Лабы / probnik

import pandas as pd
import numpy as np
import torch

n = [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.75, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.8, 0.85, 0.85, 0.85, 0.85, 0.85, 0.85, 0.85, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 0.95, 1, 1, 1, 1, 1, 1, 1, 1, 1.05, 1.05, 1.05, 1.05, 1.05, 1.05, 1.05, 1.05, 1.05, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1, 1.1]
n_vector = np.array(n)
n_vector = n_vector.reshape((71, 1))
Epsilon = [1.145, 1.140, 1.13, 1.11, 1.09, 1.08, 1.166, 1.16, 1.15, 1.14, 1.12, 1.11, 1.08, 1.19, 1.185, 1.18, 1.16, 1.13, 1.105, 1.095, 1.22, 1.21, 1.20, 1.185, 1.17, 1.144, 1.11, 1.246, 1.24, 1.232, 1.22, 1.205, 1.183, 1.155, 1.12, 1.276, 1.27, 1.26, 1.25, 1.23, 1.21, 1.18, 1.145, 1.135, 1.31, 1.3, 1.29, 1.27, 1.25, 1.23, 1.195, 1.15, 1.345, 1.34, 1.32, 1.30, 1.29, 1.27, 1.245, 1.21, 1.165, 1.382, 1.38, 1.37, 1.36, 1.35, 1.33, 1.305, 1.275, 1.24, 1.18]

Q = [245, 280, 340, 400, 440, 465, 265, 320, 360, 400, 440, 460, 495, 280, 320, 360, 420, 480, 520, 530, 300, 360, 400, 440, 480, 520, 560, 315, 360, 400, 440, 480, 520, 560, 600, 330, 380, 420, 460, 500, 540, 580, 620, 630, 350, 420, 450, 500, 540, 580, 620, 665, 370, 420, 480, 525, 550, 580, 620, 660, 695, 385, 420, 460, 490, 510, 560, 600, 640, 680, 730]
Q_vector = np.array(Q)
Q_vector = Q_vector.reshape((71, 1))

X = np.hstack((n_vector,Q_vector))
X = torch.Tensor(X)

print(X)