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methcalchimplugin-autotooltip__default plugin-autotooltip_bigCalculation methods applied to chemistry

Synopsis (english)

Mathematical prerequisites

Programming bases and tools

* Python programming language * LearnPython.org interactive tutorial with code execution * DataCamp free course "Intro to Python for Data Science" * Python 3 Tutorial, interactive, with code use in web browser * MOOCs (massive open online courses) :
5 Occurrences trouvées, Dernière modification:
ps://www.coursera.org/course/interactivepython|An Introduction to Interactive Programming in Python (Beginners)]... ] (Coursera) * [[https://www.edx.org/course/introduction-computer-science-mitx-6-00-1x-9|Introduction to Computer Science and Programming Using Python]] (edX) * [[wp>... l/norvig.com/ipython/Probability.ipynb|A Concrete Introduction to Probability (using Python)]] ==== MOOCs ====
root-finding_algorithmplugin-autotooltip__default plugin-autotooltip_bigRoot findings : equations f(x) = 0

* Polynomial equations : Bairstow's method is an efficient algorithm for finding the roots of a real polynomial of arbitrary degree * Polynomials in NumPy * polynomial module, including polyroots(c) to compute the roots of a polynomial.

* Bisection method (dichotomy) : very simple and robust method, but relatively slow. It assumes continuity of the function, and obtain one roots. The algorithm is based on a
1 Occurrences trouvées, Dernière modification:
finding an nonlinear sets of equations * 9.0 Introduction * 9.1 Bracketing and Bisection * 9.2 Seca
system_of_linear_equationsplugin-autotooltip__default plugin-autotooltip_bigSystem of linear equations

Time_complexityi.e. Theory

* System_of_linear_equations * Gaussian_elimination, Gauss and Gauss-Jordan eliminations (diagonalization, triangularization) * Pivot_element, pivoting * LU_decomposition * Triangular_matrix

* Chapter 2 in the book “Numerical Recipes” : * 2.0 Introduction * 2.1 Gauss-Jordan Elimination
1 Occurrences trouvées, Dernière modification:
ter 2 in the book "Numerical Recipes" : * 2.0 Introduction * 2.1 Gauss-Jordan Elimination * 2.2 Gaus
numerical_integrationplugin-autotooltip__default plugin-autotooltip_bigNumerical integration

Error estimation

* Equally spaced methods : * Numerical_integration * Trapezoidal_rule * Newton–Cotes_formulas * Simpson's rule and composite Simpson's rule

* If intervals between interpolation points vary : * Gaussian_quadrature

* Chapter 4 in the book “Numerical Recipes” : Integration of Functions * 4.0 Introduction * 4.1 Classical Formulas for Equally Spaced Abscissas
1 Occurrences trouvées, Dernière modification:
cal Recipes” : Integration of Functions * 4.0 Introduction * 4.1 Classical Formulas for Equally Spaced A
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• Dernière modification: 2020/10/02 14:58
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