andrewgiessel

andrewgiessel

andrewgiessel

andrewgiessel

andrewgiessel

PREFIX=$HOME
VERSION=1.2.3

# Install Protocol Buffers
wget http://protobuf.googlecode.com/files/protobuf-2.4.1.tar.bz2
tar -xf protobuf-2.4.1.tar.bz2 
cd protobuf-2.4.1
./configure --prefix=$PREFIX
make
make install

andrewgiessel

from scipy.signal import butter, lfilter

def butter_bandpass_filter(data, lowcut, highcut, fs, order=5):
    nyq = 0.5 * fs
    low = lowcut / nyq
    high = highcut / nyq

    b, a = butter(order, [low, high], btype='band')
    y = lfilter(b, a, data)
    return y

andrewgiessel

import numpy as np
def histeq(im,nbr_bins=256):

   #get image histogram
   imhist,bins = np.histogram(im.flatten(),nbr_bins,normed=True)
   cdf = imhist.cumsum() #cumulative distribution function
   cdf = 255 * cdf / cdf[-1] #normalize

   #use linear interpolation of cdf to find new pixel values
   im2 = np.interp(im.flatten(),bins[:-1],cdf)

andrewgiessel

import numpy as np

def makeGaussian(size, fwhm = 3, center=None):
    """ Make a square gaussian kernel.

    size is the length of a side of the square
    fwhm is full-width-half-maximum, which
    can be thought of as an effective radius.
    """

andrewgiessel

import matplotlib.pyplot as plt
import numpy as np

data = np.fromfile('/path/to/file.csv', sep=',')

fig = plt.figure()
plt.plot(data)
fig.savefig('/path/to/file.svg', format='svg')

andrewgiessel

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