forecasting/raw_ndvi_pred/json_parser.py
def interpolate_and_scale(a, new_length, order=3, scale=1):
    ' interpolates and returns a new array and scales to a required new scale value'
    old_indices = np.arange(0, len(a))
    new_indices = np.linspace(0, len(a) - 1, new_length)
    spl = UnivariateSpline(old_indices, a, k=order, s=0)
    new_array = spl(new_indices)
    return scale*new_array
 interpolates and returns a new array and scales to a required new scale value
interpolates and returns a new array and scales to a required new scale value
interpolates and returns a new array and scales to a required new scale value
def interpolate_and_scale(a, new_length, order=3, scale=1):
    old_indices = np.arange(0, len(a))
    new_indices = np.linspace(0, len(a) - 1, new_length)
    spl = UnivariateSpline(old_indices, a, k=order, s=0)
    new_array = spl(new_indices)
    return scale*new_array
def interpolate_and_scale ( a , new_length , order = 3 , scale = 1 ) : old_indices = np . arange ( 0 , len ( a ) ) new_indices = np . linspace ( 0 , len ( a ) - 1 , new_length ) spl = UnivariateSpline ( old_indices , a , k = order , s = 0 ) new_array = spl ( new_indices ) return scale * new_array
interpolates and returns a new array and scales to a required new scale value
interpolates and returns a new array and scales to a required new scale value
' interpolates and returns a new array and scales to a required new scale value'
a
new_length
order
scale