Refactor (#70)

* Refactor

* Fix tests

Author: alex98247

README.md

@@ -24,21 +24,23 @@ You're all set! You can now import and use the statistical tests in your Python
 
 ## PySATL Criterion module usage example:
 
+Statistic calculation example:
 ```python
 # import needed criterion from pysatl_criterion
-from pysatl_criterion import KolmogorovSmirnovNormalityGofStatistic
+from pysatl_criterion.statistics import KolmogorovSmirnovNormalityGofStatistic
+
 
 # make a criterion object
-criterion = KolmogorovSmirnovNormalityGofStatistic(mean=0, var=1)
+statistic = KolmogorovSmirnovNormalityGofStatistic(mean=0, var=1)
 
 # initialize test data
 x = [0.1, 0.7, 0.5, 0.3]
 
 # then run algorithm
-statistic = criterion.execute_statistic(x)
+result = statistic.execute_statistic(x)
 
 # print the results
-print(f"Statistic result: {statistic}")
+print(f"Statistic result: {result}")
 # output:
 # Statistic result: 0.539827837277029
 ```

pyproject.toml

@@ -13,7 +13,8 @@ dependencies = [
     "scipy>=1.11.2",
     "pandas>=2.2.1",
     "typing-extensions>=4.12.2",
-    "networkx ==3.4.2"
+    "networkx == 3.4.2",
+    "sqlalchemy == 2.0.41"
 ]
 
 [project.urls]
@@ -48,7 +49,6 @@ ruff = "0.7.4"
 pytest-mock = "3.14.0"
 pre-commit = "4.0.1"
 mypy = "1.15.0"
-sqlalchemy = "2.0.41"
 
 [tool.isort]
 line_length = 100

pysatl_criterion/constants.py

@@ -0,0 +1,2 @@
+LOCAL_LIMIT_DISTRIBUTION_URL = "sqlite:///limit_distributions.sqlite"
+REMOTE_LIMIT_DISTRIBUTION_URL = "postgresql://postgres:postgres@localhost/pysatl"

…satl_criterion/cv_calculator/__init__.py …atl_criterion/critical_value/__init__.pypysatl_criterion/cv_calculator/__init__.py renamed to pysatl_criterion/critical_value/__init__.py pysatl_criterion/cv_calculator/__init__.py renamed to pysatl_criterion/critical_value/__init__.py

@@ -0,0 +1,38 @@
+from dataclasses import dataclass
+
+from pysatl_criterion.critical_value.critical_area.model import CriticalArea
+
+
+@dataclass
+class LeftCriticalArea(CriticalArea):
+    critical_value: float
+
+    def __init__(self, critical_value: float):
+        self.critical_value = critical_value
+
+    def contains(self, value: float) -> bool:
+        return value >= self.critical_value
+
+
+@dataclass
+class RightCriticalArea(CriticalArea):
+    critical_value: float
+
+    def __init__(self, critical_value: float):
+        self.critical_value = critical_value
+
+    def contains(self, value: float) -> bool:
+        return value <= self.critical_value
+
+
+@dataclass
+class TwoSidedCriticalArea(CriticalArea):
+    left_cv: float
+    right_cv: float
+
+    def __init__(self, left_cv: float, right_cv: float):
+        self.left_cv = left_cv
+        self.right_cv = right_cv
+
+    def contains(self, value: float) -> bool:
+        return self.left_cv <= value <= self.right_cv

…criterion/p_value_calculator/__init__.py …critical_value/critical_area/__init__.pypysatl_criterion/p_value_calculator/__init__.py renamed to pysatl_criterion/critical_value/critical_area/__init__.py pysatl_criterion/p_value_calculator/__init__.py renamed to pysatl_criterion/critical_value/critical_area/__init__.py

@@ -0,0 +1,11 @@
+from abc import ABC, abstractmethod
+
+
+class CriticalArea(ABC):
+    @abstractmethod
+    def contains(self, value: float) -> bool:
+        """
+        Check critical area contains value.
+        :param value: true, if critical area contains value, false otherwise
+        """
+        pass

pysatl_criterion/critical_value/critical_area/critical_areas.py

@@ -0,0 +1,35 @@
+import logging
+
+from pysatl_criterion.persistence.model.limit_distribution.limit_distribution import (
+    CriticalValueQuery,
+    ILimitDistributionStorage,
+)
+
+
+class CriticalValueLoader:
+    def __init__(
+        self, local_storage: ILimitDistributionStorage, remote_storage: ILimitDistributionStorage
+    ):
+        self.__local_storage = local_storage
+        self.__remote_storage = remote_storage
+
+    def load(self, criterion_code: str, sample_size: int, sample_size_error: int = 0):
+        """
+        Load data from remote distribution storage to local distribution storage.
+
+        :param criterion_code: criterion code
+        :param sample_size: sample size
+        :param sample_size_error: sample size error.
+        Get sample_size - sample_size_error <= sample_size <= sample_size + sample_size_error
+        """
+
+        logging.info(f"Load criterion {criterion_code} with size {sample_size} from remote")
+        query = CriticalValueQuery(criterion_code, sample_size, sample_size_error)
+        remote_data = self.__remote_storage.get_data_for_cv(query)
+
+        if remote_data is not None:
+            self.__local_storage.insert_data(remote_data)
+        else:
+            logging.warning(
+                f"Remote data for criterion {criterion_code} " f"with size {sample_size} not found"
+            )