diff --git a/statistiline_filter.py b/statistical_filter.py
similarity index 96%
rename from statistiline_filter.py
rename to statistical_filter.py
index a68cbd7..569050c 100644
--- a/statistiline_filter.py
+++ b/statistical_filter.py
@@ -1,84 +1,84 @@
-import h5py
-import os
-import pandas as pd
-
-h5_file = 'ltcc_current.h5'
-
-sobiv_eid_list = []
-ttx_eid_list = []
-teised_eid_list = []
-
-with h5py.File(h5_file, 'r') as h5_file:
-
-    for eid in h5_file.keys():
-        if 'tag' in h5_file[eid].attrs:
-            tag_val = h5_file[eid].attrs['tag']
-
-            if isinstance(tag_val, bytes):
-                tag_val = tag_val.decode('utf-8')
-
-        puhas_eid = eid.replace(" ", "_").replace(":", "-")
-        fit_result_eid = "fit_results_" + puhas_eid
-
-        if tag_val == 'iso':
-            sobiv_eid_list.append(fit_result_eid)
-        elif tag_val == 'ttx':
-            ttx_eid_list.append(fit_result_eid)
-        else:
-            teised_eid_list.append(fit_result_eid)
-
-file = 'ltcc_current.h5'
-
-with h5py.File(file, 'r') as h5_file:
-    for eid in h5_file.keys():
-        puhastatud_eid = eid.replace(" ", "_").replace(":", "-")
-
-        atribuudid = h5_file[eid].attrs
-        sex = atribuudid.get('sex')
-        spid = atribuudid.get('spid')
-
-        csv_file_name = f"fit_results_{puhastatud_eid}.csv"
-
-        if os.path.exists(csv_file_name):
-            df = pd.read_csv(csv_file_name)
-
-            df['sex'] = sex
-            df['spid'] = spid.replace("Mouse AGAT", "")
-            df['eid'] = eid
-            df.to_csv(csv_file_name, index=False)
-
-for fail in os.listdir():
-    if fail.endswith('.csv'):
-
-        eksperiment_id = fail.replace(".csv", "")
-
-        if eksperiment_id in sobiv_eid_list:
-
-            df = pd.read_csv(fail)
-            df['tag'] = 'iso'
-            df.to_csv(fail, index=False)
-
-        elif eksperiment_id in ttx_eid_list:
-
-            df = pd.read_csv(fail)
-            df['tag'] = 'ttx'
-            df.to_csv(fail, index=False)
-
-        else:
-
-            df = pd.read_csv(fail)
-            df['tag'] = 'teised'
-            df.to_csv(fail, index=False)
-
-comb_df = pd.DataFrame()
-
-for filename in os.listdir():
-
-    if filename.endswith('.csv'):
-        df = pd.read_csv(filename)
-
-        if 'tag' in df.columns and df['tag'].isin(['iso', 'ttx']).all():
-
-            comb_df = pd.concat([comb_df, df], ignore_index=True)
-
-print(comb_df)
+import h5py
+import os
+import pandas as pd
+
+h5_file = 'ltcc_current.h5'
+
+sobiv_eid_list = []
+ttx_eid_list = []
+teised_eid_list = []
+
+with h5py.File(h5_file, 'r') as h5_file:
+
+    for eid in h5_file.keys():
+        if 'tag' in h5_file[eid].attrs:
+            tag_val = h5_file[eid].attrs['tag']
+
+            if isinstance(tag_val, bytes):
+                tag_val = tag_val.decode('utf-8')
+
+        puhas_eid = eid.replace(" ", "_").replace(":", "-")
+        fit_result_eid = "fit_results_" + puhas_eid
+
+        if tag_val == 'iso':
+            sobiv_eid_list.append(fit_result_eid)
+        elif tag_val == 'ttx':
+            ttx_eid_list.append(fit_result_eid)
+        else:
+            teised_eid_list.append(fit_result_eid)
+
+file = 'ltcc_current.h5'
+
+with h5py.File(file, 'r') as h5_file:
+    for eid in h5_file.keys():
+        puhastatud_eid = eid.replace(" ", "_").replace(":", "-")
+
+        atribuudid = h5_file[eid].attrs
+        sex = atribuudid.get('sex')
+        spid = atribuudid.get('spid')
+
+        csv_file_name = f"fit_results_{puhastatud_eid}.csv"
+
+        if os.path.exists(csv_file_name):
+            df = pd.read_csv(csv_file_name)
+
+            df['sex'] = sex
+            df['spid'] = spid.replace("Mouse AGAT", "")
+            df['eid'] = eid
+            df.to_csv(csv_file_name, index=False)
+
+for fail in os.listdir():
+    if fail.endswith('.csv'):
+
+        eksperiment_id = fail.replace(".csv", "")
+
+        if eksperiment_id in sobiv_eid_list:
+
+            df = pd.read_csv(fail)
+            df['tag'] = 'iso'
+            df.to_csv(fail, index=False)
+
+        elif eksperiment_id in ttx_eid_list:
+
+            df = pd.read_csv(fail)
+            df['tag'] = 'ttx'
+            df.to_csv(fail, index=False)
+
+        else:
+
+            df = pd.read_csv(fail)
+            df['tag'] = 'teised'
+            df.to_csv(fail, index=False)
+
+comb_df = pd.DataFrame()
+
+for filename in os.listdir():
+
+    if filename.endswith('.csv'):
+        df = pd.read_csv(filename)
+
+        if 'tag' in df.columns and df['tag'].isin(['iso', 'ttx']).all():
+
+            comb_df = pd.concat([comb_df, df], ignore_index=True)
+
+print(comb_df)