calc_mean_array_clip.py

""" Calculate mean std of clipped array"""
import numpy as np
from scipy import interpolate

def calc_func_clipped(X, Y, func=np.mean, npoints=None, verbose=False):
    """ Calculates func of Y values, where Y is clipped to the longest continuous
    values of X to prevent aliasing
        
    """
    # Size of each data vector
    npoints = npoints or Y.shape[1]
    
    # Finding consecutive value measurements
    xmax = np.inf
    xmin = -np.inf
    for x in X:
        if x.max() < xmax:
            xmax = x.max()
        if x.min() > xmin:
            xmin = x.min()
    if verbose:
        print 'Clipped to:', xmin,xmax
    # Clipping data
    newx = np.linspace(xmin, xmax, npoints)
    newy = []
    for x,y in zip(X,Y):
        valid_idx = (x>xmin)*(x<xmax)
        f = interpolate.interp1d(x,y)
        yi = f(newx)
        newy.append(yi)

    if verbose:
        print newy
    # Calculating function
    newy = np.array(newy)
    newy = func(newy, axis=0)
    return newx, newy