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How to use psh method in fMBT

Best Python code snippet using fMBT_python

ModelSetUp.py

Source:ModelSetUp.py

...31    def add_var_e(self, var_name):32        return self.gur_model.addVars(self.e_system.parameter['EName'], ub=float('inf'),lb=-float('inf'), vtype="C", name=var_name)33    def add_var_I(self, var_name):34        return self.gur_model.addVars(self.e_system.parameter['EName'], vtype="B", name=var_name)35    def add_var_psh(self, var_name):36        return self.gur_model.addVars(self.psh_system.parameter['PSHName'], ub=float('inf'),lb=-float('inf'),vtype="C",name=var_name)37    def add_constraint_week_rolling(self):38        print(type(self.e_prev[0]))39        print(type(self.e_system.parameter['EStart']))40        print(type(self.e['Reservoir1']))41        for k in self.e_system.parameter['EName']:42            for i in range(self.one_day_period):43                if i == 0:44                    LHS = self.e_prev[i][k] + grb.quicksum(self.psh_gen_prev[i][j] / self.psh_system.parameter['GenEfficiency'] for j in self.psh_system.parameter['PSHName']) \45                                                  - grb.quicksum(self.psh_pump_prev[i][j] * self.psh_system.parameter['PumpEfficiency'] for j in self.psh_system.parameter['PSHName'])46                    RHS = self.e_system.parameter['EStart']47                    self.gur_model.addConstr(LHS == RHS, name='%s_%s' % ('SOC', i))48                else:49                    LHS = self.e_prev[i][k] + grb.quicksum(self.psh_gen_prev[i][j] / self.psh_system.parameter['GenEfficiency'] for j in self.psh_system.parameter['PSHName']) \50                                                  - grb.quicksum(self.psh_pump_prev[i][j] * self.psh_system.parameter['PumpEfficiency'] for j in self.psh_system.parameter['PSHName'])51                    RHS = self.e_prev[i-1][k]52                    self.gur_model.addConstr(LHS == RHS, name='%s_%s' % ('SOC', i))53        for k in self.e_system.parameter['EName']:54            LHS = self.e[k] + grb.quicksum(self.psh_gen[j] / self.psh_system.parameter['GenEfficiency'] for j in self.psh_system.parameter['PSHName']) \55                                          - grb.quicksum(self.psh_pump[j] * self.psh_system.parameter['PumpEfficiency'] for j in self.psh_system.parameter['PSHName'])56            RHS = self.e_prev[self.one_day_period-1][k]57            ### if we calculate the first one, we use 'SOC0', and the last we use 'End'; or we choose the SOC0 to "beginning", at the same time the last we use 'SOC'.58            self.gur_model.addConstr(LHS == RHS, name='%s_%s' % ('SOC0', k))59    def add_constraint_week_epsh(self):60        for j in self.psh_system.parameter['PSHName']:  # all are lists61            self.gur_model.addConstr(self.psh_gen[j] <= self.psh_system.parameter['GenMax'], name='%s_%s' % ('psh_gen_max0', j))62            self.gur_model.addConstr(self.psh_gen[j] >= self.psh_system.parameter['GenMin'], name='%s_%s' % ('psh_gen_min0', j))63            self.gur_model.addConstr(self.psh_pump[j] <= self.psh_system.parameter['PumpMax'], name='%s_%s' % ('psh_pump_max0', j))64            self.gur_model.addConstr(self.psh_pump[j] >= self.psh_system.parameter['PumpMin'], name='%s_%s' % ('psh_pump_min0', j))65            for i in range(self.one_day_period):66                self.gur_model.addConstr(self.psh_gen_prev[i][j] <= self.psh_system.parameter['GenMax'], name='%s_%s' % ('psh_gen_max'+str(i),j))67                