visualization_utils/plotting.py [969:1082]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - budget_alpha = 1 non_optimization_alpha = .1 budget_marker = "_" regu_marker = "." budget_marker_size = 4 regu_marker_size = 1 #itrColNum = all_res_column_name_number["iteration cnt"] #distColNum = all_res_column_name_number["dist_to_goal_non_cost"] trueNum = all_res_column_name_number["move validity"] move_name_number = all_res_column_name_number["move name"] # experiment_names experiment_names = [] file_full_addr_list = [] for dir_name in input_dir_names: file_full_addr = os.path.join(dir_name, "result_summary/FARSI_simple_run_0_1_all_reults.csv") file_full_addr_list.append(file_full_addr) experiment_name = get_experiments_name(file_full_addr, res_column_name_number) experiment_names.append(experiment_name) #color_values = ["r","b","y","black","brown","purple"] color_values = {} color_values["latency_edge_detection"] = color_values["best_des_so_far_latency_edge_detection"] =color_values["latency_budget_edge_detection"] = matplotlib.colors.to_rgba("red") color_values["latency_hpvm_cava"] =color_values["best_des_so_far_latency_hpvm_cava"] = color_values["latency_budget_hpvm_cava"] = matplotlib.colors.to_rgba("magenta") color_values["latency_audio_decoder"] = color_values["best_des_so_far_latency_audio_decoder"] =color_values["latency_budget_audio_decoder"] = matplotlib.colors.to_rgba("orange") color_values["area_non_dram"] =color_values["best_des_so_far_area_non_dram"] = color_values["area_budget"] = matplotlib.colors.to_rgba("forestgreen") color_values["brown"] = (1,0,0,1) color_values["power"] = color_values["best_des_so_far_power"] =color_values["power_budget"] = matplotlib.colors.to_rgba("mediumblue") color_values["latency_budget_edge_detection"] = matplotlib.colors.to_rgba("white") color_values["latency_budget_hpvm_cava"] = matplotlib.colors.to_rgba("white") color_values["latency_budget_audio_decoder"] = matplotlib.colors.to_rgba("white") color_values["area_budget"] = matplotlib.colors.to_rgba("white") color_values["power_budget"] = matplotlib.colors.to_rgba("white") column_name_color_val_dict = {"best_des_so_far_power":"purple", "power_budget":"purple","best_des_so_far_area_non_dram":"blue", "area_budget":"blue", "latency_budget_hpvm_cava":"orange", "latency_budget_audio_decoder":"yellow", "latency_budget_edge_detection":"red", "best_des_so_far_latency_hpvm_cava":"orange", "best_des_so_far_latency_audio_decoder": "yellow","best_des_so_far_latency_edge_detection": "red", "latency_budget":"white" } """ column_name_color_val_dict = {"power":"purple", "power_budget":"purple","area_non_dram":"blue", "area_budget":"blue", "latency_budget_hpvm_cava":"orange", "latency_budget_audio_decoder":"yellow", "latency_budget_edge_detection":"red", "latency_hpvm_cava":"orange", "latency_audio_decoder": "yellow","latency_edge_detection": "red", "latency_budget":"white" } """ axis_font = {'size': '20'} fontSize = 20 x_column_name = "iteration cnt" #y_column_name_list = ["power", "area_non_dram", "latency", "latency_budget", "power_budget","area_budget"] y_column_name_list = ["power", "area_non_dram", "latency"] experiment_column_value = {} for file_full_addr in file_full_addr_list: experiment_name = get_experiments_name(file_full_addr, res_column_name_number) experiment_column_value[experiment_name] = {} for y_column_name in y_column_name_list: if "budget" in y_column_name : prefix = "" else: prefix = "best_des_so_far_" y_column_name = prefix+y_column_name y_column_number = res_column_name_number[y_column_name] x_column_number = res_column_name_number[x_column_name] #dis_to_goal_column_number = res_column_name_number["dist_to_goal_non_cost"] #ref_des_dis_to_goal_column_number = res_column_name_number["ref_des_dist_to_goal_non_cost"] if not y_column_name == prefix+"latency": experiment_column_value[experiment_name][y_column_name] = [] with open(file_full_addr, newline='') as csvfile: resultReader = csv.reader(csvfile, delimiter=',', quotechar='|') for i, row in enumerate(resultReader): if i > 1: if row[trueNum] == "FALSE" or row[move_name_number]=="identity": continue metric_chosen = row[res_column_name_number["transformation_metric"]] workload_chosen = row[res_column_name_number["workload"]] if "budget" in y_column_name: alpha = budget_alpha elif metric_chosen in y_column_name : alpha = 1 else: alpha = non_optimization_alpha col_value = row[y_column_number] if ";" in col_value: col_value = col_value[:-1] col_values = col_value.split(";") for col_val in col_values: if "=" in col_val: if "budget" in y_column_name: alpha = budget_alpha elif workload_chosen in col_val: alpha = 1 else: alpha = non_optimization_alpha val_splitted = col_val.split("=") value_to_add = (float(row[x_column_number]), (val_splitted[0], val_splitted[1]), alpha) else: value_to_add = (float(row[x_column_number]), col_val, alpha) if y_column_name in [prefix+"latency", prefix+"latency_budget"] : - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - visualization_utils/plotting.py [1224:1337]: - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - budget_alpha = 1 non_optimization_alpha = .1 budget_marker = "_" regu_marker = "." budget_marker_size = 4 regu_marker_size = 1 #itrColNum = all_res_column_name_number["iteration cnt"] #distColNum = all_res_column_name_number["dist_to_goal_non_cost"] trueNum = all_res_column_name_number["move validity"] move_name_number = all_res_column_name_number["move name"] # experiment_names experiment_names = [] file_full_addr_list = [] for dir_name in input_dir_names: file_full_addr = os.path.join(dir_name, "result_summary/FARSI_simple_run_0_1_all_reults.csv") file_full_addr_list.append(file_full_addr) experiment_name = get_experiments_name(file_full_addr, res_column_name_number) experiment_names.append(experiment_name) #color_values = ["r","b","y","black","brown","purple"] color_values = {} color_values["latency_edge_detection"] = color_values["best_des_so_far_latency_edge_detection"] =color_values["latency_budget_edge_detection"] = matplotlib.colors.to_rgba("red") color_values["latency_hpvm_cava"] =color_values["best_des_so_far_latency_hpvm_cava"] = color_values["latency_budget_hpvm_cava"] = matplotlib.colors.to_rgba("magenta") color_values["latency_audio_decoder"] = color_values["best_des_so_far_latency_audio_decoder"] =color_values["latency_budget_audio_decoder"] = matplotlib.colors.to_rgba("orange") color_values["area_non_dram"] =color_values["best_des_so_far_area_non_dram"] = color_values["area_budget"] = matplotlib.colors.to_rgba("forestgreen") color_values["brown"] = (1,0,0,1) color_values["power"] = color_values["best_des_so_far_power"] =color_values["power_budget"] = matplotlib.colors.to_rgba("mediumblue") color_values["latency_budget_edge_detection"] = matplotlib.colors.to_rgba("white") color_values["latency_budget_hpvm_cava"] = matplotlib.colors.to_rgba("white") color_values["latency_budget_audio_decoder"] = matplotlib.colors.to_rgba("white") color_values["area_budget"] = matplotlib.colors.to_rgba("white") color_values["power_budget"] = matplotlib.colors.to_rgba("white") column_name_color_val_dict = {"best_des_so_far_power":"purple", "power_budget":"purple","best_des_so_far_area_non_dram":"blue", "area_budget":"blue", "latency_budget_hpvm_cava":"orange", "latency_budget_audio_decoder":"yellow", "latency_budget_edge_detection":"red", "best_des_so_far_latency_hpvm_cava":"orange", "best_des_so_far_latency_audio_decoder": "yellow","best_des_so_far_latency_edge_detection": "red", "latency_budget":"white" } """ column_name_color_val_dict = {"power":"purple", "power_budget":"purple","area_non_dram":"blue", "area_budget":"blue", "latency_budget_hpvm_cava":"orange", "latency_budget_audio_decoder":"yellow", "latency_budget_edge_detection":"red", "latency_hpvm_cava":"orange", "latency_audio_decoder": "yellow","latency_edge_detection": "red", "latency_budget":"white" } """ axis_font = {'size': '20'} fontSize = 20 x_column_name = "iteration cnt" #y_column_name_list = ["power", "area_non_dram", "latency", "latency_budget", "power_budget","area_budget"] y_column_name_list = ["power", "area_non_dram", "latency"] experiment_column_value = {} for file_full_addr in file_full_addr_list: experiment_name = get_experiments_name(file_full_addr, res_column_name_number) experiment_column_value[experiment_name] = {} for y_column_name in y_column_name_list: if "budget" in y_column_name : prefix = "" else: prefix = "best_des_so_far_" y_column_name = prefix+y_column_name y_column_number = res_column_name_number[y_column_name] x_column_number = res_column_name_number[x_column_name] #dis_to_goal_column_number = res_column_name_number["dist_to_goal_non_cost"] #ref_des_dis_to_goal_column_number = res_column_name_number["ref_des_dist_to_goal_non_cost"] if not y_column_name == prefix+"latency": experiment_column_value[experiment_name][y_column_name] = [] with open(file_full_addr, newline='') as csvfile: resultReader = csv.reader(csvfile, delimiter=',', quotechar='|') for i, row in enumerate(resultReader): if i > 1: if row[trueNum] == "FALSE" or row[move_name_number]=="identity": continue metric_chosen = row[res_column_name_number["transformation_metric"]] workload_chosen = row[res_column_name_number["workload"]] if "budget" in y_column_name: alpha = budget_alpha elif metric_chosen in y_column_name : alpha = 1 else: alpha = non_optimization_alpha col_value = row[y_column_number] if ";" in col_value: col_value = col_value[:-1] col_values = col_value.split(";") for col_val in col_values: if "=" in col_val: if "budget" in y_column_name: alpha = budget_alpha elif workload_chosen in col_val: alpha = 1 else: alpha = non_optimization_alpha val_splitted = col_val.split("=") value_to_add = (float(row[x_column_number]), (val_splitted[0], val_splitted[1]), alpha) else: value_to_add = (float(row[x_column_number]), col_val, alpha) if y_column_name in [prefix+"latency", prefix+"latency_budget"] : - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -