def test_simulate_lightcurve_flux():
event = mock.MagicMock()
telescope = mock.MagicMock()
telescope.name = 'NDG'
telescope.lightcurve_flux = np.array([[0, 51, 69], [2, 42, 28.65]])
event.telescopes = []
event.telescopes.append(telescope)
model = microlsimulator.simulate_a_microlensing_model(event)
parameters = microlsimulator.simulate_microlensing_model_parameters(model)
fake_flux_parameters = microlsimulator.simulate_fluxes_parameters(
event.telescopes)
pyLIMA_parameters = model.compute_pyLIMA_parameters(parameters +
fake_flux_parameters)
microlsimulator.simulate_lightcurve_flux(model, pyLIMA_parameters, 'No')
assert np.all(telescope.lightcurve_flux[:, 1] != [51, 42])
assert np.all(telescope.lightcurve_flux[:, 2] != [69, 28.65])
microlsimulator.simulate_lightcurve_flux(model, pyLIMA_parameters, 'Yes')
assert np.all(telescope.lightcurve_flux[:, 1] != [51, 42])
assert np.all(telescope.lightcurve_flux[:, 2] != [69, 28.65])
def test_simulate_lightcurve_flux():
event = mock.MagicMock()
telescope = mock.MagicMock()
telescope.name = 'NDG'
telescope.lightcurve_flux = np.array([[0, 51, 69], [2, 42, 28.65]])
event.telescopes = []
event.telescopes.append(telescope)
model = microlsimulator.simulate_a_microlensing_model(event)
parameters = microlsimulator.simulate_microlensing_model_parameters(model)
fake_flux_parameters = microlsimulator.simulate_fluxes_parameters(event.telescopes)
pyLIMA_parameters = model.compute_pyLIMA_parameters(parameters + fake_flux_parameters)
microlsimulator.simulate_lightcurve_flux(model, pyLIMA_parameters, 'No')
assert np.all(telescope.lightcurve_flux[:, 1] != [51, 42])
assert np.all(telescope.lightcurve_flux[:, 2] != [69, 28.65])
microlsimulator.simulate_lightcurve_flux(model, pyLIMA_parameters, 'Yes')
assert np.all(telescope.lightcurve_flux[:, 1] != [51, 42])
assert np.all(telescope.lightcurve_flux[:, 2] != [69, 28.65])
# [magnitude_source_SAAO_V, blending ratio_SAAO_V]], i.e [[18.5,0.3],[19.5,1.2],[20.2,1.6]] (example).
my_own_flux_parameters = microlsimulator.simulate_fluxes_parameters(
my_own_creation.telescopes)
my_own_parameters += my_own_flux_parameters
#Now we need to transform these parameters into a parameter class object (this is a "technical" part but the interested reader can found the function here [pyLIMA #documentation](file/../../doc/build/html/pyLIMA.microlmodels.html))
# Transform into pyLIMA standards
pyLIMA_parameters = my_own_model.compute_pyLIMA_parameters(my_own_parameters)
#Ok now we have the model we want to simulate, we then need to updates our telescopes observations!
# update the telescopes lightcurve in your event :
microlsimulator.simulate_lightcurve_flux(my_own_model,
pyLIMA_parameters,
red_noise_apply='Yes')
#### Plot it!
for telescope in my_own_creation.telescopes:
plt.errorbar(telescope.lightcurve_magnitude[:, 0] - 2450000,
telescope.lightcurve_magnitude[:, 1],
yerr=telescope.lightcurve_magnitude[:, 2],
fmt='.',
label=telescope.name)
# A list of commentary to explain parameters. Of couse, this is valable only for the DSPL models.
parameter_commentary = [
'time of minimum impact parameter for source 1',
'minimum impact parameter for source 1',