create_timeseries_windows.py

acts = ["jogging","standing","downstairs","upstairs","walkfast","walkmod","walkslow","lying","sitting"]
def create_windows(subjects): 
  length = 100
  stride = 50
  sample = 10
  framelist = []
  targetlist = [] 
  global acts
  for act in acts:
    for f in glob.glob(subjects + act):
      d = pd.read_csv(f, header = None)
      
      ns = len(d) // length
      ns *= length
      for i in range(0, ns - length, stride):
        snap = d.iloc[i : i + length,:]
        snap = snap.iloc[::sample,:] ;
        framelist.append(snap)
        targetlist.append(act) 
  X = np.stack(framelist)
  Y = np.array(targetlist)
  Y = pd.Series(Y)
  Y = Y.astype("category")
  Y = Y.cat.codes 
  #for i, j in zip(np.arange(9), Y.cat.categories):
  # print(i,j)
  x = np.ndarray.flatten(X)
  x = np.reshape(x, newshape = (X.shape[0], X.shape[1] * X.shape[2]))
  pd.DataFrame(x)
  X = x
  #print(X.shape, Y.shape)
  Y = Y[:,np.newaxis]
  return X, Y