예제 #1
0
class PnccdDetector(DetectorBase):
    """
    Class for lcls detectors.
    """
    def __init__(self, geom, beam, run_num=0):
        """
        Initialize a pnccd detector.

        :param geom: The path to the geometry .data file.
        :param beam: The beam object.
        :param run_num: The run_num containing the background, rms and gain and the other pixel
        pixel properties.
        """
        super(PnccdDetector, self).__init__()

        # Parse the path to extract the necessary information to use psana modules
        parsed_path = geom.split('/')
        # Notify the user that the path should be as deep as the geometry profile
        if parsed_path[-2] != "geometry":
            # print parsed_path[-1]
            raise Exception(
                " Sorry, at present, the package is not very smart. Please specify "
                +
                "the path of the detector as deep as the geometry profile. \n "
                + "And example would be like:" +
                "/reg/d/psdm/amo/experiment_name/calib/group/source/geometry/0-end.data \n"
                +
                "where the '/calib/group/source/geometry/0-end.data' part is essential. \n"
                +
                "The address before that part is not essential and can be replaced with"
                + " your absolute address or relative address.\n"
                "The experiment_name is also essential in Python 3.")

        self.initialize(geom=geom, run_num=run_num)

        # Initialize the pixel effects
        self.initialize_pixels_with_beam(beam=beam)

    def initialize(self, geom, run_num=0):
        """
        Initialize the detector as pnccd
        :param geom: The pnccd .data file which characterize the geometry profile.
        :param run_num: The run_num containing the background, rms and gain and the other
                        pixel pixel properties.
        :return:  None
        """

        # Redirect the output stream
        old_stdout = sys.stdout
        f = six.StringIO()
        # f = open('Detector_initialization.log', 'w')
        sys.stdout = f

        ###########################################################################################
        # Initialize the geometry configuration
        ############################################################################################
        self.geometry = GeometryAccess(geom, 0o377)
        self.run_num = run_num

        # Set coordinate in real space
        temp = self.geometry.get_pixel_coords()
        temp_index = self.geometry.get_pixel_coord_indexes()

        self.panel_num = temp[0].shape[1] * temp[0].shape[2]
        self.distance = temp[2][0, 0, 0, 0, 0] * 1e-6  # Convert to m

        self.pixel_position = np.zeros(
            (self.panel_num, temp[0].shape[3], temp[0].shape[4], 3))
        self.pixel_index_map = np.zeros(
            (self.panel_num, temp[0].shape[3], temp[0].shape[4], 2))

        for l in range(temp[0].shape[1]):
            for m in range(temp[0].shape[2]):
                for n in range(3):
                    self.pixel_position[m + l * temp[0].shape[2], :, :,
                                        n] = temp[n][0, l, m]
                for n in range(2):
                    self.pixel_index_map[m + l * temp[0].shape[2], :, :,
                                         n] = temp_index[n][0, l, m]

        self.pixel_index_map = self.pixel_index_map.astype(np.int64)

        # Get the range of the pixel index
        self.detector_pixel_num_x = np.max(self.pixel_index_map[:, :, :,
                                                                0]) + 1
        self.detector_pixel_num_y = np.max(self.pixel_index_map[:, :, :,
                                                                1]) + 1

        self.panel_pixel_num_x = np.array([
            self.pixel_index_map.shape[1],
        ] * self.panel_num)
        self.panel_pixel_num_y = np.array([
            self.pixel_index_map.shape[2],
        ] * self.panel_num)
        self.pixel_num_total = np.sum(
            np.multiply(self.panel_pixel_num_x, self.panel_pixel_num_y))

        tmp = float(self.geometry.get_pixel_scale_size() *
                    1e-6)  # Convert to m
        self.pixel_width = np.ones((self.panel_num, self.panel_pixel_num_x[0],
                                    self.panel_pixel_num_y[0])) * tmp
        self.pixel_height = np.ones((self.panel_num, self.panel_pixel_num_x[0],
                                     self.panel_pixel_num_y[0])) * tmp

