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# -*- coding: utf-8 -*-
#
# This file is part of Mantis, a Multivariate ANalysis Tool for Spectromicroscopy.
#
# Copyright (C) 2015 Benjamin Watts, Paul Scherrer Institut
# License: GNU GPL v3
#
# Mantis is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# any later version.
#
# Mantis is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details <http://www.gnu.org/licenses/>.
from __future__ import print_function
import json
import re, numpy, sys
from os.path import splitext, isfile
from collections import OrderedDict
title = 'JSON'
extension = ['*.json', '*.hdr']
read_types = ['spectrum','image','stack']
write_types = []
def identify(filename):
try:
if isfile(splitext(filename)[0] + '.json'):
JS = JS_FileLoader(splitext(filename)[0] + '.json')
return JS.num_regions>0 # return true if file contains at least one region
else:
return False
except:
return False
def GetFileStructure(FileName):
JS = JS_FileLoader(FileName)
if JS.num_regions<2 and JS.num_channels<2 and isfile(splitext(FileName)[0] + '.json'): #if json file exists, skip datachoicedialog
print("JSON-file found.")
return None # exit if only one choice
D = OrderedDict()
for i,R in enumerate(['Region_'+str(r) for r in range(JS.num_regions)]):
D[R] = OrderedDict()
D[R].definition = 'JSON'
D[R].scan_type = JS.js['ScanDefinition']['Type']
D[R].data_shape = JS.data_size[i]
D[R].data_axes = [JS.js['ScanDefinition']['Regions'][1]['PAxis']['Name'],JS.js['ScanDefinition']['Regions'][1]['QAxis']['Name'],JS.js['ScanDefinition']['StackAxis']['Name']]
for ch in range(1,JS.num_channels+1):
D[R][JS.js['Channels'][ch]['Name']] = OrderedDict()
return D
#-----------------------------------------------------------------------
class JS_FileLoader:
"""Parse .hdr file for metadata."""
js = []
f = []
def __init__(self, fileName,identify=False):
fileName = (splitext(fileName)[0] + '.json')
if not JS_FileLoader.js or JS_FileLoader.f != fileName: # prevent class from fetching and parsing the *.hdr file multiple times. Use the class attribute "hdr" instead if available and check if a new file is loaded.
# Parse the JSON file
with open(fileName) as f:
JS_FileLoader.js = json.load(f)
JS_FileLoader.f = fileName
else:
None
self.js = JS_FileLoader.js
if 'ScanDefinition' in self.js:
self.num_regions = int(self.js['ScanDefinition']['Regions'][0])
self.num_channels = int(self.js['Channels'][0])
self.file_path, self.file_ext = splitext(fileName)
self.data_size = self.parse_DataSize()
self.data_names = self.parseDataNames()
else:
self.num_regions = 0
self.num_channels = 0
#-----------------------------------------------------------------------
def parseDataNames(self):
"""Figure out names for the .xsp or .xim files that contain the actual data, then check that the files actually exist, printing warnings if they don't."""
DataNames = []
DataFlag = self.js['ScanDefinition']['Flags']
# Only for spectra:
if DataFlag in ['Spectra','Multi-Region Spectra']:
for num_R in range(self.num_regions):
DataNames2 = []
for num_Ch in range(self.num_channels):
DataNames2.append([self.file_path+'_'+str(num_R)+'.xsp'])
DataNames.append(DataNames2)
return DataNames
Alphabet = 'abcdefghijklmnopqrstuvwxyz'
boollst = [self.data_size[0][2] > 1,self.num_regions > 1]
bitfield = sum(val << bool for bool, val in enumerate(boollst[::-1]))
# Different detection channels can occur
# Four cases have to be distinguished.
if bitfield == 3: # multi region stack
DataNames = [[[self.file_path + '_' + Alphabet[num_Ch] + str(num_E).zfill(3) + str(num_R) + '.xim' for num_E in
range(self.data_size[0][2])] for num_Ch in range(self.num_channels)] for num_R in
range(self.num_regions)]
elif bitfield == 2 and not DataFlag in ['Image']: # single region stack excluding line scans!
DataNames = [[[self.file_path + '_' + Alphabet[num_Ch] + str(num_E).zfill(3) + '.xim' for num_E in
range(self.data_size[0][2])] for num_Ch in range(self.num_channels)]]
elif bitfield == 1: # multi region image
DataNames = [[[self.file_path + '_' + Alphabet[num_Ch] + str(num_R) + '.xim'] for num_Ch in range(self.num_channels)] for
num_R in range(self.num_regions)]
else: # single region image
DataNames = [[[self.file_path + '_' + Alphabet[num_Ch] + '.xim'] for num_Ch in range(self.num_channels)]]
return DataNames
#-----------------------------------------------------------------------
def parse_DataSize(self):
"""Calculate data array size. This is useful for making sure all of the lists of data are the correct length."""
