How To: Measure Colony Size and Intensity

Extract area, perimeter, circularity, and intensity statistics from detected colonies using MeasureSize, MeasureShape, and MeasureIntensity.

import phenotypic as pht
from phenotypic.data import load_yeast_plate
from phenotypic.enhance import GaussianBlur, CLAHE
from phenotypic.detect import OtsuDetector
from phenotypic.measure import MeasureSize, MeasureShape, MeasureIntensity

pipeline = pht.ImagePipeline(
    ops=[GaussianBlur(sigma=2.0), CLAHE(clip_limit=0.01), OtsuDetector()],
    meas=[MeasureSize(), MeasureShape(), MeasureIntensity()],
)
df = pipeline.apply_and_measure(load_yeast_plate())

Size Metrics

df[["Size_Area", "Size_IntegratedIntensity"]].describe()

	Size_Area	Size_IntegratedIntensity
count	9.000000	9.000000
mean	13022.000000	7611.638046
std	7822.634291	4614.804011
min	1.000000	0.417128
25%	13265.000000	7496.736623
50%	15974.000000	9187.353835
75%	17006.000000	9988.807077
max	22337.000000	13087.327242

Shape Metrics

df[["Shape_Circularity", "Shape_Solidity", "Shape_Eccentricity"]].describe()

	Shape_Circularity	Shape_Solidity	Shape_Eccentricity
count	7.000000	7.000000	9.000000
mean	0.645563	35.970507	0.216800
std	0.067261	3.078440	0.127882
min	0.510927	32.051948	0.000000
25%	0.637557	34.176161	0.214815
50%	0.654747	36.115014	0.265906
75%	0.674367	36.926526	0.281954
max	0.729419	41.421217	0.338132

Intensity Metrics

df[["Intensity_MeanIntensity", "Intensity_MedianIntensity", "Intensity_StandardDeviationIntensity"]].describe()

	Intensity_MeanIntensity	Intensity_MedianIntensity	Intensity_StandardDeviationIntensity
count	9.000000	9.000000	9.000000
mean	0.550580	0.557417	0.031153
std	0.066774	0.070707	0.017925
min	0.417128	0.417128	0.000000
25%	0.565152	0.574650	0.035816
50%	0.575144	0.582211	0.037242
75%	0.585904	0.595740	0.042424
max	0.611042	0.622127	0.044072

The DataFrame has one row per colony. Filter, sort, and group using standard pandas operations to answer biological questions.