# coding: utf-8

# In[1]:

from __future__ import print_function, division

get_ipython().magic(u'matplotlib inline')

import thinkdsp

import thinkplot

import thinkstats2

import numpy as np

import pandas as pd

import scipy.signal

np.set_printoptions(precision=3, suppress=True)

# In[2]:

PI2 = 2 * np.pi

GRAY = '0.7'

# In[3]:

signal = thinkdsp.SquareSignal(freq=440)

wave = signal.make_wave(duration=1, framerate=4400)

segment = wave.segment(duration=0.01)

# In[4]:

window = np.ones(11)

window /= sum(window)

# In[5]:

ys = segment.ys

N = len(ys)

padded = thinkdsp.zero_pad(window, N)

# In[6]:

prod = padded * ys

# In[7]:

sum(ys)

# In[8]:

convolved = np.convolve(ys, window, mode='valid')

smooth2 = thinkdsp.Wave(convolved, framerate=wave.framerate)

smooth2

# In[9]:

spectrum = wave.make_spectrum()

spectrum.plot(color='GRAY')

# In[10]:

convolved = np.convolve(wave.ys, window, mode='same')

smooth = thinkdsp.Wave(convolved, framerate=wave.framerate)

spectrum2 = smooth.make_spectrum()

spectrum2.plot()

# In[11]:

amps = spectrum.amps

amps2 = spectrum2.amps

ratio = amps2 / amps

ratio[amps<560] = 0

thinkplot.plot(ratio)

# In[12]:

padded = zero_pad(window, N)

dft_window = np.fft.rfft(padded)

thinkplot.plot(abs(dft_window))

# In[ ]:

gaussian = scipy.signal.gaussian(M=11, std=2)

gaussian /= sum(gaussian)

# In[ ]:

names = ['date', 'open', 'high', 'low', 'close', 'volume']

df = pd.read_csv('C:\Users\esehu\Downloads\FB.csv', header=0, names=names, parse_dates=[0])

df.head()

# In[ ]:

signal = thinkdsp.SawtoothSignal(freq=440)

wave = signal.make_wave(duration=1.0, framerate=44100)

wave.make_audio()

# In[ ]:

window = np.ones(11)

window /= sum(window)

thinkplot.plot(window)

# In[ ]:

segment = wave.segment(duration=0.01)

segment.plot()

thinkplot.config(xlabel='Time (s)', ylim=[-1.05, 1.05])

# In[ ]:

N = len(segment)

padded = thinkdsp.zero_pad(window, N)

thinkplot.plot(padded)

thinkplot.config(xlabel='Index')

# In[ ]:

prod = padded * segment.ys

print(sum(prod))

# In[ ]:

smoothed = np.zeros(N)

rolled = padded.copy()

for i in range(N):

smoothed[i] = sum(rolled * segment.ys)

rolled = np.roll(rolled, 1)

# In[ ]:

segment.plot(color=GRAY)

smooth = thinkdsp.Wave(smoothed, framerate=wave.framerate)

smooth.plot()

thinkplot.config(xlabel='Time(s)', ylim=[-1.05, 1.05])

# In[ ]:

segment.plot(color=GRAY)

ys = np.convolve(segment.ys, window, mode='valid')

smooth2 = thinkdsp.Wave(ys, framerate=wave.framerate)

smooth2.plot()

thinkplot.config(xlabel='Time(s)', ylim=[-1.05, 1.05])

# In[ ]:

convolved = np.convolve(wave.ys, window, mode='same')

smooth = thinkdsp.Wave(convolved, framerate=wave.framerate)

smooth.make_audio()

# In[ ]:

spectrum = wave.make_spectrum()

spectrum.plot(color=GRAY)

spectrum2 = smooth.make_spectrum()

spectrum2.plot()

thinkplot.config(xlabel='Frequency (Hz)',

ylabel='Amplitude',

xlim=[0, 22050])

# In[ ]:

amps = spectrum.amps

amps2 = spectrum2.amps

ratio = amps2 / amps

ratio[amps<280] = 0

thinkplot.plot(ratio)

thinkplot.config(xlabel='Frequency (Hz)',

ylabel='Amplitude ratio',

xlim=[0, 22050])

# In[ ]:

padded = thinkdsp.zero_pad(window, len(wave))

dft_window = np.fft.rfft(padded)

thinkplot.plot(abs(dft_window), color=GRAY, label='DFT(window)')

thinkplot.plot(ratio, label='amplitude ratio')

thinkplot.config(xlabel='Frequency (Hz)',

ylabel='Amplitude ratio',

xlim=[0, 22050], loc='upper right')

# In[ ]:

boxcar = np.ones(11)

boxcar /= sum(boxcar)

# In[ ]:

gaussian = scipy.signal.gaussian(M=11, std=2)

gaussian /= sum(gaussian)

# In[ ]:

thinkplot.preplot(2)

thinkplot.plot(boxcar, label='boxcar')

thinkplot.plot(gaussian, label='Gaussian')

thinkplot.config(xlabel='Index',

loc='upper right')

# In[ ]:

ys = np.convolve(wave.ys, gaussian, mode='same')

smooth = thinkdsp.Wave(ys, framerate=wave.framerate)

spectrum2 = smooth.make_spectrum()

# In[ ]:

amps = spectrum.amps

amps2 = spectrum2.amps

ratio = amps2 / amps

ratio[amps<560] = 0

# In[ ]:

padded = thinkdsp.zero_pad(gaussian, len(wave))

dft_gaussian = np.fft.rfft(padded)

# In[ ]:

thinkplot.plot(abs(dft_gaussian), color='0.7', label='Gaussian filter')

thinkplot.plot(ratio, label='amplitude ratio')

thinkplot.config(xlabel='Frequency (Hz)',

ylabel='Amplitude ratio',

xlim=[0, 22050])

# In[ ]:

def plot_filter(M=11, std=2):

ylim=[0, 1.05])

# In[15]:

plot_filter

# In[13]:

plot_filter(M=11, std=2)

# In[14]:

from ipywidgets import interact, interactive, fixed

import ipywidgets as widgets

slider = widgets.IntSlider(min=2, max=100, value=11)

slider2 = widgets.FloatSlider(min=0, max=20, value=2)

interact(plot_filter, M=slider, std=slider2);