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        "author": "Gabriel Petrini da Silveira",
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        "description": "==========\npysolve\n==========\nSolving systems of linear equations\n-----------------------------------\n\nThe purpose of this code is to aid in expressing and solving\nsets of equations using Python.\n\nThis tool will take a textual description of the equations \nand then run the solver iteratively until it converges to a solution.\n\nThe solver provides the following choices for solving:\n- Gauss-Seidel\n- Newton-Raphson\n- Broyden\n\nIt also uses parts of sympy to aid in parsing the equations.\n\nThe initial motivation for this tool was to solve economic\nmodels based on Stock Flow Consistent (SFC) models.\n\n\nInstallation\n--------------\n::\n\tpip3 install pysolve\n\n\nUsage\n-------------\n\n.. code::\n\n\tfrom pysolve3.model import Model\n\tfrom pysolve3.utils import round_solution,is_close\n\n\tmodel = Model()\n\n\tmodel.set_var_default(0)\n\tmodel.var('Cd', desc='Consumption goods demand by households')\n\tmodel.var('Cs', desc='Consumption goods supply')\n\tmodel.var('Gs', desc='Government goods, supply')\n\tmodel.var('Hh', desc='Cash money held by households')\n\tmodel.var('Hs', desc='Cash money supplied by the government')\n\tmodel.var('Nd', desc='Demand for labor')\n\tmodel.var('Ns', desc='Supply of labor')\n\tmodel.var('Td', desc='Taxes, demand')\n\tmodel.var('Ts', desc='Taxes, supply')\n\tmodel.var('Y', desc='Income = GDP')\n\tmodel.var('YD', desc='Disposable income of households')\t\n\n\t# This is a shorter way to declare multiple variables\n\t# model.vars('Y', 'YD', 'Ts', 'Td', 'Hs', 'Hh', 'Gs', 'Cs',\n\t#            'Cd', 'Ns', 'Nd')\n\tmodel.param('Gd', desc='Government goods, demand', initial=20)\n\tmodel.param('W', desc='Wage rate', initial=1)\n\tmodel.param('alpha1', desc='Propensity to consume out of income', initial=0.6)\n\tmodel.param('alpha2', desc='Propensity to consume o of wealth', initial=0.4)\n\tmodel.param('theta', desc='Tax rate', initial=0.2)\n\n\tmodel.add('Cs = Cd')\n\tmodel.add('Gs = Gd')\n\tmodel.add('Ts = Td')\n\tmodel.add('Ns = Nd')\n\tmodel.add('YD = (W*Ns) - Ts')\n\tmodel.add('Td = theta * W * Ns')\n\tmodel.add('Cd = alpha1*YD + alpha2*Hh(-1)')\n\tmodel.add('Hs - Hs(-1) =  Gd - Td')\n\tmodel.add('Hh - Hh(-1) = YD - Cd')\n\tmodel.add('Y = Cs + Gs')\n\tmodel.add('Nd = Y/W')\n\n\t# solve until convergence\n\tfor _ in xrange(100):\n\t    model.solve(iterations=100, threshold=1e-3)\n\n\t    prev_soln = model.solutions[-2]\n\t    soln = model.solutions[-1]\n\t    if is_close(prev_soln, soln, rtol=1e-3):\n\t        break\n\n\tprint round_solution(model.solutions[-1], decimals=1)\n\nFor additional examples, view the iPython notebooks at\n\thttp://nbviewer.ipython.org/github/kennt/monetary-economics/tree/master/\n\n\nTutorial\n--------\nA short tutorial with more explanation is available at\n\thttp://nbviewer.ipython.org/github/kennt/monetary-economics/blob/master/extra/pysolve%20tutorial.ipynb\n\n\n\n",
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