A few more tests

py-forust/forust/__init__.py

@@ -433,14 +433,7 @@ def fit(
 
         if sample_weight is None:
             sample_weight = np.ones(y_.shape, dtype="float64")
-        sample_weight_ = (
-            sample_weight.to_numpy()
-            if isinstance(sample_weight, pd.Series)
-            else sample_weight
-        )
-
-        if not np.issubdtype(sample_weight_.dtype, "float64"):
-            sample_weight_ = sample_weight_.astype("float64", copy=False)
+        sample_weight_ = _convert_input_array(sample_weight)
 
         # Convert the monotone constraints into the form needed
         # by the rust code.

py-forust/forust/serialize.py

@@ -13,27 +13,13 @@
 
 
 class BaseSerializer(ABC, Generic[T]):
-    def __call__(self, obj: Union[T, str]) -> Union[T, str]:
-        """Serializer is callable, if it's a string we are deserializing, anything else we are serializing. For the string serializer, this works as well, because both serialize and deserialize just return itself.
-
-        Args:
-            obj (T | str): Object either to serialize, or deserialize.
-
-        Returns:
-            T | str: Object that is either serialized or deserialized.
-        """
-        if isinstance(obj, str):
-            return self.deserialize(obj)
-        else:
-            return self.serialize(obj)
-
     @abstractmethod
     def serialize(self, obj: T) -> str:
-        ...
+        """serialize method - should take an object and return a string"""
 
     @abstractmethod
     def deserialize(self, obj_repr: str) -> T:
-        ...
+        """deserialize method - should take a string and return original object"""
 
 
 Scaler = Union[int, float, str]
@@ -80,4 +66,8 @@ def serialize(self, obj: npt.NDArray) -> str:
 
     def deserialize(self, obj_repr: str) -> npt.NDArray:
         data = NumpyData(**json.loads(obj_repr))
-        return np.array(data.array, dtype=data.dtype, shape=data.shape)  # type: ignore
+        a = np.array(data.array, dtype=data.dtype)  # type: ignore
+        if len(data.shape) == 1:
+            return a
+        else:
+            return a.reshape(data.shape)

py-forust/tests/test_serailze.py

@@ -1,8 +1,15 @@
 from __future__ import annotations
 
+import numpy as np
 import pytest
 
-from forust.serialize import ObjectItem, ObjectSerializer, Scaler, ScalerSerializer
+from forust.serialize import (
+    NumpySerializer,
+    ObjectItem,
+    ObjectSerializer,
+    Scaler,
+    ScalerSerializer,
+)
 
 scaler_values = [
     1,
@@ -36,3 +43,18 @@ def test_object(value: ObjectItem):
     r = serializer.serialize(value)
     assert isinstance(r, str)
     assert value == serializer.deserialize(r)
+
+
+numpy_values = [
+    np.array([1.0, 2.23]),
+    np.array([1, 2, 3, 4, 5, 6]).reshape((2, 3)),
+    np.array([1, 2, 3, 4, 5, 6], dtype="int").reshape((2, 3)),
+]
+
+
+@pytest.mark.parametrize("value", numpy_values)
+def test_numpy(value: np.ndarray):
+    serializer = NumpySerializer()
+    r = serializer.serialize(value)
+    assert isinstance(r, str)
+    assert np.array_equal(value, serializer.deserialize(r))