def __init__(self, experiment, diffraction_rings=None, log_scale=False):
self.experiment = experiment
self.center = self.experiment.det.geometry.point_coord_indexes((0, 0))
# ! Wavenumber definition != beam's.
self.wavenumber = np.linalg.norm(self.experiment.beam.get_wavevector())
self.distance = self.experiment.det.distance
pixel_width = asnumpy(self.experiment.det.pixel_width)
# Cupy doesn't have median yet.
self.pix_width = np.median(pixel_width)
recidet = ReciprocalDetector(self.experiment.det, self.experiment.beam)
self.q_max = asnumpy(
np.min(( # Max inscribed radius
xp.max(recidet.pixel_position_reciprocal[..., 1]),
-xp.min(recidet.pixel_position_reciprocal[..., 1]),
xp.max(recidet.pixel_position_reciprocal[..., 0]),
-xp.min(recidet.pixel_position_reciprocal[..., 0]))))
self._auto_rings = False
if diffraction_rings is not None:
if diffraction_rings.lower() == "auto":
self._auto_rings = True
else:
raise ValueError(
"Unrecognized value '{}' for argument diffraction_rings"
"".format(diffraction_rings))
if log_scale:
self._norm = LogNorm()
else:
self._norm = None
def get_reciprocal_mesh(self, voxel_number_1d):
"""
Get the proper reciprocal mesh.
:param voxel_number_1d: The voxel number along 1 dimension.
:return: The reciprocal mesh, voxel length.
"""
dist_max = xp.max(self.pixel_distance_reciprocal)
return pg.get_reciprocal_mesh(voxel_number_1d, dist_max)
def preferred_reciprocal_mesh_number(self, wave_vector):
"""
If one want to put the diffraction pattern into 3D reciprocal space, then one needs to
select a proper voxel number for a proper voxel length for the reciprocal space.
This function gives a reasonable estimation of this length and voxel number
:param wave_vector: The wavevector of in this experiment.
:return: The reciprocal mesh number along 1 dimension
"""
""" Return the prefered the reciprocal voxel grid number along 1 dimension. """
voxel_length = self.preferred_voxel_length(wave_vector)
reciprocal_space_range = xp.max(self.pixel_distance_reciprocal)
# The voxel number along 1 dimension is 2*voxel_half_num_1d+1
voxel_half_num_1d = int(
xp.floor_divide(reciprocal_space_range, voxel_length) + 1)
voxel_num_1d = int(2 * voxel_half_num_1d + 1)
return voxel_num_1d
def initialize(self, geom, beam):
"""
Initialize the detector with user defined parameters
:param geom: The dictionary containing all the necessary information to initialized the
detector.
:param beam: The beam object
:return: None
"""
"""
Doc:
To use this class, the user has to provide the necessary information to initialize
the detector.
All the necessary entries are listed in the example notebook.
"""
# 'detector distance': detector distance in (m)
##########################################################################################
# Extract necessary information
##########################################################################################
# Define the hierarchy system. For simplicity, we only use two-layer structure.
for key in {'panel number', 'panel pixel num x', 'panel pixel num y'}:
if key not in geom:
raise KeyError("Missing required '{}' key.".format(key))
self.panel_num = int(geom['panel number'])
self.panel_pixel_num_x = int(geom['panel pixel num x'])
self.panel_pixel_num_y = int(geom['panel pixel num y'])
self._shape = (self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y)
# Define all properties the detector should have
self._distance = None
if 'pixel center z' in geom:
if 'detector distance' in geom:
raise ValueError("Please provide one of "
"'pixel center z' or 'detector distance'.")
self.center_z = xp.asarray(geom['pixel center z'],
dtype=xp.float64)
self._distance = float(self.center_z.mean())
else:
if 'detector distance' not in geom:
KeyError("Missing required 'detector distance' key.")
