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#!/usr/bin/env python3
import lzma
import numpy as np
import os
import struct
import sys
import xml.etree.ElementTree as ET
filename = sys.argv[1]
with open(filename, 'rb') as logfile:
lines = []
line = ''
if '.xz' in filename:
f = lzma.open(logfile)
else:
f = logfile
while line != '</dlog>\n':
line = f.readline().decode()
lines.append(line)
xml_header = ''.join(lines)
raw_header = f.read(8)
data_offset = f.tell()
raw_data = f.read()
xml_header = xml_header.replace('1ua>', 'X1ua>')
xml_header = xml_header.replace('2ua>', 'X2ua>')
dlog = ET.fromstring(xml_header)
channels = []
for channel in dlog.findall('channel'):
channel_id = int(channel.get('id'))
sense_curr = channel.find('sense_curr').text
sense_volt = channel.find('sense_volt').text
model = channel.find('ident').find('model').text
if sense_volt == '1':
channels.append((channel_id, model, 'V'))
if sense_curr == '1':
channels.append((channel_id, model, 'A'))
num_channels = len(channels)
duration = int(dlog.find('frame').find('time').text)
interval = float(dlog.find('frame').find('tint').text)
real_duration = interval * int(len(raw_data) / (4 * num_channels))
data = np.ndarray(shape=(num_channels, int(len(raw_data) / (4 * num_channels))), dtype=np.float32)
iterator = struct.iter_unpack('>f', raw_data)
channel_offset = 0
measurement_offset = 0
for value in iterator:
data[channel_offset, measurement_offset] = value[0]
if channel_offset + 1 == num_channels:
channel_offset = 0
measurement_offset += 1
else:
channel_offset += 1
if int(real_duration) != duration:
print('Measurement duration: {:f} of {:d} seconds at {:f} µs per sample'.format(
real_duration, duration, interval * 1000000))
else:
print('Measurement duration: {:d} seconds at {:f} µs per sample'.format(
duration, interval * 1000000))
for i, channel in enumerate(channels):
channel_id, channel_model, channel_type = channel
print('channel {:d} ({:s}): min {:f}, max {:f}, mean {:f} {:s}'.format(
channel_id, channel_model, np.min(data[i]), np.max(data[i]), np.mean(data[i]),
channel_type))
if i > 0 and channel_type == 'A' and channels[i-1][2] == 'V' and channel_id == channels[i-1][0]:
power = data[i-1] * data[i]
print('channel {:d} ({:s}): min {:f}, max {:f}, mean {:f} W'.format(
channel_id, channel_model, np.min(power), np.max(power), np.mean(power)))
#print(xml_header)
#print(raw_header)
#print(channels)
#print(data)
#print(np.mean(data[0]))
#print(np.mean(data[1]))
#print(np.mean(data[0] * data[1]))
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