        # Calculate the pixel area
        self.pixel_area = np.multiply(self.pixel_height, self.pixel_width)

        ###########################################################################################
        # Initialize the pixel effects
        ###########################################################################################
        # first we should parse the path
        parsed_path = geom.split('/')
        source = parsed_path[-3]

        if six.PY2:
            cbase = CalibParsBasePnccdV1()
            calibdir = '/'.join(parsed_path[:-4])
            group = parsed_path[-4]
            pbits = 255
            gcp = GenericCalibPars(cbase, calibdir, group, source, run_num,
                                   pbits)

            self._pedestals = gcp.pedestals()
            self._pixel_rms = gcp.pixel_rms()
            self._pixel_mask = gcp.pixel_mask()
            self._pixel_bkgd = gcp.pixel_bkgd()
            self._pixel_status = gcp.pixel_status()
            self._pixel_gain = gcp.pixel_gain()
        else:
            self.det = "pnccd_000" + source[-1]
            self.exp = parsed_path[-5]

            self._pedestals = None
            self._pixel_rms = None
            self._pixel_mask = None
            self._pixel_bkgd = None
            self._pixel_status = None
            self._pixel_gain = None

        # Redirect the output stream
        sys.stdout = old_stdout
        # f.close()
        # os.remove('./Detector_initialization.log')

    @property
    def pedestals(self):
        if six.PY3 and not self._pedestals:
            self._pedestals = calib_constants(self.det,
                                              exp=self.exp,
                                              ctype="pedestals",
                                              run=self.run_num)[0]
        return self._pedestals

    @property
    def pixel_rms(self):
        if six.PY3 and not self._pixel_rms:
            self._pixel_rms = calib_constants(self.det,
                                              exp=self.exp,
                                              ctype="pixel_rms",
                                              run=self.run_num)[0]
        return self._pixel_rms

    @property
    def pixel_mask(self):
        if six.PY3 and not self._pixel_mask:
            self._pixel_mask = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype="pixel_mask",
                                               run=self.run_num)[0]
        return self._pixel_mask

    @property
    def pixel_bkgd(self):
        if six.PY3 and not self._pixel_bkgd:
            self._pixel_bkgd = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype="pixel_bkgd",
                                               run=self.run_num)[0]
        return self._pixel_bkgd

    @property
    def pixel_status(self):
        if six.PY3 and not self._pixel_status:
            self._pixel_status = calib_constants(self.det,
                                                 exp=self.exp,
                                                 ctype="pixel_status",
                                                 run=self.run_num)[0]
        return self._pixel_status

    @property
    def pixel_gain(self):
        if six.PY3 and not self._pixel_gain:
            self._pixel_gain = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype="pixel_gain",
                                               run=self.run_num)[0]
        return self._pixel_gain

    def assemble_image_stack(self, image_stack):
        """
        Assemble the image stack into a 2D diffraction pattern.
        For this specific object, since it only has one panel, the result is to remove the
        first dimension.

        :param image_stack: The [1, num_x, num_y] numpy array.
        :return: The [num_x, num_y] numpy array.
        """
        # construct the image holder:
        image = np.zeros(
            (self.detector_pixel_num_x, self.detector_pixel_num_y))
        for l in range(self.panel_num):
            image[self.pixel_index_map[l, :, :, 0],
                  self.pixel_index_map[l, :, :, 1]] = image_stack[l, :, :]

        return image

    def assemble_image_stack_batch(self, image_stack_batch):
        """
        Assemble the image stack batch into a stack of 2D diffraction patterns.
        For this specific object, since it has only one panel, the result is a simple reshape.

        :param image_stack_batch: The [stack_num, 1, num_x, num_y] numpy array
        :return: The [stack_num, num_x, num_y] numpy array
        """
        stack_num = image_stack_batch.shape[0]

        # construct the image holder:
        image = np.zeros(
            (stack_num, self.detector_pixel_num_x, self.detector_pixel_num_y))
        for l in range(self.panel_num):
            idx_map_1 = self.pixel_index_map[l, :, :, 0]
            idx_map_2 = self.pixel_index_map[l, :, :, 1]
            image[:, idx_map_1, idx_map_2] = image_stack_batch[:, l]

        return image
예제 #2
0
파일: lcls.py 프로젝트: rdeeban/pysingfel
class LCLSDetector(DetectorBase):
    """
    Class for lcls detectors.
    """

    def __init__(self, geom, beam=None, run_num=0):
        """
        Initialize a pnccd detector.

