santiago-salas-v

import win32evtlog
import win32evtlogutil
import win32con
import winerror
import time
import sys
import traceback
from os.path import exists
from pandas import read_csv
from matplotlib import pyplot as plt

santiago-salas-v

from matplotlib import pyplot as plt
from numpy.random import random
from numpy import linspace, log
%matplotlib inline
x = linspace(0.01, 2, 40)
rand_list = (random(len(x))-0.5)
y = log(x-1e-3) + rand_list
y2 = log(x+1e-2*8) + rand_list
x_mid, y_mid = x[int(len(x)/2)], y[int(len(x)/2)]
x_low, y_low = x[3], y[3]

santiago-salas-v

import matplotlib.pyplot as plt
from numpy import finfo, array, sqrt

def y(x):
    return x**3 + 4 * x**2 - 10

max_it = 100
tol = finfo(float).eps
alpha = 1e-4
y_list = []

santiago-salas-v

import matplotlib.pyplot as plt
from matplotlib import patches
from matplotlib.collections import LineCollection
from numpy import finfo, array, sqrt, isnan, concatenate, sin, exp


def secant_ls_3p(y, x_0, tol, max_it=100):
    x_k = x_0
    y_k = y(x_k)
    g_k = 1 / 2 * y_k**2

santiago-salas-v

from numpy import array, exp, real, imag, empty, finfo

# Ref. Press, William H., et al. "Numerical recipes in C++." The art of scientific computing 2 (2007): 1002.

def zroots(a, polish=False):
    eps = 1.0e-14 # a small number
    m = len(a)-1
    roots = empty(len(a)-1, dtype=complex)
    # copy coefficients for successful deflation
    ad = a.copy()

santiago-salas-v

#include<complex>
#include<vector>
#include<limits>

using namespace std;

typedef complex<double> Complex;
//typedef const vector<complex<double>> VecComplex_I;
typedef vector<complex<double>> VecComplex_I;
typedef vector<complex<double>> VecComplex, VecComplex_O;

santiago-salas-v

from numpy import array, ones
from numpy.linalg import inv
import matplotlib.pyplot as plt

# Ref. E. L Cussler - Diffusion mass transfer in fluid systems 2009

m = array([14])

text_data = """
0 14.0153

santiago-salas-v

from numpy import array, lexsort, pi, cos, arccos, log10, complex


def solve_cubic(abcd):
    """ solve cubic polynomial - Tartaglia-Cardano

    ref. Polyanin, Manzhirov Handbook of Mathematics for engineers
    and scientists

    a*x^3+b*x^2+c*x+d=0

santiago-salas-v

santiago-salas-v

from numpy import array, linspace, exp, zeros, diff
from scipy.integrate import odeint, ode
from matplotlib import pyplot as plt
import ctypes  # Needed to set the app icon correctly

r1, r2, r3 = [0.33, 1, -0.33]
d21 = d12 = d23 = d32 = 1e-5 # m^2/s
d13 = d31 = 1/10 * d12
y0 = [0.3, 0.7, 0]