```python
%matplotlib inline
```

# 592B, Class 3.2 (09/19). Square waves, resampling adventures

You can get `librosa` by following the instructions at the [librosa github site](https://github.com/librosa/librosa). Follow the instructions for Anaconda. You should also take a look at the [demo jupyter notebook](http://nbviewer.jupyter.org/github/librosa/librosa/blob/master/examples/LibROSA%20demo.ipynb). Note for example, that by default, when audio files are read in they are remixed to mono and resampled to 22050 Hz.

```python
import numpy as np
import matplotlib.pyplot as plt
import scipy.io.wavfile as wavfile
import scipy.signal as signal
import librosa #new!

from ipywidgets import interactive
from IPython.display import Audio, display
```

## Review questions

### Define a square wave function

Define a square wave function $f(t)$ with a period of $T=0.5s$, with a range of [0,2], with a value of 0 at $x=0$.

(1a) Do this using [`scipy.signal.square`](https://docs.scipy.org/doc/scipy-0.14.0/reference/generated/scipy.signal.square.html).

To help understand `scipy.signal.square`, first let's look at the examples from `help` for `scipy.signal.square` and try out the first one--just copy and paste the code in.

```python
help(signal.square)
```

    Help on function square in module scipy.signal.waveforms:

    square(t, duty=0.5)
        Return a periodic square-wave waveform.

        The square wave has a period ``2*pi``, has value +1 from 0 to
        ``2*pi*duty`` and -1 from ``2*pi*duty`` to ``2*pi``. `duty` must be in
        the interval [0,1].

        Note that this is not band-limited.  It produces an infinite number
        of harmonics, which are aliased back and forth across the frequency
        spectrum.

        Parameters
        ----------
        t : array_like
            The input time array.
        duty : array_like, optional
            Duty cycle.  Default is 0.5 (50% duty cycle).
            If an array, causes wave shape to change over time, and must be the
            same length as t.

        Returns
        -------
        y : ndarray
            Output array containing the square waveform.

        Examples
        --------
        A 5 Hz waveform sampled at 500 Hz for 1 second:

        >>> from scipy import signal
        >>> import matplotlib.pyplot as plt
        >>> t = np.linspace(0, 1, 500, endpoint=False)
        >>> plt.plot(t, signal.square(2 * np.pi * 5 * t))
        >>> plt.ylim(-2, 2)

        A pulse-width modulated sine wave:

        >>> plt.figure()
        >>> sig = np.sin(2 * np.pi * t)
        >>> pwm = signal.square(2 * np.pi * 30 * t, duty=(sig + 1)/2)
        >>> plt.subplot(2, 1, 1)
        >>> plt.plot(t, sig)
        >>> plt.subplot(2, 1, 2)
        >>> plt.plot(t, pwm)
        >>> plt.ylim(-1.5, 1.5)

Here's the first example:

> A 5 Hz waveform sampled at 500 Hz for 1 second:

```python
from scipy import signal
import matplotlib.pyplot as plt
t = np.linspace(0, 1, 500, endpoint=False)
plt.plot(t, signal.square(2 * np.pi * 5 * t))
plt.ylim(-2, 2)
```

Let's try it:

```python
t = np.linspace(0, 3, 500, endpoint=False)
#plt.plot(t, signal.square(2 * np.pi * 5 * t))
#plt.plot(t, signal.square(t))
# Plot a square wave with a period of 1s (1Hz)

#plt.plot(t, signal.square(2 * np.pi * 1 * t))

# Plot a square wave with a period of 3s, (1/3 Hz)
plt.plot(t, 0.5 + 0.5 * signal.square(2 * np.pi * 1/3 * t))
plt.ylim(-1, 3)
```

Note that this function `signal.square(2 * np.pi * 5 * t)` has an f0 of 5Hz, a period of 1/5 s, and a range of [-1,1].

(1b) Define the same function using a conditional `if`...`else` structure, and Python's [*modulus* operator](https://docs.python.org/2/reference/expressions.html#binary-arithmetic-operations), `%`.

