def emi_reader(filename, dump_xml=False, verbose=False, **kwds):
# TODO: recover the tags from the emi file. It is easy: just look for
# <ObjectInfo> and </ObjectInfo>. It is standard xml :)
objects = get_xml_info_from_emi(filename)
filename = os.path.splitext(filename)[0]
if dump_xml is True:
for i, obj in enumerate(objects):
with open(filename + '-object-%s.xml' % i, 'w') as f:
f.write(obj)
ser_files = glob(filename + '_[0-9].ser')
sers = []
for f in ser_files:
if verbose is True:
print "Opening ", f
try:
sers.append(ser_reader(f, objects))
except IOError: # Probably a single spectrum that we don't support
continue
index = int(os.path.splitext(f)[0].split("_")[-1]) - 1
op = DictionaryBrowser(sers[-1]['original_parameters'])
emixml2dtb(ET.fromstring(objects[index]), op)
sers[-1]['original_parameters'] = op.as_dictionary()
return sers
def emi_reader(filename, dump_xml=False, verbose=False, **kwds):
# TODO: recover the tags from the emi file. It is easy: just look for
# <ObjectInfo> and </ObjectInfo>. It is standard xml :)
objects = get_xml_info_from_emi(filename)
filename = os.path.splitext(filename)[0]
if dump_xml is True:
for i, obj in enumerate(objects):
with open(filename + '-object-%s.xml' % i, 'w') as f:
f.write(obj)
ser_files = glob(filename + '_[0-9].ser')
sers = []
for f in ser_files:
if verbose is True:
print "Opening ", f
try:
sers.append(ser_reader(f, objects))
except IOError: # Probably a single spectrum that we don't support
continue
index = int(os.path.splitext(f)[0].split("_")[-1]) - 1
op = DictionaryBrowser(sers[-1]['original_parameters'])
emixml2dtb(ET.fromstring(objects[index]), op)
sers[-1]['original_parameters'] = op.as_dictionary()
return sers
def file_reader(filename, encoding='latin-1', **kwds):
parameters = {}
mapped = DictionaryBrowser({})
with codecs.open(
filename,
encoding=encoding,
errors='replace') as spectrum_file:
y = []
# Read the keywords
data_section = False
for line in spectrum_file.readlines():
if data_section is False:
if line[0] == "#":
try:
key,value = line.split(': ')
value = value.strip()
except ValueError:
key = line
value = None
key = key.strip('#').strip()
if key != 'SPECTRUM':
parameters[key] = value
else:
data_section = True
else:
# Read the data
if line[0] != "#" and line.strip():
if parameters['DATATYPE'] == 'XY':
xy = line.replace(',', ' ').strip().split()
y.append(float(xy[1]))
elif parameters['DATATYPE'] == 'Y':
data = [
float(i) for i in line.replace(',', ' ').strip().split()]
y.extend(data)
# We rewrite the format value to be sure that it complies with the
# standard, because it will be used by the writer routine
parameters['FORMAT'] = "EMSA/MAS Spectral Data File"
# Convert the parameters to the right type and map some
# TODO: the msa format seems to support specifying the units of some
# parametes. We should add this feature here
for parameter, value in parameters.iteritems():
# Some parameters names can contain the units information
# e.g. #AZIMANGLE-dg: 90.
if '-' in parameter:
clean_par, units = parameter.split('-')
clean_par, units = clean_par.strip(), units.strip()
else:
clean_par, units = parameter, None
if clean_par in keywords:
try:
parameters[parameter] = keywords[clean_par]['dtype'](value)
except:
# Normally the offending mispelling is a space in the scientic
# notation, e.g. 2.0 E-06, so we try to correct for it
try:
parameters[parameter] = keywords[clean_par]['dtype'](
value.replace(' ', ''))
except:
print("The %s keyword value, %s " % (parameter, value) +
"could not be converted to the right type" )
if keywords[clean_par]['mapped_to'] is not None:
mapped.set_item(keywords[clean_par]['mapped_to'],
parameters[parameter])
if units is not None:
mapped.set_item(keywords[clean_par]['mapped_to'] +
'_units',units)
# The data parameter needs some extra care
# It is necessary to change the locale to US english to read the date
# keyword
loc = locale.getlocale(locale.LC_TIME)
