Process Watcher

A method for installed playback systems. Set as a login item for macOS. Adjust the target process and launch file as necessary. The watcher script will check that the defined process exists. If not, it will relaunch the target file. Based on the work of Jim Bell for Generativity by Fernanda D'Agostino, Suyama Space, Seattle WA, … Continue reading Process Watcher →

Updates on Github/Kreivalabs

Numerous updates have been made to the repositories at https://www.github.com/kreivalabs. Rather than continually update the printed code in the previous posts, please head over to the git repositories (and follow the page, if you like) to be notified of updates. Previous code posts will make their way over to the Projects page.

Speaker coverage measurements with Python

NOTE: visit https://www.github.com/kreivalabs for current code versions. Calculate the coverage pattern area of a point-source loudspeaker based on its dispersion angle and the measured distance from source to listener (or some other point). This method uses Future functionality from www.python-future.org:

#!/usr/bin/env python
# @version 1.1 02-November-2017
# @language: python3
# @requirements: Future additions (http://www.python-future.org)
# @description: Calculate speaker coverage based on driver dispersion angle and measured distance from source.

# Import Future functions
from __future__ import absolute_import, division, print_function, unicode_literals
from builtins import input
import math

title="Loudspeaker Coverage Calculator"
print(title)
print("=" * 80)

# Prompt for user input
cone_degrees = int(input("Enter speaker dispersion angle in degrees: "))
measured_distance = float(input("Enter measured distance from speaker in feet: "))

# Convert angles to radians
angle_radians = math.radians(cone_degrees)
radians_div = angle_radians / 2

# Calculate coverage pattern
coverage_pattern = ((math.tan(radians_div)) * measured_distance)* 2

# Round results to two decimal places
coverage_pattern_round = str(round(coverage_pattern, 2))

# Return results, prompt for user input to quit
print("Approximate speaker coverage pattern is: ", coverage_pattern_round, "ft.")

# Return results, prompt for user input to quit.
print("=" * 80)
print("Speaker coverage pattern is: ", coverage_pattern_round, "ft.")
>>>>>>> Stashed changes
print()
print("Press the <Enter> key to exit.")
input()

#!/usr/bin/env python

# @version 1.1 02-November-2017

# @language: python3

# @requirements: Future additions (http://www.python-future.org)

# @description: Calculate speaker coverage based on driver dispersion angle and measured distance from source.

# Import Future functions

from __future__ import absolute_import, division, print_function, unicode_literals

from builtins import input

import math

title="Loudspeaker Coverage Calculator"

print(title)

print("=" * 80)

# Prompt for user input

cone_degrees = int(input("Enter speaker dispersion angle in degrees: "))

measured_distance = float(input("Enter measured distance from speaker in feet: "))

# Convert angles to radians

angle_radians = math.radians(cone_degrees)

radians_div = angle_radians / 2

# Calculate coverage pattern

coverage_pattern = ((math.tan(radians_div)) * measured_distance)* 2

# Round results to two decimal places

coverage_pattern_round = str(round(coverage_pattern, 2))

# Return results, prompt for user input to quit

print("Approximate speaker coverage pattern is: ", coverage_pattern_round, "ft.")

# Return results, prompt for user input to quit.

print("=" * 80)

print("Speaker coverage pattern is: ", coverage_pattern_round, "ft.")

>>>>>>> Stashed changes

print()

print("Press the <Enter> key to exit.")

input()

Convert Samples to Time with Python

NOTE: visit https://www.github.com/kreivalabs for up to date code versions. The following will calculate elapsed time in milliseconds and seconds for a given sample rate and time (entered in seconds). It will also calculate the number of individual samples elapsed based on sample rate and time (seconds). This Python script utilizes the Future functions available for … Continue reading Convert Samples to Time with Python →

Acoustic Velocity and Loudspeaker Delay with Temperature and Python

NOTE: visit https://www.github.com/kreivalabs for the current code versions. Building on the method below, here is the same calculator in Python (hooray for cross-platform!). Save the text below as a .py file to run in the Terminal of your choice. Python 2:

#!/usr/bin/env python

# Version 1.4 / 08-November-2017

title="Acoustic Velocity and Loudspeaker Delay Calculator"
print title
print"=" * 80

# Prompt for user input
temp_fahrenheit = float(input("Enter temperture in degrees Fahrenheit: "))
measured_distance = float(input("Enter measured distance between speakers in feet: "))

# Convert Fahrenheit to degrees Celsius
temp_celsius = (temp_fahrenheit - 32) * 5/9      

# Calculate acoustic velocity in meters/second
meters_seconds = (temp_celsius * 0.606) + 331.3    

# Convert meters/second to feet/millisecond
feet_milliseconds = meters_seconds * 0.00328084  

# Calculate time differential based on acoustic velocity and measured distance
delay_time = measured_distance / feet_milliseconds

# Round results to two decimal places - suitable for most loudspeaker processing hardware and software
meters_seconds_round = str(round(meters_seconds, 4))
feet_milliseconds_round = str(round(feet_milliseconds, 4))
delay_time_round = str(round(delay_time, 4))

# Return results
print"=" * 80
print"Approximate acoustic velocity is:" 
print meters_seconds_round, "m/s, or", feet_milliseconds_round, "ft/ms." 
print""
print"Approximate delay time is" , delay_time_round, "ms."
print""
print"Press <Enter> to exit."
raw_input()

#!/usr/bin/env python

# Version 1.4 / 08-November-2017

title="Acoustic Velocity and Loudspeaker Delay Calculator"

print title

print"=" * 80

# Prompt for user input

temp_fahrenheit = float(input("Enter temperture in degrees Fahrenheit: "))

measured_distance = float(input("Enter measured distance between speakers in feet: "))

