# udacity373_code / unit5_5.py

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69``` ```# ----------- # User Instructions # # Define a function smooth that takes a path as its input # (with optional parameters for weight_data, weight_smooth) # and returns a smooth path. # # 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 previous video: # # If your function isn't submitting it is possible that the # runtime is too long. Try sacrificing accuracy for speed. # ----------- from math import * # 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]] # ------------------------------------------------ # smooth coordinates # def smooth(path, weight_data = 0.0, weight_smooth = 0.1, tolerance = 0.0001): # Make a deep copy of path into newpath newpath = [[0 for col in range(len(path[0]))] for row in range(len(path))] for i in range(len(path)): for j in range(len(path[0])): newpath[i][j] = path[i][j] #### ENTER CODE BELOW THIS LINE ### change = tolerance while change >= tolerance: change = 0.0 for i in range(1, len(newpath) - 1): for j in range(len(newpath[0])): aux = newpath[i][j] x = path[i][j] newpath[i][j] += weight_data * (x- newpath[i][j]) newpath[i][j] += weight_smooth * (newpath[i+1][j] + newpath[i-1][j] - 2 * newpath[i][j]) change += abs(aux - newpath[i][j]) return newpath # Leave this line for the grader! # feel free to leave this and the following lines if you want to print. newpath = smooth(path) # thank you - EnTerr - for posting this on our discussion forum for i in range(len(path)): print '['+ ', '.join('%.3f'%x for x in path[i]) +'] -> ['+ ', '.join('%.3f'%x for x in newpath[i]) +']' ```