self.gur_model.addConstr(self.psh_gen_prev[i][j] >= self.psh_system.parameter['GenMin'], name='%s_%s' % ('psh_gen_min'+str(i),j))68                self.gur_model.addConstr(self.psh_pump_prev[i][j] <= self.psh_system.parameter['PumpMax'], name='%s_%s' % ('psh_pump_max'+str(i),j))69                self.gur_model.addConstr(self.psh_pump_prev[i][j] >= self.psh_system.parameter['PumpMin'], name='%s_%s' % ('psh_pump_min'+str(i),j))70        for k in self.e_system.parameter['EName']:71            self.gur_model.addConstr(self.e[k] <= self.e_system.parameter['EMax'], name='%s_%s' % ('e_max0', k))72            self.gur_model.addConstr(self.e[k] >= self.e_system.parameter['EMin'], name='%s_%s' % ('e_min0', k))73            for i in range(self.one_day_period):74                self.gur_model.addConstr(self.e_prev[i][k] <= self.e_system.parameter['EMax'], name='%s_%s' % ('e_max'+ str(i), k))75                self.gur_model.addConstr(self.e_prev[i][k] >= self.e_system.parameter['EMin'], name='%s_%s' % ('e_min0'+ str(i), k))76    def add_constraint_curve(self):77        for k in self.e_system.parameter['EName']:78            _temp_sum = 079            for i in range(self.curve.numbers):80                _temp_sum += self.soc[i][k]81            LHS = self.e[k]82            RHS = _temp_sum  # RHS=soc[0][k]+soc[1][k]+soc[2][k]+soc[3][k]+soc[4][k]83            self.gur_model.addConstr(LHS == RHS, name='%s_%s' % ('curve', k))84    def add_constraint_soc(self):85    ### how to constraint for  d_1I_2 <= soc_1 <=d_1I_1? ############################86        for k in self.e_system.parameter['EName']:87            for i in range(self.curve.numbers):88                name_num = str(i + 1)89                bench_num = i90                if bench_num == 0:91                    self.gur_model.addConstr(self.soc[bench_num][k] <= float(self.d[bench_num]) * self.I[bench_num][k],92                                    name='%s_%s' % ('soc_' + name_num + '_max', k))93                    self.gur_model.addConstr(float(self.d[bench_num]) * self.I[bench_num + 1][k] <= self.soc[bench_num][k],94                                    name='%s_%s' % ('soc_' + name_num + '_min', k))95                elif bench_num == self.curve.numbers - 1:96                    self.gur_model.addConstr(self.soc[bench_num][k] <= float(self.d[bench_num]) * self.I[bench_num][k],97                                    name='%s_%s' % ('soc_' + name_num + '_max', k))98                    self.gur_model.addConstr(0 <= self.soc[bench_num][k], name='%s_%s' % ('soc_' + name_num + '_min', k))99                else:100                    self.gur_model.addConstr(self.soc[bench_num][k] <= float(self.d[bench_num]) * self.I[bench_num][k],101                                    name='%s_%s' % ('soc_' + name_num + '_max', k))102                    self.gur_model.addConstr(float(self.d[bench_num]) * self.I[bench_num + 1][k] <= self.soc[bench_num][k],103                                    name='%s_%s' % ('soc_' + name_num + '_min', k))104    def add_constraint_I(self):105        for k in self.e_system.parameter['EName']:106            for i in range(self.curve.numbers - 1):107                name_num = str(i + 1)108                name_num_next = str(i + 2)109                bench_num = i110                self.gur_model.addConstr(self.I[bench_num + 1][k] <= self.I[bench_num][k],111                                name='%s_%s' % ('I_' + name_num_next + '_' + name_num, k))112    def add_contraint_terminal(self):113        beta = 0.001  # 0.001114        