PyDSTool.Model.Model:
General-purpose Hybrid and Non-Hybrid Model abstract class.
PyDSTool.Model.HybridModel:
obsvars specifies the observable variables for this model, which
must be present in all trajectory segments (regardless of which
other variables are specified in those segments).
PyDSTool.MProject.ModelLibrary:
Store a set of related candidate model types, and within each,
represent various relevant "dimensions" along which the
model can be augmented structurally.
PyDSTool.ModelConstructor'.GDescriptor:
All-in-one descriptor class for single Generators, and information
necessary to be able to build a Model object using a
ModelConstructor call -- i.e.
PyDSTool.ModelConstructor'.MDescriptor:
All-in-one descriptor class for hybrid model definitions and
information necessary to be able to build a Model object using a
ModelConstructor call.
PyDSTool.Toolbox.phaseplane.distance_to_pointset:
First and second maximum and/or minimum distances of a point q
to a set of points, returning a dictionary keyed by 'min' and
'max' to dictionaries keyed by integers 1 and 2 (respectively).
PyDSTool.MProject.GeneratorInterface:
Wrapper for Generator (for non-hybrid models) that shares similar
API with ModelInterface for use in HybridModel objects.
PyDSTool.MProject.ModelInterface:
Model constraints expressed as a uni-directional interface to another
formal system model:
- Made up of conditions imposed on the other system's test trajectory.
PyDSTool.MProject.extModelInterface:
Interface from a trajectory of numerical data and test conditions
providing external evaluation criteria for a model.
PyDSTool.Toolbox.phaseplane.dx_scaled_2D:
Supports a delta x vector that automatically re-scales according to
the known scalings of each of the vector's component directions.
PyDSTool.MProject.binary_feature:
Use this as a binary switch feature, toggled by a given variable
name 'varname' that is supplied in the pars dict at initialization.
PyDSTool.Toolbox.neuro_data.get_burst_spikes:
Requires a get_spike_data and get_spike_model instance to be the
only sub-features (supplied as a dict with keys 'is_spike_data' and
'is_spike_model').
PyDSTool.common.fit_quadratic_at_vertex:
Fit a quadratic function y=a*(x+h)**2+k to the (x,y) array data,
constrained to have a vertex at (h, k), leaving only the free
parameter a for the curvature.
PyDSTool.Toolbox.phaseplane.fixedpoint_nD:
IMPORTANT: Any complex eigenvectors are stored as pairs of real eigenvectors,
with the understanding that the corresponding complex eigenvalues indicate the
use of these eigenvectors as a solution basis with the trig functions.
PyDSTool.Toolbox.phaseplane.fixedpoint_2D:
IMPORTANT: Any complex eigenvectors are stored as pairs of real eigenvectors,
with the understanding that the corresponding complex eigenvalues indicate the
use of these eigenvectors as a solution basis with the trig functions.
PyDSTool.common.metric_weighted_L2:
Measures the standard "distance" between two 1D pointsets
or arrays using the L-2 norm, after weighting by weights attribute
(must set weights after creation, e.g.
PyDSTool.Toolbox.neuro_data.spike_metric:
Measures the distance between spike time and height, using an
inherent weighting of height suited to neural voltage signals (0.05
of time distance).
PyDSTool.ModelSpec'.nameResolverClass:
This class keeps a tab of how many times a local name has been used
for a given specfication type ('var', 'par', 'input' or 'auxfn'),
and renames it with an appropriate globalized name (hierarchical
according to declared parent object, with possible numbered suffix
for multiple name declarations).