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        "author": "Michael Hayes",
        "author_email": "michael.hayes@canterbury.ac.nz",
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            "License :: OSI Approved :: GNU Lesser General Public License v2 or later (LGPLv2+)",
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            "Programming Language :: Python :: 3"
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        "description": "Lcapy is a Python package for linear circuit analysis.  It uses SymPy\nfor symbolic mathematics.\n\n![Run tests and checks](https://github.com/mph-/lcapy/workflows/Run%20tests%20and%20checks/badge.svg)\n[![Binder](http://mybinder.org/badge.svg)](https://mybinder.org/v2/gh/mph-/lcapy/master)\n![Documentation](https://readthedocs.org/projects/docs/badge/?version=latest)\n\nLcapy can symbolically analyse circuits described with netlists or by series/parallel combinations of components.  It can also manipulate continuous-time and discret-time expressions.\n\nComprehensive documentation can be found at https://lcapy.readthedocs.io/en/latest/\n\n\nCircuit analysis\n----------------\n\nThe circuit is described using netlists, similar to SPICE, with\narbitrary node names (except for the ground node which is labelled 0).\nThe netlists can be loaded from a file or created at run-time.  For\nexample:\n\n    >>> from lcapy import Circuit, s, t\n    >>> cct = Circuit(\"\"\"\n    ... Vs 2 0 {5 * u(t)}\n    ... Ra 2 1\n    ... Rb 1 0\n    ... \"\"\")\n\nThe circuit can then be interrogated to determine branch currents,\nbranch voltages, and node voltages (with respect to the ground node 0).  For example:\n\n    >>> cct[1].V(t)\n    5\u22c5R_b\u22c5u(t)\n    \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n     R\u2090 + R_b\n    >>> cct.Ra.I(t)\n     5\u22c5u(t)\n    \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n    R\u2090 + R_b\n    >>> cct.Ra.V(s)\n       5\u22c5R\u2090\n    \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\n    s\u22c5(R\u2090 + R_b)\n\n\nOne-port networks\n-----------------\n\nOne-port networks can be created by series and parallel combinations\nof other one-port networks.  The primitive one-port networks are the\nfollowing ideal components:\n\n- V independent voltage source\n- I independent current source\n- R resistor\n- C capacitor\n- L inductor\n\nThese components are converted to s-domain models and so capacitor and\ninductor components can be specified with initial voltage and\ncurrents, respectively, to model transient responses.\n\nThe components have the following attributes:\n\n- Zoc open-circuit impedance\n- Ysc short-circuit admittance\n- Voc open-circuit voltage\n- Isc short-circuit current\n\nThe component values can be specified numerically or symbolically\nusing strings, for example,\n\n    >>> from lcapy import Vdc, R, L, C, s, t\n    >>> R1 = R('R_1')\n    >>> L1 = L('L_1')\n    >>> a = Vdc(10) + R1 + L1\n\nHere a is the name of the network formed with a 10 V DC voltage source in\nseries with R1 and L1.\n\nThe s-domain open circuit voltage across the network can be printed with:\n\n    >>> a.V(s)\n    10/s\n\nThe time domain open circuit voltage is given by:\n\n    >>> a.V(t)\n    10\n\nThe s-domain short circuit current through the network can be printed with:\n\n    >>> a.Isc(s)\n    10/(L_1*s**2 + R_1*s)\n\nThe time domain short circuit current is given by:\n\n    >>> a.Isc(t)\n    10/R_1\n\nIf you want units displayed:\n\n    >>> state.show_units=True\n    >>> a.Isc(t)\n    10/R_1.A\n\n\n\nTwo-port networks\n-----------------\n\nOne-port networks can be combined to form two-port networks.  Methods\nare provided to determine transfer responses between the ports.\n\nHere's an example of creating a voltage divider (L section)\n\n    >>> from lcapy import *\n    >>> a = LSection(R('R_1'), R('R_2'))\n\n\nLimitations\n-----------\n\n1. Non-linear components cannot be modelled (apart from a linearisation around a bias point).\n\n2. High order systems can go crazy.\n\n3. Some two-ports generate singular matrices.\n\n\nSchematics\n----------\n\nLaTeX schematics can be generated using circuitikz from the netlist.\nAdditional drawing hints, such as direction and size are required.\n\n    >>> from lcapy import Circuit\n    >>> cct = Circuit(\"\"\"\n    ... P1 1 0; down\n    ... R1 1 3; right\n    ... L1 3 2; right\n    ... C1 3 0_1; down\n    ... P2 2 0_2; down\n    ... W 0 0_1; right\n    ... W 0_1 0_2; right\"\"\")\n    >>> cct.draw(filename='pic.tex')\n\nIn this example, P denotes a port (open-circuit) and W denotes a wire\n(short-circuit).  The drawing hints are separated from the netlist\narguments by a semicolon.  They are a comma separated list of\nkey-value pairs except for directions where the dir keyword is\noptional.  The symbol label can be changed using the l keyword; the\nvoltage and current labels are specified with the v and i keywords.\nFor example,\n\n    >>> from lcapy import Circuit\n    >>> cct = Circuit(\"\"\"\n    ... V1 1 0; down\n    ... R1 1 2; left=2, i=I_1, v=V_{R_1}\n    ... R2 1 3; right=2, i=I_2, v=V_{R_2}\n    ... L1 2 0_1; down, i=I_1, v=V_{L_1}\n    ... L2 3 0_3; down, i=I_1, v=V_{L_2}\n    ... W 0 0_3; right\n    ... W 0 0_1; left\"\"\")\n    >>> cct.draw(scale=3, filename='pic2.svg')\n\nThe drawing direction is with respect to the positive node; i.e., the\ndrawing is performed from the positive to the negative node.  Since\nlower voltages are usually lower in a schematic, then the direction of\nvoltage sources and ports is usually down.\n\nBy default, component (and current) labels are drawn above horizontal\ncomponents and to the right of vertical components.  Voltage labels\nare drawn below horizontal components and to the left of vertical\ncomponents.\n\nNode names containing a dot or underscore are not displayed.\n\n\nJupyter notebooks\n-----------------\n\nLcapy can be used with [Jupyter Notebooks](https://jupyter.org/).  For a number of examples see https://github.com/mph-/lcapy/tree/master/doc/examples/notebooks .  These include:\n\n- [AC analysis of a first-order RC filter](https://github.com/mph-/lcapy/blob/master/doc/examples/notebooks/RC-lpf1.ipynb)\n\n- [A demonstration of the principle of superposition](https://github.com/mph-/lcapy/blob/master/doc/examples/notebooks/superposition2.ipynb)\n\n- [Non-inverting operational amplifier](https://github.com/mph-/lcapy/blob/master/doc/examples/notebooks/opamp-noninverting-amplifier1.ipynb)\n\n- [State-space analysis](https://github.com/mph-/lcapy/blob/master/doc/examples/notebooks/state-space1.ipynb)\n\n\nDocumentation\n-------------\n\nFor comprehensive documentation, see http://lcapy.readthedocs.io/en/latest (alternatively, the documentation can be viewed in a web browser after running 'make doc' in the top-level directory).\n\nFor release notes see http://lcapy.readthedocs.io/en/latest/releases.html\n\nFor another view on Lcapy see https://blog.ouseful.info/2018/08/07/an-easier-approach-to-electrical-circuit-diagram-generation-lcapy/\n\n\nCitation\n--------\n\nTo cite Lcapy in publications use\n\n> Hayes M. 2022. Lcapy: symbolic linear circuit analysis with Python. PeerJ Computer Science 8:e875 https://doi.org/10.7717/peerj-cs.875\n\nA BibTeX entry for LaTeX users is\n\n``` bibtex\n@article{10.7717/peerj-cs.875,\n title = {Lcapy: symbolic linear circuit analysis with {Python}},\n author = {Hayes, Michael},\n year = 2022,\n month = Feb,\n keywords = {Linear circuit analysis, symbolic computation, Python},\n pages = {e875},\n journal = {PeerJ Computer Science},\n issn = {2376-5992},\n url = {https://doi.org/10.7717/peerj-cs.875},\n doi = {10.7717/peerj-cs.875}\n}\n```\n\n\nCopyright 2014--2022 Michael Hayes, UCECE\n\n\n",
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