# Setting locale can raise an exception because
# their name depends on library versions, platform etc.
try:
if os_name == 'posix':
locale.setlocale(locale.LC_TIME, ('en_US', 'utf8'))
elif os_name == 'windows':
locale.setlocale(locale.LC_TIME, 'english')
try:
H, M = time.strptime(parameters['TIME'], "%H:%M")[3:5]
mapped['time'] = datetime.time(H, M)
except:
if 'TIME' in parameters and parameters['TIME']:
print('The time information could not be retrieved')
try:
Y, M, D = time.strptime(parameters['DATE'], "%d-%b-%Y")[0:3]
mapped['date'] = datetime.date(Y, M, D)
except:
if 'DATE' in parameters and parameters['DATE']:
print('The date information could not be retrieved')
except:
warnings.warn("I couldn't write the date information due to"
"an unexpected error. Please report this error to "
"the developers")
locale.setlocale(locale.LC_TIME, loc) # restore saved locale
axes = []
axes.append({
'size' : len(y),
'index_in_array' : 0,
'name' : parameters['XLABEL'] if 'XLABEL' in parameters else '',
'scale': parameters['XPERCHAN'] if 'XPERCHAN' in parameters else 1,
'offset' : parameters['OFFSET'] if 'OFFSET' in parameters else 0,
'units' : parameters['XUNITS'] if 'XUNITS' in parameters else '',
})
mapped['original_filename'] = filename
mapped['record_by'] = 'spectrum'
if mapped.has_item('signal_type'):
if mapped.signal_type == 'ELS':
mapped.signal_type = 'EELS'
else:
# Defaulting to EELS looks reasonable
mapped.signal_type = 'EELS'
dictionary = {
'data' : np.array(y),
'axes' : axes,
'mapped_parameters': mapped.as_dictionary(),
'original_parameters' : parameters
}
return [dictionary,]
def file_reader(filename, encoding='latin-1', **kwds):
parameters = {}
mapped = DictionaryBrowser({})
with codecs.open(filename, encoding=encoding,
errors='replace') as spectrum_file:
y = []
# Read the keywords
data_section = False
for line in spectrum_file.readlines():
if data_section is False:
if line[0] == "#":
try:
key, value = line.split(': ')
value = value.strip()
except ValueError:
key = line
value = None
key = key.strip('#').strip()
if key != 'SPECTRUM':
parameters[key] = value
else:
data_section = True
else:
# Read the data
if line[0] != "#" and line.strip():
if parameters['DATATYPE'] == 'XY':
xy = line.replace(',', ' ').strip().split()
y.append(float(xy[1]))
elif parameters['DATATYPE'] == 'Y':
data = [
float(i)
for i in line.replace(',', ' ').strip().split()
]
y.extend(data)
# We rewrite the format value to be sure that it complies with the
# standard, because it will be used by the writer routine
parameters['FORMAT'] = "EMSA/MAS Spectral Data File"
# Convert the parameters to the right type and map some
# TODO: the msa format seems to support specifying the units of some
# parametes. We should add this feature here
for parameter, value in parameters.iteritems():
# Some parameters names can contain the units information
# e.g. #AZIMANGLE-dg: 90.
if '-' in parameter:
clean_par, units = parameter.split('-')
clean_par, units = clean_par.strip(), units.strip()
else:
clean_par, units = parameter, None
if clean_par in keywords:
try:
parameters[parameter] = keywords[clean_par]['dtype'](value)
except:
# Normally the offending mispelling is a space in the scientic
# notation, e.g. 2.0 E-06, so we try to correct for it
try:
parameters[parameter] = keywords[clean_par]['dtype'](
value.replace(' ', ''))
except:
print("The %s keyword value, %s " % (parameter, value) +
"could not be converted to the right type")
if keywords[clean_par]['mapped_to'] is not None:
mapped.set_item(keywords[clean_par]['mapped_to'],
parameters[parameter])
if units is not None:
mapped.set_item(
keywords[clean_par]['mapped_to'] + '_units', units)
# The data parameter needs some extra care
# It is necessary to change the locale to US english to read the date
# keyword
loc = locale.getlocale(locale.LC_TIME)
