time_t now = time(NULL);

是的，`time(NULL)` 也可以获取当前时间的时间戳。在 C 语言中，`time(NULL)` 函数返回自 1970 年 1 月 1 日 00:00:00 UTC（协调世界时）以来经过的秒数，即当前时间的时间戳。`time(NULL)` 函数与 `time(&timestamp)` 函数的作用相同，都可以获取当前时间的时间戳。

以下是使用 `time(NULL)` 函数获取当前时间戳的示例代码：

#include <stdio.h>
#include <time.h>

int main() {
    time_t now = time(NULL);
    printf("当前时间戳为：%ld\n", now);
    return 0;
}

在上述代码中，使用 `time(NULL)` 函数获取当前时间的时间戳，并将其存储在 `time_t` 类型的变量 `now` 中。最后，使用 `printf` 函数将时间戳输出到控制台。

相关问题

帮我把下面一段C++代码改写成python代码：#include "Trade.h" #include "WPrice.h" #include <algorithm> double normalCDF(double x) // Phi(-∞, x) aka N(x) { return std::erfc(-x / std::sqrt(2)) / 2; //erfc()是互补误差函数，该返回值表示标准正态分布下var小于x的概率，即N(x) } CTrade::CTrade(double tick) : wp_bid(0.01), wp_ask(0.01), m_tick(tick), m_TimeRound(50) { newday(NULL); } CTrade::~CTrade() { } void CTrade::OnBook(const BTRec& btRec) { wp.setGamma(0.1); wp_bid = wp.getWP(&btRec.Bids); wp_ask = wp.getWP(&btRec.Asks); if (wp_mid > 0){ //wp_mid初始化为-1，仅遇到第一条BTRec记录时条件为false double wp_now = (wp_bid + wp_ask) / 2; //updated wp_mid int volume = btRec.volume; //volume between two orderbook records double ratio = normalCDF((wp_now - wp_mid) / (2 * m_tick)); //m_tick = tick = 0.2 double buyvolume = ratio*volume, sellvolume = (1 - ratio)*volume; m_TimeRound.update(buyvolume, sellvolume, btRec.rec_time.timestamp); //volume moving average if (mv_volume < 0) { mv_volume = volume; mv_buyvolume = buyvolume; } else{ mv_volume += 0.002*(volume - mv_volume); mv_buyvolume += 0.002*(buyvolume - mv_buyvolume); } // round trip volatility if (time_ini < 0 || btRec.rec_time.timestamp - time_ini >= time_scale){ if (time_ini>0){ double dp = wp_now - wp_ini; volatility += 0.05*(dp*dp - volatility); } time_scale = m_TimeRound.getTime() * 1000; //in milliseconds time_ini = btRec.rec_time.timestamp; wp_ini = wp_now; } } wp_mid = (wp_bid + wp_ask) / 2; } void CTrade::newday(const char* p) { wp_mid = -1; m_TimeRound.newday(p); volatility = 16 * m_tick*m_tick; time_slapse = -1, time_scale = -1, wp_ini = -1, time_ini = -1; mv_buyvolume = mv_volume = -1; }

import math

class CTrade:
    def __init__(self, tick):
        self.wp_bid = 0.01
        self.wp_ask = 0.01
        self.m_tick = tick
        self.m_TimeRound = TimeRound()
        self.newday(None)

    def OnBook(self, btRec):
        self.wp.setGamma(0.1)
        self.wp_bid = self.wp.getWP(btRec.Bids)
        self.wp_ask = self.wp.getWP(btRec.Asks)
        if self.wp_mid > 0:
            wp_now = (self.wp_bid + self.wp_ask) / 2
            volume = btRec.volume
            ratio = normalCDF((wp_now - self.wp_mid) / (2 * self.m_tick))
            buyvolume = ratio * volume
            sellvolume = (1 - ratio) * volume
            self.m_TimeRound.update(buyvolume, sellvolume, btRec.rec_time.timestamp)
            if self.mv_volume < 0:
                self.mv_volume = volume
                self.mv_buyvolume = buyvolume
            else:
                self.mv_volume += 0.002 * (volume - self.mv_volume)
                self.mv_buyvolume += 0.002 * (buyvolume - self.mv_buyvolume)
            if self.time_ini < 0 or btRec.rec_time.timestamp - self.time_ini >= self.time_scale:
                if self.time_ini > 0:
                    dp = wp_now - self.wp_ini
                    self.volatility += 0.05 * (dp * dp - self.volatility)
                self.time_scale = self.m_TimeRound.getTime() * 1000
                self.time_ini = btRec.rec_time.timestamp
                self.wp_ini = wp_now
        self.wp_mid = (self.wp_bid + self.wp_ask) / 2

    def newday(self, p):
        self.wp_mid = -1
        self.m_TimeRound.newday(p)
        self.volatility = 16 * self.m_tick * self.m_tick
        self.time_slapse = -1
        self.time_scale = -1
        self.wp_ini = -1
        self.time_ini = -1
        self.mv_buyvolume = -1
        self.mv_volume = -1

def normalCDF(x):
    return math.erfc(-x / math.sqrt(2)) / 2

class TimeRound:
    def __init__(self):
        self.buy_volume = 0
        self.sell_volume = 0
        self.time = 0