self._distance = float(geom['detector distance'])
self.center_z = self._distance * xp.ones(self._shape,
dtype=xp.float64)
# Below: [panel number, pixel num x, pixel num y] in (m)
# Change dtype and make numpy/cupy array
self.pixel_width = xp.asarray(geom['pixel width'], dtype=xp.float64)
self.pixel_height = xp.asarray(geom['pixel height'], dtype=xp.float64)
self.center_x = xp.asarray(geom['pixel center x'], dtype=xp.float64)
self.center_y = xp.asarray(geom['pixel center y'], dtype=xp.float64)
self.orientation = np.array([0, 0, 1])
# construct the the pixel position array
self.pixel_position = xp.zeros(self._shape + (3, ))
self.pixel_position[..., 0] = self.center_x
self.pixel_position[..., 1] = self.center_y
self.pixel_position[..., 2] = self.center_z
# Pixel map
if 'pixel map' in geom:
# [panel number, pixel num x, pixel num y]
self.pixel_index_map = xp.asarray(geom['pixel map'],
dtype=xp.int64)
# Detector pixel number info
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)
# Panel pixel number info
# number of pixels in each panel in x/y direction
self.panel_pixel_num_x = self.pixel_index_map.shape[1]
self.panel_pixel_num_y = self.pixel_index_map.shape[2]
# total number of pixels (px*py)
self.pixel_num_total = np.prod(self._shape)
###########################################################################################
# Do necessary calculation to finishes the initialization
###########################################################################################
# self.geometry currently only work for the pre-defined detectors
self.geometry = geom
# Calculate the pixel area
self.pixel_area = xp.multiply(self.pixel_height, self.pixel_width)
# Get reciprocal space configurations and corrections.
self.initialize_pixels_with_beam(beam=beam)
##########################################################################################
# Do necessary calculation to finishes the initialization
##########################################################################################
# Detector effects
if 'pedestal' in geom:
self._pedestal = xp.asarray(geom['pedestal'], dtype=xp.float64)
else:
self._pedestal = xp.zeros((self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
if 'pixel rms' in geom:
self._pixel_rms = xp.asarray(geom['pixel rms'], dtype=xp.float64)
else:
self._pixel_rms = xp.zeros((self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
if 'pixel bkgd' in geom:
self._pixel_bkgd = xp.asarray(geom['pixel bkgd'], dtype=xp.float64)
else:
self._pixel_bkgd = xp.zeros(
(self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
if 'pixel status' in geom:
self._pixel_status = xp.asarray(geom['pixel status'],
dtype=xp.float64)
else:
self._pixel_status = xp.zeros(
(self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
if 'pixel mask' in geom:
self._pixel_mask = xp.asarray(geom['pixel mask'], dtype=xp.float64)
else:
self._pixel_mask = xp.zeros(
(self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
if 'pixel gain' in geom:
self._pixel_gain = xp.asarray(geom['pixel gain'], dtype=xp.float64)
else:
self._pixel_gain = xp.ones((self.panel_num, self.panel_pixel_num_x,
self.panel_pixel_num_y))
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
def __init__(self, N_pixel, det_size, det_distance, beam=None):
"""
Initialize the detector
:param N_pixel: Number of pixels per dimension.
:param det_size: Length of detector sides (m).
:param det_distance: Sample-Detector distance (m).
"""
super(SimpleSquareDetector, self).__init__()
ar = xp.arange(N_pixel)
sep = float(det_size) / N_pixel
x = -det_size / 2 + sep / 2 + ar * sep
y = -det_size / 2 + sep / 2 + ar * sep
X, Y = xp.meshgrid(x, y, indexing='xy')
Xar, Yar = xp.meshgrid(ar, ar, indexing='xy')
self.panel_num = 1
self.panel_pixel_num_x = N_pixel
self.panel_pixel_num_y = N_pixel
self._shape = (1, N_pixel, N_pixel)
# Define all properties the detector should have
self._distance = det_distance
self.center_z = self._distance * xp.ones(self._shape, dtype=xp.float64)
p_center_x = xp.stack((X, ))
p_center_y = xp.stack((Y, ))
self.pixel_width = sep * xp.ones(self._shape, dtype=xp.float64)
self.pixel_height = sep * xp.ones(self._shape, dtype=xp.float64)
self.center_x = p_center_x
self.center_y = p_center_y
# construct the the pixel position array
self.pixel_position = xp.zeros(self._shape + (3, ))
self.pixel_position[..., 0] = self.center_x
self.pixel_position[..., 1] = self.center_y
self.pixel_position[..., 2] = self.center_z
# Pixel map
p_map_x = xp.stack((Xar, ))
p_map_y = xp.stack((Yar, ))
# [panel number, pixel num x, pixel num y]
self.pixel_index_map = xp.stack((p_map_x, p_map_y), axis=-1)
# Detector pixel number info
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)
# Panel pixel number info
# number of pixels in each panel in x/y direction
self.panel_pixel_num_x = self.pixel_index_map.shape[1]
self.panel_pixel_num_y = self.pixel_index_map.shape[2]
# total number of pixels (px*py)
self.pixel_num_total = np.prod(self._shape)
# Calculate the pixel area
self.pixel_area = xp.multiply(self.pixel_height, self.pixel_width)
# Get reciprocal space configurations and corrections.
self.initialize_pixels_with_beam(beam=beam)
