def detectorbase_start(self):
from iotbx.detectors.noir import NoirImage
self.detectorbase = NoirImage(self._image_file)
self.detectorbase.open_file = self.open_file
self.detectorbase.readHeader()
class FormatSMVNOIR(FormatSMVRigaku):
'''A class for reading SMV format ALS 4.2.2 NOIR images, and correctly
constructing a model for the experiment from this.'''
@staticmethod
def understand(image_file):
'''Check to see if this looks like a ALS 4.2.2 NOIR SMV format image,
i.e. we can make sense of it. Essentially that will be if it contains
all of the keys we are looking for.'''
size, header = FormatSMVRigaku.get_smv_header(image_file)
wanted_header_items = [
'DETECTOR_NUMBER',
'DETECTOR_NAMES',
'CRYSTAL_GONIO_NUM_VALUES',
'CRYSTAL_GONIO_NAMES',
'CRYSTAL_GONIO_UNITS',
'CRYSTAL_GONIO_VALUES',
'NOIR1_CREATED',
'ROTATION',
'ROTATION_AXIS_NAME',
'ROTATION_VECTOR',
'SOURCE_VECTORS',
'SOURCE_WAVELENGTH',
'SOURCE_POLARZ',
'DIM',
'SIZE1',
'SIZE2',
]
for header_item in wanted_header_items:
if not header_item in header:
return False
detector_prefix = header['DETECTOR_NAMES'].split()[0].strip()
more_wanted_header_items = [
'DETECTOR_DIMENSIONS', 'DETECTOR_SIZE', 'DETECTOR_VECTORS',
'GONIO_NAMES', 'GONIO_UNITS', 'GONIO_VALUES', 'GONIO_VECTORS',
'SPATIAL_BEAM_POSITION'
]
for header_item in more_wanted_header_items:
if not '%s%s' % (detector_prefix, header_item) in header:
return False
return True
def __init__(self, image_file, **kwargs):
'''Initialise the image structure from the given file, including a
proper model of the experiment. Easy from Rigaku Saturn images as
they contain everything pretty much we need...'''
from dxtbx import IncorrectFormatError
if not self.understand(image_file):
raise IncorrectFormatError(self, image_file)
FormatSMVRigaku.__init__(self, image_file, **kwargs)
self.detector_class = 'NOIR1'
self.detector = 'adsc'
def _start(self):
FormatSMVRigaku._start(self)
def detectorbase_start(self):
from iotbx.detectors.noir import NoirImage
self.detectorbase = NoirImage(self._image_file)
self.detectorbase.open_file = self.open_file
self.detectorbase.readHeader()
def _goniometer(self):
'''Initialize the structure for the goniometer - this will need to
correctly compose the axes given in the image header. In this case
this is made rather straightforward as the image header has the
calculated rotation axis stored in it. We could work from the
rest of the header and construct a goniometer model.'''
axis = tuple(
map(float, self._header_dictionary['ROTATION_VECTOR'].split()))
return self._goniometer_factory.known_axis(axis)
def _detector(self):
'''Return a model for the detector, allowing for two-theta offsets
and the detector position. This will be rather more complex...'''
