def test_generator(self):
class MockProp:
pass
pop = Population(propagator = MockProp)
pop.allocate(10)
for ind in range(10):
pop.data[ind] = (ind,
7000,
0.0,
69,
ind,
0.0,
0.0,
57125.7729,
)
gen = pop.generator
assert isinstance(gen, types.GeneratorType)
lst = [obj for obj in gen]
assert len(lst) == 10
for ind, obj in enumerate(lst):
assert isinstance(obj, SpaceObject)
nt.assert_almost_equal(obj.oid, float(ind), decimal = 7)
def test_get_item_nan(self):
pop = Population(
fields = Population._default_fields + ['m', 'color'],
dtypes = [Population._default_dtype]*len(Population._default_fields) + ['float64', 'U20'],
)
pop.allocate(2)
test = pop[0,:]
assert np.isnan(test[9])
def test_iter(self):
pop = Population()
pop.allocate(10)
pop['oid'] = np.arange(10)
itres = 0
for ind, row in enumerate(pop.data):
self.assertEqual(int(row[0]), ind)
self.assertEqual(len(row), 8)
itres += 1
self.assertEqual(itres, 10)
def test_constructor(self):
pop = Population()
self.assertEqual(len(pop.fields), len(Population._default_fields))
self.assertEqual(pop.data.shape, (0,))
self.assertEqual(len(pop.data.dtype), len(Population._default_fields))
for ind in range(len(pop.data.dtype)):
self.assertEqual(pop.data.dtype[ind], np.dtype(Population._default_dtype))
def test_get_item(self):
pop = Population(
fields = Population._default_fields + ['m', 'color'],
)
pop.allocate(10)
for ind in range(10):
pop.data[ind] = (ind,
7000,
0.0,
69,
ind,
0.0,
0.0,
57125.7729,
123,
1223,
)
ms = pop['m']
es = pop['e']
row = pop[0]
assert len(ms) == 10
assert len(row) == len(pop.fields)
for ind in range(len(pop.fields)):
nt.assert_almost_equal(row[ind], pop.data[0][ind], decimal=9)
for ind in range(len(pop)):
nt.assert_almost_equal(es[ind], pop.data['e'][ind], decimal=9)
for ind in range(len(pop)):
nt.assert_almost_equal(ms[ind], pop.data[ind][8], decimal=9)
vec = pop[4,:-1]
assert len(vec) == len(pop.fields)-1
vec = pop[:,3]
assert len(vec) == len(pop)
point = pop[3,3]
mat = pop[:,:]
assert mat.shape == pop.shape
mat = pop[2:6,1:2:-1]
def test_constructor_arguemnts(self):
pop = Population(
fields = ['x', 'y'],
dtypes = ['float64', 'float32'],
)
self.assertEqual(len(pop.fields), 2)
self.assertEqual(pop.data.shape, (0,))
self.assertEqual(len(pop.data.dtype), 2)
self.assertEqual(pop.data.dtype[0], np.dtype('float64'))
self.assertEqual(pop.data.dtype[1], np.dtype('float32'))
def test_space_object(self):
from sorts.propagator import SGP4
pop = Population(propagator = SGP4)
pop.allocate(1)
for ind in range(1):
pop.data[ind] = (ind,
7000e3,
0.0,
69,
ind,
0.0,
0.0,
57125.7729,
)
pop.in_frame = 'TEME'
pop.out_frame = 'TEME'
obj = pop.get_object(0)
assert obj.in_frame == 'TEME'
assert obj.out_frame == 'TEME'
assert isinstance(obj, SpaceObject)
state = obj.get_state(0)
assert state.shape == (6,1)
#3 decimals to account for SGP4 bad conversion
nt.assert_almost_equal(state, obj.orbit.cartesian, decimal=3)
ref = np.array([
0,
obj.orbit.a,
obj.orbit.e,
obj.orbit.i,
obj.orbit.omega,
obj.orbit.Omega,
obj.orbit.anom,
obj.epoch.mjd,
], dtype=Population._default_dtype)
for ind in range(8):
nt.assert_almost_equal(pop.data[0][ind], ref[ind], decimal=6)
def test_column_order(self):
pop = Population()
ref = Population._default_fields
keys = pop.data.dtype.fields.keys()
for ind in range(len(pop.fields)):
assert pop.fields[ind] in keys
assert pop.fields[ind] in ref
pop.allocate(1)
pop[0,0] = 1.0
self.assertEqual(pop['oid'][0], 1.0)
vec = np.arange(len(pop.fields))
pop[0,:] = vec.copy()
