def read_lsm(filename,channel=0):
"""Read an lsm image
:Parameters:
- `filename` (str) - name of the file to read
- `channel` (int) - optional
"""
# LSM reader
imageFile = lsmreader.Lsmimage(filename)
imageFile.open()
_info = {}
#LSM header
_VX = imageFile.header['CZ LSM info']['Voxel Size X']
_VY = imageFile.header['CZ LSM info']['Voxel Size Y']
_VZ = imageFile.header['CZ LSM info']['Voxel Size Z']
_vx = _VX * 10**6
_vy = _VY * 10**6
_vz = _VZ * 10**6
_PIXSIZE = imageFile.header['Image'][0]['Bit / Sample']
_info["TYPE"] = 'unsigned fixed'
_info["PIXSIZE"] = str(_PIXSIZE)
_info["SCALE"] = 2
_info["CPU"] = 'decm'
_info["#GEOMETRY"] = 'CARTESIAN'
#LSM datas
_data = imageFile.image['data'][channel]
im = SpatialImage(_data)
im.resolution = _vx,_vy,_vz
im.info = _info
return im
def read_tif(filename,channel=0):
"""Read a tif image
:Parameters:
- `filename` (str) - name of the file to read
"""
# TIF reader
tif = libtiff.TIFF.open(filename)
if tif.GetField('ImageDescription'):
tif = TIFFfile(filename)
arr = tif.get_tiff_array()
_data = arr[:].T
info_str = tif.get_info()
else:
i = 1
while not tif.LastDirectory():
i+=1
tif.ReadDirectory()
tif.SetDirectory(0)
_data = np.zeros((i,)+tif.read_image().shape,dtype=tif.read_image().dtype)
for ii,i in enumerate(tif.iter_images()):
_data[ii] = i
_data = _data.transpose(2, 1, 0)
info_str = tif.info()
nx, ny, nz = _data.shape
# -- prepare metadata dictionnary --
info_dict = dict( filter( lambda x: len(x)==2,
(inf.split(':') for inf in info_str.split("\n"))
) )
info_dict.update(dict( filter( lambda x: len(x)==2,(inf.split('=') for inf in info_str.split("\n"))) ))
for k,v in info_dict.iteritems():
info_dict[k] = v.strip()
info_dict.update({'Filename':filename.split('/')[-1]})
print info_dict
# -- getting the voxelsizes from the tiff image: sometimes
# there is a BoundingBox attribute, sometimes there are
# XResolution, YResolution, ZResolution or spacing.
# the object returned by get_tiff_array has a "get_voxel_sizes()"
# method but it fails, so here we go. --
if "BoundingBox" in info_dict:
bbox = info_dict["BoundingBox"]
xm, xM, ym, yM, zm, zM = map(float,bbox.split())
_vx = (xM-xm)/nx
_vy = (yM-ym)/ny
_vz = (zM-zm)/nz
else:
# -- When we have [XYZ]Resolution fields, it describes the
# number of voxels per real unit. In SpatialImage we want the
# voxelsizes, which is the number of real units per voxels.
# So we must invert the result. --
if "XResolution" in info_dict:
# --resolution is stored in a [(values, precision)] list-of-one-tuple, or
# sometimes as a single number --
xres_str = eval(info_dict["XResolution"])
if isinstance(xres_str, list) and isinstance(xres_str[0], tuple):
xres_str = xres_str[0]
_vx = float(xres_str[0])/xres_str[1]
elif isinstance(xres_str, (int, float)):
_vx = float(xres_str)
else:
_vx = 1.
_vx = 1./_vx if _vx != 0 else 1.
else:
_vx = 1.0 # dumb fallback, maybe we will find something smarter later on
if "YResolution" in info_dict:
# --resolution is stored in a [(values, precision)] list-of-one-tuple, or
# sometimes as a single number --
yres_str = eval(info_dict["YResolution"])
if isinstance(yres_str, list) and isinstance(yres_str[0], tuple):
yres_str = yres_str[0]
_vy = float(yres_str[0])/yres_str[1]
elif isinstance(yres_str, (int, float)):
_vy = float(yres_str)
else:
_vy = 1.
_vy = 1./_vy if _vy != 0 else 1.
else:
_vy = 1.0 # dumb fallback, maybe we will find something smarter later on
if "ZResolution" in info_dict:
# --resolution is stored in a [(values, precision)] list-of-one-tuple, or
# sometimes as a single number --
zres_str = eval(info_dict["ZResolution"])
if isinstance(zres_str, list) and isinstance(zres_str[0], tuple):
zres_str = zres_str[0]
_vz = float(zres_str[0])/zres_str[1]
elif isinstance(zres_str, (int, float)):
_vz = float(zres_str)
else:
_vz = 1.
_vz = 1./_vz if _vz != 0 else 1.
else:
if "spacing" in info_dict:
_vz = eval(info_dict["spacing"])
else:
_vz = 1.0 # dumb fallback, maybe we will find something smarter later on
tif.close()
# -- dtypes are not really stored in a compatible way (">u2" instead of uint16)
# but we can convert those --
dt = np.dtype(_data.dtype.name)
# -- Return a SpatialImage please! --
im = SpatialImage(_data, dtype=dt)
im.resolution = _vx,_vy,_vz
im.info = info_dict
return im
