mehdidc

import numpy as np
from scipy.spatial.distance import cdist
from lapjv import lapjv

def grid_embedding(h):
    assert int(np.sqrt(h.shape[0])) ** 2 == h.shape[0], 'Nb of examples must be a square number'
    size = np.sqrt(h.shape[0])
    grid = np.dstack(np.meshgrid(np.linspace(0, 1, size), np.linspace(0, 1, size))).reshape(-1, 2)
    cost_matrix = cdist(grid, h, "sqeuclidean").astype('float32')
    cost_matrix = cost_matrix * (100000 / cost_matrix.max())

mehdidc

import PIL.Image
from cStringIO import StringIO
import IPython.display
import numpy as np
def showarray(a, fmt='png'):
    a = np.uint8(a)
    f = StringIO()
    PIL.Image.fromarray(a).save(f, fmt)
    IPython.display.display(IPython.display.Image(data=f.getvalue()))

mehdidc

from subprocess import call
import numpy as np
import os

import pandas as pd
from skimage.io import imsave

def download(url):
    fname = os.path.basename(url)
    if not os.path.exists(fname):

mehdidc

import pickle
import sys
import numpy as np
import os
from subprocess import call

import pandas as pd
from skimage.io import imsave

mehdidc

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

mehdidc

mehdidc

# remap prefix from 'C-b' to 'C-a'
unbind C-b
set-option -g prefix C-a
bind-key C-a send-prefix
# Start window numbering at 1
set -g base-index 1

set -g @plugin 'tmux-plugins/tpm'
set -g @plugin 'tmux-plugins/tmux-sensible'
set -g @plugin 'tmux-plugins/tmux-copycat'

mehdidc

# docker build -t ubuntu1604py36
FROM ubuntu:16.04

RUN apt-get update
RUN apt-get install -y software-properties-common vim
RUN add-apt-repository ppa:jonathonf/python-3.6
RUN apt-get update

RUN apt-get install -y build-essential python3.6 python3.6-dev python3-pip python3.6-venv
RUN apt-get install -y git

mehdidc

Cython

Cython has two major benefits:

1. Making python code faster, particularly things that can't be done in scipy/numpy
2. Wrapping/interfacing with C/C++ code

Cython gains most of it's benefit from statically typing arguments. However, statically typing is not required, in fact, regular python code is valid cython (but don't expect much of a speed up). By incrementally adding more type information, the code can speed up by several factors. This gist just provides a very basic usage of cython.

mehdidc

# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,