certik

#! /bin/bash

set -e

g++ -o test_offscreen.o -c test_offscreen.cpp -I$PYTHONHPC/include/vtk-6.0
g++ -o test_offscreen test_offscreen.o $PYTHONHPC/lib/libvtk*.so
LD_LIBRARY_PATH=$PYTHONHPC/lib/ ./test_offscreen

mmechtley

import numpy as np

arr = np.arange(100).reshape(4,5,5)

indexes = np.arange(5)
np.random.shuffle(indexes)

dim2shuff = arr[:,indexes,:]
dim3shuff = arr[:,:,indexes]

mabdrabo

import pyaudio
import wave
 
FORMAT = pyaudio.paInt16
CHANNELS = 2
RATE = 44100
CHUNK = 1024
RECORD_SECONDS = 5
WAVE_OUTPUT_FILENAME = "file.wav"
 

bsweger

Useful Pandas Snippets

A personal diary of DataFrame munging over the years.

Data Types and Conversion

Convert Series datatype to numeric (will error if column has non-numeric values)
(h/t @makmanalp)

teeks99

I wasn't able to get the basic quickstart example for Boost.Python working without some modifications, so I wanted to document it for others.

Here are the various issues I encountered with the default example:

• The Bjam file (in the root of boost or in the quickstart, i'm not sure) defaults to threading=single, but something else is defaulting to threading=multi, so they are incompatible (shows up as saying the boost_python-vcXXX-mt-gd-1_XX.lib is not found when it just generated boost_python-vcXXX-gd-1_XX.lib). Manually specifying threading=multi for the bjam commands seems to fix things.
• I wanted to get this going with boost 1.57.0, but there was a change to the boost::build directory structure in 1.56+ that hasn't been reflected in the quickstarts boost-build.jam file, so I reverted back to 1.55.0.
• Visual Studio 2010 (msvc-10.0) has a bug that keeps it

RobertoSchneiders

I am deploying with this IAM using Codeship and Circle CI to Elastic Beanstalk. I had a lot of trouble with this config. I talked to the aws support for about 6 hours until this worked properly, so, I guess it is worth to share.

UPDATE: In the end, I have to use the AWSElasticBeanstalkFullAccess policy. My custom policy keep breaking every week with some new added permission or some EB internal change. Anyway, the IAM I was using is below.

This works for me with CircleCI and EB Cli.

{
    "Version": "2012-10-17",
    "Statement": [
        {

baraldilorenzo

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman

IamAdiSri

First install pip for Python2. Download the get-pip.py file from https://bootstrap.pypa.io/get-pip.py
$ cd <download location>
$ sudo -H python ./get-pip.py

Installing pip also installs Python3
To run Python3
$ python3

Install pip3 by just executing the same file as in the step above, but this time using Python3
$ sudo -H python3 ./get-pip.py

karpathy

""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym

# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward

wassname

"""
Here is a dice loss for keras which is smoothed to approximate a linear (L1) loss.
It ranges from 1 to 0 (no error), and returns results similar to binary crossentropy
"""

# define custom loss and metric functions 

from keras import backend as K

def dice_coef(y_true, y_pred, smooth=1):