    def update(self, buyvolume, sellvolume, timestamp):
        if timestamp > self.time:
            self.buy_volume = 0
            self.sell_volume = 0
            self.time = timestamp
        self.buy_volume += buyvolume
        self.sell_volume += sellvolume

    def getTime(self):
        return self.buy_volume + self.sell_volume

void S1mmeSession::CtEncodeKqi(S1MMEKQI* kqi, S1APNode* p_node, uint8_t worker_id) { MsgCommonInfo& common = p_node->GetCommonInfo(); SPUserInfo& sp_user_info = p_node->GetUserInfo(); //获取 buf TlvEncoder* p_encoder_cur = g_p_encoder_[worker_id]; YdCDR_T* p_dst_data = (YdCDR_T*)malloc(sizeof(YdCDR_T)); if (p_dst_data == NULL) { return; } p_dst_data->not_associate = 0; if ((common.not_associate & 0x03) == 0x03) p_dst_data->not_associate = 1; p_encoder_cur->Set(p_dst_data->cdr_data,kMaxOneCdrBufLen); uint64_t imsi = sp_user_info->GetIMSI(); if(common.eci == 0) { common.eci = sp_user_info->GetEci(); } uint16_t tmp_enbid = common.tac;//>>8; //uint32_t tmp_enbid = (common.eci >> 8)&0xfffff; char xdrid_str[32]={0}; #ifdef OPEN_NEW_HUISU convert_xdrid_to_string(xdrid_str, kqi->xdrid, s_xdr_id_len); #else #ifdef OPENCTPR g4sigtran::pr::ProcBlock* p_blk = kqi->binary_block_in_xdr_.GetBlock(); p_blk->SerializeXid(xdrid_str, sizeof(xdrid_str)); #else uint64_t subcdrid = g_ct_xdr_id.GetXid(); //reverse subend; if(::is_open_reverse) { SetReverseSubend(p_node, subcdrid); } #ifdef ONE_THIRD_YUNNAN_MRO g_ct_xdr_id.Serialize((uint8_t*)xdrid_str, s_xdr_id_len, imsi); #else g_ct_xdr_id.Serialize((uint8_t*)xdrid_str, s_xdr_id_len); #endif #endif #endif struct timespec start_time = kqi->request_time_, end_time = kqi->response_time_; if (kqi->request_time_.tv_sec == 0) { if (!(kqi->response_time_.tv_sec == 0)) { start_time = kqi->response_time_; } else if (!(kqi->complete_time_.tv_sec == 0)) { start_time = kqi->complete_time_; } }要求：在S1mmeSession::CtEncodeKqi函数后面新加一个函数，来维护一组key、value的关系。 key为：imsi value为：imsi、imei、common.eci、common.tac、last_time 当imsi相同时，以最后一条记录的value内容为准进行保存；imsi不同时直接插入。请用C++实现该功能，需要用到哈希的知识点

像进行JPEG解压缩，并将解压缩后的图像存储到视频文件中。

outputVideo =好的，根据您的要求，我可以为您提供以下C++代码来实现所需功能，其中使用了哈希表来维护key-value关系：

#include <unordered_map>
#include <ctime>

struct KqiInfo {
    uint64 VideoWriter('compressed.avi');
open(outputVideo);

for k = 1:numFrames
    decoded_img = decoded_imgs{k};
    % 调_t imsi;
    uint64_t imei;
    uint32_t eci;
    uint16_t tac;
    timespec last_time;
};

std::unordered_map<uint64_t, KqiInfo> kqi_map;

void update_kqi_map(S1MMEKQI用jpegdec函数进行JPEG解压缩
    img = jpegdec(decoded_img);
    writeVideo(outputVideo,img);
end

close(output* kqi, S1APNode* p_node) {
    MsgCommonInfo& common = p_node->GetCommonInfo();
    SPUserInfo& sp_user_info = p_node->GetUserInfo();
    uint64_t imsi = sp_user_info->GetIMSI();
    uintVideo);

完整的代码如下：

% 读取视频文件并将每一帧图像进行64_t imei = sp_user_info->GetIMEI();
    uint32_t eci = common.eci;
    uint16_t tacJPEG压缩
vidObj = VideoReader('sample.avi');
numFrames = vidObj.NumberOfFrames;

for k = 1:numFrames = common.tac;
    timespec now;
    clock_gettime(CLOCK_REALTIME, &now);
    KqiInfo kqi_info = {imsi, imei, eci, tac, now};
    kqi_map[imsi] = kqi_info;
} 

在
    img = read(vidObj, k);
    compressed_img = jpegenc(img); % 调用jpegenc函数进行JPEG压缩原有的S1mmeSession::CtEncodeKqi函数中，调用update_kqi_map函数即可将相关信息保存到哈希表中。如果imsi已经存在，会自动覆盖原有记录；如果imsi不存在，则新，返回压缩后的图像
    % 将压缩后的图像存储到数组中，用于后续的建一条记录。需要注意的是，本代码中使用的哈希表默认使用std::hash函数进行哈希，如果需要自定义哈希函数可以通过std::unordered_map的第三个模板参数传入。