[analyzer] Add experimental data utilities and 1D CANN bump fitting (#19)

* Add experimental data utilities and 1D CANN bump fitting

Introduces universal data loading utilities in _datasets.py, experimental data processing in analyzer/experimental_data, and 1D CANN bump fitting and animation in CANN1D.py. Updates __init__.py files to expose new modules and functions for streamlined access to datasets and analysis tools.

Co-Authored-By: Airs702 <116141471+Airs702@users.noreply.github.com>

* Update main block in CANN1D.py for bump fitting

Uncommented and updated the main execution block to load ROI data and perform bump fitting with specified parameters. Also refactored the animation creation call for clarity. Fixed boolean value in pyproject.toml for dynamic versioning configuration.

* Add CANN1D bump analysis example and refactor analyzer

Introduces examples/cann1d_bump_analysis.py to demonstrate bump fitting and animation. Refactors and improves code in analyzer and experimental_data modules for clarity, typing, and robustness. Fixes import paths, updates __init__.py files, and enhances dataset utility functions. Minor formatting and logic improvements throughout for consistency and maintainability.

---------

Co-authored-by: Airs702 <116141471+Airs702@users.noreply.github.com>

Author: Routhleck

examples/cann1d_bump_analysis.py

@@ -0,0 +1,67 @@
+#!/usr/bin/env python3
+"""
+CANN 1D Bump Analysis Example
+
+This example demonstrates how to use the bump_fits and create_1d_bump_animation functions
+from the experimental data analyzer to analyze 1D CANN bumps.
+"""
+
+import numpy as np
+from canns.analyzer.experimental_data import bump_fits, create_1d_bump_animation
+
+
+def main():
+    """Demonstrate bump analysis and animation creation."""
+    # Generate sample data for demonstration
+    # In practice, you would load your experimental data
+    np.random.seed(42)
+    n_steps = 1000
+    n_roi = 16
+    
+    # Simulate some bump-like activity data
+    data = np.random.rand(n_steps, n_roi) * 0.1
+    
+    # Add some bump-like patterns
+    for i in range(n_steps):
+        center = (i * 0.01) % n_roi
+        for j in range(n_roi):
+            distance = min(abs(j - center), n_roi - abs(j - center))
+            data[i, j] += 0.5 * np.exp(-distance**2 / 2.0)
+    
+    print("Running bump fitting analysis...")
+    
+    # Run bump fitting analysis
+    bumps, fits, nbump, centrbump = bump_fits(
+        data,
+        n_steps=n_steps,
+        n_roi=n_roi,
+        n_bump_max=2,
+        sigma_diff=0.5,
+        ampli_min=2.0,
+        random_seed=42
+    )
+    
+    print(f"Analysis complete!")
+    print(f"Found {len(fits)} time steps with bump data")
+    print(f"Average number of bumps: {np.mean(nbump):.2f}")
+    
+    # Create animation of the bump evolution
+    print("Creating bump animation...")
+    
+    create_1d_bump_animation(
+        fits,
+        show=False,
+        save_path="examples/bump_analysis_demo.gif",
+        max_height_value=0.8,
+        nframes=min(100, len(fits)),
+        fps=10,
+        title="1D CANN Bump Analysis Demo"
+    )
+    
+    print("Animation saved as 'examples/bump_analysis_demo.gif'")
+    
+    return bumps, fits, nbump, centrbump
+
+
+if __name__ == "__main__":
+    results = main()

pyproject.toml

@@ -103,7 +103,7 @@ source = "uv-dynamic-versioning"
 [tool.uv-dynamic-versioning]
 vcs = "git"
 style = "pep440"
-bump = "true"
+bump = true
 
 [tool.hatch.build.targets.wheel]
 # The source location for the package.

src/canns/__init__.py

@@ -1,3 +1,4 @@
+from . import _datasets as _datasets
 from . import analyzer as analyzer
 from . import misc as misc
 from . import models as models
@@ -14,7 +15,8 @@
 
 __all__ = [
     "analyzer",
-    "misc", 
+    "_datasets",
+    "misc",
     "models",
     "pipeline",
     "trainer",