        :param geom: The path to the geometry .data file.
        :param beam: The beam object.
        :param run_num: The run_num containing the background, rms and gain and the other pixel
        pixel properties.
        """
        super(LCLSDetector, self).__init__()

        # Parse the path to extract the necessary information to use psana modules
        parsed_path = geom.split('/')
        # Notify the user that the path should be as deep as the geometry profile
        if parsed_path[-2] != "geometry":
            # print parsed_path[-1]
            raise Exception(
                " Sorry, at present, the package is not very smart. Please specify " +

                "the path of the detector as deep as the geometry profile. \n " +
                "And example would be like:" +
                "/reg/d/psdm/amo/experiment_name/calib/group/source/geometry/0-end.data \n" +
                "where the '/calib/group/source/geometry/0-end.data' part is essential. \n" +
                "The address before that part is not essential and can be replaced with" +
                " your absolute address or relative address.\n"
                "The experiment_name is also essential in Python 3.")

        self.initialize(geom=geom, run_num=run_num)
        # Initialize the pixel effects
        self.initialize_pixels_with_beam(beam=beam)

    def initialize(self, geom, run_num=0):
        """
        Initialize the detector as pnccd
        :param geom: The pnccd .data file which characterize the geometry profile.
        :param run_num: The run_num containing the background, rms and gain and the other
                        pixel pixel properties.
        :return:  None
        """
        # Redirect the output stream
        old_stdout = sys.stdout
        f = six.StringIO()
        # f = open('Detector_initialization.log', 'w')
        sys.stdout = f

        ###########################################################################################
        # Initialize the geometry configuration
        ############################################################################################
        self.geometry = GeometryAccess(geom, 0)
        self.run_num = run_num

        # Set coordinate in real space (convert to m)
        temp = [xp.asarray(t) * 1e-6 for t in self.geometry.get_pixel_coords()]
        temp_index = [xp.asarray(t)
                      for t in self.geometry.get_pixel_coord_indexes()]

        self.panel_num = np.prod(temp[0].shape[:-2])
        self._distance = float(temp[2].mean())

        self._shape = (self.panel_num, temp[0].shape[-2], temp[0].shape[-1])
        self.pixel_position = xp.zeros(self._shape + (3,))
        self.pixel_index_map = xp.zeros(self._shape + (2,))

        for n in range(3):
            self.pixel_position[..., n] = temp[n].reshape(self._shape)
        for n in range(2):
            self.pixel_index_map[..., n] = temp_index[n].reshape(self._shape)

        self.pixel_index_map = self.pixel_index_map.astype(xp.int64)

        # Get the range of the pixel index
        self.detector_pixel_num_x = asnumpy(
            xp.max(self.pixel_index_map[..., 0]) + 1)
        self.detector_pixel_num_y = asnumpy(
            xp.max(self.pixel_index_map[..., 1]) + 1)

        self.panel_pixel_num_x = np.array([self.pixel_index_map.shape[1], ] * self.panel_num)
        self.panel_pixel_num_y = np.array([self.pixel_index_map.shape[2], ] * self.panel_num)
        self.pixel_num_total = np.sum(np.multiply(self.panel_pixel_num_x, self.panel_pixel_num_y))

        tmp = float(self.geometry.get_pixel_scale_size() * 1e-6)  # Convert to m
        self.pixel_width = xp.ones(
            (self.panel_num, self.panel_pixel_num_x[0], self.panel_pixel_num_y[0])) * tmp
        self.pixel_height = xp.ones(
            (self.panel_num, self.panel_pixel_num_x[0], self.panel_pixel_num_y[0])) * tmp

        # Calculate the pixel area
        self.pixel_area = xp.multiply(self.pixel_height, self.pixel_width)

        ###########################################################################################
        # Initialize the pixel effects
        ###########################################################################################
        # first we should parse the path
        parsed_path = geom.split('/')
        group = parsed_path[-4]
        source = parsed_path[-3]

        self._pedestals = None
        self._pixel_rms = None
        self._pixel_mask = None
        self._pixel_bkgd = None
        self._pixel_status = None
        self._pixel_gain = None

        if six.PY2:
            try:
                cbase = self._get_cbase()
                calibdir = '/'.join(parsed_path[:-4])
                pbits = 255
                gcp = GenericCalibPars(cbase, calibdir, group, source, run_num, pbits)

                self._pedestals = gcp.pedestals()
                self._pixel_rms = gcp.pixel_rms()
                self._pixel_mask = gcp.pixel_mask()
                self._pixel_bkgd = gcp.pixel_bkgd()
                self._pixel_status = gcp.pixel_status()
                self._pixel_gain = gcp.pixel_gain()
            except NotImplementedError:
                # No GenericCalibPars information.
                pass
        else:
            try:
                self.det = self._get_det_id(source)
            except NotImplementedError:
                # No GenericCalibPars information.
                self.det = None
            self.exp = parsed_path[-5]

