Python function.diff函数代码示例

def solve_ODE_first_order(eq, f):
    """
    solves many kinds of first order odes, different methods are used
    depending on the form of the given equation. Now the linear
    and Bernoulli cases are implemented.
    """
    from sympy.integrals.integrals import integrate
    x = f.args[0]
    f = f.func

    #linear case: a(x)*f'(x)+b(x)*f(x)+c(x) = 0
    a = Wild('a', exclude=[f(x)])
    b = Wild('b', exclude=[f(x)])
    c = Wild('c', exclude=[f(x)])

    r = eq.match(a*diff(f(x),x) + b*f(x) + c)
    if r:
        t = C.exp(integrate(r[b]/r[a], x))
        tt = integrate(t*(-r[c]/r[a]), x)
        return (tt + Symbol("C1"))/t

    #Bernoulli case: a(x)*f'(x)+b(x)*f(x)+c(x)*f(x)^n = 0
    n = Wild('n', exclude=[f(x)])

    r = eq.match(a*diff(f(x),x) + b*f(x) + c*f(x)**n)
    if r:
        t = C.exp((1-r[n])*integrate(r[b]/r[a],x))
        tt = (r[n]-1)*integrate(t*r[c]/r[a],x)
        return ((tt + Symbol("C1"))/t)**(1/(1-r[n]))

    #other cases of first order odes will be implemented here

    raise NotImplementedError("solve_ODE_first_order: Cannot solve " + str(eq))

 def _do(f, ab):
     dab_dsym = diff(ab, sym)
     if not dab_dsym:
         return S.Zero
     if isinstance(f, Integral):
         limits = [(x, x) if (len(l) == 1 and l[0] == x) else l for l in f.limits]
         f = self.func(f.function, *limits)
     return f.subs(x, ab) * dab_dsym

def solve_ODE_second_order(eq, f):
    """
    solves many kinds of second order odes, different methods are used
    depending on the form of the given equation. So far the constants
    coefficients case and a special case are implemented.
    """
    x = f.args[0]
    f = f.func

    #constant coefficients case: af''(x)+bf'(x)+cf(x)=0
    a = Wild('a', exclude=[x])
    b = Wild('b', exclude=[x])
    c = Wild('c', exclude=[x])

    r = eq.match(a*f(x).diff(x,x) + c*f(x))
    if r:
        return Symbol("C1")*C.sin(sqrt(r[c]/r[a])*x)+Symbol("C2")*C.cos(sqrt(r[c]/r[a])*x)

    r = eq.match(a*f(x).diff(x,x) + b*diff(f(x),x) + c*f(x))
    if r:
        r1 = solve(r[a]*x**2 + r[b]*x + r[c], x)
        if r1[0].is_real:
            if len(r1) == 1:
                return (Symbol("C1") + Symbol("C2")*x)*exp(r1[0]*x)
            else:
                return Symbol("C1")*exp(r1[0]*x) + Symbol("C2")*exp(r1[1]*x)
        else:
            r2 = abs((r1[0] - r1[1])/(2*S.ImaginaryUnit))
            return (Symbol("C2")*C.cos(r2*x) + Symbol("C1")*C.sin(r2*x))*exp((r1[0] + r1[1])*x/2)

    #other cases of the second order odes will be implemented here

    #special equations, that we know how to solve
    a = Wild('a')
    t = x*exp(f(x))
    tt = a*t.diff(x, x)/t
    r = eq.match(tt.expand())
    if r:
        return -solve_ODE_1(f(x), x)

    t = x*exp(-f(x))
    tt = a*t.diff(x, x)/t
    r = eq.match(tt.expand())
    if r:
        #check, that we've rewritten the equation correctly:
        #assert ( r[a]*t.diff(x,2)/t ) == eq.subs(f, t)
        return solve_ODE_1(f(x), x)

    neq = eq*exp(f(x))/exp(-f(x))
    r = neq.match(tt.expand())
    if r:
        #check, that we've rewritten the equation correctly:
        #assert ( t.diff(x,2)*r[a]/t ).expand() == eq
        return solve_ODE_1(f(x), x)

    raise NotImplementedError("solve_ODE_second_order: cannot solve " + str(eq))

def line_integrate(field, curve, vars):
    """line_integrate(field, Curve, variables)

    Compute the line integral.

