ito4303

---
title: "R Notebook"
output: html_notebook
---

```{r}
library(rstan)
options(mc.cores = parallel::detectCores())
library(bayesplot)
```

mGBUfLn9

I was drawn to programming, science, technology and science fiction
ever since I was a little kid. I can't say it's because I wanted to
make the world a better place. Not really. I was simply drawn to it
because I was drawn to it. Writing programs was fun. Figuring out how
nature works was fascinating. Science fiction felt like a grand
adventure.

Then I started a software company and poured every ounce of energy
into it. It failed. That hurt, but that part is ok. I made a lot of
mistakes and learned from them. This experience made me much, much

duncangh

import boto3
import pandas as pd
from io import BytesIO

bucket, filename = "bucket_name", "filename.csv"

s3 = boto3.resource('s3')
obj = s3.Object(bucket, filename)
with BytesIO(obj.get()['Body'].read()) as bio:
    df = pd.read_csv(bio)

DavisVaughan

# This example demonstrates running furrr code distributed on 2 AWS instances ("nodes").

# The instances have already been created.

library(future)
library(furrr)

# Two t2.micro AWS instances
# Created from http://www.louisaslett.com/RStudio_AMI/
public_ip <- c("34.205.155.182", "34.201.26.217")

mdsumner

fast_extract <- function(x, y, ...) {
  ## BEWARE no extract options are respected
  raster::extract(x, sfpoly_cells(x, y))
}

sfpoly_cells <- function(rast, sfpoly) {
  ## BEWARE, could be a big-data, this is not
  ## sparsely specified, so it's wasteful on memory, but fast (if you have the mem)
  which(!is.na(fasterize::fasterize(sfpoly, rast)[]))
}

felixgwu

import torch
from torch import nn

__all__ = ['FCDenseNet', 'fcdensenet_tiny', 'fcdensenet56_nodrop',
           'fcdensenet56', 'fcdensenet67', 'fcdensenet103',
           'fcdensenet103_nodrop']


class DenseBlock(nn.Module):

cpsievert

# devtools::install_github("ropensci/plotly")
library(plotly)

nc <- sf::st_read(system.file("shape/nc.shp", package = "sf"))

# shared data will make the polygons "query-able"
ncsd <- crosstalk::SharedData$new(nc)

p <- ggplot(ncsd) +
  geom_sf(aes(fill = AREA, text = paste0(NAME, "\n", "FIPS: ", FIPS))) +

asksven

If 2fa is enabled on github switch to ssh instead of https on linux

1. generate an ssh keypair on your linux box
ssh-keygen -t {rsa|dsa} 

2. add the public key to github: profile - settings - ssh keys

3. switch from https to ssh

Check your repo remote:

rmaia

require(rstan)
require(geiger)
require(MCMCglmm)

# load data
data(geospiza)
dat <- geospiza$geospiza.data

# create fake sample of trees
tr <- drop.tip(geospiza$geospiza.tree, 'olivacea')