fig bug with nans (#136)

Author: aloctavodia

pymc_bart/__init__.py

@@ -25,7 +25,7 @@
 )
 
 __all__ = ["BART", "PGBART"]
-__version__ = "0.5.6"
+__version__ = "0.5.7"
 
 
 pm.STEP_METHODS = list(pm.STEP_METHODS) + [PGBART]

pymc_bart/pgbart.py

@@ -157,7 +157,7 @@ def __init__(
 
         for idx, rule in enumerate(self.split_rules):
             if rule is ContinuousSplitRule:
-                self.X[:, idx] = jitter_duplicated(self.X[:, idx], np.std(self.X[:, idx]))
+                self.X[:, idx] = jitter_duplicated(self.X[:, idx], np.nanstd(self.X[:, idx]))
 
         init_mean = self.bart.Y.mean()
         self.num_observations = self.X.shape[0]
@@ -700,7 +700,7 @@ def jitter_duplicated(array: npt.NDArray[np.float_], std: float) -> npt.NDArray[
     if are_whole_number(array):
         seen = []
         for idx, num in enumerate(array):
-            if num in seen:
+            if num in seen and not np.isnan(num):
                 array[idx] = num + np.random.normal(0, std / 12)
             else:
                 seen.append(num)
@@ -711,8 +711,7 @@ def jitter_duplicated(array: npt.NDArray[np.float_], std: float) -> npt.NDArray[
 @njit
 def are_whole_number(array: npt.NDArray[np.float_]) -> np.bool_:
     """Check if all values in array are whole numbers"""
-    new_array = np.mod(array, 1)
-    return np.all(new_array == 0)
+    return np.all(np.mod(array[~np.isnan(array)], 1) == 0)
 
 
 def logp(point, out_vars, vars, shared):  # pylint: disable=redefined-builtin