# Setting locale can raise an exception because
# their name depends on library versions, platform etc.
try:
if os_name == 'posix':
locale.setlocale(locale.LC_TIME, ('en_US', 'utf8'))
elif os_name == 'windows':
locale.setlocale(locale.LC_TIME, 'english')
try:
H, M = time.strptime(parameters['TIME'], "%H:%M")[3:5]
mapped['time'] = datetime.time(H, M)
except:
if 'TIME' in parameters and parameters['TIME']:
print('The time information could not be retrieved')
try:
Y, M, D = time.strptime(parameters['DATE'], "%d-%b-%Y")[0:3]
mapped['date'] = datetime.date(Y, M, D)
except:
if 'DATE' in parameters and parameters['DATE']:
print('The date information could not be retrieved')
except:
warnings.warn("I couldn't write the date information due to"
"an unexpected error. Please report this error to "
"the developers")
locale.setlocale(locale.LC_TIME, loc) # restore saved locale
axes = []
axes.append({
'size':
len(y),
'index_in_array':
0,
'name':
parameters['XLABEL'] if 'XLABEL' in parameters else '',
'scale':
parameters['XPERCHAN'] if 'XPERCHAN' in parameters else 1,
'offset':
parameters['OFFSET'] if 'OFFSET' in parameters else 0,
'units':
parameters['XUNITS'] if 'XUNITS' in parameters else '',
})
mapped['original_filename'] = filename
mapped['record_by'] = 'spectrum'
if mapped.has_item('signal_type'):
if mapped.signal_type == 'ELS':
mapped.signal_type = 'EELS'
else:
# Defaulting to EELS looks reasonable
mapped.signal_type = 'EELS'
dictionary = {
'data': np.array(y),
'axes': axes,
'mapped_parameters': mapped.as_dictionary(),
'original_parameters': parameters
}
return [
dictionary,
]
def __init__(self, imdict, file, order="C", record_by=None):
self.imdict = DictionaryBrowser(imdict)
self.file = file
self._order = order if order else "C"
self._record_by = record_by
def stack(
signal_list,
axis=None,
new_axis_name='stack_element',
mmap=False,
mmap_dir=None,
):
"""Concatenate the signals in the list over a given axis or a new axis.
The title is set to that of the first signal in the list.
Parameters
----------
signal_list : list of Signal instances
axis : {None, int, str}
If None, the signals are stacked over a new axis. The data must
have the same dimensions. Otherwise the
signals are stacked over the axis given by its integer index or
its name. The data must have the same shape, except in the dimension
corresponding to `axis`.
new_axis_name : string
The name of the new axis when `axis` is None.
If an axis with this name already
exists it automatically append '-i', where `i` are integers,
until it finds a name that is not yet in use.
mmap: bool
If True and stack is True, then the data is stored
in a memory-mapped temporary file.The memory-mapped data is
stored on disk, and not directly loaded into memory.
Memory mapping is especially useful for accessing small
fragments of large files without reading the entire file into
memory.
mmap_dir : string
If mmap_dir is not None, and stack and mmap are True, the memory
mapped file will be created in the given directory,
otherwise the default directory is used.
Returns
-------
signal : Signal instance (or subclass, determined by the objects in
signal list)
Examples
--------
>>> data = np.arange(20)
>>> s = utils.stack([signals.Spectrum(data[:10]), signals.Spectrum(data[10:])])
>>> s
<Spectrum, title: Stack of , dimensions: (2, 10)>
>>> s.data
array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14, 15, 16, 17, 18, 19]])
"""
for i, obj in enumerate(signal_list):
if i == 0:
if axis is None:
original_shape = obj.data.shape
stack_shape = tuple([
len(signal_list),
]) + original_shape
tempf = None
if mmap is False:
data = np.empty(stack_shape, dtype=obj.data.dtype)
else:
tempf = tempfile.NamedTemporaryFile(dir=mmap_dir)
data = np.memmap(
tempf,
dtype=obj.data.dtype,
mode='w+',
shape=stack_shape,
)
signal = type(obj)(data=data)
signal.axes_manager._axes[1:] = obj.axes_manager._axes
axis_name = new_axis_name
axis_names = [
axis_.name for axis_ in signal.axes_manager._axes[1:]
]
j = 1
while axis_name in axis_names:
axis_name = new_axis_name + "-%i" % j
j += 1
eaxis = signal.axes_manager._axes[0]
eaxis.name = axis_name
eaxis.navigate = True # This triggers _update_parameters
signal.mapped_parameters = obj.mapped_parameters
# Get the title from 1st object
signal.mapped_parameters.title = ("Stack of " +
