by Angel Leon. March 17, 2015;
Last update on December 14, 2023
Updated on February 27, 2023
Updated August 29, 2019.
// source: https://msdn.microsoft.com/en-us/library/bb259689.aspx | |
//------------------------------------------------------------------------------ | |
// <copyright company="Microsoft"> | |
// Copyright (c) 2006-2009 Microsoft Corporation. All rights reserved. | |
// </copyright> | |
//------------------------------------------------------------------------------ | |
using System; | |
using System.Text; |
#!/usr/bin/env python | |
import caffe | |
from caffe.proto import caffe_pb2 | |
from google.protobuf import text_format | |
class structtype: | |
pass | |
def loadSolver(fn): | |
with open(fn) as f: |
# -*- coding: utf-8 -*- | |
''' | |
Ranking code based on: | |
https://github.com/coleifer/peewee/blob/master/playhouse/sqlite_ext.py | |
''' | |
import struct | |
import math |
This simple script will take a picture of a whiteboard and use parts of the ImageMagick library with sane defaults to clean it up tremendously.
The script is here:
#!/bin/bash
convert "$1" -morphology Convolve DoG:15,100,0 -negate -normalize -blur 0x1 -channel RBG -level 60%,91%,0.1 "$2"
;; based on http://talks.golang.org/2012/concurrency.slide#50 | |
(ns robpike | |
(:require [cljs.core.async :as async :refer [<! >! chan close!]]) | |
(:require-macros [cljs.core.async.macros :as m :refer [go alt!]])) | |
(defn timeout [ms] | |
(let [c (chan)] | |
(js/setTimeout (fn [] (close! c)) ms) | |
c)) |
Latency Comparison Numbers (~2012) | |
---------------------------------- | |
L1 cache reference 0.5 ns | |
Branch mispredict 5 ns | |
L2 cache reference 7 ns 14x L1 cache | |
Mutex lock/unlock 25 ns | |
Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
Compress 1K bytes with Zippy 3,000 ns 3 us | |
Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.
The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy