本文整理匯總了Python中scipy.spatial.distance.braycurtis方法的典型用法代碼示例。如果您正苦於以下問題：Python distance.braycurtis方法的具體用法？Python distance.braycurtis怎麽用？Python distance.braycurtis使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類scipy.spatial.distance的用法示例。
在下文中一共展示了distance.braycurtis方法的3個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: score_braycurtis
# 需要導入模塊: from scipy.spatial import distance [as 別名]
# 或者: from scipy.spatial.distance import braycurtis [as 別名]
def score_braycurtis(self, term1, term2, **kwargs):
"""
Compute a weighting score based on the "City Block" distance between
the kernel density estimates of two terms.
Args:
term1 (str)
term2 (str)
Returns: float
"""
t1_kde = self.kde(term1, **kwargs)
t2_kde = self.kde(term2, **kwargs)
return 1-distance.braycurtis(t1_kde, t2_kde) 示例2: __calc_distances__
# 需要導入模塊: from scipy.spatial import distance [as 別名]
# 或者: from scipy.spatial.distance import braycurtis [as 別名]
def __calc_distances__(self, v1s, v2s, is_sparse=True):
if is_sparse:
dcosine = np.array([cosine(x.toarray(), y.toarray()) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dcityblock = np.array([cityblock(x.toarray(), y.toarray()) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dcanberra = np.array([canberra(x.toarray(), y.toarray()) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
deuclidean = np.array([euclidean(x.toarray(), y.toarray()) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dminkowski = np.array([minkowski(x.toarray(), y.toarray(), 3) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dbraycurtis = np.array([braycurtis(x.toarray(), y.toarray()) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dskew_q1 = [skew(x.toarray().ravel()) for x in v1s]
dskew_q2 = [skew(x.toarray().ravel()) for x in v2s]
dkur_q1 = [kurtosis(x.toarray().ravel()) for x in v1s]
dkur_q2 = [kurtosis(x.toarray().ravel()) for x in v2s]
dskew_diff = np.abs(np.array(dskew_q1) - np.array(dskew_q2)).reshape((-1,1))
dkur_diff = np.abs(np.array(dkur_q1) - np.array(dkur_q2)).reshape((-1,1))
else:
dcosine = np.array([cosine(x, y) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dcityblock = np.array([cityblock(x, y) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dcanberra = np.array([canberra(x, y) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
deuclidean = np.array([euclidean(x, y) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dminkowski = np.array([minkowski(x, y, 3) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dbraycurtis = np.array([braycurtis(x, y) for (x, y) in zip(v1s, v2s)]).reshape((-1,1))
dskew_q1 = [skew(x) for x in v1s]
dskew_q2 = [skew(x) for x in v2s]
dkur_q1 = [kurtosis(x) for x in v1s]
dkur_q2 = [kurtosis(x) for x in v2s]
dskew_diff = np.abs(np.array(dskew_q1) - np.array(dskew_q2)).reshape((-1,1))
dkur_diff = np.abs(np.array(dkur_q1) - np.array(dkur_q2)).reshape((-1,1))
return np.hstack((dcosine,dcityblock,dcanberra,deuclidean,dminkowski,dbraycurtis,dskew_diff,dkur_diff)) 示例3: get_distance_function
# 需要導入模塊: from scipy.spatial import distance [as 別名]
# 或者: from scipy.spatial.distance import braycurtis [as 別名]
def get_distance_function(requested_metric):
"""
This function returns a specified distance function.
Paramters
---------
requested_metric: str
Distance function. Can be any function in: https://docs.scipy.org/doc/scipy/reference/spatial.distance.html.
Returns
-------
requested_metric : distance function
"""
distance_options = {
'braycurtis': distance.braycurtis,
'canberra': distance.canberra,
'chebyshev': distance.chebyshev,
'cityblock': distance.cityblock,
'correlation': distance.correlation,
'cosine': distance.cosine,
'euclidean': distance.euclidean,
'sqeuclidean': distance.sqeuclidean,
'dice': distance.dice,
'hamming': distance.hamming,
'jaccard': distance.jaccard,
'kulsinski': distance.kulsinski,
'matching': distance.matching,
'rogerstanimoto': distance.rogerstanimoto,
'russellrao': distance.russellrao,
'sokalmichener': distance.sokalmichener,
'sokalsneath': distance.sokalsneath,
'yule': distance.yule,
}
if requested_metric in distance_options:
return distance_options[requested_metric]
else:
raise ValueError('Distance function cannot be found.')