neuro_dot.Visualizations

Module Contents

Functions

adjust_brain_pos(meshL, meshR[, params])	ADJUST_BRAIN_POS Repositions mesh orientations for display.
applycmap(overlay, underlay, params)	APPLYCMAP Performs color mapping and fuses images with anatomical models.
DrawColoredSynchPoints(info_in, subplt[, SPfr])	DRAWCOLOREDSYNCHPOINTS Draws vertical lines over a plot/imagesc type axis to delineate synchronization points on time traces.
nlrGrayPlots_220324(nlrdata, info[, mode])	NLRGRAYPLOTS_220324 This function generates a gray plot figure for measurement pairs
PlotInterpSurfMesh(volume, meshL, meshR, dim, params)	PLOTINTERPSURFMESH Interpolates volumetric data onto hemispheric meshes for display.
Plot_RawData_Cap_DQC(data, info_in[, params])	PLOT_RAWDATA_CAP_DQC Generates plots of cap data quality.
defineticks(start, end, steps[, blankLabels])	DEFINETICKS Defines tick marks based on a start point, end point, and step size.
PlotFalloffData(fall_data, separations[, params, ax])	PLOTFALLOFFDATA A basic falloff plotting function.
PlotFalloffLL(data, info[, params, ax])	PLOTFALLOFFLL A light-level falloff visualization.
PlotLRMeshes(meshL, meshR, params)	PLOTLRMESHES Renders a pair of hemispheric meshes.
Plot_RawData_Metrics_I_DQC(data, info[, params])	PLOT_RAWDATA_METRICS_I_DQC Generates a single-page data quality report including various metrics of the raw data quality.
Plot_RawData_Metrics_II_DQC(data, info[, params])	PLOT_RAWDATA_METRICS_II_DQC Generates a single-page data quality report including various metrics of the raw data quality.
Plot_RawData_Time_Traces_Overview(data, info_in[, params])	PLOT_RAWDATA_TIME_TRACES_OVERVIEW Generates a plot of raw data time traces.
cylinder(r[, h, a, nt, nv])	CYLINDER Parameterizes the cylinder of radius r, height h, and base point a.
PlotCapData(SrcRGB, DetRGB, info[, fig_axes, params])	PLOTCAPDATA A basic plotting function for generating and labeling cap grids.
PlotCapGoodMeas(info[, fig_axes, params])	PLOTCAPGOODMEAS A "Good Measurements" visualization overlaid on a cap grid.
PlotCapMeanLL(data, info[, fig_axes, params])	PLOTCAPMEANLL A visualization of mean light levels overlaid on a cap
PlotCapPhysiologyPower(data, info[, fig_axes, params])	PLOTCAPPHYSIOLOGYPOWER A visualization of band limited power OR band-referenced SNR for each optode.
PlotSlices_correct_orientation(m)	PLOTSLICES_CORRECT_ORIENTATION Used in PlotSlices to transpose the dimension, given by "m".
PlotSlices(underlay[, infoVol, params, overlay])	PLOTSLICES Creates an interactive 3D plot, including transverse, sagittal, and coronal slices.
PlotSlicesTimeTrace(underlay[, infoVol, params, ...])	PLOTSLICESTIMETRACE Creates an interactive 4D plot, including transverse, sagittal, and coronal slices, in addition to a voxel time trace.
PlotTimeTraceData(data, time[, params, fig_axes, ...])	PLOTTIMETRACEDATA A basic time traces plotting function.
vol2surf_mesh(Smesh, volume, dim[, params])	VOL2SURF_MESH Interpolates volumetric data onto a surface mesh.

neuro_dot.Visualizations.adjust_brain_pos(meshL, meshR, params=None)

ADJUST_BRAIN_POS Repositions mesh orientations for display.

[Lnodes, Rnodes] = ADJUST_BRAIN_POS(meshL, meshR) takes the left and right hemispheric meshes “meshL” and “meshR”, respectively, and repositions them to the proper perspective for display.

