e2scapy 0.0.1

this solve electrical circuits by symbolic way

Hi welcome to E2SCAPy V 0.0.1

E2SCAPy is : Electronic & Electronic Symbolic Circuit Analisys on Python

here you can understand how to use this library...

1.- formulation:

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E2SCAPy is simple and powerfull

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ESCAPy works whit MNA (Modify Nodal Analisys) theory and MNA is a formulation used for electrical circuit and all theory was obteined for Mourad Fakhfakh, Esteban Tlelo Cuautle Francisco V. Fernandez and other authors and MNA gets an algebraic system by the way Ax = z where A is a square matrix, x is incognigts vector and z is an input system where z have independent sources like voltage and current sources.

other important think is Netlist input, the algorithm works whit an Netlist input this netlist can be generated by spice tool in my personal experience I had been used LTSPICE works good and is open source, this Netlist should be a order for example if we have a circuit like this Netlist:

V1 1 0
R1 1 2
C1 2 0
L1 2 3
R2 3 0
I1 0 3

I recomend reorder al elements by type and numbrer like this:

V1 1 0
R1 1 2
R2 3 0
C1 2 0
L1 2 3
I1 0 3

and before save the Netlist whit .cir extension this is necesary put this .cir whit program.py in other words in the same folder.

Important if you have been interested in how to learn do Netlist easy and fast I recomend you visist scam MATLAB for Erik Cheever web site:

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https://lpsa.swarthmore.edu/Systems/Electrical/mna/MNA6.html

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but dont worry I have been generated some examples you can check it in examples.

2.- solutions:

the solution for A matrix should be do it by Gauss Elimination (GE), adjunte matrix (ADJ) and Lower and Upper method (LU) all of this are implemented by Sympy and collected on ESCAPy but if you are searching power compute... Welcome to DDD (Determinant Diagram Decision) this idea was collected from Sheldon Tan and developed for me.

DDD Method should compute matrix whit size 4x4 and up. If you try compute a system 3x3 or 2x2 is important don't use DDD, just use Sympy method (ADJ, GE or LU).

DDD works whit symengine is fast and also DDD works better.

3.- outputs:

you can have an output in latex way or simple aoutput, and also you can have an estetic output, depend of size circuit, and oviously output size.

4.- instructions for use E2SCAPy:

you can use this repository or simple install library by pip,

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pip install e2scapy

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do a netlist, import escapy and put netlist name and extension let me show you:

from e2scapy import e2scapy as e2
escapy.MNAf('3_OpAmps.cir')

A,x,z = e2.formula_DDD()
Xout = e2.resuelve_serie_DDD(A,x,z)
x_out = e2.simplifica(Xout)

also you can use a multiprocess method for solve a determinant in DDD:

from e2scapy import e2scapy as e2 
e2.MNAf('3_OpAmps.cir')

A,x,z = e2.formula_DDD()
Xout = e2.resuelve_paralelo_DDD(A,x,z)
x_out = e2.simplifica(Xout)

and if you prefer use an sympy method:

from e2scapy import e2scapy as
e2.MNAf('3_OpAmps.cir')

A,x,z = e2.formula_sympy()
Xout = e2.resuelve_LU(A,x,z)
x_out = e2.simplifica(X1)

finaly in terminal you can write:

x_out 
x

or

print(x_out)
print(x)

remember all incongnits x verctor represent an output from x_out

be happy and anjoy!