def vector_apply(f, x, *arg):
"""
apply **f** to array **x** with given arguments fast. This is a fast
version of::
np.array([f(xi,*arg) for xi in x ])
useful when you try to plot something
"""
return _vector_apply(f, x, arg)
def vector_apply(f, x, *arg):
"""
apply **f** to array **x** with given arguments fast. This is a fast
version of::
np.array([f(xi,*arg) for xi in x ])
useful when you try to plot something
"""
return _vector_apply(f, x, arg)
def fwhm_f(f, range, arg=None, bins=1000):
arg=tuple() if arg is None else arg
x = np.linspace(range[0], range[1], bins)
y = _vector_apply(f, x, arg)
imax = np.argmax(y)
ymax = y[imax]
rs = y[imax:]-ymax/2.0
ls = y[:imax]-ymax/2.0
xl = 0
xr = 0
il = first_neg(ls, 'l')
#print il,x[il],ls[il],x[il+1],ls[il+1]
xl = xintercept(x[il], ls[il], x[il+1], ls[il+1])
ir = first_neg(rs, 'r')
#print ir,x[imax+ir],rs[ir],x[ir+1],rs[ir+1]
xr = xintercept(x[imax+ir], rs[ir], x[imax+ir-1], rs[ir-1])
return (xl, xr)
