This gist shows how to create a GIF screencast using only free OS X tools: QuickTime, ffmpeg, and gifsicle.
To capture the video (filesize: 19MB), using the free "QuickTime Player" application:
tell application "iCal" | |
set results to "" | |
set todaysDate to current date | |
repeat with a in every calendar | |
set results to results & return & (name of a) | |
tell a | |
set eventList to {} | |
repeat with b in every event | |
if (recurrence of b) = "FREQ=YEARLY;WKST=SU" then | |
set startDate to start date of b |
(defun forward-evil-word (&optional count) | |
"" | |
(let ((init-point (point))) | |
(forward-symbol (or count 1)) | |
(if (= (point) init-point) | |
count 0))) | |
(setq evil-symbol-word-search t) |
There are several common ways to do rsync backups of hosts over ssh:
Here is another option t
if (-not ("Windows.Native.Kernel32" -as [type])) | |
{ | |
Add-Type -TypeDefinition @" | |
namespace Windows.Native | |
{ | |
using System; | |
using System.ComponentModel; | |
using System.IO; | |
using System.Runtime.InteropServices; | |
IP=10.0.1.18 | |
for f in *; do | |
echo ">>> Uploading $f <<<" | |
curl \ | |
--progress-bar \ | |
--form "files[]=@$f" \ | |
http://"$IP"/upload.json \ | |
| tee -a vlc-ios-upload.log; test ${PIPESTATUS[0]} -eq 0 |
"""Simple example on how to log scalars and images to tensorboard without tensor ops. | |
License: BSD License 2.0 | |
""" | |
__author__ = "Michael Gygli" | |
import tensorflow as tf | |
from StringIO import StringIO | |
import matplotlib.pyplot as plt | |
import numpy as np |
#!/bin/bash | |
# Script for installing tmux on systems where you don't have root access. | |
# tmux will be installed in $INSTALL_DIR/local/bin. | |
# It's assumed that wget and a C/C++ compiler are installed. | |
# exit on error | |
set -e | |
TMUX_VERSION=2.3 |
pandas slinear: [60.0, 60.0, 60.0, 60.0, 59.999999999999993, 60.0, 60.0, 60.0] | |
pandas linear: [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0] | |
scipy slinear: [60.0, 60.0, 60.0, 60.0, 59.999999999999993, 60.0, 60.0, 60.0] | |
scipy linear: [60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0, 60.0] | |
F | |
====================================================================== | |
FAIL: Proof that linear and slinear are not equal. | |
---------------------------------------------------------------------- | |
Traceback (most recent call last): | |
File "....", line 329, in test_slinear_versus_linear |
This is the lookup table linking the transport block size index (determined by modulation and coding scheme) and the number of resource blocks to an LTE transport block size. It's taken from 3GPP [TS 36.213][36.213] (Table 7.1.7.2.1-1) at version 15.0.0. Multiply a TBS by 1000 to get the max throughput in bps.