def split(self,xcol,func=None):
"""Splits the current AnalyseFile object into multiple AnalyseFile objects where each one contains the rows
from the original object which had the same value of a given column.
@param xcol The index of the column to look for values in. This can be a list in which case a DataFolder with groups
with subfiles is built up by applying each item in the xcol list recursively.
@param func A callable function that can be evaluated to find the value to determine which output object
each row belongs in. If this is left as the default None then the column value is converted to a string and that is used.
The function to be of the form f(x,r) where x is a single float value and r is a list of floats representing the complete row.
The return value should be a hashable value. @a func can also be a list if @A xcol is a list, in which the @a func values are used along
with the @a xcol values.
@return A DataFolder object containing the individual AnalyseFile objects
"""
from Stoner.Folders import DataFolder
out=DataFolder(nolist=True)
files=dict()
morecols=[]
morefuncs=None
if isinstance(xcol,list) and len(xcol)<=1:
xcol=xcol[0]
elif isinstance(xcol,list):
morecols=xcol[1:]
xcol=xcol[0]
if isinstance(func,list) and len(func)<=1:
func=func[0]
elif isinstance(func,list):
morefuncs=func[1:]
func=func[0]
if func is None:
for val in numpy.unique(self.column(xcol)):
files[str(val)]=self.clone
files[str(val)].data=self.search(xcol,val)
else:
xcol=self.find_col(xcol)
for r in self.rows():
x=r[xcol]
key=func(x,r)
if key not in files:
files[key]=self.clone
files[key].data=numpy.array([r])
else:
files[key]=files[key]+r
for k in files:
files[k].filename="{}={}".format(xcol,k)
if len(morecols)>0:
for k in sorted(files.keys()):
out.groups[k]=files[k].split(morecols,morefuncs)
else:
out.files=[files[k] for k in sorted(files.keys())]
return out