    Examples
    ========

    >>> from sympy import Curve, line_integrate, E, ln
    >>> from sympy.abc import x, y, t
    >>> C = Curve([E**t + 1, E**t - 1], (t, 0, ln(2)))
    >>> line_integrate(x + y, C, [x, y])
    3*sqrt(2)

    See Also
    ========

    integrate, Integral
    """
    from sympy.geometry import Curve
    F = sympify(field)
    if not F:
        raise ValueError(
            "Expecting function specifying field as first argument.")
    if not isinstance(curve, Curve):
        raise ValueError("Expecting Curve entity as second argument.")
    if not is_sequence(vars):
        raise ValueError("Expecting ordered iterable for variables.")
    if len(curve.functions) != len(vars):
        raise ValueError("Field variable size does not match curve dimension.")

    if curve.parameter in vars:
        raise ValueError("Curve parameter clashes with field parameters.")

    # Calculate derivatives for line parameter functions
    # F(r) -> F(r(t)) and finally F(r(t)*r'(t))
    Ft = F
    dldt = 0
    for i, var in enumerate(vars):
        _f = curve.functions[i]
        _dn = diff(_f, curve.parameter)
        # ...arc length
        dldt = dldt + (_dn * _dn)
        Ft = Ft.subs(var, _f)
    Ft = Ft * sqrt(dldt)

    integral = Integral(Ft, curve.limits).doit(deep=False)
    return integral

    def _eval_imageset(self, f):
        from sympy.functions.elementary.miscellaneous import Min, Max
        from sympy.solvers import solve
        from sympy.core.function import diff
        from sympy.series import limit
        from sympy.calculus.singularities import singularities
        # TODO: handle piecewise defined functions
        # TODO: handle functions with infinitely many solutions (eg, sin, tan)
        # TODO: handle multivariate functions

        expr = f.expr
        if len(expr.free_symbols) > 1 or len(f.variables) != 1:
            return
        var = f.variables[0]

        if not self.start.is_comparable or not self.end.is_comparable:
            return

        try:
            sing = [x for x in singularities(expr, var) if x.is_real and x in self]
        except NotImplementedError:
            return

        if self.left_open:
            _start = limit(expr, var, self.start, dir="+")
        elif self.start not in sing:
            _start = f(self.start)
        if self.right_open:
            _end = limit(expr, var, self.end, dir="-")
        elif self.end not in sing:
            _end = f(self.end)

        if len(sing) == 0:
            solns = solve(diff(expr, var), var)

            extr = [_start, _end] + [f(x) for x in solns
                                     if x.is_real and x in self]
            start, end = Min(*extr), Max(*extr)

            left_open, right_open = False, False
            if _start <= _end:
                # the minimum or maximum value can occur simultaneously
                # on both the edge of the interval and in some interior
                # point
                if start == _start and start not in solns:
                    left_open = self.left_open
                if end == _end and end not in solns:
                    right_open = self.right_open
            else:
                if start == _end and start not in solns:
                    left_open = self.right_open
                if end == _start and end not in solns:
                    right_open = self.left_open

            return Interval(start, end, left_open, right_open)
        else:
            return imageset(f, Interval(self.start, sing[0],
                                        self.left_open, True)) + \
                Union(*[imageset(f, Interval(sing[i], sing[i + 1]), True, True)
                        for i in range(1, len(sing) - 1)]) + \
                imageset(f, Interval(sing[-1], self.end, True, self.right_open))

def _set_function(f, x):
    from sympy.functions.elementary.miscellaneous import Min, Max
    from sympy.solvers.solveset import solveset
    from sympy.core.function import diff, Lambda
    from sympy.series import limit
    from sympy.calculus.singularities import singularities
    from sympy.sets import Complement
    # TODO: handle functions with infinitely many solutions (eg, sin, tan)
    # TODO: handle multivariate functions

    expr = f.expr
    if len(expr.free_symbols) > 1 or len(f.variables) != 1:
        return
    var = f.variables[0]

    if expr.is_Piecewise:
        result = S.EmptySet
        domain_set = x
        for (p_expr, p_cond) in expr.args:
            if p_cond is true:
                intrvl = domain_set
            else:
                intrvl = p_cond.as_set()
                intrvl = Intersection(domain_set, intrvl)

            if p_expr.is_Number:
                image = FiniteSet(p_expr)
            else:
                image = imageset(Lambda(var, p_expr), intrvl)
            result = Union(result, image)