detector_name = self._header_dictionary['DETECTOR_NAMES'].split(
)[0].strip()
detector_axes = map(
float, self._header_dictionary['%sDETECTOR_VECTORS' %
detector_name].split())
detector_fast = matrix.col(tuple(detector_axes[:3]))
detector_slow = matrix.col(tuple(detector_axes[3:]))
beam_pixels = map(
float, self._header_dictionary['%sSPATIAL_BEAM_POSITION' %
detector_name].split()[:2])
pixel_size = map(
float, self._header_dictionary['%sSPATIAL_DISTORTION_INFO' %
detector_name].split()[2:])
image_size = map(
int, self._header_dictionary['%sDETECTOR_DIMENSIONS' %
detector_name].split())
detector_origin = - (beam_pixels[0] * pixel_size[0] * detector_fast + \
beam_pixels[1] * pixel_size[1] * detector_slow)
gonio_axes = map(
float,
self._header_dictionary['%sGONIO_VECTORS' % detector_name].split())
gonio_values = map(
float,
self._header_dictionary['%sGONIO_VALUES' % detector_name].split())
gonio_units = self._header_dictionary['%sGONIO_UNITS' %
detector_name].split()
gonio_num_axes = int(self._header_dictionary['%sGONIO_NUM_VALUES' %
detector_name])
rotations = []
translations = []
for j, unit in enumerate(gonio_units):
axis = matrix.col(gonio_axes[3 * j:3 * (j + 1)])
if unit == 'deg':
rotations.append(
axis.axis_and_angle_as_r3_rotation_matrix(gonio_values[j],
deg=True))
translations.append(matrix.col((0.0, 0.0, 0.0)))
elif unit == 'mm':
rotations.append(
matrix.sqr((1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0)))
translations.append(gonio_values[j] * axis)
else:
raise RuntimeError('unknown axis unit %s' % unit)
rotations.reverse()
translations.reverse()
for j in range(gonio_num_axes):
detector_fast = rotations[j] * detector_fast
detector_slow = rotations[j] * detector_slow
detector_origin = rotations[j] * detector_origin
detector_origin = translations[j] + detector_origin
overload = int(float(self._header_dictionary['SATURATED_VALUE']))
underload = 0
return self._detector_factory.complex('CCD', detector_origin.elems,
detector_fast.elems,
detector_slow.elems, pixel_size,
image_size,
(underload, overload))
def _beam(self):
'''Return a simple model for the beam.'''
beam_direction = map(
float, self._header_dictionary['SOURCE_VECTORS'].split()[:3])
polarization = map(float,
self._header_dictionary['SOURCE_POLARZ'].split())
p_fraction = polarization[0]
p_plane = polarization[1:]
wavelength = float(
self._header_dictionary['SOURCE_WAVELENGTH'].split()[-1])
return self._beam_factory.complex(beam_direction, p_fraction, p_plane,
wavelength)
def _scan(self):
'''Return the scan information for this image.'''
rotation = map(float, self._header_dictionary['ROTATION'].split())
format = self._scan_factory.format('SMV')
epoch = time.mktime(
time.strptime(self._header_dictionary['NOIR1_CREATED'],
'%m/%d/%y %H:%M:%S'))
exposure_time = rotation[3]
osc_start = rotation[0]
osc_range = rotation[2]
return self._scan_factory.single(self._image_file, format,
exposure_time, osc_start, osc_range,
epoch)
def get_raw_data(self):
'''Get the pixel intensities (i.e. read the image and return as a
flex array of integers.)'''
from boost.python import streambuf
from dxtbx import read_uint16, read_uint16_bs, is_big_endian
from scitbx.array_family import flex
assert (len(self.get_detector()) == 1)
panel = self.get_detector()[0]
size = panel.get_image_size()
f = FormatSMVNOIR.open_file(self._image_file, 'rb')
f.read(self._header_size)
if self._header_dictionary['BYTE_ORDER'] == 'big_endian':
big_endian = True
else:
big_endian = False
if big_endian == is_big_endian():
raw_data = read_uint16(streambuf(f), int(size[0] * size[1]))
else:
raw_data = read_uint16_bs(streambuf(f), int(size[0] * size[1]))
image_size = panel.get_image_size()
raw_data.reshape(flex.grid(image_size[1], image_size[0]))
return raw_data
class FormatSMVNOIR(FormatSMVRigaku):
"""A class for reading SMV format ALS 4.2.2 NOIR images, and correctly
constructing a model for the experiment from this."""
@staticmethod
def understand(image_file):
"""Check to see if this looks like a ALS 4.2.2 NOIR SMV format image,
i.e. we can make sense of it. Essentially that will be if it contains
all of the keys we are looking for."""
