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

# MAT 201A Winter 2016 
# HW 4 
# Qiaodong Cui

# In[1]:


get_ipython().run_line_magic('pylab', 'inline')
rcParams['figure.figsize'] = (10, 4) #wide graphs by default
from __future__ import print_function
from __future__ import division
from scipy.io import wavfile
get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


rtom, tom = wavfile.read('tom.wav')      #read music file
rpia, pia = wavfile.read('piano.wav')
rglo, glo = wavfile.read('glockenspiel.wav')


# In[3]:


from IPython.display import Audio
Audio(tom,rate=rtom)


# In[4]:


Audio(pia,rate=rpia)


# In[5]:


Audio(glo,rate=rglo)


# In[6]:


plot(tom)   #plot first music


# In[7]:


X = abs(fft.rfft(glo)) / (glo.size/2)   #rfft, normalize, for the glockenspiel music


# In[8]:


plot(X)     #plot frequency for glockenspiel
xlim(1000,1200)   #the maximum freq bin is within this range


# In[9]:


argmax(X)    #find maximum bin


# $$  f  = \frac{f_0 * f_s}{N} $$
# $ f $ frequency, $ f_0 $ freq bin, $f_s$ sample rate, $N$ number of samples

# In[10]:


def get_Pin(wav, srate):
    X = abs(fft.rfft(wav)) / (wav.size/2)    #first do a rfft, and normalize
    b = argmax(X)    #find maximum bin
    return b*srate / wav.size     #the above equation


# In[11]:


get_Pin(tom, rtom)    #maximum frequency for tom.wav


# In[12]:


get_Pin(pia, rpia)     #maximum frequency for piano.wav


# In[13]:


get_Pin(glo, rglo)    #maximum frequency for glockenspiel.wav


# In[ ]: