def get_data(filename):
"""
Grabs the data (z and stellar birth density in mh / cm^3).
"""
data = load(filename)
birth_densities = data.stars.birth_densities.to("g/cm**3") / mh.to("g")
birth_redshifts = 1 / data.stars.birth_scale_factors.value - 1
return birth_densities.value, birth_redshifts
def get_data(filename):
"""
Grabs the data (MMF and stellar birth density in mh / cm^3).
"""
data = load(filename)
birth_densities = data.stars.birth_densities.to("g/cm**3") / mh.to("g")
try:
metal_mass_fractions = data.stars.smoothed_metal_mass_fractions.value
except AttributeError:
metal_mass_fractions = data.stars.metal_mass_fractions.value
below_Z_min = np.where(
metal_mass_fractions < metal_mass_fraction_bounds[0])
# Stars with Z < lowest Z in the figure should be added to the lowest-Z bin
metal_mass_fractions[below_Z_min] = metal_mass_fraction_bounds[0] * (
1.0 + 1e-3 / bins)
return birth_densities.value, metal_mass_fractions
"$z > 3$": axes[2],
}
for label, ax in ax_dict.items():
ax.loglog()
ax.text(0.025,
1.0 - 0.025 * 3,
label,
transform=ax.transAxes,
ha="left",
va="top")
for color, (snapshot, name) in enumerate(zip(data, names)):
stars_SNII_densities = snapshot.stars.densities_at_last_supernova_event.to(
"g/cm**3") / mh.to("g")
# swift-colibre master branch as of Feb 26 2021
try:
stars_SNII_redshifts = (
1 / snapshot.stars.last_sniithermal_feedback_scale_factors.value -
1)
# swift-colibre master prior to Feb 26 2021
except AttributeError:
stars_SNII_redshifts = (
1 / snapshot.stars.last_sniifeedback_scale_factors.value - 1)
gas_SNII_densities = snapshot.gas.densities_at_last_supernova_event.to(
"g/cm**3") / mh.to("g")
try:
"$1 < z < 3$": axes[1],
"$z > 3$": axes[2],
}
for label, ax in ax_dict.items():
ax.loglog()
ax.text(0.025,
1.0 - 0.025 * 3,
label,
transform=ax.transAxes,
ha="left",
va="top")
for color, (snapshot, name) in enumerate(zip(data, names)):
birth_densities = snapshot.stars.birth_densities.to("g/cm**3") / mh.to("g")
birth_redshifts = 1 / snapshot.stars.birth_scale_factors.value - 1
# Segment birth densities into redshift bins
birth_densities_by_redshift = {
"$z < 1$":
birth_densities[birth_redshifts < 1],
"$1 < z < 3$":
birth_densities[np.logical_and(birth_redshifts > 1,
birth_redshifts < 3)],
"$z > 3$":
birth_densities[birth_redshifts > 3],
}
# Compute the critical density from DV&S2012
SNII_heating_temperature = float(