U
    ;qLeE                     @   s  d dl mZ d dlmZ d dlmZmZ d dlmZ d dl	m
Z
 d dlmZ d dlmZ d dlmZmZmZ d d	lmZ d d
lmZ d dlmZmZ d dlmZ d dlmZ d dlmZ d dlm Z m!Z! d dl"m#Z# dd Z$d ddZ%dd Z&dd Z'dd Z(ddddZ)dS )!    )Add)factor_terms)
expand_log_mexpand)Pow)S)ordered)Dummy)LambertWexplog)root)roots)Polyfactor)separatevars)collect)powsimp)solve_invert)uniqc                    s^    fdd| j D }t|D ]<}d| }||kr||kr| d tjk	rN|}|| q|S )a  process the generators of ``poly``, returning the set of generators that
    have ``symbol``.  If there are two generators that are inverses of each other,
    prefer the one that has no denominator.

    Examples
    ========

    >>> from sympy.solvers.bivariate import _filtered_gens
    >>> from sympy import Poly, exp
    >>> from sympy.abc import x
    >>> _filtered_gens(Poly(x + 1/x + exp(x)), x)
    {x, exp(x)}

    c                    s   h | ]} |j kr|qS  free_symbols).0gsymbolr   n/home/p21-0144/sympy/latex2sympy2solve-back-end/sympyEq/lib/python3.8/site-packages/sympy/solvers/bivariate.py	<setcomp>%   s     
 z!_filtered_gens.<locals>.<setcomp>   )genslistas_numer_denomr   Oneremove)polyr   r!   r   Zagr   r   r   _filtered_gens   s    r'   Nc                    sP    fdd|  D }t|dkr,|d S |rLttt|fdddS dS )	a+  Returns the term in lhs which contains the most of the
    func-type things e.g. log(log(x)) wins over log(x) if both terms appear.

    ``func`` can be a function (exp, log, etc...) or any other SymPy object,
    like Pow.

    If ``X`` is not ``None``, then the function returns the term composed with the
    most ``func`` having the specified variable.

    Examples
    ========

    >>> from sympy.solvers.bivariate import _mostfunc
    >>> from sympy import exp
    >>> from sympy.abc import x, y
    >>> _mostfunc(exp(x) + exp(exp(x) + 2), exp)
    exp(exp(x) + 2)
    >>> _mostfunc(exp(x) + exp(exp(y) + 2), exp)
    exp(exp(y) + 2)
    >>> _mostfunc(exp(x) + exp(exp(y) + 2), exp, x)
    exp(x)
    >>> _mostfunc(x, exp, x) is None
    True
    >>> _mostfunc(exp(x) + exp(x*y), exp, x)
    exp(x)
    c                    s4   g | ],} r, j r |jks, j s| r|qS r   )	is_Symbolr   hasr   tmp)Xr   r   
<listcomp>J   s      
 
z_mostfunc.<locals>.<listcomp>r    r   c                    s
   |   S N)count)x)funcr   r   <lambda>P       z_mostfunc.<locals>.<lambda>)keyN)atomslenmaxr"   r   )lhsr1   r,   Zftermsr   )r,   r1   r   	_mostfunc/   s    r9   c                 C   s   t |  } | |\}}| jrH|jrHt||\}}}|| || |fS | js^d}|| }}n|}t|j|dd\}}| r| }| }|||fS )a  Return ``a, b, X`` assuming ``arg`` can be written as ``a*X + b``
    where ``X`` is a symbol-dependent factor and ``a`` and ``b`` are
    independent of ``symbol``.

    Examples
    ========

    >>> from sympy.solvers.bivariate import _linab
    >>> from sympy.abc import x, y
    >>> from sympy import exp, S
    >>> _linab(S(2), x)
    (2, 0, 1)
    >>> _linab(2*x, x)
    (2, 0, x)
    >>> _linab(y + y*x + 2*x, x)
    (y + 2, y, x)
    >>> _linab(3 + 2*exp(x), x)
    (2, 3, exp(x))
    r   Fas_Add)r   expandas_independentis_Mulis_Add_linabr   could_extract_minus_sign)argr   inddepabr0   r   r   r   r@   T   s    r@   c                    s  t t| } t| t|}|s g S | |d}t| tr|| | ||jd } |jd }t|tsfg S | jd  }| |7 } ||jkrg S t||\}}t	| | |}|
|  dks| jkrg S |jd }t||\}}	|	|krg S tdt|	 |}
ddg}g }| |      \}}| \}}t|| }td} fddt|| | | D }|D ]^}|D ]R}t||}|r|jsq|    |  |fdd	|
D  qq||S )
z
    Given an expression assumed to be in the form
        ``F(X, a..f) = a*log(b*X + c) + d*X + f = 0``
    where X = g(x) and x = g^-1(X), return the Lambert solution,
        ``x = g^-1(-c/b + (a/d)*W(d/(a*b)*exp(c*d/a/b)*exp(-f/a)))``.
    r   Nrhstc                    s   g | ]}   | qS r   r   )r   rI   )rE   rF   dr   r   r-      s     z_lambert.<locals>.<listcomp>c                 3   s   | ]}|  V  qd S r.   )subs)r   Zxu)rG   ur   r   	<genexpr>   s     z_lambert.<locals>.<genexpr>)r   r   r9   r   rK   
isinstanceargsr   r@   r   as_coefficientr	   r   r#   as_coeff_Mulr   r   keysr
   is_realextend)eqr0   mainlogotherfZX2logtermlogargcX1ZxusolnsZlambert_real_branchessolnumdenperI   rO   rB   kwr   )rE   rF   rJ   rG   rL   r   _lamberty   sP    






