def test_003(self):
offsets = (6, 3, 8)
key = pmt.string_to_symbol('key')
srcid = pmt.string_to_symbol('qa_tag_utils')
tags = []
for k in offsets:
t = gr.tag_t()
t.offset = k
t.key = key
t.value = pmt.from_long(k)
t.srcid = srcid
tags.append(t)
for k, t in zip(sorted(offsets),
sorted(tags, key=gr.tag_t_offset_compare_key())):
self.assertEqual(t.offset, k)
self.assertTrue(pmt.equal(t.key, key))
self.assertTrue(pmt.equal(t.value, pmt.from_long(k)))
self.assertTrue(pmt.equal(t.srcid, srcid))
tmin = min(tags, key=gr.tag_t_offset_compare_key())
self.assertEqual(tmin.offset, min(offsets))
self.assertTrue(pmt.equal(tmin.key, key))
self.assertTrue(pmt.equal(tmin.value, pmt.from_long(min(offsets))))
self.assertTrue(pmt.equal(tmin.srcid, srcid))
tmax = max(tags, key=gr.tag_t_offset_compare_key())
self.assertEqual(tmax.offset, max(offsets))
self.assertTrue(pmt.equal(tmax.key, key))
self.assertTrue(pmt.equal(tmax.value, pmt.from_long(max(offsets))))
self.assertTrue(pmt.equal(tmax.srcid, srcid))
def test_003(self):
offsets = (6, 3, 8)
key = pmt.string_to_symbol('key')
srcid = pmt.string_to_symbol('qa_tag_utils')
tags = []
for k in offsets:
t = gr.tag_t()
t.offset = k
t.key = key
t.value = pmt.from_long(k)
t.srcid = srcid
tags.append(t)
for k, t in zip(sorted(offsets),
sorted(tags, key=gr.tag_t_offset_compare_key())):
self.assertEqual(t.offset, k)
self.assertTrue(pmt.equal(t.key, key))
self.assertTrue(pmt.equal(t.value, pmt.from_long(k)))
self.assertTrue(pmt.equal(t.srcid, srcid))
tmin = min(tags, key=gr.tag_t_offset_compare_key())
self.assertEqual(tmin.offset, min(offsets))
self.assertTrue(pmt.equal(tmin.key, key))
self.assertTrue(pmt.equal(tmin.value, pmt.from_long(min(offsets))))
self.assertTrue(pmt.equal(tmin.srcid, srcid))
tmax = max(tags, key=gr.tag_t_offset_compare_key())
self.assertEqual(tmax.offset, max(offsets))
self.assertTrue(pmt.equal(tmax.key, key))
self.assertTrue(pmt.equal(tmax.value, pmt.from_long(max(offsets))))
self.assertTrue(pmt.equal(tmax.srcid, srcid))
def test_tag_propagation(self):
'''
test_tag_propagation: test that non length tags are handled correctly
'''
prepad = 10
postpad = 10
length1 = 15
length2 = 25
gap_len = 5
lentag1_offset = 0
lentag2_offset = length1 + gap_len
tag1_offset = 0 # accompanies first length tag
tag2_offset = length1 + gap_len # accompanies second length tag
tag3_offset = 2 # in ramp-up state
tag4_offset = length1 + 2 # in gap; tag will be dropped
tag5_offset = length1 + gap_len + 7 # in copy state
data = np.concatenate(
(np.ones(length1), np.zeros(gap_len), -1.0 * np.ones(length2)))
window = np.concatenate((-2.0 * np.ones(5), -4.0 * np.ones(5)))
tags = (make_length_tag(lentag1_offset, length1),
make_length_tag(lentag2_offset, length2),
make_tag(tag1_offset, 'head', pmt.intern('tag1')),
make_tag(tag2_offset, 'head', pmt.intern('tag2')),
make_tag(tag3_offset, 'body', pmt.intern('tag3')),
make_tag(tag4_offset, 'body', pmt.intern('tag4')),
make_tag(tag5_offset, 'body', pmt.intern('tag5')))
expected = np.concatenate(
(np.zeros(prepad), window[0:5], np.ones(length1 - len(window)),
window[5:10], np.zeros(postpad + prepad), -1.0 * window[0:5],
-1.0 * np.ones(length2 - len(window)), -1.0 * window[5:10],
np.zeros(postpad)))
