Modules

Summary

module truncated documentation
__init__ module ensae_teaching_cs Main file source on GitHub
__init__ module ensae_teaching_cs.automation Shortcuts for automation source on GitHub
__init__ module ensae_teaching_cs.automation_students Shortcuts for automation_students source on GitHub
__init__ module ensae_teaching_cs.data shortcuts for data source on GitHub
__init__ module ensae_teaching_cs.encrypted shortcuts for encrypted source on GitHub
__init__ module ensae_teaching_cs.faq @breif shortcuts for FAQ source on GitHub
__init__ module ensae_teaching_cs.helpers Shortcuts for helpers source on GitHub
__init__ module ensae_teaching_cs.homeblog Shortcuts for homeblog Some shortcuts I use for windows. Launch Scite: :: set CURRENT=%~dp0 set PYTHONPATH=%CURRENT%__home_GitHubpyquickhelpersrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubpyquickhelpersrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubjyquickhelpersrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubpyensaesrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubpyrsslocalsrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubpymmailssrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubensae_teaching_cssrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubmlstatpysrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubjupytalksrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubcode_beatrixsrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubactuariat_pythonsrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubensae_projectssrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubpysqllikesrc set PYTHONPATH=%PYTHONPATH%;%CURRENT%__home_GitHubteachpyxsrc start wscitescite.exe source on GitHub
__init__ module ensae_teaching_cs.ml Shortcuts for ML source on GitHub
__init__ module ensae_teaching_cs.pythonnet Uses pythonnet. .. faqref:: :tag: windows :title: Unhandled Exception: System.IO.FileLoadException when using Python.Runtime.dll with Python 3.5) When running for the first time on Python 3.5, the following error came up:: Unhandled Exception: System.IO.FileLoadException: Could not load file or assembly ‘file:///<apath>Python.Runtime.dll’ or one of its dependencies. Operation is not supported. (Exception from HRESULT: 0x80131515) —> System.NotSupportedException: An attempt was made to load an assembly from a network location which would have caused the assembly to be sandboxed in previous versions of the .NET Framework. This release of the .NET Framework does not enable CAS policy by default, so this load may be dangerous. If this load is not intended to sandbox the assembly, please enable the loadFromRemoteSources switch. See http://go.microsoft.com/fwlink/?LinkId=155569 for more information. — End of inner exception stack trace — at System.Reflection.RuntimeAssembly._nLoad(AssemblyName fileName, String codeBase, Evidence assemblySecurity, RuntimeAssembly locationHint, StackCrawlMark& stackMark, IntPtr pPrivHostBinder, Boolean throwOnFileNotFound, Boolean forIntrospection, Boolean suppressSecurityChecks) at System.Reflection.RuntimeAssembly.InternalLoadAssemblyName(AssemblyName assemblyRef, Evidence assemblySecurity, RuntimeAssembly reqAssembly, StackCrawlMark& stackMark, IntPtr pPrivHostBinder, Boolean throwOnFileNotFound, Boolean forIntrospection, Boolean suppressSecurityChecks) at System.Reflection.RuntimeAssembly.InternalLoadFrom(String assemblyFile, Evidence securityEvidence, Byte[] hashValue, AssemblyHashAlgorithm hashAlgorithm, Boolean forIntrospection, Boolean suppressSecurityChecks, StackCrawlMark& stackMark) at System.Reflection.Assembly.LoadFrom(String assemblyFile) at clrModule.PyInit_clr() In that case, I suggest to get the source at sdpython/pythonnet and to compile them with VS 2015 on your machine. It will import the missing DLL which I’m still trying to find out. The DLL was compiled on an Azure Virtual Machine. source on GitHub
__init__ module ensae_teaching_cs.special Shortcuts to special .. _l-almost_reusable: List of almost reusable algorithms implemented in this module +++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++ * tsp_kruskal_algorithm(): TSP * draw_line(): Bresenham algorithm (line) * draw_ellipse(): Bresenham algorithm (ellipse) * distance_haversine(): distance of Haversine * bellman(): shortest paths in a graph with Bellman-Ford * connected_components(): computes the connected components * graph_degree(): computes the degree of each node in a graph degree * GraphDistance: computes a distance between two graphs (acyclic), see Distance between two graphs * resolution_sudoku(): solves a sudoku source on GitHub
__init__ module ensae_teaching_cs.td_1a Shortcuts to td1a source on GitHub
__init__ module ensae_teaching_cs.td_2a Shortcuts for td_2a source on GitHub
american_cities module ensae_teaching_cs.tests.american_cities Function to test others functionalities source on GitHub
