def read_parnames(runpath):
"""
Author: Kari A. Frank
Date: March 20, 2014
Purpose: Read in parameters.txt file from an xmc run to get
names of columns in deconvolution files.
Usage: parnames = read_parnames(runpath)
Input:
runpath -- Path to xmc run directory, containing the file parameters.txt.
Only the first line of the file is read. Parameter names
should contain no spaces or punctuation and are assumed to be
separated by commas. They should correspond to the columns
of the deconvolution files.
Output:
returns string list of column (parameter) names
Usage Notes:
"""
#--Set file paths--
parfile = runpath+'/parameters.txt'
outpars = fu.parse_file_line(parfile)
#--return string list--
return outpars
def merge_output(runpath='./',filetype='deconvolution',save=True,sep='\t'):
"""
Author: Kari A. Frank
Date: October 16, 2015
Purpose: Read in deconvolution, statistic, or other files from
an xmc run and merge into a single dataframe, with an extra
column to specify iteration. optionally can also save as
a text file.
Usage: merge_output(runpath='./',filetype='deconvolution',save=True)
Input:
runpath -- Path to xmc run directory, containing the
deconvolution, statistic, etc. files
filetype -- string containing the type of xmc file to merge
deconvolution, statistic, sigma, mean, changed
save -- boolean switch to prevent saving of the merged
file. use save=False if all that is need is the merged
dataframe (default=True).
sep -- optionally specify the delimiter in the output file
(default='\t', tab-separated)
Output:
- if save=True, writes a text file <filetype>_merged.txt into the
runpath directory
- returns a pandas dataframe containing data from all the input files
Usage Notes:
- overwrites the file if it already exists
- automatically includes all iterations present
- iterations are not written in order, but an extra column is added
to specify which iteration each row is associated with
- the created file can be read into a dataframe using
datatable = pd.read_table(mergedfile,sep='\t',index_col=0)
"""
# - get list of files -
filelist = fu.ls_to_list(runpath,ls_args = filetype+'.*')
# --Initialize dataframe with first file --
# - read file -
datatable = pd.read_table(runpath+'/'+filelist[0],sep='\s+',header=None)
# - check for nans and drop them -
datatable = remove_nans(datatable,filename=filelist[0])
# - add headers -
parnames = []
# read header information
if filetype == 'statistic':
parnames = ['stat1','dof','oversim','nblobs','alpha','chi2']
datatable.columns = parnames
if filetype == 'deconvolution':
if os.path.isfile(runpath+'/parameters.txt'):
parnames = fu.parse_file_line(runpath+'/parameters.txt')
datatable.columns = parnames
# - get iteration number and add as column -
iternum = int(filelist[0].split('.')[-1]) # returns integer
datatable['iteration'] = iternum
# -- Loop through files and concatenate into single dataframe --
for f in filelist[1:]:
if os.stat(runpath+'/'+f).st_size > 0:
newframe = pd.read_table(runpath+'/'+f,sep='\s+',
header=None)
iternum = int(f.split('.')[-1]) # returns integer
if len(parnames) > 0: newframe.columns=parnames
newframe['iteration'] = iternum
# - check for nans and drop them -
newframe = remove_nans(newframe,filename=f)
datatable = pd.concat([datatable,newframe],
ignore_index=True)
else:
print 'Warning: '+f+' is missing or empty. Skipping.'
# -- Write to file --
if save == True: datatable.to_csv(runpath+'/'+filetype+'_merged.txt',
sep=sep)
return datatable