Add Activity Recognizer for Python and own gitignore

code/lukas/ActivityRecognition_Python/DataReader.py

@@ -0,0 +1,63 @@
+import numpy as np
+import pandas as pd
+
+
+data_paths = ["Data/WalkingStairs", "Data/Standing",
+              "Data/Walking", "Data/Fahrstuhl"]
+
+
+def read_data_files(path):
+    accelerometer = pd.read_csv(
+        path + "/Accelerometer.csv", sep=";", skiprows=1, header=0, names=["t", "ax", "ay", "az"])
+
+    barometer = pd.read_csv(path + "/Barometer.csv", sep=";",
+                            skiprows=1, header=0, names=["t", "bx", "by", "bz"])
+
+    events = pd.read_csv(path + "/Events.txt", sep=";",
+                         skiprows=0, header=None, names=["t", "event"])
+
+    data = pd.merge(accelerometer, barometer, on="t", how="outer")
+    data = pd.merge(data, events, on="t", how="outer")
+    data = data.sort_values('t')
+
+    # Fill all nan values in event with the last known event
+    data['event'] = data['event'].fillna(method='pad')
+
+    # Add additional magnitude column
+    data['magnitude'] = np.sqrt(data['ax']**2 + data['ay']**2 + data['az']**2)
+
+    return data
+
+
+def increment_timestamps(data_frames):
+    """
+    data_frames: list
+    """
+    max_t = 0
+    for frame in data_frames:
+        frame['t'] += max_t
+        max_t = frame['t'].iloc[-1]
+
+    return data_frames
+
+
+def merge_data_frames(data_frames):
+    df = pd.DataFrame()
+
+    for frame in data_frames:
+        df = df.append(frame, ignore_index=True)
+
+    return df
+
+
+def load_all_data():
+    print("Loading data files...")
+    d = []
+    for path in data_paths:
+        data = read_data_files(path)
+        d.append(data)
+
+    d = increment_timestamps(d)
+    data = merge_data_frames(d)
+
+    return data