[Lnodes, Rnodes] = ADJUST_BRAIN_POS(meshL, meshR, params) allows the user to specify parameters for plot creation.

Params:

ctx:

Defines inflation of mesh. std: standard pial mesh Default inf: inflated mesh vinf: very inflated mesh flat: flat mesh

orientation:

Select orientation of volume. t: transverse Default s: for sagittal

view:

Sets the view perspective. lat: lateral view Default post: posterior view dorsal: dorsal view

Dependencies: ROTATE_CAP, ROTATION_MATRIX.

See Also: PLOTLRMESHES.

neuro_dot.Visualizations.applycmap(overlay, underlay, params)

APPLYCMAP Performs color mapping and fuses images with anatomical models.

mapped = APPLYCMAP(overlay) fuses the N-D image array “overlay” with a default flat gray background and applies a number of other default settings to create a scaled and colormapped N-D x 3 RGB image array “mapped”.

mapped = APPLYCMAP(overlay, underlay) fuses the image array “overlay” with the anatomical atlas volume input “underlay” as the background.

mapped = APPLYCMAP(overlay, underlay, params) allows the user to specify parameters for plot creation.

Params:

TC:

Direct map integer data values to defined color map (“True Color”). Default Value: 0

DR:

Dynamic range. Default Value: 1000

Scale:

Maximum value to which image is scaled. Default Value: 90% max

PD:

If PD = 1, Sets the entirety of the colormap to run from zero to the Scale value. If PD = 0, Colormap is centered around zero. Default Value: 0

BG:

Background color, as an RGB triplet. Default Value: [0.5, 0.5, 0.5]

Saturation:

Sets the transparency of the colors. Size: equal to the size of the data. Must be within range [0, 1]. Default Value: none

Cmap.P:

Colormap for positive data values. Default Value: jet

Cmap.N:

Colormap for negative data values. Default Value: none

Cmap.flipP:

Logical, flips the positive colormap. Default Value: 0

Cmap.flipN:

Logical, flips the negative colormap. Default Value: 0

Th.P:

Value of min threshold to display positive data values. Default Value: 25% max

Th.N:

Value of max threshold to display negative data values. Default Value: -Th.P

returns:

mapped, map_out, params

See Also: PLOTSLICES, PLOTINTERPSURFMESH, PLOTLRMESHES, PLOTCAPMEANLL.

neuro_dot.Visualizations.DrawColoredSynchPoints(info_in, subplt, SPfr=0)

DRAWCOLOREDSYNCHPOINTS Draws vertical lines over a plot/imagesc type axis to delineate synchronization points on time traces. This function assumes the standard NeuroDOT info structure and paradigm format

Info:

info.paradigm:

Contains all paradigm timing information

info.paradigm.synchpts:

Contains sample points corresponding to stimulus time points of interest (e.g. onsets, rest, etc.)

info.paradigm.synchtype:

Optional field that contains a marker to distinguish between synchronization types, traditionally as sound boops of differing frequencies, i.e., 25, 30, 35 (Hz).

info.paradigm.Pulse_1:

Indices of synchpts that denote ‘bookends’ of data collection as well as resting (or OFF) periods of a given stimulus.

info.paradigm.Pulse_2:

Indices of synchpts that correspond to the start of a given stimulus epoch (e.g., the start of a flickering checkerboard)

info.paradigm.Pulse_3:

Indices of synchpts of a 2nd stimulus type

info.paradigm.Pulse_4:

Indices of synchpts of a 3rd stimulus type

The 2nd input, SPfr, selects whether or not to adjust synchpoint timing based on framerate of data. (Default=0).

neuro_dot.Visualizations.nlrGrayPlots_220324(nlrdata, info, mode='auto')

NLRGRAYPLOTS_220324 This function generates a gray plot figure for measurement pairs using only clean data from wavelength 2. Input data “nlrdata” is assumed to be filtered and resampled. The data is grouped into info.pairs.r2d<20, 20<=info.pairs.r2d<30, and 30<=info.pairs.r2d<40.

neuro_dot.Visualizations.PlotInterpSurfMesh(volume, meshL, meshR, dim, params)

PLOTINTERPSURFMESH Interpolates volumetric data onto hemispheric meshes for display.

