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# coding: utf-8
#
# OS X 11 (macOS ) 之后不再支持 PPTP VPN. 但 Cisco IPSec VPN 不支持像 PPTP 的
# /etc/ppp/ip-up 和 /etc/ppp/ip-down 一样方便j的机制来更新 chnroute 路由表。
# 这个脚本尝试在 Cisco IPSec VPN 下自动处理 chnroute, 做的主要工作是监听 syslog,
# 发现 IPSec VPN 连接建立或断开后去修改路由表。
#
# NOTE: 使用前可能需要修改 CUSTOMED_ROUTE_DATA, 建议将其设为
# 排除VPN子网后的 rfc1918 定义的内网IP段
#

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#!/usr/bin/env python3
"""
Running this script is (intended to be) equivalent to running the following Snakefile:

include: "pipeline.conf"  # Should be an empty file

shell.prefix("set -euo pipefail;")

rule all:
    input:

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References:

• https://support.basespace.illumina.com/knowledgebase/articles/403618-python-run-downloader
• https://developer.basespace.illumina.com/docs/content/documentation/rest-api/api-reference

Steps:

1. Follow steps 1-5 in the first link above to acquire access_token. This will take a while, but you only need to do this once. Never share this token!!
2. Find the file you want to download. Copy the link, which looks something like: https://basespace.illumina.com/sample/9804795/files/tree/NA12878-L1_S1_L001_R1_001.fastq.gz?id=515013503. The "id" is the unique file identifier.
3. Download the file with: wget -O filename 'https://api.basespace.illumina.com/v1pre3/files/{id}/content?access_token={token}', where {token} is from step 1 and {id} from step 2.

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from sklearn.base import BaseEstimator, TransformerMixin

class Transformer(BaseEstimator, TransformerMixin):
    def __init__(self, fn):
        self.fn = fn

    def fit(self, X, y):
        return self

    def transform(self, X):

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"""
Usage: python remove_output.py notebook.ipynb [ > without_output.ipynb ]
Modified from remove_output by Minrk

"""
import sys
import io
import os
from IPython.nbformat.current import read, write

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#!/usr/bin/env python
r"""Cluster submission

Light helper script for submitting jobs to a cluster. For instance, to submit
a job that calls the command hostname, just use:

    $ sub hostname

Additionally, you can specify the name of the job:

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This post examines the features of [R Markdown](http://www.rstudio.org/docs/authoring/using_markdown) 
using [knitr](http://yihui.name/knitr/) in Rstudio 0.96.
This combination of tools provides an exciting improvement in usability for 
[reproducible analysis](http://stats.stackexchange.com/a/15006/183).
Specifically, this post 
(1) discusses getting started with R Markdown and `knitr` in  Rstudio 0.96;
(2) provides a basic example of producing console output and plots using R Markdown;
(3) highlights several code chunk options such as caching and controlling how input and output is displayed;
(4) demonstrates use of standard Markdown notation as well as the extended features of formulas and tables; and 
(5) discusses the implications of R Markdown.

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# EXAMPLE USAGE

# example of colsidecolors rowsidecolors (single column, single row)
mat <- matrix(1:100, byrow=T, nrow=10)
column_annotation <- sample(c("red", "blue", "green"), 10, replace=T)
column_annotation <- as.matrix(column_annotation)
colnames(column_annotation) <- c("Variable X")

row_annotation <- sample(c("red", "blue", "green"), 10, replace=T)
row_annotation <- as.matrix(t(row_annotation))