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How to use cln method in fMBT

Best Python code snippet using fMBT_python

results.py

Source:results.py

...10                  'K1': s*s/fact(5)/fact(4),11                  'K2': t*t/fact(5)/fact(4),12                  'K3': s*(3*s*s-2*s*t+t*t)/fact(5)/fact(4)/fact(3)/9,13                  'K4': t*(3*t*t-2*s*t+s*s)/fact(5)/fact(4)/fact(3)/9,14                 'L1': (s**3*cln(-210))/fact(6)/fact(5)/fact(4)/fact(3),15                 'L2': (t**3*cln(-210))/fact(6)/fact(5)/fact(4)/fact(3),16                 'L3': (s**4*cln(-430)/21+s**3*t*cln(4)/9-s**2*t**2*cln(1)/18)/fact(6)/fact(5)/fact(4)/fact(3), #correct17                 'L4': (-s**2*t**2*cln(1)/18+s*t**3*cln(4)/9+t**4*cln(-430)/21)/fact(6)/fact(5)/fact(4)/fact(3),18                 'L5': (s**4*cln(-20)/3+s**3*t*cln(8)/9-s**2*t**2*cln(1)/9)/fact(6)/fact(5)/fact(4)/fact(3), #correct19                 'L6': (-s**2*t**2*cln(1)/9+s*t**3*cln(8)/9)/fact(6)/fact(5)/fact(4)/fact(3),20                 'L7': (-cln(45)/14*s**5+s**4*t*(cln(18)/7)+s**3*t**2*cln(-27)/14+s*s*t**3*(cln(9)/7)+s*t**4*cln(-9)/14)/fact(6)/fact(5)/fact(4)/fact(3),21                 'L8': (s*t**4*(cln(18)/7)+s**2*t**3*cln(-27)/14+s**3*t**2*(cln(9)/7)+t*s**4*cln(-9)/14-cln(45)/14*t**5)/fact(6)/fact(5)/fact(4)/fact(3), #corect22                 'L9': (s**5*cln(-15)/28+s**4*t*cln(25)/7/9+s**3*t**2*cln(-65)/7/4/9+s**2*t**3*cln(5)/42+s*t**4*(-cln(1)/28))/fact(6)/fact(5)/fact(4)/fact(3), #correct23                 'L10': (s**4*t*(-cln(1)/28)+s**3*t**2*cln(5)/42 + s**2*t**3*cln(-65)/7/4/9+t**4*s*cln(25)/7/9+t**5*cln(-15)/28)/fact(6)/fact(5)/fact(4)/fact(3),24                 'L11': cln(0),25                 'L12': cln(0),26                 'L13': cln(0),27                 'L14': cln(0),28                 'L15': cln(0),29                  }30print res_d8_kazakov31#D8_s_s_s_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.1M:result = 0.00034717706155927514732#D8_s_s_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.1M:result = -7.71577109669606447e-0533#D8_1|234||||:0|0_0_0||||:s|0|s|t|t/1|234||||:0|0_0_0||||:s|0|s|t|t_0_V3_E0.run.res.1M:result = 0.16666638078993067934#D8_s_1|234|3|45|||:0|0_0_0|0|0_0|||:s|0|t|0|t|s/1|234|3|45|||:0|0_0_0|0|0_0|||:s|0|t|0|t|s_0_V5_E-1.run.res.1M:result = -0.013886323804284202535#D8_s_s_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s/1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s_0_V7_E-2.run.res.1M:result = 0.0020336130469667495936#D8_s_t_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.1M:result = 3.85783339864735573e-0537#D8_s_t_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s/1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s_0_V7_E-2.run.res.1M:result = 1.15723241185716754e-0638# D8_1|234||||:0|0_0_0||||:s|0|s|t|t/1|234||||:0|0_0_0||||:s|0|s|t|t_0_V3_E0.run.res.10000000:result = 0.16666680164104566439# D8_1|234||||:0|0_0_0||||:s|0|s|t|t/1|234||||:0|0_0_0||||:s|0|s|t|t_0_V3_E0.run.res.100000000:result = 0.16666673725766045840# D8_s_1|234|3|45|||:0|0_0_0|0|0_0|||:s|0|t|0|t|s/1|234|3|45|||:0|0_0_0|0|0_0|||:s|0|t|0|t|s_0_V5_E-1.run.res.100000000:result = -0.006944439500525969841# D8_s_s_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s/1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s_0_V7_E-2.run.res.100000000:result = 0.00034722242744591606942# D8_s_s_s_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.100000000:result = 1.92902197684449618e-0543# D8_s_s_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.100000000:result = -1.28600777698412859e-0544# D8_s_s_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s_0_V7_E-2.run.res.100000000:result = 6.43009917744553122e-0645# D8_s_t_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t_0_V7_E-2.run.res.100000000:result = 6.4300638832171996e-0646# D8_s_t_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s_0_V7_E-2.run.res.100000000:result = -1.28601020109254184e-0547# D8_t_1|234|3|45|||:0|0_0_0|0|0_0|||:t|0|s|0|s|t/1|234|3|45|||:0|0_0_0|0|0_0|||:t|0|s|0|s|t_0_V5_E-1.run.res.100000000:result = -0.0069444411682917294948# D8_t_t_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:t|0|0|s|s|0|t/1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:t|0|0|s|s|0|t_0_V7_E-2.run.res.100000000:result = 0.00034722050463016244449# D8_t_t_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s/1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s_0_V7_E-2.run.res.100000000:result = 1.92901204043652127e-0550res_d8_mk =  {'I1': 0.166666380789930679,  # D8_1|234||||:0|0_0_0||||:s|0|s|t|t51              'J1': -0.0069444395005259698*s + 0*t,  # D8_s_1|234|3|45|||:0|0_0_0|0|0_0|||:s|0|t|0|t|s52              'J2': -0.00694444116829172949*t + 0*s,  # D8_t_1|234|3|45|||:0|0_0_0|0|0_0|||:t|0|s|0|s|t53              'K1': s**2*0.000347222427445916069,   # D8_s_t_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:s|0|0|t|t|0|s54              'K2': t**2*0.000347220504630162444,  # D8_s_t_1|234|345|5|5|6||:0|0_0_0|0_0_0|0|0|0||:t|0|0|s|s|0|t55              'K3': s**3*1.92902197684449618e-05+s**2*t*(-1.28600777698412859e-05)+s*t**2*6.4300638832171996e-06+t**3*0,   # D8_s_s_s_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:s|0|t|0|s|0|t56              'K4': s**3*0+s**2*t*(6.43009917744553122e-06)+s*t**2*(-1.28601020109254184e-05)+t**3*1.92901204043652127e-05,   # D8_t_t_t_1|23456|3|45|5|6||:0|0_0_1_0_0|0|0_0|0|0||:t|0|s|0|t|0|s57              'L1': s**3*(-1.68785995602744613e-05),58              'L2': t**3*(-1.68778695435609865e-05),59              'L3': s**4*(-1.64567102125066986e-06)+s**3*t*(3.57204561294340108e-08)+s*s*t*t*(-4.46518959518477966e-09), #correct s*s*t*t60              'L4': s*s*t*t*(-4.46518959518477966e-09)+s*t**3*(3.57204561294340108e-08)+t**4*(-1.64567102125066986e-06),61              'L5': s**4*(-2.75253142702371203e-07 -1.42726868721902996e-07 -3.44893147619749901e-08-8.33243335550604943e-08)+s**3*t*(7.14458251862796748e-08)+s*s*t*t*(-8.93056087494089887e-09), #correct s*s*t*t62              'L6': s*s*t*t*(-8.93056087494089887e-09)+s*t**3*(7.14458251862796748e-08)+t**4*(-2.75253142702371203e-07 -1.42726868721902996e-07 -3.44893147619749901e-08-8.33243335550604943e-08),63              'L7': s**5*(-2.58350887957834037e-07)+s**4*t*(2.06686192690137045e-07)+s**3*t**2*(-1.55011566907761635e-07)+s**2*t**3*(1.03337882470582075e-07)+s*t**4*(-5.16715122528733594e-08),64              'L8': s**4*t*(-5.16715122528733594e-08)+s**3*t**2*(1.03337882470582075e-07)+s**2*t**3*(-1.55011566907761635e-07)+s**1*t**4*(2.06686192690137045e-07)+t**5*(-2.58350887957834037e-07),  #correct t^565              'L9': s*t**4*(-2.87039517787842645e-09)+s**2*t**3*(9.56890571755092227e-09)+s**3*t**2*(-2.07308801741647146e-08)+s**4*t*(2.55016905933046112e-08+4.50545680076137807e-09+1.88880929057826021e-09)+s**5*(-2.60895992478026868e-08-7.03329483134756389e-10-1.62670686265519564e-08), #correct s*s*t*t66              