Update match_reprtranscript_expressionlevel.py

scripts/match_reprtranscript_expressionlevel.py

-
 import pandas as pd
 import json
 import re
@@ -6,7 +5,7 @@ import representative as repr
 import os
 
 
-def dict_reprTrans_to_df(dict_reprTrans: dict):
+def dict_reprTrans_to_df(dict_reprTrans: dict[str,str])-> pd.Dataframe:
 
     """Convert a dictionary of genes and their representative transcript into a dataframe 
 
@@ -17,11 +16,18 @@ def dict_reprTrans_to_df(dict_reprTrans: dict):
             Pandas dataframe having Gene and transcript as columns
       
         Raises:
-            /!\ None, I wasn't able to make a TypeError with dict  
-            : Only dict made of key string and value string is allowed
+            Only dict are allowed
+            Key should be strings
+            Value should be strings
           
     """
     pass
+    if not type(dict_reprTrans) is dict :
+        raise TypeError("Only dict are allowed")
+    if type(list(dict_reprTrans.keys())[0]) is not str :
+        raise TypeError("Key should be strings")
+    if type(list(dict_reprTrans.values())[0]) is not str :
+        raise TypeError("Values should be strings")
 
     df_reprTrans = pd.DataFrame.from_dict(dict_reprTrans, orient="index", columns=["reprTranscript"])
     df_reprTrans = df_reprTrans.reset_index(level=0)
@@ -30,7 +36,7 @@ def dict_reprTrans_to_df(dict_reprTrans: dict):
     return df_reprTrans
 
 
-def txt_to_dict(dict_txt: str):
+def txt_to_dict(dict_txt: str) -> dict:
     """Convert a txt file into a dictionary 
 
         Args:
@@ -52,13 +58,14 @@ def txt_to_dict(dict_txt: str):
 
 
 
-def transcripts_by_gene_inDf(df_gtfSelection: str) -> pd.DataFrame:
+def transcripts_by_gene_inDf(df_gtfSelection: pd.DataFrame) -> pd.DataFrame:
     """Convert multiindex dataframe from function into a simple dataframe 
 
         Args:
-            df_gtfSelection (str): Pandas multiindex dataframe having Gene,
+            df_gtfSelection : Pandas multiindex dataframe having Gene,
             transcript as indexs and support level as columns. 
             Come from the function import_gtfSelection_to_df()
+            from representative.py script. 
 
         Returns:
             df_gene (str): Pandas dataframe having Gene and
@@ -75,7 +82,7 @@ def transcripts_by_gene_inDf(df_gtfSelection: str) -> pd.DataFrame:
     return df_gene
 
 
-def tsv_or_csv_to_df(input_txt:str) :
+def tsv_or_csv_to_df(input_txt:str) -> pd.DataFrame :
     """Convert tsv or csv file into a pandas dataframe
 
         Args:
@@ -95,12 +102,15 @@ def tsv_or_csv_to_df(input_txt:str) :
     return df_input
 
 
-def exprLevel_byGene(df_exprTrasncript:str, df_output_gtf_selection:str) -> pd.DataFrame :
-    """Find matching transcripts bewteen the 2 args 
+def exprLevel_byGene(df_exprTrasncript:pd.DataFrame, df_output_gtf_selection:pd.DataFrame) -> pd.DataFrame :
+    """find the gene of each transcipt given by the expression level csv/tsv file,
+       and summ expression level of all transcipts from the same gene. 
 
         Args:
-            df_exprTranscript (str): pandas Dataframe containing transcript and their expression level
-            df_output_gtf_selection (str) : pandas Dataframe containing genes and transcripts 
+            df_exprTranscript : pandas Dataframe containing transcript and their expression level,
+            generated by "tsv_or_csv_to_df" function
+            df_output_gtf_selection : pandas Dataframe containing genes and transcripts,
+            generated by "transcripts_by_gene_inDf" function 
 
         Returns:
             Pandas dataframe having gene and sum of its transcript expression level
@@ -113,14 +123,16 @@ def exprLevel_byGene(df_exprTrasncript:str, df_output_gtf_selection:str) -> pd.D
     df_sum = df_merged.groupby("Gene").sum("Expression_level") # sum transcripts comming from the same gene  
     return df_sum
 
-def match_byGene(df_reprTranscript:str, df_expressionLevel_byGene:str) -> pd.DataFrame: 
+def match_byGene(df_reprTranscript: pd.DataFrame, df_expressionLevel_byGene:pd.DataFrame) -> pd.DataFrame: 
     """Find matching genes bewteen the 2 args 
 
         Args:
-            df_reprTranscript (str): pandas Dataframe containing genes 
-            and their representative transcript
-            df_expressionLevel_byGene (str) : pandas Dataframe containing 
-            genes and their expression level 
+            df_reprTranscript : pandas Dataframe containing genes 
+            and their representative transcript, generated by
+            "dict_reprTrans_to_df()" 
+            df_expressionLevel_byGene : pandas Dataframe containing 
+            genes and their expression level generated by 
+            "transcript_by_gene_inDf()"
 
         Returns:
             Pandas dataframe having representative trasncripts 
@@ -135,7 +147,7 @@ def match_byGene(df_reprTranscript:str, df_expressionLevel_byGene:str) -> pd.Dat
     df_clean = df_clean.loc[:, ["reprTrans","Expression_level"]]
     return df_clean
 
-def output_tsv(dataframe:str)-> pd.DataFrame :
+def output_tsv(dataframe: pd.DataFrame)-> pd.DataFrame :
     """Convert pandas dataframe into a tsv file 
 
         Args:
@@ -195,6 +207,6 @@ def match_reprTranscript_expressionLevel(exprTrans:str, dict_reprTrans:dict, int
 #match_final = match_reprTranscript_expressionLevel(input_expr, dict_reprTrans, input_intermediate_file)
 #print("this is the function :\n\n {}".format(match_final))
 
-#if __name__ == "__main__":  
-#    match_reprTranscript_expressionLevel()
+if __name__ == "__main__":  
+    match_reprTranscript_expressionLevel()