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-rwxr-xr-xlib/keysightdlog.py85
1 files changed, 85 insertions, 0 deletions
diff --git a/lib/keysightdlog.py b/lib/keysightdlog.py
new file mode 100755
index 0000000..3864d6e
--- /dev/null
+++ b/lib/keysightdlog.py
@@ -0,0 +1,85 @@
+#!/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]))