In [1]:

    

from __future__ import division, print_function

%matplotlib inline
%config InlineBackend.figure_format = "retina"

from matplotlib import rcParams
rcParams["savefig.dpi"] = 100
rcParams["font.size"] = 20


    

In [85]:

    

import kplr
import numpy as np
import matplotlib.pyplot as pl

from IPython.display import Audio


    

In [259]:

    

def envelope(attack, decay, sustain, release, sustain_level, t):
    t1 = decay + attack
    t2 = decay + attack + sustain
    t3 = decay + attack + sustain + release
    return (
        (0 <= t) * (t < attack) * t / attack +
        (attack <= t) * (t < t1) * (1.0 - (1 - sustain_level) * (t - attack) / decay) +
        (t1 <= t) * (t < t2) * sustain_level +
        (t2 <= t) * (t < t3) * sustain_level * (1.0 -  (t - t2) / release)
    )
    

def render_note(amp, freq, t0, t, attack=0.01, decay=0.1, sustain=0.4, release=0.2, sustain_level=0.3, out=None):
    if out is None:
        out = np.zeros_like(t)
    out[:] += amp * envelope(attack, decay, sustain, release, sustain_level, t - t0) * np.sin(2 * np.pi * freq * t)
    return out


    

In [260]:

    

client = kplr.API()
kois = client.kois(where="koi_disposition+like+'CONFIRMED'")


    

In [261]:

    

radii = [k.koi_prad for k in kois if k.koi_prad is not None and k.koi_prad < 7.0 and k.koi_period < 10.0]
periods = [k.koi_period for k in kois if k.koi_prad is not None and k.koi_prad < 7.0 and k.koi_period < 10.0]
t0s = [k.koi_time0bk % k.koi_period for k in kois if k.koi_prad is not None and k.koi_prad < 7.0 and k.koi_period < 10.0]


    

In [272]:

    

notes = [
#  65.406,  # C
# #  69.296,
#  73.416,  # D
#  77.782,
# #  82.407,  # E
#  87.307,  # F
# #  92.499,
#  97.999,  # G
# #  103.826,
# #  110.000,  # A
#  116.541,
# #  123.471,  # B
 130.813,  # C
#  138.591,
#  146.832,  # D
#  155.563,
 164.814,  # E
#  174.614,  # F
#  184.997,
 195.998,  # G
#  207.652,
#  220.000,  # A
#  233.082,
 246.942,  # B
 261.626,  # C
#  277.183,
#  293.665,  # D
#  311.127,
 329.628,  # E
#  349.228,  # F
#  369.994,
 391.995,  # G
#  415.305,
#  440.000,  # A
 466.164,  
#  493.883,  # B
 523.251,  # C
#  554.365,
#  587.330,  # D
#  622.254,
 659.255,  # E
#  698.456,  # F
# #  739.989,
#  783.991,  # G
# #  830.609,
# #  880.000,  # A
#  932.328,
# #  987.767,  # B
]


    

In [273]:

    

n, bins, _ = pl.hist(np.log(radii), len(notes) - 1);


    

In [274]:

    

radius_inds = np.digitize(radii, bins) - 1


    

In [275]:

    

print(max(radius_inds), len(notes))


    

    




9 10

In [276]:

    

sample_rate = 22100


    

In [277]:

    

t = np.arange(0, 10., 1.0 / sample_rate)

y = None
factor = 10.0
for i in range(len(periods)):
    t0 = factor * t0s[i]
    freq = notes[np.random.randint(len(notes))]
    while t0 < t[-1]:
        y = render_note(1. - 0.2 * (radii[i] - np.min(radii)) / (np.max(radii) - np.min(radii)),
                        freq, t0, t, out=y)
        t0 += factor * periods[i]


    

In [278]:

    

Audio(data=y, rate=sample_rate)


    

    
Out[278]:





                
              

In [269]:

    

pl.plot(t, y)
# for i in range(len(periods)):
#     pl.axvline(t0s[i], color="k", alpha=0.1)


    

    
Out[269]:





[<matplotlib.lines.Line2D at 0x116037310>]






    

In [132]:

    

t2 = np.arange(0, 1., 1.0 / sample_rate)
y2 = render_note(1.0, 440., 0.0, t2)


    

In [140]:

    

pl.plot(t2, y2)


    

    
Out[140]:





[<matplotlib.lines.Line2D at 0x10bec0690>]






    

In [134]:

    

Audio(data=y2, rate=sample_rate)


    

    
Out[134]:





                
              

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