def plot_data(ax, data, dwarf):
"""
Plots an individual dwarf galaxy's abundance data on the subplot.
Parameters
==========
ax :: matplotlib subplot
The axis to plot the abundance data on
data :: 2D-list
The raw data itself
dwarf :: str
A key denoting which dwarf is being plotted. These appear in the first
column of the argument data.
"""
FeH_column = 12
MgFe_column = 14
fltrd = list(filter(lambda x: x[0] == dwarf, data))
kwargs = {
"c": visuals.colors()[_COLORS_[dwarf]],
"marker": visuals.markers()[_MARKERS_[dwarf]],
"linestyle": "None",
"label": _NAMES_[dwarf],
"s": _SIZES_[dwarf]
}
if dwarf == "LeoI": kwargs["zorder"] = 0
ax.scatter([row[FeH_column] for row in fltrd],
[row[MgFe_column] for row in fltrd], **kwargs)
def plot_yield(ax, element, study, MH, vrot, marker, color):
"""
Plots a single IMF-averaged CCSN yield of Sr on the axis
Parameters
==========
ax :: subplot
The matplotlib axis object to plot on
element :: str
The element to plot the yield of
study :: str
The study to adopt the yields from
MH :: real number
The value of [M/H] to calculate the yield for
vrot :: real number
The rotational velocity of the stars in km/s
marker :: str
The name of the marker to plot the point in
color :: str
The name of the color to plot the yield in
"""
y = vice.yields.ccsne.fractional(element,
study=study,
MoverH=MH,
rotation=vrot)[0]
ax.scatter(MH,
y,
c=visuals.colors()[color],
marker=visuals.markers()[marker],
s=100)
def plot_ssp_legend(ax):
"""
Draws the labels for the SN Ia DTD
Parameters
==========
ax :: subplot
The matplotlib axis object to put the legend on
"""
lines = 2 * [None]
labels = [
r"$R_\text{Ia}\propto t^{-1.1}$",
r"$R_\text{Ia}\propto e^{-t/\tau_\text{Ia}}$"
]
for i in range(2):
lines[i] = ax.plot([1, 2], [1, 2],
c=visuals.colors()["black"],
label=labels[i],
linestyle=[':', '--'][i])[0]
leg = ax.legend(loc=visuals.mpl_loc()["upper left"],
ncol=1,
bbox_to_anchor=(0.01, 0.99),
frameon=False)
for i in range(2):
lines[i].remove()
def plot_fractional_ssp_yield(ax, element, color, linestyle, z, ria): """ Plot the fractional single stellar population yield for a given element and metallicity of the stellar population. Parameters ========== ax :: subplot The matplotlib axis object to plot on element :: str The element to plot the enrichment of color :: str The name of the color to plot in linestyle :: str The matplotlib linestyle to use z :: real number The metallicity of the stellar population ria :: real number The SN Ia DTD to adopt """ mass, times = vice.single_stellar_population(element, Z = z, RIa = ria) final = mass[-1] fractional = [i/final for i in mass] ax.plot(times, fractional, c = visuals.colors()[color], linestyle = linestyle)
def legend(ax):
"""
Draws the legend differentiating between the yield models
Parameters
==========
ax :: subplot
The matplotlib axis object to put the yield on
"""
lines = 3 * [None]
colors = ["black", "deepskyblue", "crimson"]
labels = [
r"Constant $y_\text{Sr}^\text{CC}$",
r"$y_\text{Sr}^\text{CC} \propto 1-e^{-kZ}$",
r"$y_\text{Sr}^\text{CC} \propto Z$"
]
for i in range(3):
lines[i] = ax.plot([1, 2], [1, 2],
c=visuals.colors()["white"],
label=labels[i])[0]
leg = ax.legend(loc=visuals.mpl_loc()["lower right"],
ncol=1,
bbox_to_anchor=(0.98, 0.02),
frameon=False,
handlelength=0)
for i in range(3):
lines[i].remove()
leg.get_texts()[i].set_color(colors[i])
def plot_vs_metallicity_legend(ax):
"""
Plots the legend on the late-time panel denoting the form of the adopted
CCSN yield of Sr
Parameters
==========
ax :: subplot
