def setup_weights():
Tns.w0_array = []
Tns.w0 = Weights(Tns.w0_array, 1)
Tns.w1_array = [[j / 63.0 for j in range(i * 8, 8 + i * 8)] for i in range(8)]
Tns.w1 = Weights(Tns.w1_array, 1)
Tns.w2_array = [
[j / 63.0 for j in list(itertools.chain(*zip(itertools.repeat(NAN), range(i * 8, 4 + i * 8))))]
for i in range(8)
]
Tns.w2 = Weights(Tns.w2_array, 1)
Tns.w3_array = (
numpy.array(
splice(
[
(
list(itertools.chain(*zip(range(i * 8, 4 + i * 8), itertools.repeat(NAN)))),
list(itertools.chain(*zip(itertools.repeat(NAN), range(i * 8, 4 + i * 8)))),
)
for i in range(4)
]
),
dtype=float,
)
/ 63.0
)
Tns.w3 = Weights(Tns.w3_array, 1)
def test_rectilinear_ouput_rate_encoder_update_rates_and_get_rates():
rore = RectilinearOutputRateEncoder(Tns.p_mock, 8, 8, Tns.rore1_update_p, Tns.rore1_win_width) # 22 # 200
Tns.a_counter = 0
def inc_by_3(*args):
Tns.a_counter += 1
return Tns.a_counter / 64 * 3
Tns.count_mock.get = inc_by_3
for i in range(Tns.rore1_win_width / Tns.rore1_update_p + 1):
rore.update_rates(i * 22)
Tns.count_mock.assert_called()
for r in splice(rore.get_rates()):
assert_allclose(r, 3.0 / 22, atol=0.0001)
def test_rectilinear_ouput_rate_encoder_update_rates_with_irregular_period():
rore = RectilinearOutputRateEncoder(Tns.p_mock, 8, 8, Tns.rore1_update_p, Tns.rore1_win_width) # 22 # 200
Tns.a_counter = 0
def inc_by_3_or_6(*args):
cycle = Tns.a_counter / 64
Tns.a_counter += 1
return cycle / 2 * 6 + (cycle + 1) / 2 * 3
Tns.count_mock.get = inc_by_3_or_6
for i in range(2 * Tns.rore1_win_width / Tns.rore1_update_p + 1):
# 0 -> 0, 1 -> 11, 2 -> 33, 3 -> 44
rore.update_rates(i / 2 * 22 + (i + 1) / 2 * 11)
Tns.count_mock.assert_called()
for r in splice(rore.get_rates()):
assert_allclose(r, 9.0 / 33, atol=0.0001)
def test_rectilinear_ouput_rate_encoder_update_rates_and_get_rates():
rore = RectilinearOutputRateEncoder(
Tns.p_mock,
8,
8,
Tns.rore1_update_p, # 22
Tns.rore1_win_width) # 200
Tns.a_counter = 0
def inc_by_3(*args):
Tns.a_counter += 1
return Tns.a_counter / 64 * 3
Tns.count_mock.get = inc_by_3
for i in range(Tns.rore1_win_width / Tns.rore1_update_p + 1):
rore.update_rates(i * 22)
Tns.count_mock.assert_called()
for r in splice(rore.get_rates()):
assert_allclose(r, 3.0 / 22, atol=0.0001)
def select_kwta_winners(population, k, presentation_duration):
"""Returns the list of coordinates of the k most active units in
the population for the the presentation duration to the current
simulator time. Ties are broken using uniform random selection."""
argwinners = []
if k > 0:
rate_enc = get_rate_encoder(population)
rates = list(itertools.izip(splice(rate_enc.get_rates(t=presentation_duration)),
infinite_xrange()))
# we need to shuffle to randomize ties resolution
numpy.random.shuffle(rates)
winners = rates[0:k]
heapq.heapify(winners)
for r in rates[k:]:
if r[0] > winners[0][0]:
heapq.heapreplace(winners, r)
argwinners = [(w[1] / rate_enc.shape[0], w[1] % rate_enc.shape[0])
for w in winners]
return argwinners
def select_kwta_winners(population, k, presentation_duration):
"""Returns the list of coordinates of the k most active units in
the population for the the presentation duration to the current
simulator time. Ties are broken using uniform random selection."""