size, header = FormatSMVRigaku.get_smv_header(image_file)
wanted_header_items = [
"DETECTOR_NUMBER",
"DETECTOR_NAMES",
"CRYSTAL_GONIO_NUM_VALUES",
"CRYSTAL_GONIO_NAMES",
"CRYSTAL_GONIO_UNITS",
"CRYSTAL_GONIO_VALUES",
"NOIR1_CREATED",
"ROTATION",
"ROTATION_AXIS_NAME",
"ROTATION_VECTOR",
"SOURCE_VECTORS",
"SOURCE_WAVELENGTH",
"SOURCE_POLARZ",
"DIM",
"SIZE1",
"SIZE2",
]
if any(item not in header for item in wanted_header_items):
return False
detector_prefix = header["DETECTOR_NAMES"].split()[0].strip()
more_wanted_header_items = [
"DETECTOR_DIMENSIONS",
"DETECTOR_SIZE",
"DETECTOR_VECTORS",
"GONIO_NAMES",
"GONIO_UNITS",
"GONIO_VALUES",
"GONIO_VECTORS",
"SPATIAL_BEAM_POSITION",
]
if any("%s%s" % (detector_prefix, item) not in header
for item in more_wanted_header_items):
return False
return True
def __init__(self, image_file, **kwargs):
"""Initialise the image structure from the given file, including a
proper model of the experiment. Easy from Rigaku Saturn images as
they contain everything pretty much we need..."""
from dxtbx import IncorrectFormatError
if not self.understand(image_file):
raise IncorrectFormatError(self, image_file)
FormatSMVRigaku.__init__(self, image_file, **kwargs)
self.detector_class = "NOIR1"
self.detector = "adsc"
def detectorbase_start(self):
from iotbx.detectors.noir import NoirImage
self.detectorbase = NoirImage(self._image_file)
self.detectorbase.open_file = self.open_file
self.detectorbase.readHeader()
def _goniometer(self):
"""Initialize the structure for the goniometer - this will need to
correctly compose the axes given in the image header. In this case
this is made rather straightforward as the image header has the
calculated rotation axis stored in it. We could work from the
rest of the header and construct a goniometer model."""
axis = tuple(
map(float, self._header_dictionary["ROTATION_VECTOR"].split()))
return self._goniometer_factory.known_axis(axis)
def get_beam_pixels(self, detector_name):
return [
float(bp)
for bp in self._header_dictionary["%sSPATIAL_BEAM_POSITION" %
detector_name].split()[:2]
]
def _detector(self):
"""Return a model for the detector, allowing for two-theta offsets
and the detector position. This will be rather more complex..."""
detector_name = self._header_dictionary["DETECTOR_NAMES"].split(
)[0].strip()
detector_axes = self.get_detector_axes(detector_name)
detector_fast = matrix.col(tuple(detector_axes[:3]))
detector_slow = matrix.col(tuple(detector_axes[3:]))
beam_pixels = self.get_beam_pixels(detector_name)
pixel_size = self.get_pixel_size(detector_name)
image_size = self.get_image_size(detector_name)
detector_origin = -(beam_pixels[0] * pixel_size[0] * detector_fast +
beam_pixels[1] * pixel_size[1] * detector_slow)
gonio_axes = self.get_gonio_axes(detector_name)
gonio_values = self.get_gonio_values(detector_name)
gonio_units = self._header_dictionary["%sGONIO_UNITS" %
detector_name].split()
gonio_num_axes = int(self._header_dictionary["%sGONIO_NUM_VALUES" %
detector_name])
rotations = []
translations = []
for j, unit in enumerate(gonio_units):
axis = matrix.col(gonio_axes[3 * j:3 * (j + 1)])
if unit == "deg":
rotations.append(
axis.axis_and_angle_as_r3_rotation_matrix(gonio_values[j],
deg=True))
translations.append(matrix.col((0.0, 0.0, 0.0)))
elif unit == "mm":
rotations.append(
matrix.sqr((1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0)))
translations.append(gonio_values[j] * axis)
else:
raise RuntimeError("unknown axis unit %s" % unit)
rotations.reverse()
translations.reverse()
for j in range(gonio_num_axes):
detector_fast = rotations[j] * detector_fast
detector_slow = rotations[j] * detector_slow
detector_origin = rotations[j] * detector_origin
detector_origin = translations[j] + detector_origin
overload = int(float(self._header_dictionary["SATURATED_VALUE"]))
underload = 0
return self._detector_factory.complex(
"CCD",
detector_origin.elems,
detector_fast.elems,
detector_slow.elems,
pixel_size,
image_size,
(underload, overload),
)
def _beam(self):
"""Return a simple model for the beam."""
