Added NumPy-vectorised version of cort (dtw is as V1)

pyfiles/dtw_cort_dist/todo_V11_numpy_vec/dtw_cort_dist_mat.py

+#!/usr/bin/env python3
+
+from functools import partial
+from runpy import run_path
+from pathlib import Path
+
+import numpy as np
+import math
+
+util = run_path(Path(__file__).absolute().parent.parent / "util.py")
+
+
+def serie_pair_index_generator(number):
+    """ generator for pair index (i, j) such that i < j < number
+
+    :param number: the upper bound
+    :returns: pairs (lower, greater)
+    :rtype: a generator
+    """
+    return (
+        (_idx_greater, _idx_lower)
+        for _idx_greater in range(number)
+        for _idx_lower in range(number)
+        if _idx_lower < _idx_greater
+    )
+
+
+def DTWDistance(s1, s2):
+    """ Computes the dtw between s1 and s2 with distance the absolute distance
+
+    :param s1: the first serie (ie an iterable over floats64)
+    :param s2: the second serie (ie an iterable over floats64)
+    :returns: the dtw distance
+    :rtype: float64
+    """
+    len_s1 = len(s1)
+    len_s2 = len(s2)
+
+    _dtw_mat = np.empty([len_s1, len_s2])
+    _dtw_mat[0, 0] = abs(s1[0] - s2[0])
+
+    #  two special cases : filling first row and columns
+    for j in range(1, len_s2):
+        dist = abs(s1[0] - s2[j])
+        _dtw_mat[0, j] = dist + _dtw_mat[0, j - 1]
+
+    for i in range(1, len_s1):
+        dist = abs(s1[i] - s2[0])
+        _dtw_mat[i, 0] = dist + _dtw_mat[i - 1, 0]
+
+    #  filling the matrix
+    for i in range(1, len_s1):
+        for j in range(1, len_s2):
+            dist = abs(s1[i] - s2[j])
+            _dtw_mat[(i, j)] = dist + min(
+                _dtw_mat[i - 1, j], _dtw_mat[i, j - 1], _dtw_mat[i - 1, j - 1]
+            )
+
+    return _dtw_mat[len_s1 - 1, len_s2 - 1]
+
+
+def cort(s1, s2):
+    """ Computes the cort between series one and two (assuming they have the same length)
+
+    :param s1: the first serie (or any iterable over floats64)
+    :param s2: the second serie (or any iterable over floats64)
+    :returns: the cort distance
+    :rtype: float64
+
+    """
+
+    slope_1 = s1[1:] - s1[:-1]
+    slope_2 = s2[1:] - s2[:-1]
+    num = np.sum(slope_1 * slope_2)
+    sum_square_x = np.sum(slope_1 * slope_1)
+    sum_square_y = np.sum(slope_2 * slope_2)
+
+    return num / (math.sqrt(sum_square_x * sum_square_y))
+
+
+def compute(series, nb_series):
+    gen = serie_pair_index_generator(nb_series)
+    _dist_mat_dtw = np.zeros((nb_series, nb_series), dtype=np.float64)
+    _dist_mat_cort = np.zeros((nb_series, nb_series), dtype=np.float64)
+    for t1, t2 in gen:
+        dist_dtw = DTWDistance(series[t1], series[t2])
+        _dist_mat_dtw[t1, t2] = dist_dtw
+        _dist_mat_dtw[t2, t1] = dist_dtw
+        dist_cort = 0.5 * (1 - cort(series[t1], series[t2]))
+        _dist_mat_cort[t1, t2] = dist_cort
+        _dist_mat_cort[t2, t1] = dist_cort
+
+    return _dist_mat_dtw, _dist_mat_cort
+
+
+main = partial(util["main"], compute)
+
+if __name__ == "__main__":
+    main()