'L10': s**4*t*(-2.87039517787842645e-09)+s**3*t**2*(9.56890571755092227e-09)+s**2*t**3*(-2.07308801741647146e-08)+t**4*s*(2.55016905933046112e-08+4.50545680076137807e-09+1.88880929057826021e-09)+t**5*(-2.60895992478026868e-08-7.03329483134756389e-10-1.62670686265519564e-08),67              'L11': cln(0),68              'L12': cln(0),69              'L13': cln(0),70              'L14': cln(0),71              'L15': cln(0),72              }73for i in sorted(res_d8_mk.keys()):74    print i, "\t", (res_d8_kazakov[i].expand()).evalf() if i in res_d8_kazakov else None, "\n\t", res_d8_mk[i], \75        "\ndelta =", ((res_d8_kazakov[i].expand()).evalf()-res_d8_mk[i]).expand() if i in res_d8_kazakov else None76    print i, "\t", (res_d8_kazakov[i])*fact(6)*fact(5)*fact(4)*fact(3)77    print78sys.exit()79print80print81print "D=6"82print83res_d6_kazakov = {'K3': cln(1)/6,84                 'K4': cln(1)/6,85                 'L1': cln(0),86                 'L2': cln(0),87                 'L3': cln(1)/48,88                 'L4': cln(1)/48,89                 'L5': cln(1)/24,90                 'L6': cln(1)/24,91                 'L7': cln(0),92                 'L8': cln(0),93                 'L9': (t-s)/3/48,94                 'L10': (s-t)/3/48,95                 'L11': cln(0),96                 'L12': cln(0),97                 'L13': cln(0),98                 'L14': cln(0),99                 'L15': cln(0),100                 }101# D6_1|234|34567|5|6|67|7||:0|0_0_0|0_0_0_0_1|0|0|0_0|0||:s|0|0|t|t|0|0|s/1|234|34567|5|6|67|7||:0|0_0_0|0_0_0_0_1|0|0|0_0|0||:s|0|0|t|t|0|0|s_0_V11_E-1.run.res.10000000:result = 0.0208328082549803541102# D6_1|23456|34|45|567|6|||:0|0_0_1_0_0|0_0|0_0|0_0_0|0|||:t|0|s|0|0|0|s|t/1|23456|34|45|567|6|||:0|0_0_1_0_0|0_0|0_0|0_0_0|0|||:t|0|s|0|0|0|s|t_0_V11_E-1.run.res.10000000:result = 0.0416652289605569243103# D6_s_1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:s|0|t|0|0|t|s|0/1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:s|0|t|0|0|t|s|0_0_V11_E-1.run.res.10000000:result = -0.00694435447490225188104# D6_s_1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:t|0|s|0|0|s|t|0/1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:t|0|s|0|0|s|t|0_0_V11_E-1.run.res.10000000:result = 0.00694435967527374902105# D6_t_1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:s|0|t|0|0|t|s|0/1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:s|0|t|0|0|t|s|0_0_V11_E-1.run.res.10000000:result = 0.00694430532353083625106# D6_t_1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:t|0|s|0|0|s|t|0/1|23456|3|4567|57|7|7||:0|0_0_0_0_1|0|0_1_0_0|0_0|0|0||:t|0|s|0|0|s|t|0_0_V11_E-1.run.res.10000000:result = -0.00694409525342296833107res_d6_mk = {'K3': 0.166672811495946843,108                 'K4': 0.166630234959756984,109                 'L1': cln(0),110                 'L2': cln(0),111                 'L3': 0.0208328082549803541,112                 'L4': cln(1)/48,113                 'L5':  0.0416652289605569243,114                 'L6': cln(1)/24,115                 'L7': 0.,116                 'L8': 0.,117                 'L9': -0.00694435447490225188*s+0.006944359675273749026*t,118                 'L10': 0.00694430532353083625*s+(-0.00694409525342296833)*t,119                 'L11': cln(0),120                 'L12': cln(0),121                 'L13': cln(0),122                 'L14': cln(0),123                 'L15': cln(0),124                 }125for i in sorted(res_d6_kazakov.keys()):126    print i,"\t", (res_d6_kazakov[i].expand()).evalf(),"\n\t",res_d6_mk[i],"\ndelta =", ((res_d6_kazakov[i].expand()).evalf()-res_d6_mk[i]).expand()...

