Configuration file

The DryMass configuration file drymass.cfg is located in the root of the output folder (“_dm” appended to the data path). The configuration file is divided into sections.

[bg] Background correction

DryMass uses the Python library qpimage for background correction. For detailed information on the algorithms (and the corresponding keyword arguments) used, please see qpimage.bg_estimate.

  • amplitude data = none (int_or_str) – Amplitude bg correction file or index
    Image indexing starts with 1.
  • amplitude offset = mean (lcstr) – Amplitude bg correction offset method
    Valid values are defined in qpimage.bg_estimate.VALID_FIT_OFFSETS.
  • amplitude profile = tilt (lcstr) – Amplitude bg correction profile method
    Valid values are defined in qpimage.bg_estimate.VALID_FIT_PROFILES.
  • amplitude binary threshold = nan (float_or_str) – Binary image threshold value or method
    If not nan, defines either a threshold for background segmentation or a method in skimage.filters.
  • amplitude border perc = 10 (float) – Amplitude bg border region to analyze [%]
  • amplitude border px = 5 (int) – Amplitude bg border region to analyze [px]
  • enabled = True (fbool) – Enable bg correction globally
    Set to False when manually editing roi_slices.txt.
  • phase data = none (int_or_str) – Phase bg correction file or index
    Image indexing starts with 1.
  • phase offset = mean (lcstr) – Phase bg correction offset method
    Valid values are defined in qpimage.bg_estimate.VALID_FIT_OFFSETS.
  • phase profile = tilt (lcstr) – Phase bg correction profile method
    Valid values are defined in qpimage.bg_estimate.VALID_FIT_PROFILES.
  • phase binary threshold = nan (float_or_str) – Binary image threshold value or method
    If not nan, defines either a threshold for background segmentation or a method in skimage.filters.
  • phase border perc = 10 (float) – Phase bg border region to analyze [%]
  • phase border px = 5 (int) – Phase bg border region to analyze [px]

[holo] Hologram analysis

These parameters tune the hologram analysis step (if applicable). The parameters shown are passed to qpimage.holo.get_field().

  • filter name = disk (str) – Filter name for sideband isolation
  • filter size = 1/3 (float) – Filter size (fraction of the sideband frequency
  • sideband = 1 (floattuple_or_one) – Sideband ±1 or frequency coordinates

[meta] Image meta data

This section contains meta data of the experiment.

  • medium index = nan (float) – Refractive index of the surrounding medium
  • pixel size um = nan (float) – Detector pixel size [µm]
  • wavelength nm = nan (float) – Imaging wavelength [nm]

[output] Supplementary data output

This section defines what additional data are written to disk.

  • roi images = True (fbool) – Rendered phase images with ROI location
  • sphere images = True (fbool) – Phase/Intensity images for sphere analysis
  • sensor tif data = True (fbool) – Phase/Amplitude sensor tif data

[roi] Extraction of regions of interest

The extraction of ROIs is done in drymass.extractroi.extract_roi().

  • dist border px = 10 (int) – Minimum distance of objects to image border [px]
  • eccentricity max = 0.7 (float) – Allowed maximal eccentricity of the specimen
  • enabled = True (fbool) – Perform automated search for ROIs
    If set to False, the file “roi_slices.txt” must contain ROIs.
  • exclude overlap px = 30.0 (float) – Allowed distance between two objects [px]
  • force = () (tupletupleint) – Force ROI coordinates (x1,x2,y1,y2) [px]
  • pad border px = 40 (int) – Padding of object regions [px]
  • size variation = 0.5 (float01) – Allowed variation relative to specimen size

[specimen] Specimen parameters

Prior information about the analyzed object(s).

  • size um = 10 (float) – Approximate diameter of the specimen [µm]
    This is used as the initial value for the sphere analysis.

[sphere] Sphere-based image analysis

Retrieval of refractive index and radius is done with the Python module qpsphere. The parameters either apply to qpsphere.edgefit.contour_canny() or to qpsphere.imagefit.alg.match_phase(), depending on which analysis approach is used.

  • edge coarse = 0.4 (float) – Coarse edge detection filter size
  • edge fine = 0.1 (float) – Fine edge detection filter size
  • edge clip radius min = 0.9 (float) – Interior edge point filtering radius
  • edge clip radius max = 1.1 (float) – Exterior edge point filtering radius
  • edge iter = 20 (int) – Maximum number iterations for coarse edge detection
  • image fit range position = 0.05 (float) – Fit interpolation range for radius
  • image fit range radius = 0.05 (float) – Fit interpolation range for radius
  • image fit range refractive index = 0.10 (float) – Fit interpolation range for refractive index
  • image fix phase offset = False (fbool) – Fix the simulation background phase to zero
  • image iter = 100 (int) – Maximum number of iterations for image fitting
  • image stop delta position = 1 (float) – Stopping criterion for position
  • image stop delta radius = 0.0010 (float) – Stopping criterion for radius
  • image stop delta refractive index = 0.0005 (float) – Stopping criterion for refractive index
  • image verbosity = 1 (int) – Verbosity level of image fitting algorithm
  • method = edge (lcstr) – Method for determining sphere parameters
    Valid values are edge (edge-detection approach) or image (2D phase image fitting).
  • model = projection (lcstr) – Physical sphere model
    Valid values are defined in qpsphere.models.available. If method=edge, then model must be set to projection. If method=image, setting model to rytov-sc has the best trade-off between accuracy and speed.
  • refraction increment = 0.18 (float) – Refraction increment [mL/g]
  • radial inclusion factor = 1.2 (float) – Radial inclusion factor for dry mass computation