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The package will help MIPT students to draw graphs easier

Project description

Documentation Status

Длинное описание, которое когда-то появится

Для сборки:

python -m pip install --upgrade build wheel twine
python -m pip install -r requirements.txt
python -m build --no-isolation
twine upload dist/*

Для установки:

pip install -i https://test.pypi.org/simple/ miptlabs

Чтобы нарисовать что-то:

from miptlabs.plotter import pretty_plot, show
from numpy import linspace

# точки для построения графика
x = linspace(0, 5, 20) 
y = x * x

pretty_plot(x, y)
show()

base_graph

Точки можно просто соединить написав line=True:

pretty_plot(x, y, line=True, legend='$y = x^2$')

with_line_graph

Так как для данный с лаб простое соединение вряд ли подойдет, то в пакете есть разные апроксиматоры Для примера можно взять зависимость координаты от рвемени при равноускоренном движении

from src.miptlabs.plotter import pretty_plot, show
from src.miptlabs.approximators import Polynomial
from numpy import linspace
import numpy as np


# точки для построения графика
x = linspace(0, 5, 20)
y = x * x + np.random.normal(size=x.shape)
ax = pretty_plot(x, y, legend='$x = t^2$ + random')


# Апроксимация
approximator = Polynomial(deg=2)
appr_x, appr_y = approximator.approximate(x, y)
# Вывод формулы для латеха
print(approximator.label('t', 'x'))
# >>> $y = 1.03t^{2}-0.205t+0.158$

№ Построение графика. Параметры говорят сами за себя
pretty_plot(appr_x, appr_y, axes=ax, points=False, line=True,
            legend=approximator.label('t', 'x'), xlabel='t, сек', ylabel='x, м', title='График $x(t)$')

ax.figure.savefig('examples/approx.png')
show()

approx_graph

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