diskpy.clumps.simclumps package

Module contents

Created on Sat Jul 18 15:36:26 2015

@author: ibackus

diskpy.clumps.simclumps.newSimgroup(simlist)

Generates a new simgroup object from a list of clumplists.

diskpy.clumps.simclumps.newSim(clumplist)

Generates a sim object from a list of clump dictionaries for an entire simulation.

diskpy.clumps.simclumps.newClump(clumpDict)

Generates a new clump object from a clump dictionary (see clumps.blank_clump and clumps.build_clumps).

diskpy.clumps.simclumps.clump(nt)

Generates a clump object, which is basically just a pynbody SimSnap where time steps are represented by particles.

ARGUMENTS

nt : int

Number of time steps in the simulation

class diskpy.clumps.simclumps.sim

Bases: numpy.ndarray

The sim class. sims are basically just numpy arrays containing clump objects. It stores data for all the clumps in a given simulation (for all available time steps). Additionally, slicing can be done in different ways (see below)

To initialize a blank sim object:

>>> s = sim(nClumps)

To generate a sim object from a list of clumpDicts for a simulation (ie the output of clumps.clump_tracker())

>>> s = newSim(clumplist)

Where nClumps is the number of clumps in the simulation

Accessing different quantites:

>>> s = newSim(clumplist) # create sim object from clumplist
>>> x = s('x', t=slice(None)) # get x for all clumps at all times
# Get the mass for the first time step at which the clumps exist
>>> m0 = s('mass',t=0,clumpexist=True)
# Get velocity for the final timestep at which a clump exists
>>> vf = s('vel', t=-1, clumpexist=True)
# Get masses of all clumps at end of simulation
>>> all_masses = s('mass', t=-1)
>>> mask = ~np.isnan(all_masses)
>>> mf = all_masses[mask]

Print available keys:

>>> s.keys()

Select a sub-group of clumps by normal array slicing:

>>> s1 = s[0:10]

CALL FUNCTION ARGUMENTS s(key, t=None, clumpexist=False, clump=None)

key : str

Clump key to access

t : slicer

Anything that can be used to slice a numpy array, eg [1,2,4] or slice(0,-1). Slices according to the simulation time

clumpexist : bool

Filter out all quantities by whether the clump exists at that time. e.g., this makes it easy to select the first timestep when a clump exists

clump : slicer

Anything that can be used to slice a numpy array, eg [1,2,4] or slice(0,-1). Slices by clump number

keys()

Return keys present in all clumps

nClumps()

Returns the number of clumps in the simulation

nt()

Returns the number of timesteps in the simulation

class diskpy.clumps.simclumps.simgroup

Bases: numpy.ndarray

The simgroup class. Basically just an array containing a bunch of sim objects. Meant to contain information for clumps in a suite of simulations

To initialize a blank sim group:

>>> sgrp = simgroup(nSims)

To initialize from a list of simulations (ie a list of the outputs from clumps.clumptracker()):

>>> sgrp = newSimgroup(simlist)

Accessing different quantites:

>>> s = newSimgroup(simlist) # create sim object from simlist
>>> x = s('x', t=slice(None)) # get x for all clumps at all times
# Get the mass for the first time step at which the clumps exist
>>> m0 = s('mass',t=0,clumpexist=True)
# Get velocity for the final timestep at which a clump exists
>>> vf = s('vel', t=-1, clumpexist=True)
# Get masses of all clumps at end of simulation
>>> all_masses = s('mass', t=-1)
>>> mask = ~np.isnan(all_masses)
>>> mf = all_masses[mask]

Print available keys:

>>> s.keys()

Select a sub-group of simulations by normal array slicing:

>>> s1 = s[0:10]

CALL FUNCTION ARGUMENTS s(key, t=None, clumpexist=False, clump=None, sims=None)

key : str

Clump key to access

t : slicer

Anything that can be used to slice a numpy array, eg [1,2,4] or slice(0,-1). Slices according to the simulation time

clumpexist : bool

Filter out all quantities by whether the clump exists at that time. e.g., this makes it easy to select the first timestep when a clump exists

clump : slicer

Anything that can be used to slice a numpy array, eg [1,2,4] or slice(0,-1). Slices by clump number

sims : slicer

Anything that can be used to slice a numpy array, eg [1,2,4] or slice(0,-1). Slices by simulation number

keys()

Return keys present in all clumps

nClumps()

nsim()

Return the number of simulations present here

diskpy.clumps.simclumps.exists(sim)

Defines a pynbody derived array which determines the time steps a clump exists at

diskpy.clumps.simclumps.len2(x)

A modified version of len() to work with numbers. Numbers have a length of 1

diskpy.clumps.simclumps.arraylistcat(arraylist)

Concatenate a list of like arrays (or SimArrays) into a single array. Concatenates along the first dimension Returns None for an empty list