fperez

#!/usr/bin/env python
"""
Interactive execution with automatic history, tries to mimic Mathematica's
prompt system. This environment's main features are:

- Numbered prompts (In/Out) similar to Mathematica. Only actions that produce
  output (NOT assingments, for example) affect the counter and cache.

- The following GLOBAL variables always exist (so don't overwrite them!):
  _p: stores previous result which generated printable output.

jboner

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

cosmoscalibur

def eval_fun(f, **args):
   ''' (str, dict) -> object
   f: Function as string.
   args: dictionary with arbitrary variables.
   Use arbitrary args in **args to eval general functions.
   Examples:
   >> eval_fun('x**2',x=5)
   25
   >> eval_fun('x*y', x=3, y=2)
   6

nicoguaro

#!/bin/bash
#
# Generate an animation (.avi, .gif) from a sequence of image with
# the same name and a sequence of numbers.
#

mencoder "mf://*.png" -mf type=png:fps=5 -ovc lavc -o vid.avi
convert img*.png -delay 20 -loop 0 -channel Alpha  vid.gif
rm img*.png

yuanqing

 0000
00  00
00  00
00  00
 0000

1111
  11
  11
  11

franktoffel

conda create --name nikolaenv python=3
activate nikolaenv
conda install pillow lxml
pip install Nikola[extras]

cosmoscalibur

conda create -y -n pyinstaller python=3.6
conda activate pyinstaller
pip install pyinstaller
echo 'print("hola mundo")' > hola.py
pyinstaller --onefile hola.py
./dist/hola

mikhailov-work

# Copyright 2019 Google LLC.
# SPDX-License-Identifier: Apache-2.0

# Author: Anton Mikhailov

turbo_colormap_data = [[0.18995,0.07176,0.23217],[0.19483,0.08339,0.26149],[0.19956,0.09498,0.29024],[0.20415,0.10652,0.31844],[0.20860,0.11802,0.34607],[0.21291,0.12947,0.37314],[0.21708,0.14087,0.39964],[0.22111,0.15223,0.42558],[0.22500,0.16354,0.45096],[0.22875,0.17481,0.47578],[0.23236,0.18603,0.50004],[0.23582,0.19720,0.52373],[0.23915,0.20833,0.54686],[0.24234,0.21941,0.56942],[0.24539,0.23044,0.59142],[0.24830,0.24143,0.61286],[0.25107,0.25237,0.63374],[0.25369,0.26327,0.65406],[0.25618,0.27412,0.67381],[0.25853,0.28492,0.69300],[0.26074,0.29568,0.71162],[0.26280,0.30639,0.72968],[0.26473,0.31706,0.74718],[0.26652,0.32768,0.76412],[0.26816,0.33825,0.78050],[0.26967,0.34878,0.79631],[0.27103,0.35926,0.81156],[0.27226,0.36970,0.82624],[0.27334,0.38008,0.84037],[0.27429,0.39043,0.85393],[0.27509,0.40072,0.86692],[0.27576,0.41097,0.87936],[0.27628,0.42118,0.89123],[0.27667,0.43134,0.90254],[0.27691,0.44145,0.913

mikhailov-work

// Copyright 2019 Google LLC.
// SPDX-License-Identifier: Apache-2.0

// Polynomial approximation in GLSL for the Turbo colormap
// Original LUT: https://gist.github.com/mikhailov-work/ee72ba4191942acecc03fe6da94fc73f

// Authors:
//   Colormap Design: Anton Mikhailov (mikhailov@google.com)
//   GLSL Approximation: Ruofei Du (ruofei@google.com)