for k in self.e_system.parameter['EName']:115            curr_day = self.curr_model_para.day_period - self.curr_model_para.curr_day116            LHS_1 = self.e[k] - self.e_system.parameter['EEnd']117            RHS_1 = (curr_day) * self.psh_system.parameter['GenMax'] / (118                        self.psh_system.parameter['GenEfficiency'] + beta)  # PSHmax_g[0] / PSHefficiency[0]119            self.gur_model.addConstr(LHS_1 <= RHS_1, name='%s_%s' % ('final_upper', k))120        for k in self.e_system.parameter['EName']:121            curr_day = self.curr_model_para.day_period - self.curr_model_para.curr_day122            LHS_2 = self.e[k] - self.e_system.parameter['EEnd']123            RHS_2 = -(curr_day) * self.psh_system.parameter['PumpMax'] * (124                        self.psh_system.parameter['PumpEfficiency'] - beta)  # PSHmax_p[0] * PSHefficiency[0]125            self.gur_model.addConstr(LHS_2 >= RHS_2, name='%s_%s' % ('final_lower', k))126    def add_week_contraint_terminal(self):127        for k in self.e_system.parameter['EName']:128            LHS = self.e[k] - self.e_system.parameter['EEnd']129            RHS = 0130            self.gur_model.addConstr(LHS == RHS, name='%s_%s' % ('final_up_down', k))131##the following is for set upt elements of optimization problems132    def set_up_week_variable(self):133    # add gen_prev, pump_prev, e_prev134        self.one_day_period = 23135        self.psh_gen_prev = []136        self.psh_pump_prev  = []137        self.e_prev = []138        for i in range(self.one_day_period):139            name_num = str(i + 1)140            self.psh_gen_prev.append((self.add_var_psh('first_23_psh_gen_' + name_num)))141            self.psh_pump_prev.append((self.add_var_psh('first_23_psh_pump_' + name_num)))142            self.e_prev.append((self.add_var_e('first_23_e_' + name_num)))143    # add gen/pump144        self.psh_gen = self.add_var_psh('psh_gen_main')145        self.psh_pump = self.add_var_psh('psh_pump_main')146    #add e147        self.e = self.add_var_e('e_main')148    #add soc and I149        #self.len_var = self.curve.numbers #len(self.curve.point_X)-1150        self.soc = []151        self.I = []152        for i in range(self.curve.numbers):153        #for i in range(self.curve.numbers ):154            name_num = str(i + 1)155            self.soc.append(self.add_var_e('soc_' + name_num))156            self.I.append(self.add_var_I('I_' + name_num))157    #add d158        d = []159        for i in range(self.curve.numbers):160        #for i in range(self.curve.numbers ):161            d.append(self.curve.point_X[i+1] - self.curve.point_X[i])162        self.d = d163        self.gur_model.update()164    def set_up_constraint(self):165    # rolling constraint E_start = E_end +pump + gen166        self.add_constraint_week_rolling()167    # upper and lower constraint168        self.add_constraint_week_epsh()169    # curve constraint170        self.add_constraint_curve()171    # constraint for  d_1I_2 <= soc_1 <=d_1I_1?##172        self.add_constraint_soc()173    # constraint for I_1<=I_2<=I_3174        self.add_constraint_I()175    # terminal constraint176        if self.curr_model_para.curr_day == 6:####6:177            self.add_week_contraint_terminal()178        self.gur_model.update()179    def set_up_week_object(self):180        self.profit_max = []181        for j in self.psh_system.parameter['PSHName']:182            self.profit_max.append((self.psh_gen[j] - self.psh_pump[j]) * self.lmp.lmp_scenarios)...

