defdap.hrdic module¶

class defdap.hrdic.Map(path, fname, dataType=None)[source]¶

Bases: Map

Class to encapsulate DIC map data and useful analysis and plotting methods.

format¶

Software name.

Type:: str

version¶

Software version.

Type:: str

binning¶

Sub-window size in pixels.

Type:: int

xdim¶

Size of map along x (from header).

Type:: int

ydim¶

Size of map along y (from header).

Type:: int

xc¶

X coordinates.

Type:: numpy.ndarray

yc¶

Y coordinates.

Type:: numpy.ndarray

xd¶

X displacement.

Type:: numpy.ndarray

yd¶

Y displacement.

Type:: numpy.ndarray

corrVal¶

Correlation value.

Type:: numpy.ndarray

ebsdMap¶

EBSD map linked to DIC map.

Type:: defdap.ebsd.Map

ebsdTransform¶

Transform from EBSD to DIC coordinates.

Type:: various

ebsdTransformInv¶

Transform from DIC to EBSD coordinates.

Type:: various

ebsdGrainIds¶

EBSD grain IDs corresponding to DIC map grain IDs.

Type:: list

patternImPath¶

Path to BSE image of map.

Type:: str

plotHomog¶: Map to use for defining homologous points (defaults to plotMaxShear).

highlightAlpha¶

Alpha (transparency) of grain highlight.

Type:: float

bseScale¶

Size of a pixel in the correlated images.

Type:: float

patScale¶

Size of pixel in loaded pattern relative to pixel size of dic data i.e 1 means they are the same size and 2 means the pixels in the pattern are half the size of the dic data.

Type:: float

path¶

File path.

Type:: str

fname¶

File name.

Type:: str

xDim¶

Size of map along x (after cropping).

Type:: int

yDim¶

Size of map along y (after cropping).

Type:: int

self.x_map¶

Map of u displacement component along x.

Type:: numpy.ndarray

self.y_map¶

Map of v displacement component along x.

Type:: numpy.ndarray

f11, f22, f12, f21 ; numpy.ndarray: Components of the deformation gradient, where 1=x and 2=y.

e11, e22, e12

Components of the green strain , where 1=x and 2=y.

Type:: numpy.ndarray

eMaxShear¶

Max shear component np.sqrt(((e11 - e22) / 2.)**2 + e12**2).

Type:: numpy.ndarray

cropDists¶

Crop distances (default all zeros).

Type:: numpy.ndarray

property crystalSym¶

loadData(fileDir, fileName, dataType=None)[source]¶

Load DIC data from file.

Parameters:

fileDir (str) – Path to file.
fileName (str) – Name of file including extension.
dataType (str, {'DavisText'}) – Type of data file.

loadCorrValData(fileDir, fileName, dataType=None)[source]¶

Load correlation value for DIC data

Parameters:

fileDir (str) – Path to file.
fileName (str) – Name of file including extension.
dataType (str, {'DavisImage'}) – Type of data file.

retrieveName()[source]¶: Gets the first name assigned to the a map, as a string

setScale(micrometrePerPixel)[source]¶

Sets the scale of the map.

Parameters:: micrometrePerPixel (float) – Length of pixel in original BSE image in micrometres.

property scale¶: Returns the number of micrometers per pixel in the DIC map.

printStatsTable(percentiles, components)[source]¶

Print out a statistics table for a DIC map

Parameters:

percentiles (list(float)) – list of percentiles to print i.e. 0, 50, 99.
components (list(str)) – list of map components to print i.e. e11, f11, eMaxShear, x_map.

setCrop(xMin=None, xMax=None, yMin=None, yMax=None, updateHomogPoints=False)[source]¶

Set a crop for the DIC map.

Parameters:

xMin (int) – Distance to crop from left in pixels.
xMax (int) – Distance to crop from right in pixels.
yMin (int) – Distance to crop from top in pixels.
yMax (int) – Distance to crop from bottom in pixels.
updateHomogPoints (bool, optional) – If true, change homologous points to reflect crop.

crop(mapData, binned=True)[source]¶

Crop given data using crop parameters stored in map i.e. cropped_data = DicMap.crop(DicMap.data_to_crop).

Parameters:

mapData (numpy.ndarray) – Bap data to crop.
binned (bool) – True if mapData is binned i.e. binned BSE pattern.

setHomogPoint(points=None, display=None, **kwargs)[source]¶

Set homologous points. Uses interactive GUI if points is None.

Parameters:

points (list, optional) – homologous points to set.
display (string, optional) – Use max shear map if set to ‘maxshear’ or pattern if set to ‘pattern’.

linkEbsdMap(ebsdMap, transformType='affine', **kwargs)[source]¶

Calculates the transformation required to align EBSD dataset to DIC.

Parameters:

ebsdMap (defdap.ebsd.Map) – EBSD map object to link.
transformType (str, optional) – affine, piecewiseAffine or polynomial.
kwargs – All arguments are passed to estimate method of the transform.

checkEbsdLinked()[source]¶

Check if an EBSD map has been linked.

