foa3d.printing

foa3d.printing.color_text(r, g, b, text)

Get colored text string.

Parameters

  • r (int) – red channel value

  • g (int) – green channel value

  • b (int) – blue channel value

  • text (str) – text string

Returns

clr_text – colored text

Return type

str

foa3d.printing.print_blur(sigma_um, psf_fwhm)

Print the standard deviation of the smoothing Gaussian filter.

Parameters

  • sigma_um (numpy.ndarray (shape=(3,), dtype=int)) – 3D standard deviation of the smoothing Gaussian filter [μm] (resolution anisotropy correction)

  • psf_fwhm (numpy.ndarray (shape=(3,), dtype=float)) – 3D FWHM of the PSF [μm]

Return type

None

foa3d.printing.print_flsh(string_to_print='', end='\n')

Print string and flush output data buffer.

Parameters

  • string_to_print (str) – string to be printed

  • end (str) – string appended after the last value, default a newline

Return type

None

foa3d.printing.print_frangi_config(in_img, cfg)

Print Frangi filter stage heading.

Parameters

  • in_img (dict) –

    input image dictionary (extended)

    data: numpy.ndarray or NumPy memory-map object (axis order=(Z,Y,X) or (Z,Y,X,C) or (Z,C,Y,X))

    3D microscopy image

    ts_msk: numpy.ndarray (dtype=bool)

    tissue reconstruction binary mask

    ch_ax: int

    RGB image channel axis (either 1, 3, or None for grayscale images)

    fb_ch: int

    neuronal fibers channel

    bc_ch: int

    brain cell soma channel

    msk_bc: bool

    if True, mask neuronal bodies within the optionally provided channel

    psf_fwhm: numpy.ndarray (shape=(3,), dtype=float)

    3D FWHM of the PSF [μm]

    px_sz: numpy.ndarray (shape=(3,), dtype=float)

    pixel size [μm]

    name: str

    name of the 3D microscopy image

    is_vec: bool

    vector field flag

    shape: numpy.ndarray (shape=(3,), dtype=int)

    total image shape

    shape_um: numpy.ndarray (shape=(3,), dtype=float)

    total image shape [μm]

    item_sz: int

    image item size [B]

  • cfg (dict) –

    Frangi filter configuration

    alpha: float

    plate-like score sensitivity

    beta: float

    blob-like score sensitivity

    gamma: float

    background score sensitivity

    scales_px: numpy.ndarray (dtype=float)

    Frangi filter scales [px]

    scales_um: numpy.ndarray (dtype=float)

    Frangi filter scales [μm]

    smooth_sd: numpy.ndarray (shape=(3,), dtype=int)

    3D standard deviation of the smoothing Gaussian filter [px]

    px_sz: numpy.ndarray (shape=(3,), dtype=float)

    pixel size [μm]

    fb_thr: float or str

    image thresholding applied to the Frangi filter response

    msk_bc: bool

    if True, mask neuronal bodies within the optionally provided channel

    hsv_cmap: bool

    generate HSV colormap of 3D fiber orientations

    exp_all: bool

    export all images

    rsz: numpy.ndarray (shape=(3,), dtype=float)

    3D image resize ratio

    ram: float

    maximum RAM available to the Frangi filter stage [B]

    jobs: int

    number of parallel jobs (threads) used by the Frangi filter stage

    batch: int

    slice batch size

    slc_shp: numpy.ndarray (shape=(3,), dtype=int)

    shape of the basic image slices analyzed using parallel threads [px]

    ovlp: int

    overlapping range between image slices along each axis [px]

    tot_slc: int

    total number of image slices

    z_out: NumPy slice object

    output z-range

Return type

None

foa3d.printing.print_frangi_progress(start_time, batch, tot, not_bg, verbose=5)

Print Frangi filter progress.

Parameters

  • start_time (float) – start time [s]

  • batch (int) – slice batch size

  • tot (int) – total number of image slices

  • not_bg (bool) – foreground slice flag

  • verbose (int) – verbosity level (print info only every “verbose” slices)

Return type

None

foa3d.printing.print_image_info(in_img)

Print information on the input microscopy image (shape, voxel size, PSF size).

Parameters

in_img (dict) – input image dictionary

Return type

None

foa3d.printing.print_import_time(start_time)

Print image import time.

Parameters

start_time (float) – import start time

Return type

None

foa3d.printing.print_odf_info(odf_scales_um, odf_degrees)

Print ODF analysis heading.

Parameters

  • odf_scales_um (list (dtype=float)) – fiber ODF resolutions (super-voxel sides [μm])

  • odf_degrees (int) – degrees of the spherical harmonics series expansion

Return type

None

foa3d.printing.print_pipeline_heading()

Print Foa3D tool heading.

Return type

None

foa3d.printing.print_prepro_heading()

Print preprocessing heading.

Return type

None

foa3d.printing.print_slicing_info(img_shp_um, slc_shp_um, px_sz, item_sz, msk_bc)

Print information on the slicing of the basic image sub-volumes processed by the Foa3D tool.

Parameters

  • img_shp_um (numpy.ndarray (shape=(3,), dtype=float)) – 3D microscopy image [μm]

  • slc_shp_um (numpy.ndarray (shape=(3,), dtype=float)) – shape of the analyzed image slices [μm]

  • px_sz (numpy.ndarray (shape=(3,), dtype=float)) – pixel size [μm]

  • item_sz (int) – image item size (in bytes)

  • msk_bc (bool) – if True, mask neuronal bodies within the optionally provided channel

Return type

None