DataSize = []
for R_num in range(self.num_regions):
DataSize.append([1,1,1])# [PAxis,QAxis,StackAxis] (switch to [X1,X2,E] later)]
DataSize[R_num][0] = int(self.js['ScanDefinition']['Regions'][R_num+1]['PAxis']['Points'][0])
if 'QAxis' in self.js['ScanDefinition']['Regions'][R_num+1] and 'Points' in self.js['ScanDefinition']['Regions'][R_num+1]['QAxis']:
DataSize[R_num][1] = int(self.js['ScanDefinition']['Regions'][R_num+1]['QAxis']['Points'][0])
if 'StackAxis' in self.js['ScanDefinition'] and 'Points' in self.js['ScanDefinition']['StackAxis']:
DataSize[R_num][2] = int(self.js['ScanDefinition']['StackAxis']['Points'][0])
if self.js['ScanDefinition']['Type'] in ['NEXAFS Point Scan','NEXAFS Line Scan']:
DataSize[R_num] = [DataSize[R_num][1],1,DataSize[R_num][0]]#switch to [X1,X2,E] format
# DataSize[R_num] = [1,DataSize[R_num][1],DataSize[R_num][0]]#also works, but might be problematic for finding number of spatial points
return DataSize
#-----------------------------------------------------------------------
def read(filename, self, selection=None, *args, **kwargs):
JS = JS_FileLoader(filename)
allowed = ['Image Stack', 'Image', 'Multi-Region Image Stack']
if JS.js['ScanDefinition']['Flags'] in allowed:
self.x_dist = numpy.array([float(i) for i in JS.js['ScanDefinition']['Regions'][selection[0]+1]['PAxis']['Points'][1:] ])
self.y_dist = numpy.array([float(i) for i in JS.js['ScanDefinition']['Regions'][selection[0]+1]['QAxis']['Points'][1:] ])
self.ev = numpy.array([float(i) for i in JS.js['ScanDefinition']['StackAxis']['Points'][1:] ])
self.n_cols = len(self.x_dist)
self.n_rows = len(self.y_dist)
self.n_ev = len(self.ev)
msec = float(JS.js['ScanDefinition']['Dwell'])
self.data_dwell = numpy.ones((self.n_ev))*msec
imagestack = numpy.empty((self.n_cols,self.n_rows,self.n_ev), numpy.int32)
for i in range(len(JS.data_names[selection[0]][selection[1]])):
try:
imagestack[:,:,i] = numpy.loadtxt(JS.data_names[selection[0]][selection[1]][i], numpy.int32).T
except ValueError:
print("Aborted stack or XIMs with inconsistent dimensions.")
imagestack[:,:,i] = numpy.nan
except IOError:
print("Image file not found.")
imagestack[:,:,i] = numpy.nan
self.absdata = numpy.empty((self.n_cols,self.n_rows, self.n_ev))
self.absdata = numpy.reshape(imagestack, (self.n_cols,self.n_rows, self.n_ev), order='F')
self.fill_h5_struct_from_stk()
else:
print("Unknown Format")
return
#-----------------------------------------------------------------------
def read_js_i0(self, filename, *args, **kwargs):
JS = JS_FileLoader(filename)
if 'ScanType' in JS.js['ScanDefinition'] and JS.js['ScanDefinition']['ScanType'] == 'Spectra':
Energies = JS.js['ScanDefinition']['Regions'][1]['PAxis']['Points'][1:]
tempimage = numpy.loadtxt(JS.data_names[0][0][0], numpy.float32)
Data = tempimage[:,1]
elif JS.js['ScanDefinition']['Type'] == 'NEXAFS Line Scan':
Energies = JS.js['ScanDefinition']['Regions'][1]['PAxis']['Points'][1:]
tempimage = numpy.loadtxt(JS.data_names[0][0][0], numpy.int32)
Data = numpy.mean(tempimage,axis=0)
else:# Image Stack
Energies = JS.js['ScanDefinition']['StackAxis']['Points'][1:]
tempimage = numpy.empty((JS.data_size[0][0],JS.data_size[0][1]), numpy.int32)
Data = numpy.empty((JS.data_size[0][2]), numpy.int32)
for i in range(len(JS.data_names[0][0])):
tempimage = numpy.loadtxt(JS.data_names[0][0][i], numpy.int32)
Data[i] = numpy.mean(tempimage)
msec = float(JS.js['ScanDefinition']['Dwell'])#shouldn't this be needed?
self.i0_dwell = msec
self.evi0 = numpy.array([float(i) for i in Energies])
self.i0data = Data
return
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