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AdAdjust

Package allowing to fit any mathematical function to (for now 1-D only) data.

Installation

pip install adadjust

Usage

from adadjust import Function
import numpy as np
import matplotlib.pyplot as plt
plt.rcParams.update({"text.usetex": True})  # Needs texlive installed

nsamples = 1000
a = 0.3
b = -10
xstart = 0
xend = 1
noise = 0.01
x = np.linspace(xstart, xend, nsamples)
y = a * x ** 2 + b + np.random.normal(0, noise, nsamples)


def linfunc(xx, p):
    return xx * p[0] + p[1]


def square(xx, p):
    return xx ** 2 * p[0] + p[1]


func = Function(linfunc, "$a \\times p[0] + p[1]$")
func2 = Function(square, "$a^2 \\times p[0] + p[1]$")

params = func.fit(x, y, np.array([0, 0]))[0]
rr = func.compute_rsquared(x, y, params)

params2 = func2.fit(x, y, np.array([0, 0]))[0]
rr2 = func2.compute_rsquared(x, y, params2)

table = Function.make_table(
    [func, func2], [params, params2], [rr, rr2], caption="Linear and Square fit", path_output="table.pdf"
)
table.compile()
Function.plot(x, [func, func2], [params, params2], y=y, rsquared=[rr, rr2])
plt.gcf().savefig("plot.pdf")

NOTE : to have pretty gaphs, put the line plt.rcParams.update({"text.usetex": True}) just after you imported adadjust. This requiers that you have TexLive full installed on your computer.

The result will be :