def median(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
2.8457023092205441E+03, -1.3743409994304559E+03,
2.1471357617794106E+02, -1.0848792769803225E+01,
-2.0324959993835455E+03, 9.8002820939498724E+02,
h_coeff_for_skyloc_degr_median(z, y_in), 7.8192633019180278E+00,
4.4177241494019597E+02, -2.1249570923561649E+02,
3.3291629235881828E+01, -1.6959101369918415E+00,
-2.9845727080411464E+01, 1.4304500965970789E+01,
-2.2345651945720704E+00, 1.1358425193111543E-01
]
z_c = 0.7348467697913533
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
1.2465381910224887E+03, -5.3166515192541397E+02,
6.9340006135764682E+01, -2.6231710939190109E+00,
-1.0029085039541454E+03, 4.3711571189478315E+02,
h_coeff_for_skyloc_degr_68lower(z, y_in), 2.5085855756714679E+00,
2.2338279685673797E+02, -9.7242482036654820E+01,
1.3364803208426839E+01, -5.6560098821400118E-01,
-1.4662680185865964E+01, 6.2897138516024587E+00,
-8.4776685692089870E-01, 3.4863045058159514E-02
]
z_c = 0.5806809392180451
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
-8.7376945488669276E+02, 3.8499068441662774E+02,
-5.7938147381113602E+01, 2.9477763885576111E+00,
1.9801903871916835E+02, -6.8567561673040018E+01,
h_coeff_for_skyloc_degr_95upper(z, y_in), -2.8913081360235182E-01,
2.4581078394043146E+01, -1.8181113727943558E+01,
3.6795387069285921E+00, -2.2757997386074180E-01,
-5.0485595056846346E+00, 2.8964450146420528E+00,
-5.2093928063805350E-01, 3.0117752179478430E-02
]
z_c = 0.5907525970680451
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
4.9473683393202504E+02, -2.3927674396837460E+02,
3.6401416102336590E+01, -1.7509090490919390E+00,
-4.6115843319589129E+02, 2.2378917207856858E+02,
h_coeff_for_dl_degr_68upper(z, y_in), 1.7561232704339460E+00,
1.1677906280675273E+02, -5.6730283951842075E+01,
8.9206150121733430E+00, -4.5507126395882125E-01,
-8.7048515477317228E+00, 4.2256233623649493E+00,
-6.6595836858979851E-01, 3.4155791138488212E-02
]
z_c = 0.29044140424135334
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
2.1235503930191753E+03, -1.0622441526685693E+03,
1.7192167644391731E+02, -9.0480834063898570E+00,
-1.6883307861407529E+03, 8.4114930983007343E+02,
h_coeff_for_skyloc_degr_68upper(z, y_in), 7.2457044076971542E+00,
4.0286888928282923E+02, -2.0029922300300294E+02,
3.2552813919403476E+01, -1.7321118409508358E+00,
-2.9578170416747565E+01, 1.4681227526619065E+01,
-2.3859192882702587E+00, 1.2712227881161198E-01
]
z_c = 0.6020666843323308
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
1.3808636388946959E+03, -6.4182596315324656E+02,
9.6286773396675670E+01, -4.6516334615305333E+00,
-9.7059546494459607E+02, 4.5212313686780260E+02,
h_coeff_for_dl_degr_68lower(z, y_in), 3.3460523598831422E+00,
2.0739834073564381E+02, -9.6519310146513959E+01,
1.4606245467534528E+01, -7.1645794447563560E-01,
-1.3752233528992607E+01, 6.3768212839695799E+00,
-9.6166253635520604E-01, 4.7022475138305708E-02
]
z_c = 0.29082312627781953
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
-5.5805132377241542E+01, 2.7982912070311507E+01,
c_coeff_for_dl_degr_95upper(z, y_in), 4.0503889992627751E-01,
-9.7626367059612150E+01, 4.7644773444667621E+01,
-7.1097606197328655E+00, 3.3153342244428641E-01,
4.4147258832646173E+01, -2.1649237407048389E+01,
3.3952527469853560E+00, -1.7259028246107633E-01,
-4.1522877946664138E+00, 2.0365067468384059E+00,
-3.2255957245318534E-01, 1.6682956115293024E-02
]
