import matplotlib.pyplot as plt
import numpy as np

data = [
    [
        0.2459764731981373,
        0.3959689257620598,
        0.3959732217974079,
        0.39584259817898193,
        0.39579974532044626,
        0.395794076384441,
        0.3958077264081723,
        0.39579875646712037,
        0.3958011556927499,
        0.3958033962001042,
    ],
    [
        -0.27365268296889433,
        -0.00046921958193724134,
        2.2715471051926173e-5,
        -7.358616407326934e-5,
        -8.723023031975696e-5,
        -8.153727384807574e-5,
        -9.090152038249144e-5,
        -8.414070625384351e-5,
        -8.612395652507487e-5,
        -8.776483357408882e-5,
    ],
    [
        -0.2735443105544536,
        -0.00028474270293821213,
        8.010969853944339e-5,
        1.778613185088318e-5,
        4.7477053195521535e-5,
        6.325645641669375e-5,
        3.616223928570861e-5,
        5.6782533604415875e-5,
        5.090395966433903e-5,
        4.564750978897081e-5,
    ],
    [
        -0.2735985403453548,
        -0.00030936685630689187,
        0.0001020650955725344,
        7.978835482247426e-5,
        -3.943681093321327e-5,
        -3.438668332045314e-5,
        -2.0189312051055452e-5,
        -2.874604966751626e-5,
        -2.7004076400216626e-5,
        -2.4825341293444048e-5,
    ],
    [
        -0.2735978414571252,
        -0.0003035764863147383,
        0.00010924132501810568,
        0.00015586851063420504,
        -2.4490574906943507e-5,
        -1.7902688270066136e-5,
        1.6650197575129866e-5,
        -7.59094323854459e-6,
        -3.342059771260786e-6,
        2.8747982954158147e-6,
    ],
    [
        -0.2735903179661431,
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        9.381673405162161e-5,
        5.37083752694123e-5,
        -1.5304054572173875e-5,
        -9.256441461102938e-7,
        -6.723313460188507e-6,
        8.254317026779034e-6,
        1.4014954192731466e-6,
        -2.3551311784109075e-6,
    ],
    [
        -0.2735913164499213,
        -0.0003096809009284218,
        9.614021286852292e-5,
        7.174695932898878e-5,
        -1.8277500006158576e-5,
        -4.939460848452093e-6,
        -3.07613414929353e-6,
        6.533050137313978e-6,
        4.1030853825674285e-8,
        -2.2538858418519325e-6,
    ],
    [
        -0.2735934576092922,
        -0.0003078627597422612,
        0.00010028017311203286,
        0.000106444698403374,
        -2.0882908283836876e-5,
        -1.088501621504534e-5,
        2.1767025349062052e-5,
        -3.2850608882029064e-6,
        -2.3900967810464024e-6,
        5.198947351736649e-6,
    ],
    [
        -0.27359291909954975,
        -0.00030836014251955923,
        9.919773853384051e-5,
        9.61302294200106e-5,
        -2.0296397885921635e-5,
        -9.659277290574586e-6,
        9.207541751266035e-6,
        -2.0492995951304493e-6,
        -2.5594252984761923e-6,
        7.261965937477299e-7,
    ],
    [
        -0.2735923872283933,
        -0.0003088364016595735,
        9.815642481170173e-5,
        8.721442142234359e-5,
        -1.962601701765987e-5,
        -8.169525936518873e-6,
        3.1747640369950147e-6,
        5.728083307676712e-7,
        -1.945445256779088e-6,
        -1.066192182985759e-6,
    ],
]

n = [
    [
        0.2459764731981373,
        0.3959689257620598,
        0.3959732217974079,
        0.39584259817898193,
        0.39579974532044626,
        0.395794076384441,
        0.3958077264081723,
        0.39579875646712037,
        0.3958011556927499,
        0.3958033962001042,
    ],
    [
        -0.27365268296889433,
        -0.00046921958193724134,
        2.2715471051926173e-5,
        -7.358616407326934e-5,
        -8.723023031975696e-5,
        -8.153727384807574e-5,
        -9.090152038249144e-5,
        -8.414070625384351e-5,
        -8.612395652507487e-5,
        -8.776483357408882e-5,
    ],
    [
        -0.2735443105544536,
        -0.00028474270293821213,
        8.010969853944339e-5,
        1.778613185088318e-5,
        4.7477053195521535e-5,
        6.325645641669375e-5,
        3.616223928570861e-5,
        5.6782533604415875e-5,
        5.090395966433903e-5,
        4.564750978897081e-5,
    ],
    [
        -0.2735985403453548,
        -0.00030936685630689187,
        0.0001020650955725344,
        7.978835482247426e-5,
        -3.943681093321327e-5,
        -3.438668332045314e-5,
        -2.0189312051055452e-5,
        -2.874604966751626e-5,
        -2.7004076400216626e-5,
        -2.4825341293444048e-5,
    ],
    [
        -0.2735978414571252,
        -0.0003035764863147383,
        0.00010924132501810568,
        0.00015586851063420504,
        -2.4490574906943507e-5,
        -1.7902688270066136e-5,
        1.6650197575129866e-5,
        -7.59094323854459e-6,
        -3.342059771260786e-6,
        2.8747982954158147e-6,
    ],
    [
        -0.2735903179661431,
        -0.00031160663209994777,
        9.381673405162161e-5,
        5.37083752694123e-5,
        -1.5304054572173875e-5,
        -9.256441461102938e-7,
        -6.723313460188507e-6,
        8.254317026779034e-6,
        1.4014954192731466e-6,
        -2.3551311784109075e-6,
    ],
    [
        -0.2735913164499213,
        -0.0003096809009284218,
        9.614021286852292e-5,
        7.174695932898878e-5,
        -1.8277500006158576e-5,
        -4.939460848452093e-6,
        -3.07613414929353e-6,
        6.533050137313978e-6,
        4.1030853825674285e-8,
        -2.2538858418519325e-6,
    ],
    [
        -0.2735934576092922,
        -0.0003078627597422612,
        0.00010028017311203286,
        0.000106444698403374,
        -2.0882908283836876e-5,
        -1.088501621504534e-5,
        2.1767025349062052e-5,
        -3.2850608882029064e-6,
        -2.3900967810464024e-6,
        5.198947351736649e-6,
    ],
    [
        -0.27359291909954975,
        -0.00030836014251955923,
        9.919773853384051e-5,
        9.61302294200106e-5,
        -2.0296397885921635e-5,
        -9.659277290574586e-6,
        9.207541751266035e-6,
        -2.0492995951304493e-6,
        -2.5594252984761923e-6,
        7.261965937477299e-7,
    ],
    [
        -0.2735923872283933,
        -0.0003088364016595735,
        9.815642481170173e-5,
        8.721442142234359e-5,
        -1.962601701765987e-5,
        -8.169525936518873e-6,
        3.1747640369950147e-6,
        5.728083307676712e-7,
        -1.945445256779088e-6,
        -1.066192182985759e-6,
    ],
]
n = [10,100,200, 500,1000,2000,5000,7500,10000,15000];


for n_o in range(len(data)):
    # plt.scatter([n_o] * len(data[n_o]), data[n_o])
    plt.plot(n, data[n_o])
plt.show()