def test_lineFunction(self):
x = range(10)
y = range(10)
plt.scatter(x,y)
params = CurveFit.getParamsAfterFittingData(x, y, CurveFit.lineFunction, [1., 1.])
plt.plot(x, CurveFit.getYValues(CurveFit.lineFunction, params, x))
plt.show()
def test_lineFunction(self):
x = range(10)
y = range(10)
plt.scatter(x, y)
params = CurveFit.getParamsAfterFittingData(x, y,
CurveFit.lineFunction,
[1., 1.])
plt.plot(x, CurveFit.getYValues(CurveFit.lineFunction, params, x))
plt.show()
def test_curveFitdemo(self):
real = lambda p, x: p[0] * scipy.exp(-((x-p[1])/p[2])**2) + scipy.rand(100)
functionToFit = lambda p, x: p[0] * scipy.exp(-((x-p[1])/p[2])**2)
initialParameters = [5., 7., 3.]
dataX = scipy.linspace(0, 10, 100)
dataY = real(initialParameters, dataX)
cf = CurveFit(functionToFit, initialParameters, dataX, dataY)
cf.estimate()
cf.plot()
def test_curveFitdemo(self):
real = lambda p, x: p[0] * scipy.exp(-(
(x - p[1]) / p[2])**2) + scipy.rand(100)
functionToFit = lambda p, x: p[0] * scipy.exp(-((x - p[1]) / p[2])**2)
initialParameters = [5., 7., 3.]
dataX = scipy.linspace(0, 10, 100)
dataY = real(initialParameters, dataX)
cf = CurveFit(functionToFit, initialParameters, dataX, dataY)
cf.estimate()
cf.plot()
def test_exponentialFunctions(self):
x, p = 85079, [ 1.09194452e+03, 1.03448106e+00]
self.assertTrue(x==int(CurveFit.inverseOfDecreasingExponentialFunction(p, CurveFit.decreasingExponentialFunction(p, x))))
self.assertTrue(x==int(CurveFit.inverseOfIncreasingExponentialFunction(p, CurveFit.increasingExponentialFunction(p, x))))