PLOTINTERPSURFMESH(volume, meshL, meshR, dim) takes functional imaging data “volume” and interpolates it onto the left and right hemispheric surface meshes given in “meshL” and “meshR”, respectively, using the spatial information in “dim”. The result is a bilateral sagittal view of the activations overlain onto the surface of the brain represented by the meshes.

PLOTINTERPSURFMESH(volume, meshL, meshR, dim, params) allows the user to specify parameters for plot creation.

Params:

Scale:

(90% max) Maximum value to which image is scaled.

Th.P:

(25% max) Value of min threshold to display positive data values.

Th.N:

(-Th.P) Value of max threshold to display negative data values.

Dependencies: VOL2SURF_MESH, PLOTLRMESHES, ADJUST_BRAIN_POS, ROTATE_CAP, ROTATION_MATRIX.

See Also: PLOTSLICES.

neuro_dot.Visualizations.Plot_RawData_Cap_DQC(data, info_in, params=None)

PLOT_RAWDATA_CAP_DQC Generates plots of cap data quality.

Includes: Relative average light levels for 2 sets of distances of source-detector measurements, the cap good measurements plot, and a measure of the pulse power at each optode location.

neuro_dot.Visualizations.defineticks(start, end, steps, blankLabels=False)

DEFINETICKS Defines tick marks based on a start point, end point, and step size.

See: PLOT_RAWDATA_METRICS_I_DQC

neuro_dot.Visualizations.PlotFalloffData(fall_data, separations, params=None, ax=None)

PLOTFALLOFFDATA A basic falloff plotting function.

PLOTFALLOFFDATA(data, info) takes one input array “fall_data” and plots it against another “separations” to create a falloff plot.

PLOTFALLOFFDATA(data, info, params) allows the user to specify parameters for plot creation.

h = PLOTFALLOFFDATA(…) passes the handles of the plot line objects created.

Params:

fig_size:

[200, 200, 560, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

xlimits:

‘auto’ Limits of x-axis.

xscale:

‘linear’ Scaling of x-axis.

ylimits:

‘auto’ Limits of y-axis.

yscale:

‘log’ Scaling of y-axis.

See Also: PLOTFALLOFFLL.

neuro_dot.Visualizations.PlotFalloffLL(data, info, params=None, ax=None)

PLOTFALLOFFLL A light-level falloff visualization.

PLOTFALLOFFLL(data, info) takes a light-level array “data” of the MEAS x TIME format, and generates a plot of each channel’s temporal mean against its source-detector distance, in the specified groupings.

PLOTFALLOFFLL(data, info, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[200, 200, 560, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

dimension:

‘2D’ Dimension of pair radii used.

rlimits:

(all R2D) Limits of pair radii displayed.

Nnns:

(all NNs) Number of NNs displayed.

Nwls:

(all WLs) Number of WLs displayed.

useGM:

0 Use Good Measurements.

xlimits:

[0, 60] Limits of x-axis.

xscale:

‘linear’ Scaling of x-axis.

ylimits:

[1e-6, 1e1] Limits of y-axis.

yscale:

‘log’ Scaling of y-axis.

Dependencies: PLOTFALLOFFDATA

neuro_dot.Visualizations.PlotLRMeshes(meshL, meshR, params)

PLOTLRMESHES Renders a pair of hemispheric meshes.

PLOTLRMESHES(meshL, meshR) renders the data in a pair of left and right hemispheric meshes “meshL.data” and “meshR.data”, respectively, and applies full color mapping to them. If no data is present for either mesh, a default gray mesh will be plotted.

PLOTLRMESHES(meshL, meshR, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[20, 200, 960, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

Scale:

(90% max) Maximum value to which image is scaled.

