queriedSample#

Example Usage#

Full Contents:#

class @queriedSample.queriedSample(sampleStruct)#

Bases: sphinxcontrib.mat_types.handle

QUERIEDSAMPLE Object for manipulating subset of atlas

Class for manipulating a queried subset of the dynamicAtlas Holds a subset of embryos in the atlas and offers methods for interrogating the properties of those embryos, such as loading the data, smoothed data, gradients, flow fields.

Note that a queriedSample can slice across embryos, labels, genotypes, or timestamps. There are few restrictions about what kinds of embryos can be contained in the queried sample. For example, da.findTime() will return a queriedSample of all embryos of any genotype in the da (dynamicAtlas instance) that match a timestamp range.

meta: struct with fields

folders : Nx1 cell array of paths to label data names : Nx1 cell array of label data filenames embryoIDs : Nx1 cell array of embryoIDs times : Nx1 cell array of timestamps (each could be array) unc : Nx1 cell array of timestamp uncertainties nTimePoints : Nx1 int array of #timepoints in each dataset

datainitially empty cell of data images

can be populated via qs.getData()

gradientsinitially empty cell of gradient images

can be populated via qs.getGradients()

smoothinitially empty cell of smoothed data images

can be populated via qs.getSmooth()

pivinitially empty cell of velocity fields

can be populated via qs.getPIV()

Example

a = dynamicAtlas(‘./’, {‘WT’}) qs = a.findLabel(‘Eve’) qs.getData() qs.getGradients(‘dx’, 10) qs.getSmooth()

NPMitchell 2020

buildPIVStack(da, genotype, labels, deltaTime)#

Build a stack of PIV flow fields over time

data = None#

embryoIDs, times, uncs, tiffpages, nTimePoints

dynamicAtlas = None#

dynamicAtlas object from which qs is made

ensurePIV(options)#

Make sure each embryo in the queriedSample has PIV and PIV_filtered measurements: one .mat per timepoint

getData()#

GETDATA(obj) Load the TIFFs for all data in this queriedSample

Returns

dataCell – The requested raw data images

Return type

N x 1 cell of 2d uint16 arrays

getGradients(xymag, sigma, step)#
GETGRADIENTS(obj)

Load the gradient TIFFs for all data in this queriedSample

Parameters

  • xymag (optional str ('x', 'y', 'mag'), default='mag') – whether to grab AP gradient (x), DV gradient (y), or normed magnitude of gradient

  • sigma (optional int, default=10) – length scale over which data is smoothed before gradient computed

  • step (optional int, default=1) – length scale over which gradient is computed

Returns

dataCell – The requested gradient images

Return type

N x 1 cell of 2d uint16 arrays

getMaxTime()#

Measure the largest timestamp value in the queried sample

getMeanData(normalizeEach, preview)#

Load all data and take the mean of all data in the sampling

Parameters

  • obj (queriedSample instance (self)) –

  • normalizeEach (bool (default = true)) – normalize the intensity of each frame as we sum them (recommended)

  • preview (bool (default = false)) – preview the averaging of all members of the queriedSample, element by element as we sum them

Returns

meanIm – mean image intensity for all samples in queriedSample instance

Return type

2D double array

getMeanPIV(options)#

meanPIV = getMeanPIV(obj, options) Load PIV results for all entries in queriedSample collection

Parameters

options (struct with fields) – method : ‘default’ or ‘pivlab’

Returns

mean flow across all samples in the queriedSample

Return type

meanPIV

getMinTime()#

Measure the samllest timestamp value in the queried sample

getPIV(options)#

piv = getPIV(obj, options)

Parameters

options (optional struct with optional fields) –

methodstring specifier (‘default’ or ‘pivlab’)

how the piv was computed.

Returns

piv – vx vy

Return type

struct with fields

getSmooth(sigma, step)#
GETGRADIENTS(obj)

Load the smoothed TIFFs for all data in this queriedSample

Parameters

  • sigma (optional int, default=10) – length scale over which data is smoothed before gradient computed

  • step (optional int, default=1) – length scale over which gradient is computed

Returns

dataCell – The requested gradient images

Return type

N x 1 cell of 2d uint16 arrays

gradients = 'struct()'#

struct with fields dx, dy, mag

meanPIV = "struct('vx', [], \n'vy', [])"#

cell array of average velocity field across sample

meta = None#

struct with fields labels, folders, names, …

piv = "struct('vx', [], \n'vy', [], \n'rescaleFactor', 0.4)"#

cell array of velocity fields

queriedSample(sampleStruct)#

sampleStruct: struct with fields labels, folders, names, … embryoIDs, times, uncs, tiffpages, nTimePoints

smooth = None#

cell array of images

@queriedSample.timeStamp(qs, label, options)#

Assign a timestamp to each member of the queriedSample qs.

This method applies only to queriedSamples of identical genotype, which is doubly enforced by passing the argument ‘genotype’.

Parameters

  • da (dynamicAtlas instance) – The collection of data for which timing of each embryo in genotype/label/ is applied.

  • genotype (char) – The genotype of the timing label (for ex, “WT” to timestamp embryos in WT/<label>/)

  • label (char) – The label used for timestamping (for ex, “Runt” to timestamp embryos in <genotype>/Runt/

  • Options (struct with fields) –

    method’stripe7’ or <new method string specifier>

    how to timestamp the embryo

    save_fancybool

    save a png image of the stripe extraction overlaid against data

    hands_onbool

    if true, use gui-based timing

    cdf_min0-1 float

    minimim in cumulative distribution function at which we threshold the image to extract a stripe/feature

    cdf_max0-1 float

    maximum in cumulative distribution function at which we threshold the image to extract a stripe/feature

    optimize_transbool

    allow translations (but not rotations) of the stripe in optimization

    timelineLabel : optional char, default=Runt timelineLeadingTrailing : ‘leading’ or ‘trailing’, default=leading sigmastep : optional char refDir : optional char

Returns

  • Saves to disk

  • ————-

NPMitchell 2020-2022

Indices and tables#