def test_odd_length_filter(self):
start = datetime(1951, 3, 31)
end = datetime(1958, 12, 31)
x = self.data[0]
res = convolution_filter(x, [.75, .5, .3, .2, .1])
expected = self.expected.conv2_odd
np.testing.assert_almost_equal(res.values.squeeze(), expected)
np.testing.assert_(res.index[0] == start)
np.testing.assert_(res.index[-1] == end)
res = convolution_filter(x, [.75, .5, .3, .2, .1], nsides=1)
expected = self.expected.conv1_odd
np.testing.assert_almost_equal(res.values.squeeze(), expected)
np.testing.assert_(res.index[0] == start)
np.testing.assert_(res.index[-1] == end)
# with no NAs
# not a stable filter
res = recursive_filter(x, [.75, .5, .3, .2, .1], init=[150, 100,
125, 135,
145])
expected = self.expected.recurse_odd
# only have 12 characters in R and this blows up and gets big
np.testing.assert_almost_equal(res.values.squeeze(), expected, 4)
np.testing.assert_(res.index[0] == start)
np.testing.assert_(res.index[-1] == end)
def test_pandas(self):
start = datetime(1951, 3, 31)
end = datetime(1958, 12, 31)
x = self.data[0]
res = convolution_filter(x, [.75, .25])
assert_(res.index[0] == start)
assert_(res.index[-1] == end)
res = convolution_filter(x, [.75, .25], nsides=1)
assert_(res.index[0] == start)
# with no nan-padding q1 if not
assert_(res.index[-1] == end)
res = recursive_filter(x, [.75, .25])
assert_(res.index[0] == start)
assert_(res.index[-1] == end)
x = self.datana
res = recursive_filter(x, [.75, .25])
assert_(res.index[0] == start)
assert_(res.index[-1] == end)
def test_recursive(self):
x = self.data.values.squeeze()
res = recursive_filter(x, [.75, .25])
expected = self.expected.recurse
np.testing.assert_almost_equal(res, expected)
res = recursive_filter(x, [.75, .25], init=[150, 100])
expected = self.expected.recurse_init
np.testing.assert_almost_equal(res, expected)
x = self.datana.values.squeeze()
res = recursive_filter(x, [.75, .25])
expected = self.expected.recurse_na
np.testing.assert_almost_equal(res, expected)
res = recursive_filter(x, [.75, .25], init=[150, 100])
expected = self.expected.recurse_init_na
np.testing.assert_almost_equal(res, expected)
assert_raises(ValueError, recursive_filter, x,
[.75, .25, .5], [150, 100])
def recursive_filter_function(signal):
signal = shift_array(signal)
filter_length = len(filter_freq)
signal = recursive_filter(signal, filter_freq)[300:]
return signal
def rec_fil(x):
xtmp = x.iloc[1:301].append(x.iloc[1:])
ftmp = recursive_filter(xtmp, taps)[300:]
return ftmp
def adstock(x, rate, y):
y['adstock'] = sm.recursive_filter(x,rate)
return y