代码搜索：Amsterdam
找到约 3,357 项符合「Amsterdam」的源代码
代码结果 3,357
www.eeworm.com/read/38039/1106774
amsterdam
www.eeworm.com/read/337276/3342536
amsterdam
# created by tools/tclZIC.tcl - do not edit
set TZData(:Europe/Amsterdam) {
{-9223372036854775808 1172 0 LMT}
{-4260212372 1172 0 AMT}
{-1693700372 4772 1 NST}
{-1680484772 1172 0 AMT
www.eeworm.com/read/154805/5633997
amsterdam
# created by ../tools/tclZIC.tcl - do not edit
set TZData(:Europe/Amsterdam) {
{-9223372036854775808 1172 0 LMT}
{-4260212372 1172 0 AMT}
{-1693700372 4772 1 NST}
{-1680484772 1172 0
www.eeworm.com/read/286440/8763846
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be zero; 0 (
www.eeworm.com/read/164260/10120774
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be zero; 0 (
www.eeworm.com/read/357772/10201260
m matdistance.m
function d = matdistance(a,b)
% DISTANCE - computes Euclidean distance matrix
%
% E = distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
%
% Returns:
% E - (MxN) Euclidean distan
www.eeworm.com/read/198944/7903390
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be ze
www.eeworm.com/read/397758/8024433
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be ze
www.eeworm.com/read/195849/8126645
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be ze
www.eeworm.com/read/333410/12684449
m l2_distance.m
function d = L2_distance(a,b,df)
% L2_DISTANCE - computes Euclidean distance matrix
%
% E = L2_distance(A,B)
%
% A - (DxM) matrix
% B - (DxN) matrix
% df = 1, force diagonals to be ze