Let V(h) be an approximation of Vexact, obtained using a composite quadrature rule with equally-spaced subintervals of width h to approximate S(z)dz. Write a function estimate_snowfall(snow_depth, params, L, method) which takes four input arguments:snow_depth, a NumPy vector containing a set of measurements of snow depth s(z), which are equally spaced over [0, L] (and include both endpoints),params , a NumPy array with 3 rows and M columns, containing the values of the Hi, i, and o parameters in its first, second, and third row respectively,L , a floating point number representing the total length of the hill range in metres,method, a string which can take the values 'riemann_left' or 'trapezoid',and returns V(h), obtained using the composite quadrature rule indicated by method, using all available measurements in the snow_depth vector (except the last one for the 'riemann_left' method). Hints:The value of h can be directly obtained from the function inputs. You may wish to write a helper function to calculate the exact integral of r(x) over an arbitrary interval [a, b], using the erf() function