def _init_header(self, path):
config = _load_config(path)
metadata = config['metadata']
header = Stats()
config_key = self._config['header_sampling_rate_key']
try:
header.sampling_rate = float(metadata[config_key])
except KeyError:
raise KeyError("The following key was not found in the metadata: " +
"{}. Did you set the correct ".format(config_key) +
"'sample rate metadata key' in PAL H5 Output module?")
header.npts = int(metadata[self._config['header_samples_per_record_key']]) - 1
try:
if self._config['dd_300']:
header.calib = metadata['dd_300_calibration']
elif self._config['dd_900']:
header.calib = metadata['dd_900_calibration']
elif self._config['vd_08']:
header.calib = metadata['vd_08_calibration']
elif self._config['vd_09']:
header.calib = metadata['vd_09_calibration']
except KeyError:
pass
header.comments = str(config['comments'])
header.place = metadata
if self._config['header_extra1_name'] != '' and self._config['header_extra1_val'] != '':
header[self._config['header_extra1_name']] = self._config['header_extra1_val']
if self._config['header_extra2_name'] != '' and self._config['header_extra2_val'] != '':
header[self._config['header_extra2_name']] = self._config['header_extra2_val']
return header
def _init_header(self, path):
config = _load_config(path)
metadata = config['metadata']
header = Stats()
if 'ATS9440' in config['plugins'].keys():
ats_config = config['plugins']['ATS9440']['config']
elif 'ATS660' in config['plugins'].keys():
ats_config = config['plugins']['ATS660']['config']
else:
raise KeyError('Cannot locate trace config data')
if 'Polytec' in config['plugins'].keys():
polytec_config = config['plugins']['Polytec']['config']
else:
raise KeyError('Cannot locate vibrometer config data')
header.sampling_rate = _calc_sampling_rate(ats_config['sample_rate'])
header.npts = int(ats_config['pre_trigger_samples'] +
ats_config['post_trigger_samples']) - 1
if polytec_config['dd_300']:
header.calib = float(
re.findall(_NUMBER, polytec_config['dd_300_range'])[0])
elif polytec_config['dd_900']:
header.calib = float(
re.findall(_NUMBER, polytec_config['dd_900_range'])[0])
elif polytec_config['vd_08']:
header.calib = float(
re.findall(_NUMBER, polytec_config['vd_08_range'])[0])
elif polytec_config['vd_09']:
header.calib = float(
re.findall(_NUMBER, polytec_config['vd_09_range'])[0])
else:
raise KeyError('Cannot locate vibrometer calibration data')
header.comments = str(config['comments'])
header.place = metadata
if self._config['header_extra1_name'] != '' and self._config[
'header_extra1_val'] != '':
header[self._config['header_extra1_name']] = self._config[
'header_extra1_val']
if self._config['header_extra2_name'] != '' and self._config[
'header_extra2_val'] != '':
header[self._config['header_extra2_name']] = self._config[
'header_extra2_val']
return header
def _init_header(self, path):
config = _load_config(path)
metadata = config['metadata']
header = Stats()
if 'ATS9440' in config['plugins'].keys():
ats_config = config['plugins']['ATS9440']['config']
elif 'ATS660' in config['plugins'].keys():
ats_config = config['plugins']['ATS660']['config']
else:
raise KeyError('Cannot locate trace config data')
if 'Polytec' in config['plugins'].keys():
polytec_config = config['plugins']['Polytec']['config']
else:
raise KeyError('Cannot locate vibrometer config data')
header.sampling_rate = _calc_sampling_rate(ats_config['sample_rate'])
header.npts = int(ats_config['pre_trigger_samples'] +
ats_config['post_trigger_samples']) - 1
if polytec_config['dd_300']:
header.calib = float(re.findall(
_NUMBER, polytec_config['dd_300_range'])[0])
elif polytec_config['dd_900']:
header.calib = float(re.findall(
_NUMBER, polytec_config['dd_900_range'])[0])
elif polytec_config['vd_08']:
header.calib = float(re.findall(
_NUMBER, polytec_config['vd_08_range'])[0])
elif polytec_config['vd_09']:
header.calib = float(re.findall(
_NUMBER, polytec_config['vd_09_range'])[0])
else:
raise KeyError('Cannot locate vibrometer calibration data')
header.comments = str(config['comments'])
header.place = metadata
if self._config['header_extra1_name'] != '' and self._config['header_extra1_val'] != '':
header[self._config['header_extra1_name']
] = self._config['header_extra1_val']
if self._config['header_extra2_name'] != '' and self._config['header_extra2_val'] != '':
header[self._config['header_extra2_name']
] = self._config['header_extra2_val']
return header
def parseISF(self, isf_data, header_only=None, convert=None):
"""
Determine starting point of data.
Header has something like 'CURVE #520000', where ascii '5' is the
length of the length field '20000'.
::
'CURVE #520000xxxx...'
^ ^^ ^
| || +---- data_loc: location of first valid byte of data
| |+--------- len_loc: location of first byte of data length field
| +---------- len_len_loc: location of length of length
+----------------- tag_loc: location of start tag
"""
start_tag = 'CURVE #'
tag_loc = int(isf_data.find(start_tag))
len_len_loc = tag_loc + len(start_tag)
len_loc = len_len_loc + 1
len_len = int(isf_data[len_len_loc]) # e.g. 5
data_loc = len_loc + len_len
data_len = int(isf_data[len_loc:len_loc+len_len]) # e.g. 20000
# Extract and parse header
header = isf_data[:tag_loc]
# Reformat the header into a dictionary
header_dict = {}
items = header.replace(':WFMPRE:','').replace(':','').split(';') # list of "key value" pairs
for item in items:
if(item):
key, value = item.split(' ', 1) # maxsplit 1 to ignore subsequent spaces in value
value = value.replace('"', '')
header_dict[key] = value
if(header_only):
return header_dict
# Extract data and convert from string to integer value
data = isf_data[data_loc:]
stats = Stats()
stats.npts = int(header_dict['NR_PT'])
stats.calib = float(header_dict['YMULT'])
byte_order = header_dict['BYT_OR'] # 'MSB' or 'LSB'
if(byte_order == 'MSB'):
byte_order = '>'
else:
byte_order = '<'
points = []
for i in range(0, stats.npts*2, 2):
value = data[i:i+2] # as string
converted = struct.unpack('%sh' % byte_order, value)[0]
points.append(converted)
# Optionally convert points to engineering units
if(convert):
try:
points = np.array(points) * stats.calib # requires numpy
except NameError:
# If numpy not available, use list instead.
p = []
for point in points:
p.append(point * stats.calib)
points = p
stats.time_offset = float(header_dict['XZERO'])
stats.calib_unit = header_dict['YUNIT']
stats.delta = float(header_dict['XINCR'])
stats.amp_offset = float(header_dict['YOFF'])
stats.comments = header_dict['WFID']
stats.channel = header_dict['WFID'][0:3]
return stats, points
