SymCircuit 0.2.0

Symbolic electronic circuit analysis

SymCircuit

Provides classes to do electronic circuit analysys using symbolic equations. For example, it is possible to automatically find equations using Kirchhoff's laws and solve them for specific properties.

As a bonus, the equation solving part can be used independently of the rest.

Installation

Minimal install using pip (just the equation solver):

pip install SymCircuit

Full install using pip:

pip install SymCircuit[EE]

Usage

For more detailed examples, see the files in directory examples/.

Example of using a netlist for a random arrangement of elements:

from io import StringIO

import plotkit.plotkit as pk

from symcircuit.bode import plot_system
from symcircuit.spice import Circuit
from symcircuit.system import SymbolicSystem

circ = Circuit()
circ.parse_spice_netlist(StringIO(r"""
* examples\network1.asc
R1 N001 0 1k
R2 N002 0 3k
C1 N002 0 50µ
L1 N001 N002 120µ
V1 N001 0 AC 1
.ac dec 30 10 10000
.backanno
.end
"""))

# translate to equation system
s = SymbolicSystem(circ.to_system_description())

# Add "measurement" characteristics
s.extend(SymbolicSystem("""
Zsys == V1 / i_V1
"""))
print(s.info())

# find transfer function
impedance = s.focus("Zsys")["Zsys"]
print("System Impedance = ", impedance)
# System Impedance =  -R1*(C1*L1*R2*s**2 + L1*s + R2)/(C1*L1*R2*s**2 + L1*s + R1*(C1*R2*s + 1) + R2)

# plot parameterised transfer function
v = dict(
    R1=1e3,
    R2=3e3,
    C1=50e-6,
    L1=120e-6,
)
fig = plot_system(impedance, 10, 50000, values=v, amplitude_linear=True, return_fig=True)
pk.finalize(fig)

Result:

Credits:

• NetworkX is used for graph analysis
• The focus and seek methods are based on the implementation proposed by Christopher Smith @smichr in a sympy issue.