代码搜索：objects
找到约 10,000 项符合「objects」的源代码
代码结果 10,000
www.eeworm.com/read/289413/8553462
makefile
objects = data.o fpgrowth.o fptree.o item.o testfpgrowth.o
CC = g++
flags = -O6 -Wall
fpgrowth: $(objects)
$(CC) $(flags) $(objects) -o fpgrowth
data.o: data.cpp data.h
$(CC) $(flags) -c data.cpp
www.eeworm.com/read/188268/8554152
makefile
objects = data.o fpgrowth.o fptree.o item.o testfpgrowth.o
CC = g++
flags = -O6 -Wall
fpgrowth: $(objects)
$(CC) $(flags) $(objects) -o fpgrowth
data.o: data.cpp data.h
$(CC) $(flags) -c data.cpp
www.eeworm.com/read/432289/8613839
cpp objcount.cpp
//: C03:Objcount.cpp
// From Thinking in C++, 2nd Edition
// at http://www.BruceEckel.com
// (c) Bruce Eckel 1999
// Copyright notice in Copyright.txt
// Counts objects in existence
#include
www.eeworm.com/read/288619/8618200
makefile
#############################################################################
# Makefile for building button
# Generated by tmake at 20:51, 2008/03/08
# Project: button
# Template: app
########
www.eeworm.com/read/288527/8625461
makefile
#
# Makefile for Simple Genetic Algorithm C code
#
#####################################
# Define implicit compilation rules #
#####################################
# uncomment following lines
www.eeworm.com/read/187475/8637508
makefile
CC = g++ -Wall -g
LDLIBS = -lm
OBJECTS=IntList.o NArray.o NPoint.o DensityMap.o HashTree.o HashForest.o
HEADERS=$(OBJECTS:.o=.h)
TARGETS=main
all: $(TARGETS)
$(TARGETS): $(OBJECTS)
$(CC) -o $@ $@
www.eeworm.com/read/288078/8653208
cpp objectmanager.cpp
/*
This file is part of SWAIN (http://sourceforge.net/projects/swain).
Copyright (C) 2006 Daniel Lindstr鰉 and Daniel Nilsson
This program is free software; you can redistribute it and/or
modify
www.eeworm.com/read/431675/8661709
m modeseek.m
%MODESEEK Clustering by modeseeking
%
% [labels,J] = modeseek(D,k)
%
% If D is a n*n distance matrix between object then a k-nn
% modeseeking method is used to assign each object to its nearest
%
www.eeworm.com/read/431675/8662148
m distm.m
%DISTM Distance matrix between two datasets.
%
% D = distm(A,B)
%
% Computation of the distance matrix D between two datasets A and B.
% Distances are computed as squared Euclidean. If A has m obj