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2024-11-09 11:24:25 +03:00

124 KiB

In [1]:
# %load /home/glebi/git/experiment-automation/processing_tools.py
import numpy as np
from scipy.optimize import curve_fit
import pandas as pd

import matplotlib.pyplot as plt
import matplotlib
import scienceplots

plt.style.use(['science', 'russian-font'])

matplotlib.rcParams.update({
    'figure.figsize': [6, 4],
    'savefig.facecolor': 'white',
    'figure.dpi': 150.0,
    'font.size': 12.0,
})
In [2]:
data = np.loadtxt("data.csv", delimiter=",")
Utp, R2 = data.T # mV, Ohm

f = 622 # Hz
c = 41e-6 # V/K
T0 = 25 + 273.15 # K
T = Utp*1e-3/c + T0
T_sigma = .01*1e-3/c

R1 = 220 # Ohm
R3 = 560 # Ohm
l = 40e-3 # m
S = 4.1e-3 * 4.15e-3 # m^2
sigma_x = (l / S) * (R1 / R3) * (1 / R2)
In [3]:
plt.errorbar(T, sigma_x, xerr=T_sigma, yerr=0, fmt=".", markersize=1.5, label="Экспериментальные данные")
plt.xlabel("Температура, K")
plt.ylabel(r"Удельная электропроводность $\sigma_x$, 1/м$\cdot$Ом")

# plt.yscale("log")
plt.legend()
plt.savefig("sigmaOnT.png")
plt.show()