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# -*- coding: utf-8 -*-
import numpy as np
import pylab as pl

__author__ = 'Takuya Nairihira'

def compute_belonging(x, c):
    dist_NxK = (x**2).sum(axis=1)[:,np.newaxis] - 2. * np.dot(x, c.T)  + (c**2).sum(axis=1)[np.newaxis]
    return dist_NxK.argmin(axis=1)

tnarihi

tnarihi

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tnarihi

tnarihi

/*
 * No Copyright
 */
#include <boost/algorithm/string.hpp>
#include <boost/foreach.hpp>
#include <boost/shared_ptr.hpp>
#include <boost/lexical_cast.hpp>
#include <iostream>  // NOLINT(readability/streams)
#include <fstream>  // NOLINT(readability/streams)
#include <string>

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[
	{ "keys": ["ctrl+x", "["], "command": "move_to", "args": {"to": "bof", "extend": false} },
	{ "keys": ["ctrl+x", "]"], "command": "move_to", "args": {"to": "eof", "extend": false} },
	{ "keys": ["ctrl+shift+2"], "command": "sbp_set_mark" },
	{ "keys": ["ctrl+[", "w"], "command": "sbp_kill_ring_save" },
	{ "keys": ["ctrl+[", "b"], "command": "move", "args": {"by": "subwords", "forward": false} },
	{ "keys": ["ctrl+[", "f"], "command": "move", "args": {"by": "subword_ends", "forward": true} },
	{ "keys": ["ctrl+[", "d"], "command": "sbp_delete_word", "args": { "forward": true } },
	{ "keys": ["ctrl+[", "backspace"], "command": "sbp_delete_word", "args": { "forward": false } },
	{ "keys": ["ctrl+x", "ctrl+w"], "command": "prompt_save_as" },

tnarihi

# Filename: $HOME/.screenrc
# Purpose:  Setup file for program "(GNU) screen"
# Latest change: Mon Jan 26 10:51:50 CET 2004
# Author: Michael Prokop / <[email protected]> / www.michael-prokop.at
# ===============================================================
#
# ===============================================================
# SEE ALSO:
# ===============================================================
# SCREEN Pages:

tnarihi

Examples of Python OpenCV2 and Scikit.Image and their comparisons

See the iPython notebook link. In this notebook, you can see various image maniputaion examples using both Python extension of OpenCV2 and Scikit.Image.

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tnarihi

Behaviors of Python threading, multiprocessing and concurrent.futures

I saw the behaviors as follows:

1. threading.Thread and multiprocessing.Process do not raise to the main thread.
2. multiprocessing.Pool and multiprocessing.pool.ThreadPool (this is not documented at all) leave zombie threads.

The results show that concurrent.futures is the best choice for threading and multiprocessing in Python!

I did this experiment on Python 2.7.9, and Python 2.x does not have concurrent.futures, so I installed it by pip command pip install futures.