refined_md.py

Source:refined_md.py

1from utility import *2import matplotlib.pyplot as plt3from numpy import linspace4from scipy.integrate import odeint5class Model():6    def __init__(7            self, init_paras, max_t, max_ite, title8    ):9        self.init_paras = init_paras10        self.max_t = max_t11        self.max_ite = max_ite12        self.title = title13        # initial species counts and sojourn times14        self.initital_conditions = {15            "p_s": [self.init_paras['p_s']],16            "p_cln": [self.init_paras['p_cln']],17            "h_s": [self.init_paras['h_s']],18            "h_cln": [self.init_paras['h_cln']],19            "nur_s": [self.init_paras['nur_s']],20            "nur_cln": [self.init_paras['nur_cln']],21            "time": [0.0],22        }23        # propensity functions24        self.propensities = {25            # patient gets colonized through contacts from HCWs26            0: lambda d: self.init_paras['r_hcw_p'] * d["p_s"][-1] * d["h_cln"][-1] / self.init_paras['N_h'],27            # patient gets colonized through contacts from nurses28            1: lambda d: self.init_paras['r_nur_p'] * d["p_s"][-1] * d["nur_cln"][-1] / self.init_paras['N_nur'],29            # HCW gets colonized30            2: lambda d: self.init_paras['r_p_hcw']* d["h_s"][-1] * d["p_cln"][-1] / self.init_paras['N_h'],31            # colonized HCW washes hands to eliminate pathogen32            3: lambda d: self.init_paras['r_hw_hcw'] * d["h_cln"][-1],33            # Nurse gets colonized34            4: lambda d: self.init_paras['r_p_nur']* d["nur_s"][-1] * d["p_cln"][-1] / self.init_paras['N_nur'],35            # colonized Nurse washes hands to eliminate pathogen36            5: lambda d: self.init_paras['r_hw_nur'] * d["nur_cln"][-1],37            # colonized patient is detected38            6: lambda d: self.init_paras['r_det'] * d["p_cln"][-1],39            # patient is regularly removed from the ward40            7: lambda d: self.init_paras['r_rm'] * d["p_cln"][-1],41            # Proportion of admissions already colonized42            8: lambda d: self.init_paras['pro_cln'] * (self.init_paras['r_rm'] * (d["p_s"][-1] + d["p_cln"][-1] +43                        self.init_paras['r_det'] * d["p_cln"][-1]) + self.init_paras['r_det'] * d["p_cln"][-1]),44        }45        # change in species for each propensity46        self.stoichiometry = {47            0: {"p_s": -1, "p_cln": 1,  "h_s": 0,  "h_cln": 0,  "nur_s":0,  "nur_cln":0 },48            1: {"p_s": -1, "p_cln": 1,  "h_s": 0,  "h_cln": 0,  "nur_s":0,  "nur_cln":0 },49            2: {"p_s": 0,  "p_cln": 0,  "h_s": -1, "h_cln": 1,  "nur_s":0,  "nur_cln":0 },50            3: {"p_s": 0,  "p_cln": 0,  "h_s": 1,  "h_cln": -1, "nur_s":0,  "nur_cln":0 },51            4: {"p_s": 0,  "p_cln": 0,  "h_s": 0,  "h_cln": 0,  "nur_s":-1, "nur_cln":1 },52            5: {"p_s": 0,  "p_cln": 0,  "h_s": 0,  "h_cln": 0,  "nur_s":1,  "nur_cln":-1},53            6: {"p_s": 1,  "p_cln": -1, "h_s": 0,  "h_cln": 0,  "nur_s":0,  "nur_cln":0 },54            7: {"p_s": 1,  "p_cln": -1, "h_s": 0,  "h_cln": 0,  "nur_s":0,  "nur_cln":0 },55            8: {"p_s": -1, "p_cln": 1,  "h_s": 0,  "h_cln": 0,  "nur_s":0,  "nur_cln":0 }56        }57    def __call__(self, plot = True,save = True):58        plt.figure(figsize=(10,10), dpi=500)59        fig = plt.gcf()60        fig.suptitle(self.title, fontsize=16)61        axes_p_cln = plt.subplot(311)62        axes_p_cln.set_ylabel("number of infected patients")63        axes_p_cln.set_xlabel('$t$')64        