 (
"rd   c                    s   fdd}| j dd\}}| }fdd D }|s@t |jsN|jr:tdj|fdd	fd
d	}|jr|r|d}|| }	|| }
|	js|
r|	t	j
t	jstt|	t|
 }||S nN|jr,|r,tt|dd}t|}|r,|jr,|| }||S |i}tt|dd}t }t|| \}}|||i}g }|sDt|t}|rD|jr|dkrtt|t| }n|jrD||d}|r6|js6fdd|tD r6|st|t||  }nt|| t||  }tt|}nt|| }|st|t}|rt||}|jr|dkrttt|t| }nf|jr||d}|| }|| }| r| r|d9 }|d9 }t|t| }tt|}|st|t}|r|jjkrt||}|jrX|dkrXttt|t| }nB|jr||d}|| }|| }t|t| }tt|}|std|  tt|S )a  Return solution to ``f`` if it is a Lambert-type expression
    else raise NotImplementedError.

    For ``f(X, a..f) = a*log(b*X + c) + d*X - f = 0`` the solution
    for ``X`` is ``X = -c/b + (a/d)*W(d/(a*b)*exp(c*d/a/b)*exp(f/a))``.
    There are a variety of forms for `f(X, a..f)` as enumerated below:

    1a1)
      if B**B = R for R not in [0, 1] (since those cases would already
      be solved before getting here) then log of both sides gives
      log(B) + log(log(B)) = log(log(R)) and
      X = log(B), a = 1, b = 1, c = 0, d = 1, f = log(log(R))
    1a2)
      if B*(b*log(B) + c)**a = R then log of both sides gives
      log(B) + a*log(b*log(B) + c) = log(R) and
      X = log(B), d=1, f=log(R)
    1b)
      if a*log(b*B + c) + d*B = R and
      X = B, f = R
    2a)
      if (b*B + c)*exp(d*B + g) = R then log of both sides gives
      log(b*B + c) + d*B + g = log(R) and
      X = B, a = 1, f = log(R) - g
    2b)
      if g*exp(d*B + h) - b*B = c then the log form is
      log(g) + d*B + h - log(b*B + c) = 0 and
      X = B, a = -1, f = -h - log(g)
    3)
      if d*p**(a*B + g) - b*B = c then the log form is
      log(d) + (a*B + g)*log(p) - log(b*B + c) = 0 and
      X = B, a = -1, d = a*log(p), f = -log(d) - g*log(p)
    c                    sL    fdddD \}}t |}||kr@|t | tt|S )a  Return the unique solutions of equations derived from
        ``expr`` by replacing ``t`` with ``+/- symbol``.

        Parameters
        ==========

        expr : Expr
            The expression which includes a dummy variable t to be
            replaced with +symbol and -symbol.

        symbol : Symbol
            The symbol for which a solution is being sought.

        Returns
        =======

        List of unique solution of the two equations generated by
        replacing ``t`` with positive and negative ``symbol``.

        Notes
        =====

        If ``expr = 2*log(t) + x/2` then solutions for
        ``2*log(x) + x/2 = 0`` and ``2*log(-x) + x/2 = 0`` are
        returned by this function. Though this may seem
        counter-intuitive, one must note that the ``expr`` being
        solved here has been derived from a different expression. For
        an expression like ``eq = x**2*g(x) = 1``, if we take the
        log of both sides we obtain ``log(x**2) + log(g(x)) = 0``. If
        x is positive then this simplifies to
        ``2*log(x) + log(g(x)) = 0``; the Lambert-solving routines will
        return solutions for this, but we must also consider the
        solutions for  ``2*log(-x) + log(g(x))`` since those must also
        be a solution of ``eq`` which has the same value when the ``x``
        in ``x**2`` is negated. If `g(x)` does not have even powers of
        symbol then we do not want to replace the ``x`` there with
        ``-x``. So the role of the ``t`` in the expression received by
        this function is to mark where ``+/-x`` should be inserted
        before obtaining the Lambert solutions.

