-
Notifications
You must be signed in to change notification settings - Fork 0
/
generate_submission.py
76 lines (50 loc) · 1.71 KB
/
generate_submission.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
import sys
import numpy as np
from scipy.io import wavfile
def output(partIdx):
outputString = ''
if partIdx == '1': # This is ScaledFFTdB
from assignment1 import scaled_fft_db
r,x = wavfile.read('data/a1_submissionInput.wav')
X = scaled_fft_db(x)
for val in X:
outputString += '%.5f ' % (val)
elif partIdx == '2': # This is PrototypeFilter
from assignment2 import prototype_filter
h = prototype_filter()
# test signal
s = np.loadtxt('data/a2_submissionInput.txt')
r = np.convolve(h, s)[4*512:5*512]/2
for val in r:
outputString += '%.5f ' % val
elif partIdx == '3': # This is SubbandFiltering
from assignment3 import subband_filtering
r,x = wavfile.read('data/a3_submissionInput.wav')
h = np.hanning(512)
X = subband_filtering(x, h)
for val in X:
outputString += '%.5f ' % (val)
elif partIdx == '4': # This is Quantization
from assignment4 import quantization
from parameters import EncoderParameters
params = EncoderParameters(44100, 2, 64)
val_in = np.loadtxt('data/a4_submissionInput.txt')
for r,row in enumerate(val_in):
val = row[0]
scf = row[1]
ba = int(row[2])
QCa = params.table.qca[ba-2]
QCb = params.table.qcb[ba-2]
val = quantization(val, scf, ba, QCa, QCb)
outputString += '%d ' % (val)
else:
print "Unknown assigment part number"
if len(outputString) > 0:
fileName = "res%s.txt" % partIdx;
with open(fileName, "w") as f:
f.write(outputString.strip())
print "You can now submit the file " + fileName
else:
print "there was an error with the computation. Please check your code"
if __name__ == "__main__":
output(sys.argv[1])