teaching:methcalchim:start

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teaching:methcalchim:start [2020/09/01 09:52] – [Miscellaneous] villersdteaching:methcalchim:start [2021/02/23 09:42] – [References] villersd
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     * Diagonalisation and triangularisation     * Diagonalisation and triangularisation
     * LU decomposition : factorization in triangular matrices     * LU decomposition : factorization in triangular matrices
-  * [[numerical_integration|Numerical intégration]] (integrals) 
-    * Simpson method and gaussian quadratures 
   * [[root-finding_algorithm|Root findings :  equations f(x) = 0]]   * [[root-finding_algorithm|Root findings :  equations f(x) = 0]]
     * Polynomial equations     * Polynomial equations
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     * Secant method, Regula falsi     * Secant method, Regula falsi
     * Newton-Raphson method     * Newton-Raphson method
 +  * [[numerical_integration|Numerical intégration]] (integrals)
 +    * Simpson method and gaussian quadratures
 +
 +<note tip>
 +Learning outcomes :
 +  * Systems of linear equations
 +    * failing of the theoretical way to solve a linear system using determinant and cofactors (np complexity)
 +    * triangularisation and diagonalisation principles : algorithm and complexity
 +    * "divide by zero" errors and pivot solutions
 +    * extension towards the matrix inversion
 +    * lower-upper LU decomposition and complexity (N³ for the decomposition step and N² for substitution step). How to solve systems with varying independant vectors
 +    * special matrix require special algorithms : tridiagonal matrix algorithm (Thomas algorithm)
 +  * Root findings
 +    * Bisection method (dichotomy) : simple and robust algorithm, invariant loop, slow convergence
 +    * iterative transformation x = f(x), convergence and divergence situations
 +    * secant and regula falsi methods, Convergence Criterion of the Fixed Point Method
 +    * Newton-Raphson method (use of derivatives), quadratic convergence, failure, tolerance and stop condition
 +    * Van Wijngaardeb-Dekker-Brent method ("black box" in numerical packages)
 +    * Roots of polynomials and Bairstow's method
 +  * Numerical intégration
 +    * Equally Spaced methods (trapezoidal, Simpson), accuracy, error dependance,...
 +    * Gaussian Quadratures and orthogonal polynomials (special integrals, scale transformations,  error estimates,...)
 +</note>
  
 ==== Classical numerical methods ==== ==== Classical numerical methods ====
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   * chemistry   * chemistry
     * misc docs :     * misc docs :
-      * [[https://pdfs.semanticscholar.org/3161/89e419212794e74bf83442f65de96b5320ba.pdf|Extraction of chemical  +      * [[https://pdfs.semanticscholar.org/3161/89e419212794e74bf83442f65de96b5320ba.pdf|Extraction of chemical structures and reactions from the literature]] 
-structures and reactions from the literature]]+  * Blog articles 
 +    * [[https://py.plainenglish.io/linear-regression-in-plain-python-3b20bb56b31d|Simple Linear Regression Explained With Python - Explained in details which are easy to understand]] Arjan de Haan, Medium, Jan 23 (+ [[https://github.com/Vepnar/Script-Collection/blob/master/linear-regression/Linear%20regression.ipynb|jupyter notebook]]) 
  
  
  • teaching/methcalchim/start.txt
  • Dernière modification : 2023/04/12 10:08
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