Getaji

#概要

　黒魔術ライブラリことLombokについての解説です。公式ドキュメントからの和訳と多分な意訳によって構成されています。

　すでにこちらの”JavaでAndroid開発をするなら絶対に導入したいLombok - 超戦士が秘めたる13のパワー[劇場版]”で解説がありますが、当記事では各パラメータやオプションの解説も行っていきます。そういった部分も把握して使いこなしたい、と言った場合に参考にしていただければと思います。

　Experimental features（実験的な機能）はバージョンアップによって削除される可能性が高いため解説は行いません。Lombokのアップデートによってメインパッケージへと移動した場合は追記を行う予定です。

　かなり長くなるので見出しをご活用ください。

yasaichi

"""
以下の論文で提案された改良x-means法の実装

クラスター数を自動決定するk-meansアルゴリズムの拡張について
http://www.rd.dnc.ac.jp/~tunenori/doc/xmeans_euc.pdf
"""

import numpy as np
from scipy import stats
from sklearn.cluster import KMeans

dyndna

Docker build "Could not resolve 'archive.ubuntu.com'" apt-get fails to install anything

In Ubuntu Precise 12.04 LTS, after executing docker build command, e.g., docker build -t myimages/pcawg3_1 -f ./icgc_rnaseq_align/, build engine may halt at step 1: apt-get with errors similar to Could not resolve 'archive.ubuntu.com'. This is occurring most likely because of inability of docker ubuntu image to resolve apt-get urls with default Google DNS.

To resolve this issue: [Ref. http://stackoverflow.com/a/24991137]

1. Uncomment following line in /etc/default/docker, and preferably replace Google DNS with those from your own ISP:

DOCKER_OPTS="--dns 8.8.8.8 --dns 8.8.4.4"

2. Restart docker by sudo service docker restart or service restart command for other platforms.
3. Reissue docker build, and add no-cache=true flag to force docker image fetch new DNS, e.g., docker build --no-cache=true -t myimages/pcawg3_2 -f ./icgc_rnaseq_align/

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

MitI-7

import numpy as np
from sklearn.cluster import KMeans


class Cluster:

    def __init__(self, ids: [str], features: [[float]], centroid: []):
        self.ids = np.array(ids)
        self.features = np.array(features)
        self.centroid = centroid

tkuchiki

$ ./put-s3 --help
sage: put-s3 --file=FILE --bucket=BUCKET --region=REGION [<flags>]

Flags:
      --help                 Show context-sensitive help (also try --help-long and --help-man).
  -f, --file=FILE            upload file
  -b, --bucket=BUCKET        bucket
  -r, --region=REGION        region
 --path=PATH path

civitaspo

in:
  type: s3
  access_key_id: "{{ env.AWS_ACCESS_KEY_ID }}"
  secret_access_key: "{{ env.AWS_SECRET_ACCESS_KEY }}"
  bucket: "{{ env.S3_BUCKET }}"
  path_prefix: "{{ env.INPUT_PREFIX }}"
  decoders:
    - type: gzip
  parser:
    type: csv

jaredhowland

#Quick Guide sudo atsutil databases -remove

atsutil server -shutdown

atsutil server -ping

#Extended Guide from http://doc.extensis.com/Font-Management-in-OSX-Best-Practices-Guide.pdf

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward