def test_intialisation_b(self):
_ = SFH(time_axis / 1e9,
sfh_type="b",
parameters_dict={
'T0': 1,
'constant': 1
})
class TestSFHCustom(object):
def test_intialisation(self):
_ = SFH(time_axis, sfh_type="custom", sfh_arr=sfr)
def test_model_not_recognised(self):
with pytest.raises(HokiTypeError):
_ = SFH(time_axis, sfh_type="afs", sfh_arr=sfr)
def test_input_sizes(self):
with pytest.raises(HokiFormatError):
_ = SFH(time_axis[1:], sfh_type="custom", sfh_arr=sfr)
sfh = SFH(time_axis, sfh_type="custom", sfh_arr=sfr)
def test_sfr_at(self):
assert np.isclose(
[self.sfh(i) for i in time_axis],
sfr).all(),\
"Something is wrong with the stellar formation rate."
def test_mass_per_bin(self):
mass_per_bin = np.loadtxt(
f"{data_path}/csp_test_data/mass_per_bin.txt")
result = self.sfh.mass_per_bin(np.linspace(0, HOKI_NOW, 101),
sample_rate=100)
assert np.allclose(result, mass_per_bin),\
"The mass per bin is calculated incorrectly."
def test_type_check_history(self):
csp = CSP()
# define pyton callable
def x(i):
return i
# define SFH object
time_axis = np.linspace(0, 13e9, 1000)
sfh = SFH(time_axis, "b", {"constant": 10, "T0": 5e9})
# Check Types
with pytest.raises(HokiTypeError):
csp._type_check_histories([10], [0])
with pytest.raises(HokiTypeError):
csp._type_check_histories([10], 0)
with pytest.raises(HokiTypeError):
csp._type_check_histories([x, x], [x, 10])
# Check Format
with pytest.raises(HokiFormatError):
csp._type_check_histories([x], [x, x])
with pytest.raises(HokiFormatError):
csp._type_check_histories([x, x], [x])
with pytest.raises(HokiFormatError):
csp._type_check_histories([x], [])
# Checking if the correct input does run
assert csp._type_check_histories([x], [x]) == ([x], [x])
assert csp._type_check_histories([x, x], [x, x]) == ([x, x], [x, x])
assert csp._type_check_histories(x, x) == ([x], [x])
assert csp._type_check_histories([x], x) == ([x], [x])
assert csp._type_check_histories(sfh, x) == ([sfh], [x])
assert csp._type_check_histories([sfh], [x]) == ([sfh], [x])
class TestSFHParametric(object):
def test_intialisation_c(self):
_ = SFH(time_axis / 1e9, sfh_type="c", parameters_dict={'constant': 1})
def test_intialisation_b(self):
_ = SFH(time_axis / 1e9,
sfh_type="b",
parameters_dict={
'T0': 1,
'constant': 1
})
def test_intialisation_e(self):
_ = SFH(time_axis / 1e9,
sfh_type="e",
parameters_dict={
'tau': 1,
'T0': 1,
'constant': 1
})
def test_intialisation_de(self):
_ = SFH(time_axis / 1e9,
sfh_type="de",
parameters_dict={
'tau': 1,
'T0': 1,
'constant': 1
})
def test_intialisation_dpl(self):
_ = SFH(time_axis / 1e9,
sfh_type="dpl",
parameters_dict={
'tau': 1,
'alpha': 1,
'beta': 1,
'constant': 1
})
def test_intialisation_ln(self):
_ = SFH(time_axis / 1e9,
sfh_type="ln",
parameters_dict={
'tau': 1,
'T0': 1,
'constant': 1
})
sfh = SFH(time_axis, sfh_type="c", parameters_dict={'constant': 1})
def test_sfr_at(self):
# this only works for constant sfr = 1
assert np.isclose([self.sfh(i) for i in time_axis], [1]*len(time_axis)).all(),\
"Something is wrong with the stellar formation rate."
def test_mass_per_bin(self):
assert np.isclose(self.sfh.mass_per_bin([2, 3, 6, 8]), [1., 3., 2.]).all(),\
"The mass per bin is calculated incorrectly."
def test_intialisation_dpl(self):
_ = SFH(time_axis / 1e9,
sfh_type="dpl",
parameters_dict={
'tau': 1,
'alpha': 1,
'beta': 1,
'constant': 1
})
def test_input_sizes(self):
with pytest.raises(HokiFormatError):
_ = SFH(time_axis[1:], sfh_type="custom", sfh_arr=sfr)
def test_model_not_recognised(self):
with pytest.raises(HokiTypeError):
_ = SFH(time_axis, sfh_type="afs", sfh_arr=sfr)
def test_intialisation(self):
_ = SFH(time_axis, sfh_type="custom", sfh_arr=sfr)
def Z_fnc(x):
return 0.00001
def vec_sfh(x):
return np.zeros(len(x)) + 1
def vec_Z(x):
return np.zeros(len(x)) + 0.00001
# define SFH object
time_axis = np.linspace(0, HOKI_NOW, 1000)
sfh = SFH(time_axis, "c", {"constant": 1})
class TestCSPEventRate():
data = model_output(f"{data_path}/supernova-bin-imf135_300.zem5.dat")
# Check initalisation
@patch("hoki.load.model_output")
def test_init(self, mock_model_output):
mock_model_output.return_value = self.data
_ = er.CSPEventRate(f"{data_path}", "imf135_300")
def test_input_functions_at_time(self):
assert np.isclose(
self.CSP.at_time([sfh_fnc], [Z_fnc], ["Ia"], 0,