def windowed_data_lstm(window_size, *ts_data):
dataset = np.ndarray((len(ts_data[0]) - window_size + 1, window_size, len(ts_data)))
for i, ts in enumerate(ts_data):
dataset[:, :, i] = sliding_window_view(ts, (window_size,), 1)
return dataset
def peaksToFingerprints(local_peaks, fn=15, songName = "None"):
"""Welcome to peaksToFingerprints.
Args:
local_peaks : The list of local peaks (a boolean array)
fn :
Returns:
fingerprints : a np array with all fingerprints (size 4)
"""
times, freqs = np.where(local_peaks.T)
fp = []
f = sliding_window_view(freqs, window_shape=(len(freqs)-fn,), step = 1)
t = sliding_window_view(freqs, window_shape=(len(times)-fn,), step = 1)
fp.extend(list(zip(np.tile(freqs[:-fn], fn), f[1:].flatten(), (t[1::]-times[np.newaxis, :-fn]).flatten(), np.tile(times[:-fn], fn))))
return fp
def windowed_data(window_size, *ts_data):
k = window_size * len(ts_data)
dataset = np.ndarray((len(ts_data[0]) - window_size + 1, k))
for i, ts in enumerate(ts_data):
dataset[:, window_size * i:window_size * (i + 1)] = sliding_window_view(ts, (window_size,), 1)
return dataset[:-1]
def win_ver(board):
h = sliding_window_view(board, (1, 4), (1, 1)).reshape(
-1, 4) #gets size (1, 4) windows(horizontal).
for i in h: #compare the windows to see if they have 4 ones or 4 twos
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
v = sliding_window_view(board, (4, 1), (1, 1)).reshape(
-1, 4) #gets size (4, 1) windows(vertical).
for i in v:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
d1 = np.sum(sliding_window_view(board, (4, 4),
(1, 1)).reshape(-1, 4, 4) * d1_filter,
axis=1,
dtype=int)
#gets size (4, 4) windows(potential diagonal win).
#Apply identity matrix inorder to keep main diagonal.
#then flatten into shape(1, 4) arrays.
for i in d1:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
d2 = np.sum(sliding_window_view(board, (4, 4),
(1, 1)).reshape(-1, 4, 4) * d2_filter,
axis=1,
dtype=int)
#same process using the second filter.
for i in d2:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
def win_ver(board):
h = sliding_window_view(board, (1, 4), (1, 1)).reshape(-1, 4)
for i in h:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
v = sliding_window_view(board, (4, 1), (1, 1)).reshape(-1, 4)
for i in v:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
d1 = np.sum(sliding_window_view(board, (4, 4),
(1, 1)).reshape(-1, 4, 4) * d1_filter,
axis=1,
dtype=int)
for i in d1:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins
d2 = np.sum(sliding_window_view(board, (4, 4),
(1, 1)).reshape(-1, 4, 4) * d2_filter,
axis=1,
dtype=int)
for i in d2:
c = list(i)
if c == [1, 1, 1, 1]:
return True #True = player1 wins
if c == [2, 2, 2, 2]:
return False #False = player2 wins