obj.mapped_parameters.title)
signal.original_parameters = DictionaryBrowser({})
else:
axis = obj.axes_manager[axis]
signal = obj.deepcopy()
signal.original_parameters.add_node('stack_elements')
# Store parameters
signal.original_parameters.stack_elements.add_node('element%i' % i)
node = signal.original_parameters.stack_elements['element%i' % i]
node.original_parameters = \
obj.original_parameters.as_dictionary()
node.mapped_parameters = \
obj.mapped_parameters.as_dictionary()
if axis is None:
if obj.data.shape != original_shape:
raise IOError(
"Only files with data of the same shape can be stacked")
signal.data[i, ...] = obj.data
del obj
if axis is not None:
signal.data = np.concatenate([signal_.data for signal_ in signal_list],
axis=axis.index_in_array)
signal.get_dimensions_from_data()
return signal
def file_reader(filename, rpl_info=None, encoding="latin-1",
mmap_mode='c', *args,**kwds):
"""Parses a Lispix (http://www.nist.gov/lispix/) ripple (.rpl) file
and reads the data from the corresponding raw (.raw) file;
or, read a raw file if the dictionary rpl_info is provided.
This format is often uses in EDS/EDX experiments.
Images and spectral images or data cubes that are written in the
(Lispix) raw file format are just a continuous string of numbers.
Data cubes can be stored image by image, or spectrum by spectrum.
Single images are stored row by row, vector cubes are stored row by row
(each row spectrum by spectrum), image cubes are stored image by image.
All of the numbers are in the same format, such as 16 bit signed integer,
IEEE 8-byte real, 8-bit unsigned byte, etc.
The "raw" file should be accompanied by text file with the same name and
".rpl" extension. This file lists the characteristics of the raw file so
that it can be loaded without human intervention.
Alternatively, dictionary 'rpl_info' containing the information can
be given.
Some keys are specific to Hyperspy and will be ignored by other software.
RPL stands for "Raw Parameter List", an ASCII text, tab delimited file in
which Hyperspy reads the image parameters for a raw file.
TABLE OF RPL PARAMETERS
key type description
---------- ------------ --------------------
# Mandatory keys:
width int # pixels per row
height int # number of rows
depth int # number of images or spectral pts
offset int # bytes to skip
data-type str # 'signed', 'unsigned', or 'float'
data-length str # bytes per pixel '1', '2', '4', or '8'
byte-order str # 'big-endian', 'little-endian', or 'dont-care'
record-by str # 'image', 'vector', or 'dont-care'
# X-ray keys:
ev-per-chan int # optional, eV per channel
detector-peak-width-ev int # optional, FWHM for the Mn K-alpha line
# Hyperspy-specific keys
depth-origin int # energy offset in pixels
depth-scale float # energy scaling (units per pixel)
depth-units str # energy units, usually eV
depth-name str # Name of the magnitude stored as depth
width-origin int # column offset in pixels
width-scale float # column scaling (units per pixel)
width-units str # column units, usually nm
width-name str # Name of the magnitude stored as width
height-origin int # row offset in pixels
height-scale float # row scaling (units per pixel)
height-units str # row units, usually nm
height-name str # Name of the magnitude stored as height
signal str # Name of the signal stored, e.g. HAADF
convergence-angle float # TEM convergence angle in mrad
collection-angle float # EELS spectrometer collection angle in mrad
beam-energy float # TEM beam energy in keV
NOTES
When 'data-length' is 1, the 'byte order' is not relevant as there is only
one byte per datum, and 'byte-order' should be 'dont-care'.
When 'depth' is 1, the file has one image, 'record-by' is not relevant and
should be 'dont-care'. For spectral images, 'record-by' is 'vector'.
For stacks of images, 'record-by' is 'image'.
Floating point numbers can be IEEE 4-byte, or IEEE 8-byte. Therefore if
data-type is float, data-length MUST be 4 or 8.
The rpl file is read in a case-insensitive manner. However, when providing
a dictionary as input, the keys MUST be lowercase.
Comment lines, beginning with a semi-colon ';' are allowed anywhere.
The first non-comment in the rpl file line MUST have two column names:
'name_1'<TAB>'name_2'; any name would do e.g. 'key'<TAB>'value'.
