07/20 18:30

import numpy, math, cv2, pandas, seaborn
from matplotlib import pyplot

d = cv2.imread('1.jpg', cv2.IMREAD_GRAYSCALE)

#基本資料
print("basic information of picture:")
print("xsize =", d.shape[1])
print("ysize =", d.shape[0])


##高階處理
fd = d.tolist()

def toGraph(originalGraph, shrinkRate):

    xSize = len(originalGraph)
    ySize = len(originalGraph[0])
    fixed_xSize = xSize // shrinkRate
    fixed_ySize = ySize // shrinkRate
    fixed_graph = numpy.zeros((fixed_xSize, fixed_ySize))

    for xi in range(fixed_xSize):
        for yi in range(fixed_ySize):
            for xj in range(shrinkRate):
                for yj in range(shrinkRate):
                    fixed_graph[xi][yi] += originalGraph[xi * shrinkRate + xj][yi * shrinkRate + yj]
            fixed_graph[xi][yi] //= shrinkRate * shrinkRate

    fixed_result = numpy.array(pandas.value_counts(fixed_graph.flatten()))
    returnVar = numpy.arange(1, len(fixed_result) + 1)

    pyplot.figure(figsize=(15, 5))
    pyplot.subplot(1, 2, 1)
    pyplot.plot(returnVar, fixed_result)
    pyplot.title(f"{shrinkRate} * {shrinkRate}")
    pyplot.ylabel('appear time')
    pyplot.xlabel('rank')

    pyplot.subplot(1, 2, 2)
    pyplot.plot(returnVar, fixed_result)
    pyplot.xscale('log')
    pyplot.yscale('log')
    pyplot.title(f"{shrinkRate} * {shrinkRate}")
    pyplot.ylabel('appear time(log_10)')
    pyplot.xlabel('rank(log_10)')

    return [returnVar, fixed_result]

fixed_resultList = []
for i in range(1, 10 + 1):
    fixed_resultList.append(toGraph(fd, i))


#畫總圖

pyplot.figure(figsize=(15, 5))
pyplot.subplot(1, 2, 1)
for i in fixed_resultList:
    pyplot.plot(i[0], i[1])
pyplot.title('total')
pyplot.ylabel('appear time')
pyplot.xlabel('rank')


pyplot.subplot(1, 2, 2)
for i in fixed_resultList:
    pyplot.plot(i[0], i[1])
pyplot.xscale('log')
pyplot.yscale('log')
pyplot.title('total')
pyplot.ylabel('appear time(log_10)')
pyplot.xlabel('rank(log_10)')


#分析圖

logarithmic_resultList = [] #[x, y]
for i in fixed_resultList:
    logarithmic_resultList.append([numpy.log10(i[0]), numpy.log10(i[1])])


pyplot.figure(figsize=(15, 5))
pyplot.subplot(1, 2, 1)

for i in range(10):
    u=seaborn.regplot(logarithmic_resultList[i][0],
                      logarithmic_resultList[i][1],
                      label = f"{i + 1} * {i + 1}")
u.set_title('analyze')
u.set_ylabel('appear time(log_10)')
u.set_xlabel('rank(log_10)')
u.legend(loc = 'upper right')

#線條
pyplot.subplot(1, 2, 2)

for i in range(10):
    v = seaborn.regplot(logarithmic_resultList[i][0],
                      logarithmic_resultList[i][1],
                      label = f"{i + 1} * {i + 1}",
                      scatter = False)
v.set_title('analyze')
v.set_ylabel('appear time(log_10)')
v.set_xlabel('rank(log_10)')
v.legend(loc = 'upper right')

#取數值
pyplot.figure(figsize = (0.001, 0.001))


axList = []

for i in range(10):
    pyplot.subplot(1, 10, i + 1)
    axList.append(seaborn.regplot(logarithmic_resultList[i][0],
                                  logarithmic_resultList[i][1],
                                  scatter = False))

slopeList = []

for i in range(10):
    slope, intercept = numpy.polyfit(axList[i].get_lines()[0].get_xdata(),
                                     axList[i].get_lines()[0].get_ydata(),
                                     1)
    print(f"slope {i + 1} = {slope}")
    slopeList.append(slope)

print('the average of slopes =', sum(slopeList) / 10)