def testCheckNames(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm3 = FCMdata('test_fcm3', pnts, ['fsc', 'ssc', 'cd4'], [0, 1])
fcms1 = FCMcollection('fcms1', [fcm1, fcm2])
fcms2 = FCMcollection('fcms2', [fcm1, fcm2, fcm3, fcms1])
check1 = fcms1.check_names()
assert check1[fcms1.name] == [True, True, True]
check2 = fcms2.check_names()
assert check2[fcms2.name] == [check1, True, True, False]
def testListFitting(self):
true1, data1 = self.generate_data()
true2, data2 = self.generate_data()
model = DPMixtureModel(3,2000,100,1, type='BEM')
rs = model.fit([data1,data2])
assert(len(rs) == 2)
for r in rs:
print 'mu ',r.mus
diffs = {}
for i in gen_mean:
diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
#print i, gen_mean[i], diffs[i], np.vdot(diffs[i],diffs[i])
assert( np.vdot(diffs[i],diffs[i]) < 1)
fcm1 = FCMdata('test_fcm1', data1, ['fsc','ssc'], [0,1])
fcm2 = FCMdata('test_fcm2', data2, ['fsc','ssc'], [0,1])
c = FCMcollection('fcms', [fcm1, fcm2])
rs = model.fit(c)
assert(len(rs) == 2)
for r in rs:
print 'mu ',r.mus
diffs = {}
for i in gen_mean:
diffs[i] = np.min(np.abs(r.mus-gen_mean[i]),0)
#print i, gen_mean[i], diffs[i], np.vdot(diffs[i],diffs[i])
assert( np.vdot(diffs[i],diffs[i]) < 1)
def testCheckNames(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm3 = FCMdata('test_fcm3', pnts, ['fsc', 'ssc', 'cd4'], [0, 1])
fcms1 = FCMcollection('fcms1', [fcm1, fcm2])
fcms2 = FCMcollection('fcms2', [fcm1, fcm2, fcm3, fcms1])
check1 = fcms1.check_names()
assert check1[fcms1.name] == [True, True, True]
check2 = fcms2.check_names()
assert check2[fcms2.name] == [check1, True, True, False]
def setUp(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
self.fcms = FCMcollection('fcms', [fcm1, fcm2])
class FCMcollectionTestCase(unittest.TestCase):
def setUp(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
self.fcms = FCMcollection('fcms', [fcm1, fcm2])
def testCheckNames(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm3 = FCMdata('test_fcm3', pnts, ['fsc', 'ssc', 'cd4'], [0, 1])
fcms1 = FCMcollection('fcms1', [fcm1, fcm2])
fcms2 = FCMcollection('fcms2', [fcm1, fcm2, fcm3, fcms1])
check1 = fcms1.check_names()
assert check1[fcms1.name] == [True, True, True]
check2 = fcms2.check_names()
assert check2[fcms2.name] == [check1, True, True, False]
def testCompensate(self):
# no fcmdata.compensate method???
pass
def testTransform(self):
tmp = self.fcms['test_fcm1'][:]
self.fcms.log([0, 1, 2])
ltmp = array([[-1, -1, -1], [-1, -1, -1]])
for i in range(3):
ltmp[:, i] = where(tmp[:, i] <= 1, 0, log10(tmp[:, i]))
assert_array_equal(self.fcms['test_fcm1'], ltmp,
'Log transform failed')
assert_array_equal(self.fcms['test_fcm2'], ltmp,
'Log transform failed')
self.fcms.logicle()