Parameters can be in ANY order.
In the rpl file, the parameter name is followed by ONE tab (spaces are
ignored) e.g.: 'data-length'<TAB>'2'
In the rpl file, other data and more tabs can follow the two items on
each row, and are ignored.
Other keys and values can be included and are ignored.
Any number of spaces can go along with each tab.
"""
if not rpl_info:
if filename[-3:] in file_extensions:
with codecs.open(filename, encoding = encoding,
errors = 'replace') as f:
rpl_info = parse_ripple(f)
else:
raise IOError, 'File has wrong extension: "%s"' % filename[-3:]
for ext in ['raw', 'RAW']:
rawfname = filename[:-3] + ext
if os.path.exists(rawfname):
break
else:
rawfname = ''
if not rawfname:
raise IOError, 'RAW file "%s" does not exists' % rawfname
else:
data = read_raw(rpl_info, rawfname, mmap_mode=mmap_mode)
if rpl_info['record-by'] == 'vector':
print 'Loading as spectrum'
record_by = 'spectrum'
elif rpl_info['record-by'] == 'image':
print 'Loading as Image'
record_by = 'image'
else:
if len(data.shape) == 1:
print 'Loading as spectrum'
record_by = 'spectrum'
else:
print 'Loading as image'
record_by = 'image'
if rpl_info['record-by'] == 'vector':
idepth, iheight, iwidth = 2, 0, 1
names = ['height', 'width', 'depth', ]
else:
idepth, iheight, iwidth = 0, 1, 2
names = ['depth', 'height', 'width']
scales = [1, 1, 1]
origins = [0, 0, 0]
units = ['', '', '']
sizes = [rpl_info[names[i]] for i in xrange(3)]
if 'signal' not in rpl_info:
rpl_info['signal'] = ""
if rpl_info.has_key('detector-peak-width-ev'):
original_parameters['detector-peak-width-ev'] = \
rpl_info['detector-peak-width-ev']
if rpl_info.has_key('depth-scale'):
scales[idepth] = rpl_info['depth-scale']
# ev-per-chan is the only calibration supported by the original ripple
# format
elif rpl_info.has_key('ev-per-chan'):
scales[idepth] = rpl_info['ev-per-chan']
if rpl_info.has_key('depth-origin'):
origins[idepth] = rpl_info['depth-origin']
if rpl_info.has_key('depth-units'):
units[idepth] = rpl_info['depth-units']
if rpl_info.has_key('depth-name'):
names[idepth] = rpl_info['depth-name']
if rpl_info.has_key('width-origin'):
origins[iwidth] = rpl_info['width-origin']
if rpl_info.has_key('width-scale'):
scales[iwidth] = rpl_info['width-scale']
if rpl_info.has_key('width-units'):
units[iwidth] = rpl_info['width-units']
if rpl_info.has_key('width-name'):
names[iwidth] = rpl_info['width-name']
if rpl_info.has_key('height-origin'):
origins[iheight] = rpl_info['height-origin']
if rpl_info.has_key('height-scale'):
scales[iheight] = rpl_info['height-scale']
if rpl_info.has_key('height-units'):
units[iheight] = rpl_info['height-units']
if rpl_info.has_key('height-name'):
names[iheight] = rpl_info['height-name']
mp = DictionaryBrowser({
'record_by': record_by,
'original_filename': os.path.split(filename)[1],
'signal_type': rpl_info['signal'],
})
if 'convergence-angle' in rpl_info:
mp.set_item('TEM.convergence_angle',
rpl_info['convergence-angle'])
if 'collection-angle' in rpl_info:
mp.set_item('TEM.EELS.collection_angle',
rpl_info['collection-angle'])
if 'beam-energy' in rpl_info:
mp.set_item('TEM.beam_energy',
rpl_info['beam-energy'])
axes = []
index_in_array = 0
for i in xrange(3):
if sizes[i] > 1:
axes.append({
'size' : sizes[i],
'index_in_array' : index_in_array ,
'name' : names[i],
'scale': scales[i],
'offset' : origins[i],
'units' : units[i],
})
index_in_array += 1
dictionary = {
'data': data.squeeze(),
'axes': axes,
'mapped_parameters': mp.as_dictionary(),
'original_parameters': rpl_info
}
return [dictionary, ]
def file_reader(filename,
rpl_info=None,
encoding="latin-1",
mmap_mode='c',
*args,
**kwds):
"""Parses a Lispix (http://www.nist.gov/lispix/) ripple (.rpl) file
and reads the data from the corresponding raw (.raw) file;
or, read a raw file if the dictionary rpl_info is provided.
