thearn

from numpy.fft import fft, ifft, fft2, ifft2, fftshift
import numpy as np

def fft_convolve2d(x,y):
    """ 2D convolution, using FFT"""
    fr = fft2(x)
    fr2 = fft2(np.flipud(np.fliplr(y)))
    m,n = fr.shape
    cc = np.real(ifft2(fr*fr2))
    cc = np.roll(cc, -m/2+1,axis=0)

thearn

import numpy as np


def low_rank_approx(SVD=None, A=None, r=1):
    """
    Computes an r-rank approximation of a matrix
    given the component u, s, and v of it's SVD

    Requires: numpy
    """

thearn

import pickle
import gzip

def save(object, filename, protocol = 0):
        """Saves a compressed object to disk
        """
        file = gzip.GzipFile(filename, 'wb')
        file.write(pickle.dumps(object, protocol))
        file.close()

thearn

import pprocess
import time
import numpy as np

# Define a function to parallelize:
def takeuptime(x):
    """A function to waste CPU cycles"""
    time.sleep(0.1)
    return x[-1]
    

thearn

def adjust(t, og):
    t2 = 1.34722124e-4 * t
    t3 = 2.04052596e-6 * t ** 2
    t4 = 2.32820948e-9 * t ** 3
    sgcf = 1.00130346 - t2 + t3 - t4
    sg = og * sgcf
    adjusted_og = sg
    OE = -668.962 + 1262.45 * sg - 776.43 * sg * sg + 182.94 * sg * sg * sg
    abv_max = (sg - 1) * 105 * 1.25

thearn

import numpy as np
import time


class bandProcess(object):

    """
    Component to isolate specific frequency bands
    """

thearn

import urllib
import re
import time
import datetime


def get_ip():
    group = re.compile(u'(?P<ip>\d+\.\d+\.\d+\.\d+)').search(
        urllib.URLopener().open('http://jsonip.com/').read()).groupdict()
    return group['ip']

thearn

import base64
import time
import urllib2

import cv2
import numpy as np


"""
Examples of objects for image frame aquisition from both IP and

thearn

import cv2

# Create object to read images from camera 0
cam = cv2.VideoCapture(1)


class imgSlice(object):

    def __init__(self):
        self.x = 0

thearn

import time
import Image
import ImageGrab

while True:
    time.sleep(0.5)
    t = str(time.time()).replace('.','-')
    tt = time.time()
    img=ImageGrab.grab()
    img = img.resize((800,600))