As well as the ability to extract data out of catalogues in a more efficient way, the VELOCIraptor python toolkit also contains useful tools for creating plots in a programatic way. These tools are available in the :mod:`velociraptor.tools` module.
You can automatically generate labels for a given dataset using the :func:`velociraptor.tools.labels.get_full_label` function, as follows:
from velociraptor import load
from velociraptor.tools.labels import get_full_label
data = load("...properties")
m = data.masses.mass_200crit
label = get_full_label(m)This label is a LaTeX string containing a description of the dataset and
the symbolic units of whatever you converted it to.
You can also generate labels for mass functions:
from velociraptor.tools.labels import get_mass_function_label
import unyt
label = get_mass_function_label("*", unyt.Mpc**(-3))which produces d$n(M_*)$/d$log_{10}M_*$ [Mpc$^{-3}$].
One frequent activity is to generate binned lines for a figure, for instance in a plot of x against y you may wish to have the mean or median of y in equally spaced bins of x.
We provide two functions, :func:`velociraptor.tools.lines.binned_mean_line` and :func:`velociraptor.tools.lines.binned_median_line`, to perform this task for mean and median bins respectively. They both return scatter, with the mean line returning the standard deviation and the median line by default returning the 16-86 percentile scatter.
from velociraptor import load
from velociraptor.tools.lines import binned_median_line
from numpy import logspace
from unyt import unyt_array, Solar_Mass
data = load("...properties")
bins = unyt_array(np.logspace(10, 15, 25), units=Solar_Mass)
centers, median, deviation = binned_mean_line(
x=data.apertures.mass_30_kpc.to(Solar_Mass),
y=data.apertures.rhalfmass_30_kpc,
x_bins=bins
)Generating mass functions can be tricky, especially if you wish to plot them on 'true' axes (i.e. plotting mass on the x axis, not log(mass)). We provide functionality to create the mass function through :func:`velociraptor.tools.mass_functions.create_mass_function`. This returns the bin centers, mass function, and poisson scatter in that bin. If you wish to use your own mass bins, you can use the alternative :func:`velociraptor.tools.mass_functions.create_mass_function_given_bins`.
from velociraptor import load
from velociraptor.tools.mass_functions import create_mass_function
from unyt import Solar_Mass
data = load("...properties")
masses = data.masses.mass_200mean
box_volume = data.units.comoving_box_volume
centers, mf, scatter = create_mass_function(
masses=masses,
lowest_mass=1e8*Solar_Mass,
highest_mass=1e15*Solar_Mass,
box_volume=box_volume,
n_bins=25
)We also provide an adaptive mass function plotting code; this allows for
variable bin widths and is useful in the case where you have very few data
points. It is called through
:func:`velociraptor.tools.mass_functions.create_adaptive_mass_function` and
has the same parameters as create_mass_function except that n_bins is
now base_n_bins. The algorithm works as follows:
- Attempt to use the standard binning scheme based on fixed-width bins, by trawling the data from left (low M_*) to right (high M_*).
- If you have passed more than n items by the time you get to the next bin (standard is 0.2 dex in M_*)$, create the bin as normal and plot the point as the median mass value.
- If not, continue until you have at least n items in the bin. Once you do, call this a new 'bin' with the right edge of the bin being the value you just found. Place the point at the median value of M_* in this bin.
- The highest mass value within a given bin becomes the right edge of that bin and hence the left edge of the next bin.
- Once you have reached the end of the data, attempt to make one final bin with the leftovers. If there is only one item in the final bin, we extend the previous bin to include it.
By default n = 3.