z_c = 0.2853228215725564
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def median(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
8.0391341572972931E+02, -3.6986896436120571E+02,
5.4020391370719892E+01, -2.4891911926904968E+00,
-6.2895349113882821E+02, 2.9180709926436793E+02,
h_coeff_for_dl_degr_median(z, y_in), 2.0831603590791907E+00,
1.4319372303013498E+02, -6.6556028797141636E+01,
9.9976087684236674E+00, -4.8337991643279565E-01,
-9.8865830515359345E+00, 4.5838856450466103E+00,
-6.8778344406265290E-01, 3.3278950485168934E-02
]
z_c = 0.28863839319097745
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
9.5021318911793060E+02, -3.6797919723945603E+02,
3.9917357950555292E+01, -9.0084079602867906E-01,
-8.3677461947383324E+02, 3.4403469738300157E+02,
h_coeff_for_skyloc_degr_95lower(z, y_in), 1.5121451042414709E+00,
1.9182904263860496E+02, -7.9391546915186979E+01,
1.0098908579415509E+01, -3.7189027540559039E-01,
-1.2610848786693349E+01, 5.1254117146821780E+00,
-6.3408772187359830E-01, 2.2158921390939668E-02
]
z_c = 0.5693628053139097
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [
1.9664199451451052E+03, -9.2900665018717621E+02,
1.4275363274662467E+02, -7.1307773805937140E+00,
-1.3230254859889239E+03, 6.2511885922657279E+02,
h_coeff_for_dl_degr_95lower(z, y_in), 4.8453064965904815E+00,
2.7565837069357849E+02, -1.3005859569566366E+02,
2.0050392228814484E+01, -1.0081232732255501E+00,
-1.8052245880872238E+01, 8.4914871656316997E+00,
-1.3053965295960381E+00, 6.5471847806520600E-02
]
z_c = 0.2876975804417293
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-1.3345301786377374E+02,
1.3088418536752886E+02,
-3.3953513083215789E+01,
2.5947694107776176E+00,
-1.8309060213370934E+01,
-3.2866925890160353E+01,
h_coeff_for_massratio_degr_68lower(z, y_in),
-1.1913852271741385E+00,
1.2570903112305297E+01,
2.4171701192360846E+00,
-2.0048597878981700E+00,
2.0498247169654249E-01,
-8.9864517589466786E-01,
-1.3699375805686786E-01,
1.2995308692929797E-01,
-1.3421154802529145E-02
]
z_c = 0.3535346468954887
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def median(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-3.7757817992650030E+02,
2.4591068045645105E+02,
-5.1696162898553304E+01,
3.4915073025982597E+00,
1.2889369373230198E+02,
g_coeff_for_massratio_degr_median(z, y_in),
2.4019387654367968E+01,
-1.7381871421690605E+00,
-1.6275114415939562E+01,
1.6092818864769374E+01,
-4.1347430418741320E+00,
3.1393459758453446E-01,
9.2635479705335921E-01,
-1.0058780295676080E+00,
2.6607178179250468E-01,
-2.0436547601718758E-02
]
z_c = 0.3612267063992481
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-8.4437424557915210E+02,
4.6296205419751499E+02,
-8.4837369921004580E+01,
5.1555866092458453E+00,
4.1334224276122143E+02,
-2.3375040113495123E+02,
h_coeff_for_massratio_degr_95upper(z, y_in),
-2.7345485375017198E+00,
-7.2037697182364369E+01,
4.1749661868701999E+01,
-8.0162417543974094E+00,
5.0707109977412301E-01,
4.5191974863700475E+00,
-2.6528166859160240E+00,
5.1433851165711530E-01,
-3.2746694526110787E-02
]
z_c = 0.3351163261973684
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [2.2912742300556333E+03,
-1.0636052150470962E+03,
1.5963001353543299E+02,
-7.7233077824021201E+00,
-1.5580518746314297E+03,
7.2797010980585503E+02,
h_coeff_for_massratio_degr_95lower(z, y_in),
5.4268050219803001E+00,
3.3013514807283394E+02,
-1.5495528729579982E+02,
