fix: update MCMC and DE tutorials for v1.0.0 API - lambda closures, parameter renames, tuple unpacking

python/optimizr/core.py

@@ -47,13 +47,13 @@ except ImportError:
 
 
 def mcmc_sample(
-    log_likelihood_fn: Callable[[List[float], List[float]], float],
-    data: np.ndarray,
+    log_likelihood_fn: Callable[[List[float]], float],  # Updated: closure captures data
     initial_params: np.ndarray,
     param_bounds: List[Tuple[float, float]],
     n_samples: int = 10000,
     burn_in: int = 1000,
     proposal_std: float = 0.1,
+    data: Optional[np.ndarray] = None,  # Deprecated: use closure instead
 ) -> np.ndarray:
     """
     MCMC Metropolis-Hastings sampler.
@@ -65,9 +65,10 @@ def mcmc_sample(
     ----------
     log_likelihood_fn : callable
         Function that computes log P(data | params). Should accept
-        (params: list, data: list) and return float.
-    data : np.ndarray
-        Observed data (passed to log_likelihood_fn)
+        (params: list) and return float. Data should be captured in closure.
+    data : np.ndarray, optional (deprecated)
+        This parameter is deprecated and ignored. Capture data in the
+        log_likelihood_fn closure instead.
     initial_params : np.ndarray
         Starting parameter values
     param_bounds : list of (float, float)
@@ -103,17 +104,16 @@ def mcmc_sample(
     """
     if RUST_AVAILABLE:
         # Convert to lists if numpy arrays
-        data_list = data.tolist() if hasattr(data, 'tolist') else list(data)
+        # Note: data is now captured in log_likelihood_fn closure
         params_list = initial_params.tolist() if hasattr(initial_params, 'tolist') else list(initial_params)
         
+        # Rust function uses different parameter names
         samples = _rust_mcmc_sample(
             log_likelihood_fn=log_likelihood_fn,
-            data=data_list,
-            initial_params=params_list,
-            param_bounds=param_bounds,
+            initial_state=params_list,  # Rust expects 'initial_state'
             n_samples=n_samples,
+            step_size=proposal_std,  # Rust expects 'step_size'
             burn_in=burn_in,
-            proposal_std=proposal_std,
         )
         return np.array(samples)
     else: