Aivia Software
Advanced Measurement Functions
- Aiden Maloney-Bertelli (Unlicensed)
Advanced Measurement Functions can be used to define custom measurements for your analysis results through the Advanced Measurements interface, which is accessed from the Spreadsheet.
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Table of Advanced Measurement Functions
Function Name(Input 1, Input 2,...) | Description |
|---|---|
ClassificationNodeIndex() | When RTree is applied, this outputs the node index which decided classification |
ClassificationValue() | Retrieves the first instance of classification defined for the object |
ClassificationGroup() | Retrieves the classification group the object belongs to |
NoveltyScore() | Retrieves the novelty score, if it exists, for the object |
ClassConfidenceScore() | Retrieves the confidence score for the object being in the assigned class, if it exists |
MaxOverTime(Track Measurement) | Retrieves the maximum value of the given input |
MaxToCurrent(Track Measurement) | Retrieves the maximum value of the given input from the beginning to the current frame being processed |
MinOverTime(Track Measurement) | Retrieves the minimum value of the given input |
MinToCurrent(Track Measurement) | Retrieves the minimum value of the given input from the beginning to the current frame being processed |
Sum(Track Measurement) | Calculates the sum of the given input measurement |
SumToCurrent(Track Measurement) | Calculates the sum value of the given input measurement from the beginning to the current frame being processed |
Average(Track Measurement) | Calculates the average of the given input measurement |
Average(Track Measurement, End T Frame) | Calculates the average of the given input measurement from the beginning of the measurement data to the defined static time frame |
Average(Track Measurement, Start T Frame, End T Frame) | Calculates the average of the given input measurement between the two (2) given static time frames |
AverageToCurrent(Track Measurement) | Calculates the average value of the given input measurement from the beginning to the current frame being processed |
AverageOverTime(Track Measurement, Window Length Backwards, Window Length Forwards) | Calculates the average of the given input measurement between the two (2) defined value offsets from the current frame being processed (windowing around the center frame) |
Mode(Track Measurement) | Calculates the mode of the given input measurement |
Mode(Track Measurement, End T Frame) | Calculates the mode of the given input measurement from the beginning of the measurement data to the defined static time frame |
Mode(Track Measurement, Start T Frame, End T Frame) | Calculates the mode of the given input measurement between the two (2) given static time frames |
ModeToCurrent(Track Measurement) | Calculates the mode value of the given input measurement from the beginning to the current frame being processed |
ModeOverTime(Track Measurement, Window Length Backwards, Window Length Forwards) | Calculates the mode of the given input measurement between the two (2) defined value offsets from the current frame being processed (windowing around the center frame) |
Median(Track Measurement) | Calculates the median of the given input measurement |
Median(Track Measurement, End T Frame) | Calculates the median of the given input measurement from the beginning of the measurement data to the defined static time frame |
Median(Track Measurement, Start T Frame, End T Frame) | Calculates the median of the given input measurement between the two (2) given static time frames |
MedianToCurrent(Track Measurement) | Calculates the median value of the given input measurement from the beginning to the current frame being processed |
MedianOverTime(Track Measurement, Window Length Backwards, Window Length Forwards) | Calculates the median of the given input measurement between the two (2) defined value offsets from the current frame being processed (windowing around the center frame) |
StandardDeviation(Track Measurement) | Calculates the standard deviation of the given input measurement |
StandardDeviation(Track Measurement, End T Frame) | Calculates the standard deviation of the given input measurement from the beginning of the measurement data to the defined static time frame |
StandardDeviation(Track Measurement, Start T Frame, End T Frame) | Calculates the standard deviation of the given input measurement between the two (2) given static time frames |
StandardDeviationToCurrent(Track Measurement) | Calculates the standard deviation value of the given input measurement from the beginning to the current frame being processed |
StandardDeviationOverTime(Track Measurement, Window Length Backwards, Window Length Forwards) | Calculates the standard deviation of the given input measurement between the two (2) defined value offsets from the current frame being processed (windowing around the center frame) |
Max(Value 1, Value 2) | Retrieves the maximum of the two (2) defined values |
Min(Value 1, Value 2) | Retrieves the minimum of the two (2) defined values |
PI() | Retrieves the defined value of π (3.14159265358979323846) |
E() | Retrieves the defined value of e (2.7182818284590452354) |
Ceiling(Value) | Returns the smallest integral value that is greater than or equal to the specified number |
Floor(Value) | Returns the largest integer less than or equal to the specified number |
Sin(Value) | Returns the sine of the specified angle |
Cos(Value) | Returns the cosine of the specified angle |
Tan(Value) | Returns the tangent of the specified angle |
Sinh(Value) | Returns the hyperbolic sine of the specified angle |
Cosh(Value) | Returns the hyperbolic cosine of the specified angle |
Tanh(Value) | Returns the hyperbolic tangent of the specified angle |
Asin(Value) | Returns the angle whose sine is the specified number |
Acos(Value) | Returns the angle whose cosine is the specified number |
Atan(Value) | Returns the angle whose tangent is the specified number |
Atan2(y, x) | Returns the angle whose tangent is the quotient of the two (2) specified numbers |
Sqrt(Value) | Returns the square root of the specified number |
Ln(Value) | Returns the natural (base e) logarithm of the specified number |
Log(Value, Base) | Returns the logarithm of the specified number in the specified base |
Log(Value) | Returns the base 10 logarithm of the specified number |
Exp(Value) | Returns e raised to the specified power |
Abs(Value) | Returns the absolute value of the given input |
RelationCount() | Returns the number of objects that are related to the tracked object |
RelationCount(Related Object Set) | Returns the number of objects that are related to the tracked object from the specified object set |
RelationCountAtFrame() | Returns the number of objects that are related to the object on any given frame, excluding objects related through lineage |
RelationCountAtFrame(Related Object Set) | Returns the number of objects that are related to the object from the specified object set on any given frame, excluding objects related through lineage |
RelatedObjects(Statistic Type, Measurement to Summarize) | Calculates the statistical type on the related objects |
RelatedObjects(Statistic Type, Measurement to Summarize, Related Object Set) | Calculates the statistical type on the related objects which are from the specified, related object set |
RelatedSecondaryObjects(Statistic Type, Measurement to Summarize, Related Object Set) | Calculates the statistical type on the related objects which are from the related object set; the primary related objects are the ones which are statistically grouped |
Pearsons(Channel A, Channel B) | Calculates the Pearson's correlation coefficient |
PearsonsUnderMask(Channel A, Channel B) | Calculates the Pearson's correlation coefficient in the area defined by the objects in the set |
PearsonsUnderMaskPerObject(Channel A, Channel B) | Calculates the Pearson's correlation coefficient in the area defined by the objects in the set |
PearsonsWholeImageIntersection(Channel A, Channel B, Related Object Set) | Calculates the Pearson's correlation coefficient in the area defined by the objects in set A intersected with their relations in set B |
PearsonsPerObjectIntersection(Channel A, Channel B, Related Object Set) | Calculates the Pearson's correlation coefficient in the area defined by the object in set A intersected with related object in set B |
MandersOverlap(Channel A, Channel B) | Calculates the Manders' overlap coefficient |
MandersOverlapUnderMask(Channel A, Channel B) | Calculates the Manders' overlap coefficient in the area defined by the object |
MandersOverlapWholeImageUnderMaskIntersection(Channel A, Channel B, Related Object Set) | Calculates the Manders' overlap coefficient in the area defined by the objects in set A intersecting with related in set B |
MandersOverlapPerObjectUnderMaskIntersection(Channel A, Channel B, Related Object Set) | Calculates the Manders' overlap coefficient in the area defined by the object in set A intersecting with relation in set B |
MandersOverlayTMPerObject(Channel A, Related Object Set) | Calculates Manders' TM value: sum of intersected intensity on channel A divided by sum of intensity on channel A |
MandersOverlapTM(Channel A, Related Object Set) | Calculates Manders' TM value: sum of objects' intersected intensities on channel A divided by sum of objects' intensities on channel A |
Count() | Returns the number of objects |
TrackCount() | Returns the number of track objects |
DendriteCount() | Returns the number of dendrite objects |
SpineCount() | Returns the number of spine objects |
HeadCount() | Returns the number of head objects |
MeanDistance() | Returns average distance to all other objects in the set using the bounding box xyz location |
MaxDistance() | Returns the greatest distance to all other objects in the set using the bounding box xyz location |
MinDistance() | Returns the smallest distance to all other objects in the set using the bounding box xyz location |
SummaryNoParent(Statistic Type, Measurement) | Returns the smallest distance to all other objects in the set using the bounding box xyz location |
Summary(Statistic Type, Measurement) | Uses all objects frame by frame to calculate the input statistic type of the input measurement |
SummarySingleValue(Measurement) | Returns the value input but on the Summary tab of the Spreadsheet |
SummaryMultiValue(Measurement) | Returns the value input for the current time frame but on the Summary tab of the Spreadsheet |
IndexOf(Value to Find, Series to Search) | Returns the index in the domain of the series to search in which the value is first found; returns NaN if value is not found |
IndexOf(Value to Find, Tolerance, Series to Search) | Returns the index in the domain of the series to search in which the value is first found within the defined tolerance range; returns NaN if value is not found |
ValueAtIndex(Series to Search, Index of Value) | Returns the value at the given index in the series provided; returns NaN if out of range |
ValueAtFrame(Series to Search, Frame of Value) | Returns the value at the given frame in the series provided; returns NaN if out of range |
FrameOfClosest(Value to Find, Series to Search) | Returns the frame in which the difference between the value at that frame and the value to find is the smallest; returns NaN if value is not found |
FrameOf(Value to Find, Series to Search) | Returns the frame in which the value is first found; returns NaN if value is not found |
FrameOf(Value to Find, Tolerance, Series to Search) | Returns the frame in which the value is first found within the defined tolerance range; returns NaN if value is not found |
DeltaT() | Returns the time calibration of the image |
XResolution() | Returns the X calibration of the image |
YResolution() | Returns the Y calibration of the image |
ZResolution() | Returns the Z calibration of the image |
ImageHeight() | Returns the height of the image/field |
ImageWidth() | Returns the width of the image/field |
ImageDepth() | Returns the Z depth of the image/field |
ImageVolume() | Returns the calibrated volume of the image |
ImageArea() | Returns the calibrated area of the image |
Statistic Type Inputs
For Statistic Type inputs, the following options are available:
Total
Mean
Maximum
Minimum
Median
Variance
StdDev
Example: Summary(Mean, [Area (channel 1)])