General:
Tools | Description |
---|---|
flank | Create new intervals from the flanks of existing intervals. |
slop | Adjust the size of intervals. |
shift | Adjust the position of intervals. |
subtract | Remove intervals based on overlaps b/w two files. |
library(plyranges) | |
set.seed(1) | |
x <- data.frame(seqnames=1, start=0:9 * 100 + 1, | |
width=20, id=1:10) %>% | |
as_granges() | |
y <- data.frame(seqnames=1, start=round(runif(4,100,900)), | |
width=10, id=letters[1:4]) %>% | |
as_granges() %>% |
""" | |
Simple example to demostrate the embedding visualization for word embeddings in tensorflow / tensorboard | |
https://www.tensorflow.org/how_tos/embedding_viz/ | |
""" | |
import tensorflow as tf | |
import os | |
assert tf.__version__ == '1.0.0-rc0' # if code breaks, check tensorflow version | |
from tensorflow.contrib.tensorboard.plugins import projector |
Installation:
A quick installation does not require root access, as shown:
(wget -O - pi.dk/3 || curl pi.dk/3/ || fetch -o - http://pi.dk/3) | bash
For other installation options see http://git.savannah.gnu.org/cgit/parallel.git/tree/README
""" | |
Learning Task: | |
Given a sequence, predict a label based on the first value of the sequence | |
Explanation of stateful LSTM and setup: | |
http://philipperemy.github.io/keras-stateful-lstm/ | |
Exmple: | |
given a sequence [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], predict 1 | |
given a sequence [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], predict 0 |
import asyncio | |
import aiohttp | |
import bs4 | |
import tqdm | |
@asyncio.coroutine | |
def get(*args, **kwargs): | |
response = yield from aiohttp.request('GET', *args, **kwargs) | |
return (yield from response.read_and_close(decode=True)) |