PD:

0 Declares that input image is positive definite.

cblabels:

([-90% max, 90% max]) Colorbar axis labels. Min defaults to 0 if PD==1, both default to +/- Scale if supplied.

cbticks:

(none) Specifies positions of tick marks on colorbar axis.

alpha:

1. Transparency of mesh.

view:

‘lat’ Sets the view perspective.

Dependencies: ADJUST_BRAIN_POS, ROTATE_CAP, ROTATION_MATRIX, APPLYCMAP.

See Also: PLOTINTERPSURFMESH, VOL2SURF_MESH.

neuro_dot.Visualizations.Plot_RawData_Metrics_I_DQC(data, info, params=None)

PLOT_RAWDATA_METRICS_I_DQC Generates a single-page data quality report including various metrics of the raw data quality. Light fall off as a function of Rsd, SNR plots vs. mean light level, Source-detector mean light-level plots, Power spectra for 830nm at 2 Rsd, and Histogram for measurement noise.

neuro_dot.Visualizations.Plot_RawData_Metrics_II_DQC(data, info, params=None)

PLOT_RAWDATA_METRICS_II_DQC Generates a single-page data quality report including various metrics of the raw data quality.

Zoomed raw time traces, Light fall off as a function of Rsd, Power spectra for 830nm at 2 Rsd, and Histogram for measurement noise.

neuro_dot.Visualizations.Plot_RawData_Time_Traces_Overview(data, info_in, params=None)

PLOT_RAWDATA_TIME_TRACES_OVERVIEW Generates a plot of raw data time traces. Time Traces are separated by wavelength (columns). The top row shows time traces for all measurements within a source-detector distance range (defaults as 0.1 - 5.0 cm). The bottom row shows the same measurements but including only measurements passing a variance threshold (default: 0.075) as well as vertical lines corresponding to the stimulus paradigm.

neuro_dot.Visualizations.cylinder(r, h=1, a=0, nt=100, nv=50)

CYLINDER Parameterizes the cylinder of radius r, height h, and base point a.

See: PlotCapData

neuro_dot.Visualizations.PlotCapData(SrcRGB, DetRGB, info, fig_axes=None, params=None)

PLOTCAPDATA A basic plotting function for generating and labeling cap grids.

PLOTCAPDATA(SrcRGB, DetRGB, info) plots the input RGB information in one of three modes:

Modes:

text:

• Optode numbers are arranged in a cap grid and colored with the RGB input.

patch:

• Optodes are plotted as patches and colored with the RGB input.

textpatch:

• Optodes are plotted as patches and colored with the RGB input, with optode numbers overlain in white.

PLOTCAPDATA(SrcRGB, DetRGB, info, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[20, 200, 1240, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

dimension:

‘2D’ Specifies either a 2D or 3D plot rendering.

mode:

‘textpatch’ Display mode.

See Also: PLOTCAP, PLOTCAPGOODMEAS, PLOTCAPMEANLL.

neuro_dot.Visualizations.PlotCapGoodMeas(info, fig_axes=None, params=None)

PLOTCAPGOODMEAS A “Good Measurements” visualization overlaid on a cap grid.

PLOTCAPGOODMEAS(info) plots a visualization of the Good Measurements determined by FINDGOODMEAS and arranges them based on the metadata in “info.optodes”. Good channels are depicted as green lines, bad channels red lines; sources and detectors are given lettering in light blue and red.

The plot title provides tallies for all specified groupings. The next line of the title lists how many optodes for which only 33% of their measurements are good. These optodes are surrounded with white circles.

PLOTCAPGOODMEAS(info, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[20, 200, 1240, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

dimension:

‘2D’ Specifies either a 2D or 3D plot rendering.

rlimits:

(all R2D) Limits of pair radii displayed.

Nnns:

(all NNs) Number of NNs displayed.

Nwls:

(all WLs) Number of WLs averaged and displayed.

mode:

‘good’ Display mode. ‘good’ displays channels above noise threhsold, ‘bad’ below.

Dependencies: PLOTCAPDATA, ISTABLEVAR.

