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Use linear regression in sigproc

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Roman Zeyde
2014-08-01 10:42:08 +03:00
parent 5508ffc0d3
commit b8f486dd65
2 changed files with 17 additions and 19 deletions
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20
test_sigproc.py
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@@ -1,12 +1,12 @@
import sigproc
import itertools
import common
import config
import numpy as np
import random
def test_qam():
q = sigproc.QAM(common.symbols)
q = sigproc.QAM(config.symbols)
r = random.Random(0)
m = q.bits_per_symbol
bits = [tuple(r.randint(0, 1) for j in range(m)) for i in range(1024)]
@@ -16,12 +16,10 @@ def test_qam():
assert decoded == bits
def test_drift():
fc = 10e3
df = 1.23
f = fc + df
x = np.cos(2 * np.pi * f / common.Fs * np.arange(common.Fs))
S = sigproc.extract_symbols(x, fc)
S = np.array(list(S))
df_ = sigproc.drift(S) / common.Tsym
assert abs(df - df_) < 1e-5, (df, df_)
def test_linreg():
x = np.array([1, 3, 2, 8, 4, 6, 9, 7, 0, 5])
a, b = 12.3, 4.56
y = a * x + b
a_, b_ = sigproc.linear_regression(x, y)
assert abs(a - a_) < 1e-10
assert abs(b - b_) < 1e-10