def readData(filename, x=all, y=all, z=all, **args):
"""Read data from a single tif image or stack
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
array: image data
"""
dsize = dataSize(filename)
#print("dsize %s" % str(dsize);
if len(dsize) == 2:
data = tiff.imread(filename, key=0)
#print("data.shape %s" % str(data.shape);
return io.dataToRange(data.transpose([1, 0]), x=x, y=y)
#return io.dataToRange(data, x = x, y = y);
else:
if z is all:
data = tiff.imread(filename)
if data.ndim == 2:
# data = data
data = data.transpose([1, 0])
elif data.ndim == 3:
#data = data.transpose([1,2,0]);
data = data.transpose([2, 1, 0])
elif data.ndim == 4: # multi channel image
#data = data.transpose([1,2,0,3]);
data = data.transpose([2, 1, 0, 3])
else:
raise RuntimeError('readData: dimension %d not supproted!' %
data.ndim)
return io.dataToRange(data, x=x, y=y, z=all)
else: #optimize for z ranges
ds = io.dataSizeFromDataRange(dsize, x=x, y=y, z=z)
t = tiff.TiffFile(filename)
p = t.pages[0]
data = numpy.zeros(ds, dtype=p.dtype)
rz = io.toDataRange(dsize[2], r=z)
#print("test"
#print(rz;
#print(dsize
for i in range(rz[0], rz[1]):
xydata = t.pages[i].asarray()
#data[:,:,i-rz[0]] = io.dataToRange(xydata, x = x, y = y);
data[:, :, i - rz[0]] = io.dataToRange(xydata.transpose([1,
0]),
x=x,
y=y)
return data
def readData(filename, x = all, y = all, z = all, **args):
"""Read data from a single tif image or stack
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
array: image data
"""
dsize = dataSize(filename);
#print "dsize %s" % str(dsize);
if len(dsize) == 2:
data = tiff.imread(filename, key = 0);
#print "data.shape %s" % str(data.shape);
return io.dataToRange(data.transpose([1,0]), x = x, y = y);
#return io.dataToRange(data, x = x, y = y);
else:
if z is all:
data = tiff.imread(filename);
if data.ndim == 2:
# data = data
data = data.transpose([1,0]);
elif data.ndim == 3:
#data = data.transpose([1,2,0]);
data = data.transpose([2,1,0]);
elif data.ndim == 4: # multi channel image
#data = data.transpose([1,2,0,3]);
data = data.transpose([2,1,0,3]);
else:
raise RuntimeError('readData: dimension %d not supproted!' % data.ndim)
return io.dataToRange(data, x = x, y = y, z = all);
else: #optimize for z ranges
ds = io.dataSizeFromDataRange(dsize, x = x, y = y, z = z);
t = tiff.TiffFile(filename);
p = t.pages[0];
data = numpy.zeros(ds, dtype = p.dtype);
rz = io.toDataRange(dsize[2], r = z);
#print "test"
#print rz;
#print dsize
for i in range(rz[0], rz[1]):
xydata = t.pages[i].asarray();
#data[:,:,i-rz[0]] = io.dataToRange(xydata, x = x, y = y);
data[:,:,i-rz[0]] = io.dataToRange(xydata.transpose([1,0]), x = x, y = y);
return data
def readData(filename, x = all, y = all, z = all):
"""Read data from raw/mhd image
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
array: image data
"""
imr = vtk.vtkMetaImageReader()
imr.SetFileName(filename);
imr.Update()
im = imr.GetOutput()
dims = im.GetDimensions()
print dims
sc = im.GetPointData().GetScalars()
img = vtk_to_numpy(sc)
#print img.shape
dims = list(dims);
dims[0:3] = [dims[2], dims[1], dims[0]];
imgs = list(img.shape);
if len(imgs) > 1:
imgs.pop(0);
dims = dims + imgs;
img = img.reshape(dims)
#img = img.transpose([1,2,0]);
tp = [2,1,0];
tp = tp + [i for i in range(3, len(dims))];
img = img.transpose(tp);
return io.dataToRange(img, x = x, y = y, z = z);
def readData(filename, x=all, y=all, z=all):
"""Read data from raw/mhd image
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
array: image data
"""
imr = vtk.vtkMetaImageReader()
imr.SetFileName(filename)
imr.Update()
im = imr.GetOutput()
dims = im.GetDimensions()
print dims
sc = im.GetPointData().GetScalars()
img = vtk_to_numpy(sc)
#print img.shape
dims = list(dims)
dims[0:3] = [dims[2], dims[1], dims[0]]
imgs = list(img.shape)
if len(imgs) > 1:
imgs.pop(0)
dims = dims + imgs
img = img.reshape(dims)
#img = img.transpose([1,2,0]);
tp = [2, 1, 0]
tp = tp + [i for i in range(3, len(dims))]
img = img.transpose(tp)
return io.dataToRange(img, x=x, y=y, z=z)
def writeData(filename, data, options={}, separateHeader=False, x = all, y = all, z = all):
"""Write data to nrrd file
Arguments:
filename (str): file name as regular expression
data (array): image data
options (dict): options dictionary
separateHeader (bool): write a separate header file
Returns:
str: nrrd output file name
To sample data use `options['spacings'] = [s1, s2, s3]` for
3d data with sampling deltas `s1`, `s2`, and `s3` in each dimension.