beam_direction = self.get_beam_direction()
p_fraction, p_plane = self.get_beam_polarization()
wavelength = float(
self._header_dictionary["SOURCE_WAVELENGTH"].split()[-1])
return self._beam_factory.complex(beam_direction, p_fraction, p_plane,
wavelength)
def _scan(self):
"""Return the scan information for this image."""
epoch = time.strptime(self._header_dictionary["NOIR1_CREATED"],
"%m/%d/%y %H:%M:%S")
return self._create_single_SVM_scan(epoch)
def get_raw_data(self):
"""Get the pixel intensities (i.e. read the image and return as a
flex array of integers.)"""
assert len(self.get_detector()) == 1
panel = self.get_detector()[0]
image_size = panel.get_image_size()
raw_data = self._get_endianic_raw_data(size=image_size)
return raw_data
def detectorbase_start(self): from iotbx.detectors.noir import NoirImage self.detectorbase = NoirImage(self._image_file) self.detectorbase.readHeader()
class FormatSMVNOIR(FormatSMVRigaku):
'''A class for reading SMV format ALS 4.2.2 NOIR images, and correctly
constructing a model for the experiment from this.'''
@staticmethod
def understand(image_file):
'''Check to see if this looks like a ALS 4.2.2 NOIR SMV format image,
i.e. we can make sense of it. Essentially that will be if it contains
all of the keys we are looking for.'''
size, header = FormatSMVRigaku.get_smv_header(image_file)
wanted_header_items = [
'DETECTOR_NUMBER', 'DETECTOR_NAMES',
'CRYSTAL_GONIO_NUM_VALUES', 'CRYSTAL_GONIO_NAMES',
'CRYSTAL_GONIO_UNITS', 'CRYSTAL_GONIO_VALUES',
'NOIR1_CREATED',
'ROTATION', 'ROTATION_AXIS_NAME', 'ROTATION_VECTOR',
'SOURCE_VECTORS', 'SOURCE_WAVELENGTH',
'SOURCE_POLARZ', 'DIM', 'SIZE1', 'SIZE2',
]
for header_item in wanted_header_items:
if not header_item in header:
return False
detector_prefix = header['DETECTOR_NAMES'].split()[0].strip()
more_wanted_header_items = [
'DETECTOR_DIMENSIONS', 'DETECTOR_SIZE', 'DETECTOR_VECTORS',
'GONIO_NAMES', 'GONIO_UNITS', 'GONIO_VALUES', 'GONIO_VECTORS',
'SPATIAL_BEAM_POSITION'
]
for header_item in more_wanted_header_items:
if not '%s%s' % (detector_prefix, header_item) in header:
return False
return True
def __init__(self, image_file):
'''Initialise the image structure from the given file, including a
proper model of the experiment. Easy from Rigaku Saturn images as
they contain everything pretty much we need...'''
assert(self.understand(image_file))
FormatSMVRigaku.__init__(self, image_file)
self.detector_class = 'NOIR1'
self.detector = 'adsc'
return
def _start(self):
FormatSMVRigaku._start(self)
def detectorbase_start(self):
from iotbx.detectors.noir import NoirImage
self.detectorbase = NoirImage(self._image_file)
self.detectorbase.readHeader()
def _goniometer(self):
'''Initialize the structure for the goniometer - this will need to
correctly compose the axes given in the image header. In this case
this is made rather straightforward as the image header has the
calculated rotation axis stored in it. We could work from the
rest of the header and construct a goniometer model.'''
axis = tuple(map(float, self._header_dictionary[
'ROTATION_VECTOR'].split()))
return self._goniometer_factory.known_axis(axis)
def _detector(self):
'''Return a model for the detector, allowing for two-theta offsets
and the detector position. This will be rather more complex...'''
