330 lines
6.9 KiB
Plaintext
330 lines
6.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {
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"collapsed": true
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},
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"source": [
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"# Opérations NumPy"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Arithmétique\n",
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"\n",
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"Vous pouvez facilement effectuer un tableau avec l'arithmétique tableau, ou scalaire avec l'arithmétique tableau. Voyons quelques exemples :"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"arr = np.arange(0,10)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0, 2, 4, 6, 8, 10, 12, 14, 16, 18])"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"arr + arr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0, 1, 4, 9, 16, 25, 36, 49, 64, 81])"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"arr * arr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([0, 0, 0, 0, 0, 0, 0, 0, 0, 0])"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"arr - arr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/marci/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:1: RuntimeWarning: invalid value encountered in true_divide\n",
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" if __name__ == '__main__':\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"array([ nan, 1., 1., 1., 1., 1., 1., 1., 1., 1.])"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Avertissement en cas de division par zéro, mais pas une erreur !\n",
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"# Seulement remplacé par nan\n",
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"arr/arr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/marci/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:1: RuntimeWarning: divide by zero encountered in true_divide\n",
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" if __name__ == '__main__':\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"array([ inf, 1. , 0.5 , 0.33333333, 0.25 ,\n",
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" 0.2 , 0.16666667, 0.14285714, 0.125 , 0.11111111])"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Avertissement aussi, mais pas une erreur, remplacé par l'infini\n",
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"1/arr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0, 1, 8, 27, 64, 125, 216, 343, 512, 729])"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"arr**3"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Fonctions universelles de tableau\n",
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"\n",
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"Numpy vient avec beaucoup de [fonctions universelles de tableau](http://docs.scipy.org/doc/numpy/reference/ufuncs.html), qui sont essentiellement juste des opérations mathématiques que vous pouvez utiliser pour effectuer l'opération à travers le tableau. En voici quelques unes :"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0. , 1. , 1.41421356, 1.73205081, 2. ,\n",
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" 2.23606798, 2.44948974, 2.64575131, 2.82842712, 3. ])"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Prendre la racine carrée\n",
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"np.sqrt(arr)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 1.00000000e+00, 2.71828183e+00, 7.38905610e+00,\n",
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" 2.00855369e+01, 5.45981500e+01, 1.48413159e+02,\n",
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" 4.03428793e+02, 1.09663316e+03, 2.98095799e+03,\n",
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" 8.10308393e+03])"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Calcul exponentiel (e^)\n",
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"np.exp(arr)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"9"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.max(arr) # comme arr.max()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"array([ 0. , 0.84147098, 0.90929743, 0.14112001, -0.7568025 ,\n",
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" -0.95892427, -0.2794155 , 0.6569866 , 0.98935825, 0.41211849])"
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]
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},
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"execution_count": 15,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.sin(arr)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/marci/anaconda/lib/python3.5/site-packages/ipykernel/__main__.py:1: RuntimeWarning: divide by zero encountered in log\n",
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" if __name__ == '__main__':\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"array([ -inf, 0. , 0.69314718, 1.09861229, 1.38629436,\n",
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" 1.60943791, 1.79175947, 1.94591015, 2.07944154, 2.19722458])"
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]
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},
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"execution_count": 16,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"np.log(arr)"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Bon travail!\n",
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"\n",
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"C'est tout ce que nous avons besoin de savoir pour l'instant !"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.7.5"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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