--- a
+++ b/examples/mitdb/extract.py
@@ -0,0 +1,62 @@
+from __future__ import print_function
+
+import cPickle as pickle
+import glob
+import numpy as np
+import os
+import subprocess
+
+WFDB = "/deep/group/med/tools/wfdb-10.5.24/build/bin/"
+DATA = "/deep/group/med/mitdb"
+
+def extract_wave(idx):
+    """
+    Reads .dat file and returns in numpy array. Assumes 2 channels.  The
+    returned array is n x 3 where n is the number of samples. The first column
+    is the sample number and the second two are the first and second channel
+    respectively.
+    """
+    rdsamp = os.path.join(WFDB, 'rdsamp')
+    output = subprocess.check_output([rdsamp, '-r', idx], cwd=DATA)
+    data = np.fromstring(output, dtype=np.int32, sep=' ')
+    return data.reshape((-1, 3))
+
+def extract_annotation(idx):
+    """
+    The annotation file column names are:
+        Time, Sample #, Type, Sub, Chan, Num, Aux
+    The Aux is optional, it could be left empty. Type is the beat type and Aux
+    is the transition label.
+    """
+    rdann = os.path.join(WFDB, 'rdann')
+    output = subprocess.check_output([rdann, '-r', idx, '-a', 'atr'], cwd=DATA)
+    labels = (line.split() for line in output.strip().split("\n"))
+    labels = [(l[0], int(l[1]), l[2], l[6] if len(l) == 7 else None)
+                for l in labels]
+    return labels
+
+def extract(idx):
+    """
+    Extracts data and annotations from .dat and .atr files.
+    Returns a numpy array for the data and a list of tuples for the labels.
+    """
+    data = extract_wave(idx)
+    labels = extract_annotation(idx)
+    return data, labels
+
+def save(example, idx):
+    """
+    Saves data with numpy.save (load with numpy.load) and pickles labels. The
+    files are saved in the same place as the raw data.
+    """
+    np.save(os.path.join(DATA, idx), example[0])
+    with open(os.path.join(DATA, "{}.pkl".format(idx)), 'w') as fid:
+        pickle.dump(example[1], fid)
+
+if __name__ == "__main__":
+    files = glob.glob(os.path.join(DATA, "*.dat"))
+    idxs = [os.path.basename(f).split(".")[0] for f in files]
+    for idx in idxs:
+        example = extract(idx)
+        save(example, idx)
+        print("Example {}".format(idx))