"""An implementation of the TIFF image reader for Bruker images"""


import datetime
import struct
import sys
import time

from boost_adaptbx.boost.python import streambuf
from iotbx.detectors.mar import MARImage
from scitbx.array_family import flex

from dxtbx.ext import read_uint16
from dxtbx.format.FormatTIFF import FormatTIFF


class FormatTIFFBruker(FormatTIFF):
    """A class for reading TIFF format Bruker images, and correctly
    constructing a model for the experiment from this."""

    @staticmethod
    def understand(image_file):
        """Check to see if this looks like an Bruker TIFF format image,
        i.e. we can make sense of it. This simply checks that records which
        describe the size of the image match with the TIFF records which do
        the same."""

        width, height, depth, order, bytes = FormatTIFF.get_tiff_header(image_file)

        if width == height:
            return False

        assert len(bytes) == 4096

        if order == FormatTIFF.LITTLE_ENDIAN:
            endian = "<"
        else:
            endian = ">"

        _I = endian + "I"

        _width = struct.unpack(_I, bytes[1024 + 80 : 1024 + 84])[0]
        _height = struct.unpack(_I, bytes[1024 + 84 : 1024 + 88])[0]
        _depth = struct.unpack(_I, bytes[1024 + 88 : 1024 + 92])[0]

        if width != _width or height != _height or depth != _depth:
            return False

        nimages = struct.unpack(_I, bytes[1024 + 112 : 1024 + 116])[0]
        origin = struct.unpack(_I, bytes[1024 + 116 : 1024 + 120])[0]
        orientation = struct.unpack(_I, bytes[1024 + 120 : 1024 + 124])[0]
        view = struct.unpack(_I, bytes[1024 + 124 : 1024 + 128])[0]

        if nimages != 1 or origin != 0 or orientation != 0 or view != 0:
            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."""

        width, height, depth, order, bytes = FormatTIFF.get_tiff_header(image_file)

        # comment block - where the detector serial number may (or may not) be stored
        # comments = bytes[1024+1440:1024+1440+512]

        self._header_size = 4096

        if order == FormatTIFF.LITTLE_ENDIAN:
            self._I = "<I"
            self._i = "<i"
            self._ii = "<ii"
        else:
            self._I = ">I"
            self._i = ">i"
            self._ii = ">ii"

        super().__init__(image_file, **kwargs)

    def detectorbase_start(self):
        self.detectorbase = MARImage(self._image_file)
        self.detectorbase.readHeader()

    # FIXME have implemented none of those which follow...

    def _goniometer(self):
        """Return a model for goniometer corresponding to the values stored
        in the image header. In the first instance assume this is a single
        axis and raise exception otherwise."""

        starts, ends, offset, width = self._get_bruker_scan_angles()

        for j, starts_j in enumerate(starts):
            if j != offset:
                assert starts_j == ends[j]

        # these angles are != 0 and probably define the full goniometer i.e,
        # two-theta, omega, kappa, phi; work on interpreting...

        return self._goniometer_factory.single_axis()

    def _detector(self):
        """Return a model for a simple detector, which at the moment [NKS does not] insist
        that the offsets and rotations are all 0.0."""

        starts, ends, offset, width = self._get_bruker_scan_angles()
        # rotations = self._get_bruker_detector_rotations()

        # in here either (i) use rotations or (ii) assert that they are all small

        # NKS removed the assertion that two-theta offset is 0.0;
        # support the general case
        assert starts[0] == ends[0]
        two_theta = starts[0]

        # assert that the rotations are all 0.0

        distance = self._get_bruker_distance()
        beam_x, beam_y = self._get_bruker_beam_xy()
        pixel_size = self._get_bruker_pixel_size()
        image_size = self._tiff_width, self._tiff_height
        overload = struct.unpack(self._i, self._tiff_header_bytes[1128:1132])[0]
        underload = 0

        bias = int(round(self._get_bruker_bias()))
        underload -= bias
        overload -= bias

        beam = beam_x * pixel_size[0], beam_y * pixel_size[1]

        return self._detector_factory.two_theta(
            "CCD",
            distance,
            beam,
            "+x",
            "-y",
            "+x",
            two_theta,
            pixel_size,
            image_size,
            (underload, overload),
            [],
        )

    def _beam(self):
        """Return a simple model for the beam."""