PerfectOpt.py

Source:PerfectOpt.py

1import pandas as pd2from gurobipy import *3import gurobipy as grb4import matplotlib.pyplot as plt5import numpy as np6def Perfect_Opt(Total_hour, Input_folder,Output_folder,date, RT_DA ,probabilistic, time_total, scenario):7    print('################################## LAC_PSH_profit_max #', Total_hour, 'probabilistic=',probabilistic,' ##################################')8    ################################### Read Data ####################################9    ##read PSH10    filename = Input_folder + '/PSH.csv'11    Data = pd.read_csv(filename)12    df=pd.DataFrame(Data)13    PSHmin_g = df['GenMin']14    PSHmax_g = df['GenMax']15    PSHmin_p = df['PumpMin']16    PSHmax_p = df['PumpMax']17    PSHefficiency = list(df['Efficiency'])18    PSHname = list(df['Name'])19    ##read E20    filename = Input_folder + '/Reservoir.csv'21    Data = pd.read_csv(filename)22    df=pd.DataFrame(Data)23    Emin = df['Min']24    Emax = df['Max']25    Ename = df['Name']26    Edayend= float(df['End'])27    Estart = df['Start']28    ##read price29    filename = Input_folder + '/DECO_prd_dataframe_Perfect_October 1521 2019.csv'30    Data = pd.read_csv(filename)31    df = pd.DataFrame(Data)32    Column_name = list(Data.columns)33    Column_name = Column_name[scenario]34    lmp_quantiles = [1]35    lmp_scenarios = []36    Nlmp_s = 137    # the scenario you want38    lmp_scenarios.append(df[Column_name])39    lmp_scenarios = list(lmp_scenarios[0])40    e_time_periods = [] # è¿ä¸ªæ¯æ»æ¶é´å°141    for i in range(1, len(lmp_scenarios)):42    #for i in range(len(lmp_scenarios)):43        e_time_periods.append('T' + str(i))44    ################################### Build Model ####################################45    model = Model('DAMarket')46    ### define variables47    psh_max_g={}48    psh_min_g={}49    psh_max_p = {}50    psh_min_p = {}51    e_max={}52    e_min={}53    for i in e_time_periods:54        for k in PSHname:55            for s in range(Nlmp_s):56                psh_max_g[(s, i, k)] = list(PSHmax_g)[list(PSHname).index(k)]57                psh_min_g[(s, i, k)] = list(PSHmin_g)[list(PSHname).index(k)]58                psh_max_p[(s, i, k)] = list(PSHmax_p)[list(PSHname).index(k)]59                psh_min_p[(s, i, k)] = list(PSHmin_p)[list(PSHname).index(k)]60    for i in e_time_periods:61        for f in Ename:62            for s in range(Nlmp_s):63                e_max[(s, i, f)] = list(Emax)[list(Ename).index(f)]64                e_min[(s, i, f)] = list(Emin)[list(Ename).index(f)]65    e_max_inf = {}66    e_min_inf = {}67    psh_max_inf = {}68    psh_min_inf = {}69    for i in e_time_periods:70        for k in PSHname:71            for s in range(Nlmp_s):72                psh_max_inf[(s, i, k)] = float('inf')73                psh_min_inf[(s, i, k)] = -float('inf')74    for i in e_time_periods:75        for f in Ename:76            for s in range(Nlmp_s):77                e_max_inf[(s, i, f)] = float('inf')78                e_min_inf[(s, i, f)] = -float('inf')79    # psh0 and e0 are the first stage deterministic variables, while psh and e are stochastic variables.80    psh0_gen= model.addVars(list(PSHname), ub=float('inf'), lb=-float('inf'), name='PSH0_gen')81    psh0_pump= model.addVars(list(PSHname), ub=float('inf'), lb=-float('inf'), name='PSH0_pump')82    psh_gen = model.addVars(range(Nlmp_s), e_time_periods, list(PSHname), ub = psh_max_inf, lb = psh_min_inf, name = 'PSH_gen')83    psh_pump = model.addVars(range(Nlmp_s), e_time_periods, list(PSHname), ub = psh_max_inf, lb = psh_min_inf, name = 'PSH_pump')84    e0 = model.addVars(list(Ename), ub = float('inf'), lb = -float('inf'), name='E0')85    e = model.addVars(range(Nlmp_s), e_time_periods, list(Ename), ub=e_max_inf, lb=e_min_inf, name='E')86    model.update()87    ### add constraints88    # fix start state of energy stored in reservoir89    for j in Ename:90        print('Estart:', float(Estart))91        LHS = e0[j] + grb.quicksum(psh0_gen[j]/PSHefficiency[PSHname.index(j)] for j in PSHname)\92              - grb.quicksum(psh0_pump[j]*PSHefficiency[PSHname.index(j)] for j in PSHname) - float(Estart)93        RHS = 094        print(LHS, RHS)95        model.addConstr(LHS == RHS, name='%s_%s' % ('SOC0', j))96    # state of charge97    for i in e_time_periods:98        time_id = e_time_periods.index(i)99        if time_id == 0: #ç¸å½äºé¤äºe0çç¬¬ä¸ä¸ªï¼éè¦åe0äº¤æ¢100            for s in range(Nlmp_s):101                for j in Ename:102                    print('Estart:',float(Estart))103                    LHS = e[s, i, j] + grb.quicksum(psh_gen[s,i,j]/PSHefficiency[PSHname.index(j)] for j in PSHname)\104                    - grb.quicksum(psh_pump[s, i, j] * PSHefficiency[PSHname.index(j)] for j in PSHname)- e0[j]105                    