def getSOM(self, som_id=None, **kwargs):
"""
This method parses the resource and creates a SOM from the information.
@param som_id: The name of the SOM. The default value is C{None}. This
retrieves all information.
@param kwargs: A list of keyword arguments that the function accepts:
@keyword no_sqr: Do not square the error values from the file. This is
important if the data will be subsequently plotted.
The default value is I{False}.
@type no_sqr: C{boolean}
"""
try:
self.__no_sqr__ = kwargs["no_sqr"]
except KeyError:
self.__no_sqr__ = False
som = SOM.SOM()
som.setDataSetType("density")
self.__set_axes(som)
self.__readData(som)
som.setYLabel("Counts")
uscale = som.getAxisUnits(1) + " " + som.getAxisUnits(0)
som.setYUnits("Counts / " + uscale)
som.attr_list = dst_utils.parse_spec_header(self.__file)
return som
def getSOM(self, som_id=None, **kwargs):
"""
This method parses the resource and creates a SOM from the information.
@param som_id: The name of the SOM. The default value is C{None}. This
retrieves all information.
@param kwargs: A list of keyword arguments that the function accepts:
@keyword no_sqr: Do not square the error values from the file. This is
important if the data will be subsequently plotted.
The default value is I{False}.
@type no_sqr: C{boolean}
"""
try:
self.__no_sqr__ = kwargs["no_sqr"]
except KeyError:
self.__no_sqr__ = False
som = SOM.SOM()
som.setDataSetType("density")
self.__set_axes(som)
self.__readData(som)
som.setYLabel("Counts")
uscale = som.getAxisUnits(1) + " " + som.getAxisUnits(0)
som.setYUnits("Counts / " + uscale)
som.attr_list = dst_utils.parse_spec_header(self.__file)
return som
def getSOM(self, som_id=None, **kwargs):
"""
This method parses the resource and creates a SOM from the information.
@param som_id: The name of the SOM. The default value is C{None}. This
retrieves all information. If multiple detector IDs are
specified, they should be comma-separated.
@type som_id: C{string}
@param kwargs: A list of keyword arguments that the function accepts:
@keyword roi_file: A list of spectrum IDs to filter the data on
@type roi_file: C{string}
@keyword mask_file: A list of spectrum IDs to filter (exclude) the
data on
@type mask_file: C{string}
@keyword no_sqr: Do not square the error values from the file. This is
important if the data will be subsequently plotted.
The default value is I{False}.
@type no_sqr: C{boolean}
"""
# Check for list of detector IDs
if som_id is not None:
if "," in som_id:
som_ids = som_id.split(',')
else:
som_ids = [som_id]
# Check to see if an ROI file was passed
try:
roi_filename = kwargs["roi_file"]
try:
roi = SOM.Roi(roi_filename)
except TypeError:
# roi_filename is None
roi = None
except KeyError:
roi = None
# Check to see if a mask file was passed
try:
mask_filename = kwargs["mask_file"]
try:
mask = SOM.Roi(mask_filename)
except TypeError:
# mask_filename is None
mask = None
except KeyError:
mask = None
try:
self.__no_sqr__ = kwargs["no_sqr"]
except KeyError:
self.__no_sqr__ = False
som = SOM.SOM()
som.attr_list = dst_utils.parse_spec_header(self.__file)
# Reset file read to not miss #L line
fname = self.__file.name
self.release_resource
self.__file = open(fname, "r")
for line in self.__file:
if line.startswith("#L"):
self.readSOM(som, line)
elif line.startswith("("):
lparts = line.split()
# The spectrum ID is the first three slots
so_id = SOM.NeXusId.fromList(lparts[0:3])
filter_so = False
# Check the list of detector IDs
if som_id is not None:
if so_id.getDetId() not in som_ids:
filter_so = True
# Check the ROI list
if roi is not None:
if so_id not in roi:
filter_so = True
# Check the Mask list
if mask is not None:
if so_id in mask:
filter_so = True
if not filter_so:
self.readSO(som, so_id.toTuple(), lparts)
return som
def getSOM(self, som_id=None, **kwargs):
"""
This method parses the resource and creates a SOM from the information.
@param som_id: The name of the SOM. The default value is C{None}. This
retrieves all information.
@param kwargs: A list of keyword arguments that the function accepts:
@keyword roi_file: A list of spectrum IDs to filter the data on
@type roi_file: C{string}
@keyword no_sqr: Do not square the error values from the file. This is
important if the data will be subsequently plotted.
The default value is I{False}.
@type no_sqr: C{boolean}
"""
import os
try:
roi_filename = kwargs["roi_file"]
try:
roi = SOM.Roi(roi_filename)
except TypeError:
# roi_filename is None
roi = None
except KeyError:
roi = None
try:
self.__no_sqr__ = kwargs["no_sqr"]
except KeyError:
self.__no_sqr__ = False
som = SOM.SOM()
som.attr_list = dst_utils.parse_spec_header(self.__file)
# Setup some things for working through the data
got_columns = False
got_header = False
nexus_id = None
data_lines = []
for line in self.__file:
if line.startswith("#S"):
self.__readSO(data_lines, nexus_id, som)
data_lines = []
parts = line.split()
try:
nexus_id = SOM.NeXusId.fromList(parts[4:])
except TypeError:
# ID is not a pixel format
nexus_id = parts[-1]
# Check the ROI list
if roi is not None:
if nexus_id not in roi:
nexus_id = None
elif line.startswith("#L"):
if not got_header:
self.__readSOM(som, line.lstrip("#L "))
got_header = True
elif line.startswith("#N"):
if not got_columns:
self.__columns = int(line.split()[-1].strip())
got_columns = True
elif line.startswith(os.linesep):
continue
else:
data_lines.append(line)
# One spectrum or final spectrum won't get processed in the above
# so we must force processing
self.__readSO(data_lines, nexus_id, som)
return som