def __init__(self, parameters):
self._parameters = dict(parameters) # to not modify parameters
self._integer = parameters['integer_flux']
self._boxes = {
'SE':
BoxSource('SE'),
'INCUB':
BoxConvolution('INCUB', compute_khi_delay(self.delay('dm_incub')),
self._integer),
'IR':
BoxConvolution('IR', compute_khi_exp(self.delay('dm_r')),
self._integer),
'IH':
BoxConvolution('IH', compute_khi_exp(self.delay('dm_h')),
self._integer),
'SM':
BoxConvolution('SM', compute_khi_exp(self.delay('dm_sm')),
self._integer),
'SI':
BoxConvolution('SI', [
0, 0.03, 0.03, 0.04, 0.05, 0.05, 0.05, 0.05, 0.1, 0.1, 0.1,
0.1, 0.1, 0.1, 0.05, 0.03, 0.02
], self._integer),
'SS':
BoxConvolution('SS', compute_khi_exp(self.delay('dm_ss')),
self._integer),
'R':
BoxTarget('R'),
'DC':
BoxTarget('DC')
}
# src -> [targets]
def lambda_coefficient(a, b=None):
if isinstance(a, int):
return lambda: a
elif b == None:
return lambda: self.coefficient(a)
else:
return lambda: self.coefficient(a) * self.coefficient(b)
self._moves = {
'INCUB': [('IH', lambda_coefficient('pc_ih')),
('IR', lambda_coefficient('pc_ir'))],
'IR': [('R', lambda_coefficient(1))],
'IH': [('SM', lambda_coefficient('pc_sm')),
('SI', lambda_coefficient('pc_si'))],
'SM': [('SI', lambda_coefficient('pc_sm_si')),
('DC', lambda_coefficient('pc_sm_dc')),
('SS', lambda_coefficient('pc_sm_out', 'pc_h_ss')),
('R', lambda_coefficient('pc_sm_out', 'pc_h_r'))],
'SI': [('DC', lambda_coefficient('pc_si_dc')),
('SS', lambda_coefficient('pc_si_out', 'pc_h_ss')),
('R', lambda_coefficient('pc_si_out', 'pc_h_r'))],
'SS': [('R', lambda_coefficient(1))]
}
self.time = -1 # first step should be t=0
self.e0 = int(self.constant('population') * self.coefficient('kpe'))
self.box('SE').add(self.e0 - self.constant('patient0'))
self.box('INCUB').add(self.constant('patient0'))
def test_box_source4(self):
box = BoxSource('SOURCE')
box.add(100)
box.step()
self.assertEqual(box.size(), 100)
self.assertEqual(box.output(), 100)
box.step()
self.assertEqual(box.size(), 100)
self.assertEqual(box.output(), 100)
box.remove(10)
box.step()
self.assertEqual(box.size(), 90)
self.assertEqual(box.output(), 90)
def test_box_source2(self):
box = BoxSource('SOURCE')
box.add(100)
self.assertEqual(box.input(), 100)
box.step()
self.assertEqual(box.output(), 100)
box.step()
self.assertEqual(box.output(), 100)
box.add(10)
box.step()
self.assertEqual(box.input(), 0)
self.assertEqual(box.size(), 110)
self.assertEqual(box.output(), 110)
def test_box_source3(self):
box = BoxSource('SOURCE')
box.add(100)
self.assertEqual(box.input(), 100)
box.step()
self.assertEqual(box.output(), 100)
box.remove(10)
self.assertEqual(box.removed(), 10)
box.step()
self.assertEqual(box.removed(1), 10)
self.assertEqual(box.removed(), 0)
self.assertEqual(box.output(), 90)
box.remove(10)
box.remove(10)
self.assertEqual(box.removed(), 20)
box.step()
self.assertEqual(box.removed(1), 20)
self.assertEqual(box.removed(), 0)
self.assertEqual(box.output(), 70)
def test_box_source6(self):
box = BoxSource('SOURCE')
box.add(100)
box.step()
for i in range(1, 10):
box.remove(i)
box.step()
self.assertEqual(box.get_input_history(), [100]+[0]*10)
self.assertEqual(box.get_removed_history(), [
0]+list(range(1, 10)) + [0])
self.assertEqual(box.get_output_history(), [0]+[
100-int(n*(n+1)/2) for n in range(1, 10)] + [100-45])
self.assertEqual(box.get_output_history(), box.get_size_history())