lcapy.network.Network

class lcapy.network.Network

Bases: object

This is the base class for network objects.

Methods

circuit()	Convert a Network object into a Circuit object.
describe()	Print a message describing how network is solved.
draw([filename, layout, form, evalf])	Draw schematic of network.
latex(**kwargs)
netlist([layout, evalf])	Create a netlist.
noisy([T])	Create noisy network model by replacing resistances with a series combination of a resistance and a noise voltage source.
pdb()	Enter the python debugger.
pprint()
pretty(**kwargs)
sch([layout, evalf])	Convert a Network object into a Schematic object.
simplify()
subs(*args, **kwargs)
transform([form])	Transform the network impedance into an alternative form.

Attributes

analysis
cct	Convert a Network object into a Circuit object.
cpt_type
has_ac
has_dc
has_ic
has_independent_source
has_transient
initial_value_problem
is_IVP
is_ac
is_capacitor
is_causal
is_conductor
is_current_source
is_dc
is_inductor
is_noiseless
is_parallel
is_resistor
is_series
is_transformer
is_voltage_source
kinds	Return list of transform domain kinds.
kwargs
netkeyword
params	Return list of symbols used as arguments in the network.
symbols	Return dictionary of symbols defined in the network.
zeroic

property cct

Convert a Network object into a Circuit object.

circuit()

Convert a Network object into a Circuit object.

describe()

Print a message describing how network is solved.

draw(filename=None, layout='horizontal', form=None, evalf=False, **kwargs)

Draw schematic of network.

Parameters:

• filename – The name of the file to produce. If None, the schematic is displayed on the screen.

• layout – This is either ‘horizontal’, ‘vertical’, or ‘ladder’.

• evalf – This can be False or an integer specifying the number of decimal places used to evaluate floats.

• kwargs – These include:

• label_ids (-)

• label_values (-)

• draw_nodes (-) –

  • True: show all nodes

  • False: show no nodes

  • ’primary’: show primary nodes

  • ’connections’: show nodes that connect more than two components

  • ’all’: show all nodes

• label_nodes (-) –

  • True: label all nodes

  • False: label no nodes

  • ’primary’: label primary nodes

  • ’alpha’: label nodes starting with a letter

  • ’pins’: label nodes that are pins on a chip

  • ’all’: label all nodes

• style (-)

• scale (-)

• node_spacing (-)

• cpt_size (-)

• dpi (-)

• help_lines (-)

• debug (-)

Notes

If using Jupyter, then need to first issue command %matplotlib inline

property kinds

Return list of transform domain kinds.

netlist(layout='horizontal', evalf=None)

Create a netlist.

layout can be ‘horizontal’, ‘vertical’, or ‘ladder’.

evalf can be False or an integer specifying the number of decimal places used to evaluate floats.

noisy(T='T')

Create noisy network model by replacing resistances with a series combination of a resistance and a noise voltage source.

property params

Return list of symbols used as arguments in the network.

pdb()

Enter the python debugger.

sch(layout='horizontal', evalf=False)

Convert a Network object into a Schematic object.

property symbols

Return dictionary of symbols defined in the network.

transform(form='cauerI')

Transform the network impedance into an alternative form. The transformation is performed using network synthesis of the network’s impedance (note, this ignores the sources). form includes: cauerI, cauerII, fosterI, fosterII.

Note some methods generate networks with negative value components.