# Brian package structureÂ¶

List of modules with descriptions of contents:

**Root package**

`base`

- Shared base classes for some Brian clases. At the moment, just the
`ObjectContainer`

class used to implement the`contained_objects`

protocol. `clock`

- The
`Clock`

object,`guess_clock()`

function, and other clock manipulation functions. `compartments`

- A class used in compartmental modelling (see user documentation).
`connection`

- Everything to do with connections, including the
`Connection`

and`DelayConnection`

classes, but also construction/connection matrices and connection vector code. One of the longest and most technical parts of Brian. `correlatedspikes`

- A tool for producing correlated spike trains.
`directcontrol`

- Classes for producing groups which fire spikes at user specified times.
`equations`

- Everything to do with the
`Equations`

class. `globalprefs`

- Global preferences for Brian, a few routines for getting and setting.
`group`

- A base class for
`NeuronGroup`

which creates an`_S`

attribute from an`Equations`

object with the appropriate dynamical variables, and allows these variables to be accessed by e.g.`grp.V`

by overriding the`__getattr__`

and`__setattr__`

methods. `inspection`

- Utility functions for inspecting namespaces, checking consistency of equations, some code manipulation, etc.
`log`

- Brian’s somewhat under-developed logging capabilities.
`magic`

- Classes and functions for tracking and finding instances of classes.
`membrane_equations`

- More code for compartmental modelling (see user docs).
`monitor`

- All the monitors, including
`SpikeMonitor`

and`StateMonitor`

. `network`

- The
`Network`

and`MagicNetwork`

classes as well as the`NetworkOperation`

class. Also includes the`run()`

, etc. functions. `neurongroup`

- The
`NeuronGroup`

definition and some related stuff, including linked variables (the`LinkedVar`

class) and`PoissonGroup`

. `optimiser`

- Some tools for freezing expressions (converting e.g.
`3*ms`

into 0.003) and simplifying some equations (e.g.`a/(10*ms)`

converted to`a*100`

). `plotting`

- Plotting tools, mostly
`raster_plot`

. `quantityarray`

- A leftover from the day when Brian had support for arrays with units, will be removed when practical.
`reset`

- Reset classes.
`stateupdater`

- State update classes and the
`magic_state_updater()`

function. `stdp`

- STDP features.
`stdunits`

- Standard unit names such as
`mV`

for`mvolt`

, etc. `stp`

- Short term plasticity features.
`threshold`

- Threshold classes.
`timedarray`

- The
`TimedArray`

class and related functions. `units`

- The Brian units package, including the
`Quantity`

class. `unitsafefunctions`

- Some functions which override the numpy ones which are safe to use with
units, e.g.
`sin(3*volt)`

raises a dimensionality error.

**``library`` subpackage**

`electrophysiology`

- Electrophysiology library with electrode and amplifier models.
`IF`

- Integrate-and-fire models (leaky, quadratic, exponential...).
`ionic_currents`

- Ionic current models (K+, Na+...).
`random_processes`

- Currently only Ornstein-Uhlenbeck.
`synapses`

- Synaptic models (exponential, alpha and biexponential models).

**``utils`` subpackage**

`approximatecomparisons`

- Some tools for doing approximate comparisons with floating point numbers (because they are inexact).
`autodiff`

- Automatic differentiation routines (for single-valued functions).
`circular`

and the`ccircular`

subpackage- The important
`SpikeContainer`

and related classes. The`C`

version uses SWIG and is much faster but requires the user to compile themselves at the moment (this will be addressed at some point in the future). `documentation`

- Some utility functions related to documentation.
`information_theory`

- Entropy and mutual information estimators. Requires the ANN wrapper in scikits.
`parallelpython`

- A utility function for using the Parallel Python module.
`parameters`

- The
`Parameters`

class, basically independent of Brian but potentially useful. `progressreporting`

- A progress reporting framework which
`Network.run()`

can use to report how long it is taking to run, with text or graphical options. `statistics`

- Statistics of spike trains (CV, vector strength, correlograms...).
`tabulate`

- Tabulation of numerical functions (precalculation).