for ind in range(len(pop.fields)):
nt.assert_almost_equal(pop[0,ind], vec[ind])
nt.assert_almost_equal(pop[ref[ind]][0], vec[ind])
nt.assert_almost_equal(pop[0,ind], pop[ref[ind]][0])
pop = Population(
fields = ['x', 'y'],
dtypes = ['float64', 'float32'],
)
ref = ['x', 'y']
keys = pop.data.dtype.fields.keys()
for ind in range(len(pop.fields)):
assert pop.fields[ind] in keys
assert pop.fields[ind] in ref
pop.allocate(1)
pop[0,0] = 1.0
self.assertEqual(pop['x'][0], 1.0)
vec = np.arange(len(pop.fields))
pop[0,:] = vec.copy()
for ind in range(len(pop.fields)):
nt.assert_almost_equal(pop[0,ind], vec[ind])
nt.assert_almost_equal(pop[ref[ind]][0], vec[ind])
nt.assert_almost_equal(pop[0,ind], pop[ref[ind]][0])
def test_filter(self):
pop = Population()
pop.allocate(10)
for ind in range(10):
pop.data[ind] = (ind,
7000e3,
0.0,
69,
ind,
0.0,
0.0,
57125.7729,
)
pop.filter('raan', lambda theta: theta > 5.5)
assert len(pop) == 4
def test_allocate(self):
pop = Population()
pop.allocate(10)
self.assertEqual(pop.data.shape, (10,))
self.assertEqual(len(pop.data.dtype), len(Population._default_fields))
for ind in range(len(pop.data.dtype)):
self.assertEqual(pop.data.dtype[ind], np.dtype(Population._default_dtype))
self.assertEqual(len(pop), 10)
pop = Population(
fields = ['x', 'y'],
dtypes = ['float64', 'float32'],
)
pop.allocate(10)
self.assertEqual(len(pop.fields), 2)
self.assertEqual(pop.data.shape, (10,))
self.assertEqual(len(pop.data.dtype), 2)
self.assertEqual(pop.data.dtype[0], np.dtype('float64'))
self.assertEqual(pop.data.dtype[1], np.dtype('float32'))
self.assertEqual(len(pop), 10)
def test_shape(self):
pop = Population()
shape = pop.shape
self.assertEqual(shape, (0,len(Population._default_fields)))
pop.allocate(123)
shape = pop.shape
self.assertEqual(shape, (123,len(Population._default_fields)))
pop = Population(
fields = ['x', 'y'],
dtypes = ['float64', 'float32'],
)
shape = pop.shape
self.assertEqual(shape, (0,2))
pop.allocate(123)
shape = pop.shape
self.assertEqual(shape, (123,2))
def test_set_item(self):
pop0 = Population()
pop = Population(
fields = Population._default_fields + ['m', 'color'],
dtypes = [Population._default_dtype]*len(Population._default_fields) + ['float64', 'U20'],
)
pop0.allocate(2)
pop.allocate(2)
pop[1,5] = 1
nt.assert_almost_equal(pop.data[1][pop.fields[5]], 1)
pop[1,9] = 'WAT'
pop0[0] = np.random.rand(len(pop.fields))
pop['m'] = np.random.randn(len(pop))
pop[:,3] = np.ones((len(pop),1))*3
pop[:,5:8] = np.ones((len(pop),3))*4
self.assertEqual(str(pop.data[1]['color']), 'WAT')
self.assertEqual(str(pop.data[0]['color']), '')
nt.assert_almost_equal(pop.data[1][pop.fields[5]], 4)
nt.assert_almost_equal(pop.data[1][pop.fields[3]], 3)
import numpy as np
import matplotlib.pyplot as plt
from sorts.propagator import SGP4
from sorts import Population
from sorts import plotting
t = np.linspace(0, 3600 * 10, num=2000)
pop = Population(fields=[
'oid', 'a', 'e', 'i', 'raan', 'aop', 'mu0', 'mjd0', 'm', 'A', 'C_R', 'C_D'
],
space_object_fields=['oid', 'm', 'A', 'C_R', 'C_D'],
state_fields=['a', 'e', 'i', 'raan', 'aop', 'mu0'],
epoch_field={
'field': 'mjd0',
'format': 'mjd',
'scale': 'utc'
},
propagator=SGP4,
propagator_options=dict(settings=dict(out_frame='TEME', ), ))
pop.allocate(100)
#for consistency
np.random.seed(120389)
# * 0: oid - Object ID
# * 1: a - Semi-major axis in m
# * 2: e - Eccentricity
# * 3: i - Inclination in degrees
# * 4: raan - Right Ascension of ascending node in degrees