See Also: FINDGOODMEAS, PLOTCAP, PLOTCAPMEANLL.

neuro_dot.Visualizations.PlotCapMeanLL(data, info, fig_axes=None, params=None)

PLOTCAPMEANLL A visualization of mean light levels overlaid on a cap grid.

PLOTCAPMEANLL(data, info) plots an intensity map of the mean light levels for specified measurement groupings of each optode on the cap and arranges them based on the metadata in “info.optodes”.

PLOTCAPMEANLL(data, info, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[20, 200, 1240, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

dimension:

‘2D’ Specifies either a 2D or 3D plot rendering.

rlimits:

(all R2D) Limits of pair radii displayed.

Nnns:

(all NNs) Number of NNs displayed.

Nwls:

(all WLs) Number of WLs averaged and displayed.

useGM:

0 Use Good Measurements.

Cmap.P:

‘hot’ Default color mapping.

Dependencies: PLOTCAPDATA, ISTABLEVAR, APPLYCMAP.

See Also: PLOTCAP, PLOTCAPGOODMEAS.

neuro_dot.Visualizations.PlotCapPhysiologyPower(data, info, fig_axes=None, params=None)

PLOTCAPPHYSIOLOGYPOWER A visualization of band limited power OR band-referenced SNR for each optode.

Params:

fig_size:

[20, 200, 1240, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

dimension:

‘2D’ Specifies either a 2D or 3D plot rendering.

rlimits:

(all R2D) Limits of pair radii displayed.

Nnns:

(all NNs) Number of NNs displayed.

Nwls:

(all WLs) Number of WLs averaged and displayed.

useGM:

0 Use Good Measurements.

Cmap.P:

‘hot’ Default color mapping.

Dependencies: PLOTCAPDATA, ISTABLEVAR, APPLYCMAP.

See Also: PLOTCAP, PLOTCAPGOODMEAS.

neuro_dot.Visualizations.PlotSlices_correct_orientation(m)

PLOTSLICES_CORRECT_ORIENTATION Used in PlotSlices to transpose the dimension, given by “m”.

neuro_dot.Visualizations.PlotSlices(underlay, infoVol=None, params=None, overlay=None)

PLOTSLICES Creates an interactive 3D plot, including transverse, sagittal, and coronal slices.

PLOTSLICES(underlay) takes a 3D voxel space image “underlay” and generates views along the three canonical axes.

In interactive mode, left-click on any point to move to those slices. To reset to the middle of the volume, right-click anywhere. To cancel interactive mode, press “Q”, “Esc”, or the middle mouse button.

PLOTSLICES(underlay, infoVol) uses the volumetric data in “infoVol” to display spatial coordinates of the slices in question.

PLOTSLICES(underlay, infoVol, params) allows the user to specify parameters for plot creation.

Params:

fig_size:

[20, 200, 1240, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

CH:

1 Turns crosshairs on (1) and off (0).

Scale:

(90% max) Maximum value to which image is scaled.

PD:

0 Declares that input image is positive definite.

cbmode:

0 Specifies whether to use custom colorbar axis labels.

cboff:

0 If set to 1, no colorbar is displayed

cblabels:

([-90% max, 90% max]) Colorbar axis labels. When cbmode==1, min defaults to 0 if PD==1, both default to +/- Scale if supplied. When cbmode==0, then cblabels dictates colorbar axis limits.

cbticks:

(none) When cbmode==1, specifies positions of tick marks on colorbar axis.

slices:

(center frames) Select which slices are displayed. If empty, activates interactive navigation.

slices_type:

‘idx’ Use MATLAB indexing (‘idx’) for slices, or spatial coordinates (‘coord’) as provided by invoVol.

orientation:

‘t’ Select orientation of volume. ‘t’ for transverse, ‘s’ for sagittal.

Note: APPLYCMAP has further options for using “params” to specify parameters for the fusion, scaling, and colormapping process.

PLOTSLICES(underlay, infoVol, params, overlay) overlays the image provided by “overlay”. When this is done, all color mapping is applied to the overlay image, and the underlay is rendered as a grayscale image times the RGB triplet in “params.BG”.