buildkeywords module ensae_teaching_cs.homeblog.buildkeywords Contains the main function to published my blog (http://www.xavierdupre.fr/blog). executed: source on GitHub
buildrss module ensae_teaching_cs.homeblog.buildrss About RSS source on GitHub
categories_to_integers module ensae_teaching_cs.ml.categories_to_integers Implements a transformation which can be put in a pipeline to transform categories in integers. source on GitHub
classiques module ensae_teaching_cs.td_1a.classiques quelques fonctions à propos de la première séance source on GitHub
clean_python_script_before_exporting_outside module ensae_teaching_cs.homeblog.clean_python_script_before_exporting_outside Too old to remember what it is needed source on GitHub
coding_party1_velib module ensae_teaching_cs.coding_party.coding_party1_velib Une solution au problème proposée : Reconstruction de trajectoire velib source on GitHub
colorsdef module ensae_teaching_cs.helpers.colorsdef Definition of colors source on GitHub
competitions module ensae_teaching_cs.ml.competitions Compute metrics in for a competition source on GitHub
construction_classique module ensae_teaching_cs.td_1a.construction_classique Quelques constructions classiques pour éviter de recoder des variantes d’algorithmes. classiques. source on GitHub
copyfile module ensae_teaching_cs.homeblog.copyfile Copy files source on GitHub
corde module ensae_teaching_cs.special.corde Simulates a string which is falling but tied by its extremities. See Simulation d’une corde qui chute. source on GitHub
crypt_helper module ensae_teaching_cs.data.crypt_helper Data for competitions source on GitHub
custom_magics module ensae_teaching_cs.mypython.custom_magics An example of a custom magic for IPython. source on GitHub
data1a module ensae_teaching_cs.data.data1a Data mostly for the first year. source on GitHub
data_helper module ensae_teaching_cs.data.data_helper Helpers to get data including in the module itself. source on GitHub
datacpt module ensae_teaching_cs.data.datacpt Data for competitions source on GitHub
datasql module ensae_teaching_cs.data.datasql Example of databases source on GitHub
dataweb module ensae_teaching_cs.data.dataweb Data from the web source on GitHub
datazips module ensae_teaching_cs.data.datazips Data mostly for the first year. source on GitHub
discours_politique module ensae_teaching_cs.td_1a.discours_politique Retrive political speeches from Internet source on GitHub
edit_distance module ensae_teaching_cs.td_1a.edit_distance edit distance source on GitHub
einstein_prolog module ensae_teaching_cs.special.einstein_prolog This programs solves Einstein’s riddle ou en Français Intégramme. The algorithm is based on logic and its clause. source on GitHub
elections module ensae_teaching_cs.special.elections Contains a class to process elections results (France) source on GitHub
faq_cvxopt module ensae_teaching_cs.faq.faq_cvxopt Quelques problèmes récurrents avec CVXOPT. source on GitHub
faq_cython module ensae_teaching_cs.faq.faq_cython Cython helpers source on GitHub
faq_hadoop module ensae_teaching_cs.faq.faq_hadoop Quelques questions autour de Hadoop source on GitHub
faq_jupyter module ensae_teaching_cs.faq.faq_jupyter Quelques problèmes récurrents avec Jupyter. source on GitHub
faq_jupyter_helper module ensae_teaching_cs.faq.faq_jupyter_helper Helpers for jupyter, inspired from nbopen.py source on GitHub
faq_matplotlib module ensae_teaching_cs.faq.faq_matplotlib Quelques problèmes récurrents avec matplotlib. source on GitHub
faq_pandas module ensae_teaching_cs.faq.faq_pandas Quelques problèmes récurrents avec pandas. source on GitHub
faq_python module ensae_teaching_cs.faq.faq_python Quelques questions d’ordre général autour du langage Python. source on GitHub
faq_web module ensae_teaching_cs.faq.faq_web A few functions about scrapping source on GitHub
