visualization_utils/plotting_Iulian.py [349:376]:
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    data = pd.read_csv(csv_file_addr)
    blk_cnt = list(data["blk_cnt"])
    pe_cnt = list(data["pe_cnt"])
    mem_cnt = list(data["mem_cnt"])
    bus_cnt = list(data["bus_cnt"])
    pa_sim_time = list(data["PA simulation time"])
    farsi_sim_time = list(data["FARSI simulation time"])
    pa_predicted_lat = list(data["PA_predicted_latency"])
    tmp_reformatted_df_data = [pa_predicted_lat * 2, pa_sim_time + farsi_sim_time,
                               ["PA"] * len(blk_cnt) + ["FARSI"] * len(blk_cnt)]
    reformatted_df_data = [[tmp_reformatted_df_data[j][i] for j in range(len(tmp_reformatted_df_data))] for i in
                           range(len(blk_cnt) * 2)]
    # print(reformatted_df_data[0:3])
    # exit()
    # for col in reformatted_df_data:
    #    print("Len of col is {}".format(len(col)))
    reformatted_df = pd.DataFrame(reformatted_df_data,
                                  columns=["PA Predicted Latency", "Simulation Time", "FARSI or PA"])

    reformatted_df = pd.DataFrame(reformatted_df_data,
                                  columns=["PA _predicted_latencys", "Simulation Time",
                                           "FARSI or PA"])
    print(reformatted_df.head())

    df_blk_avg = get_df_as_avg_for_each_x_coord(reformatted_df, "PA _predicted_latencys")

    df_avg = get_df_as_avg_for_each_x_coord(reformatted_df, x_coord_name="PA _predicted_latencys", y_coord_name="Simulation Time",
                                            hue_col="FARSI or PA")
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visualization_utils/plotting_Iulian.py [426:453]:
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    data = pd.read_csv(csv_file_addr)
    blk_cnt = list(data["blk_cnt"])
    pe_cnt = list(data["pe_cnt"])
    mem_cnt = list(data["mem_cnt"])
    bus_cnt = list(data["bus_cnt"])
    pa_sim_time = list(data["PA simulation time"])
    farsi_sim_time = list(data["FARSI simulation time"])
    pa_predicted_lat = list(data["PA_predicted_latency"])
    tmp_reformatted_df_data = [pa_predicted_lat * 2, pa_sim_time + farsi_sim_time,
                               ["PA"] * len(blk_cnt) + ["FARSI"] * len(blk_cnt)]
    reformatted_df_data = [[tmp_reformatted_df_data[j][i] for j in range(len(tmp_reformatted_df_data))] for i in
                           range(len(blk_cnt) * 2)]
    # print(reformatted_df_data[0:3])
    # exit()
    # for col in reformatted_df_data:
    #    print("Len of col is {}".format(len(col)))
    reformatted_df = pd.DataFrame(reformatted_df_data,
                                  columns=["PA Predicted Latency", "Simulation Time", "FARSI or PA"])

    reformatted_df = pd.DataFrame(reformatted_df_data,
                                  columns=["PA _predicted_latencys", "Simulation Time",
                                           "FARSI or PA"])
    print(reformatted_df.head())

    df_blk_avg = get_df_as_avg_for_each_x_coord(reformatted_df, "PA _predicted_latencys")

    df_avg = get_df_as_avg_for_each_x_coord(reformatted_df, x_coord_name="PA _predicted_latencys", y_coord_name="Simulation Time",
                                            hue_col="FARSI or PA")
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