%pylab inline
from __future__ import print_function
from __future__ import division
from scipy.io import wavfile
import wave
sr, mysamples = wavfile.read('03.wav')
plot(mysamples)
Populating the interactive namespace from numpy and matplotlib
[<matplotlib.lines.Line2D at 0x1477c1cd0>]
ratio = 1
threshold = 16000
mod = 4
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x147898f50>
ratio = 1
threshold = 16000
mod = 7
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x14ab0e4d0>
ratio = 1
threshold = 16000
mod = 10
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x1484b64d0>
ratio = 1
threshold = 25000
mod = 4
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x13e89d910>
ratio = 1
threshold = 25000
mod = 7
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x13a8adf50>
ratio = 1
threshold = 25000
mod = 10
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x149179a10>
ratio = 1
threshold = 30000
mod = 4
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x141bbdf50>
ratio = 1
threshold = 30000
mod = 7
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x149e3df50>
ratio = 1
threshold = 30000
mod = 10
height = int(sqrt(len(mysamples)/ratio))
width = int(height * ratio)
flag = 1
flag2 = 1
img = zeros([height,width],uint8)
for i in range(0,height):
for j in range(0,width):
if mysamples[i*width+j] > threshold:
img[i,j] = 3*mysamples[i*width+j]
flag = (flag+1)%mod
if flag == (mod-1):
flag2 = (flag2+1)%2
img[i,j] = int(255) * flag2
imshow(img,cmap=cm.gray)
<matplotlib.image.AxesImage at 0x143558a10>