add PreprocessInterface

alphastats/DataSet.py

@@ -8,7 +8,7 @@
 
 
 from alphastats.DataSet_Plot import Plot
-from alphastats.DataSet_Preprocess import Preprocess
+from alphastats.DataSet_Preprocess import Preprocess, PreprocessInterface
 from alphastats.DataSet_Pathway import Enrichment
 from alphastats.DataSet_Statistics import Statistics
 from alphastats.utils import LoaderError
@@ -34,7 +34,7 @@
 plotly.io.templates.default = "simple_white+alphastats_colors"
 
 
-class DataSet(Statistics, Plot, Enrichment):
+class DataSet(PreprocessInterface, Statistics, Plot, Enrichment):
     """Analysis Object"""
 
     def __init__(self, loader, metadata_path=None, sample_column=None):
@@ -83,7 +83,18 @@ def __init__(self, loader, metadata_path=None, sample_column=None):
         print("DataSet has been created.")
         self.overview()
 
-    def preprocess(self, **kwargs):
+    def preprocess(
+        self,
+        log2_transform: bool = True,
+        remove_contaminations: bool = False,
+        subset: bool = False,
+        data_completeness: float = 0,
+        normalization: str = None,
+        imputation: str = None,
+        remove_samples: list = None,
+        **kwargs,
+    ):
+        """See documentation in the class implementing PreprocessInterface."""
         pp = Preprocess(
             self.filter_columns,
             self.rawinput,
@@ -94,7 +105,16 @@ def preprocess(self, **kwargs):
             self.mat,
         )
 
-        self.mat, self.metadata, self.preprocessing_info = pp.preprocess(**kwargs)
+        self.mat, self.metadata, self.preprocessing_info = pp.preprocess(
+            log2_transform,
+            remove_contaminations,
+            subset,
+            data_completeness,
+            normalization,
+            imputation,
+            remove_samples,
+            **kwargs,
+        )
         self.preprocessed = True
 
     def reset_preprocessing(self):

alphastats/DataSet_Preprocess.py

@@ -1,4 +1,5 @@
 import logging
+from abc import ABC, abstractmethod
 
 import numpy as np
 import pandas as pd
@@ -12,7 +13,23 @@
 from alphastats.utils import ignore_warning
 
 
-class Preprocess:
+class PreprocessInterface(ABC):
+    @abstractmethod
+    def preprocess(
+        self,
+        log2_transform: bool,
+        remove_contaminations: bool,
+        subset: bool,
+        data_completeness: float,
+        normalization: str,
+        imputation: str,
+        remove_samples: list,
+        **kwargs,
+    ):
+        pass
+
+
+class Preprocess(PreprocessInterface):
     imputation_methods = ["mean", "median", "knn", "randomforest"]
     normalization_methods = ["vst", "zscore", "quantile"]