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import numpy as np | |
import sympy as sp | |
from matplotlib import pyplot as plt | |
import mpmath as mp | |
mp.mp.dps = 4000 | |
print(mp.mp) | |
sqrt = mp.sqrt | |
def xsqrta(x, a): |
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import numpy as np | |
import sympy as sp | |
sin, cos = sp.sin, sp.cos | |
k1, k2 = sp.symbols("k1 k2", real=True, positive=True) | |
L1, L2 = sp.symbols("L1 L2", real=True, positive=True) | |
a, p, m= sp.symbols("a p m", real=True, positive=True) | |
theta = sp.symbols("theta") | |
dtheta = sp.symbols("dtheta") |
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import numpy as np | |
import sympy as sp | |
from numpy import linalg as la | |
""" | |
https://mathoverflow.net/questions/425067/block-matrix-reduce-system-for-finite-element-method | |
""" | |
def random_sym_matrix(side): | |
F = np.random.rand(side, side) |
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###################################### | |
# Description # | |
###################################### | |
# | |
# This algorithm finds the solution of an non-linear equation | |
# The equation is the catenary, that is like | |
# h(x) = a * cosh(x/a) | |
# We want to find the value of "a" such that h(x0) = y0 | |
# Where (x0, y0) is known | |
# |
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import tkinter as tk | |
import negocio | |
import numpy as np | |
import matplotlib.ticker as ticker | |
import gi | |
gi.require_version('Gtk', '3.0') | |
from gi.repository import Gtk | |
from matplotlib.figure import Figure | |
from matplotlib.backends.backend_gtk3agg import FigureCanvasGTK3Agg |
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#include <iostream> | |
using namespace std; | |
struct elemento | |
{ | |
int valor; | |
elemento *proximo; | |
}; |
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