{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "*ENSAM-Bordeaux, Mathématiques et informatique. Date : le 11/10/19. Auteur : Éric Ducasse. Version : 1.0*" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "
*On pourra faire exécuter ce notebook cellule par cellule $\\left(\\mathtt{Maj+Entrée}\\right)$ ou intégralement par $\\mathtt{\\;Kernel\\rightarrow Restart\\;\\&\\;Run\\;All}$.*
" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "import sympy as sb\n", "sb.init_printing()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "print(f\"Version de sympy : {sb.__version__}\") " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "# Déclaration de symboles" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Noms de symboles" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "a = sb.symbols(\"a\") ; a" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "b,c,d = sb.symbols(\"b,c,d\") ; c" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "a_0,a_1,a_2 = sb.symbols(\"a_0^*,a_1^*,a_2^*\") ; a_2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "a_3 = sb.symbols(\"a_3^[c]\") ; a_3" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Hypothèses sur les symboles" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *Non nul*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "y = sb.symbols(\"y\") # Symbole sans hypothèse\n", "(sb.Eq(y,0),sb.Ne(y,0))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = sb.symbols(\"x\", zero=False)\n", "(sb.Eq(x,0),sb.Ne(x,0))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x.assumptions0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *Réels*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = sb.symbols(\"x\", real=True)\n", "x.assumptions0" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = sb.symbols(\"x\", nonzero=True) # Réel non nul\n", "x.assumptions0" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = sb.symbols(\"x\", positive=True) # Strictement positif\n", "x.assumptions0" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "x = sb.symbols(\"x\", negative=True) # Strictement positif\n", "(x.equals(0),x.is_zero,x.is_real,x.is_nonzero,x.is_nonpositive)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *Entiers*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "i,j,k = sb.symbols(\"i,j,k\", integer=True)\n", "(sb.sin(sb.pi*k),sb.cos(sb.pi*k))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "((i+j).is_integer,(i-j).is_integer,(i*j).is_integer)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "m = sb.symbols(\"m\", integer=True, positive=True)\n", "m.assumptions0" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "(m > 0, m+1 > 0, 2*m > 0)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *Complexe*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "z = sb.symbols(\"z\", complex=True)\n", "z.assumptions0" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "#### *Imaginaire pur*" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "b = sb.symbols(\"b\", imaginary=True)\n", "b.conjugate()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 2 }