kaanaksit

import torch
import sys
import math
from odak.learn.wave import propagate_beam, generate_complex_field, wavenumber, calculate_phase, calculate_amplitude, quadratic_phase_function
from odak.learn.tools import save_image, convolve2d
from odak.tools import check_directory, shell_command
from tqdm import tqdm


def generate(resolution, delay, distance=0.15, wavelength = 532e-9, pixel_pitch = 8e-6, propagation_type='TR Fresnel'):

kaanaksit

'''
This is tested with an Ubuntu 19.10. I tested this script with %60 volume and a Bistee Smart WiFi Bulb E26 7W RGBW --> https://smile.amazon.com/gp/product/B07YDKD274/ref=ppx_yo_dt_b_asin_title_o00_s00?ie=UTF8&psc=1

(1) Assuming that you set the default input device on your machine as monitor of your soundcard (check input devices in `pavucontrol`).
(2) Assuming that you installed sounddevice, flux_led using pip3: sudo pip3 install sounddevice, flux_led .
(3) make sure that you set the ip address of your smart bulb correctly. Check ip_address line in this script.
(4) Simply run this script to make your light dance!
(5) If the light transition isn't good as you want, try playing with kd and kp variables in below.
'''
import sounddevice as sd

kaanaksit

#!/usr/bin/python
# -*- coding: utf-8 -*-

__author__ = ('Kaan Akşit')
__version__ = '0.1'

# Importing necessary libraries.
try:
    import sys,glob,time,copy
    import numpy as np

kaanaksit

#!/usr/bin/python
# -*- coding: utf-8 -*-

__author__ = ('Kaan Akşit')
__version__ = '0.1'

# Importing necessary libraries.
try:
    import sys,time,os,datetime,logging
    from kivy.logger import Logger

kaanaksit

#!/usr/bin/python
# -*- coding: utf-8 -*-

__author__  = ('Kaan Akşit')
                                                                                                                                     
try:                                                                                                                                 
    import sys,time                                                                                                                  
    from array import array                                                                                                          
    from jnius import autoclass                                                                                                      
    from jnius import cast