ebenolson

#!/bin/bash
if [ ! -f convert_mod.py ]; then
    wget https://gist.github.com/ebenolson/07af5bf0919dfa7f5585577ad073c120/raw/fc15e516ff21a503833d9157f52de9334139ce7b/convert_mod.py
fi

docker run -it -v `pwd`:`pwd`:rw -w `pwd` ebenolson/kicad:5.0.0 bash -c "python convert_mod.py $1 $2"

sudo chown -R $USER $2

ebenolson

import sys
from pcbnew import *

infile = sys.argv[1]
outdir = sys.argv[2]

inplugin = IO_MGR.PluginFind(IO_MGR.GuessPluginTypeFromLibPath(infile))
outplugin = IO_MGR.PluginFind(IO_MGR.GuessPluginTypeFromLibPath(outdir))

for name in inplugin.FootprintEnumerate(infile):

ebenolson

javascript:(function(){
function copyStringToClipboard (str) {
   var el = document.createElement('textarea');
   el.value = str;
   el.setAttribute('readonly', '');
   el.style = {position: 'absolute', left: '-9999px'};
   document.body.appendChild(el);
   el.select();
   document.execCommand('copy');
   document.body.removeChild(el);

ebenolson

#!/bin/bash
docker run -i ebenolson/mscomplex-tri-docker bash -c 'cat > input && mscomplex-tri-cl-tool -o input &> log && cat input.mscomplex.full.bin' < $1 > "$1.mscomplex.full.bin"

ebenolson

ebenolson

ebenolson

# Context manager to generate batches in the background via a process pool
# Usage:
#
# def batch(seed):
#    .... # generate minibatch
#    return minibatch
#
# with BatchGenCM(batch) as bg:
#    minibatch = next(bg)
#    .... # do something with minibatch

ebenolson

ebenolson

import theano, numpy
from theano import tensor as T
import lasagne

#fake data, same shapes
train_in = numpy.zeros((100,46,30)).astype('float32')
train_out = numpy.zeros((100,46)).astype('int32')
mask_train = numpy.zeros((100,46)).astype('float32')

input_var = T.tensor3('input_var')

ebenolson

FROM ubuntu:trusty

########################################
#
# openslide 3.4.1 image based on Ubuntu:trusty
#
#######################################

# Set Locale