Here's an example to get you started, for `scipy.signal.square` with a range of [-1,1], $T=2$, and $f(0)=1$. First let's plot what this looks like.

```python
t = np.linspace(0, 5, 500)
plt.plot(t, signal.square(2*np.pi*0.5*t))
plt.axhline(y=0, color='r', linestyle='-') # Show x-axis
```

To define this "by hand", I need to say something like:
> From 0 to $\pi$, $f(t)=1$. From $\pi$ to $2\pi$, $f(t) = -1$. And so on, for a period of $T=2\pi$.

In other words,
- if $t/2$ has a remainder < 1, then $f(t)=1$.
- Otherwise, $f(t)=-1$.

We can implement this as follows:

```python
def my_square(x): # define your own square function!
    if (x % 2 < 1): # if x/2 has a remainder < 1
        y = 1 # then return y=1
    else:
        y = -1 # else, return y=-1
    return(y)

# Spot checks, compare to what we expect
print(my_square(2))
print(my_square(2.5))
print(my_square(3))
print(my_square(3.5))
print(my_square(4))

# Now let's try using a list comprehension over a vector of t-values
ts = np.linspace(0, 5, 500)
plt.plot(t, [my_square(t) for t in ts])
plt.axhline(y=0, color='r', linestyle='-') # Show x-axis
```

***Now you try, for a square wave function f(t) with a period of $T=3s$, a range of [0,2], and a value of 0 at $x=0$.***

### Resampling adventures

For some further reading on resampling audio in Python, check out [Joachim Thiemann's blog post](https://signalsprocessed.blogspot.com/2017/05/resampling-in-python-electric-bugaloo.html). This is from 2017, so it may be a little outdated, but it's still interesting.

First, let's read in the WAV file and print the sampling rate `fs` and the number of samples in the signal, `len(data)`.

```python
fs, data = wavfile.read('hmong_m6_24_c.wav')
ns = len(data) # number of samples
print("The sampling rate is", fs, "Hz.")
print("The number of samples is", ns, "samples.")
```

    The sampling rate is 22050 Hz.
    The number of samples is 35015 samples.

***In-class exercise: What is the duration of the audio file? Define `t_start` = 0, and `t_stop` as the total duration you compute.***

```python
t_start = 0
t_stop = ns/fs
print(t_stop)
```

    1.587981859410431

Here's an example reading in an audio file with `librosa.load` and resampling with librosa `librosa.core.resample`. The original WAV file in this case is already sampled at 22050 Hz. We re-sample to 8000 Hz and 2000 Hz.

***In-class exercise: Play around with different rates for resampling. At what sampling rate do you start hearing a difference between the resampled audio and the original? What kind of difference do you hear as the sampling rate drops?***

```python
y, sr = librosa.load("hmong_m6_24_c.wav")
print(type(y)) # Note that it is a numpy array
print("The sampling rate is: ", sr, "Hz")

y_8k = librosa.resample(y, sr, 8000)
y_2k = librosa.resample(y, sr, 2000)
y_500 = librosa.resample(y, sr, 500)

display(Audio(data=y,rate = sr))
display(Audio(data=y_8k,rate = 8000))
display(Audio(data=y_2k,rate = 2000))
display(Audio(data=y_500,rate = 500))
```

    <class 'numpy.ndarray'>
    The sampling rate is:  22050 Hz

<audio  controls="controls" >
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***In-class exercise: What if the WAV file had been sampled at 44.kHz and you didn't want it to be resampled when read into python? How would you do that? How does the resampling algorithm used by librosa compared to that used by scipy.signal?***

Now let's try resampling from $f_s=22.05\,kHz$ to $f_{s,new} = 11\,kHz$.
To do that, we need to specify a new number of samples for the resampled signal, $ns_{new}$.
Note that the ratio by which we "downsample", $22.05/11$, is the ratio by which the number of samples increases. That is:

\begin{equation}
\frac{ns_{new}}{ns} = \frac{f_{s}}{f_{s,new}}
\end{equation}

and therefore,

\begin{equation}
ns_{new} = \frac{f_{s}}{f_{s,new}} \cdot ns
\end{equation}
So we can resample as follows:

```python
fs_new = 6000

y_new = librosa.resample(y, sr, fs_new)
print("The number of samples in the re-sampled signal is", len(y_new), "samples.")

#Note that `signal.resample` can also take an additional argument,
#the original vector of sampled timepoints, and then return
#the new vector of sampled timepoints for the resampled signal.
```

    The number of samples in the re-sampled signal is 9528 samples.

