clbarnes

def get_beta_params(mu, var):
    """
    From this answer http://stats.stackexchange.com/a/12239/101211
    """
    alpha = mu**2 * ( ((1-mu)/var) - 1/mu )
    beta = alpha * (1/mu - 1)
    assert alpha > 0 and beta > 0
    return alpha, beta

clbarnes

#!/usr/bin/env python
from subprocess import call
import os
import argparse

parser = argparse.ArgumentParser(description='Do an emergency backup of all git repositories.')
parser.add_argument('output_dir', help='Root directory whither to back up the git repos.')
parser.add_argument('--input', '-i', nargs='+', default=('.',), help='Root directory(s) within which to look for git \
        repos.')
parser.add_argument('--git', '-g', default='git', help='Path to git binary')

clbarnes

#!/bin/bash

set -e

USERNAME = "cbarnes"  # change this
COMPRESSION = ".tar.gz"

STARTING_DIR = pwd
ARCHIVE_DIR = dirname $1
FOLDER_NAME = basename $1 $COMPRESSION

clbarnes

import os
import argparse

parser = argparse.ArgumentParser(description='Generate contents pages for the given directory and all subdirectories.')
parser.add_argument('root', nargs='+', default=['.'], help='Target directory.')
parser.add_argument('--dryrun', '-d', action='store_true', help='Do not actually write the contents files.')

args = parser.parse_args()

clbarnes

clbarnes

Install instructions

These instructions are for installing NEURON and NetPyNE with linux and a conda environment.

Create a neuron directory in your home directory, put the gzipped source files in it, and expand them.

cd $HOME
mkdir neuron
mv iv-mm.tar.gz neuron

clbarnes

import os
import csv

FILE_EXT = '.dat'
SEARCH_TERMS = ('one line to search for \n', 'another line to search for\n')


file_list = [f for f in os.listdir() if f.endswith(FILE_EXT)]

output = [['file name', 'search term 1 exists', 'search term 2 exists']]

clbarnes

"""
Note that this constrains the dependent variable from going *any further* past the constraints.
The ODE will still treat it as if it were at the value of the constraint, 
and with a small step size any problems should be minimal,
but you may still have slightly out-of-range numbers in your solution.
"""

import numpy as np
from functools import wraps

clbarnes

#!/bin/bash
_complete_source_activate_conda(){
      if [ ${COMP_WORDS[COMP_CWORD-1]} != "activate" ]
      then
          return 0
      fi
      local cur=${COMP_WORDS[COMP_CWORD]}
      COMPREPLY=($(ls ~/anaconda3/envs | xargs -I dirs bash -c "compgen -W dirs $cur"))
      return 0
}

clbarnes

name: catmaid
dependencies:
- backports=1.0=py27_0
- boost=1.60.0=py27_0
- decorator=4.0.10=py27_0
- enum34=1.1.6=py27_0
- get_terminal_size=1.0.0=py27_0
- gevent=1.1.2=py27_0
- greenlet=0.4.10=py27_0
- icu=54.1=0