wleepang

#!/bin/bash
set -e

function get_instance_storage_nvme() {
    for nvme_device_name in `lsblk | cut --delimiter=" " --fields=1 | grep ^nvme | sort -n`; do
        local nvme_device="/dev/${nvme_device_name}"
        if ( nvme id-ctrl "${nvme_device}" | grep --quiet "^mn\\s*:\\s*Amazon EC2 NVMe Instance Storage\\s*$" ); then
            echo "${nvme_device}"
        fi
    done

wleepang

"""
Reads a fastq file directly from the 1000genomes AWS public dataset
into a Bio.SeqRecord set

Requires an AWS Account
"""

from smart_open import open
from Bio import SeqIO

wleepang

SP = sin(0.5*tt) + cos(.8*tt) + 5

wleepang

SP = rep(10, length(tt))
SP[which(tt >= 30)] = 5
SP[which(tt >= 60)] = 20

wleepang

for (k in 2:length(tt)) {
  PV[k] = pv(PV[k-1], U[k-1], tt[k])
  E[k] = PV[k] - SP[k]
  
  EI[k] = EI[k-1] + E[k]*dt  # integral
  ED[k] = (E[k] - E[k-1])/dt # derivative
  
  U[k] = Kp*(E[k] + (1/Ti)*sum(E*dt) + Td*ED[k]) 
  
  if (U[k] < 0) U[k] = 0

wleepang

MultiSetFun = function(fun, x) {
  # performs a set function (e.g. intersect, setdiff) on x
  # where x is a list of vectors of the same type but not necessarily the same length
  
  fun = tolower(fun)
  
  this.intersect = function(M, v) {
    return(names(which(rowSums(M) == sum(v))))
  }
  

wleepang

# controller parameters
Kp = 10                 # proportional gain
Ti = 1                  # integral time
Td = 0.01               # derivative time

# simulation parameters
dt = .1                 # time step
tt = seq(0, 100, by=dt) # time vector

# initialize the following to a vector of zeros

wleepang

# assuming --pylab ipython
import numpy as np
from lmfit import minimize, Parameters

s = np.float_(np.array(range(0,1201,1200/8)))
v = np.round(120*s/(171+s) + np.random.uniform(size=9), 2)

def residual(p, x, data):
    vmax = p['vmax'].value
    km = p['km'].value

wleepang

pv = function(pv.prev, u, tt) {
  out = pv.prev*1.1 + .5           # exponential growth + linear growth 
  out = out - 0.1*u                # the control response
  out = out + .5*runif(length(tt)) # a little noise, just for fun
  
  if (out < 0) out = 0             # keep values positive
  return(out)
}

wleepang

function cmap = colorRamp(colors, varargin)
% colorRamp produces a color ramp for use in figure colormaps
%   cmap = colorRamp(colors)
%   cmap = colorRamp(colors, nlevels)
%
%   Interpolates between color stops specified in the m-by-3 matrix colors.
%   Each row represents one color stop.
%   Assumes color stops are equally spaced.
%
%   By default, produces a cmap with 32-levels, unless the nlevels argument