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

# # MAT-201A ASSIGNMENT 2
# ## Ambika Yadav
# 
# Sonification on an Image by using image data as the spectrum on which an STFT was performed. To perform the STFT , the image data is extracted and stored as 1D arrays. These 1D arrays are accessed one window at a time and their corresponding fft is computed and stored in the final_sig.
# 

# In[2]:


get_ipython().run_line_magic('pylab', 'inline')
from __future__ import print_function
from __future__ import division
import IPython


# In[3]:


from scipy.io import wavfile


# In[17]:


img = imread('image2.png')
img2= imread('image4.jpg')


# Using a spiral grayscale image to create more pronounced sounds

# In[13]:


imshow(img)


# Use the green channel flattened array of the image as the magnitude spectrum.

# In[7]:


## Flattening the image (2D) into a (1D) array
sig_mag = array((img[:,:,1]).flat)
sig_phs = (array((img[:,:,0]).flat) + array((img[:,:,2]).flat))

#computing the length of the array
a= len(sig_mag)
# making a window of size 1/100th of the complete length of the arrays
windowsize = a/100
win_start = arange(0, a, windowsize)

mag_spec = []
phs_spec = []
final_sig = [] 

#computing ffts per window and adding on to the final signal final_sig
for i in win_start:
    mag_spec = sig_mag[i : i + windowsize]
    phs_spec = sig_phs[i : i + windowsize]
    X = [np.complex(cos(phs)* mag, -sin(phs)* mag) for mag, phs in zip(mag_spec, phs_spec)]
    x= fft.irfft(X) 
    final_sig = final_sig + list (x*100)
plot(final_sig)
    
    


# Use the sum of blue and red channel flattened array of the image as the phase spectrum.

# In[8]:


from IPython.display import Audio
Audio(final_sig,rate=16000)


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imshow(img2)


# In[19]:


## Flattening the image (2D) into a (1D) array
sig_mag = array((img2[:,:,1]).flat)
sig_phs = (array((img2[:,:,0]).flat) + array((img2[:,:,2]).flat))

#computing the length of the array
a= len(sig_mag)
# making a window of size 1/100th of the complete length of the arrays
windowsize = a/100
win_start = arange(0, a, windowsize)

mag_spec = []
phs_spec = []
final_sig = [] 

#computing ffts per window and adding on to the final signal final_sig
for i in win_start:
    mag_spec = sig_mag[i : i + windowsize]
    phs_spec = sig_phs[i : i + windowsize]
    X = [np.complex(cos(phs)* mag, -sin(phs)* mag) for mag, phs in zip(mag_spec, phs_spec)]
    x= fft.irfft(X) 
    final_sig = final_sig + list (x*100)
plot(final_sig)
    


# In[20]:


Audio(final_sig,rate=16000)