elentag1_offset = 0
elentag2_offset = length1 + prepad + postpad
etag1_offset = 0
etag2_offset = elentag2_offset
etag3_offset = prepad + tag3_offset
etag5_offset = 2 * prepad + postpad + tag5_offset - gap_len
etags = (make_length_tag(elentag1_offset, length1 + prepad + postpad),
make_length_tag(elentag2_offset, length2 + prepad + postpad),
make_tag(etag1_offset, 'head', pmt.intern('tag1')),
make_tag(etag2_offset, 'head', pmt.intern('tag2')),
make_tag(etag3_offset, 'body', pmt.intern('tag3')),
make_tag(etag5_offset, 'body', pmt.intern('tag5')))
# flowgraph
source = blocks.vector_source_f(data, tags=tags)
shaper = digital.burst_shaper_ff(window,
pre_padding=prepad,
post_padding=postpad)
sink = blocks.vector_sink_f()
self.tb.connect(source, shaper, sink)
self.tb.run()
# checks
self.assertFloatTuplesAlmostEqual(sink.data(), expected, 6)
for x, y in zip(sorted(sink.tags(), key=gr.tag_t_offset_compare_key()),
sorted(etags, key=gr.tag_t_offset_compare_key())):
self.assertTrue(compare_tags(x, y))
def test_tag_propagation (self):
'''
test_tag_propagation: test that non length tags are handled correctly
'''
prepad = 10
postpad = 10
length1 = 15
length2 = 25
gap_len = 5
lentag1_offset = 0
lentag2_offset = length1 + gap_len
tag1_offset = 0 # accompanies first length tag
tag2_offset = length1 + gap_len # accompanies second length tag
tag3_offset = 2 # in ramp-up state
tag4_offset = length1 + 2 # in gap; tag will be dropped
tag5_offset = length1 + gap_len + 7 # in copy state
data = np.concatenate((np.ones(length1), np.zeros(gap_len),
-1.0*np.ones(length2)))
window = np.concatenate((-2.0*np.ones(5), -4.0*np.ones(5)))
tags = (make_length_tag(lentag1_offset, length1),
make_length_tag(lentag2_offset, length2),
make_tag(tag1_offset, 'head', pmt.intern('tag1')),
make_tag(tag2_offset, 'head', pmt.intern('tag2')),
make_tag(tag3_offset, 'body', pmt.intern('tag3')),
make_tag(tag4_offset, 'body', pmt.intern('tag4')),
make_tag(tag5_offset, 'body', pmt.intern('tag5')))
expected = np.concatenate((np.zeros(prepad), window[0:5],
np.ones(length1 - len(window)), window[5:10],
np.zeros(postpad + prepad), -1.0*window[0:5],
-1.0*np.ones(length2 - len(window)),
-1.0*window[5:10], np.zeros(postpad)))
elentag1_offset = 0
elentag2_offset = length1 + prepad + postpad
etag1_offset = 0
etag2_offset = elentag2_offset
etag3_offset = prepad + tag3_offset
etag5_offset = 2*prepad + postpad + tag5_offset - gap_len
etags = (make_length_tag(elentag1_offset, length1 + prepad + postpad),
make_length_tag(elentag2_offset, length2 + prepad + postpad),
make_tag(etag1_offset, 'head', pmt.intern('tag1')),
make_tag(etag2_offset, 'head', pmt.intern('tag2')),
make_tag(etag3_offset, 'body', pmt.intern('tag3')),
make_tag(etag5_offset, 'body', pmt.intern('tag5')))
# flowgraph
source = blocks.vector_source_f(data, tags=tags)
shaper = digital.burst_shaper_ff(window, pre_padding=prepad,
post_padding=postpad)
sink = blocks.vector_sink_f()
self.tb.connect(source, shaper, sink)
self.tb.run ()
# checks
self.assertFloatTuplesAlmostEqual(sink.data(), expected, 6)
for x, y in zip(sorted(sink.tags(), key=gr.tag_t_offset_compare_key()),
sorted(etags, key=gr.tag_t_offset_compare_key())):
self.assertTrue(compare_tags(x, y))
