def _setup_all_procs(self):
# make a list of all the types of processors
processors = []
processors.append(proc.BufferProcessor())
processors.append(proc.Average())
processors.append(proc.Raw())
processors.append(proc.AverageN(1))
processors.append(proc.Chunk(1,0,1))
return processors
def test_total_records_not_divisible_by_n(self):
params = mock_acq_params()
assert params["records_per_acquisition"] % 3 != 0
ave_n = proc.AverageN(3)
bufs = buffers_same_val(params, 1)
emulate_acq(params, bufs, ave_n)
ave_n.get_result()
def check_process_for_n_val(self, n_val, params):
ave_n = proc.AverageN(n_val)
bufs = buffers_random(params, 0, 255)
raw_dat = bufs_to_raw_array(bufs, params)
correct_results = [np.empty((n_val, params["samples_per_record"]), np.float)
for _ in range(params["channel_count"])]
# make the correct averaged data
for rec_type in range(n_val):
for result, chan_dat in zip(correct_results, raw_dat):
result[rec_type] = np.mean(chan_dat[rec_type::n_val],axis=0)
emulate_acq(params, bufs, ave_n)
result = ave_n.get_result()
for (correct, returned) in zip(correct_results, result):
assert (correct == returned).all()
def test_negative_n(self):
proc.AverageN(-1)
def test_zero_n(self):
proc.AverageN(0)