The matplotlib axis object to put the legend on
"""
lines = 4 * [None]
labels = [
r"$y_\text{Sr}^\text{CC} = 0$", r"Constant $y_\text{Sr}^\text{CC}$",
r"$y_\text{Sr}^\text{CC} \propto Z$",
r"$y_\text{Sr}^\text{CC} \propto 1 - e^{-kZ}$"
]
colors = ["black", "crimson", "lime", "deepskyblue"]
for i in range(len(lines)):
lines[i] = ax.plot([1, 2], [1, 2],
c=visuals.colors()["white"],
label=labels[i])[0]
leg = ax.legend(loc=visuals.mpl_loc()["upper left"],
ncol=1,
bbox_to_anchor=(0.02, 0.98),
frameon=False,
handlelength=0)
for i in range(len(lines)):
lines[i].remove()
leg.get_texts()[i].set_color(colors[i])
def plot_legend(ax):
"""
Draws the legend denoting the yield assumptions
Parameters
==========
ax :: subplot
The matplotlib axis object to put the legend on
"""
lines = 4 * [None]
colors = ["black", "deepskyblue", "lime", "crimson"]
labels = [
r"Constant $y_\text{Sr}^\text{CC}$",
r"$y_\text{Sr}^\text{CC} \propto 1 - e^{-kZ}$",
r"$y_\text{Sr}^\text{CC} \propto Z$", r"$y_\text{Sr}^\text{CC}$ = 0"
]
for i in range(4):
lines[i] = ax.plot([1, 2], [1, 2],
c=visuals.colors()["white"],
label=labels[i])[0]
leg = ax.legend(loc=visuals.mpl_loc()["upper left"],
ncol=1,
bbox_to_anchor=(0.0, 0.99),
frameon=False,
handlelength=0)
for i in range(4):
lines[i].remove()
leg.get_texts()[i].set_color(colors[i])
def plot_history(axes, name, color, linestyle = '-'): """ Plots the relevant information for a given history on the 2x2 axis grid Parameters ========== axes :: list The 2x2 list of matplotlib axis objects to plot on name :: str The name of the model to plot color :: str The name of the color to use in plotting the model """ hist = vice.history(name) # axes[0][0].plot(hist["time"], hist["ifr"], linestyle = '--', # c = visuals.colors()[color]) axes[0][0].plot(hist["time"], hist["sfr"], c = visuals.colors()[color], linestyle = linestyle) if linestyle == '-': axes[0][1].plot(hist["[Fe/H]"], hist["[O/Fe]"], c = visuals.colors()[color], linestyle = linestyle) axes[1][0].plot(hist["time"], hist["[O/H]"], linestyle = '--', c = visuals.colors()[color]) axes[1][0].plot(hist["time"], hist["[Fe/H]"], linestyle = '-', c = visuals.colors()[color]) else: axes[1][0].plot(hist["time"], hist["[O/H]"], linestyle = linestyle, c = visuals.colors()[color]) axes[1][0].plot(hist["time"], hist["[Fe/H]"], linestyle = linestyle, c = visuals.colors()[color]) axes[1][1].plot(hist["time"], hist["[O/Fe]"], c = visuals.colors()[color], linestyle = linestyle)
def plot_AGB_yields_fixed_Z(ax, m, y, color): """ Plots AGB star yields as a function of mass on a given subplot Parameters ========== ax :: subplot The matplotlib axis object to plot on m :: list The stellar masses y :: list The fractional yields color :: str The name of the color to plot the yields in """ ax.scatter(m, y, c = visuals.colors()[color], marker = visuals.markers()["circle"]) ax.plot(m, y, c = visuals.colors()[color])
def plot_oscillatory(axes, output, color): """ Plot the oscillations in [O/Fe] and [Fe/H] against time Parameters ========== axes :: list The list of matplotlib axis objects to plot on output :: vice.output The VICE output object containing the simulation results color :: str The name of the color to plot in """ axes[0].plot(output.history["time"], output.history["[Fe/H]"], c = visuals.colors()[color]) axes[1].plot(output.history["time"], output.history["[O/Fe]"], c = visuals.colors()[color])
def plot_legend(ax):
"""
Draws the legend on the axis
Parameters
==========
ax :: subplot
The matplotlib axis object to put the legend on
"""