filefunction module ensae_teaching_cs.homeblog.filefunction Helpers for files source on GitHub
filename_helper module ensae_teaching_cs.homeblog.filename_helper Helpers around file names. source on GitHub
flask_helper module ensae_teaching_cs.td_1a.flask_helper Helpers for Flask source on GitHub
ftp_publish_helper module ensae_teaching_cs.automation.ftp_publish_helper Helpers to publish the documentation of python to a website source on GitHub
geo_helper module ensae_teaching_cs.helpers.geo_helper helpers about longitude, latitude source on GitHub
geometry_point module ensae_teaching_cs.special.geometry_point Defines a point in N-dimension source on GitHub
geometry_polygone module ensae_teaching_cs.special.geometry_polygone defines a polyline source on GitHub
geometry_segment module ensae_teaching_cs.special.geometry_segment Defines a segment source on GitHub
git_helper module ensae_teaching_cs.automation_students.git_helper Some automation helpers to grab mails from students about projects. source on GitHub
graph_distance module ensae_teaching_cs.special.graph_distance First approach for a edit distance between two graphs See Distance between two graphs. source on GitHub
graphviz_helper module ensae_teaching_cs.helpers.graphviz_helper graphviz helper source on GitHub
gutenberg module ensae_teaching_cs.data.gutenberg Link to data from Gutenberg, provides an automated way to get the data from this website. Some data may be replicated here to unit test notebooks. source on GitHub
hermionne module ensae_teaching_cs.special.hermionne Implémentation de la résolution de l’énigme d’Hermionne (Harry Potter tome 1) source on GitHub
hermionne_classes module ensae_teaching_cs.special.hermionne_classes Implémentation de la résolution de l’énigme d’Hermionne (Harry Potter tome 1) avec des classes. logique. source on GitHub
image_helper module ensae_teaching_cs.helpers.image_helper image helpers source on GitHub
image_synthese_base module ensae_teaching_cs.special.image.image_synthese_base définition des objets permettant de construire une image de synthèse source on GitHub
image_synthese_facette module ensae_teaching_cs.special.image.image_synthese_facette définition d’une facette source on GitHub
image_synthese_facette_image module ensae_teaching_cs.special.image.image_synthese_facette_image image et synthèse source on GitHub
image_synthese_phong module ensae_teaching_cs.special.image.image_synthese_phong implémentation du modèle d’illumination de Phong source on GitHub
image_synthese_scene module ensae_teaching_cs.special.image.image_synthese_scene définition d’une scène source on GitHub
image_synthese_sphere module ensae_teaching_cs.special.image.image_synthese_sphere définition d’une sphère source on GitHub
interro_motif module ensae_teaching_cs.automation_students.interro_motif Retrieve python files and run them. source on GitHub
jenkins_helper module ensae_teaching_cs.automation.jenkins_helper Set up a jenkins server with all the necessary job source on GitHub
keras_mnist module ensae_teaching_cs.examples.keras_mnist Taken from mnist_cnn.py Trains a simple convnet on the MNIST dataset. Gets to 99.25% test accuracy after 12 epochs (there is still a lot of margin for parameter tuning). 16 seconds per epoch on a GRID K520 GPU. source on GitHub
latex2html module ensae_teaching_cs.homeblog.latex2html Convert a short latex script into an image source on GitHub
latex_file module ensae_teaching_cs.homeblog.latex_file Ths file contains some functions to extract pieces of codes from a latex file source on GitHub
latex_helper module ensae_teaching_cs.homeblog.latex_helper Various function about processing latex file source on GitHub
latex_svg_gif module ensae_teaching_cs.homeblog.latex_svg_gif Svg, Latex source on GitHub
mail_helper module ensae_teaching_cs.automation_students.mail_helper Some automation helpers to grab mails from student about project. source on GitHub
matplotlib_helper_xyz module ensae_teaching_cs.helpers.matplotlib_helper_xyz scatter plots source on GitHub
modifypost module ensae_teaching_cs.homeblog.modifypost Helpers which modify a post. source on GitHub
module_backup module ensae_teaching_cs.automation.module_backup backup the list of modules source on GitHub
modules_documentation module ensae_teaching_cs.automation.modules_documentation Customize a Windows Setup for these teachings source on GitHub
