Fixed #1111 Add module for sliding dot product; Include pyfftw as (soft) dependency

stumpy/core.py

@@ -12,10 +12,9 @@
 from numba import cuda, njit, prange
 from scipy import linalg
 from scipy.ndimage import maximum_filter1d, minimum_filter1d
-from scipy.signal import convolve
 from scipy.spatial.distance import cdist
 
-from . import config
+from . import config, sdp
 
 try:
     from numba.cuda.cudadrv.driver import _raise_driver_not_found
@@ -652,7 +651,8 @@ def check_window_size(m, max_size=None, n=None):
 @njit(fastmath=config.STUMPY_FASTMATH_TRUE)
 def _sliding_dot_product(Q, T):
     """
-    A Numba JIT-compiled implementation of the sliding window dot product.
+    A wrapper for numba JIT-compiled implementation of
+    the sliding dot product.
 
     Parameters
     ----------
@@ -667,18 +667,12 @@ def _sliding_dot_product(Q, T):
     out : numpy.ndarray
         Sliding dot product between `Q` and `T`.
     """
-    m = Q.shape[0]
-    l = T.shape[0] - m + 1
-    out = np.empty(l)
-    for i in range(l):
-        out[i] = np.dot(Q, T[i : i + m])
-
-    return out
+    return sdp._njit_sliding_dot_product(Q, T)
 
 
 def sliding_dot_product(Q, T):
     """
-    Use FFT convolution to calculate the sliding window dot product.
+    Compute the sliding dot product between `Q` and `T`.
 
     Parameters
     ----------
@@ -692,27 +686,8 @@ def sliding_dot_product(Q, T):
     -------
     output : numpy.ndarray
         Sliding dot product between `Q` and `T`.
-
-    Notes
-    -----
-    Calculate the sliding dot product
-
-    `DOI: 10.1109/ICDM.2016.0179 \
-    <https://www.cs.ucr.edu/~eamonn/PID4481997_extend_Matrix%20Profile_I.pdf>`__
-
-    See Table I, Figure 4
-
-    Following the inverse FFT, Fig. 4 states that only cells [m-1:n]
-    contain valid dot products
-
-    Padding is done automatically in fftconvolve step
     """
-    n = T.shape[0]
-    m = Q.shape[0]
-    Qr = np.flipud(Q)  # Reverse/flip Q
-    QT = convolve(Qr, T)
-
-    return QT.real[m - 1 : n]
+    return sdp._sliding_dot_product(Q, T)
 
 
 @njit(