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# -*- coding: utf-8 -*-
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"""
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Created on Thu Oct 6 19:17:27 2022
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@author: anna
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"""
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import numpy as np
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import matplotlib.pyplot as plt
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import csv
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from scipy.optimize import curve_fit
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def read_csv(file_name):
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with open(file_name) as file:
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reader = list(csv.reader(file, delimiter=';',
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quotechar=',', quoting=csv.QUOTE_MINIMAL))
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return reader
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def make_latex_table(data):
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table = []
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table.append("\\begin{table}".replace('//', '\\'))
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table.append("\label{}".replace('/', '\\'))
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table.append('\caption{}'.replace('/', '\\'))
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leng = len(data[0])
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stroka = 'c'.join(['|' for _ in range(leng+1)])
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table.append('\\begin{tabular}{'.replace('//', '\\')+stroka+'}')
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table.append('\hline')
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for i in range(len(data)):
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table.append(' & '.join(data[i]) + ' \\\\')
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table.append('\hline')
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table.append("\end{tabular}".replace('/', '\\'))
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table.append("\end{table}".replace('/', '\\'))
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return table
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def make_point_grafic(x, y, xlabel, ylabel, caption, xerr, yerr,
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subplot=None, color=None, center=None, s=15):
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if not subplot:
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subplot = plt
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if type(yerr) == float or type(yerr) == int:
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yerr = [yerr for _ in y]
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if type(xerr) == float or type(xerr) == int:
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xerr = [xerr for _ in x]
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if xerr[1] != 0 or yerr[1] != 0:
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subplot.errorbar(x, y, yerr=yerr, xerr=xerr, linewidth=4,
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linestyle='', label=caption, color=color,
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ecolor=color, elinewidth=1, capsize=3.4,
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capthick=1.4)
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else:
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subplot.scatter(x, y, linewidth=0.005, label=caption,
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color=color, edgecolor='black', s=s)
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# ax = plt.subplots()
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# ax.grid())
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if not center:
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plt.xlabel(xlabel)
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plt.ylabel(ylabel)
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else:
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ax = plt.gca()
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ax.spines['top'].set_visible(False)
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ax.spines['right'].set_visible(False)
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ax.spines['bottom'].set_position('zero')
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ax.spines['left'].set_position('zero')
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ax.set_xlabel(ylabel, labelpad=-180, fontsize=14) # +
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ax.set_ylabel(xlabel, labelpad=-260, rotation=0, fontsize=14)
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def make_line_grafic(xmin, xmax, xerr, yerr, xlabel, ylabel, k, b, caption,
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subplot=None, color=None, linestyle='-'):
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if not subplot:
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subplot = plt
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x = np.arange(xmin, xmax, (xmax-xmin)/10000)
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subplot.plot(x, k*x+b, label=caption, color=color, linewidth=2.4,
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linestyle=linestyle)
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def make_graffic(x, y, xlabel, ylabel, caption_point, xerr, yerr, k=None,
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b=None, filename=None, color=None, koef=[0.9, 1.1]):
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if not color:
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color = ['limegreen', 'indigo']
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make_point_grafic(x, y, xlabel=xlabel,
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ylabel=ylabel, caption=caption_point,
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xerr=xerr, yerr=yerr, subplot=plt, color=color[0])
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if k and b:
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make_line_grafic(xmin=min(x)-1, xmax=max(x)+1, xerr=xerr, yerr=yerr,
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xlabel='', ylabel='', k=k, b=b,
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caption='Theoretical dependence', subplot=plt,
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color='red')
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if type(yerr) == float or type(yerr) == int:
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yerr = [yerr for _ in y]
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k, b, sigma = approx(x, y, b, yerr)
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sigma[0] = abs(k*((sigma[0]/k)**2+(np.mean(yerr)/np.mean(y))**2 +
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(np.mean(xerr)/np.mean(x))**2)**0.5)
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if (b != 0):
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sigma[1] = abs(b*((sigma[1]/b)**2+(np.mean(yerr)/np.mean(y))**2 +
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(np.mean(xerr)/np.mean(x))**2)**0.5)
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else:
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sigma[1] = 0
