def _loadBioformats(self, filename):
#from PYME.IO.FileUtils import readTiff
from PYME.IO.DataSources import BioformatsDataSource
try:
import bioformats
except ImportError:
logger.exception(
'Error importing bioformats - is the python-bioformats module installed?'
)
raise
#mdfn = self.FindAndParseMetadata(filename)
print("Bioformats:loading data")
self.dataSource = BioformatsDataSource.DataSource(filename, None)
self.mdh = MetaDataHandler.NestedClassMDHandler(MetaData.BareBones)
print("Bioformats:loading metadata")
OMEXML = bioformats.get_omexml_metadata(filename).encode('utf8')
print("Bioformats:parsing metadata")
OMEmd = MetaDataHandler.OMEXMLMDHandler(OMEXML)
self.mdh.copyEntriesFrom(OMEmd)
print("Bioformats:done")
print(self.dataSource.shape)
self.dataSource = BufferedDataSource.DataSource(
self.dataSource, min(self.dataSource.getNumSlices(), 50))
self.data = self.dataSource #this will get replaced with a wrapped version
print(self.data.shape)
#from PYME.ParallelTasks.relativeFiles import getRelFilename
self.seriesName = getRelFilename(filename)
self.mode = 'default'
def Export(self,
data,
outFile,
xslice,
yslice,
zslice,
metadata=None,
events=None,
origName=None,
progressCallback=None):
from PYME.contrib.gohlke import tifffile
from PYME.IO import dataWrap
def _bool_to_uint8(data):
if data.dtype == 'bool':
return data.astype('uint8')
else:
return data
if data.nbytes > 2e9:
warnings.warn(
'Data is larger than 2GB, generated TIFF may not read in all software'
)
if data.nbytes > 4e9:
raise RuntimeError(
'TIFF has a maximum file size of 4GB, crop data or save as HDF'
)
dw = dataWrap.ListWrap([
numpy.atleast_3d(
_bool_to_uint8(data[xslice, yslice, zslice, i].squeeze()))
for i in range(data.shape[3])
])
#xmd = None
if not metadata is None:
xmd = MetaDataHandler.OMEXMLMDHandler(mdToCopy=metadata)
if not origName is None:
xmd.setEntry('cropping.originalFile', origName)
xmd.setEntry('cropping.xslice', xslice.indices(data.shape[0]))
xmd.setEntry('cropping.yslice', yslice.indices(data.shape[1]))
xmd.setEntry('cropping.zslice', zslice.indices(data.shape[2]))
description = xmd.getXML(dw)
else:
description = None
tifffile.imsave_f(outFile, dw, description=description)
if progressCallback:
try:
progressCallback(100, 100)
except:
pass
def Export(self,
data,
outFile,
xslice,
yslice,
zslice,
metadata=None,
events=None,
origName=None,
progressCallback=None):
from PYME.contrib.gohlke import tifffile
from PYME.IO import dataWrap
def _bool_to_uint8(data):
if data.dtype == 'bool':
return data.astype('uint8')
else:
return data
dw = dataWrap.ListWrap([
numpy.atleast_3d(
_bool_to_uint8(data[xslice, yslice, zslice, i].squeeze()))
for i in range(data.shape[3])
])
#xmd = None
if not metadata is None:
xmd = MetaDataHandler.OMEXMLMDHandler(mdToCopy=metadata)
if not origName is None:
xmd.setEntry('cropping.originalFile', origName)
xmd.setEntry('cropping.xslice', xslice.indices(data.shape[0]))
xmd.setEntry('cropping.yslice', yslice.indices(data.shape[1]))
xmd.setEntry('cropping.zslice', zslice.indices(data.shape[2]))
description = xmd.getXML(dw)
else:
description = None
tifffile.imsave_f(outFile, dw, description=description)
if progressCallback:
try:
progressCallback(100, 100)
except:
pass
def _findAndParseMetadata(self, filename):
"""Try and find and load a .xml or .md metadata file that might be ascociated
with a given image filename. See the relevant metadatahandler classes
for details."""