This format is often uses in EDS/EDX experiments.
Images and spectral images or data cubes that are written in the
(Lispix) raw file format are just a continuous string of numbers.
Data cubes can be stored image by image, or spectrum by spectrum.
Single images are stored row by row, vector cubes are stored row by row
(each row spectrum by spectrum), image cubes are stored image by image.
All of the numbers are in the same format, such as 16 bit signed integer,
IEEE 8-byte real, 8-bit unsigned byte, etc.
The "raw" file should be accompanied by text file with the same name and
".rpl" extension. This file lists the characteristics of the raw file so
that it can be loaded without human intervention.
Alternatively, dictionary 'rpl_info' containing the information can
be given.
Some keys are specific to Hyperspy and will be ignored by other software.
RPL stands for "Raw Parameter List", an ASCII text, tab delimited file in
which Hyperspy reads the image parameters for a raw file.
TABLE OF RPL PARAMETERS
key type description
---------- ------------ --------------------
# Mandatory keys:
width int # pixels per row
height int # number of rows
depth int # number of images or spectral pts
offset int # bytes to skip
data-type str # 'signed', 'unsigned', or 'float'
data-length str # bytes per pixel '1', '2', '4', or '8'
byte-order str # 'big-endian', 'little-endian', or 'dont-care'
record-by str # 'image', 'vector', or 'dont-care'
# X-ray keys:
ev-per-chan int # optional, eV per channel
detector-peak-width-ev int # optional, FWHM for the Mn K-alpha line
# Hyperspy-specific keys
depth-origin int # energy offset in pixels
depth-scale float # energy scaling (units per pixel)
depth-units str # energy units, usually eV
depth-name str # Name of the magnitude stored as depth
width-origin int # column offset in pixels
width-scale float # column scaling (units per pixel)
width-units str # column units, usually nm
width-name str # Name of the magnitude stored as width
height-origin int # row offset in pixels
height-scale float # row scaling (units per pixel)
height-units str # row units, usually nm
height-name str # Name of the magnitude stored as height
signal str # Name of the signal stored, e.g. HAADF
convergence-angle float # TEM convergence angle in mrad
collection-angle float # EELS spectrometer collection angle in mrad
beam-energy float # TEM beam energy in keV
elevation-angle float # Elevation angle of the EDS detector
azimuth-angle float # Elevation angle of the EDS detector
live-time float # Live time per spectrum
energy-resolution float # Resolution of the EDS (FHWM of MnKa)
tilt-stage float # The tilt of the stage
NOTES
When 'data-length' is 1, the 'byte order' is not relevant as there is only
one byte per datum, and 'byte-order' should be 'dont-care'.
When 'depth' is 1, the file has one image, 'record-by' is not relevant and
should be 'dont-care'. For spectral images, 'record-by' is 'vector'.
For stacks of images, 'record-by' is 'image'.
Floating point numbers can be IEEE 4-byte, or IEEE 8-byte. Therefore if
data-type is float, data-length MUST be 4 or 8.
The rpl file is read in a case-insensitive manner. However, when providing
a dictionary as input, the keys MUST be lowercase.
Comment lines, beginning with a semi-colon ';' are allowed anywhere.
The first non-comment in the rpl file line MUST have two column names:
'name_1'<TAB>'name_2'; any name would do e.g. 'key'<TAB>'value'.
Parameters can be in ANY order.
In the rpl file, the parameter name is followed by ONE tab (spaces are
ignored) e.g.: 'data-length'<TAB>'2'
In the rpl file, other data and more tabs can follow the two items on
each row, and are ignored.
Other keys and values can be included and are ignored.
Any number of spaces can go along with each tab.