detector_name = self._header_dictionary[
'DETECTOR_NAMES'].split()[0].strip()
detector_axes = map(float, self._header_dictionary[
'%sDETECTOR_VECTORS' % detector_name].split())
detector_fast = matrix.col(tuple(detector_axes[:3]))
detector_slow = matrix.col(tuple(detector_axes[3:]))
beam_pixels = map(float, self._header_dictionary[
'%sSPATIAL_BEAM_POSITION' % detector_name].split()[:2])
pixel_size = map(float, self._header_dictionary[
'%sSPATIAL_DISTORTION_INFO' % detector_name].split()[2:])
image_size = map(int, self._header_dictionary[
'%sDETECTOR_DIMENSIONS' % detector_name].split())
detector_origin = - (beam_pixels[0] * pixel_size[0] * detector_fast + \
beam_pixels[1] * pixel_size[1] * detector_slow)
gonio_axes = map(float, self._header_dictionary[
'%sGONIO_VECTORS' % detector_name].split())
gonio_values = map(float, self._header_dictionary[
'%sGONIO_VALUES' % detector_name].split())
gonio_units = self._header_dictionary[
'%sGONIO_UNITS' % detector_name].split()
gonio_num_axes = int(self._header_dictionary[
'%sGONIO_NUM_VALUES' % detector_name])
rotations = []
translations = []
for j, unit in enumerate(gonio_units):
axis = matrix.col(gonio_axes[3 * j:3 * (j + 1)])
if unit == 'deg':
rotations.append(axis.axis_and_angle_as_r3_rotation_matrix(
gonio_values[j], deg = True))
translations.append(matrix.col((0.0, 0.0, 0.0)))
elif unit == 'mm':
rotations.append(matrix.sqr((1.0, 0.0, 0.0,
0.0, 1.0, 0.0,
0.0, 0.0, 1.0)))
translations.append(gonio_values[j] * axis)
else:
raise RuntimeError, 'unknown axis unit %s' % unit
rotations.reverse()
translations.reverse()
for j in range(gonio_num_axes):
detector_fast = rotations[j] * detector_fast
detector_slow = rotations[j] * detector_slow
detector_origin = rotations[j] * detector_origin
detector_origin = translations[j] + detector_origin
overload = int(float(self._header_dictionary['SATURATED_VALUE']))
underload = 0
return self._detector_factory.complex(
'CCD', detector_origin.elems, detector_fast.elems,
detector_slow.elems, pixel_size, image_size, (underload, overload))
def _beam(self):
'''Return a simple model for the beam.'''
beam_direction = map(float, self._header_dictionary[
'SOURCE_VECTORS'].split()[:3])
polarization = map(float, self._header_dictionary[
'SOURCE_POLARZ'].split())
p_fraction = polarization[0]
p_plane = polarization[1:]
wavelength = float(
self._header_dictionary['SOURCE_WAVELENGTH'].split()[-1])
return self._beam_factory.complex(
beam_direction, p_fraction, p_plane, wavelength)
def _scan(self):
'''Return the scan information for this image.'''
rotation = map(float, self._header_dictionary['ROTATION'].split())
format = self._scan_factory.format('SMV')
epoch = time.mktime(time.strptime(self._header_dictionary[
'NOIR1_CREATED'], '%m/%d/%y %H:%M:%S'))
exposure_time = rotation[3]
osc_start = rotation[0]
osc_range = rotation[2]
return self._scan_factory.single(
self._image_file, format, exposure_time,
osc_start, osc_range, epoch)
def get_raw_data(self):
'''Get the pixel intensities (i.e. read the image and return as a
flex array of integers.)'''
from boost.python import streambuf
from dxtbx import read_uint16, read_uint16_bs, is_big_endian
from scitbx.array_family import flex
assert(len(self.get_detector()) == 1)
panel = self.get_detector()[0]
size = panel.get_image_size()
f = FormatSMVNOIR.open_file(self._image_file, 'rb')
f.read(self._header_size)
if self._header_dictionary['BYTE_ORDER'] == 'big_endian':
big_endian = True
else:
big_endian = False
if big_endian == is_big_endian():
raw_data = read_uint16(streambuf(f), int(size[0] * size[1]))
else:
raw_data = read_uint16_bs(streambuf(f), int(size[0] * size[1]))
image_size = panel.get_image_size()
raw_data.reshape(flex.grid(image_size[1], image_size[0]))
return raw_data
def detectorbase_start(self):
self.detectorbase = NoirImage(self._image_file)
self.detectorbase.open_file = self.open_file
self.detectorbase.readHeader()