# First label the studies ...
lines = len(_STUDIES_) * [None]
for i in range(len(lines)):
lines[i] = ax.plot([-1, -2], [1.e-8, 1.e-6],
c=visuals.colors()["white"],
label=_NAMES_[_STUDIES_[i]])[0]
leg = ax.legend(loc=visuals.mpl_loc()["lower right"],
ncol=1,
bbox_to_anchor=(0.99, 0.01),
frameon=False,
handlelength=0,
fontsize=18)
for i in range(len(lines)):
lines[i].remove()
leg.get_texts()[i].set_color(_COLORS_[_STUDIES_[i]])
ax.add_artist(leg)
# ... then label the rotational velocities
points = 3 * [None]
for i in range(len(points)):
points[i] = ax.scatter(
[-1, -2], [1.e-8, 1.e-6],
c=visuals.colors()["black"],
s=50,
marker=visuals.markers()[_MARKERS_[[0, 150, 300][i]]],
label=r"$v_\text{rot}$ = %g km s$^{-1}$" % ([0, 150, 300][i]))
ax.legend(loc=visuals.mpl_loc()["upper left"],
ncol=1,
bbox_to_anchor=(0.01, 0.99),
frameon=False,
fontsize=18,
handlelength=1)
for i in range(len(points)):
points[i].remove()
def plot_legend(ax):
lines = 3 * [None]
linestyles = ['-', ':', '--']
colors = ["red", "black", "black"]
labels = ["Sr", r"Fe; $R_\text{Ia}\propto t^{-1.1}$",
r"Fe; $R_\text{Ia}\propto e^{-t/\tau_\text{Ia}}$"]
for i in range(3):
lines[i] = ax.plot([1, 2], [1, 2], c = visuals.colors()[colors[i]],
linestyle = linestyles[i], label = labels[i])[0]
leg = ax.legend(loc = visuals.mpl_loc()["lower left"], ncol = 1,
bbox_to_anchor = (0.01, 0.01), frameon = False)
for i in range(3):
lines[i].remove()
def plot_output(axes, name, color):
"""
Plots a VICE output on the output figure
Parameters
==========
axes :: 1-D list
The list of matplotlib axis objects to plot on
name :: str
The name of the VICE output
color :: str
The name of the color to plot in
"""
out = vice.output(name)
axes[0].plot(out.history["[Fe/H]"],
out.history["[Sr/Fe]"],
c=visuals.colors()[color])
bin_centers = list(
map(lambda x, y: (x + y) / 2., out.mdf["bin_edge_left"],
out.mdf["bin_edge_right"]))
axes[1].plot(bin_centers,
out.mdf["dn/d[sr/fe]"],
c=visuals.colors()[color])
def plot_output_3axes(axes, name, color):
"""
Overrides the visuals.plot_output_3axes function to omit time = 0 for the
infall rate. VICE does not know the infall rate at time = 0 when ran in
star formation mode.
"""
out = vice.output(name)
axes[0].plot(out.history["time"][1:],
out.history["ifr"][1:],
c=visuals.colors()[color],
linestyle='--')
axes[0].plot(out.history["time"],
out.history["sfr"],
c=visuals.colors()[color],
linestyle='-')
axes[1].plot(out.history["[Fe/H]"],
out.history["[O/Fe]"],
c=visuals.colors()[color])
axes[2].plot(list(
map(lambda x, y: (x + y) / 2., out.mdf["bin_edge_left"],
out.mdf["bin_edge_right"])),
out.mdf["dn/d[O/Fe]"],
c=visuals.colors()[color])
def plot_track(ax, name, ref, color, linestyle): """ Plots [O/X]-[X/H] tracks on a matplotlib subplot Args: ===== ax: The name of the subplot name: The name of the VICE output ref: The symbol for the reference element color: The color of the line linestyle: The linestyle to use """ out = vice.output(name) ax.plot(out.history["[%s/h]" % (ref)], out.history["[o/%s]" % (ref)], c = visuals.colors()[color], linestyle = linestyle)
def plot_functional(ax, func): """ Plots the yield as a function of metallicity on the axis Parameters ========== ax :: subplot The matplotlib axis object to plot on func :: <function> The function to plot on the axis """ small, big = ax.get_xlim() xvals = [small + (big - small) / 1000 * i for i in range(1000)] ax.plot(xvals, list(map(func, xvals)), linestyle = ':', c = visuals.colors()["black"])
def plot_track(ax, name, color): """ Plots a single [Sr/O]-[O/H] track Parameters ========== ax :: subplot The matplotlib axis object to plot on name :: str The name of the VICE output color :: str The name of the color to plot in """ output = vice.output(name) ax.plot(output.history["[O/H]"], output.history["[Sr/O]"], c = visuals.colors()[color])
def plot_vice_comparison(ax, name):
"""
Plots the [Mg/Fe]-[Fe/H] track of a given VICE model on the subplot.
