Metadata-Version: 2.1
Name: escapy
Version: 0.0.1
Summary: this solve electrical circuits by symbolic way
Author-email: luisCorl <lui.corl.ing@hotmail.com>
Project-URL: Homepage, https://github.com/luisCorl/escapy
Project-URL: Issues, https://github.com/luisCorl/escapy
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Requires-Python: >=3.4
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# Hi welcome to ESCAPy V 0.0.1
# ESCAPy is : Electronic Symbolic Circuit Analisys on Python
#
# here you can understand how to use this library...



>> 1.- formulation:

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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 ESCAPy:

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



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


>>
	from escapy import scapy 
	escapy.MNAf('3_OpAmps.cir')

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

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

>>
	from escapy import scapy 
	scapy.MNAf('3_OpAmps.cir')

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

and if you prefer use an sympy method:

>>
	from escapy import scapy 
	escapy.MNAf('3_OpAmps.cir')

	A,x,z = scapy.formula_sympy()
	Xout = scapy.resuelve_LU(A,x,z)
	x_out = scapy.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!