"""
if not rpl_info:
if filename[-3:] in file_extensions:
with codecs.open(filename, encoding=encoding,
errors='replace') as f:
rpl_info = parse_ripple(f)
else:
raise IOError, 'File has wrong extension: "%s"' % filename[-3:]
for ext in ['raw', 'RAW']:
rawfname = filename[:-3] + ext
if os.path.exists(rawfname):
break
else:
rawfname = ''
if not rawfname:
raise IOError, 'RAW file "%s" does not exists' % rawfname
else:
data = read_raw(rpl_info, rawfname, mmap_mode=mmap_mode)
if rpl_info['record-by'] == 'vector':
print 'Loading as spectrum'
record_by = 'spectrum'
elif rpl_info['record-by'] == 'image':
print 'Loading as Image'
record_by = 'image'
else:
if len(data.shape) == 1:
print 'Loading as spectrum'
record_by = 'spectrum'
else:
print 'Loading as image'
record_by = 'image'
if rpl_info['record-by'] == 'vector':
idepth, iheight, iwidth = 2, 0, 1
names = [
'height',
'width',
'depth',
]
else:
idepth, iheight, iwidth = 0, 1, 2
names = ['depth', 'height', 'width']
scales = [1, 1, 1]
origins = [0, 0, 0]
units = ['', '', '']
sizes = [rpl_info[names[i]] for i in xrange(3)]
if 'signal' not in rpl_info:
rpl_info['signal'] = ""
if rpl_info.has_key('detector-peak-width-ev'):
original_parameters['detector-peak-width-ev'] = \
rpl_info['detector-peak-width-ev']
if rpl_info.has_key('depth-scale'):
scales[idepth] = rpl_info['depth-scale']
# ev-per-chan is the only calibration supported by the original ripple
# format
elif rpl_info.has_key('ev-per-chan'):
scales[idepth] = rpl_info['ev-per-chan']
if rpl_info.has_key('depth-origin'):
origins[idepth] = rpl_info['depth-origin']
if rpl_info.has_key('depth-units'):
units[idepth] = rpl_info['depth-units']
if rpl_info.has_key('depth-name'):
names[idepth] = rpl_info['depth-name']
if rpl_info.has_key('width-origin'):
origins[iwidth] = rpl_info['width-origin']
if rpl_info.has_key('width-scale'):
scales[iwidth] = rpl_info['width-scale']
if rpl_info.has_key('width-units'):
units[iwidth] = rpl_info['width-units']
if rpl_info.has_key('width-name'):
names[iwidth] = rpl_info['width-name']
if rpl_info.has_key('height-origin'):
origins[iheight] = rpl_info['height-origin']
if rpl_info.has_key('height-scale'):
scales[iheight] = rpl_info['height-scale']
if rpl_info.has_key('height-units'):
units[iheight] = rpl_info['height-units']
if rpl_info.has_key('height-name'):
names[iheight] = rpl_info['height-name']
mp = DictionaryBrowser({
'record_by': record_by,
'original_filename': os.path.split(filename)[1],
'signal_type': rpl_info['signal'],
})
if 'convergence-angle' in rpl_info:
mp.set_item('TEM.convergence_angle', rpl_info['convergence-angle'])
if 'tilt-stage' in rpl_info:
mp.set_item('TEM.tilt_stage', rpl_info['tilt-stage'])
if 'collection-angle' in rpl_info:
mp.set_item('TEM.EELS.collection_angle', rpl_info['collection-angle'])
if 'beam-energy' in rpl_info:
mp.set_item('TEM.beam_energy', rpl_info['beam-energy'])
if 'elevation-angle' in rpl_info:
mp.set_item('TEM.EDS.elevation_angle', rpl_info['elevation-angle'])
if 'azimuth-angle' in rpl_info:
mp.set_item('TEM.EDS.azimuth_angle', rpl_info['azimuth-angle'])
if 'energy-resolution' in rpl_info:
mp.set_item('TEM.EDS.energy_resolution_MnKa',
rpl_info['energy-resolution'])
if 'live-time' in rpl_info:
mp.set_item('TEM.EDS.live_time', rpl_info['live-time'])
axes = []
index_in_array = 0
for i in xrange(3):
if sizes[i] > 1:
axes.append({
'size': sizes[i],
'index_in_array': index_in_array,
'name': names[i],
'scale': scales[i],
'offset': origins[i],
'units': units[i],
})
index_in_array += 1
dictionary = {
'data': data.squeeze(),
'axes': axes,
'mapped_parameters': mp.as_dictionary(),
'original_parameters': rpl_info
}
return [
dictionary,
]