benfasoli

import asyncio
from typing import Coroutine, List, Sequence


def _limit_concurrency(
    coroutines: Sequence[Coroutine], concurrency: int
) -> List[Coroutine]:
    """Decorate coroutines to limit concurrency.

    Enforces a limit on the number of coroutines that can run concurrently in higher

benfasoli

#!/usr/bin/env Rscript

options(dplyr.summarise.inform = F)

library(data.table)
library(htmlwidgets)
library(leaflet)
library(tidyverse)

benfasoli

library(ggplot2)
library(metR)

time <- Sys.time()
n <- 50
data <- data.frame(
  time = seq(time - 3600, time, length.out = n),
  direction = seq(0, 359, length.out = n),
  magnitude = 5 * sin(seq(0, 2 * pi, length.out = n))
)

benfasoli

#!/usr/bin/env python3

import io

import pandas as pd


api_response_csv = """
x, y, z
1, 2, 3

benfasoli

#!/bin/bash
set -e

if [[ "$HOSTNAME" == "notchpeak"* ]]; then
  CLUSTER="np"
elif [[ "$HOSTNAME" == "kingspeak"* ]]; then
  CLUSTER="kp"
else
  echo "Unable to determine cluster from hostname: $HOSTNAME" > /dev/stderr
  exit 1

benfasoli

#!/usr/bin/env Rscript
# Ben Fasoli | benfasoli@gmail.com

# Return number of R processes currently running for active user
get_process_count <- function(x = NA) {
  as.integer(system('pgrep -U $USER R | wc -l', intern = T))
}


N_FORKS <- 2

benfasoli

#!/usr/bin/env python
# -*- coding: utf-8 -*-

from datetime import datetime, timedelta
from multiprocessing import cpu_count, Pool
import os
from typing import List

from google.cloud import bigquery
import pandas as pd

benfasoli

#!/usr/bin/env python3

import io
import os
import subprocess

import pandas as pd


class ReadTrajException(Exception):

benfasoli

#!/usr/bin/env Rscript

library(raster)
library(tidyverse)

# Time integrate footprints to a single layer
r0 <- sum(brick('footprint0.nc'))
r1 <- sum(brick('footprint1.nc'))

control <- values(r0)

benfasoli

#!/bin/bash

EXE=./hycs_std
OUTPUT=PARTICLE.DAT
COUNT=0

while ! grep -q NaN $OUTPUT; do
    $EXE
    let COUNT=COUNT+1
done