from timeit import default_timer as timer

import cv2
import numpy as np
import matplotlib.pyplot as plt


def time_fn(fn, img, iters=16):
    start = timer()
    for i in range(iters):
        fn(img)
    end = timer()
    return ((end - start) / iters) * 1000


# By http://stackoverflow.com/users/7938192/liam-lawrence
def foo1(img):
    pxList = ''
    # The height and width of your Mat
    height = np.size(img, 0)
    width = np.size(img, 1)

    # Iterates through the values of your Mat and stores them in pxList
    for i in range(height):
        for j in range(width):
            pxList = pxList + " " + str(img[i][j])

    pxList = pxList[1:] # Drop the first space
    return pxList

def foo2(img):
    return ' '.join(map(str,img.flatten().tolist()))

def foo3(img):
    return ' '.join(map(str,img.flatten()))

# Based on idea by http://stackoverflow.com/users/7847456/manel-fornos
def foo4(img):
    return str(img.flatten().tolist()).strip('[]').replace(',','')



def run_test(sz, iters):
    test_img = np.ones((sz, sz),np.uint8) * 255


    a = time_fn(foo1, test_img, iters)
    b = time_fn(foo2, test_img, iters)
    c = time_fn(foo3, test_img, iters)
    d = time_fn(foo4, test_img, iters)

    return (sz*sz,a,b,c,d)

results = [
    foo1(img = np.ones((128, 128),np.uint8) * 255)
    , foo2(img = np.ones((128, 128),np.uint8) * 255)
    , foo3(img = np.ones((128, 128),np.uint8) * 255)
    , foo4(img = np.ones((128, 128),np.uint8) * 255)
]

print results[0] == results[1]
print results[0] == results[2]
print results[0] == results[3]

times = []
for i in range(1,17):
    times.append(run_test(32*i, 4))
    print times[-1]

times = np.array(times)


def plot_times(times):
    fig = plt.figure(figsize=(12, 8), dpi=200)

    plt.plot(times[:,0], times[:,1], 'b+-', label='Variant 1')
    plt.plot(times[:,0], times[:,2], 'y+-', label='Variant 2')
    plt.plot(times[:,0], times[:,3], 'r+-', label='Variant 3')
    plt.plot(times[:,0], times[:,4], 'g+-', label='Variant 4')

    plt.title('Algorithm timings')
    plt.xlabel('Pixel count')
    plt.ylabel('Iteration time (ms)')
    plt.legend()

    fig.tight_layout()
    fig.savefig('ibad_timing_1234.png', dpi=fig.dpi)
    plt.close(fig)

def plot_times2(times):
    fig = plt.figure(figsize=(12, 8), dpi=200)

    #plt.plot(times[:,0], times[:,1], 'b+-', label='Variant 1')
    plt.plot(times[:,0], times[:,2], 'y+-', label='Variant 2')
    #plt.plot(times[:,0], times[:,3], 'r+-', label='Variant 3')
    plt.plot(times[:,0], times[:,4], 'g+-', label='Variant 4')

    plt.title('Algorithm timings')
    plt.xlabel('Pixel count')
    plt.ylabel('Iteration time (ms)')
    plt.legend()

    fig.tight_layout()
    fig.savefig('ibad_timing_24.png', dpi=fig.dpi)
    plt.close(fig)


plot_times(times)
plot_times2(times)