        wavelength = (
            struct.unpack(self._i, self._tiff_header_bytes[1932:1936])[0] * 1.0e-5
        )

        return self._beam_factory.simple(wavelength)

    def _scan(self):
        """Return the scan information for this image."""

        exposure_time = self._get_bruker_times()[1]
        epoch = time.mktime(self._get_bruker_timestamp())

        starts, ends, offset, width = self._get_bruker_scan_angles()

        osc_start = starts[offset]
        osc_range = width

        return self._scan_factory.single_file(
            self._image_file, exposure_time, osc_start, osc_range, epoch
        )

    ####################################################################
    #                                                                  #
    # Helper methods to get all of the values out of the TIFF header   #
    # - separated out to assist with code clarity                      #
    #                                                                  #
    ####################################################################

    def _get_bruker_distance(self):
        """Look in the usual places for the detector distance, return this
        as a float in mm."""

        distance = struct.unpack(self._i, self._tiff_header_bytes[1664:1668])[0]

        if distance != 0:
            return distance * 0.001

        distance = struct.unpack(self._i, self._tiff_header_bytes[1720:1724])[0]

        if distance != 0:
            return distance * 0.001

        raise RuntimeError("cannot find distance in header")

    def _get_bruker_beam_xy(self):
        """Get the beam x, y positions which are defined in the standard
        to be in pixels. X and Y are not defined by the documentation, so
        taking as a given that these are horizontal and vertical. N.B.
        the documentation states that the horizontal direction is fast."""

        beam_x, beam_y = struct.unpack(self._ii, self._tiff_header_bytes[1668:1676])[:2]

        return beam_x * 0.001, beam_y * 0.001

    def _get_bruker_pixel_size(self):
        """Get the pixel sizes in mm."""

        pixel_x, pixel_y = struct.unpack(self._ii, self._tiff_header_bytes[1796:1804])[
            :2
        ]

        return pixel_x * 1.0e-6, pixel_y * 1.0e-6

    def _get_bruker_times(self):
        """Get the integration, exposure times in seconds."""

        integration, exposure = struct.unpack(
            self._ii, self._tiff_header_bytes[1676:1684]
        )[:2]

        return integration * 0.001, exposure * 0.001

    def _get_bruker_timestamp(self):
        """Get the image acquisition timestamp."""

        return datetime.datetime(1970, 1, 1, 1, 1, 1).timetuple()

        # timestamp = self._tiff_header_bytes[2368:2400]

        # if not timestamp.strip():
        #    return datetime.datetime(1970, 1, 1, 1, 1, 1).timetuple()

        # month = int(timestamp[:2])
        # day = int(timestamp[2:4])
        # hour = int(timestamp[4:6])
        # minute = int(timestamp[6:8])
        # year = int(timestamp[8:12])
        # second = int(timestamp[13:15])
        # return datetime.datetime(year, month, day, hour, minute, second).timetuple()

    def _get_bruker_scan_angles(self):
        """Get the scan angles for: twotheta, omega, chi, kappa, phi, delta,
        gamma. The exact definitions for these are somewhat poorly defined,
        though I presume that they will come from some kind of standard
        goniometer definition... Also returns the scan axis offset and
        the apparent oscillation width, as these are sometimes not properly
        recorded elsewhere."""

        if self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN:
            iiiiiii = "<iiiiiii"
        else:
            iiiiiii = ">iiiiiii"

        start_angles = struct.unpack(iiiiiii, self._tiff_header_bytes[1692:1720])[:7]

        end_angles = struct.unpack(iiiiiii, self._tiff_header_bytes[1724:1752])[:7]

        axis_offset = struct.unpack(self._i, self._tiff_header_bytes[1756:1760])[0]

        axis_range = struct.unpack(self._i, self._tiff_header_bytes[1760:1764])[0]

        starts_degrees = [s * 0.001 for s in start_angles]
        ends_degrees = [e * 0.001 for e in end_angles]

        return starts_degrees, ends_degrees, axis_offset, axis_range * 0.001

    def _get_bruker_detector_rotations(self):
        """Get the recorded rotx, roty, rotz of the detector - which in most
        cases will probably all be 0.0."""

        if self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN:
            iii = "<iii"
        else:
            iii = ">iii"

        rot_angles = struct.unpack(iii, self._tiff_header_bytes[1764:1776])[:3]

        rot_degrees = [r * 0.001 for r in rot_angles]

        return rot_degrees

    def _get_bruker_bias(self):
        """Get the image bias."""

        bias = struct.unpack(self._i, self._tiff_header_bytes[1804:1808])[0]

        return bias * 1.0e-3

    def get_raw_data(self):
        """Get the pixel intensities (i.e. read the image and return as a
        flex array of integers.)"""