argwinners = []
if k > 0:
rate_enc = get_rate_encoder(population)
rates = list(
itertools.izip(splice(rate_enc.get_rates(t=presentation_duration)),
infinite_xrange()))
# we need to shuffle to randomize ties resolution
numpy.random.shuffle(rates)
winners = rates[0:k]
heapq.heapify(winners)
for r in rates[k:]:
if r[0] > winners[0][0]:
heapq.heapreplace(winners, r)
argwinners = [(w[1] / rate_enc.shape[0], w[1] % rate_enc.shape[0])
for w in winners]
return argwinners
def test_rectilinear_ouput_rate_encoder_update_rates_with_irregular_period():
rore = RectilinearOutputRateEncoder(
Tns.p_mock,
8,
8,
Tns.rore1_update_p, # 22
Tns.rore1_win_width) # 200
Tns.a_counter = 0
def inc_by_3_or_6(*args):
cycle = Tns.a_counter / 64
Tns.a_counter += 1
return cycle / 2 * 6 + (cycle + 1) / 2 * 3
Tns.count_mock.get = inc_by_3_or_6
for i in range(2 * Tns.rore1_win_width / Tns.rore1_update_p + 1):
# 0 -> 0, 1 -> 11, 2 -> 33, 3 -> 44
rore.update_rates(i / 2 * 22 + (i + 1) / 2 * 11)
Tns.count_mock.assert_called()
for r in splice(rore.get_rates()):
assert_allclose(r, 9.0 / 33, atol=0.0001)
def setup_weights():
Tns.w0_array = []
Tns.w0 = Weights(Tns.w0_array, 1)
Tns.w1_array = [[j / 63. for j in range(i * 8, 8 + i * 8)]
for i in range(8)]
Tns.w1 = Weights(Tns.w1_array, 1)
Tns.w2_array = [[
j / 63. for j in list(
itertools.chain(
*zip(itertools.repeat(NAN), range(i * 8, 4 + i * 8))))
] for i in range(8)]
Tns.w2 = Weights(Tns.w2_array, 1)
Tns.w3_array = numpy.array(splice(
[(list(
itertools.chain(*zip(range(i * 8, 4 +
i * 8), itertools.repeat(NAN)))),
list(
itertools.chain(
*zip(itertools.repeat(NAN), range(i * 8, 4 + i * 8)))))
for i in range(4)]),
dtype=float) / 63.
Tns.w3 = Weights(Tns.w3_array, 1)
def test_presynaptic_outputs_1_to_1_connectivity():
for u in Tns.p2:
assert_allclose(presynaptic_outputs(u, Tns.prj1_2), [splice(Tns.r)[Tns.p2.id_to_index(u)]])
def test_presynaptic_outputs_full_connectivity():
for u in Tns.p2:
assert_allclose(presynaptic_outputs(u, Tns.prj1_2), splice(Tns.r))
def list_units(ril):
"""Returns the list of PyNN units linked by the given rectilinear
input layer."""
return [b for _, b in list(splice(ril.unit_adapters_mat))]
NAN = float("NaN")
CWD = os.getcwd()
BASE_DATA_TESTPATH = CWD[: CWD.rfind("/pycogmo")] + "/pycogmo/tests/test_data/"
VALID_SAMPLE_INPUT_FILEPATHS = {
"png": [BASE_DATA_TESTPATH + "bnw_checker_8x8_24bit.png", BASE_DATA_TESTPATH + "bnw_checker_8x8_2bit.png"],
"colorpng": [
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_red.png",
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_green.png",
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_blue.png",
],
"csv": [BASE_DATA_TESTPATH + "csv_checker.txt"],
}
ALL_SAMPLE_INPUT_FILES = splice(VALID_SAMPLE_INPUT_FILEPATHS.values())
Tns.csv_checker_8x8_expected = Tns.png_checker_8x8_expected = [[1, 0] * 4, [0, 1] * 4] * 4
def list_units(ril):
"""Returns the list of PyNN units linked by the given rectilinear
input layer."""
return [b for _, b in list(splice(ril.unit_adapters_mat))]
def setup_weights():
Tns.w0_array = []
Tns.w0 = Weights(Tns.w0_array, 1)
Tns.w1_array = [[j / 63.0 for j in range(i * 8, 8 + i * 8)] for i in range(8)]
Tns.w1 = Weights(Tns.w1_array, 1)
def test_presynaptic_outputs_1_to_1_connectivity():
for u in Tns.p2:
assert_allclose(presynaptic_outputs(u, Tns.prj1_2),
[splice(Tns.r)[Tns.p2.id_to_index(u)]])
def test_presynaptic_outputs_full_connectivity():
for u in Tns.p2:
assert_allclose(presynaptic_outputs(u, Tns.prj1_2), splice(Tns.r))
def list_units(ril):
"""Returns the list of PyNN units linked by the given rectilinear
input layer."""
return [b for _, b in list(splice(ril.unit_adapters_mat))]
CWD = os.getcwd()
BASE_DATA_TESTPATH = CWD[:CWD.rfind("/pycogmo")] + \
"/pycogmo/tests/test_data/"
VALID_SAMPLE_INPUT_FILEPATHS = {
"png": [
BASE_DATA_TESTPATH + "bnw_checker_8x8_24bit.png",
BASE_DATA_TESTPATH + "bnw_checker_8x8_2bit.png",
],
"colorpng": [
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_red.png",
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_green.png",
BASE_DATA_TESTPATH + "color_checker_8x8_24bit_blue.png",
],
"csv": [BASE_DATA_TESTPATH + "csv_checker.txt"]
}
ALL_SAMPLE_INPUT_FILES = splice(VALID_SAMPLE_INPUT_FILEPATHS.values())
Tns.csv_checker_8x8_expected = \
Tns.png_checker_8x8_expected = [[1, 0] * 4, [0, 1] * 4] * 4
def list_units(ril):
"""Returns the list of PyNN units linked by the given rectilinear
input layer."""
return [b for _, b in list(splice(ril.unit_adapters_mat))]
def setup_weights():
Tns.w0_array = []
Tns.w0 = Weights(Tns.w0_array, 1)
Tns.w1_array = [[j / 63. for j in range(i * 8, 8 + i * 8)]