RHS = 0106                    print(LHS,RHS)107                    model.addConstr(LHS == RHS, name='%s_%s_%d_%d' % ('SOC', j, time_id, s))108                # if time_id == len(e_time_periods) - 1:109                #     for j in Ename:110                #         print('Edayend:', Edayend)111                #         LHS = Edayend - e[s, i, j]112                #         RHS = 0113                #         print(LHS,RHS)114                #         model.addConstr(LHS == RHS, name='%s_%s_%d_%d' % ('SOC', j, len(e_time_periods),s))115        else:116            for s in range(Nlmp_s):117                time_previous=e_time_periods[time_id-1]118                for j in Ename:119                    LHS=e[s,i,j] + grb.quicksum(psh_gen[s,i,j]/PSHefficiency[PSHname.index(j)] for j in PSHname)\120                    - grb.quicksum(psh_pump[s,i,j]*PSHefficiency[PSHname.index(j)] for j in PSHname)-e[s,time_previous,j]121                    RHS= 0122                    print(LHS, RHS)123                    model.addConstr(LHS == RHS, name='%s_%s_%d_%d' % ('SOC', j, time_id, s))124                if time_id == len(e_time_periods) - 1:125                    for j in Ename:126                        print('Edayend:', Edayend)127                        LHS = Edayend - e[s, i, j]128                        RHS = 0129                        print(LHS,RHS)130                        model.addConstr(LHS == RHS, name='%s_%s_%d_%d' % ('SOC', j, len(e_time_periods),s))131    # Upper and lower bounds132    for j in PSHname:133        model.addConstr(psh0_gen[j] <= PSHmax_g, name='%s_%s' % ('psh_gen_max0', j))134        model.addConstr(psh0_gen[j] >= PSHmin_g, name='%s_%s' % ('psh_gen_min0', j))135        model.addConstr(psh0_pump[j] <= PSHmax_p, name='%s_%s' % ('psh_pump_max0', j))136        model.addConstr(psh0_pump[j] >= PSHmin_p, name='%s_%s' % ('psh_pump_min0', j))137    for k in Ename:138        model.addConstr(e0[k] <= Emax, name='%s_%s' % ('e_max0', k))139        model.addConstr(e0[k] >= Emin, name='%s_%s' % ('e_min0', k))140    for s in range(Nlmp_s):141        for i in e_time_periods:142            for j in PSHname:143                model.addConstr(psh_gen[s, i, j] <= psh_max_g[s, i, j], name='%s_%s_%s_%s' % ('psh_gen_max',s, i, j))144                model.addConstr(psh_gen[s, i, j] >= psh_min_g[s, i, j], name='%s_%s_%s_%s' % ('psh_gen_min',s, i, j))145                model.addConstr(psh_pump[s, i, j] <= psh_max_p[s, i, j], name='%s_%s_%s_%s' % ('psh_pump_max', s, i, j))146                model.addConstr(psh_pump[s, i, j] >= psh_min_p[s, i, j], name='%s_%s_%s_%s' % ('psh_pump_min', s, i, j))147            for k in Ename:148                model.addConstr(e[s, i, k] <= e_max[s, i, k], name='%s_%s_%s_%s' % ('e_max',s, i, k))149                model.addConstr(e[s, i, k] >= e_min[s, i, k], name='%s_%s_%s_%s' % ('e_min',s, i, k))150    ### Objective function151    psh_max=[]152    for s in range(Nlmp_s):153        p_s = lmp_quantiles[s]154        for j in PSHname:155            psh_max.append((psh0_gen[j] - psh0_pump[j]) * lmp_scenarios[0] * p_s)156            for i in e_time_periods:157                lac_lmp = lmp_scenarios[e_time_periods.index(i)+1]   #whyè¿éå ä¸1158                psh_max.append((psh_gen[s, i, j] - psh_pump[s, i, j]) * lac_lmp * p_s)159    obj = quicksum(psh_max)160    ################################### Solve Model ####################################161    model.setObjective(obj, GRB.MAXIMIZE)162    model.optimize()163    ####print the first result164    obj = model.getObjective()  # self.calculate_pts(self.optimal_soc_sum)165    # self.optimal_profit = obj.getValue()166    print('the optimal profit is #####', obj.getValue())167    print('#####')168    # print results for variables169    for v in model.getVars():170        print("%s %f" % (v.Varname, v.X))171    ## add psh172    psh0=[]173    PSH0=[]174    for v in [v for v in model.getVars() if 'PSH0_gen' in v.Varname]:175        psh = v.X176        psh0.append(psh)177    for v in [v for v in model.getVars() if 'PSH0_pump' in v.Varname]:178        psh = v.X179        psh0.append(-psh)180    PSH0.append(sum(psh0))181    #if LAC_last_windows:182    psh_last_window_gen=[]183    psh_last_window_pump=[]184    PSH=[PSH0[0]]185    ## add soc186    SOC=[]187    for v in [v for v in model.getVars() if 'PSH_gen' in v.Varname]:188        psh = v.X189        psh_last_window_gen.append(psh)190    for v in [v for v in model.getVars() if 'PSH_pump' in v.Varname]:191        psh = v.X192        psh_last_window_pump.append(psh)193    for i in range(len(psh_last_window_gen)):194        PSH.append(psh_last_window_gen[i]-psh_last_window_pump[i])195    for v in [v for v in model.getVars() if 'E' in v.Varname]:196        soc = v.X197        SOC.append(soc)...