import xml.parsers.expat
from PYME.IO import unifiedIO
if not self.mdh is None:
return #we already have metadata (probably passed in on command line)
mdf = None
xmlfn = os.path.splitext(filename)[0] + '.xml'
xmlfnmc = os.path.splitext(filename)[0].split('__')[0] + '.xml'
if os.path.exists(xmlfn):
try:
self.mdh = MetaDataHandler.NestedClassMDHandler(
MetaData.TIRFDefault)
self.mdh.copyEntriesFrom(MetaDataHandler.XMLMDHandler(xmlfn))
mdf = xmlfn
except xml.parsers.expat.ExpatError:
#fix for bug in which PYME .md was written with a .xml extension
self.mdh = MetaDataHandler.NestedClassMDHandler(
MetaData.BareBones)
self.mdh.copyEntriesFrom(
MetaDataHandler.SimpleMDHandler(xmlfn))
mdf = xmlfn
elif os.path.exists(
xmlfnmc): #this is a single colour channel of a pair
self.mdh = MetaDataHandler.NestedClassMDHandler(
MetaData.TIRFDefault)
self.mdh.copyEntriesFrom(MetaDataHandler.XMLMDHandler(xmlfnmc))
mdf = xmlfnmc
else:
self.mdh = MetaDataHandler.NestedClassMDHandler(MetaData.BareBones)
#check for simple metadata (python code with an .md extension which
#fills a dictionary called md)
mdfn = os.path.splitext(filename)[0] + '.md'
jsonfn = os.path.splitext(filename)[0] + '.json'
if os.path.exists(mdfn):
self.mdh.copyEntriesFrom(MetaDataHandler.SimpleMDHandler(mdfn))
mdf = mdfn
elif os.path.exists(jsonfn):
import json
with open(jsonfn, 'r') as f:
mdd = json.load(f)
self.mdh.update(mdd)
elif filename.endswith('.lsm'):
#read lsm metadata
from PYME.contrib.gohlke.tifffile import TIFFfile
tf = TIFFfile(filename)
lsm_info = tf[0].cz_lsm_scan_information
self.mdh['voxelsize.x'] = lsm_info['line_spacing']
self.mdh['voxelsize.y'] = lsm_info['line_spacing']
self.mdh['voxelsize.z'] = lsm_info['plane_spacing']
def lsm_pop(basename, dic):
for k, v in dic.items():
if isinstance(v, list):
#print k, v
for i, l_i in enumerate(v):
#print i, l_i, basename
lsm_pop(
basename + k + '.' + k[:-1] + '%i.' % i,
l_i)
else:
self.mdh[basename + k] = v
lsm_pop('LSM.', lsm_info)
elif filename.endswith('.tif'):
#look for OME data...
from PYME.contrib.gohlke.tifffile import TIFFfile
tf = TIFFfile(filename)
if tf.is_ome:
try:
omemdh = MetaDataHandler.OMEXMLMDHandler(
tf.pages[0].tags['image_description'].value)
self.mdh.copyEntriesFrom(omemdh)
except IndexError:
pass
elif filename.endswith('.dcimg'): #Bewersdorf lab Biplane
# FIXME load seriesXX.json for seriesXX_chunkXX.dcimg files more elegantly
jsonfn = filename[:-22] + '.json'
import json
try:
mdd = json.loads(unifiedIO.read(jsonfn))
self.mdh.update(mdd)
except IOError:
pass
elif filename.endswith('.dbl'): #Bewersdorf lab STED
mdfn = filename[:-4] + '.txt'
entrydict = {}
try: #try to read in extra metadata if possible
with unifiedIO.openFile(mdfn, 'r') as mf:
for line in mf:
s = line.split(':')
if len(s) == 2:
entrydict[s[0]] = s[1]
except IOError:
pass
# vx, vy = entrydict['Pixel size (um)'].split('x')
# self.mdh['voxelsize.x'] = float(vx)
# self.mdh['voxelsize.y'] = float(vy)
# self.mdh['voxelsize.z'] = 0.2 #FIXME for stacks ...
#
# sx, sy = entrydict['Image format'].split('x')
# self.mdh['Camera.ROIWidth'] = int(sx)
# self.mdh['Camera.ROIHeight'] = int(sy)
#
# self.mdh['NumImages'] = int(entrydict['# Images'])
with unifiedIO.openFile(filename) as df:
s = df.read(8)
Z, X, Y, T = numpy.fromstring(s, '>u2')
s = df.read(16)
depth, width, height, elapsed = numpy.fromstring(s, '<f4')
self.mdh['voxelsize.x'] = width / X
self.mdh['voxelsize.y'] = height / Y
self.mdh['voxelsize.z'] = depth
self.mdh['Camera.ROIWidth'] = X
self.mdh['Camera.ROIHeight'] = Y
self.mdh['NumImages'] = Z * T
def _sanitise_key(key):
k = key.replace('#', 'Num')
k = k.replace('(%)', '')
k = k.replace('(', '')
k = k.replace(')', '')
k = k.replace('.', '')
k = k.replace('/', '')
k = k.replace('?', '')
k = k.replace(' ', '')
if not k[0].isalpha():
k = 's' + k
return k
for k, v in entrydict.items():
self.mdh['STED.%s' % _sanitise_key(k)] = v
#else: #try bioformats
# OMEXML = bioformats.get_omexml_metadata(filename).encode('utf8')
# OMEmd = MetaDataHandler.OMEXMLMDHandler(OMEXML)
# self.mdh.copyEntriesFrom(OMEmd)
if self.haveGUI and not ('voxelsize.x' in self.mdh.keys()
and 'voxelsize.y' in self.mdh.keys()):
from PYME.DSView.voxSizeDialog import VoxSizeDialog
dlg = VoxSizeDialog(None)
dlg.ShowModal()
self.mdh.setEntry('voxelsize.x', dlg.GetVoxX())
self.mdh.setEntry('voxelsize.y', dlg.GetVoxY())
self.mdh.setEntry('voxelsize.z', dlg.GetVoxZ())
return mdf
def _loadBioformats(self, filename):
try:
import bioformats
except ImportError:
logger.exception(
'Error importing bioformats - is the python-bioformats module installed?'
)
raise
from PYME.IO.DataSources import BioformatsDataSource
series_num = None
if '?' in filename:
#we have a query string to pick the series
from six.moves import urllib
filename, query = filename.split('?')
try:
series_num = int(urllib.parse.parse_qs(query)['series'][0])
except KeyError:
pass
#mdfn = self.FindAndParseMetadata(filename)
print("Bioformats:loading data")
bioformats_file = BioformatsDataSource.BioformatsFile(filename)
if series_num is None and bioformats_file.series_count > 1:
print('File has multiple series, need to pick one.')
if self.haveGUI:
import wx
dlg = wx.SingleChoiceDialog(None, 'Series', 'Select a series',
bioformats_file.series_names)
if dlg.ShowModal() == wx.ID_OK:
series_num = dlg.GetSelection()
else:
logger.warning('No GUI, using 0th series.')
self.dataSource = BioformatsDataSource.DataSource(bioformats_file,
series=series_num)
self.mdh = MetaDataHandler.NestedClassMDHandler(MetaData.BareBones)
# NOTE: We are triple-loading metadata. BioformatsDataSource.BioformatsFile.rdr has metadata (hard to access),
# BioformatsDataSource.BioformatsFile has metadata, and now we are loading the same metadata again here.
print("Bioformats:loading metadata")
OMEXML = bioformats.get_omexml_metadata(filename).encode('utf8')
print("Bioformats:parsing metadata")
OMEmd = MetaDataHandler.OMEXMLMDHandler(OMEXML)
self.mdh.copyEntriesFrom(OMEmd)
print("Bioformats:done")
#fix voxelsizes if not specified in OME metadata
if self.haveGUI and ((self.mdh['voxelsize.x'] < 0) or
(self.mdh['voxelsize.y'] < 0)):
from PYME.DSView.voxSizeDialog import VoxSizeDialog
dlg = VoxSizeDialog(None)
dlg.ShowModal()
self.mdh.setEntry('voxelsize.x', dlg.GetVoxX())
self.mdh.setEntry('voxelsize.y', dlg.GetVoxY())
self.mdh.setEntry('voxelsize.z', dlg.GetVoxZ())
dlg.Destroy()
print(self.dataSource.shape)
self.dataSource = BufferedDataSource.DataSource(
self.dataSource, min(self.dataSource.getNumSlices(), 50))
self.data = self.dataSource #this will get replaced with a wrapped version
print(self.data.shape)
#from PYME.ParallelTasks.relativeFiles import getRelFilename
self.seriesName = getRelFilename(filename)
self.mode = 'default'