        # currently have no non-little-endian machines...

        assert self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN

        bias = int(round(self._get_bruker_bias()))

        assert len(self.get_detector()) == 1
        size = self.get_detector()[0].get_image_size()
        f = FormatTIFF.open_file(self._image_file)
        f.read(self._header_size)
        raw_data = read_uint16(streambuf(f), int(size[0] * size[1])) - bias
        image_size = self.get_detector()[0].get_image_size()
        raw_data.reshape(flex.grid(image_size[1], image_size[0]))

        return raw_data


if __name__ == "__main__":
    for arg in sys.argv[1:]:
        print(FormatTIFFBruker.understand(arg))

"""An implementation of the TIFF image reader for Bruker images"""


import datetime
import struct
import sys
import time

from boost_adaptbx.boost.python import streambuf
from iotbx.detectors.mar import MARImage
from scitbx.array_family import flex

from dxtbx.ext import read_uint16
from dxtbx.format.FormatTIFF import FormatTIFF


class FormatTIFFBruker(FormatTIFF):
    """A class for reading TIFF format Bruker images, and correctly
    constructing a model for the experiment from this."""

    @staticmethod
    def understand(image_file):
        """Check to see if this looks like an Bruker TIFF format image,
        i.e. we can make sense of it. This simply checks that records which
        describe the size of the image match with the TIFF records which do
        the same."""

        width, height, depth, order, bytes = FormatTIFF.get_tiff_header(image_file)

        if width == height:
            return False

        assert len(bytes) == 4096

        if order == FormatTIFF.LITTLE_ENDIAN:
            endian = "<"
        else:
            endian = ">"

        _I = endian + "I"

        _width = struct.unpack(_I, bytes[1024 + 80 : 1024 + 84])[0]
        _height = struct.unpack(_I, bytes[1024 + 84 : 1024 + 88])[0]
        _depth = struct.unpack(_I, bytes[1024 + 88 : 1024 + 92])[0]

        if width != _width or height != _height or depth != _depth:
            return False

        nimages = struct.unpack(_I, bytes[1024 + 112 : 1024 + 116])[0]
        origin = struct.unpack(_I, bytes[1024 + 116 : 1024 + 120])[0]
        orientation = struct.unpack(_I, bytes[1024 + 120 : 1024 + 124])[0]
        view = struct.unpack(_I, bytes[1024 + 124 : 1024 + 128])[0]

        if nimages != 1 or origin != 0 or orientation != 0 or view != 0:
            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."""

        width, height, depth, order, bytes = FormatTIFF.get_tiff_header(image_file)

        # comment block - where the detector serial number may (or may not) be stored
        # comments = bytes[1024+1440:1024+1440+512]

        self._header_size = 4096

        if order == FormatTIFF.LITTLE_ENDIAN:
            self._I = "<I"
            self._i = "<i"
            self._ii = "<ii"
        else:
            self._I = ">I"
            self._i = ">i"
            self._ii = ">ii"

        super().__init__(image_file, **kwargs)

    def detectorbase_start(self):
        self.detectorbase = MARImage(self._image_file)
        self.detectorbase.readHeader()

    # FIXME have implemented none of those which follow...

    def _goniometer(self):
        """Return a model for goniometer corresponding to the values stored
        in the image header. In the first instance assume this is a single
        axis and raise exception otherwise."""

        starts, ends, offset, width = self._get_bruker_scan_angles()

        for j, starts_j in enumerate(starts):
            if j != offset:
                assert starts_j == ends[j]

        # these angles are != 0 and probably define the full goniometer i.e,
        # two-theta, omega, kappa, phi; work on interpreting...

        return self._goniometer_factory.single_axis()

    def _detector(self):
        """Return a model for a simple detector, which at the moment [NKS does not] insist
        that the offsets and rotations are all 0.0."""

        starts, ends, offset, width = self._get_bruker_scan_angles()
        # rotations = self._get_bruker_detector_rotations()

        # in here either (i) use rotations or (ii) assert that they are all small

        # NKS removed the assertion that two-theta offset is 0.0;
        # support the general case
        assert starts[0] == ends[0]
        two_theta = starts[0]

