def dataSize(filename, **args):
"""Returns size of data in tif file
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
t = tiff.TiffFile(filename);
d3 = len(t.pages);
d2 = t.pages[0].shape;
#d2 = (d2[0], d2[1]);
if len(d2) == 3:
d2 = (d2[2], d2[1], d2[0]);
else:
d2 = (d2[1], d2[0]);
if d3 > 1:
dims = d2 + (d3,);
else:
dims = d2;
return io.dataSizeFromDataRange(dims, **args);
def dataSize(filename, **args):
"""Returns size of data in tif file
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
t = tiff.TiffFile(filename);
d3 = len(t.pages);
d2 = t.pages[0].shape;
#d2 = (d2[0], d2[1]);
if len(d2) == 3:
d2 = (d2[2], d2[1], d2[0]);
else:
d2 = (d2[1], d2[0]);
if d3 > 1:
dims = d2 + (d3,);
else:
dims = d2;
return io.dataSizeFromDataRange(dims, **args);
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 dataSize(filename, **args):
"""Read data size from nrrd image
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
header = readHeader(filename);
dims = header['sizes'];
#dims[0:2] = [dims[1], dims[0]];
return io.dataSizeFromDataRange(dims, **args);
def dataSize(filename, **args):
"""Read data size from nrrd image
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
header = readHeader(filename)
dims = header['sizes']
#dims[0:2] = [dims[1], dims[0]];
return io.dataSizeFromDataRange(dims, **args)
def dataSize(filename, **args):
"""Returns size of data stored as a file list
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
fp, fl = readFileList(filename)
nz = len(fl)
d2 = io.dataSize(os.path.join(fp, fl[0]))
if not len(d2) == 2:
raise RuntimeError("FileList: importing multiple files of dim %d not supported!" % len(d2))
dims = d2 + (nz,)
return io.dataSizeFromDataRange(dims, **args)
def dataSize(filename, resolution = 0, channel = 0, timepoint = 0, **args):
"""Read data size of the imaris image data set
Arguments:
filename (str): imaris file name
resolution (int): resolution level
channel (int): color channel
timepoint (int): time point
Returns:
tuple: image data size
"""
f = openFile(filename);
ds = readDataSet(f, resolution = resolution, channel = channel, timepoint = timepoint);
dims = list(ds.shape);
dims = (dims[2], dims[1], dims[0]);
return io.dataSizeFromDataRange(dims, **args);
def dataSize(filename, **args):
"""Read data size from raw/mhd image
Arguments:
filename (str): imaris file name
x,y,z (tuple or all): range specifications
Returns:
int: raw image data size
"""
imr = vtk.vtkMetaImageReader()
imr.SetFileName(filename);
imr.Update()
im = imr.GetOutput()
dims = im.GetDimensions();
#dims = list(dims);
#dims[0:2] = [dims[1], dims[0]];
#dims = tuple(dims);
return io.dataSizeFromDataRange(dims, **args);
def dataSize(filename, **args):
"""Read data size from raw/mhd image
Arguments:
filename (str): imaris file name
x,y,z (tuple or all): range specifications
Returns:
int: raw image data size
"""
imr = vtk.vtkMetaImageReader()
imr.SetFileName(filename)
imr.Update()
im = imr.GetOutput()
dims = im.GetDimensions()
#dims = list(dims);
#dims[0:2] = [dims[1], dims[0]];
#dims = tuple(dims);
return io.dataSizeFromDataRange(dims, **args)
def dataSize(filename, **args):
"""Returns size of data stored as a file list
Arguments:
filename (str): file name as regular expression
x,y,z (tuple): data range specifications
Returns:
tuple: data size
"""
fp, fl = readFileList(filename)
nz = len(fl)
d2 = io.dataSize(os.path.join(fp, fl[0]))
if not len(d2) == 2:
raise RuntimeError(
"FileList: importing multiple files of dim %d not supported!" %
len(d2))
dims = d2 + (nz, )
return io.dataSizeFromDataRange(dims, **args)
