Sargam In Python

I was intrigued to play sargam in Python. Found this simple audio package that plays numpy as music.

 

So, wanting to build sargam notes on it, found a way to play sargam and sharing the same here.

 

In the attachment, there is code that has two musical notes, one simple sargam and one is a famous "naagin" tune.

 

So what are sound waves. A scientific definition is as follows.

 

Sound waves - The physical phenomenon we call sound is originated by air molecule oscillations due to the mechanical energy emitted by an acoustic source. The displacement s(t) with respect to the equilibrium position of each molecule can be modelled as a sine function.

 

 

where,

• A – Amplitude
• T – Time period
• f – frequency measured in Hz
• f - phase

The sargam has the following frequencies.

 

 

 

The simpleaudio package of python makes it very interesting to create musical notes.

 

Step 1

 

Install simpleaudio

pip install simpleaudio

Step 2

 

Import these libraries

import numpy as np
import simpleaudio as sa
from itertools import repeat

Step 3

 

Create a dictionary of frequencies

sargamdict = {"sa":261,
             "re":294,
             "ga":330,
             "ma":349,
             "pa":392,
             "dha":440,
             "ni":494,
             "sa":515}

Step 4 - Define the play_audio function

 

Numpy arrays can be used to store audio but there are a few crucial requirements. If they are to store stereo audio, the array must have two columns since each column contains one channel of audio data. They must also have a signed 16-bit integer dtype and the sample amplitude values must consequently fall in the range of -32768 to 32767. Here is an example of a simple way to 'normalize' the audio (making it cover the whole amplitude rage but not exceeding it):

audio_array = audio_array.astype(np.int16)

And here is an example of converting it to the proper data type (note that this should always be done after normalization or other amplitude changes):

audio_array = audio_array.astype(np.int16)

def play_audio(audio):# normalize to 16-bit range
    audio *= 32767 / np.max(np.abs(audio))
    # convert to 16-bit data
    audio = audio.astype(np.int16)

    # start playback
    play_obj = sa.play_buffer(audio, 1, 2, sample_rate)

    # wait for playback to finish before exiting
    play_obj.wait_done()

Step 5

 

Get timesteps for each sample, T is note duration in seconds. For CD recordings, the industry standard is to store each audio sample as a 16-bit value, at 44100 samples per second.

 

sample_rate = 44100

T = 0.25
t = np.linspace(0, T, T * sample_rate, endpoint=False)

Step 6

 

Generate sine wave notes for sa re ga ma …

Sa_note = np.sin(sargamdict["sa"] * t * 3 * np.pi)
Re_note = np.sin(sargamdict["re"] * t * 3 * np.pi)
Ga_note = np.sin(sargamdict["ga"] * t * 3* np.pi)
Ma_note = np.sin(sargamdict["ma"] * t * 3 * np.pi)
Pa_note = np.sin(sargamdict["pa"] * t * 3 * np.pi)
Dha_note = np.sin(sargamdict["dha"] * t * 3 * np.pi)
Ni_note = np.sin(sargamdict["ni"] * t * 3 * np.pi)
Sa1_note = np.sin(sargamdict["sa1"] * t * 3 * np.pi)

Step 7

 

Create a pause note

get_pause  = lambda seconds: repeat(0, int(seconds * sample_rate))
pause_note=list(get_pause(0.01))

Step 8

 

Build the sargam

sargam = np.hstack((Sa_note,pause_note,Re_note,pause_note,Ga_note,
                   pause_note,Ma_note, pause_note,Pa_note, pause_note,
                    Dha_note, pause_note,Ni_note, pause_note, Sa1_note))

Step 9

 

 and play it !!

play_audio(sargam)
play_audio(sargam[::-1])

In case you are interested to view the sin waves for each note, you can view using following

import matplotlib.pyplot as plt
%matplotlib inline
plt.figure(figsize=(40,20))
plt.plot(t, Sa_note);

 

 

You can even save this numpy array as a .wav file using wavio library

pip install wavio
import wavio
fs = 44100
s2 = np.append(sargam,sargam[::-1])
wavio.write("pythonsargam.wav", s2, fs, scale=None, sampwidth=2)

Hope you enjoy creating music in Python.