def metadata_NXlog(self, spec_metadata, description):
"""Return the specific metadata in an NXlog object."""
from spec2nexus import utils
nxlog = NXlog()
nxlog.attrs['description'] = description
for subkey, value in spec_metadata.items():
clean_name = utils.sanitize_name(nxlog, subkey)
nxlog[clean_name] = NXfield(value)
nxlog[clean_name].original_name = subkey
return nxlog
def metadata_NXlog(self, spec_metadata, description):
'''
return the specific metadata in an NXlog object
'''
from spec2nexus import utils
nxlog = NXlog()
nxlog.attrs['description'] = description
for subkey, value in spec_metadata.items():
clean_name = utils.sanitize_name(nxlog, subkey)
nxlog[clean_name] = NXfield(value)
nxlog[clean_name].original_name = subkey
return nxlog
def parser_1D_columns(self, nxdata, scan):
'''generic data parser for 1-D column data'''
from spec2nexus import utils
for column in scan.L:
if column in scan.data:
clean_name = utils.sanitize_name(nxdata, column)
nxdata[clean_name] = NXfield(scan.data[column])
nxdata[clean_name].original_name = column
signal = utils.sanitize_name(nxdata, scan.column_last) # primary Y axis
axis = utils.sanitize_name(nxdata, scan.column_first) # primary X axis
nxdata.nxsignal = nxdata[signal]
nxdata.nxaxes = nxdata[axis]
self.parser_mca_spectra(nxdata, scan, axis)
def parser_1D_columns(self, nxdata, scan):
'''generic data parser for 1-D column data'''
from spec2nexus import utils
for column in scan.L:
if column in scan.data:
clean_name = utils.sanitize_name(nxdata, column)
nxdata[clean_name] = NXfield(scan.data[column])
nxdata[clean_name].original_name = column
signal = utils.sanitize_name(nxdata,
scan.column_last) # primary Y axis
axis = utils.sanitize_name(nxdata, scan.column_first) # primary X axis
nxdata.nxsignal = nxdata[signal]
nxdata.nxaxes = nxdata[axis]
self.parser_mca_spectra(nxdata, scan, axis)
def parser_mesh(self, nxdata, scan):
'''data parser for 2-D mesh and hklmesh'''
# 2-D parser: http://www.certif.com/spec_help/mesh.html
# mesh motor1 start1 end1 intervals1 motor2 start2 end2 intervals2 time
# 2-D parser: http://www.certif.com/spec_help/hklmesh.html
# hklmesh Q1 start1 end1 intervals1 Q2 start2 end2 intervals2 time
# mesh: nexpy/examples/33id_spec.dat scan 22 (also has MCA, thus 3-D data)
# hklmesh: nexpy/examples/33bm_spec.dat scan 17 (no MCA data)
from spec2nexus import utils
label1, start1, end1, intervals1, label2, start2, end2, intervals2, time = scan.scanCmd.split(
)[1:]
if label1 not in scan.data:
label1 = scan.L[0] # mnemonic v. name
if label2 not in scan.data:
label2 = scan.L[1] # mnemonic v. name
axis1 = scan.data.get(label1)
axis2 = scan.data.get(label2)
intervals1, intervals2 = int(intervals1), int(intervals2)
start1, end1 = float(start1), float(end1)
start2, end2 = float(start2), float(end2)
time = float(time)
if len(axis1) < intervals1: # stopped scan before second row started
self.parser_1D_columns(nxdata, scan) # fallback support
# TODO: what about the MCA data in this case?
else:
axis1 = axis1[0:intervals1 + 1]
axis2 = [
axis2[row] for row in range(len(axis2))
if row % (intervals1 + 1) == 0
]
column_labels = scan.L
column_labels.remove(label1) # special handling
column_labels.remove(label2) # special handling
if scan.scanCmd.startswith('hkl'):
# find the reciprocal space axis held constant
label3 = [
key for key in ('H', 'K', 'L')
if key not in (label1, label2)
][0]
axis3 = scan.data.get(label3)[0]
nxdata[label3] = NXfield(axis3)
column_labels.remove(label3) # already handled
nxdata[label1] = NXfield(axis1) # 1-D array
nxdata[label2] = NXfield(axis2) # 1-D array
# build 2-D data objects (do not build label1, label2, [or label3] as 2-D objects)
data_shape = [len(axis2), len(axis1)]
for label in column_labels:
axis = np.array(scan.data.get(label))
clean_name = utils.sanitize_name(nxdata, label)
nxdata[clean_name] = NXfield(
utils.reshape_data(axis, data_shape))
nxdata[clean_name].original_name = label
signal_axis_label = utils.sanitize_name(nxdata, scan.column_last)
nxdata.nxsignal = nxdata[signal_axis_label]
nxdata.nxaxes = [nxdata[label2], nxdata[label1]]