Dependencies: APPLYCMAP.

See Also: PLOTINTERPSURFMESH, PLOTSLICESMOV, PLOTSLICESTIMETRACE.

neuro_dot.Visualizations.PlotSlicesTimeTrace(underlay, infoVol=None, params=None, overlay=None, info=None)

PLOTSLICESTIMETRACE Creates an interactive 4D plot, including transverse, sagittal, and coronal slices, in addition to a voxel time trace.

PLOTSLICESTIMETRACE(underlay, infoVol, params, overlay) uses the same basic inputs as the function PLOTSLICES to create an interactive 3-axis plot of a 4D volume, plus an axis for the time trace of the selected voxel.

PLOTSLICESTIMETRACE(…, info) allows the user to input an “info” structure to provide information about the 4D volume’s native framerate. The default framerate is 1 Hz.

Params:

fig_size:

[20, 200, 840, 720] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

CH:

1 Turns crosshairs on (1) and off (0).

Scale:

(90% max) Maximum value to which image is scaled.

PD:

0 Declares that input image is positive definite.

cbmode:

0 Specifies whether to use custom colorbar axis labels.

cblabels:

([-90% max, 90% max]) Colorbar axis labels. When cbmode==1, min defaults to 0 if PD==1, both default to +/- Scale if supplied. When cbmode==0, then cblabels dictates colorbar axis limits.

cbticks:

(none) When cbmode==1, specifies positions of tick marks on colorbar axis.

slices:

(center frames) Select which slices are displayed. If empty, activates interactive navigation.

slices_type:

‘idx’ Use MATLAB indexing (‘idx’) for slices, or spatial coordinates (‘coord’) as provided by invoVol.

orientation:

‘t’ Select orientation of volume. ‘t’ for transverse, ‘s’ for sagittal.

kernel:

[1] A sampling kernel for the time trace plot. Other options: ‘gaussian’ | ‘cube’ | ‘sphere’.

Note: APPLYCMAP has further options for using “params” to specify parameters for the fusion, scaling, and colormapping process.

Dependencies: APPLYCMAP.

See Also: PLOTINTERPSURFMESH, PLOTSLICES.

neuro_dot.Visualizations.PlotTimeTraceData(data, time, params=None, fig_axes=None, coordinates=[1, 1])

PLOTTIMETRACEDATA A basic time traces plotting function.

PLOTTIMETRACEDATA(data, time) takes a light-level array “data” of the MEAS x TIME format, and plots its time traces.

PLOTTIMETRACEDATA(data, time, params) allows the user to specify parameters for plot creation.

h = PLOTTIMETRACEDATA(…) passes the handles of the plot line objects created.

Params:

fig_size:

[200, 200, 560, 420] Default figure position vector.

fig_handle:

(none) Specifies a figure to target. If empty, spawns a new figure.

xlimits:

‘auto’ Limits of x-axis.

xscale:

‘linear’ Scaling of x-axis.

ylimits:

‘auto’ Limits of y-axis.

yscale:

‘linear’ Scaling of y-axis.

See Also: PLOTTIMETRACEALLMEAS, PLOTTIMETRACEMEAN.

neuro_dot.Visualizations.vol2surf_mesh(Smesh, volume, dim, params=None)

VOL2SURF_MESH Interpolates volumetric data onto a surface mesh.

Smesh = VOL2SURF_MESH(mesh_in, volume, dim) takes the mesh “Smesh” and interpolates the values of the volumetric data “volume” at the mesh’s surface, using the spatial information in “dim”. These values are output as “Smesh”.

Smesh = VOL2SURF_MESH(Smesh, volume, dim, params) allows the user to specify parameters for plot creation.

Params:

OL:

0 If “overlap” data is presented (OL==1), this sets the interpolation method to “nearest”. Default is “linear”.

See Also: PLOTINTERPSURFMESH, GOOD_VOX2VOL, AFFINE3D_IMG.