axes_p_cln.set_xlim([0, self.max_t])65        axes_p_cln.set_ylim([0, self.init_paras['N_p']])66        axes_hcw_cln = plt.subplot(312)67        axes_hcw_cln.set_ylabel("number of colonized HCWs")68        axes_hcw_cln.set_xlabel('$t$')69        axes_hcw_cln.set_xlim([0, self.max_t])70        axes_hcw_cln.set_ylim([0, self.init_paras['N_h']])71        axes_nur_cln = plt.subplot(313)72        axes_nur_cln.set_ylabel("number of colonized nurses")73        axes_nur_cln.set_xlabel('$t$')74        axes_nur_cln.set_xlim([0, self.max_t])75        axes_nur_cln.set_ylim([0, self.init_paras['N_nur']])76        # instantiate the epidemic SSA model container77        epidemic = SSAModel(78            self.initital_conditions,79            self.propensities,80            self.stoichiometry81        )82        # instantiate the SSA container with model83        epidemic_generator = SSA(epidemic, self.max_t)84        # simulate and plot 30 trajectories85        trajectories = 086        for trajectory in epidemic_generator.direct():87            axes_p_cln.step(trajectory["time"], trajectory["p_cln"], color="orange")88            axes_hcw_cln.step(trajectory["time"], trajectory["h_cln"], color="orange")89            axes_nur_cln.step(trajectory["time"], trajectory["nur_cln"], color="orange")90            trajectories += 191            if trajectories == self.max_ite:92                break93        # numerical solution using an ordinary differential equation solversir94        t = linspace(0, self.max_t, num=self.max_t*10)95        y0 = (self.init_paras['p_s'], self.init_paras['p_cln'],96              self.init_paras['h_s'], self.init_paras['h_cln'],97              self.init_paras['nur_s'], self.init_paras['nur_cln'])98        solution = odeint(self.differential_SIR, y0, t,99                          args=(self.init_paras['r_hcw_p'], self.init_paras['r_p_hcw'],100                                self.init_paras['r_hw_hcw'],101                                self.init_paras['r_nur_p'], self.init_paras['r_p_nur'],102                                self.init_paras['r_hw_nur'],103                                self.init_paras['r_det'],104                                self.init_paras['r_rm'], self.init_paras['pro_cln']))105        solution = [[row[i] for row in solution] for i in range(6)]106        # plot numerical solution107        axes_p_cln.plot(t, solution[1], color="black")108        axes_hcw_cln.plot(t, solution[3], color="black")109        axes_nur_cln.plot(t, solution[5], color="black")110        fig = plt.gcf()111        if plot:112            plt.show()113        if save:114            fig.savefig(self.title+'.png', dpi=800)115    def differential_SIR(self, n, t,  r_hcw_p, r_p_hcw, r_hw_hcw,  r_nur_p, r_p_nur, r_hw_nur, r_det, r_rm, pro_cln):116        dps_dt = -pro_cln * (r_rm * (n[0] + n[1]) + r_det * n[1]) \117                 - r_nur_p * n[0] * n[5] / self.init_paras['N_nur'] \118                 - r_hcw_p * n[0] * n[3] / self.init_paras['N_h'] + (r_det+r_rm) * n[1]119        dpc_dt = pro_cln * (r_rm * (n[0] + n[1]) + r_det * n[1]) \120                 + r_nur_p * n[0] * n[5] / self.init_paras['N_nur'] \121                 + r_hcw_p * n[0] * n[3] / self.init_paras['N_h'] - (r_det+r_rm) * n[1]122        dhs_dt = -r_p_hcw * n[2] * n[1] / self.init_paras['N_h'] + r_hw_hcw * n[3]123        dhc_dt = r_p_hcw * n[2] * n[1] / self.init_paras['N_h'] - r_hw_hcw * n[3]124        dnurs_dt = -r_p_nur * n[4] * n[1] / self.init_paras['N_nur'] + r_hw_nur * n[5]125        dnurc_dt = r_p_nur * n[4] * n[1] / self.init_paras['N_nur'] - r_hw_nur * n[5]...

