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/** | |
* Extrait de code à exécuter dans la console du navigateur pour ajouter | |
* sous les prix le prix au mètre-carré et le prix par chambre dans les | |
* résultats de logement sur pap.fr | |
* Fonctionne au 17/04/2017, mais puisque le code est très ad-hoc il faudra | |
* sûrement le mettre à jour à chaque màj de pap.fr | |
* | |
* Existe aussi pour seloger.com : | |
* https://gist.github.com/eliemichel/1c6f27be406a22a0d5114020c616d3e8 | |
* |
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/** | |
* Extrait de code à exécuter dans la console du navigateur pour ajouter | |
* sous les prix le prix au mètre-carré et le prix par chambre dans les | |
* résultats de logement sur seloger.com | |
* Fonctionne au 17/04/2017, mais puisque le code est très ad-hoc il faudra | |
* sûrement le mettre à jour à chaque màj de seloger.com | |
* | |
* Existe aussi pour pap.fr : | |
* https://gist.github.com/eliemichel/e292bae7b439e15cf7da37ae518f08dc | |
* |
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def getNearestUCDpulse(azimuth, elevation, h3D): | |
""" | |
retrieves the impulse response from h3D that is closest to the specified | |
azimuth and elevation (in degrees) | |
h3D is the array containing all HRTFs for a given subject (left or right) | |
""" | |
elmax = 50 | |
elindices = np.arange(elmax) | |
elevations = -45 + 5.625 * elindices |
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# ########################################################################### # | |
# MVA -- Reinforcement Learning -- TP2 | |
# ########################################################################### # | |
# | |
# Code base for the TP2 of the MVA lecture Reinforcement Learning, by | |
# Alessandro Lazaric. This is a Python port of the MATLAB base provided by the | |
# TP advisor Émilie Kaufmann: | |
# http://chercheurs.lille.inria.fr/ekaufman/teaching.html | |
# | |
# Do not hesitate to report any suggestion or bugfix to |
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# Example of use of Afanasy's API to generate a summary of the state of the | |
# render farm. | |
# Copyright (c) 2016 rise|fx (Elie Michel) - Released under MIT License | |
import af | |
cmd = af.Cmd() | |
def isSysJob(job): | |
return job['st'] == 0 |
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import sys | |
import cv2 | |
import numpy as np | |
""" | |
Convert image to Gimp gradient. | |
Usage: python image2gradient.py input_image | |
Output gradient in stdout. Place it in something like | |
~/.config/GIMP/2.x/gradients or |
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