Searched refs:np (Results 1 – 7 of 7) sorted by relevance
17 import numpy as np namespace234 tailless_buffer = np.array(buffer[:len(buffer) - tail_length])238 downsampled_values = np.mean(239 np.resize(240 np.append(self._leftovers, tailless_buffer),
19 import numpy as np namespace101 tx_power_derivative = np.diff(tx_power_list)114 tx_power_steady_state_derivative = np.diff(tx_power_steady_state_list)118 [i for i in list(np.diff(pwlv_steady_index)) if i > 3])124 pwlv_derivative_bool = list(np.diff(pwlv_steady_state_list) == 1)
22 import numpy as np namespace429 readings = np.zeros((len(buffer.samples), 5))431 measurements = np.array([sample.values for sample in buffer.samples])432 calibrated_value = np.zeros((len(buffer.samples), 2))458 readings[:, channel] = np.where(
21 import numpy as np namespace356 measurements = np.array([sample.values for sample in buffer.samples])357 readings = np.zeros((len(buffer.samples), 5))375 readings[:, channel] = np.where(
20 import numpy as np namespace591 reported_asu_power = np.nanmean(down_power_measured)669 avg_up_power = np.nanmean(up_power_per_chain[0])670 if np.isnan(avg_up_power):
18 import numpy as np namespace212 pairs = zip(percentiles, np.percentile(arrays[seg_name],
23 import numpy as np namespace238 std_deviation = np.std(raw_rssi)