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dials.image_viewer¶
Introduction¶
This program can be used for viewing diffraction images, optionally overlayed with the results of spot finding, indexing or integration.
Examples:
dials.image_viewer image.cbf
dials.image_viewer models.expt
dials.image_viewer models.expt strong.refl
dials.image_viewer models.expt integrated.refl
Basic parameters¶
brightness = 100
color_scheme = *grayscale rainbow heatmap invert
show_beam_center = True
show_resolution_rings = False
show_ice_rings = False
show_ctr_mass = True
show_max_pix = True
show_all_pix = True
show_shoebox = True
show_predictions = True
show_miller_indices = False
show_indexed = False
show_integrated = False
show_mask = False
show_basis_vectors = True
display = *image mean variance dispersion sigma_b sigma_s threshold \
global_threshold
nsigma_b = 6
nsigma_s = 3
global_threshold = 0
kernel_size = 3,3
min_local = 2
gain = 1
d_min = None
mask = None
powder_arcs {
show = False
code = None
}
calibrate_silver = False
calibrate_pdb {
code = None
d_min = 20.
}
calibrate_unitcell {
unitcell = None
d_min = 20.
spacegroup = None
}
masking {
border = 0
use_trusted_range = False
d_min = None
d_max = None
resolution_range = None
untrusted {
panel = 0
circle = None
rectangle = None
polygon = None
pixel = None
}
ice_rings {
filter = False
}
}
output {
mask = pixels.mask
mask_params = mask.phil
}
predict_reflections = False
profile {
algorithm = *gaussian_rs
gaussian_rs {
scan_varying = False
min_spots {
overall = 50
per_degree = 20
}
sigma_m_algorithm = basic *extended
centroid_definition = com *s1
parameters {
n_sigma = 3.0
sigma_b = None
sigma_m = None
}
filter {
min_zeta = 0.05
}
fitting {
scan_step = 5
grid_size = 5
threshold = 0.02
grid_method = single *regular_grid circular_grid spherical_grid
fit_method = *reciprocal_space detector_space
detector_space {
deconvolution = False
}
}
}
}
prediction {
d_min = None
d_max = None
margin = 1
force_static = False
padding = 1.0
}
load_models = True
Full parameter definitions¶
brightness = 100
.type = int(allow_none=True)
color_scheme = *grayscale rainbow heatmap invert
.type = choice
show_beam_center = True
.type = bool
show_resolution_rings = False
.type = bool
show_ice_rings = False
.type = bool
show_ctr_mass = True
.type = bool
show_max_pix = True
.type = bool
show_all_pix = True
.type = bool
show_shoebox = True
.type = bool
show_predictions = True
.type = bool
show_miller_indices = False
.type = bool
show_indexed = False
.type = bool
show_integrated = False
.type = bool
show_mask = False
.type = bool
show_basis_vectors = True
.type = bool
display = *image mean variance dispersion sigma_b sigma_s threshold \
global_threshold
.type = choice
nsigma_b = 6
.type = float(value_min=0, allow_none=True)
nsigma_s = 3
.type = float(value_min=0, allow_none=True)
global_threshold = 0
.type = float(value_min=0, allow_none=True)
kernel_size = 3,3
.type = ints(size=2, value_min=1)
min_local = 2
.type = int(allow_none=True)
gain = 1
.help = "Set gain for the thresholding algorithm. This does not override the"
"detector's panel gain, but acts as a multiplier for it."
.type = float(value_min=0, allow_none=True)
sum_images = 1
.type = int(value_min=1, allow_none=True)
.expert_level = 2
d_min = None
.type = float(value_min=0, allow_none=True)
mask = None
.help = "path to mask pickle file"
.type = path
powder_arcs {
show = False
.help = "show powder arcs calculated from PDB file."
.type = bool
code = None
.help = "PDB code (4 characters) for file; fetch it from the Internet."
.type = str
}
calibrate_silver = False
.help = "Open special GUI for distance/metrology from silver behenate."
.type = bool
calibrate_pdb {
code = None
.help = "Option is mutually exclusive with calibrate silver, unit cell and"
"powder arcs options."
.type = str
d_min = 20.
.help = "Limiting resolution to calculate powder rings"
.type = float(allow_none=True)
}
calibrate_unitcell {
unitcell = None
.help = "Option is mutually exclusive with calibrate silver, pdb and"
"powder arcs options."
.type = unit_cell
d_min = 20.
.help = "Limiting resolution to calculate powder rings"
.type = float(allow_none=True)
spacegroup = None
.help = "Specify spacegroup for the unit cell"
.type = str
}
format
.help = "Options to pass to the Format class"
.expert_level = 2
{
dynamic_shadowing = auto
.help = "Enable dynamic shadowing"
.type = bool
multi_panel = False
.help = "Enable a multi-panel detector model. (Not supported by all"
"detector formats)"
.type = bool
}
masking {
border = 0
.help = "The border around the edge of the image."