        # assert that the rotations are all 0.0

        distance = self._get_bruker_distance()
        beam_x, beam_y = self._get_bruker_beam_xy()
        pixel_size = self._get_bruker_pixel_size()
        image_size = self._tiff_width, self._tiff_height
        overload = struct.unpack(self._i, self._tiff_header_bytes[1128:1132])[0]
        underload = 0

        bias = int(round(self._get_bruker_bias()))
        underload -= bias
        overload -= bias

        beam = beam_x * pixel_size[0], beam_y * pixel_size[1]

        return self._detector_factory.two_theta(
            "CCD",
            distance,
            beam,
            "+x",
            "-y",
            "+x",
            two_theta,
            pixel_size,
            image_size,
            (underload, overload),
            [],
        )

    def _beam(self):
        """Return a simple model for the beam."""

        wavelength = (
            struct.unpack(self._i, self._tiff_header_bytes[1932:1936])[0] * 1.0e-5
        )

        return self._beam_factory.simple(wavelength)

    def _scan(self):
        """Return the scan information for this image."""

        exposure_time = self._get_bruker_times()[1]
        epoch = time.mktime(self._get_bruker_timestamp())

        starts, ends, offset, width = self._get_bruker_scan_angles()

        osc_start = starts[offset]
        osc_range = width

        return self._scan_factory.single_file(
            self._image_file, exposure_time, osc_start, osc_range, epoch
        )

    ####################################################################
    #                                                                  #
    # Helper methods to get all of the values out of the TIFF header   #
    # - separated out to assist with code clarity                      #
    #                                                                  #
    ####################################################################

    def _get_bruker_distance(self):
        """Look in the usual places for the detector distance, return this
        as a float in mm."""

        distance = struct.unpack(self._i, self._tiff_header_bytes[1664:1668])[0]

        if distance != 0:
            return distance * 0.001

        distance = struct.unpack(self._i, self._tiff_header_bytes[1720:1724])[0]

        if distance != 0:
            return distance * 0.001

        raise RuntimeError("cannot find distance in header")

    def _get_bruker_beam_xy(self):
        """Get the beam x, y positions which are defined in the standard
        to be in pixels. X and Y are not defined by the documentation, so
        taking as a given that these are horizontal and vertical. N.B.
        the documentation states that the horizontal direction is fast."""

        beam_x, beam_y = struct.unpack(self._ii, self._tiff_header_bytes[1668:1676])[:2]

        return beam_x * 0.001, beam_y * 0.001

    def _get_bruker_pixel_size(self):
        """Get the pixel sizes in mm."""

        pixel_x, pixel_y = struct.unpack(self._ii, self._tiff_header_bytes[1796:1804])[
            :2
        ]

        return pixel_x * 1.0e-6, pixel_y * 1.0e-6

    def _get_bruker_times(self):
        """Get the integration, exposure times in seconds."""

        integration, exposure = struct.unpack(
            self._ii, self._tiff_header_bytes[1676:1684]
        )[:2]

        return integration * 0.001, exposure * 0.001

    def _get_bruker_timestamp(self):
        """Get the image acquisition timestamp."""

        return datetime.datetime(1970, 1, 1, 1, 1, 1).timetuple()

        # timestamp = self._tiff_header_bytes[2368:2400]

        # if not timestamp.strip():
        #    return datetime.datetime(1970, 1, 1, 1, 1, 1).timetuple()

        # month = int(timestamp[:2])
        # day = int(timestamp[2:4])
        # hour = int(timestamp[4:6])
        # minute = int(timestamp[6:8])
        # year = int(timestamp[8:12])
        # second = int(timestamp[13:15])
        # return datetime.datetime(year, month, day, hour, minute, second).timetuple()

    def _get_bruker_scan_angles(self):
        """Get the scan angles for: twotheta, omega, chi, kappa, phi, delta,
        gamma. The exact definitions for these are somewhat poorly defined,
        though I presume that they will come from some kind of standard
        goniometer definition... Also returns the scan axis offset and
        the apparent oscillation width, as these are sometimes not properly
        recorded elsewhere."""