if '_mca_' in scan.data: # 3-D array
# TODO: ?merge with parser_mca_spectra()?
for mca_key, mca_data in scan.data['_mca_'].items():
key = "__" + mca_key
spectra_lengths = list(map(len, mca_data))
num_channels = max(spectra_lengths)
if num_channels != min(spectra_lengths):
msg = 'MCA spectra have different lengths'
msg += ' in scan #' + str(scan.scanNum)
msg += ' in file ' + str(scan.specFile)
raise ValueError(msg)
data_shape += [
num_channels,
]
mca = np.array(mca_data)
nxdata[key] = NXfield(utils.reshape_data(mca, data_shape))
nxdata[key].units = "counts"
try:
# use MCA channel numbers as known at time of scan
chan1 = scan.MCA['first_saved']
chanN = scan.MCA['last_saved']
channel_range = range(chan1, chanN + 1)
except:
# basic indices
channel_range = range(1, num_channels + 1)
ch_key = key + "_channel"
nxdata[ch_key] = NXfield(channel_range)
nxdata[ch_key].units = 'channel'
axes = (label1, label2, ch_key)
nxdata[key].axes = ':'.join(axes)
def parser_mesh(self, nxdata, scan):
'''data parser for 2-D mesh and hklmesh'''
# 2-D parser: http://www.certif.com/spec_help/mesh.html
# mesh motor1 start1 end1 intervals1 motor2 start2 end2 intervals2 time
# 2-D parser: http://www.certif.com/spec_help/hklmesh.html
# hklmesh Q1 start1 end1 intervals1 Q2 start2 end2 intervals2 time
# mesh: nexpy/examples/33id_spec.dat scan 22 (also has MCA, thus 3-D data)
# hklmesh: nexpy/examples/33bm_spec.dat scan 17 (no MCA data)
from spec2nexus import utils
label1, start1, end1, intervals1, label2, start2, end2, intervals2, time = scan.scanCmd.split()[1:]
if label1 not in scan.data:
label1 = scan.L[0] # mnemonic v. name
if label2 not in scan.data:
label2 = scan.L[1] # mnemonic v. name
axis1 = scan.data.get(label1)
axis2 = scan.data.get(label2)
intervals1, intervals2 = int(intervals1), int(intervals2)
start1, end1 = float(start1), float(end1)
start2, end2 = float(start2), float(end2)
time = float(time)
if len(axis1) < intervals1: # stopped scan before second row started
self.parser_1D_columns(nxdata, scan) # fallback support
# TODO: what about the MCA data in this case?
else:
axis1 = axis1[0:intervals1+1]
axis2 = [axis2[row] for row in range(len(axis2)) if row % (intervals1+1) == 0]
column_labels = scan.L
column_labels.remove(label1) # special handling
column_labels.remove(label2) # special handling
if scan.scanCmd.startswith('hkl'):
# find the reciprocal space axis held constant
label3 = [key for key in ('H', 'K', 'L') if key not in (label1, label2)][0]
axis3 = scan.data.get(label3)[0]
nxdata[label3] = NXfield(axis3)
column_labels.remove(label3) # already handled
nxdata[label1] = NXfield(axis1) # 1-D array
nxdata[label2] = NXfield(axis2) # 1-D array
# build 2-D data objects (do not build label1, label2, [or label3] as 2-D objects)
data_shape = [len(axis2), len(axis1)]
for label in column_labels:
axis = np.array( scan.data.get(label) )
clean_name = utils.sanitize_name(nxdata, label)
nxdata[clean_name] = NXfield(utils.reshape_data(axis, data_shape))
nxdata[clean_name].original_name = label
signal_axis_label = utils.sanitize_name(nxdata, scan.column_last)
nxdata.nxsignal = nxdata[signal_axis_label]
nxdata.nxaxes = [nxdata[label2], nxdata[label1]]
if '_mca_' in scan.data: # 3-D array
# TODO: ?merge with parser_mca_spectra()?
for mca_key, mca_data in scan.data['_mca_'].items():
key = "__" + mca_key
spectra_lengths = list(map(len, mca_data))
num_channels = max(spectra_lengths)
if num_channels != min(spectra_lengths):
msg = 'MCA spectra have different lengths'
msg += ' in scan #' + str(scan.scanNum)
msg += ' in file ' + str(scan.specFile)
raise ValueError(msg)
data_shape += [num_channels, ]
mca = np.array(mca_data)
nxdata[key] = NXfield(utils.reshape_data(mca, data_shape))
nxdata[key].units = "counts"
try:
# use MCA channel numbers as known at time of scan
chan1 = scan.MCA['first_saved']
chanN = scan.MCA['last_saved']
channel_range = range(chan1, chanN+1)
except:
# basic indices
channel_range = range(1, num_channels+1)
ch_key = key + "_channel"
nxdata[ch_key] = NXfield(channel_range)
nxdata[ch_key].units = 'channel'
axes = (label1, label2, ch_key)
nxdata[key].axes = ':'.join( axes )