Parameters
==========
ax :: matplotlib subplot
The axis to plot on
name :: str
The relative path to the VICE output
"""
out = vice.output(name)
ax.plot(out.history["[fe/h]"],
out.history["[mg/fe]"],
c=visuals.colors()["black"],
linestyle='--')
def plot_pdf(ax, output, color):
"""
Plot the [O/Fe] PDF in the specified [Fe/H] bin
Parameters
==========
ax :: subplot
The matplotlib axis object to plot on
output :: vice.output
The VICE output object containing the simulation results
color :: str
The color to plot in
"""
bins, pdf = get_ofe_pdf(output)
centers = list(map(lambda x, y: (x + y) / 2., bins[1:], bins[:-1]))
ax.plot(centers, pdf, c=visuals.colors()[color])
def plot_ifr(ax, name, color): """ Plots the gas inflow rate on a given matplotlib subplot given the name of the VICE output Parameters ========== ax :: subplot The matplotlib axis to plot the inflow rate on name :: str The name of the VICE output color :: str The name of the color to plot in """ out = vice.output(name) ax.plot(out.history["time"], out.history["ifr"], linestyle = '--', c = visuals.colors()[color])
def draw_ofe_legend(ax): """ Draws the legend differentiating between oxygen and iron in the plot of [X/H] against time. Parameters ========== ax :: subplot The matplotlib axis object to put the legend on """ lines = 2 * [None] for i in range(2): lines[i] = ax.plot([1, 2], [1, 2], c = visuals.colors()["black"], label = ["O", "Fe"][i], linestyle = ['--', '-'][i])[0] ax.legend(loc = visuals.mpl_loc()["upper left"], frameon = False, bbox_to_anchor = (0.01, 0.99)) for i in range(2): lines[i].remove()
def plot_AGB_legend(ax, z): """ Draws the legend for the AGB yields on the subplot Parameters ========== ax :: subplot The matplotlib axis object to plot on z :: list The metallicities """ lines = len(z) * [None] for i in range(len(z)): lines[i] = ax.plot([1, 2], [1, 2], c = visuals.colors()["white"], label = "Z = %g" % (z[i]))[0] leg = ax.legend(loc = visuals.mpl_loc()["upper right"], ncol = 1, bbox_to_anchor = (0.99, 0.99), frameon = False, handlelength = 0) for i in range(len(z)): lines[i].remove() leg.get_texts()[i].set_color(_COLORS_[i])
def plot_yield_against_metallicity(ax, element, color, linestyle):
"""
Plots the late-time fractional yield of a given element against
metallicity.
Parameters
==========
ax :: subplot
The matplotlib axis object to plot on
element :: str
The element to plot the yield of
color :: str
The name of the color to plot in
linestyle :: str
The linestyle to adopt
"""
MonH = [-4. + 0.01 * i for i in range(401)]
fractional = len(MonH) * [0.]
for i in range(len(fractional)):
mass, times = vice.single_stellar_population(element,
Z=_Z_SOLAR_ * 10**MonH[i])
fractional[i] = 1.e8 * mass[-1] / 1.e6
ax.plot(MonH, fractional, c=visuals.colors()[color], linestyle=linestyle)
def plot_representative_errorbar(ax, data, dwarf):
"""
Plots a representative error bar in the lower-left corner of the figure
Parameters
==========
ax :: matplotlib subplot
The axis object to put the errorbar on
data :: 2D-list
The raw data itself
dwarf :: str
The name of the dwarf to take the median errors from
"""
err_FeH_column = 13
err_MgFe_column = 15
fltrd = list(filter(lambda x: x[0] == dwarf, data))
ax.errorbar(-2.8,
-0.4,
xerr=sorted([row[err_FeH_column]
for row in fltrd])[len(fltrd) // 2],
yerr=sorted([row[err_MgFe_column]
for row in fltrd])[len(fltrd) // 2],
ms=0,
color=visuals.colors()[_COLORS_[dwarf]])
