def compareEdgeLengthsBetweenShapes(drift):
"""
returns the average edge length for the control set and the drift set
for a variable drift
"""
control, test = patientGen.patientList(drift)
t = 0
c = 0
for shape in control:
c += shape.frameLength()
for shape in test:
t += shape.frameLength()
return (t / len(control), c / len(test))
def differencesBetweenLandmarksOverTime(drift="a", kwarg=None):
"""
takes a variable drift and generates the control and test patient set
then calculates the differences between each landmark and returns a difference vector.
"""
before, after = patientGen.patientList(drift, kwarg)
diff = []
x = before[0].x.shape[0] * len(before)
y = before[0].x.shape[1]
for eachB, eachA in zip(before, after):
diff.append(eachB.x - eachA.x)
diff = np.array(diff).reshape(x, y)
return diff
def EDMA():
drift = 0.2
control, test = patientGen.patientList(drift)
aveCont = euclideanDistanceMatrix( coordinateWiseAverageOfShapes(control) )
aveTest = euclideanDistanceMatrix( coordinateWiseAverageOfShapes(test) )
D, Dbar = averageFormDifferenceMatrix(aveCont,aveTest)
T4 = fourTtest(D, Dbar)
T4s = bootstrappingTheNullDistribution(control,test)
print "Our T4: %s" %T4
print "The random permuation distribution: %s" %np.mean(T4s)
plt.clf()
fig = plt.hist(T4s)
ymax = max(np.histogram(T4s)[0])
plt.plot((T4, T4), (0, ymax*1.15), 'k-')
plt.title("EDMA with drift %s and sigma: 0.1"%drift)
plt.show()
