jeffwright13

 Python code to calculate inflection points

K-Wu

/*
 * From https://www.open-mpi.org/faq/?category=runcuda
 * Command:
 * $ mpic++ cuda_aware_check.cpp 
 * $ mpirun a.out
 * Program that shows the use of CUDA-aware macro and runtime check.
 * Requires Open MPI v2.0.0 or later.
 */
#include <stdio.h>
#include "mpi.h"

Velocet

#Requires -RunAsAdministrator
# Unlock-PowerCfg - v22.05.11

# Disable "Connected Standby"
Set-ItemProperty -Path 'HKLM:\SYSTEM\CurrentControlSet\Control\Power' -Name 'CSEnabled' -Value 0 -Force

# Get Power Settings entries and add/set 'Attributes' to 2 to unhide
$PowerCfg = (Get-ChildItem 'HKLM:\SYSTEM\CurrentControlSet\Control\Power\PowerSettings' -Recurse).Name -notmatch '\bDefaultPowerSchemeValues|(\\[0-9]|\b255)$'
foreach ($item in $PowerCfg) { Set-ItemProperty -Path $item.Replace('HKEY_LOCAL_MACHINE','HKLM:') -Name 'Attributes' -Value 2 -Force }

Eddy-Barraud

#!/bin/bash

find . -regex ".*\.\(opus\|ogg\|m4a\)" -print0 | 
    while IFS= read -r -d $'\0' filename; do 
        echo $filename
        name="${filename%.*}"
        < /dev/null ffmpeg -nostats -loglevel 0 -n -i "$filename" -b:a 0 -codec:a libmp3lame -vn "./$name.mp3"
    done

shane5ul

def blockAverage(datastream, isplot=True, maxBlockSize=0):
    
	"""This program computes the block average of a potentially correlated timeseries "x", and 
	provides error bounds for the estimated mean <x>. 
	As input provide a vector or timeseries "x", and the largest block size.
	
	Check out writeup in the following blog posts for more:
	http://sachinashanbhag.blogspot.com/2013/08/block-averaging-estimating-uncertainty_14.html
	http://sachinashanbhag.blogspot.com/2013/08/block-averaging-estimating-uncertainty.html
	"""

thenadz

#!/bin/bash -e
 
# Distro: Amazon Linux AMI release 2015.03
# Derived from https://trac.ffmpeg.org/wiki/CompilationGuide/Centos
 
# Builds the dependencies in parallel prior to starting FFmpeg build.

sudo yum update -y
sudo yum install -y autoconf automake cmake freetype-devel gcc gcc-c++ git libtool make mercurial nasm pkgconfig zlib-devel yasm libogg libvorbis-devel libvpx-devel

elyase

from scipy.interpolate import UnivariateSpline
import numpy as np

def curvature_splines(x, y=None, error=0.1):
    """Calculate the signed curvature of a 2D curve at each point
    using interpolating splines.

    Parameters
    ----------
    x,y: numpy.array(dtype=float) shape (n_points, )

anshula

Table of Contents

• Installing
• Adding A Shortcut
• Process
• Features

earthgecko

#!/bin/bash
# bash generate random alphanumeric string
#

# bash generate random 32 character alphanumeric string (upper and lowercase) and 
NEW_UUID=$(cat /dev/urandom | tr -dc 'a-zA-Z0-9' | fold -w 32 | head -n 1)

# bash generate random 32 character alphanumeric string (lowercase only)
cat /dev/urandom | tr -dc 'a-z0-9' | fold -w 32 | head -n 1