config_data¶
The "config_data" file defines parameters needed to format data for phasing. The input is an instrument corrected data file obtained in the beamline preprocessing phase.
Parameters¶
data_dir
Optional, defaults to <experiment_dir>/preprocessed_data in cohere experiment directory structure.
Defines directory that contains data.tif file with beamline preprocessed experiment data.
data_dir = "/path/to/data_dir"
alien_alg
Optional, if not defined, no alien algorithm is used.
Name of method used to remove aliens. Possible options are: 'block_aliens', 'alien_file', and 'AutoAlien1'. The 'block_aliens' algorithm will zero out defined blocks, 'alien_file' method will use given file as a mask, and 'AutoAlien1' will use auto mechanism to remove aliens. Each of these algorithms require different parameters, explained below.
alien_alg = "AutoAlien1"
aliens
Needed when the 'block_aliens' method is configured. Used when the data contains regions with intensity produced by interference. The regions are zeroed out. The aliens can be defined as regions, each region defined by coordinates of starting point, and ending point (i.e. [[xb0,yb0,zb0,xe0,ye0,ze0],[xb1,yb1,zb1,xe1,ye1,ze1],...[xbn,ybn,zbn,xen,yen,zen]] ).
aliens = [[170,220,112,195,245,123], [50,96,10,60,110,20]]
alien_file
Needed when the 'alien_file' method is configured. User can produce a file in npy format that contains zeros and ones, where zero means to set the pixel to zero, and one to leave it.
alien_file = "/path/to/mask_file/AlienImg.npy"
AA1_size_threshold
Used in the 'AutoAliens1' method. If not given it will default to 0.01. The AutoAlien1 algorithm will calculate relative sizes of all clusters with respect to the biggest cluster. The clusters with relative size smaller than the given threshold will be possibly deemed aliens. It also depends on asymmetry.
AA1_size_threshold = 0.01
AA1_asym_threshold
Used in the 'AutoAliens1' method. If not given it will default to 1.75. The AutoAlien1 algorithm will calculate average asymmetry of all clusters. The clusters with average asymmetry greater than the given threshold will be possibly deemed aliens. It also depends on relative size.
AA1_asym_threshold = 1.75
AA1_min_pts
used in the 'AutoAliens1' method. If not given it will default to 5. Defines minimum non zero points in neighborhood to count the area of data as cluster.
AA1_min_pts = 5
AA1_eps
Used in the 'AutoAliens1' method. If not given it will default to 1.1. Defines neighborhood Used in the clustering algorithm.
AA1_eps = 1.1
AA1_amp_threshold
Mandatory in the 'AutoAliens1' method. Used to zero data points below that threshold.
AA1_amp_threshold = 6
AA1_save_arrs
Used in the 'AutoAliens1' method, optional. If given and set to True multiple results of alien analysis will be saved in files.
AA1_save_arrs = True
AA1_expandcleanedsigma
Used in the 'AutoAliens1' method, optional. If given the algorithm will apply last step of cleaning the data using the configured sigma.
AA1_expandcleanedsigma = 5.0
auto_intensity_threshold
Optional, defaults to False.
The intensity threshold is calculated programmatically if set to True, otherwise must be provided.
auto_intensity_threshold = True
intensity_threshold
Mandatory, if auto_intensity_threshold is not set. Intensity values below this value are set to 0. The threshold is applied after removing aliens.
If auto_data is configured , this value is overridden by calculated value.
intensity_threshold = 25.0
crop_pad
Optional, a list of numbers defining how to adjust the size at each side of 3D data. If number is positive, the array will be padded. If negative, cropped. The parameters correspond to [x left, x right, y left, y right, z left, z right]. The final dimensions will be adjusted up to the good number for the FFT such as product of powers of 2, 3 or 5.
crop_pad = [13, 0, -65, -65, -65, -65]
center_shift
Optional, defines offset of max element from the array center.
center_shift = [0,0,0]
no_center_max
Optional, defaults to False. If False the array maximum is centered, otherwise max is not moved.
no_center_max = False
binning
Optional, a list that defines binning values in respective dimensions, [1,1,1] has no effect.
binning = [1,1,1]