            # remove the part which has been `imaged`
            domain_set = Complement(domain_set, intrvl)
            if domain_set.is_EmptySet:
                break
        return result

    if not x.start.is_comparable or not x.end.is_comparable:
        return

    try:
        sing = [i for i in singularities(expr, var)
            if i.is_real and i in x]
    except NotImplementedError:
        return

    if x.left_open:
        _start = limit(expr, var, x.start, dir="+")
    elif x.start not in sing:
        _start = f(x.start)
    if x.right_open:
        _end = limit(expr, var, x.end, dir="-")
    elif x.end not in sing:
        _end = f(x.end)

    if len(sing) == 0:
        solns = list(solveset(diff(expr, var), var))

        extr = [_start, _end] + [f(i) for i in solns
                                 if i.is_real and i in x]
        start, end = Min(*extr), Max(*extr)

        left_open, right_open = False, False
        if _start <= _end:
            # the minimum or maximum value can occur simultaneously
            # on both the edge of the interval and in some interior
            # point
            if start == _start and start not in solns:
                left_open = x.left_open
            if end == _end and end not in solns:
                right_open = x.right_open
        else:
            if start == _end and start not in solns:
                left_open = x.right_open
            if end == _start and end not in solns:
                right_open = x.left_open

        return Interval(start, end, left_open, right_open)
    else:
        return imageset(f, Interval(x.start, sing[0],
                                    x.left_open, True)) + \
            Union(*[imageset(f, Interval(sing[i], sing[i + 1], True, True))
                    for i in range(0, len(sing) - 1)]) + \
            imageset(f, Interval(sing[-1], x.end, True, x.right_open))

 def _eval_derivative(self, s):
     return Piecewise(*[(diff(e, s), c) for e, c in self.args])

    def _eval_imageset(self, f):
        from sympy import Dummy
        from sympy.functions.elementary.miscellaneous import Min, Max
        from sympy.solvers import solve
        from sympy.core.function import diff
        from sympy.series import limit
        from sympy.calculus.singularities import singularities
        # TODO: handle piecewise defined functions
        # TODO: handle functions with infinitely many solutions (eg, sin, tan)
        # TODO: handle multivariate functions

        # var and expr are being defined this way to
        # support Python lambda and not just sympy Lambda
        try:
            var = Dummy()
            expr = f(var)
            if len(expr.free_symbols) > 1:
                raise TypeError
        except TypeError:
            raise NotImplementedError("Sorry, Multivariate imagesets are"
                                      " not yet implemented, you are welcome"
                                      " to add this feature in Sympy")

        if not self.start.is_comparable or not self.end.is_comparable:
            raise NotImplementedError("Sets with non comparable/variable"
                                      " arguments are not supported")

        sing = [x for x in singularities(expr, var) if x.is_real and x in self]

        if self.left_open:
            _start = limit(expr, var, self.start, dir="+")
        elif self.start not in sing:
            _start = f(self.start)
        if self.right_open:
            _end = limit(expr, var, self.end, dir="-")
        elif self.end not in sing:
            _end = f(self.end)

        if len(sing) == 0:
            solns = solve(diff(expr, var), var)

            extr = [_start, _end] + [f(x) for x in solns
                                     if x.is_real and x in self]
            start, end = Min(*extr), Max(*extr)

            left_open, right_open = False, False
            if _start <= _end:
                # the minimum or maximum value can occur simultaneously
                # on both the edge of the interval and in some interior
                # point
                if start == _start and start not in solns:
                    left_open = self.left_open
                if end == _end and end not in solns:
                    right_open = self.right_open
            else:
                if start == _end and start not in solns:
                    left_open = self.right_open
                if end == _start and end not in solns:
                    right_open = self.left_open

            return Interval(start, end, left_open, right_open)
        else:
            return imageset(f, Interval(self.start, sing[0],
                                        self.left_open, True)) + \
                Union(*[imageset(f, Interval(sing[i], sing[i + 1]), True, True)
                        for i in range(1, len(sing) - 1)]) + \
                imageset(f, Interval(sing[-1], self.end, True, self.right_open))