smoother.py

# -*- coding: utf-8 -*-
"""
Created on Wed Mar 18 10:31:58 2020

@author: cenic
"""

# -----------
# User Instructions
#
# Define a function smooth that takes a path as its input
# (with optional parameters for weight_data, weight_smooth,
# and tolerance) and returns a smooth path. The first and 
# last points should remain unchanged.
#
# Smoothing should be implemented by iteratively updating
# each entry in newpath until some desired level of accuracy
# is reached. The update should be done according to the
# gradient descent equations given in the instructor's note
# below (the equations given in the video are not quite 
# correct).
# -----------

from copy import deepcopy

# thank you to EnTerr for posting this on our discussion forum
def printpaths(path,newpath):
    for old,new in zip(path,newpath):
        print ('['+ ', '.join('%.3f'%x for x in old) + \
               '] -> ['+ ', '.join('%.3f'%x for x in new) +']')

# Don't modify path inside your function.
path = [[0, 0],
        [0, 1],
        [0, 2],
        [1, 2],
        [2, 2],
        [3, 2],
        [4, 2],
        [4, 3],
        [4, 4]]

def smooth(path, weight_data = 0.5, weight_smooth = 0.1, tolerance = 0.000001):

    # Make a deep copy of path into newpath
    newpath = deepcopy(path)

    #######################
    ### ENTER CODE HERE ###
    #######################
    error=tolerance+1
    while(error>tolerance):
        ngradient_v =[[weight_data * (path[i][j] - newpath[i][j]) + 
                 weight_smooth * (newpath[i-1][j] + newpath[i+1][j] - 2.0 * newpath[i][j]) for j in range(2)]
                 for i in range(1,len(path)-1)]
        print(ngradient_v)
        newpath =[newpath[0]]+[[newpath[i][j]+ngradient_v[i-1][j] for j in range(2)] for i in range(1,len(path)-1) ]+[newpath[-1]]
        error =sum([x[0]*x[0]+x[1]*x[1] for x in ngradient_v])**.5
        print(error)
    
    return newpath # Leave this line for the grader!

printpaths(path,smooth(path))