notebook_test_helper module ensae_teaching_cs.automation.notebook_test_helper Some automation helpers to test notebooks and check they are still working fine. source on GitHub
numpys module ensae_teaching_cs.td_1a.numpys Quelques constructions classiques pour éviter de recoder des variantes d’algorithmes. classiques. source on GitHub
optimisation_contrainte module ensae_teaching_cs.td_1a.optimisation_contrainte quelques fonctions sur l’optimisation quadratique avec contraintes source on GitHub
pandas_helper module ensae_teaching_cs.pandas_helper Collection of function to help with pandas source on GitHub
parallel_thread module ensae_teaching_cs.td_2a.parallel_thread Ce fichier contient un exemple qui permet d’exécuter plusieurs threads. source on GitHub
postclassification module ensae_teaching_cs.homeblog.postclassification Helpers for blog classification source on GitHub
program_helper module ensae_teaching_cs.homeblog.program_helper Various function about programs such as guessing the language of a code source on GitHub
projects_helper module ensae_teaching_cs.automation_students.projects_helper A couple of functons which automates everything. source on GitHub
projects_repository module ensae_teaching_cs.automation_students.projects_repository Some automation helpers to grab mails from students about their projects. source on GitHub
propagation_epidemic module ensae_teaching_cs.special.propagation_epidemic Simple simulation of an epidemic. It makes a couple of assumption on how the disease is transmitted and its effect on a person. The user can specify many parameters. source on GitHub
puzzle_girafe module ensae_teaching_cs.special.puzzle_girafe Fonctions, classes pour résoudre un puzzle à 9 pièces disposé en carré 3x3. Voir Résolution d’un puzzle. source on GitHub
py2html module ensae_teaching_cs.homeblog.py2html Mark-up Python code file using HTML for syntax highlighting. Syntax highlighting rules are in the spirit of IDLE. Unless the -r 0 option is used it will also format the code by applying some of the PEP8 spacing guidelines to expressions and assignments. For those that want a GUI you can try py2htmTk.pyw - (it’s minimal but functional). :: USAGE in command line mode: py2html [options] [-i filename]|-I] OPTIONS: -h Print this command line summary –help Print more detailed help on styles and revision info. -o filename Output file (default is “py2html.html”) -i filename Source file. See -I. -p filename HTML page template (must include a %s for inserting the code). If not specified then a default is used. -s filename Use a style-file otherwise use built in styles (see –help for details) -r 0|1|2 Reformat expressions and definitions. -r 0 No formatting -r 1 Format as a = 3+4; b = [1, 2, 3] (default) -r 2 Format as a = 3 + 4; b = [1 , 2 , 3] -R Replace newlines with <br>, tabs and multi-spaces with &nbsp; -B Just make a block (ignores -p) -O Print to sys.stdout (ignores -o, no file created) -I Use stdin as source file (ignore -i option) -E 0|1|2|3|4 0 - Don’t do entity substitution. 1 - Substitute < > and & (default) 2 - Substitute < > & and ” 3 - Substitute <> & ” and ‘ 4 - Substitute all non-ASCIIalphanumeric source on GitHub
pygame_helper module ensae_teaching_cs.helpers.pygame_helper pygame helpers The module pygame is not imported in this module but sent to every function as a parameter to avoid importing the module if not needed. source on GitHub
pyhomeftp module ensae_teaching_cs.homeblog.pyhomeftp provides some functionalities to upload file to a website .. deprecated:: 0.8 source on GitHub
pypdf_helper module ensae_teaching_cs.helpers.pypdf_helper globals functions to manipulate PDF files source on GitHub
python_exemple_py_to_html module ensae_teaching_cs.homeblog.python_exemple_py_to_html Helper for HTML source on GitHub
pythoncs module ensae_teaching_cs.td_2a.pythoncs Helpers autour de C# source on GitHub
repository_exception module ensae_teaching_cs.automation_students.repository_exception Some automation helpers to grab mails from students about projects. source on GitHub
rss_teachings_blog module ensae_teaching_cs.automation.rss_teachings_blog Function to capture RSS stream from modules for this teachings. source on GitHub
rues_paris module ensae_teaching_cs.special.rues_paris Code implémentant la première solution proposée à Parcourir les rues de Paris. source on GitHub
send_feedback module ensae_teaching_cs.automation_students.send_feedback Some automation helpers to grab mails from students about projects. source on GitHub