        # Redirect the output stream
        sys.stdout = old_stdout
        # f.close()
        # os.remove('./Detector_initialization.log')

    def _get_cbase(self):
        """Get detector calibration base object.

        Psana 1 only.
        """
        raise NotImplementedError()

    def _get_det_id(self, source):
        """Get detector ID form source.

        Psana 2 only.
        """
        raise NotImplementedError()

    def _get_calib_constants(self, name):
        _name = "_" + name
        attribute = getattr(self, _name)
        if six.PY3 and attribute is None and self.det is not None:
            # We haven't tried to get the calib_constant yet.
            attribute = calib_constants(
                self.det, exp=self.exp, ctype=name,
                run=self.run_num)[0]
        if attribute is None:
            # We still don't have it
            raise RuntimeError("No {} available for this detector"
                               "".format(name))
        setattr(self, _name, attribute)
        return attribute

    @property
    def pedestals(self):
        return self._get_calib_constants("pedestals")

    @property
    def pixel_rms(self):
        return self._get_calib_constants("pixel_rms")

    @property
    def pixel_mask(self):
        return self._get_calib_constants("pixel_mask")

    @property
    def pixel_bkgd(self):
        return self._get_calib_constants("pixel_bkgd")

    @property
    def pixel_status(self):
        return self._get_calib_constants("pixel_status")

    @property
    def pixel_gain(self):
        return self._get_calib_constants("pixel_gain")
예제 #3
0
파일: lcls.py 프로젝트: ExaFEL/pysingfel
class LCLSDetector(DetectorBase):
    """
    Class for LCLS detectors.
    """
    def __init__(self, geom, beam=None, run_num=0, cframe=0):
        """
        Initialize a LCLS detector.

        :param geom: The path to the geometry .data file.
        :param beam: The beam object.
        :param run_num: The run_num containing the background, rms and gain and the other pixel
        pixel properties.
        :param cframe: The desired coordinate frame, 0 for psana and 1 for lab conventions. The
        default (psana) matches the convention of non-LCLS detectors. Lab frame yields the transpose.
        """
        super(LCLSDetector, self).__init__()

        # Parse the path to extract the necessary information to use psana modules
        parsed_path = geom.split('/')
        # Notify the user that the path should be as deep as the geometry profile
        if parsed_path[-2] != "geometry":
            # print parsed_path[-1]
            raise Exception(
                " Sorry, at present, the package is not very smart. Please specify "
                +
                "the path of the detector as deep as the geometry profile. \n "
                + "And example would be like:" +
                "/reg/d/psdm/amo/experiment_name/calib/group/source/geometry/0-end.data \n"
                +
                "where the '/calib/group/source/geometry/0-end.data' part is essential. \n"
                +
                "The address before that part is not essential and can be replaced with"
                + " your absolute address or relative address.\n"
                "The experiment_name is also essential in Python 3.")

        self.initialize(geom=geom, run_num=run_num, cframe=cframe)
        # Initialize the pixel effects, enforcing detector distance to be positive
        if self.distance < 0:
            self.distance *= -1
        self.initialize_pixels_with_beam(beam=beam)

    def initialize(self, geom, run_num=0, cframe=0):
        """
        Initialize the detector
        :param geom: The *-end.data file which characterizes the geometry profile.
        :param run_num: The run_num containing the background, rms and gain and the other
                        pixel pixel properties.
        :param cframe: The desired coordinate frame, 0 for psana and 1 for lab conventions.
        :return:  None
        """
        # Redirect the output stream
        old_stdout = sys.stdout
        f = six.StringIO()
        # f = open('Detector_initialization.log', 'w')
        sys.stdout = f

