Esempio n. 1
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def ast_to_sympy(expr):
    '''Converts an AST expression to a sympy expression (STUPID)'''
    from dolang import to_source
    s = to_source(expr)
    not_to_be_treated_as_functions = ['alpha', 'beta', 'gamma', 'zeta', 'Chi']
    d = {v: sympy.Symbol(v) for v in not_to_be_treated_as_functions}
    return sympy.sympify(s, locals=d)
Esempio n. 2
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def ast_to_sympy(expr):
    '''Converts an AST expression to a sympy expression (STUPID)'''
    from dolang import to_source
    s = to_source(expr)
    not_to_be_treated_as_functions = ['alpha','beta', 'gamma','zeta', 'Chi']
    d = {v: sympy.Symbol(v) for v in not_to_be_treated_as_functions}
    return sympy.sympify(s, locals=d)
Esempio n. 3
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def eval_formula(expr, dataframe=None, context=None):
    '''
    expr: string
        Symbolic expression to evaluate.
        Example: `k(1)-delta*k-i`
    table: (optional) pandas dataframe
        Each column is a time series, which can be indexed with dolo notations.
    context: dict or CalibrationDict
    '''

    if context is None:
        dd = {}  # context dictionary
    elif isinstance(context, CalibrationDict):
        dd = context.flat.copy()
    else:
        dd = context.copy()

    # compat since normalize form for parameters doesn't match calib dict.
    for k in [*dd.keys()]:
        dd[stringify(k)] = dd[k]

    from numpy import log, exp
    dd['log'] = log
    dd['exp'] = exp

    if dataframe is not None:

        import pandas as pd
        tvariables = dataframe.columns
        for k in tvariables:
            if k in dd:
                dd[k + '_ss'] = dd[k]  # steady-state value
            dd[stringify((k, 0))] = dataframe[k]
            for h in range(1, 3):  # maximum number of lags
                dd[stringify((k, -h))] = dataframe[k].shift(h)
                dd[stringify((k, h))] = dataframe[k].shift(-h)
        dd['t'] = pd.Series(dataframe.index, index=dataframe.index)

        import ast
        expr_ast = ast.parse(expr).body[0].value
        # nexpr = StandardizeDatesSimple(tvariables).visit(expr_ast)
        print(tvariables)
        nexpr = normalize(expr_ast, variables=tvariables)

        expr = to_source(nexpr)

    res = eval(expr, dd)

    return res
Esempio n. 4
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def get_factory(model, eq_type: str, tshift: int = 0):

    from dolo.compiler.model import decode_complementarity

    from dolo.compiler.recipes import recipes
    from dolang.symbolic import stringify, stringify_symbol

    equations = model.equations

    if eq_type == "auxiliary":
        eqs = [('{}({})'.format(s, 0)) for s in model.symbols['auxiliaries']]
        specs = {
            'eqs': [['exogenous', 0, 'm'], ['states', 0, 's'],
                    ['controls', 0, 'x'], ['parameters', 0, 'p']]
        }
    else:
        eqs = equations[eq_type]
        if eq_type in ('controls_lb', 'controls_ub'):
            specs = {
                'eqs':
                recipes['dtcc']['specs']['arbitrage']['complementarities'][
                    'left-right']
            }
        else:
            specs = recipes['dtcc']['specs'][eq_type]

    specs = shift_spec(specs, tshift=tshift)

    preamble_tshift = set([s[1] for s in specs['eqs'] if s[0] == 'states'])
    preamble_tshift = preamble_tshift.intersection(
        set([s[1] for s in specs['eqs'] if s[0] == 'controls']))

    args = []
    for sg in specs['eqs']:
        if sg[0] == 'parameters':
            args.append([s for s in model.symbols["parameters"]])
        else:
            args.append([(s, sg[1]) for s in model.symbols[sg[0]]])
    args = [[stringify_symbol(e) for e in vg] for vg in args]

    arguments = dict(zip([sg[2] for sg in specs['eqs']], args))

    # temp
    eqs = [eq.replace("==","=").replace("=","==") for eq in eqs]

    if 'target' in specs:
        sg = specs['target']
        targets = [(s, sg[1]) for s in model.symbols[sg[0]]]
        eqs = [eq.split('==')[1] for eq in eqs]
    else:
        eqs = [("({1})-({0})".format(*eq.split('==')) if '==' in eq else eq)
               for eq in eqs]
        targets = [('out{}'.format(i), 0) for i in range(len(eqs))]

    eqs = [str.strip(eq) for eq in eqs]
    eqs = [dolang.parse_string(eq) for eq in eqs]
    es = ExpressionSanitizer(model.variables)
    eqs = [es.visit(eq) for eq in eqs]

    eqs = [time_shift(eq, tshift) for eq in eqs]
    eqs = [stringify(eq) for eq in eqs]
    eqs = [dolang.to_source(eq) for eq in eqs]

    targets = [stringify_symbol(e) for e in targets]

    # sanitize defs ( should be )
    defs = dict()
    for k in model.definitions:
        if '(' not in k:
            s = "{}(0)".format(k)
            val = model.definitions[k]
            val = es.visit(dolang.parse_string(val))
            for t in preamble_tshift:
                s = stringify_symbol((k, t))
                vv = stringify(time_shift(val, t))
                defs[s] = dolang.to_source(vv)

    preamble = reorder_preamble(defs)

    eqs = dict(zip(targets, eqs))
    ff = FlatFunctionFactory(preamble, eqs, arguments, eq_type)

    return ff
Esempio n. 5
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def print_matlab(sexpr):
    ss = (to_source(sexpr))
    ss = ss.replace(' ** ', '.^')
    ss = ss.replace(' * ', '.*')
    ss = ss.replace(' / ', './')
    return ss
Esempio n. 6
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def print_matlab(sexpr):
    ss = (to_source(sexpr))
    ss = ss.replace(' ** ', '.^')
    ss = ss.replace(' * ', '.*')
    ss = ss.replace(' / ', './')
    return ss