serialization module ensae_teaching_cs.td_2a.serialization Sérialization source on GitHub
session_pandas module ensae_teaching_cs.td_2a.session_pandas Quelques fonctions à propos de la première séance (2A) source on GitHub
simple_flask_site module ensae_teaching_cs.td_1a.simple_flask_site Defines a simple web site in Flask which allows unit testing source on GitHub
size_helper module ensae_teaching_cs.helpers.size_helper Functions to measure the size of an object. source on GitHub
sklearn_base_classifier module ensae_teaching_cs.ml.sklearn_base_classifier Defines SkBaseClassifier source on GitHub
sklearn_base_learner module ensae_teaching_cs.ml.sklearn_base_learner Defines a custom class to define a learner which follows the same API than any scikit-learn learner. source on GitHub
sklearn_base_regressor module ensae_teaching_cs.ml.sklearn_base_regressor Defines SkBaseRegressor source on GitHub
sklearn_example_classifier module ensae_teaching_cs.ml.sklearn_example_classifier Defines SkCustomKnn source on GitHub
sklearn_parameters module ensae_teaching_cs.ml.sklearn_parameters Defines SkLearnParameters source on GitHub
sound_helper module ensae_teaching_cs.helpers.sound_helper sound helpers source on GitHub
sudoku module ensae_teaching_cs.special.sudoku This file proposes a simple algorithm to solve a Sudoku. It finds the first possible solution. source on GitHub
table_formula module ensae_teaching_cs.homeblog.table_formula Implements TableFormula. source on GitHub
table_formula_stat module ensae_teaching_cs.homeblog.table_formula_stat Contains TableFormulaStat. source on GitHub
theano_logreg module ensae_teaching_cs.examples.theano_logreg Taken from Tutorial on logistic regression This tutorial introduces logistic regression using Theano and stochastic gradient descent. Logistic regression is a probabilistic, linear classifier. It is parametrized by a weight matrix W and a bias vector b. Classification is done by projecting data points onto a set of hyperplanes, the distance to which is used to determine a class membership probability. Mathematically, this can be written as: .. math:: P(Y=i|x, W,b) &= f_i(W x + b) \ &= frac {e^{W_i x + b_i}} {sum_j e^{W_j x + b_j}} f_i` is the activation function attached to the neuron i (see rectifier). The output of the model or prediction is then done by taking the argmax of the vector whose i’th element is P(Y=i|x). .. math:: y_{pred} = arg max_i P(Y=i|x,W,b) This tutorial presents a stochastic gradient descent optimization method suitable for large datasets. Example: :: from src.ensae_teaching_cs.examples.theano_logreg import sgd_optimization_mnist, predict from pyensae.datasource import download_data dataset = “mnist.pkl.gz” if not os.path.exists(dataset): download_data(dataset, website =”http://deeplearning.net/data/mnist/”) model = “log_reg_theano.bin” sgd_optimization_mnist(dataset=dataset, saved_model=model, n_epochs=2, fLOG=print) pred = predict(model, dataset, 10) source on GitHub
tsp_bresenham module ensae_teaching_cs.special.tsp_bresenham ce module contient la fonction trace_ligne qui retourne l’ensemble des pixels concernés par le tracé d’une ligne en 8-connexité entre deux pixels source on GitHub
tsp_kohonen module ensae_teaching_cs.special.tsp_kohonen Réseaux de Kohonen pour résoudre le problème du voyageur de commerce. source on GitHub
tsp_kruskal module ensae_teaching_cs.special.tsp_kruskal Implémente un algorithme qui cherche le plus court chemin passant par tous les noeuds d’un graphe (TSP). Applique un algorithme de Kruskal puis cherche à améliorer le chemin localement. Voir Circuit hamiltonien et Kruskal. La fonction principale est tsp_kruskal_algorithm(). source on GitHub
utils_file module ensae_teaching_cs.homeblog.utils_file Reasonably inefficient functions about files. source on GitHub
video_helper module ensae_teaching_cs.helpers.video_helper video helpers source on GitHub
vigenere module ensae_teaching_cs.td_1a.vigenere quelques fonctions à propos de la séance 3 source on GitHub
voisinage_evolution module ensae_teaching_cs.special.voisinage_evolution Implémente une simulation d’évolution des catégories de population selon un modèle de Schelling. source on GitHub
win_setup_helper module ensae_teaching_cs.automation.win_setup_helper Customize a Windows Setup for these teachings source on GitHub