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Package PyDSTool :: Module Variable'
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Module Variable'

source code

Variable is a one-dimensional discrete and continuous real variable class.

Robert Clewley, July 2005

Classes [hide private]
  HybridVariable
Mimics part of the API of a non-hybrid variable.
  OutputFn
One-dimensional function wrapper.
  VarDiagnostics
  Variable
One-dimensional discrete and continuous real variable class.
Functions [hide private]
 
iscontinuous(var)
Determine if variable is continuously defined on its input and output domains.		 source code
 
isdiscrete(var)
Determine if variable is discretely defined on its input and output domains.		 source code
 
isinputcts(obj) source code
 
isinputdiscrete(var) source code
 
isoutputcts(var) source code
 
isoutputdiscrete(obj) source code
 
numeric_to_vars(vals, coordnames, indepvar=None, indepvarname='t', indepdomain=None, all_types_float=True, discrete=True, abseps=None, labels=None)
Utility to convert numeric types to a dictionary of Variables.		 source code
 
pointset_to_vars(pts, discrete=True)
Utility to convert Pointset to a dictionary of Variables.		 source code
Variables [hide private]
  API = API_class()
  Continuous = Continuous Domain
  Discrete = Discrete Domain
  Inf = inf
  LargestInt32 = 2147483647
  NaN = nan
  _1DimplicitSolveMethods = ['newton', 'bisect', 'steffe']
  _all_complex = (<type 'complex'>, <type 'numpy.complexfloating...
  _all_float = (<type 'float'>, <type 'numpy.floating'>, <type '...
  _all_int = (<type 'int'>, <type 'numpy.integer'>, <type 'numpy...
  _all_numpy_complex = (<type 'numpy.complex128'>, <type 'numpy....
  _all_numpy_float = (<type 'numpy.float64'>, <type 'numpy.float...
  _all_numpy_int = (<type 'numpy.int32'>, <type 'numpy.int32'>, ...
  _complex_types = (<type 'complex'>, <type 'numpy.complexfloati...
  _float_types = (<type 'float'>, <type 'numpy.floating'>)
  _implicitSolveMethods = ['newton', 'bisect', 'steffe', 'fsolve']
  _int_types = (<type 'int'>, <type 'numpy.integer'>)
  _num_equivtype = {<type 'float'>: <type 'numpy.float64'>, <typ...
  _num_maxmin = {<type 'numpy.int32'>: [-2147483648, 2147483647]...
  _num_name2equivtypes = {'float': (<type 'float'>, <type 'numpy...
  _num_name2type = {'float': <type 'numpy.float64'>, 'int': <typ...
  _num_type2name = {<type 'float'>: 'float', <type 'int'>: 'int'...
  _num_types = (<type 'float'>, <type 'int'>, <type 'numpy.float...
  _pytypefromtype = {<type 'numpy.int32'>: <type 'int'>, <type '...
  _real_types = (<type 'int'>, <type 'numpy.integer'>, <type 'fl...
  _seq_types = (<type 'list'>, <type 'tuple'>, <type 'numpy.ndar...
  contained = contained
  isfinite = <ufunc 'isfinite'>
  notcontained = notcontained
  null_predicate = null_predicate_class(None)
  targetLangs = ['c', 'python', 'matlab']
  uncertain = uncertain
Function Details [hide private]

numeric_to_vars(vals, coordnames, indepvar=None, indepvarname='t', indepdomain=None, all_types_float=True, discrete=True, abseps=None, labels=None)

source code 

Utility to convert numeric types to a dictionary of Variables. If discrete option set to True (default is False) then the Variables will be linearly interpolated within their domain.

pointset_to_vars(pts, discrete=True)

source code 

Utility to convert Pointset to a dictionary of Variables. If discrete option set to False (default is True) then the Variables will be linearly interpolated within their domain.

Any labels in the pointset will be preserved in the Variables in case of their re-extraction using the getDataPoints method.


Variables Details [hide private]

_all_complex

Value:
(<type 'complex'>,
 <type 'numpy.complexfloating'>,
 <type 'numpy.complex128'>,
 <type 'numpy.complex64'>,
 <type 'numpy.complex128'>)

_all_float

Value:
(<type 'float'>,
 <type 'numpy.floating'>,
 <type 'numpy.float64'>,
 <type 'numpy.float32'>,
 <type 'numpy.float64'>)

_all_int

Value:
(<type 'int'>,
 <type 'numpy.integer'>,
 <type 'numpy.int32'>,
 <type 'numpy.int32'>,
 <type 'numpy.int8'>,
 <type 'numpy.int16'>,
 <type 'numpy.int32'>,
 <type 'numpy.int64'>)

_all_numpy_complex

Value:
(<type 'numpy.complex128'>,
 <type 'numpy.complex64'>,
 <type 'numpy.complex128'>)

_all_numpy_float

Value:
(<type 'numpy.float64'>,
 <type 'numpy.float32'>,
 <type 'numpy.float64'>)

_all_numpy_int

Value:
(<type 'numpy.int32'>,
 <type 'numpy.int32'>,
 <type 'numpy.int8'>,
 <type 'numpy.int16'>,
 <type 'numpy.int32'>,
 <type 'numpy.int64'>)

_complex_types

Value:
(<type 'complex'>, <type 'numpy.complexfloating'>)

_num_equivtype

Value:
{<type 'float'>: <type 'numpy.float64'>,
 <type 'int'>: <type 'numpy.int32'>,
 <type 'numpy.integer'>: <type 'numpy.int32'>,
 <type 'numpy.floating'>: <type 'numpy.float64'>,
 <type 'numpy.int8'>: <type 'numpy.int32'>,
 <type 'numpy.int16'>: <type 'numpy.int32'>,
 <type 'numpy.int32'>: <type 'numpy.int32'>,
 <type 'numpy.int32'>: <type 'numpy.int32'>,
...

_num_maxmin

Value:
{<type 'numpy.int32'>: [-2147483648, 2147483647],
 <type 'numpy.float64'>: [-inf, inf]}

_num_name2equivtypes

Value:
{'float': (<type 'float'>,
           <type 'numpy.floating'>,
           <type 'numpy.float64'>,
           <type 'numpy.float32'>,
           <type 'numpy.float64'>),
 'int': (<type 'int'>,
         <type 'numpy.integer'>,
         <type 'numpy.int32'>,
...

_num_name2type

Value:
{'float': <type 'numpy.float64'>, 'int': <type 'numpy.int32'>}

_num_type2name

Value:
{<type 'float'>: 'float',
 <type 'int'>: 'int',
 <type 'numpy.integer'>: 'int',
 <type 'numpy.floating'>: 'float',
 <type 'numpy.int8'>: 'int',
 <type 'numpy.int16'>: 'int',
 <type 'numpy.int32'>: 'int',
 <type 'numpy.int32'>: 'int',
...

_num_types

Value:
(<type 'float'>,
 <type 'int'>,
 <type 'numpy.floating'>,
 <type 'numpy.integer'>)

_pytypefromtype

Value:
{<type 'numpy.int32'>: <type 'int'>,
 <type 'numpy.float64'>: <type 'float'>}

_real_types

Value:
(<type 'int'>,
 <type 'numpy.integer'>,
 <type 'float'>,
 <type 'numpy.floating'>)

_seq_types

Value:
(<type 'list'>, <type 'tuple'>, <type 'numpy.ndarray'>)

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