[ Checking a variable ]

Currently I have code that takes to vectors and makes a third one:

for b in range(2047):
    for a in range(b+1,2048):
        vector1 = (l[b][0],l[b][1],l[b][2])
        vector2 = (l[a][0],l[a][1],l[a][2])

        x = vector1
        y = vector2
        vector3 = list(np.array(x) - np.array(y))

        dotProduct = reduce( operator.add, map( operator.mul, vector3, vector3))

        dp = dotProduct**.5
        data_points = dp


       bin = int(dp/bin_width)
          if bin < num_bins: 

            bins[bin][2] += 1.0/bin_volumes[bin]    

ps b = 36771.881 But I want to say that if (vector 3 dot product with b) is greater than (b dot product b)/2 Then vector 3 = vector3 - b

and if (Vector 3 dot product b) is less than (-b dot product with b)/2

then vector 3 = vector 3 + b

How do I add this into my loop so that it checks vector 3 for these two situations every time it makes a vector 3?

packages being used :

import operator
import matplotlib.pyplot as plt
import numpy as np

current code:

limit = 36771.881
for b in range(2047):
    for a in range(b+1,2048):
        vector1 = (l[b][0],l[b][1],l[b][2])
        vector2 = (l[a][0],l[a][1],l[a][2])

        x = vector1
        y = vector2
        vector3 = list(np.array(x) - np.array(y))

        dotProduct = reduce( operator.add, map( operator.mul, vector3, vector3))

        dp = dotProduct**.5
    data_points = dp
    if np.dot(data_points,limit) > (np.dot(limit,limit)
            dp = dp - limit
        bin = int(dp/bin_width)
            if bin < num_bins: 
            # add 1 to the count of that bin
                bins[bin][2] += 1.0/bin_volumes[bin]    
    else np.dot(data_points,limit) < (np.dot(-limit,limit)
       dp = dp + limit
       bin = int(dp/bin_width)
           if bin < num_bins: 
            # add 1 to the count of that bin
            bins[bin][2] += 1.0/bin_volumes[bin]    
   else if
        bin = int(dp/bin_width)
            if bin < num_bins: 
                # add 1 to the count of that bin
                bins[bin][2] += 1.0/bin_volumes[bin] 

Answer 1

For two arrays a and b, numpy.dot returns the inner product ("dot product").

E.g.,

>>> import numpy as np
>>> x = np.array([4,5,6])
>>> y = np.array([1,2,3])
>>> np.dot(x,y)
32
>>> np.dot(x,y) == (x * y).sum()
True