Returns:: Returns True if EBSD map linked.
Return type:: bool
Raises:: Exception – If EBSD map not linked.

warpToDicFrame(mapData, cropImage=True, order=1, preserve_range=False)[source]¶

Warps a map to the DIC frame.

Parameters:

mapData (numpy.ndarray) – Data to warp.
cropImage (bool, optional) – Crop to size of DIC map if true.
order (int, optional) – Order of interpolation (0: Nearest-neighbor, 1: Bi-linear…).
preserve_range (bool, optional) – Keep the original range of values.

Returns:

Map (i.e. EBSD map data) warped to the DIC frame.

Return type:

numpy.ndarray

warp_lines_to_dic_frame(lines)[source]¶

Warp a set of lines to the DIC reference frame.

Parameters:: lines (list of tuples) – Lines to warp. Each line is represented as a tuple of start and end coordinates (x, y).
Returns:: List of warped lines with same representation as input.
Return type:: list of tuples

property boundaries¶: Returns EBSD map grain boundaries warped to DIC frame.

property boundaryLines¶

property phaseBoundaryLines¶

generateThresholdMask(mask, dilation=0, preview=True)[source]¶

Generate a dilated mask, based on a boolean array and previews the appication of this mask to the max shear map.

Parameters:

mask (numpy.array(bool)) – A boolean array where points to be removed are True
dilation (int, optional) – Number of pixels to dilate the mask by. Useful to remove anomalous points around masked values. No dilation applied if not specified.
preview (bool) – If true, show the mask and preview the masked effective shear strain map.

Examples

To remove data points in dicMap where eMaxShear is above 0.8, use:

>>> mask = dicMap.eMaxShear > 0.8

To remove data points in dicMap where e11 is above 1 or less than -1, use:

>>> mask = (dicMap.e11 > 1) | (dicMap.e11 < -1)

To remove data points in dicMap where corrVal is less than 0.4, use:

>>> mask = dicMap.corrVal < 0.4

Note: correlation value data needs to be loaded seperately from the DIC map, see defdap.hrdic.loadCorrValData()

applyThresholdMask()[source]¶: Apply mask to all DIC map data by setting masked values to nan.

setPatternPath(filePath, windowSize)[source]¶

Set the path to the image of the pattern.

Parameters:

filePath (str) – Path to image.
windowSize (float) – Size of pixel in pattern image relative to pixel size of DIC data i.e 1 means they are the same size and 2 means the pixels in the pattern are half the size of the dic data.

plotPattern(**kwargs)[source]¶

Plot BSE image of Map. For use with setting homog points.

Parameters:: kwargs – All arguments are passed to defdap.plotting.MapPlot.create().
Return type:: defdap.plotting.MapPlot

plotMap(component, **kwargs)[source]¶

Plot a map from the DIC data.

Parameters:

component – Map component to plot i.e. e11, f11, eMaxShear.
kwargs – All arguments are passed to defdap.plotting.MapPlot.create().

Returns:

Plot containing map.

Return type:

defdap.plotting.MapPlot

plotMaxShear(**kwargs)[source]¶

Plot a map of maximum shear strain.

Parameters:: kwargs – All arguments are passed to defdap.hrdic.plotMap().
Returns:: Plot containing map.
Return type:: defdap.plotting.MapPlot

plotGrainAvMaxShear(**kwargs)[source]¶

Plot grain map with grains filled with average value of max shear. This uses the max shear values stored in grain objects, to plot other data use plotGrainAv().

Parameters:: kwargs – All arguments are passed to defdap.base.Map.plotGrainDataMap().

findGrains(algorithm=None, minGrainSize=10)[source]¶

Finds grains in the DIC map.

Parameters:

algorithm (str {'warp', 'floodfill'}) – Use floodfill or warp algorithm.
minGrainSize (int) – Minimum grain area in pixels for floodfill algorithm.

floodFill(x, y, grainIndex, points_left)[source]¶

Flood fill algorithm that uses the combined x and y boundary array to fill a connected area around the seed point. The points are inserted into a grain object and the grain map array is updated.

Parameters:

x (int) – Seed point x for flood fill
y (int) – Seed point y for flood fill
grainIndex (int) – Value to fill in grain map
points_left (numpy.ndarray) – Boolean map of the points that have not been assigned a grain yet

Returns:

currentGrain – New grain object with points added

Return type:

defdap.hrdic.Grain

runGrainInspector(vmax=0.1, corrAngle=0)[source]¶

Run the grain inspector interactive tool.

Parameters:

vmax (float) – Maximum value of the colour map.
corrAngle (float) – Correction angle in degrees to subtract from measured angles to account for small rotation between DIC and EBSD frames. Approximately the rotation component of affine transform.

class defdap.hrdic.Grain(grainID, dicMap)[source]¶