Exploratory ananlysis

.gitignore

@@ -127,3 +127,5 @@ dmypy.json
 
 # Pyre type checker
 .pyre/
+.ipynb_checkpoints 
+

exploratory_analysis.py

@@ -0,0 +1,69 @@
+import os
+import wfdb
+import numpy as np
+import pandas as pd
+import neurokit2 as nk
+from pathlib import Path
+from collections import Counter
+import itertools
+
+def categorize_records(folder_path):
+    """ 
+    Categorize record files with their labels.
+
+    Parameters:
+    - folder_path (str): The path to the folder containing WFDB records.
+
+    Returns:
+    - records_category (dict): A dictionary mapping file names to their corresponding labels.
+    """
+    labels = []
+    file_names = []
+    files = os.listdir(folder_path)
+    files = [f[:-4] for f in files if f.endswith(".hea")]
+
+    for file in files:        
+        file_names.append(file)
+        try:
+            label = wfdb.rdrecord(os.path.join(folder_path, file)).comments
+            labels.append(label)
+        except Exception as e:
+            print(f"Error processing {file}: {e}")
+
+    records_category = dict(zip(file_names, labels))
+    return records_category
+
+def get_duration(folder_path):
+    """
+    Calculate the duration of each record in the specified folder_path.
+
+    Parameters:
+    - folder_path (str): The path to the folder containing WFDB records.
+
+    Returns:
+    - duration_list (list): A list of durations corresponding to each record.
+    """
+    duration_list=[]
+    files=os.listdir(folder_path)
+    files=[f[:-4] for f in files if f.endswith(".hea")]
+
+    for file in files:
+        record_path=os.path.join(folder_path,file)
+        try:
+            record_data=wfdb.rdsamp(record_path)
+            sample_point=record_data[0][0]
+            sampling_frequency=record_data[1]['fs']
+            duration=sample_point/sampling_frequency
+            duration_list.append(duration)
+        except Exception as e:
+            print(f'Error processing {record_path}:{e}')
+    return duration_list
+
+test_categorize_records=categorize_records("D:/RA/Project/Database/CPSC2021/Training_set_II")
+print(len(test_categorize_records))
+
+Counter(itertools.chain.from_iterable(test_categorize_records.values()))
+
+print(test_categorize_records)
+get_duration("D:/RA/Project/Database/CPSC2021/Training_set_II")
+get_duration("D:/RA/Project/Database/CPSC2021/Training_set_I")

requirements.txt

@@ -1,7 +1,10 @@
-numpy==1.16.2
-scipy==1.2.1
-wfdb==2.2.1
-matplotlib==3.0.3
-pandas==0.24.2
-peakutils==1.3.3
-scikit_learn==0.24.1
+numpy
+scipy
+wfdb
+matplotlib
+pandas
+peakutils
+scikit_learn
+neurokit2
+tensorflow
+