"""
data = io.dataToRange(data, x = x, y = y, z = z);
# Infer a number of fields from the ndarray and ignore values
# in the options dictionary.
options['type'] = _TYPEMAP_NUMPY2NRRD[data.dtype.str[1:]]
if data.dtype.itemsize > 1:
options['endian'] = _NUMPY2NRRD_ENDIAN_MAP[data.dtype.str[:1]]
# if 'space' is specified 'space dimension' can not. See http://teem.sourceforge.net/nrrd/format.html#space
if 'space' in options.keys() and 'space dimension' in options.keys():
del options['space dimension']
options['dimension'] = data.ndim
dsize = list(data.shape);
#dsize[0:2] = [dsize[1], dsize[0]];
options['sizes'] = dsize;
# The default encoding is 'gzip'
if 'encoding' not in options:
options['encoding'] = 'gzip'
# A bit of magic in handling options here.
# If *.nhdr filename provided, this overrides `separate_header=False`
# If *.nrrd filename provided AND separate_header=True, separate files
# written.
# For all other cases, header & data written to same file.
if filename[-5:] == '.nhdr':
separate_header = True
if 'data file' not in options:
datafilename = filename[:-4] + str('raw')
if options['encoding'] == 'gzip':
datafilename += '.gz'
options['data file'] = datafilename
else:
datafilename = options['data file']
elif filename[-5:] == '.nrrd' and separate_header:
separate_header = True
datafilename = filename
filename = filename[:-4] + str('nhdr')
else:
# Write header & data as one file
datafilename = filename;
separate_header = False;
with open(filename,'wb') as filehandle:
filehandle.write(b'NRRD0005\n')
filehandle.write(b'# This NRRD file was generated by pynrrd\n')
filehandle.write(b'# on ' +
datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S').encode('ascii') +
b'(GMT).\n')
filehandle.write(b'# Complete NRRD file format specification at:\n');
filehandle.write(b'# http://teem.sourceforge.net/nrrd/format.html\n');
# Write the fields in order, this ignores fields not in _NRRD_FIELD_ORDER
for field in _NRRD_FIELD_ORDER:
if field in options:
outline = (field + ': ' +
_NRRD_FIELD_FORMATTERS[field](options[field]) +
'\n').encode('ascii')
filehandle.write(outline)
d = options.get('keyvaluepairs', {})
for (k,v) in sorted(d.items(), key=lambda t: t[0]):
outline = (str(k) + ':=' + str(v) + '\n').encode('ascii')
filehandle.write(outline)
# Write the closing extra newline
filehandle.write(b'\n')
# If a single file desired, write data
if not separate_header:
_write_data(data, filehandle, options)
# If separate header desired, write data to different file
if separate_header:
with open(datafilename, 'wb') as datafilehandle:
_write_data(data, datafilehandle, options)
return filename;
def writeData(filename,
data,
options={},
separateHeader=False,
x=all,
y=all,
z=all):
"""Write data to nrrd file
Arguments:
filename (str): file name as regular expression
data (array): image data
options (dict): options dictionary
separateHeader (bool): write a separate header file
Returns:
str: nrrd output file name
To sample data use `options['spacings'] = [s1, s2, s3]` for
3d data with sampling deltas `s1`, `s2`, and `s3` in each dimension.
"""
data = io.dataToRange(data, x=x, y=y, z=z)
# Infer a number of fields from the ndarray and ignore values
# in the options dictionary.
options['type'] = _TYPEMAP_NUMPY2NRRD[data.dtype.str[1:]]
if data.dtype.itemsize > 1:
options['endian'] = _NUMPY2NRRD_ENDIAN_MAP[data.dtype.str[:1]]
# if 'space' is specified 'space dimension' can not. See http://teem.sourceforge.net/nrrd/format.html#space
if 'space' in options.keys() and 'space dimension' in options.keys():
del options['space dimension']
options['dimension'] = data.ndim
dsize = list(data.shape)
#dsize[0:2] = [dsize[1], dsize[0]];
options['sizes'] = dsize
# The default encoding is 'gzip'
if 'encoding' not in options:
options['encoding'] = 'gzip'
# A bit of magic in handling options here.
# If *.nhdr filename provided, this overrides `separate_header=False`
# If *.nrrd filename provided AND separate_header=True, separate files
# written.
# For all other cases, header & data written to same file.
if filename[-5:] == '.nhdr':
separate_header = True
if 'data file' not in options:
datafilename = filename[:-4] + str('raw')
if options['encoding'] == 'gzip':
datafilename += '.gz'
options['data file'] = datafilename
else:
datafilename = options['data file']
elif filename[-5:] == '.nrrd' and separate_header:
separate_header = True
datafilename = filename
filename = filename[:-4] + str('nhdr')
else:
# Write header & data as one file
datafilename = filename
separate_header = False
with open(filename, 'wb') as filehandle:
filehandle.write(b'NRRD0005\n')
filehandle.write(b'# This NRRD file was generated by pynrrd\n')
filehandle.write(
b'# on ' +
datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S').encode('ascii') +
b'(GMT).\n')
filehandle.write(b'# Complete NRRD file format specification at:\n')
filehandle.write(b'# http://teem.sourceforge.net/nrrd/format.html\n')
# Write the fields in order, this ignores fields not in _NRRD_FIELD_ORDER
for field in _NRRD_FIELD_ORDER:
if field in options:
outline = (field + ': ' +
_NRRD_FIELD_FORMATTERS[field](options[field]) +
'\n').encode('ascii')
filehandle.write(outline)
d = options.get('keyvaluepairs', {})
for (k, v) in sorted(d.items(), key=lambda t: t[0]):
outline = (str(k) + ':=' + str(v) + '\n').encode('ascii')
filehandle.write(outline)
# Write the closing extra newline
filehandle.write(b'\n')
# If a single file desired, write data
if not separate_header:
_write_data(data, filehandle, options)
# If separate header desired, write data to different file
if separate_header:
with open(datafilename, 'wb') as datafilehandle:
_write_data(data, datafilehandle, options)
return filename