hardcoded.py

Source:hardcoded.py

...4import graph_util_ms5import graph_state6import graphine7from rggraphenv.symbolic_functions import cln, log, p8ln43 = log(cln(4)/cln(3))9ONE_LOOP = dict()10from rggraphenv import symbolic_functions11ONE_LOOP[graph_util_ms.from_str("e11|e|:00_aA_aA|00|::::").to_graph_state()] = {"iw": {-1: cln(1)/cln(4)}, "p2": {-1: -cln(1)/cln(8)}, "tau": {-1: -cln(1)/cln(2)}}12ONE_LOOP[graph_util_ms.from_str("e12|e2|e|:00_Aa_aA|00_aA|00|::::").to_graph_state()] = {"log": {-1: cln(1)/cln(4)}}13assert len(ONE_LOOP) == 214TWO_LOOPS = dict()15# TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_Aa_aA|00_aA|00_Aa|aA_aA||::::").to_graph_state()] = {"log": {-2: cln(1)/cln(64), -1: -cln(3)/cln(32)-ln43/cln(64)}}16# TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_aA_aA|00_Aa|00_aA|Aa_Aa||::::").to_graph_state()] = {"log": {-2: cln(3)/cln(128), -1: -cln(3)*ln43/cln(128)-cln(1)/cln(32)}}17# TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_Aa_Aa|00_Aa|00_aA|Aa_Aa||::::").to_graph_state()] = {"log": {-2: cln(3)/cln(128), -1: -cln(3)*ln43/cln(128)-cln(1)/cln(32)}}18TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_Aa_aA|00_aA|00_Aa|aA_aA||::::").to_graph_state()] = {"log": {-2: cln(1)/cln(64), -1: -cln(1)/cln(32)-ln43/cln(64)}}19TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_aA_aA|00_Aa|00_aA|Aa_Aa||::::").to_graph_state()] = {"log": {-2: cln(3)/cln(128), -1: -cln(3)*ln43/cln(128)}}20TWO_LOOPS[graph_util_ms.from_str("e12|e3|e4|44||:00_Aa_Aa|00_Aa|00_aA|Aa_Aa||::::").to_graph_state()] = {"log": {-2: cln(3)/cln(128), -1: -cln(3)*ln43/cln(128)}}21TWO_LOOPS[graph_util_ms.from_str("e12|34|34|e|e|:00_aA_aA|aA_aA|aA_aA|00|00|::::").to_graph_state()] = {"log": {-1: ln43*cln(3)/cln(8)}}22# delete23# TWO_LOOPS[graph_util_ms.from_str("e12|34|34|e|e|:00_Aa_Aa|Aa_Aa|Aa_Aa|00|00|::::").to_graph_state()] = {"log": {-1: ln43*cln(3)/cln(8)}}24TWO_LOOPS[graph_util_ms.from_str("e12|34|34|e|e|:00_aA_aA|aA_aA|Aa_aA|00|00|::::").to_graph_state()] = {"log": {-1: ln43/cln(8)}}25TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_aA_aA|00_aA|aA_aA|aA|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)+ln43)/cln(32)}}26TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_Aa_Aa|00_Aa|Aa_Aa|Aa|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)+ln43)/cln(32)}}27TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_aA_aA|00_aA|Aa_aA|aA|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)-3*ln43)/cln(32)}}28TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_Aa_Aa|00_Aa|aA_Aa|Aa|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)-3*ln43)/cln(32)}}29# delete30# TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_aA_aA|00_Aa|aA_aA|Aa|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (ln43-cln(1))/cln(32)}}31TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_Aa_Aa|00_aA|Aa_Aa|aA|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (ln43-cln(1))/cln(32)}}32# delete33# TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_aA_aA|00_Aa|aA_aA|aA|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)-3*ln43)/cln(32)}}34TWO_LOOPS[graph_util_ms.from_str("e12|e3|34|4|e|:00_Aa_Aa|00_aA|Aa_Aa|Aa|00|::::").to_graph_state()] = {"log": {-2: -cln(1)/cln(32), -1: (cln(1)-3*ln43)/cln(32)}}35# assert len(TWO_LOOPS) == 936# TWO_LOOPS[graph_util_ms.from_str("e12|23|3|e|:00_aA_aA|aA_aA|aA|00|::::").to_graph_state()] = {"iw": {-2: -cln(1)/cln(16), -1: (cln(1)-ln43)/cln(16)},37#                                                                                                "p2": {-2: cln(1)/cln(32), -1: -cln(7)/cln(192)+ln43/cln(16)},38#                                                                                                "tau": {-1: cln(1)/cln(8), -2: cln(1)/cln(8)}}39TWO_LOOPS[graph_util_ms.from_str("e12|23|3|e|:00_aA_aA|aA_aA|aA|00|::::").to_graph_state()] = {"iw": {-2: -cln(1)/cln(16), -1: (cln(1)-ln43)/cln(16)},40                                                                                               "p2": {-2: cln(1)/cln(32), -1: -cln(7)/cln(192)+ln43/cln(16)},41                                                                                               "tau": {-1: -cln(1)/cln(8), -2: cln(1)/cln(8)}}42# TWO_LOOPS[graph_util_ms.from_str("e12|e3|33||:00_aA_aA|00_Aa|aA_aA||::::").to_graph_state()] = {"iw": {-2: cln(1)/cln(64), -1: -cln(3)/cln(32)-ln43/cln(64)},43#                                                                                               "p2": {-2: -cln(3)/cln(256), -1: cln(3)*ln43/cln(256)+cln(67)/cln(1536)},44#                                                                                               "tau": {-1: -cln(1)/cln(8)}}45TWO_LOOPS[graph_util_ms.from_str("e12|e3|33||:00_aA_aA|00_Aa|aA_aA||::::").to_graph_state()] = {"iw": {-2: cln(1)/cln(64), -1: -cln(1)/cln(32)-ln43/cln(64)},46                                                                                                "p2": {-2: -cln(3)/cln(256), -1: cln(3)*ln43/cln(256)+cln(19)/cln(1536)},47                                                                                                "tau": {-1: cln(3)/cln(32)}}48# # assert len(TWO_LOOPS) == 1149# a = TWO_LOOPS[graph_util_ms.from_str("e12|23|3|e|:00_aA_aA|aA_aA|aA|00|::::").to_graph_state()]["p2"][-1]50# b = TWO_LOOPS[graph_util_ms.from_str("e12|e3|33||:00_aA_aA|00_Aa|aA_aA||::::").to_graph_state()]["p2"][-1]/251# print a+b52# exit(1)53def kr1(graph, operation):54    graph = graphine.Graph(map(lambda e: e.copy(fields=graph_state.Fields("00")) if e.is_external() else e, graph))55    if graph.loops_count == 1:56        return ONE_LOOP[graph.to_graph_state()][operation]57    elif graph.loops_count == 2:58        return TWO_LOOPS[graph.to_graph_state()][operation]59    assert False60def kr1_eps(graph, operation):61    result = symbolic_functions.CLN_ZERO...

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