import numpy as np
import mytimer

@mytimer.timer
def dot_function(x,y):
    diff = x - y
    return diff.T.dot(diff)

@mytimer.timer
def npdot_function(x,y):
    diff = x - y
    return np.dot(diff.T,diff)

@mytimer.timer
def sqsum_function(x,y):
    diff = x - y
    return np.square(diff).sum()

if __name__=='__main__':
    arr_res = []
    mat_res = []
    funs = [sqsum_function,dot_function, npdot_function]
    labs = ['np.square(diff).sum()','diff.T.dot(diff)','np.dot(diff.T,diff)']
    cols  = ['r','b','y']
    
    for i in range(25):
        N  = 2**i
        x  = np.random.random((N,1))
        y  = np.random.random((N,1))
        xx = np.asmatrix(x)
        yy = np.asmatrix(y)
        for f, lab, col in zip(funs,labs,cols):
            r,t1 = f(x,y)
            r,t2 = f(xx,yy)
            lab = lab if i==0 else ''  # ternary, label only for first value in the data set
            arr_res.append([N,t1,lab,col])
            mat_res.append([N,t2,lab,col])
            
    import matplotlib.pyplot as plt
    plt.switch_backend('TkAgg')
    for r in arr_res:
        N,t,lab,col = r
        plt.loglog(N,t,'o',color=col, label=lab)
        
    for r in mat_res:
        N,t,lab,col = r
        plt.loglog(N,t,'s',color=col, label=lab)

    plt.title('Dot product using array or matrix')    
    plt.xlabel('N')
    plt.ylabel('time (s)')
    plt.legend()
    plt.show()