#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Date : 2026-01-01
# Author : Lancelot PINCET
# GitHub : https://github.com/LancelotPincet
# Library : funcLP
# %% Libraries
import numpy as np
from funclp import Function, Parameter, ufunc
# %% Parameters
def a(res, *args) :
return np.nanmean(np.gradient(res,args[0]))/2
def b(res, *args) :
return np.nanmean(np.gradient(res-a(res,args[0])*args[0]**2,args[0]))
def c(res, *args) :
return np.nanmean(res - a(res,args[0])*args[0]**2 - b(res,args[0])*args[0])
# %% Function
[docs]
class Polynomial2(Function):
@ufunc(
variables=["x"],
parameters=[
Parameter("a", 1., estimate=a),
Parameter("b", 0., estimate=b),
Parameter("c", 0., estimate=c),
],
)
def function(x, /, a=1., b=0., c=0.) :
return a * x**2 + b * x + c
# Parameters derivatives
@ufunc()
def d_a(x, /, a, b, c) :
return x**2
@ufunc()
def d_b(x, /, a, b, c) :
return x
@ufunc()
def d_c(x, /, a, b, c) :
return 1
# Other attributes
@property
def roots(self) :
return np.roots([self.a,self.b,self.c])
@property
def delta(self) :
return self.b**2 - 4* self.a *self.c
# %% Test function run
if __name__ == "__main__":
from corelp import debug
from funclp import plot
import numpy as np
debug_folder = debug(__file__)
# Inputs
variables = (
np.linspace(-10, 10, 1000),
)
parameters = dict()
# Plot function
instance = Polynomial2()
plot(instance, debug_folder, variables, parameters)