""" Unit tests for Invertor class """ # Disable "missing docstring" complaint # pylint: disable-msg=C0111 # Disable "too many methods" complaint # pylint: disable-msg=R0904 import unittest, math, numpy, pylab from sans.pr.invertor import Invertor class TestBasicComponent(unittest.TestCase): def setUp(self): self.invertor = Invertor() self.invertor.d_max = 100.0 # Test array self.ntest = 5 self.x_in = numpy.ones(self.ntest) for i in range(self.ntest): self.x_in[i] = 1.0*(i+1) def testset_dmax(self): """ Set and read d_max """ value = 15.0 self.invertor.d_max = value self.assertEqual(self.invertor.d_max, value) def testset_alpha(self): """ Set and read alpha """ value = 15.0 self.invertor.alpha = value self.assertEqual(self.invertor.alpha, value) def testset_x_1(self): """ Setting and reading the x array the hard way """ # Set x self.invertor.x = self.x_in # Read it back npts = self.invertor.get_nx() x_out = numpy.ones(npts) self.invertor.get_x(x_out) for i in range(self.ntest): self.assertEqual(self.x_in[i], x_out[i]) def testset_x_2(self): """ Setting and reading the x array the easy way """ # Set x self.invertor.x = self.x_in # Read it back x_out = self.invertor.x for i in range(self.ntest): self.assertEqual(self.x_in[i], x_out[i]) def testset_y(self): """ Setting and reading the y array the easy way """ # Set y self.invertor.y = self.x_in # Read it back y_out = self.invertor.y for i in range(self.ntest): self.assertEqual(self.x_in[i], y_out[i]) def testset_err(self): """ Setting and reading the err array the easy way """ # Set err self.invertor.err = self.x_in # Read it back err_out = self.invertor.err for i in range(self.ntest): self.assertEqual(self.x_in[i], err_out[i]) def test_iq(self): """ Test iq calculation """ q = 0.11 v1 = 8.0*math.pi**2/q * self.invertor.d_max *math.sin(q*self.invertor.d_max) v1 /= ( math.pi**2 - (q*self.invertor.d_max)**2.0 ) pars = numpy.ones(1) self.assertAlmostEqual(self.invertor.iq(pars, q), v1, 2) def test_pr(self): """ Test pr calculation """ r = 10.0 v1 = 2.0*r*math.sin(math.pi*r/self.invertor.d_max) pars = numpy.ones(1) self.assertAlmostEqual(self.invertor.pr(pars, r), v1, 2) def test_getsetters(self): self.invertor.new_data = 1.0 self.assertEqual(self.invertor.new_data, 1.0) self.assertEqual(self.invertor.test_no_data, None) def test_inversion(self): """ Test an inversion for which we know the answer """ x, y, err = load("sphere_80.txt") # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = 1e-7 # Set data self.invertor.x = x self.invertor.y = y self.invertor.err = err # Perform inversion out, cov = self.invertor.invert(10) # This is a very specific case # We should make sure it always passes self.assertTrue(self.invertor.chi2/len(x)<200.00) # Check the computed P(r) with the theory # for shpere of radius 80 x = pylab.arange(0.01, self.invertor.d_max, self.invertor.d_max/51.0) y = numpy.zeros(len(x)) dy = numpy.zeros(len(x)) y_true = numpy.zeros(len(x)) sum = 0.0 sum_true = 0.0 for i in range(len(x)): #y[i] = self.invertor.pr(out, x[i]) (y[i], dy[i]) = self.invertor.pr_err(out, cov, x[i]) sum += y[i] if x[i]<80.0: y_true[i] = pr_theory(x[i], 80.0) else: y_true[i] = 0 sum_true += y_true[i] y = y/sum*self.invertor.d_max/len(x) dy = dy/sum*self.invertor.d_max/len(x) y_true = y_true/sum_true*self.invertor.d_max/len(x) chi2 = 0.0 for i in range(len(x)): res = (y[i]-y_true[i])/dy[i] chi2 += res*res try: self.assertTrue(chi2/51.0<10.0) except: print "chi2 =", chi2/51.0 raise def test_q_zero(self): """ Test error condition where a point has q=0 """ x, y, err = load("sphere_80.txt") x[0] = 0.0 # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = 1e-7 # Set data def doit(): self.invertor.x = x self.assertRaises(ValueError, doit) def test_q_neg(self): """ Test error condition where a point has q<0 """ x, y, err = load("sphere_80.txt") x[0] = -0.2 # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = 1e-7 # Set data self.invertor.x = x self.invertor.y = y self.invertor.err = err # Perform inversion out, cov = self.invertor.invert(4) try: self.assertTrue(self.invertor.chi2>0) except: print "Chi2 =", self.invertor.chi2 raise def test_Iq_zero(self): """ Test error condition where a point has q<0 """ x, y, err = load("sphere_80.txt") y[0] = 0.0 # Choose the right d_max... self.invertor.d_max = 160.0 # Set a small alpha self.invertor.alpha = 1e-7 # Set data self.invertor.x = x self.invertor.y = y self.invertor.err = err # Perform inversion out, cov = self.invertor.invert(4) try: self.assertTrue(self.invertor.chi2>0) except: print "Chi2 =", self.invertor.chi2 raise def pr_theory(r, R): """ P(r) for a sphere """ if r<=2*R: return 12.0* ((0.5*r/R)**2) * ((1.0-0.5*r/R)**2) * ( 2.0 + 0.5*r/R ) else: return 0.0 def load(path = "sphere_60_q0_2.txt"): import numpy, math, sys # Read the data from the data file data_x = numpy.zeros(0) data_y = numpy.zeros(0) data_err = numpy.zeros(0) if not path == None: input_f = open(path,'r') buff = input_f.read() lines = buff.split('\n') for line in lines: try: toks = line.split() x = float(toks[0]) y = float(toks[1]) data_x = numpy.append(data_x, x) data_y = numpy.append(data_y, y) # Set the error of the first point to 5% # to make theory look like data scale = 0.1/math.sqrt(data_x[0]) data_err = numpy.append(data_err, scale*math.sqrt(y)) except: pass return data_x, data_y, data_err if __name__ == '__main__': unittest.main()