name__ == '__main__':
     main()
 
+

experiments/homology_basis.py

@@ -1,6 +1,6 @@
 import numpy as np
 from itertools import product
-from .tensor_ops import range_tensor, is_degen, dimen
+from simplicial_tensors.tensor_ops import range_tensor, is_degen, dimen
 
 
 def standard_basis_tensor(idx, shape):

experiments/homotopy_constraint_verification.py

@@ -1,20 +1,9 @@
-import numpy as np
 import itertools
 
+import numpy as np
 
-# We will use functions from your existing scripts.
-# Ensure tensor_ops.py and horn_map_reduce.py are in the same directory.
-try:
-    from .tensor_ops import face
-    from .horn_map_reduce import compute_missing_indices_dask
-except ImportError as e:
-    print(f"Error: Could not import required functions. {e}")
-    print("Please ensure tensor_ops.py and horn_map_reduce.py are in the same directory.")
-    # Define dummy functions to avoid crashing the script
-    def face(m, i): return np.array([])
-    def dimen(t): return 0
-    def compute_missing_indices_dask(shape, horn_j): return set()
-
+from horn_map_reduce import compute_missing_indices_dask
+from simplicial_tensors.tensor_ops import face
 
 def standard_basis_tensor(idx, shape):
     """
@@ -102,10 +91,13 @@ def main():
 
     print("\n-------------------------------------------")
     if all_passed:
-        print("✅ All tested shapes passed the constraint verification.")
+        print("All tested shapes passed the constraint verification.")
     else:
-        print("❌ Some shapes failed the constraint verification.")
+        print("Some shapes failed the constraint verification.")
 
 if __name__ == '__main__':
     main()
 
+
+
+

experiments/homotopy_constraint_verification_with_independence_test.py

@@ -1,20 +1,9 @@
-import numpy as np
 import itertools
 
-# We will use functions from your existing scripts.
-# Ensure tensor_ops.py and horn_map_reduce.py are in the same directory.
-try:
-    from .tensor_ops import face, dimen
-    from .horn_map_reduce import compute_missing_indices_dask
-except ImportError as e:
-    print(f"Error: Could not import required functions. {e}")
-    print("Please ensure tensor_ops.py and horn_map_reduce.py are in the same directory.")
-    # Define dummy functions to avoid crashing the script
-    def face(m, i): return np.array([])
-    def dimen(t): return min(t.shape) - 1 if t.shape else -1
-    # CORRECTED DUMMY FUNCTION SIGNATURE:
-    def compute_missing_indices_dask(shape, horn_j): return set()
+import numpy as np
 
+from horn_map_reduce import compute_missing_indices_dask
+from simplicial_tensors.tensor_ops import dimen, face
 
 def standard_basis_tensor(idx, shape):
     """
@@ -132,9 +121,9 @@ def main():
 
     print("\n-------------------------------------------")
     if li_passed:
-        print("✅ Linear independence premise holds for all tested cases.")
+        print("Linear independence premise holds for all tested cases.")
     else:
-        print("❌ Linear independence premise FAILED for one or more cases.")
+        print("Linear independence premise FAILED for one or more cases.")
 
 
     print("\n\n======================================================")
@@ -151,10 +140,15 @@ def main():
 
     print("\n-------------------------------------------")
     if constraints_passed:
-        print("✅ All tested shapes passed the constraint verification.")
+        print("All tested shapes passed the constraint verification.")
     else:
-        print("❌ Some shapes failed the constraint verification.")
+        print("Some shapes failed the constraint verification.")
 
 if __name__ == '__main__':
     main()
 
+
+
+
+
+

experiments/n_cycle_conjugation.py

@@ -1,7 +1,7 @@
 # n_cycle_conjugation.py
 
 from sympy import simplify
-from .symbolic_tensor_ops import SymbolicTensor
+from simplicial_tensors.symbolic_tensor_ops import SymbolicTensor
 import numpy as np
 from collections import Counter
 

experiments/n_hypergroupoid_conjecture.py

@@ -22,7 +22,7 @@
 import numpy as np
 import random
 from typing import Tuple # , List, Union, Any
-from .tensor_ops import (n_hypergroupoid_conjecture, n_hypergroupoid_comparison, 
+from simplicial_tensors.tensor_ops import (n_hypergroupoid_conjecture, n_hypergroupoid_comparison, 
                         bdry, degen, is_degen, ___SEED___, random_tensor, order, dimen, face) 
 
 

experiments/normalized_moore_complex_homology.py

@@ -1,6 +1,6 @@
 import numpy as np
 from collections import deque
-from .tensor_ops import face, degen, bdry, is_degen, random_tensor
+from simplicial_tensors.tensor_ops import face, degen, bdry, is_degen, random_tensor
 from scipy.linalg import null_space
 
 # Generate a unique key for caching simplices