        c                    s   g | ]}  | iqS r   )xreplace)r   sgnexprr   rI   r   r   r-     s    zC_solve_lambert.<locals>._solve_even_degree_expr.<locals>.<listcomp>)rH   r    )_solve_lambertrT   r"   r   )rh   rI   r   ZnlhsZplhssols)r!   rg   r   _solve_even_degree_expr   s    *
z/_solve_lambert.<locals>._solve_even_degree_exprTr:   c                    s0   g | ](}|j ttfks(|jr |jjkr|qS r   )r1   r   r   is_Powr   r*   r   r   r   r-     s
     z"_solve_lambert.<locals>.<listcomp>rI   c                    s   | j o| j ko| jjS r.   )rl   baser   is_evenir   r   r   r2   (  s    z _solve_lambert.<locals>.<lambda>c                    s
    | j  S r.   )r   ro   )rI   r   r   r2   *  s    r   )force)deepc                    s   g | ]} |j kr|qS r   r   r*   r   r   r   r-   \  s   
rH   z:%s does not appear to have a solution in terms of LambertW)rI   )r=   NotImplementedErrorr?   r>   r	   assumptions0replacer)   rK   r   ComplexInfinityNaNr   r   re   r   r   r   r9   rd   r5   r   r   r   rA   r   r"   r   )rX   r   r!   rk   Znrhsr8   rG   ZlamcheckZt_indepZt_term_rhsrU   rrp   solnrV   rW   diffZmainexpZmaintermZmainpowr   )r!   r   rI   r   ri      s    "6





ri   Tfirstc                   s:  t ddd}|rt|  }| } t  }t  }tt|  ||i||||dd}|r| |i}	|d |	|d |	|d fS d	S | }| } t| }
g }|
D ]<}t| | }|j	} |ks܈|kr q|
| q  t| |fS  fd
d}g }| }||krt| | |}t|| |}||  ||  | }|d	k	r|  |  ||fS g }| }||kr6tdD ]}t| | |  |}t|| |}||  ||  |  }|d	k	r(|   |  ||f  S    qd	S )a  Given an expression, f, 3 tests will be done to see what type
    of composite bivariate it might be, options for u(x, y) are::

        x*y
        x+y
        x*y+x
        x*y+y

    If it matches one of these types, ``u(x, y)``, ``P(u)`` and dummy
    variable ``u`` will be returned. Solving ``P(u)`` for ``u`` and
    equating the solutions to ``u(x, y)`` and then solving for ``x`` or
    ``y`` is equivalent to solving the original expression for ``x`` or
    ``y``. If ``x`` and ``y`` represent two functions in the same
    variable, e.g. ``x = g(t)`` and ``y = h(t)``, then if ``u(x, y) - p``
    can be solved for ``t`` then these represent the solutions to
    ``P(u) = 0`` when ``p`` are the solutions of ``P(u) = 0``.

    Only positive values of ``u`` are considered.

    Examples
    ========

    >>> from sympy import solve
    >>> from sympy.solvers.bivariate import bivariate_type
    >>> from sympy.abc import x, y
    >>> eq = (x**2 - 3).subs(x, x + y)
    >>> bivariate_type(eq, x, y)
    (x + y, _u**2 - 3, _u)
    >>> uxy, pu, u = _
    >>> usol = solve(pu, u); usol
    [sqrt(3)]
    >>> [solve(uxy - s) for s in solve(pu, u)]
    [[{x: -y + sqrt(3)}]]
    >>> all(eq.subs(s).equals(0) for sol in _ for s in sol)
    True

    rL   T)positiveFr|   r   r       Nc                    s.   t | ||}|j} |ks&|kr*d S |S r.   )r   rK   r   )rX   vr[   newfreer0   yr   r   ok  s    zbivariate_type.<locals>.ok)r	   r   as_exprbivariate_typerK   re   r   	make_argsr   r   appenddegreer   coeff_monomialrange)rX   r0   r   r}   rL   r`   _x_yrvrepsrO   r   rE   r   r   rJ   rF   Zitryr   r   r   r     sR    '&"



r   )N)*Zsympy.core.addr   sympy.core.exprtoolsr   sympy.core.functionr   r   sympy.core.powerr   Zsympy.core.singletonr   sympy.core.sortingr   sympy.core.symbolr	   &sympy.functions.elementary.exponentialr
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