tcp_map.py

Source:tcp_map.py

1# -*- coding: utf-8 -*-2# Copyright 2017, A10 Networks3# Author: Mike Thompson: @mike @t @a10@networks!com4# tcp reference for events, flags, states5_TCP_STATES = [6    'CLOSED',7    'LISTEN',8    'SYN_RCVD',9    'ESTABLISHED',10    'SYN_SENT',11    'FIN_WAIT_1',12    'FIN_WAIT_2',13    'TIME_WAIT',14    'CLOSING',15    'CLOSE_WAIT',16    'LAST_ACK',17]18TCP_EVENTS = [19    'PASSIVE',20    'ACTIVE',21    'SYN',22    'SYNACK',23    'ACK',24    'RDATA',25    'SDATA',26    'FIN',27    'CLOSE',28    'TIMEOUT',29]30_flag_map_hex = {31    0x00: 'NONE',32    0x01: 'FIN',33    0x02: 'SYN',34    0x03: 'FIN-SYN',35    0x04: 'RST',36    0x08: 'PSH',37    0x09: 'FIN-PSH',38    0x0A: 'SYN-PSH',39    0x0B: 'FIN-SYN-PSH',40    0x10: 'ACK',41    0x11: 'FIN-ACK',42    0x12: 'SYN-ACK',43    0x14: 'RST-ACK',44    0x13: 'FIN-SYN-ACK',45    0x18: 'PSH-ACK',46    0x19: 'FIN-PSH-ACK',47    0x1A: 'SYN-PSH-ACK',48    0x1B: 'FIN-SYN-PSH-ACK',49    0x1C: 'RST-PSH-ACK',50    0x20: 'URG',51    0x40: 'ECE',52    0x41: 'FIN-ECE',53    0x42: 'SYN-ECE',54    0x43: 'FIN-SYN-ECE',55    0x48: 'PSH-ECE',56    0x49: 'FIN-PSH-ECE',57    0x4A: 'SYN-PSH-ECE',58    0x4B: 'FIN-SYN-PSH-ECE',59    0x50: 'ACK-ECE',60    0x51: 'FIN-ACK-ECE',61    0x52: 'SYN-ACK-ECE',62    0x53: 'FIN-SYN-ACK-ECE',63    0x58: 'PSH-ACK-ECE',64    0x59: 'FIN-PSH-ACK-ECE',65    0x5A: 'SYN-PSH-ACK-ECE',66    0x5B: 'FIN-SYN-PSH-ACK-ECE',67    0x80: 'CWR',68    0x81: 'FIN-CWR',69    0x82: 'SYN-CWR',70    0x83: 'FIN-SYN-CWR',71    0x88: 'PSH-CWR',72    0x89: 'FIN-PSH-CWR',73    0x8A: 'SYN-PSH-CWR',74    0x8B: 'FIN-SYN-PSH-CWR',75    0x90: 'ACK-CWR',76    0x91: 'FIN-ACK-CWR',77    0x92: 'SYN-ACK-CWR',78    0x93: 'FIN-SYN-ACK-CWR',79    0x98: 'PSH-ACK-CWR',80    0x99: 'FIN-PSH-ACK-CWR',81    0x9A: 'SYN-PSH-ACK-CWR',82    0x9B: 'FIN-SYN-PSH-ACK-CWR',83    0xC0: 'ECE-CWR',84    0xC1: 'FIN-ECE-CWR',85    0xC2: 'SYN-ECE-CWR',86    0xC3: 'FIN-SYN-ECE-CWR',87    0xC8: 'PSH-ECE-CWR',88    0xC9: 'FIN-PSH-ECE-CWR',89    0xCA: 'SYN-PSH-ECE-CWR',90    0xCB: 'FIN-SYN-PSH-ECE-CWR',91    0xD0: 'ACK-ECE-CWR',92    0xD1: 'FIN-ACK-ECE-CWR',93    0xD2: 'SYN-ACK-ECE-CWR',94    0xD3: 'FIN-SYN-ACK-ECE-CWR',95    0xD8: 'PSH-ACK-ECE-CWR',96    0xD9: 'FIN-PSH-ACK-ECE-CWR',97    0xDA: 'SYN-PSH-ACK-ECE-CWR',98    0xDB: 'FIN-SYN-PSH-ACK-ECE-CWR'99}100# tcp_flag_map_dec = {101#102# }103# from collections import OrderedDict104#105# sorted_dictionary = OrderedDict(sorted(_flag_map_hex.items(), key=lambda v: v, reverse=False))106# print '{'107# for k,v in sorted_dictionary.items():108#     print str(k) +':"'+v+'"'...

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