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LoadGudrunOutput.py
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LoadGudrunOutput.py
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# Mantid Repository : https://github.com/mantidproject/mantid
#
# Copyright © 2018 ISIS Rutherford Appleton Laboratory UKRI,
# NScD Oak Ridge National Laboratory, European Spallation Source,
# Institut Laue - Langevin & CSNS, Institute of High Energy Physics, CAS
# SPDX - License - Identifier: GPL - 3.0 +
from mantid.api import (FileProperty, WorkspaceProperty, PythonAlgorithm,
AlgorithmFactory, FileAction, PropertyMode)
from mantid.kernel import Direction
from mantid.simpleapi import LoadAscii, CreateWorkspace
import itertools
class LoadGudrunOutput(PythonAlgorithm):
def name(self):
return 'LoadGudrunOutput'
def category(self):
return 'DataHandling'
def summary(self):
return 'Loads the common outputs created from Gudrun'
def PyInit(self):
self.declareProperty(FileProperty(name='InputFile', defaultValue='', action=FileAction.Load,
extensions=[".dcs01",
".mdsc01",
".mint01",
".mdor01",
".mgor01"]),
doc="Gudrun output file to be loaded.")
self.declareProperty(WorkspaceProperty(name='OutputWorkspace', defaultValue='',
direction=Direction.Output,
optional=PropertyMode.Optional),
doc="If No OutputWorkspace is provided, then the workpsace name "
"will be obtained from the meta data in the input file.")
def PyExec(self):
input_file = self.getProperty('InputFile').value
output_ws = self.getPropertyValue('OutputWorkspace')
if not output_ws:
output_ws = self.get_title(input_file)
number_of_columns, data_line_start = self.find_number_of_columns(input_file)
self.load_gudrun_file(input_file, output_ws, number_of_columns, data_line_start)
self.setProperty('OutputWorkspace', output_ws)
def get_title(self, input_file):
"""
Return the title from the file meta data
:param input_file: file to get meta data from
:return: (title)
"""
with open(input_file, 'r') as gudrun_file:
first_line = gudrun_file.readline()
first_line = first_line[2:]
return first_line.replace('.', '-')
def find_number_of_columns(self, input_file):
"""
Evaluate how many columns of data there are in the file
:param input_file: The file to check
:return: (The number of columns of data, the first line of data)
"""
with open(input_file, 'r') as gudrun_file:
data_line_start = 0
while gudrun_file.readline().startswith('#'):
# skip over lines that are commented
data_line_start += 1
row = self.format_data_row(gudrun_file.readline().split(" "))
return len(row), data_line_start
def load_gudrun_file(self, input_file, output_workspace, number_of_columns, first_data_line):
"""
Loads the gudrun file using the mantid LoadAscii algorithm
:param input_file: The file to load
:param output_workspace: The workspace to be the result of the load
:param number_of_columns: The number of columns in the file being loaded
:param first_data_line: The first line to expect data on
:return: The outputWorkspace of the Load Algorithm
"""
if number_of_columns % 2 == 0:
print(number_of_columns)
raise ValueError('Incorrect data format: The input file {} must have an odd number '
'of columns in the format X , Y , E, Y1, E1, Y2, E2, ...'.format(input_file))
elif number_of_columns == 3:
LoadAscii(Filename=input_file, OutputWorkspace=output_workspace, CommentIndicator='#')
else:
self.load_multi_column_file(input_file, output_workspace, first_data_line)
def load_multi_column_file(self, input_file, output_workspace, first_data_line):
"""
Load a file that has an odd number of columns that is more than 3
:param input_file: The file to extract the data from
:param output_workspace: tThe file to put the data into
:param first_data_line: The first line to expect data on
:return: The outputWorkspace pointer
"""
with open(input_file, 'r') as gudrun_file:
data_rows = [self.format_data_row(line.split(" ")) for line in gudrun_file.readlines()[first_data_line:]]
x_data, y_data, e_data = self.create_2d_data_arrays(data_rows)
n_spec = int((len(data_rows[0]) - 1) / 2)
CreateWorkspace(OutputWorkspace=output_workspace,
DataX=x_data,
DataY=y_data,
DataE=e_data,
NSpec=n_spec)
def format_data_row(self, data_row):
"""
Remove special characters and empty lines from data list
:param data_row: The data to format
:return: a formatted data row
"""
formatted_row = [data.rstrip() for data in data_row if data != '']
return formatted_row
def create_2d_data_arrays(self, all_data):
"""
Create 1d x data array and 2d y and e data arrays
:param all_data: All the data to create arrays from. Assumed format of:
X, Y, E, Y1, E1, Y2, E2 ... (first bin)
X, Y, E, Y1, E1, Y2, E2 ... (second bin)
:return: ([x_data], [y, y1, y2, y3], [e, e1, e2, e3])
"""
row_length = len(all_data[0])
x_data = []
# Create empty 2d lists
y_data = [[] for _ in range(int((row_length - 1) / 2.0))]
e_data = [[] for _ in range(int((row_length - 1) / 2.0))]
for data_row in all_data:
x_data.append(float(data_row[0]))
for row_index in range(1, len(data_row)):
if row_index % 2 == 1:
# y_data
data_array_index = int((row_index/2.0)-0.5)
y_data[data_array_index].append(float(data_row[row_index]))
else:
# e_data
data_array_index = int((row_index/2.0)-1.0)
e_data[data_array_index].append(float(data_row[row_index]))
# collapse 2d lists
y_data = list(itertools.chain.from_iterable(y_data))
e_data = list(itertools.chain.from_iterable(e_data))
return x_data, y_data, e_data
AlgorithmFactory.subscribe(LoadGudrunOutput)