def compute_features()

in imaging/src/radiomics_utils.py [0:0]

• 16 lines of code
• 3 McCabe index (conditional complexity)

def compute_features(imageName, maskName):
    extractor = featureextractor.RadiomicsFeatureExtractor()
    featureVector = extractor.execute(imageName, maskName)
    
    new_dict={}
    for featureName in featureVector.keys():
        print("Computed %s: %s" % (featureName, featureVector[featureName]))
        print(type(featureVector[featureName]))
        if isinstance(featureVector[featureName], np.ndarray):
            new_dict[featureName]=float(featureVector[featureName])
        else:
            new_dict[featureName]=featureVector[featureName]
            
    df=pd.DataFrame.from_dict(new_dict, orient='index').T
    df=df.convert_dtypes(convert_integer=False)
    df['imageName']=imageName
    df['maskName']=maskName

    return df