        if self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN:
            iiiiiii = "<iiiiiii"
        else:
            iiiiiii = ">iiiiiii"

        start_angles = struct.unpack(iiiiiii, self._tiff_header_bytes[1692:1720])[:7]

        end_angles = struct.unpack(iiiiiii, self._tiff_header_bytes[1724:1752])[:7]

        axis_offset = struct.unpack(self._i, self._tiff_header_bytes[1756:1760])[0]

        axis_range = struct.unpack(self._i, self._tiff_header_bytes[1760:1764])[0]

        starts_degrees = [s * 0.001 for s in start_angles]
        ends_degrees = [e * 0.001 for e in end_angles]

        return starts_degrees, ends_degrees, axis_offset, axis_range * 0.001

    def _get_bruker_detector_rotations(self):
        """Get the recorded rotx, roty, rotz of the detector - which in most
        cases will probably all be 0.0."""

        if self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN:
            iii = "<iii"
        else:
            iii = ">iii"

        rot_angles = struct.unpack(iii, self._tiff_header_bytes[1764:1776])[:3]

        rot_degrees = [r * 0.001 for r in rot_angles]

        return rot_degrees

    def _get_bruker_bias(self):
        """Get the image bias."""

        bias = struct.unpack(self._i, self._tiff_header_bytes[1804:1808])[0]

        return bias * 1.0e-3

    def get_raw_data(self):
        """Get the pixel intensities (i.e. read the image and return as a
        flex array of integers.)"""

        # currently have no non-little-endian machines...

        assert self._tiff_byte_order == FormatTIFF.LITTLE_ENDIAN

        bias = int(round(self._get_bruker_bias()))

        assert len(self.get_detector()) == 1
        size = self.get_detector()[0].get_image_size()
        f = FormatTIFF.open_file(self._image_file)
        f.read(self._header_size)
        raw_data = read_uint16(streambuf(f), int(size[0] * size[1])) - bias
        image_size = self.get_detector()[0].get_image_size()
        raw_data.reshape(flex.grid(image_size[1], image_size[0]))

        return raw_data


if __name__ == "__main__":
    for arg in sys.argv[1:]:
        print(FormatTIFFBruker.understand(arg))

An implementation of the TIFF image reader for Bruker images A class for reading TIFF format Bruker images, and correctly     constructing a model for the experiment from this. Check to see if this looks like an Bruker TIFF format image,         i.e. we can make sense of it. This simply checks that records which         describe the size of the image match with the TIFF records which do         the same. Initialise the image structure from the given file, including a         proper model of the experiment. # comment block - where the detector serial number may (or may not) be stored # comments = bytes[1024+1440:1024+1440+512] # FIXME have implemented none of those which follow... Return a model for goniometer corresponding to the values stored         in the image header. In the first instance assume this is a single         axis and raise exception otherwise. # these angles are != 0 and probably define the full goniometer i.e, # two-theta, omega, kappa, phi; work on interpreting... Return a model for a simple detector, which at the moment [NKS does not] insist         that the offsets and rotations are all 0.0. # rotations = self._get_bruker_detector_rotations() # in here either (i) use rotations or (ii) assert that they are all small # NKS removed the assertion that two-theta offset is 0.0; # support the general case # assert that the rotations are all 0.0 Return a simple model for the beam. Return the scan information for this image. #################################################################### #                                                                  # # Helper methods to get all of the values out of the TIFF header   # # - separated out to assist with code clarity                      # #                                                                  # #################################################################### Look in the usual places for the detector distance, return this         as a float in mm. Get the beam x, y positions which are defined in the standard         to be in pixels. X and Y are not defined by the documentation, so         taking as a given that these are horizontal and vertical. N.B.         the documentation states that the horizontal direction is fast. Get the pixel sizes in mm. Get the integration, exposure times in seconds. Get the image acquisition timestamp. # timestamp = self._tiff_header_bytes[2368:2400] # if not timestamp.strip(): #    return datetime.datetime(1970, 1, 1, 1, 1, 1).timetuple() # month = int(timestamp[:2]) # day = int(timestamp[2:4]) # hour = int(timestamp[4:6]) # minute = int(timestamp[6:8]) # year = int(timestamp[8:12]) # second = int(timestamp[13:15]) # return datetime.datetime(year, month, day, hour, minute, second).timetuple() Get the scan angles for: twotheta, omega, chi, kappa, phi, delta,         gamma. The exact definitions for these are somewhat poorly defined,         though I presume that they will come from some kind of standard         goniometer definition... Also returns the scan axis offset and         the apparent oscillation width, as these are sometimes not properly         recorded elsewhere. Get the recorded rotx, roty, rotz of the detector - which in most         cases will probably all be 0.0. Get the image bias. Get the pixel intensities (i.e. read the image and return as a         flex array of integers.) # currently have no non-little-endian machines...