Merge pull request #12 from AutoResearch/feat-make-compatible-with-state

feat: make compatible with state and work with pd.DataFrames

src/autora/experimentalist/nearest_value/__init__.py

@@ -1,21 +1,22 @@
-from typing import Iterable, Sequence, Union
+from typing import Iterable, Union
 
 import numpy as np
+import pandas as pd
 
 from autora.utils.deprecation import deprecated_alias
 
 
 def sample(
-    samples: Union[Iterable, Sequence],
+    conditions: Union[pd.DataFrame, np.ndarray],
     allowed_values: np.ndarray,
     num_samples: int,
 ):
     """
-    A sampler which returns the nearest values between the input samples and the allowed values,
-    without replacement.
+    A experimentalist which returns the nearest values between the input samples and the allowed
+    values, without replacement.
 
     Args:
-        samples: input conditions
+        conditions: input conditions
         allowed_values: allowed conditions to sample from
         num_samples: number of samples
 
@@ -30,27 +31,20 @@ def sample(
     if len(allowed_values.shape) == 1:
         allowed_values = allowed_values.reshape(-1, 1)
 
-    if isinstance(samples, Iterable):
-        samples = np.array(list(samples))
-
     if allowed_values.shape[0] < num_samples:
         raise Exception(
             "More samples requested than samples available in the set allowed of values."
         )
 
-    if isinstance(samples, Iterable) or isinstance(samples, Sequence):
-        samples = np.array(list(samples))
+    X = np.array(conditions)
 
-    if hasattr(samples, "shape"):
-        if samples.shape[0] < num_samples:
-            raise Exception(
-                "More samples requested than samples available in the pool."
-            )
+    if X.shape[0] < num_samples:
+        raise Exception("More samples requested than samples available in the pool.")
 
     x_new = np.empty((num_samples, allowed_values.shape[1]))
 
     # get index of row in x that is closest to each sample
-    for row, sample in enumerate(samples):
+    for row, sample in enumerate(X):
 
         if row >= num_samples:
             break
@@ -60,6 +54,9 @@ def sample(
         x_new[row, :] = allowed_values[idx, :]
         allowed_values = np.delete(allowed_values, idx, axis=0)
 
+    if isinstance(conditions, pd.DataFrame):
+        x_new = pd.DataFrame(x_new, columns=conditions.columns)
+
     return x_new