Now let's try plotting the two signals for comparison, adapting from the help example code.

```python
plt.plot(y,'g.', y_new, '.-')
plt.xlim(3000,4000)
plt.legend(['y', 'y_new'], loc='best')
plt.xlabel("Sample number")
plt.ylabel("Amplitude")
```

***In-class exercise. Examine this plot and comment on it. Then, plot with time in seconds on the x-axis rather than number of samples.***

```python
ns_new = int(np.floor((t_stop - t_start) * fs_new + 1))

print(ns_new)
print(len(y_new))

x = np.linspace(t_start, t_stop, ns)
x_new = np.linspace(t_start, t_stop, ns_new)

plt.plot(x, y,'g.', x_new, y_new,'.-')
plt.xlim(0.5,0.51)
plt.legend(['data', 'resampled'], loc='best')
plt.xlabel("Time(s)")
plt.ylabel("Amplitude")

```

OK, now let's try listening to this.

```python
display(Audio(data=y_new,rate = fs_new))
```

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type="audio/wav" />
    Your browser does not support the audio element.
</audio>

***In-class exercise: suppose you sample at a sampling rate of 4.5 Hz. Overlay the stem plot with the original signal for this sampling rate (like the previous plots).***

## The sampling theorem

The minimal sampling rate that can be used to reconstruct a signal from its samples is two times the frequency of the highest frequency component $\nu_{max}$ in the signal:

   sampling rate $> 2\nu_{max}$

The frequency 2$\nu_{max}$ is often called the **Nyquist frequency**.

***In-class exercise: What is the Nyquist frequency for $y(t)$ below?***

$$y(t) = \cos \left(\frac{9\pi}{2}t\right ) $$

So for a complex wave (a sum of sinusoids), increasing the frequency of the highest frequency component $\nu_{max}$ drives up the required sampling rate for reconstruction. Sometimes there is no highest frequency, e.g., in an infinite series like for a square wave.

Here's a intuitive example to play with. Plot a signal composed of a low frequency sinusoid and a high frequency sinusoid. As the gap in frequencies between the two frequency components increases, the resulting complex wave looks closer and closer to the lower frequency component, with lots of squigglies up and down at the frequency of the higher frequency component.

```python
def plot_play_summed_sines(f1 = 440, f2 = 880, t_start = 0, t_stop = 2, fs = 44100, xlim_max = 0.01):
    x = np.linspace(t_start, t_stop, fs * (t_stop - t_start))
    y1 = np.sin(2*np.pi*f1*x)
    y2 = np.sin(2*np.pi*f2*x)

    plt.xlim(t_start,xlim_max)
    plt.plot(x , y1, "-g", label="y1")
    plt.plot(x , y2, "-b", label="y2")
    plt.plot(x , y1 + y2, "-r", label="y1+y2")
    plt.legend(loc="upper right")
    plt.xlabel('Time (s)')
    plt.ylabel('Amplitude (dB)')
    plt.title("Adding up sines")

    display(Audio(data=y1, rate=fs))
    display(Audio(data=y2, rate=fs))
    display(Audio(data=y1+y2, rate=fs))

v = interactive(plot_play_summed_sines, f1=(50,200), f2=(1000,5000), t_start = (0,0), t_stop = (0,5), xlim_max = (0.01,0.5))
display(v)
```

    interactive(children=(IntSlider(value=200, description='f1', max=200, min=50), IntSlider(value=1000, descripti…

If we **undersample**, we get **aliasing**: two functions may be indistinguishable based on our sampling, and we may recover a lower frequency alias of the actual signal. We can also have [visual aliasing](http://danielwalsh.tumblr.com/post/54400376441/playing-detective-with-rolling-shutter-photos).