Function partial

recipes/Python/580610_Auto_differentiation/recipe-580610.py:181–192

Partial derivative at a given point >>> func = lambda x, y: x*y + sin(x) >>> point = (2.5, 3.5) >>> partial(func, point, 0) # Partial with respect to x 2.6988563844530664 >>> partial(func, point, 1) # Partial with respect to y

(func, point, index)

##  Vector Functions  ######################################################

def partial(func, point, index):
    ''' Partial derivative at a given point

        >>> func = lambda x, y:  x*y + sin(x)
        >>> point = (2.5, 3.5)
        >>> partial(func, point, 0)             # Partial with respect to x
        2.6988563844530664
        >>> partial(func, point, 1)             # Partial with respect to y
        2.5

    '''
    return d(func(*[Num(x, i==index) for i, x in enumerate(point)]))

def gradient(func, point):
    ''' Vector of the partial derivatives of a scalar field