# figure out what to assert...
def testGate(self):
verts = array([[-.1, -.1], [-.1, 1.1], [1.1, 1.1], [1.1, -.1]])
cols = [0, 1]
g = PolyGate(verts, cols)
self.fcms.gate(g)
assert_array_equal(self.fcms['test_fcm1'].view(), array([[1, 1, 1]]),
'Gating failed')
assert_array_equal(self.fcms['test_fcm2'].view(), array([[1, 1, 1]]),
'Gating failed')
def testFit(self):
from fcm.statistics import DPMixtureModel, DPMixture
k = 16
niter = 10
model = DPMixtureModel(k, niter, 0, 1)
results = self.fcms.fit(model)
assert_equal(len(results.keys()), 2,
'fitting produced wrong shaped dict')
for i in self.fcms:
assert isinstance(
results[i],
DPMixture), 'fitting produced a non-DPMixture object'
def testClassify(self):
from fcm.statistics import DPCluster, DPMixture
mu1 = array([0, 0, 0])
sig = eye(3)
mu2 = array([5, 5, 5])
clst1 = DPCluster(.5, mu1, sig)
clst2 = DPCluster(.5, mu2, sig)
mix = DPMixture([clst1, clst2])
cls = self.fcms.classify(mix)
assert_array_equal(cls['test_fcm1'], array([0, 1]), 'Calssify failed')
assert_array_equal(cls['test_fcm2'], array([0, 1]), 'Calssify failed')
def testSummary(self):
msg = self.fcms.summary()
assert isinstance(msg, str), "summary failed"
def setUp(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
self.fcms = FCMcollection('fcms', [fcm1, fcm2])
class FCMcollectionTestCase(unittest.TestCase):
def setUp(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
self.fcms = FCMcollection('fcms', [fcm1, fcm2])
def testCheckNames(self):
pnts = array([[1, 1, 1], [5, 5, 5]])
fcm1 = FCMdata('test_fcm1', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm2 = FCMdata('test_fcm2', pnts, ['fsc', 'ssc', 'cd3'], [0, 1])
fcm3 = FCMdata('test_fcm3', pnts, ['fsc', 'ssc', 'cd4'], [0, 1])
fcms1 = FCMcollection('fcms1', [fcm1, fcm2])
fcms2 = FCMcollection('fcms2', [fcm1, fcm2, fcm3, fcms1])
check1 = fcms1.check_names()
assert check1[fcms1.name] == [True, True, True]
check2 = fcms2.check_names()
assert check2[fcms2.name] == [check1, True, True, False]
def testCompensate(self):
# no fcmdata.compensate method???
pass
def testTransform(self):
tmp = self.fcms['test_fcm1'][:]
self.fcms.log([0, 1, 2])
ltmp = array([[-1, -1, -1], [-1, -1, -1]])
for i in range(3):
ltmp[:, i] = where(tmp[:, i] <= 1, 0, log10(tmp[:, i]))
assert_array_equal(
self.fcms['test_fcm1'], ltmp, 'Log transform failed')
assert_array_equal(
self.fcms['test_fcm2'], ltmp, 'Log transform failed')
self.fcms.logicle()
# figure out what to assert...
def testGate(self):
verts = array([[-.1, -.1], [-.1, 1.1], [1.1, 1.1], [1.1, -.1]])
cols = [0, 1]
g = PolyGate(verts, cols)
self.fcms.gate(g)
assert_array_equal(
self.fcms['test_fcm1'].view(), array([[1, 1, 1]]), 'Gating failed')
assert_array_equal(
self.fcms['test_fcm2'].view(), array([[1, 1, 1]]), 'Gating failed')
def testFit(self):
from fcm.statistics import DPMixtureModel, DPMixture
k = 16
niter = 10
model = DPMixtureModel(k, niter, 0, 1)
results = self.fcms.fit(model)
assert_equal(
len(results.keys()), 2, 'fitting produced wrong shaped dict')
for i in self.fcms:
assert isinstance(
results[i], DPMixture), 'fitting produced a non-DPMixture object'
def testClassify(self):
from fcm.statistics import DPCluster, DPMixture
mu1 = array([0, 0, 0])
sig = eye(3)
mu2 = array([5, 5, 5])
clst1 = DPCluster(.5, mu1, sig)
clst2 = DPCluster(.5, mu2, sig)
mix = DPMixture([clst1, clst2])
cls = self.fcms.classify(mix)
assert_array_equal(cls['test_fcm1'], array([0, 1]), 'Calssify failed')
assert_array_equal(cls['test_fcm2'], array([0, 1]), 'Calssify failed')
def testSummary(self):
msg = self.fcms.summary()
assert isinstance(msg, str), "summary failed"