        ###########################################################################################
        # Initialize the geometry configuration
        ############################################################################################
        self.geometry = GeometryAccess(geom, cframe=cframe)
        self.run_num = run_num

        # Set coordinate in real space (convert to m)
        temp = [
            xp.asarray(t) * 1e-6
            for t in self.geometry.get_pixel_coords(cframe=cframe)
        ]
        temp_index = [
            xp.asarray(t)
            for t in self.geometry.get_pixel_coord_indexes(cframe=cframe)
        ]

        self.panel_num = np.prod(temp[0].shape[:-2])
        self._distance = float(temp[2].mean())

        self._shape = (self.panel_num, temp[0].shape[-2], temp[0].shape[-1])
        self.pixel_position = xp.zeros(self._shape + (3, ))
        self.pixel_index_map = xp.zeros(self._shape + (2, ))

        for n in range(3):
            self.pixel_position[..., n] = temp[n].reshape(self._shape)
        for n in range(2):
            self.pixel_index_map[..., n] = temp_index[n].reshape(self._shape)

        self.pixel_index_map = self.pixel_index_map.astype(xp.int64)

        # Get the range of the pixel index
        self.detector_pixel_num_x = asnumpy(
            xp.max(self.pixel_index_map[..., 0]) + 1)
        self.detector_pixel_num_y = asnumpy(
            xp.max(self.pixel_index_map[..., 1]) + 1)

        self.panel_pixel_num_x = np.array([
            self.pixel_index_map.shape[1],
        ] * self.panel_num)
        self.panel_pixel_num_y = np.array([
            self.pixel_index_map.shape[2],
        ] * self.panel_num)
        self.pixel_num_total = np.sum(
            np.multiply(self.panel_pixel_num_x, self.panel_pixel_num_y))

        tmp = float(self.geometry.get_pixel_scale_size() *
                    1e-6)  # Convert to m
        self.pixel_width = xp.ones((self.panel_num, self.panel_pixel_num_x[0],
                                    self.panel_pixel_num_y[0])) * tmp
        self.pixel_height = xp.ones((self.panel_num, self.panel_pixel_num_x[0],
                                     self.panel_pixel_num_y[0])) * tmp

        # Calculate the pixel area
        self.pixel_area = xp.multiply(self.pixel_height, self.pixel_width)

        ###########################################################################################
        # Initialize the pixel effects
        ###########################################################################################
        # first we should parse the path
        parsed_path = geom.split('/')
        self.exp = parsed_path[-5]
        if self.exp == 'calib':
            self.exp = parsed_path[-6]
        self.group = parsed_path[-4]
        self.source = parsed_path[-3]

        self._pedestals = None
        self._pixel_rms = None
        self._pixel_mask = None
        self._pixel_bkgd = None
        self._pixel_status = None
        self._pixel_gain = None

        if six.PY2:
            try:
                cbase = self._get_cbase()
                self.calibdir = '/'.join(parsed_path[:-4])
                pbits = 255
                gcp = GenericCalibPars(cbase, self.calibdir, self.group,
                                       self.source, run_num, pbits)

                self._pedestals = gcp.pedestals()
                self._pixel_rms = gcp.pixel_rms()
                self._pixel_mask = gcp.pixel_mask()
                self._pixel_bkgd = gcp.pixel_bkgd()
                self._pixel_status = gcp.pixel_status()
                self._pixel_gain = gcp.pixel_gain()
            except NotImplementedError:
                # No GenericCalibPars information.
                pass
        else:
            try:
                self.det = self._get_det_id(self.group)
            except NotImplementedError:
                # No GenericCalibPars information.
                self.det = None

        # Redirect the output stream
        sys.stdout = old_stdout
        # f.close()
        # os.remove('./Detector_initialization.log')

    def _get_cbase(self):
        """Get detector calibration base object.

        Psana 1 only.
        """
        raise NotImplementedError()

    def _get_det_id(self, group):
        """Get detector ID form source.

