def test_chain_all():
# Test that running the simulation functions in chain works
table = make_base_catalog_galactic(n_sources=10, random_state=0)
table = add_snr_parameters(table)
table = add_pulsar_parameters(table, random_state=0)
table = add_pwn_parameters(table)
table = add_observed_parameters(table)
d = table[0]
# Note: the individual functions are tested above.
# Here we just run them in a chain and do very basic asserts
# on the output so that we make sure we notice changes.
assert len(table) == 10
assert len(table.colnames) == 34
assert table["r_out_PWN"].unit == "pc"
assert_allclose(d["r_out_PWN"], 1.378224, atol=1e-4)
assert table["RA"].unit == "deg"
assert_allclose(d["RA"], 244.347149, atol=1e-5)
def test_add_observed_parameters():
table = make_base_catalog_galactic(n_sources=10, random_state=0)
table = add_observed_parameters(table)
d = table[0]
assert len(table) == 10
assert len(table.colnames) == 20
assert table["distance"].unit == "pc"
assert_allclose(d["distance"], 13016.572756, atol=1e-5)
assert table["GLON"].unit == "deg"
assert_allclose(d["GLON"], -27.156565, atol=1e-5)
assert table["GLAT"].unit == "deg"
assert_allclose(d["GLAT"], 0.101948, atol=1e-5)
assert table["VGLON"].unit == "deg / Myr"
assert_allclose(d["VGLON"], 0.368166, atol=1e-5)
assert table["VGLAT"].unit == "deg / Myr"
assert_allclose(d["VGLAT"], -0.209514, atol=1e-5)
assert table["RA"].unit == "deg"
assert_allclose(d["RA"], 244.347149, atol=1e-5)
assert table["DEC"].unit == "deg"
assert_allclose(d["DEC"], -50.410142, atol=1e-5)
luminosity_min = 4e34
# Maximum source luminosity (ph s^-1)
luminosity_max = 4e37
# Luminosity function differential power-law index
luminosity_index = 1.5
# Assigns luminosities to sources
luminosity = sample_powerlaw(luminosity_min,
luminosity_max,
luminosity_index,
n_sources,
random_state=0)
table['luminosity'] = luminosity
# Adds parameters to table: distance, glon, glat, flux, angular_extension
table = population.add_observed_parameters(table)
table.meta['Energy Bins'] = np.array([10, 500]) * u.GeV
# Create image
image = catalog_image(reference,
psf,
catalog='simulation',
source_type='point',
total_flux=True,
sim_table=table)
# Plot
fig = FITSFigure(image.to_fits()[0], figsize=(15, 5))
fig.show_colorscale(interpolation='bicubic',
cmap='afmhot',
stretch='log',
vmin=1E30,
spiralarms=spiralarms, random_state=0)
# Minimum source luminosity (ph s^-1)
luminosity_min = 4e34
# Maximum source luminosity (ph s^-1)
luminosity_max = 4e37
# Luminosity function differential power-law index
luminosity_index = 1.5
# Assigns luminosities to sources
luminosity = sample_powerlaw(luminosity_min, luminosity_max, luminosity_index,
n_sources, random_state=0)
table['luminosity'] = luminosity
# Adds parameters to table: distance, glon, glat, flux, angular_extension
table = population.add_observed_parameters(table)
table.meta['Energy Bins'] = np.array([10, 500]) * u.GeV
# Create image
image = catalog_image(reference, psf, catalog='simulation', source_type='point',
total_flux=True, sim_table=table)
# Plot
fig = FITSFigure(image.to_fits()[0], figsize=(15, 5))
fig.show_colorscale(interpolation='bicubic', cmap='afmhot', stretch='log', vmin=1E30, vmax=1E35)
fig.tick_labels.set_xformat('ddd')
fig.tick_labels.set_yformat('dd')
ticks = np.logspace(30, 35, 6)
fig.add_colorbar(ticks=ticks, axis_label_text='Flux (ph s^-1)')
fig.colorbar._colorbar_axes.set_yticklabels(['{:.0e}'.format(_) for _ in ticks])
plt.tight_layout()
plt.show()