.type = int(allow_none=True)
use_trusted_range = False
.help = "Use the trusted range to mask bad pixels."
.type = bool
d_min = None
.help = "The high resolution limit in Angstrom for a pixel to be accepted"
"by the filtering algorithm."
.type = float(value_min=0, allow_none=True)
d_max = None
.help = "The low resolution limit in Angstrom for a pixel to be accepted"
"by the filtering algorithm."
.type = float(value_min=0, allow_none=True)
resolution_range = None
.help = "an untrusted resolution range"
.type = floats(size=2)
.multiple = True
untrusted
.multiple = True
{
panel = 0
.help = "The panel number"
.type = int(allow_none=True)
circle = None
.help = "An untrusted circle (xc, yc, r)"
.type = ints(size=3)
rectangle = None
.help = "An untrusted rectangle (x0, x1, y0, y1)"
.type = ints(size=4)
polygon = None
.help = "The pixel coordinates (fast, slow) that define the corners of"
"the untrusted polygon. Spots whose centroids fall within the"
"bounds of the untrusted polygon will be rejected."
.type = ints(value_min=0)
pixel = None
.help = "An untrusted pixel (y, x)"
.type = ints(size=2, value_min=0)
}
ice_rings {
filter = False
.type = bool
unit_cell = 4.498,4.498,7.338,90,90,120
.help = "The unit cell to generate d_spacings for powder rings."
.type = unit_cell
.expert_level = 1
space_group = 194
.help = "The space group used to generate d_spacings for powder rings."
.type = space_group
.expert_level = 1
width = 0.002
.help = "The width of an ice ring (in 1/d^2)."
.type = float(value_min=0, allow_none=True)
.expert_level = 1
d_min = None
.help = "The high resolution limit (otherwise use detector d_min)"
.type = float(value_min=0, allow_none=True)
.expert_level = 1
}
}
output {
mask = pixels.mask
.help = "Name of output mask file"
.type = path
mask_params = mask.phil
.help = "Name of output mask parameter file"
.type = path
}
predict_reflections = False
.help = "Predict reflections if no reflections provided in input"
.type = bool
profile
.help = "The interface definition for a profile model."
{
algorithm = *gaussian_rs
.help = "The choice of algorithm"
.type = choice
gaussian_rs
.help = "An extension class implementing a reciprocal space gaussian"
"profile model."
{
scan_varying = False
.help = "Calculate a scan varying model"
.type = bool
min_spots
.help = "if (total_reflections > overall or reflections_per_degree >"
"per_degree) then do the profile modelling."
{
overall = 50
.help = "The minimum number of spots needed to do the profile"
"modelling"
.type = int(value_min=0, allow_none=True)
per_degree = 20
.help = "The minimum number of spots needed to do the profile"
"modelling"
.type = int(value_min=0, allow_none=True)
}
sigma_m_algorithm = basic *extended
.help = "The algorithm to compute mosaicity"
.type = choice
centroid_definition = com *s1
.help = "The centroid to use as beam divergence (centre of mass or s1)"
.type = choice
parameters {
n_sigma = 3.0
.help = "Sigma multiplier for shoebox"
.type = float(value_min=0, allow_none=True)
sigma_b = None
.help = "Override the sigma_b value (degrees)"
.type = float(value_min=0, allow_none=True)
sigma_m = None
.help = "Override the sigma_m value (degrees)"
.type = float(value_min=0, allow_none=True)
}
filter {
min_zeta = 0.05
.help = "Filter reflections by min zeta"
.type = float(allow_none=True)
}
fitting {
scan_step = 5
.help = "Space between profiles in degrees"
.type = float(allow_none=True)
grid_size = 5
.help = "The size of the profile grid."
.type = int(allow_none=True)
threshold = 0.02
.help = "The threshold to use in reference profile"
.type = float(allow_none=True)
grid_method = single *regular_grid circular_grid spherical_grid
.help = "Select the profile grid method"
.type = choice
fit_method = *reciprocal_space detector_space
.help = "The fitting method"
.type = choice
detector_space {
deconvolution = False
.help = "Do deconvolution in detector space"
.type = bool
}
}
}
}
prediction {
d_min = None
.help = "The maximum resolution limit"
.type = float(allow_none=True)
d_max = None
.help = "The minimum resolution limit"
.type = float(allow_none=True)
margin = 1
.help = "The margin to use to scan varying prediction"
.type = int(allow_none=True)
force_static = False
.help = "For scan-varying prediction force scan-static prediction"
.type = bool
padding = 1.0
.help = "The padding in degrees"
.type = float(value_min=0, allow_none=True)
}
load_models = True
.help = "Whether to load every model, which matters for large image files"
.type = bool