        Psana 2 only.
        """
        raise NotImplementedError()

    def _get_calib_constants(self, name):
        _name = "_" + name
        attribute = getattr(self, _name)
        if six.PY3 and attribute is None and self.det is not None:
            # We haven't tried to get the calib_constant yet.
            attribute = calib_constants(self.det,
                                        exp=self.exp,
                                        ctype=name,
                                        run=self.run_num)[0]
        if attribute is None:
            # We still don't have it
            raise RuntimeError("No {} available for this detector"
                               "".format(name))
        setattr(self, _name, attribute)
        return attribute

    @property
    def pedestals(self):
        return self._get_calib_constants("pedestals")

    @property
    def pixel_rms(self):
        return self._get_calib_constants("pixel_rms")

    @property
    def pixel_mask(self):
        return self._get_calib_constants("pixel_mask")

    @property
    def pixel_bkgd(self):
        return self._get_calib_constants("pixel_bkgd")

    @property
    def pixel_status(self):
        return self._get_calib_constants("pixel_status")

    @property
    def pixel_gain(self):
        return self._get_calib_constants("pixel_gain")

    @pedestals.setter
    def pedestals(self, value):
        self._pedestals = value

    @pixel_rms.setter
    def pixel_rms(self, value):
        self._pixel_rms = value

    @pixel_mask.setter
    def pixel_mask(self, value):
        self._pixel_mask = value

    @pixel_bkgd.setter
    def pixel_bkgd(self, value):
        self._pixel_bkgd = value

    @pixel_status.setter
    def pixel_status(self, value):
        self._pixel_status = value

    @pixel_gain.setter
    def pixel_gain(self, value):
        self._pixel_gain = value

    def reset_calib(self, run_num):
        """
        Update calibration pixel effects based on new run number.
        """
        old_stdout = sys.stdout
        f = six.StringIO()
        sys.stdout = f

        self.run_num = run_num

        if six.PY2:
            try:
                pbits = 255
                gcp = GenericCalibPars(self._get_cbase(), self.calibdir,
                                       self.group, self.source, self.run_num,
                                       pbits)
                self._pedestals = gcp.pedestals()
                self._pixel_rms = gcp.pixel_rms()
                self._pixel_mask = gcp.pixel_mask()
                self._pixel_bkgd = gcp.pixel_bkgd()
                self._pixel_status = gcp.pixel_status()
                self._pixel_gain = gcp.pixel_gain()
            except NotImplementedError:
                pass
        else:
            self._pedestals = calib_constants(self.det,
                                              exp=self.exp,
                                              ctype='pedestals',
                                              run=self.run_num)[0]
            self._pixel_rms = calib_constants(self.det,
                                              exp=self.exp,
                                              ctype='pixel_rms',
                                              run=self.run_num)[0]
            self._pixel_mask = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype='pixel_mask',
                                               run=self.run_num)[0]
            self._pixel_bkgd = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype='pixel_bkgd',
                                               run=self.run_num)[0]
            self._pixel_status = calib_constants(self.det,
                                                 exp=self.exp,
                                                 ctype='pixel_status',
                                                 run=self.run_num)[0]
            self._pixel_gain = calib_constants(self.det,
                                               exp=self.exp,
                                               ctype='pixel_gain',
                                               run=self.run_num)[0]

        sys.stdout = old_stdout

        return

    ###########################################################################################
    # Functionality for adding dark noise
    ###########################################################################################
    def _calibrate_evt(self, evt):
        """
        Retrieve calibrated data from psana event object. Applied corrections are 
        pedestal, common mode, gain mask, gain, and pixel status mask, performed
        by the psana.Detector class.
    
        :param evt: psana event object
        :return data: calibrated image
        """
        import psana

        # retrieve psana.Source alias
        det_type = self.__class__.__name__.split("Detector")[0].lower()
        alias = None

        for key in evt.keys():
            if det_type in key.alias().lower():
                alias = key.alias()
                break
            else:
                srcname = key.src()
                if srcname.__class__.__name__ == 'DetInfo':
                    if det_type in srcname.devName().lower():
                        alias = str(srcname)
                        break

        # retrieve calibrated shot
        det = psana.Detector(alias)
        return det.calib(evt)

    def _retrieve_batch_evt(self, num_shots):
        """
        Retrieve num_shots patterns from a run of the experiment.
        