2.3668905207833269E+01,
-1.1730145405658163E+00,
-2.2133760416320285E+01,
1.0413645826849525E+01,
-1.5962850201934202E+00,
7.9522067003381380E-02
]
z_c = 0.35296969958909774
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-6.9359700997068308E+02,
3.9411174715068643E+02,
-7.4590140556169743E+01,
4.6575117044023031E+00,
3.3012442343317576E+02,
g_coeff_for_massratio_degr_68upper(z, y_in),
3.8623111044116328E+01,
-2.4834720982310738E+00,
-5.7547247144940691E+01,
3.5490233646177060E+01,
-7.1431552266075098E+00,
4.6791643350330503E-01,
3.6746087728280221E+00,
-2.2997788029950375E+00,
4.6720200983692450E-01,
-3.0760109154414295E-02
]
z_c = 0.3442742143067669
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [5.2978518208808651E+01,
3.5381997097271729E+01,
-1.7814273749894234E+01,
1.6930538140408400E+00,
-1.3995232030031266E+02,
g_coeff_for_mchirp_degr_68lower(z, y_in),
2.7098874357917797E+00,
-6.0082549942397456E-01,
3.7699014146353036E+01,
-1.0461480521082313E+01,
1.7881891585445819E-01,
8.2514838286962267E-02,
-2.5687116616731340E+00,
7.1959942634471452E-01,
-1.5416449578439462E-02,
-5.2602258193132911E-03
]
z_c = 0.3542061792890977
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def median(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-2.0750761608577693E+02,
1.5861081896955889E+02,
-3.6919876082811854E+01,
2.6648442969478729E+00,
1.8301621903164712E+01,
g_coeff_for_mchirp_degr_median(z, y_in),
1.4407092232126228E+01,
-1.1993976979890366E+00,
6.4866587580750004E+00,
4.4128240621014347E+00,
-2.1525099898846936E+00,
2.0269239106144354E-01,
-5.8157111154880470E-01,
-2.3161911642217925E-01,
1.3457904372290841E-01,
-1.3051264134048779E-02
]
z_c = 0.35060618803120297
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-7.4940405168837333E+02,
4.1416320400132372E+02,
-7.6589013134561313E+01,
4.6950046078692509E+00,
3.5144771234370751E+02,
g_coeff_for_mchirp_degr_95upper(z, y_in),
3.8607902421475437E+01,
-2.4346233912502679E+00,
-5.9325172502605525E+01,
3.5240111878740393E+01,
-6.9137307427265480E+00,
4.4533582759153489E-01,
3.6781340555308777E+00,
-2.2221261181924277E+00,
4.4137155485960733E-01,
-2.8658571007099454E-02
]
z_c = 0.3336238385300752
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_95lower(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [2.6785029941521548E+03,
-1.2618588361220379E+03,
1.9315870111028732E+02,
-9.5982148478495741E+00,
-1.7994059638836768E+03,
g_coeff_for_mchirp_degr_95lower(z, y_in),
-1.3144651776987618E+02,
6.6030779337020533E+00,
3.7832096287001139E+02,
-1.7969650735421376E+02,
2.7872087356015818E+01,
-1.4092234799173582E+00,
-2.5249278928753750E+01,
1.2015602135415349E+01,
-1.8688648020703340E+00,
9.4866689107902857E-02
]
z_c = 0.3536044677233083
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
def quantile_68upper(x_in, y_in, z):
value = 0.0
# coefficients
coeff = [-5.4555388067796264E+02,
3.1808090875470560E+02,
-6.1721618049077570E+01,
3.9375937259508649E+00,
2.3332513376019543E+02,
g_coeff_for_mchirp_degr_68upper(z, y_in),
3.0214569394800513E+01,
-2.0123195562972356E+00,
-3.7580740070400658E+01,
2.5249811915193099E+01,
-5.4063001193342561E+00,
3.7050196080064524E-01,
2.3509719659283626E+00,
-1.6206618718594701E+00,
3.5196408969452619E-01,
-2.4292875687592641E-02
]
z_c = 0.34467532294774433
value = fit_formula.formula_for_uncertainty_degr(coeff, z_c, x_in, y_in, z)
return value
