Python int_to_roman Examples

Example #1

File: test_util.py Project: livnehra/tardis

def test_int_to_roman(test_input, expected_result):
    assert int_to_roman(test_input) == expected_result

    with pytest.raises(TypeError):
        int_to_roman(1.5)

    with pytest.raises(ValueError):
        int_to_roman(0)

    with pytest.raises(ValueError):
        int_to_roman(4000)

Example #2

File: test_util.py Project: karandesai-96/tardis

def test_int_to_roman(test_input, expected_result):
    assert int_to_roman(test_input) == expected_result

    with pytest.raises(TypeError):
        int_to_roman(1.5)

    with pytest.raises(ValueError):
        int_to_roman(0)

    with pytest.raises(ValueError):
        int_to_roman(4000)

Example #3

    #normalizing the level_populations for Si II
    current_level_population = nebular_plasma.level_populations.ix[
        14, 1] / nebular_plasma.ion_populations.ix[14, 1]
    #normalizing with statistical weight
    current_level_population /= atom_data.levels.ix[14, 1].g

    level_populations[t_rad] = current_level_population

ion_colors = ['b', 'g', 'r', 'k']

for ion_number in [0, 1, 2, 3]:
    current_ion_density = ion_number_densities.ix[14, ion_number]
    ax1.plot(current_ion_density.index,
             current_ion_density.values,
             '%s-' % ion_colors[ion_number],
             label='Si %s W=1.0' % util.int_to_roman(ion_number + 1).upper())

#only plotting every 5th radiation temperature
t_rad_normalizer = colors.Normalize(vmin=2000, vmax=20000)
t_rad_color_map = plt.cm.ScalarMappable(norm=t_rad_normalizer, cmap=plt.cm.jet)

for t_rad in t_rads[::5]:
    ax2.plot(level_populations[t_rad].index,
             level_populations[t_rad].values,
             color=t_rad_color_map.to_rgba(t_rad))
    ax2.semilogy()

#Calculating the different ion populations for the given temperatures with W=0.5
ion_number_densities = pd.DataFrame(index=nebular_plasma.ion_populations.index)
for t_rad in t_rads:
    nebular_plasma.update_radiationfield(t_rad, w=0.5)

Example #4

File: lte_ionization_balance.py Project: nathanielatom/tardis

    # normalizing the level_populations for Si II
    current_level_population = lte_plasma.level_populations.ix[14, 1] / lte_plasma.ion_populations.ix[14, 1]
    # normalizing with statistical weight
    current_level_population /= atom_data.levels.ix[14, 1].g

    level_populations[t_rad] = current_level_population

ion_colors = ["b", "g", "r", "k"]

for ion_number in [0, 1, 2, 3]:
    current_ion_density = ion_number_densities.ix[14, ion_number]
    ax1.plot(
        current_ion_density.index,
        current_ion_density.values,
        "%s-" % ion_colors[ion_number],
        label="Si %s W=1.0" % util.int_to_roman(ion_number + 1).upper(),
    )


# only plotting every 5th radiation temperature
t_rad_normalizer = colors.Normalize(vmin=2000, vmax=20000)
t_rad_color_map = plt.cm.ScalarMappable(norm=t_rad_normalizer, cmap=plt.cm.jet)

for t_rad in t_rads[::5]:
    ax2.plot(level_populations[t_rad].index, level_populations[t_rad].values, color=t_rad_color_map.to_rgba(t_rad))
    ax2.semilogy()

t_rad_color_map.set_array(t_rads)
cb = plt.figure(2).colorbar(t_rad_color_map)

ax1.set_xlabel("T [K]")

Example #5

File: nebular_ionization_balance.py Project: lukeshingles/tardis

    ion_density = nebular_plasma.ion_populations / si_number_density
    ion_number_densities[t_rad] = ion_density

    #normalizing the level_populations for Si II
    current_level_population = nebular_plasma.level_populations.ix[14, 1] / nebular_plasma.ion_populations.ix[14, 1]
    #normalizing with statistical weight
    current_level_population /= atom_data.levels.ix[14, 1].g

    level_populations[t_rad] = current_level_population

ion_colors = ['b', 'g', 'r', 'k']

for ion_number in [0, 1, 2, 3]:
    current_ion_density = ion_number_densities.ix[14, ion_number]
    ax1.plot(current_ion_density.index, current_ion_density.values, '%s-' % ion_colors[ion_number],
             label='Si %s W=1.0' % util.int_to_roman(ion_number + 1).upper())


#only plotting every 5th radiation temperature
t_rad_normalizer = colors.Normalize(vmin=2000, vmax=20000)
t_rad_color_map = plt.cm.ScalarMappable(norm=t_rad_normalizer, cmap=plt.cm.jet)

for t_rad in t_rads[::5]:
    ax2.plot(level_populations[t_rad].index, level_populations[t_rad].values, color=t_rad_color_map.to_rgba(t_rad))
    ax2.semilogy()

#Calculating the different ion populations for the given temperatures with W=0.5
ion_number_densities = pd.DataFrame(index=nebular_plasma.ion_populations.index)
for t_rad in t_rads:
    nebular_plasma.update_radiationfield(t_rad, w=0.5)
    #getting total si number density