#!/usr/bin/env python # FormatSMVNOIR.py # Copyright (C) 2011 Diamond Light Source, Graeme Winter # # This code is distributed under the BSD license, a copy of which is # included in the root directory of this package. # # An implementation of the SMV image reader for Rigaku Saturn images. # Inherits from FormatSMVRigaku. from __future__ import division import time from scitbx import matrix from dxtbx.format.FormatSMVRigaku import FormatSMVRigaku 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) 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) if __name__ == '__main__': import sys for arg in sys.argv[1:]: print FormatSMVNOIR.understand(arg)