Fix mSPRT

frouros/callbacks/streaming/msprt.py

@@ -97,18 +97,14 @@ def tau(self, value: Optional[float]) -> None:
             raise TypeError("tau must be a float or None")
         self._tau = value
 
-    def on_fit_end(self, **kwargs) -> None:
-        """On fit end method."""
-        self.incremental_mean.num_values = len(kwargs["X"])
-
     def on_update_end(self, value: Union[int, float], **kwargs) -> None:
         """On update end method.
 
         :param value: value to update detector
         :type value: int
         """
         self.incremental_mean.update(value=value)
-        self.p_value, likelihood = self._calculate_p_value(value=value)
+        self.p_value, likelihood = self._calculate_p_value()
 
         self.logs.update(
             {
@@ -134,14 +130,13 @@ def _calculate_tau_squared(
         tau_squared = sigma_squared * minus_b_cdf / (1 / b * norm.pdf(b) - minus_b_cdf)
         return tau_squared
 
-    def _calculate_p_value(self, value: float) -> Tuple[float, float]:
+    def _calculate_p_value(self) -> Tuple[float, float]:
         likelihood = self._likelihood_normal_mixing_distribution(
             mean=self.incremental_mean.get(),
             sigma=self.sigma,
             sigma_squared=self.sigma_squared,
             tau_squared=self.tau_squared,
             two_sigma_squared=self.two_sigma_squared,
-            value=value,
             n=self.detector.num_instances,  # type: ignore
         )
         p_value = min(
@@ -157,15 +152,14 @@ def _likelihood_normal_mixing_distribution(
         sigma_squared: float,
         tau_squared: float,
         two_sigma_squared: float,
-        value: float,
         n: int,
     ) -> float:
         n_tau_squared = n * tau_squared
         sigma_squared_plus_n_tau_squared = sigma_squared + n_tau_squared
         likelihood = (sigma / np.sqrt(sigma_squared_plus_n_tau_squared)) * np.exp(
             n
             * n_tau_squared
-            * (mean - value) ** 2
-            / (two_sigma_squared * (sigma_squared_plus_n_tau_squared))
+            * mean**2  # (mean - theta) ** 2, theta = 0 (H_0 value, no distance)
+            / (two_sigma_squared * sigma_squared_plus_n_tau_squared)
         )
         return likelihood

frouros/tests/integration/test_callback.py

@@ -242,7 +242,7 @@ def test_streaming_warning_samples_buffer_on_concept_drift(
     " expected_p_value,"
     " expected_likelihood",
     [
-        (MMDStreaming, 40, 0.08821576, 0.00494882, 202.06836342),
+        (MMDStreaming, 31, 0.34147982, 0.0487643, 20.50680424),
     ],
 )
 def test_streaming_msprt_multivariate_different_distribution(

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "frouros"
-version = "0.2.5"
+version = "0.2.6"
 description = "A Python library for drift detection in Machine Learning problems"
 authors = [
     {name = "Jaime Céspedes Sisniega", email = "cespedes@ifca.unican.es"}