def generate_steady_rt_pic(process_data, para_meter, scale, steady_time):
pic_path_steady = para_meter['<STR_LIT:filename>'] + '<STR_LIT>'<EOL>plt.figure(figsize=(<NUM_LIT:4> * scale, <NUM_LIT> * scale))<EOL>for key in process_data.keys():<EOL><INDENT>if len(process_data[key]) < steady_time:<EOL><INDENT>steady_time = len(process_data[key])<EOL><DEDENT>plt.scatter(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>],<EOL>process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:1>], label=str(key), s=<NUM_LIT:10>)<EOL>steady_value = np.mean(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:1>])<EOL>steady_value_5 = steady_value * (<NUM_LIT:1> + <NUM_LIT>)<EOL>steady_value_10 = steady_value * (<NUM_LIT:1> + <NUM_LIT:0.1>)<EOL>steady_value_ng_5 = steady_value * (<NUM_LIT:1> - <NUM_LIT>)<EOL>steady_value_ng_10 = steady_value * (<NUM_LIT:1> - <NUM_LIT:0.1>)<EOL>plt.plot(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>], [steady_value] * steady_time, '<STR_LIT:b>')<EOL>plt.plot(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>], [steady_value_5] * steady_time, '<STR_LIT:g>')<EOL>plt.plot(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>],<EOL>[steady_value_ng_5] * steady_time, '<STR_LIT:g>')<EOL>plt.plot(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>], [steady_value_10] * steady_time, '<STR_LIT:r>')<EOL>plt.plot(process_data[key][-<NUM_LIT:1> * steady_time:, <NUM_LIT:0>],<EOL>[steady_value_ng_10] * steady_time, '<STR_LIT:r>')<EOL><DEDENT>plt.title(para_meter['<STR_LIT:title>'] + '<STR_LIT>')<EOL>plt.xlabel(para_meter['<STR_LIT>'] + '<STR_LIT>')<EOL>plt.ylabel(para_meter['<STR_LIT>'] + '<STR_LIT>')<EOL>plt.legend(loc='<STR_LIT>')<EOL>plt.savefig(pic_path_steady)<EOL>return pic_path_steady<EOL>
generate rate steady