function [OP_Cost,GOP]=MTOA(Fcn_Name,Par_Interval,No_GTs,No_LTs,RM,Rm,Max_Itr,Beta,Lambda,Theta,Graphic_on) 把这段MATLAB代码转换为python代码

Here's the Python version of the given MATLAB code:

def MTOA(Fcn_Name,Par_Interval,No_GTs,No_LTs,RM,Rm,Max_Itr,Beta,Lambda,Theta,Graphic_on):
    # function body goes here
    pass # replace this with your implementation

Note that since the function body is not given, I have used `pass` statement. Please replace it with your implementation of the function.

相关问题

for Itr=1:Max_Itr for i=1:nop % Determin RSs and Search by LTs %-------------------------------------------------------- Rf=((i-1)/(nop-1))(RM-Rm)+Rm; Rd=norm(GOP-GTs(:,RKs(i))); Rs=Rf(Rf>=Rd)+Rd*(Rd>Rf); LTs_C=Create_LTs(No_LTs,Rs,Dim); LTs=repmat(GTs(:,RKs(i)),1,No_LTs)+LTs_C; LTs=SS(LTs,Par_Interval); %---------------- if Graphic_on==1 subplot(2,2,1) hold off pause(0.000001); plot(LTs(1,:),LTs(2,:),'x'); hold on ezplot(['(x-' num2str(GTs(1,RKs(i))) ')^2 + (y-' num2str(GTs(2,RKs(i))) ')^2 -' num2str(Rs^2)],[0 10],[0 10]); hold off xlim([Par_Interval(1,1) Par_Interval(1,2)]); ylim([Par_Interval(2,1) Par_Interval(2,2)]); pbaspect([1 1 1]) title('Local Search') xlabel('x_1') ylabel('x_2') end %---------------- LTs_Cost=Ev_Fcn(LTs,Fcn_Name); [L_min,L_inx]= min(LTs_Cost); if L_min<=LP_Cost(RKs(i)) LP(:,RKs(i))=LTs(:,L_inx); LP_Cost(RKs(i))=L_min; end if L_min<=GOP_Cost GOP_Cost=L_min; GOP=LTs(:,L_inx); end end % Search by GTs %-------------------------------------------------------- for i=1:nop GTs(:,i)=New_GT(GTs(:,i),LP(:,i),GOP,Lambda,Theta,Beta); GTs(:,i)=SS(GTs(:,i),Par_Interval); GTs_Cost(i)=Ev_Fcn(GTs(:,i),Fcn_Name); end % Ranking %-------------------------------------------------------- [Gts_Sorted,RKs]=sort(GTs_Cost); GOP_B=GTs(:,RKs(1)); GOP_Cost_B=Gts_Sorted(1); if GOP_Cost_B<=GOP_Cost GOP_Cost=GOP_Cost_B; GOP=GOP_B; end OP_Cost(Itr+1)=GOP_Cost; %---------------- if Graphic_on==1 subplot(2,2,2) hold off pause(.000001) plot(GTs(1,:),GTs(2,:),'*') hold on plot(GOP(1,:),GOP(2,:),'X','color','red') xlim([Par_Interval(1,1) Par_Interval(1,2)]); ylim([Par_Interval(2,1) Par_Interval(2,2)]); hold off pbaspect([1 1 1]*3) title('Global Search') xlabel('x_1') ylabel('x_2') end %---------------- %---------------- if Graphic_on==1 subplot(2,2,3) hold off pause(.000001) plot(OP_Cost(1:Itr+1)) pbaspect([2 1 1]) xlim([1 Max_Itr+1]) title(['Cost=' num2str(GOP_Cost,'%4.10f')]) xlabel('Iteration') ylabel('Cost') else hold off pause(.000001) plot(0:Itr,OP_Cost(1:Itr+1),'.','MarkerSize',15,'LineStyle','-','Color',[214 30 0]/255,'MarkerEdgeColor',[3 93 118]/255) pbaspect([2 1 1]) title(['Itr=' num2str(Itr) ', Cost=' num2str(GOP_Cost,'%4.10f')]) xlim([0 Max_Itr]) xlabel('Iteration') ylabel('Cost') end %---------------- end 把这段MATLAB代码转换为python代码

以下是将给定的MATLAB代码转换为Python代码的结果：

for Itr in range(1, Max_Itr + 1):
    for i in range(1, nop + 1):
        # Determine RSs and search by LTs
        # --------------------------------------------------------
        Rf = ((i - 1) / (nop - 1)) * (RM - Rm) + Rm
        Rd = np.linalg.norm(GOP - GTs[:, RKs[i - 1]])
        Rs = Rf[Rf >= Rd] + Rd * (Rd > Rf)
        LTs_C = Create_LTs(No_LTs, Rs, Dim)
        LTs = np.tile(GTs[:, RKs[i - 1]], (1, No_LTs)) + LTs_C
        LTs = SS(LTs, Par_Interval)

        # ----------------
        if Graphic_on == 1:
            plt.subplot(2, 2, 1)
            plt.cla()
            plt.plot(LTs[0, :], LTs[1, :], 'x')
            plt.hold(True)
            ezplot('(x - %f)^2 + (y - %f)^2 - %f' % (GTs[0, RKs[i - 1]],
                                                      GTs[1, RKs[i - 1]], Rs ** 2),
                                                      [0, 10], [0, 10])
            plt.hold(False)
            plt.xlim([Par_Interval[0, 0], Par_Interval[0, 1]])
            plt.ylim([Par_Interval[1, 0], Par_Interval[1, 1]])
            plt.gca().set_aspect('equal', adjustable='box')
            plt.title('Local Search')
            plt.xlabel('x_1')
            plt.ylabel('x_2')

        # ----------------
        LTs_Cost = Ev_Fcn(LTs, Fcn_Name)
        L_min, L_inx = np.min(LTs_Cost), np.argmin(LTs_Cost)
        if L_min <= LP_Cost[RKs[i - 1]]:
            LP[:, RKs[i - 1]] = LTs[:, L_inx]
            LP_Cost[RKs[i - 1]] = L_min
        if L_min <= GOP_Cost:
            GOP_Cost = L_min
            GOP = LTs[:, L_inx]

        # Search by GTs
        # --------------------------------------------------------
        for j in range(1, nop + 1):
            GTs[:, j - 1] = New_GT(GTs[:, j - 1], LP[:, j - 1], GOP, Lambda, Theta, Beta)
            GTs[:, j - 1] = SS(GTs[:, j - 1], Par_Interval)
            GTs_Cost[j - 1] = Ev_Fcn(GTs[:, j - 1], Fcn_Name)

        # Ranking
        # --------------------------------------------------------
        Gts_Sorted = np.sort(GTs_Cost)
        RKs = np.argsort(GTs_Cost)
        GOP_B = GTs[:, RKs[0]]
        GOP_Cost_B = Gts_Sorted[0]
        if GOP_Cost_B <= GOP_Cost:
            GOP_Cost = GOP_Cost_B
            GOP = GOP_B
        OP_Cost[Itr] = GOP_Cost

        # ----------------
        if Graphic_on == 1:
            plt.subplot(2, 2, 2)
            plt.cla()
            plt.plot(GTs[0, :], GTs[1, :], '*')
            plt.hold(True)
            plt.plot(GOP[0, :], GOP[1, :], 'X', color='red')
            plt.xlim([Par_Interval[0, 0], Par_Interval[0, 1]])
            plt.ylim([Par_Interval[1, 0], Par_Interval[1, 1]])
            plt.hold(False)
            plt.gca().set_aspect('equal', adjustable='box')
            plt.title('Global Search')
            plt.xlabel('x_1')
            plt.ylabel('x_2')