# Convert Fahrenheit to degrees Celsius

temp_celsius = (temp_fahrenheit - 32) * 5/9

# Calculate acoustic velocity in meters/second

meters_seconds = (temp_celsius * 0.606) + 331.3

# Convert meters/second to feet/millisecond

feet_milliseconds = meters_seconds * 0.00328084

# Calculate time differential based on acoustic velocity and measured distance

delay_time = measured_distance / feet_milliseconds

# Round results to two decimal places - suitable for most loudspeaker processing hardware and software

meters_seconds_round = str(round(meters_seconds, 4))

feet_milliseconds_round = str(round(feet_milliseconds, 4))

delay_time_round = str(round(delay_time, 4))

# Return results

print"=" * 80

print"Approximate acoustic velocity is:"

print meters_seconds_round, "m/s, or", feet_milliseconds_round, "ft/ms."

print""

print"Approximate delay time is" , delay_time_round, "ms."

print""

print"Press <Enter> to exit."

raw_input()

Python 3:

#!/usr/bin/env python

# Version 1.4 / 08-November-2017

title='Acoustic Velocity and Loudspeaker Delay Calculator'
print(title)
print('=' * 80)

# Prompt for user input
temp_fahrenheit = float(input("Enter temperture in degrees Fahrenheit: "))
measured_distance = float(input("Enter measured distance between speakers in feet: "))

# Convert Fahrenheit to degrees Celsius
temp_celsius = (temp_fahrenheit - 32) * 5/9      

# Calculate acoustic velocity in meters/second
meters_seconds = (temp_celsius * 0.606) + 331.3    

# Convert meters/second to feet/millisecond
feet_milliseconds = meters_seconds * 0.00328084  

# Calculate time differential based on acoustic velocity and measured distance
delay_time = measured_distance / feet_milliseconds

# Round results to two decimal places - suitable for most loudspeaker processing hardware and software
meters_seconds_round = str(round(meters_seconds, 4))
feet_milliseconds_round = str(round(feet_milliseconds, 4))
delay_time_round = str(round(delay_time, 4))

# Return results
print('=' * 80)
print('Approximate acoustic velocity is:' 
print(meters_seconds_round, 'm/s, or', feet_milliseconds_round, 'ft/ms.') 
print()
print('Approximate delay time is', delay_time_round, 'ms.')
print()
print('Press <Enter> key to exit.')
input()

#!/usr/bin/env python

# Version 1.4 / 08-November-2017

title='Acoustic Velocity and Loudspeaker Delay Calculator'

print(title)

print('=' * 80)

# Prompt for user input

temp_fahrenheit = float(input("Enter temperture in degrees Fahrenheit: "))

measured_distance = float(input("Enter measured distance between speakers in feet: "))

# Convert Fahrenheit to degrees Celsius

temp_celsius = (temp_fahrenheit - 32) * 5/9

# Calculate acoustic velocity in meters/second

meters_seconds = (temp_celsius * 0.606) + 331.3

# Convert meters/second to feet/millisecond

feet_milliseconds = meters_seconds * 0.00328084

# Calculate time differential based on acoustic velocity and measured distance

delay_time = measured_distance / feet_milliseconds

# Round results to two decimal places - suitable for most loudspeaker processing hardware and software

meters_seconds_round = str(round(meters_seconds, 4))

feet_milliseconds_round = str(round(feet_milliseconds, 4))

delay_time_round = str(round(delay_time, 4))

# Return results

print('=' * 80)

print('Approximate acoustic velocity is:'

print(meters_seconds_round, 'm/s, or', feet_milliseconds_round, 'ft/ms.')

print()

print('Approximate delay time is', delay_time_round, 'ms.')

print()

print('Press <Enter> key to exit.')

input()

And a version if you have Future installed, … Continue reading Acoustic Velocity and Loudspeaker Delay with Temperature and Python →

Further Adventures with Twitter, node-red and Sonic Pi

Building upon the methods explored here, I've been experimenting with using node-red's Twitter node to interface directly with ruby files in Sonic Pi by means of shell scripting. By creating multiple instances of the Twitter nodes in a single flow, I can set unique search terms, strings, hash tags, etc per node, which correspond to … Continue reading Further Adventures with Twitter, node-red and Sonic Pi →

Control QLab with Twitter

UPDATE 7/10/17 - Check out the contributed module from Sam Levey, with nodes to control QLab via OSC messages and a node to control node-red from QLab: https://www.npmjs.com/package/node-red-contrib-qlab This eliminates some steps from the method described below. ORIGINAL: Utilizing node-RED, QLab can respond to hash tags, text strings, etc via OSC messages and UDP packets. … Continue reading Control QLab with Twitter →

Make a secure ad hoc wireless control network

At some point along the way (I can't remember when...), Apple removed authentication security from the ad hoc network function "Create a network..." in the Wi-Fi setup. I use ad hoc networks to link up mobile devices to Macs running Max, QLab, Isadora, etc, and not being able to lock up the network is a … Continue reading Make a secure ad hoc wireless control network →

Qlab->Terminal->SonicPi

Controlling Sonic Pi from QLab – Use Sonic Pi to generate pre-show music for your designs. Sonic Pi, created by Sam Aaron at Cambridge University, is a fantastic live-coding music synth utilizing Ruby script and the SuperCollider synth engine. Originally developed for the Raspberry Pi platform, it is also available, free, on Windows, Mac OS X and desktop Linux. … Continue reading Qlab->Terminal->SonicPi →