        :param num_shots: number of patterns to retrieve
        :return data: array of patterns in shape (num_shots, n_pedestals, ped_x, ped_y)
        """
        # set up psana1 DataSource object
        from psana import DataSource
        ds = DataSource('exp=%s:run=%i' % (self.exp, self.run_num))

        # set up storage array
        if self.pedestals.ndim == 4:
            pshape = self.pedestals.shape[1:]
        else:
            pshape = self.pedestals.shape
        data = np.zeros((num_shots, pshape[0], pshape[1], pshape[2]))

        # retrieve multiple events (shots)
        counter = 0
        for num, evt in enumerate(ds.events()):
            if counter < num_shots:
                data[counter] = np.array(self._calibrate_evt(evt))
                counter += 1
            else:
                break

        # if run is shorter than num_shots, fill in remainder by linear combination
        if counter < num_shots:
            for i in range(counter, num_shots):
                indices = np.random.randint(0, high=counter, size=2)
                weights = np.random.dirichlet(np.ones(2))
                data[i] = weights[0] * data[indices[0]] + weights[1] * data[
                    indices[1]]

        return data

    def _random_dark_index(self):
        """
        Return the run index of random dark run, assuming that the indices of dark
        runs can be inferred from the pedestal nomenclature.
        
        :return dark_idx: index of random dark run, -1 if no dark runs available
        """
        import glob

        # list of available pedestals
        pnames = glob.glob(
            "/reg/d/psdm/%s/%s/calib/%s/%s/pedestals/*-end.data" %
            (self.exp[:3].upper(), self.exp, self.group, self.source))

        # add run indices from pedestals list if associated XTC files exist
        dark_indices = list()
        for pn in pnames:
            temp_str = pn.split("/")[-1]
            temp_idx = int(temp_str.split("-")[0])
            fnames = glob.glob("/reg/d/psdm/%s/%s/xtc/*-r%04d-*.xtc" %
                               (self.exp[:3].upper(), self.exp, temp_idx))
            if len(fnames) > 0:
                dark_indices.append(temp_idx)

        # return random dark run or -1 if none available
        if len(dark_indices) != 0:
            return np.random.choice(np.array(dark_indices))
        else:
            return -1

    def add_dark_noise(self,
                       num_shots,
                       det_shape=True,
                       dark_idx=None,
                       mask_neg=True):
        """
        Retrieve calibrated images from dark runs.
    
        :param num_shots: number of calibrated dark shots to retreive
        :param det_shape: boolean, if True reassemble panels into detector's shape
        :param dark_idx: index of dark run; if None, a run number will be chosen randomly
        :param mask_neg: boolean, if True set negative-valued pixels to zero
        :return dark_data: array of calibrated dark shots with shape 
           (num_shots, det_x, det_y) if det_shape is True 
           (num_shots, n_panels, panel_x, panel_y) if det_shape is False
           None if pedestals and/or XTC files for a dark run are unavailable
        """
        if six.PY3:
            raise NotImplementedError(
                'Currently only implemented for psana2/python3.')
            return

        # grab index of random dark run and reset calibration attributes to match
        if dark_idx == None:
            dark_idx = self._random_dark_index()
            if dark_idx == -1:
                print("Pedestals and/or XTC data are unavailable.")
                return
        self.reset_calib(dark_idx)

        # retrieve dark data
        dark_data = self._retrieve_batch_evt(num_shots)

        # floor: set negative intensities to zero
        if mask_neg:
            dark_data[dark_data < 0] = 0

        # optionally reshape to match detector's shape
        if det_shape:
            dark_data = self.assemble_image_stack_batch(dark_data)

        return dark_data
예제 #4
0
def read_slac_metrology(path = None, geometry = None, plot=False, include_asic_offset=False):
  if path is None and geometry is None:
    raise Sorry("Need to provide a geometry object or a path to a geometry file")

  if path is not None and geometry is not None:
    raise Sorry("Cannot provide a geometry object and a geometry file. Ambiguous")

  if geometry is None:
    try:
      from PSCalib.GeometryAccess import GeometryAccess
      geometry = GeometryAccess(path)
    except Exception as e:
      raise Sorry("Can't parse this metrology file")

  metro = {}
  pixel_size = geometry.get_pixel_scale_size()/1000
  null_ori = matrix.col((0,0,1)).axis_and_angle_as_unit_quaternion(0, deg=True)

