vice.output

Reads in the output from singlezone simulations and allows the user to access it easily via dataframes.

Signature: vice.output(name)

Parameters

namestr

The full or relative path to the output directory. The ‘.vice’ extension is not required.

Note

If name corresponds to output from the multizone class, a multioutput object is created instead.

Attributes

namestr

The name of the .vice directory containing the simulation output.

elementstuple

The symbols of the elements whose enrichment was tracked by the simulation, as they appear on the periodic table.

historydataframe

The dataframe read in via vice.history.

mdfdataframe

The dataframe read in via vice.mdf.

agb_yieldsdataframe

The asymptotic giant branch star yields employed in the simulation.

ccsne_yieldsdataframe

The core-collapse supernova yields employed in the simulation.

sneia_yieldsdataframe

The type Ia supernova yields employed in the simulation.

Note

Reinstancing functional yields and simulation parameters requires dill, an extension to pickle in the python standard library. It is recommand that VICE users install dill >= 0.2.0.

Tip

VICE outputs are stored in directories with a ‘.vice’ extension following the name of the simulation. This allows users to run <command> *.vice in a terminal to run commands on all VICE outputs in a given directory.

Functions

See also

  • vice.history

  • vice.mdf

  • vice.multioutput

Example Code

>>> import vice
>>> out = vice.output("example")
>>> out.history[100]
        vice.dataframe{
                time -----------> 1.0
                mgas -----------> 5795119000.0
                mstar ----------> 2001106000.0
                sfr ------------> 2.897559
                ifr ------------> 9.1
                ofr ------------> 7.243899
                eta_0 ----------> 2.5
                r_eff ----------> 0.3534769
                z_in(fe) -------> 0.0
                z_in(sr) -------> 0.0
                z_in(o) --------> 0.0
                z_out(fe) ------> 0.0002769056
                z_out(sr) ------> 3.700754e-09
                z_out(o) -------> 0.001404602
                mass(fe) -------> 1604701.0
                mass(sr) -------> 21.44631
                mass(o) --------> 8139837.0
                z(fe) ----------> 0.0002769056166059748
                z(sr) ----------> 3.700754031107903e-09
                z(o) -----------> 0.0014046022178319376
                [fe/h] ---------> -0.6682579454664828
                [sr/h] ---------> -1.1074881208001155
                [o/h] ----------> -0.6098426789720387
                [sr/fe] --------> -0.43923017533363273
                [o/fe] ---------> 0.05841526649444406
                [o/sr] ---------> 0.4976454418280768
                z --------------> 0.0033582028978416337
                [m/h] ----------> -0.6200211036287412
                lookback -------> 9.0
        }
>>> out.mdf[60]
        vice.dataframe{
                bin_edge_left --> 0.0
                bin_edge_right -> 0.05
                dn/d[fe/h] -----> 0.0
                dn/d[sr/h] -----> 0.0
                dn/d[o/h] ------> 0.0
                dn/d[sr/fe] ----> 0.06001488
                dn/d[o/fe] -----> 0.4337209
                dn/d[o/sr] -----> 0.0
        }