        # ----------------
        if Graphic_on == 1:
            plt.subplot(2, 2, 3)
            plt.cla()
            plt.plot(OP_Cost[0:Itr + 1])
            plt.gca().set_aspect('equal', adjustable='box')
            plt.xlim([1, Max_Itr + 1])
            plt.title('Cost = %f' % GOP_Cost)
            plt.xlabel('Iteration')
            plt.ylabel('Cost')
        else:
            plt.cla()
            plt.plot(range(Itr + 1), OP_Cost[0:Itr + 1], '.', MarkerSize=15, LineStyle='-',
                     Color=[214, 30, 0] / 255, MarkerEdgeColor=[3, 93, 118] / 255)
            plt.gca().set_aspect('equal', adjustable='box')
            plt.xlim([0, Max_Itr])
            plt.title('Itr = %d, Cost = %f' % (Itr, GOP_Cost))
            plt.xlabel('Iteration')
            plt.ylabel('Cost')

        # ----------------
        plt.pause(0.0001)
    # --------------
# ----------------

需要注意的是，这里的代码仅为转换结果，因此无法保证代码正确性。您需要根据原始MATLAB代码和转换结果进行逐行比较，以确保转换结果的正确性。

Nal 数据通过av_interleaved_write_frame 输出ts格式

将 NAL 数据输出到 TS 格式文件中，可以按照以下步骤进行：

1. 初始化 AVFormatContext 和 AVOutputFormat，设置输出文件名和格式参数。

    AVFormatContext *ofmt_ctx = NULL;
    avformat_alloc_output_context2(&ofmt_ctx, NULL, "mpegts", out_filename);
    AVOutputFormat *ofmt = ofmt_ctx->oformat;

2. 打开输出文件。

    if (!(ofmt->flags & AVFMT_NOFILE)) {
        if (avio_open(&ofmt_ctx->pb, out_filename, AVIO_FLAG_WRITE) < 0) {
            printf("Could not open output file '%s'", out_filename);
            return -1;
        }
    }

3. 添加视频流到输出文件中，设置编码参数，打开编码器。

    AVStream *out_stream = avformat_new_stream(ofmt_ctx, NULL);
    AVCodecParameters *codecpar = out_stream->codecpar;
    codecpar->codec_id = AV_CODEC_ID_H264;
    codecpar->codec_type = AVMEDIA_TYPE_VIDEO;
    codecpar->format = AV_PIX_FMT_YUV420P;
    codecpar->width = width;
    codecpar->height = height;
    codecpar->extradata_size = sps_len + pps_len;
    codecpar->extradata = av_mallocz(sps_len + pps_len + AV_INPUT_BUFFER_PADDING_SIZE);
    memcpy(codecpar->extradata, sps_pps_data, sps_len + pps_len);
    out_stream->time_base = (AVRational){1, fps};
    AVCodec *codec = avcodec_find_encoder(codecpar->codec_id);
    AVCodecContext *codec_ctx = avcodec_alloc_context3(codec);
    avcodec_parameters_to_context(codec_ctx, codecpar);
    codec_ctx->time_base = out_stream->time_base;
    codec_ctx->gop_size = 10;
    codec_ctx->max_b_frames = 1;
    codec_ctx->bit_rate = bitrate;
    codec_ctx->rc_min_rate = bitrate;
    codec_ctx->rc_max_rate = bitrate;
    codec_ctx->rc_buffer_size = bitrate;
    avcodec_open2(codec_ctx, codec, NULL);

4. 循环读取 NAL 数据，将数据写入 AVPacket 中，并设置时间戳和时长。

    while (read_len > 0) {
        AVPacket pkt;
        av_init_packet(&pkt);
        pkt.data = buf;
        pkt.size = read_len;
        pkt.pts = pts++;
        pkt.dts = pkt.pts;
        pkt.duration = 1;
        pkt.stream_index = out_stream->index;
        av_interleaved_write_frame(ofmt_ctx, &pkt);
        av_packet_unref(&pkt);
        read_len = fread(buf, 1, buf_size, fp);
    }

5. 写入文件尾，并释放资源。

    av_write_trailer(ofmt_ctx);
    avcodec_close(codec_ctx);
    avcodec_free_context(&codec_ctx);
    av_freep(&codecpar->extradata);
    avio_close(ofmt_ctx->pb);
    avformat_free_context(ofmt_ctx);

完整代码示例可以参考以下链接：https://gist.github.com/mstorsjo/012b5861e1fca20f1b2b961d853e49ec