  # collapse any transformations above those of the quadrants into one X/Y offset,
  # but don't keep Z transformations, as those come from the XTC stream
  root = geometry.get_top_geo()
  root_basis = basis_from_geo(root, use_z=False)
  while len(root.get_list_of_children()) != 4 and len(root.get_list_of_children()) != 32:
    assert len(root.get_list_of_children()) == 1
    root = root.get_list_of_children()[0]
    root_basis *= basis_from_geo(root, use_z=False)

  metro[(0,)] = root_basis

  def add_sensor(quad_id, sensor_id, sensor):
    metro[(0,quad_id,sensor_id)] = basis_from_geo(sensor)

    x, y, z = sensor.get_pixel_coords()
    x/=1000; y/=1000; z/=1000
    assert x.shape == y.shape == z.shape
    sensor_px_slow = x.shape[0]
    sensor_px_fast = x.shape[1]
    assert sensor_px_fast % 2 == 0

    a0ul = sul = matrix.col((x[0,0],y[0,0],z[0,0]))
    a1ur = sur = matrix.col((x[0,sensor_px_fast-1],y[0,sensor_px_fast-1],z[0,sensor_px_fast-1]))
    a1lr = slr = matrix.col((x[sensor_px_slow-1,sensor_px_fast-1],y[sensor_px_slow-1,sensor_px_fast-1],z[sensor_px_slow-1,sensor_px_fast-1]))
    a0ll = sll = matrix.col((x[sensor_px_slow-1,0],y[sensor_px_slow-1,0],z[sensor_px_slow-1,0]))

    a0ur = matrix.col((x[0,sensor_px_fast//2-1],y[0,sensor_px_fast//2-1],z[0,sensor_px_fast//2-1]))
    a0lr = matrix.col((x[sensor_px_slow-1,sensor_px_fast//2-1],y[sensor_px_slow-1,sensor_px_fast//2-1],z[sensor_px_slow-1,sensor_px_fast//2-1]))

    a1ul = matrix.col((x[0,sensor_px_fast//2],y[0,sensor_px_fast//2],z[0,sensor_px_fast//2]))
    a1ll = matrix.col((x[sensor_px_slow-1,sensor_px_fast//2],y[sensor_px_slow-1,sensor_px_fast//2],z[sensor_px_slow-1,sensor_px_fast//2]))

    sensor_center = center([sul,sur,slr,sll])
    asic0_center = center([a0ul,a0ur,a0lr,a0ll])
    asic1_center = center([a1ul,a1ur,a1lr,a1ll])

    asic_trans0 = (asic0_center-sensor_center).length()
    asic_trans1 = (asic1_center-sensor_center).length()

    if include_asic_offset:
      rotated_ori = matrix.col((1,0,0)).axis_and_angle_as_unit_quaternion(180.0, deg=True)
      offset_fast = -pixel_size*((sensor_px_fast) / 4) # 4 because sensor_px_fast is for sensor
      offset_slow = +pixel_size*((sensor_px_slow) / 2) # Sensor is divided into 2 only in fast direction
      metro[(0,quad_id,sensor_id,0)] = basis(orientation=rotated_ori,translation=matrix.col((-asic_trans0,0,0)))
      metro[(0,quad_id,sensor_id,1)] = basis(orientation=rotated_ori,translation=matrix.col((+asic_trans1,0,0)))
      metro[(0,quad_id,sensor_id,0)].translation += matrix.col((offset_fast, offset_slow, 0))
      metro[(0,quad_id,sensor_id,1)].translation += matrix.col((offset_fast, offset_slow, 0))
    else:
      metro[(0,quad_id,sensor_id,0)] = basis(orientation=null_ori,translation=matrix.col((-asic_trans0,0,0)))
      metro[(0,quad_id,sensor_id,1)] = basis(orientation=null_ori,translation=matrix.col((+asic_trans1,0,0)))

  if len(root.get_list_of_children()) == 4:
    for quad_id, quad in enumerate(root.get_list_of_children()):
      metro[(0,quad_id)] = basis_from_geo(quad)
      for sensor_id, sensor in enumerate(quad.get_list_of_children()):
        add_sensor(quad_id, sensor_id, sensor)
  elif len(root.get_list_of_children()) == 32:
    for quad_id in range(4):
      metro[(0,quad_id)] = basis(orientation = null_ori, translation = matrix.col((0,0,0)))
      sensors = root.get_list_of_children()
      for sensor_id in range(8):
        add_sensor(quad_id, sensor_id, sensors[quad_id*4+sensor_id])
  else:
    assert False

  return metro