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make_line_grafic(xmin=min(x)*koef[0], xmax=max(x)*koef[1], xerr=xerr,
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yerr=yerr, xlabel='', ylabel='', k=k, b=b, caption=None,
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subplot=plt, color=color[1])
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plt.legend()
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return k, b, sigma
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def approx(x, y, b, sigma_y, f=None):
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if sigma_y[0] != 0:
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sigma_y = [1/i**2 for i in sigma_y]
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else:
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sigma_y = np.array([1 for _ in y])
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if f is None:
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if b == 0:
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def f(x, k):
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return k*x
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k, sigma = curve_fit(f, xdata=x, ydata=y, sigma=sigma_y)
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sigma = np.sqrt(np.diag(sigma))
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return k, b, [sigma, 0]
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else:
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def f(x, k, b):
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return x*k + b
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k, sigma = curve_fit(f, xdata=x, ydata=y, sigma=sigma_y)
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sigma_b = np.sqrt(sigma[1][1])
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b = k[1]
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k = k[0]
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sigma = np.sqrt(sigma[0][0])
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return k, b, [sigma, sigma_b]
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else:
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k, sigma = curve_fit(f, xdata=x, ydata=y, sigma=sigma_y)
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sigma = np.sqrt(np.diag(sigma))
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b = k[1]
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k = k[0]
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return k, b, sigma
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def find_delivation(data):
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data = np.array(data).astype(np.float)
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s = sum(data)/len(data)
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su = 0
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for i in data:
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su += (i-s)**2
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return (su/(len(data)-1))**0.5
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def make_dic(filename):
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data = np.array(read_csv(filename))
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data = np.transpose(data)
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dic = {}
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for i in range(len(data)):
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dic[data[i][0]] = np.array(data[i][1:]).astype(np.float)
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data = dic
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return data
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def make_fun(A0, T):
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def f(t, k, b):
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return A0/(1+A0*b*t)-k*0*A0*t/T
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return f
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def make_fun_grafic(xmin, xmax, xerr, yerr, xlabel, ylabel, f, k, b, caption,
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subplot=None, color=None):
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if not subplot:
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subplot = plt
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x = np.arange(xmin, xmax, (xmax-xmin)/10000)
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subplot.plot(x, f(x, k, b), label=caption, color=color)
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def make_smth(r):
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if (r == 0):
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s = 'U(nu)_0.csv'
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else:
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s = 'U(nu)_R.csv'
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nu = chr(957)
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eps_u = 2.5/100
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eps_nu = 0.1/100
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data_0 = make_dic(s)
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nu_m_0 = 0
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U_m_0 = 0
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j = 0
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for i in range(len(data_0['U'])):
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if (data_0['U'][i] >= U_m_0):
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U_m_0 = data_0['U'][i]
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nu_m_0 = data_0['nu'][i]
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j = i
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x = data_0['nu']/nu_m_0
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y = data_0['U']/U_m_0
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eps_nu_0 = abs(data_0['nu'][j-1]-data_0['nu'][j+1])/data_0['nu'][j]
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xerr = eps_nu*2**0.5*x
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yerr = eps_u*2**0.5*y
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xlabel = nu + '/ '+nu+'$_m$'
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ylabel = '$U/U_m$'
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if r == 0:
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caption = 'R = 0'
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else:
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caption = 'R = 100 Ом'
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make_point_grafic(x, y, xlabel, ylabel, caption, xerr, yerr)
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plt.grid(True)
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cons = 0.727
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j1 = len(x)
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j2 = len(x)
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for i in range(len(x)-1):
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if y[i] >= cons and y[i+1] <= cons:
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j2 = i
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if y[i] <= cons and y[i+1] >= cons:
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j1 = i
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x1 = x[j1] + (cons - y[j1])*(x[j1+1]-x[j1])/(y[j1+1]-y[j1])
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x2 = x[j2] + (cons - y[j2])*(x[j2+1]-x[j2])/(y[j2+1]-y[j2])
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anna
