thomaspinder

import gpflow
import tensorflow as tf
import matplotlib.pyplot as plt
from gpflow.models import GPModel, InternalDataTrainingLossMixin, GPR
from gpflow.kernels import SquaredExponential, Kernel
from gpflow.likelihoods import Gaussian
from gpflow.mean_functions import Zero
from gpflow.base import Parameter
from time import time
from gpflow.utilities import print_summary

woodbri

#!/usr/bin/env python3
'''
    get-winds.py

    - get the latest data from nomads.ncep.noaa.gov unless we have it already
    - generate file /maps/wms/data/windy.json
    - generate windy.latest file with time stamp

'''

crittermike

# One liner
wget --recursive --page-requisites --adjust-extension --span-hosts --convert-links --restrict-file-names=windows --domains yoursite.com --no-parent yoursite.com

# Explained
wget \
     --recursive \ # Download the whole site.
     --page-requisites \ # Get all assets/elements (CSS/JS/images).
     --adjust-extension \ # Save files with .html on the end.
     --span-hosts \ # Include necessary assets from offsite as well.
     --convert-links \ # Update links to still work in the static version.

sim642

Installing boost libraries for GCC (MinGW) on Windows

Folder setup

1. Extract downloaded boost source, e.g. C:\Program Files\boost_1_59_0.
2. Create a folder for Boost.Build installation, e.g. C:\Program Files\boost-build.
3. Create a folder within for building, i.e. C:\Program Files\boost_1_59_0\build.
4. Create a folder for installation, e.g. C:\Program Files\boost.

GCC setup

1. Open Command Prompt.

calstad

Quick List of Resources for Topological Data Analysis with Emphasis on Machine Learning

This is just a quick list of resourses on TDA that I put together for @rickasaurus after he was asking for links to papers, books, etc on Twitter and is by no means an exhaustive list.

Survey Papers

Both Carlsson's and Ghrist's survey papers offer a very good introduction to the subject

• Topology and Data by Gunnar Carlsson
• Barcodes: The Persistent Topology of Data by Robert Ghrist

Other Papers and Web Resources

• Extracting insights from the shape of complex data using topology A good introductory paper in Nature on the Mapper algorithm.

rrnewton

#include "papi.h"
#include <stdlib.h>
#include <stdio.h>

// Make sure to create some cache misses:
void do_misses() {
  int i;
  int sz = 30 * 1000 * 1000;
  double* data = malloc(sz * sizeof(double));
  for(i=0; i<sz; i++) data[i] = i*100;

chenshuo

// FIXME: memory leaks

#include <stdio.h>
#include <deque>
#include <set>

struct Node
{
  int value;
  Node* parent;